WorldWideScience

Sample records for climate variability project

  1. US Climate Variability and Predictability Project

    Energy Technology Data Exchange (ETDEWEB)

    Patterson, Mike [University Corporation for Atmospheric Research (UCAR), Boulder, CO (United States)

    2017-11-14

    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 support 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.

  2. Human activity and climate variability project: annual report 2001

    International Nuclear Information System (INIS)

    Harle, K.J.; Heijnis, H.; Henderson-Sellers, A.; Sharmeen, S.; Zahorowski, W.

    2002-01-01

    Knowledge of the state of the Australian environment, including natural climate variability, prior to colonial settlement is vital if we are to define and understand the impact of over two hundred years of post-industrial human activity on our landscape. ANSTO, in conjunction with university partners, is leading a major research effort to provide natural archives of human activity and climate variability over the last 500 years in Australia, utilising a variety of techniques, including lead-210 and radiocarbon dating and analyses of proxy indicators (such as microfossils) as well as direct evidence (such as trace elements) of human activity and climate variability. The other major project objectives were to contribute to the understanding of the impact of human induced and natural aerosols in the East Asian region on climate through analysis and sourcing of fine particles and characterisation of air samples using radon concentrations and to contribute to the improvement of land surface parameterisation schemes and investigate the potential to use stable isotopes to improve global climate models and thus improve our understanding of future climate

  3. Climate variability and climate change

    International Nuclear Information System (INIS)

    Rind, D.

    1990-01-01

    Changes of variability with climate change are likely to have a substantial impact on vegetation and society, rivaling the importance of changes in the mean values themselves. A variety of paleoclimate and future climate simulations performed with the GISS global climate model is used to assess how the variabilities of temperature and precipitation are altered as climate warms or cools. In general, as climate warms, temperature variability decreases due to reductions in the latitudinal temperature gradient and precipitation variability increases together with the intensity of the hydrologic cycle. If future climate projections are accurate, the reduction in temperature variability will be minimized by the rapid change in mean temperatures, but the hydrologic variability will be amplified by increased evapotranspiration. Greater hydrologic variability would appear to pose a potentially severe problem for the next century

  4. Climate variability and climate change

    International Nuclear Information System (INIS)

    Rind, D.

    1991-01-01

    Changes of variability with climate change are likely to have a substantial impact on vegetation and society, rivaling the importance of changes in the mean values themselves. A variety of paleoclimate and future climate simulations performed with the GISS global climate model is used to assess how the variabilities of temperature and precipitation are altered as climate warms or cools. In general, as climate warms, temperature variability decreases due to reductions in the latitudinal temperature gradient and precipitation variability increases together with the intensity of the hydrologic cycle. If future climate projections are accurate, the reduction in temperature variability will be minimized by the rapid change in mean temperatures, but the hydrologic variability will be amplified by increased evapotranspiration. Greater hydrologic variability would appear to pose a potentially severe problem for the next century. 19 refs.; 3 figs.; 2 tabs

  5. Climate related diseases. Current regional variability and projections to the year 2100

    Directory of Open Access Journals (Sweden)

    Błażejczyk Krzysztof

    2018-03-01

    Full Text Available The health of individuals and societies depends on different factors including atmospheric conditions which influence humans in direct and indirect ways. The paper presents regional variability of some climate related diseases (CRD in Poland: salmonellosis intoxications, Lyme boreliosis, skin cancers (morbidity and mortality, influenza, overcooling deaths, as well as respiratory and circulatory mortality. The research consisted of two stages: 1 statistical modelling basing on past data and 2 projections of CRD for three SRES scenarios of climate change (A1B, A2, B1 to the year 2100. Several simple and multiply regression models were found for the relationships between climate variables and CRD. The models were applied to project future levels of CRD. At the end of 21st century we must expect increase in: circulatory mortality, Lyme boreliosis infections and skin cancer morbidity and mortality. There is also projected decrease in: respiratory mortality, overcooling deaths and influenza infections.

  6. Climate Projections and Uncertainty Communication.

    Science.gov (United States)

    Joslyn, Susan L; LeClerc, Jared E

    2016-01-01

    Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists' estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis was tested in two experiments. Results suggest that including uncertainty estimates along with climate projections leads to an increase in participants' trust in the information. Analyses explored the roles of time, place, demographic differences (e.g., age, gender, education level, political party affiliation), and initial belief in climate change. Implications are discussed in terms of the potential benefit of adding uncertainty estimates to public climate projections. Copyright © 2015 Cognitive Science Society, Inc.

  7. Climate change projections of heat stress in Europe: From meteorological variables to impacts on productivity

    Science.gov (United States)

    Casanueva, Ana; Kotlarski, Sven; Liniger, Mark A.

    2017-04-01

    Future climate change is likely to have important impacts in many socio-economic sectors. In particular, higher summer temperatures or more prolonged heat waves may be responsible for health problems and productivity losses related to heat stress, especially affecting people exposed to such situations (e.g. working under outside settings or in non-acclimatized workplaces). Heat stress on the body under work load and consequently their productivity loss can be described through heat stress indices that are based on multiple meteorological parameters such as temperature, humidity, wind and radiation. Exploring the changes of these variables under a warmer climate is of prime importance for the Impacts, Adaptation and Vulnerability communities. In particular, the H2020 project HEAT-SHIELD aims at analyzing the impact of climate change on heat stress in strategic industries in Europe (manufacturing, construction, transportation, tourism and agriculture) within an inter-sectoral framework (climate scientists, biometeorologists, physiologists and stakeholders). In the present work we explore present and future heat stress over Europe using an ensemble of the state-of-the-art RCMs from the EURO-CORDEX initiative. Since RCMs cannot be directly used in impact studies due to their partly substantial biases, a standard bias correction method (empirical quantile mapping) is applied to correct the individual variables that are then used to derive heat stress indices. The objectives of this study are twofold, 1) to test the ability of the separately bias corrected variables to reproduce the main characteristics of heat stress indices in present climate conditions and 2) to explore climate change projections of heat stress indices. We use the wet bulb globe temperature (WBGT) as primary heat stress index, considering two different versions for indoor (or in the shade, based on temperature and humidity conditions) and outdoor settings (including also wind and radiation). The WBGT

  8. Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies

    International Nuclear Information System (INIS)

    Fatichi, S.; Rimkus, S.; Burlando, P.; Bordoy, R.

    2014-01-01

    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. - Highlights:

  9. Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies

    Energy Technology Data Exchange (ETDEWEB)

    Fatichi, S., E-mail: simone.fatichi@ifu.baug.ethz.ch; 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. - Highlights:

  10. Climate Change and Variability in Ghana: Stocktaking

    Directory of Open Access Journals (Sweden)

    Felix A. Asante

    2014-12-01

    Full Text Available This paper provides a holistic literature review of climate change and variability in Ghana by examining the impact and projections of climate change and variability in various sectors (agricultural, health and energy and its implication on ecology, land use, poverty and welfare. The findings suggest that there is a projected high temperature and low rainfall in the years 2020, 2050 and 2080, and desertification is estimated to be proceeding at a rate of 20,000 hectares per annum. Sea-surface temperatures will increase in Ghana’s waters and this will have drastic effects on fishery. There will be a reduction in the suitability of weather within the current cocoa-growing areas in Ghana by 2050 and an increase evapotranspiration of the cocoa trees. Furthermore, rice and rooted crops (especially cassava production are expected to be low. Hydropower generation is also at risk and there will be an increase in the incidence rate of measles, diarrheal cases, guinea worm infestation, malaria, cholera, cerebro-spinal meningitis and other water related diseases due to the current climate projections and variability. These negative impacts of climate change and variability worsens the plight of the poor, who are mostly women and children.

  11. Effects of interannual climate variability on tropical tree cover

    NARCIS (Netherlands)

    Holmgren, M.; Hirota, M.; Nes, van E.H.; Scheffer, M.

    2013-01-01

    Climatic warming is substantially intensifying the global water cycle1 and is projected to increase rainfall variability2. Using satellite data, we show that higher climatic variability is associated with reduced tree cover in the wet tropics globally. In contrast, interannual variability in

  12. A modelling framework to project future climate change impacts on streamflow variability and extremes in the West River, China

    Directory of Open Access Journals (Sweden)

    Y. Fei

    2014-09-01

    Full Text Available In this study, a hydrological modelling framework was introduced to assess the climate change impacts on future river flow in the West River basin, China, especially on streamflow variability and extremes. The modelling framework includes a delta-change method with the quantile-mapping technique to construct future climate forcings on the basis of observed meteorological data and the downscaled climate model outputs. This method is able to retain the signals of extreme weather events, as projected by climate models, in the constructed future forcing scenarios. Fed with the historical and future forcing data, a large-scale hydrologic model (the Variable Infiltration Capacity model, VIC was executed for streamflow simulations and projections at daily time scales. A bootstrapping resample approach was used as an indirect alternative to test the equality of means, standard deviations and the coefficients of variation for the baseline and future streamflow time series, and to assess the future changes in flood return levels. The West River basin case study confirms that the introduced modelling framework is an efficient effective tool to quantify streamflow variability and extremes in response to future climate change.

  13. Post-Fire Recovery of Eco-Hydrologic Behavior Given Historic and Projected Climate Variability in California Mediterranean Type Environments

    Science.gov (United States)

    Seaby, L. P.; Tague, C. L.; Hope, A. S.

    2006-12-01

    The Mediterranean type environments (MTEs) of California are characterized by a distinct wet and dry season and high variability in inter-annual climate. Water limitation in MTEs makes eco-hydrological processes highly sensitive to both climate variability and frequent fire disturbance. This research modeled post-fire eco- hydrologic behavior under historical and moderate and extreme scenarios of future climate in a semi-arid chaparral dominated southern California MTE. We used a physically-based, spatially-distributed, eco- hydrological model (RHESSys - Regional Hydro-Ecologic Simulation System), to capture linkages between water and vegetation response to the combined effects of fire and historic and future climate variability. We found post-fire eco-hydrologic behavior to be strongly influenced by the episodic nature of MTE climate, which intensifies under projected climate change. Higher rates of post-fire net primary productivity were found under moderate climate change, while more extreme climate change produced water stressed conditions which were less favorable for vegetation productivity. Precipitation variability in the historic record follows the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), and these inter-annual climate characteristics intensify under climate change. Inter-annual variation in streamflow follows these precipitation patterns. Post-fire streamflow and carbon cycling trajectories are strongly dependent on climate characteristics during the first 5 years following fire, and historic intra-climate variability during this period tends to overwhelm longer term trends and variation that might be attributable to climate change. Results have implications for water resource availability, vegetation type conversion from shrubs to grassland, and changes in ecosystem structure and function.

  14. Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies.

    Science.gov (United States)

    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. Multi-wheat-model ensemble responses to interannual climatic variability

    DEFF Research Database (Denmark)

    Ruane, A C; Hudson, N I; Asseng, S

    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 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......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 1981–2010 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...

  16. Downscaled Climate Change Projections for the Southern Colorado Plateau: Variability and Implications for Vegetation Changes

    Science.gov (United States)

    Garfin, G. M.; Eischeid, J. K.; Cole, K. L.; Ironside, K.; Cobb, N. S.

    2008-12-01

    most striking aspect of projections of future precipitation is steadily decreasing May-June precipitation during the twenty-first century. Though absolute precipitation during this season is small, declining moisture during the arid pre-monsoon will likely decrease soil moisture, and increase drought stress - consequently, increasing vegetation susceptibility the insect outbreaks and disease. Summer precipitation projections show considerable multi-decade variability, but no substantial trends. Winter precipitation shows little interannual variability and no strong trends. By 2090, annual precipitation is projected to decline by 1-5% across much of the region, with greater declines in the southern part of the domain and increases of 1-5% in the northwestern and northeastern parts of the domain. As part of a National Institute for Climate Change Research project, these projected changes will be input into a USDA-FS vegetation response model, in order to estimate species-specific responses to projected climate changes. We expect increasing temperatures, declining annual precipitation, and extreme declines in pre-monsoon season precipitation to generate significant redistribution of some plant species in the Southern Colorado Plateau.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  19. Human activity and climate variability project - annual report 2002

    International Nuclear Information System (INIS)

    Chambers, S.; Harle, K.J.; Sharmeen, S.; Zahorowski, W.; Cohen, D.; Heijnis, H.; Henderson-Sellers, A

    2002-01-01

    Work is well underway on identifying the spatial and temporal extent, direction and range of trace element transport across Tasmania through analysis of lake sediments; A follow up investigation of sedimentation and pollution in the Nattai River catchment following the devastating 2001 bushfires in the region has been completed; The project has been extended to include investigations of evidence of human impacts in the highly sensitive and ecologically important Great Lakes of coastal NSW. This has involved the expansion of our collaboration to include Geoscience Australia; Contributions have been made to the IGBP HITE project. Further contributions will be made as the evidence gathered is drawn together and interpreted; Over the coming year, focus will be placed on completion of the investigation of the extent of aerial transport of trace elements across Tasmania over the last 200 years as well as evidence for human activity and impacts on the Great Lakes region of NSW. Further investigation of potential climate signals from sites in northern Australia will also be made. The first 12 months of data for all ACE-Asia radon and fine particle sites is now available with preliminary analyses performed; The seasonal variability of background radon concentration at each of the radon monitoring sites has been characterised for the available data; Major components related to industrial pollution and soil sources in China have been identified and quantified; Regional and seasonal variations and trends in aerosol constituents have been measured and compared across more than 2.8Mk 2 of sampling area; The Hok Tsui and Kosan detectors were visited for general maintenance and recalibration; A grant application to the APN has been submitted in support of regional inventory analyses based on radon time series; Progress on the processing and interpretation of radon data was presented at the Cape Grim Science Meeting (6-7 February 2002) and the 7th Biennial SPERA Conference on

  20. Human activity and climate variability project - annual report 2002

    Energy Technology Data Exchange (ETDEWEB)

    Chambers, S; Harle, K J; Sharmeen, S; Zahorowski, W; Cohen, D; Heijnis, H; Henderson-Sellers, A [Australian Nuclear Science and Technology Organisation, Menai, NSW (Australia)

    2002-07-01

    Work is well underway on identifying the spatial and temporal extent, direction and range of trace element transport across Tasmania through analysis of lake sediments; A follow up investigation of sedimentation and pollution in the Nattai River catchment following the devastating 2001 bushfires in the region has been completed; The project has been extended to include investigations of evidence of human impacts in the highly sensitive and ecologically important Great Lakes of coastal NSW. This has involved the expansion of our collaboration to include Geoscience Australia; Contributions have been made to the IGBP HITE project. Further contributions will be made as the evidence gathered is drawn together and interpreted; Over the coming year, focus will be placed on completion of the investigation of the extent of aerial transport of trace elements across Tasmania over the last 200 years as well as evidence for human activity and impacts on the Great Lakes region of NSW. Further investigation of potential climate signals from sites in northern Australia will also be made. The first 12 months of data for all ACE-Asia radon and fine particle sites is now available with preliminary analyses performed; The seasonal variability of background radon concentration at each of the radon monitoring sites has been characterised for the available data; Major components related to industrial pollution and soil sources in China have been identified and quantified; Regional and seasonal variations and trends in aerosol constituents have been measured and compared across more than 2.8Mk{sup 2} of sampling area; The Hok Tsui and Kosan detectors were visited for general maintenance and recalibration; A grant application to the APN has been submitted in support of regional inventory analyses based on radon time series; Progress on the processing and interpretation of radon data was presented at the Cape Grim Science Meeting (6-7 February 2002) and the 7th Biennial SPERA Conference on

  1. AMOC decadal variability in Earth system models: Mechanisms and climate impacts

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, Alexey [Yale Univ., New Haven, CT (United States)

    2017-09-06

    This is the final report for the project titled "AMOC decadal variability in Earth system models: Mechanisms and climate impacts". The central goal of this one-year research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) within a hierarchy of climate models ranging from realistic ocean GCMs to Earth system models. The AMOC is a key element of ocean circulation responsible for oceanic transport of heat from low to high latitudes and controlling, to a large extent, climate variations in the North Atlantic. The questions of the AMOC stability, variability and predictability, directly relevant to the questions of climate predictability, were at the center of the research work.

