observed climate variables: Topics by Science.gov

observed climate variables: Topics by Science.gov
Science.gov

Sample records for observed climate variables

  1. Observed climate variability over Chad using multiple observational and reanalysis datasets

    NASA Astrophysics Data System (ADS)

    Maharana, Pyarimohan; Abdel-Lathif, Ahmat Younous; Pattnayak, Kanhu Charan

    2018-03-01

    Chad is the largest of Africa’s landlocked countries and one of the least studied region of the African continent. The major portion of Chad lies in the Sahel region, which is known for its rapid climate change. In this study, multiple observational datasets are analyzed from 1950 to 2014, in order to examine the trend of precipitation and temperature along with their variability over Chad to understand possible impacts of climate change over this region. Trend analysis of the climatic fields has been carried out using Mann-Kendall test. The precipitation over Chad is mostly contributed during summer by West African Monsoon, with maximum northward limit of 18° N. The Atlantic Ocean as well as the Mediterranean Sea are the major source of moisture for the summer rainfall over Chad. Based on the rainfall time series, the entire study period has been divided in to wet (1950 to 1965), dry (1966 to 1990) and recovery period (1991 to 2014). The rainfall has decreased drastically for almost 3 decades during the dry period resulted into various drought years. The temperature increases at a rate of 0.15 °C/decade during the entire period of analysis. The seasonal rainfall as well as temperature plays a major role in the change of land use/cover. The decrease of monsoon rainfall during the dry period reduces the C4 cover drastically; this reduction of C4 grass cover leads to increase of C3 grass cover. The slow revival of rainfall is still not good enough for the increase of shrub cover but it favors the gradual reduction of bare land over Chad.

  2. Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century

    NASA Astrophysics Data System (ADS)

    Kravtsov, Sergey

    2017-06-01

    Identification and dynamical attribution of multidecadal climate undulations to either variations in external forcings or to internal sources is one of the most important topics of modern climate science, especially in conjunction with the issue of human-induced global warming. Here we utilize ensembles of twentieth century climate simulations to isolate the forced signal and residual internal variability in a network of observed and modeled climate indices. The observed internal variability so estimated exhibits a pronounced multidecadal mode with a distinctive spatiotemporal signature, which is altogether absent in model simulations. This single mode explains a major fraction of model-data differences over the entire climate index network considered; it may reflect either biases in the models’ forced response or models’ lack of requisite internal dynamics, or a combination of both.Plain Language SummaryGlobal and regional warming trends over the course of the twentieth century have been nonuniform, with decadal and longer periods of faster or slower warming, or even cooling. Here we show that state-of-the-art global models used to predict climate fail to adequately reproduce such multidecadal climate variations. In particular, the models underestimate the magnitude of the observed variability and misrepresent its spatial pattern. Therefore, our ability to interpret the observed climate change using these models is limited.

  3. Interannual variability and climatic noise in satellite-observed outgoing longwave radiation

    NASA Technical Reports Server (NTRS)

    Short, D. A.; Cahalan, R. F.

    1983-01-01

    Upwelling-IR observations of the North Pacific by polar orbiters NOAA 3, 4, 5, and 6 and TIROS-N from 1974 to 1981 are analyzed statistically in terms of interannual variability (IAV) in monthly averages and climatic noise due to short-term weather fluctuations. It is found that although the daily variance in the observations is the same in summer and winter months, and although IAV in winter is smaller than that in summer, the climatic noise in winter is so much smaller that a greater fraction of winter anomalies are statistically significant. The smaller winter climatic noise level is shown to be due to shorter autocorrelation times. It is demonstrated that increasing averaging area does not reduce the climatic noise level, suggesting that continuing collection of high-resolution satellite IR data on a global basis is necessary if better models of short-term variability are to be constructed.

  4. Regionalizing Africa: Patterns of Precipitation Variability in Observations and Global Climate Models

    NASA Technical Reports Server (NTRS)

    Badr, Hamada S.; Dezfuli, Amin K.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.

    2016-01-01

    Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios.

  5. Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

    NASA Astrophysics Data System (ADS)

    Parsons, Luke Alexander

    structure of the variance spectrum has important consequences for the probability of multi-year drought. Our lake record suggests there is a significant background threat of multi-year, and even decade-length, drought in western Amazonia, whereas climate model simulations indicate most droughts likely last no longer than one to three years. These findings suggest climate models may underestimate the future risk of extended drought in this important region. In Appendix C, we expand our analysis of climate variability beyond South America. We use observations, well-constrained tropical paleoclimate, and Earth system model data to examine the overall shape of the climate spectrum across interannual to century frequencies. We find a general agreement among observations and models that temperature variability increases with timescale across most of the globe outside the tropics. However, as compared to paleoclimate records, climate models generate too little low-frequency variability in the tropics (e.g., Laepple and Huybers, 2014). When we compare the shape of the simulated climate spectrum to the spectrum of a simple autoregressive process, we find much of the modeled surface temperature variability in the tropics could be explained by ocean smoothing of weather noise. Importantly, modeled precipitation tends to be similar to white noise across much of the globe. By contrast, paleoclimate records of various types from around the globe indicate that both temperature and precipitation variability should experience much more low-frequency variability than a simple autoregressive or white-noise process. In summary, state-of-the-art climate models generate some degree of dynamically driven low-frequency climate variability, especially at high latitudes. However, the latest climate models, observations, and paleoclimate data provide us with drastically different pictures of the background climate system and its associated risks. This research has important consequences for improving

  6. An observational and modeling study of the regional impacts of climate variability

    NASA Astrophysics Data System (ADS)

    Horton, Radley M.

    Climate variability has large impacts on humans and their agricultural systems. Farmers are at the center of this agricultural network, but it is often agricultural planners—regional planners, extension agents, commodity groups and cooperatives—that translate climate information for users. Global climate models (GCMs) are a leading tool for understanding and predicting climate and climate change. Armed with climate projections and forecasts, agricultural planners adapt their decision-making to optimize outcomes. This thesis explores what GCMs can, and cannot, tell us about climate variability and change at regional scales. The question is important, since high-quality regional climate projections could assist farmers and regional planners in key management decisions, contributing to better agricultural outcomes. To answer these questions, climate variability and its regional impacts are explored in observations and models for the current and future climate. The goals are to identify impacts of observed variability, assess model simulation of variability, and explore how climate variability and its impacts may change under enhanced greenhouse warming. Chapter One explores how well Goddard Institute for Space Studies (GISS) atmospheric models, forced by historical sea surface temperatures (SST), simulate climatology and large-scale features during the exceptionally strong 1997–1999 El Nino Southern Oscillation (ENSO) cycle. Reasonable performance in this ‘proof of concept’ test is considered a minimum requirement for further study of variability in models. All model versions produce appropriate local changes with ENSO, indicating that with correct ocean temperatures these versions are capable of simulating the large-scale effects of ENSO around the globe. A high vertical resolution model (VHR) provides the best simulation. Evidence is also presented that SST anomalies outside the tropical Pacific may play a key role in generating remote teleconnections even

  7. Observed and Aogcm Simulated Relationships Between us Wind Speeds and Large Scale Modes of Climate Variability

    NASA Astrophysics Data System (ADS)

    Schoof, J. T.; Pryor, S. C.; Barthelmie, R. J.

    2013-12-01

    Previous research has indicated that large-scale modes of climate variability, such as El Niño – Southern Oscillation (ENSO), the Arctic Oscillation (AO) and the Pacific-North American pattern (PNA), influence the inter-annual and intra-annual variability of near-surface and upper-level wind speeds over the United States. For example, we have shown that rawinsonde derived wind speeds indicate that 90th percentile of wind speeds at 700 hPa over the Pacific Northwest and Southwestern USA are significantly higher under the negative phase of the PNA, and the Central Plains experiences higher wind speeds at 850 hPa under positive phase Southern Oscillation index while the Northeast exhibits higher wind speeds at 850 hPa under positive phase NAO. Here, we extend this research by further investigating these relationships using both reanalysis products and output from coupled atmosphere-ocean general circulation models (AOGCMs) developed for the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). The research presented has two specific goals. First, we evaluate the AOGCM simulations in terms of their ability to represent the temporal and spatial representations of ENSO, the AO, and the PNA pattern relative to historical observations. The diagnostics used include calculation of the power spectra (and thus representation of the fundamental frequencies of variability) and Taylor diagrams (for comparative assessment of the spatial patterns and their intensities). Our initial results indicate that most AOGCMs produce modes that are qualitatively similar to those observed, but that differ slightly in terms of the spatial pattern, intensity of specific centers of action, and variance explained. Figure 1 illustrates an example of the analysis of the frequencies of variability of two climate modes for the NCEP-NCAR reanalysis (NNR) and a single AOGCM (BCC CSM1). The results show a high degree of similarity in the power spectra but for this AOGCM the variance of the PNA

  8. Climate Variability Program

    NASA Technical Reports Server (NTRS)

    Halpern, David (Editor)

    2002-01-01

    The Annual Report of the Climate Variability Program briefly describes research activities of Principal Investigators who are funded by NASA’s Earth Science Enterprise Research Division. The report is focused on the year 2001. Utilization of satellite observations is a singularity of research on climate science and technology at JPL (Jet Propulsion Laboratory). Research at JPL has two foci: generate new knowledge and develop new technology.

  9. Filtering and Gridding Satellite Observations of Cloud Variables to Compare with Climate Model Output

    NASA Astrophysics Data System (ADS)

    Pitts, K.; Nasiri, S. L.; Smith, N.

    2013-12-01

    Global climate models have improved considerably over the years, yet clouds still represent a large factor of uncertainty for these models. Comparisons of model-simulated cloud variables with equivalent satellite cloud products are the best way to start diagnosing the differences between model output and observations. Gridded (level 3) cloud products from many different satellites and instruments are required for a full analysis, but these products are created by different science teams using different algorithms and filtering criteria to create similar, but not directly comparable, cloud products. This study makes use of a recently developed uniform space-time gridding algorithm to create a new set of gridded cloud products from each satellite instrument’s level 2 data of interest which are each filtered using the same criteria, allowing for a more direct comparison between satellite products. The filtering is done via several variables such as cloud top pressure/height, thermodynamic phase, optical properties, satellite viewing angle, and sun zenith angle. The filtering criteria are determined based on the variable being analyzed and the science question at hand. Each comparison of different variables may require different filtering strategies as no single approach is appropriate for all problems. Beyond inter-satellite data comparison, these new sets of uniformly gridded satellite products can also be used for comparison with model-simulated cloud variables. Of particular interest to this study are the differences in the vertical distributions of ice and liquid water content between the satellite retrievals and model simulations, especially in the mid-troposphere where there are mixed-phase clouds to consider. This presentation will demonstrate the proof of concept through comparisons of cloud water path from Aqua MODIS retrievals and NASA GISS-E2-[R/H] model simulations archived in the CMIP5 data portal.

  10. Observed 20th Century Desert Dust Variability: Impact on Climate and Biogeochemistry

    SciTech Connect

    Mahowald, Natalie; Kloster, Silvia; Engelstaedter, S.

    2010-01-01

    Desert dust perturbs climate by directly and indirectly interacting with incoming solar and outgoing long wave radiation, thereby changing precipitation and temperature, in addition to modifying ocean and land biogeochemistry. While we know that desert dust is sensitive to perturbations in climate and human land use, previous studies have been unable to determine whether humans were increasing or decreasing desert dust in the global average. Here we present observational estimates of desert dust based on paleodata proxies showing a doubling of desert dust during the 20th century over much, but not all the globe. Large uncertainties remain in estimates ofmore » desert dust variability over 20th century due to limited data. Using these observational estimates of desert dust change in combination with ocean, atmosphere and land models, we calculate the net radiative effect of these observed changes (top of atmosphere) over the 20th century to be -0.14 {+-} 0.11 W/m (1990-1999 vs. 1905-1914). The estimated radiative change due to dust is especially strong between the heavily loaded 1980-1989 and the less heavily loaded 1955-1964 time periods (-0.57 {+-} 0.46 W/m), which model simulations suggest may have reduced the rate of temperature increase between these time periods by 0.11 C. Model simulations also indicate strong regional shifts in precipitation and temperature from desert dust changes, causing 6 ppm (12 PgC) reduction in model carbon uptake by the terrestrial biosphere over the 20th century. Desert dust carries iron, an important micronutrient for ocean biogeochemistry that can modulate ocean carbon storage; here we show that dust deposition trends increase ocean productivity by an estimated 6% over the 20th century, drawing down an additional 4 ppm (8 PgC) of carbon dioxide into the oceans. Thus, perturbations to desert dust over the 20th century inferred from observations are potentially important for climate and biogeochemistry, and our

  11. Ocean impact on decadal Atlantic climate variability revealed by sea-level observations.

    PubMed

    McCarthy, Gerard D; Haigh, Ivan D; Hirschi, Joël J-M; Grist, Jeremy P; Smeed, David A

    2015-05-28

    Decadal variability is a notable feature of the Atlantic Ocean and the climate of the regions it influences. Prominently, this is manifested in the Atlantic Multidecadal Oscillation (AMO) in sea surface temperatures. Positive (negative) phases of the AMO coincide with warmer (colder) North Atlantic sea surface temperatures. The AMO is linked with decadal climate fluctuations, such as Indian and Sahel rainfall, European summer precipitation, Atlantic hurricanes and variations in global temperatures. It is widely believed that ocean circulation drives the phase changes of the AMO by controlling ocean heat content. However, there are no direct observations of ocean circulation of sufficient length to support this, leading to questions about whether the AMO is controlled from another source. Here we provide observational evidence of the widely hypothesized link between ocean circulation and the AMO. We take a new approach, using sea level along the east coast of the United States to estimate ocean circulation on decadal timescales. We show that ocean circulation responds to the first mode of Atlantic atmospheric forcing, the North Atlantic Oscillation, through circulation changes between the subtropical and subpolar gyres–the intergyre region. These circulation changes affect the decadal evolution of North Atlantic heat content and, consequently, the phases of the AMO. The Atlantic overturning circulation is declining and the AMO is moving to a negative phase. This may offer a brief respite from the persistent rise of global temperatures, but in the coupled system we describe, there are compensating effects. In this case, the negative AMO is associated with a continued acceleration of sea-level rise along the northeast coast of the United States.

  12. Climate Observations from Space

    NASA Astrophysics Data System (ADS)

    Briggs, Stephen

    2016-07-01

    The latest Global Climate Observing System (GCOS) Status Report on global climate observations, delivered to the UNFCCC COP21 in November 2016, showed how satellite data are critical for observations relating to climate. Of the 50 Essential Climate Variables (ECVs) identified by GCOS as necessary for understanding climate change, about half are derived only from satellite data while half of the remainder have a significant input from satellites. Hence data from Earth observing satellite systems are now a fundamental requirement for understanding the climate system and for managing the consequences of climate change. Following the Paris Agreement of COP21 this need is only greater. Not only will satellites have to continue to provide data for modelling and predicting climate change but also for a much wider range of actions relating to climate. These include better information on loss and damage, resilience, improved adaptation to change, and on mitigation including information on greenhouse gas emissions. In addition there is an emerging need for indicators of the risks associated with future climate change which need to be better quantified, allowing policy makers both to understand what decisions need to be taken, and to see the consequences of their actions. The presentation will set out some of the ways in which satellite data are important in all aspects of understanding, managing and predicting climate change and how they may be used to support future decisions by those responsible for policy related to managing climate change and its consequences.

  13. Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity from Observations

    NASA Technical Reports Server (NTRS)

    Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

    2018-01-01

    An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2-radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

  14. Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations

    NASA Astrophysics Data System (ADS)

    Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

    2018-02-01

    An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

  15. Climate Impact of Solar Variability

    NASA Technical Reports Server (NTRS)

    Schatten, Kenneth H. (Editor); Arking, Albert (Editor)

    1990-01-01

    The conference on The Climate Impact of Solar Variability, was held at Goddard Space Flight Center from April 24 to 27, 1990. In recent years they developed a renewed interest in the potential effects of increasing greenhouse gases on climate. Carbon dioxide, methane, nitrous oxide, and the chlorofluorocarbons have been increasing at rates that could significantly change climate. There is considerable uncertainty over the magnitude of this anthropogenic change. The climate system is very complex, with feedback processes that are not fully understood. Moreover, there are two sources of natural climate variability (volcanic aerosols and solar variability) added to the anthropogenic changes which may confuse our interpretation of the observed temperature record. Thus, if we could understand the climatic impact of the natural variability, it would aid our interpretation and understanding of man-made climate changes.

  16. Observations of Local Positive Low Cloud Feedback Patterns and Their Role in Internal Variability and Climate Sensitivity

    NASA Astrophysics Data System (ADS)

    Yuan, Tianle; Oreopoulos, Lazaros; Platnick, Steven E.; Meyer, Kerry

    2018-05-01

    Modeling studies have shown that cloud feedbacks are sensitive to the spatial pattern of sea surface temperature (SST) anomalies, while cloud feedbacks themselves strongly influence the magnitude of SST anomalies. Observational counterparts to such patterned interactions are still needed. Here we show that distinct large-scale patterns of SST and low-cloud cover (LCC) emerge naturally from objective analyses of observations and demonstrate their close coupling in a positive local SST-LCC feedback loop that may be important for both internal variability and climate change. The two patterns that explain the maximum amount of covariance between SST and LCC correspond to the Interdecadal Pacific Oscillation and the Atlantic Multidecadal Oscillation, leading modes of multidecadal internal variability. Spatial patterns and time series of SST and LCC anomalies associated with both modes point to a strong positive local SST-LCC feedback. In many current climate models, our analyses suggest that SST-LCC feedback strength is too weak compared to observations. Modeled local SST-LCC feedback strength affects simulated internal variability so that stronger feedback produces more intense and more realistic patterns of internal variability. To the extent that the physics of the local positive SST-LCC feedback inferred from observed climate variability applies to future greenhouse warming, we anticipate significant amount of delayed warming because of SST-LCC feedback when anthropogenic SST warming eventually overwhelm the effects of internal variability that may mute anthropogenic warming over parts of the ocean. We postulate that many climate models may be underestimating both future warming and the magnitude of modeled internal variability because of their weak SST-LCC feedback.

  17. The Spatiotemporal Structure of 20th Century Climate Variations in Observations and Reanalyses. Part 2; Pacific Pan-Decadal Variability

    NASA Technical Reports Server (NTRS)

    Chen, Junye; DelGenio, Anthony D.; Carlson, Barbara E.; Bosilovich, Michael G.

    2007-01-01

    The dominant interannual El Nino-Southern Oscillation phenomenon (ENSO) and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENS0 signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, we develop an ENSO-removal method through which the ENS0 signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations, namely, the global warming trend (GW) and the Pacific pan-decadal variability (PDV), are isolated at middle and low latitudes in the climate parameter fields from observed and reanalyses datasets. In this study, we show that one of several PDV interdecadal regime shifts occurred during the 1990s. This significant change in the Pacific basin is comparable but opposite in phase to the 1976 climate regime shift, which results persisting warming in the central-eastern Pacific, and cooling in the North and South Pacific. The 1990s PDV regime shift is consistent with observed changes in ocean biosphere and ocean circulation. A comprehensive picture of PDV as manifested in the troposphere and at the surface is described. In general, the PDV spatial patterns in different parameter fields share some similarities with the patterns associated with ENSO, but important differences exist. First, the PDV atmospheric circulation pattern is shifted westward by about 20deg and its zonal extent is limited to approx.60deg compared to approx.110deg for ENS0 pattern. The westward shift of the PDV wave train produces a different, more west-east oriented, North American teleconnection pattern. The lack of a strong PDV surface temperature (ST) signal in the western equatorial Pacific and the relatively strong ST signal in the subtropical regions are consistent with an atmospheric overturning circulation response that

  18. A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability

    NASA Astrophysics Data System (ADS)

    Wang, Kaicun; Dickinson, Robert E.

    2012-06-01

    This review surveys the basic theories, observational methods, satellite algorithms, and land surface models for terrestrial evapotranspiration, E (or λE, i.e., latent heat flux), including a long-term variability and trends perspective. The basic theories used to estimate E are the Monin-Obukhov similarity theory (MOST), the Bowen ratio method, and the Penman-Monteith equation. The latter two theoretical expressions combine MOST with surface energy balance. Estimates of E can differ substantially between these three approaches because of their use of different input data. Surface and satellite-based measurement systems can provide accurate estimates of diurnal, daily, and annual variability of E. But their estimation of longer time variability is largely not established. A reasonable estimate of E as a global mean can be obtained from a surface water budget method, but its regional distribution is still rather uncertain. Current land surface models provide widely different ratios of the transpiration by vegetation to total E. This source of uncertainty therefore limits the capability of models to provide the sensitivities of E to precipitation deficits and land cover change.

  19. Implication of observed cloud variability for parameterizations of microphysical and radiative transfer processes in climate models

    NASA Astrophysics Data System (ADS)

    Huang, D.; Liu, Y.

    2014-12-01

    The effects of subgrid cloud variability on grid-average microphysical rates and radiative fluxes are examined by use of long-term retrieval products at the Tropical West Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy’s Atmospheric Radiation Measurement (ARM) Program. Four commonly used distribution functions, the truncated Gaussian, Gamma, lognormal, and Weibull distributions, are constrained to have the same mean and standard deviation as observed cloud liquid water content. The PDFs are then used to upscale relevant physical processes to obtain grid-average process rates. It is found that the truncated Gaussian representation results in up to 30% mean bias in autoconversion rate whereas the mean bias for the lognormal representation is about 10%. The Gamma and Weibull distribution function performs the best for the grid-average autoconversion rate with the mean relative bias less than 5%. For radiative fluxes, the lognormal and truncated Gaussian representations perform better than the Gamma and Weibull representations. The results show that the optimal choice of subgrid cloud distribution function depends on the nonlinearity of the process of interest and thus there is no single distribution function that works best for all parameterizations. Examination of the scale (window size) dependence of the mean bias indicates that the bias in grid-average process rates monotonically increases with increasing window sizes, suggesting the increasing importance of subgrid variability with increasing grid sizes.

  20. Current Climate Variability & Change

    NASA Astrophysics Data System (ADS)

    Diem, J.; Criswell, B.; Elliott, W. C.

    2013-12-01

    Current Climate Variability & Change is the ninth among a suite of ten interconnected, sequential labs that address all 39 climate-literacy concepts in the U.S. Global Change Research Program’s Climate Literacy: The Essential Principles of Climate Sciences. The labs are as follows: Solar Radiation & Seasons, Stratospheric Ozone, The Troposphere, The Carbon Cycle, Global Surface Temperature, Glacial-Interglacial Cycles, Temperature Changes over the Past Millennium, Climates & Ecosystems, Current Climate Variability & Change, and Future Climate Change. All are inquiry-based, on-line products designed in a way that enables students to construct their own knowledge of a topic. Questions representative of various levels of Webb’s depth of knowledge are embedded in each lab. In addition to the embedded questions, each lab has three or four essential questions related to the driving questions for the lab suite. These essential questions are presented as statements at the beginning of the material to represent the lab objectives, and then are asked at the end as questions to function as a summative assessment. For example, the Current Climate Variability & Change is built around these essential questions: (1) What has happened to the global temperature at the Earth’s surface, in the middle troposphere, and in the lower stratosphere over the past several decades?; (2) What is the most likely cause of the changes in global temperature over the past several decades and what evidence is there that this is the cause?; and (3) What have been some of the clearly defined effects of the change in global temperature on the atmosphere and other spheres of the Earth system? An introductory Prezi allows the instructor to assess students’ prior knowledge in relation to these questions, while also providing ‘hooks’ to pique their interest related to the topic. The lab begins by presenting examples of and key differences between climate variability (e.g., Mt. Pinatubo eruption) and

  1. NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

    NASA Technical Reports Server (NTRS)

    Hou, Arthur Y.

    2004-01-01

    Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) – as their quality continues to improve – have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation – especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has

  2. NPOESS, Essential Climates Variables and Climate Change

    NASA Astrophysics Data System (ADS)

    Forsythe-Newell, S. P.; Bates, J. J.; Barkstrom, B. R.; Privette, J. L.; Kearns, E. J.

    2008-12-01

    Advancement in understanding, predicting and mitigating against climate change implies collaboration, close monitoring of Essential Climate Variable (ECV)s through development of Climate Data Record (CDR)s and effective action with specific thematic focus on human and environmental impacts. Towards this end, NCDC’s Scientific Data Stewardship (SDS) Program Office developed Climate Long-term Information and Observation system (CLIO) for satellite data identification, characterization and use interrogation. This “proof-of-concept” online tool provides the ability to visualize global CDR information gaps and overlaps with options to temporally zoom-in from satellite instruments to climate products, data sets, data set versions and files. CLIO provides an intuitive one-stop web site that displays past, current and planned launches of environmental satellites in conjunction with associated imagery and detailed information. This tool is also capable of accepting and displaying Web-based input from Subject Matter Expert (SME)s providing a global to sub-regional scale perspective of all ECV’s and their impacts upon climate studies. SME’s can access and interact with temporal data from the past and present, or for future planning of products, datasets/dataset versions, instruments, platforms and networks. CLIO offers quantifiable prioritization of ECV/CDR impacts that effectively deal with climate change issues, their associated impacts upon climate, and this offers an intuitively objective collaboration and consensus building tool. NCDC’s latest tool empowers decision makers and the scientific community to rapidly identify weaknesses and strengths in climate change monitoring strategies and significantly enhances climate change collaboration and awareness.

  3. Climate variability and trends in biogenic emissions imprinted on satellite observations of formaldehyde from SCIAMACHY and OMI sounders

    NASA Astrophysics Data System (ADS)

    Stavrakou, Trissevgeni; Müller, Jean-François; Bauwens, Maite; De Smedt, Isabelle; Van Roozendael, Michel

    2017-04-01

    Biogenic hydrocarbon emissions (BVOC) respond to temperature, photosynthetically active radiation, leaf area index, as well as to factors like leaf age, soil moisture, and ambient CO2 concentrations. Isoprene is the principal contributor to BVOC emissions and accounts for about half of the estimated total emissions on the global scale, whereas monoterpenes are also significant over boreal ecosystems. Due to their large emissions, their major role in the tropospheric ozone formation and contribution to secondary organic aerosols, BVOCs are highly relevant to both air quality and climate. Their oxidation in the atmosphere leads to the formation of formaldehyde (HCHO) at high yields. Satellite observations of HCHO abundances can therefore inform us on the spatial and temporal variability of the underlying sources and on their emission trends. The main objective of this study is to investigate the interannual variability and trends of observed HCHO columns during the growing season, when BVOC emissions are dominant, and interpret them in terms of BVOC emission flux variability. To this aim, we use the MEGAN-MOHYCAN model driven by the ECMWF ERA-interim meteorology to calculate bottom-up BVOC fluxes on the global scale (Müller et al. 2008, Stavrakou et al. 2014) over 2003-2015, and satellite HCHO observations from SCIAMACHY (2003-2011) and OMI (2005-2015) instruments (De Smedt et al. 2008, 2015). We focus on mid- and high-latitude regions of the Northern Hemisphere in summertime, as well as tropical regions taking care to exclude biomass burning events which also lead to HCHO column enhancements. We find generally a very strong temporal correlation (>0.7) between the simulated BVOC emissions and the observed HCHO columns over temperate and boreal ecosystems. Positive BVOC emission trends associated to warming climate are found in almost all regions and are well corroborated by the observations. Furthermore, using OMI HCHO observations over 2005-2015 as constraints in

  4. Groundwater vulnerability to climate variability: modelling experience and field observations in the lower Magra Valley (Liguria, Italy)

    NASA Astrophysics Data System (ADS)

    Menichini, Matia; Doveri, Marco; El Mansoury, Bouabid; El Mezouary, Lhoussaine; Lelli, Matteo; Raco, Brunella; Scozzari, Andrea; Soldovieri, Francesco

    2016-04-01

    The aquifer of the Lower Magra Valley (SE Liguria, Italy) extends in a flat plain, where two main rivers (Magra and Vara) flow. These rivers are characterized by a wide variation of water level and water chemical composition (TDS, Cl and SO4) due to the combination of rainfall regime and the presence of thermal springs in the inner part of the catchment area. Groundwater flow is apparently controlled by stream water infiltration, which affects both water levels and water quality. In particular, the wide range of variation of some particular chemical species in the stream water influences the groundwater chemistry on a seasonal basis. In the area of interest, there is an important well-field, which supplies most of the drinking water to the nearby city of La Spezia. In this context, the groundwater system is exposed to a high degree of vulnerability, both in terms of quality and quantity. This study is aimed to develop a predictive flow and transport model in order to assess the vulnerability s.l. of the Magra Valley aquifer system and to evaluate its behaviour in awaited climate scenarios. A flow and transport model was developed by using MODFLOW and MT3DMS codes, and it’s been calibrated in both steady state and transient conditions. The model confirmed the importance of the Magra river in the water balance and chemical composition of the extracted groundwater. In addition, a data-driven modelling approach was applied in order to determine boundary conditions (e.g. rivers and constant head or general head boundaries) of the physical model under hypothetic future climate scenarios. For this purpose, fully synthetic datasets have been generated as a training set of the data-driven scheme, with input variables inspired by selected climate models and input/output relationships estimated by past observations. An experimental run of the flow-transport model for 30 years ahead was performed, based on such hypothetic scenarios. This approach highlighted how the

  5. Surfing wave climate variability

    NASA Astrophysics Data System (ADS)

    Espejo, Antonio; Losada, Iñigo J.; Méndez, Fernando J.

    2014-10-01

    International surfing destinations are highly dependent on specific combinations of wind-wave formation, thermal conditions and local bathymetry. Surf quality depends on a vast number of geophysical variables, and analyses of surf quality require the consideration of the seasonal, interannual and long-term variability of surf conditions on a global scale. A multivariable standardized index based on expert judgment is proposed for this purpose. This index makes it possible to analyze surf conditions objectively over a global domain. A summary of global surf resources based on a new index integrating existing wave, wind, tides and sea surface temperature databases is presented. According to general atmospheric circulation and swell propagation patterns, results show that west-facing low to middle-latitude coasts are more suitable for surfing, especially those in the Southern Hemisphere. Month-to-month analysis reveals strong seasonal variations in the occurrence of surfable events, enhancing the frequency of such events in the North Atlantic and the North Pacific. Interannual variability was investigated by comparing occurrence values with global and regional modes of low-frequency climate variability such as El Niño and the North Atlantic Oscillation, revealing their strong influence at both the global and the regional scale. Results of the long-term trends demonstrate an increase in the probability of surfable events on west-facing coasts around the world in recent years. The resulting maps provide useful information for surfers, the surf tourism industry and surf-related coastal planners and stakeholders.

  6. The Climate Variability & Predictability (CVP) Program at NOAA – Observing and Understanding Processes Affecting the Propagation of Intraseasonal Oscillations in the Maritime Continent Region

    NASA Astrophysics Data System (ADS)

    Lucas, S. E.

    2017-12-01

    The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA’s Climate Program Office (http://cpo.noaa.gov/CVP). In 2017, the CVP Program had a call for proposals focused on observing and understanding processes affecting the propagation of intraseasonal oscillations in the Maritime Continent region. This poster will present the recently funded CVP projects, the expected scientific outcomes, the geographic areas of their work in the Maritime Continent region, and the collaborations with the Office of Naval Research, Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and other partners.

  7. Climate Variability and Ecosystem Response

    Treesearch

    David Greenland; Lloyd W. Swift; [Editors

    1990-01-01

    Nine papers describe studies of climate variability and ecosystem response. The studies were conducted at LTER (Long-Term Ecological Research) sites representing forest, agricultural, and aquatic ecosystems and systems in which extreme climates limit vegetational cover. An overview paper prepared by the LTER Climate Committee stresses the importance of (1) clear…

  8. Climate variation explains a third of global crop yield variability

    PubMed Central

    Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

    2015-01-01

    Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

  9. Ocean Observations of Climate Change

    NASA Astrophysics Data System (ADS)

    Chambers, Don

    2016-01-01

    The ocean influences climate by storing and transporting large amounts of heat, freshwater, and carbon, and exchanging these properties with the atmosphere. About 93% of the excess heat energy stored by the earth over the last 50 years is found in the ocean. More than three quarters of the total exchange of water between the atmosphere and the earth’s surface through evaporation and precipitation takes place over the oceans. The ocean contains 50 times more carbon than the atmosphere and is at present acting to slow the rate of climate change by absorbing one quarter of human emissions of carbon dioxide from fossil fuel burning, cement production, deforestation and other land use change.Here I summarize the observational evidence of change in the ocean, with an emphasis on basin- and global-scale changes relevant to climate. These include: changes in subsurface ocean temperature and heat content, evidence for regional changes in ocean salinity and their link to changes in evaporation and precipitation over the oceans, evidence of variability and change of ocean current patterns relevant to climate, observations of sea level change and predictions over the next century, and biogeochemical changes in the ocean, including ocean acidification.

  10. Observed Temporal and Spatial Variability in the Marine Environment at the Sub-Antarctic Prince Edward Islands – Evidence of a Changing Climate?

    NASA Astrophysics Data System (ADS)

    Asdar, S.; Deshayes, J.; Ansorge, I. J.

    2016-02-01

    The sub-Antarctic Prince Edward Islands (PEI) (47°S,38°E) are classified as isolated, hostile, impoverished regions, in which the terrestrial and marine ecosystems are relatively simple and extremely sensitive to perturbations. Their location between the Sub-Antarctic Front (SAF) and the Antarctic Polar Front (APF), bordering the Antarctic Circumpolar Current (ACC) provides an ideal natural laboratory for studying how organisms, ecological processes and ecosystems respond to a changing ocean climate in the Southern Ocean. Recent studies have proposed that climate changes reported at the PEI may correspond in time to a southward shift of the ACC and in particular of the SAF. This southward migration in the geographic position is likely to coincide with dramatic changes in the distribution of species and total productivity of this region. This study focuses on the inter-comparison of observations available at these islands. Using spectral analysis which is a study of the frequency domain characteristics of a process, we first determine the dominant characteristics of both the temporal and spatial variability of physical and biogeochemical properties. In doing so the authors are able to determine whether and how these indices of variability interact with one another in order to understand better the mechanisms underpinning this variability, i.e. the seasonal zonal migrations associated with the SAF. Additionally, we include in our analysis recent data from 2 ADCP moorings deployed between the islands from 2014 to 2015. These in-situ observations of circulation and hydrography in the vicinity of the islands provide a unique opportunity to establish a better understanding of how large scale climatic variability may impact local conditions, and more importantly its influence on the fragile ecosystem surrounding the PEI.

  11. The role of clouds in driving North Atlantic multi-decadal climate variability in observations and models

    NASA Astrophysics Data System (ADS)

    Clement, A. C.; Bellomo, K.; Murphy, L.

    2013-12-01

    Large scale warming and cooling periods of the North Atlantic is known as the Atlantic Multidecadal Oscillation (AMO). The pattern of warming and cooling in the North Atlantic Ocean over the 20th century that has a characteristic spatial structure with maximum warming in the mid-latitudes and subtropics. This has been most often attributed to changes in the strength of the Atlantic Meridional Overturning Circulation (AMOC), which in turn affects poleward heat transport. A recent modeling study by Booth et al. (2012), however, suggested that aerosols can explain both the spatial pattern and temporal history of Atlantic SST through indirect effects of aerosols on cloud cover; although this idea is controversial (Zhang et al., 2013). We have found observational evidence that changes in cloud amount can drive SST changes on multi-decadal timescale. We hypothesize that a positive local feedback between SST and cloud radiative effect amplifies SST and gives rise to the observed pattern of SST change. During cool North Atlantic periods, a southward shift of the ITCZ strengthens the trade winds in the tropical North Atlantic and increases low-level cloud cover, which acts to amplify the SST cooling in the North Atlantic. During warm periods in the North Atlantic, the opposite response occurs. We are testing whether the amplitude of this feedback is realistically simulated in the CMIP5 models, and whether inter-model differences in the amplitude of the feedback can explain differences in model simulations of Atlantic multi-decadal variability.

  12. The ARGO Project: Global Ocean Observations for Understanding and Prediction of Climate Variability. Report for Calendar Year 2004

    DTIC Science & Technology

    2004-01-01

    international Argo practices. Data appropriate for research applications and for comparison with climate change models are not available for several…global ocean heat and fresh water storage and the detection and attribution of climate change . These presentations can be accessed at http…stresses on ocean ecosystems have serious consequences, and sometimes dramatic ones, such as coral reef bleaching . In the future, the impacts of a

  13. Solar variability, weather, and climate

    NASA Technical Reports Server (NTRS)

    1982-01-01

    Advances in the understanding of possible effects of solar variations on weather and climate are most likely to emerge by addressing the subject in terms of fundamental physical principles of atmospheric sciences and solar-terrestrial physis. The limits of variability of solar inputs to the atmosphere and the depth in the atmosphere to which these variations have significant effects are determined.

  14. Variable Star Observing in Hungary

    NASA Astrophysics Data System (ADS)

    Mizser, Attila

    1986-12-01

    Astronomy and variable star observing has a long history in Hungary, dating back to the private observatories erected by the Hungarian nobility in the late 19th Century. The first organized network of amateur variable star observers, the Variable Star Section of the new Hungarian Astronomical Association, was organized around the Urania Observatory in Budapest in 1948. Other groups, dedicated to various types of variables, have since been organized.

  15. Temporal variability of total cloud cover at a Mediterranean megacity in the 20th century: Evidence from visual observations and climate models

    NASA Astrophysics Data System (ADS)

    Founda, Dimitra; Giannakopoulos, Christos; Pierros, Fragiskos

    2013-04-01

    Cloud cover is one of the major factors that determine the radiation budget and the climate system of the Earth. Moreover, the response of clouds has always been an important source of uncertainty in global climate models. Visual surface observations of clouds have been conducted at the National Observatory of Athens (NOA) since the mid 19th century. The historical archive of cloud reports at NOA since 1860 has been digitized and updated, spanning now a period of one and a half century. Mean monthly values of total cloud cover were derived by averaging subdaily observations of cloud cover (3 observations/day). Changes in observational practice (e.g. from 1/10 to 1/8 units) were considered, however, subjective measures of cloud cover from trained observers introduces some kind of uncertainty in the time series. Data before 1884 were considered unreliable, so the analysis was restricted to the series from 1884 to 2012. The time series of total cloud cover at NOA is validated and correlated with historical time series of other (physically related) variables such as the total sunshine duration as well as DTR (Diurnal Temperature Range) which are independently measured. Trend analysis was performed on the mean annual and seasonal series of total cloud cover from 1884-2012. The mean annual values show a marked temporal variability with sub periods of decreasing and increasing tendencies, however, the overall linear trend is positive and statistically significant (p

  16. Climate variability drives population cycling and synchrony

    Treesearch

    Lars Y. Pomara; Benjamin Zuckerberg

    2017-01-01

    Aim There is mounting concern that climate change will lead to the collapse of cyclic population dynamics, yet the influence of climate variability on population cycling remains poorly understood. We hypothesized that variability in survival and fecundity, driven by climate variability at different points in the life cycle, scales up from…

  17. Variability of hydrological extreme events in East Asia and their dynamical control: a comparison between observations and two high-resolution global climate models

    NASA Astrophysics Data System (ADS)

    Freychet, N.; Duchez, A.; Wu, C.-H.; Chen, C.-A.; Hsu, H.-H.; Hirschi, J.; Forryan, A.; Sinha, B.; New, A. L.; Graham, T.; Andrews, M. B.; Tu, C.-Y.; Lin, S.-J.

    2017-02-01

    This work investigates the variability of extreme weather events (drought spells, DS15, and daily heavy rainfall, PR99) over East Asia. It particularly focuses on the large scale atmospheric circulation associated with high levels of the occurrence of these extreme events. Two observational datasets (APHRODITE and PERSIANN) are compared with two high-resolution global climate models (HiRAM and HadGEM3-GC2) and an ensemble of other lower resolution climate models from CMIP5. We first evaluate the performance of the high resolution models. They both exhibit good skill in reproducing extreme events, especially when compared with CMIP5 results. Significant differences exist between the two observational datasets, highlighting the difficulty of having a clear estimate of extreme events. The link between the variability of the extremes and the large scale circulation is investigated, on monthly and interannual timescales, using composite and correlation analyses. Both extreme indices DS15 and PR99 are significantly linked to the low level wind intensity over East Asia, i.e. the monsoon circulation. It is also found that DS15 events are strongly linked to the surface temperature over the Siberian region and to the land-sea pressure contrast, while PR99 events are linked to the sea surface temperature anomalies over the West North Pacific. These results illustrate the importance of the monsoon circulation on extremes over East Asia. The dependencies on of the surface temperature over the continent and the sea surface temperature raise the question as to what extent they could affect the occurrence of extremes over tropical regions in future projections.

  18. Advances in Understanding Decadal Climate Variability

    NASA Technical Reports Server (NTRS)

    Busalaacchi, Antonio J.

    1998-01-01

    Recently, a joint Brazil-France-U.S. program, known as PIRATA (Pilot Research moored Array in the Tropical Atlantic), was proposed to begin the deployment of moored measurement platforms in the tropical Atlantic in order to enhance the existing observational data base and subsequent understanding of the processes by which the ocean and atmosphere couple in key regions of the tropical Atlantic Ocean. Empirical studies have suggested that there are strong relationships between tropical Atlantic upper ocean variability, SST, ocean-atmosphere coupling and regional climate variability. During the early 1980’s a coordinated set of surface wind, subsurface thermal structure, and subsurface current observations were obtained as part of the U.S.-France SEQUAL- FOCAL process experiment designed to observe the seasonal response of the tropical Atlantic Ocean to surface forcing. Since that time, however, the observational data base for the tropical Atlantic Ocean has disintegrated to a few shiptracks measuring ocean temperatures and a small collection of tide gauge stations measuring sea level. A more comprehensive set of observations, modeling and empirical studies is now in order to make progress on understanding the regional climate variability. The proposed PIRATA program will use mooring platforms similar to the tropical Pacific Ocean TAO array to measure surface fluxes of momentum and heat and the corresponding changes in the upper ocean thermal structure. It is anticipated that the oceanic data from this monitoring array will also be used in a predictive mode for initialization studies of regional coupled climate models. Of particular interest are zonal and meridional modes of ocean-atmosphere variability within the tropical Atlantic basin that have significant impacts on the regional climate of the bordering continents.

  19. Advances in Understanding Decadal Climate Variability

    NASA Technical Reports Server (NTRS)

    Busalacchi, Antonio J.

    1999-01-01

    Recently, a joint Brazil-France-U.S. program, known as PIRATA (Pilot Research moored Array in the Tropical Atlantic), was proposed to begin the deployment of moored measurement platforms in the tropical Atlantic in order to enhance the existing observational data base and subsequent understanding of the processes by which the ocean and atmosphere couple in key regions of the tropical Atlantic Ocean. Empirical studies have suggested that there are strong relationships between tropical Atlantic upper ocean variability, SST, ocean-atmosphere coupling and regional climate variability. During the early 1980’s a coordinated set of surface wind, subsurface thermal structure, and subsurface current observations were obtained as part of the U.S.-France SEQUAL-FOCAL process experiment designed to observe the seasonal response of the tropical Atlantic Ocean to surface forcing. Since that time, however, the observational data base for the tropical Atlantic Ocean has disintegrated to a few ship-tracks measuring ocean temperatures and a small collection of tide gauge stations measuring sea level. A more comprehensive set of observations, modeling and empirical studies is now in order to make progress on understanding the regional climate variability. The proposed PIRATA program will use mooring platforms similar to the tropical Pacific Ocean TAO array to measure surface fluxes of momentum and heat and the corresponding changes in the upper ocean thermal structure. It is anticipated that the oceanic data from this monitoring array will also be used in a predictive mode for initialization studies of regional coupled climate models. Of particular interest are zonal and meridional modes of ocean-atmosphere variability within the tropical Atlantic basin that have significant impacts on the regional climate of the bordering continents.

  20. The essential interactions between understanding climate variability and climate change

    NASA Astrophysics Data System (ADS)

    Neelin, J. D.

    2017-12-01

    Global change is sometimes perceived as a field separate from other aspects of atmospheric and oceanic sciences. Despite the long history of communication between the scientific communities studying global change and those studying interannual variability and weather, increasing specialization and conflicting societal demands on the fields can put these interactions at risk. At the same time, current trajectories for greenhouse gas emissions imply substantial adaptation to climate change will be necessary. Instead of simply projecting effects to be avoided, the field is increasingly being asked to provide regional-level information for specific adaptation strategies—with associated requirements for increased precision on projections. For extreme events, challenges include validating models for rare events, especially for events that are unprecedented in the historical record. These factors will be illustrated with examples of information transfer to climate change from work on fundamental climate processes aimed originally at timescales from hours to interannual. Work to understand the effects that control probability distributions of moisture, temperature and precipitation in historical weather can yield new factors to examine for the changes in the extremes of these distributions under climate change. Surprisingly simple process models can give insights into the behavior of vastly more complex climate models. Observation systems and model ensembles aimed at weather and interannual variations prove valuable for global change and vice versa. Work on teleconnections in the climate system, such as the remote impacts of El Niño, is informing analysis of projected regional rainfall change over California. Young scientists need to prepare to work across the full spectrum of climate variability and change, and to communicate their findings, as they and our society head for future that is more interesting than optimal.

  1. The Role of Climatic Conditions in Controlling Observed Variability of Timing and Peak Discharge of Glacial Lake Outburst Floods: Lago Cachet Dos, Chile

    NASA Astrophysics Data System (ADS)

    Jacquet, J.; McCoy, S. W.; McGrath, D.; Nimick, D.; Friesen, B.; Fahey, M. J.; Leidich, J.; Okuinghttons, J.

    2016-12-01

    The sudden release of water from an ice-dammed lake poses substantial hazard to the downstream environment, but predicting the timing and magnitude of such an event is difficult. We use a series of high-resolution discharge measurements from a glacier-dammed lake, Lago Cachet Dos (LC2), during outburst events to evaluate the environmental conditions that influence the timing of initiation and peak discharge of observed glacial lake outburst floods (GLOFs). Since April 2008, 20 GLOFs have initiated out of LC2, located on the eastern edge of the Northern Patagonia Icefield, Chile and flooded areas along the Rio Colonia- Rio Baker system. GLOF frequency has averaged 2-3 events annually and peak discharges exiting LC2 have ranged widely from 2,000 to >15,000 m3 s-1. Although some LC2 GLOFs are consistent with global compilations relating peak discharge to lake volume, large deviations from the global trend and large intra-event variability are striking and call into question the predictive ability of simple empirical scaling equations. To evaluate the environmental conditions that lead to variability in observed peak discharge, we use a variation of the theoretical model of Nye (1976), which describes the process of englacial conduit evolution as a competition between thermally induced conduit growth and viscous flow of ice causing conduit collapse. We show that, consistent with theory, initial lake volume, lake temperature, and the rate of meltwater input into the glacially dammed lake all influence the peak discharge of measured GLOFs. Consequently, evolving climatic conditions of a region can greatly influence the potential hazard of GLOFs. Our results suggest that more accurate predictions of GLOF timing and magnitude from ice dammed lakes can be made by incorporating additional measurements of environmental conditions.

  2. Evaluating climate models: Should we use weather or climate observations?

    SciTech Connect

    Oglesby, Robert J; Erickson III, David J

    2009-12-01

    Calling the numerical models that we use for simulations of climate change ‘climate models’ is a bit of a misnomer. These ‘general circulation models’ (GCMs, AKA global climate models) and their cousins the ‘regional climate models’ (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into ‘real climate statistics’. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM’s downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

  3. Climate variability and the European agricultural production

    NASA Astrophysics Data System (ADS)

    Guimarães Nobre, Gabriela; Hunink, Johannes E.; Baruth, Bettina; Aerts, Jeroen C. J. H.; Ward, Philip J.

    2017-04-01

    By 2050, the global demand for maize, wheat and other major crops is expected to grow sharply. To meet this challenge, agricultural systems have to increase substantially their production. However, the expanding world population, coupled with a decline of arable land per person, and the variability in global climate, are obstacles to achieving the increasing demand. Creating a resilient agriculture system requires the incorporation of preparedness measures against weather-related events, which can trigger disruptive risks such as droughts. This study examines the influence of large-scale climate variability on agriculture production applying a robust decision-making tool named fast-and-frugal trees (FFT). We created FFTs using a dataset of crop production and indices of climate variability: the El Niño Southern Oscillation (SOI) and the North Atlantic Oscillation (NAO). Our main goal is to predict the occurrence of below-average crop production, using these two indices at different lead times. Initial results indicated that SOI and NAO have strong links with European low sugar beet production. For some areas, the FFTs were able to detect below-average productivity events six months before harvesting with hit rate and predictive positive value higher than 70%. We found that shorter lead times, such as three months before harvesting, have the highest predictive skill. Additionally, we observed that the responses of low production events to the phases of the NAO and SOI vary spatially and seasonally. Through the comprehension of the relationship between large scale climate variability and European drought related agricultural impact, this study reflects on how this information could potentially improve the management of the agricultural sector by coupling the findings with seasonal forecasting system of crop production.

  4. Climate variability and vulnerability to climate change: a review

    PubMed Central

    Thornton, Philip K; Ericksen, Polly J; Herrero, Mario; Challinor, Andrew J

    2014-01-01

    The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades. PMID:24668802

  5. Timing of climate variability and grassland productivity

    PubMed Central

    Craine, Joseph M.; Nippert, Jesse B.; Elmore, Andrew J.; Skibbe, Adam M.; Hutchinson, Stacy L.; Brunsell, Nathaniel A.

    2012-01-01

    Future climates are forecast to include greater precipitation variability and more frequent heat waves, but the degree to which the timing of climate variability impacts ecosystems is uncertain. In a temperate, humid grassland, we examined the seasonal impacts of climate variability on 27 y of grass productivity. Drought and high-intensity precipitation reduced grass productivity only during a 110-d period, whereas high temperatures reduced productivity only during 25 d in July. The effects of drought and heat waves declined over the season and had no detectable impact on grass productivity in August. If these patterns are general across ecosystems, predictions of ecosystem response to climate change will have to account not only for the magnitude of climate variability but also for its timing. PMID:22331914

  6. Photometric variability in earthshine observations.

    PubMed

    Langford, Sally V; Wyithe, J Stuart B; Turner, Edwin L

    2009-04-01

    The identification of an extrasolar planet as Earth-like will depend on the detection of atmospheric signatures or surface non-uniformities. In this paper we present spatially unresolved flux light curves of Earth for the purpose of studying a prototype extrasolar terrestrial planet. Our monitoring of the photometric variability of earthshine revealed changes of up to 23% per hour in the brightness of Earth’s scattered light at around 600 nm, due to the removal of specular reflection from the view of the Moon. This variability is accompanied by reddening of the spectrum and results from a change in surface properties across the continental boundary between the Indian Ocean and Africa’s east coast. Our results based on earthshine monitoring indicate that specular reflection should provide a useful tool in determining the presence of liquid water on extrasolar planets via photometric observations.

  7. Advancing Technologies for Climate Observation

    NASA Technical Reports Server (NTRS)

    Wu, D.; Esper, J.; Ehsan, N.; Johnson, T.; Mast, W.; Piepmeier, J.; Racette, P.

    2014-01-01

    Climate research needs Accurate global cloud ice measurements Cloud ice properties are fundamental controlling variables of radiative transfer and precipitation Cost-effective, sensitive instruments for diurnal and wide-swath coverage Mature technology for space remote sensing IceCube objectivesDevelop and validate a flight-qualified 883 GHz receiver for future use in ice cloud radiometer missions Raise TRL (57) of 883 GHz receiver technology Reduce instrument cost and risk by developing path to space for COTS sub-mm-wave receiver systems Enable remote sensing of global cloud ice with advanced technologies and techniques

  8. Statistical structure of intrinsic climate variability under global warming

    NASA Astrophysics Data System (ADS)

    Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

    2017-04-01

    Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

  9. Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

    NASA Technical Reports Server (NTRS)

    Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

    2016-01-01

    We compare 27 wheat models’ yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models’ climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models’ sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

  10. An ‘Observational Large Ensemble’ to compare observed and modeled temperature trend uncertainty due to internal variability.

    NASA Astrophysics Data System (ADS)

    Poppick, A. N.; McKinnon, K. A.; Dunn-Sigouin, E.; Deser, C.

    2017-12-01

    Initial condition climate model ensembles suggest that regional temperature trends can be highly variable on decadal timescales due to characteristics of internal climate variability. Accounting for trend uncertainty due to internal variability is therefore necessary to contextualize recent observed temperature changes. However, while the variability of trends in a climate model ensemble can be evaluated directly (as the spread across ensemble members), internal variability simulated by a climate model may be inconsistent with observations. Observation-based methods for assessing the role of internal variability on trend uncertainty are therefore required. Here, we use a statistical resampling approach to assess trend uncertainty due to internal variability in historical 50-year (1966-2015) winter near-surface air temperature trends over North America. We compare this estimate of trend uncertainty to simulated trend variability in the NCAR CESM1 Large Ensemble (LENS), finding that uncertainty in wintertime temperature trends over North America due to internal variability is largely overestimated by CESM1, on average by a factor of 32%. Our observation-based resampling approach is combined with the forced signal from LENS to produce an ‘Observational Large Ensemble’ (OLENS). The members of OLENS indicate a range of spatially coherent fields of temperature trends resulting from different sequences of internal variability consistent with observations. The smaller trend variability in OLENS suggests that uncertainty in the historical climate change signal in observations due to internal variability is less than suggested by LENS.

  11. Changes of reference evapotranspiration in the Haihe River Basin: Present observations and future projection from climatic variables through multi-model ensemble

    NASA Astrophysics Data System (ADS)

    Xing, Wanqiu; Wang, Weiguang; Shao, Quanxi; Peng, Shizhang; Yu, Zhongbo; Yong, Bin; Taylor, John

    2014-04-01

    As the most excellent indicator for hydrological cycle and a central link to water-balance calculations, the reference evapotranspiration (ET0) is of increasing importance in assessing the potential impacts of climate change on hydrology and water resources systems since the climate change has been becoming more pronounced. In this study, we conduct an investigation on the spatial and temporal changes in ET0 of the Haihe River Basin in present and future stages. The ET0 in the past five decades (1961-2010) are calculated by the Penman-Monteith method with historical climatic variables in 40 sites while the ET0 estimation for the future period of 2011-2099 is based on the related climatic variables projected by Coupled General Circulation Model (CGCM) multimodel ensemble projections in Phase 3 of the Coupled Model Intercomparison Project (CMIP3) using the Bayesian Model Average (BMA) approach. Results can be summarized for the present and future as follows. (1) No coherent spatial patterns in ET0 changes are seen in the whole basin. Half of the stations distributed mainly in the eastern and southeastern plain regions present significant negative trends, while only 3 stations in the western mountainous and plateau basin show significant positive trends. Radiation is mainly responsible for the ET0 change in the southern and eastern basin, whereas relative humidity and wind speed are the leading factors in the eastern coastal and north parts. (2) BMA ensemble method is competent to produce lower bias in comparison with other common methods in this basin. Future spatiotemporal ET0 pattern analysis by means of the BMA method based on the ensembles of four CGCMs suggested that although the spatial patterns under three scenarios are different in the forthcoming two decades, generally increasing trends can be found in the 21st century, which is mainly attributed to the significant increasing temperature. In addition, the implication of future ET0 change in agriculture and

  12. Processes Understanding of Decadal Climate Variability

    NASA Astrophysics Data System (ADS)

    Prömmel, Kerstin; Cubasch, Ulrich

    2016-04-01

    The realistic representation of decadal climate variability in the models is essential for the quality of decadal climate predictions. Therefore, the understanding of those processes leading to decadal climate variability needs to be improved. Several of these processes are already included in climate models but their importance has not yet completely been clarified. The simulation of other processes requires sometimes a higher resolution of the model or an extension by additional subsystems. This is addressed within one module of the German research program “MiKlip II – Decadal Climate Predictions” (http://www.fona-miklip.de/en/) with a focus on the following processes. Stratospheric processes and their impact on the troposphere are analysed regarding the climate response to aerosol perturbations caused by volcanic eruptions and the stratospheric decadal variability due to solar forcing, climate change and ozone recovery. To account for the interaction between changing ozone concentrations and climate a computationally efficient ozone chemistry module is developed and implemented in the MiKlip prediction system. The ocean variability and air-sea interaction are analysed with a special focus on the reduction of the North Atlantic cold bias. In addition, the predictability of the oceanic carbon uptake with a special emphasis on the underlying mechanism is investigated. This addresses a combination of physical, biological and chemical processes.

  13. New Perspectives on the Role of Internal Variability in Regional Climate Change and Climate Model Evaluation

    NASA Astrophysics Data System (ADS)

    Deser, C.

    2017-12-01

    Natural climate variability occurs over a wide range of time and space scales as a result of processes intrinsic to the atmosphere, the ocean, and their coupled interactions. Such internally generated climate fluctuations pose significant challenges for the identification of externally forced climate signals such as those driven by volcanic eruptions or anthropogenic increases in greenhouse gases. This challenge is exacerbated for regional climate responses evaluated from short (observations also places strong constraints on how well the spatial and temporal characteristics of natural climate variability are known, especially on multi-decadal time scales. The observational constraints, in turn, pose challenges for evaluation of climate models, including their representation of internal variability and assessing the accuracy of their responses to natural and anthropogenic radiative forcings. A promising new approach to climate model assessment is the advent of large (10-100 member) “initial-condition” ensembles of climate change simulations with individual models. Such ensembles allow for accurate determination, and straightforward separation, of externally forced climate signals and internal climate variability on regional scales. The range of climate trajectories in a given model ensemble results from the fact that each simulation represents a particular sequence of internal variability superimposed upon a common forced response. This makes clear that nature’s single realization is only one of many that could have unfolded. This perspective leads to a rethinking of approaches to climate model evaluation that incorporate observational uncertainty due to limited sampling of internal variability. Illustrative examples across a range of well-known climate phenomena including ENSO, volcanic eruptions, and anthropogenic climate change will be discussed.

  14. Impact of climate variability on tropospheric ozone.

    PubMed

    Grewe, Volker

    2007-03-01

    A simulation with the climate-chemistry model (CCM) E39/C is presented, which covers both the troposphere and stratosphere dynamics and chemistry during the period 1960 to 1999. Although the CCM, by its nature, is not exactly representing observed day-by-day meteorology, there is an overall model’s tendency to correctly reproduce the variability pattern due to an inclusion of realistic external forcings, like observed sea surface temperatures (e.g. El Niño), major volcanic eruption, solar cycle, concentrations of greenhouse gases, and Quasi-Biennial Oscillation. Additionally, climate-chemistry interactions are included, like the impact of ozone, methane, and other species on radiation and dynamics, and the impact of dynamics on emissions (lightning). However, a number of important feedbacks are not yet included (e.g. feedbacks related to biogenic emissions and emissions due to biomass burning). The results show a good representation of the evolution of the stratospheric ozone layer, including the ozone hole, which plays an important role for the simulation of natural variability of tropospheric ozone. Anthropogenic NO(x) emissions are included with a step-wise linear trend for each sector, but no interannual variability is included. The application of a number of diagnostics (e.g. marked ozone tracers) allows the separation of the impact of various processes/emissions on tropospheric ozone and shows that the simulated Northern Hemisphere tropospheric ozone budget is not only dominated by nitrogen oxide emissions and other ozone pre-cursors, but also by changes of the stratospheric ozone budget and its flux into the troposphere, which tends to reduce the simulated positive trend in tropospheric ozone due to emissions from industry and traffic during the late 80s and early 90s. For tropical regions the variability in ozone is dominated by variability in lightning (related to ENSO) and stratosphere-troposphere exchange (related to Northern Hemisphere Stratospheric

  15. Terrestrial essential climate variables (ECVs) at a glance

    USGS Publications Warehouse

    Stitt, Susan; Dwyer, John; Dye, Dennis; Josberger, Edward

    2011-01-01

    The Global Terrestrial Observing System, Global Climate Observing System, World Meteorological Organization, and Committee on Earth Observation Satellites all support consistent global land observations and measurements. To accomplish this goal, the Global Terrestrial Observing System defined ‘essential climate variables’ as measurements of atmosphere, oceans, and land that are technically and economically feasible for systematic observation and that are needed to meet the United Nations Framework Convention on Climate Change and requirements of the Intergovernmental Panel on Climate Change. The following are the climate variables defined by the Global Terrestrial Observing System that relate to terrestrial measurements. Several of them are currently measured most appropriately by in-place observations, whereas others are suitable for measurement by remote sensing technologies. The U.S. Geological Survey is the steward of the Landsat archive, satellite imagery collected from 1972 to the present, that provides a potential basis for deriving long-term, global-scale, accurate, timely and consistent measurements of many of these essential climate variables.

  16. Water vapor variability and comparisons in the subtropical Pacific from The Observing System Research and Predictability Experiment-Pacific Asian Regional Campaign (T-PARC) Driftsonde, Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), and reanalyses

    NASA Astrophysics Data System (ADS)

    Wang, Junhong; Zhang, Liangying; Lin, Po-Hsiung; Bradford, Mark; Cole, Harold; Fox, Jack; Hock, Terry; Lauritsen, Dean; Loehrer, Scot; Martin, Charlie; Vanandel, Joseph; Weng, Chun-Hsiung; Young, Kathryn

    2010-11-01

    During the THORPEX (The Observing System Research and Predictability Experiment) Pacific Asian Regional Campaign (T-PARC), from 1 August to 30 September 2008, ˜1900 high-quality, high vertical resolution soundings were collected over the Pacific Ocean. These include dropsondes deployed from four aircrafts and zero-pressure balloons in the stratosphere (NCAR’s Driftsonde system). The water vapor probability distribution and spatial variability in the northern subtropical Pacific (14°-20°N, 140°E-155°W) are studied using Driftsonde and COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) data and four global reanalysis products. Driftsonde data analysis shows distinct differences of relative humidity (RH) distributions in the free troposphere between the Eastern and Western Pacific (EP and WP, defined as east and west of 180°, respectively), very dry with a single peak of ˜1% RH in the EP and bi-modal distributions in the WP with one peak near ice saturation and one varying with altitude. The frequent occurrences of extreme dry air are found in the driftsonde data with 59% and 19% of RHs less than or equal to 5% and at 1% at 500 hPa in the EP, respectively. RH with respect to ice in the free troposphere exhibits considerable longitudinal variations, very low (

  17. Climate-based seed zones for Mexico: guiding reforestation under observed and projected climate change

    Treesearch

    Dante Castellanos-Acuña; Kenneth W. Vance-Borland; J. Bradley St. Clair; Andreas Hamann; Javier López-Upton; Erika Gómez-Pineda; Juan Manuel Ortega-Rodríguez; Cuauhtémoc Sáenz-Romero

    2018-01-01

    Seed zones for forest tree species are a widely used tool in reforestation programs to ensure that seedlings are well adapted to their planting environments. Here, we propose a climate-based seed zone system for Mexico to address observed and projected climate change. The proposed seed zone classification is based on bands of climate variables often related to genetic…

  18. Detecting Climate Variability in Tropical Rainfall

    NASA Astrophysics Data System (ADS)

    Berg, W.

    2004-05-01

    A number of satellite and merged satellite/in-situ rainfall products have been developed extending as far back as 1979. While the availability of global rainfall data covering over two decades and encompassing two major El Niño events is a valuable resource for a variety of climate studies, significant differences exist between many of these products. Unfortunately, issues such as availability often determine the use of a product for a given application instead of an understanding of the strengths and weaknesses of the various products. Significant efforts have been made to address the impact of sparse sampling by satellite sensors of variable rainfall processes by merging various satellite and in-situ rainfall products. These combine high spatial and temporal frequency satellite infrared data with higher quality passive microwave observations and rain gauge observations. Combining such an approach with spatial and temporal averaging of the data can reduce the large random errors inherent in satellite rainfall estimates to very small levels. Unfortunately, systematic biases can and do result in artificial climate signals due to the underconstrained nature of the rainfall retrieval problem. Because all satellite retrieval algorithms make assumptions regarding the cloud structure and microphysical properties, systematic changes in these assumed parameters between regions and/or times results in regional and/or temporal biases in the rainfall estimates. These biases tend to be relatively small compared to random errors in the retrieval, however, when random errors are reduced through spatial and temporal averaging for climate applications, they become the dominant source of error. Whether or not such biases impact the results for climate studies is very much dependent on the application. For example, all of the existing satellite rainfall products capture the increased rainfall in the east Pacific associated with El Niño, however, the resulting tropical response to

  19. Quantitative Assessment of Antarctic Climate Variability and Change

    NASA Astrophysics Data System (ADS)

    Ordonez, A.; Schneider, D. P.

    2013-12-01

    The Antarctic climate is both extreme and highly variable, but there are indications it may be changing. As the climate in Antarctica can affect global sea level and ocean circulation, it is important to understand and monitor its behavior. Observational and model data have been used to study climate change in Antarctica and the Southern Ocean, though observational data is sparse and models have difficulty reproducing many observed climate features. For example, a leading hypothesis that ozone depletion has been responsible for sea ice trends is struggling with the inability of ozone-forced models to reproduce the observed sea ice increase. The extent to which this data-model disagreement represents inadequate observations versus model biases is unknown. This research assessed a variety of climate change indicators to present an overview of Antarctic climate that will allow scientists to easily access this data and compare indicators with other observational data and model output. Indicators were obtained from observational and reanalysis data for variables such as temperature, sea ice area, and zonal wind stress. Multiple datasets were used for key variables. Monthly and annual anomaly data from Antarctica and the Southern Ocean as well as tropical indices were plotted as time series on common axes for comparison. Trends and correlations were also computed. Zonal wind, surface temperature, and austral springtime sea ice had strong relationships and were further discussed in terms of how they may relate to climate variability and change in the Antarctic. This analysis will enable hypothesized mechanisms of Antarctic climate change to be critically evaluated.