  2. What Climate Sensitivity Index Is Most Useful for Projections?

    Science.gov (United States)

    Grose, Michael R.; Gregory, Jonathan; Colman, Robert; Andrews, Timothy

    2018-02-01

    Transient climate response (TCR), transient response at 140 years (T140), and equilibrium climate sensitivity (ECS) indices are intended as benchmarks for comparing the magnitude of climate response projected by climate models. It is generally assumed that TCR or T140 would explain more variability between models than ECS for temperature change over the 21st century, since this timescale is the realm of transient climate change. Here we find that TCR explains more variability across Coupled Model Intercomparison Project phase 5 than ECS for global temperature change since preindustrial, for 50 or 100 year global trends up to the present, and for projected change under representative concentration pathways in regions of delayed warming such as the Southern Ocean. However, unexpectedly, we find that ECS correlates higher than TCR for projected change from the present in the global mean and in most regions. This higher correlation does not relate to aerosol forcing, and the physical cause requires further investigation.

  3. Present and Future Modes of Low Frequency Climate Variability

    Energy Technology Data Exchange (ETDEWEB)

    Cane, Mark A.

    2014-02-20

    This project addressed area (1) of the FOA, “Interaction of Climate Change and Low Frequency Modes of Natural Climate Variability”. Our overarching objective is to detect, describe and understand the changes in low frequency variability between model simulations of the preindustrial climate and simulations of a doubled CO2 climate. The deliverables are a set of papers providing a dynamical characterization of interannual, decadal, and multidecadal variability in coupled models with attention to the changes in this low frequency variability between pre-industrial concentrations of greenhouse gases and a doubling of atmospheric concentrations of CO2. The principle mode of analysis, singular vector decomposition, is designed to advance our physical, mechanistic understanding. This study will include external natural variability due to solar and volcanic aerosol variations as well as variability internal to the climate system. An important byproduct is a set of analysis tools for estimating global singular vector structures from the archived output of model simulations.

  4. Impact of internal variability on projections of Sahel precipitation change

    Science.gov (United States)

    Monerie, Paul-Arthur; Sanchez-Gomez, Emilia; Pohl, Benjamin; Robson, Jon; Dong, Buwen

    2017-11-01

    The impact of the increase of greenhouse gases on Sahelian precipitation is very uncertain in both its spatial pattern and magnitude. In particular, the relative importance of internal variability versus external forcings depends on the time horizon considered in the climate projection. In this study we address the respective roles of the internal climate variability versus external forcings on Sahelian precipitation by using the data from the CESM Large Ensemble Project, which consists of a 40 member ensemble performed with the CESM1-CAM5 coupled model for the period 1920-2100. We show that CESM1-CAM5 is able to simulate the mean and interannual variability of Sahel precipitation, and is representative of a CMIP5 ensemble of simulations (i.e. it simulates the same pattern of precipitation change along with equivalent magnitude and seasonal cycle changes as the CMIP5 ensemble mean). However, CESM1-CAM5 underestimates the long-term decadal variability in Sahel precipitation. For short-term (2010-2049) and mid-term (2030-2069) projections the simulated internal variability component is able to obscure the projected impact of the external forcing. For long-term (2060-2099) projections external forcing induced change becomes stronger than simulated internal variability. Precipitation changes are found to be more robust over the central Sahel than over the western Sahel, where climate change effects struggle to emerge. Ten (thirty) members are needed to separate the 10 year averaged forced response from climate internal variability response in the western Sahel for a long-term (short-term) horizon. Over the central Sahel two members (ten members) are needed for a long-term (short-term) horizon.

  5. Selecting downscaled climate projections for water resource impacts and adaptation

    Science.gov (United States)

    Vidal, Jean-Philippe; Hingray, Benoît

    2015-04-01

    Increasingly large ensembles of global and regional climate projections are being produced and delivered to the climate impact community. However, such an enormous amount of information can hardly been dealt with by some impact models due to computational constraints. Strategies for transparently selecting climate projections are therefore urgently needed for informing small-scale impact and adaptation studies and preventing potential pitfalls in interpreting ensemble results from impact models. This work proposes results from a selection approach implemented for an integrated water resource impact and adaptation study in the Durance river basin (Southern French Alps). A large ensemble of 3000 daily transient gridded climate projections was made available for this study. It was built from different runs of 4 ENSEMBLES Stream2 GCMs, statistically downscaled by 3 probabilistic methods based on the K-nearest neighbours resampling approach (Lafaysse et al., 2014). The selection approach considered here exemplifies one of the multiple possible approaches described in a framework for identifying tailored subsets of climate projections for impact and adaptation studies proposed by Vidal & Hingray (2014). It was chosen based on the specificities of both the study objectives and the characteristics of the projection dataset. This selection approach aims at propagating as far as possible the relative contributions of the four different sources of uncertainties considered, namely GCM structure, large-scale natural variability, structure of the downscaling method, and catchment-scale natural variability. Moreover, it took the form of a hierarchical structure to deal with the specific constraints of several types of impact models (hydrological models, irrigation demand models and reservoir management models). The implemented 3-layer selection approach is therefore mainly based on conditioned Latin Hypercube sampling (Christierson et al., 2012). The choice of conditioning

  6. Projected climate change futures for Southern Africa

    CSIR Research Space (South Africa)

    Tadross, M

    2017-10-01

    Full Text Available of the Council for Scientific and Industrial Research (CSIR) in South Africa. In these experiments, a variable-resolution atmospheric global circulation model, CCAM, was applied as a regional climate model (RCM) to simulate both present-day and future climate... climate projection Observed climate RCM Climate forcing Climate simulation Statistical downscaling Dynamical downscaling 22 | Second Edition There are four pathways – RCP2.6, RCP4.5, RCP6.0 and RCP8.5. RCP 2.6 describes a scenario of very low...

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

    Science.gov (United States)

    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.

  8. The GHG-CCI Project to Deliver the Essential Climate Variable Greenhouse Gases: Current status

    Science.gov (United States)

    Buchwitz, M.; Boesch, H.; Reuter, M.

    2012-04-01

    The GHG-CCI project (http://www.esa-ghg-cci.org) is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs). The goal of GHG-CCI is to deliver global satellite-derived data sets of the two most important anthropogenic greenhouse gases (GHGs) carbon dioxide (CO2) and methane (CH4) suitable to obtain information on regional CO2 and CH4 surface sources and sinks as needed for better climate prediction. The GHG-CCI core ECV data products are column-averaged mole fractions of CO2 and CH4, XCO2 and XCH4, retrieved from SCIAMACHY on ENVISAT and TANSO on GOSAT. Other satellite instruments will be used to provide constraints in upper layers such as IASI, MIPAS, and ACE-FTS. Which of the advanced algorithms, which are under development, will be the best for a given data product still needs to be determined. For each of the 4 GHG-CCI core data products - XCO2 and XCH4 from SCIAMACHY and GOSAT - several algorithms are bing further developed and the corresponding data products are inter-compared to identify which data product is the most appropriate. This includes comparisons with corresponding data products generated elsewhere, most notably with the operational data products of GOSAT generated at NIES and the NASA/ACOS GOSAT XCO2 product. This activity, the so-called "Round Robin exercise", will be performed in the first two years of this project. At the end of the 2 year Round Robin phase (end of August 2012) a decision will be made which of the algorithms performs best. The selected algorithms will be used to generate the first version of the ECV GHG. In the last six months of this 3 year project the resulting data products will be validated and made available to all interested users. In the presentation and overview about this project will be given focussing on the latest results.

  9. Climate Variability and Sugarcane Yield in Louisiana.

    Science.gov (United States)

    Greenland, David

    2005-11-01

    )], mean maximum August temperature, mean minimum February temperature, soil water surplus between April and September, and occurrence of autumn (fall) hurricanes, were built into a model to simulate adjusted yield values. The CCV model simulates the yield value with an rmse of 5.1 t ha-1. The mean of the adjusted yield data over the study period was 60.4 t ha-1, with values for the highest and lowest years being 73.1 and 50.6 t ha-1, respectively, and a standard deviation of 5.9 t ha-1. Presumably because of the almost constant high water table and soil water availability, higher precipitation totals, which are inversely related to radiation and temperature, tend to have a negative effect on the yields. Past trends in the values of critical climatic variables and general projections of future climate suggest that, with respect to the climatic environment and as long as land drainage is continued and maintained, future levels of sugarcane yield will rise in Louisiana.

  10. Changes in field workability and drought risk from projected climate change drive spatially variable risks in Illinois cropping systems.

    Directory of Open Access Journals (Sweden)

    Bradley J Tomasek

    Full Text Available As weather patterns become more volatile and extreme, risks introduced by weather variability will become more critical to agricultural production. The availability of days suitable for field work is driven by soil temperature and moisture, both of which may be altered by climate change. We projected changes in Illinois season length, spring field workability, and summer drought risk under three different emissions scenarios (B1, A1B, and A2 down to the crop district scale. Across all scenarios, thermal time units increased in parallel with a longer frost-free season. An increase in late March and Early April field workability was consistent across scenarios, but a decline in overall April through May workable days was observed for many cases. In addition, summer drought metrics were projected to increase for most scenarios. These results highlight how the spatial and temporal variability in climate change may present unique challenges to mitigation and adaptation efforts.

  11. Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

    Science.gov (United States)

    Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim

    2016-04-01

    The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

  12. A Framework for Benefit-Cost Analysis of Adaptation to Climate Change and Climate Variability

    International Nuclear Information System (INIS)

    Leary, N.A.

    1999-01-01

    The potential damages of climate change and climate variability are dependent upon the responses or adaptations that people make to their changing environment. By adapting the management of resources, the mix and methods of producing goods and services, choices of leisure activities, and other behavior, people can lessen the damages that would otherwise result. A framework for assessing the benefits and costs of adaptation to both climate change and climate variability is described in the paper. The framework is also suitable for evaluating the economic welfare effects of climate change, allowing for autonomous adaptation by private agents. The paper also briefly addresses complications introduced by uncertainty regarding the benefits of adaptation and irreversibility of investments in adaptation. When investment costs are irreversible and there is uncertainty about benefits, the usual net present value criterion for evaluating the investment gives the wrong decision. If delaying an adaptation project is possible, and if delay will permit learning about future benefits of adaptation, it may be preferable to delay the project even if the expected net present value is positive. Implications of this result for adaptation policy are discussed in the paper. 11 refs

  13. Extreme climate in China. Facts, simulation and projection

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Hui-Jun; Sun, Jian-Qi; Chen, Huo-Po; Zhu, Ya-Li; Zhang, Ying; Jiang, Da-Bang; Lang, Xian-Mei; Fan, Ke; Yu, En-Tao [Chinese Academy of Sciences, Beijing (China). Inst. of Atmospheric Physics; Yang, Song [NOAA Climate Prediction Center, Camp Springs, MD (United States)

    2012-06-15

    In this paper, studies on extreme climate in China including extreme temperature and precipitation, dust weather activity, tropical cyclone activity, intense snowfall and cold surge activity, floods, and droughts are reviewed based on the peer-reviewed publications in recent decades. The review is focused first on the climatological features, variability, and trends in the past half century and then on simulations and projections based on global and regional climate models. As the annual mean surface air temperature (SAT) increased throughout China, heat wave intensity and frequency overall increased in the past half century, with a large rate after the 1980s. The daily or yearly minimum SAT increased more significantly than the mean or maximum SAT. The long-term change in precipitation is predominantly characterized by the so-called southern flood and northern drought pattern in eastern China and by the overall increase over Northwest China. The interdecadal variation of monsoon, represented by the monsoon weakening in the end of 1970s, is largely responsible for this change in mean precipitation. Precipitation-related extreme events (e.g., heavy rainfall and intense snowfall) have become more frequent and intense generally over China in the recent years, with large spatial features. Dust weather activity, however, has become less frequent over northern China in the recent years, as result of weakened cold surge activity, reinforced precipitation, and improved vegetation condition. State-of-the-art climate models are capable of reproducing some features of the mean climate and extreme climate events. However, discrepancies among models in simulating and projecting the mean and extreme climate are also demonstrated by many recent studies. Regional models with higher resolutions often perform better than global models. To predict and project climate variations and extremes, many new approaches and schemes based on dynamical models, statistical methods, or their

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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...

  16. Climate variability and sedimentation of a hydropower reservoir

    International Nuclear Information System (INIS)

    Riedel, M.

    2008-01-01

    As part of the relicensing of a large Hydroelectric Project in the central Appalachians, large scale watershed and reservoir sedimentation models were developed to forecast potential sedimentation scenarios. The GIS based watershed model was spatially explicit and calibrated to long term observed data. Potential socio/economic development scenarios were used to construct future watershed land cover scenarios. Climatic variability and potential change analysis were used to identify future climate regimes and shifts in precipitation and temperature patterns. Permutations of these development and climate changes were forecasted over 50 years and used to develop sediment yield regimes to the project reservoir. Extensive field work and reservoir survey, including current and wave instrumentation, were used to characterize the project watershed, rivers and reservoir hydrodynamics. A fully 3 dimensional hydrodynamic reservoir sedimentation model was developed for the project and calibrated to observed data. Hydrologic and sedimentation results from watershed forecasting provided boundary conditions for reservoir inputs. The calibrated reservoir model was then used to forecast changes in reservoir sedimentation and storage capacity under different future climate scenarios. Results indicated unique zones of advancing sediment deltas and temporary storage areas. Forecasted changes in reservoir bathymetry and sedimentation patterns were also developed for the various climate change scenarios. The warmer and wetter scenario produced sedimentation impacts similar to extensive development under no climate change. The results of these analyses are being used to develop collaborative watershed and soil conservation partnerships to reduce future soil losses and reservoir sedimentation from projected development. (author)

  17. Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands

    Science.gov (United States)

    Hamlet, Alan F.; Palen, Wendy J.; Lawler, Joshua J.; Halabisky, Meghan

    2015-01-01

    Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916–2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce

  18. Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands.