  20. Climate Variability and Sugarcane Yield in Louisiana.

    NASA Astrophysics Data System (ADS)

    Greenland, David

    2005-11-01

    This paper seeks to understand the role that climate variability has on annual yield of sugarcane in Louisiana. Unique features of sugarcane growth in Louisiana and nonclimatic, yield-influencing factors make this goal an interesting and challenging one. Several methods of seeking and establishing the relations between yield and climate variables are employed. First, yield climate relations were investigated at a single research station where crop variety and growing conditions could be held constant and yield relations could be established between a predominant older crop variety and a newer one. Interviews with crop experts and a literature survey were used to identify potential climatic factors that control yield. A statistical analysis was performed using statewide yield data from the American Sugar Cane League from 1963 to 2002 and a climate database. Yield values for later years were adjusted downward to form an adjusted yield dataset. The climate database was principally constructed from daily and monthly values of maximum and minimum temperature and daily and monthly total precipitation for six cooperative weather-reporting stations representative of the area of sugarcane production. The influence of 74 different, though not independent, climate-related variables on sugarcane yield was investigated. The fact that a climate signal exists is demonstrated by comparing mean values of the climate variables corresponding to the upper and lower third of adjusted yield values. Most of these mean-value differences show an intuitively plausible difference between the high- and low-yield years. The difference between means of the climate variables for years corresponding to the upper and lower third of annual yield values for 13 of the variables is statistically significant at or above the 90% level. A correlation matrix was used to identify the variables that had the largest influence on annual yield. Four variables [called here critical climatic variables (CCV

  1. Climate variability and the Icelandic marine ecosystem

    NASA Astrophysics Data System (ADS)

    Astthorsson, Olafur S.; Gislason, Astthor; Jonsson, Steingrimur

    2007-11-01

    This paper describes the main features of the Icelandic marine ecosystem and its response to climate variations during the 20th century. The physical oceanographic character and faunal composition in the southern and western parts of the Icelandic marine ecosystem are different from those in the northern and the eastern areas. The former areas are more or less continuously bathed by warm and saline Atlantic water while the latter are more variable and influenced by Atlantic, Arctic and even Polar water masses to different degrees. Mean annual primary production is higher in the Atlantic water than in the more variable waters north and east of Iceland, and higher closer to land than farther offshore. Similarly, zooplankton production is generally higher in the Atlantic water than in the waters north and east of Iceland. The main spawning grounds of most of the exploited fish stocks are in the Atlantic water south of the country while nursery grounds are off the north coast. In the recent years the total catch of fish and invertebrates has been in the range of 1.6-2.4 million ton. Capelin ( Mallotus villosus) is the most important pelagic stock and cod ( Gadus morhua) is by far the most important demersal fish stock. Whales are an important component of the Icelandic marine ecosystem, and Icelandic waters are an important habitat for some of the largest seabird populations in the Northeast Atlantic. In the waters to the north and east of Iceland, available information suggests the existence of a simple bottom-up controlled food chain from phytoplankton through Calanus, capelin and to cod. Less is known about the structure of the more complex southern part of the ecosystem. The Icelandic marine ecosystem is highly sensitive to climate variations as demonstrated by abundance and distribution changes of many species during the warm period in the 1930s, the cold period in the late 1960s and warming observed during the recent years. Some of these are highlighted in the

  2. Challenges of coordinating global climate observations – Role of satellites in climate monitoring

    NASA Astrophysics Data System (ADS)

    Richter, C.

    2017-12-01

    Global observation of the Earth’s atmosphere, ocean and land is essential for identifying climate variability and change, and for understanding their causes. Observation also provides data that are fundamental for evaluating, refining and initializing the models that predict how the climate system will vary over the months and seasons ahead, and that project how climate will change in the longer term under different assumptions concerning greenhouse gas emissions and other human influences. Long-term observational records have enabled the Intergovernmental Panel on Climate Change to deliver the message that warming of the global climate system is unequivocal. As the Earth’s climate enters a new era, in which it is forced by human activities, as well as natural processes, it is critically important to sustain an observing system capable of detecting and documenting global climate variability and change over long periods of time. High-quality climate observations are required to assess the present state of the ocean, cryosphere, atmosphere and land and place them in context with the past. The global observing system for climate is not a single, centrally managed observing system. Rather, it is a composite “system of systems” comprising a set of climate-relevant observing, data-management, product-generation and data-distribution systems. Data from satellites underpin many of the Essential Climate Variables(ECVs), and their historic and contemporary archives are a key part of the global climate observing system. In general, the ECVs will be provided in the form of climate data records that are created by processing and archiving time series of satellite and in situ measurements. Early satellite data records are very valuable because they provide unique observations in many regions which were not otherwise observed during the 1970s and which can be assimilated in atmospheric reanalyses and so extend the satellite climate data records back in time.

  3. Harvesting Atlantic Cod under Climate Variability

    NASA Astrophysics Data System (ADS)

    Oremus, K. L.

    2016-12-01

    Previous literature links the growth of a fishery to climate variability. This study uses an age-structured bioeconomic model to compare optimal harvest in the Gulf of Maine Atlantic cod fishery under a variable climate versus a static climate. The optimal harvest path depends on the relationship between fishery growth and the interest rate, with higher interest rates dictating greater harvests now at the cost of long-term stock sustainability. Given the time horizon of a single generation of fishermen under assumptions of a static climate, the model finds that the economically optimal management strategy is to harvest the entire stock in the short term and allow the fishery to collapse. However, if the biological growth of the fishery is assumed to vary with climate conditions, such as the North Atlantic Oscillation, there will always be pulses of high growth in the stock. During some of these high-growth years, the growth of the stock and its economic yield can exceed the growth rate of the economy even under high interest rates. This implies that it is not economically optimal to exhaust the New England cod fishery if NAO is included in the biological growth function. This finding may have theoretical implications for the management of other renewable yet exhaustible resources whose growth rates are subject to climate variability.

  4. US Climate Variability and Predictability Project

    SciTech Connect

    Patterson, Mike

    The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year supportmore » of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.« less

  5. Reservoirs performances under climate variability: a case study

    NASA Astrophysics Data System (ADS)

    Longobardi, A.; Mautone, M.; de Luca, C.

    2014-09-01

    A case study, the Piano della Rocca dam (southern Italy) is discussed here in order to quantify the system performances under climate variability conditions. Different climate scenarios have been stochastically generated according to the tendencies in precipitation and air temperature observed during recent decades for the studied area. Climate variables have then been filtered through an ARMA model to generate, at the monthly scale, time series of reservoir inflow volumes. Controlled release has been computed considering the reservoir is operated following the standard linear operating policy (SLOP) and reservoir performances have been assessed through the calculation of reliability, resilience and vulnerability indices (Hashimoto et al. 1982), comparing current and future scenarios of climate variability. The proposed approach can be suggested as a valuable tool to mitigate the effects of moderate to severe and persistent droughts periods, through the allocation of new water resources or the planning of appropriate operational rules.

  6. Linking the Observation of Essential Variables to Societal Benefits

    NASA Astrophysics Data System (ADS)

    Sylak-Glassman, E.

    2017-12-01

    Different scientific communities have established sets of commonly agreed upon essential variables to help coordinate data collection in a variety of Earth observation areas. As an example, the World Meteorological Organization Global Climate Observing System has identified 50 Essential Climate Variables (ECVs), such as sea-surface temperature and carbon dioxide, which are required to monitoring the climate and detect and attribute climate change. In addition to supporting climate science, measuring these ECVs deliver many types of societal benefits, ranging from disaster mitigation to agricultural productivity to human health. While communicating the value in maintaining and improving observational records for these variables has been a challenge, quantifying how the measurement of these ECVs results in the delivery of many different societal benefits may help support their continued measurement. The 2016 National Earth Observation Assessment (EOA 2016) quantified the impact of individual Earth observation systems, sensors, networks, and surveys (or Earth observation systems, for short) on the achievement of 217 Federal objectives in 13 societal benefit areas (SBAs). This study will demonstrate the use of the EOA 2016 dataset to show the different Federal objectives and SBAs that are impacted by the Earth observation systems used to measure ECVs. Describing how the measurements from these Earth observation systems are used not only to maintain the climate record but also to meet additional Federal objectives may help articulate the continued measurement of the ECVs. This study will act as a pilot for the use of the EOA 2016 dataset to map between the measurements required to observe additional sets of variables, such as the Essential Ocean Variables and Essential Biodiversity Variables, and the ability to achieve a variety of societal benefits.

  7. Climatic Variability In Tropical Countries

    NASA Astrophysics Data System (ADS)

    Seneviratne, L. W.

    2003-04-01

    atmospheric condition and hence reduces rainfall for about 1.5 years in tropical countries. This was proved in 2001. This forecast was presented as a paper in 1998 Stockholm Water Symposium. The results were true for Brazil as well. The danger is now over when the episode is relaxed. Second half of 2002 was heavily wet and all the tanks in Sri Lanka except Kirindioya complex in Hambanthoa area got filled. This condition was seen in 1997 where all tanks got filled. El Nino analysts declared 1997 as a drought year as the previous year had experienced warming in Pacific Ocean. Southern Oscillation events are now dissociating to conformity. Discussion Hambanthoa District remained in the dry zone of Sri Lanka for 2000 years as the soil forms expressed as reddish brown earths. Original kingdoms had its base in Anuradhapura in Northcentral Province and Magama in Hambanthota district. Tools used by contemporary farmers were not powerful to use enormous water resources in wet zone. A system of diversion dams and use of run of the river irrigation has proved as the main criteria of that era. Diversion dams and canal projects were in existence. The diversion dams with special shape was mistaken by british surveyors and marked as broken dams in plans. DLOMendis later identified these as effective deflecting dams. The purpose was to wet the area to do cultivation. This system of wetting the land was suitable for dry climates with low rainfall. High technology was introduced by Irrigation Department to construct several reservoirs in Hambanthota. This was planned after the insufficient water use of Ellagala anicut from Kirindi Oya. Next step was to plan a reservoir project at Lunugamvehera dam site. Precipitation data available for 50 years were studied and a reservoir was designed for 20 000acres of paddy. It was planned to cultivate rice for Maha season and other field crops for Yala season. Cultivation commenced in 1985 and the farmers had enough water for 20000acres including

  8. Future warming patterns linked to today’s climate variability

    SciTech Connect

    Dai, Aiguo

    The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

  9. Future warming patterns linked to today’s climate variability

    DOE PAGES

    Dai, Aiguo

    2016-01-11

    The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

  10. Future Warming Patterns Linked to Today’s Climate Variability.

    PubMed

    Dai, Aiguo

    2016-01-11

    The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21(st) century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations during 1950-1979 having more GHG-induced warming in the 21(st) century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950-2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21(st) century in models and in the real world. They support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.

  11. North Pacific decadal climate variability since 1661

    USGS Publications Warehouse

    Biondi, Franco; Gershunov, Alexander; Cayan, Daniel R.

    2001-01-01

    Climate in the North Pacific and North American sectors has experienced interdecadal shifts during the twentieth century. A network of recently developed tree-ring chronologies for Southern and Baja California extends the instrumental record and reveals decadal-scale variability back to 1661. The Pacific decadal oscillation (PDO) is closely matched by the dominant mode of tree-ring variability that provides a preliminary view of multiannual climate fluctuations spanning the past four centuries. The reconstructed PDO index features a prominent bidecadal oscillation, whose amplitude weakened in the late l700s to mid-1800s. A comparison with proxy records of ENSO suggests that the greatest decadal-scale oscillations in Pacific climate between 1706 and 1977 occurred around 1750, 1905, and 1947.

  12. Time series of Essential Climate Variables from Satellite Data

    NASA Astrophysics Data System (ADS)

    Werscheck, M.

    2010-09-01

    Climate change is a fact. We need to know how the climate system will develop in future and how this will affect workaday life. To do this we need climate models for prediction of the future on all time scales, and models to assess the impact of the prediction results to the various sectors of social and economic life. With this knowledge we can take measures to mitigate the causes and adapt to changes. Prerequisite for this is a careful and thorough monitoring of the climate systems. Satellite data are an increasing & valuable source of information to observe the climate system. For many decades now satellite data are available to derive information about our planet earth. EUMETSAT is the European Organisation in charge of the exploitation of satellite data for meteorology and (since the year 2000) climatology. Within the EUMETSAT Satellite Application Facility (SAF) Network, comprising 8 initiatives to derive geophysical parameters from satellite, the Satellite Application Facility on Climate Monitoring (CM SAF) is especially dedicated to provide climate relevant information from satellite data. Many products as e.g. water vapour, radiation at surface and top of atmosphere, cloud properties are available, some of these for more then 2 decades. Just recently the European Space Agency (ESA) launched the Climate Change Initiative (CCI) to derive Essential Climate Variables (ECVs) from satellite data, including e.g. cloud properties, aerosol, ozone, sea surface temperature etc.. The presentation will give an overview on some relevant European activities to derive Essential Climate Variables from satellite data and the links to Global Climate Observing System (GCOS), the Global Satellite Intercalibration System (GSICS) as well as the Sustained Co-ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE CM).

  13. The role of climate variability in extreme floods in Europe

    NASA Astrophysics Data System (ADS)

    Guimarães Nobre, Gabriela; Aerts, Jeroen C. J. H.; Jongman, Brenden; Ward, Philip J.

    2017-04-01

    Between 1980 and 2015, Europe experienced 18% of worldwide weather-related loss events, which accounted for over US500 billion in damage. Consequently, it is urgent to further develop adaptation strategies to mitigate the consequences of weather-related disasters, such as floods. Europe’s capability to prepare for such disasters is challenged by a large range of uncertainties and a limited understanding of the driving forces of hydrometeorological hazards. One of the major sources of uncertainty is the relationship between climate variability and weather-related losses. Previous studies show that climate variability drives temporal changes in hydrometereological variables in Europe. However, their influence on flood risk has received little attention. We investigated the influence of the positive and negative phases of El Niño Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Arctic Oscillation (AO), on the seasonal frequency and intensity of extreme rainfall, and anomalies in flood occurrence and damage compared to the neutral phases of the indices of climate variability. Using statistical methods to analyze relationships between the indices of climate variability and four indicators of flooding, we found that positive and negative phases of NAO and AO are associated with more (or less) frequent and intense seasonal extreme rainfall over large areas of Europe. The relationship between ENSO and both the occurrence of extreme rainfall and intensity of extreme rainfall in Europe is much smaller than the relationship with NAO or AO, but still significant in some regions. We observe that flood damage and flood occurrence have strong links with climate variability, especially in southern and eastern Europe. Therefore, when investigating flooding across Europe, all three indices of climate variability should be considered. Seasonal forecasting of flooding could be enhanced by the inclusion of climate variability indicators .

  14. Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

    NASA Technical Reports Server (NTRS)

    Roberts, Yolanda; Pilewskie, Peter; Kindel, Bruce; Feldman, Daniel; Collins, William D.

    2012-01-01

    The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth’s climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth’s present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time

  15. Short-term climate variability and atmospheric teleconnections from satellite-observed outgoing longwave radiation. I Simultaneous relationships. II – Lagged correlations

    NASA Technical Reports Server (NTRS)

    Lau, K.-M.; Chan, P. H.

    1983-01-01

    Attention is given to the low-frequency variability of outgoing longwave radiation (OLR) fluctuations, their possible correlations over different parts of the globe, and their relationships with teleconnections obtained from other meteorological parameters, for example, geopotential and temperature fields. Simultaneous relationships with respect to the Southern Oscillation (Namais, 1978; Barnett, 1981) signal and the reference OLR fluctuation over the equatorial central Pacific are investigated. Emphasis is placed on the relative importance of the Southern Oscillation (SO) signal over preferred regions. Using lag cross-correlation statistics, possible lagged relationships between the tropics and midlatitudes and their relationships with the SO are then investigated. Only features that are consistent with present knowledge of the dynamics of the system are emphasized. Certain features which may not meet rigorous statistical significance tests but yet are either expected a priori from independent observations or are predicted from dynamical theories are also explored.

  16. Inferring climate variability from skewed proxy records

    NASA Astrophysics Data System (ADS)

    Emile-Geay, J.; Tingley, M.

    2013-12-01

    Many paleoclimate analyses assume a linear relationship between the proxy and the target climate variable, and that both the climate quantity and the errors follow normal distributions. An ever-increasing number of proxy records, however, are better modeled using distributions that are heavy-tailed, skewed, or otherwise non-normal, on account of the proxies reflecting non-normally distributed climate variables, or having non-linear relationships with a normally distributed climate variable. The analysis of such proxies requires a different set of tools, and this work serves as a cautionary tale on the danger of making conclusions about the underlying climate from applications of classic statistical procedures to heavily skewed proxy records. Inspired by runoff proxies, we consider an idealized proxy characterized by a nonlinear, thresholded relationship with climate, and describe three approaches to using such a record to infer past climate: (i) applying standard methods commonly used in the paleoclimate literature, without considering the non-linearities inherent to the proxy record; (ii) applying a power transform prior to using these standard methods; (iii) constructing a Bayesian model to invert the mechanistic relationship between the climate and the proxy. We find that neglecting the skewness in the proxy leads to erroneous conclusions and often exaggerates changes in climate variability between different time intervals. In contrast, an explicit treatment of the skewness, using either power transforms or a Bayesian inversion of the mechanistic model for the proxy, yields significantly better estimates of past climate variations. We apply these insights in two paleoclimate settings: (1) a classical sedimentary record from Laguna Pallcacocha, Ecuador (Moy et al., 2002). Our results agree with the qualitative aspects of previous analyses of this record, but quantitative departures are evident and hold implications for how such records are interpreted, and

  17. Observing Two Important Teaching Variables.

    ERIC Educational Resources Information Center

    Gustafson, John A.

    1986-01-01

    Two behaviors essential to good teaching, teacher expectation and teacher flexibility, have been incorporated into the observation system used in the student teacher program at the University of New Mexico. The importance of these behaviors in teaching and in evaluating student teachers is discussed. (MT)

  18. Essential climatic variables estimation with satellite imagery

    NASA Astrophysics Data System (ADS)

    Kolotii, A.; Kussul, N.; Shelestov, A.; Lavreniuk, M. S.

    2016-12-01

    According to Sendai Framework for Disaster Risk Reduction 2015 – 2030 Leaf Area Index (LAI) is considered as one of essential climatic variables. This variable represents the amount of leaf material in ecosystems and controls the links between biosphere and atmosphere through various processes and enables monitoring and quantitative assessment of vegetation state. LAI has added value for such important global resources monitoring tasks as drought mapping and crop yield forecasting with use of data from different sources [1-2]. Remote sensing data from space can be used to estimate such biophysical parameter at regional and national scale. High temporal satellite imagery is usually required to capture main parameters of crop growth [3]. Sentinel-2 mission launched in 2015 be ESA is a source of high spatial and temporal resolution satellite imagery for mapping biophysical parameters. Products created with use of automated Sen2-Agri system deployed during Sen2-Agri country level demonstration project for Ukraine will be compared with our independent results of biophysical parameters mapping. References Shelestov, A., Kolotii, A., Camacho, F., Skakun, S., Kussul, O., Lavreniuk, M., & Kostetsky, O. (2015, July). Mapping of biophysical parameters based on high resolution EO imagery for JECAM test site in Ukraine. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1733-1736 Kolotii, A., Kussul, N., Shelestov, A., Skakun, S., Yailymov, B., Basarab, R., … & Ostapenko, V. (2015). Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 39-44. Kussul, N., Lemoine, G., Gallego, F. J., Skakun, S. V., Lavreniuk, M., & Shelestov, A. Y. Parcel-Based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 (6), 2500-2508.

  19. Do bioclimate variables improve performance of climate envelope models?

    USGS Publications Warehouse

    Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

    2012-01-01

    Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

  20. Canopy interception variability in changing climate

    NASA Astrophysics Data System (ADS)

    Kalicz, Péter; Herceg, András; Kisfaludi, Balázs; Csáki, Péter; Gribovszki, Zoltán

    2017-04-01

    Tree canopies play a rather important role in forest hydrology. They intercept significant amounts of precipitation and evaporate back into the atmosphere during and after precipitation event. This process determines the net intake of forest soils and so important factor of hydrological processes in forested catchments. Average amount of interception loss is determined by the storage capacity of tree canopies and the rainfall distribution. Canopy storage capacity depends on several factors. It shows strong correlation with the leaf area index (LAI). Some equations are available to quantify this dependence. LAI shows significant variability both spatial and temporal scale. There are several methods to derive LAI from remote sensed data which helps to follow changes of it. In this study MODIS sensor based LAI time series are used to estimate changes of the storage capacity. Rainfall distribution derived from the FORESEE database which is developed for climate change related impact studies in the Carpathian Basin. It contains observation based precipitation data for the past and uses bias correction method for the climate projections. In this study a site based estimation is outworked for the Sopron Hills area. Sopron Hills is located at the eastern foothills of the Alps in Hungary. The study site, namely Hidegvíz Valley experimental catchment, is located in the central valley of the Sopron Hills. Long-term interception measurements are available in several forest sites in Hidegvíz Valley. With the combination of the ground based observations, MODIS LAI datasets a simple function is developed to describe the average yearly variations in canopy storage. Interception measurements and the CREMAP evapotranspiration data help to calibrate a simple interception loss equation based on Merriam’s work. Based on these equation and the FORESEE bias corrected precipitation data an estimation is outworked for better understanding of the feedback of forest crown on hydrological

  1. Transient nature of late Pleistocene climate variability.

    PubMed

    Crowley, Thomas J; Hyde, William T

    2008-11-13

    Climate in the early Pleistocene varied with a period of 41 kyr and was related to variations in Earth’s obliquity. About 900 kyr ago, variability increased and oscillated primarily at a period of approximately 100 kyr, suggesting that the link was then with the eccentricity of Earth’s orbit. This transition has often been attributed to a nonlinear response to small changes in external boundary conditions. Here we propose that increasing variablility within the past million years may indicate that the climate system was approaching a second climate bifurcation point, after which it would transition again to a new stable state characterized by permanent mid-latitude Northern Hemisphere glaciation. From this perspective the past million years can be viewed as a transient interval in the evolution of Earth’s climate. We support our hypothesis using a coupled energy-balance/ice-sheet model, which furthermore predicts that the future transition would involve a large expansion of the Eurasian ice sheet. The process responsible for the abrupt change seems to be the albedo discontinuity at the snow-ice edge. The best-fit model run, which explains almost 60% of the variance in global ice volume during the past 400 kyr, predicts a rapid transition in the geologically near future to the proposed glacial state. Should it be attained, this state would be more ‘symmetric’ than the present climate, with comparable areas of ice/sea-ice cover in each hemisphere, and would represent the culmination of 50 million years of evolution from bipolar nonglacial climates to bipolar glacial climates.

  2. Climatic variability leads to later seasonal flowering of Floridian plants.

    PubMed

    Von Holle, Betsy; Wei, Yun; Nickerson, David

    2010-07-21

    Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses.

  3. Climatic Variability Leads to Later Seasonal Flowering of Floridian Plants

    PubMed Central

    Von Holle, Betsy; Wei, Yun; Nickerson, David

    2010-01-01

    Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses. PMID:20657765

  4. Weighting climate model projections using observational constraints.

    PubMed

    Gillett, Nathan P

    2015-11-13

    Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081-2100 relative to 1986-2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5-95% warming range of 0.8-2.5 K is somewhat lower than the unweighted range of 1.1-2.6 K reported in the IPCC AR5. © 2015 The Authors.

  5. Climate Variability and Wildfires: Insights from Global Earth System Models

    NASA Astrophysics Data System (ADS)

    Ward, D. S.; Shevliakova, E.; Malyshev, S.; Lamarque, J. F.; Wittenberg, A. T.

    2016-12-01

    Better understanding of the relationship between variability in global climate and emissions from wildfires is needed for predictions of fire activity on interannual to multi-decadal timescales. Here we investigate this relationship using the long, preindustrial control simulations and historical ensembles of two Earth System models; CESM1 and the NOAA/GFDL ESM2Mb. There is smaller interannual variability of global fires in both models than in present day inventories, especially in boreal regions where observed fires vary substantially from year to year. Patterns of fire response to climate oscillation indices, including the El Niño / Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Meridional Oscillation (AMO) are explored with the model results and compared to the response derived from satellite measurements and proxy observations. Increases in fire emissions in southeast Asia and boreal North America are associated with positive ENSO and PDO, while United States fires and Sahel fires decrease for the same climate conditions. Boreal fire emissions decrease in CESM1 for the warm phase of the AMO, while ESM2Mb did not produce a reliable AMO. CESM1 produces a weak negative trend in global fire emissions for the period 1920 to 2005, while ESM2Mb produces a positive trend over the same period. Both trends are statistically significant at a confidence level of 95% or greater given the variability derived from the respective preindustrial controls. In addition to climate variability impacts on fires, we also explore the impacts of fire emissions on climate variability and atmospheric chemistry. We analyze three long, free-evolving ESM2Mb simulations; one without fire emissions, one with constant year-over-year fire emissions based on a present day inventory, and one with interannually varying fire emissions coupled between the terrestrial and atmospheric components of the model, to gain a better understanding of the role of fire emissions in

  6. Solar Variability in the Context of Other Climate Forcing Mechanisms

    NASA Technical Reports Server (NTRS)

    Hansen, James E.

    1999-01-01

    I compare and contrast climate forcings due to solar variability with climate forcings due to other mechanisms of climate change, interpretation of the role of the sun in climate change depends upon climate sensitivity and upon the net forcing by other climate change mechanisms. Among the potential indirect climate forcings due to solar variability, only that due to solar cycle induced ozone changes has been well quantified. There is evidence that the sun has been a significant player in past climate change on decadal to century time scales, and that it has the potential to contribute to climate change in the 21st century.

  7. North Atlantic sub-decadal variability in climate models

    NASA Astrophysics Data System (ADS)

    Reintges, Annika; Martin, Thomas; Latif, Mojib; Park, Wonsun

    2017-04-01

    The North Atlantic Oscillation (NAO) is the dominant variability mode for the winter climate of the North Atlantic sector. During a positive (negative) NAO phase, the sea level pressure (SLP) difference between the subtropical Azores high and the subpolar Icelandic low is anomalously strong (weak). This affects, for example, temperature, precipitation, wind, and surface heat flux over the North Atlantic, and over large parts of Europe. In observations we find enhanced sub-decadal variability of the NAO index that goes along with a dipolar sea surface temperature (SST) pattern. The corresponding SLP and SST patterns are reproduced in a control experiment of the Kiel Climate Model (KCM). Large-scale air-sea interaction is suggested to be essential for the North Atlantic sub-decadal variability in the KCM. The Atlantic Meridional Overturning Circulation (AMOC) plays a key role, setting the timescale of the variability by providing a delayed negative feedback to the NAO. The interplay of the NAO and the AMOC on the sub-decadal timescale is further investigated in the CMIP5 model ensemble. For example, the average CMIP5 model AMOC pattern associated with sub-decadal variability is characterized by a deep-reaching dipolar structure, similar to the KCM’s sub-decadal AMOC variability pattern. The results suggest that dynamical air-sea interactions are crucial to generate enhanced sub-decadal variability in the North Atlantic climate.

  8. Variable temperature seat climate control system

    DOEpatents

    Karunasiri, Tissa R.; Gallup, David F.; Noles, David R.; Gregory, Christian T.

    1997-05-06

    A temperature climate control system comprises a variable temperature seat, at least one heat pump, at least one heat pump temperature sensor, and a controller. Each heat pump comprises a number of Peltier thermoelectric modules for temperature conditioning the air in a main heat exchanger and a main exchanger fan for passing the conditioned air from the main exchanger to the variable temperature seat. The Peltier modules and each main fan may be manually adjusted via a control switch or a control signal. Additionally, the temperature climate control system may comprise a number of additional temperature sensors to monitor the temperature of the ambient air surrounding the occupant as well as the temperature of the conditioned air directed to the occupant. The controller is configured to automatically regulate the operation of the Peltier modules and/or each main fan according to a temperature climate control logic designed both to maximize occupant comfort during normal operation, and minimize possible equipment damage, occupant discomfort, or occupant injury in the event of a heat pump malfunction.

  9. Atmospheric River Characteristics under Decadal Climate Variability

    NASA Astrophysics Data System (ADS)

    Done, J.; Ge, M.

    2017-12-01

    How does decadal climate variability change the nature and predictability of atmospheric river events? Decadal swings in atmospheric river frequency, or shifts in the proportion of precipitation falling as rain, could challenge current water resource and flood risk management practice. Physical multi-scale processes operating between Pacific sea surface temperatures (SSTs) and atmospheric rivers over the Western U.S. are explored using the global Model for Prediction Across Scales (MPAS). A 45km global mesh is refined over the Western U.S. to 12km to capture the major terrain effects on precipitation. The performance of the MPAS is first evaluated for a case study atmospheric river event over California. Atmospheric river characteristics are then compared in a pair of idealized simulations, each driven by Pacific SST patterns characteristic of opposite phases of the Interdecadal Pacific Oscillation (IPO). Given recent evidence that we have entered a positive phase of the IPO, implications for current reservoir management practice over the next decade will be discussed. This work contributes to the NSF-funded project UDECIDE (Understanding Decision-Climate Interactions on Decadal Scales). UDECIDE brings together practitioners, engineers, statisticians, and climate scientists to understand the role of decadal climate information for water management and decisions.

  10. Variability of precipitation in Poland under climate change

    NASA Astrophysics Data System (ADS)

    Szwed, Małgorzata

    2018-02-01

    The surface warming has been widespread over the entire globe. Central Europe, including Poland, is not an exception. Global temperature increases are accompanied by changes in other climatic variables. Climate change in Poland manifests itself also as change in annual sums of precipitation. They have been slightly growing but, what is more important, seasonal and monthly distributions of precipitation have been also changing. The most visible increases have been observed during colder half-year, especially in March. A decreasing contribution of summer precipitation total (June-August) to the annual total is observed. Climate projections for Poland predict further warming and continuation of already observed changes in the quantity of precipitation as well as its spatial and seasonal distribution.

  11. Climate variability and Port wine quality

    NASA Astrophysics Data System (ADS)

    Gouveia, Celia; Liberato, Margarida L. R.; Trigo, Ricardo M.; Dacamara, Carlos

    2010-05-01

    ), suggesting that this type of analysis may be used in developing a tool that may help anticipating a vintage year, based on already available seasonal climate outlooks. Célia Gouveia and Ricardo M. Trigo. “Influence of climate variability on wheat production in Portugal”. GeoENV2006- 6th International Conference on Geostatistics for Environmental Applications, Rhodes, October, 25-27, 2006 Miranda, P.M.A., F. Coelho, A. R. Tomé, M. A Valente., A. Carvalho, C. Pires, H. O. Pires, V. C. Cabrinha and C. Ramalho (2002) “20th Century Portuguese Climate and Climate Scenarios”, in Santos, F.D., K Forbes and R. Moita (eds) Climate Change in Portugal: Scenarios, Impacts and Adptation Measures”, 27-83. Gradiva

  12. Climate-mediated spatiotemporal variability in terrestrial productivity across Europe

    NASA Astrophysics Data System (ADS)

    Wu, X.; Babst, F.; Ciais, P.; Frank, D.; Reichstein, M.; Wattenbach, M.; Zang, C.; Mahecha, M. D.

    2014-06-01

    Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from impacts of other mechanisms underlying the spatiotemporal patterns of IAV of the ecosystem productivity. In this study we investigated the spatiotemporal patterns of IAV of historical observations of European crop yields in tandem with a set of climate variables. We further evaluated if relevant remote-sensing retrievals of NDVI (normalized difference vegetation index) and FAPAR (fraction of absorbed photosynthetically active radiation) depict a similar behaviour. Our results reveal distinct spatial patterns in the IAV of the analysed proxies linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions in both crop yield and remote-sensing observations. Our results further indicate that variations in the water balance during the active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity-related variables in temperate Europe. Overall, we observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe during the 1975-2009 period. In the same regions, a simultaneous increase in the IAV of water availability was detected. These findings suggest intricate responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become potentially more sensitive to changes in water availability in the dry regions in Europe. The changing sensitivity of terrestrial productivity accompanied by the changing IAV of climate is expected to impact carbon stocks and the net carbon balance

  13. A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

    PubMed Central

    Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

    2013-01-01

    We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

  14. Impacts of climate change and internal climate variability on french rivers streamflows

    NASA Astrophysics Data System (ADS)

    Dayon, Gildas; Boé, Julien; Martin, Eric

    2016-04-01

    The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability

  15. Observation, Serendipity, and Climatic Change

    ERIC Educational Resources Information Center

    Schaefer, Vincent J.

    1974-01-01

    Provides an illustration of the contribution of serendipitous happenings to scientific information and relates this to a consideration of social and technical problems confronting mankind. The author decries an unfortunate tendency in science today: that of discarding observational aspects of field activities which cannot easily be made…

  16. Emergent constraint on equilibrium climate sensitivity from global temperature variability.

    PubMed

    Cox, Peter M; Huntingford, Chris; Williamson, Mark S

    2018-01-17

    Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO 2 ) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO 2 . Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

  17. Emergent constraint on equilibrium climate sensitivity from global temperature variability

    NASA Astrophysics Data System (ADS)

    Cox, Peter M.; Huntingford, Chris; Williamson, Mark S.

    2018-01-01

    Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

  18. Online Impact Prioritization of Essential Climate Variables on Climate Change

    NASA Astrophysics Data System (ADS)

    Forsythe-Newell, S. P.; Barkstrom, B. B.; Roberts, K. P.

    2007-12-01

    The National Oceanic & Atmospheric Administration (NOAA)’s NCDC Scientific Data Stewardship (SDS) Team has developed an online prototype that is capable of displaying the “big picture” perspective of all Essential Climate Variable (ECV) impacts on society and value to the IPCC. This prototype ECV-Model provides the ability to visualize global ECV information with options to drill down in great detail. It offers a quantifiable prioritization of ECV impacts that potentially may significantly enhance collaboration with respect to dealing effectively with climate change. The ECV-Model prototype assures anonymity and provides an online input mechanism for subject matter experts and decision makers to access, review and submit: (1) ranking of ECV”s, (2) new ECV’s and associated impact categories and (3) feedback about ECV”s, satellites, etc. Input and feedback are vetted by experts before changes or additions are implemented online. The SDS prototype also provides an intuitive one-stop web site that displays past, current and planned launches of satellites; and general as well as detailed information in conjunction with imagery. NCDC’s version 1.0 release will be available to the public and provide an easy “at-a-glance” interface to rapidly identify gaps and overlaps of satellites and associated instruments monitoring climate change ECV’s. The SDS version 1.1 will enhance depiction of gaps and overlaps with instruments associated with In-Situ and Satellites related to ECVs. NOAA’s SDS model empowers decision makers and the scientific community to rapidly identify weaknesses and strengths in monitoring climate change ECV’s and potentially significantly enhance collaboration.

  19. A Numerical Climate Observing Network Design Study

    NASA Technical Reports Server (NTRS)

    Stammer, Detlef

    2003-01-01

    This project was concerned with three related questions of an optimal design of a climate observing system: 1. The spatial sampling characteristics required from an ARGO system. 2. The degree to which surface observations from ARGO can be used to calibrate and test satellite remote sensing observations of sea surface salinity (SSS) as it is anticipated now. 3. The more general design of an climate observing system as it is required in the near future for CLIVAR in the Atlantic. An important question in implementing an observing system is that of the sampling density required to observe climate-related variations in the ocean. For that purpose this project was concerned with the sampling requirements for the ARGO float system, but investigated also other elements of a climate observing system. As part of this project we studied the horizontal and vertical sampling characteristics of a global ARGO system which is required to make it fully complementary to altimeter data with the goal to capture climate related variations on large spatial scales (less thanAttachment: 1000 km). We addressed this question in the framework of a numerical model study in the North Atlantic with an 1/6 horizontal resolution. The advantage of a numerical design study is the knowledge of the full model state. Sampled by a synthetic float array, model results will therefore allow to test and improve existing deployment strategies with the goal to make the system as optimal and cost-efficient as possible. Attachment: “Optimal observations for variational data assimilation”.

  20. Food Price Volatility and Decadal Climate Variability

    NASA Astrophysics Data System (ADS)

    Brown, M. E.

    2013-12-01

    The agriculture system is under pressure to increase production every year as global population expands and more people move from a diet mostly made up of grains, to one with more meat, dairy and processed foods. Weather shocks and large changes in international commodity prices in the last decade have increased pressure on local food prices. This paper will review several studies that link climate variability as measured with satellite remote sensing to food price dynamics in 36 developing countries where local monthly food price data is available. The focus of the research is to understand how weather and climate, as measured by variations in the growing season using satellite remote sensing, has affected agricultural production, food prices and access to food in agricultural societies. Economies are vulnerable to extreme weather at multiple levels. Subsistence small holders who hold livestock and consume much of the food they produce are vulnerable to food production variability. The broader society, however, is also vulnerable to extreme weather because of the secondary effects on market functioning, resource availability, and large-scale impacts on employment in trading, trucking and wage labor that are caused by weather-related shocks. Food price variability captures many of these broad impacts and can be used to diagnose weather-related vulnerability across multiple sectors. The paper will trace these connections using market-level data and analysis. The context of the analysis is the humanitarian aid community, using the guidance of the USAID Famine Early Warning Systems Network and the United Nation’s World Food Program in their response to food security crises. These organizations have worked over the past three decades to provide baseline information on food production through satellite remote sensing data and agricultural yield models, as well as assessments of food access through a food price database. Econometric models and spatial analysis are used

  1. Nonlinear dynamical modes of climate variability: from curves to manifolds

    NASA Astrophysics Data System (ADS)

    Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

    2016-04-01

    The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

  2. Climate variability drives recent tree mortality in Europe.

    PubMed

    Neumann, Mathias; Mues, Volker; Moreno, Adam; Hasenauer, Hubert; Seidl, Rupert

    2017-11-01

    Tree mortality is an important process in forest ecosystems, frequently hypothesized to be highly climate sensitive. Yet, tree death remains one of the least understood processes of forest dynamics. Recently, changes in tree mortality have been observed in forests around the globe, which could profoundly affect ecosystem functioning and services provisioning to society. We describe continental-scale patterns of recent tree mortality from the only consistent pan-European forest monitoring network, identifying recent mortality hotspots in southern and northern Europe. Analyzing 925,462 annual observations of 235,895 trees between 2000 and 2012, we determine the influence of climate variability and tree age on interannual variation in tree mortality using Cox proportional hazard models. Warm summers as well as high seasonal variability in precipitation increased the likelihood of tree death. However, our data also suggest that reduced cold-induced mortality could compensate increased mortality related to peak temperatures in a warming climate. Besides climate variability, age was an important driver of tree mortality, with individual mortality probability decreasing with age over the first century of a trees life. A considerable portion of the observed variation in tree mortality could be explained by satellite-derived net primary productivity, suggesting that widely available remote sensing products can be used as an early warning indicator of widespread tree mortality. Our findings advance the understanding of patterns of large-scale tree mortality by demonstrating the influence of seasonal and diurnal climate variation, and highlight the potential of state-of-the-art remote sensing to anticipate an increased likelihood of tree mortality in space and time. © 2017 John Wiley & Sons Ltd.

  3. Climate controls on streamflow variability in the Missouri River Basin

    NASA Astrophysics Data System (ADS)

    Wise, E.; Woodhouse, C. A.; McCabe, G. J., Jr.; Pederson, G. T.; St-Jacques, J. M.

    2017-12-01

    The Missouri River’s hydroclimatic variability presents a challenge for water managers, who must balance many competing demands on the system. Water resources in the Missouri River Basin (MRB) have increasingly been challenged by the droughts and floods that have occurred over the past several decades and the potential future exacerbation of these extremes by climate change. Here, we use observed and modeled hydroclimatic data and estimated natural flow records to describe the climatic controls on streamflow in the upper and lower portions of the MRB, examine atmospheric and oceanic patterns associated with high- and low-flow years, and investigate trends in climate and streamflow over the instrumental period. Results indicate that the two main source regions for total outflow, in the uppermost and lowermost parts of the basin, are under the influence of very different sets of climatic controls. Winter precipitation, impacted by changes in zonal versus meridional flow from the Pacific Ocean, as well as spring precipitation and temperature, play a key role in surface water supply variability in the upper basin. Lower basin flow is significantly correlated with precipitation in late spring and early summer, indicative of Atlantic-influenced circulation variability affecting the flow of moisture from the Gulf of Mexico. The upper basin, with decreasing snowpack and streamflow and warming spring temperatures, will be less likely to provide important flow supplements to the lower basin in the future.

  4. Revealing Relationships among Relevant Climate Variables with Information Theory

    NASA Technical Reports Server (NTRS)

    Knuth, Kevin H.; Golera, Anthony; Curry, Charles T.; Huyser, Karen A.; Kevin R. Wheeler; Rossow, William B.

    2005-01-01

    The primary objective of the NASA Earth-Sun Exploration Technology Office is to understand the observed Earth climate variability, thus enabling the determination and prediction of the climate’s response to both natural and human-induced forcing. We are currently developing a suite of computational tools that will allow researchers to calculate, from data, a variety of information-theoretic quantities such as mutual information, which can be used to identify relationships among climate variables, and transfer entropy, which indicates the possibility of causal interactions. Our tools estimate these quantities along with their associated error bars, the latter of which is critical for describing the degree of uncertainty in the estimates. This work is based upon optimal binning techniques that we have developed for piecewise-constant, histogram-style models of the underlying density functions. Two useful side benefits have already been discovered. The first allows a researcher to determine whether there exist sufficient data to estimate the underlying probability density. The second permits one to determine an acceptable degree of round-off when compressing data for efficient transfer and storage. We also demonstrate how mutual information and transfer entropy can be applied so as to allow researchers not only to identify relations among climate variables, but also to characterize and quantify their possible causal interactions.

  5. Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

    NASA Astrophysics Data System (ADS)

    Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

    2018-04-01

    This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus’ analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent

  6. Assessing the Effects of Climate on Global Fluvial Discharge Variability

    NASA Astrophysics Data System (ADS)

    Hansford, M. R.; Plink-Bjorklund, P.

    2017-12-01

    Plink-Bjorklund (2015) established the link between precipitation seasonality and river discharge variability in the monsoon domain and subtropical rivers (see also Leier et al, 2005; Fielding et al., 2009), resulting in distinct morphodynamic processes and a sedimentary record distinct from perennial precipitation zone in tropical rainforest zone and mid latitudes. This study further develops our understanding of discharge variability using a modern global river database created with data from the Global Runoff Data Centre (GRDC). The database consists of daily discharge for 595 river stations and examines them using a series of discharge variability indexes (DVI) on different temporal scales to examine how discharge variability occurs in river systems around the globe. These indexes examine discharge of individual days and monthly averages that allows for comparison of river systems against each other, regardless of size of the river. Comparing river discharge patterns in seven climate zones (arid, cold, humid subtropics, monsoonal, polar, rainforest, and temperate) based off the Koppen-Geiger climate classifications reveals a first order climatic control on discharge patterns and correspondingly sediment transport. Four groupings of discharge patterns emerge when coming climate zones and DVI: persistent, moderate, seasonal, and erratic. This dataset has incredible predictive power about the nature of discharge in fluvial systems around the world. These seasonal effects on surface water supply affects river morphodynamics and sedimentation on a wide timeframe, ranging from large single events to an inter-annual or even decadal timeframe. The resulting sedimentary deposits lead to differences in fluvial architecture on a range of depositional scales from sedimentary structures and bedforms to channel complex systems. These differences are important to accurately model for several reasons, ranging from stratigraphic and paleoenviromental reconstructions to more

  7. Solar forcing synchronizes decadal North Atlantic climate variability.

    PubMed

    Thiéblemont, Rémi; Matthes, Katja; Omrani, Nour-Eddine; Kodera, Kunihiko; Hansen, Felicitas

    2015-09-15

    Quasi-decadal variability in solar irradiance has been suggested to exert a substantial effect on Earth’s regional climate. In the North Atlantic sector, the 11-year solar signal has been proposed to project onto a pattern resembling the North Atlantic Oscillation (NAO), with a lag of a few years due to ocean-atmosphere interactions. The solar/NAO relationship is, however, highly misrepresented in climate model simulations with realistic observed forcings. In addition, its detection is particularly complicated since NAO quasi-decadal fluctuations can be intrinsically generated by the coupled ocean-atmosphere system. Here we compare two multi-decadal ocean-atmosphere chemistry-climate simulations with and without solar forcing variability. While the experiment including solar variability simulates a 1-2-year lagged solar/NAO relationship, comparison of both experiments suggests that the 11-year solar cycle synchronizes quasi-decadal NAO variability intrinsic to the model. The synchronization is consistent with the downward propagation of the solar signal from the stratosphere to the surface.

  8. Quality Assurance for Essential Climate Variables

    NASA Astrophysics Data System (ADS)

    Folkert Boersma, K.; Muller, Jan-Peter

    2015-04-01

    Satellite data are of central interest to the QA4ECV project. Satellites have revolutionized the Earth’s observation system of climate change and air quality over the past three decades, providing continuous data for the entire Earth. However, many users of these data are lost in the fog as to the quality of these satellite data. Because of this, the European Union expressed in its 2013 FP7 Space Research Call a need for reliable, traceable, and understandable quality information on satellite data records that could serve as a blueprint contribution to a future Copernicus Climate Change Service. The potential of satellite data to benefit climate change and air quality services is too great to be ignored. QA4ECV therefore bridges the gap between end-users of satellite data and the satellite data products. We are developing an internationally acceptable Quality Assurance (QA) framework that provides understandable and traceable quality information for satellite data used in climate and air quality services. Such a framework should deliver the historically linked long-term data sets that users need, in a format that they can readily use. QA4ECV has approached more than 150 users and suppliers of satellite data to collect their needs and expectations. The project will use their response as a guideline for developing user-friendly tools to obtain information on the completeness, accuracy, and fitness-for-purpose of the satellite datasets. QA4ECV collaborates with 4 joint FP7 Space projects in reaching out to scientists, policy makers, and other end-users of satellite data to improve understanding of the special challenges -and also opportunities- of working with satellite data for climate and air quality purposes. As a demonstration of its capacity, QA4ECV will generate multi-decadal climate data records for 3 atmospheric ECV precursors (nitrogen dioxide, formaldehyde, and carbon monoxide) and 3 land ECVs (albedo, leaf area index and absorbed photosynthetically active

  9. Catchments’ hedging strategy on evapotranspiration for climatic variability

    NASA Astrophysics Data System (ADS)

    Ding, W.; Zhang, C.; Li, Y.; Tang, Y.; Wang, D.; Xu, B.

    2017-12-01

    Hydrologic responses to climate variability and change are important for human society. Here we test the hypothesis that natural catchments utilize hedging strategies for evapotranspiration and water storage carryover with uncertain future precipitation. The hedging strategy for evapotranspiration in catchments under different levels of water availability is analytically derived from the economic perspective. It is found that there exists hedging between evapotranspiration for current and future only with a portion of water availability. Observation data sets of 160 catchments in the United States covering the period from 1983 to 2003 demonstrate the existence of hedging in catchment hydrology and validate the proposed hedging strategies. We also find that more water is allocated to carryover storage for hedging against the future evapotranspiration risk in the catchments with larger aridity indexes or with larger uncertainty in future precipitation, i.e., long-term climate and precipitation variability control the degree of hedging.

  10. Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics.

    PubMed

    Itter, Malcolm S; Finley, Andrew O; D’Amato, Anthony W; Foster, Jane R; Bradford, John B

    2017-06-01

    Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics-changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly

  11. Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics

    USGS Publications Warehouse

    Itter, Malcolm S.; Finley, Andrew O.; D’Amato, Anthony W.; Foster, Jane R.; Bradford, John B.

    2017-01-01

    Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics—changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly

  12. The influence of climate variables on dengue in Singapore.

    PubMed

    Pinto, Edna; Coelho, Micheline; Oliver, Leuda; Massad, Eduardo

    2011-12-01

    In this work we correlated dengue cases with climatic variables for the city of Singapore. This was done through a Poisson Regression Model (PRM) that considers dengue cases as the dependent variable and the climatic variables (rainfall, maximum and minimum temperature and relative humidity) as independent variables. We also used Principal Components Analysis (PCA) to choose the variables that influence in the increase of the number of dengue cases in Singapore, where PC₁ (Principal component 1) is represented by temperature and rainfall and PC₂ (Principal component 2) is represented by relative humidity. We calculated the probability of occurrence of new cases of dengue and the relative risk of occurrence of dengue cases influenced by climatic variable. The months from July to September showed the highest probabilities of the occurrence of new cases of the disease throughout the year. This was based on an analysis of time series of maximum and minimum temperature. An interesting result was that for every 2-10°C of variation of the maximum temperature, there was an average increase of 22.2-184.6% in the number of dengue cases. For the minimum temperature, we observed that for the same variation, there was an average increase of 26.1-230.3% in the number of the dengue cases from April to August. The precipitation and the relative humidity, after analysis of correlation, were discarded in the use of Poisson Regression Model because they did not present good correlation with the dengue cases. Additionally, the relative risk of the occurrence of the cases of the disease under the influence of the variation of temperature was from 1.2-2.8 for maximum temperature and increased from 1.3-3.3 for minimum temperature. Therefore, the variable temperature (maximum and minimum) was the best predictor for the increased number of dengue cases in Singapore.

  13. Observations and simulations of the ionospheric lunar tide: Seasonal variability

    NASA Astrophysics Data System (ADS)

    Pedatella, N. M.

    2014-07-01

    The seasonal variability of the ionospheric lunar tide is investigated using a combination of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations and thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM) simulations. The present study focuses on the seasonal variability of the lunar tide in the ionosphere and its potential connection to the occurrence of stratosphere sudden warmings (SSWs). COSMIC maximum F region electron density (NmF2) and total electron content observations reveal a primarily annual variation of the ionospheric lunar tide, with maximum amplitudes occurring at low latitudes during December-February. Simulations of the lunar tide climatology in TIME-GCM display a similar annual variability as the COSMIC observations. This leads to the conclusion that the annual variability of the lunar tide in the ionosphere is not solely due to the occurrence of SSWs. Rather, the annual variability of the lunar tide in the ionosphere is generated by the seasonal variability of the lunar tide at E region altitudes. However, compared to the observations, the ionospheric lunar tide annual variability is weaker in the climatological simulations which is attributed to the occurrence of SSWs during the majority of the years included in the observations. Introducing a SSW into the TIME-GCM simulation leads to an additional enhancement of the lunar tide during Northern Hemisphere winter, increasing the lunar tide annual variability and resulting in an annual variability that is more consistent with the observations. The occurrence of SSWs can therefore potentially bias lunar tide climatologies, and it is important to consider these effects in studies of the lunar tide in the atmosphere and ionosphere.

  14. Ecological Assimilation of Land and Climate Observations – the EALCO model

    NASA Astrophysics Data System (ADS)

    Wang, S.; Zhang, Y.; Trishchenko, A.

    2004-05-01

    Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net

  15. On the Reprocessing and Reanalysis of Observations for Climate

    NASA Technical Reports Server (NTRS)

    Bosilovich, Michael G.; Kennedy, John; Dee, Dick; Allan, R.; O’Neill, Alan

    2013-01-01

    The long observational record is critical to our understanding of the Earths climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and to summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide an climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

  16. Effects of climatic variability and change

    Treesearch

    Michael G. Ryan; James M. Vose

    2012-01-01

    Climate profoundly shapes forests. Forest species composition, productivity, availability of goods and services, disturbance regimes, and location on the landscape are all regulated by climate. Much research attention has focused on the problem of projecting the response of forests to changing climate, elevated atmospheric carbon dioxide (CO2)…

  17. The Dependencies of Ecosystem Pattern, Structure, and Dynamics on Climate, Climate Variability, and Climate Change

    NASA Astrophysics Data System (ADS)

    Flanagan, S.; Hurtt, G. C.; Fisk, J. P.; Rourke, O.

    2012-12-01

    A robust understanding of the sensitivity of the pattern, structure, and dynamics of ecosystems to climate, climate variability, and climate change is needed to predict ecosystem responses to current and projected climate change. We present results of a study designed to first quantify the sensitivity of ecosystems to climate through the use of climate and ecosystem data, and then use the results to test the sensitivity of the climate data in a state-of the art ecosystem model. A database of available ecosystem characteristics such as mean canopy height, above ground biomass, and basal area was constructed from sources like the National Biomass and Carbon Dataset (NBCD). The ecosystem characteristics were then paired by latitude and longitude with the corresponding climate characteristics temperature, precipitation, photosynthetically active radiation (PAR) and dew point that were retrieved from the North American Regional Reanalysis (NARR). The average yearly and seasonal means of the climate data, and their associated maximum and minimum values, over the 1979-2010 time frame provided by NARR were constructed and paired with the ecosystem data. The compiled results provide natural patterns of vegetation structure and distribution with regard to climate data. An advanced ecosystem model, the Ecosystem Demography model (ED), was then modified to allow yearly alterations to its mechanistic climate lookup table and used to predict the sensitivities of ecosystem pattern, structure, and dynamics to climate data. The combined ecosystem structure and climate data results were compared to ED’s output to check the validity of the model. After verification, climate change scenarios such as those used in the last IPCC were run and future forest structure changes due to climate sensitivities were identified. The results of this study can be used to both quantify and test key relationships for next generation models. The sensitivity of ecosystem characteristics to climate data

  18. How does spatial variability of climate affect catchment streamflow predictions?

    EPA Science Inventory

    Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distribute…

  19. Observations of cataclysmic variables with IUE

    NASA Technical Reports Server (NTRS)

    Hartmann, L.; Raymond, J.

    1981-01-01

    Observations are reported of the cataclysmic variables AN UMa, 2AO311-227, VV Pup, DQ Her, and GK Per. Continuum emission was detected in the short wavelength region in DQ Her. This object exhibits a quasi-blackbody spectrum at short wavelengths, such blackbody components are a common property of the variables AM Her, SS Cyg, and U Gem, suggesting an underlying similarity in the activity of these diverse systems. Flat continuum components at longer wavelengths in general are not compatible with standard disk models. The emission line ratios in AE Aqr are anomalous in that C IV is absent to a very low level relative to N V.

  20. Detection and attribution of climate extremes in the observed record

    DOE PAGES

    Easterling, David R.; Kunkel, Kenneth E.; Wehner, Michael F.; …

    2016-01-18

    We present an overview of practices and challenges related to the detection and attribution of observed changes in climate extremes. Detection is the identification of a statistically significant change in the extreme values of a climate variable over some period of time. Issues in detection discussed include data quality, coverage, and completeness. Attribution takes that detection of a change and uses climate model simulations to evaluate whether a cause can be assigned to that change. Additionally, we discuss a newer field of attribution, event attribution, where individual extreme events are analyzed for the express purpose of assigning some measure ofmore » whether that event was directly influenced by anthropogenic forcing of the climate system.« less

  1. Range expansion through fragmented landscapes under a variable climate

    PubMed Central

    Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

    2013-01-01

    Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species’ range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species’ range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

  2. Climate Change and Climate Variability in the Latin American Region

    NASA Astrophysics Data System (ADS)

    Magrin, G. O.; Gay Garcia, C.; Cruz Choque, D.; Gimenez-Sal, J. C.; Moreno, A. R.; Nagy, G. J.; Nobre, C.; Villamizar, A.

    2007-05-01

    Over the past three decades LA was subjected to several climate-related impacts due to increased El Niño occurrences. Two extremely intense episodes of El Niño and other increased climate extremes happened during this period contributing greatly to augment the vulnerability of human systems to natural disasters. In addition to weather and climate, the main drivers of the increased vulnerability are demographic pressure, unregulated urban growth, poverty and rural migration, low investment in infrastructure and services, and problems in inter-sector coordination. As well, increases in temperature and increases/decreases in precipitation observed during the last part of 20th century have yet led to intensification of glaciers melting, increases in floods/droughts and forest fires frequency, increases in morbidity and mortality, increases in plant diseases incidence; lost of biodiversity, reduction in dairy cattle production, and problems with hydropower generation, highly affecting LA human system. For the end of the 21st century, the projected mean warming for LA ranges from 1 to 7.5ºC and the frequency of weather and climate extremes could increase. Additionally, deforestation is projected to continue leading to a reduction of 25 percent in Amazonia forest in 2020 and 40 percent in 2050. Soybeans planted area in South America could increase by 55 percent by 2020 enhancing aridity/desertification in many of the already water- stressed regions. By 2050 LA population is likely to be 50 percent larger than in 2000, and migration from the country sides to the cities will continue. In the near future, these predicted changes are very likely to severely affect a number of ecosystems and sectors distribution; b) Disappearing most tropical glaciers; c) Reducing water availability and hydropower generation; d) Increasing desertification and aridity; e) Severely affecting people, resources and economic activities in coastal areas; f) Increasing crop’s pests and diseases

  3. Climate change enhances interannual variability of the Nile river flow

    NASA Astrophysics Data System (ADS)

    Siam, Mohamed S.; Eltahir, Elfatih A. B.

    2017-04-01

    The human population living in the Nile basin countries is projected to double by 2050, approaching one billion. The increase in water demand associated with this burgeoning population will put significant stress on the available water resources. Potential changes in the flow of the Nile River as a result of climate change may further strain this critical situation. Here, we present empirical evidence from observations and consistent projections from climate model simulations suggesting that the standard deviation describing interannual variability of total Nile flow could increase by 50% (+/-35%) (multi-model ensemble mean +/- 1 standard deviation) in the twenty-first century compared to the twentieth century. We attribute the relatively large change in interannual variability of the Nile flow to projected increases in future occurrences of El Niño and La Niña events and to observed teleconnection between the El Niño-Southern Oscillation and Nile River flow. Adequacy of current water storage capacity and plans for additional storage capacity in the basin will need to be re-evaluated given the projected enhancement of interannual variability in the future flow of the Nile river.

  4. LAMPPOST: A Mnemonic Device for Teaching Climate Variables

    ERIC Educational Resources Information Center

    Fahrer, Chuck; Harris, Dan

    2004-01-01

    This article introduces the word “LAMPPOST” as a mnemonic device to aid in the instruction of climate variables. It provides instructors with a framework for discussing climate patterns that is based on eight variables: latitude, altitude, maritime influence and continentality, pressure systems, prevailing winds, ocean currents, storms, and…

  5. Influence of Climate Variability on US Regional Homicide Rates

    NASA Astrophysics Data System (ADS)

    Harp, R. D.; Karnauskas, K. B.

    2017-12-01

    Recent studies have found consistent evidence of a relationship between temperature and criminal behavior. However, despite agreement in the overall relationship, little progress has been made in distinguishing between two proposed explanatory theories. The General Affective Aggression Model (GAAM) suggests that high temperatures create periods of higher heat stress that enhance individual aggressiveness, whereas the Routine Activities Theory (RAT) theorizes that individuals are more likely to be outdoors interacting with others during periods of pleasant weather with a resulting increase in both interpersonal interactions and victim availability. Further, few studies have considered this relationship within the context of climate change in a quantitative manner. In an effort to distinguish between the two theories, and to examine the statistical relationships on a broader spatial scale than previously, we combined data from the Supplementary Homicide Report (SHR—compiled by the Federal Bureau of Investigation) and the North American Regional Reanalysis (NARR—compiled by the National Centers for Environmental Protection, a branch of the National Oceanic and Atmospheric Administration). US homicide data described by the SHR was compared with seven relevant observed climate variables (temperature, dew point, relative humidity, accumulated precipitation, accumulated snowfall, snow cover, and snow depth) provided by the NARR atmospheric reanalysis. Relationships between homicide rates and climate variables, as well as reveal regional spatial patterns will be presented and discussed, along with the implications due to future climate change. This research lays the groundwork for the refinement of estimates of an oft-overlooked climate change impact, which has previously been estimated to cause an additional 22,000 murders between 2010 and 2099, including providing important constraints for empirical models of future violent crime incidences in the face of global

  6. How resilient are ecosystems in adapting to climate variability

    NASA Astrophysics Data System (ADS)

    Savenije, Hubert H. G.

    2015-04-01

    The conclusion often drawn in the media is that ecosystems may perish as a result of climate change. Although climatic trends may indeed lead to shifts in ecosystem composition, the challenge to adjust to climatic variability – even if there is no trend – is larger, particularly in semi-arid or topical climates where climatic variability is large compared to temperate climates. How do ecosystems buffer for climatic variability? The most powerful mechanism is to invest in root zone storage capacity, so as to guarantee access to water and nutrients during period of drought. This investment comes at a cost of having less energy available to invest in growth or formation of fruits. Ecosystems are expected to create sufficient buffer to overcome critical periods of drought, but not more than is necessary to survive or reproduce. Based on this concept, a methodology has been developed to estimate ecosystem root zone storage capacity at local, regional and global scale. These estimates correspond well with estimates made by combining soil and ecosystem information, but are more accurate and more detailed. The methodology shows that ecosystems have intrinsic capacity to adjust to climatic variability and hence have a high resilience to both climatic variability and climatic trends.

  7. Observed Budgets for the Global Climate

    NASA Astrophysics Data System (ADS)

    Kottek, M.; Haimberger, L.; Rubel, F.; Hantel, M.

    2003-04-01

    A global dataset for selected budget quantities specifying the present climate for the period 1991-1995 has been compiled. This dataset is an essential component of the new climate volume within the series Landolt Boernstein – Numerical Data and Functional Relationships in Science and Technology, to be published this year. Budget quantities are those that appear in a budget equation. Emphasis in this collection is placed on observational data of both in situ and remotely sensed quantities. The fields are presented as monthly means with a uniform space resolution of one degree. Main focus is on climatologically relevant state and flux quantities at the earth’s surface and at the top of atmosphere. Some secondary and complex climate elements are also presented (e.g. tornadoe frequency). The progress of this collection as compared to other climate datasets is, apart from the quality of the input data, that all fields are presented in standardized form as far as possible. Further, visualization loops of the global fields in various projections will be available for the user in the eventual book. For some budget quantities, e.g. precipitation, it has been necessary to merge data from different sources; insufficiently observed parameters have been supplemented through the ECMWF ERA-40 reanalyses. If all quantities of a budget have been evaluated the gross residual represents an estimate of data quality. For example, the global water budget residual is found to be up to 30 % depending on the used data. This suggests that the observation of global climate parameters needs further improvement.

  8. Disease in a more variable and unpredictable climate

    NASA Astrophysics Data System (ADS)

    McMahon, T. A.; Raffel, T.; Rohr, J. R.; Halstead, N.; Venesky, M.; Romansic, J.

    2014-12-01

    Global climate change is shifting the dynamics of infectious diseases of humans and wildlife with potential adverse consequences for disease control. Despite this, the role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial. Climate change is expected to increase climate variability in addition to increasing mean temperatures, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments and field data on disease-associated frog declines in Latin America support this framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was inconsistent with the pattern of Bd growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. Consistent with our laboratory experiments, increased regional temperature variability associated with global El Niño climatic events was the best predictor of widespread amphibian losses in the genus Atelopus. Thus, incorporating the effects of small-scale temporal variability in climate can greatly improve our ability to predict the effects of climate change on disease.

  9. Productivity in the Barents Sea – Response to Recent Climate Variability

    PubMed Central

    Dalpadado, Padmini; Arrigo, Kevin R.; Hjøllo, Solfrid S.; Rey, Francisco; Ingvaldsen, Randi B.; Sperfeld, Erik; van Dijken, Gert L.; Stige, Leif C.; Olsen, Are; Ottersen, Geir

    2014-01-01

    The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region. PMID:24788513

  10. Information transfer across the scales of climate data variability

    NASA Astrophysics Data System (ADS)

    Palus, Milan; Jajcay, Nikola; Hartman, David; Hlinka, Jaroslav

    2015-04-01

    Multitude of scales characteristic of the climate system variability requires innovative approaches in analysis of instrumental time series. We present a methodology which starts with a wavelet decomposition of a multi-scale signal into quasi-oscillatory modes of a limited band-with, described using their instantaneous phases and amplitudes. Then their statistical associations are tested in order to search for interactions across time scales. In particular, an information-theoretic formulation of the generalized, nonlinear Granger causality is applied together with surrogate data testing methods [1]. The method [2] uncovers causal influence (in the Granger sense) and information transfer from large-scale modes of climate variability with characteristic time scales from years to almost a decade to regional temperature variability on short time scales. In analyses of daily mean surface air temperature from various European locations an information transfer from larger to smaller scales has been observed as the influence of the phase of slow oscillatory phenomena with periods around 7-8 years on amplitudes of the variability characterized by smaller temporal scales from a few months to annual and quasi-biennial scales [3]. In sea surface temperature data from the tropical Pacific area an influence of quasi-oscillatory phenomena with periods around 4-6 years on the variability on and near the annual scale has been observed. This study is supported by the Ministry of Education, Youth and Sports of the Czech Republic within the Program KONTAKT II, Project No. LH14001. [1] M. Palus, M. Vejmelka, Phys. Rev. E 75, 056211 (2007) [2] M. Palus, Entropy 16(10), 5263-5289 (2014) [3] M. Palus, Phys. Rev. Lett. 112, 078702 (2014)

  11. Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

    NASA Astrophysics Data System (ADS)

    Safavi, Hamid R.; Sajjadi, Sayed Mahdi; Raghibi, Vahid

    2017-10-01

    Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971-2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015-2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.

  12. North Tropical Atlantic Climate Variability and Model Biases

    NASA Astrophysics Data System (ADS)

    Yang, Y.

    2017-12-01

    Remote forcing from El Niño-Southern Oscillation (ENSO) and local ocean-atmosphere feedback are important for climate variability over the North Tropical Atlantic. These two factors are extracted by the ensemble mean and inter-member difference of a 10-member Pacific Ocean-Global Atmosphere (POGA) experiment, in which sea surface temperatures (SSTs) are restored to the observed anomalies over the tropical Pacific but fully coupled to the atmosphere elsewhere. POGA reasonably captures main features of observed North Tropical Atlantic variability. ENSO forced and local North Tropical Atlantic modes (NTAMs) develop with wind-evaporation-SST feedback, explaining one third and two thirds of total variance respectively. Notable biases, however, exist. The seasonality of the simulated NTAM is delayed by one month, due to the late development of the North Atlantic Oscillation (NAO) in the model. A spurious band of enhanced sea surface temperature (SST) variance (SBEV) is identified over the northern equatorial Atlantic in POGA and 14 out of 23 CMIP5 models. The SBEV is especially pronounced in boreal spring and due to the combined effect of both anomalous atmospheric thermal forcing and oceanic vertical upwelling. While the tropical North Atlantic variability is only weakly correlated with the Atlantic Zonal Mode (AZM) in observations, the SBEV in CMIP5 produces conditions that drive and intensify the AZM variability via triggering the Bjerknes feedback. This partially explains why AZM is strong in some CMIP5 models even though the equatorial cold tongue and easterly trades are biased low.

  13. Observing campaign on 5 variables in Cygnus

    NASA Astrophysics Data System (ADS)

    Waagen, Elizabeth O.

    2015-10-01

    Dr. George Wallerstein (University of Washington) has requested AAVSO assistance in monitoring 5 variable stars in Cygnus now through December 2015. He is working to complete the radial velocity curves for these stars, and needs optical light curves for correlation with the spectra he will be obtaining. Wallerstein writes: “I need to know the time of max or min so I can assign a phase to each spectrum. Most classical Cepheids are quite regular so once a time of max or min can be established I can derive the phase of each observation even if my obs are several cycles away from the established max or min. MZ Cyg is a type II Cepheid and they are less regular than their type I cousins.” SZ Cyg, X Cyg, VX Cyg, and TX Cyg are all classical Cepheids. V and visual observations are requested. These are long-period Cepheids, so nightly observations are sufficient. Finder charts with sequence may be created using the AAVSO Variable Star Plotter (https://www.aavso.org/vsp). Observations should be submitted to the AAVSO International Database. See full Alert Notice for more details.

  14. Slowing down of North Pacific climate variability and its implications for abrupt ecosystem change.

    PubMed

    Boulton, Chris A; Lenton, Timothy M

    2015-09-15

    Marine ecosystems are sensitive to stochastic environmental variability, with higher-amplitude, lower-frequency–i.e., “redder”–variability posing a greater threat of triggering large ecosystem changes. Here we show that fluctuations in the Pacific Decadal Oscillation (PDO) index have slowed down markedly over the observational record (1900-present), as indicated by a robust increase in autocorrelation. This “reddening” of the spectrum of climate variability is also found in regionally averaged North Pacific sea surface temperatures (SSTs), and can be at least partly explained by observed deepening of the ocean mixed layer. The progressive reddening of North Pacific climate variability has important implications for marine ecosystems. Ecosystem variables that respond linearly to climate forcing will have become prone to much larger variations over the observational record, whereas ecosystem variables that respond nonlinearly to climate forcing will have become prone to more frequent “regime shifts.” Thus, slowing down of North Pacific climate variability can help explain the large magnitude and potentially the quick succession of well-known abrupt changes in North Pacific ecosystems in 1977 and 1989. When looking ahead, despite model limitations in simulating mixed layer depth (MLD) in the North Pacific, global warming is robustly expected to decrease MLD. This could potentially reverse the observed trend of slowing down of North Pacific climate variability and its effects on marine ecosystems.

  15. Impacts of Considering Climate Variability on Investment Decisions in Ethiopia

    NASA Astrophysics Data System (ADS)

    Strzepek, K.; Block, P.; Rosegrant, M.; Diao, X.

    2005-12-01

    In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country’s future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.

  16. Predictability of North Atlantic Multidecadal Climate Variability

    PubMed

    Griffies; Bryan

    1997-01-10

    Atmospheric weather systems become unpredictable beyond a few weeks, but climate variations can be predictable over much longer periods because of the coupling of the ocean and atmosphere. With the use of a global coupled ocean-atmosphere model, it is shown that the North Atlantic may have climatic predictability on the order of a decade or longer. These results suggest that variations of the dominant multidecadal sea surface temperature patterns in the North Atlantic, which have been associated with changes in climate over Eurasia, can be predicted if an adequate and sustainable system for monitoring the Atlantic Ocean exists.

  17. The influence of internal climate variability on heatwave frequency trends

    NASA Astrophysics Data System (ADS)

    E Perkins-Kirkpatrick, S.; Fischer, E. M.; Angélil, O.; Gibson, P. B.

    2017-04-01

    Understanding what drives changes in heatwaves is imperative for all systems impacted by extreme heat. We examine short- (13 yr) and long-term (56 yr) heatwave frequency trends in a 21-member ensemble of a global climate model (Community Earth System Model; CESM), where each member is driven by identical anthropogenic forcings. To estimate changes dominantly due to internal climate variability, trends were calculated in the corresponding pre-industrial control run. We find that short-term trends in heatwave frequency are not robust indicators of long-term change. Additionally, we find that a lack of a long-term trend is possible, although improbable, under historical anthropogenic forcing over many regions. All long-term trends become unprecedented against internal variability when commencing in 2015 or later, and corresponding short-term trends by 2030, while the length of trend required to represent regional long-term changes is dependent on a given realization. Lastly, within ten years of a short-term decline, 95% of regional heatwave frequency trends have reverted to increases. This suggests that observed short-term changes of decreasing heatwave frequency could recover to increasing trends within the next decade. The results of this study are specific to CESM and the ‘business as usual’ scenario, and may differ under other representations of internal variability, or be less striking when a scenario with lower anthropogenic forcing is employed.

  18. Globally Gridded Satellite observations for climate studies

    USGS Publications Warehouse

    Knapp, K.R.; Ansari, S.; Bain, C.L.; Bourassa, M.A.; Dickinson, M.J.; Funk, Chris; Helms, C.N.; Hennon, C.C.; Holmes, C.D.; Huffman, G.J.; Kossin, J.P.; Lee, H.-T.; Loew, A.; Magnusdottir, G.

    2011-01-01

    Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them that no central archive of geostationary data for all international satellites exists, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multisatellite climate studies. The International Satellite Cloud Climatology Project (ISCCP) set the stage for overcoming these issues by archiving a subset of the full-resolution geostationary data at ~10-km resolution at 3-hourly intervals since 1983. Recent efforts at NOAA’s National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in Network Common Data Format (netCDF) using standards that permit a wide variety of tools and libraries to process the data quickly and easily. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone.

  19. Climate variability risks for electricity supply

    NASA Astrophysics Data System (ADS)

    Kling, Harald

    2017-12-01

    Hydropower represents about 20% of sub-Saharan electricity, and expansion is underway. Rainfall varies year-to-year in geographical clusters, increasing the risk of climate-related electricity supply disruption in dry years.

  20. Variability in Temperature-Related Mortality Projections under Climate Change

    PubMed Central

    Benmarhnia, Tarik; Sottile, Marie-France; Plante, Céline; Brand, Allan; Casati, Barbara; Fournier, Michel

    2014-01-01

    Background: Most studies that have assessed impacts on mortality of future temperature increases have relied on a small number of simulations and have not addressed the variability and sources of uncertainty in their mortality projections. Objectives: We assessed the variability of temperature projections and dependent future mortality distributions, using a large panel of temperature simulations based on different climate models and emission scenarios. Methods: We used historical data from 1990 through 2007 for Montreal, Quebec, Canada, and Poisson regression models to estimate relative risks (RR) for daily nonaccidental mortality in association with three different daily temperature metrics (mean, minimum, and maximum temperature) during June through August. To estimate future numbers of deaths attributable to ambient temperatures and the uncertainty of the estimates, we used 32 different simulations of daily temperatures for June–August 2020–2037 derived from three global climate models (GCMs) and a Canadian regional climate model with three sets of RRs (one based on the observed historical data, and two on bootstrap samples that generated the 95% CI of the attributable number (AN) of deaths). We then used analysis of covariance to evaluate the influence of the simulation, the projected year, and the sets of RRs used to derive the attributable numbers of deaths. Results: We found that variability in the distributions of simulated temperature for June–August of 2020–2037 was explained by differences among the simulations. Estimated ANs for 2020–2037 ranged from 34 to 174 per summer (i.e., June–August). Most of the variability in mortality projections (38%) was related to the temperature–mortality RR used to estimate the ANs. Conclusions: The choice of the RR estimate for the association between temperature and mortality may be important to reduce uncertainty in mortality projections. Citation: Benmarhnia T, Sottile MF, Plante C, Brand A

  1. Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

    NASA Technical Reports Server (NTRS)

    Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.

    2015-01-01

    Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

  2. Rising climate variability and synchrony in North Pacific ecosystems

    NASA Astrophysics Data System (ADS)

    Black, Bryan

    2017-04-01

    Rising climate variability and synchrony in North Pacific ecosystems Evidence is growing that climate variability of the northeast Pacific Ocean has increased over the last century, culminating in such events as the record-breaking El Niño years 1983, 1998, and 2016 and the unusually persistent 2014/15 North Pacific Ocean heat wave known as “The Blob.” Of particular concern is that rising variability could increase synchrony within and among North Pacific ecosystems, which could reduce the diversity of biological responses to climate (i.e. the “portfolio effect”), diminish resilience, and leave populations more prone to extirpation. To test this phenomenon, we use a network of multidecadal fish otolith growth-increment chronologies that were strongly correlated to records of winter (Jan-Mar) sea level. These biological and physical datasets spanned the California Current through the Gulf of Alaska. Synchrony was quantified as directional changes in running (31-year window) mean pairwise correlation within sea level and then within otolith time series. Synchrony in winter sea level at the nine stations with the longest records has increased by more than 40% over the 1950-2015 interval. Likewise, synchrony among the eight longest otolith chronologies has increased more than 100% over a comparable time period. These directional changes in synchrony are highly unlikely due to chance alone, as confirmed by comparing trends in observed data to those in simulated data (n = 10,000 iterations) with time series of identical number, length, and autocorrelation. Ultimately, this trend in rising synchrony may be linked to increased impacts of the El Niño Southern Oscillation (ENSO) on mid-latitude ecosystems of North America, and may therefore reflect a much broader, global-scale signature.

  3. Dynamical variability in the modelling of chemistry-climate interactions.

    PubMed

    Pyle, J A; Braesicke, P; Zeng, G

    2005-01-01

    We have used a version of the Met Office’s climate model, into which we have introduced schemes for atmospheric chemistry, to study chemistry-dynamics-climate interactions. We have considered the variability of the stratospheric polar vortex, whose behaviour influences stratospheric ozone loss and will affect ozone recovery. In particular, we analyse the dynamical control of high latitude ozone in a model version which includes an assimilation of the equatorial quasi-biennial oscillation (QBO), demonstrating the stability of the linear relation between vortex strength and high latitude ozone. We discuss the effect of interactive model ozone on polar stratospheric cloud (PSC) area/volume and winter-spring stratospheric ozone loss in the northern hemisphere. In general we find larger polar ozone losses calculated in those model integrations in which modelled ozone is used interactively in the radiation scheme, even though we underestimate the slope of the ozone loss per PSC volume relation derived from observations. We have also looked at the influence of changing stratosphere-to-troposphere exchange on the tropospheric oxidizing capacity and, in particular, have considered the variability of tropospheric composition under different climate regimes (El Niño/La Niña, etc.). Focusing on the UT/LS, we show the response of ozone to El Niño in two different model set-ups (tropospheric/ stratospheric). In the stratospheric model set-up we find a distinct signal in the lower tropical stratosphere, which shows an anti-correlation between the Niño 3 index and the ozone column amount. In contrast ozone generally increases in the upper troposphere of the tropospheric model set-up after an El Niño. Understanding future trends in stratospheric ozone and tropospheric oxidizing capacity requires an understanding of natural variability, which we explore here.

  4. Atmospheric Teleconnection and Climate Variability: Affecting Rice Productivity of Bihar, India

    NASA Astrophysics Data System (ADS)

    Saini, A.

    2017-12-01

    Climate variability brought various negative results to the environment around us and area under rice crop in Bihar has also faced a lot of negative impacts due to variability in temperature and rainfall. Location of Bihar in Northern Plain of India automatically makes it prime location for agriculture and therefore variability in climatic variables brings highly sensitive results to the agricultural production (especially rice). In this study, rainfall and temperature variables are taken into consideration to investigate the impact on rice cultivated area. Change in climate variable with the passage of time is prevailing since the start of geological time scale, how the variability in climate variables has affected the major crops. Climate index of Pacific Ocean and Indian Ocean influences the seasonal weather in Bihar and therefore role of ENSO and IOD is an interesting point of inquiry. Does there exists direct relation between climate variability and area under agricultural crops? How many important variables directly signals towards the change in area under agriculture production? These entire questions are answered with respect to change in area under rice cultivation of Bihar State of India. Temperature, rainfall and ENSO are a good indicator with respect to rice cultivation in Indian subcontinent. Impact on the area under rice has been signaled through ONI, Niño3 and DMI. Increasing range of temperature in the rice productivity declining years is observed since 1990.

  5. Orbital Forcing driving climate variability on Tropical South Atlantic

    NASA Astrophysics Data System (ADS)

    Oliveira, A. S.; Baker, P. A.; Silva, C. G.; Dwyer, G. S.; Chiessi, C. M.; Rigsby, C. A.; Ferreira, F.

    2017-12-01

    Past research on climate response to orbital forcing in tropical South America has emphasized on high precession cycles influencing low latitude hydrologic cycles, and driving the meridional migration of Intertropical Convergence Zone (ITCZ).However, marine proxy records from the tropical Pacific Ocean showed a strong 41-ka periodicities in Pleistocene seawater temperature and productivity related to fluctuations in Earth’s obliquity. It Indicates that the western Pacific ITCZ migration was influenced by combined precession and obliquity changes. To reconstruct different climate regimes over the continent and understand the orbital cycle forcing over Tropical South America climate, hydrological reconstruction have been undertaken on sediment cores located on the Brazilian continental slope, representing the past 1.6 million years. Core CDH 79 site is located on a 2345 m deep seamount on the northern Brazilian continental slope (00° 39.6853′ N, 44° 20.7723′ W), 320 km from modern coastline of the Maranhão Gulf. High-resolution XRF analyses of Fe, Ti, K and Ca are used to define the changes in precipitation and sedimentary input history of Tropical South America. The response of the hydrology cycle to orbital forcing was studied using spectral analysis.The 1600 ka records of dry/wet conditions presented here indicates that orbital time-scale climate change has been a dominant feature of tropical climate. We conclude that the observed oscillation reflects variability in the ITCZ activity associated with the Earth’s tilt. The prevalence of the eccentricity and obliquity signals in continental hydrology proxies (Ti/Ca and Fe/K) as implicated in our precipitation records, highlights that these orbital forcings play an important role in tropics hydrologic cycles. Throughout the Quaternary abrupt shifts of tropical variability are temporally correlated with abrupt climate changes and atmospheric reorganization during Mid-Pleistocene Transition and Mid-Brunhes Events

  6. Wind Stress Variability Observed Over Coastal Waters

    NASA Astrophysics Data System (ADS)

    Ortiz-Suslow, D. G.; Haus, B. K.; Laxague, N.; Williams, N. J.; Graber, H. C.

    2016-02-01

    The wind stress on the ocean surface generates waves, drives currents, and enhances gas exchange; and a significant amount of work has been done to characterize the air-sea momentum flux in terms of bulk oceanographic and atmospheric parameters. However, the majority of this work to develop operational algorithms has been focused on the deep ocean and the suitability of these methods in the coastal regime has not been evaluated. The findings from a two-part field campaign will be presented which highlight the divergence of nearshore wind stress observations from conventional, deep water results. The first set of data comes from a coastal region near a relatively small, natural tidal inlet. A high degree of spatial variability was observed in both the wind stress magnitude and direction, suggestive of coastal processes (e.g., depth-limited wave affects and horizontal current shear) modulating the momentum flux from the atmosphere to the ocean surface. These shallow-water processes are typically not accounted for in conventional parameterizations. Across the experimental domain and for a given wind speed, the stress magnitude was found to be nearly 2.5 times that predicted by conventional methods; also, a high propensity for stress steering off the mean azimuthal wind direction (up to ±70 degrees) was observed and linked to horizontal current gradients produced by the tidal inlet. The preliminary findings from a second data set taken in the vicinity of the macrotidal Columbia River Mouth will also be presented. Compared to the first data set, a similar degree of variability is observed here, but the processes responsible for this are present at a much larger scale. Specifically, the Columbia River Mouth observations were made in the presence of significant swell wave energy and during periods of very high estuarine discharge. The relative angle between the wind and swell direction is expected to be significant with regards to the observed momentum flux. Also, these

  7. Impact of Holocene climate variability on Arctic vegetation

    NASA Astrophysics Data System (ADS)

    Gajewski, K.

    2015-10-01

    This paper summarizes current knowledge about the postglacial history of the vegetation of the Canadian Arctic Archipelago (CAA) and Greenland. Available pollen data were used to understand the initial migration of taxa across the Arctic, how the plant biodiversity responded to Holocene climate variability, and how past climate variability affected primary production of the vegetation. Current evidence suggests that most of the flora arrived in the area during the Holocene from Europe or refugia south or west of the region immediately after local deglaciation, indicating rapid dispersal of propagules to the region from distant sources. There is some evidence of shrub species arriving later in Greenland, but it is not clear if this is dispersal limited or a response to past climates. Subsequent climate variability had little effect on biodiversity across the CAA, with some evidence of local extinctions in areas of Greenland in the late Holocene. The most significant impact of climate changes is on vegetation density and/or plant production.

  8. Variability of the recent climate of eastern Africa

    NASA Astrophysics Data System (ADS)

    Schreck, Carl J., III; Semazzi, Fredrick H. M.

    2004-05-01

    The primary objective of this study is to investigate the recent variability of the eastern African climate. The region of interest is also known as the Greater Horn of Africa (GHA), and comprises the countries of Burundi, Djibouti, Eritrea, Ethiopia, Kenya, Rwanda, Somalia, Sudan, Uganda, and Tanzania.The analysis was based primarily on the construction of empirical orthogonal functions (EOFs) of gauge rainfall data and on CPC Merged Analysis of Precipitation (CMAP) data, derived from a combination of rain-gauge observations and satellite estimates. The investigation is based on the period 1961-2001 for the short rains season of eastern Africa of October through to December. The EOF analysis was supplemented by projection of National Centers for Environmental Prediction wind data onto the rainfall eigenmodes to understand the rainfall-circulation relationships. Furthermore, correlation and composite analyses have been performed with the Climatic Research Unit globally averaged surface-temperature time series to explore the potential relationship between the climate of eastern Africa and global warming.The most dominant mode of variability (EOF1) based on CMAP data over eastern Africa corresponds to El Niño-southern oscillation (ENSO) climate variability. It is associated with above-normal rainfall amounts during the short rains throughout the entire region, except for Sudan. The corresponding anomalous low-level circulation is dominated by easterly inflow from the Indian Ocean, and to a lesser extent the Congo tropical rain forest, into the positive rainfall anomaly region that extends across most of eastern Africa. The easterly inflow into eastern Africa is part of diffluent outflow from the maritime continent during the warm ENSO events. The second eastern African EOF (trend mode) is associated with decadal variability. In distinct contrast from the ENSO mode pattern, the trend mode is characterized by positive rainfall anomalies over the northern sector of

  9. Impacts of Interannual Climate Variability on Agricultural and Marine Ecosystems

    NASA Technical Reports Server (NTRS)

    Cane, M. A.; Zebiak, S.; Kaplan, A.; Chen, D.

    2001-01-01

    The El Nino – Southern Oscillation (ENSO) is the dominant mode of global interannual climate variability, and seems to be the only mode for which current prediction methods are more skillful than climatology or persistence. The Zebiak and Cane intermediate coupled ocean-atmosphere model has been in use for ENSO prediction for more than a decade, with notable success. However, the sole dependence of its original initialization scheme and the improved initialization on wind fields derived from merchant ship observations proved to be a liability during 1997/1998 El Nino event: the deficiencies of wind observations prevented the oceanic component of the model from reaching the realistic state during the year prior to the event, and the forecast failed. Our work on the project was concentrated on the use of satellite data for improving various stages of ENSO prediction technology: model initialization, bias correction, and data assimilation. Close collaboration with other teams of the IDS project was maintained throughout.

  10. Climatic variability in sclerochronological records from the northern North Sea

    NASA Astrophysics Data System (ADS)

    Trofimova, T.; Andersson Dahl, C.; Bonitz, F. G. W.

    2016-12-01

    Highly resolved palaeoreconstructions that can extend instrumental records back through time is a fundament for our understanding of a climate of the last millennia. Only a few established extratropical marine paleo archives enable the reconstruction of key ocean processes at annual to sub-annual time scales. Bivalves have been shown to provide a useful archive with high temporal resolution. The species Arctica islandica is unique proxy due to its exceptional longevity combined with sensitivity to changes in environmental conditions. In this study, we investigate the impact of climate variability on sclerochronological records of A. islandica from the Viking Bank in the northern North Sea. The hydrographical characteristics of this location are mainly controlled by the major inflow of Atlantic water in the North Sea and can potentially be reflected in the shell composition and growth of A. islandica. To reconstruct environment conditions, we use shells of living and subfossil specimens of A. islandica collected by dredging at depths around 100 meters. The annual growth bands within the shells were determined and growth increments widths were measured. By cross-matching 30 individual increment-width time series, we built an absolutely dated 265-year long shell-growth chronology spanning the time interval 1748-2013 AD. The relatively high Rbar (>0.5) and EPS (>0.85) values indicate a common environmental forcing on the shell growth within the population. The growth chronology preserves a 20-30 yr variability prior to 1900 which fades out towards the present. That change suggests a possible regime shift at the beginning of a 20th century. Ongoing work mainly focuses on comparing the shell-growth chronology with existing observational time series of climatic parameters to determine controlling factors and test the use of growth chronologies for climate reconstruction in this area. For reconstructing seasonality, we analyse the stable oxygen isotope composition of the

  11. Estimating daily climatologies for climate indices derived from climate model data and observations

    PubMed Central

    Mahlstein, Irina; Spirig, Christoph; Liniger, Mark A; Appenzeller, Christof

    2015-01-01

    Climate indices help to describe the past, present, and the future climate. They are usually closer related to possible impacts and are therefore more illustrative to users than simple climate means. Indices are often based on daily data series and thresholds. It is shown that the percentile-based thresholds are sensitive to the method of computation, and so are the climatological daily mean and the daily standard deviation, which are used for bias corrections of daily climate model data. Sample size issues of either the observed reference period or the model data lead to uncertainties in these estimations. A large number of past ensemble seasonal forecasts, called hindcasts, is used to explore these sampling uncertainties and to compare two different approaches. Based on a perfect model approach it is shown that a fitting approach can improve substantially the estimates of daily climatologies of percentile-based thresholds over land areas, as well as the mean and the variability. These improvements are relevant for bias removal in long-range forecasts or predictions of climate indices based on percentile thresholds. But also for climate change studies, the method shows potential for use. Key Points More robust estimates of daily climate characteristics Statistical fitting approach Based on a perfect model approach PMID:26042192

  12. The SASSCAL contribution to climate observation, climate data management and data rescue in Southern Africa

    NASA Astrophysics Data System (ADS)

    Kaspar, F.; Helmschrot, J.; Mhanda, A.; Butale, M.; de Clercq, W.; Kanyanga, J. K.; Neto, F. O. S.; Kruger, S.; Castro Matsheka, M.; Muche, G.; Hillmann, T.; Josenhans, K.; Posada, R.; Riede, J.; Seely, M.; Ribeiro, C.; Kenabatho, P.; Vogt, R.; Jürgens, N.

    2015-07-01

    A major task of the newly established “Southern African Science Service Centre for Climate Change and Adaptive Land Management” (SASSCAL; www.sasscal.org) and its partners is to provide science-based environmental information and knowledge which includes the provision of consistent and reliable climate data for Southern Africa. Hence, SASSCAL, in close cooperation with the national weather authorities of Angola, Botswana, Germany and Zambia as well as partner institutions in Namibia and South Africa, supports the extension of the regional meteorological observation network and the improvement of the climate archives at national level. With the ongoing rehabilitation of existing weather stations and the new installation of fully automated weather stations (AWS), altogether 105 AWS currently provide a set of climate variables at 15, 30 and 60 min intervals respectively. These records are made available through the SASSCAL WeatherNet, an online platform providing near-real time data as well as various statistics and graphics, all in open access. This effort is complemented by the harmonization and improvement of climate data management concepts at the national weather authorities, capacity building activities and an extension of the data bases with historical climate data which are still available from different sources. These activities are performed through cooperation between regional and German institutions and will provide important information for climate service related activities.

  13. CLIMATE VARIABILITY, CHANGE, AND CONSEQUENCES IN ESTUARIES

    EPA Science Inventory

    Climate change operates at global, hemispheric, and regional scales, sometimes involving rapid shifts in ocean and atmospheric circulation. Changes of global scope occurred in the transition into the Little Ice Age (1350-1880) and subsequent warming during the 20th century. In th…

  14. Climate models predict increasing temperature variability in poor countries.

    PubMed

    Bathiany, Sebastian; Dakos, Vasilis; Scheffer, Marten; Lenton, Timothy M

    2018-05-01

    Extreme events such as heat waves are among the most challenging aspects of climate change for societies. We show that climate models consistently project increases in temperature variability in tropical countries over the coming decades, with the Amazon as a particular hotspot of concern. During the season with maximum insolation, temperature variability increases by ~15% per degree of global warming in Amazonia and Southern Africa and by up to 10%°C -1 in the Sahel, India, and Southeast Asia. Mechanisms include drying soils and shifts in atmospheric structure. Outside the tropics, temperature variability is projected to decrease on average because of a reduced meridional temperature gradient and sea-ice loss. The countries that have contributed least to climate change, and are most vulnerable to extreme events, are projected to experience the strongest increase in variability. These changes would therefore amplify the inequality associated with the impacts of a changing climate.

  15. Land Use and Climate Variability Amplify Contaminant Pulses

    EPA Science Inventory

    Converting land to human-dominated uses has increased contaminant loads in streams and rivers and vastly transformed hydrological cycles (Vitousek et al. 1997). More recently, climate change has further altered hydrologic cycles and variability of precipitation (IPCC 2007). Toge…

  16. Climate models predict increasing temperature variability in poor countries

    PubMed Central

    Dakos, Vasilis; Scheffer, Marten

    2018-01-01

    Extreme events such as heat waves are among the most challenging aspects of climate change for societies. We show that climate models consistently project increases in temperature variability in tropical countries over the coming decades, with the Amazon as a particular hotspot of concern. During the season with maximum insolation, temperature variability increases by ~15% per degree of global warming in Amazonia and Southern Africa and by up to 10%°C−1 in the Sahel, India, and Southeast Asia. Mechanisms include drying soils and shifts in atmospheric structure. Outside the tropics, temperature variability is projected to decrease on average because of a reduced meridional temperature gradient and sea-ice loss. The countries that have contributed least to climate change, and are most vulnerable to extreme events, are projected to experience the strongest increase in variability. These changes would therefore amplify the inequality associated with the impacts of a changing climate. PMID:29732409

  17. Impact of climate variability on vector-borne disease transmission

    USDA-ARS?s Scientific Manuscript database

    We will discuss the impact of climate variability on vector borne diseases and demonstrate that global climate teleconnections can be used to anticipate and forecast, in the case of Rift Valley fever, epidemics and epizootics. In this context we will examine significant worldwide weather anomalies t…

  18. Intraseasonal Variability in the Atmosphere-Ocean Climate System. Second Edition

    NASA Technical Reports Server (NTRS)

    Lau, William K. M.; Waliser, Duane E.

    2011-01-01

    Understanding and predicting the intraseasonal variability (ISV) of the ocean and atmosphere is crucial to improving long-range environmental forecasts and the reliability of climate change projections through climate models. This updated, comprehensive and authoritative second edition has a balance of observation, theory and modeling and provides a single source of reference for all those interested in this important multi-faceted natural phenomenon and its relation to major short-term climatic variations.

  19. Frontiers in Decadal Climate Variability: Proceedings of a Workshop

    SciTech Connect

    Purcell, Amanda

    A number of studies indicate an apparent slowdown in the overall rise in global average surface temperature between roughly 1998 and 2014. Most models did not predict such a slowdown–a fact that stimulated a lot of new research on variability of Earth’s climate system. At a September 2015 workshop, leading scientists gathered to discuss current understanding of climate variability on decadal timescales (10 to 30 years) and whether and how prediction of it might be improved. Many researchers have focused their attention on the climate system itself, which is known to vary across seasons, decades, and other timescales. Several naturalmore » variables produce “ups and downs” in the climate system, which are superimposed on the long-term warming trend due to human influence. Understanding decadal climate variability is important not only for assessing global climate change but also for improving decision making related to infrastructure, water resources, agriculture, energy, and other realms. Like the well-studied El Nino and La Nina interannual variations, decadal climate variability is associated with specific regional patterns of temperature and precipitation, such as heat waves, cold spells, and droughts. Several participants shared research that assesses decadal predictive capability of current models.« less

  20. Intensified Indian Ocean climate variability during the Last Glacial Maximum

    NASA Astrophysics Data System (ADS)

    Thirumalai, K.; DiNezro, P.; Tierney, J. E.; Puy, M.; Mohtadi, M.

    2017-12-01

    Climate models project increased year-to-year climate variability in the equatorial Indian Ocean in response to greenhouse gas warming. This response has been attributed to changes in the mean climate of the Indian Ocean associated with the zonal sea-surface temperature (SST) gradient. According to these studies, air-sea coupling is enhanced due to a stronger SST gradient driving anomalous easterlies that shoal the thermocline in the eastern Indian Ocean. We propose that this relationship between the variability and the zonal SST gradient is consistent across different mean climate states. We test this hypothesis using simulations of past and future climate performed with the Community Earth System Model Version 1 (CESM1). We constrain the realism of the model for the Last Glacial Maximum (LGM) where CESM1 simulates a mean climate consistent with a stronger SST gradient, agreeing with proxy reconstructions. CESM1 also simulates a pronounced increase in seasonal and interannual variability. We develop new estimates of climate variability on these timescales during the LGM using δ18O analysis of individual foraminifera (IFA). IFA data generated from four different cores located in the eastern Indian Ocean indicate a marked increase in δ18O-variance during the LGM as compared to the late Holocene. Such a significant increase in the IFA-δ18O variance strongly supports the modeling simulations. This agreement further supports the dynamics linking year-to-year variability and an altered SST gradient, increasing our confidence in model projections.

  1. The Variable Climate Impact of Volcanic Eruptions

    NASA Astrophysics Data System (ADS)

    Graf, H.

    2011-12-01

    The main effect of big volcanic eruptions in the climate system is due to their efficient transport of condensable gases and their precursors into the stratosphere. There the formation of aerosols leads to effects on atmospheric radiation transfer inducing a reduction of incoming solar radiation by reflection (i.e. cooling of the Earth surface) and absorption of near infrared radiation (i.e. heating) in the aerosol laden layers. In the talk processes determining the climate effect of an eruption will be illustrated by examples, mainly from numerical modelling. The amount of gases released from a magma during an eruption and the efficiency of their transport into very high altitudes depends on the geological setting (magma type) and eruption style. While mid-sized eruption plumes of Plinian style quickly can develop buoyancy by entrainment of ambient air, very large eruptions with high magma flux rates often tend to collapsing plumes and co-ignimbrite style. These cover much bigger areas and are less efficient in entraining ambient air. Vertical transport in these plumes is chaotic and less efficient, leading to lower neutral buoyancy height and less gas and particles reaching high stratospheric altitudes. Explosive energy and amount of released condensable gases are not the only determinants for the climatic effect of an eruption. The effect on shortwave radiation is not linear with the amount of aerosols formed since according to the Lambert-Beer Law atmospheric optical depth reaches a saturation limit with increased absorber concentration. In addition, if more condensable gas is available for aerosol growth, particles become larger and this affects their optical properties to less reflection and more absorption. Larger particles settle out faster, thus reducing the life time of the aerosol disturbance. Especially for big tropical eruptions the strong heating of the stratosphere in low latitudes leads to changes in atmospheric wave propagation by strengthened

  2. Human Responses to Climate Variability: The Case of South Africa

    NASA Astrophysics Data System (ADS)

    Oppenheimer, M.; Licker, R.; Mastrorillo, M.; Bohra-Mishra, P.; Estes, L. D.; Cai, R.

    2014-12-01

    Climate variability has been associated with a range of societal and individual outcomes including migration, violent conflict, changes in labor productivity, and health impacts. Some of these may be direct responses to changes in mean temperature or precipitation or extreme events, such as displacement of human populations by tropical cyclones. Others may be mediated by a variety of biological, social, or ecological factors such as migration in response to long-term changes in crops yields. Research is beginning to elucidate and distinguish the many channels through which climate variability may influence human behavior (ranging from the individual to the collective, societal level) in order to better understand how to improve resilience in the face of current variability as well as future climate change. Using a variety of data sets from South Africa, we show how climate variability has influenced internal (within country) migration in recent history. We focus on South Africa as it is a country with high levels of internal migration and dramatic temperature and precipitation changes projected for the 21st century. High poverty rates and significant levels of rain-fed, smallholder agriculture leave large portions of South Africa’s population base vulnerable to future climate change. In this study, we utilize two complementary statistical models – one micro-level model, driven by individual and household level survey data, and one macro-level model, driven by national census statistics. In both models, we consider the effect of climate on migration both directly (with gridded climate reanalysis data) and indirectly (with agricultural production statistics). With our historical analyses of climate variability, we gain insights into how the migration decisions of South Africans may be influenced by future climate change. We also offer perspective on the utility of micro and macro level approaches in the study of climate change and human migration.

  3. Influence of climate variability on terrestrial hydrology in North America

    NASA Astrophysics Data System (ADS)

    Chen, Ji

    A large-area basin-scale (LABs) model is developed for regional, continental and global hydrologic studies. The heterogeneity in the soil-moisture distribution within a basin is parameterized through the statistical moments of the probability distribution function of the topographic (wetness) index. The role of topographic influence in hydrologic prediction is studied using the LABs model and ISLSCP data for 1987 and 1988 in North America. Improvement in the terrestrial water balance and streamflow is observed due to improvements in the surface runoff and baseflow components achieved by incorporating the basin topographic features. These enhancements also impact the surface energy balance, Daily streamflow observations of the Mississippi river and its four tributaries are used for evaluating the LABs performance. It is observed that model baseflow has a significant contribution to the streamflow and is important in realistically capturing the seasonal and annual cycles. To study the impacts of climate variations on the terrestrial hydrologic processes, ERA-15 dataset (1979-1993) is used to drive LABs for all basins over North America. The anomalies of the model forcing and output are correlated with climate anomalies, such as ENSO, NAO and PNA. It is found that the terrestrial hydrology has a delayed response to the ENSO signal, as compared to the precipitation, and the delay may range from a month to a season or longer. The soil moisture storage plays a very vital role in delaying the effects of the climate variability on the terrestrial hydrology and in extending the influences of the El Niña and La Niña events. The fluctuation of the soil temperature anomaly is correlated with ENSO in certain geographic regions, and the strength and the associated time lag of this correlation increase with increasing soil depth. In addition, the NAO and PNA correlations with downward longwave radiation, surface temperature and ground heat flux in North America show a seesaw

  4. An Observational Study of Cataclysmic Variable Evolution

    NASA Astrophysics Data System (ADS)

    Araujo-Betancor, Sofia

    2004-03-01

    In this thesis I present an observational study of the evolution of Cataclysmic Variables (CVs). Disrupted magnetic braking has been the standard paradigm of CV evolution for the past twenty years. Unfortunately, some of its predictions are in strong disagreement with the observations. In recent years, a number of additions/alternatives to the standard model have been proposed. Yet, none have been able to explain all of the features observed in the currently known CV population. The work presented in this thesis is based mainly on a large-scale search for CVs. The primary aim of this project is to resolve the disagreement between theory and observations by eliminating the observational biases of the present CV sample. Here, I use two complementary approaches to search for CVs: (1) from the spectroscopic appearance in the Hamburg Quasar Survey (HQS), and (2) by using a combination of ROSAT and 2MASS archival data. So far, we have discovered 52 new CVs in the HQS and 11 new CVs (the majority of them magnetic) and 1 pre-CV in the ROSAT/2MASS. Follow-up observations of two newly discovered HQS CVs, 1RXS J062518.2+733433 and HS 2331+3905, resulted in the classification of the first as an Intermediate Polar, with P_orb = 283.0 min and P_spin = 19.8 min, and the second as a short orbital period system, P_orb = 81.0 min, harbouring a white dwarf pulsator. In addition, we found that the dominant ~3.5 h radial velocity variation of HS 2331+3905 does not correspond to the orbital period of the system, contrary to all other CVs. Despite its novel selection criterion, the HQS does not provide many short-period CVs — even though tests with the known CVs included in the survey have shown that it is very sensitive to those objects. The biggest surprise in the new HQS sample is the discovery of many new SW Sex stars. The clustering of SW Sex stars in the 3-4 h period range is probably an important feature in the evolution of CVs that we currently do not understand at all. To

  5. Observer variability in estimating numbers: An experiment

    USGS Publications Warehouse

    Erwin, R.M.

    1982-01-01

    Census estimates of bird populations provide an essential framework for a host of research and management questions. However, with some exceptions, the reliability of numerical estimates and the factors influencing them have received insufficient attention. Independent of the problems associated with habitat type, weather conditions, cryptic coloration, ete., estimates may vary widely due only to intrinsic differences in observers? abilities to estimate numbers. Lessons learned in the field of perceptual psychology may be usefully applied to ‘real world’ problems in field ornithology. Based largely on dot discrimination tests in the laboratory, it was found that numerical abundance, density of objects, spatial configuration, color, background, and other variables influence individual accuracy in estimating numbers. The primary purpose of the present experiment was to assess the effects of observer, prior experience, and numerical range on accuracy in estimating numbers of waterfowl from black-and-white photographs. By using photographs of animals rather than black dots, I felt the results could be applied more meaningfully to field situations. Further, reinforcement was provided throughout some experiments to examine the influence of training on accuracy.

  6. Relationships between northern Adriatic Sea mucilage events and climate variability.

    PubMed

    Deserti, Marco; Cacciamani, Carlo; Chiggiato, Jacopo; Rinaldi, Attilio; Ferrari, Carla R

    2005-12-15

    A long term analysis (1865-2002) of meteorological data collected in the Po Valley and Northern Adriatic Basin have been analysed to find possible links between variability in the climatic parameters and the phenomenon of mucilage. Seasonal anomalies of temperature, calculated as spatial mean over the Po Valley area, and anomalies of North Atlantic Oscillation were compared with the historical record of mucilage episodes. Both climatic indices were found to be positively correlated with mucilage events, suggesting a possible relationship between climatic variability and the increased appearance of mucilage aggregates.

  7. Historical Phenological Observations: Past Climate Impact Analyses and Climate Reconstructions

    NASA Astrophysics Data System (ADS)

    Rutishauser, T.; Luterbacher, J.; Meier, N.; Jeanneret, F.; Pfister, C.; Wanner, H.

    2007-12-01

    Plant phenological observations have been found an important indicator of climate change impacts on seasonal and interannual vegetation development for the late 20th/early 21st century. Our contribution contains three parts that are essential for the understanding (part 1), the analysis (part 2) and the application (part 3) of historical phenological observations in global change research. First, we propose a definition for historical phenonolgy (Rutishauser, 2007). We shortly portray the first appearance of phenological observations in Medieval philosophical and literature sources, the usage and application of this method in the Age of Enlightenment (Carl von Linné, Charles Morren), as well as the development in the 20th century (Schnelle, Lieth) to present-day networks (COST725, USA-NPN) Second, we introduce a methodological approach to estimate ‘Statistical plants’ from historical phenological observations (Rutishauser et al., JGR-Biogeoscience, in press). We combine spatial averaging methods and regression transfer modeling to estimate ‘statistical plant’ dates from historical observations that often contain gaps, changing observers and changing locations. We apply the concept to reconstruct a statistical ‘Spring plant’ as the weighted mean of the flowering date of cherry and apple tree and beech budburst of Switzerland 1702- 2005. Including dating total data uncertainty we estimate 10 at interannual and 3.4 days at decadal time scales. Third, we apply two long-term phenological records to describe plant phenological response to spring temperature and reconstruct warm-season temperatures from grape harvest dates (Rutishauser et al, submitted; Meier et al, GRL, in press).

  8. Climate Variability and Oceanographic Settings Associated with Interannual Variability in the Initiation of Dinophysis acuminata Blooms

    PubMed Central

    Díaz, Patricio A.; Reguera, Beatriz; Ruiz-Villarreal, Manuel; Pazos, Yolanda; Velo-Suárez, Lourdes; Berger, Henrick; Sourisseau, Marc

    2013-01-01

    In 2012, there were exceptional blooms of D. acuminata in early spring in what appeared to be a mesoscale event affecting Western Iberia and the Bay of Biscay. The objective of this work was to identify common climatic patterns to explain the observed anomalies in two important aquaculture sites, the Galician Rías Baixas (NW Spain) and Arcachon Bay (SW France). Here, we examine climate variability through physical-biological couplings, Sea Surface Temperature (SST) anomalies and time of initiation of the upwelling season and its intensity over several decades. In 2012, the mesoscale features common to the two sites were positive anomalies in SST and unusual wind patterns. These led to an atypical predominance of upwelling in winter in the Galician Rías, and increased haline stratification associated with a southward advection of the Gironde plume in Arcachon Bay. Both scenarios promoted an early phytoplankton growth season and increased stability that enhanced D. acuminata growth. Therefore, a common climate anomaly caused exceptional blooms of D. acuminata in two distant regions through different triggering mechanisms. These results increase our capability to predict intense diarrhetic shellfish poisoning outbreaks in the early spring from observations in the preceding winter. PMID:23959151

  9. Women’s role in adapting to climate change and variability

    NASA Astrophysics Data System (ADS)

    Carvajal-Escobar, Y.; Quintero-Angel, M.; García-Vargas, M.

    2008-04-01

    Given that women are engaged in more climate-related change activities than what is recognized and valued in the community, this article highlights their important role in the adaptation and search for safer communities, which leads them to understand better the causes and consequences of changes in climatic conditions. It is concluded that women have important knowledge and skills for orienting the adaptation processes, a product of their roles in society (productive, reproductive and community); and the importance of gender equity in these processes is recognized. The relationship among climate change, climate variability and the accomplishment of the Millennium Development Goals is considered.

  10. Large-Scale Circulation and Climate Variability. Chapter 5

    NASA Technical Reports Server (NTRS)

    Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

    2017-01-01

    The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

  11. Has solar variability caused climate change that affected human culture?

    NASA Astrophysics Data System (ADS)

    Feynman, Joan

    If solar variability affects human culture it most likely does so by changing the climate in which the culture operates. Variations in the solar radiative input to the Earth’s atmosphere have often been suggested as a cause of such climate change on time scales from decades to tens of millennia. In the last 20 years there has been enormous progress in our knowledge of the many fields of research that impinge on this problem; the history of the solar output, the effect of solar variability on the Earth’s mean climate and its regional patterns, the history of the Earth’s climate and the history of mankind and human culture. This new knowledge encourages revisiting the question asked in the title of this talk. Several important historical events have been reliably related to climate change including the Little Ice Age in northern Europe and the collapse of the Classical Mayan civilization in the 9th century AD. In the first section of this paper we discus these historical events and review the evidence that they were caused by changes in the solar output. Perhaps the most important event in the history of mankind was the development of agricultural societies. This began to occur almost 12,000 years ago when the climate changed from the Pleistocene to the modern climate of the Holocene. In the second section of the paper we will discuss the suggestion ( Feynman and Ruzmaikin, 2007) that climate variability was the reason agriculture developed when it did and not before.

  12. Climate Observing Systems: Where are we and where do we need to be in the future

    NASA Astrophysics Data System (ADS)

    Baker, B.; Diamond, H. J.

    2017-12-01

    Climate research and monitoring requires an observational strategy that blends long-term, carefully calibrated measurements as well as short-term, focused process studies. The operation and implementation of operational climate observing networks and the provision of related climate services, both have a significant role to play in assisting the development of national climate adaptation policies and in facilitating national economic development. Climate observing systems will require a strong research element for a long time to come. This requires improved observations of the state variables and the ability to set them in a coherent physical (as well as a chemical and biological) framework with models. Climate research and monitoring requires an integrated strategy of land/ocean/atmosphere observations, including both in situ and remote sensing platforms, and modeling and analysis. It is clear that we still need more research and analysis on climate processes, sampling strategies, and processing algorithms.

  13. Seasonal climate variability in Medieval Europe (1000 to 1499)

    NASA Astrophysics Data System (ADS)

    Pfister, C.

    2009-04-01

    In his fundamental work on medieval climate Alexandre (1987) highlighted the significance of dealing with contemporary sources. Recently, long series of temperature indices for “summer” and “winter” were set up by Shabalova and van Engelen (2003) for the Low Countries, but the time resolution is not strictly seasonal. This paper worked out within the EU 6th Framework Project “Millennium” draws on critically reviewed documentary evidence from a spatially extensive area of Western and Central Europe (basically England, France, BENELUX, Western Germany, Switzerland, Austria, Poland, Hungary and todays Czech Republic. The narrative evidence is complemented with dendro-climatic series from the Alps (Büntgen et al. 2006). Each “climate observation” is georeferenced which allows producing spatial displays of the data for selected spaces and time-frames. The spatial distribution of the information charts can be used as a tool for the climatological verification of the underlying data. Reconstructions for winter (DJF) and summer (JJA) are presented in the form of time series and charts. Cold winters were frequent from 1205 to 1235 i.e. in the “Medieval Warm Period” and in the Little Ice Age (1306-1330; 1390-1470). Dry and warm summers prevailed in Western and Central Europe in the first half of the 13th century. During the Little Ice Age cold-wet summers (triggered by volcanic explosions in the tropics) were more frequent, though summer climate remained highly variable. Results are discussed with regard to the “Greenhouse Debate” and the relationship to glacier fluctuations in the Alps is explored. References -Alexandre, Pierre, 1987: Le Climat en Europe au Moyen Age. Contribution à l’histoire des variations climatiques de 1000 à 1425. Paris. -Büntgen, Ulf et al. 2006: Summer Temperature Variation in the European Alps, AD. 755-2004, J. of Climate 19 5606-5623. – Pfister, Christian et al. 1998: Winter air temperature variations in Central Europe during the Early and

  14. Changing precipitation in western Europe, climate change or natural variability?

    NASA Astrophysics Data System (ADS)

    Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

    2017-04-01

    Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members – the combined result of model uncertainty and natural variability of the climate system – is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given

  15. Skilful multi-year predictions of tropical trans-basin climate variability

    PubMed Central

    Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

    2015-01-01

    Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation. PMID:25897996

  16. Skilful multi-year predictions of tropical trans-basin climate variability.

    PubMed

    Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

    2015-04-21

    Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation.

  17. Tropical convection regimes in climate models: evaluation with satellite observations

    NASA Astrophysics Data System (ADS)

    Steiner, Andrea K.; Lackner, Bettina C.; Ringer, Mark A.

    2018-04-01

    High-quality observations are powerful tools for the evaluation of climate models towards improvement and reduction of uncertainty. Particularly at low latitudes, the most uncertain aspect lies in the representation of moist convection and interaction with dynamics, where rising motion is tied to deep convection and sinking motion to dry regimes. Since humidity is closely coupled with temperature feedbacks in the tropical troposphere, a proper representation of this region is essential. Here we demonstrate the evaluation of atmospheric climate models with satellite-based observations from Global Positioning System (GPS) radio occultation (RO), which feature high vertical resolution and accuracy in the troposphere to lower stratosphere. We focus on the representation of the vertical atmospheric structure in tropical convection regimes, defined by high updraft velocity over warm surfaces, and investigate atmospheric temperature and humidity profiles. Results reveal that some models do not fully capture convection regions, particularly over land, and only partly represent strong vertical wind classes. Models show large biases in tropical mean temperature of more than 4 K in the tropopause region and the lower stratosphere. Reasonable agreement with observations is given in mean specific humidity in the lower to mid-troposphere. In moist convection regions, models tend to underestimate moisture by 10 to 40 % over oceans, whereas in dry downdraft regions they overestimate moisture by 100 %. Our findings provide evidence that RO observations are a unique source of information, with a range of further atmospheric variables to be exploited, for the evaluation and advancement of next-generation climate models.

  18. Deglacial climate variability in central Florida, USA

    USGS Publications Warehouse

    Willard, D.A.; Bernhardt, C.E.; Brooks, G.R.; Cronin, T. M.; Edgar, T.; Larson, R.

    2007-01-01

    Pollen and ostracode evidence from lacustrine sediments underlying modern Tampa Bay, Florida, document frequent and abrupt climatic and hydrological events superimposed on deglacial warming in the subtropics. Radiocarbon chronology on well-preserved mollusk shells and pollen residue from core MD02-2579 documents continuous sedimentation in a variety of non-marine habitats in a karst-controlled basin from 20 ka to 11.5 ka. During the last glacial maximum (LGM), much drier and cooler-than-modern conditions are indicated by pollen assemblages enriched in Chenopodiaceae and Carya, with rare Pinus (Pinus pollen increased to 20–40% during the warming of the initial deglaciation (∼ 17.2 ka), reaching near modern abundance (60–80%) during warmer, moister climates of the Bølling/Allerød interval (14.7–12.9 ka). Within the Bølling/Allerød, centennial-scale dry events corresponding to the Older Dryas and Intra-Allerød Cold Period indicate rapid vegetation response (

  19. News and Views: Kleopatra a pile of rubble, shedding moons; Did plasma flow falter to stretch solar minimum? Amateurs hit 20 million variable-star observations; Climate maths; Planetary priorities; New roles in BGA

    NASA Astrophysics Data System (ADS)

    2011-04-01

    Metallic asteroid 216 Kleopatra is shaped like a dog’s bone and has two tiny moons – which came from the asteroid itself – according to a team of astronomers from France and the US, who also measured its surprisingly low density and concluded that it is a collection of rubble. The recent solar minimum was longer and lower than expected, with a low polar field and an unusually large number of days with no sunspots visible. Models of the magnetic field and plasma flow within the Sun suggest that fast, then slow meridional flow could account for this pattern. Variable stars are a significant scientific target for amateur astronomers. The American Association of Variable Star Observers runs the world’s largest database of variable star observations, from volunteers, and reached 20 million observations in February.

  20. Thermal barriers constrain microbial elevational range size via climate variability.

    PubMed

    Wang, Jianjun; Soininen, Janne

    2017-08-01

    Range size is invariably limited and understanding range size variation is an important objective in ecology. However, microbial range size across geographical gradients remains understudied, especially on mountainsides. Here, the patterns of range size of stream microbes (i.e., bacteria and diatoms) and macroorganisms (i.e., macroinvertebrates) along elevational gradients in Asia and Europe were examined. In bacteria, elevational range size showed non-significant phylogenetic signals. In all taxa, there was a positive relationship between niche breadth and species elevational range size, driven by local environmental and climatic variables. No taxa followed the elevational Rapoport’s rule. Climate variability explained the most variation in microbial mean elevational range size, whereas local environmental variables were more important for macroinvertebrates. Seasonal and annual climate variation showed negative effects, while daily climate variation had positive effects on community mean elevational range size for all taxa. The negative correlation between range size and species richness suggests that understanding the drivers of range is key for revealing the processes underlying diversity. The results advance the understanding of microbial species thermal barriers by revealing the importance of seasonal and diurnal climate variation, and highlight that aquatic and terrestrial biota may differ in their response to short- and long-term climate variability. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

  1. Quantifying the increasing sensitivity of power systems to climate variability

    NASA Astrophysics Data System (ADS)

    Bloomfield, H. C.; Brayshaw, D. J.; Shaffrey, L. C.; Coker, P. J.; Thornton, H. E.

    2016-12-01

    Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insufficient for providing robust power system planning guidance. This suggests renewable integration studies—widely used in policy, investment and system design—should adopt a more robust approach to climate characterisation.

  2. Taking the pulse of mountains: Ecosystem responses to climatic variability

    USGS Publications Warehouse

    Fagre, Daniel B.; Peterson, David L.; Hessl, Amy E.

    2003-01-01

    An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change

  3. Environmental variability and indicators: a few observations

    Treesearch

    William F. Laudenslayer

    1991-01-01

    Abstract The environment of the earth is exceedingly complex and variable. Indicator species are used to reduce thaf complexity and variability to a level that can be more emily understood. In recent years, use of indicators has increased dramatically. For the Forest Service, as an example, regulations that interpret the National Forest Management Act require the use…

  4. Observing climate change trends in ocean biogeochemistry: when and where.

    PubMed

    Henson, Stephanie A; Beaulieu, Claudie; Lampitt, Richard

    2016-04-01

    Understanding the influence of anthropogenic forcing on the marine biosphere is a high priority. Climate change-driven trends need to be accurately assessed and detected in a timely manner. As part of the effort towards detection of long-term trends, a network of ocean observatories and time series stations provide high quality data for a number of key parameters, such as pH, oxygen concentration or primary production (PP). Here, we use an ensemble of global coupled climate models to assess the temporal and spatial scales over which observations of eight biogeochemically relevant variables must be made to robustly detect a long-term trend. We find that, as a global average, continuous time series are required for between 14 (pH) and 32 (PP) years to distinguish a climate change trend from natural variability. Regional differences are extensive, with low latitudes and the Arctic generally needing shorter time series (observing networks for detection and monitoring of climate change-driven responses in the marine ecosystem. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

  5. Climate Variability, Climate Change and Social Vulnerability in the Semi-arid Tropics

    NASA Astrophysics Data System (ADS)

    Ribot, Jesse C.; Rocha Magalhaes, Antonio; Panagides, Stahis

    1996-06-01

    Climate changes can trigger events that lead to mass migration, hunger, and even famine. Rather than focus on the impacts that result from climatic fluctuations, the authors look at the underlying conditions that cause social vulnerability. Once we understand why individuals, households, nations, and regions are vulnerable, and how they have buffered themselves against climatic and environmental shifts, then present and future vulnerability can be redressed. By using case studies from across the globe, the authors explore past experiences with climate variability, and the likely effects of–and the possible policy responses to–the types of climatic events that global warming might bring.

  6. Conveying the Science of Climate Change: Explaining Natural Variability

    NASA Astrophysics Data System (ADS)

    Chanton, J.

    2011-12-01

    One of the main problems in climate change education is reconciling the role of humans and natural variability. The climate is always changing, so how can humans have a role in causing change? How do we reconcile and differentiate the anthropogenic effect from natural variability? This talk will offer several approaches that have been successful for the author. First, the context of climate change during the Pleistocene must be addressed. Second, is the role of the industrial revolution in significantly altering Pleistocene cycles, and introduction of the concept of the Anthropocene. Finally the positive feedbacks between climatic nudging due to increased insolation and greenhouse gas forcing can be likened to a rock rolling down a hill, without a leading cause. This approach has proven successful in presentations to undergraduates to state agencies.

  7. Climate variability has a stabilizing effect on the coexistence of prairie grasses

    PubMed Central

    Adler, Peter B.; HilleRisLambers, Janneke; Kyriakidis, Phaedon C.; Guan, Qingfeng; Levine, Jonathan M.

    2006-01-01

    How expected increases in climate variability will affect species diversity depends on the role of such variability in regulating the coexistence of competing species. Despite theory linking temporal environmental fluctuations with the maintenance of diversity, the importance of climate variability for stabilizing coexistence remains unknown because of a lack of appropriate long-term observations. Here, we analyze three decades of demographic data from a Kansas prairie to demonstrate that interannual climate variability promotes the coexistence of three common grass species. Specifically, we show that (i) the dynamics of the three species satisfy all requirements of “storage effect” theory based on recruitment variability with overlapping generations, (ii) climate variables are correlated with interannual variation in species performance, and (iii) temporal variability increases low-density growth rates, buffering these species against competitive exclusion. Given that environmental fluctuations are ubiquitous in natural systems, our results suggest that coexistence based on the storage effect may be underappreciated and could provide an important alternative to recent neutral theories of diversity. Field evidence for positive effects of variability on coexistence also emphasizes the need to consider changes in both climate means and variances when forecasting the effects of global change on species diversity. PMID:16908862

  8. Does global warming amplify interannual climate variability?

    NASA Astrophysics Data System (ADS)

    He, Chao; Li, Tim

    2018-06-01

    Based on the outputs of 30 models from Coupled Model Intercomparison Project Phase 5 (CMIP5), the fractional changes in the amplitude interannual variability (σ) for precipitation (P’) and vertical velocity (ω’) are assessed, and simple theoretical models are constructed to quantitatively understand the changes in σ(P’) and σ(ω’). Both RCP8.5 and RCP4.5 scenarios show similar results in term of the fractional change per degree of warming, with slightly lower inter-model uncertainty under RCP8.5. Based on the multi-model median, σ(P’) generally increases but σ(ω’) generally decreases under global warming but both are characterized by non-uniform spatial patterns. The σ(P’) decrease over subtropical subsidence regions but increase elsewhere, with a regional averaged value of 1.4% K- 1 over 20°S-50°N under RCP8.5. Diagnoses show that the mechanisms for the change in σ(P’) are different for climatological ascending and descending regions. Over ascending regions, the increase of mean state specific humidity contributes to a general increase of σ(P’) but the change of σ(ω’) dominates its spatial pattern and inter-model uncertainty. But over descending regions, the change of σ(P’) and its inter-model uncertainty are constrained by the change of mean state precipitation. The σ(ω’) is projected to be weakened almost everywhere except over equatorial Pacific, with a regional averaged fractional change of – 3.4% K- 1 at 500 hPa. The overall reduction of σ(ω’) results from the increased mean state static stability, while the substantially increased σ(ω’) at the mid-upper troposphere over equatorial Pacific and the inter-model uncertainty of the changes in σ(ω’) are dominated by the change in the interannual variability of diabatic heating.

  9. Climate change: Conflict of observational science, theory, and politics

    USGS Publications Warehouse

    Gerhard, L.C.

    2004-01-01

    Debate over whether human activity causes Earth climate change obscures the immensity of the dynamic systems that create and maintain climate on the planet. Anthropocentric debate leads people to believe that they can alter these planetary dynamic systems to prevent that they perceive as negative climate impacts on human civilization. Although politicians offer simplistic remedies, such as the Kyoto Protocol, global climate continues to change naturally. Better planning for the inevitable dislocations that have followed natural global climate changes throughout human history requires us to accept the fact that climate will change, and that human society must adapt to the changes. Over the last decade, the scientific literature reported a shift in emphasis from attempting to build theoretical models of putative human impacts on climate to understanding the planetwide dynamic processes that are the natural climate drivers. The current scientific literature is beginning to report the history of past climate change, the extent of natural climate variability, natural system drivers, and the episodicity of many climate changes. The scientific arguments have broadened from focus upon human effects on climate to include the array of natural phenomena that have driven global climate change for eons. However, significant political issues with long-term social consequences continue their advance. This paper summarizes recent scientific progress in climate science and arguments about human influence on climate. ?? 2004. The American Association of Petroleum Geologists. All rights reserved.

  10. Earth System Science Education Centered on Natural Climate Variability

    NASA Astrophysics Data System (ADS)

    Ramirez, P. C.; Ladochy, S.; Patzert, W. C.; Willis, J. K.

    2009-12-01

    Several new courses and many educational activities related to climate change are available to teachers and students of all grade levels. However, not all new discoveries in climate research have reached the science education community. In particular, effective learning tools explaining natural climate change are scarce. For example, the Pacific Decadal Oscillation (PDO) is a main cause of natural climate variability spanning decades. While most educators are familiar with the shorter-temporal events impacting climate, El Niño and La Niña, very little has trickled into the climate change curriculum on the PDO. We have developed two online educational modules, using an Earth system science approach, on the PDO and its role in climate change and variability. The first concentrates on the discovery of the PDO through records of salmon catch in the Pacific Northwest and Alaska. We present the connection between salmon abundance in the North Pacific to changing sea surface temperature patterns associated with the PDO. The connection between sea surface temperatures and salmon abundance led to the discovery of the PDO. Our activity also lets students explore the role of salmon in the economy and culture of the Pacific Northwest and Alaska and the environmental requirements for salmon survival. The second module is based on the climate of southern California and how changes in the Pacific Ocean , such as the PDO and ENSO (El Niño-Southern Oscillation), influence regional climate variability. PDO and ENSO signals are evident in the long-term temperature and precipitation record of southern California. Students are guided in the module to discover the relationships between Pacific Ocean conditions and southern California climate variability. The module also provides information establishing the relationship between climate change and variability and the state’s water, energy, agriculture, wildfires and forestry, air quality and health issues. Both modules will be

  11. Future local climate unlike currently observed anywhere

    NASA Astrophysics Data System (ADS)

    Dahinden, Fabienne; Fischer, Erich M.; Knutti, Reto

    2017-08-01

    The concept of spatial climate analogs, that is identifying a place with a present-day climate similar to the projections of a place of interest, is a promising method for visualizing and communicating possible effects of climate change. We show that when accounting for seasonal cycles of both temperature and precipitation, it is impossible to find good analogs for projections at many places across the world. For substantial land fractions, primarily in the tropics and subtropics, there are no analogs anywhere with current seasonal cycles of temperature and precipitation matching their projected future conditions. This implies that these places experience the emergence of novel climates. For 1.5 °C global warming about 15% and for 2 °C warming about 21% of the global land is projected to experience novel climates, whereas for a 4 °C warming the corresponding novel climates may emerge on more than a third of the global land fraction. Similar fractions of today’s climates, mainly found in the tropics, subtropics and polar north, are anticipated to disappear in the future. Note that the exact quantification of the land fraction is sensitive to the threshold selection. Novel and disappearing climates may have serious consequences for impacts that are sensitive to the full seasonal cycle of temperature and precipitation. For individual seasons, however, spatial analogs may still be a powerful tool for climate change communication.

  12. Designing the Climate Observing System of the Future

    NASA Astrophysics Data System (ADS)

    Weatherhead, Elizabeth C.; Wielicki, Bruce A.; Ramaswamy, V.; Abbott, Mark; Ackerman, Thomas P.; Atlas, Robert; Brasseur, Guy; Bruhwiler, Lori; Busalacchi, Antonio J.; Butler, James H.; Clack, Christopher T. M.; Cooke, Roger; Cucurull, Lidia; Davis, Sean M.; English, Jason M.; Fahey, David W.; Fine, Steven S.; Lazo, Jeffrey K.; Liang, Shunlin; Loeb, Norman G.; Rignot, Eric; Soden, Brian; Stanitski, Diane; Stephens, Graeme; Tapley, Byron D.; Thompson, Anne M.; Trenberth, Kevin E.; Wuebbles, Donald

    2018-01-01

    Climate observations are needed to address a large range of important societal issues including sea level rise, droughts, floods, extreme heat events, food security, and freshwater availability in the coming decades. Past, targeted investments in specific climate questions have resulted in tremendous improvements in issues important to human health, security, and infrastructure. However, the current climate observing system was not planned in a comprehensive, focused manner required to adequately address the full range of climate needs. A potential approach to planning the observing system of the future is presented in this article. First, this article proposes that priority be given to the most critical needs as identified within the World Climate Research Program as Grand Challenges. These currently include seven important topics: melting ice and global consequences; clouds, circulation and climate sensitivity; carbon feedbacks in the climate system; understanding and predicting weather and climate extremes; water for the food baskets of the world; regional sea-level change and coastal impacts; and near-term climate prediction. For each Grand Challenge, observations are needed for long-term monitoring, process studies and forecasting capabilities. Second, objective evaluations of proposed observing systems, including satellites, ground-based and in situ observations as well as potentially new, unidentified observational approaches, can quantify the ability to address these climate priorities. And third, investments in effective climate observations will be economically important as they will offer a magnified return on investment that justifies a far greater development of observations to serve society’s needs.

  13. US Climate Variability and Predictability (CLIVAR) Project- Final Report

    SciTech Connect

    Patterson, Mike

    The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year supportmore » of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.« less

  14. The Grand Challenges of WCRP and the Climate Observing System of the Future

    NASA Astrophysics Data System (ADS)

    Brasseur, G. P.

    2017-12-01

    The successful implementation the Paris agreement on climate change (COP21) calls for a well-designed global monitoring system of essential climate variables, climate processes and Earth system budgets. The Grand Challenges implemented by the World Climate Research Programme (WCRP) provide an opportunity to investigate issues of high societal relevance, directly related to sea level rise, droughts, floods, extreme heat events, food security, and fresh water availability. These challenges would directly benefit from a well-designed suite of systematic climate observations. Quantification of the evolution of the global energy, water and carbon budgets as well as the development and the production of near-term and regional climate predictions require that a comprehensive, focused, multi-platform observing system (satellites, ground-based and in situ observations) be established in an international context. This system must be accompanied by the development of climate services that should translate and disseminate scientific outcomes as actionable information for users and stakeholders.

  15. Validation of China-wide interpolated daily climate variables from 1960 to 2011

    NASA Astrophysics Data System (ADS)

    Yuan, Wenping; Xu, Bing; Chen, Zhuoqi; Xia, Jiangzhou; Xu, Wenfang; Chen, Yang; Wu, Xiaoxu; Fu, Yang

    2015-02-01

    Temporally and spatially continuous meteorological variables are increasingly in demand to support many different types of applications related to climate studies. Using measurements from 600 climate stations, a thin-plate spline method was applied to generate daily gridded climate datasets for mean air temperature, maximum temperature, minimum temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, and precipitation over China for the period 1961-2011. A comprehensive evaluation of interpolated climate was conducted at 150 independent validation sites. The results showed superior performance for most of the estimated variables. Except for wind speed, determination coefficients ( R 2) varied from 0.65 to 0.90, and interpolations showed high consistency with observations. Most of the estimated climate variables showed relatively consistent accuracy among all seasons according to the root mean square error, R 2, and relative predictive error. The interpolated data correctly predicted the occurrence of daily precipitation at validation sites with an accuracy of 83 %. Moreover, the interpolation data successfully explained the interannual variability trend for the eight meteorological variables at most validation sites. Consistent interannual variability trends were observed at 66-95 % of the sites for the eight meteorological variables. Accuracy in distinguishing extreme weather events differed substantially among the meteorological variables. The interpolated data identified extreme events for the three temperature variables, relative humidity, and sunshine duration with an accuracy ranging from 63 to 77 %. However, for wind speed, air pressure, and precipitation, the interpolation model correctly identified only 41, 48, and 58 % of extreme events, respectively. The validation indicates that the interpolations can be applied with high confidence for the three temperatures variables, as well as relative humidity and sunshine duration based

  16. Uncertainty information in climate data records from Earth observation

    NASA Astrophysics Data System (ADS)

    Merchant, Christopher J.; Paul, Frank; Popp, Thomas; Ablain, Michael; Bontemps, Sophie; Defourny, Pierre; Hollmann, Rainer; Lavergne, Thomas; Laeng, Alexandra; de Leeuw, Gerrit; Mittaz, Jonathan; Poulsen, Caroline; Povey, Adam C.; Reuter, Max; Sathyendranath, Shubha; Sandven, Stein; Sofieva, Viktoria F.; Wagner, Wolfgang

    2017-07-01

    The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). The paper discusses the many sources of error in CDRs, noting that different errors may be correlated across a wide range of timescales and space scales. Error effects that contribute negligibly to the total uncertainty in a single-satellite measurement can be the dominant sources of uncertainty in a CDR on the large space scales and long timescales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. The characterization of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the

  17. Trends in seasonal warm anomalies across the contiguous United States: Contributions from natural climate variability

    Treesearch

    Lejiang Yu; Shiyuan Zhong; Warren E. Heilman; Xindi Bian

    2018-01-01

    Many studies have shown the importance of anthropogenic greenhouse gas emissions in contributing to observed upward trends in the occurrences of temperature extremes over the U.S. However, few studies have investigated the contributions of internal variability in the climate system to these observed trends. Here we use daily maximum temperature time series from the…

  18. Vegetation Interaction Enhances Interdecadal Climate Variability in the Sahel

    NASA Technical Reports Server (NTRS)

    Zeng, Ning; Neelin, J. David; Lau, William K.-M.