    Science.gov (United States)

    Lee, Se-Yeun; Ryan, Maureen E; Hamlet, Alan F; Palen, Wendy J; Lawler, Joshua J; Halabisky, Meghan

    2015-01-01

    Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916-2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce

  19. Long-term trends in geomagnetic and climatic variability

    Czech Academy of Sciences Publication Activity Database

    Bucha, Václav

    2002-01-01

    Roč. 27, 6/7 (2002), s. 427-731 ISSN 1474-7065 R&D Projects: GA AV ČR IAA3012806 Institutional research plan: CEZ:AV0Z3012916 Keywords : geomagnetic forcing * climatic variability * global warming Subject RIV: DE - Earth Magnetism, Geodesy, Geography

  20. How Useful Are Climate Projections for Adaptation Decision Making?

    Science.gov (United States)

    Smith, J. B.; Vogel, J. M.

    2011-12-01

    Decision making is often portrayed as a linear process that assumes scientific knowledge is a necessary precursor to effective policy and is used directly in policy making. Yet, in practice, the use of scientific information in decision making is more complex than the linear model implies. The use of climate projections in adaptation decision making is a case in point. This paper briefly reviews efforts by some decision makers to understand climate change risks and to apply this knowledge when making decisions on management of climate sensitive resources and infrastructure . In general, and in spite of extensive efforts to study climate change at the regional and local scale to support decision making, few decisions outside of adapting to sea level rise appear to directly apply to climate change projections. A number of U.S. municipalities and states, including Seattle, New York City, Phoenix, and the States of California and Washington, have used climate change projections to assess their vulnerability to various climate change impacts. Some adaptation decisions have been made based on projections of sea level rise, such as change in location of infrastructure. This may be because a future rise is sea level is virtually certain. In contrast, decision making on precipitation has been more limited, even where there is consensus on likely changes in sign of the variable. Nonetheless, decision makers are adopting strategies that can be justified based on current climate and climate variability and that also reduce risks to climate change. A key question for the scientific community is whether improved projections will add value to decision making. For example, it remains unclear how higher-resolution projections can change decision making as long as the sign and magnitude of projections across climate models and downscaling techniques retains a wide range of uncertainty. It is also unclear whether even better information on the sign and magnitude of change would

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

    Science.gov (United States)

    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

  2. Projection of future climate changes

    International Nuclear Information System (INIS)

    Boucher, Olivier; Dufresne, Jean-Louis; Vial, Jessica; Brun, Eric; Cattiaux, Julien; Chauvin, Fabrice; Salas y Melia, David; Voldoire, Aurore; Bopp, Laurent; Braconnot, Pascale; Ciais, Philippe; Yiou, Pascal; Guilyardi, Eric; Mignot, Juliette; Guivarch, Celine

    2015-01-01

    Climate models provide the opportunity to anticipate how the climate system may change due to anthropogenic activities during the 21. century. Studies are based on numerical simulations that explore the evolution of the mean climate and its variability according to different socio-economic scenarios. We present a selection of results from phase 5 of the Climate model intercomparison project (CMIP5) with an illustrative focus on the two French models that participated to this exercise. We describe the effects of human perturbations upon surface temperature, precipitation, the cryo-sphere, but also extreme weather events and the carbon cycle. Results show a number of robust features, on the amplitude and geographical patterns of the expected changes and on the processes at play in these changes. They also show the limitations of such a prospective exercise and persistent uncertainties on some key aspects. (authors)

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

    Science.gov (United States)

    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.

  4. Spatiotemporal modes of climatic variability: building blocks of complex networks?

    Czech Academy of Sciences Publication Activity Database

    Vejmelka, Martin; Hlinka, Jaroslav; Hartman, David; Paluš, Milan

    2012-01-01

    Roč. 14, - (2012), s. 14275 ISSN 1607-7962. [European Geosciences Union General Assembly 2012. 22.04.2012-27.04.2012, Vienna] R&D Projects: GA ČR GCP103/11/J068 Institutional support: RVO:67985807 Keywords : climate variability * dimensionality reduction * principal component analysis * surrogate data * climate network Subject RIV: BB - Applied Statistics, Operational Research

  5. Climate projections FAQ

    Science.gov (United States)

    A.E. Daniels; J.F. Morrison; L.A. Joyce; N.L. Crookston; S.C. Chen; S.G. McNulty

    2012-01-01

    Climate scenarios offer one way to identify and examine the land management challenges posed by climate change. Selecting projections, however, requires careful consideration of the natural resources under study, and where and how they are sensitive to climate. Selection also depends on the robustness of different projections for the resources and geographic area of...

  6. Nature and dynamics of climate variability in the uganda cattle corridor

    African Journals Online (AJOL)

    Meteology Department

    2013-08-12

    Aug 12, 2013 ... 1Department of Geography, Geo-Informatics and Climatic Sciences, Makerere University, Uganda. 2Africa Innovations Institute, Kampala, Uganda. 3Department of Biology, Gulu ..... research activities under the project “Adaptation to the. Impact of Climate Variability on Food and Health Security in the Cattle ...

  7. Projection of climatic suitability for Aedes albopictus Skuse (Culicidae) in Europe under climate change conditions

    Science.gov (United States)

    Fischer, Dominik; Thomas, Stephanie Margarete; Niemitz, Franziska; Reineking, Björn; Beierkuhnlein, Carl

    2011-07-01

    During the last decades the disease vector Aedes albopictus ( Ae. albopictus) has rapidly spread around the globe. The spread of this species raises serious public health concerns. Here, we model the present distribution and the future climatic suitability of Europe for this vector in the face of climate change. In order to achieve the most realistic current prediction and future projection, we compare the performance of four different modelling approaches, differentiated by the selection of climate variables (based on expert knowledge vs. statistical criteria) and by the geographical range of presence records (native range vs. global range). First, models of the native and global range were built with MaxEnt and were either based on (1) statistically selected climatic input variables or (2) input variables selected with expert knowledge from the literature. Native models show high model performance (AUC: 0.91-0.94) for the native range, but do not predict the European distribution well (AUC: 0.70-0.72). Models based on the global distribution of the species, however, were able to identify all regions where Ae. albopictus is currently established, including Europe (AUC: 0.89-0.91). In a second step, the modelled bioclimatic envelope of the global range was projected to future climatic conditions in Europe using two emission scenarios implemented in the regional climate model COSMO-CLM for three time periods 2011-2040, 2041-2070, and 2071-2100. For both global-driven models, the results indicate that climatically suitable areas for the establishment of Ae. albopictus will increase in western and central Europe already in 2011-2040 and with a temporal delay in eastern Europe. On the other hand, a decline in climatically suitable areas in southern Europe is pronounced in the Expert knowledge based model. Our projections appear unaffected by non-analogue climate, as this is not detected by Multivariate Environmental Similarity Surface analysis. The generated risk maps

  8. Rates of change in climatic niches in plant and animal populations are much slower than projected climate change

    Science.gov (United States)

    Jezkova, Tereza

    2016-01-01

    Climate change may soon threaten much of global biodiversity. A critical question is: can species undergo niche shifts of sufficient speed and magnitude to persist within their current geographic ranges? Here, we analyse niche shifts among populations within 56 plant and animal species using time-calibrated trees from phylogeographic studies. Across 266 phylogeographic groups analysed, rates of niche change were much slower than rates of projected climate change (mean difference > 200 000-fold for temperature variables). Furthermore, the absolute niche divergence among populations was typically lower than the magnitude of projected climate change over the next approximately 55 years for relevant variables, suggesting the amount of change needed to persist may often be too great, even if these niche shifts were instantaneous. Rates were broadly similar between plants and animals, but especially rapid in some arthropods, birds and mammals. Rates for temperature variables were lower at lower latitudes, further suggesting that tropical species may be especially vulnerable to climate change. PMID:27881748

  9. Multi-scale climate modelling over Southern Africa using a variable-resolution global model

    CSIR Research Space (South Africa)

    Engelbrecht, FA

    2011-12-01

    Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

  10. Future projection of mean and variability of the Asian Summer Monsoon and Indian Ocean Climate systems

    Energy Technology Data Exchange (ETDEWEB)

    Annamalai, H. [Univ. of Hawaii, Honolulu, HI (United States)

    2014-09-15

    The overall goal of this project is to assess the ability of the CMIP3/5 models to simulate the Indian-Ocean monsoon systems. The PI along with post-docs investigated research issues ranging from synoptic systems to long-term trends over the Asian monsoon region. The PI applied diagnostic tools such as moist static energy (MSE) to isolate: the moist and radiative processes responsible for extended monsoon breaks over South Asia, precursors in the ENSO-monsoon association, reasons for the drying tendency over South Asia and the possible effect on tropical Indian Ocean climate anomalies influencing certain aspects of ENSO characteristics. By diagnosing various observations and coupled model simulations, we developed working hypothesis and tested them by carrying out sensitivity experiments with both linear and nonlinear models. Possible physical and dynamical reasons for model sensitivities were deduced. On the teleconnection front, the ability of CMIP5 models in representing the monsoon-desert mechanism was examined recently. Further more, we have applied a suite of diagnostics and have performed an in depth analysis on CMIP5 integrations to isolate the possible reasons for the ENSO-monsoon linkage or lack thereof. The PI has collaborated with Dr. K.R. Sperber of PCMDI and other CLIVAR Asian-Australian monsoon panel members in understanding the ability of CMIP3/5 models in capturing monsoon and its spectrum of variability. The objective and process-based diagnostics aided in selecting models that best represent the present-day monsoon and its variability that are then employed for future projections. Two major highlights were an invitation to write a review on present understanding monsoons in a changing climate in Nature Climate Change, and identification of an east-west shift in observed monsoon rainfall (more rainfall over tropical western Pacific and drying tendency over South Asia) in the last six decades and attributing that shift to SST rise over the tropical

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  15. Climate projections in the Hornsund area, Southern Spitsbergen

    Directory of Open Access Journals (Sweden)

    Osuch Marzena

    2016-09-01

    Full Text Available The aim of this study was to provide an estimation of climate variability in the Hornsund area in Southern Spitsbergen in the period 1976-2100. The climatic variables were obtained from the Polar-CORDEX initiative in the form of time series of daily air temperature and precipitation derived from four global circulation models (GCMs following representative concentration pathways (RCP RCP 4.5 and RCP 8.5 emission scenarios. In the first stage of the analysis, simulations for the reference period from 1979 to 2005 were compared with observations at the Polish Polar Station Hornsund from the same period of time. In the second step, climatic projections were derived and monthly and annual means/sums were analysed as climatic indices. Following the standard methods of trend analysis, the changes of these indices over three time periods - the reference period 1976-2005, the near-future period 2021-2050, and far-future period 2071-2100 - were examined. The projections of air temperature were consistent. All analysed climate models simulated an increase of air temperature with time. Analyses of changes at a monthly scale indicated that the largest increases were estimated for winter months (more than 11°C for the far future using the RCP 8.5 scenario. The analyses of monthly and annual sums of precipitation also indicated increasing tendencies for changes with time, with the differences between mean monthly sums of precipitation for the near future and the reference period similar for each months. In the case of changes between far future and reference periods, the highest increases were projected for the winter months.

  16. Comparing climate projections to observations up to 2011

    International Nuclear Information System (INIS)

    Rahmstorf, Stefan; Foster, Grant; Cazenave, Anny

    2012-01-01

    We analyse global temperature and sea-level data for the past few decades and compare them to projections published in the third and fourth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). The results show that global temperature continues to increase in good agreement with the best estimates of the IPCC, especially if we account for the effects of short-term variability due to the El Niño/Southern Oscillation, volcanic activity and solar variability. The rate of sea-level rise of the past few decades, on the other hand, is greater than projected by the IPCC models. This suggests that IPCC sea-level projections for the future may also be biased low. (letter)

  17. Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

    Science.gov (United States)

    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

  18. Projecting climate effects on birds and reptiles of the Southwestern United States

    Science.gov (United States)

    van Riper, Charles; Hatten, James R.; Giermakowski, J. Tomasz; Mattson, David; Holmes, Jennifer A.; Johnson, Matthew J.; Nowak, Erika M.; Ironside, Kirsten; Peters, Michael; Heinrich, Paul; Cole, K.L.; Truettner, C.; Schwalbe, Cecil R.

    2014-01-01

    We modeled the current and future breeding ranges of seven bird and five reptile species in the Southwestern United States with sets of landscape, biotic (plant), and climatic global circulation model (GCM) variables. For modeling purposes, we used PRISM data to characterize the climate of the Western United States between 1980 and 2009 (baseline for birds) and between 1940 and 2009 (baseline for reptiles). In contrast, we used a pre-selected set of GCMs that are known to be good predictors of southwestern climate (five individual and one ensemble GCM), for the A1B emission scenario, to characterize future climatic conditions in three time periods (2010–39; 2040–69; and, 2070–99). Our modeling approach relied on conceptual models for each target species to inform selection of candidate explanatory variables and to interpret the ecological meaning of developed probabilistic distribution models. We employed logistic regression and maximum entropy modeling techniques to create a set of probabilistic models for each target species. We considered climatic, landscape, and plant variables when developing and testing our probabilistic models. Climatic variables included the maximum and minimum mean monthly and seasonal temperature and precipitation for three time periods. Landscape features included terrain ruggedness and insolation. We also considered plant species distributions as candidate explanatory variables where prior ecological knowledge implicated a strong association between a plant and animal species. Projected changes in range varied widely among species, from major losses to major gains. Breeding bird ranges exhibited greater expansions and contractions than did reptile species. We project range losses for Williamson’s sapsucker and pygmy nuthatch of a magnitude that could move these two species close to extinction within the next century. Although both species currently have a relatively limited distribution, they can be locally common, and neither

  19. Analyses of historical and projected climates to support climate adaptation in the northern Rocky Mountains: Chapter 4

    Science.gov (United States)

    Gross, John E.; Tercek, Michael; Guay, Kevin; Chang, Tony; Talbert, Marian; Rodman, Ann; Thoma, David; Jantz, Patrick; Morisette, Jeffrey T.