    1999-01-01

    The role of naturally varying vegetation in influencing the climate variability in the Sahel is explored in a coupled atmosphere-land-vegetation model. The Sahel rainfall variability is influenced by sea surface temperature (SST) variations in the oceans. Land-surface feedback is found to increase this variability both on interannual and interdecadal time scales. Interactive vegetation enhances the interdecadal variation significantly, but can reduce year to year variability due to a phase lag introduced by the relatively slow vegetation adjustment time. Variations in vegetation accompany the changes in rainfall, in particular, the multi-decadal drying trend from the 1950s to the 80s.

  19. Local air temperature tolerance: a sensible basis for estimating climate variability

    NASA Astrophysics Data System (ADS)

    Kärner, Olavi; Post, Piia

    2016-11-01

    The customary representation of climate using sample moments is generally biased due to the noticeably nonstationary behaviour of many climate series. In this study, we introduce a moment-free climate representation based on a statistical model fitted to a long-term daily air temperature anomaly series. This model allows us to separate the climate and weather scale variability in the series. As a result, the climate scale can be characterized using the mean annual cycle of series and local air temperature tolerance, where the latter is computed using the fitted model. The representation of weather scale variability is specified using the frequency and the range of outliers based on the tolerance. The scheme is illustrated using five long-term air temperature records observed by different European meteorological stations.

  20. Climate Variability and Phytoplankton in the Pacific Ocean

    NASA Technical Reports Server (NTRS)

    Rousseaux, Cecile

    2012-01-01

    The effect of climate variability on phytoplankton communities was assessed for the tropical and sub-tropical Pacific Ocean between 1998 and 2005 using an established biogeochemical assimilation model. The phytoplankton communities exhibited wide range of responses to climate variability, from radical shifts in the Equatorial Pacific, to changes of only a couple of phytoplankton groups in the North Central Pacific, to no significant changes in the South Pacific. In the Equatorial Pacific, climate variability dominated the variability of phytoplankton. Here, nitrate, chlorophyll and all but one of the 4 phytoplankton types (diatoms, cyanobacteria and coccolithophores) were strongly correlated (pclimate variability can play in ocean biology.

  1. Assessing Portuguese Guadiana Basin water management impacts under climate change and paleoclimate variability

    NASA Astrophysics Data System (ADS)

    Maia, Rodrigo; Oliveira, Bruno; Ramos, Vanessa; Brekke, Levi

    2014-05-01

    indicates an increase in temperatures and a reduction of the precipitation values which go well beyond the observed values and, therefore, must be forcefully included in any realistic proactive water resource management decision. Using the results of this study it is possible to estimate future water availability and consumption satisfaction allowing for the elaboration of informed management decisions. In this study, the CMIP 3 Global Climate Models were considered for the definition of the effects of climate change, using the median and extreme tendencies based on the range of variation of the multiple climate projection scenarios. The observed climate variability, along with these model-derived tendencies, were used to inform the hydrology and water management models for the historical and future periods, respectively. Additionally, for a more comprehensive analysis on climate variability, a stochastic model was implemented based on the paleoclimate variability obtained from tree-ring records.

  2. Sensitivity of global terrestrial ecosystems to climate variability.

    PubMed

    Seddon, Alistair W R; Macias-Fauria, Marc; Long, Peter R; Benz, David; Willis, Kathy J

    2016-03-10

    The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems–be they natural or with a strong anthropogenic signature–to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

  3. Sensitivity of global terrestrial ecosystems to climate variability

    NASA Astrophysics Data System (ADS)

    Seddon, Alistair W. R.; Macias-Fauria, Marc; Long, Peter R.; Benz, David; Willis, Kathy J.

    2016-03-01

    The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems—be they natural or with a strong anthropogenic signature—to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

  4. Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

    NASA Astrophysics Data System (ADS)

    Williams, C.; Kniveton, D.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  5. Correlation dimensions of climate subsystems and their geographic variability

    NASA Astrophysics Data System (ADS)

    Gan, Thian Yew; Wang, Qiang; Seneka, Michael

    2002-12-01

    The correlation dimension D2 of precipitation (Canada and Africa), air temperature (Canada, New Zealand, and Southern Hemisphere), geo-potential height (Canada), and unregulated streamflow (Canada, USA, and Africa) were estimated using the Hill procedure of Mikosch and Wang [1995] and the bias correction of Wang and Gan [1998]. After bias correction, it seems that D2 is distinct between climate subsystems, such that for precipitation, it is between 8 and 9, for streamflow, it is between 7 and 9, for temperature, it is between 10 and 11, and for geo-potential heights, it is between 12 and 14. The results seem to suggest that climate might be viewed as a loosely coupled set of fairly high-dimensional subsystems and that different climate variables can yield different D2 values. Further, results also suggest that the D2 values of the climate subsystems studied, generally, have low geographic variability, as found between the precipitation data of Western Canada and Uganda, between the streamflow data of basins representing wide range climate and scales from Canada, USA, and Africa, and among the temperature data of Western Canada, New Zealand, and the southern hemisphere, and that the original D2 values analyzed from Canadian geo-potential heights are similar to that of Western Europe, eastern North America, and Germany. There is at most a weak relationship among basin physical characteristics, location, basin scale, and streamflow D2, while climatic influence is more obvious, as shown by drier basins having slightly higher D2 values than basins of wetter climate, basins from temperate climate having higher D2 values than those from cold or hot climates, and comparable D2 values between precipitation and streamflow data.

  6. Climatic variability effects on summer cropping systems of the Iberian Peninsula

    NASA Astrophysics Data System (ADS)

    Capa-Morocho, M.; Rodríguez-Fonseca, B.; Ruiz-Ramos, M.

    2012-04-01

    Climate variability and changes in the frequency of extremes events have a direct impact on crop yield and damages. Climate anomalies projections at monthly and yearly timescale allows us for adapting a cropping system (crops, varieties and management) to take advantage of favorable conditions or reduce the effect of adverse conditions. The objective of this work is to develop indices to evaluate the effect of climatic variability in summer cropping systems of Iberian Peninsula, in an attempt of relating yield variability to climate variability, extending the work of Rodríguez-Puebla (2004). This paper analyses the evolution of the yield anomalies of irrigated maize in several representative agricultural locations in Spain with contrasting temperature and precipitation regimes and compare it to the evolution of different patterns of climate variability, extending the methodology of Porter and Semenov (2005). To simulate maize yields observed daily data of radiation, maximum and minimum temperature and precipitation were used. These data were obtained from the State Meteorological Agency of Spain (AEMET). Time series of simulated maize yields were computed with CERES-maize model for periods ranging from 22 to 49 years, depending on the observed climate data available for each location. The computed standardized anomalies yields were projected on different oceanic and atmospheric anomalous fields and the resulting patterns were compared with a set of documented patterns from the National Oceanic and Atmospheric Administration (NOAA). The results can be useful also for climate change impact assessment, providing a scientific basis for selection of climate change scenarios where combined natural and forced variability represent a hazard for agricultural production. Interpretation of impact projections would also be enhanced.

  7. Country-Specific Effects of Climate Variability on Human Migration.

    PubMed

    Gray, Clark; Wise, Erika

    2016-04-01

    Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe.

  8. Country-Specific Effects of Climate Variability on Human Migration

    PubMed Central

    Gray, Clark; Wise, Erika

    2016-01-01

    Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe. PMID:27092012

  9. Linking the variability of atmospheric carbon monoxide to climate modes in the Southern Hemisphere

    NASA Astrophysics Data System (ADS)

    Buchholz, Rebecca; Monks, Sarah; Hammerling, Dorit; Worden, Helen; Deeter, Merritt; Emmons, Louisa; Edwards, David

    2017-04-01

    Biomass burning is a major driver of atmospheric carbon monoxide (CO) variability in the Southern Hemisphere. The magnitude of emissions, such as CO, from biomass burning is connected to climate through both the availability and dryness of fuel. We investigate the link between CO and climate using satellite measured CO and climate indices. Observations of total column CO from the satellite instrument MOPITT are used to build a record of interannual variability in CO since 2001. Four biomass burning regions in the Southern Hemisphere are explored. Data driven relationships are determined between CO and climate indices for the climate modes: El Niño Southern Oscillation (ENSO); the Indian Ocean Dipole (IOD); the Tropical Southern Atlantic (TSA); and the Southern Annular Mode (SAM). Stepwise forward and backward regression is used to select the best statistical model from combinations of lagged indices. We find evidence for the importance of first-order interaction terms of the climate modes when explaining CO variability. Implications of the model results are discussed for the Maritime Southeast Asia and Australasia regions. We also draw on the chemistry-climate model CAM-chem to explain the source contribution as well as the relative contributions of emissions and meteorology to CO variability.

  10. The Climate Variability & Predictability (CVP) Program at NOAA – Recent Program Advancements in Understanding AMOC

    NASA Astrophysics Data System (ADS)

    Lucas, S. E.

    2016-12-01

    The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA’s Climate Program Office (http://cpo.noaa.gov/CVP). This poster will present the recently funded CVP projects on improving the understanding Atlantic Meridional Overturning Circulation (AMOC), its impact on decadal predictability, and its relationship with the overall climate system.

  11. Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Observed Regional Climate Variability and Evaluating Model Performance: Focus on North African Rainfall in CESM

    NASA Astrophysics Data System (ADS)

    Wang, F.; Notaro, M.; Yu, Y.; Mao, J.; Shi, X.; Wei, Y.

    2016-12-01

    North (N.) African rainfall is characterized by dramatic interannual to decadal variability with serious socio-economic ramifications. The Sahel and West African Monsoon (WAM) region experienced a dramatic shift to persistent drought by the late 1960s, while the Horn of Africa (HOA) underwent drying since the 1990s. Large disagreementregarding the dominant oceanic drivers of N. African hydrologic variability exists among modeling studies, leading to notable spread in Sahel summer rainfall projections for this century among Coupled Model Intercomparison Project models. In order to gain a deeper understanding of the oceanic drivers of N. African rainfall and establish a benchmark for model evaluation, a statistical method, the multivariate Generalized Equilibrium Feedback Assessment, is validated and applied to observations and a control run from the Community Earth System Model (CESM). This study represents the first time that the dominant oceanic drivers of N. African rainfall were evaluated and systematically compared between observations and model simulations. CESM and the observations consistently agree that tropical oceanic modes are the dominant controls of N. African rainfall. During the monsoon season, CESM and observations agree that an anomalously warm eastern tropical Pacific shifts the Walker Circulation eastward, with its descending branch supporting Sahel drying. CESM and the observations concur that a warmer tropical eastern Atlantic favors a southward-shifted Intertropical Convergence Zone, which intensifies WAM monsoonal rainfall. An observed reduction in Sahel rainfall accompanies this enhanced WAM rainfall, yet is confined to the Atlantic in CESM. During the short rains, both observations and CESM indicate that a positive phase of tropical Indian Ocean dipole (IOD) mode [anomalously warm (cold) in western (eastern) Indian] enhances HOA rainfall. The observed IOD impacts are limited to the short rains, while the simulated impacts are year-round.

  12. 2500 Years of European Climate Variability and Human Susceptibility

    NASA Astrophysics Data System (ADS)

    Büntgen, Ulf; Tegel, Willy; Nicolussi, Kurt; McCormick, Michael; Frank, David; Trouet, Valerie; Kaplan, Jed O.; Herzig, Franz; Heussner, Karl-Uwe; Wanner, Heinz; Luterbacher, Jürg; Esper, Jan

    2011-02-01

    Climate variations influenced the agricultural productivity, health risk, and conflict level of preindustrial societies. Discrimination between environmental and anthropogenic impacts on past civilizations, however, remains difficult because of the paucity of high-resolution paleoclimatic evidence. We present tree ring-based reconstructions of central European summer precipitation and temperature variability over the past 2500 years. Recent warming is unprecedented, but modern hydroclimatic variations may have at times been exceeded in magnitude and duration. Wet and warm summers occurred during periods of Roman and medieval prosperity. Increased climate variability from ~250 to 600 C.E. coincided with the demise of the western Roman Empire and the turmoil of the Migration Period. Such historical data may provide a basis for counteracting the recent political and fiscal reluctance to mitigate projected climate change.

  13. Agricultural management options for climate variability and change: conservation tillage

    USDA-ARS?s Scientific Manuscript database

    Adapting to climate variability and change can be achieved through a broad range of management alternatives and technological advances. This publication is focused on the use of conservation tillage in crop production systems. The publication outlines ways that conservation tillage can reduce risk r…

  14. Predicting drought in an agricultural watershed given climate variability

    USDA-ARS?s Scientific Manuscript database

    Changes in the future hydrologic cycle due to changes in temperature (T) and precipitation (P) are likely to be associated with increases in hydrologic extremes. This study evaluates the impacts of climate variability on drought using the Soil and Water Assessment Tool (SWAT) in Goodwater Creek Expe…

  15. Forests: the potential consequences of climate variability and change

    Treesearch

    USDA Forest Service

    2001-01-01

    This pamphlet reports the recent scientific assessment that analyzed how future climate variablity and change may affect forests in the United States. The assessment, sponsored by the USDA Forest Service, and supported, in part, by the U.S Department of Energy, and the National Atmospheric and Space Administration, describes the suite of potential impacts on forests….

  16. Vulnerability to climate variability and change in East Timor.

    PubMed

    Barnett, Jon; Dessai, Suraje; Jones, Roger N

    2007-07-01

    This paper presents the results of a preliminary study of climate vulnerability in East Timor. It shows the results of projections of climate change in East Timor. The country’s climate may become hotter, drier, and increasingly variable. Sea levels are likely to rise. The paper then considers the implications of these changes on three natural resources–water, soils, and the coastal zone–and finds all to be sensitive to changes in climate and sea level. Changes in the abundance and distribution of these resources is likely to cause a reduction in agricultural production and food security, and sea-level rise is likely to damage coastal areas, including Dili, the capital city.

  17. Rainfall pattern variability as climate change impact in The Wallacea Region

    NASA Astrophysics Data System (ADS)

    Pujiastuti, I.; Nurjani, E.

    2018-04-01

    The objective of the study is to observe the characteristic variability of rainfall pattern in the city located in every rainfall type, local (Kendari), monsoon (Manado), and equatorial (Palu). The result will be compared to determine which has the most significantly precipitation changing due to climate change impact. Rainfall variability in Indonesia illustrates precipitation variation thus the important variability is the variability of monthly rainfall. Monthly precipitation data for the period of 1961-2010 are collected from Indonesian Agency for Meteorological, Climatological, and Geophysical Agency. This data is calculated with the normal test statistical method to analyze rainfall variability. The result showed the pattern of trend and variability of rainfall in every city with the own characteristic which determines the rainfall type. Moreover, there is comparison of rainfall pattern changing between every rainfall type. This information is useful for climate change mitigation and adaptation strategies especially in water resource management form precipitation as well as the occurrence of meteorological disasters.

  18. Carbon cycle observations: gaps threaten climate mitigation policies

    Treesearch

    Richard Birdsey; Nick Bates; MIke Behrenfeld; Kenneth Davis; Scott C. Doney; Richard Feely; Dennis Hansell; Linda Heath; et al.

    2009-01-01

    Successful management of carbon dioxide (CO2) requires robust and sustained carbon cycle observations. Yet key elements of a national observation network are lacking or at risk. A U.S. National Research Council review of the U.S. Climate Change Science Program earlier this year highlighted the critical need for a U.S. climate observing system to…

  19. Subtropical Gyre Variability Observed by Ocean Color Satellites

    NASA Technical Reports Server (NTRS)

    McClain, Charles R.; Signorini, Sergio R.; Christian, James R.

    2002-01-01

    The subtropical gyres of the world are extensive, coherent regions that occupy about 40% of the surface of the earth. Once thought to be homogeneous and static habitats, there is increasing evidence that mid-latitude gyres exhibit substantial physical and biological variability on a variety of time scales. While biological productivity within these oligotrophic regions may be relatively small, their immense size makes their total contribution significant. Global distributions of dynamic height derived from satellite altimeter data, and chlorophyll concentration derived from satellite ocean color data, show that the dynamic center of the gyres, the region of maximum dynamic height where the thermocline is deepest, does not coincide with the region of minimum chlorophyll concentration. The physical and biological processes by which this distribution of ocean properties is maintained, and the spatial and temporal scales of variability associated with these processes, are analyzed using global surface chlorophyll-a concentrations, sea surface height, sea surface temperature and surface winds from operational satellite and meteorological sources, and hydrographic data from climatologies and individual surveys. Seasonal and interannual variability in the areal extent of the subtropical gyres are examined using 8 months (November 1996 – June 1997) of OCTS and nearly 5 years (September 1997 – June 02) of SeaWiFS ocean color data and are interpreted in the context of climate variability and measured changes in other ocean properties (i.e., wind forcing, surface currents, Ekman pumping, and vertical mixing). The North Pacific and North Atlantic gyres are observed to be shrinking over this period, while the South Pacific, South Atlantic, and South Indian Ocean gyres appear to be expanding.

  20. Discovery and observation of BY Draconis variables

    NASA Astrophysics Data System (ADS)

    Bopp, B. W.; Noah, P. V.; Klimke, A.; Africano, J.

    1981-10-01

    The discovery of BY Draconis variables was efficiently accomplished by a spectroscopic survey of dK-M stars for weak H-alpha emissions, using 1-2 A resolution. The four BY Dra variables discovered are all spectroscopic binaries with P values lower than about 10 d, in light of which, it is noted that the onset of high surface activity and appearance of H-alpha emission occur sharply at v(equator) of approximately 5 km/sec. At v(equator) of about 3 km/sec, dK-M stars have low levels of surface activity. It is found that while there is a range of Ca II emission strength, and only the strongest emitters of this line are BY Dra and/or flare stars, the H-alpha feature changes abruptly to an emission feature signaling the onset of flaring and/or the BY Dra syndrome. An increase of the rotation rate above v(equator) 5 km/sec does not appear to increase the level of surface activity.

  1. Actual vs. Perceived Climate Variability among Smallholding Rice Farmers

    NASA Astrophysics Data System (ADS)

    Carrico, A.; Gilligan, J. M.; Truelove, H. B.

    2016-12-01

    It is recognized that those engaged in resource-dependent livelihoods often hold extensive knowledge of their surrounding environment that, in some cases, facilitates sustainable practices and adaptation to environmental shocks. However, there remain significant gaps in our understanding of how actors at this scale perceive, understand, and respond to climate variability, particularly in the absence of good information. There are further unanswered questions about how these perceptions translate into livelihood decisions. In this paper, we use data collected in 2015 from 607 paddy farmers living in 12 villages throughout the heavily agricultural dry zone of Sri Lanka. Farmers were asked to report their perceptions of decadal scale changes in temperature and rainfall along a number of dimensions (e.g., annual rainfall, onset of monsoon rains, frequency of droughts, temperature). These data are compared to local meteorological data collected over the same time period to examine the perceptions of meteorological trends. Furthermore, we examine heterogeneity in perceptions as a function of demographic factors, reliance on irrigation, use of agricultural technology, and other socioeconomic characteristics of the farmer. The impact of perceptions on agricultural practices such as crop selection and water management, and resultant yields, will also be examined. Preliminary results based on five communities suggest a strong negativity bias in perceptions, with widespread agreement that meteorological conditions have become less hospitable for farming. Perceptions of temperature changes largely corresponded to meteorological records; however, perceptions of rainfall changes did not. There was some evidence that length of time spent in a village and the presence of elders in the household was associated with perceptions that more closely corresponded to the observed meteorological data. Updated analyses based on the complete data set will be presented. We will discuss the

  2. Effects of climate variability on global scale flood risk

    NASA Astrophysics Data System (ADS)

    Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.

    2013-12-01

    In this contribution we demonstrate the influence of climate variability on flood risk. Globally, flooding is one of the worst natural hazards in terms of economic damages; Munich Re estimates global losses in the last decade to be in excess of $240 billion. As a result, scientifically sound estimates of flood risk at the largest scales are increasingly needed by industry (including multinational companies and the insurance industry) and policy communities. Several assessments of global scale flood risk under current and conditions have recently become available, and this year has seen the first studies assessing how flood risk may change in the future due to global change. However, the influence of climate variability on flood risk has as yet hardly been studied, despite the fact that: (a) in other fields (drought, hurricane damage, food production) this variability is as important for policy and practice as long term change; and (b) climate variability has a strong influence in peak riverflows around the world. To address this issue, this contribution illustrates the influence of ENSO-driven climate variability on flood risk, at both the globally aggregated scale and the scale of countries and large river basins. Although it exerts significant and widespread influences on flood peak discharges in many parts of the world, we show that ENSO does not have a statistically significant influence on flood risk once aggregated to global totals. At the scale of individual countries, though, strong relationships exist over large parts of the Earth’s surface. For example, we find particularly strong anomalies of flood risk in El Niño or La Niña years (compared to all years) in southern Africa, parts of western Africa, Australia, parts of Central Eurasia (especially for El Niño), the western USA (especially for La Niña), and parts of South America. These findings have large implications for both decadal climate-risk projections and long-term future climate change

  3. Pollen-based reconstruction of Holocene climate variability in the Eifel region evaluated with stable isotopes

    NASA Astrophysics Data System (ADS)

    Kühl, Norbert; Moschen, Robert; Wagner, Stefanie

    2010-05-01

    Pollen as well as stable isotopes have great potential as climate proxy data. While variability in these proxy data is frequently assumed to reflect climate variability, other factors than climate, including human impact and statistical noise, can often not be excluded as primary cause for the observed variability. Multiproxy studies offer the opportunity to test different drivers by providing different lines of evidence for environmental change such as climate variability and human impact. In this multiproxy study we use pollen and peat humification to evaluate to which extent stable oxygen and carbon isotope series from the peat bog “Dürres Maar” reflect human impact rather than climate variability. For times before strong anthropogenic vegetation change, isotope series from Dürres Maar were used to validate quantitative reconstructions based on pollen. Our study site is the kettle hole peat bog “Dürres Maar” in the Eifel low mountain range, Germany (450m asl), which grew 12m during the last 10,000 years. Pollen was analysed with a sum of at least 1000 terrestrial pollen grains throughout the profile to minimize statistical effects on the reconstructions. A recently developed probabilistic indicator taxa method (“pdf-method”) was used for the quantitative climate estimates (January and July temperature) based on pollen. For isotope analysis, attention was given to use monospecific Sphagnum leaves whenever possible, reducing the potential of a species effect and any potential artefact that can originate from selective degradation of different morphological parts of Sphagnum plants (Moschen et al., 2009). Pollen at “Dürres Maar” reflect the variable and partly strong human impact on vegetation during the last 4000 years. Stable isotope time series were apparently not influenced by human impact at this site. This highlights the potential of stable isotope investigations from peat for climatic interpretation, because stable isotope series from lacustrine

  4. The response of the southwest Western Australian wave climate to Indian Ocean climate variability

    NASA Astrophysics Data System (ADS)

    Wandres, Moritz; Pattiaratchi, Charitha; Hetzel, Yasha; Wijeratne, E. M. S.

    2018-03-01

    Knowledge of regional wave climates is critical for coastal planning, management, and protection. In order to develop a regional wave climate, it is important to understand the atmospheric systems responsible for wave generation. This study examines the variability of the southwest Western Australian (SWWA) shelf and nearshore wind wave climate and its relationship to southern hemisphere climate variability represented by various atmospheric indices: the southern oscillation index (SOI), the Southern Annular Mode (SAM), the Indian Ocean Dipole Mode Index (DMI), the Indian Ocean Subtropical Dipole (IOSD), the latitudinal position of the subtropical high-pressure ridge (STRP), and the corresponding intensity of the subtropical ridge (STRI). A 21-year wave hindcast (1994-2014) of the SWWA continental shelf was created using the third generation wave model Simulating WAves Nearshore (SWAN), to analyse the seasonal and inter-annual wave climate variability and its relationship to the atmospheric regime. Strong relationships between wave heights and the STRP and the STRI, a moderate correlation between the wave climate and the SAM, and no significant correlation between SOI, DMI, and IOSD and the wave climate were found. Strong spatial, seasonal, and inter-annual variability, as well as seasonal longer-term trends in the mean wave climate were studied and linked to the latitudinal changes in the subtropical high-pressure ridge and the Southern Ocean storm belt. As the Southern Ocean storm belt and the subtropical high-pressure ridge shifted southward (northward) wave heights on the SWWA shelf region decreased (increased). The wave height anomalies appear to be driven by the same atmospheric conditions that influence rainfall variability in SWWA.

  5. Role of the North Atlantic Ocean in Low Frequency Climate Variability

    NASA Astrophysics Data System (ADS)

    Danabasoglu, G.; Yeager, S. G.; Kim, W. M.; Castruccio, F. S.

    2017-12-01

    The Atlantic Ocean is a unique basin with its extensive, North – South overturning circulation, referred to as the Atlantic meridional overturning circulation (AMOC). AMOC is thought to represent the dynamical memory of the climate system, playing an important role in decadal and longer time scale climate variability as well as prediction of the earth’s future climate on these time scales via its large heat and salt transports. This oceanic memory is communicated to the atmosphere primarily through the influence of persistent sea surface temperature (SST) variations. Indeed, many modeling studies suggest that ocean circulation, i.e., AMOC, is largely responsible for the creation of coherent SST variability in the North Atlantic, referred to as Atlantic Multidecadal Variability (AMV). AMV has been linked to many (multi)decadal climate variations in, e.g., Sahel and Brazilian rainfall, Atlantic hurricane activity, and Arctic sea-ice extent. In the absence of long, continuous observations, much of the evidence for the ocean’s role in (multi)decadal variability comes from model simulations. Although models tend to agree on the role of the North Atlantic Oscillation in creating the density anomalies that proceed the changes in ocean circulation, model fidelity in representing variability characteristics, mechanisms, and air-sea interactions remains a serious concern. In particular, there is increasing evidence that models significantly underestimate low frequency variability in the North Atlantic compared to available observations. Such model deficiencies can amplify the relative influence of external or stochastic atmospheric forcing in generating (multi)decadal variability, i.e., AMV, at the expense of ocean dynamics. Here, a succinct overview of the current understanding of the (North) Atlantic Ocean’s role on the regional and global climate, including some outstanding questions, will be presented. In addition, a few examples of the climate impacts of the AMV via

  6. Uncertainty information in climate data records from Earth observation

    NASA Astrophysics Data System (ADS)

    Merchant, C. J.

    2017-12-01

    How to derive and present uncertainty in climate data records (CDRs) has been debated within the European Space Agency Climate Change Initiative, in search of common principles applicable across a range of essential climate variables. Various points of consensus have been reached, including the importance of improving provision of uncertainty information and the benefit of adopting international norms of metrology for language around the distinct concepts of uncertainty and error. Providing an estimate of standard uncertainty per datum (or the means to readily calculate it) emerged as baseline good practice, and should be highly relevant to users of CDRs when the uncertainty in data is variable (the usual case). Given this baseline, the role of quality flags is clarified as being complementary to and not repetitive of uncertainty information. Data with high uncertainty are not poor quality if a valid estimate of the uncertainty is available. For CDRs and their applications, the error correlation properties across spatio-temporal scales present important challenges that are not fully solved. Error effects that are negligible in the uncertainty of a single pixel may dominate uncertainty in the large-scale and long-term. A further principle is that uncertainty estimates should themselves be validated. The concepts of estimating and propagating uncertainty are generally acknowledged in geophysical sciences, but less widely practised in Earth observation and development of CDRs. Uncertainty in a CDR depends in part (and usually significantly) on the error covariance of the radiances and auxiliary data used in the retrieval. Typically, error covariance information is not available in the fundamental CDR (FCDR) (i.e., with the level-1 radiances), since provision of adequate level-1 uncertainty information is not yet standard practice. Those deriving CDRs thus cannot propagate the radiance uncertainty to their geophysical products. The FIDUCEO project (www.fiduceo.eu) is

  7. Climate Drivers of Spatiotemporal Variability of Precipitation in the Source Region of Yangtze River

    NASA Astrophysics Data System (ADS)

    Du, Y.; Berndtsson, R.; An, D.; Yuan, F.

    2017-12-01

    Variability of precipitation regime has significant influence on the environment sustainability in the source region of Yangtze River, especially when the vegetation degradation and biodiversity reduction have already occurred. Understanding the linkage between variability of local precipitation and global teleconnection patterns is essential for water resources management. Based on physical reasoning, indices of the climate drivers can provide a practical way of predicting precipitation. Due to high seasonal variability of precipitation, climate drivers of the seasonal precipitation also varies. However, few reports have gone through the teleconnections between large scale patterns with seasonal precipitation in the source region of Yangtze River. The objectives of this study are therefore (1) assessment of temporal trend and spatial variability of precipitation in the source region of Yangtze River; (2) identification of climate indices with strong influence on seasonal precipitation anomalies; (3) prediction of seasonal precipitation based on revealed climate indices. Principal component analysis and Spearman rank correlation were used to detect significant relationships. A feed-forward artificial neural network(ANN) was developed to predict seasonal precipitation using significant correlated climate indices. Different influencing climate indices were revealed for precipitation in each season, with significant level and lag times. Significant influencing factors were selected to be the predictors for ANN model. With correlation coefficients between observed and simulated precipitation over 0.5, the results were eligible to predict the precipitation of spring, summer and winter using teleconnections, which can improve integrated water resources management in the source region of Yangtze River.

  8. Climate variability during the Holocene inferred from northeastern Iberian speleothems

    NASA Astrophysics Data System (ADS)

    Moreno, A.; Bartolomé, M.; Sancho, C.; Belmonte, Á.; Stoll, H.; Cacho, I.; Edwards, R. L.; Hellstrom, J.

    2012-04-01

    Although the general climate trends during the Holocene in the Iberian Peninsula have been well described after the study of marine and lacustrine records, many questions regarding the timing of some of the events together with the characterization of the higher-frequency climate variability are still poorly understood. New speleothem records from several caves in northeastern Iberia provide data to explore Holocene climate changes. The selected caves are located in a latitudinal transect from the Pyrenees to the Iberian Range and placed at different altitude. Two of them, 5 de Agosto and Pot au Feu, belong to the same karstic complex in Cotiella massif (Central Pyrenees, 1600 m asl). Seso Cave, also in the Central Pyrenees but at 781 m of altitude, and Molinos cave, a cavity very rich in speleothems located at 1040 m in the Iberian Range, complete the transect. Although in all the caves precipitation coming from Atlantic fronts dominates over the year, a significant Mediterranean influence, specially in summer months, is identified after rainfall monitoring. Speleothem formation during the Holocene occurred at a very low pace in 5 de Agosto cave (80yrs/mm) and increased dramatically at low-altitude caves and during particular periods proved to be wetter (eg. Early Holocene in Molinos cave, less than 10yr/mm). In Seso and Pot au Feu caves, up to seven studied speleothems only grew during short climatic events such as the Iron Cold Period (3000-2500 cal yr BP) or the Little Ice Age (1300-1850 yr AD) that, although cold, were particularly humid periods in northeastern Spain. First stable isotope results highlight the importance of comparing speleothems with similar growing rates and from the same cave to extract climate information and discard other influences. From the integration of four stalagmites from Molinos cave covering since the Holocene onset to 2000 cal yrs BP, the Early Holocene (11.7-8.5 ka BP) with d13C values between -11 and – 9‰ appears as the

  9. Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.

    PubMed

    Kukal, Meetpal S; Irmak, Suat

    2018-02-22

    Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.

  10. Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions

    USGS Publications Warehouse

    Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T.

    2009-01-01

    Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

  11. Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions

    USGS Publications Warehouse

    Jackson, S.T.; Betancourt, J.L.; Booth, R.K.; Gray, S.T.

    2009-01-01

    Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and morefundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

  12. Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions

    PubMed Central

    Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T.

    2009-01-01

    Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics. PMID:19805104

  13. Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay

    PubMed Central

    Harding, Jr., Lawrence W.; Mallonee, Michael E.; Perry, Elgin S.; Miller, W. David; Adolf, Jason E.; Gallegos, Charles L.; Paerl, Hans W.

    2016-01-01

    Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km2 watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945–1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981–2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries. PMID:27026279

  14. Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay

    NASA Astrophysics Data System (ADS)

    Harding, Lawrence W., Jr.; Mallonee, Michael E.; Perry, Elgin S.; Miller, W. David; Adolf, Jason E.; Gallegos, Charles L.; Paerl, Hans W.

    2016-03-01

    Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km2 watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945-1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981-2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries.

  15. Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay.

    PubMed

    Harding, Lawrence W; Mallonee, Michael E; Perry, Elgin S; Miller, W David; Adolf, Jason E; Gallegos, Charles L; Paerl, Hans W

    2016-03-30

    Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km(2) watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945-1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981-2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries.

  16. The role of internal climate variability for interpreting climate change scenarios

    NASA Astrophysics Data System (ADS)

    Maraun, Douglas

    2013-04-01

    When communicating information on climate change, the use of multi-model ensembles has been advocated to sample uncertainties over a range as wide as possible. To meet the demand for easily accessible results, the ensemble is often summarised by its multi-model mean signal. In rare cases, additional uncertainty measures are given to avoid loosing all information on the ensemble spread, e.g., the highest and lowest projected values. Such approaches, however, disregard the fundamentally different nature of the different types of uncertainties and might cause wrong interpretations and subsequently wrong decisions for adaptation. Whereas scenario and climate model uncertainties are of epistemic nature, i.e., caused by an in principle reducible lack of knowledge, uncertainties due to internal climate variability are aleatory, i.e., inherently stochastic and irreducible. As wisely stated in the proverb “climate is what you expect, weather is what you get”, a specific region will experience one stochastic realisation of the climate system, but never exactly the expected climate change signal as given by a multi model mean. Depending on the meteorological variable, region and lead time, the signal might be strong or weak compared to the stochastic component. In cases of a low signal-to-noise ratio, even if the climate change signal is a well defined trend, no trends or even opposite trends might be experienced. Here I propose to use the time of emergence (TOE) to quantify and communicate when climate change trends will exceed the internal variability. The TOE provides a useful measure for end users to assess the time horizon for implementing adaptation measures. Furthermore, internal variability is scale dependent – the more local the scale, the stronger the influence of internal climate variability. Thus investigating the TOE as a function of spatial scale could help to assess the required spatial scale for implementing adaptation measures. I exemplify this proposal with

  17. Climate Variability and Human Migration in the Netherlands, 1865–1937

    PubMed Central

    Jennings, Julia A.; Gray, Clark L.

    2014-01-01

    Human migration is frequently cited as a potential social outcome of climate change and variability, and these effects are often assumed to be stronger in the past when economies were less developed and markets more localized. Yet, few studies have used historical data to test the relationship between climate and migration directly. In addition, the results of recent studies that link demographic and climate data are not consistent with conventional narratives of displacement responses. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate data that cover the same period, we examine the effects of climate variability on migration using event history models. Only internal moves in the later period and for certain social groups are associated with negative climate conditions, and the strength and direction of the observed effects change over time. International moves decrease with extreme rainfall, suggesting that the complex relationships between climate and migration that have been observed for contemporary populations extend into the nineteenth century. PMID:25937689

  18. NASA Scientific Forum on Climate Variability and Global Change: UNISPACE 3

    NASA Technical Reports Server (NTRS)

    Schiffer, Robert A.; Unninayar, Sushel

    1999-01-01

    The Forum on Climate Variability and Global Change is intended to provide a glimpse into some of the advances made in our understanding of key scientific and environmental issues resulting primarily from improved observations and modeling on a global basis. This publication contains the papers presented at the forum.

  19. Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

    NASA Astrophysics Data System (ADS)

    Jones, Philip D.; Harpham, Colin; Troccoli, Alberto; Gschwind, Benoit; Ranchin, Thierry; Wald, Lucien; Goodess, Clare M.; Dorling, Stephen

    2017-07-01

    The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979-2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from climate.copernicus.eu” target=”_blank”>ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.

  20. The Climate Variability & Predictability (CVP) Program at NOAA – Recent Program Advancements

    NASA Astrophysics Data System (ADS)

    Lucas, S. E.; Todd, J. F.

    2015-12-01

    The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA’s Climate Program Office (http://cpo.noaa.gov/CVP). The CVP Program currently supports multiple projects in areas that are aimed at improved representation of physical processes in global models. Some of the topics that are currently funded include: i) Improved Understanding of Intraseasonal Tropical Variability – DYNAMO field campaign and post -field projects, and the new climate model improvement teams focused on MJO processes; ii) Climate Process Teams (CPTs, co-funded with NSF) with projects focused on Cloud macrophysical parameterization and its application to aerosol indirect effects, and Internal-Wave Driven Mixing in Global Ocean Models; iii) Improved Understanding of Tropical Pacific Processes, Biases, and Climatology; iv) Understanding Arctic Sea Ice Mechanism and Predictability;v) AMOC Mechanisms and Decadal Predictability Recent results from CVP-funded projects will be summarized. Additional information can be found at http://cpo.noaa.gov/CVP.

  1. Sensitivity of ground – water recharge estimates to climate variability and change, Columbia Plateau, Washington

    USGS Publications Warehouse

    Vaccaro, John J.

    1992-01-01

    The sensitivity of groundwater recharge estimates was investigated for the semiarid Ellensburg basin, located on the Columbia Plateau, Washington, to historic and projected climatic regimes. Recharge was estimated for predevelopment and current (1980s) land use conditions using a daily energy-soil-water balance model. A synthetic daily weather generator was used to simulate lengthy sequences with parameters estimated from subsets of the historical record that were unusually wet and unusually dry. Comparison of recharge estimates corresponding to relatively wet and dry periods showed that recharge for predevelopment land use varies considerably within the range of climatic conditions observed in the 87-year historical observation period. Recharge variations for present land use conditions were less sensitive to the same range of historical climatic conditions because of irrigation. The estimated recharge based on the 87-year historical climatology was compared with adjustments to the historical precipitation and temperature records for the same record to reflect CO2-doubling climates as projected by general circulation models (GCMs). Two GCM scenarios were considered: an average of conditions for three different GCMs with CO2 doubling, and a most severe “maximum” case. For the average GCM scenario, predevelopment recharge increased, and current recharge decreased. Also considered was the sensitivity of recharge to the variability of climate within the historical and adjusted historical records. Predevelopment and current recharge were less and more sensitive, respectively, to the climate variability for the average GCM scenario as compared to the variability within the historical record. For the maximum GCM scenario, recharge for both predevelopment and current land use decreased, and the sensitivity to the CO2-related climate change was larger than sensitivity to the variability in the historical and adjusted historical climate records.

  2. Atmospheric Variability of CO2 impact on space observation Requirements

    NASA Astrophysics Data System (ADS)

    Swanson, A. L.; Sen, B.; Newhart, L.; Segal, G.

    2009-12-01

    If International governments are to reduce GHG levels by 80% by 2050, as recommended by most scientific bodies concerned with avoiding the most hazardous changes in climate, then massive investments in infrastructure and new technology will be required over the coming decades. Such an investment will be a huge commitment by governments and corporations, and while it will offer long-term dividends in lower energy costs, a healthier environment and averted additional global warming, the shear magnitude of upfront costs will drive a call for a monitoring and verification system. Such a system will be required to offer accountability to signatories of governing bodies, as well as, for the global public. Measuring the average global distribution of CO2 is straight forward, as exemplified by the long running station measurements managed by NOAA’s Global Monitoring Division that includes the longterm Keeling record. However, quantifying anthropogenic and natural source/sink distributions and atmospheric mixing have been much more difficult to constrain. And, yet, an accurate accounting of all anthropogenic source strengths is required for Global Treaty verification. The only way to accurately assess Global GHG emissions is to construct an integrated system of ground, air and space based observations with extensive chemical modeling capabilities. We look at the measurement requirements for the space based component of the solutions. To determine what space sensor performance requirements for ground resolution, coverage, and revisit, we have analyzed regional CO2 distributions and variability using NASA and NOAA aircraft flight campaigns. The results of our analysis are presented as variograms showing average spatial variability over several Northern Hemispheric regions. There are distinct regional differences with the starkest contrast between urban versus rural and Coastal Asia versus Coastal US. The results suggest specific consequences on what spatial and temporal

  3. Variability, trends, and teleconnections of observed precipitation over Pakistan

    NASA Astrophysics Data System (ADS)

    Iqbal, Muhammad Farooq; Athar, H.

    2017-10-01

    The precipitation variability, trends, and teleconnections are studied over six administrative regions of Pakistan (Gilgit-Baltistan or GB, Azad Jammu and Kashmir or AJK, Khyber Pakhtoonkhawa or KPK, Punjab, Sindh, and Balochistan) on multiple timescales for the period of recent 38 years (1976-2013) using precipitation data of 42 stations and circulation indices datasets (Indian Ocean Dipole [IOD], North Atlantic Oscillation [NAO], Arctic Oscillation [AO], El Niño Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], Atlantic Multidecadal Oscillation [AMO], and Quasi-Biennial Oscillation [QBO]). The summer monsoon season received the highest precipitation, amounting to 45%, whereas the winter and pre-monsoon (post-monsoon) seasons contributed 30 and 20% (5%), respectively, of the annual total precipitation. Positive percentile changes were observed in GB, KPK, Punjab, and Balochistan regions during pre-monsoon season and in Balochistan region during post-monsoon season in second half as compared to first half of 38-year period. The Mann-Kendall test revealed increasing trends for the period of 1995-2013 as compared to period of 1976-1994 for entire Pakistan during monsoon season and on annual timescale. A significant influence of ENSO was observed in all the four seasons in Balochistan, KPK, Punjab, and AJK regions during monsoon and post-monsoon seasons. This study not only offers an understanding of precipitation variability linkages with large-scale circulations and trends, but also it contributes as a resource document for policy makers to take measures for adaptation and mitigation of climate change and its impacts with special focus on precipitation over different administrative regions of Pakistan.

  4. Relationship of suicide rates with climate and economic variables in Europe during 2000-2012.

    PubMed

    Fountoulakis, Konstantinos N; Chatzikosta, Isaia; Pastiadis, Konstantinos; Zanis, Prodromos; Kawohl, Wolfram; Kerkhof, Ad J F M; Navickas, Alvydas; Höschl, Cyril; Lecic-Tosevski, Dusica; Sorel, Eliot; Rancans, Elmars; Palova, Eva; Juckel, Georg; Isacsson, Goran; Jagodic, Helena Korosec; Botezat-Antonescu, Ileana; Rybakowski, Janusz; Azorin, Jean Michel; Cookson, John; Waddington, John; Pregelj, Peter; Demyttenaere, Koen; Hranov, Luchezar G; Stevovic, Lidija Injac; Pezawas, Lucas; Adida, Marc; Figuera, Maria Luisa; Jakovljević, Miro; Vichi, Monica; Perugi, Giulio; Andreassen, Ole A; Vukovic, Olivera; Mavrogiorgou, Paraskevi; Varnik, Peeter; Dome, Peter; Winkler, Petr; Salokangas, Raimo K R; From, Tiina; Danileviciute, Vita; Gonda, Xenia; Rihmer, Zoltan; Forsman, Jonas; Grady, Anne; Hyphantis, Thomas; Dieset, Ingrid; Soendergaard, Susan; Pompili, Maurizio; Bech, Per

    2016-01-01

    It is well known that suicidal rates vary considerably among European countries and the reasons for this are unknown, although several theories have been proposed. The effect of economic variables has been extensively studied but not that of climate. Data from 29 European countries covering the years 2000-2012 and concerning male and female standardized suicidal rates (according to WHO), economic variables (according World Bank) and climate variables were gathered. The statistical analysis included cluster and principal component analysis and categorical regression. The derived models explained 62.4 % of the variability of male suicidal rates. Economic variables alone explained 26.9 % and climate variables 37.6 %. For females, the respective figures were 41.7, 11.5 and 28.1 %. Male suicides correlated with high unemployment rate in the frame of high growth rate and high inflation and low GDP per capita, while female suicides correlated negatively with inflation. Both male and female suicides correlated with low temperature. The current study reports that the climatic effect (cold climate) is stronger than the economic one, but both are present. It seems that in Europe suicidality follows the climate/temperature cline which interestingly is not from south to north but from south to north-east. This raises concerns that climate change could lead to an increase in suicide rates. The current study is essentially the first successful attempt to explain the differences across countries in Europe; however, it is an observational analysis based on aggregate data and thus there is a lack of control for confounders.

  5. Antarctic cloud and surface properties: Satellite observations and climate implications

    NASA Astrophysics Data System (ADS)

    Berque, Joannes

    2004-12-01

    The radiative effect of clouds in the Antarctic, although small at the top of the atmosphere, is very large within the surface-atmosphere system, and influences a variety of climate processes on a global scale. Because field observations are difficult in the Antarctic interior, satellite observations may be especially valuable in this region; but the remote sensing of clouds and surface properties over the high ice sheets is problematic due to the lack of radiometric contrast between clouds and the snow. A radiative transfer model of the Antarctic snow-atmosphere system is developed, and a new method is proposed for the examination of the problem of cloud properties retrieval from multi-spectral measurements. Key limitations are identified, and a method is developed to overcome them. Using data from the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Agency (NOAA) polar orbiters, snow grain size is retrieved over the course of a summer. Significant variability is observed, and it appears related to major precipitation events. A radiative transfer model and a single-column model are used to evaluate the impact of this variability on the Antarctic plateau. The range of observed grain size induces changes of up to 30 Wm-2 on the absorption of shortwave radiation in both models. Cloud properties are then retrieved in summertime imagery of the South Pole. Comparison of model to observations over a wide range of cloud optical depths suggests that this method allows the meaningful interpretation of AVHRR radiances in terms of cloud properties over the Antarctic plateau. The radiative effect of clouds at the top of the atmosphere is evaluated over the South Pole with ground-based lidar observations and data from Clouds and the Earth Radiant Energy System (CERES) onboard NASA’s Terra satellite. In accord with previous work, results indicate that the shortwave and net effect are one of cooling throughout the year, while the longwave

  6. Monthly means of selected climate variables for 1985 – 1989

    NASA Technical Reports Server (NTRS)

    Schubert, S.; Wu, C.-Y.; Zero, J.; Schemm, J.-K.; Park, C.-K.; Suarez, M.

    1992-01-01

    Meteorologists are accustomed to viewing instantaneous weather maps, since these contain the most relevant information for the task of producing short-range weather forecasts. Climatologists, on the other hand, tend to deal with long-term means, which portray the average climate. The recent emphasis on dynamical extended-range forecasting and, in particular measuring and predicting short term climate change makes it important that we become accustomed to looking at variations on monthly and longer time scales. A convenient toll for researchers to familiarize themselves with the variability which occurs in selected parameters on these time scales is provided. The format of the document was chosen to help facilitate the intercomparison of various parameters and highlight the year-to-year variability in monthly means.

  7. Climate-mediated spatiotemporal variability in the terrestrial productivity across Europe

    NASA Astrophysics Data System (ADS)

    Wu, X.; Mahecha, M. D.; Reichstein, M.; Ciais, P.; Wattenbach, M.; Babst, F.; Frank, D.; Zang, C.

    2013-11-01

    Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a~temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems.

  8. Tropical cloud feedbacks and natural variability of climate

    NASA Technical Reports Server (NTRS)

    Miller, R. L.; Del Genio, A. D.

    1994-01-01

    Simulations of natural variability by two general circulation models (GCMs) are examined. One GCM is a sector model, allowing relatively rapid integration without simplification of the model physics, which would potentially exclude mechanisms of variability. Two mechanisms are found in which tropical surface temperature and sea surface temperature (SST) vary on interannual and longer timescales. Both are related to changes in cloud cover that modulate SST through the surface radiative flux. Over the equatorial ocean, SST and surface temperature vary on an interannual timescale, which is determined by the magnitude of the associated cloud cover anomalies. Over the subtropical ocean, variations in low cloud cover drive SST variations. In the sector model, the variability has no preferred timescale, but instead is characterized by a ‘red’ spectrum with increasing power at longer periods. In the terrestrial GCM, SST variability associated with low cloud anomalies has a decadal timescale and is the dominant form of global temperature variability. Both GCMs are coupled to a mixed layer ocean model, where dynamical heat transports are prescribed, thus filtering out El Nino-Southern Oscillation (ENSO) and thermohaline circulation variability. The occurrence of variability in the absence of dynamical ocean feedbacks suggests that climatic variability on long timescales can arise from atmospheric processes alone.

  9. Recent changes in county-level corn yield variability in the United States from observations and crop models

    SciTech Connect

    Leng, Guoyong

    The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially

  10. The Women’s Role in the Adaptation to Climate Variability and Climate Change: Its Contribution to the Risk Management

    NASA Astrophysics Data System (ADS)

    Quintero Angel, M.; Carvajal Escobar, Y.; Garcia Vargas, M.

    2007-05-01

    Recently, there is evidence of an increase in the amount of severity in extreme events associated with the climate variability or climate change; which demonstrates that climate in this planet is changing. There is an observation of increasing damages, and of social economical cost associated with these phenomena’s, mostly do to more people are living in hazard vulnerable conditions. The victims of natural disasters have increase from 147 to 211 million between 1991 and 2000. In same way more than 665.000 people have died in 2557 natural disasters, which 90% are associated with water and climate. (UNESCO & WWAP, 2003). The actual tendency and the introduction of new factors of risk, suggest lost increase in the future, obligating actions to manage and reduce risk of disaster. Bind work, health, poverty, education, water, climate, and disasters is not an error, is an obligation. Vulnerability of society to natural hazards and to poverty are bond, to reduce the risk of disasters is frequently united with the reduction of poverty and in the other way too (Sen, 2000). In this context, extreme events impact societies in all the world, affecting differently men and women, do to the different roles they play in the society, the different access in the control of resources, the few participation that women have in taking decisions with preparedness, mitigation, rehabilitation of disasters, impacting more women in developing countries. Although, women understand better the causes and local consequences in changes of climate conditions. They have a pile of knowledge and abilities for guiding adaptation, playing a very important role in vulnerable communities. This work shows how these topics connect with the millennium development goals; particularly how it affects its accomplishment. It also describes the impact of climate variability and climate change in developing countries. Analyzing adaptation responses that are emerging; especially from women initiation.

  11. Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability.

    PubMed

    Booth, Ben B B; Dunstone, Nick J; Halloran, Paul R; Andrews, Timothy; Bellouin, Nicolas

    2012-04-04

    Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean. These links are extensive, influencing a range of climate processes such as hurricane activity and African Sahel and Amazonian droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations. A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures, but climate models have so far failed to reproduce these interactions and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860-2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910-1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol-cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol-cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions.

  12. Smallholder agriculture in India and adaptation to current and future climate variability and climate change

    NASA Astrophysics Data System (ADS)

    Murari, K. K.; Jayaraman, T.

    2014-12-01

    Modeling studies have indicated that global warming, in many regions, will increase the exposure of major crops to rainfall and temperature stress, leading to lower crop yields. Climate variability alone has a potential to decrease yield to an extent comparable to or greater than yield reductions expected due to rising temperature. For India, where agriculture is important, both in terms of food security as well as a source of livelihoods to a majority of its population, climate variability and climate change are subjects of serious concern. There is however a need to distinguish the impact of current climate variability and climate change on Indian agriculture, especially in relation to their socioeconomic impact. This differentiation is difficult to determine due to the secular trend of increasing production and yield of the past several decades. The current research in this aspect is in an initial stage and requires a multi-disciplinary effort. In this study, we assess the potential differential impacts of environmental stress and shock across different socioeconomic strata of the rural population, using village level survey data. The survey data from eight selected villages, based on the Project on Agrarian Relations in India conducted by the Foundation for Agrarian Studies, indicated that income from crop production of the top 20 households (based on the extent of operational land holding, employment of hired labour and asset holdings) is a multiple of the mean income of the village. In sharp contrast, the income of the bottom 20 households is a fraction of the mean and sometimes negative, indicating a net loss from crop production. The considerable differentials in output and incomes suggest that small and marginal farmers are far more susceptible to climate variability and climate change than the other sections. Climate change is effectively an immediate threat to small and marginal farmers, which is driven essentially by socioeconomic conditions. The impact

  13. Observed Oceanic and Terrestrial Drivers of North African Climate

    NASA Astrophysics Data System (ADS)

    Yu, Y.; Notaro, M.; Wang, F.; Mao, J.; Shi, X.; Wei, Y.

    2015-12-01

    Hydrologic variability can pose a serious threat to the poverty-stricken regions of North Africa. Yet, the current understanding of oceanic versus terrestrial drivers of North African droughts/pluvials is largely model-based, with vast disagreement among models. In order to identify the observed drivers of North African climate and develop a benchmark for model evaluations, the multivariate Generalized Equilibrium Feedback Assessment (GEFA) is applied to observations, remotely sensed data, and reanalysis products. The identified primary oceanic drivers of North African rainfall variability are the Atlantic, tropical Indian, and tropical Pacific Oceans and Mediterranean Sea. During the summer monsoon, positive tropical eastern Atlantic sea-surface temperature (SST) anomalies are associated with a southward shift of the Inter-Tropical Convergence Zone, enhanced ocean evaporation, and greater precipitable water across coastal West Africa, leading to increased West African monsoon (WAM) rainfall and decreased Sahel rainfall. During the short rains, positive SST anomalies in the western tropical Indian Ocean and negative anomalies in the eastern tropical Indian Ocean support greater easterly oceanic flow, evaporation over the western ocean, and moisture advection to East Africa, thereby enhancing rainfall. The sign, magnitude, and timing of observed vegetation forcing on rainfall vary across North Africa. The positive feedback of leaf area index (LAI) on rainfall is greatest during DJF for the Horn of Africa, while it peaks in autumn and is weakest during the summer monsoon for the Sahel. Across the WAM region, a positive LAI anomaly supports an earlier monsoon onset, increased rainfall during the pre-monsoon, and decreased rainfall during the wet season. Through unique mechanisms, positive LAI anomalies favor enhanced transpiration, precipitable water, and rainfall across the Sahel and Horn of Africa, and increased roughness, ascent, and rainfall across the WAM region

  14. Climate variability slows evolutionary responses of Colias butterflies to recent climate change.

    PubMed

    Kingsolver, Joel G; Buckley, Lauren B

    2015-03-07

    How does recent climate warming and climate variability alter fitness, phenotypic selection and evolution in natural populations? We combine biophysical, demographic and evolutionary models with recent climate data to address this question for the subalpine and alpine butterfly, Colias meadii, in the southern Rocky Mountains. We focus on predicting patterns of selection and evolution for a key thermoregulatory trait, melanin (solar absorptivity) on the posterior ventral hindwings, which affects patterns of body temperature, flight activity, adult and egg survival, and reproductive success in Colias. Both mean annual summer temperatures and thermal variability within summers have increased during the past 60 years at subalpine and alpine sites. At the subalpine site, predicted directional selection on wing absorptivity has shifted from generally positive (favouring increased wing melanin) to generally negative during the past 60 years, but there is substantial variation among years in the predicted magnitude and direction of selection and the optimal absorptivity. The predicted magnitude of directional selection at the alpine site declined during the past 60 years and varies substantially among years, but selection has generally been positive at this site. Predicted evolutionary responses to mean climate warming at the subalpine site since 1980 is small, because of the variability in selection and asymmetry of the fitness function. At both sites, the predicted effects of adaptive evolution on mean population fitness are much smaller than the fluctuations in mean fitness due to climate variability among years. Our analyses suggest that variation in climate within and among years may strongly limit evolutionary responses of ectotherms to mean climate warming in these habitats. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  15. Sensitivity of the East African rift lakes to climate variability

    NASA Astrophysics Data System (ADS)

    Olaka, L.; Trauth, M. H.

    2009-04-01

    Lakes in the East African Rift have provided excellent proxies to reconstruct past climate changes in the low latitudes. The lakes occupy volcano-tectonic depressions with highly variable climate and hydrological setting, that present a good opportunity to study the climatic and hydrogeological influences on the lake water budget. Previous studies have used lake floor sediments to establish the sensitivity of the East African rift lakes. This study focuses on geomorphology and climate to offer additional or alternative record of lake history that are key to quantifying sensitivity of these lakes as archives to external and internal climatic forcings. By using the published Holocene lake areas and levels, we analyze twelve lakes on the eastern arm of the East African rift; Ziway, Awassa, Turkana, Suguta, Baringo, Nakuru, Elmenteita, Naivasha, Natron, Manyara and compare with Lake Victoria, that occupies the plateau between the east and the western arms of the rift. Using the SRTM data, Hypsometric (area-altitude) analysis has been used to compare the lake basins between latitude 80 North and 30 South. The mean elevation for the lakes, is between 524 and 2262 meters above sea level, the lakes’ hypsometric integrals (HI), a measure of landmass volume above the reference plane, vary from 0.31 to 0.76. The aridity index (Ai), defined as Precipitation/ Evapotranspiration, quantifies the water available to a lake, it encompasses land cover and climatic effects. It is lowest (arid) in the basin between the Ethiopian rift and the Kenyan rift and at the southern termination of the Kenyan Rift in the catchments of lake Turkana, Suguta, Baringo and Manyara with values of 0.55, 0.43, 0.43 and 0.5 respectively. And it is highest (wet) in the catchments of, Ziway, Awassa, Nakuru and Naivasha as 1.33,1.03 and 1.2 respectively, which occupy the highest points of the rift. Lake Victoria has an index of 1.42 the highest of these lakes and receives a high precipitation. We use a

  16. Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

    SciTech Connect

    Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef

    Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

  17. Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

    DOE PAGES

    Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; …

    2016-10-04

    Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

  18. Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

    NASA Astrophysics Data System (ADS)

    Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; Hu, Aixue; Hamlington, Benjamin; Kenigson, Jessica; Palanisamy, Hindumathi; Thompson, Philip

    2017-01-01

    Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modes and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this paper, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.

  19. The Last Interglacial Climate Variability in Northern China

    NASA Astrophysics Data System (ADS)

    Li, X.; Lu, Y.; Sinha, A.; Ma, Z.; Tan, M.; Edwards, R.; Cheng, H.

    2013-12-01

    Speleothem oxygen isotope (δ18O) records can reconstruct high-resolution and absolutely dated climate history, in particular, the variability of monsoon precipitation that is associated with the changes in atmospheric circulation and, in turn, the δ18O of precipitation. In the East Asian monsoon domain, although speleothem records have been established in southeastern China over the last decade, including several records covering the last interglacial period (MIS 5e), similar records are virtually absent in northern China. This hampers our understanding of the mechanism of the East Asian monsoon changes, because the northern China δ18O record is, as recently shown by modeling work, more sensitive to changes in summer monsoon precipitation than that from southeastern China. Here we provide a high-resolution and absolutely dated speleothem δ18O record between ~129 and 119 ka BP from Kulishu cave, Beijing, northern China. It shows an abrupt onset of MIS 5e at 129.4×0.7 ka BP, similar within dating uncertainty to the Dongge, Hulu, and Sanbao records from southeastern China. However, the end of MIS 5e is rather gradual in comparison to the southern China counterparts. While overall MIS5e monsoon climate appears to be rather stable on orbital timescales, broadly following northern hemisphere summer insolation, millennial/centennial-scale events punctuate the Kulishu record. Spectral analysis reveals a significant quasi-1500 year periodicity, comparable to the Bond cycle, first observed in the North Atlantic during the Holocene, and more recently in interglacial East Asian monsoon cave records. As such, events with a ~1500 year pacing appear to be a persistent characteristic of the East Asian monsoon for good portions of the past two glacial-interglacial periods. Changes in solar output would be one possibility for the trigger; changes in ocean circulation with a ~1500-year time constant would be another. Comparison with Hulu(MSX, Cheng et al., 2006)-Dongge(D3, D4

  20. Characterization of Climate Change and Variability with GPS

    NASA Technical Reports Server (NTRS)

    Kursinski, R.

    1999-01-01

    influence of natural climate variability. S. Leroy concludes that the signal-to-noise ratio of global warming detection increases by unity approximately every 10 years if a single oceanic region is chosen. Less time for detection is likely when many global regions are considered simultaneously. GPS occultation constellations allow the possibility of detecting small changes in upper air temperature with inconsequential calibration errors, making occultation an ideal data type for global warming detection studies. Our initial study of a 22-GHz satellite-satellite occultation system predicts upper troposphere moisture sensitivities of 3-5 ppmv and 1-2 percent in the middle and lower troposphere. Additional information contained in original.

  1. Climate Variability and Inter-Provincial Migration in South America, 1970-2011.

    PubMed

    Thiede, Brian; Gray, Clark; Mueller, Valerie

    2016-11-01

    We examine the effect of climate variability on human migration in South America. Our analyses draw on over 21 million observations of adults aged 15-40 from 25 censuses conducted in eight South American countries. Addressing limitations associated with methodological diversity among prior studies, we apply a common analytic approach and uniform definitions of migration and climate across all countries. We estimate the effects of climate variability on migration overall and also investigate heterogeneity across sex, age, and socioeconomic groups, across countries, and across historical climate conditions. We also disaggregate migration by the rural/urban status of destination. We find that exposure to monthly temperature shocks has the most consistent effects on migration relative to monthly rainfall shocks and gradual changes in climate over multi-year periods. We also find evidence of heterogeneity across demographic groups and countries. Analyses that disaggregate migration by the rural/urban status of destination suggest that much of the climate-related inter-province migration is directed toward urban areas. Overall, our results underscore the complexity of environment-migration linkages and challenge simplistic narratives that envision a linear and monolithic migratory response to changing climates.

  2. Climate Variability and Inter-Provincial Migration in South America, 1970-2011

    PubMed Central

    Thiede, Brian; Gray, Clark; Mueller, Valerie

    2016-01-01

    We examine the effect of climate variability on human migration in South America. Our analyses draw on over 21 million observations of adults aged 15-40 from 25 censuses conducted in eight South American countries. Addressing limitations associated with methodological diversity among prior studies, we apply a common analytic approach and uniform definitions of migration and climate across all countries. We estimate the effects of climate variability on migration overall and also investigate heterogeneity across sex, age, and socioeconomic groups, across countries, and across historical climate conditions. We also disaggregate migration by the rural/urban status of destination. We find that exposure to monthly temperature shocks has the most consistent effects on migration relative to monthly rainfall shocks and gradual changes in climate over multi-year periods. We also find evidence of heterogeneity across demographic groups and countries. Analyses that disaggregate migration by the rural/urban status of destination suggest that much of the climate-related inter-province migration is directed toward urban areas. Overall, our results underscore the complexity of environment-migration linkages and challenge simplistic narratives that envision a linear and monolithic migratory response to changing climates. PMID:28413264

  3. Association between Climatic Variables and Malaria Incidence: A Study in Kokrajhar District of Assam, India

    PubMed Central

    Nath, Dilip C.; Mwchahary, Dimacha Dwibrang

    2013-01-01

    A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with z malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; pclimatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a

  4. Association between climatic variables and malaria incidence: a study in Kokrajhar district of Assam, India.

    PubMed

    Nath, Dilip C; Mwchahary, Dimacha Dwibrang

    2012-11-11

    A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with forest malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall

  5. Surface Observation Climatic Summaries for Ansbach AHP/Katterbach, Germany

    DTIC Science & Technology

    1992-05-01

    SURFACE OBSERVATIONS CLIMATIC SWUMWN (LISOCS). EXISTING RUSSWOS AND LISOCS WILL CONTINUE IN USE , BUT WILL EVENTUALLY BE BY A 8OCS. 12A. DISTRIBUTION…OBSERVATION CLIMATIC 8UMW*IY). RUSSWOS AND LISOCS NOW IN EXISTENCE WILL CON- TIhUE TO BE USED UNTIL THEY ARE EVENTUALLY REPLACED BY SOCS. THIS PIODUCT…LOCATION A AT ASHEVILLE, NC 28901-2723. HERE, CLIMATOLOGISTS USE STATE-OF-THE-ART COM- PUTER TECHNOLOGY TO SUMMARIZE WEATHER OBSERVATIONS COLLECTED

  6. Impacts of Austrian Climate Variability on Honey Bee Mortality

    NASA Astrophysics Data System (ADS)

    Switanek, Matt; Brodschneider, Robert; Crailsheim, Karl; Truhetz, Heimo

    2015-04-01

    Global food production, as it is today, is not possible without pollinators such as the honey bee. It is therefore alarming that honey bee populations across the world have seen increased mortality rates in the last few decades. The challenges facing the honey bee calls into question the future of our food supply. Beside various infectious diseases, Varroa destructor is one of the main culprits leading to increased rates of honey bee mortality. Varroa destructor is a parasitic mite which strongly depends on honey bee brood for reproduction and can wipe out entire colonies. However, climate variability may also importantly influence honey bee breeding cycles and bee mortality rates. Persistent weather events affects vegetation and hence foraging possibilities for honey bees. This study first defines critical statistical relationships between key climate indicators (e.g., precipitation and temperature) and bee mortality rates across Austria, using 6 consecutive years of data. Next, these leading indicators, as they vary in space and time, are used to build a statistical model to predict bee mortality rates and the respective number of colonies affected. Using leave-one-out cross validation, the model reduces the Root Mean Square Error (RMSE) by 21% with respect to predictions made with the mean mortality rate and the number of colonies. Furthermore, a Monte Carlo test is used to establish that the model’s predictions are statistically significant at the 99.9% confidence level. These results highlight the influence of climate variables on honey bee populations, although variability in climate, by itself, cannot fully explain colony losses. This study was funded by the Austrian project ‘Zukunft Biene’.

  7. Interaction Between Ecohydrologic Dynamics and Microtopographic Variability Under Climate Change

    NASA Astrophysics Data System (ADS)

    Le, Phong V. V.; Kumar, Praveen

    2017-10-01

    Vegetation acclimation resulting from elevated atmospheric CO2 concentration, along with response to increased temperature and altered rainfall pattern, is expected to result in emergent behavior in ecologic and hydrologic functions. We hypothesize that microtopographic variability, which are landscape features typically of the length scale of the order of meters, such as topographic depressions, will play an important role in determining this dynamics by altering the persistence and variability of moisture. To investigate these emergent ecohydrologic dynamics, we develop a modeling framework, Dhara, which explicitly incorporates the control of microtopographic variability on vegetation, moisture, and energy dynamics. The intensive computational demand from such a modeling framework that allows coupling of multilayer modeling of the soil-vegetation continuum with 3-D surface-subsurface flow processes is addressed using hybrid CPU-GPU parallel computing framework. The study is performed for different climate change scenarios for an intensively managed agricultural landscape in central Illinois, USA, which is dominated by row-crop agriculture, primarily soybean (Glycine max) and maize (Zea mays). We show that rising CO2 concentration will decrease evapotranspiration, thus increasing soil moisture and surface water ponding in topographic depressions. However, increased atmospheric demand from higher air temperature overcomes this conservative behavior resulting in a net increase of evapotranspiration, leading to reduction in both soil moisture storage and persistence of ponding. These results shed light on the linkage between vegetation acclimation under climate change and microtopography variability controls on ecohydrologic processes.