    2016-01-01

    Most of the western United States is experiencing the effects of rapid and directional climate change (Garfin et al. 2013). These effects, along with forecasts of profound changes in the future, provide strong motivation for resource managers to learn about and prepare for future changes. Climate adaptation plans are based on an understanding of historic climate variation and their effects on ecosystems and on forecasts of future climate trends. Frameworks for climate adaptation thus universally identify the importance of a summary of historical, current, and projected climates (Glick, Stein, and Edelson 2011; Cross et al. 2013; Stein et al. 2014). Trends in physical climate variables are usually the basis for evaluating the exposure component in vulnerability assessments. Thus, this chapter focuses on step 2 of the Climate-Smart Conservation framework (chap. 2): vulnerability assessment. We present analyses of historical and current observations of temperature, precipitation, and other key climate measurements to provide context and a baseline for interpreting the ecological impacts of projected climate changes.

  20. A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, Alexey V. [Yale Univ., New Haven, CT (United States)

    2015-01-14

    The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth system models, to the stability and variability of the AMOC in past climates.

  1. Solar Variability and Planetary Climates

    CERN Document Server

    Calisesi, Y; Gray, L; Langen, J; Lockwood, M

    2007-01-01

    Variations in solar activity, as revealed by variations in the number of sunspots, have been observed since ancient times. To what extent changes in the solar output may affect planetary climates, though, remains today more than ever a subject of controversy. In 2000, the SSSI volume on Solar Variability and Climate reviewed the to-date understanding of the physics of solar variability and of the associated climate response. The present volume on Solar Variability and Planetary Climates provides an overview of recent advances in this field, with particular focus at the Earth's middle and lower atmosphere. The book structure mirrors that of the ISSI workshop held in Bern in June 2005, the collection of invited workshop contributions and of complementary introductory papers synthesizing the current understanding in key research areas such as middle atmospheric processes, stratosphere-troposphere dynamical coupling, tropospheric aerosols chemistry, solar storm influences, solar variability physics, and terrestri...

  2. Climate variability of heat wave and projection of warming scenario in Taiwan

    Science.gov (United States)

    Lin, C. Y.; Chien, Y. Y.; Su, C. J.

    2017-12-01

    This study examined the climate variability of heat wave (HW) according to air temperature and relative humidity to determine trends of variation and stress threshold in three major cities of Taiwan, Taipei (TP), Taichung (TC) and Kaohsiung (KH), during in the past four decades (1971-2010). According to data available, the wet-bulb globe temperature (WBGT) heat stress for the three studied cities was also calculated for the past (2003-2012) and simulated under the projected warming scenario for the end of this century (2075-2099) using ECHAM5/MPIOM-WRF (ECW) dynamic downscaling 5-km resolution Analysis showed that past decade (2001-2010) saw increase not only in number of HW days in all three cities but also the duration of each HW event in TP and KH. Simulation results revealed that ECW captures well the characteristics of data distribution in these three cities during 2003-2012. Under the A1B projection, ECW yielded higher WBGT in all three cities for 2075-2099. The WBGT in TP indicated that the heat stress for 50% of the days in July and August by 2075-2099 will be at danger level (WBGT ³ 31 °C). Even the median WBGT in TC and KH (30.91°C and 30.88°C, respectively), are close to 31°C. Hence, the heat stress in all three cities will either exceed or approach the danger level by the end of this century. Such projection under the global warming trend would necessitate adaptation and mitigation, and the huge impact of dangerous heat stress on public health merits urgent attention for Taiwan.

  3. An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change.

    Directory of Open Access Journals (Sweden)

    Nicolas Casajus

    Full Text Available An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.

  4. An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change.

    Science.gov (United States)

    Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique

    2016-01-01

    An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.

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

    Science.gov (United States)

    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.

  6. Impacts of Climate Trends and Variability on Livestock Production in Brazil

    Science.gov (United States)

    Cohn, A.; Munger, J.; Gibbs, H.

    2015-12-01

    Cattle systems of Brazil are of major economic and environmental importance. They occupy ¼ of the land surface of the country, account for over 15 billion USD of annual revenue through the sale of beef, leather, and milk, are closely associated with deforestation, and have been projected to substantially grow in the coming decades. Sustainable intensification of production in the sector could help to limit environmental harm from increased production, but productivity growth could be inhibited by climate change. Gauging the potential future impacts of climate change on the Brazilian livestock sector can be aided by examining past evidence of the link between climate and cattle production and productivity. We use statistical techniques to investigate the contribution of climate variability and climate change to variability in cattle system output in Brazil's municipalities over the period 1974 to 2013. We find significant impacts of both temperature and precipitation variability and temperature trends on municipality-level exports and the production of both milk and beef. Pasture productivity, represented by a vegetation index, also varies significantly with climate shocks. In some regions, losses from exposure to climate trends were of comparable magnitude to technology and/or market-driven productivity gains over the study period.

  7. "Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

    Science.gov (United States)

    Taylor, Patrick C.; Baker, Noel C.

    2015-01-01

    Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

  8. Ecological and evolutionary impacts of changing climatic variability.

    Science.gov (United States)

    Vázquez, Diego P; Gianoli, Ernesto; Morris, William F; Bozinovic, Francisco

    2017-02-01

    While average temperature is likely to increase in most locations on Earth, many places will simultaneously experience higher variability in temperature, precipitation, and other climate variables. Although ecologists and evolutionary biologists widely recognize the potential impacts of changes in average climatic conditions, relatively little attention has been paid to the potential impacts of changes in climatic variability and extremes. We review the evidence on the impacts of increased climatic variability and extremes on physiological, ecological and evolutionary processes at multiple levels of biological organization, from individuals to populations and communities. Our review indicates that climatic variability can have profound influences on biological processes at multiple scales of organization. Responses to increased climatic variability and extremes are likely to be complex and cannot always be generalized, although our conceptual and methodological toolboxes allow us to make informed predictions about the likely consequences of such climatic changes. We conclude that climatic variability represents an important component of climate that deserves further attention. © 2015 Cambridge Philosophical Society.

  9. The value of seasonal forecasting and crop mix adaptation to climate variability for agriculture under climate change

    Science.gov (United States)

    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.

  10. Probabilistic projections of 21st century climate change over Northern Eurasia

    Science.gov (United States)

    Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang

    2013-12-01

    We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.

  11. Probabilistic projections of 21st century climate change over Northern Eurasia

    International Nuclear Information System (INIS)

    Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang

    2013-01-01

    We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia. (letter)

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

    Science.gov (United States)

    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.

  13. Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

    Science.gov (United States)

    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

  14. Improving Climate Projections Using "Intelligent" Ensembles

    Science.gov (United States)

    Baker, Noel C.; Taylor, Patrick C.

    2015-01-01

    Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and

  15. Responses of runoff to historical and future climate variability over China

    Science.gov (United States)

    Wu, Chuanhao; Hu, Bill X.; Huang, Guoru; Wang, Peng; Xu, Kai

    2018-03-01

    China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal-spatial patterns of water resources. Based on the long-term (1960-2008) water budget data and climate projections from 28 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.1 to 3.2) and potential evaporation (PET) elasticity (from -2.2 to -0.1) across China. The P elasticity is larger in north-eastern and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties' elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960-2008, the climate contribution to R ranges from -2.4 to 3.6 % yr-1 across China, with the negative contribution in north-eastern China and the positive contribution in western China and some parts of the south-west. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071-2100, the mean annual P is projected to increase in most parts of China, especially the western regions, while the mean annual PET is projected to increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China are projected to become wetter and drier in the period 2071-2100, respectively (relative to the baseline 1971-2000).

  16. Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

    Science.gov (United States)

    Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

    2016-04-01

    The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample

  17. Uncertainties in projecting climate-change impacts in marine ecosystems

    DEFF Research Database (Denmark)

    Payne, Mark; Barange, Manuel; Cheung, William W. L.

    2016-01-01

    with a projection and building confidence in its robustness. We review how uncertainties in such projections are handled in marine science. We employ an approach developed in climate modelling by breaking uncertainty down into (i) structural (model) uncertainty, (ii) initialization and internal variability......Projections of the impacts of climate change on marine ecosystems are a key prerequisite for the planning of adaptation strategies, yet they are inevitably associated with uncertainty. Identifying, quantifying, and communicating this uncertainty is key to both evaluating the risk associated...... and highlight the opportunities and challenges associated with doing a better job. We find that even within a relatively small field such as marine science, there are substantial differences between subdisciplines in the degree of attention given to each type of uncertainty. We find that initialization...

  18. Multi-GCM projections of future drought and climate variability indicators for the Mediterranean region

    Czech Academy of Sciences Publication Activity Database

    Dubrovský, Martin; Hayes, M.; Duce, P.; Trnka, Miroslav; Svoboda, M.; Zara, P.

    2014-01-01

    Roč. 14, č. 5 (2014), s. 1907-1919 ISSN 1436-3798 R&D Projects: GA MŠk(CZ) EE2.3.20.0248; GA MŠk(CZ) EE2.4.31.0056 Institutional support: RVO:67179843 Keywords : climate change * mediteranean * global climate models * temperature * precipitation * drought * palmer drought severity index * weather generator Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.628, year: 2014

  19. A method to encapsulate model structural uncertainty in ensemble projections of future climate: EPIC v1.0

    Science.gov (United States)

    Lewis, Jared; Bodeker, Greg E.; Kremser, Stefanie; Tait, Andrew

    2017-12-01

    A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X) into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC) method. Each ensemble member is constructed by adding contributions from (1) a climatology derived from observations that represents the time-invariant part of the signal; (2) a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal); and (3) a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability) and Tglobal are obtained in a training phase. Then, in an implementation phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs) and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in the training phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs) are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of magnitude more

  20. Deducing Climatic Elasticity to Assess Projected Climate Change Impacts on Streamflow Change across China

    Science.gov (United States)

    Liu, Jianyu; Zhang, Qiang; Zhang, Yongqiang; Chen, Xi; Li, Jianfeng; Aryal, Santosh K.

    2017-10-01

    Climatic elasticity has been widely applied to assess streamflow responses to climate changes. To fully assess impacts of climate under global warming on streamflow and reduce the error and uncertainty from various control variables, we develop a four-parameter (precipitation, catchment characteristics n, and maximum and minimum temperatures) climatic elasticity method named PnT, based on the widely used Budyko framework and simplified Makkink equation. We use this method to carry out the first comprehensive evaluation of the streamflow response to potential climate change for 372 widely spread catchments in China. The PnT climatic elasticity was first evaluated for a period 1980-2000, and then used to evaluate streamflow change response to climate change based on 12 global climate models under Representative Concentration Pathway 2.6 (RCP2.6) and RCP 8.5 emission scenarios. The results show that (1) the PnT climatic elasticity method is reliable; (2) projected increasing streamflow takes place in more than 60% of the selected catchments, with mean increments of 9% and 15.4% under RCP2.6 and RCP8.5 respectively; and (3) uncertainties in the projected streamflow are considerable in several regions, such as the Pearl River and Yellow River, with more than 40% of the selected catchments showing inconsistent change directions. Our results can help Chinese policy makers to manage and plan water resources more effectively, and the PnT climatic elasticity should be applied to other parts of the world.

  1. Climate project screening tool: an aid for climate change adaptation

    Science.gov (United States)

    Toni Lyn Morelli; Sharon Yeh; Nikola M. Smith; Mary Beth Hennessy; Constance I. Millar

    2012-01-01

    To address the impacts of climate change, land managers need techniques for incorporating adaptation into ongoing or impending projects. We present a new tool, the Climate Project Screening Tool (CPST), for integrating climate change considerations into project planning as well as for developing concrete adaptation options for land managers. We designed CPST as part of...

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  4. Precipitation variability increases in a warmer climate.

    Science.gov (United States)

    Pendergrass, Angeline G; Knutti, Reto; Lehner, Flavio; Deser, Clara; Sanderson, Benjamin M

    2017-12-21

    Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle's response to warming and its impacts. While changes in mean and extreme precipitation have been studied intensively, precipitation variability has received less attention, despite its theoretical and practical importance. Here, we show that precipitation variability in most climate models increases over a majority of global land area in response to warming (66% of land has a robust increase in variability of seasonal-mean precipitation). Comparing recent decades to RCP8.5 projections for the end of the 21 st century, we find that in the global, multi-model mean, precipitation variability increases 3-4% K -1 globally, 4-5% K -1 over land and 2-4% K -1 over ocean, and is remarkably robust on a range of timescales from daily to decadal. Precipitation variability increases by at least as much as mean precipitation and less than moisture and extreme precipitation for most models, regions, and timescales. We interpret this as being related to an increase in moisture which is partially mitigated by weakening circulation. We show that changes in observed daily variability in station data are consistent with increased variability.

  5. Statistical variability of hydro-meteorological variables as indicators ...

    African Journals Online (AJOL)

    Statistical variability of hydro-meteorological variables as indicators of climate change in north-east Sokoto-Rima basin, Nigeria. ... water resources development including water supply project, agriculture and tourism in the study area. Key word: Climate change, Climatic variability, Actual evapotranspiration, Global warming ...

  6. Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin

    Science.gov (United States)

    Ahmadalipour, Ali; Moradkhani, Hamid; Rana, Arun

    2018-01-01

    Climate change is expected to have severe impacts on natural systems as well as various socio-economic aspects of human life. This has urged scientific communities to improve the understanding of future climate and reduce the uncertainties associated with projections. In the present study, ten statistically downscaled CMIP5 GCMs at 1/16th deg. spatial resolution from two different downscaling procedures are utilized over the Columbia River Basin (CRB) to assess the changes in climate variables and characterize the associated uncertainties. Three climate variables, i.e. precipitation, maximum temperature, and minimum temperature, are studied for the historical period of 1970-2000 as well as future period of 2010-2099, simulated with representative concentration pathways of RCP4.5 and RCP8.5. Bayesian Model Averaging (BMA) is employed to reduce the model uncertainty and develop a probabilistic projection for each variable in each scenario. Historical comparison of long-term attributes of GCMs and observation suggests a more accurate representation for BMA than individual models. Furthermore, BMA projections are used to investigate future seasonal to annual changes of climate variables. Projections indicate significant increase in annual precipitation and temperature, with varied degree of change across different sub-basins of CRB. We then characterized uncertainty of future projections for each season over CRB. Results reveal that model uncertainty is the main source of uncertainty, among others. However, downscaling uncertainty considerably contributes to the total uncertainty of future projections, especially in summer. On the contrary, downscaling uncertainty appears to be higher than scenario uncertainty for precipitation.

  7. Modelling climate impact on floods under future emission scenarios using an ensemble of climate model projections

    Science.gov (United States)

    Wetterhall, F.; Cloke, H. L.; He, Y.; Freer, J.; Pappenberger, F.