  8. Sub-Milankovitch millennial-scale climate variability in Middle Eocene deep-marine sediments

    NASA Astrophysics Data System (ADS)

    Scotchman, J. I.; Pickering, K. T.; Robinson, S. A.

    2009-12-01

    Sub-Milankovitch millennial scale climate variability appears ubiquitous throughout the Quaternary and Pleistocene palaeoenvironmental records (e.g. McManus et al., 1999) yet the driving mechanism remains elusive. Possible mechanisms are generally linked to Quaternary-specific oceanic and cryospheric conditions (e.g. Maslin et al., 2001). An alternative external control, such as solar forcing, however, remains a compelling alternative hypothesis (e.g. Bond et al., 2001). This would imply that millennial-scale cycles are an intrinsic part of the Earth’s climatic system and not restricted to any specific period of time. Determining which of these hypotheses is correct impacts on our understanding of the climate system and its role as a driver of cyclic sedimentation during both icehouse and greenhouse climates. Here we show that Middle Eocene, laminated deep-marine sediments deposited in the Ainsa Basin, Spanish Pyrenees, contain 1,565-year (469 mm) cycles modulated by a 7,141-year (2157 mm) period. Climatic oscillations of 1,565-years recorded by element/Al ratios, are interpreted as representing climatically driven variation in sediment supply (terrigenous run-off) to the Ainsa basin. Climatic oscillations with this period are comparable to Quaternary Bond (~1,500-year), Dansgaard-Oeschger (~1,470-year) and Heinrich (~7,200-year) climatic events. Recognition of similar millennial-scale oscillations in the greenhouse climate of the Middle Eocene would appear inconsistent with an origin dependent upon Quaternary-specific conditions. Our observations lend support for pervasive millennial-scale climatic variability present throughout geologic time likely driven by an external forcing mechanism such as solar forcing. References Bond, G., Kromer, B., Beer, J., Muscheler, R., Evans, M.N., Showers, W., Hoffmann, S., Lotti-Bond, R., Hajdas, I., Bonani, G. 2001. Persistent Solar Influence on North Atlantic Climate During the Holocene. Science, 294, 2130-2136 Maslin, M

  9. Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

    NASA Astrophysics Data System (ADS)

    Dakhlaoui, H.; Ruelland, D.; Tramblay, Y.; Bargaoui, Z.

    2017-07-01

    To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that must be fairly reliable under changing climate conditions. The aim of this study was thus to assess the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in northern Tunisia under long-term climate variability, in the light of available future climate scenarios for this region. The robustness of the models was evaluated using a differential split sample test based on a climate classification of the observation period that simultaneously accounted for precipitation and temperature conditions. The study catchments include the main hydrographical basins in northern Tunisia, which produce most of the surface water resources in the country. A 30-year period (1970-2000) was used to capture a wide range of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while model transferability was evaluated based on the Nash-Sutcliffe efficiency criterion and volume error. The three hydrological models were shown to behave similarly under climate variability. The models simulated the runoff pattern better when transferred to wetter and colder conditions than to drier and warmer ones. It was shown that their robustness became unacceptable when climate conditions involved a decrease of more than 25% in annual precipitation and an increase of more than +1.75 °C in annual mean temperatures. The reduction in model robustness may be partly due to the climate dependence of some parameters. When compared to precipitation and temperature projections in the region, the limits of transferability obtained in this study are generally respected for short and middle term. For long term projections under the most pessimistic emission gas scenarios, the limits of transferability are generally not respected, which may hamper the

  10. Temporal changes in climatic variables and their impact on crop yields in southwestern China.

    PubMed

    Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

    2014-08-01

    Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing-a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series (Pobserved during the oilseed rape growth period (Pclimatic variables in this region. Yield of rice increased with rainfall (Pclimatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

  11. Temporal changes in climatic variables and their impact on crop yields in southwestern China

    NASA Astrophysics Data System (ADS)

    Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

    2014-08-01

    Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing—a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series ( P observed during the oilseed rape growth period ( P climatic variables in this region. Yield of rice increased with rainfall ( P climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

  12. Uncertainties in Future Regional Sea Level Trends: How to Deal with the Internal Climate Variability?

    NASA Astrophysics Data System (ADS)

    Becker, M.; Karpytchev, M.; Hu, A.; Deser, C.; Lennartz-Sassinek, S.

    2017-12-01

    Today, the Climate models (CM) are the main tools for forecasting sea level rise (SLR) at global and regional scales. The CM forecasts are accompanied by inherent uncertainties. Understanding and reducing these uncertainties is becoming a matter of increasing urgency in order to provide robust estimates of SLR impact on coastal societies, which need sustainable choices of climate adaptation strategy. These CM uncertainties are linked to structural model formulation, initial conditions, emission scenario and internal variability. The internal variability is due to complex non-linear interactions within the Earth Climate System and can induce diverse quasi-periodic oscillatory modes and long-term persistences. To quantify the effects of internal variability, most studies used multi-model ensembles or sea level projections from a single model ran with perturbed initial conditions. However, large ensembles are not generally available, or too small, and computationally expensive. In this study, we use a power-law scaling of sea level fluctuations, as observed in many other geophysical signals and natural systems, which can be used to characterize the internal climate variability. From this specific statistical framework, we (1) use the pre-industrial control run of the National Center for Atmospheric Research Community Climate System Model (NCAR-CCSM) to test the robustness of the power-law scaling hypothesis; (2) employ the power-law statistics as a tool for assessing the spread of regional sea level projections due to the internal climate variability for the 21st century NCAR-CCSM; (3) compare the uncertainties in predicted sea level changes obtained from a NCAR-CCSM multi-member ensemble simulations with estimates derived for power-law processes, and (4) explore the sensitivity of spatial patterns of the internal variability and its effects on regional sea level projections.

  13. Variability in soybean yield in Brazil stemming from the interaction of heterogeneous management and climate variability

    NASA Astrophysics Data System (ADS)

    Cohn, A.; Bragança, A.; Jeffries, G. R.

    2017-12-01

    An increasing share of global agricultural production can be found in the humid tropics. Therefore, an improved understanding of the mechanisms governing variability in the output of tropical agricultural systems is of increasing importance for food security including through climate change adaptation. Yet, the long window over which many tropical crops can be sown, the diversity of crop varieties and management practices combine to challenge inference into climate risk to cropping output in analyses of tropical crop-climate sensitivity employing administrative data. In this paper, we leverage a newly developed spatially explicit dataset of soybean yields in Brazil to combat this problem. The dataset was built by training a model of remotely-sensed vegetation index data and land cover classification data using a rich in situ dataset of soybean yield and management variables collected over the period 2006 to 2016. The dataset contains soybean yields by plant date, cropping frequency, and maturity group for each 5km grid cell in Brazil. We model variation in these yields using an approach enabling the estimation of the influence of management factors on the sensitivity of soybean yields to variability in: cumulative solar radiation, extreme degree days, growing degree days, flooding rain in the harvest period, and dry spells in the rainy season. We find strong variation in climate sensitivity by management class. Planting date and maturity group each explained a great deal more variation in yield sensitivity than did cropping frequency. Brazil collects comparatively fine spatial resolution yield data. But, our attempt to replicate our results using administrative soy yield data revealed substantially lesser crop-climate sensitivity; suggesting that previous analyses employing administrative data may have underestimated climate risk to tropical soy production.

  14. Continuity of Climate Data Records derived from Microwave Observations

    NASA Astrophysics Data System (ADS)

    Mears, C. A.; Wentz, F. J.; Brewer, M.; Meissner, T.; Ricciardulli, L.

    2017-12-01

    Remote Sensing Systems (www.remss.com) has been producing and distributing microwave climate data products from microwave imagers (SSMI, TMI, AMSR, WindSat, GMI, Aquarius, SMAP) over the global oceans since the launch of the first SSMI in 1987. Interest in these data products has been significant as researchers around the world have downloaded the approximate equivalent of 1 million satellite years of processed data. Users, including NASA, NOAA, US National Laboratories, US Navy, UK Met, ECMWF, JAXA, JMA, CMC, the Australian Bureau of Meteorology, as well as many hundreds of other agencies and universities routinely access these microwave data products. The quality of these data records has increased as more observations have become available and inter-calibration techniques have improved. The impending end of missions for WindSat, AMSR-2, and the remaining SSMIs will have significant impact on the quality and continuity of long term microwave climate data records. In addition to the problem of reduced numbers of observations, there is a real danger of losing overlapping observations. Simultaneous operation of satellites, especially when the observations are at similar local crossing times, provides a significant benefit in the effort to inter-calibrate satellites to yield accurate and stable long-term records. The end of WindSat and AMSR-2 will leave us without microwave SSTs in cold water, as there will be no microwave imagers with C-band channels. Microwave SSTs have a crucial advantage over IR SSTs, which is not able to measure SST in clouds or if aerosols are present. The gap in ocean wind vectors will be somewhat mitigated as the European ASCAT C-band scatterometer mission on MetOp is continuing. Nonetheless, the anticipated cease of several microwave satellite radiometers retrieving ocean winds in the coming years will lead to a significant gap in temporal coverage. Atmospheric water vapor, cloud liquid water, and rain rate are all important climate

  15. Climate variability and marine ecosystem impacts: a North Atlantic perspective

    NASA Astrophysics Data System (ADS)

    Parsons, L. S.; Lear, W. H.

    In recent decades it has been recognized that in the North Atlantic climatic variability has been largely driven by atmospheric forcing related to the North Atlantic Oscillation (NAO). The NAO index began a pronounced decline around 1950 to a low in the 1960s. From 1970 onward the NAO index increased to its most extreme and persistent positive phase during the late 1980s and early 1990s. Changes in the pattern of the NAO have differential impacts on the opposite sides of the North Atlantic and differential impacts in the north and south. The changes in climate resulting from changes in the NAO appear to have had substantial impacts on marine ecosystems, in particular, on fish productivity, with the effects varying from region to region. An examination of several species and stocks, e.g. gadoids, herring and plankton in the Northeast Atlantic and cod and shellfish in the Northwest Atlantic, indicates that there is a link between long-term trends in the NAO and the productivity of various components of the marine ecosystem. While broad trends are evident, the mechanisms are poorly understood. Further research is needed to improve our understanding of how this climate variability affects the productivity of various components of the North Atlantic marine ecosystem.

  16. Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

    NASA Astrophysics Data System (ADS)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  17. Marine assemblages respond rapidly to winter climate variability.

    PubMed

    Morley, James W; Batt, Ryan D; Pinsky, Malin L

    2017-07-01

    Even species within the same assemblage have varied responses to climate change, and there is a poor understanding for why some taxa are more sensitive to climate than others. In addition, multiple mechanisms can drive species’ responses, and responses may be specific to certain life stages or times of year. To test how marine species respond to climate variability, we analyzed 73 diverse taxa off the southeast US coast in 26 years of scientific trawl survey data and determined how changes in distribution and biomass relate to temperature. We found that winter temperatures were particularly useful for explaining interannual variation in species’ distribution and biomass, although the direction and magnitude of the response varied among species from strongly negative, to little response, to strongly positive. Across species, the response to winter temperature varied greatly, with much of this variation being explained by thermal preference. A separate analysis of annual commercial fishery landings revealed that winter temperatures may also impact several important fisheries in the southeast United States. Based on the life stages of the species surveyed, winter temperature appears to act through overwinter mortality of juveniles or as a cue for migration timing. We predict that this assemblage will be responsive to projected increases in temperature and that winter temperature may be broadly important for species relationships with climate on a global scale. © The Authors Global Change Biology Published by John Wiley & Sons Ltd.

  18. Intraseasonal and Interannual Variability of Mars Present Climate

    NASA Astrophysics Data System (ADS)

    Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

    1996-01-01

    This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to investigate the nature of intraseasonal and interannual variability of Mars’present climate. We have applied a three-dimensional climate model based on the full hydrostatic primitive equations to determine the spatial, but primarily, the temporal structures of the planet’s large-scale circulation as it evolves during a given seasonal advance, and, over multi-annual cycles. The particular climate model applies simplified physical parameterizations and is computationally efficient. It could thus easily be integrated in a perpetual season or advancing season configuration, as well as over many Mars years. We have assessed both high and low-frequency components of the circulation (i.e., motions having periods of Omicron(2-10 days) or greater than Omicron(10 days), respectively). Results from this investigation have explored the basic issue whether Mars’ climate system is naturally ‘chaotic’ associated with nonlinear interactions of the large-scale circulation-regardless of any allowance for year-to-year variations in external forcing mechanisms. Titles of papers presented at scientific conferences and a manuscript to be submitted to the scientific literature are provided. An overview of a areas for further investigation is also presented.

  19. Regional Climate Variability Under Model Simulations of Solar Geoengineering

    NASA Astrophysics Data System (ADS)

    Dagon, Katherine; Schrag, Daniel P.

    2017-11-01

    Solar geoengineering has been shown in modeling studies to successfully mitigate global mean surface temperature changes from greenhouse warming. Changes in land surface hydrology are complicated by the direct effect of carbon dioxide (CO2) on vegetation, which alters the flux of water from the land surface to the atmosphere. Here we investigate changes in boreal summer climate variability under solar geoengineering using multiple ensembles of model simulations. We find that spatially uniform solar geoengineering creates a strong meridional gradient in the Northern Hemisphere temperature response, with less consistent patterns in precipitation, evapotranspiration, and soil moisture. Using regional summertime temperature and precipitation results across 31-member ensembles, we show a decrease in the frequency of heat waves and consecutive dry days under solar geoengineering relative to a high-CO2 world. However in some regions solar geoengineering of this amount does not completely reduce summer heat extremes relative to present day climate. In western Russia and Siberia, an increase in heat waves is connected to a decrease in surface soil moisture that favors persistent high temperatures. Heat waves decrease in the central United States and the Sahel, while the hydrologic response increases terrestrial water storage. Regional changes in soil moisture exhibit trends over time as the model adjusts to solar geoengineering, particularly in Siberia and the Sahel, leading to robust shifts in climate variance. These results suggest potential benefits and complications of large-scale uniform climate intervention schemes.

  20. The effect of modeled absolute timing variability and relative timing variability on observational learning.

    PubMed

    Grierson, Lawrence E M; Roberts, James W; Welsher, Arthur M

    2017-05-01

    There is much evidence to suggest that skill learning is enhanced by skill observation. Recent research on this phenomenon indicates a benefit of observing variable/erred demonstrations. In this study, we explore whether it is variability within the relative organization or absolute parameterization of a movement that facilitates skill learning through observation. To do so, participants were randomly allocated into groups that observed a model with no variability, absolute timing variability, relative timing variability, or variability in both absolute and relative timing. All participants performed a four-segment movement pattern with specific absolute and relative timing goals prior to and following the observational intervention, as well as in a 24h retention test and transfers tests that featured new relative and absolute timing goals. Absolute timing error indicated that all groups initially acquired the absolute timing, maintained their performance at 24h retention, and exhibited performance deterioration in both transfer tests. Relative timing error revealed that the observation of no variability and relative timing variability produced greater performance at the post-test, 24h retention and relative timing transfer tests, but for the no variability group, deteriorated at absolute timing transfer test. The results suggest that the learning of absolute timing following observation unfolds irrespective of model variability. However, the learning of relative timing benefits from holding the absolute features constant, while the observation of no variability partially fails in transfer. We suggest learning by observing no variability and variable/erred models unfolds via similar neural mechanisms, although the latter benefits from the additional coding of information pertaining to movements that require a correction. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Climate change and climate variability: personal motivation for adaptation and mitigation

    PubMed Central

    2011-01-01

    Background Global climate change impacts on human and natural systems are predicted to be severe, far reaching, and to affect the most physically and economically vulnerable disproportionately. Society can respond to these threats through two strategies: mitigation and adaptation. Industry, commerce, and government play indispensable roles in these actions but so do individuals, if they are receptive to behavior change. We explored whether the health frame can be used as a context to motivate behavioral reductions of greenhouse gas emissions and adaptation measures. Methods In 2008, we conducted a cross-sectional survey in the United States using random digit dialing. Personal relevance of climate change from health threats was explored with the Health Belief Model (HBM) as a conceptual frame and analyzed through logistic regressions and path analysis. Results Of 771 individuals surveyed, 81% (n = 622) acknowledged that climate change was occurring, and were aware of the associated ecologic and human health risks. Respondents reported reduced energy consumption if they believed climate change could affect their way of life (perceived susceptibility), Odds Ratio (OR) = 2.4 (95% Confidence Interval (CI): 1.4 – 4.0), endanger their life (perceived severity), OR = 1.9 (95% CI: 1.1 – 3.1), or saw serious barriers to protecting themselves from climate change, OR = 2.1 (95% CI: 1.2 – 3.5). Perceived susceptibility had the strongest effect on reduced energy consumption, either directly or indirectly via perceived severity. Those that reported having the necessary information to prepare for climate change impacts were more likely to have an emergency kit OR = 2.1 (95% CI: 1.4 – 3.1) or plan, OR = 2.2 (95% CI: 1.5 -3.2) for their household, but also saw serious barriers to protecting themselves from climate change or climate variability, either by having an emergency kit OR = 1.6 (95% CI: 1.1 – 2.4) or an emergency plan OR = 1.5 (95%CI: 1.0 – 2.2). Conclusions Motivation for

  2. Climate change and climate variability: personal motivation for adaptation and mitigation.

    PubMed

    Semenza, Jan C; Ploubidis, George B; George, Linda A

    2011-05-21

    Global climate change impacts on human and natural systems are predicted to be severe, far reaching, and to affect the most physically and economically vulnerable disproportionately. Society can respond to these threats through two strategies: mitigation and adaptation. Industry, commerce, and government play indispensable roles in these actions but so do individuals, if they are receptive to behavior change. We explored whether the health frame can be used as a context to motivate behavioral reductions of greenhouse gas emissions and adaptation measures. In 2008, we conducted a cross-sectional survey in the United States using random digit dialing. Personal relevance of climate change from health threats was explored with the Health Belief Model (HBM) as a conceptual frame and analyzed through logistic regressions and path analysis. Of 771 individuals surveyed, 81% (n = 622) acknowledged that climate change was occurring, and were aware of the associated ecologic and human health risks. Respondents reported reduced energy consumption if they believed climate change could affect their way of life (perceived susceptibility), Odds Ratio (OR) = 2.4 (95% Confidence Interval (CI): 1.4-4.0), endanger their life (perceived severity), OR = 1.9 (95% CI: 1.1-3.1), or saw serious barriers to protecting themselves from climate change, OR = 2.1 (95% CI: 1.2-3.5). Perceived susceptibility had the strongest effect on reduced energy consumption, either directly or indirectly via perceived severity. Those that reported having the necessary information to prepare for climate change impacts were more likely to have an emergency kit OR = 2.1 (95% CI: 1.4-3.1) or plan, OR = 2.2 (95% CI: 1.5-3.2) for their household, but also saw serious barriers to protecting themselves from climate change or climate variability, either by having an emergency kit OR = 1.6 (95% CI: 1.1-2.4) or an emergency plan OR = 1.5 (95%CI: 1.0-2.2). Motivation for voluntary mitigation is mostly dependent on

  3. Solar variability, coupling between atmospheric layers and climate change.

    PubMed

    Arnold, Neil

    2002-12-15

    One of the enduring puzzles of atmospheric physics is the extent to which changes in the Sun can influence the behaviour of the climate system. While solar-flux changes tend to be relatively modest, a number of observations of atmospheric parameters indicates a disproportionately large response. Global-scale models of the coupled middle and upper atmosphere have provided new insights into some of the mechanisms that may be responsible for the amplification of the solar signal. In particular, modification of the transport of heat and chemicals such as ozone by waves during periods of solar activity has been shown to make an important contribution to the climate of the stratosphere and mesosphere. In this paper, a review of some of the recent advances in understanding the coupling between atmospheric layers and how this work relates to Sun-weather relations and climate change in the troposphere will be presented, along with a discussion of some of the challenges that remain.

  4. Assessing the observed impact of anthropogenic climate change

    DOE PAGES

    Hansen, Gerrit; Stone, Dáithí

    2015-12-21

    Impacts of recent regional changes in climate on natural and human systems are documented across the globe, yet studies explicitly linking these observations to anthropogenic forcing of the climate are scarce. Here in this work, we provide a systematic assessment of the role of anthropogenic climate change for the range of impacts of regional climate trends reported in the IPCC’s Fifth Assessment Report. We find that almost two-thirds of the impacts related to atmospheric and ocean temperature can be confidently attributed to anthropogenic forcing. In contrast, evidence connecting changes in precipitation and their respective impacts to human influence is stillmore » weak. Moreover, anthropogenic climate change has been a major influence for approximately three-quarters of the impacts observed on continental scales. Finally, hence the effects of anthropogenic emissions can now be discerned not only globally, but also at more regional and local scales for a variety of natural and human systems.« less

  5. Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

    NASA Astrophysics Data System (ADS)

    Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

    2017-04-01

    Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information – to locally observed discharge – can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to

  6. Climate variability controls on unsaturated water and chemical movement, High Plains aquifer, USA

    USGS Publications Warehouse

    Gurdak, J.J.; Hanson, R.T.; McMahon, P.B.; Bruce, B.W.; McCray, J.E.; Thyne, G.D.; Reedy, R.C.

    2007-01-01

    Responses in the vadose zone and groundwater to interannual, interdecadal, and multidecadal climate variability have important implications for groundwater resource sustainability, yet they are poorly documented and not well understood in most aquifers of the USA. This investigation systematically examines the role of interannual to multidecadal climate variability on groundwater levels, deep infiltration (3-23 m) events, and downward displacement (>1 m) of chloride and nitrate reservoirs in thick (15-50 m) vadose zones across the regionally extensive High Plains aquifer. Such vadose zone responses are unexpected across much of the aquifer given a priori that unsaturated total-potential profiles indicate upward water movement from the water table toward the root zone, mean annual potential evapotranspiration exceeds mean annual precipitation, and millennia-scale evapoconcentration results in substantial vadose zone chloride and nitrate reservoirs. Using singular spectrum analysis (SSA) to reconstruct precipitation and groundwater level time-series components, variability was identified in all time series as partially coincident with known climate cycles, such as the Pacific Decadal Oscillation (PDO) (10-25 yr) and the El Nin??o/Southern Oscillation (ENSO) (2-6 yr). Using these lag-correlated hydrologic time series, a new method is demonstrated to estimate climate-varying unsaturated water flux. The results suggest the importance of interannual to interdecadal climate variability on water-flux estimation in thick vadose zones and provide better understanding of the climate-induced transients responsible for the observed deep infiltration and chemical-mobilization events. Based on these results, we discuss implications for climate-related sustainability of the High Plains aquifer. ?? Soil Science Society of America.

  7. The Climate Variability & Predictability (CVP) Program at NOAA – DYNAMO Recent Project Advancements

    NASA Astrophysics Data System (ADS)

    Lucas, S. E.; Todd, J. F.; Higgins, W.

    2013-12-01

    The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International Geosphere-Biosphere Programme (IGBP), and the U.S. Global Change Research Program (USGCRP). The CVP program sits within the Earth System Science (ESS) Division at NOAA’s Climate Program Office. Dynamics of the Madden-Julian Oscillation (DYNAMO): The Indian Ocean is one of Earth’s most sensitive regions because the interactions between ocean and atmosphere there have a discernable effect on global climate patterns. The tropical weather that brews in that region can move eastward along the equator and reverberate around the globe, shaping weather and climate in far-off places. The vehicle for this variability is a phenomenon called the Madden-Julian Oscillation, or MJO. The MJO, which originates over the Indian Ocean roughly every 30 to 90 days, is known to influence the Asian and Australian monsoons. It can also enhance hurricane activity in the northeast Pacific and Gulf of Mexico, trigger torrential rainfall along the west coast of North America, and affect the onset of El Niño. CVP-funded scientists participated in the DYNAMO field campaign in 2011-12. Results from this international campaign are expected to improve researcher’s insights into this influential phenomenon. A better understanding of the processes governing MJO is an essential step toward

  8. Surface Observation Climatic Summaries for Nellis AFB, Nevada

    DTIC Science & Technology

    1992-05-01

    DISTRIBUTION OF THIS DOMWI! TO THE PUBLIC AT LARGE, OR BY THE DEFENSE TECHNICAL IMKNMTI1M CENTER (DTIC) TO THE NATIOAL T•ECICRL INFO TION SERVICE (NTS). JOSEPH…DOCUMENTS FORMERLY KNOW AS THE REVISED UNIFON4 StlMMRRY OF SURFACE OBSERVATIONS (RUSSW) AND THE LIMITED SURFACE OBSERVATIONS CLIMATIC SWSU.R (LISOCS…RECORD (POR). -SUMMARY OF DAY- (SOD) INFOEATIOR IS SUMMARIZED )FRO ALL AVAILABLE DATA IN THE OL-A, USARETJC CLIMATIC DATABASE. 14. SUBJECT TOM

  9. Response of the Amazon rainforest to late Pleistocene climate variability

    NASA Astrophysics Data System (ADS)

    Häggi, Christoph; Chiessi, Cristiano M.; Merkel, Ute; Mulitza, Stefan; Prange, Matthias; Schulz, Michael; Schefuß, Enno

    2017-12-01

    Variations in Amazonian hydrology and forest cover have major consequences for the global carbon and hydrological cycles as well as for biodiversity. Yet, the climate and vegetation history of the lowland Amazon basin and its effect on biogeography remain debated due to the scarcity of suitable high-resolution paleoclimate records. Here, we use the isotopic composition (δD and δ13C) of plant-waxes from a high-resolution marine sediment core collected offshore the Amazon River to reconstruct the climate and vegetation history of the integrated lowland Amazon basin for the period from 50,000 to 12,800 yr before present. Our results show that δD values from the Last Glacial Maximum were more enriched than those from Marine Isotope Stage (MIS) 3 and the present-day. We interpret this trend to reflect long-term changes in precipitation and atmospheric circulation, with overall drier conditions during the Last Glacial Maximum. Our results thus suggest a dominant glacial forcing of the climate in lowland Amazonia. In addition to previously suggested thermodynamic mechanisms of precipitation change, which are directly related to temperature, we conclude that changes in atmospheric circulation are crucial to explain the temporal evolution of Amazonian rainfall variations, as demonstrated in climate model experiments. Our vegetation reconstruction based on δ13C values shows that the Amazon rainforest was affected by intrusions of savannah or more open vegetation types in its northern sector during Heinrich Stadials, while it was resilient to glacial drying. This suggests that biogeographic patterns in tropical South America were affected by Heinrich Stadials in addition to glacial-interglacial climate variability.

  10. Observing Climate with Satellites – Are We on Thin Ice?

    NASA Technical Reports Server (NTRS)

    Tucker, Compton

    2012-01-01

    The Earth s climate is determined by irradiance from the Sun and properties of the atmosphere, oceans, and land that determine the reflection, absorption, and emission of energy within our atmosphere and at the Earth s surface. Since the 1970s, Earth-viewing satellites have complimented non-satellite geophysical observations with consistent, quantitative, and spatially-continuous measurements that have led to an unprecedented understanding of the Earth s climate system. I will describe the Earth s climate system as elaborated by satellite and in situ observations, review arguments against global warming, and show the convergence of evidence for human-caused warming of our planet.

  11. [Modelling the effect of local climatic variability on dengue transmission in Medellin (Colombia) by means of time series analysis].

    PubMed

    Rúa-Uribe, Guillermo L; Suárez-Acosta, Carolina; Chauca, José; Ventosilla, Palmira; Almanza, Rita

    2013-09-01

    Dengue fever is a major impact on public health vector-borne disease, and its transmission is influenced by entomological, sociocultural and economic factors. Additionally, climate variability plays an important role in the transmission dynamics. A large scientific consensus has indicated that the strong association between climatic variables and disease could be used to develop models to explain the incidence of the disease. To develop a model that provides a better understanding of dengue transmission dynamics in Medellin and predicts increases in the incidence of the disease. The incidence of dengue fever was used as dependent variable, and weekly climatic factors (maximum, mean and minimum temperature, relative humidity and precipitation) as independent variables. Expert Modeler was used to develop a model to better explain the behavior of the disease. Climatic variables with significant association to the dependent variable were selected through ARIMA models. The model explains 34% of observed variability. Precipitation was the climatic variable showing statistically significant association with the incidence of dengue fever, but with a 20 weeks delay. In Medellin, the transmission of dengue fever was influenced by climate variability, especially precipitation. The strong association dengue fever/precipitation allowed the construction of a model to help understand dengue transmission dynamics. This information will be useful to develop appropriate and timely strategies for dengue control.

  12. High-resolution regional climate model evaluation using variable-resolution CESM over California

    NASA Astrophysics Data System (ADS)

    Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

    2015-12-01

    Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California’s diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine

  13. IUE observations of variability in winds from hot stars

    NASA Technical Reports Server (NTRS)

    Grady, C. A.; Snow, T. P., Jr.

    1981-01-01

    Observations of variability in stellar winds or envelopes provide an important probe of their dynamics. For this purpose a number of O, B, Be, and Wolf-Rayet stars were repeatedly observed with the IUE satellite in high resolution mode. In the course of analysis, instrumental and data handling effects were found to introduce spurious variability in many of the spectra. software was developed to partially compensate for these effects, but limitations remain on the type of variability that can be identified from IUE spectra. With these contraints, preliminary results of multiple observations of two OB stars, one Wolf-Rayet star, and a Be star are discussed.

  14. Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

    NASA Astrophysics Data System (ADS)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2010-01-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with

  15. Decoding the spatial signatures of multi-scale climate variability – a climate network perspective

    NASA Astrophysics Data System (ADS)

    Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

    2017-12-01

    During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale – amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results

  16. Impacts of climate variability and future climate change on harmful algal blooms and human health.

    PubMed

    Moore, Stephanie K; Trainer, Vera L; Mantua, Nathan J; Parker, Micaela S; Laws, Edward A; Backer, Lorraine C; Fleming, Lora E

    2008-11-07

    Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes to vertical mixing, upwelling, precipitation, and evaporation patterns. The potential consequences of these changes for harmful algal blooms (HABs) have received relatively little attention and are not well understood. Given the apparent increase in HABs around the world and the potential for greater problems as a result of climate change and ocean acidification, substantial research is needed to evaluate the direct and indirect associations between HABs, climate change, ocean acidification, and human health. This research will require a multidisciplinary approach utilizing expertise in climatology, oceanography, biology, epidemiology, and other disciplines. We review the interactions between selected patterns of large-scale climate variability and climate change, oceanic conditions, and harmful algae.

  17. Impacts of climate variability and future climate change on harmful algal blooms and human health

    PubMed Central

    Moore, Stephanie K; Trainer, Vera L; Mantua, Nathan J; Parker, Micaela S; Laws, Edward A; Backer, Lorraine C; Fleming, Lora E

    2008-01-01

    Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes to vertical mixing, upwelling, precipitation, and evaporation patterns. The potential consequences of these changes for harmful algal blooms (HABs) have received relatively little attention and are not well understood. Given the apparent increase in HABs around the world and the potential for greater problems as a result of climate change and ocean acidification, substantial research is needed to evaluate the direct and indirect associations between HABs, climate change, ocean acidification, and human health. This research will require a multidisciplinary approach utilizing expertise in climatology, oceanography, biology, epidemiology, and other disciplines. We review the interactions between selected patterns of large-scale climate variability and climate change, oceanic conditions, and harmful algae. PMID:19025675

  18. Smoothing of millennial scale climate variability in European Loess (and other records)

    NASA Astrophysics Data System (ADS)

    Zeeden, Christian; Obreht, Igor; Hambach, Ulrich; Veres, Daniel; Marković, Slobodan B.; Lehmkuhl, Frank

    2017-04-01

    Millennial scale climate variability is seen in various records of the northern hemisphere in the last glacial cycle, and their expression represents a correlation tool beyond the resolution of e.g. luminescence dating. Highest (correlative) dating accuracy is a prerequisite of comparing different geoarchives, especially when related to archaeological findings. Here we attempt to constrain the timing of loess geoarchives representing the environmental context of early humans in south-eastern Europe, and discuss the challenge of dealing with smoothed records. In this contribution, we present rock magnetic and grain size data from the Rasova loess record in the Lower Danube basin (Romania), showing millennial scale climate variability. Additionally, we summarize similar data from the Lower and Middle Danube Basins. A comparison of these loess data and reference records from Greenland ice cores and the Mediterranean-Black Sea region indicates a rather unusual expression of millennial scale climate variability recorded in loess. To explain the observed patterns, we experiment with low-pass filters of reference records to simulate a signal smoothing by natural processes such as e.g. bioturbation and pervasive diagenesis. Low-pass filters avoid high frequency oscillations and focus on the longer period (lower frequency) variability, here using cut-off periods from 1-15 kyr. In our opinion low-pass filters represent simple models for the expression of millennial scale climate variability in low sedimentation environments, and in sediments where signals are smoothed by e.g. bioturbation and/or diagenesis. Using different low-pass filter thresholds allows us to (a) explain observed patterns and their relation to millennial scale climate variability, (b) propose these filtered/smoothed signals as correlation targets for records lacking millennial scale recording, but showing smoothed climate variability on supra-millennial scales, and (c) determine which time resolution

  19. Internal variability of a dynamically downscaled climate over North America

    NASA Astrophysics Data System (ADS)

    Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

    2018-06-01

    This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

  20. Multidecadal climate variability of global lands and oceans

    USGS Publications Warehouse

    McCabe, G.J.; Palecki, M.A.

    2006-01-01

    Principal components analysis (PCA) and singular value decomposition (SVD) are used to identify the primary modes of decadal and multidecadal variability in annual global Palmer Drought Severity Index (PDSI) values and sea-surface temperature (SSTs). The PDSI and SST data for 1925-2003 were detrended and smoothed (with a 10-year moving average) to isolate the decadal and multidecadal variability. The first two principal components (PCs) of the PDSI PCA explained almost 38% of the decadal and multidecadal variance in the detrended and smoothed global annual PDSI data. The first two PCs of detrended and smoothed global annual SSTs explained nearly 56% of the decadal variability in global SSTs. The PDSI PCs and the SST PCs are directly correlated in a pairwise fashion. The first PDSI and SST PCs reflect variability of the detrended and smoothed annual Pacific Decadal Oscillation (PDO), as well as detrended and smoothed annual Indian Ocean SSTs. The second set of PCs is strongly associated with the Atlantic Multidecadal Oscillation (AMO). The SVD analysis of the cross-covariance of the PDSI and SST data confirmed the close link between the PDSI and SST modes of decadal and multidecadal variation and provided a verification of the PCA results. These findings indicate that the major modes of multidecadal variations in SSTs and land-surface climate conditions are highly interrelated through a small number of spatially complex but slowly varying teleconnections. Therefore, these relations may be adaptable to providing improved baseline conditions for seasonal climate forecasting. Published in 2006 by John Wiley & Sons, Ltd.

  1. Internal variability of a dynamically downscaled climate over North America

    SciTech Connect

    Wang, Jiali; Bessac, Julie; Kotamarthi, Rao

    This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 km and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemblemore » during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.« less

  2. Internal variability of a dynamically downscaled climate over North America

    SciTech Connect

    Wang, Jiali; Bessac, Julie; Kotamarthi, Rao

    This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble duringmore » the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.« less

  3. Internal variability of a dynamically downscaled climate over North America

    NASA Astrophysics Data System (ADS)

    Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

    2017-09-01

    This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

  4. Two centuries of observed atmospheric variability and change over the North Sea region

    NASA Astrophysics Data System (ADS)

    Stendel, Martin; van den Besselaar, Else; Hannachi, Abdel; Kent, Elizabeth; Lefebvre, Christiana; van Oldenborgh, Geert Jan; Rosenhagen, Gudrun; Schenk, Frederik; van der Schrier, Gerard

    2015-04-01

    Situated in northwestern Europe, the North Sea region is under influence of air masses from subtropical to arctic origin, and thus exhibits significant natural climate variability. As the land areas surrounding the North Sea are densely populated, climate change is an important issue in terms of e.g. coastal protection, fishery and trade. This study is part of the NOSCCA initiative (North Sea Region Climate Change Assessment) and presents observed variability and changes in atmospheric parameters during the last roughly 200 years. Circulation patterns show considerable decadal variability. In recent decades, a northward shift of storm tracks and increased cyclonic activity has been observed. There is also an indication of increased persistence of weather types. The wind climate is dominated by large multidecadal variability, and no robust long-term trends can be identified in the available datasets. There is a clear positive trend in near-surface temperatures, in particular during spring and winter. Over the region as a whole, no clear long-term precipitation trends are visible, although regional indications exist for an increased risk of extreme precipitation events.

  5. The Safe Yield and Climatic Variability: Implications for Groundwater Management.

    PubMed

    Loáiciga, Hugo A

    2017-05-01

    Methods for calculating the safe yield are evaluated in this paper using a high-quality and long historical data set of groundwater recharge, discharge, extraction, and precipitation in a karst aquifer. Consideration is given to the role that climatic variability has on the determination of a climatically representative period with which to evaluate the safe yield. The methods employed to estimate the safe yield are consistent with its definition as a long-term average extraction rate that avoids adverse impacts on groundwater. The safe yield is a useful baseline for groundwater planning; yet, it is herein shown that it is not an operational rule that works well under all climatic conditions. This paper shows that due to the nature of dynamic groundwater processes it may be most appropriate to use an adaptive groundwater management strategy that links groundwater extraction rates to groundwater discharge rates, thus achieving a safe yield that represents an estimated long-term sustainable yield. An example of the calculation of the safe yield of the Edwards Aquifer (Texas) demonstrates that it is about one-half of the average annual recharge. © 2016, National Ground Water Association.

  6. Farmers’ Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China.

    PubMed

    Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; Zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

    2016-05-01

    Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers’ perceptions of climate variability and adaptation. Yet, without an understanding of farmers’ perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers’ perceptions of climate variability. We found that farmers’ were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers’ characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads’ education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers’ perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China’s agricultural assets.

  7. Farmers’ Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China

    NASA Astrophysics Data System (ADS)

    Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

    2016-05-01

    Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers’ perceptions of climate variability and adaptation. Yet, without an understanding of farmers’ perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers’ perceptions of climate variability. We found that farmers’ were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers’ characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads’ education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers’ perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China’s agricultural assets.

  8. Trends in Extreme Rainfall Frequency in the Contiguous United States: Attribution to Climate Change and Climate Variability Modes

    NASA Astrophysics Data System (ADS)

    Armal, S.; Devineni, N.; Khanbilvardi, R.

    2017-12-01

    This study presents a systematic analysis for identifying and attributing trends in the annual frequency of extreme rainfall events across the contiguous United States to climate change and climate variability modes. A Bayesian multilevel model is developed for 1,244 stations simultaneously to test the null hypothesis of no trend and verify two alternate hypotheses: Trend can be attributed to changes in global surface temperature anomalies, or to a combination of cyclical climate modes with varying quasi-periodicities and global surface temperature anomalies. The Bayesian multilevel model provides the opportunity to pool information across stations and reduce the parameter estimation uncertainty, hence identifying the trends better. The choice of the best alternate hypotheses is made based on Watanabe-Akaike Information Criterion, a Bayesian pointwise predictive accuracy measure. Statistically significant time trends are observed in 742 of the 1,244 stations. Trends in 409 of these stations can be attributed to changes in global surface temperature anomalies. These stations are predominantly found in the Southeast and Northeast climate regions. The trends in 274 of these stations can be attributed to the El Nino Southern Oscillations, North Atlantic Oscillation, Pacific Decadal Oscillation and Atlantic Multi-Decadal Oscillation along with changes in global surface temperature anomalies. These stations are mainly found in the Northwest, West and Southwest climate regions.

  9. Explaining European fungal fruiting phenology with climate variability.

    PubMed

    Andrew, Carrie; Heegaard, Einar; Høiland, Klaus; Senn-Irlet, Beatrice; Kuyper, Thomas W; Krisai-Greilhuber, Irmgard; Kirk, Paul M; Heilmann-Clausen, Jacob; Gange, Alan C; Egli, Simon; Bässler, Claus; Büntgen, Ulf; Boddy, Lynne; Kauserud, Håvard

    2018-06-01

    Here we assess the impact of geographically dependent (latitude, longitude, and altitude) changes in bioclimatic (temperature, precipitation, and primary productivity) variability on fungal fruiting phenology across Europe. Two main nutritional guilds of fungi, saprotrophic and ectomycorrhizal, were further separated into spring and autumn fruiters. We used a path analysis to investigate how biogeographic patterns in fungal fruiting phenology coincided with seasonal changes in climate and primary production. Across central to northern Europe, mean fruiting varied by approximately 25 d, primarily with latitude. Altitude affected fruiting by up to 30 d, with spring delays and autumnal accelerations. Fruiting was as much explained by the effects of bioclimatic variability as by their large-scale spatial patterns. Temperature drove fruiting of autumnal ectomycorrhizal and saprotrophic groups as well as spring saprotrophic groups, while primary production and precipitation were major drivers for spring-fruiting ectomycorrhizal fungi. Species-specific phenology predictors were not stable, instead deviating from the overall mean. There is significant likelihood that further climatic change, especially in temperature, will impact fungal phenology patterns at large spatial scales. The ecological implications are diverse, potentially affecting food webs (asynchrony), nutrient cycling and the timing of nutrient availability in ecosystems. © 2018 by the Ecological Society of America.

  10. Impact of Variable-Resolution Meshes on Regional Climate Simulations

    NASA Astrophysics Data System (ADS)

    Fowler, L. D.; Skamarock, W. C.; Bruyere, C. L.

    2014-12-01

    The Model for Prediction Across Scales (MPAS) is currently being used for seasonal-scale simulations on globally-uniform and regionally-refined meshes. Our ongoing research aims at analyzing simulations of tropical convective activity and tropical cyclone development during one hurricane season over the North Atlantic Ocean, contrasting statistics obtained with a variable-resolution mesh against those obtained with a quasi-uniform mesh. Analyses focus on the spatial distribution, frequency, and intensity of convective and grid-scale precipitations, and their relative contributions to the total precipitation as a function of the horizontal scale. Multi-month simulations initialized on May 1st 2005 using ERA-Interim re-analyses indicate that MPAS performs satisfactorily as a regional climate model for different combinations of horizontal resolutions and transitions between the coarse and refined meshes. Results highlight seamless transitions for convection, cloud microphysics, radiation, and land-surface processes between the quasi-uniform and locally- refined meshes, despite the fact that the physics parameterizations were not developed for variable resolution meshes. Our goal of analyzing the performance of MPAS is twofold. First, we want to establish that MPAS can be successfully used as a regional climate model, bypassing the need for nesting and nudging techniques at the edges of the computational domain as done in traditional regional climate modeling. Second, we want to assess the performance of our convective and cloud microphysics parameterizations as the horizontal resolution varies between the lower-resolution quasi-uniform and higher-resolution locally-refined areas of the global domain.

  11. Impact of Variable-Resolution Meshes on Regional Climate Simulations

    NASA Astrophysics Data System (ADS)

    Fowler, L. D.; Skamarock, W. C.; Bruyere, C. L.

    2013-12-01

    The Model for Prediction Across Scales (MPAS) is currently being used for seasonal-scale simulations on globally-uniform and regionally-refined meshes. Our ongoing research aims at analyzing simulations of tropical convective activity and tropical cyclone development during one hurricane season over the North Atlantic Ocean, contrasting statistics obtained with a variable-resolution mesh against those obtained with a quasi-uniform mesh. Analyses focus on the spatial distribution, frequency, and intensity of convective and grid-scale precipitations, and their relative contributions to the total precipitation as a function of the horizontal scale. Multi-month simulations initialized on May 1st 2005 using NCEP/NCAR re-analyses indicate that MPAS performs satisfactorily as a regional climate model for different combinations of horizontal resolutions and transitions between the coarse and refined meshes. Results highlight seamless transitions for convection, cloud microphysics, radiation, and land-surface processes between the quasi-uniform and locally-refined meshes, despite the fact that the physics parameterizations were not developed for variable resolution meshes. Our goal of analyzing the performance of MPAS is twofold. First, we want to establish that MPAS can be successfully used as a regional climate model, bypassing the need for nesting and nudging techniques at the edges of the computational domain as done in traditional regional climate modeling. Second, we want to assess the performance of our convective and cloud microphysics parameterizations as the horizontal resolution varies between the lower-resolution quasi-uniform and higher-resolution locally-refined areas of the global domain.

  12. Patterns of interannual climate variability in large marine ecosystems

    NASA Astrophysics Data System (ADS)

    Soares, Helena Cachanhuk; Gherardi, Douglas Francisco Marcolino; Pezzi, Luciano Ponzi; Kayano, Mary Toshie; Paes, Eduardo Tavares

    2014-06-01

    The purpose of this study is to investigate the vulnerability of the Brazilian and western African Large Marine Ecosystems (LMEs) to local and remote forcing, including the Pacific Decadal Oscillation (PDO) regime shift. The analyses are based on the total and partial correlation between climate indices (Niño3, tropical South Atlantic (TSA), tropical North Atlantic (TNA) and Antarctic oscillation (AAO) and oceanic and atmospheric variables (sea surface temperature (SST), wind stress, Ekman transport, sea level pressure and outgoing longwave radiation). Differences in the correlation fields between the cold and warm PDO indicate that this mode exerts a significant impact on the thermodynamic balance of the ocean-atmosphere system on the South Atlantic ocean, mainly in the South Brazil and Benguela LMEs. The PDO regime shift also resulted in an increase in the spatial variability of SST and wind stress anomalies, mainly along the western African LMEs. Another important finding is the strong AAO influence on the SST anomalies (SSTA) in the South Brazil LME. It is also striking that TSA modulates the relation between El Niño-Southern Oscillation (ENSO) and SSTA, by reducing the influence of ENSO on SSTA during the warm PDO period in the North and East Brazil LMEs and in the Guinea Current LME. The relation between AAO and SSTA on the tropical area is also influenced by the TSA. The results shown here give a clear indication that future ecosystem-based management actions aimed at the conservation of marine resources under climate change need to consider the high complexity of basin-scale interactions between local and remote climate forcings, including their effects on the ocean-atmosphere system of the South Atlantic ocean.

  13. Replumbing of the Biological Pump caused by Millennial Climate Variability

    NASA Astrophysics Data System (ADS)

    Galbraith, E.; Sarmiento, J.

    2008-12-01

    It has been hypothesized that millennial-timescale variability in the biological pump was a critical instigator of glacial-interglacial cycles. However, even in the absence of changes in ecosystem function (e.g. due to iron fertilization), determining the mechanisms by which physical climate variability alters the biological pump is not simple. Changes in upper ocean circulation and deep water formation have previously been shown to alter both the downward flux of organic matter and the mass of respired carbon in the ocean interior, often in non- intuitive ways. For example, a reduced upward flux of nutrients at the global scale will decrease the global rate of export production, but it could either increase or decrease the respired carbon content of the ocean interior, depending on where the reduced upward flux of nutrients occurs. Furthermore, viable candidates for physical climate forcing are numerous, including changes in the westerly winds, changes in the depth of the thermocline, and changes in the formation rate of North Atlantic Deep Water, among others. We use a simple, prognostic, light-and temperature-dependent model of biogeochemical cycling within a state-of-the- art global coupled ocean-atmosphere model to examine the response of the biological pump to changes in the coupled Earth system over multiple centuries. The biogeochemical model explicitly distinguishes respired carbon from preformed and saturation carbon, allowing the activity of the biological pump to be clearly quantified. Changes are forced in the model by altering the background climate state, and by manipulating the flux of freshwater to the North Atlantic region. We show how these changes in the physical state of the coupled ocean-atmosphere system impact the distribution and mass of respired carbon in the ocean interior, and the relationship these changes bear to global patterns of export production via the redistribution of nutrients.

  14. Linking Indigenous Knowledge and Observed Climate Change Studies

    NASA Technical Reports Server (NTRS)

    Alexander, Chief Clarence; Bynum, Nora; Johnson, Liz; King, Ursula; Mustonen, Tero; Neofotis, Peter; Oettle, Noel; Rosenzweig, Cynthia; Sakakibara, Chie; Shadrin, Chief Vyacheslav; hidehide

    2010-01-01

    We present indigenous knowledge narratives and explore their connections to documented temperature and other climate changes and observed climate change impact studies. We then propose a framework for enhancing integration of these indigenous narratives of observed climate change with global assessments. Our aim is to contribute to the thoughtful and respectful integration of indigenous knowledge with scientific data and analysis, so that this rich body of knowledge can inform science, and so that indigenous and traditional peoples can use the tools and methods of science for the benefit of their communities if they choose to do so. Enhancing ways of understanding such connections are critical as the Intergovernmental Panel on Climate Change Fifth Assessment process gets underway.

  15. The Impact of Ocean Observations in Seasonal Climate Prediction

    NASA Technical Reports Server (NTRS)

    Rienecker, Michele; Keppenne, Christian; Kovach, Robin; Marshak, Jelena

    2010-01-01

    The ocean provides the most significant memory for the climate system. Hence, a critical element in climate forecasting with coupled models is the initialization of the ocean with states from an ocean data assimilation system. Remotely-sensed ocean surface fields (e.g., sea surface topography, SST, winds) are now available for extensive periods and have been used to constrain ocean models to provide a record of climate variations. Since the ocean is virtually opaque to electromagnetic radiation, the assimilation of these satellite data is essential to extracting the maximum information content. More recently, the Argo drifters have provided unprecedented sampling of the subsurface temperature and salinity. Although the duration of this observation set has been too short to provide solid statistical evidence of its impact, there are indications that Argo improves the forecast skill of coupled systems. This presentation will address the impact these different observations have had on seasonal climate predictions with the GMAO’s coupled model.

  16. Quantifying the Hydrologic Effect of Climate Variability in the Lower Colorado Basin

    NASA Astrophysics Data System (ADS)

    Switanek, M.; Troch, P. A.

    2007-12-01

    Regional climate patterns are driven in large part by ocean states and associated atmospheric circulations, but modified through feedbacks from land surface conditions. The latter defines the climate elasticity of a river basin. Many regions that lie between semi-arid and semi-humid zones with seasonal rainfall, for instance, experience prolonged periods of wet and dry spells. Understanding the triggers that bring a river basin from one state (e.g. wet period of late 90s in the Colorado basin) abruptly to another state (multi-year drought initiated in 2001 to present) is what motivates the present study. Our research methodology investigates the causes of regional climate variability and its effect on hydrologic response. By correlating, using different monthly time lags, sea surface temperatures (SST) and sea level pressures (SLP) with basin averaged precipitation and surface temperature, we determine the most influential regions of the Pacific Ocean on lower Colorado climate variability. Using the most correlated data for each month, we derive precipitation and temperature distributions under similar conditions to that of the El Niño Southern Oscillation (ENSO). We compare the distributions of the climatic data, given ENSO constraints on SST and SLP, to the distributions considering non-ENSO years. Finally, we use observed stream flows and climatic data to determine the basin’s climate elasticity. This allows us to quantitatively translate the predicted regional climate effects of ENSO on hydrologic response. Our presentation will use data for the Little Colorado as an example to demonstrate the procedure and produce preliminary results.

  17. Ice_Sheets_CCI: Essential Climate Variables for the Greenland Ice Sheet

    NASA Astrophysics Data System (ADS)

    Forsberg, R.; Sørensen, L. S.; Khan, A.; Aas, C.; Evansberget, D.; Adalsteinsdottir, G.; Mottram, R.; Andersen, S. B.; Ahlstrøm, A.; Dall, J.; Kusk, A.; Merryman, J.; Hvidberg, C.; Khvorostovsky, K.; Nagler, T.; Rott, H.; Scharrer, M.; Shepard, A.; Ticconi, F.; Engdahl, M.

    2012-04-01

    As part of the ESA Climate Change Initiative (www.esa-cci.org) a long-term project “ice_sheets_cci” started January 1, 2012, in addition to the existing 11 projects already generating Essential Climate Variables (ECV) for the Global Climate Observing System (GCOS). The “ice_sheets_cci” goal is to generate a consistent, long-term and timely set of key climate parameters for the Greenland ice sheet, to maximize the impact of European satellite data on climate research, from missions such as ERS, Envisat and the future Sentinel satellites. The climate parameters to be provided, at first in a research context, and in the longer perspective by a routine production system, would be grids of Greenland ice sheet elevation changes from radar altimetry, ice velocity from repeat-pass SAR data, as well as time series of marine-terminating glacier calving front locations and grounding lines for floating-front glaciers. The ice_sheets_cci project will involve a broad interaction of the relevant cryosphere and climate communities, first through user consultations and specifications, and later in 2012 optional participation in “best” algorithm selection activities, where prototype climate parameter variables for selected regions and time frames will be produced and validated using an objective set of criteria (“Round-Robin intercomparison”). This comparative algorithm selection activity will be completely open, and we invite all interested scientific groups with relevant experience to participate. The results of the “Round Robin” exercise will form the algorithmic basis for the future ECV production system. First prototype results will be generated and validated by early 2014. The poster will show the planned outline of the project and some early prototype results.

  18. The contribution of natural variability to GCM bias: Can we effectively bias-correct climate projections?

    NASA Astrophysics Data System (ADS)

    McAfee, S. A.; DeLaFrance, A.

    2017-12-01

    Investigating the impacts of climate change often entails using projections from inherently imperfect general circulation models (GCMs) to drive models that simulate biophysical or societal systems in great detail. Error or bias in the GCM output is often assessed in relation to observations, and the projections are adjusted so that the output from impacts models can be compared to historical or observed conditions. Uncertainty in the projections is typically accommodated by running more than one future climate trajectory to account for differing emissions scenarios, model simulations, and natural variability. The current methods for dealing with error and uncertainty treat them as separate problems. In places where observed and/or simulated natural variability is large, however, it may not be possible to identify a consistent degree of bias in mean climate, blurring the lines between model error and projection uncertainty. Here we demonstrate substantial instability in mean monthly temperature bias across a suite of GCMs used in CMIP5. This instability is greatest in the highest latitudes during the cool season, where shifts from average temperatures below to above freezing could have profound impacts. In models with the greatest degree of bias instability, the timing of regional shifts from below to above average normal temperatures in a single climate projection can vary by about three decades, depending solely on the degree of bias assessed. This suggests that current bias correction methods based on comparison to 20- or 30-year normals may be inappropriate, particularly in the polar regions.

  19. Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records

    NASA Astrophysics Data System (ADS)

    Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

    2016-02-01

    An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation-climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America – 2k initiative that provides the ideal

  20. The effects of variable biome distribution on global climate

    SciTech Connect

    Noever, D.A.; Brittain, A.; Matsos, H.C.

    1996-12-31

    In projecting climatic adjustments to anthropogenically elevated atmospheric carbon dioxide, most global climate models fix biome distribution to current geographic conditions. The authors develop a model that examines the albedo-related effects of biome distribution on global temperature. The model was tested on historical biome changes since 1860 and the results fit both the observed trend and order of magnitude change in global temperature. Once backtested in this way on historical data, the model is then used to generate an optimized future biome distribution which minimizes projected greenhouse effects on global temperature. Because of the complexity of this combinatorial search anmore » artificial intelligence method, the genetic algorithm, was employed. The genetic algorithm assigns various biome distributions to the planet, then adjusts their percentage area and albedo effects to regulate or moderate temperature changes.« less

  1. Role of internal variability in recent decadal to multidecadal tropical Pacific climate changes

    NASA Astrophysics Data System (ADS)

    Bordbar, Mohammad Hadi; Martin, Thomas; Latif, Mojib; Park, Wonsun

    2017-05-01

    While the Earth’s surface has considerably warmed over the past two decades, the tropical Pacific has featured a cooling of sea surface temperatures in its eastern and central parts, which went along with an unprecedented strengthening of the equatorial trade winds, the surface component of the Pacific Walker Circulation (PWC). Previous studies show that this decadal trend in the trade winds is generally beyond the range of decadal trends simulated by climate models when forced by historical radiative forcing. There is still a debate on the origin of and the potential role that internal variability may have played in the recent decadal surface wind trend. Using a number of long control (unforced) integrations of global climate models and several observational data sets, we address the question as to whether the recent decadal to multidecadal trends are robustly classified as an unusual event or the persistent response to external forcing. The observed trends in the tropical Pacific surface climate are still within the range of the long-term internal variability spanned by the models but represent an extreme realization of this variability. Thus, the recent observed decadal trends in the tropical Pacific, though highly unusual, could be of natural origin. We note that the long-term trends in the selected PWC indices exhibit a large observational uncertainty, even hindering definitive statements about the sign of the trends.Plain Language SummaryWhile the Earth’s surface has considerably warmed over the past two decades, the tropical Pacific has featured a cooling of sea surface temperatures in its eastern and central parts, which went along with an unprecedented strengthening of the equatorial trade winds. Here we show that climate models simulate a high level of internal variability, so that the recent changes in the tropical Pacific could still be due to natural processes.

  2. On the Reprocessing and Reanalysis of Observations for Climate

    NASA Technical Reports Server (NTRS)

    Bosilovich, Michael G.; Kennedy, John; Dee, Dick; ONeill, Alan

    2012-01-01

    The long observational record is critical to our understanding of the Earth s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. WCRP provides the means to bridge the different motivating objectives on which national efforts focus.

  3. Application of Climate Assessment Tool (CAT) to estimate climate variability impacts on nutrient loading from local watersheds

    Treesearch

    Ying Ouyang; Prem B. Parajuli; Gary Feng; Theodor D. Leininger; Yongshan Wan; Padmanava Dash

    2018-01-01

    A vast amount of future climate scenario datasets, created by climate models such as general circulation models (GCMs), have been used in conjunction with watershed models to project future climate variability impact on hydrological processes and water quality. However, these low spatial-temporal resolution datasets are often difficult to downscale spatially and…

  4. Climate and climate variability of the wind power resources in the Great Lakes region of the United States

    Treesearch

    X. Li; S. Zhong; X. Bian; W.E. Heilman

    2010-01-01

    The climate and climate variability of low-level winds over the Great Lakes region of the United States is examined using 30 year (1979-2008) wind records from the recently released North American Regional Reanalysis (NARR), a three-dimensional, high-spatial and temporal resolution, and dynamically consistent climate data set. The analyses focus on spatial distribution…

  5. Causes and implications of the growing divergence between climate model simulations and observations

    NASA Astrophysics Data System (ADS)

    Curry, Judith

    2014-03-01

    For the past 15+ years, there has been no increase in global average surface temperature, which has been referred to as a ‘hiatus’ in global warming. By contrast, estimates of expected warming in the first several decades of 21st century made by the IPCC AR4 were 0.2C/decade. This talk summarizes the recent CMIP5 climate model simulation results and comparisons with observational data. The most recent climate model simulations used in the AR5 indicate that the warming stagnation since 1998 is no longer consistent with model projections even at the 2% confidence level. Potential causes for the model-observation discrepancies are discussed. A particular focus of the talk is the role of multi-decadal natural internal variability on the climate variability of the 20th and early 21st centuries. The “stadium wave” climate signal is described, which propagates across the Northern Hemisphere through a network of ocean, ice, and atmospheric circulation regimes that self-organize into a collective tempo. The stadium wave hypothesis provides a plausible explanation for the hiatus in warming and helps explain why climate models did not predict this hiatus. Further, the new hypothesis suggests how long the hiatus might last. Implications of the hiatus are discussed in context of climate model sensitivity to CO2 forcing and attribution of the warming that was observed in the last quarter of the 20th century.

  6. Galactic water vapor emission: further observations of variability.

    PubMed

    Knowles, S H; Mayer, C H; Sullivan, W T; Cheung, A C

    1969-10-10

    Recent observations of the 1.35-centimeter line emission of water vapor from galactic sources show short-term variability in the spectra of several sources. Two additional sources, Cygnus 1 and NGC 6334N, have been observed, and the spectra of W49 and VY Canis Majoris were measured over a wider range of radial velocity.

  7. Holocene climate variability and oceanographic changes off western South Africa

    NASA Astrophysics Data System (ADS)

    Zhao, Xueqin; Dupont, Lydie; E Meadows, Michael; Schefuß, Enno; Bouimetarhan, Ilham; Wefer, Gerold

    2017-04-01

    South Africa is located at a critical transition zone between subtropical and warm-temperate climate zones influenced by the Indian and Atlantic oceans. Presently, the seasonal changes of atmospheric and oceanic systems induce a pronounced rainfall seasonality comprised of two different rainfall zones over South Africa. How did this seasonality develop during the Holocene? To obtain a better understanding of how South African climates have evolved during the Holocene, we conduct a comprehensive spatial-temporal approach including pollen and dinoflagellate cyst records from marine sediment samples retrieved from the Namaqualand mudbelt, a Holocene terrigenous mud deposit on the shelf of western South Africa. The representation of different vegetation communities in western South Africa is assessed through pollen analysis of surface sediments. This approach allows for climate reconstructions of the summer rainfall zone (SRZ) using Group 1 (Poaceae, Cyperaceae, Phragmites-type and Typha) and winter rainfall zone (WRZ) using Group 2 (Restionaceae, Ericaceae, Anthospermum, Stoebe/Elytropappus-type, Cliffortia, Passerina, Artemisia-type and Pentzia-type) from a single marine archive. The fossil pollen data from gravity core GeoB8331-4 indicate contrasting climate patterns in the SRZ and WRZ especially during the early and middle Holocene. The rainfall amount in the SRZ is dominated by insolation forcing, while in the WRZ it is mainly attributed to the latitudinal position of the southern westerlies. Dinoflagellate cyst data show significantly different oceanographic conditions associated with climate changes on land. High percentages of autotrophic taxa like Operculodinium centrocarpum and Spiniferites spp. indicate warm and stratified conditions during the early Holocene, suggesting reduced upwelling. In contrast, the middle Holocene is characterized by a strong increase in heterotrophic taxa in particular Lejeunecysta paratenella and Echinidinium spp., indicating cool

  8. Central Tropical Pacific Variability And ENSO Response To Changing Climate Boundary Conditions: Evidence From Individual Line Island Foraminifera

    NASA Astrophysics Data System (ADS)

    Rustic, G. T.; Polissar, P. J.; Ravelo, A. C.; White, S. M.

    2017-12-01

    The El Niño Southern Oscillation (ENSO) plays a dominant role in Earth’s climate variability. Paleoceanographic evidence suggests that ENSO has changed in the past, and these changes have been linked to large-scale climatic shifts. While a close relationship between ENSO evolution and climate boundary conditions has been predicted, testing these predictions remains challenging. These climate boundary conditions, including insolation, the mean surface temperature gradient of the tropical Pacific, global ice volume, and tropical thermocline depth, often co-vary and may work together to suppress or enhance the ocean-atmosphere feedbacks that drive ENSO variability. Furthermore, suitable paleo-archives spanning multiple climate states are sparse. We have aimed to test ENSO response to changing climate boundary conditions by generating new reconstructions of mixed-layer variability from sedimentary archives spanning the last three glacial-interglacial cycles from the Central Tropical Pacific Line Islands, where El Niño is strongly expressed. We analyzed Mg/Ca ratios from individual foraminifera to reconstruct mixed-layer variability at discrete time intervals representing combinations of climatic boundary conditions from the middle Holocene to Marine Isotope Stage (MIS) 8. We observe changes in the mixed-layer temperature variability during MIS 5 and during the previous interglacial (MIS 7) showing significant reductions in ENSO amplitude. Differences in variability during glacial and interglacial intervals are also observed. Additionally, we reconstructed mixed-layer and thermocline conditions using multi-species Mg/Ca and stable isotope measurements to more fully characterize the state of the Central Tropical Pacific during these intervals. These reconstructions provide us with a unique view of Central Tropical Pacific variability and water-column structure at discrete intervals under varying boundary climate conditions with which to assess factors that shape ENSO

  9. Spatial variability in forest growth—climate relationships in the Olympic Mountains, Washington.

    Treesearch

    Jill M. Nakawatase; David L. Peterson

    2006-01-01

    For many Pacific Northwest forests, little is known about the spatial and temporal variability in tree growth – climate relationships, yet it is this information that is needed to predict how forests will respond to future climatic change. We studied the effects of climatic variability on forest growth at 74 plots in the western and northeastern Olympic Mountains….

  10. Spectral Kernel Approach to Study Radiative Response of Climate Variables and Interannual Variability of Reflected Solar Spectrum

    NASA Technical Reports Server (NTRS)

    Jin, Zhonghai; Wielicki, Bruce A.; Loukachine, Constantin; Charlock, Thomas P.; Young, David; Noeel, Stefan

    2011-01-01

    The radiative kernel approach provides a simple way to separate the radiative response to different climate parameters and to decompose the feedback into radiative and climate response components. Using CERES/MODIS/Geostationary data, we calculated and analyzed the solar spectral reflectance kernels for various climate parameters on zonal, regional, and global spatial scales. The kernel linearity is tested. Errors in the kernel due to nonlinearity can vary strongly depending on climate parameter, wavelength, surface, and solar elevation; they are large in some absorption bands for some parameters but are negligible in most conditions. The spectral kernels are used to calculate the radiative responses to different climate parameter changes in different latitudes. The results show that the radiative response in high latitudes is sensitive to the coverage of snow and sea ice. The radiative response in low latitudes is contributed mainly by cloud property changes, especially cloud fraction and optical depth. The large cloud height effect is confined to absorption bands, while the cloud particle size effect is found mainly in the near infrared. The kernel approach, which is based on calculations using CERES retrievals, is then tested by direct comparison with spectral measurements from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (a different instrument on a different spacecraft). The monthly mean interannual variability of spectral reflectance based on the kernel technique is consistent with satellite observations over the ocean, but not over land, where both model and data have large uncertainty. RMS errors in kernel ]derived monthly global mean reflectance over the ocean compared to observations are about 0.001, and the sampling error is likely a major component.

  11. Caroline Furness and the Evolution of Visual Variable Star Observing

    NASA Astrophysics Data System (ADS)

    Larsen, Kristine

    2017-01-01

    An Introduction to the Study of Variable Stars by Dr. Caroline Ellen Furness (1869-1936), Director of the Vassar College Observatory, was published in October 2015. Issued in honor of the fiftieth anniversary of the founding of Vassar College, the work was meant to fill a void in the literature, namely as both an introduction to the topic of variable stars as well as a manual explaining how they should be observed and the resulting data analyzed. It was judged to be one of the hundred best books written by an American woman in the last hundred years at the 1933 World’s Fair in Chicago. The book covers the relevant history of and background on types of variable stars, star charts, catalogs, and the magnitude scale, then describes observing techniques, including visual, photographic, and photoelectric photometry. The work finishes with a discussion of light curves and patterns of variability, with a special emphasis on eclipsing binaries and long period variables. Furness’s work is therefore a valuable snapshot of the state of astronomical knowledge, technology, and observing techniques from a century ago. Furness’s book and its reception in the scientific community are analyzed, and parallels with (and departures from) the current advice given by the AAVSO to beginning variable star observers today are highlighted.

  12. Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

    PubMed

    Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

    2017-11-08

    malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention.

  13. Climate variability and salmonellosis in Singapore – A time series analysis.

    PubMed

    Aik, Joel; Heywood, Anita E; Newall, Anthony T; Ng, Lee-Ching; Kirk, Martyn D; Turner, Robin

    2018-10-15

    Climate change is expected to bring about global warming and an increase in the frequency of extreme weather events. This may consequently influence the transmission of food-borne diseases. The short term associations between climatic conditions and Salmonella infections are well documented in temperate climates but not in the tropics. We conducted an ecological time series analysis to estimate the short term associations between non-outbreak, non-travel associated reports of Salmonella infections and observed climatic conditions from 2005 to 2015 for Singapore. We used a negative binomial time series regression model to analyse the associations on a weekly scale, controlling for season, long term trend, delayed weather effects, autocorrelation and the period where Salmonella was made legally notifiable. There were a total of 11,324 Salmonella infections reported during our study period. A 1 °C increase in mean ambient air temperature was associated with a 4.3% increase (Incidence Rate Ratio [IRR]: 1.043, 95% confidence interval [CI] = 1.003, 1.084) in reported Salmonella infections in the same week and a 6.3% increase (IRR: 1.063, 95% CI = 1.022, 1.105) three weeks later. A 1% increase in the mean relative humidity was associated with a 1.3% decrease (IRR: 0.987, 95% CI = 0.981, 0.994) in cases six weeks later, while a 10 mm increase in weekly cumulative rainfall was associated with a 0.8% increase (IRR: 1.008, 95% CI = 1.002, 1.015) in cases 2 weeks later but a 0.9% decrease (IRR: 0.991, 95% CI = 0.984, 0.998) in cases 5 weeks later. No thresholds for these weather effects were detected. This study confirms the short-term influence of climatic conditions on Salmonella infections in Singapore and the potential impact of climate change on Salmonellosis in the tropics. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  14. The effects of variable biome distribution on global climate.

    PubMed

    Noever, D A; Brittain, A; Matsos, H C; Baskaran, S; Obenhuber, D

    1996-01-01

    In projecting climatic adjustments to anthropogenically elevated atmospheric carbon dioxide, most global climate models fix biome distribution to current geographic conditions. Previous biome maps either remain unchanging or shift without taking into account climatic feedbacks such as radiation and temperature. We develop a model that examines the albedo-related effects of biome distribution on global temperature. The model was tested on historical biome changes since 1860 and the results fit both the observed temperature trend and order of magnitude change. The model is then used to generate an optimized future biome distribution that minimizes projected greenhouse effects on global temperature. Because of the complexity of this combinatorial search, an artificial intelligence method, the genetic algorithm, was employed. The method is to adjust biome areas subject to a constant global temperature and total surface area constraint. For regulating global temperature, oceans are found to dominate continental biomes. Algal beds are significant radiative levers as are other carbon intensive biomes including estuaries and tropical deciduous forests. To hold global temperature constant over the next 70 years this simulation requires that deserts decrease and forested areas increase. The effect of biome change on global temperature is revealed as a significant forecasting factor.

  15. Near-infrared observations of the variable crab nebula

    NASA Astrophysics Data System (ADS)

    Yamamoto, M.; Mori, K.; Shibata, S.; Tsujimoto, M.; Misawa, T.; Burrows, D.; Kawai, N.

    We present three near-infrared NIR observations of the Crab Nebula obtained with CISCO on the Subaru Telescope and Quick Infrared Camera on the University of HAWAII 88 inch Telescope The observations were performed on 2004 September 2005 February and 2005 October and were coordinated with X-ray observations obtained with the Chandra X-ray observatory within 10 days As shown in previous optical and X-ray monitoring observations outward-moving wisps and variable knots are detected also in our NIR observations The NIR variations are closely correlated with variations in the X-ray observations indicating that both variations are driven by the same physical process We discuss the origin of NIR-emitting particles based on the temporal variations as well as the spectral energy distributions of each variable component

  16. Century to Millennium-Scale Late Quaternary Natural Climate Variability in the Midwestern United States

    NASA Astrophysics Data System (ADS)

    Jaumann, Peter Josef

    1995-01-01

    Estimates of past natural climatic variability on long time scales (centuries to millennia) are crucial in testing climate models. The process of model validation takes advantage of long general circulation model (GCM) integrations, instrumental and satellite observations, and paleoclimatic records. Here I use paleoclimatic proxy records from central North America spanning the last 150 ka to characterize climatic variability on sub-orbital time scales. A terrestrial last interglacial (~ 130 to 75 kyr BP) pollen sequence from south-central Illinois, U.S.A., contains climatic variance in frequency bands between 1 cycle/10 kyr and 1 cycle/1 kyr. The temporal variance is best developed as alternating cycles of pollen assemblages indicative of wet and dry conditions. Spectral cross-correlations between selected pollen types and potential forcings (ETP (eccentricity, tilt, precession), SPECMAP delta^O) implicate oceanic and solar processes as possible mechanisms driving last interglacial vegetation and climate change in the Midwestern U.S. During the last glacial stage (LGS; 20 to 16 kyr BP) a lacustrine sequence from the central Mississippi River valley experienced major flooding events caused by intermittent melting of the Laurentide ice sheet. Rock -magnetic and grain size data confirm the physical record of flood clays. Correlation of the flood clays to the Greenland (GRIP) ice core is weak. However, the Laurentide melting events seem to fall temporally between the releases of minor LGS iceberg discharges into the North Atlantic. The GRIP delta^O and the Midwestern U.S. magnetic susceptibility time series indicate sub-Milankovitch climate variability modes. Mapping, multivariate, and time series analyses of Holocene (8 to 1 ka) pollen sequences from central North America suggest spatial patterns of vegetation and climate change on sub-orbital to millennial time scales. The rate, magnitude, and spatial patterns of change varied considerably over the study

  17. Nevada Monitoring System to Assess Climate Variability and Change

    NASA Astrophysics Data System (ADS)

    Devitt, D. A.; Arnone, J.; Biondi, F.; Fenstermaker, L. F.; Saito, L.; Young, M.; Riddle, B.; Strachan, S. D.; Bird, B.; McCurdy, G.; Lyles, B. F.

    2010-12-01

    The Nevada System of Higher Education (University of Nevada Las Vegas, University of Nevada Reno and the Desert Research Institute) was awarded a multiyear NSF EPSCoR grant to support infrastructure associated with regional climate change research. The overall project is comprised of 5 components: education, cyberinfrastructure, policy, climate modeling and water/ecology. The water and ecology components are using their infrastructure funding for the assessment of climate variability and change on ecosystem function and hydrologic services. A series of 10 m tall towers are under construction and are being equipped with a wide array of sensors to monitor atmospheric, soil and plant parameters over time. The towers are located within the Mojave and Great Basin Deserts in two transects; the Mojave Desert transect is located in the southern Nevada Sheep Mountain Range and the Great Basin transect is located in the east central Nevada Snake Mountain Range. The towers are centrally positioned in well-defined vegetation zones. In southern Nevada these zones are represented by the following plant species: Creosote/Bursage (Creosotebush scrub zone); Blackbrush/Joshua Tree (Blackbrush zone); Pinyon/ Juniper (pygmy conifer zone), Ponderosa Pine (montane zone) and Bristlecone Pine (subalpine zone). The Snake Mountain transect incorporates the eastern and western valleys on both sides of the mountain range. The vegetation zones are represented by: Greasewood and mixed shrub (salt desert zone); Big Sage (sagebrush zone); Pinyon/Juniper (pygmy conifer zone); White/Douglas Fir, Ponderosa Pine and Aspen (montane zone); and Bristlecone/Limber Pine and Engelmann Spruce (subalpine zone). We are currently in the third year of funding with a goal of having the majority of towers fully operational by winter 2010. In close collaboration with our cyberinfrastructure component team, all data acquired from the transect monitoring stations will be made available to other researchers and the

  18. Climate variability and dengue fever in warm and humid Mexico.

    PubMed

    Colón-González, Felipe J; Lake, Iain R; Bentham, Graham

    2011-05-01

    Multiple linear regression models were fitted to look for associations between changes in the incidence rate of dengue fever and climate variability in the warm and humid region of Mexico. Data were collected for 12 Mexican provinces over a 23-year period (January 1985 to December 2007). Our results show that the incidence rate or risk of infection is higher during El Niño events and in the warm and wet season. We provide evidence to show that dengue fever incidence was positively associated with the strength of El Niño and the minimum temperature, especially during the cool and dry season. Our study complements the understanding of dengue fever dynamics in the region and may be useful for the development of early warning systems.

  19. Stochastic investigation of temperature process for climatic variability identification

    NASA Astrophysics Data System (ADS)

    Lerias, Eleutherios; Kalamioti, Anna; Dimitriadis, Panayiotis; Markonis, Yannis; Iliopoulou, Theano; Koutsoyiannis, Demetris

    2016-04-01

    The temperature process is considered as the most characteristic hydrometeorological process and has been thoroughly examined in the climate-change framework. We use a dataset comprising hourly temperature and dew point records to identify statistical variability with emphasis on the last period. Specifically, we investigate the occurrence of mean, maximum and minimum values and we estimate statistical properties such as marginal probability distribution function and the type of decay of the climacogram (i.e., mean process variance vs. scale) for various time periods. Acknowledgement: This research is conducted within the frame of the undergraduate course “Stochastic Methods in Water Resources” of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

  20. Stochastic investigation of wind process for climatic variability identification

    NASA Astrophysics Data System (ADS)

    Deligiannis, Ilias; Tyrogiannis, Vassilis; Daskalou, Olympia; Dimitriadis, Panayiotis; Markonis, Yannis; Iliopoulou, Theano; Koutsoyiannis, Demetris

    2016-04-01

    The wind process is considered one of the hydrometeorological processes that generates and drives the climate dynamics. We use a dataset comprising hourly wind records to identify statistical variability with emphasis on the last period. Specifically, we investigate the occurrence of mean, maximum and minimum values and we estimate statistical properties such as marginal probability distribution function and the type of decay of the climacogram (i.e., mean process variance vs. scale) for various time periods. Acknowledgement: This research is conducted within the frame of the undergraduate course “Stochastic Methods in Water Resources” of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

  1. Climate Variability and Dengue Fever in Warm and Humid Mexico

    PubMed Central

    Colón-González, Felipe J.; Lake, Iain R.; Bentham, Graham

    2011-01-01

    Multiple linear regression models were fitted to look for associations between changes in the incidence rate of dengue fever and climate variability in the warm and humid region of Mexico. Data were collected for 12 Mexican provinces over a 23-year period (January 1985 to December 2007). Our results show that the incidence rate or risk of infection is higher during El Niño events and in the warm and wet season. We provide evidence to show that dengue fever incidence was positively associated with the strength of El Niño and the minimum temperature, especially during the cool and dry season. Our study complements the understanding of dengue fever dynamics in the region and may be useful for the development of early warning systems. PMID:21540386

  2. The Response of Ice Sheets to Climate Variability

    NASA Astrophysics Data System (ADS)

    Snow, K.; Goldberg, D. N.; Holland, P. R.; Jordan, J. R.; Arthern, R. J.; Jenkins, A.

    2017-12-01

    West Antarctic Ice Sheet loss is a significant contributor to sea level rise. While the ice loss is thought to be triggered by fluctuations in oceanic heat at the ice shelf bases, ice sheet response to ocean variability remains poorly understood. Using a synchronously coupled ice-ocean model permitting grounding line migration, this study evaluates the response of an ice sheet to periodic variations in ocean forcing. Resulting oscillations in grounded ice volume amplitude is shown to grow as a nonlinear function of ocean forcing period. This implies that slower oscillations in climatic forcing are disproportionately important to ice sheets. The ice shelf residence time offers a critical time scale, above which the ice response amplitude is a linear function of ocean forcing period and below which it is quadratic. These results highlight the sensitivity of West Antarctic ice streams to perturbations in heat fluxes occurring at decadal time scales.

  3. Investigating the Contribution of Climate Variables to Estimates of Net Primary Productivity in a Tropical Ecosystem in India

    NASA Astrophysics Data System (ADS)

    Tripathi, P.; Behera, M. D.; Behera, S. K.; Sahu, N.

    2016-12-01

    Investigating the impact of climate variables on net primary productivity is crucial to evaluate the ecosystem health and the status of forest type response to climate change. The objective of this paper is (1) to analyze the spatio-temporal pattern of net primary productivity (NPP) in a tropical forest ecosystem situated along the Himalayan foothills in India and (2) to investigate the continuous and delayed effects of climatic variables. Weapplied simple Monteith equation based Light use efficiency model for two dominant plant functional types; sal (Shorea robusta) forest and teak (Tectona grandis) plantation to estimate the NPP for a decadal period from 2001 to 2010. The impact of climate variables on NPP for these 10 years was seen by applying two correlation analyses; generalized linear modelling (GLM) and time lag correlation approach.The impact of different climate variables was observed to vary throughout the study period.A decline in mean NPP during 2002-2003, 2005 and 2008 to 2010 could be attributed to drought, increased vapour pressure deficit, and decreased humidity and solar radiation. In time lag correlation analysis, precipitation and humidity were observed to be the major variables affecting NPP; whereas combination of temperature, humidity and VPD showed dominant effect on NPP in GLM. Shorea robusta forest showed slightly higher NPP than that of Tectona grandis plantation throughout the study period. Highest decrease in NPP was observed during 2010,pertaining to lower solar radiation, humidity and precipitation along with increased VPD.Higher gains in NPP by sal during all years indicates their better adaptability to climate compared to teak. Contribution of different climatic variables through some link process is revealed in statistical analysis clearly indicates the co-dominance of all the variables in explaining NPP. Lacking of site specific meteorological observations and microclimate put constraint on broad level analyses.

  4. Climate variability, weather and enteric disease incidence in New Zealand: time series analysis.

    PubMed

    Lal, Aparna; Ikeda, Takayoshi; French, Nigel; Baker, Michael G; Hales, Simon

    2013-01-01

    Evaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases. To examine the associations between regional climate variability and enteric disease incidence in New Zealand. Associations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models. No climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β = 0.130, SE = 0.060, p observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.

  5. Understanding climate variability and global climate change using high-resolution GCM simulations

    NASA Astrophysics Data System (ADS)

    Feng, Xuelei

    In this study, three climate processes are examined using long-term simulations from multiple climate models with increasing horizontal resolutions. These simulations include the European Center for Medium-range Weather Forecasts (ECMWF) atmospheric general circulation model (AGCM) runs forced with observed sea surface temperatures (SST) (the Athena runs) and a set of coupled ocean-atmosphere seasonal hindcasts (the Minerva runs). Both sets of runs use different AGCM resolutions, the highest at 16 km. A pair of the Community Climate System Model (CCSM) simulations with ocean general circulation model (OGCM) resolutions at 100 and 10 km are also examined. The higher resolution CCSM run fully resolves oceanic mesoscale eddies. The resolution influence on the precipitation climatology over the Gulf Stream (GS) region is first investigated. In the Athena simulations, the resolution increase generates enhanced mean GS precipitation moderately in both large-scale and sub-scale rainfalls in the North Atlantic, with the latter more tightly confined near the oceanic front. However, the non-eddy resolving OGCM in the Minerva runs simulates a weaker oceanic front and weakens the mean GS precipitation response. On the other hand, an increase in CCSM oceanic resolutions from non-eddy-resolving to eddy resolving regimes greatly improves the model’s GS precipitation climatology, resulting in both stronger intensity and more realistic structure. Further analyses show that the improvement of the GS precipitation climatology due to resolution increases is caused by the enhanced atmospheric response to an increased SST gradient near the oceanic front, which leads to stronger surface convergence and upper level divergence. Another focus of this study is on the global warming impacts on precipitation characteristic changes using the high-resolution Athena simulations under the SST forcing from the observations and a global warming scenario. As a comparison, results from the coarse

  6. Creating Fidelitious Climate Data Records from Meteosat First Generation Observations

    NASA Astrophysics Data System (ADS)

    Quast, Ralf; Govaerts, Yves; Ruthrich, Frank; Giering, Ralf; Roebeling, Rob

    2016-08-01

    A novel method for reconstructing the spectral response function of the Meteosat visible (VIS) channels is presented and applied to the Meteosat-10 Spinning Enhanced Visible and Infrared Imager (SEVIRI) high-resolution visible (HRV) channel as the first real-world benchmark. The method incorporates advanced radiative transfer modelling and inverse modelling techniques. Once established, EUMETSAT will use the reconstructed spectral response and uncertainty information to increase the calibration accuracy of Meteosat First Generation VIS observations, which will provide the basis for the Fidelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) Horizon 2020 project to produce new fundamental (reflectance) and thematic (albedo and aerosol) climate data records.

  7. Environmental forcing and Southern Ocean marine predator populations: effects of climate change and variability.

    PubMed

    Trathan, P N; Forcada, J; Murphy, E J

    2007-12-29

    The Southern Ocean is a major component within the global ocean and climate system and potentially the location where the most rapid climate change is most likely to happen, particularly in the high-latitude polar regions. In these regions, even small temperature changes can potentially lead to major environmental perturbations. Climate change is likely to be regional and may be expressed in various ways, including alterations to climate and weather patterns across a variety of time-scales that include changes to the long interdecadal background signals such as the development of the El Niño-Southern Oscillation (ENSO). Oscillating climate signals such as ENSO potentially provide a unique opportunity to explore how biological communities respond to change. This approach is based on the premise that biological responses to shorter-term sub-decadal climate variability signals are potentially the best predictor of biological responses over longer time-scales. Around the Southern Ocean, marine predator populations show periodicity in breeding performance and productivity, with relationships with the environment driven by physical forcing from the ENSO region in the Pacific. Wherever examined, these relationships are congruent with mid-trophic-level processes that are also correlated with environmental variability. The short-term changes to ecosystem structure and function observed during ENSO events herald potential long-term changes that may ensue following regional climate change. For example, in the South Atlantic, failure of Antarctic krill recruitment will inevitably foreshadow recruitment failures in a range of higher trophic-level marine predators. Where predator species are not able to accommodate by switching to other prey species, population-level changes will follow. The Southern Ocean, though oceanographically interconnected, is not a single ecosystem and different areas are dominated by different food webs. Where species occupy different positions in

  8. Adaptation of rainfed agriculture to climatic variability in the Mixteca Alta Region of Oaxaca, Mexico

    NASA Astrophysics Data System (ADS)

    Rogé, P.; Friedman, A. R.; Astier, M.; Altieri, M.

    2015-12-01

    The traditional management systems of the Mixteca Alta Region of Oaxaca, Mexico offer historical lessons about resilience to climatic variability. We interviewed small farmers to inquire about the dynamics of abandonment and persistence of a traditional management systems. We interpret farmers’ narratives from a perspective of general agroecological resilience. In addition, we facilitated workshops in small farmers described their adaptation to past climate challenges and identified 14 indicators that they subsequently used to evaluate the condition of their agroecosystems. The most recent years presented increasingly extreme climatic and socioeconomic hardships: increased temperatures, delayed rainy seasons, reduced capacity of soils to retain soil moisture, changing cultural norms, and reduced rural labor. Farmers reported that their cropping systems were changing for multiple reasons: more drought, later rainfall onset, decreased rural labor, and introduced labor-saving technologies. Examination of climate data found that farmers’ climate narratives were largely consistent with the observational record. There have been increases in temperature and rainfall intensity, and an increase in rainfall seasonality that may be perceived as later rainfall onset. Farmers ranked landscape-scale indicators as more marginal than farmer management or soil quality indicators. From this analysis, farmers proposed strategies to improve the ability of their agroecosystems to cope with climatic variability. Notably, they recognized that social organizing and education are required for landscape-level indicators to be improved. Transformative change is required to develop novel cropping systems and complementary activities to agriculture that will allow for farming to be sustained in the face of these challenges. Climate change adaptation by small farmers involves much more than just a set of farming practices, but also community action to tackle collective problems.

  9. Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

    PubMed

    Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

    2015-04-01

    Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran’s I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for

  10. Statistical link between external climate forcings and modes of ocean variability

    NASA Astrophysics Data System (ADS)

    Malik, Abdul; Brönnimann, Stefan; Perona, Paolo

    2017-07-01

    In this study we investigate statistical link between external climate forcings and modes of ocean variability on inter-annual (3-year) to centennial (100-year) timescales using de-trended semi-partial-cross-correlation analysis technique. To investigate this link we employ observations (AD 1854-1999), climate proxies (AD 1600-1999), and coupled Atmosphere-Ocean-Chemistry Climate Model simulations with SOCOL-MPIOM (AD 1600-1999). We find robust statistical evidence that Atlantic multi-decadal oscillation (AMO) has intrinsic positive correlation with solar activity in all datasets employed. The strength of the relationship between AMO and solar activity is modulated by volcanic eruptions and complex interaction among modes of ocean variability. The observational dataset reveals that El Niño southern oscillation (ENSO) has statistically significant negative intrinsic correlation with solar activity on decadal to multi-decadal timescales (16-27-year) whereas there is no evidence of a link on a typical ENSO timescale (2-7-year). In the observational dataset, the volcanic eruptions do not have a link with AMO on a typical AMO timescale (55-80-year) however the long-term datasets (proxies and SOCOL-MPIOM output) show that volcanic eruptions have intrinsic negative correlation with AMO on inter-annual to multi-decadal timescales. The Pacific decadal oscillation has no link with solar activity, however, it has positive intrinsic correlation with volcanic eruptions on multi-decadal timescales (47-54-year) in reconstruction and decadal to multi-decadal timescales (16-32-year) in climate model simulations. We also find evidence of a link between volcanic eruptions and ENSO, however, the sign of relationship is not consistent between observations/proxies and climate model simulations.

  11. Solar spectral irradiance variability in cycle 24: observations and models

    NASA Astrophysics Data System (ADS)

    Marchenko, Sergey V.; DeLand, Matthew T.; Lean, Judith L.

    2016-12-01

    Utilizing the excellent stability of the Ozone Monitoring Instrument (OMI), we characterize both short-term (solar rotation) and long-term (solar cycle) changes of the solar spectral irradiance (SSI) between 265 and 500 nm during the ongoing cycle 24. We supplement the OMI data with concurrent observations from the Global Ozone Monitoring Experiment-2 (GOME-2) and Solar Radiation and Climate Experiment (SORCE) instruments and find fair-to-excellent, depending on wavelength, agreement among the observations, and predictions of the Naval Research Laboratory Solar Spectral Irradiance (NRLSSI2) and Spectral And Total Irradiance REconstruction for the Satellite era (SATIRE-S) models.

  12. Assessing the Impact of Climatic Variability and Change on Maize Production in the Midwestern USA

    NASA Astrophysics Data System (ADS)

    Andresen, J.; Jain, A. K.; Niyogi, D. S.; Alagarswamy, G.; Biehl, L.; Delamater, P.; Doering, O.; Elias, A.; Elmore, R.; Gramig, B.; Hart, C.; Kellner, O.; Liu, X.; Mohankumar, E.; Prokopy, L. S.; Song, C.; Todey, D.; Widhalm, M.

    2013-12-01

    Weather and climate remain among the most important uncontrollable factors in agricultural production systems. In this study, three process-based crop simulation models were used to identify the impacts of climate on the production of maize in the Midwestern U.S.A. during the past century. The 12-state region is a key global production area, responsible for more than 80% of U.S. domestic and 25% of total global production. The study is a part of the Useful to Useable (U2U) Project, a USDA NIFA-sponsored project seeking to improve the resilience and profitability of farming operations in the region amid climate variability and change. Three process-based crop simulation models were used in the study: CERES-Maize (DSSAT, Hoogenboom et al., 2012), the Hybrid-Maize model (Yang et al., 2004), and the Integrated Science Assessment Model (ISAM, Song et al., 2013). Model validation was carried out with individual plot and county observations. The models were run with 4 to 50 km spatial resolution gridded weather data for representative soils and cultivars, 1981-2012, to examine spatial and temporal yield variability within the region. We also examined the influence of different crop models and spatial scales on regional scale yield estimation, as well as a yield gap analysis between observed and attainable yields. An additional study was carried out with the CERES-Maize model at 18 individual site locations 1901-2012 to examine longer term historical trends. For all simulations, all input variables were held constant in order to isolate the impacts of climate. In general, the model estimates were in good agreement with observed yields, especially in central sections of the region. Regionally, low precipitation and soil moisture stress were chief limitations to simulated crop yields. The study suggests that at least part of the observed yield increases in the region during recent decades have occurred as the result of wetter, less stressful growing season weather conditions.

  13. The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

    NASA Technical Reports Server (NTRS)

    Robertson, Franklin R.

    1997-01-01

    The earth’s climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation– the major mode of interannual variability– is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the “memory” of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth’s climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being “data poor’ has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

  14. Alexander Polonsky Global warming hiatus, ocean variability and regional climate change

    NASA Astrophysics Data System (ADS)

    Polonsky, A.

    2016-02-01

    This presentation generalizes the results concerning ocean variability, large-scale interdecadal ocean-atmosphere interaction in the Atlantic and Pacific Oceans and their impact on global and regional climate change carried out by the author and his colleagues for about 20 years. It is demonstrated once more that Atlantic Multidecadal Oscillation (AMO, which was early referred by the author as “interdecadal mode of North Atlantic Oscillation”) is the crucial natural interdecadal climatic signal for the Atlantic-European and Mediterranean regions. It is characterized by amplitude which is the same order as human-induced centennial climate change and exceeds trend-like anthropogenic change at the decadal scale. Fast increasing of the global and Northern Hemisphere air temperature in the last 30 yrs of XX century (especially pronounced in the North Atlantic region and surrounded areas) is due to coincidence of human-induced positive trend and transition from the negative to the positive phase of AMO. AMO accounts for about 50% (60%) of the global (Northern Hemisphere) temperature trend in that period. Recent global warming hiatus is mostly the result of switch off the AMO phase. Typical AMO temporal scale is dictated by meridional overturning variability in the Atlantic Ocean and associated magnitude of meridional heat transport. Pacific Decadal Oscillation (PDO) is the other natural interdecadal signal which significantly impacts the global and regional climate variability. The rate of the ocean warming for different periods assessed separately for the upper mixed layer and deeper layers using data of oceanic re-analysis since 1959 confirms the principal role of the natural interdecadal oceanic modes (AMO and PDO) in observing climate change. At the same time a lack of deep-ocean long-term observing system restricts the accuracy of assessment of the heat redistribution in the World Ocean. I thanks to Pavel Sukhonos for help in the presentation preparing.

  15. Variability of North Atlantic Hurricane Frequency in a Large Ensemble of High-Resolution Climate Simulations

    NASA Astrophysics Data System (ADS)

    Mei, W.; Kamae, Y.; Xie, S. P.

    2017-12-01

    Forced and internal variability of North Atlantic hurricane frequency during 1951-2010 is studied using a large ensemble of climate simulations by a 60-km atmospheric general circulation model that is forced by observed sea surface temperatures (SSTs). The simulations well capture the interannual-to-decadal variability of hurricane frequency in best track data, and further suggest a possible underestimate of hurricane counts in the current best track data prior to 1966 when satellite measurements were unavailable. A genesis potential index (GPI) averaged over the Main Development Region (MDR) accounts for more than 80% of the forced variations in hurricane frequency, with potential intensity and vertical wind shear being the dominant factors. In line with previous studies, the difference between MDR SST and tropical mean SST is a simple but useful predictor; a one-degree increase in this SST difference produces 7.1±1.4 more hurricanes. The hurricane frequency also exhibits internal variability that is comparable in magnitude to the interannual variability. The 100-member ensemble allows us to address the following important questions: (1) Are the observations equivalent to one realization of such a large ensemble? (2) How many ensemble members are needed to reproduce the variability in observations and in the forced component of the simulations? The sources of the internal variability in hurricane frequency will be identified and discussed. The results provide an explanation for the relatively week correlation ( 0.6) between MDR GPI and hurricane frequency on interannual timescales in observations.

  16. Climate Change Observation Accuracy: Requirements and Economic Value

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce; Cooke, Roger; Golub, Alexander; Baize, Rosemary; Mlynczak, Martin; Lukashin, Constantin; Thome, Kurt; Shea, Yolanda; Kopp, Greg; Pilewskie, Peter; hidehide

    2016-01-01

    This presentation will summarize a new quantitative approach to determining the required accuracy for climate change observations. Using this metric, most current global satellite observations struggle to meet this accuracy level. CLARREO (Climate Absolute Radiance and Refractivity Observatory) is a new satellite mission designed to resolve this challenge is by achieving advances of a factor of 10 for reflected solar spectra and a factor of 3 to 5 for thermal infrared spectra. The CLARREO spectrometers can serve as SI traceable benchmarks for the Global Satellite Intercalibration System (GSICS) and greatly improve the utility of a wide range of LEO and GEO infrared and reflected solar satellite sensors for climate change observations (e.g. CERES, MODIS, VIIIRS, CrIS, IASI, Landsat, etc). A CLARREO Pathfinder mission for flight on the International Space Station is included in the U.S. President—TM”s fiscal year 2016 budget, with launch in 2019 or 2020. Providing more accurate decadal change trends can in turn lead to more rapid narrowing of key climate science uncertainties such as cloud feedback and climate sensitivity. A new study has been carried out to quantify the economic benefits of such an advance and concludes that the economic value is $9 Trillion U.S. dollars. The new value includes the cost of carbon emissions reductions.

  17. Sustainability or Collapse: Interplay Between Decadal Climate Variability and Human Activities Matters

    NASA Astrophysics Data System (ADS)

    Lu, Y.; Hu, H.; Tian, F.

    2016-12-01

    The Aral Sea Crisis and the deterioration of Tarim River Basin are representative cases of emergent water deficit problems in arid areas. Comparing cases of water deficit problems in different regions and considering the in the perspective of socio-hydrology is helpful to obtain guidance on integrated management of arid area basins. Analyzing the interplay between decadal climate variability and human activities in both basins, the important role of human activities is observed. Decadal climate variability tempts people to adapt fast to increasing water resources and slowly to decreasing water resources, while using unsustainable technical measures to offset water shortage. Due to this asymmetry the situation deteriorates with technically enhanced capabilities of societies to exploit water resources, and more integrated long-term management capacity is in high demand.

  18. Assessment of Human Health Vulnerability to Climate Variability and Change in Cuba

    PubMed Central

    Bultó, Paulo Lázaro Ortíz; Rodríguez, Antonio Pérez; Valencia, Alina Rivero; Vega, Nicolás León; Gonzalez, Manuel Díaz; Carrera, Alina Pérez

    2006-01-01

    In this study we assessed the potential effects of climate variability and change on population health in Cuba. We describe the climate of Cuba as well as the patterns of climate-sensitive diseases of primary concern, particularly dengue fever. Analyses of the associations between climatic anomalies and disease patterns highlight current vulnerability to climate variability. We describe current adaptations, including the application of climate predictions to prevent disease outbreaks. Finally, we present the potential economic costs associated with future impacts due to climate change. The tools used in this study can be useful in the development of appropriate and effective adaptation options to address the increased climate variability associated with climate change. PMID:17185289

  19. Hydrologic sensitivity of headwater catchments to climate and landscape variability

    NASA Astrophysics Data System (ADS)

    Kelleher, Christa; Wagener, Thorsten; McGlynn, Brian; Nippgen, Fabian; Jencso, Kelsey

    2013-04-01

    Headwater streams cumulatively represent an extensive portion of the United States stream network, yet remain largely unmonitored and unmapped. As such, we have limited understanding of how these systems will respond to change, knowledge that is important for preserving these unique ecosystems, the services they provide, and the biodiversity they support. We compare responses across five adjacent headwater catchments located in Tenderfoot Creek Experimental Forest in Montana, USA, to understand how local differences may affect the sensitivity of headwaters to change. We utilize global, variance-based sensitivity analysis to understand which aspects of the physical system (e.g., vegetation, topography, geology) control the variability in hydrologic behavior across these basins, and how this varies as a function of time (and therefore climate). Basin fluxes and storages, including evapotranspiration, snow water equivalent and melt, soil moisture and streamflow, are simulated using the Distributed Hydrology-Vegetation-Soil Model (DHSVM). Sensitivity analysis is applied to quantify the importance of different physical parameters to the spatial and temporal variability of different water balance components, allowing us to map similarities and differences in these controls through space and time. Our results show how catchment influences on fluxes vary across seasons (thus providing insight into transferability of knowledge in time), and how they vary across catchments with different physical characteristics (providing insight into transferability in space).

  20. Societal Impacts of Natural Decadal Climate Variability – The Pacemakers of Civilizations

    NASA Astrophysics Data System (ADS)

    Mehta, V. M.

    2017-12-01

    Natural decadal climate variability (DCV) is one of the oldest areas of climate research. Building on centuries-long literature, a substantial body of research has emerged in the last two to three decades, focused on understanding causes, mechanisms, and impacts of DCV. Several DCV phenomena – the Pacific Decadal Oscillation (PDO) or the Interdecadal Pacific Oscillation (IPO), tropical Atlantic sea-surface temperature gradient variability (TAG for brevity), West Pacific Warm Pool variability, and decadal variability of El Niño-La Niña events – have been identified in observational records; and are associated with variability of worldwide atmospheric circulations, water vapor transport, precipitation, and temperatures; and oceanic circulations, salinity, and temperatures. Tree-ring based drought index data going back more than 700 years show presence of decadal hydrologic cycles (DHCs) in North America, Europe, and South Asia. Some of these cycles were associated with the rise and fall of civilizations, large-scale famines which killed millions of people, and acted as catalysts for socio-political revolutions. Instrument-measured data confirm presence of such worldwide DHCs associated with DCV phenomena; and show these DCV phenomena’s worldwide impacts on river flows, crop productions, inland water-borne transportation, hydro-electricity generation, and agricultural irrigation. Fish catch data also show multiyear to decadal catch variability associated with these DCV phenomena in all oceans. This talk, drawn from my recently-published book (Mehta, V.M., 2017: Natural Decadal Climate Variability: Societal Impacts. CRC Press, Boca Raton, Florida, 326 pp.), will give an overview of worldwide impacts of DCV phenomena, with specific examples of socio-economic-political impacts. This talk will also describe national and international security implications of such societal impacts, and worldwide food security implications. The talk will end with an outline of needed

  1. Climate change and observed climate trends in the fort cobb experimental watershed.

    PubMed

    Garbrecht, J D; Zhang, X C; Steiner, J L

    2014-07-01

    Recurring droughts in the Southern Great Plains of the United States are stressing the landscape, increasing uncertainty and risk in agricultural production, and impeding optimal agronomic management of crop, pasture, and grazing systems. The distinct possibility that the severity of recent droughts may be related to a greenhouse-gas induced climate change introduces new challenges for water resources managers because the intensification of droughts could represent a permanent feature of the future climate. Climate records of the Fort Cobb watershed in central Oklahoma were analyzed to determine if recent decade-long trends in precipitation and air temperature were consistent with climate change projections for central Oklahoma. The historical precipitation record did not reveal any compelling evidence that the recent 20-yr-long decline in precipitation was related to climate change. Also, precipitation projections by global circulation models (GCMs) displayed a flat pattern through the end of the 21st century. Neither observed nor projected precipitation displayed a multidecadal monotonic rising or declining trend consistent with an ongoing warming climate. The recent trend in observed annual precipitation was probably a decade-scale variation not directly related to the warming climate. On the other hand, the observed monotonic warming trend of 0.34°C decade that started around 1978 is consistent with GCM projections of increasing temperature for central Oklahoma. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  2. Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

    NASA Astrophysics Data System (ADS)

    Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

    2013-12-01

    Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at

  3. Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis

    PubMed Central

    Botai, Joel O.; Rautenbach, Hannes; Ncongwane, Katlego P.; Botai, Christina M.

    2017-01-01

    % in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention. PMID:29117114

  4. A perspective on sustained marine observations for climate modelling and prediction

    PubMed Central

    Dunstone, Nick J.

    2014-01-01

    Here, I examine some of the many varied ways in which sustained global ocean observations are used in numerical modelling activities. In particular, I focus on the use of ocean observations to initialize predictions in ocean and climate models. Examples are also shown of how models can be used to assess the impact of both current ocean observations and to simulate that of potential new ocean observing platforms. The ocean has never been better observed than it is today and similarly ocean models have never been as capable at representing the real ocean as they are now. However, there remain important unanswered questions that can likely only be addressed via future improvements in ocean observations. In particular, ocean observing systems need to respond to the needs of the burgeoning field of near-term climate predictions. Although new ocean observing platforms promise exciting new discoveries, there is a delicate balance to be made between their funding and that of the current ocean observing system. Here, I identify the need to secure long-term funding for ocean observing platforms as they mature, from a mainly research exercise to an operational system for sustained observation over climate change time scales. At the same time, considerable progress continues to be made via ship-based observing campaigns and I highlight some that are dedicated to addressing uncertainties in key ocean model parametrizations. The use of ocean observations to understand the prominent long time scale changes observed in the North Atlantic is another focus of this paper. The exciting first decade of monitoring of the Atlantic meridional overturning circulation by the RAPID-MOCHA array is highlighted. The use of ocean and climate models as tools to further probe the drivers of variability seen in such time series is another exciting development. I also discuss the need for a concerted combined effort from climate models and ocean observations in order to understand the current slow

  5. Analysis of the Relationship Between Climate and NDVI Variability at Global Scales

    NASA Technical Reports Server (NTRS)

    Zeng, Fan-Wei; Collatz, G. James; Pinzon, Jorge; Ivanoff, Alvaro

    2011-01-01

    interannual variability in modeled (CASA) C flux is in part caused by interannual variability in Normalized Difference Vegetation Index (NDVI) Fraction of Photosynthetically Active Radiation (FPAR). This study confirms a mechanism producing variability in modeled NPP: — NDVI (FPAR) interannual variability is strongly driven by climate; — The climate driven variability in NDVI (FPAR) can lead to much larger fluctuation in NPP vs. the NPP computed from FPAR climatology

  6. Regional agricultural susceptibility to climate variability: A district level analysis of Maharashtra, India

    NASA Astrophysics Data System (ADS)

    Swami, D.; Parthasarathy, D.; Dave, P.

    2016-12-01

    Climate variability (CV) has adverse impact on crop production and inadequate research carried out to assess the impact of CV on crop production has aggravated the ability of farmers to adapt (Jones et al., 2000). A better understanding of CV is required to reduce the vulnerability of farmers towards existing and future CV. Further, a wide variation in policies related to climate change exists at global level and considering the state/nation as a single unit for policy formulations may lead to under-representation of regional problems. Hence, the present work chooses to focus on CVassessment at the regional/district level of Maharashtra state in India. Here, interannual variability of wet and dry spells from year 1951-2013, are used as a measure of CV. Statistical declining trend of wet spells for (12/34) districts was observed across all the districts of Maharashtra. Districts showing highest change in wet spell pre and post 1976/77 are Beed, Latur and Osmanabad belong to Central Maharashtra Plateau zone and Western Maharashtra scarcity zone. Dry spells for (8/34) districts were found to statistically increase across all the districts of Maharashtra. Washim, Yavatmal of Vidarbha zone; and Latur, Parbhani of Amravati division belonging to Central Maharashtra Plateau zone and Central Vidarbha zone are found to reflect the large variation in their behavior pre and post 1976/77. Findings reveal that districts from the same agro-climate zones respond differently to CV, indicating significant spatial heterogeneity within the region. Trend in monsoon variability was found to be prominent after 1976/77, suggesting an enhanced role of climate change on climate variability after 1977. It necessitates separate policy formulation related to CV and agriculture for each district to bring out the solution for regional issues (socio-political, farmers, agriculturalists, economical) more clearly. Further we have attempted to link agriculture vulnerability and crop sensitivity to

  7. Quantitative Comparison of the Variability in Observed and Simulated Shortwave Reflectance

    NASA Technical Reports Server (NTRS)

    Roberts, Yolanda, L.; Pilewskie, P.; Kindel, B. C.; Feldman, D. R.; Collins, W. D.

    2013-01-01

    The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system that has been designed to monitor the Earth’s climate with unprecedented absolute radiometric accuracy and SI traceability. Climate Observation System Simulation Experiments (OSSEs) have been generated to simulate CLARREO hyperspectral shortwave imager measurements to help define the measurement characteristics needed for CLARREO to achieve its objectives. To evaluate how well the OSSE-simulated reflectance spectra reproduce the Earth s climate variability at the beginning of the 21st century, we compared the variability of the OSSE reflectance spectra to that of the reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY). Principal component analysis (PCA) is a multivariate decomposition technique used to represent and study the variability of hyperspectral radiation measurements. Using PCA, between 99.7%and 99.9%of the total variance the OSSE and SCIAMACHY data sets can be explained by subspaces defined by six principal components (PCs). To quantify how much information is shared between the simulated and observed data sets, we spectrally decomposed the intersection of the two data set subspaces. The results from four cases in 2004 showed that the two data sets share eight (January and October) and seven (April and July) dimensions, which correspond to about 99.9% of the total SCIAMACHY variance for each month. The spectral nature of these shared spaces, understood by examining the transformed eigenvectors calculated from the subspace intersections, exhibit similar physical characteristics to the original PCs calculated from each data set, such as water vapor absorption, vegetation reflectance, and cloud reflectance.

  8. Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

    NASA Astrophysics Data System (ADS)

    Khan, F.; Pilz, J.; Spöck, G.

    2017-12-01

    Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan

  9. Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

    NASA Technical Reports Server (NTRS)

    Hoffert, M. I.

    1986-01-01

    Terrestrial climatic effects associated with solar variability have been proposed for at least a century, but could not be assessed quantitatively owing to observational uncertainities in solar flux variations. Measurements from 1980 to 1984 by the Active Cavity Radiometer Irradiance Monitor (ACRIM), capable of resolving fluctuations above the sensible atmosphere less than 0.1% of the solar constant, permit direct albeit preliminary assessments of solar forcing effects on global temperatures during this period. The global temperature response to ACRIM-measured fluctuations was computed from 1980 to 1985 using the NYU transient climate model including thermal inertia effects of the world ocean; and compared the results with observations of recent temperature trends. Monthly mean ACRIM-driven global surface temperature fluctuations computed with the climate model are an order of magnitude smaller, of order 0.01 C. In constrast, global mean surface temperature observations indicate an approx. 0.1 C increase during this period. Solar variability is therefore likely to have been a minor factor in global climate change during this period compared with variations in atmospheric albedo, greenhouse gases and internal self-inducedoscillations. It was not possible to extend the applicability of the measured flux variations to longer periods since a possible correlation of luminosity with solar annual activity is not supported by statistical analysis. The continuous monitoring of solar flux by satellite-based instruments over timescales of 20 years or more comparable to timescales for thermal relaxation of the oceans and of the solar cycle itself is needed to resolve the question of long-term solar variation effects on climate.

  10. Observations of red-giant variable stars by Aboriginal Australians

    NASA Astrophysics Data System (ADS)

    Hamacher, Duane W.

    2018-04-01

    Aboriginal Australians carefully observe the properties and positions of stars, including both overt and subtle changes in their brightness, for subsistence and social application. These observations are encoded in oral tradition. I examine two Aboriginal oral traditions from South Australia that describe the periodic changing brightness in three pulsating, red-giant variable stars: Betelgeuse (Alpha Orionis), Aldebaran (Alpha Tauri), and Antares (Alpha Scorpii). The Australian Aboriginal accounts stand as the only known descriptions of pulsating variable stars in any Indigenous oral tradition in the world. Researchers examining these oral traditions over the last century, including anthropologists and astronomers, missed the description of these stars as being variable in nature as the ethnographic record contained several misidentifications of stars and celestial objects. Arguably, ethnographers working on Indigenous Knowledge Systems should have academic training in both the natural and social sciences.

  11. Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

    NASA Astrophysics Data System (ADS)

    Fisher, Jeremy Isaac

    Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980’s droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat

  12. Satellite-derived SIF and CO2 Observations Show Coherent Responses to Interannual Climate Variations

    NASA Astrophysics Data System (ADS)

    Butterfield, Z.; Hogikyan, A.; Kulawik, S. S.; Keppel-Aleks, G.

    2017-12-01

    Gross primary production (GPP) is the single largest carbon flux in the Earth system, but its sensitivity to changes in climate is subject to significant uncertainty. Satellite measurements of solar-induced chlorophyll fluorescence (SIF) offer insight into spatial and temporal patterns in GPP at a global scale and, combined with other satellite-derived datasets, provide unprecedented opportunity to explore interactions between atmospheric CO2, GPP, and climate variability. To explore potential drivers of GPP in the Northern Hemisphere (NH), we compare monthly-averaged SIF data from the Global Ozone Monitoring Experiment 2 (GOME-2) with observed anomalies in temperature (T; CRU-TS), liquid water equivalent (LWE) from the Gravity Recovery and Climate Experiment (GRACE), and photosynthetically active radiation (PAR; CERES SYN1deg). Using observations from 2007 through 2015 for several NH regions, we calculate month-specific sensitivities of SIF to variability in T, LWE, and PAR. These sensitivities provide insight into the seasonal progression of how productivity is affected by climate variability and can be used to effectively model the observed SIF signal. In general, we find that high temperatures are beneficial to productivity in the spring, but detrimental in the summer. The influences of PAR and LWE are more heterogeneous between regions; for example, higher LWE in North American temperate forest leads to decreased springtime productivity, while exhibiting a contrasting effect in water-limited regions. Lastly, we assess the influence of variations in terrestrial productivity on atmospheric carbon using a new lower tropospheric CO2 product derived from the Greenhouse Gases Observing Satellite (GOSAT). Together, these data shed light on the drivers of interannual variability in the annual cycle of NH atmospheric CO2, and may provide improved constraints on projections of long-term carbon cycle responses to climate change.

  13. Solving the African Climate Observation Puzzle, and Concurrently Building Capacity

    NASA Astrophysics Data System (ADS)

    Selker, J. S.; Van De Giesen, N.; Annor, F. O.; Hochreutener, R.; Jachens, E. R.

    2017-12-01

    The Trans-African Hydro-Meteorological Observatory (TAHMO.org) is directly addressing basic issues of climate observation, climate science, and education through a novel public-private partnership. With 500 stations now reporting from over 20 African countries, TAHMO is the largest single source of continental-scale weather and climate data for Africa. Working directly with national meteorological agencies, TAHMO first builds local human capacity and real-time data to the host country. TAHMO also provides all of these data free of charge to all researchers and teams seeking to develop peer-reviewed scientific contributions. This will be the basis of a whole new level of observation-informed science for the African continent. Most TAHMO stations are housed at African schools, with a local host-teacher who attends to basic day-to-day cleaning. These schools also receive free curricular support providing geographic, mathematical, statistical, hydrologic, and meteorological lessons that connect student to their environment and creates climate-aware citizens, which we believe is the most fundamental element of developing a climate-resilient society. Installation of these stations have been made possible through the support of private companies like IBM and development programmes through the Global Resilience Partnership, World Bank, USAID among others. The availability of these new data sets will help generate more accurate weather forecasts which will be made freely available across the African continent. TAHMO leverages low-cost cell phone data transmission with solid-state sensor technology (provided by the METER corporation) to provide a cost-effective, sustainable, and transformative solution to the climate observation gap in Africa.

  14. Life stage, not climate change, explains observed tree range shifts.

    PubMed

    Máliš, František; Kopecký, Martin; Petřík, Petr; Vladovič, Jozef; Merganič, Ján; Vida, Tomáš

    2016-05-01

    Ongoing climate change is expected to shift tree species distribution and therefore affect forest biodiversity and ecosystem services. To assess and project tree distributional shifts, researchers may compare the distribution of juvenile and adult trees under the assumption that differences between tree life stages reflect distributional shifts triggered by climate change. However, the distribution of tree life stages could differ within the lifespan of trees, therefore, we hypothesize that currently observed distributional differences could represent shifts over ontogeny as opposed to climatically driven changes. Here, we test this hypothesis with data from 1435 plots resurveyed after more than three decades across the Western Carpathians. We compared seedling, sapling and adult distribution of 12 tree species along elevation, temperature and precipitation gradients. We analyzed (i) temporal shifts between the surveys and (ii) distributional differences between tree life stages within both surveys. Despite climate warming, tree species distribution of any life stage did not shift directionally upward along elevation between the surveys. Temporal elevational shifts were species specific and an order of magnitude lower than differences among tree life stages within the surveys. Our results show that the observed range shifts among tree life stages are more consistent with ontogenetic differences in the species’ environmental requirements than with responses to recent climate change. The distribution of seedlings substantially differed from saplings and adults, while the distribution of saplings did not differ from adults, indicating a critical transition between seedling and sapling tree life stages. Future research has to take ontogenetic differences among life stages into account as we found that distributional differences recently observed worldwide may not reflect climate change but rather the different environmental requirements of tree life stages. © 2016

  15. Economic Value of an Advanced Climate Observing System

    NASA Astrophysics Data System (ADS)

    Wielicki, B. A.; Cooke, R.; Young, D. F.; Mlynczak, M. G.

    2013-12-01

    Scientific missions increasingly need to show the monetary value of knowledge advances in budget-constrained environments. For example, suppose a climate science mission promises to yield decisive information on the rate of human caused global warming within a shortened time frame. How much should society be willing to pay for this knowledge today? The US interagency memo on the social cost of carbon (SCC) creates a standard yardstick for valuing damages from carbon emissions. We illustrate how value of information (VOI) calculations can be used to monetize the relative value of different climate observations. We follow the SCC, setting uncertainty in climate sensitivity to a truncated Roe and Baker (2007) distribution, setting discount rates of 2.5%, 3% and 5%, and using one of the Integrated Assessment Models sanctioned in SCC (DICE, Nordhaus 2008). We consider three mitigation scenarios: Business as Usual (BAU), a moderate mitigation response DICE Optimal, and a strong response scenario (Stern). To illustrate results, suppose that we are on the BAU emissions scenario, and that we would switch to the Stern emissions path if we learn with 90% confidence that the decadal rate of temperature change reaches or exceeds 0.2 C/decade. Under the SCC assumptions, the year in which this happens, if it happens, depends on the uncertain climate sensitivity and on the emissions path. The year in which we become 90% certain that it happens depends, in addition, on our Earth observations, their accuracy, and their completeness. The basic concept is that more accurate observations can shorten the time for societal decisions. The economic value of the resulting averted damages depends on the discount rate, and the years in which the damages occur. A new climate observation would be economically justified if the net present value (NPV) of the difference in averted damages, relative to the existing systems, exceeds the NPV of the system costs. Our results (Cooke et al. 2013

  16. A Method of Relating General Circulation Model Simulated Climate to the Observed Local Climate. Part I: Seasonal Statistics.

    NASA Astrophysics Data System (ADS)

    Karl, Thomas R.; Wang, Wei-Chyung; Schlesinger, Michael E.; Knight, Richard W.; Portman, David

    1990-10-01

    Important surface observations such as the daily maximum and minimum temperature, daily precipitation, and cloud ceilings often have localized characteristics that are difficult to reproduce with the current resolution and the physical parameterizations in state-of-the-art General Circulation climate Models (GCMs). Many of the difficulties can be partially attributed to mismatches in scale, local topography. regional geography and boundary conditions between models and surface-based observations. Here, we present a method, called climatological projection by model statistics (CPMS), to relate GCM grid-point flee-atmosphere statistics, the predictors, to these important local surface observations. The method can be viewed as a generalization of the model output statistics (MOS) and perfect prog (PP) procedures used in numerical weather prediction (NWP) models. It consists of the application of three statistical methods: 1) principle component analysis (FICA), 2) canonical correlation, and 3) inflated regression analysis. The PCA reduces the redundancy of the predictors The canonical correlation is used to develop simultaneous relationships between linear combinations of the predictors, the canonical variables, and the surface-based observations. Finally, inflated regression is used to relate the important canonical variables to each of the surface-based observed variables.We demonstrate that even an early version of the Oregon State University two-level atmospheric GCM (with prescribed sea surface temperature) produces free-atmosphere statistics than can, when standardized using the model’s internal means and variances (the MOS-like version of CPMS), closely approximate the observed local climate. When the model data are standardized by the observed free-atmosphere means and variances (the PP version of CPMS), however, the model does not reproduce the observed surface climate as well. Our results indicate that in the MOS-like version of CPMS the differences between

  17. Climate Variability Impacts on Watershed Nutrient Delivery and Reservoir Production

    NASA Astrophysics Data System (ADS)

    White, J. D.; Prochnow, S. J.; Zygo, L. M.; Byars, B. W.

    2005-05-01

    Reservoirs in agricultural dominated watersheds tend to exhibit pulse-system behavior especially if located in climates dominated by summer convective precipitation inputs. Concentration and bulk mass of nutrient and sediment inputs into reservoir systems vary in terms of timing and magnitude of delivery from watershed sources to reservoirs under these climate conditions. Reservoir management often focuses on long-term average inputs without considering short and long-term impacts of variation in loading. In this study we modeled a watershed-reservoir system to assess how climate variability affects reservoir primary production through shifts in external loading and internal recycling of limiting nutrients. The Bosque watershed encompasses 423,824 ha in central Texas which delivers water to Lake Waco, a 2900 ha reservoir that is the primary water source for the city of Waco and surrounding areas. Utilizing the Soil Water Assessment Tool for the watershed and river simulations and the CE-Qual-2e model for the reservoir, hydrologic and nutrient dynamics were simulated for a 10 year period encompassing two ENSO cycles. The models were calibrated based on point measurement of water quality attributes for a two year time period. Results indicated that watershed delivery of nutrients was affected by the presence and density of small flood-control structure in the watershed. However, considerable nitrogen and phosphorus loadings were derived from soils in the upper watershed which have had long-term waste-application from concentrated animal feeding operations. During El Niño years, nutrient and sediment loads increased by 3 times above non-El Niño years. The simulated response within the reservoir to these nutrient and sediment loads had both direct and indirect. Productivity evaluated from chlorophyll a and algal biomass increased under El Niño conditions, however species composition shifts were found with an increase in cyanobacteria dominance. In non-El Niño years

  18. Modeling Dynamics of South American Rangelands to Climate Variability and Human Impact

    NASA Astrophysics Data System (ADS)

    Stanimirova, R.; Arevalo, P. A.; Kaufmann, R.; Maus, V.; Lesiv, M.; Havlik, P.; Friedl, M. A.

    2017-12-01

    The combined pressures of climate change and shifting dietary preferences are creating an urgent need to improve understanding of how climate and land management are jointly affecting the sustainability of rangelands. In particular, our ability to effectively manage rangelands in a manner that satisfies increasing demand for meat and dairy while reducing environmental impact depends on the sensitivity of rangelands to perturbations from both climate (e.g., drought) and land use (e.g., grazing). To characterize the sensitivity of rangeland vegetation to variation in climate, we analyzed gridded time series of satellite and climate data at 0.5-degree spatial resolution from 2003 to 2016 for rangeland ecosystems in South America. We used panel regression and canonical correlation to analyze the relationship between time series of enhanced vegetation index (EVI) derived from NASA’s Moderate Spatial Resolution Imaging Spectroradiometer (MODIS) and gridded precipitation and air temperature data from the University of East Anglia’s Climate Research Unit. To quantify the degree to which livestock management explains geographic variation of EVI, we used global livestock distribution (FAO) and feed requirements data from the Global Biosphere Management Model (GLOBIOM). Because rangeland ecosystems are sensitive to changes in meteorological variables at different time scales, we evaluated the strength of coupling between anomalies in EVI and anomalies in temperature and standardized precipitation index (SPI) data at 1-6 month lags. Our results show statistically significant relationships between EVI and precipitation during summer, fall, and winter in both tropical and subtropical agroecological zones of South America. Further, lagged precipitation effects, which reflect memory in the system, explain significant variance in winter EVI anomalies. While precipitation emerges as the dominant driver of variability in rangeland greenness, we find evidence of a management

  19. Effects of changes in climate variability and extremes on the exceedance of critical algal bloom thresholds

    NASA Astrophysics Data System (ADS)

    Hecht, J. S.; Zia, A.; Beckage, B.; Winter, J.; Schroth, A. W.; Bomblies, A.; Clemins, P. J.; Rizzo, D. M.

    2017-12-01

    Identifying critical thresholds associated with algal blooms in freshwater lakes is important for avoiding persistent eutrophic conditions and their undesirable ecological, recreational and drinking water impacts. Recent Integrated Assessment Model (IAM) and Bayesian network studies have demonstrated that future climatic changes could increase the duration and intensity of these blooms. Yet, few studies have systematically examined the sensitivity of algal blooms to projected changes in precipitation and temperature variability and extremes at storm-event to seasonal timescales. We employ an IAM, which couples downscaled Global Climate Model (GCM) output with hydrologic and water quality models, to examine the sensitivity of algal blooms in Lake Champlain’s shallow Missisquoi Bay to potential future climate changes. We first identify a set of statistically downscaled GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) that reproduce recent historical daily temperature and precipitation observations well in the Lake Champlain basin. Then, we identify plausible covarying changes in the (i) mean and variance of seasonal precipitation and temperature distributions and (ii) frequency and magnitude of individual storm events. We assess the response of water quality indicators (e.g. chlorophyll a concentrations, Trophic State Index) and societal impacts to sequences of daily meteorological series generated from distributions that account for these covarying changes. We also discuss strategies for examining the sensitivity of bloom impacts to different weather sequences generated from a single set of precipitation and temperature distributions with a limited number of computationally intensive IAM simulations. We then evaluate the implications of modeling these changes in climate variability and extreme precipitation events for nutrient management. Finally, we consider the generalizability of our findings for water bodies with different physical and

  20. Global economic impacts of climate variability and change during the 20th century.

    PubMed

    Estrada, Francisco; Tol, Richard S J; Botzen, Wouter J W

    2017-01-01

    Estimates of the global economic impacts of observed climate change during the 20th century obtained by applying five impact functions of different integrated assessment models (IAMs) are separated into their main natural and anthropogenic components. The estimates of the costs that can be attributed to natural variability factors and to the anthropogenic intervention with the climate system in general tend to show that: 1) during the first half of the century, the amplitude of the impacts associated with natural variability is considerably larger than that produced by anthropogenic factors and the effects of natural variability fluctuated between being negative and positive. These non-monotonic impacts are mostly determined by the low-frequency variability and the persistence of the climate system; 2) IAMs do not agree on the sign (nor on the magnitude) of the impacts of anthropogenic forcing but indicate that they steadily grew over the first part of the century, rapidly accelerated since the mid 1970’s, and decelerated during the first decade of the 21st century. This deceleration is accentuated by the existence of interaction effects between natural variability and natural and anthropogenic forcing. The economic impacts of anthropogenic forcing range in the tenths of percentage of the world GDP by the end of the 20th century; 3) the impacts of natural forcing are about one order of magnitude lower than those associated with anthropogenic forcing and are dominated by the solar forcing; 4) the interaction effects between natural and anthropogenic factors can importantly modulate how impacts actually occur, at least for moderate increases in external forcing. Human activities became dominant drivers of the estimated economic impacts at the end of the 20th century, producing larger impacts than those of low-frequency natural variability. Some of the uses and limitations of IAMs are discussed.

  1. Global economic impacts of climate variability and change during the 20th century

    PubMed Central

    Estrada, Francisco; Tol, Richard S. J.; Botzen, Wouter J. W.

    2017-01-01

    Estimates of the global economic impacts of observed climate change during the 20th century obtained by applying five impact functions of different integrated assessment models (IAMs) are separated into their main natural and anthropogenic components. The estimates of the costs that can be attributed to natural variability factors and to the anthropogenic intervention with the climate system in general tend to show that: 1) during the first half of the century, the amplitude of the impacts associated with natural variability is considerably larger than that produced by anthropogenic factors and the effects of natural variability fluctuated between being negative and positive. These non-monotonic impacts are mostly determined by the low-frequency variability and the persistence of the climate system; 2) IAMs do not agree on the sign (nor on the magnitude) of the impacts of anthropogenic forcing but indicate that they steadily grew over the first part of the century, rapidly accelerated since the mid 1970’s, and decelerated during the first decade of the 21st century. This deceleration is accentuated by the existence of interaction effects between natural variability and natural and anthropogenic forcing. The economic impacts of anthropogenic forcing range in the tenths of percentage of the world GDP by the end of the 20th century; 3) the impacts of natural forcing are about one order of magnitude lower than those associated with anthropogenic forcing and are dominated by the solar forcing; 4) the interaction effects between natural and anthropogenic factors can importantly modulate how impacts actually occur, at least for moderate increases in external forcing. Human activities became dominant drivers of the estimated economic impacts at the end of the 20th century, producing larger impacts than those of low-frequency natural variability. Some of the uses and limitations of IAMs are discussed. PMID:28212384

  2. Coping with climate variability and long-term climate trends for Nicaraguan maize-bean farmers (Invited)

    NASA Astrophysics Data System (ADS)

    Gourdji, S.; Zelaya Martinez, C.; Martinez Valle, A.; Mejia, O.; Laderach, P.; Lobell, D. B.

    2013-12-01

    Climate variability and change impact farmers at different timescales, but both are of concern for livelihoods and long-term viability of small farms in tropical, rain-fed agricultural systems. This study uses a historical dataset to analyze the impact of 40-year climate trends in Nicaragua on bean production, a staple crop that is an important source of calories and protein in the local diet, particularly in rural areas and in lower income classes. Bean yields are sensitive to rising temperatures, but also frequently limited by seasonal drought and low soil fertility. We use an empirical model to relate department-level yields to spatial variation and inter-annual fluctuations in historical precipitation, temperature and extreme rain events. We then use this model to quantify the impact on yields of long-term observed warming in day and night temperatures, increases in rainfall intensity, longer gaps between rain events, a shorter rainy season and overall drying in certain regions of the country. Preliminary results confirm the negative impacts of warming night temperatures, higher vapor pressure deficits, and longer gaps between rain events on bean yields, although some drying at harvest time has helped to reduce rotting. Across all bean-growing areas, these climate trends have led to a ~10% yield decline per decade relative to a stationary climate and production system, with this decline reaching up to ~20% in the dry northern highlands. In regions that have been particularly impacted by these trends, we look for evidence of farm abandonment, increases in off-farm employment, or on-farm adaptation solutions through crop diversification, use of drought or heat-tolerant seed, and adoption of rainwater harvesting. We will also repeat the modeling exercise for maize, another staple crop providing ~25% of daily calories at the national scale, but which is projected to be more resilient to climate trends.

  3. Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

    NASA Astrophysics Data System (ADS)

    Cannon, Alex J.

    2018-01-01

    Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin

  4. Climate variability and extremes, interacting with nitrogen storage, amplify eutrophication risk

    USGS Publications Warehouse

    Lee, Minjin; Shevliakova, Elena; Malyshev, Sergey; Milly, P.C.D.; Jaffe, Peter R.

    2016-01-01

    Despite 30 years of basin-wide nutrient-reduction efforts, severe hypoxia continues to be observed in the Chesapeake Bay. Here we demonstrate the critical influence of climate variability, interacting with accumulated nitrogen (N) over multidecades, on Susquehanna River dissolved nitrogen (DN) loads, known precursors of the hypoxia in the Bay. We used the process model LM3-TAN (Terrestrial and Aquatic Nitrogen), which is capable of capturing both seasonal and decadal-to-century changes in vegetation-soil-river N storage, and produced nine scenarios of DN-load distributions under different short-term scenarios of climate variability and extremes. We illustrate that after 1 to 3 yearlong dry spells, the likelihood of exceeding a threshold DN load (56 kt yr−1) increases by 40 to 65% due to flushing of N accumulated throughout the dry spells and altered microbial processes. Our analyses suggest that possible future increases in climate variability/extremes—specifically, high precipitation occurring after multiyear dry spells—could likely lead to high DN-load anomalies and hypoxia.

  5. Climate, fishery and society interactions: Observations from the North Atlantic

    NASA Astrophysics Data System (ADS)

    Hamilton, Lawrence C.

    2007-11-01

    Interdisciplinary studies comparing fisheries-dependent regions across the North Atlantic find a number of broad patterns. Large ecological shifts, disastrous to historical fisheries, have resulted when unfavorable climatic events occur atop overfishing. The “teleconnections” linking fisheries crises across long distances include human technology and markets, as well as climate or migratory fish species. Overfishing and climate-driven changes have led to a shift downwards in trophic levels of fisheries takes in some ecosystems, from dominance by bony fish to crustaceans. Fishing societies adapt to new ecological conditions through social reorganization that have benefited some people and places, while leaving others behind. Characteristic patterns of demographic change are among the symptoms of such reorganization. These general observations emerge from a review of recent case studies of individual fishing communities, such as those conducted for the North Atlantic Arc research project.