    2012-04-01

    Evidence provided by modelled assessments of climate change impact on flooding is fundamental to water resource and flood risk decision making. Impact models usually rely on climate projections from Global and Regional Climate Models, and there is no doubt that these provide a useful assessment of future climate change. However, cascading ensembles of climate projections into impact models is not straightforward because of problems of coarse resolution in Global and Regional Climate Models (GCM/RCM) and the deficiencies in modelling high-intensity precipitation events. Thus decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs, such as selection of downscaling methods and application of Model Output Statistics (MOS). In this paper a grand ensemble of projections from several GCM/RCM are used to drive a hydrological model and analyse the resulting future flood projections for the Upper Severn, UK. The impact and implications of applying MOS techniques to precipitation as well as hydrological model parameter uncertainty is taken into account. The resultant grand ensemble of future river discharge projections from the RCM/GCM-hydrological model chain is evaluated against a response surface technique combined with a perturbed physics experiment creating a probabilisic ensemble climate model outputs. The ensemble distribution of results show that future risk of flooding in the Upper Severn increases compared to present conditions, however, the study highlights that the uncertainties are large and that strong assumptions were made in using Model Output Statistics to produce the estimates of future discharge. The importance of analysing on a seasonal basis rather than just annual is highlighted. The inability of the RCMs (and GCMs) to produce realistic precipitation patterns, even in present conditions, is a major caveat of local climate impact studies on flooding, and this should be a focus for future development.

  8. Mediterranean climate modelling: variability and climate change scenarios

    International Nuclear Information System (INIS)

    Somot, S.

    2005-12-01

    Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)

  9. Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate

    Energy Technology Data Exchange (ETDEWEB)

    Di Lorenzo, Emanuele [Georgia Inst. of Technology, Atlanta, GA (United States)

    2015-02-27

    This research aimed at understanding the dynamics controlling decadal variability in the Pacific Ocean and its interactions with global-scale climate change. The first goal was to assess how the dynamics and statistics of the El Niño Southern Oscillation and the modes of Pacific decadal variability are represented in global climate models used in the IPCC. The second goal was to quantify how decadal dynamics are projected to change under continued greenhouse forcing, and determine their significance in the context of paleo-proxy reconstruction of long-term climate.

  10. Implementing Climate Services in Peru: CLIMANDES Project

    Science.gov (United States)

    Lavado-Casimiro, Waldo; Mauchle, Fabian; Diaz, Amelia; Seiz, Gabriela; Rubli, Alex; Rossa, Andrea; Rosas, Gabriela; Ita, Niceforo; Calle, Victoria; Villegas, Esequiel; Ambrosetti, Paolo; Brönnimann, Stefan; Hunziker, Stefan; Jacques, Martin; Croci-Maspoli, Mischa; Konzelmann, Thomas; Gubler, Stefanie; Rohrer, Mario

    2014-05-01

    The climate variability and change will have increasing influence on the economic and social development of all countries and regions, such as the Andes in Latin America. The CLIMANDES project (Climate services to support decision-making in the Andean Region) will address these issues in Peru. CLIMANDES supports the WMO Regional Training Centre (RTC) in Lima, which is responsible for the training of specialized human resources in meteorology and climatology in the South American Andes (Module 1). Furthermore, CLIMANDES will provide high-quality climate services to inform policy makers in the Andean region (Module 2). It is coordinated by the World Meteorological Organization (WMO) and constitutes a pilot project under the umbrella of the WMO-led Global Framework for Climate Services (GFCS). The project is funded by the Swiss Agency for Development and Cooperation (SDC) and runs from August 2012 - July 2015. Module 1 focuses on restructuring the curricula of Meteorology at the La Molina Agraria University (UNALM) and applied training of meteorologists of the Peruvian National Service of Meteorology and Hydrology (SENAMHI). In Module 2, the skills will be shared and developed in the production and delivery of high-quality climate products and services tailored to the needs of the decision makers in the pilot regions Cusco and Junín. Such services will benefit numerous sectors including agriculture, education, health, tourism, energy, transport and others. The goals of the modules 1 and 2 will be achieved through the collaboration of the UNALM, SENAMHI and the Federal Office of Meteorology and Climatology MeteoSwiss, with the support of the University of Bern (UNIBE), Meteodat and WMO.

  11. Multi-GCM projections of future drought and climate variability indicators for the Mediterranean region

    Czech Academy of Sciences Publication Activity Database

    Dubrovský, Martin; Hayes, M.; Duce, P.; Trnka, M.; Svoboda, M.; Zara, P.

    2014-01-01

    Roč. 14, č. 5 (2014), s. 1907-1919 ISSN 1436-3798 R&D Projects: GA AV ČR IAA300420806; GA MŠk LD12029 Institutional support: RVO:68378289 Keywords : mediterranean * climate change * global climate models * temperature * precipitation * drought * Palmer drought severity index * weather generator Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.628, year: 2014 http://link.springer.com/article/10.1007%2Fs10113-013-0562-z/fulltext.html

  12. Choice of baseline climate data impacts projected species' responses to climate change.

    Science.gov (United States)

    Baker, David J; Hartley, Andrew J; Butchart, Stuart H M; Willis, Stephen G

    2016-07-01

    Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species-climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040-2069, 2070-2099), using downscaled climate projections, and calculated species turnover and changes in species-specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species-specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site-level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses. © 2016 John Wiley

  13. Assessing the role of internal climate variability in Antarctica's contribution to future sea-level rise

    Science.gov (United States)

    Tsai, C. Y.; Forest, C. E.; Pollard, D.

    2017-12-01

    The Antarctic ice sheet (AIS) has the potential to be a major contributor to future sea-level rise (SLR). Current projections of SLR due to AIS mass loss remain highly uncertain. Better understanding of how ice sheets respond to future climate forcing and variability is essential for assessing the long-term risk of SLR. However, the predictability of future climate is limited by uncertainties from emission scenarios, model structural differences, and the internal variability that is inherently generated within the fully coupled climate system. Among those uncertainties, the impact of internal variability on the AIS changes has not been explicitly assessed. In this study, we quantify the effect of internal variability on the AIS evolutions by using climate fields from two large-ensemble experiments using the Community Earth System Model to force a three-dimensional ice sheet model. We find that internal variability of climate fields, particularly atmospheric fields, among ensemble members leads to significantly different AIS responses. Our results show that the internal variability can cause about 80 mm differences of AIS contribution to SLR by 2100 compared to the ensemble-mean contribution of 380-450 mm. Moreover, using ensemble-mean climate fields as the forcing in the ice sheet model does not produce realistic simulations of the ice loss. Instead, it significantly delays the onset of retreat of the West Antarctic Ice Sheet for up to 20 years and significantly underestimates the AIS contribution to SLR by 0.07-0.11 m in 2100 and up to 0.34 m in the 2250's. Therefore, because the uncertainty caused by internal variability is irreducible, we seek to highlight a critical need to assess the role of internal variability in projecting the AIS loss over the next few centuries. By quantifying the impact of internal variability on AIS contribution to SLR, policy makers can obtain more robust estimates of SLR and implement suitable adaptation strategies.

  14. Impacts of Climate Variability and Change on Banana Yields in the ...

    African Journals Online (AJOL)

    Climate variability and change are existing sets of conditions which affect crop productivity. An evaluation of their impacts on banana yield in the CDC-DelMonte Banana Project at Tiko is fundamental in conceiving adaptation strategies towards coping with, and minimizing their deleterious impacts for maximum productivity ...

  15. Regional assessment of Climate change impacts in the Mediterranean: the CIRCE project

    Science.gov (United States)

    Iglesias, A.

    2011-12-01

    The CIRCE project has developed for the first time an assessment of the climate change impacts in the Mediterranean area. The objectives of the project are: to predict and to quantify physical impacts of climate change in the Mediterranean area; to evaluate the consequences of climate change for the society and the economy of the populations located in the Mediterranean area; to develop an integrated approach to understand combined effects of climate change; and to identify adaptation and mitigation strategies in collaboration with regional stakeholders. The CIRCE Project, coordinated by the Instituto Nazionale di Geofisca e Vulcanologia, started on 1st April 2007 and ended in a policy conference in Rome on June 2011. CIRCE involves 64 partners from Europe, Middle East and North Africa working together to evaluate the best strategies of adaptation to the climate change in the Mediterranean basin. CIRCE wants to understand and to explain how climate will change in the Mediterranean area bringing together the natural sciences community and social community in a new integrated and comprehensive way. The project has investigated how global and Mediterranean climates interact, how the radiative properties of the atmosphere and the radiative fluxes vary, the interaction between cloudiness and aerosol, the modifications in the water cycle. Recent observed modifications in the climate variables and detected trends will be compared. The economic and social consequences of climate change are evaluated by analysing direct impacts on migration, tourism and energy markets together with indirect impacts on the economic system. CIRCE has produced results about the consequences on agriculture, forests and ecosystems, human health and air quality. The variability of extreme events in the future scenario and their impacts is also assessed. A rigorous common framework, including a set of quantitative indicators developed specifically for the Mediterranean environment was be developed

  16. NUTRItion and CLIMate (NUTRICLIM): investigating the relationship between climate variables and childhood malnutrition through agriculture, an exploratory study in Burkina Faso.

    Science.gov (United States)

    Sorgho, Raissa; Franke, Jonas; Simboro, Seraphin; Phalkey, Revati; Saeurborn, Rainer

    Malnutrition remains a leading cause of death in children in low- and middle-income countries; this will be aggravated by climate change. Annually, 6.9 million deaths of children under 5 were attributable directly or indirectly to malnutrition. Although these figures have recently decreased, evidence shows that a world with a medium climate (local warming up to 3-4 °C) will create an additional 25.2 million malnourished children. This proof of concept study explores the relationships between childhood malnutrition (more specifically stunting), regional agricultural yields, and climate variables through the use of remote sensing (RS) satellite imaging along with algorithms to predict the effect of climate variability on agricultural yields and on malnutrition of children under 5. The success of this proof of purpose study, NUTRItion and CLIMate (NUTRICLIM), should encourage researchers to apply both concept and tools to study of the link between weather variability, crop yield, and malnutrition on a larger scale. It would also allow for linking such micro-level data to climate models and address the challenge of projecting the additional impact of childhood malnutrition from climate change to various policy relevant time horizons.

  17. Sound transit climate risk reduction project.

    Science.gov (United States)

    2013-09-01

    The Climate Risk Reduction Project assessed how climate change may affect Sound Transit commuter rail, light rail, and express bus : services. The project identified potential climate change impacts on agency operations, assets, and long-term plannin...

  18. Land use compounds habitat losses under projected climate change in a threatened California ecosystem.

    Directory of Open Access Journals (Sweden)

    Erin Coulter Riordan

    Full Text Available Given the rapidly growing human population in mediterranean-climate systems, land use may pose a more immediate threat to biodiversity than climate change this century, yet few studies address the relative future impacts of both drivers. We assess spatial and temporal patterns of projected 21(st century land use and climate change on California sage scrub (CSS, a plant association of considerable diversity and threatened status in the mediterranean-climate California Floristic Province. Using a species distribution modeling approach combined with spatially-explicit land use projections, we model habitat loss for 20 dominant shrub species under unlimited and no dispersal scenarios at two time intervals (early and late century in two ecoregions in California (Central Coast and South Coast. Overall, projected climate change impacts were highly variable across CSS species and heavily dependent on dispersal assumptions. Projected anthropogenic land use drove greater relative habitat losses compared to projected climate change in many species. This pattern was only significant under assumptions of unlimited dispersal, however, where considerable climate-driven habitat gains offset some concurrent climate-driven habitat losses. Additionally, some of the habitat gained with projected climate change overlapped with projected land use. Most species showed potential northern habitat expansion and southern habitat contraction due to projected climate change, resulting in sharply contrasting patterns of impact between Central and South Coast Ecoregions. In the Central Coast, dispersal could play an important role moderating losses from both climate change and land use. In contrast, high geographic overlap in habitat losses driven by projected climate change and projected land use in the South Coast underscores the potential for compounding negative impacts of both drivers. Limiting habitat conversion may be a broadly beneficial strategy under climate change

  19. A method to encapsulate model structural uncertainty in ensemble projections of future climate: EPIC v1.0

    Directory of Open Access Journals (Sweden)

    J. Lewis

    2017-12-01

    Full Text Available A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC method. Each ensemble member is constructed by adding contributions from (1 a climatology derived from observations that represents the time-invariant part of the signal; (2 a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal; and (3 a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability and Tglobal are obtained in a training phase. Then, in an implementation phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in the training phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of

  20. New Tree-Ring Evidence from the Pyrenees Reveals Western Mediterranean Climate Variability since Medieval Times

    Czech Academy of Sciences Publication Activity Database

    Büntgen, Ulf; Krusic, P. J.; Verstege, A.; Sanguesa-Barreda, G.; Wagner, S.; Camarero, J. J.; Ljungqvist, F. C.; Zorita, E.; Oppenheimer, C.; Konter, O.; Tegel, W.; Gärtner, H.; Cherubini, P.; Reinig, F.; Esper, J.

    2017-01-01

    Roč. 30, č. 14 (2017), s. 5295-5318 ISSN 0894-8755 R&D Projects: GA MŠk(CZ) LO1415 Institutional support: RVO:67179843 Keywords : Europe * Volcanoes * Climate variability * Interannual variability * Multidecadal variability * Trends Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 4.161, year: 2016

  1. Linking the uncertainty of low frequency variability in tropical forcing in regional climate change

    Energy Technology Data Exchange (ETDEWEB)

    Forest, Chris E. [Pennsylvania State Univ., University Park, PA (United States). Dept. of Meteorology; Barsugli, Joseph J. [Univ. of Colorado, Boulder, CO (United States). CIRES; Li, Wei [Pennsylvania State Univ., University Park, PA (United States). Dept. of Meteorology

    2015-02-20

    The project utilizes multiple atmospheric general circulation models (AGCMs) to examine the regional climate sensitivity to tropical sea surface temperature forcing through a series of ensemble experiments. The overall goal for this work is to use the global teleconnection operator (GTO) as a metric to assess the impact of model structural differences on the uncertainties in regional climate variability.