  6. Variability in functional brain networks predicts expertise during action observation.

    PubMed

    Amoruso, Lucía; Ibáñez, Agustín; Fonseca, Bruno; Gadea, Sebastián; Sedeño, Lucas; Sigman, Mariano; García, Adolfo M; Fraiman, Ricardo; Fraiman, Daniel

    2017-02-01

    Observing an action performed by another individual activates, in the observer, similar circuits as those involved in the actual execution of that action. This activation is modulated by prior experience; indeed, sustained training in a particular motor domain leads to structural and functional changes in critical brain areas. Here, we capitalized on a novel graph-theory approach to electroencephalographic data (Fraiman et al., 2016) to test whether variability in functional brain networks implicated in Tango observation can discriminate between groups differing in their level of expertise. We found that experts and beginners significantly differed in the functional organization of task-relevant networks. Specifically, networks in expert Tango dancers exhibited less variability and a more robust functional architecture. Notably, these expertise-dependent effects were captured within networks derived from electrophysiological brain activity recorded in a very short time window (2s). In brief, variability in the organization of task-related networks seems to be a highly sensitive indicator of long-lasting training effects. This finding opens new methodological and theoretical windows to explore the impact of domain-specific expertise on brain plasticity, while highlighting variability as a fruitful measure in neuroimaging research. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. User-relevant, threshold-specific observations of climate change

    NASA Astrophysics Data System (ADS)

    Stainforth, Dave; Chapman, Sandra; Watkins, Nicholas

    2014-05-01

    Users of climate information look for details of changing climate at local scales (to inform specific activities) and on the geographical patterns of such changes (to prioritise adaptation investments). They often have user-specific thresholds of vulnerability so the changes of interest must refer to such thresholds or to the related quantile of the climatic distribution. A method for providing such information from timeseries of temperature data has recently been published [1] along with maps of changes at thresholds and quantiles [2] derived from the European Observational dataset E-Obs [3]. In this presentation we will do two things. First we will discuss the opportunities to tailor such methods to provide user-specific information through climate services, using illustrations from the existing methodology applied to daily maximum and minimum temperatures [1,2]. Second we will present new results on threshold specific observed changes in precipitation. The methodology for precipitation is related to that which has been applied to temperature but has been developed to handle the characteristics of precipitation distributions. The results identify some regions with systematic increases in precipitation on the seasonally wettest days and others which show drying across all days, on a seasonal basis. We will present the geographic locations and precipitation thresholds where strong signals of changes are seen across Europe. The coherency of such results and the methodology used to process the observational data will be discussed. We will also highlight the justifications for having confidence in the results in some regions and at some thresholds while having a lack of confidence in others. Such information should be an important element of any climate services. It is worth noting that here “wettest days” refers to events which are uncommon within a season (e.g. one in ~20 wet days). This is in contrast and complementary to, for instance, the one in a hundred year

  8. The role of climate change in interpreting historical variability

    Treesearch

    Constance I. Millar; Wallace B. Woolfenden

    1999-01-01

    Significant climate anomalies have characterized the last 1000 yr in the Sierra Nevada, California, USA. Two warm, dry periods of 150- and 200-yr duration occurred during AD 900-1350, which were followed by anomalously cold climates, known as the Little Ice Age, that lasted from AD 1400 to 1900. Climate in the last century has been significantly warmer. Regional biotic…

  9. Oscar: a portable prototype system for the study of climate variability

    NASA Astrophysics Data System (ADS)

    Madonna, Fabio; Rosoldi, Marco; Amato, Francesco

    2015-04-01

    The study of the techniques for the exploitation of solar energy implies the knowledge of nature, ecosystem, biological factors and local climate. Clouds, fog, water vapor, and the presence of large concentrations of dust can significantly affect the way to exploit the solar energy. Therefore, a quantitative characterization of the impact of climate variability at the regional scale is needed to increase the efficiency and sustainability of the energy system. OSCAR (Observation System for Climate Application at Regional scale) project, funded in the frame of the PO FESR 2007-2013, aims at the design of a portable prototype system for the study of correlations among the trends of several Essential Climate Variables (ECVs) and the change in the amount of solar irradiance at the ground level. The final goal of this project is to provide a user-friendly low cost solution for the quantification of the impact of regional climate variability on the efficiency of solar cell and concentrators to improve the exploitation of natural sources. The prototype has been designed on the basis of historical measurements performed at CNR-IMAA Atmospheric Observatory (CIAO). Measurements from satellite and data from models have been also considered as ancillary to the study, above all, to fill in the gaps of existing datasets. In this work, the results outcome from the project activities will be presented. The results include: the design and implementation of the prototype system; the development of a methodology for the estimation of the impact of climate variability, mainly due to aerosol, cloud and water vapor, on the solar irradiance using the integration of the observations potentially provided by prototype; the study of correlation between the surface radiation, precipitation and aerosols transport. In particular, a statistical study will be presented to assess the impact of the atmosphere on the solar irradiance at the ground, quantifying the contribution due to aerosol and

  10. The value of seasonal forecasting and crop mix adaptation to climate variability for agriculture under climate change

    NASA Astrophysics Data System (ADS)

    Choi, H. S.; Schneider, U.; Schmid, E.; Held, H.

    2012-04-01

    Changes to climate variability and frequency of extreme weather events are expected to impose damages to the agricultural sector. Seasonal forecasting and long range prediction skills have received attention as an option to adapt to climate change because seasonal climate and yield predictions could improve farmers’ management decisions. The value of seasonal forecasting skill is assessed with a crop mix adaptation option in Spain where drought conditions are prevalent. Yield impacts of climate are simulated for six crops (wheat, barely, cotton, potato, corn and rice) with the EPIC (Environmental Policy Integrated Climate) model. Daily weather data over the period 1961 to 1990 are used and are generated by the regional climate model REMO as reference period for climate projection. Climate information and its consequent yield variability information are given to the stochastic agricultural sector model to calculate the value of climate information in the agricultural market. Expected consumers’ market surplus and producers’ revenue is compared with and without employing climate forecast information. We find that seasonal forecasting benefits not only consumers but also producers if the latter adopt a strategic crop mix. This mix differs from historical crop mixes by having higher shares of crops which fare relatively well under climate change. The corresponding value of information is highly sensitive to farmers’ crop mix choices.

  11. Assessing risks of climate variability and climate change for Indonesian rice agriculture.

    PubMed

    Naylor, Rosamond L; Battisti, David S; Vimont, Daniel J; Falcon, Walter P; Burke, Marshall B

    2007-05-08

    El Niño events typically lead to delayed rainfall and decreased rice planting in Indonesia’s main rice-growing regions, thus prolonging the hungry season and increasing the risk of annual rice deficits. Here we use a risk assessment framework to examine the potential impact of El Niño events and natural variability on rice agriculture in 2050 under conditions of climate change, with a focus on two main rice-producing areas: Java and Bali. We select a 30-day delay in monsoon onset as a threshold beyond which significant impact on the country’s rice economy is likely to occur. To project the future probability of monsoon delay and changes in the annual cycle of rainfall, we use output from the Intergovernmental Panel on Climate Change AR4 suite of climate models, forced by increasing greenhouse gases, and scale it to the regional level by using empirical downscaling models. Our results reveal a marked increase in the probability of a 30-day delay in monsoon onset in 2050, as a result of changes in the mean climate, from 9-18% today (depending on the region) to 30-40% at the upper tail of the distribution. Predictions of the annual cycle of precipitation suggest an increase in precipitation later in the crop year (April-June) of approximately 10% but a substantial decrease (up to 75% at the tail) in precipitation later in the dry season (July-September). These results indicate a need for adaptation strategies in Indonesian rice agriculture, including increased investments in water storage, drought-tolerant crops, crop diversification, and early warning systems.

  12. Climate variability and wine quality over Portuguese regions

    NASA Astrophysics Data System (ADS)

    Gouveia, Célia M.; Gani, Érico A.; Liberato, Margarida L. R.

    2015-04-01

    characterized in each region by high/low quality wines. Finally, we also investigated how climate variability is related to DOC wine quality for different regions using North Atlantic Oscillation (NAO) index. Results reveal a strong dependence of wine quality for all regions on maximum temperature and precipitation during spring and summer (the growing season) as expected. However the role of temperature on wine quality seems to be distinct among the diverse regions probably due to their different climate zoning. Moreover, it is shown that the differences associated with high/low quality wine are in agreement with different synoptic fields patterns. Our results suggest that this type of analysis may be used in developing a tool that may help anticipating a vintage/high quality year, based on already available seasonal climate outlooks. Santo F.E., de Lima M.I.P., Ramos A.M., Trigo R.M., Trends in seasonal surface air temperature in mainland Portugal, since 1941, International Journal Climatolology, 34: 1814-1837, doi: 10.1002/joc.3803 (2014) de Lima M.I.P., Santo F.E., Ramos A.M. , Trigo, R.M., Trends and correlations in annual extreme precipitation indices for mainland Portugal, 1941-2007, Theoretical and Applied Climatology, DOI:10.1007/s00704-013-1079-6 (2014) Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAGGLO/4155/2012).

  13. Variability of attention processes in ADHD: observations from the classroom.

    PubMed

    Rapport, Mark D; Kofler, Michael J; Alderson, R Matt; Timko, Thomas M; Dupaul, George J

    2009-05-01

    Classroom- and laboratory-based efforts to study the attentional problems of children with ADHD are incongruent in elucidating attentional deficits; however, none have explored within- or between-minute variability in the classroom attentional processing in children with ADHD. High and low attention groups of ADHD children defined via cluster analysis, and 36 typically developing children, were observed while completing academic assignments in their general education classrooms. All children oscillated between attentive and inattentive states; however, children in both ADHD groups switched states more frequently and remained attentive for shorter durations relative to typically developing children. Overall differences in attention and optimal ability to maintain attention among the groups are consistent with laboratory studies of increased ADHD-related interindividual and intergroup variability but inconsistent with laboratory results of increased intra-individual variability and attention decrements over time.

  14. Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies.

    PubMed

    Fatichi, S; Rimkus, S; Burlando, P; Bordoy, R

    2014-09-15

    Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. Copyright © 2013

  15. Climate variability and human impact on the environment in South America during the last 2000 years: synthesis and perspectives

    NASA Astrophysics Data System (ADS)

    Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

    2015-07-01

    An improved understanding of present-day climate variability and change relies on high-quality data sets from the past two millennia. Global efforts to reconstruct regional climate modes are in the process of validating and integrating paleo-proxies. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to its unknown spatial and temporal coverage. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last two millennia. We identify the pollen records with the required temporal characteristics for PAGES-2 ka climate modelling and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local scale responses to climate modes, thus it is necessary to understand how vegetation-climate interactions might diverge under variable settings. Additionally, pollen is an excellent indicator of human impact through time. Evidence for human land use in pollen records is useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. The LOTRED-SA-2 k initiative provides the ideal framework for the integration of the various paleoclimatic sub-disciplines and paleo-science, thereby jumpstarting and fostering multi-disciplinary research into environmental change on centennial and millennial time scales.

  16. Sporadic sampling, not climatic forcing, drives observed early hominin diversity.

    PubMed

    Maxwell, Simon J; Hopley, Philip J; Upchurch, Paul; Soligo, Christophe

    2018-05-08

    The role of climate change in the origin and diversification of early hominins is hotly debated. Most accounts of early hominin evolution link observed fluctuations in species diversity to directional shifts in climate or periods of intense climatic instability. None of these hypotheses, however, have tested whether observed diversity patterns are distorted by variation in the quality of the hominin fossil record. Here, we present a detailed examination of early hominin diversity dynamics, including both taxic and phylogenetically corrected diversity estimates. Unlike past studies, we compare these estimates to sampling metrics for rock availability (hominin-, primate-, and mammal-bearing formations) and collection effort, to assess the geological and anthropogenic controls on the sampling of the early hominin fossil record. Taxic diversity, primate-bearing formations, and collection effort show strong positive correlations, demonstrating that observed patterns of early hominin taxic diversity can be explained by temporal heterogeneity in fossil sampling rather than genuine evolutionary processes. Peak taxic diversity at 1.9 million years ago (Ma) is a sampling artifact, reflecting merely maximal rock availability and collection effort. In contrast, phylogenetic diversity estimates imply peak diversity at 2.4 Ma and show little relation to sampling metrics. We find that apparent relationships between early hominin diversity and indicators of climatic instability are, in fact, driven largely by variation in suitable rock exposure and collection effort. Our results suggest that significant improvements in the quality of the fossil record are required before the role of climate in hominin evolution can be reliably determined. Copyright © 2018 the Author(s). Published by PNAS.

  17. Uncertain Classification of Variable Stars: Handling Observational GAPS and Noise

    NASA Astrophysics Data System (ADS)

    Castro, Nicolás; Protopapas, Pavlos; Pichara, Karim

    2018-01-01

    Automatic classification methods applied to sky surveys have revolutionized the astronomical target selection process. Most surveys generate a vast amount of time series, or “lightcurves,” that represent the brightness variability of stellar objects in time. Unfortunately, lightcurves’ observations take several years to be completed, producing truncated time series that generally remain without the application of automatic classifiers until they are finished. This happens because state-of-the-art methods rely on a variety of statistical descriptors or features that present an increasing degree of dispersion when the number of observations decreases, which reduces their precision. In this paper, we propose a novel method that increases the performance of automatic classifiers of variable stars by incorporating the deviations that scarcity of observations produces. Our method uses Gaussian process regression to form a probabilistic model of each lightcurve’s observations. Then, based on this model, bootstrapped samples of the time series features are generated. Finally, a bagging approach is used to improve the overall performance of the classification. We perform tests on the MAssive Compact Halo Object (MACHO) and Optical Gravitational Lensing Experiment (OGLE) catalogs, results show that our method effectively classifies some variability classes using a small fraction of the original observations. For example, we found that RR Lyrae stars can be classified with ~80% accuracy just by observing the first 5% of the whole lightcurves’ observations in the MACHO and OGLE catalogs. We believe these results prove that, when studying lightcurves, it is important to consider the features’ error and how the measurement process impacts it.

  18. Cataclysmic variables to be monitored for HST observations

    NASA Astrophysics Data System (ADS)

    Waagen, Elizabeth O.

    2012-09-01

    Drs. Boris Gaensicke (Warwick University), Joseph Patterson (Columbia University, Center for Backyard Astrophysics), and Arne Henden (AAVSO), on behalf of a consortium of 16 astronomers, requested the help of AAVSO observers in monitoring the ~40 cataclysmic variables in support of Hubble Space Telescope observations in the coming months. The HST COS (Cosmic Origins Spectrograph) will be carrying out far-ultraviolet spectroscopy of ~40 CVs sequentially, with the aim to measure the temperatures, atmospheric compositions, rotation rates, and eventually masses of their white dwarfs. The primary purpose of the monitoring is to know whether each target is in quiescence immediately prior to the observation window; if it is in outburst it will be too bright for the HST instrumentation. Based on the information supplied by the AAVSO, the HST scheduling team will make the decision (usually) the evening before the scheduled observing time as to whether to go forward with the HST observations. For CCD observers, simultaneous photometry [shortly before, during, and after the HST observations] would be ideal. B filter would be best for a light curve, although for the magnitude estimates, V would be best. Finder charts may be created using the AAVSO Variable Star Plotter (http://www.aavso.org/vsp). Observations should be submitted to the AAVSO International Database. If the target is seen in outburst, please contact the AAVSO immediately and post a message to the Observations and Campaigns & Observations Reports forum (http://www.aavso.org/forum). This campaign will run the better part of a year or longer. See full Alert Notice for more details and list of objects.

  19. Climate Outreach Using Regional Coastal Ocean Observing System Portals

    NASA Astrophysics Data System (ADS)

    Anderson, D. M.; Hernandez, D. L.; Wakely, A.; Bochenek, R. J.; Bickel, A.

    2015-12-01

    Coastal oceans are dynamic, changing environments affected by processes ranging from seconds to millennia. On the east and west coast of the U.S., regional observing systems have deployed and sustained a remarkable diverse array of observing tools and sensors. Data portals visualize and provide access to real-time sensor networks. Portals have emerged as an interactive tool for educators to help students explore and understand climate. Bringing data portals to outreach events, into classrooms, and onto tablets and smartphones enables educators to address topics and phenomena happening right now. For example at the 2015 Charleston Science Technology Engineering and Math (STEM) Festival, visitors navigated the SECOORA (Southeast Coastal Ocean Observing regional Association) data portal to view the real-time marine meteorological conditions off South Carolina. Map-based entry points provide an intuitive interface for most students, an array of time series and other visualizations depict many of the essential principles of climate science manifest in the coastal zone, and data down-load/ extract options provide access to the data and documentation for further inquiry by advanced users. Beyond the exposition of climate principles, the portal experience reveals remarkable technologies in action and shows how the observing system is enabled by the activity of many different partners.

  20. Spatio-temporal Variability of Stratified Snowpack Cold Content Observed in the Rocky Mountains

    NASA Astrophysics Data System (ADS)

    Schmidt, J. S.; Sexstone, G. A.; Serreze, M. C.

    2017-12-01

    Snowpack cold content (CCsnow) is the energy required to bring a snowpack to an isothermal temperature of 0.0°C. The spatio-temporal variability of CCsnow is complex as it is a measure that integrates the response of a snowpack to each component of the snow-cover energy balance. Snow and ice at high elevation is climate sensitive water storage for the Western U.S. Therefore, an improved understanding of the spatio-temporal variability of CCsnow may provide insight into snowpack dynamics and sensitivity to climate change. In this study, stratified snowpit observations of snow water equivalent (SWE) and snow temperature (Tsnow) from the USGS Rocky Mountain Snowpack network (USGS RMS) were used to evaluate vertical CCsnow profiles over a 16-year period in Montana, Idaho, Wyoming, Colorado and New Mexico. Since 1993, USGS RMS has collected snow chemistry, snow temperature, and SWE data throughout the Rocky Mountain region, making it well positioned for Anthropocene cryosphere benchmarking and climate change interpretation. Spatial grouping of locations based on similar CCsnow characteristics was evaluated and trend analyses were performed. Additionally, we evaluated the regional relation of CCsnow to snowmelt timing. CCsnow was more precisely calculated and more representative using vertically stratified field observed values than bulk values, which highlights the utility of the snowpack dataset presented here. Location specific annual and 16 year mean stratified snowpit profiles of SWE, Tsnow, and CCsnow well represent the physical geography and past weather patterns acting on the snowpack. Observed trends and spatial variability of CCsnow profiles explored by this study provides an improved understanding of changing snowpack behavior in the western U.S., and will be useful for assessing the regional sensitivity of snowpacks to future climate change.

  1. How does complex terrain influence responses of carbon and water cycle processes to climate variability and climate change?

    EPA Science Inventory

    We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site…

  2. About the relationships among variables observed in the real world

    NASA Astrophysics Data System (ADS)

    Petkov, Boyan H.

    2018-06-01

    Since a stationary chaotic system is determined by nonlinear equations connecting its components, the appurtenance of two variables to such a system has been considered a sign of nontrivial relationships between them including also other quantities. These relationships could remain hidden for the approach usually employed in the research analyses, which is based on the extent of the correlation that characterises the dependence of one variable on the other. The appurtenance to the same system can be hypothesized if the topological features of the attractors reconstructed from two time series representing the evolution of the corresponding variables are close to each other. However, the possibility that both attractors represent different systems with similar behaviour cannot be excluded. For that reason, an approach allowing the reconstruction of the attractor by using jointly two time series was proposed and the conclusion about the common origin of the variables under study can be made if this attractor is topologically similar to those built separately from the two time series. In the present study, the features of the attractors were presented by the correlation dimension and the largest Lyapunov exponent and the proposed algorithm has been tested on numerically generated sequences obtained from various maps. It is believed that this approach could be used to reveal connections among the variables observed in experiments or field measurements.

  3. Workshop on Satellite and In situ Observations for Climate Prediction

    SciTech Connect

    Acker, J.G.; Busalacchi, A.

    1995-02-01

    Participants in this workshop, which convened in Venice, Italy, 6-8 May 1993, met to consider the current state of climate monitoring programs and instrumentation for the purpose of climatological prediction on short-term (seasonal to interannual) timescales. Data quality and coverage requirements for definition of oceanographic heat and momentum fluxes, scales of inter- and intra-annual variability, and land-ocean-atmosphere exchange processes were examined. Advantages and disadvantages of earth-based and spaceborne monitoring systems were considered, as were the structures for future monitoring networks, research programs, and modeling studies.

  4. Workshop on Satellite and In situ Observations for Climate Prediction

    NASA Technical Reports Server (NTRS)

    Acker, James G.; Busalacchi, Antonio

    1995-01-01

    Participants in this workshop, which convened in Venice, Italy, 6-8 May 1993, met to consider the current state of climate monitoring programs and instrumentation for the purpose of climatological prediction on short-term (seasonal to interannual) timescales. Data quality and coverage requirements for definition of oceanographic heat and momentum fluxes, scales of inter- and intra-annual variability, and land-ocean-atmosphere exchange processes were examined. Advantages and disadvantages of earth-based and spaceborne monitoring systems were considered, as were the structures for future monitoring networks, research programs, and modeling studies.

  5. Macroweather Predictions and Climate Projections using Scaling and Historical Observations

    NASA Astrophysics Data System (ADS)

    Hébert, R.; Lovejoy, S.; Del Rio Amador, L.

    2017-12-01

    There are two fundamental time scales that are pertinent to decadal forecasts and multidecadal projections. The first is the lifetime of planetary scale structures, about 10 days (equal to the deterministic predictability limit), and the second is – in the anthropocene – the scale at which the forced anthropogenic variability exceeds the internal variability (around 16 – 18 years). These two time scales define three regimes of variability: weather, macroweather and climate that are respectively characterized by increasing, decreasing and then increasing varibility with scale.We discuss how macroweather temperature variability can be skilfully predicted to its theoretical stochastic predictability limits by exploiting its long-range memory with the Stochastic Seasonal and Interannual Prediction System (StocSIPS). At multi-decadal timescales, the temperature response to forcing is approximately linear and this can be exploited to make projections with a Green’s function, or Climate Response Function (CRF). To make the problem tractable, we exploit the temporal scaling symmetry and restrict our attention to global mean forcing and temperature response using a scaling CRF characterized by the scaling exponent H and an inner scale of linearity τ. An aerosol linear scaling factor α and a non-linear volcanic damping exponent ν were introduced to account for the large uncertainty in these forcings. We estimate the model and forcing parameters by Bayesian inference using historical data and these allow us to analytically calculate a median (and likely 66% range) for the transient climate response, and for the equilibrium climate sensitivity: 1.6K ([1.5,1.8]K) and 2.4K ([1.9,3.4]K) respectively. Aerosol forcing typically has large uncertainty and we find a modern (2005) forcing very likely range (90%) of [-1.0, -0.3] Wm-2 with median at -0.7 Wm-2. Projecting to 2100, we find that to keep the warming below 1.5 K, future emissions must undergo cuts similar to Representative

  6. Impacts of uncertainties in European gridded precipitation observations on regional climate analysis.

    PubMed

    Prein, Andreas F; Gobiet, Andreas

    2017-01-01

    Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio-temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan-European data sets and a set that combines eight very high-resolution station-based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post-processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small-scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate-mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments.

  7. Interannual to decadal climate variability of sea salt aerosols in the coupled climate model CESM1.0: Climate variability of sea salt aerosols

    SciTech Connect

    Xu, Li; Pierce, David W.; Russell, Lynn M.

    This study examines multi-year climate variability associated with sea salt aerosols and their contribution to the variability of shortwave cloud forcing (SWCF) using a 150-year simulation for pre-industrial conditions of the Community Earth System Model version 1.0 (CESM1). The results suggest that changes in sea salt and related cloud and radiative properties on interannual timescales are dominated by the ENSO cycle. Sea salt variability on longer (interdecadal) timescales is associated with low-frequency Pacific ocean variability similar to the interdecadal Pacific Oscillation (IPO), but does not show a statistically significant spectral peak. A multivariate regression suggests that sea salt aerosol variabilitymore » may contribute to SWCF variability in the tropical Pacific, explaining up to 25-35% of the variance in that region. Elsewhere, there is only a small aerosol influence on SWCF through modifying cloud droplet number and liquid water path that contributes to the change of cloud effective radius and cloud optical depth (and hence cloud albedo), producing a multi-year aerosol-cloud-wind interaction.« less

  8. Mesosphere-Stratosphere Coupling: Implications for Climate Variability and Trends

    NASA Technical Reports Server (NTRS)

    Baldwin, Mark P.

    2004-01-01

    A key aspect of this project is the establishment of a causal link from circulation anomalies in the lower mesosphere and stratopause region downward through the stratosphere to the troposphere. The observational link for stratospheric sudden warmings and surface climate is fairly clear. However, our understanding of the dynamics is incomplete. We have been making significant progress in the area of dynamical mechanisms by which circulation anomalies in the stratosphere affect the troposphere. We are trying to understand the details and sequence of events that occur when a middle atmosphere (wind) anomaly propagates downward to near the tropopause. The wind anomaly could be caused by a warming or solar variations in the low-latitude stratopause region, or could have other causes. The observations show a picture that is consistent with a circulation anomaly that descends to the tropopause region, and can be detected as low as the mid-troposphere. Processes near the stratopause in the tropics appear to be important precursors to the wintertime development of the northern polar vortex. This may affect significantly our understanding of the process by which low-latitude wind anomalies in the low mesosphere and upper stratosphere evolve through the winter and affect the polar vortex.

  9. Climate variability and Dinophysis acuta blooms in an upwelling system.

    PubMed

    Díaz, Patricio A; Ruiz-Villarreal, Manuel; Pazos, Yolanda; Moita, Teresa; Reguera, Beatriz

    2016-03-01

    Dinophysis acuta is a frequent seasonal lipophilic toxin producer in European Atlantic coastal waters associated with thermal stratification. In the Galician Rías, populations of D. acuta with their epicentre located off Aveiro (northern Portugal), typically co-occur with and follow those of Dinophysis acuminata during the upwelling transition (early autumn) as a result of longshore transport. During hotter than average summers, D. acuta blooms also occur in August in the Rías, when they replace D. acuminata. Here we examined a 30-year (1985-2014) time series of D. acuta from samples collected by the same method in the Galician Rías. Our main objective was to identify patterns of distribution and their relation with climate variability, and to explain the exceptional summer blooms of D. acuta in 1989-1990. A dome-shaped relationship was found between summer upwelling intensity and D. acuta blooms; cell maxima were associated with conditions where the balance between upwelling intensity and heating, leading to deepened thermoclines, combined with tidal phase (3 days after neap tides) created windows of opportunity for this species. The application of a generalized additive model based on biological (D. acuta inoculum) and environmental predictors (Cumulative June-August upwelling CUI JJA , average June-August SST JJA and tidal range) explained more than 70% of the deviance for the exceptional summer blooms of D. acuta, through a combination of moderate (35,000-50,000m 3 s -1 km -1 ) summer upwelling (CUI JJA ), thermal stratification (SST JJA >17°C) and moderate tidal range (∼2.5m), provided D. acuta cells (inoculum) were present in July. There was no evidence of increasing trends in D. acuta bloom frequency/intensity nor a clear relationship with NAO or other long-term climatic cycles. Instead, the exceptional summer blooms of 1989-1990 appeared linked to extreme hydroclimatic anomalies (high positive anomalies in SST and NAO index), which affected most of

  10. Changing Seasonality of Tundra Vegetation and Associated Climatic Variables

    NASA Astrophysics Data System (ADS)

    Bhatt, U. S.; Walker, D. A.; Raynolds, M. K.; Bieniek, P.; Epstein, H. E.; Comiso, J. C.; Pinzon, J.; Tucker, C. J.; Steele, M.; Ermold, W. S.; Zhang, J.

    2014-12-01

    This study documents changes in the seasonality of tundra vegetation productivity and its associated climate variables using long-term data sets. An overall increase of Pan-Arctic tundra greenness potential corresponds to increased land surface temperatures and declining sea ice concentrations. While sea ice has continued to decline, summer land surface temperature and vegetation productivity increases have stalled during the last decade in parts of the Arctic. To understand the processes behind these features we investigate additional climate parameters. This study employs remotely sensed weekly 25-km sea ice concentration, weekly surface temperature, and bi-weekly NDVI from 1982 to 2013. Maximum NDVI (MaxNDVI, Maximum Normalized Difference Vegetation Index), Time Integrated NDVI (TI-NDVI), Summer Warmth Index (SWI, sum of degree months above freezing during May-August), ocean heat content (PIOMAS, model incorporating ocean data assimilation), and snow water equivalent (GlobSnow, assimilated snow data set) are explored. We analyzed the data for the full period (1982-2013) and for two sub-periods (1982-1998 and 1999-2013), which were chosen based on the declining Pan-Arctic SWI since 1998. MaxNDVI has increased from 1982-2013 over most of the Arctic but has declined from 1999 to 2013 over western Eurasia, northern Canada, and southwest Alaska. TI-NDVI has trends that are similar to those for MaxNDVI for the full period but displays widespread declines over the 1999-2013 period. Therefore, as the MaxNDVI has continued to increase overall for the Arctic, TI-NDVI has been declining since 1999. SWI has large relative increases over the 1982-2013 period in eastern Canada and Greenland and strong declines in western Eurasia and southern Canadian tundra. Weekly Pan-Arctic tundra land surface temperatures warmed throughout the summer during the 1982-1998 period but display midsummer declines from 1999-2013. Weekly snow water equivalent over Arctic tundra has declined over

  11. Interannual variability in the gravity wave drag – vertical coupling and possible climate links

    NASA Astrophysics Data System (ADS)

    Šácha, Petr; Miksovsky, Jiri; Pisoft, Petr

    2018-05-01

    Gravity wave drag (GWD) is an important driver of the middle atmospheric dynamics. However, there are almost no observational constraints on its strength and distribution (especially horizontal). In this study we analyze orographic GWD (OGWD) output from Canadian Middle Atmosphere Model simulation with specified dynamics (CMAM-sd) to illustrate the interannual variability in the OGWD distribution at particular pressure levels in the stratosphere and its relation to major climate oscillations. We have found significant changes in the OGWD distribution and strength depending on the phase of the North Atlantic Oscillation (NAO), quasi-biennial oscillation (QBO) and El Niño-Southern Oscillation. The OGWD variability is shown to be induced by lower-tropospheric wind variations to a large extent, and there is also significant variability detected in near-surface momentum fluxes. We argue that the orographic gravity waves (OGWs) and gravity waves (GWs) in general can be a quick mediator of the tropospheric variability into the stratosphere as the modifications of the OGWD distribution can result in different impacts on the stratospheric dynamics during different phases of the studied climate oscillations.

  12. The variables V477 Peg and MW Com observation results

    NASA Astrophysics Data System (ADS)

    Bahý, V.; Gajtanska, M.; Hanisko, P.; Krišták, L.

    2018-04-01

    The paper deals with our results of the photometric observations of two variable stars and with basic interprettions of our results. We have observed the V477 Pegassi and MW Comae systems. We have obtained their light curves in the integral light and in the B, V, R and I filters. The color indices have been computed and there have been realized the models of the both systems by the usage of the BM3 software. These models are presented in our study too.

  13. Climate Variability In The Euro-atlantic Sector As Simulated By Echam4

    NASA Astrophysics Data System (ADS)

    Menezes, I.; Corte-Real, J.; Ramos, A.; Conde, F.

    The atmosphere is a fundamental component of the climate system and its influence in local and global climates results from its composition, structure and motion. The best available tools to simulate future climates are coupled atmosphere-ocean general circulation models (AOGCMs), ECHAM4 (T42 L19)[1] being a very relevant exam- ple of such a model due to its elaborated parametrizations of physical processes. The purpose of this work is twofold : (1) to assess the ability of ECHAM4 in reproducing the reference climate of 1961-1990, over the Euro-Atlantic sector (29N-71N; 67W- 59E) in terms of mean sea level pressure, surface temperature and total precipitation; (2) to evaluate the expected changes of the same climate elements in a warmer world. To attain the first goal the ECHAMSs control run output is compared with observed data obtained from the Climatic Research Unit (CRU data set)[2-5]; to achieve the second objective, the modelSs control run is compared with its transient run forced by greenhouse gases. In both cases, comparisons are made in terms of mean values, variability in space and time and extremes. References [1] E. Roeckner, K. Arpe, L. Bengtsson, M. Christoph, M. Claussen, L. Dümenil, M. Esch, M. Giorgetta, U. Schlese, and U. Schulzweida, 1996: The atmospheric gen- eral circulation model ECHAM4: Model description and simulation of present-day climate. Max Planck Institut für Meteorologie, Report No. 218, Hamburg, Germany, 90 pp. [2] M. Hulme, D. Conway, P.D. Jones, T. Jiang, E.M. Barrow, and C. Turney (1995), Construction of a 1961-90 European climatology for climate change impacts and mod- elling applications, Int. J. Climatol., 15, 1333-1363. [3] M. Hulme (1994), The cost of climate data U a European experience, Weather, 49, 168-175. [4] M. Hulme, and M.G. New (1997), Dependence of large-scale precipitation clima- tologies on temporal and spatial sampling, J. Climate, 10, 1099-1113. 1 [5] C.J. Willmot, S.M. Robeson and M.J. Janis (1996

  14. Mapping the changing pattern of local climate as an observed distribution

    NASA Astrophysics Data System (ADS)

    Chapman, Sandra; Stainforth, David; Watkins, Nicholas

    2013-04-01

    It is at local scales that the impacts of climate change will be felt directly and at which adaptation planning decisions must be made. This requires quantifying the geographical patterns in trends at specific quantiles in distributions of variables such as daily temperature or precipitation. Here we focus on these local changes and on the way observational data can be analysed to inform us about the pattern of local climate change. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs the pattern of variation in sensitivity with temperature (or occurrence likelihood), and with geographical location. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify and map the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, in press [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P

  15. Assessing Forest Carbon Response to Climate Change and Disturbances Using Long-term Hydro-climatic Observations and Simulations

    NASA Astrophysics Data System (ADS)

    Trettin, C.; Dai, Z.; Amatya, D. M.

    2014-12-01

    Long-term climatic and hydrologic observations on the Santee Experimental Forest in the lower coastal plain of South Carolina were used to estimate long-term changes in hydrology and forest carbon dynamics for a pair of first-order watersheds. Over 70 years of climate data indicated that warming in this forest area in the last decades was faster than the global mean; 35+ years of hydrologic records showed that forest ecosystem succession three years following Hurricane Hugo caused a substantial change in the ratio of runoff to precipitation. The change in this relationship between the paired watersheds was attributed to altered evapotranspiration processes caused by greater abundance of pine in the treatment watershed and regeneration of the mixed hardwood-pine forest on the reference watershed. The long-term records and anomalous observations are highly valuable for reliable calibration and validation of hydrological and biogeochemical models capturing the effects of climate variability. We applied the hydrological model MIKESHE that showed that runoff and water table level are sensitive to global warming, and that the sustained warming trends can be expected to decrease stream discharge and lower the mean water table depth. The spatially-explicit biogeochemical model Forest-DNDC, validated using biomass measurements from the watersheds, was used to assess carbon dynamics in response to high resolution hydrologic observation data and simulation results. The simulations showed that the long-term spatiotemporal carbon dynamics, including biomass and fluxes of soil carbon dioxide and methane were highly regulated by disturbance regimes, climatic conditions and water table depth. The utility of linked-modeling framework demonstrated here to assess biogeochemical responses at the watershed scale suggests applications for assessing the consequences of climate change within an urbanizing forested landscape. The approach may also be applicable for validating large

  16. Trend and variability in western and central Africa streamflow, and their relation to climate variability between 1950 and 2010

    NASA Astrophysics Data System (ADS)

    Sidibe, Moussa; Dieppois, Bastien; Mahé, Gil; Paturel, Jean-Emmanuel; Rouché, Nathalie; Amoussou, Ernest; Anifowose, Babatunde; Lawler, Damian

    2017-04-01

    Unprecedented drought episodes that struck western and central Africa between the late 1960s and 1980s. This triggered many studies investigating rainfall variability and its impacts on food production systems. However, most studies were focused at the catchment scale. In this study, we examine how rainfall variability has impacted on river flow at the subcontinental scale between 1950 and 2010, as well as the key large-scale controls on this relationship. For the first time, we establish a complete, gap-filled, monthly streamflow data set, which extends from 1950 to 2010, over the western and central African region. To achieve this, we used linear regression modelling across and between 600 flow gauging stations (see initial database information at http://www.hydrosciences.fr/sierem/index_en.htm). Streamflow trend and variability are then seasonally assessed at this subcontinental scale and compared to those observed in three different rainfall data sets (i.e. CRU TS3.24, GPCC V7, IRD-HSM). Long-term trends and variability in streamflow are mainly consistent with trends in rainfall. However, these relationships may have been moderated by: i) changes in land use; and ii) contributions from groundwater resources. In particular, we note that the recent post 1990s partial recovery in Sahel rainfall could have, at least partially, positively impacted river flows (e.g. the Senegal and Niger rivers). Using multi-temporal trend and continuous wavelet analysis, the time-evolution of western and central African river flows are analysed, and are all characterized by very strong decadal fluctuations, which can be interpreted as modulations in the baseflow. These decadal fluctuations, which are also significantly detected in rainfall, are likely related to large-scale sea-surface temperature (SST) anomaly patterns, such as the tropical Atlantic SST variability, the Atlantic Multidecadal Oscillation, the Interdecadal Pacific Oscillation and/or the Pacific Decadal Oscillation

  17. Australia: Climate-Ecosystem Variability and Impacts on Disease

    NASA Astrophysics Data System (ADS)

    Gustafson, K. C.; Diabate, M.; Anyamba, A.

    2012-12-01

    Climate variability in Australia is largely driven by an atmospheric phenomenon called the Southern Oscillation (SO), which involves a see-saw like behavior between low and high pressure systems within the equatorial Pacific regions. The interaction of SO with abnormally high sea surface temperatures (SSTs) – El Niño – or abnormally low SSTs – La Niña (“anti-El Niño”) – creates extreme drought or extreme flooding respectively throughout the Australian continent. These El Niño-Southern Oscillation (ENSO) events have significant impacts on Australia’s landscape, ecosystems, agriculture production, and, as this report show, human health. The teleconnection between ENSO and human health is straight forward but not obvious. During La Niña years, when ENSO events are characterized by increased rainfall and consequential flooding, Australia’s tropical, warm climate in addition to an associated increase in vegetation growth from the increased rainfall creates an ideal habitat for mosquito population increase. Certain species of Australian mosquitoes [Culux annulirostris] are carriers of Murray Valley Encephalitis (MVE) virus which is a rare but potentially fatal infection that attacks neurological and muscular functioning. It is hypothesized that a widespread increase in vegetation indicates an expansion of ideal mosquito production habitats and will translate to an increased risk of MVE contraction. The objective of this research is to show if a correlation exists between the ENSO-driven climate- and consequential ecosystem- changes and MVE outbreaks throughout Australia. To do so, this study makes use of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor operating on NASA’s Terra satellite to obtain monthly Normalized Difference Vegetation Index (NDVI) data. It is assumed in this research that an anomalous increase in NDVI values – indicative of vegetation growth – occurs as a result of increased rainfall. Due to Australia’s tropical positioning and

  18. Climate variables explain neutral and adaptive variation within salmonid metapopulations: The importance of replication in landscape genetics

    USGS Publications Warehouse

    Hand, Brian K.; Muhlfeld, Clint C.; Wade, Alisa A.; Kovach, Ryan; Whited, Diane C.; Narum, Shawn R.; Matala, Andrew P.; Ackerman, Michael W.; Garner, B. A.; Kimball, John S; Stanford, Jack A.; Luikart, Gordon

    2016-01-01

    Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

  19. Multiproxy evidence of Holocene climate variability from estuarine sediments, eastern North America

    USGS Publications Warehouse

    Cronin, T. M.; Thunell, R.; Dwyer, G.S.; Saenger, C.; Mann, M.E.; Vann, C.; Seal, R.R.

    2005-01-01

    We reconstructed paleoclimate patterns from oxygen and carbon isotope records from the fossil estuarine benthic foraminifera Elphidium and Mg/ Ca ratios from the ostracode Loxoconcha from sediment cores from Chesapeake Bay to examine the Holocene evolution of North Atlantic Oscillation (NAO)-type climate variability. Precipitation-driven river discharge and regional temperature variability are the primary influences on Chesapeake Bay salinity and water temperature, respectively. We first calibrated modern ??18 Owater to salinity and applied this relationship to calculate trends in paleosalinity from the ??18 Oforam, correcting for changes in water temperature estimated from ostracode Mg /Ca ratios. The results indicate a much drier early Holocene in which mean paleosalinity was ???28 ppt in the northern bay, falling ???25% to ???20 ppt during the late Holocene. Early Holocene Mg/Ca-derived temperatures varied in a relatively narrow range of 13?? to 16??C with a mean temperature of 14.2??C and excursions above 16??C; the late Holocene was on average cooler (mean temperature of 12.8??C). In addition to the large contrast between early and late Holocene regional climate conditions, multidecadal (20-40 years) salinity and temperature variability is an inherent part of the region’s climate during both the early and late Holocene, including the Medieval Warm Period and Little Ice Age. These patterns are similar to those observed during the twentieth century caused by NAO-related processes. Comparison of the midlatitude Chesapeake Bay salinity record with tropical climate records of Intertropical Convergence Zone fluctuations inferred from the Cariaco Basin titanium record suggests an anticorrelation between precipitation in the two regions at both millennial and centennial timescales. Copyright 2005 by the American Geophysical Union.

  20. Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and ‘Trends’

    NASA Technical Reports Server (NTRS)

    Molnar, Gyula; Susskind, Joel

    2008-01-01

    The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1×1 degree grid-scale “trend”-analyses of important atmospheric parameters for this 5-year period. Note that here “trend” simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

  1. Back to the Future -Precipitation Extremes, Climate Variability, Environmental Planning and Adaptation

    NASA Astrophysics Data System (ADS)

    Barros, A. P.

    2008-12-01

    –“The last major climatic oscillation peak was about 1856, or 74 years ago. Practically all of our important railroad and public highway work has been done since that time. Most of our parks systems driveways, and roads of all type for auto travel, in the various States, have been completed within the past 30 years, namely, beginning at the very lowest point of our climatic swing (1900-1910). There is every reason to believe, therefore, as the next 20 years comes on apace, we will witness considerable damage to work done during the past regime of weather.”– Schuman, 1931 At the beginning of the 21st century, as at the beginning of the 20th century, the fundamental question is whether the nation is more prepared for natural disasters today than it was eight decades ago. Indeed, the question is whether the best science, engineering and policy tools are in place to prepare for and respond to extreme events. Changes in the risk and magnitude of extreme precipitation events rank among the most studied impacts, and indicators (symptoms) of climatic variations. Extreme precipitation translates generally into extreme flooding, landslides, collapse of lifeline infrastructure, and the breakdown of public health services among others. In approaching the problem of quantifying the risk and magnitude of extreme precipitation events, there are two major challenges: 1) it is difficult to characterize “observed” (20th century) conditions due to the lack of long-term observations – i.e., short and incomplete historical records; and 2) it is difficult to characterize “predicted” (21st century) conditions due to the lack of skill of precipitation forecasts at spatial and temporal scales meaningful for impact studies, and the short-duration of climate model simulations themselves. The first challenge translates in estimating the probability of occurrence (rare) and magnitude (very large) of events that may have not happened yet. The second challenge is that of quantifying

  2. Enceladus Plume Structure and Time Variability: Comparison of Cassini Observations

    PubMed Central

    Perry, Mark E.; Hansen, Candice J.; Waite, J. Hunter; Porco, Carolyn C.; Spencer, John R.; Howett, Carly J. A.

    2017-01-01

    Abstract During three low-altitude (99, 66, 66 km) flybys through the Enceladus plume in 2010 and 2011, Cassini’s ion neutral mass spectrometer (INMS) made its first high spatial resolution measurements of the plume’s gas density and distribution, detecting in situ the individual gas jets within the broad plume. Since those flybys, more detailed Imaging Science Subsystem (ISS) imaging observations of the plume’s icy component have been reported, which constrain the locations and orientations of the numerous gas/grain jets. In the present study, we used these ISS imaging results, together with ultraviolet imaging spectrograph stellar and solar occultation measurements and modeling of the three-dimensional structure of the vapor cloud, to constrain the magnitudes, velocities, and time variability of the plume gas sources from the INMS data. Our results confirm a mixture of both low and high Mach gas emission from Enceladus’ surface tiger stripes, with gas accelerated as fast as Mach 10 before escaping the surface. The vapor source fluxes and jet intensities/densities vary dramatically and stochastically, up to a factor 10, both spatially along the tiger stripes and over time between flyby observations. This complex spatial variability and dynamics may result from time-variable tidal stress fields interacting with subsurface fissure geometry and tortuosity beyond detectability, including changing gas pathways to the surface, and fluid flow and boiling in response evolving lithostatic stress conditions. The total plume gas source has 30% uncertainty depending on the contributions assumed for adiabatic and nonadiabatic gas expansion/acceleration to the high Mach emission. The overall vapor plume source rate exhibits stochastic time variability up to a factor ∼5 between observations, reflecting that found in the individual gas sources/jets. Key Words: Cassini at Saturn—Geysers—Enceladus—Gas dynamics—Icy satellites. Astrobiology 17, 926–940. PMID:28872900

  3. Spatio-temporal Trends of Climate Variability in North Carolina

    NASA Astrophysics Data System (ADS)

    Sayemuzzaman, Mohammad

    Climatic trends in spatial and temporal variability of maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tmean) and precipitation were evaluated for 249 ground-based stations in North Carolina for 1950-2009. The Mann-Kendall (MK), the Theil-Sen Approach (TSA) and the Sequential Mann-Kendall (SQMK) tests were applied to quantify the significance of trend, magnitude of trend and the trend shift, respectively. The lag-1 serial correlation and double mass curve techniques were used to address the data independency and homogeneity. The pre-whitening technique was used to eliminate the effect of auto correlation of the data series. The difference between minimum and maximum temperatures, and so the diurnal temperature range (DTR), at some stations was found to be decreasing on both an annual and a seasonal basis, with an overall increasing trend in the mean temperature. For precipitation, a statewide increasing trend in fall (highest in November) and decreasing trend in winter (highest in February) were detected. No pronounced increasing/decreasing trends were detected in annual, spring, and summer precipitation time series. Trend analysis on a spatial scale (for three physiographic regions: mountain, piedmont and coastal) revealed mixed results. Coastal zone exhibited increasing mean temperature (warming) trend as compared to other locations whereas mountain zone showed decreasing trend (cooling). Three main moisture components (precipitation, total cloud cover, and soil moisture) and the two major atmospheric circulation modes (North Atlantic Oscillation and Southern Oscillation) were used for correlative analysis purposes with the temperature (specifically with DTR) and precipitation trends. It appears that the moisture components are associated with DTR more than the circulation modes in North Carolina.

  4. Population variability complicates the accurate detection of climate change responses.

    PubMed

    McCain, Christy; Szewczyk, Tim; Bracy Knight, Kevin

    2016-06-01

    The rush to assess species’ responses to anthropogenic climate change (CC) has underestimated the importance of interannual population variability (PV). Researchers assume sampling rigor alone will lead to an accurate detection of response regardless of the underlying population fluctuations of the species under consideration. Using population simulations across a realistic, empirically based gradient in PV, we show that moderate to high PV can lead to opposite and biased conclusions about CC responses. Between pre- and post-CC sampling bouts of modeled populations as in resurvey studies, there is: (i) A 50% probability of erroneously detecting the opposite trend in population abundance change and nearly zero probability of detecting no change. (ii) Across multiple years of sampling, it is nearly impossible to accurately detect any directional shift in population sizes with even moderate PV. (iii) There is up to 50% probability of detecting a population extirpation when the species is present, but in very low natural abundances. (iv) Under scenarios of moderate to high PV across a species’ range or at the range edges, there is a bias toward erroneous detection of range shifts or contractions. Essentially, the frequency and magnitude of population peaks and troughs greatly impact the accuracy of our CC response measurements. Species with moderate to high PV (many small vertebrates, invertebrates, and annual plants) may be inaccurate ‘canaries in the coal mine’ for CC without pertinent demographic analyses and additional repeat sampling. Variation in PV may explain some idiosyncrasies in CC responses detected so far and urgently needs more careful consideration in design and analysis of CC responses. © 2016 John Wiley & Sons Ltd.

  5. Delayed detection of climate mitigation benefits due to climate inertia and variability.

    PubMed

    Tebaldi, Claudia; Friedlingstein, Pierre

    2013-10-22

    Climate change mitigation acts by reducing greenhouse gas emissions, and thus curbing, or even reversing, the increase in their atmospheric concentration. This reduces the associated anthropogenic radiative forcing, and hence the size of the warming. Because of the inertia and internal variability affecting the climate system and the global carbon cycle, it is unlikely that a reduction in warming would be immediately discernible. Here we use 21st century simulations from the latest ensemble of Earth System Model experiments to investigate and quantify when mitigation becomes clearly discernible. We use one of the scenarios as a reference for a strong mitigation strategy, Representative Concentration Pathway (RCP) 2.6 and compare its outcome with either RCP4.5 or RCP8.5, both of which are less severe mitigation pathways. We analyze global mean atmospheric CO2, and changes in annually and seasonally averaged surface temperature at global and regional scales. For global mean surface temperature, the median detection time of mitigation is about 25-30 y after RCP2.6 emissions depart from the higher emission trajectories. This translates into detection of a mitigation signal by 2035 or 2045, depending on whether the comparison is with RCP8.5 or RCP4.5, respectively. The detection of climate benefits of emission mitigation occurs later at regional scales, with a median detection time between 30 and 45 y after emission paths separate. Requiring a 95% confidence level induces a delay of several decades, bringing detection time toward the end of the 21st century.

  6. Globally Gridded Satellite (GridSat) Observations for Climate Studies

    NASA Technical Reports Server (NTRS)

    Knapp, Kenneth R.; Ansari, Steve; Bain, Caroline L.; Bourassa, Mark A.; Dickinson, Michael J.; Funk, Chris; Helms, Chip N.; Hennon, Christopher C.; Holmes, Christopher D.; Huffman, George J.; hidehide

    2012-01-01

    Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them: there is no central archive of geostationary data for all international satellites, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multi-satellite climate studies. The International Satellite Cloud Climatology Project set the stage for overcoming these issues by archiving a subset of the full resolution geostationary data at approx.10 km resolution at 3 hourly intervals since 1983. Recent efforts at NOAA s National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in the netCDF format using standards that permit a wide variety of tools and libraries to quickly and easily process the data. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone.

  7. Observed Decrease of North American Winter Temperature Variability

    NASA Astrophysics Data System (ADS)

    Rhines, A. N.; Tingley, M.; McKinnon, K. A.; Huybers, P. J.

    2015-12-01

    There is considerable interest in determining whether temperature variability has changed in recent decades. Model ensembles project that extratropical land temperature variance will detectably decrease by 2070. We use quantile regression of station observations to show that decreasing variability is already robustly detectable for North American winter during 1979–2014. Pointwise trends from GHCND stations are mapped into a continuous spatial field using thin-plate spline regression, resolving small-scales while providing uncertainties accounting for spatial covariance and varying station density. We find that variability of daily temperatures, as measured by the difference between the 95th and 5th percentiles, has decreased markedly in winter for both daily minima and maxima. Composites indicate that the reduced spread of winter temperatures primarily results from Arctic amplification decreasing the meridional temperature gradient. Greater observed warming in the 5th relative to the 95th percentile stems from asymmetric effects of advection during cold versus warm days; cold air advection is generally from northerly regions that have experienced greater warming than western or southwestern regions that are generally sourced during warm days.

  8. Association of genetic and phenotypic variability with geography and climate in three southern California oaks.

    PubMed

    Riordan, Erin C; Gugger, Paul F; Ortego, Joaquín; Smith, Carrie; Gaddis, Keith; Thompson, Pam; Sork, Victoria L

    2016-01-01

    Geography and climate shape the distribution of organisms, their genotypes, and their phenotypes. To understand historical and future evolutionary and ecological responses to climate, we compared the association of geography and climate of three oak species (Quercus engelmannii, Quercus berberidifolia, and Quercus cornelius-mulleri) in an environmentally heterogeneous region of southern California at three organizational levels: regional species distributions, genetic variation, and phenotypic variation. We identified climatic variables influencing regional distribution patterns using species distribution models (SDMs), and then tested whether those individual variables are important in shaping genetic (microsatellite) and phenotypic (leaf morphology) variation. We estimated the relative contributions of geography and climate using multivariate redundancy analyses (RDA) with variance partitioning. The modeled distribution of each species was influenced by climate differently. Our analysis of genetic variation using RDA identified small but significant associations between genetic variation with climate and geography in Q. engelmannii and Q. cornelius-mulleri, but not in Q. berberidifolia, and climate explained more of the variation. Our analysis of phenotypic variation in Q. engelmannii indicated that climate had more impact than geography, but not in Q. berberidifolia. Throughout our analyses, we did not find a consistent pattern in effects of individual climatic variables. Our comparative analysis illustrates that climate influences tree response at all organizational levels, but the important climate factors vary depending on the level and on the species. Because of these species-specific and level-specific responses, today’s sympatric species are unlikely to have similar distributions in the future. © 2016 Botanical Society of America.

  9. Hydrological Excitations of Polar Motion Derived from Different Variables of Fgoals – g2 Climate Model

    NASA Astrophysics Data System (ADS)

    Winska, M.

    2016-12-01

    The hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from climate model as well as from GRACE (Gravity Recovery and Climate Experiment) data is discussed here for the period 2002.3-2016.0. The data set used here are Earth Orientation Parameters Combined 04 (EOP C04), Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOAL-g2) and Global Land Data Assimilation System (GLDAS) climate models and GRACE CSR RL05 data for polar motion, hydrological and gravimetric excitation, respectively. Several Hydrological Angular Momentum (HAM) functions are calculated here from the selected variables: precipitation, evaporation, runoff, soil moisture, accumulated snow of the FGOALS and GLDAS climate models as well as from the global mass change fields from GRACE data provided by the International Earth Rotation and Reference System Service (IERS) Global Geophysical Fluids Center (GGFC). The contribution of different HAM excitation functions to achieve the full agreement between geodetic observations and geophysical excitation functions of polar motion is studied here.

  10. Productivity in the barents sea–response to recent climate variability.

    PubMed

    Dalpadado, Padmini; Arrigo, Kevin R; Hjøllo, Solfrid S; Rey, Francisco; Ingvaldsen, Randi B; Sperfeld, Erik; van Dijken, Gert L; Stige, Leif C; Olsen, Are; Ottersen, Geir

    2014-01-01

    The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region.

  11. Curve number method response to historical climate variability and trends

    USDA-ARS?s Scientific Manuscript database

    With the dependence on the curve number (CN) model by the engineering community, the question arises as to whether changes in climate may affect the performance of the CN algorithm which impacts estimates of runoff. A study was conducted to determine the effects of “climate period” (period of unifor…

  12. Climate Variability and Change in the Mediterranean Region

    NASA Astrophysics Data System (ADS)

    Lionello, Piero; Özsoy, Emin; Planton, Serge; Zanchetta, Giovanni

    2017-04-01

    This special issue collects new research results on the climate of the Mediterranean region. It covers traditional topics of the MedCLIVAR programme (www.medclivar.eu, Lionello et al. 2006, Lionello et al. 2012b) being devoted to papers addressing on-going and future climate changes in the Mediterranean region and their impacts on its environment.

  13. Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China

    PubMed Central

    Zhang, Ling; Nan, Zhuotong; Xu, Yi; Li, Shuo

    2016-01-01

    Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995–2014) and near future (2015–2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses. PMID:27348224

  14. Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China.

    PubMed

    Zhang, Ling; Nan, Zhuotong; Xu, Yi; Li, Shuo

    2016-01-01

    Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995-2014) and near future (2015-2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses.

  15. Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon-Cerrado border

    NASA Astrophysics Data System (ADS)

    Ane Dionizio, Emily; Heil Costa, Marcos; de Almeida Castanho, Andrea D.; Ferreira Pires, Gabrielle; Schwantes Marimon, Beatriz; Hur Marimon-Junior, Ben; Lenza, Eddie; Martins Pimenta, Fernando; Yang, Xiaojuan; Jain, Atul K.

    2018-02-01

    Climate, fire and soil nutrient limitation are important elements that affect vegetation dynamics in areas of the forest-savanna transition. In this paper, we use the dynamic vegetation model INLAND to evaluate the influence of interannual climate variability, fire and phosphorus (P) limitation on Amazon-Cerrado transitional vegetation structure and dynamics. We assess how each environmental factor affects net primary production, leaf area index and aboveground biomass (AGB), and compare the AGB simulations to an observed AGB map. We used two climate data sets (monthly average climate for 1961-1990 and interannual climate variability for 1948-2008), two data sets of total soil P content (one based on regional field measurements and one based on global data), and the INLAND fire module. Our results show that the inclusion of interannual climate variability, P limitation and fire occurrence each contribute to simulating vegetation types that more closely match observations. These effects are spatially heterogeneous and synergistic. In terms of magnitude, the effect of fire is strongest and is the main driver of vegetation changes along the transition. Phosphorus limitation, in turn, has a stronger effect on transitional ecosystem dynamics than interannual climate variability does. Overall, INLAND typically simulates more than 80 % of the AGB variability in the transition zone. However, the AGB in many places is clearly not well simulated, indicating that important soil and physiological factors in the Amazon-Cerrado border region, such as lithology, water table depth, carbon allocation strategies and mortality rates, still need to be included in the model.

  16. An observationally centred method to quantify local climate change as a distribution

    NASA Astrophysics Data System (ADS)

    Stainforth, David; Chapman, Sandra; Watkins, Nicholas

    2013-04-01

    For planning and adaptation, guidance on trends in local climate is needed at the specific thresholds relevant to particular impact or policy endeavours. This requires quantifying trends at specific quantiles in distributions of variables such as daily temperature or precipitation. These non-normal distributions vary both geographically and in time. The trends in the relevant quantiles may not simply follow the trend in the distribution mean. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs how the trend or sensitivity varies with temperature (or occurrence likelihood), and with geographical location. These sensitivities are found to be geographically varying across Europe; as one would expect given the different influences on local climate between, say, Western Scotland and central Italy. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C

  17. Beyond a Climate-Centric View of Plant Distribution: Edaphic Variables Add Value to Distribution Models

    PubMed Central

    Beauregard, Frieda; de Blois, Sylvie

    2014-01-01

    Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species’ characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for

  18. Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models.

    PubMed

    Beauregard, Frieda; de Blois, Sylvie

    2014-01-01

    Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species’ characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential

  19. Stratospheric Aerosol–Observations, Processes, and Impact on Climate

    NASA Technical Reports Server (NTRS)

    Kresmer, Stefanie; Thomason, Larry W.; von Hobe, Marc; Hermann, Markus; Deshler, Terry; Timmreck, Claudia; Toohey, Matthew; Stenke, Andrea; Schwarz, Joshua P.; Weigel, Ralf; hidehide

    2016-01-01

    Interest in stratospheric aerosol and its role in climate have increased over the last decade due to the observed increase in stratospheric aerosol since 2000 and the potential for changes in the sulfur cycle induced by climate change. This review provides an overview about the advances in stratospheric aerosol research since the last comprehensive assessment of stratospheric aerosol was published in 2006. A crucial development since 2006 is the substantial improvement in the agreement between in situ and space-based inferences of stratospheric aerosol properties during volcanically quiescent periods. Furthermore, new measurement systems and techniques, both in situ and space based, have been developed for measuring physical aerosol properties with greater accuracy and for characterizing aerosol composition. However, these changes induce challenges to constructing a long-term stratospheric aerosol climatology. Currently, changes in stratospheric aerosol levels less than 20% cannot be confidently quantified. The volcanic signals tend to mask any nonvolcanically driven change, making them difficult to understand. While the role of carbonyl sulfide as a substantial and relatively constant source of stratospheric sulfur has been confirmed by new observations and model simulations, large uncertainties remain with respect to the contribution from anthropogenic sulfur dioxide emissions. New evidence has been provided that stratospheric aerosol can also contain small amounts of nonsulfatematter such as black carbon and organics. Chemistry-climate models have substantially increased in quantity and sophistication. In many models the implementation of stratospheric aerosol processes is coupled to radiation and/or stratospheric chemistry modules to account for relevant feedback processes.

  20. Recent Climate Variability in Antarctica from Satellite-derived Temperature Data

    NASA Technical Reports Server (NTRS)

    Schneider, David P.; Steig, Eric J.; Comiso, Josefino C.

    2004-01-01

    Recent Antarctic climate variability on month-to-month to interannual time scales is assessed through joint analysis of surface temperatures from satellite thermal infrared observations (T(sub IR)) and passive microwave brightness temperatures (T(sub B)). Although Tw data are limited to clear-sky conditions and T(sub B) data are a product of the temperature and emissivity of the upper approx. 1m of snow, the two data sets share significant covariance. This covariance is largely explained by three empirical modes, which illustrate the spatial and temporal variability of Antarctic surface temperatures. T(sub B) variations are damped compared to TIR variations, as determined by the period of the temperature forcing and the microwave emission depth; however, microwave emissivity does not vary significantly in time. Comparison of the temperature modes with Southern Hemisphere (SH) 500-hPa geopotential height anomalies demonstrates that Antarctic temperature anomalies are predominantly controlled by the principal patterns of SH atmospheric circulation. The leading surface temperature mode strongly correlates with the Southern Annular Mode (SAM) in geopotential height. The second temperature mode reflects the combined influences of the zonal wavenumber-3 and Pacific South American (PSA) patterns in 500-hPa height on month-to-month timescales. ENSO variability projects onto this mode on interannual timescales, but is not by itself a good predictor of Antarctic temperature anomalies. The third temperature mode explains winter warming trends, which may be caused by blocking events, over a large region of the East Antarctic plateau. These results help to place recent climate changes in the context of Antarctica’s background climate variability and will aid in the interpretation of ice core paleoclimate records.

  1. Assessment of Variable Planting Date as an Agricultural Adaptation to Climate Variability in Sri Lanka

    NASA Astrophysics Data System (ADS)

    Rivera, A.; Gunda, T.; Hornberger, G. M.

    2016-12-01

    Agriculture accounts for approximately 70% of global freshwater withdrawals. Changes in precipitation patterns due to climate change as well as increasing demands for water necessitate an increased understanding of the water-­food intersection, notably at a local scale to inform farmer adaptations to improve water productivity, i.e., to get more food with less water. Local assessments of water-food security are particularly important for nations with self-sufficiency policies, which prioritize in-country production of certain resources. An ideal case study is the small island nation of Sri Lanka, which has a self-sufficiency policy for its staple food of rice. Because rice is a water-intensive crop, assessment of irrigation water requirements (IWRs) and the associated changes over time is especially important. Previous studies on IWRs of rice in Sri Lanka have failed to consider the Yala (dry) season, when water is scarcest.The goal of this study is to characterize the role that a human decision, setting the planting date, can play in buffering declines in rice yield against changes in precipitation patterns. Using four meteorological stations in the main rice-growing zones in Sri Lanka, we explore (1) general changes in IWRs over time during the Yala season and (2) the impact of the rice planting date. We use both historical data from meteorological stations as well as future projections from regional climate models. Our results indicate that gains can be achieved using a variable planting date relative to a fixed date, in accordance with a similar conclusion for the Maha (wet) season. This local scale assessment of Sri Lanka IWRs will contribute to the growing global literature on the impacts of water scarcity on agriculture and the role that one adaptation measure can play in mitigating deleterious impacts.

  2. Impacts of Present and Future Climate Variability on Forest Ecosystem in Mediterranean Region

    NASA Astrophysics Data System (ADS)

    Ozcan, O.; Musaoglu, N.; Türkeş, M.

    2017-12-01

    The concept of `climate change vulnerability’ helps us to better comprehend the cause/effect relationships behind climate change and its impact on human societies, socioeconomic sectors, physiographical and ecological systems. Herein, multifactorial spatial modeling was applied to evaluate the vulnerability of a Mediterranean forest ecosystem to climate change. Thus, the geographical distribution of the final Environmental Vulnerability Areas (EVAs) of the forest ecosystem are based on the estimated final Environmental Vulnerability Index (EVI) values. This revealed that at current levels of environmental degradation, physical, geographical, policy enforcement and socioeconomic conditions, the area with a “very low” vulnerability degree covered mainly the town, its surrounding settlements and the agricultural lands found mainly over the low and flat travertine plateau and the plains at the east and southeast of the district. The spatial magnitude of the EVAs over the forest ecosystem under the current environmental degradation was also determined. This revealed that the EVAs classed as “very low” account for 21% of the total area of the forest ecosystem, those classed as “low” account for 36%, those classed as “medium” account for 20%, and those classed as “high” account for 24%. Based on regionally averaged future climate assessments and projected future climate indicators, both the study site and the western Mediterranean sub-region of Turkey will probably become associated with a drier, hotter, more continental and more water-deficient climate. This analysis holds true for all future scenarios, with the exception of RCP4.5 for the period from 2015 to 2030. However, the present dry-sub humid climate dominating this sub-region and the study area shows a potential for change towards more dry climatology and for it to become a semiarid climate in the period between 2031 and 2050 according to the RCP8.5 high emission scenario. All the observed and estimated results

  3. Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability

    NASA Astrophysics Data System (ADS)

    Dee, S. G.; Parsons, L. A.; Loope, G. R.; Overpeck, J. T.; Ault, T. R.; Emile-Geay, J.

    2017-10-01

    The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial scale) variability in the climate system. Since this low-frequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long-term, high-magnitude variability under greenhouse forcing (Laepple and Huybers, 2014a, 2014b). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper we bridge this gap via a forward proxy modeling approach, coupled to an isotope-enabled GCM. This allows us to disentangle the various contributions to signals embedded in ice cores, speleothem calcite, coral aragonite, tree-ring width, and tree-ring cellulose. The paper addresses the following questions: (1) do forward-modeled ;pseudoproxies; exhibit variability comparable to proxy data? (2) if not, which processes alter the shape of the spectrum of simulated climate variability, and are these processes broadly distinguishable from climate? We apply our method to representative case studies, and broaden these insights with an analysis of the PAGES2k database (PAGES2K Consortium, 2013). We find that current proxy system models (PSMs) can help resolve model-data discrepancies on interannual to decadal timescales, but cannot account for the mismatch in variance on multi-decadal to centennial timescales. We conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate

  4. Alternating high and low climate variability: The context of natural selection and speciation in Plio-Pleistocene hominin evolution.

    PubMed

    Potts, Richard; Faith, J Tyler

    2015-10-01

    Interaction of orbital insolation cycles defines a predictive model of alternating phases of high- and low-climate variability for tropical East Africa over the past 5 million years. This model, which is described in terms of climate variability stages, implies repeated increases in landscape/resource instability and intervening periods of stability in East Africa. It predicts eight prolonged (>192 kyr) eras of intensified habitat instability (high variability stages) in which hominin evolutionary innovations are likely to have occurred, potentially by variability selection. The prediction that repeated shifts toward high climate variability affected paleoenvironments and evolution is tested in three ways. In the first test, deep-sea records of northeast African terrigenous dust flux (Sites 721/722) and eastern Mediterranean sapropels (Site 967A) show increased and decreased variability in concert with predicted shifts in climate variability. These regional measurements of climate dynamics are complemented by stratigraphic observations in five basins with lengthy stratigraphic and paleoenvironmental records: the mid-Pleistocene Olorgesailie Basin, the Plio-Pleistocene Turkana and Olduvai Basins, and the Pliocene Tugen Hills sequence and Hadar Basin–all of which show that highly variable landscapes inhabited by hominin populations were indeed concentrated in predicted stages of prolonged high climate variability. Second, stringent null-model tests demonstrate a significant association of currently known first and last appearance datums (FADs and LADs) of the major hominin lineages, suites of technological behaviors, and dispersal events with the predicted intervals of prolonged high climate variability. Palynological study in the Nihewan Basin, China, provides a third test, which shows the occupation of highly diverse habitats in eastern Asia, consistent with the predicted increase in adaptability in dispersing Oldowan hominins. Integration of fossil, archeological

  5. Developing and Validating a New Classroom Climate Observation Assessment Tool

    PubMed Central

    Leff, Stephen S.; Thomas, Duane E.; Shapiro, Edward S.; Paskewich, Brooke; Wilson, Kim; Necowitz-Hoffman, Beth; Jawad, Abbas F.