  2. Collaborative project. Ocean-atmosphere interaction from meso-to planetary-scale. Mechanisms, parameterization, and variability

    Energy Technology Data Exchange (ETDEWEB)

    Small, Richard [National Center for Atmospheric Research, Boulder, CO (United States); Bryan, Frank [National Center for Atmospheric Research, Boulder, CO (United States); Tribbia, Joseph [National Center for Atmospheric Research, Boulder, CO (United States); Park, Sungsu [National Center for Atmospheric Research, Boulder, CO (United States); Dennis, John [National Center for Atmospheric Research, Boulder, CO (United States); Saravanan, R. [National Center for Atmospheric Research, Boulder, CO (United States); Schneider, Niklas [National Center for Atmospheric Research, Boulder, CO (United States); Kwon, Young-Oh [National Center for Atmospheric Research, Boulder, CO (United States)

    2015-06-11

    This project aims to improve long term global climate simulations by resolving ocean mesoscale activity and the corresponding response in the atmosphere. The main computational objectives are; i) to perform and assess Community Earth System Model (CESM) simulations with the new Community Atmospheric Model (CAM) spectral element dynamical core; ii) use static mesh refinement to focus on oceanic fronts; iii) develop a new Earth System Modeling tool to investigate the atmospheric response to fronts by selectively filtering surface flux fields in the CESM coupler. The climate research objectives are 1) to improve the coupling of ocean fronts and the atmospheric boundary layer via investigations of dependency on model resolution and stability functions: 2) to understand and simulate the ensuing tropospheric response that has recently been documented in observations: and 3) to investigate the relationship of ocean frontal variability to low frequency climate variability and the accompanying storm tracks and extremes in high resolution simulations. This is a collaborative multi-institution project consisting of computational scientists, climate scientists and climate model developers. It specifically aims at DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

  3. Improving niche projections of plant species under climate change: Silene acaulis on the British Isles as a case study

    Science.gov (United States)

    Ferrarini, Alessandro; Alsafran, Mohammed H. S. A.; Dai, Junhu; Alatalo, Juha M.

    2018-04-01

    Empirical works to assist in choosing climatically relevant variables in the attempt to predict climate change impacts on plant species are limited. Further uncertainties arise in choice of an appropriate niche model. In this study we devised and tested a sharp methodological framework, based on stringent variable ranking and filtering and flexible model selection, to minimize uncertainty in both niche modelling and successive projection of plant species distributions. We used our approach to develop an accurate, parsimonious model of Silene acaulis (L.) presence/absence on the British Isles and to project its presence/absence under climate change. The approach suggests the importance of (a) defining a reduced set of climate variables, actually relevant to species presence/absence, from an extensive list of climate predictors, and (b) considering climate extremes instead of, or together with, climate averages in projections of plant species presence/absence under future climate scenarios. Our methodological approach reduced the number of relevant climate predictors by 95.23% (from 84 to only 4), while simultaneously achieving high cross-validated accuracy (97.84%) confirming enhanced model performance. Projections produced under different climate scenarios suggest that S. acaulis will likely face climate-driven fast decline in suitable areas on the British Isles, and that upward and northward shifts to occupy new climatically suitable areas are improbable in the future. Our results also imply that conservation measures for S. acaulis based upon assisted colonization are unlikely to succeed on the British Isles due to the absence of climatically suitable habitat, so different conservation actions (seed banks and/or botanical gardens) are needed.

  4. Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J. [Iowa State Univ., Ames, IA (United States)

    2017-12-28

    This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASM can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes

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

    Science.gov (United States)

    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

  6. Effects of climate variability on global scale flood risk

    Science.gov (United States)

    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

  7. The Geographic Climate Information System Project (GEOCLIMA): Overview and preliminary results

    Science.gov (United States)

    Feidas, H.; Zanis, P.; Melas, D.; Vaitis, M.; Anadranistakis, E.; Symeonidis, P.; Pantelopoulos, S.

    2012-04-01

    The project GEOCLIMA aims at developing an integrated Geographic Information System (GIS) allowing the user to manage, analyze and visualize the information which is directly or indirectly related to climate and its future projections in Greece. The main components of the project are: a) collection and homogenization of climate and environmental related information, b) estimation of future climate change based on existing regional climate model (RCM) simulations as well as a supplementary high resolution (10 km x 10 km) simulation over the period 1961-2100 using RegCM3, c) compilation of an integrated uniform geographic database, and d) mapping of climate data, creation of digital thematic maps, and development of the integrated web GIS application. This paper provides an overview of the ongoing research efforts and preliminary results of the project. First, the trends in the annual and seasonal time series of precipitation and air temperature observations for all available stations in Greece are assessed. Then the set-up of the high resolution RCM simulation (10 km x 10 km) is discussed with respect to the selected convective scheme. Finally, the relationship of climatic variables with geophysical features over Greece such as altitude, location, distance from the sea, slope, aspect, distance from climatic barriers, land cover etc) is investigated, to support climate mapping. The research has been co-financed by the European Union (European Regional Development Fund) and Greek national funds through the Operational Program "Competitiveness and Entrepreneurship" of the National Strategic Reference Framework (NSRF) - Research Funding Program COOPERATION 2009.

  8. Climate Change or Climate Variability? History, Science and Politics in the Mesoamerican Climate

    Directory of Open Access Journals (Sweden)

    Daniel Poleo

    2016-08-01

    Full Text Available Climate variations in Mesoamerica have influenced the development and decay of populations from the earliest human settlements. The present time is no exception; there is no evidence that global warming will impact rainfall in the region, but rather there are important studies showing a response of rainfall to climate variability in the American tropics. Since our tropical region is vulnerable to climate variability, public policies must be congruent to avoid the mistakes of previous generations and achieve, with the help of science, a real progress in the fight against global warming.

  9. Methods for assessment of climate variability and climate changes in different time-space scales

    International Nuclear Information System (INIS)

    Lobanov, V.; Lobanova, H.

    2004-01-01

    Main problem of hydrology and design support for water projects connects with modern climate change and its impact on hydrological characteristics as observed as well as designed. There are three main stages of this problem: - how to extract a climate variability and climate change from complex hydrological records; - how to assess the contribution of climate change and its significance for the point and area; - how to use the detected climate change for computation of design hydrological characteristics. Design hydrological characteristic is the main generalized information, which is used for water management and design support. First step of a research is a choice of hydrological characteristic, which can be as a traditional one (annual runoff for assessment of water resources, maxima, minima runoff, etc) as well as a new one, which characterizes an intra-annual function or intra-annual runoff distribution. For this aim a linear model has been developed which has two coefficients connected with an amplitude and level (initial conditions) of seasonal function and one parameter, which characterizes an intensity of synoptic and macro-synoptic fluctuations inside a year. Effective statistical methods have been developed for a separation of climate variability and climate change and extraction of homogeneous components of three time scales from observed long-term time series: intra annual, decadal and centural. The first two are connected with climate variability and the last (centural) with climate change. Efficiency of new methods of decomposition and smoothing has been estimated by stochastic modeling and well as on the synthetic examples. For an assessment of contribution and statistical significance of modern climate change components statistical criteria and methods have been used. Next step has been connected with a generalization of the results of detected climate changes over the area and spatial modeling. For determination of homogeneous region with the same

  10. An attempt to assess the energy related climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Iotova, A [Bulgarian Academy of Sciences, Sofia (Bulgaria). National Inst. of Meteorology and Hydrology

    1996-12-31

    A lot of efforts are directed now to study the interactions between energy and climate because of their significant importance for our planet. Globally, energy related emissions of Greenhouse Gases (GHGs) contribute for atmospheric warming. On regional level, where it is more difficult to determine concrete direction of climate variability and change, the role of energy remains considerable being not so direct as in the case of emissions` impact. Still there is essential necessity for further analyses and assessments of energy related climate variations and change in order to understand better and to quantify the energy - climate relations. In the presentation an attempt is made to develop approach for assessment of energy related climate variations on regional level. For this purpose, data and results from the research within Bulgarian Case Study (BCS) in the DECADES Inter-Agency Project framework are used. Considering the complex nature of the examined interconnections and the medium stage of the Study`s realisation, at the moment the approach can be presented in conceptual form. Correspondingly, the obtained results are illustrative and preliminary

  11. An attempt to assess the energy related climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Iotova, A. [Bulgarian Academy of Sciences, Sofia (Bulgaria). National Inst. of Meteorology and Hydrology

    1995-12-31

    A lot of efforts are directed now to study the interactions between energy and climate because of their significant importance for our planet. Globally, energy related emissions of Greenhouse Gases (GHGs) contribute for atmospheric warming. On regional level, where it is more difficult to determine concrete direction of climate variability and change, the role of energy remains considerable being not so direct as in the case of emissions` impact. Still there is essential necessity for further analyses and assessments of energy related climate variations and change in order to understand better and to quantify the energy - climate relations. In the presentation an attempt is made to develop approach for assessment of energy related climate variations on regional level. For this purpose, data and results from the research within Bulgarian Case Study (BCS) in the DECADES Inter-Agency Project framework are used. Considering the complex nature of the examined interconnections and the medium stage of the Study`s realisation, at the moment the approach can be presented in conceptual form. Correspondingly, the obtained results are illustrative and preliminary

  12. Thermal tolerance ranges and climate variability : A comparison between bivalves from differing climates

    NARCIS (Netherlands)

    Compton, Tanya J.; Rijkenberg, Micha J. A.; Drent, Jan; Piersma, Theunis

    2007-01-01

    The climate variability hypothesis proposes that in variable temperate climates poikilothermic animals have wide thermal tolerance windows, whereas in constant tropical climates they have small thermal tolerance windows. In this study we quantified and compared the upper and lower lethal thermal

  13. Climate variability and change

    International Nuclear Information System (INIS)

    Manton, M.

    2006-01-01

    When Australia's climate should not be definite barrier to the population reaching 30 million by 2050, it is recognised that our climate has limited the development of the nation over the past 200 years. Indeed in 1911, based on a comparison of the climate and development between the US and Australia. Griffith Taylor predicted that Australia's population would be 19 million at the end of the 20th century, which is a pretty good 90-year forecast. The climate constraint is not only due to much of the country being semi-arid with an annual rainfall below 400 millimetres, but also due to the large year-to-year variability of rainfall across the country

  14. Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures.

    Directory of Open Access Journals (Sweden)

    Gisselle Yang Xie

    Full Text Available Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd, a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary, including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific and also separately per region (region-specific. One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-09-08

    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 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 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-09-08

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  19. Atmospheric River Characteristics under Decadal Climate Variability

    Science.gov (United States)

    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.

  20. Evaluating the response of Lake Prespa (SW Balkan) to future climate change projections from a high-resolution model

    Science.gov (United States)

    van der Schriek, Tim; Varotsos, Konstantinos V.; Giannakopoulos, Christos

    2017-04-01

    The Mediterranean stands out globally due to its sensitivity to (future) climate change. Projections suggest that the Balkans will experience precipitation and runoff decreases of up to 30% by 2100. However, these projections show large regional spatial variability. Mediterranean lake-wetland systems are particularly threatened by projected climate changes that compound increasingly intensive human impacts (e.g. water extraction, drainage, pollution and dam-building). Protecting the remaining systems is extremely important for supporting global biodiversity. This protection should be based on a clear understanding of individual lake-wetland hydrological responses to future climate changes, which requires fine-resolution projections and a good understanding of the impact of hydro-climate variability on individual lakes. Climate change may directly affect lake level (variability), volume and water temperatures. In turn, these variables influence lake-ecology, habitats and water quality. Land-use intensification and water abstraction multiply these climate-driven changes. To date, there are no projections of future water level and -temperature of individual Mediterranean lakes under future climate scenarios. These are, however, of crucial importance to steer preservation strategies on the relevant catchment-scale. Here we present the first projections of water level and -temperature of the Prespa Lakes covering the period 2071-2100. These lakes are of global significance for biodiversity, and of great regional socio-economic importance as a water resource and tourist attraction. Impact projections are assessed by the Regional Climate Model RCA4 of the Swedish Meteorological and Hydrological Institute (SMHI) driven by the Max Planck Institute for Meteorology global climate model MPI-ESM-LR under two RCP future emissions scenarios, the RCP4.5 and the RCP8.5, with the simulations carried out in the framework of EURO-CORDEX. Temperature, evapo(transpi)ration and

  1. Final Progress Report: Collaborative Research: Decadal-to-Centennial Climate & Climate Change Studies with Enhanced Variable and Uniform Resolution GCMs Using Advanced Numerical Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Fox-Rabinovitz, M; Cote, J

    2009-06-05

    The joint U.S-Canadian project has been devoted to: (a) decadal climate studies using developed state-of-the-art GCMs (General Circulation Models) with enhanced variable and uniform resolution; (b) development and implementation of advanced numerical techniques; (c) research in parallel computing and associated numerical methods; (d) atmospheric chemistry experiments related to climate issues; (e) validation of regional climate modeling strategies for nested- and stretched-grid models. The variable-resolution stretched-grid (SG) GCMs produce accurate and cost-efficient regional climate simulations with mesoscale resolution. The advantage of the stretched grid approach is that it allows us to preserve the high quality of both global and regional circulations while providing consistent interactions between global and regional scales and phenomena. The major accomplishment for the project has been the successful international SGMIP-1 and SGMIP-2 (Stretched-Grid Model Intercomparison Project, phase-1 and phase-2) based on this research developments and activities. The SGMIP provides unique high-resolution regional and global multi-model ensembles beneficial for regional climate modeling and broader modeling community. The U.S SGMIP simulations have been produced using SciDAC ORNL supercomputers. Collaborations with other international participants M. Deque (Meteo-France) and J. McGregor (CSIRO, Australia) and their centers and groups have been beneficial for the strong joint effort, especially for the SGMIP activities. The WMO/WCRP/WGNE endorsed the SGMIP activities in 2004-2008. This project reflects a trend in the modeling and broader communities to move towards regional and sub-regional assessments and applications important for the U.S. and Canadian public, business and policy decision makers, as well as for international collaborations on regional, and especially climate related issues.

  2. Macroweather Predictions and Climate Projections using Scaling and Historical Observations

    Science.gov (United States)

    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

  3. An Object-Based Approach to Evaluation of Climate Variability Projections and Predictions

    Science.gov (United States)

    Ammann, C. M.; Brown, B.; Kalb, C. P.; Bullock, R.

    2017-12-01

    Evaluations of the performance of earth system model predictions and projections are of critical importance to enhance usefulness of these products. Such evaluations need to address specific concerns depending on the system and decisions of interest; hence, evaluation tools must be tailored to inform about specific issues. Traditional approaches that summarize grid-based comparisons of analyses and models, or between current and future climate, often do not reveal important information about the models' performance (e.g., spatial or temporal displacements; the reason behind a poor score) and are unable to accommodate these specific information needs. For example, summary statistics such as the correlation coefficient or the mean-squared error provide minimal information to developers, users, and decision makers regarding what is "right" and "wrong" with a model. New spatial and temporal-spatial object-based tools from the field of weather forecast verification (where comparisons typically focus on much finer temporal and spatial scales) have been adapted to more completely answer some of the important earth system model evaluation questions. In particular, the Method for Object-based Diagnostic Evaluation (MODE) tool and its temporal (three-dimensional) extension (MODE-TD) have been adapted for these evaluations. More specifically, these tools can be used to address spatial and temporal displacements in projections of El Nino-related precipitation and/or temperature anomalies, ITCZ-associated precipitation areas, atmospheric rivers, seasonal sea-ice extent, and other features of interest. Examples of several applications of these tools in a climate context will be presented, using output of the CESM large ensemble. In general, these tools provide diagnostic information about model performance - accounting for spatial, temporal, and intensity differences - that cannot be achieved using traditional (scalar) model comparison approaches. Thus, they can provide more

  4. Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

    Energy Technology Data Exchange (ETDEWEB)

    Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States)

    2016-10-17

    This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate through polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.