    2011-01-01

    The climate of school classrooms, shaped by a combination of teacher practices and peer processes, is an important determinant for children’s psychosocial functioning and is a primary factor affecting bullying and victimization. Given that there are relatively few theoretically-grounded and validated assessment tools designed to measure the social climate of classrooms, our research team developed an observation tool through participatory action research (PAR). This article details how the assessment tool was designed and preliminarily validated in 18 third-, fourth-, and fifth-grade classrooms in a large urban public school district. The goals of this study are to illustrate the feasibility of a PAR paradigm in measurement development, ascertain the psychometric properties of the assessment tool, and determine associations with different indices of classroom levels of relational and physical aggression. PMID:21643447

  6. Developing and Validating a New Classroom Climate Observation Assessment Tool.

    PubMed

    Leff, Stephen S; Thomas, Duane E; Shapiro, Edward S; Paskewich, Brooke; Wilson, Kim; Necowitz-Hoffman, Beth; Jawad, Abbas F

    2011-01-01

    The climate of school classrooms, shaped by a combination of teacher practices and peer processes, is an important determinant for children’s psychosocial functioning and is a primary factor affecting bullying and victimization. Given that there are relatively few theoretically-grounded and validated assessment tools designed to measure the social climate of classrooms, our research team developed an observation tool through participatory action research (PAR). This article details how the assessment tool was designed and preliminarily validated in 18 third-, fourth-, and fifth-grade classrooms in a large urban public school district. The goals of this study are to illustrate the feasibility of a PAR paradigm in measurement development, ascertain the psychometric properties of the assessment tool, and determine associations with different indices of classroom levels of relational and physical aggression.

  7. Impacts of uncertainties in European gridded precipitation observations on regional climate analysis

    PubMed Central

    Gobiet, Andreas

    2016-01-01

    ABSTRACT Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio‐temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan‐European data sets and a set that combines eight very high‐resolution station‐based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post‐processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small‐scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate‐mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments. PMID:28111497

  8. Atmospheric CO2 Variability Observed From ASCENDS Flight Campaigns

    NASA Technical Reports Server (NTRS)

    Lin, Bing; Browell, Edward; Campbell, Joel; Choi, Yonghoon; Dobler, Jeremy; Fan, Tai-Fang; Harrison, F. Wallace; Kooi, Susan; Liu, Zhaoyan; Meadows, Byron; hidehide

    2015-01-01

    Significant atmospheric CO2 variations on various spatiotemporal scales were observed during ASCENDS flight campaigns. For example, around 10-ppm CO2 changes were found within free troposphere in a region of about 200×300 sq km over Iowa during a summer 2014 flight. Even over extended forests, about 2-ppm CO2 column variability was measured within about 500-km distance. For winter times, especially over snow covered ground, relatively less horizontal CO2 variability was observed, likely owing to minimal interactions between the atmosphere and land surface. Inter-annual variations of CO2 drawdown over cornfields in the Mid-West were found to be larger than 5 ppm due to slight differences in the corn growing phase and meteorological conditions even in the same time period of a year. Furthermore, considerable differences in atmospheric CO2 profiles were found during winter and summer campaigns. In the winter CO2 was found to decrease from about 400 ppm in the atmospheric boundary layer (ABL) to about 392 ppm above 10 km, while in the summer CO2 increased from 386 ppm in the ABL to about 396 ppm in free troposphere. These and other CO2 observations are discussed in this presentation.

  9. Converging Climate Sensitivities of European Forests Between Observed Radial Tree Growth and Vegetation Models

    NASA Technical Reports Server (NTRS)

    Zhang, Zhen; Babst, Flurin; Bellassen, Valentin; Frank, David; Launois, Thomas; Tan, Kun; Ciais, Philippe; Poulter, Benjamin

    2017-01-01

    The impacts of climate variability and trends on European forests are unevenly distributed across different bioclimatic zones and species. Extreme climate events are also becoming more frequent and it is unknown how they will affect feed backs of CO2 between forest ecosystems and the atmosphere. An improved understanding of species differences at the regional scale of the response of forest productivity to climate variation and extremes is thus important for forecasting forest dynamics. In this study, we evaluate the climate sensitivity of above ground net primary production (NPP) simulated by two dynamic global vegetation models (DGVM; ORCHIDEE and LPJ-wsl) against tree ring width (TRW) observations from about1000 sites distributed across Europe. In both the model simulations and the TRW observations, forests in northern Europe and the Alps respond positively to warmer spring and summer temperature, and their overall temperature sensitivity is larger than that of the soil-moisture-limited forests in central Europe and Mediterranean regions. Compared with TRW observations, simulated NPP from ORCHIDEE and LPJ-wsl appear to be overly sensitive to climatic factors. Our results indicate that the models lack biological processes that control time lags, such as carbohydrate storage and remobilization, that delay the effects of radial growth dynamics to climate. Our study highlights the need for re-evaluating the physiological controls on the climate sensitivity of NPP simulated by DGVMs. In particular, DGVMs could be further enhanced by a more detailed representation of carbon reserves and allocation that control year-to year variation in plant growth.

  10. AIRS Observations Based Evaluation of Relative Climate Feedback Strengths on a GCM Grid-Scale

    NASA Astrophysics Data System (ADS)

    Molnar, G. I.; Susskind, J.

    2012-12-01

    Climate feedback strengths, especially those associated with moist processes, still have a rather wide range in GCMs, the primary tools to predict future climate changes associated with man’s ever increasing influences on our planet. Here, we make use of the first 10 years of AIRS observations to evaluate interrelationships/correlations of atmospheric moist parameter anomalies computed from AIRS Version 5 Level-3 products, and demonstrate their usefulness to assess relative feedback strengths. Although one may argue about the possible usability of shorter-term, observed climate parameter anomalies for estimating the strength of various (mostly moist processes related) feedbacks, recent works, in particular analyses by Dessler [2008, 2010], have demonstrated their usefulness in assessing global water vapor and cloud feedbacks. First, we create AIRS-observed monthly anomaly time-series (ATs) of outgoing longwave radiation, water vapor, clouds and temperature profile over a 10-year long (Sept. 2002 through Aug. 2012) period using 1×1 degree resolution (a common GCM grid-scale). Next, we evaluate the interrelationships of ATs of the above parameters with the corresponding 1×1 degree, as well as global surface temperature ATs. The latter provides insight comparable with more traditional climate feedback definitions (e. g., Zelinka and Hartmann, 2012) whilst the former is related to a new definition of “local (in surface temperature too) feedback strengths” on a GCM grid-scale. Comparing the correlation maps generated provides valuable new information on the spatial distribution of relative climate feedback strengths. We argue that for GCMs to be trusted for predicting longer-term climate variability, they should be able to reproduce these observed relationships/metrics as closely as possible. For this time period the main climate “forcing” was associated with the El Niño/La Niña variability (e. g., Dessler, 2010), so these assessments may not be descriptive of longer

  11. Global observations of aerosol-cloud-precipitation-climate interactions

    NASA Astrophysics Data System (ADS)

    Rosenfeld, Daniel; Andreae, Meinrat O.; Asmi, Ari; Chin, Mian; de Leeuw, Gerrit; Donovan, David P.; Kahn, Ralph; Kinne, Stefan; Kivekäs, Niku; Kulmala, Markku; Lau, William; Schmidt, K. Sebastian; Suni, Tanja; Wagner, Thomas; Wild, Martin; Quaas, Johannes

    2014-12-01

    Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to aerosol-induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite-sensor-based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects of meteorology from those of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing. Ways to improve the retrieval accuracy include multiangle and multipolarimetric passive measurements of the optical signal and multispectral lidar polarimetric measurements. Indirect methods include proxies of trace gases, as retrieved by hyperspectral sensors. Perhaps the most promising emerging direction is retrieving the CCN properties by simultaneously retrieving convective cloud drop number concentrations and updraft speeds, which amounts to using clouds as natural CCN chambers. These satellite observations have to be constrained by in situ observations of aerosol-cloud-precipitation-climate (ACPC) interactions, which in turn constrain a hierarchy of model simulations of ACPC. Since the essence of a general circulation model is an accurate quantification of the energy and mass fluxes in all forms between the surface, atmosphere and outer space, a route to progress is proposed here in the form of a series of box flux closure experiments in the various climate regimes. A roadmap is provided for quantifying the ACPC interactions and thereby reducing the uncertainty in anthropogenic climate forcing.

  12. Two centuries of observed atmospheric variability and change over the North Sea region

    NASA Astrophysics Data System (ADS)

    Stendel, Martin; van den Besselaar, Else; Hannachi, Abdel; Kent, Elizabeth; Lefebvre, Christiana; Rosenhagen, Gudrun; Schenk, Frederik; van der Schrier, Gerard; Woollings, Tim

    2016-04-01

    In the upcoming North Sea Region Climate Change Assessment (NOSCCA), we present a synthesis of current knowledge about past, present and possible future climate change in the North Sea region. A climate change assessment from published scientific work has been conducted as a kind of regional IPCC report, and a book has been produced that will be published by Springer in 2016. In the framework of the NOSCCA project, we examine past and present studies of variability and changes in atmospheric variables within the North Sea region over the instrumental period, roughly the past 200 years, based on observations and reanalyses. The variables addressed in this presentation are large-scale circulation, pressure and wind, surface air temperature, precipitation and radiative properties (clouds, solar radiation, and sunshine duration). While air temperature over land, not unexpectedly, has increased everywhere in the North Sea region, with strongest trends in spring and in the north of the region, a precipitation increase has been observed in the north and a decrease in the south of the region. This pattern goes along with a north-eastward shift of storm tracks and is in agreement with climate model projections under enhanced greenhouse gas concentrations. For other variables, it is not obvious which part of the observed changes may be due to anthropogenic activities and which is internally forced. It remains also unclear to what extent atmospheric circulation over the North Sea region is influenced by distant factors, in particular Arctic sea-ice decline in recent decades. There are indications of an increase in the number of deep cyclones (but not in the total number of cyclones), while storminess since the late 19th century shows no robust trends. The persistence of circulation types appears to have increased over the last century, and consequently, there is an indication for ‘more extreme’ extreme events. However, changes in extreme weather events are difficult to assess

  13. Climate variables as predictors for seasonal forecast of dengue occurrence in Chennai, Tamil Nadu

    NASA Astrophysics Data System (ADS)

    Subash Kumar, D. D.; Andimuthu, R.

    2013-12-01

    Background Dengue is a recently emerging vector borne diseases in Chennai. As per the WHO report in 2011 dengue is one of eight climate sensitive disease of this century. Objective Therefore an attempt has been made to explore the influence of climate parameters on dengue occurrence and use for forecasting. Methodology Time series analysis has been applied to predict the number of dengue cases in Chennai, a metropolitan city which is the capital of Tamil Nadu, India. Cross correlation of the climate variables with dengue cases revealed that the most influential parameters were monthly relative humidity, minimum temperature at 4 months lag and rainfall at one month lag (Table 1). However due to intercorrelation of relative humidity and rainfall was high and therefore for predictive purpose the rainfall at one month lag was used for the model development. Autoregressive Integrated Moving Average (ARIMA) models have been applied to forecast the occurrence of dengue. Results and Discussion The best fit model was ARIMA (1,0,1). It was seen that the monthly minimum temperature at four months lag (β= 3.612, p = 0.02) and rainfall at one month lag (β= 0.032, p = 0.017) were associated with dengue occurrence and they had a very significant effect. Mean Relative Humidity had a directly significant positive correlation at 99% confidence level, but the lagged effect was not prominent. The model predicted dengue cases showed significantly high correlation of 0.814(Figure 1) with the observed cases. The RMSE of the model was 18.564 and MAE was 12.114. The model is limited by the scarcity of the dataset. Inclusion of socioeconomic conditions and population offset are further needed to be incorporated for effective results. Conclusion Thus it could be claimed that the change in climatic parameters is definitely influential in increasing the number of dengue occurrence in Chennai. The climate variables therefore can be used for seasonal forecasting of dengue with rise in minimum

  14. Modern nature and climate changes in Siberia: new methods and results of analysis of instrumented observations

    NASA Astrophysics Data System (ADS)

    Kabanov, Mikhail V.

    2002-02-01

    Peculiarity of nature and climate changes in middle latitudes of the Northern Hemisphere and in Siberia is that the temporal variability of meteorological quantities here has a wide range and their spatial variability has a complicated zone structure. Therefore, regional monitoring of modern nature and climate changes in Siberia is of scientific interest from the viewpoint of the global changes observed. Another Siberian peculiarity is associated with the fact that there are many unique objects that have global importance both as natural complexes (boreal forests, water- bog systems, Baikal lake, etc.) And as technogenic objects (oil and gas production, coal mining, metallurgy, transport, etc.). Therefore monitoring and modeling of regional nature and climate changes in Siberia have great practical importance, which is underestimated now, for industrial development of Siberia. Taking into account the above peculiarities and tendencies on investigation of global and regional environmental and climate changes, the multidisciplinary project on Climate and Ecological Monitoring of Siberia (CEMS) was accepted to the research and development program Sibir’ since 1993. To realize this project, the Climate and Ecological Observatory was established in Tomsk at the Institute for Optical Monitoring (IOM) SB RAS. At the present time the stations (the basic and background ones) of this observatory are in a progress and theory and instruments for monitoring are being developed as well. In this paper we discuss some results obtained in the framework of CEMS project that were partially published in the monographs, in scientific journals, and will be published in the Proceedings of the 8th Joint International Symposium on Atmospheric and Ocean Optics and Atmosphere Physics. This review has a purpose not only to discuss the obtained regularities but also to formulate scientific and technical tasks for further investigations into the regional changes of technogenic, natural, and

  15. A Scaling Model for the Anthropocene Climate Variability with Projections to 2100

    NASA Astrophysics Data System (ADS)

    Hébert, Raphael; Lovejoy, Shaun

    2017-04-01

    The determination of the climate sensitivity to radiative forcing is a fundamental climate science problem with important policy implications. We use a scaling model, with a limited set of parameters, which can directly calculate the forced globally-average surface air temperature response to anthropogenic and natural forcings. At timescales larger than an inner scale τ, which we determine as the ocean-atmosphere coupling scale at around 2 years, the global system responds, approximately, linearly, so that the variability may be decomposed into additive forced and internal components. The Ruelle response theory extends the classical linear response theory for small perturbations to systems far from equilibrium. Our model thus relates radiative forcings to a forced temperature response by convolution with a suitable Green’s function, or climate response function. Motivated by scaling symmetries which allow for long range dependence, we assume a general scaling form, a scaling climate response function (SCRF) which is able to produce a wide range of responses: a power-law truncated at τ. This allows us to analytically calculate the climate sensitivity at different time scales, yielding a one-to-one relation from the transient climate response to the equilibrium climate sensitivity which are estimated, respectively, as 1.6+0.3-0.2K and 2.4+1.3-0.6K at the 90 % confidence level. The model parameters are estimated within a Bayesian framework, with a fractional Gaussian noise error model as the internal variability, from forcing series, instrumental surface temperature datasets and CMIP5 GCMs Representative Concentration Pathways (RCP) scenario runs. This observation based model is robust and projections for the coming century are made following the RCP scenario 2.6, 4.5 and 8.5, yielding in the year 2100, respectively : 1.5 +0.3)_{-0.2K, 2.3 ± 0.4 K and 4.0 ± 0.6 K at the 90 % confidence level. For comparison, the associated projections from a CMIP5 multi

  16. European climate variability and human susceptibility over the past 2500 years

    NASA Astrophysics Data System (ADS)

    Buentgen, U.

    2010-09-01

    conditions. The complex climatic interference with agrarian civilizations, however, challenges the sustainability of this attitude. In addition to the long-term context it provides for instrumentally observed European climate variability, our study reveals critical targets for next-generation climate models to hindcast the temporal footprints and magnitudes of natural fluctuations over the Late Holocene in response to internal dynamics and external forcings.

  17. Accounting for interannual variability: A comparison of options for water resources climate change impact assessments

    NASA Astrophysics Data System (ADS)

    Johnson, Fiona; Sharma, Ashish

    2011-04-01

    Empirical scaling approaches for constructing rainfall scenarios from general circulation model (GCM) simulations are commonly used in water resources climate change impact assessments. However, these approaches have a number of limitations, not the least of which is that they cannot account for changes in variability or persistence at annual and longer time scales. Bias correction of GCM rainfall projections offers an attractive alternative to scaling methods as it has similar advantages to scaling in that it is computationally simple, can consider multiple GCM outputs, and can be easily applied to different regions or climatic regimes. In addition, it also allows for interannual variability to evolve according to the GCM simulations, which provides additional scenarios for risk assessments. This paper compares two scaling and four bias correction approaches for estimating changes in future rainfall over Australia and for a case study for water supply from the Warragamba catchment, located near Sydney, Australia. A validation of the various rainfall estimation procedures is conducted on the basis of the latter half of the observational rainfall record. It was found that the method leading to the lowest prediction errors varies depending on the rainfall statistic of interest. The flexibility of bias correction approaches in matching rainfall parameters at different frequencies is demonstrated. The results also indicate that for Australia, the scaling approaches lead to smaller estimates of uncertainty associated with changes to interannual variability for the period 2070-2099 compared to the bias correction approaches. These changes are also highlighted using the case study for the Warragamba Dam catchment.

  18. Determining the Effect of the Lunar Nodal Cycle on Tidal Mixing and North Pacific Climate Variability

    NASA Astrophysics Data System (ADS)

    Ullman, D. J.; Schmittner, A.; Danabasoglu, G.; Norton, N. J.; Müller, M.

    2016-02-01

    Oscillations in the moon’s orbit around the earth modulate regional tidal dissipation with a periodicity of 18.6 years. In regions where the diurnal tidal constituents dominate diapycnal mixing, this Lunar Nodal Cycle (LNC) may be significant enough to influence ocean circulation, sea surface temperature, and climate variability. Such periodicity in the LNC as an external forcing may provide a mechanistic source for Pacific decadal variability (i.e. Pacific Decadal Oscillation, PDO) where diurnal tidal constituents are strong. We have introduced three enhancements to the latest version of the Community Earth System Model (CESM) to better simulate tidal-forced mixing. First, we have produced a sub-grid scale bathymetry scheme that better resolves the vertical distribution of the barotropic energy flux in regions where the native CESM grid does not resolve high spatial-scale bathymetric features. Second, we test a number of alternative barotropic tidal constituent energy flux fields that are derived from various satellite altimeter observations and tidal models. Third, we introduce modulations of the individual diurnal and semi-diurnal tidal constituents, ranging from monthly to decadal periods, as derived from the full lunisolar tidal potential. Using both ocean-only and fully-coupled configurations, we test the influence of these enhancements, particularly the LNC modulations, on ocean mixing and bidecadal climate variability in CESM.

  19. Generating temporal model using climate variables for the prediction of dengue cases in Subang Jaya, Malaysia

    PubMed Central

    Dom, Nazri Che; Hassan, A Abu; Latif, Z Abd; Ismail, Rodziah

    2013-01-01

    Objective To develop a forecasting model for the incidence of dengue cases in Subang Jaya using time series analysis. Methods The model was performed using the Autoregressive Integrated Moving Average (ARIMA) based on data collected from 2005 to 2010. The fitted model was then used to predict dengue incidence for the year 2010 by extrapolating dengue patterns using three different approaches (i.e. 52, 13 and 4 weeks ahead). Finally cross correlation between dengue incidence and climate variable was computed over a range of lags in order to identify significant variables to be included as external regressor. Results The result of this study revealed that the ARIMA (2,0,0) (0,0,1)52 model developed, closely described the trends of dengue incidence and confirmed the existence of dengue fever cases in Subang Jaya for the year 2005 to 2010. The prediction per period of 4 weeks ahead for ARIMA (2,0,0)(0,0,1)52 was found to be best fit and consistent with the observed dengue incidence based on the training data from 2005 to 2010 (Root Mean Square Error=0.61). The predictive power of ARIMA (2,0,0) (0,0,1)52 is enhanced by the inclusion of climate variables as external regressor to forecast the dengue cases for the year 2010. Conclusions The ARIMA model with weekly variation is a useful tool for disease control and prevention program as it is able to effectively predict the number of dengue cases in Malaysia.

  20. Means and extremes: building variability into community-level climate change experiments.

    PubMed

    Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula

    2013-06-01

    Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of ‘generations’ based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new ‘generation’ of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.

  1. Towards an integrated set of surface meterological observations for climate science and applications

    NASA Astrophysics Data System (ADS)

    Dunn, Robert; Thorne, Peter

    2017-04-01

    We cannot predict what is not observed, and we cannot analyse what is not archived. To meet current scientific and societal demands, as well as future requirements for climate services, it is vital that the management and curation of land-based meteorological data holdings is improved. A comprehensive global set of data holdings, of known provenance, integrated across both climate variable and timescale are required to meet the wide range of user needs. Presently, the land-based holdings are highly fractured into global, region and national holdings for different variables and timescales, from a variety of sources, and in a mixture of formats. We present a high level overview, based on broad community input, of the steps that are required to bring about this integration and progress towards such a database. Any long-term, international, program creating such an integrated database will transform the our collective ability to provide societally relevant research, analysis and predictions across the globe.

  2. Land Surface Phenology in Kazakhstan: Climatic Variability and Institutional Change

    NASA Astrophysics Data System (ADS)

    de Beurs, K. M.; Henebry, G. M.

    2002-12-01

    models displayed similar timing and magnitude for NDVI. The southern irrigated area displayed different temporal developments and magnitudes of NDVI between 1985-89 and 1995-99; the second period displays higher peak NDVI. The temperature regime and the accumulation of GDD were similar in both periods. Although the imputed precipitation was significantly different, it is not likely to be responsible for the observed differences in NDVI, due to the low magnitude of precipitation relative to the crop water demands. Thus, we conclude that the climatic conditions between the two periods are not effectively different and, further, that the observed differences in the temporal development of NDVI result from changes in agricultural practices.

  3. 20 Cataclysmic variables to be observed by William Herschel Telescope

    NASA Astrophysics Data System (ADS)

    Waagen, Elizabeth O.

    2016-05-01

    Roque Ruiz-Carmona (Ph.D. candidate, Institute of Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen, The Netherlands) has requested AAVSO assistance with his campaign to observe a set of 20 cataclysmic variables (CVs) with the William Herschel Telescope (WHT) at La Palma TONIGHT. This campaign is identical in format to the ones successfully carried out by the AAVSO on his behalf in 2015 (AAVSO Alert Notices 524 and 527). The full details of and instructions for this campaign are included here although the first of the two nights for which data are requested has passed. In order for WHT to observe each of the targets safely and to maximize the science value of the observations obtained, it is essential to know whether they are in outburst or quiescence. To this end, the PI has requested our observers to obtain one image of each target on each of TWO separate nights so he may analyze them to determine the final observing list for WHT. The images must be taken and posted within a certain window. Links to finder charts as well as reporting instructions and other information may be found in the full Alert Notice.

  4. Subseasonal climate variability for North Carolina, United States

    NASA Astrophysics Data System (ADS)

    Sayemuzzaman, Mohammad; Jha, Manoj K.; Mekonnen, Ademe; Schimmel, Keith A.

    2014-08-01

    Subseasonal trends in climate variability for maximum temperature (Tmax), minimum temperature (Tmin) and precipitation were evaluated for 249 ground-based stations in North Carolina for 1950-2009. The magnitude and significance of the trends at all stations were determined using the non-parametric Theil-Sen Approach (TSA) and the Mann-Kendall (MK) test, respectively. The Sequential Mann-Kendall (SQMK) test was also applied to find the initiation of abrupt trend changes. The lag-1 serial correlation and double mass curve were employed to address the data independency and homogeneity. Using the MK trend test, statistically significant (confidence level ≥ 95% in two-tailed test) decreasing (increasing) trends by 44% (45%) of stations were found in May (June). In general, trends were decreased in Tmax and increased in Tmin data series in subseasonal scale. Using the TSA method, the magnitude of lowest (highest) decreasing (increasing) trend in Tmax is – 0.050 °C/year (+ 0.052 °C/year) in the monthly series for May (March) and for Tmin is – 0.055 °C/year (+ 0.075 °C/year) in February (December). For the precipitation time series using the TSA method, it was found that the highest (lowest) magnitude of 1.00 mm/year (- 1.20 mm/year) is in September (February). The overall trends in precipitation data series were not significant at the 95% confidence level except that 17% of stations were found to have significant (confidence level ≥ 95% in two-tailed test) decreasing trends in February. The statistically significant trend test results were used to develop a spatial distribution of trends: May for Tmax, June for Tmin, and February for precipitation. A correlative analysis of significant temperature and precipitation trend results was examined with respect to large scale circulation modes (North Atlantic Oscillation (NAO) and Southern Oscillation Index (SOI). A negative NAO index (positive-El Niño Southern Oscillation (ENSO) index) was found to be associated with

  5. Climatic variability of the column ozone over the Iranian plateau

    NASA Astrophysics Data System (ADS)

    Mousavi, Seyyed Shafi; Farajzadeh, Manuchehr; Rahimi, Yousef Ghavidel; Bidokhti, Abbasali Aliakbari

    2017-06-01

    This study analyzes the total ozone column (TOC) variability over the Iranian plateau (Esfahan) from 1978 to 2011. Results show that the annual average of TOC in Esfahan tends to decrease with time, which is strongly dependent on the season, with maximum values during the winter-spring months (more than 2.2 %/decade). By applying a defined threshold that includes the TOC monthly -2 σ, it is found that the maximum occurrence of low ozone events (LOEs) tends to be more frequent in the second half of year with about four-fifth of the observed LOEs (last summer, autumn, and early winter). During two cases of LOE, the tropopause height (TH) was uplifted 2-4 km with temperature of 10 °C colder than the long-term mean, and the synoptic pattern was characterized by high-pressure systems in UTLS region. The extreme LOEs were consistent with the horizontal transport of ozone-poor air toward the Iranian plateau and vertical advection in UTLS region. The former mechanism plays a primary role in formation of extreme LOEs based on the observed TOC reductions during previous days over the source regions (Sahara desert and Himalaya region). Day-to-day variations of maximum UV index during LOEs show that by a decrease in TOC 14 %, while the aerosol optical depth (AOD) in the cloudless condition reach their lowest rates (lower than 0.3), UV radiation exceeds very high and extreme levels in late winter and mid-spring, respectively.

  6. Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan.

    PubMed

    Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

    2016-02-03

    This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (-) and one month ago (-)), and average relative humidity (current and 9 months ago (-)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future.

  7. Solar variability and climate change: An historical perspective

    NASA Astrophysics Data System (ADS)

    Feldman, Theodore S.

    There is nothing new about the debate over the Sun’s influence on terrestrial climate.As early as the late 18th century, widespread concern for the deterioration of the Earth’s climate led to speculation about the Sun’s role in climate change [Feldman, 1993; Fleming, 1990]. Drawing analogies with variations in the brightness of stars, the British astronomer William Herschel suggested that greater sunspot activity would result in warmer terrestrial climates. Herschel supported his hypothesis by referring to price series for wheat published in Adam Smiths Wealth of Nations [Hufbauer, 1991]. Later, the eminent American physicist Joseph Henry demonstrated by thermopile measurements that, contrary to Herschel’s assumption, sunspots were cooler than the unblemished portions of the solar disk.

  8. Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan

    PubMed Central

    Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

    2016-01-01

    This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (−) and one month ago (−)), and average relative humidity (current and 9 months ago (−)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future. PMID:26848675

  9. Adapting to Climate Variability and Change: Experiences from Cereal-Based Farming in the Central Rift and Kobo Valleys, Ethiopia

    NASA Astrophysics Data System (ADS)

    Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

    2013-11-01

    Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions—the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers’ perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new

  10. Adapting to climate variability and change: experiences from cereal-based farming in the central rift and Kobo Valleys, Ethiopia.

    PubMed

    Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

    2013-11-01

    Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions-the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers’ perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new

  11. Pronounced centennial-scale Atlantic Ocean climate variability correlated with Western Hemisphere hydroclimate.

    PubMed

    Thirumalai, Kaustubh; Quinn, Terrence M; Okumura, Yuko; Richey, Julie N; Partin, Judson W; Poore, Richard Z; Moreno-Chamarro, Eduardo

    2018-01-26

    Surface-ocean circulation in the northern Atlantic Ocean influences Northern Hemisphere climate. Century-scale circulation variability in the Atlantic Ocean, however, is poorly constrained due to insufficiently-resolved paleoceanographic records. Here we present a replicated reconstruction of sea-surface temperature and salinity from a site sensitive to North Atlantic circulation in the Gulf of Mexico which reveals pronounced centennial-scale variability over the late Holocene. We find significant correlations on these timescales between salinity changes in the Atlantic, a diagnostic parameter of circulation, and widespread precipitation anomalies using three approaches: multiproxy synthesis, observational datasets, and a transient simulation. Our results demonstrate links between centennial changes in northern Atlantic surface-circulation and hydroclimate changes in the adjacent continents over the late Holocene. Notably, our findings reveal that weakened surface-circulation in the Atlantic Ocean was concomitant with well-documented rainfall anomalies in the Western Hemisphere during the Little Ice Age.

  12. Pronounced centennial-scale Atlantic Ocean climate variability correlated with Western Hemisphere hydroclimate

    USGS Publications Warehouse

    Thirumalai, Kaustubh; Quinn, Terrence M.; Okumura, Yuko; Richey, Julie; Partin, Judson W.; Poore, Richard Z.; Moreno-Chamarro, Eduardo

    2018-01-01

    Surface-ocean circulation in the northern Atlantic Ocean influences Northern Hemisphere climate. Century-scale circulation variability in the Atlantic Ocean, however, is poorly constrained due to insufficiently-resolved paleoceanographic records. Here we present a replicated reconstruction of sea-surface temperature and salinity from a site sensitive to North Atlantic circulation in the Gulf of Mexico which reveals pronounced centennial-scale variability over the late Holocene. We find significant correlations on these timescales between salinity changes in the Atlantic, a diagnostic parameter of circulation, and widespread precipitation anomalies using three approaches: multiproxy synthesis, observational datasets, and a transient simulation. Our results demonstrate links between centennial changes in northern Atlantic surface-circulation and hydroclimate changes in the adjacent continents over the late Holocene. Notably, our findings reveal that weakened surface-circulation in the Atlantic Ocean was concomitant with well-documented rainfall anomalies in the Western Hemisphere during the Little Ice Age.

  13. Arctic sea ice area in CMIP3 and CMIP5 climate model ensembles – variability and change

    NASA Astrophysics Data System (ADS)

    Semenov, V. A.; Martin, T.; Behrens, L. K.; Latif, M.

    2015-02-01

    The shrinking Arctic sea ice cover observed during the last decades is probably the clearest manifestation of ongoing climate change. While climate models in general reproduce the sea ice retreat in the Arctic during the 20th century and simulate further sea ice area loss during the 21st century in response to anthropogenic forcing, the models suffer from large biases and the model results exhibit considerable spread. The last generation of climate models from World Climate Research Programme Coupled Model Intercomparison Project Phase 5 (CMIP5), when compared to the previous CMIP3 model ensemble and considering the whole Arctic, were found to be more consistent with the observed changes in sea ice extent during the recent decades. Some CMIP5 models project strongly accelerated (non-linear) sea ice loss during the first half of the 21st century. Here, complementary to previous studies, we compare results from CMIP3 and CMIP5 with respect to regional Arctic sea ice change. We focus on September and March sea ice. Sea ice area (SIA) variability, sea ice concentration (SIC) variability, and characteristics of the SIA seasonal cycle and interannual variability have been analysed for the whole Arctic, termed Entire Arctic, Central Arctic and Barents Sea. Further, the sensitivity of SIA changes to changes in Northern Hemisphere (NH) averaged temperature is investigated and several important dynamical links between SIA and natural climate variability involving the Atlantic Meridional Overturning Circulation (AMOC), North Atlantic Oscillation (NAO) and sea level pressure gradient (SLPG) in the western Barents Sea opening serving as an index of oceanic inflow to the Barents Sea are studied. The CMIP3 and CMIP5 models not only simulate a coherent decline of the Arctic SIA but also depict consistent changes in the SIA seasonal cycle and in the aforementioned dynamical links. The spatial patterns of SIC variability improve in the CMIP5 ensemble, particularly in summer. Both

  14. Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

    NASA Astrophysics Data System (ADS)

    Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

    2018-04-01

    The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models’ limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

  15. Altimeter Observations of Wave Climate in the Arctic Ocean

    NASA Astrophysics Data System (ADS)

    Babanin, A. V.; Liu, Q.; Zieger, S.

    2016-02-01

    Wind waves are a new physical phenomenon to the Arctic Seas, which in the past were covered with ice. Now, over summer months, ice coverage retreats up to high latitudes and waves are generated. The marginal open seas provide new opportunities and new problems. Navigation and other maritime activities become possible, but wave heights, storm surges and coastal erosion will likely increase. Air-sea interactions enter a completely new regime, with momentum, energy, heat, gas and moisture fluxes being moderated or produced by the waves, and impacting on upper-ocean mixing. All these issues require knowledge of the wave climate. We will report results of investigation of wave climate and its trends by means of satellite altimetry. This is a challenging, but important topic. On one hand, no statistical approach is possible since in the past for most of the Arctic Ocean there was limited wave activity. Extrapolations of the current observations into the future are not feasible, because ice cover and wind patterns in the Arctic are changing. On the other hand, information on the mean and extreme wave properties, such as wave height, period, direction, on the frequency of occurrence and duration of the storms is of great importance for oceanographic, meteorological, climate, naval and maritime applications in the Arctic Seas.

  16. Longitudinal Ionospheric Variability Observed by LITES on the ISS

    NASA Astrophysics Data System (ADS)

    Stephan, A. W.; Finn, S. C.; Cook, T.; Geddes, G.; Chakrabarti, S.; Budzien, S. A.

    2017-12-01

    The Limb-Imaging Ionospheric and Thermospheric Extreme-Ultraviolet Spectrograph (LITES) is an imaging spectrograph designed to measure altitude profiles (150-350 km) of extreme- and far-ultraviolet airglow emissions that originate from photochemical processes in the ionosphere and thermosphere. During the daytime, LITES observes the bright O+ 83.4 nm emission from which the ionospheric profile can be inferred. At night, recombination emissions at 91.1 and 135.6 nm provide a direct measure of the electron content along the line of sight. LITES was launched and installed on the International Space Station (ISS) in late February 2017 where it has been operating along with the highly complementary GPS Radio Occultation and Ultraviolet Photometry – Colocated (GROUP-C) experiment. We will present some of the first observations from LITES in April 2017 that show longitudinal patterns in ionospheric density and the daily variability in those patterns. LITES vertical imaging from a vantage point near 410 km enables a particularly unique perspective on the altitude of the ionospheric peak density at night that can complement and inform other ground- and space-based measurements, and track the longitude-altitude variability that is reflective of changes in equatorial electrodynamics.

  17. Control of variable speed variable pitch wind turbine based on a disturbance observer

    NASA Astrophysics Data System (ADS)

    Ren, Haijun; Lei, Xin

    2017-11-01

    In this paper, a novel sliding mode controller based on disturbance observer (DOB) to optimize the efficiency of variable speed variable pitch (VSVP) wind turbine is developed and analyzed. Due to the highly nonlinearity of the VSVP system, the model is linearly processed to obtain the state space model of the system. Then, a conventional sliding mode controller is designed and a DOB is added to estimate wind speed. The proposed control strategy can successfully deal with the random nature of wind speed, the nonlinearity of VSVP system, the uncertainty of parameters and external disturbance. Via adding the observer to the sliding mode controller, it can greatly reduce the chattering produced by the sliding mode switching gain. The simulation results show that the proposed control system has the effectiveness and robustness.

  18. Trend analysis of hydro-climatic variables in the north of Iran

    NASA Astrophysics Data System (ADS)

    Nikzad Tehrani, E.; Sahour, H.; Booij, M. J.

    2018-04-01

    Trend analysis of climate variables such as streamflow, precipitation, and temperature provides useful information for understanding the hydrological changes associated with climate change. In this study, a nonparametric Mann-Kendall test was employed to evaluate annual, seasonal, and monthly trends of precipitation and streamflow for the Neka basin in the north of Iran over a 44-year period (1972 to 2015). In addition, the Inverse Distance Weight (IDW) method was used for annual seasonal, monthly, and daily precipitation trends in order to investigate the spatial correlation between precipitation and streamflow trends in the study area. Results showed a downward trend in annual and winter precipitation (Z climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value observed in the upstream part of the study area which is consistent with the streamflow trend. Also, there is a good correlation between monthly and seasonal precipitation and streamflow for all sub-basins (Sefidchah, Gelvard, Abelu). In general, from a hydro-climatic point of view, the results showed that the study area is moving towards a situation with more severe drought events.

  19. Tropical Ocean Surface Energy Balance Variability: Linking Weather to Climate Scales

    NASA Technical Reports Server (NTRS)

    Roberts, J. Brent; Clayson, Carol Anne

    2013-01-01

    Radiative and turbulent surface exchanges of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth s energy and water balance. Characterizing the spatiotemporal variability of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. These fluxes are integral components to tropical ocean-atmosphere variability; they can drive ocean mixed layer variations and modify the atmospheric boundary layer properties including moist static stability, thereby influencing larger-scale tropical dynamics. Non-parametric cluster-based classification of atmospheric and ocean surface properties has shown an ability to identify coherent weather regimes, each typically associated with similar properties and processes. Using satellite-based observational radiative and turbulent energy flux products, this study investigates the relationship between these weather states and surface energy processes within the context of tropical climate variability. Investigations of surface energy variations accompanying intraseasonal and interannual tropical variability often use composite-based analyses of the mean quantities of interest. Here, a similar compositing technique is employed, but the focus is on the distribution of the heat and moisture fluxes within their weather regimes. Are the observed changes in surface energy components dominated by changes in the frequency of the weather regimes or through changes in the associated fluxes within those regimes? It is this question that the presented work intends to address. The distribution of the surface heat and moisture fluxes is evaluated for both normal and non-normal states. By examining both phases of the climatic oscillations, the symmetry of energy and water cycle responses are considered.

  20. A Review of Pacific Interdecadal Climate Variability: Possible Mechanisms and Surface Climate Signatures in the Pacific Sector

    NASA Astrophysics Data System (ADS)

    Mantua, N. J.

    2004-12-01

    Many investigators have examined historical surface climate records from the Pacific sector and identified a relatively small number of spatial patterns varying at decadal to interdecadal time scales. “Pacific Decadal Variability” (PDV) is a label that has been used to describe this family of climate variations. Some patterns of PDV are contained completely within the northern extratropics, while others have signatures throughout the Pacific hemisphere on both sides of the equator. Mechanisms for observed patterns of PDV are not yet known, though a wide variety of hypotheses have been proposed. Various ocean-atmosphere mechanisms for PDV are contained within the extratropics, others within the tropics, while others involve tropical-extratropical interactions. Some investigators have proposed external forcing (solar, lunar, or volcanic) as potentially important for driving PDV. A relatively simple hypothesis couples ENSO forcing with upper ocean heat storage for extratropical PDV, and it suggests PDV predictability may be limited to ~2 year lead times. Paleo-PDV reconstructions have been based on materials throughout the Pacific sector using such things as extratropical tree-rings, tropical corals, extratropical clam shell growth rings, and ice cores. These different proxy records have generally provided different perspectives on paleo-PDV behavior.

  1. Climate variability and causes: from the perspective of the Tharaka people of eastern Kenya

    NASA Astrophysics Data System (ADS)

    Recha, Charles W.; Makokha, George L.; Shisanya, Chris A.

    2017-12-01

    The study assessed community understanding of climate variability in semi-arid Tharaka sub-county, Kenya. The study used four focus group discussions (FGD) ( N = 48) and a household survey ( N = 326) to obtain information from four agro-ecological zones (AEZs). The results were synthesized and descriptively presented. People in Tharaka sub-county are familiar with the term climate change and associate it with environmental degradation. There are, however, misconceptions and gaps in understanding the causes of climate change. There was a mismatch between community and individual perception of onset and cessation of rainfall—evidence that analysis of the impact of climate change should take into account the scale of interaction. To improve climate change knowledge, there is a need for climate change education by scientific institutions—to provide information on local climatic conditions and global and regional drivers of climate change to local communities.

  2. The effects of climate downscaling technique and observational data set on modeled ecological responses.

    PubMed

    Pourmokhtarian, Afshin; Driscoll, Charles T; Campbell, John L; Hayhoe, Katharine; Stoner, Anne M K

    2016-07-01

    carefully considering field observations used for training, as well as the downscaling method used to generate climate change projections, for smaller-scale modeling studies. Different sources of variability including selection of AOGCM, emissions scenario, downscaling technique, and data used for training downscaling models, result in a wide range of projected forest ecosystem responses to future climate change. © 2016 by the Ecological Society of America.

  3. Operational Production of the Total Ozone Essential Climate Variable as Part of the Copernicus Climate Change Service (C3S)

    NASA Astrophysics Data System (ADS)

    Lerot, C.; Danckaert, T.; van Gent, J.; Coldewey-Egbers, M.; Loyola, D. G.; Errera, Q.; Spurr, R. J. D.; Garane, K.; Koukouli, M.; Balis, D.; Verhoelst, T.; Granville, J.; Lambert, J. C.; Van Roozendael, M.

    2017-12-01

    Total ozone is one of the Essential Climate Variables (ECV) operationally produced within the European Copernicus Climate Change Service (C3S), which aims at providing the geophysical information needed to monitor and study our climate system. The C3S total ozone processing chain relies on algorithmic developments realized for the last six years as part of the ESA’s Ozone Climate Change Initiative (Ozone_cci) project. The C3S Climate Data Store currently contains a total ozone record based on observations from the nadir UV-Vis hyperspectral spectrometers GOME/ERS-2, SCIAMACHY/Envisat, GOME-2/Metop-A, GOME-2/Metop-B and OMI/Aura, spanning more than 23 years.Individual level-2 datasets were generated with the retrieval algorithm GODFIT (GOME-type Direct FITting). The retrievals are based on a non-linear least squares adjustment of reflectances simulated with radiative transfer tools from the LIDORT suite, to the measured spectra in the Huggins bands (325-335 nm). The inter-sensor consistency and the time stability of those data sets is significantly enhanced with the application of a soft-calibration procedure to the level-1 reflectances, in which GOME and OMI are used together as a long-term reference. Level-2 data sets are then combined to produce the level-3 GOME-type Total Ozone (GTO-ECV) record consisting of homogenized 1°x1° monthly mean grids. The merging procedure corrects for subsisting inter-satellite biases and temporal drifts. Some developments for minimizing sampling errors have also been recently investigated and will be discussed. Total ozone level-2 and level-3 data sets are regularly verified and validated by independent measurements both from space (independent algorithms and/or instruments) and ground (Brewer/Dobson/SAOZ) and their excellent quality and stability, as well as their consistency with other long-term total ozone data sets will be illustrated here. In future, in addition to be continuously extended in time, the C3S total ozone record

  4. Effect of climate variability and change on winter haze over eastern China in recent decades

    NASA Astrophysics Data System (ADS)

    Liao, Hong; Yang, Yang

    2017-04-01

    In recent years, eastern China has frequently experienced persistent and severe winter haze pollution episodes with high aerosol concentrations, which have affected half of the 1.3 billion people in China. In this work, the increases in wintertime aerosol concentrations and severe haze events in eastern China over 1985-2015 were quantified by using observed atmospheric visibility from the National Climatic Data Center Global Summary of Day database, observed PM2.5 concentrations from the network of China National Environmental Monitoring Centre (CNEMC), and simulated PM2.5 concentrations from the Goddard Earth-Observing System (GEOS) chemical transport model (GEOS-Chem). Observed winter haze days (defined as days with atmospheric visibility less than 10 km and relative humidity less than 80%) averaged over eastern China (105-122.5°E, 20-45°N) increased from 21 days in 1980 to 42 days in 2014. Observed severe haze days (defined as days with PM2.5 >150 μg m-3) occurred mainly over Northern China. Considering variations in both anthropogenic emissions and meteorological parameters, the GEOS-Chem model simulated an increasing trend in wintertime surface-layer PM2.5 concentrations of 10.5 (±6.2) μg m-3 decade-1 over eastern China in the past decades. Sensitivity studies showed that changes in anthropogenic emissions and in climate contributed 87% and 17% to this increasing trend, respectively. Wintertime severe haze events over eastern China showed large interannual variations, driven by climate variability. Process analyses were performed to identify the key meteorological parameters that determined the interannual variations of wintertime severe haze events.

  5. Exploring Pacific Climate Variability and Its Impacts on East African Water Resources and Food Security

    NASA Astrophysics Data System (ADS)

    Funk, C. C.; Hoerling, M. P.; Hoell, A.; Liebmann, B.; Verdin, J. P.; Eilerts, G.

    2014-12-01

    In 8 out the past 15 boreal springs (1999, 2000, 2004, 2008, 2009, 2011, 2012, and 2013), substantial parts of eastern East Africa experienced very low boreal spring rains. These rainfall deficits have triggered widespread food insecurity, and even contributed to the outbreak of famine conditions in Somalia in 2011. At both seasonal and decadal time scales, new science supported by the USAID Famine Early Warning Systems Network seeks to understand the mechanisms producing these droughts. We present research suggesting that the ultimate and proximate causes of these increases in aridity are i) stronger equatorial Pacific SST gradients and ii) associated increases in the strength of the Indo-Pacific Walker circulation. Using observations and new modeling ensembles, we explore the relative contributions of Pacific Decadal Variability (PDV) and global warming under warm and cold east Pacific Ocean states. This question is addressed in two ways: by using atmospheric GCMs forced with full and ENSO-only SSTs, and ii) by decomposing coupled ocean-atmosphere climate simulations into PDV and non-PDV components. These analyses allow us to explore the Walker circulation’s sensitivity to climate change under various PDV states, and inform a tentative bracketing of 2030 climate conditions. We conclude by discussing links to East African development. Regions of high rainfall sensitivity are delineated and intersected with recent changes in population and land cover/land use. The interaction of elevation and climate is shown to create climatically secure regions that are likely to remain viable even under drier and warmer conditions; such regions may be logical targets for agricultural intensification. Conversely, arid low elevation regions are likely to experience substantial temperature impacts. Continued expansion into these areas may effectively create more ‘drought’ even if rainfall increases.

  6. Simulation of Anomalous Regional Climate Events with a Variable Resolution Stretched Grid GCM

    NASA Technical Reports Server (NTRS)

    Fox-Rabinovitz, Michael S.

    1999-01-01

    The stretched-grid approach provides an efficient down-scaling and consistent interactions between global and regional scales due to using one variable-resolution model for integrations. It is a workable alternative to the widely used nested-grid approach introduced over a decade ago as a pioneering step in regional climate modeling. A variable-resolution General Circulation Model (GCM) employing a stretched grid, with enhanced resolution over the US as the area of interest, is used for simulating two anomalous regional climate events, the US summer drought of 1988 and flood of 1993. The special mode of integration using a stretched-grid GCM and data assimilation system is developed that allows for imitating the nested-grid framework. The mode is useful for inter-comparison purposes and for underlining the differences between these two approaches. The 1988 and 1993 integrations are performed for the two month period starting from mid May. Regional resolutions used in most of the experiments is 60 km. The major goal and the result of the study is obtaining the efficient down-scaling over the area of interest. The monthly mean prognostic regional fields for the stretched-grid integrations are remarkably close to those of the verifying analyses. Simulated precipitation patterns are successfully verified against gauge precipitation observations. The impact of finer 40 km regional resolution is investigated for the 1993 integration and an example of recovering subregional precipitation is presented. The obtained results show that the global variable-resolution stretched-grid approach is a viable candidate for regional and subregional climate studies and applications.

  7. Food Prices and Climate Extremes: A Model of Global Grain Price Variability with Storage

    NASA Astrophysics Data System (ADS)

    Otto, C.; Schewe, J.; Frieler, K.

    2015-12-01

    Extreme climate events such as droughts, floods, or heat waves affect agricultural production in major cropping regions and therefore impact the world market prices of staple crops. In the last decade, crop prices exhibited two very prominent price peaks in 2007-2008 and 2010-2011, threatening food security especially for poorer countries that are net importers of grain. There is evidence that these spikes in grain prices were at least partly triggered by actual supply shortages and the expectation of bad harvests. However, the response of the market to supply shocks is nonlinear and depends on complex and interlinked processes such as warehousing, speculation, and trade policies. Quantifying the contributions of such different factors to short-term price variability remains difficult, not least because many existing models ignore the role of storage which becomes important on short timescales. This in turn impedes the assessment of future climate change impacts on food prices. Here, we present a simple model of annual world grain prices that integrates grain stocks into the supply and demand functions. This firstly allows us to model explicitly the effect of storage strategies on world market price, and thus, for the first time, to quantify the potential contribution of trade policies to price variability in a simple global framework. Driven only by reported production and by long–term demand trends of the past ca. 40 years, the model reproduces observed variations in both the global storage volume and price of wheat. We demonstrate how recent price peaks can be reproduced by accounting for documented changes in storage strategies and trade policies, contrasting and complementing previous explanations based on different mechanisms such as speculation. Secondly, we show how the integration of storage allows long-term projections of grain price variability under climate change, based on existing crop yield scenarios.

  8. Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease.

    PubMed

    Rohr, Jason R; Raffel, Thomas R

    2010-05-04

    The role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial, and the effect of climatic variability, in particular, has largely been ignored. For instance, it was recently revealed that the proposed link between climate change and widespread amphibian declines, putatively caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), was tenuous because it was based on a temporally confounded correlation. Here we provide temporally unconfounded evidence that global El Niño climatic events drive widespread amphibian losses in genus Atelopus via increased regional temperature variability, which can reduce amphibian defenses against pathogens. Of 26 climate variables tested, only factors associated with temperature variability could account for the spatiotemporal patterns of declines thought to be associated with Bd. Climatic predictors of declines became significant only after controlling for a pattern consistent with epidemic spread (by temporally detrending the data). This presumed spread accounted for 59% of the temporal variation in amphibian losses, whereas El Niño accounted for 59% of the remaining variation. Hence, we could account for 83% of the variation in declines with these two variables alone. Given that global climate change seems to increase temperature variability, extreme climatic events, and the strength of Central Pacific El Niño episodes, climate change might exacerbate worldwide enigmatic declines of amphibians, presumably by increasing susceptibility to disease. These results suggest that changes to temperature variability associated with climate change might be as significant to biodiversity losses and disease emergence as changes to mean temperature.

  9. QBO Influence on Polar Stratospheric Variability in the GEOS Chemistry-Climate Model

    NASA Technical Reports Server (NTRS)

    Hurwitz, M. M.; Oman, L. D.; Li, F.; Slong, I.-S.; Newman, P. A.; Nielsen, J. E.

    2010-01-01

    The quasi-biennial oscillation modulates the strength of both the Arctic and Antarctic stratospheric vortices. Model and observational studies have found that the phase and characteristics of the quasi-biennial oscillation (QBO) contribute to the high degree of variability in the Arctic stratosphere in winter. While the Antarctic stratosphere is less variable, recent work has shown that Southern Hemisphere planetary wave driving increases in response to “warm pool” El Nino events that are coincident with the easterly phase of the QBO. These events hasten the breakup of the Antarctic polar vortex. The Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) is now capable of generating a realistic QBO, due a new parameterization of gravity wave drag. In this presentation, we will use this new model capability to assess the influence of the QBO on polar stratospheric variability. Using simulations of the recent past, we will compare the modeled relationship between QBO phase and mid-winter vortex strength with the observed Holton-Tan relation, in both hemispheres. We will use simulations of the 21 St century to estimate future trends in the relationship between QBO phase and vortex strength. In addition, we will evaluate the combined influence of the QBO and El Nino/Southern Oscillation (ENSO) on the timing of the breakup of the polar stratospheric vortices in the GEOS CCM. We will compare the influence of these two natural phenomena with trends in the vortex breakup associated with ozone recovery and increasing greenhouse gas concentrations.

  10. The Effects of Solar Variability on Earth’s Climate: A Workshop Report

    NASA Technical Reports Server (NTRS)

    2012-01-01

    irradiance (TSI), and surprising results on changes in spectral irradiance over the last solar cycle, which elicited spirited discussion. New perspectives on connections between features of the quiet and active areas of the photosphere and variations in TSI were also presented, emphasizing the importance of developing better understanding in order to extrapolate back in time using activity indices. Workshop participants reviews highlighted difficulties as well as causes for optimism in current understanding of the cosmogenic isotope record and the use of observed variability in Sun-like stars in reconstructing variations in TSI occurring on lower frequencies than the sunspot cycle. The workshop succeeded in bringing together informed, focused presentations on major drivers of the Sun-climate connection. The importance of the solar cycle as a unique quasi-periodic probe of climate responses on a timescale between the seasonal and Milankovitch cycles was recognized in several presentations. The signal need only be detectable, not dominant, for it to play this role of a useful probe. Some workshop participants also found encouraging progress in the top-down perspective, according to which solar variability affects surface climate by first perturbing the stratosphere, which then forces the troposphere and surface. This work is now informing and being informed by research on tropospheric responses to the Antarctic ozone hole and volcanic aerosols. In contrast to the top-down perspective is the bottom-up view that the interaction of solar energy with the ocean and surface leads to changes in dynamics and temperature. During the discussion of how dynamical air-sea coupling in the tropical Pacific and solar variability interact from a bottom-up perspective, several participants remarked on the wealth of open research questions in the dynamics of the climatic response to TSI and spectral variability. The discussion of the paleoclimate record emphasized that the link between solar

  11. A perspective on sustained marine observations for climate modelling and prediction.

    PubMed

    Dunstone, Nick J

    2014-09-28

    Here, I examine some of the many varied ways in which sustained global ocean observations are used in numerical modelling activities. In particular, I focus on the use of ocean observations to initialize predictions in ocean and climate models. Examples are also shown of how models can be used to assess the impact of both current ocean observations and to simulate that of potential new ocean observing platforms. The ocean has never been better observed than it is today and similarly ocean models have never been as capable at representing the real ocean as they are now. However, there remain important unanswered questions that can likely only be addressed via future improvements in ocean observations. In particular, ocean observing systems need to respond to the needs of the burgeoning field of near-term climate predictions. Although new ocean observing platforms promise exciting new discoveries, there is a delicate balance to be made between their funding and that of the current ocean observing system. Here, I identify the need to secure long-term funding for ocean observing platforms as they mature, from a mainly research exercise to an operational system for sustained observation over climate change time scales. At the same time, considerable progress continues to be made via ship-based observing campaigns and I highlight some that are dedicated to addressing uncertainties in key ocean model parametrizations. The use of ocean observations to understand the prominent long time scale changes observed in the North Atlantic is another focus of this paper. The exciting first decade of monitoring of the Atlantic meridional overturning circulation by the RAPID-MOCHA array is highlighted. The use of ocean and climate models as tools to further probe the drivers of variability seen in such time series is another exciting development. I also discuss the need for a concerted combined effort from climate models and ocean observations in order to understand the current slow

  12. Climate Change in the Western United States: Projections and Observations (Invited)

    NASA Astrophysics Data System (ADS)

    Redmond, K. T.

    2009-12-01

    The interplay between projections and observations of climate, and the role of observations as they unfold, form the primary emphasis for this talk. The consensus among climate projections is that the Western United States will warm, and that annual precipitation will increase near the Canada/US border and decrease near the Mexico/US border. Inter-model agreement is greater for temperature than precipitation, though precipitation projections show some tendency toward slow convergence. Seasonal temperature changes are expected to be similar from month to month, slightly greater in summer and slightly smaller in winter. Coastal temperature increases are expected to be smaller than inland. High elevation increases may be slightly greater than those at low elevation. The precipitation season is in general expected to be more concentrated in winter, with less (or less increase, depending on latitude) precipitation in spring, summer, and autumn than without climate change. Climate should have started to depart from the baseline (no-change) case about 30-35 years ago. Observations show that temperatures West-wide did begin to rise during the 1970s. Precipitation changes have been more ambiguous. Annual temperature increases in the U.S. have been much more prominent in the West (and to some extent the north) than in the East, especially during the last decade. Summer in particular has shown a marked temperature increase since around 2000. Minimum temperatures have shown more increase (in many cases considerably more) than maximum temperatures. Annual freezing levels, from essentially independent data sets, have risen during this time. Acceptance of climate change in the public mind is increased when evidence visibly aligns with projections. This appears to have been particularly important in the western states. However, other sources of climate variability, of human or natural origin, on seasonal to decadal scales, can obscure or partially and temporarily mask expected

  13. Observed Differences between North American Snow Extent and Snow Depth Variability

    NASA Astrophysics Data System (ADS)

    Ge, Y.; Gong, G.

    2006-12-01

    Snow extent and snow depth are two related characteristics of a snowpack, but they need not be mutually consistent. Differences between these two variables at local scales are readily apparent. However at larger scales which interact with atmospheric circulation and climate, snow extent is typically the variable used, while snow depth is often assumed to be minor and/or mutually consistent compared to snow extent, though this is rarely verified. In this study, a new regional/continental-scale gridded dataset derived from field observations is utilized to quantitatively evaluate the relationship between snow extent and snow depth over North America. Various statistical methods are applied to assess the mutual consistency of monthly snow depth vs. snow extent, including correlations, composites and principal components. Results indicate that snow depth variations are significant in their own rights, and that depth and extent anomalies are largely unrelated, especially over broad high latitude regions north of the snowline. In the vicinity of the snowline, where precipitation and ablation can affect both snow extent and snow depth, the two variables vary concurrently, especially in autumn and spring. It is also found that deeper winter snow translates into larger snow-covered area in the subsequent spring/summer season, which suggests a possible influence of winter snow depth on summer climate. The observed lack of mutual consistency at continental/regional scales suggests that snowpack depth variations may be of sufficiently large magnitude, spatial scope and temporal duration to influence regional-hemispheric climate, in a manner unrelated to the more extensively studied snow extent variations.

  14. Climate Variability, Dissolved Organic Carbon, UV Exposure, and Amphibian Decline

    NASA Astrophysics Data System (ADS)

    Brooks, P. D.; O’Reilly, C. M.; Diamond, S.; Corn, S.; Muths, E.; Tonnessen, K.; Campbell, D. H.

    2001-12-01

    Increasing levels of UV radiation represent a potential threat to aquatic organisms in a wide range of environments, yet controls on in situ variability on UV exposure are relatively unknown. The primary control on the penetration of UV radiation in surface water environments is the amount of photoreactive dissolved organic carbon (DOC). Consequently, biogeochemical processes that control the cycling of DOC also affect the exposure of aquatic organisms to UV radiation. Three years of monitoring UV extinction and DOC composition in Rocky Mountain, Glacier, Sequoia/ Kings Canyon, and Olympic National Parks demonstrate that the amount of fulvic acid DOC is much more important than the total DOC pool in controlling UV attenuation. This photoreactive component of DOC originates primarily in soil, and is subject both to biogeochemical controls (e.g. temperature, moisture, vegetation, soil type) on production, and hydrologic controls on transport to surface water and consequently UV exposure to aquatic organisms. Both of these controls are positively related to precipitation with greater production and transport associated with higher precipitation amounts. For example, an approximately 20 percent reduction in precipitation from 1999 to 2000 resulted in a 27% – 59% reduction in the amount of photoreactive DOC at three sites in Rocky Mountain National Park. These differences in the amount of hydrophobic DOC result in an increase in UV exposure in the aquatic environment by a factor of 2 or more. Implications of these findings for observed patterns of amphibian decline will be discussed.

  15. Changes in tree functional composition amplify the response of forest biomass to climate variability

    NASA Astrophysics Data System (ADS)

    Lichstein, Jeremy; Zhang, Tao; Niinemets, Ulo; Sheffield, Justin

    2017-04-01

    The response of forest carbon storage to climate change is highly uncertain, contributing substantially to the divergence among global climate model projections. Numerous studies have documented responses of forest ecosystems to climate change and variability, including drought-induced increases in tree mortality rates. However, the sensitivity of forests to climate variability – in terms of both biomass carbon storage and functional components of tree species composition – has yet to be quantified across a large region using systematically sampled data. Here, we combine systematic forest inventories across the eastern USA with a species-level drought-tolerance index, derived from a meta-analysis of published literature, to quantify changes in forest biomass and community-mean-drought-tolerance in one-degree grid cells from the 1980s to 2000s. We show that forest biomass responds to decadal-scale changes in water deficit and that this biomass response is amplified by concurrent changes in community-mean-drought-tolerance. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards more drought-tolerant but lower-biomass species. Multiple plant functional traits are correlated with the above species-level drought-tolerance index, and likely contribute to the decrease in biomass with increasing drought-tolerance. These traits include wood density and P50 (the xylem water potential at which a plant loses 50% of its hydraulic conductivity). Simulations with a trait- and competition-based dynamic global vegetation model suggest that species differences in plant carbon allocation to wood, leaves, and fine roots also likely contribute to the observed decrease in biomass with increasing drought-tolerance, because competition drives plants to over-invest in fine roots when water is limiting. Thus, the most competitive species under dry conditions have greater root allocation but

  16. Sea-Level Trend Uncertainty With Pacific Climatic Variability and Temporally-Correlated Noise

    NASA Astrophysics Data System (ADS)

    Royston, Sam; Watson, Christopher S.; Legrésy, Benoît; King, Matt A.; Church, John A.; Bos, Machiel S.

    2018-03-01

    Recent studies have identified climatic drivers of the east-west see-saw of Pacific Ocean satellite altimetry era sea level trends and a number of sea-level trend and acceleration assessments attempt to account for this. We investigate the effect of Pacific climate variability, together with temporally-correlated noise, on linear trend error estimates and determine new time-of-emergence (ToE) estimates across the Indian and Pacific Oceans. Sea-level trend studies often advocate the use of auto-regressive (AR) noise models to adequately assess formal uncertainties, yet sea level often exhibits colored but non-AR(1) noise. Standard error estimates are over- or under-estimated by an AR(1) model for much of the Indo-Pacific sea level. Allowing for PDO and ENSO variability in the trend estimate only reduces standard errors across the tropics and we find noise characteristics are largely unaffected. Of importance for trend and acceleration detection studies, formal error estimates remain on average up to 1.6 times those from an AR(1) model for long-duration tide gauge data. There is an even chance that the observed trend from the satellite altimetry era exceeds the noise in patches of the tropical Pacific and Indian Oceans and the south-west and north-east Pacific gyres. By including climate indices in the trend analysis, the time it takes for the observed linear sea-level trend to emerge from the noise reduces by up to 2 decades.

  17. Climate observing system studies: An element of the NASA Climate Research Program: Workshop report

    NASA Technical Reports Server (NTRS)

    1980-01-01

    Plans for NASA’s efforts in climatology were discussed. Targets for a comprehensive observing system for the early 1990’s were considered. A program to provide useful data in the near and mid-term, and a program to provide for a feasibility assessment of instruments and methods for the development of a long-term system were discussed. Climate parameters that cannot be measured from space were identified. Long-term calibration, intercomparison, standards, and ground truth were discussed.

  18. Variability of tropical cyclone rapid intensification in the North Atlantic and its relationship with climate variations

    NASA Astrophysics Data System (ADS)

    Wang, Chunzai; Wang, Xidong; Weisberg, Robert H.; Black, Michael L.

    2017-12-01

    The paper uses observational data from 1950 to 2014 to investigate rapid intensification (RI) variability of tropical cyclones (TCs) in the North Atlantic and its relationships with large-scale climate variations. RI is defined as a TC intensity increase of at least 15.4 m/s (30 knots) in 24 h. The seasonal RI distribution follows the seasonal TC distribution, with the highest number in September. Although an RI event can occur anywhere over the tropical North Atlantic (TNA), there are three regions of maximum RI occurrence: (1) the western TNA of 12°N-18°N and 60°W-45°W, (2) the Gulf of Mexico and the western Caribbean Sea, and (3) the open ocean southeast and east of Florida. RI events also show a minimum value in the eastern Caribbean Sea north of South America—a place called a hurricane graveyard due to atmospheric divergence and subsidence. On longer time scales, RI displays both interannual and multidecadal variability, but RI does not show a long-term trend due to global warming. The top three climate indices showing high correlations with RI are the June-November ENSO and Atlantic warm pool indices, and the January-March North Atlantic oscillation index. It is found that variabilities of vertical wind shear and TC heat potential are important for TC RI in the hurricane main development region, whereas relative humidity at 500 hPa is the main factor responsible for TC RI in the eastern TNA. However, the large-scale oceanic and atmospheric variables analyzed in this study do not show an important role in TC RI in the Gulf of Mexico and the open ocean southeast and east of Florida. This suggests that other factors such as small-scale changes of oceanic and atmospheric variables or TC internal processes may be responsible for TC RI in these two regions. Additionally, the analyses indicate that large-scale atmospheric and oceanic variables are not critical to TC genesis and formation; however, once a tropical depression forms, large-scale climate

  19. Climate, soil or both? Which variables are better predictors of the distributions of Australian shrub species?

    PubMed Central

    Esperón-Rodríguez, Manuel; Baumgartner, John B.; Beaumont, Linda J.

    2017-01-01

    Background Shrubs play a key role in biogeochemical cycles, prevent soil and water erosion, provide forage for livestock, and are a source of food, wood and non-wood products. However, despite their ecological and societal importance, the influence of different environmental variables on shrub distributions remains unclear. We evaluated the influence of climate and soil characteristics, and whether including soil variables improved the performance of a species distribution model (SDM), Maxent. Methods This study assessed variation in predictions of environmental suitability for 29 Australian shrub species (representing dominant members of six shrubland classes) due to the use of alternative sets of predictor variables. Models were calibrated with (1) climate variables only, (2) climate and soil variables, and (3) soil variables only. Results The predictive power of SDMs differed substantially across species, but generally models calibrated with both climate and soil data performed better than those calibrated only with climate variables. Models calibrated solely with soil variables were the least accurate. We found regional differences in potential shrub species richness across Australia due to the use of different sets of variables. Conclusions Our study provides evidence that predicted patterns of species richness may be sensitive to the choice of predictor set when multiple, plausible alternatives exist, and demonstrates the importance of considering soil properties when modeling availability of habitat for plants. PMID:28652933

  20. OBSERVATIONS OF THERMAL FLARE PLASMA WITH THE EUV VARIABILITY EXPERIMENT

    SciTech Connect

    Warren, Harry P.; Doschek, George A.; Mariska, John T.

    2013-06-20

    One of the defining characteristics of a solar flare is the impulsive formation of very high temperature plasma. The properties of the thermal emission are not well understood, however, and the analysis of solar flare observations is often predicated on the assumption that the flare plasma is isothermal. The EUV Variability Experiment (EVE) on the Solar Dynamics Observatory provides spectrally resolved observations of emission lines that span a wide range of temperatures (e.g., Fe XV-Fe XXIV) and allow for thermal flare plasma to be studied in detail. In this paper we describe a method for computing the differential emission measuremore » distribution in a flare using EVE observations and apply it to several representative events. We find that in all phases of the flare the differential emission measure distribution is broad. Comparisons of EVE spectra with calculations based on parameters derived from the Geostationary Operational Environmental Satellites soft X-ray fluxes indicate that the isothermal approximation is generally a poor representation of the thermal structure of a flare.« less

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