  5. Development and application of downscaled hydroclimatic predictor variables for use in climate vulnerability and assessment studies

    Science.gov (United States)

    Thorne, James; Boynton, Ryan; Flint, Lorraine; Flint, Alan; N'goc Le, Thuy

    2012-01-01

    This paper outlines the production of 270-meter grid-scale maps for 14 climate and derivative hydrologic variables for a region that encompasses the State of California and all the streams that flow into it. The paper describes the Basin Characterization Model (BCM), a map-based, mechanistic model used to process the hydrological variables. Three historic and three future time periods of 30 years (1911–1940, 1941–1970, 1971–2000, 2010–2039, 2040–2069, and 2070–2099) were developed that summarize 180 years of monthly historic and future climate values. These comprise a standardized set of fine-scale climate data that were shared with 14 research groups, including the U.S. National Park Service and several University of California groups as part of this project. We present three analyses done with the outputs from the Basin Characterization Model: trends in hydrologic variables over baseline, the most recent 30-year period; a calibration and validation effort that uses measured discharge values from 139 streamgages and compares those to Basin Characterization Model-derived projections of discharge for the same basins; and an assessment of the trends of specific hydrological variables that links historical trend to projected future change under four future climate projections. Overall, increases in potential evapotranspiration dominate other influences in future hydrologic cycles. Increased potential evapotranspiration drives decreasing runoff even under forecasts with increased precipitation, and drives increased climatic water deficit, which may lead to conversion of dominant vegetation types across large parts of the study region as well as have implications for rain-fed agriculture. The potential evapotranspiration is driven by air temperatures, and the Basin Characterization Model permits it to be integrated with a water balance model that can be derived for landscapes and summarized by watershed. These results show the utility of using a process

  6. A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers.

    Directory of Open Access Journals (Sweden)

    Sara Varela

    Full Text Available Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM. Although the selection of the variables and General Circulation Models (GCMs used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1 map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2 analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM during the LGM, and 3 quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11 are highly correlated between models. Precipitation variables (BIO12-BIO19 show no correlation between models, and specifically, BIO14 (precipitation of the driest month and BIO15 (Precipitation Seasonality (Coefficient of Variation show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of

  7. Impacts of Austrian Climate Variability on Honey Bee Mortality

    Science.gov (United States)

    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'.

  8. Effects of climatic variability and change

    Science.gov (United States)

    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)...

  9. Harvesting Atlantic Cod under Climate Variability

    Science.gov (United States)

    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.

  10. Impacts of Climate Change and Climate Variability on Cocoa ...

    African Journals Online (AJOL)

    Impacts of Climate Change and Climate Variability on Cocoa ( Theobroma Cacao ) Yields in Meme Division, South West Region of Cameroon. ... Farm selection was based on age, consistency of sizes and management practices in an attempt to keep the factors affecting cocoa yield constant. Data on cocoa yield, flowering, ...

  11. Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain

    Science.gov (United States)

    Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.

    2015-12-01

    In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.

  12. Effects of baseline conditions on the simulated hydrologic response to projected climate change

    Science.gov (United States)

    Koczot, Kathryn M.; Markstrom, Steven L.; Hay, Lauren E.

    2011-01-01

    Changes in temperature and precipitation projected from five general circulation models, using one late-twentieth-century and three twenty-first-century emission scenarios, were downscaled to three different baseline conditions. Baseline conditions are periods of measured temperature and precipitation data selected to represent twentieth-century climate. The hydrologic effects of the climate projections are evaluated using the Precipitation-Runoff Modeling System (PRMS), which is a watershed hydrology simulation model. The Almanor Catchment in the North Fork of the Feather River basin, California, is used as a case study. Differences and similarities between PRMS simulations of hydrologic components (i.e., snowpack formation and melt, evapotranspiration, and streamflow) are examined, and results indicate that the selection of a specific time period used for baseline conditions has a substantial effect on some, but not all, hydrologic variables. This effect seems to be amplified in hydrologic variables, which accumulate over time, such as soil-moisture content. Results also indicate that uncertainty related to the selection of baseline conditions should be evaluated using a range of different baseline conditions. This is particularly important for studies in basins with highly variable climate, such as the Almanor Catchment.

  13. Regional projection of climate impact indices over the Mediterranean region

    Science.gov (United States)

    Casanueva, Ana; Frías, M.; Dolores; Herrera, Sixto; Bedia, Joaquín; San Martín, Daniel; Gutiérrez, José Manuel; Zaninovic, Ksenija

    2014-05-01

    Climate Impact Indices (CIIs) are being increasingly used in different socioeconomic sectors to transfer information about climate change impacts and risks to stakeholders. CIIs are typically based on different weather variables such as temperature, wind speed, precipitation or humidity and comprise, in a single index, the relevant meteorological information for the particular impact sector (in this study wildfires and tourism). This dependence on several climate variables poses important limitations to the application of statistical downscaling techniques, since physical consistency among variables is required in most cases to obtain reliable local projections. The present study assesses the suitability of the "direct" downscaling approach, in which the downscaling method is directly applied to the CII. In particular, for illustrative purposes, we consider two popular indices used in the wildfire and tourism sectors, the Fire Weather Index (FWI) and the Physiological Equivalent Temperature (PET), respectively. As an example, two case studies are analysed over two representative Mediterranean regions of interest for the EU CLIM-RUN project: continental Spain for the FWI and Croatia for the PET. Results obtained with this "direct" downscaling approach are similar to those found from the application of the statistical downscaling to the individual meteorological drivers prior to the index calculation ("component" downscaling) thus, a wider range of statistical downscaling methods could be used. As an illustration, future changes in both indices are projected by applying two direct statistical downscaling methods, analogs and linear regression, to the ECHAM5 model. Larger differences were found between the two direct statistical downscaling approaches than between the direct and the component approaches with a single downscaling method. While these examples focus on particular indices and Mediterranean regions of interest for CLIM-RUN stakeholders, the same study

  14. Projecting future precipitation and temperature at sites with diverse climate through multiple statistical downscaling schemes

    Science.gov (United States)

    Vallam, P.; Qin, X. S.

    2017-10-01

    Anthropogenic-driven climate change would affect the global ecosystem and is becoming a world-wide concern. Numerous studies have been undertaken to determine the future trends of meteorological variables at different scales. Despite these studies, there remains significant uncertainty in the prediction of future climates. To examine the uncertainty arising from using different schemes to downscale the meteorological variables for the future horizons, projections from different statistical downscaling schemes were examined. These schemes included statistical downscaling method (SDSM), change factor incorporated with LARS-WG, and bias corrected disaggregation (BCD) method. Global circulation models (GCMs) based on CMIP3 (HadCM3) and CMIP5 (CanESM2) were utilized to perturb the changes in the future climate. Five study sites (i.e., Alice Springs, Edmonton, Frankfurt, Miami, and Singapore) with diverse climatic conditions were chosen for examining the spatial variability of applying various statistical downscaling schemes. The study results indicated that the regions experiencing heavy precipitation intensities were most likely to demonstrate the divergence between the predictions from various statistical downscaling methods. Also, the variance computed in projecting the weather extremes indicated the uncertainty derived from selection of downscaling tools and climate models. This study could help gain an improved understanding about the features of different downscaling approaches and the overall downscaling uncertainty.

  15. Impact of Climate Change on Drylands. Climate variability, livelihood strategies and policy options

    Energy Technology Data Exchange (ETDEWEB)

    Verhagen, A. [Plant Research International, Wageningen (Netherlands); Dietz, A.J. [Amsterdam Research Institute for Global Issues and Development Studies AGIDS, University of Amsterdam UvA, Amsterdam (Netherlands)

    2001-09-01

    The findings of the Impact of Climate Change on Drylands (ICCD) project were discussed during a workshop held on 26 and 27 April 2001. The aims of the workshop were to disseminate the findings of the ICCD project, create awareness of the possible effects of climate change and contribute to the dialogue on climate change research in West Africa. Both the workshop and the project were financed by the National Research Programme on Global Air Pollution and Climate Change (NRP), Centre Technique de Cooperation de Agricole et Rurale (CTA), Wageningen University (INREF), and Amsterdam Research Institute for Global Issues and Development Studies (AGIDS)

  16. Climate Ready Estuaries Partner Projects Map

    Science.gov (United States)

    CRE partners with the National Estuary Program to develop climate change projects in coastal U.S. areas, such as bays and harbors; to develop adaptation action plans, identify climate impacts and indicators, and more. This map shows project locations.

  17. Projecting species' vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?

    Science.gov (United States)

    Steen, Valerie; Sofaer, Helen R; Skagen, Susan K; Ray, Andrea J; Noon, Barry R

    2017-11-01

    Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross-validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland-dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross-validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water

  18. Disease in a more variable and unpredictable climate

    Science.gov (United States)

    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.

  19. Evaluation of Projected Agricultural Climate Risk over the Contiguous US

    Science.gov (United States)

    Zhu, X.; Troy, T. J.; Devineni, N.

    2017-12-01

    Food demands are rising due to an increasing population with changing food preferences, which places pressure on agricultural production. Additionally, climate extremes have recently highlighted the vulnerability of our agricultural system to climate variability. This study seeks to fill two important gaps in current knowledge: how does the widespread response of irrigated crops differ from rainfed and how can we best account for uncertainty in yield responses. We developed a stochastic approach to evaluate climate risk quantitatively to better understand the historical impacts of climate change and estimate the future impacts it may bring about to agricultural system. Our model consists of Bayesian regression, distribution fitting, and Monte Carlo simulation to simulate rainfed and irrigated crop yields at the US county level. The model was fit using historical data for 1970-2010 and was then applied over different climate regions in the contiguous US using the CMIP5 climate projections. The relative importance of many major growing season climate indices, such as consecutive dry days without rainfall or heavy precipitation, was evaluated to determine what climate indices play a role in affecting future crop yields. The statistical modeling framework also evaluated the impact of irrigation by using county-level irrigated and rainfed yields separately. Furthermore, the projected years with negative yield anomalies were specifically evaluated in terms of magnitude, trend and potential climate drivers. This framework provides estimates of the agricultural climate risk for the 21st century that account for the full uncertainty of climate occurrences, range of crop response, and spatial correlation in climate. The results of this study can contribute to decision making about crop choice and water use in an uncertain future climate.

  20. Impact of climatic change on ocean carbon fluxes. Role of the decadal variability

    International Nuclear Information System (INIS)

    Seferian, Roland

    2013-01-01

    Since the industrial revolution, oceans have absorbed roughly one quarter of the anthropogenic emissions of CO 2 , slowing down climate change. The evolution of the ocean carbon sink, paralleled to the anthropogenic CO 2 emissions, is ruled by the CO 2 as well as climate. Influence of atmospheric CO 2 in the recent evolution of the ocean carbon sink is well understood whilst this is not the case for the climate's one. Indeed, some authors claim that the recent variations of the ocean CO 2 sink can be attributed to climate change, whereas some others suggest that these latter are controlled by a decadal variability, which is poorly understood. In this thesis, we address question relative to the role of the decadal variability of the ocean carbon fluxes through the mean of numerical modeling. On one hand, we have demonstrated that ocean carbon fluxes exhibit decadal fluctuations within the high latitudes oceans. These fluctuations displays modes of 10 to 50-year long which account for 20 to 40% of the year-to-year variability. Thanks to Detection and Attribution methods applied to RECCAP project's reconstructions (1960-2005), we have then assessed whether the occurrence of fluctuations at decadal time scale could hamper the detection of the climate contribution to the recent evolution of ocean carbon fluxes. We have shown that the climate contribution is indeed not detected in the high latitude oceans due to the presence of decadal mode of variability. In the low latitude oceans instead, the weaker fluctuations of ocean carbon fluxes at decadal time scale favor the detection of climate influence in the recent variations of the CO 2 fluxes. (author) [fr

  1. Climatic projections and socio economic impacts of the climatic change in Colombia

    International Nuclear Information System (INIS)

    Eslava R, Jesus Antonio; Pabon Caicedo, Jose Daniel

    2001-01-01

    For the task of working out climate change projections, different methodologies have been in use, from simple extrapolations to sophisticated statistical and mathematical tools. Today, the tools most used are the models of the general circulation of the atmosphere and ocean, which include many processes of other climate components (biosphere, cryosphere, continental surface models, etc.). Different global and regional scenarios have been generated with those models. They may be of great utility in calculating projections and future scenarios for Colombia, but the representation of the country's climate in those models has to be improved in order to get projections with a higher level of certainty. The application of climate models and of the techniques of down scaling in studies of climate change is new both in Colombia and tropical America, and was introduced through the National University of Colombia's project on local and national climate change. In the first phase of the project, version 3 of the CCM (Climate Community Model) of NCAR was implemented. Parallel to that, and based on national (grid) data, maps have been prepared of the monthly temperature and precipitation of Colombia, which were used to validate the model

  2. Suitable Days for Plant Growth Disappear under Projected Climate Change: Potential Human and Biotic Vulnerability.

    Directory of Open Access Journals (Sweden)

    Camilo Mora

    2015-06-01

    Full Text Available Ongoing climate change can alter conditions for plant growth, in turn affecting ecological and social systems. While there have been considerable advances in understanding the physical aspects of climate change, comprehensive analyses integrating climate, biological, and social sciences are less common. Here we use climate projections under alternative mitigation scenarios to show how changes in environmental variables that limit plant growth could impact ecosystems and people. We show that although the global mean number of days above freezing will increase by up to 7% by 2100 under "business as usual" (representative concentration pathway [RCP] 8.5, suitable growing days will actually decrease globally by up to 11% when other climatic variables that limit plant growth are considered (i.e., temperature, water availability, and solar radiation. Areas in Russia, China, and Canada are projected to gain suitable plant growing days, but the rest of the world will experience losses. Notably, tropical areas could lose up to 200 suitable plant growing days per year. These changes will impact most of the world's terrestrial ecosystems, potentially triggering climate feedbacks. Human populations will also be affected, with up to ~2,100 million of the poorest people in the world (~30% of the world's population highly vulnerable to changes in the supply of plant-related goods and services. These impacts will be spatially variable, indicating regions where adaptations will be necessary. Changes in suitable plant growing days are projected to be less severe under strong and moderate mitigation scenarios (i.e., RCP 2.6 and RCP 4.5, underscoring the importance of reducing emissions to avoid such disproportionate impacts on ecosystems and people.

  3. Cocoa farming households' vulnerability to climate variability in Ekiti ...

    African Journals Online (AJOL)

    BRO OKOJIE

    Rural livelihoods in south western Nigeria are at risk to climate variability on the short run and climate change on .... to reduce their vulnerability to climate variability as well as longer-term climate change. Nigeria has lost her leading role in exportation of cocoa. This has been attributed .... sizes and type of farm ownership.

  4. Inferring climate variability from skewed proxy records

    Science.gov (United States)

    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

  5. Statistically downscaled climate projections to support evaluating climate change risks for hydropower

    International Nuclear Information System (INIS)

    Brekke, L.

    2008-01-01

    This paper described a web-served public access archive of down-scaled climate projections developed as a tool for water managers of river and hydropower systems. The archive provided access to climate projection data at basin-relevant resolution and included an extensive compilation of down-scale climate projects designed to support risk-based adaptation planning. Downscaled translations of 112 contemporary climate projections produced using the World Climate Research Program's coupled model intercomparison project were also included. Datasets for the coupled model included temperature and precipitation, monthly time-steps, and geographic coverage for the United States and portions of Mexico and Canada. It was concluded that the archive will be used to develop risk-based studies on shifts in seasonal patterns, changes in mean annual runoff, and associated responses in water resources and hydroelectric power management. Case studies demonstrating reclamation applications of archive content and potential applications for hydroelectric power production impacts were included. tabs., figs

  6. Arctic climate change and decadal variability

    NARCIS (Netherlands)

    Linden, van der Eveline C.

    2016-01-01

    High northern latitudes exhibit enhanced near-surface warming in a climate with increasing greenhouse gases compared to other parts of the globe, indicating an amplified climate response to external forcing. Decadal to multidecadal variability sometimes enhances and at other times reduces the

  7. Rainfall Downscaling Conditional on Upper-air Variables: Assessing Rainfall Statistics in a Changing Climate

    Science.gov (United States)

    Langousis, Andreas; Deidda, Roberto; Marrocu, Marino; Kaleris, Vassilios

    2014-05-01

    Due to its intermittent and highly variable character, and the modeling parameterizations used, precipitation is one of the least well reproduced hydrologic variables by both Global Climate Models (GCMs) and Regional Climate Models (RCMs). This is especially the case at a regional level (where hydrologic risks are assessed) and at small temporal scales (e.g. daily) used to run hydrologic models. In an effort to remedy those shortcomings and assess the effect of climate change on rainfall statistics at hydrologically relevant scales, Langousis and Kaleris (2013) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables. The developed downscaling scheme was tested using atmospheric data from the ERA-Interim archive (http://www.ecmwf.int/research/era/do/get/index), and daily rainfall measurements from western Greece, and was proved capable of reproducing several statistical properties of actual rainfall records, at both annual and seasonal levels. This was done solely by conditioning rainfall simulation on a vector of atmospheric predictors, properly selected to reflect the relative influence of upper-air variables on ground-level rainfall statistics. In this study, we apply the developed framework for conditional rainfall simulation using atmospheric data from different GCM/RCM combinations. This is done using atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com), and daily rainfall measurements for an intermediate-sized catchment in Italy; i.e. the Flumendosa catchment. Since GCM/RCM products are suited to reproduce the local climatology in a statistical sense (i.e. in terms of relative frequencies), rather than ensuring a one-to-one temporal correspondence between observed and simulated fields (i.e. as is the case for ERA-interim reanalysis data), we proceed in three steps: a) we use statistical tools to establish a linkage between ERA-Interim upper-air atmospheric forecasts and

  8. Consistency of climate change projections from multiple global and regional model intercomparison projects

    Science.gov (United States)

    Fernández, J.; Frías, M. D.; Cabos, W. D.; Cofiño, A. S.; Domínguez, M.; Fita, L.; Gaertner, M. A.; García-Díez, M.; Gutiérrez, J. M.; Jiménez-Guerrero, P.; Liguori, G.; Montávez, J. P.; Romera, R.; Sánchez, E.

    2018-03-01

    We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021-2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM-RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes.

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

    Science.gov (United States)

    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

  10. Downscaling future climate projections to the watershed scale: A north San Francisco Bay estuary case study

    Science.gov (United States)

    Micheli, Elisabeth; Flint, Lorraine; Flint, Alan; Weiss, Stuart; Kennedy, Morgan

    2012-01-01

    We modeled the hydrology of basins draining into the northern portion of the San Francisco Bay Estuary (North San Pablo Bay) using a regional water balance model (Basin Characterization Model; BCM) to estimate potential effects of climate change at the watershed scale. The BCM calculates water balance components, including runoff, recharge, evapotranspiration, soil moisture, and stream flow, based on climate, topography, soils and underlying geology, and the solar-driven energy balance. We downscaled historical and projected precipitation and air temperature values derived from weather stations and global General Circulation Models (GCMs) to a spatial scale of 270 m. We then used the BCM to estimate hydrologic response to climate change for four scenarios spanning this century (2000–2100). Historical climate patterns show that Marin’s coastal regions are typically on the order of 2 °C cooler and receive five percent more precipitation compared to the inland valleys of Sonoma and Napa because of marine influences and local topography. By the last 30 years of this century, North Bay scenarios project average minimum temperatures to increase by 1.0 °C to 3.1 °C and average maximum temperatures to increase by 2.1 °C to 3.4 °C (in comparison to conditions experienced over the last 30 years, 1981–2010). Precipitation projections for the 21st century vary between GCMs (ranging from 2 to 15% wetter than the 20th-century average). Temperature forcing increases the variability of modeled runoff, recharge, and stream discharge, and shifts hydrologic cycle timing. For both high- and low-rainfall scenarios, by the close of this century warming is projected to amplify late-season climatic water deficit (a measure of drought stress on soils) by 8% to 21%. Hydrologic variability within a single river basin demonstrated at the scale of subwatersheds may prove an important consideration for water managers in the face of climate change. Our results suggest that in arid

  11. Validation of CMIP5 multimodel ensembles through the smoothness of climate variables

    KAUST Repository

    Lee, Myoungji

    2015-05-14

    Smoothness is an important characteristic of a spatial process that measures local variability. If climate model outputs are realistic, then not only the values at each grid pixel but also the relative variation over nearby pixels should represent the true climate. We estimate the smoothness of long-term averages for land surface temperature anomalies in the Coupled Model Intercomparison Project Phase 5 (CMIP5), and compare them by climate regions and seasons. We also compare the estimated smoothness of the climate outputs in CMIP5 with those of reanalysis data. The estimation is done through the composite likelihood approach for locally self-similar processes. The composite likelihood that we consider is a product of conditional likelihoods of neighbouring observations. We find that the smoothness of the surface temperature anomalies in CMIP5 depends primarily on the modelling institution and on the climate region. The seasonal difference in the smoothness is generally small, except for some climate regions where the average temperature is extremely high or low.

  12. Quality Assurance for Essential Climate Variables

    Science.gov (United States)

    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

  13. Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

    Science.gov (United States)

    Watanabe, S.; Kim, H.; Utsumi, N.

    2017-12-01

    This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate

  14. Climate Variability and Phytoplankton in the Pacific Ocean

    Science.gov (United States)

    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 (pphytoplankton groups (chlorophytes and coccolithophores). Ocean biology in the South Pacific was not significantly correlated with MEI. During La Nina events, diatoms increased and expanded westward along the cold tongue (correlation with MEI, r=-0.81), while cyanobacteria concentrations decreased significantly (r=0.78). El Nino produced the reverse pattern, with cyanobacteria populations increasing while diatoms plummeted. The diverse response of phytoplankton in the different major basins of the Pacific suggests the different roles climate variability can play in ocean biology.

  15. Adapting to Climate Variability and Change: Experiences from Cereal-Based Farming in the Central Rift and Kobo Valleys, Ethiopia

    NARCIS (Netherlands)

    Kassie, B.T.; Hengsdijk, H.; Rötter, R.; Kahiluoto, H.; Asseng, S.; Ittersum, van M.K.

    2013-01-01

    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

  16. Comparing farmers' perception of climate change and variability with ...

    African Journals Online (AJOL)

    Perception of climate change and variability supported by local knowledge has helped to advance understanding of climate change and its impacts on agricultural land-use systems. This study compares farmers' perception of climate change and variability in four communities of the Upper East Region of Ghana. Using a ...

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

    Science.gov (United States)

    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

  18. Validation of EURO-CORDEX regional climate models in reproducing the variability of precipitation extremes in Romania

    Science.gov (United States)

    Dumitrescu, Alexandru; Busuioc, Aristita

    2016-04-01

    EURO-CORDEX is the European branch of the international CORDEX initiative that aims to provide improved regional climate change projections for Europe. The main objective of this paper is to document the performance of the individual models in reproducing the variability of precipitation extremes in Romania. Here three EURO-CORDEX regional climate models (RCMs) ensemble (scenario RCP4.5) are analysed and inter-compared: DMI-HIRHAM5, KNMI-RACMO2.2 and MPI-REMO. Compared to previous studies, when the RCM validation regarding the Romanian climate has mainly been made on mean state and at station scale, a more quantitative approach of precipitation extremes is proposed. In this respect, to have a more reliable comparison with observation, a high resolution daily precipitation gridded data set was used as observational reference (CLIMHYDEX project). The comparison between the RCM outputs and observed grid point values has been made by calculating three extremes precipitation indices, recommended by the Expert Team on Climate Change Detection Indices (ETCCDI), for the 1976-2005 period: R10MM, annual count of days when precipitation ≥10mm; RX5DAY, annual maximum 5-day precipitation and R95P%, precipitation fraction of annual total precipitation due to daily precipitation > 95th percentile. The RCMs capability to reproduce the mean state for these variables, as well as the main modes of their spatial variability (given by the first three EOF patterns), are analysed. The investigation confirms the ability of RCMs to simulate the main features of the precipitation extreme variability over Romania, but some deficiencies in reproducing of their regional characteristics were found (for example, overestimation of the mea state, especially over the extra Carpathian regions). This work has been realised within the research project "Changes in climate extremes and associated impact in hydrological events in Romania" (CLIMHYDEX), code PN II-ID-2011-2-0073, financed by the Romanian

  19. Comparison of climate envelope models developed using expert-selected variables versus statistical selection

    Science.gov (United States)

    Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

    2017-01-01

    Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

  20. The use of EuroCordex in marine climate projections

    Science.gov (United States)

    Tinker, Jonathan; Palmer, Matthew; Lowe, Jason; Howard, Tom

    2017-04-01

    The Northwest European Shelf seas (NWS, including the North Sea, Irish Sea and Celtic Sea) are of economic, environmental and cultural importance to a number of European countries. However, their representation by global climate models (GCMs) is very crude, due to their inability to represent the complex geometry and the absence of tides. Therefore, there is a need to employ dynamical downscaling methods when considering the potential impacts of climate change on the European (and other) shelf seas. Using a shelf seas model to dynamically downscale of the ocean component of the GCM is a well established method. While taking open ocean lateral boundary conditions from the GCM ocean is acceptable, using surface flux forcings from the GCM atmosphere is often problematic. The CORDEX project provides an important dataset of high spatial and temporal resolution atmospheric forcings, derived from 'parent' CMIP5 GCM simulations. We drive the NEMO shelf seas model with data from CMIP5 models and EURO-CORDEX Regional Climate Model (RCM) data to produce a set of NWS climate projections. We require relatively high temporal resolution output, and run-off (for the river forcings), and so are limited to a subset of the available EURO-CORDEX RCMs. From these we select two CMIP5 GCMs with the same RCM with two emissions scenarios to give a minimum estimate of GCM model structural and emission scenario uncertainty. Other experiments allow an initial estimate of the uncertainty associated with the model structure of both the shelf seas and the RCM. Our analysis is focused on the uncertainty associated with the mean change in a number of physical marine impacts and the drivers of coastal variability and change, including sea level and the propagation of open ocean signals onto the shelf. Our work is part of the UK Climate Projections (UKCP18) and will inform the following UK Climate Change Risk Assessments, required as part of the Climate Change Act.

  1. Input variable selection for interpolating high-resolution climate ...

    African Journals Online (AJOL)

    Although the primary input data of climate interpolations are usually meteorological data, other related (independent) variables are frequently incorporated in the interpolation process. One such variable is elevation, which is known to have a strong influence on climate. This research investigates the potential of 4 additional ...

  2. Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

    Science.gov (United States)

    Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

    2018-03-01

    Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

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

    Science.gov (United States)

    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.

  4. Climate variability and sustainable food production: Insights from ...

    African Journals Online (AJOL)

    The past two decades have seen invigorated debates on the causal link between climate variability and food crop production. This study[1] extends the debate further by investigating how climate variability has affected the production of four specific food crops: maize, millet, rice, and groundnuts in north-eastern Ghana.

  5. Electricity consumption and climate, relationship with climatic variable

    International Nuclear Information System (INIS)

    Fonte Hernandez, Aramis; Rivero Jaspe, Zoltan

    2004-01-01

    Perhaps, since in the world people is more concerned about the possibility of climatic impact on the energy consumption, actually it is an attractive theme not only for undeveloped countries, but also for developed. In this work, a study on the electricity consumption of residential sector in the province of Camaguey, Cuba, during the last ten years of X X century, was done. In it, climatic variables like temperature, relative humidity, sunshine hours, and wind speed, were included. Specifically, in the case of temperature, it was used both in its primitive form, and like a derived variable in the form of degree-day. For this reason, firstly the appropriate value of base temperature for the area under study was determined, obtaining a value of 23.6 Celsius Degrade. After that, using nonlinear regression analysis, statistical models with acceptable predictive capacity, were obtained

  6. Sensitivity of water resources in the Delaware River basin to climate variability and change

    Science.gov (United States)

    Ayers, Mark A.; Wolock, David M.; McCabe, Gregory J.; Hay, Lauren E.; Tasker, Gary D.

    1994-01-01

    Because of the greenhouse effect, projected increases in atmospheric carbon dioxide levels might cause global warming, which in turn could result in changes in precipitation patterns and evapotranspiration and in increases in sea level. This report describes the greenhouse effect; discusses the problems and uncertainties associated with the detection, prediction, and effects of climate change; and presents the results of sensitivity analyses of how climate change might affect water resources in the Delaware River basin. Sensitivity analyses suggest that potentially serious shortfalls of certain water resources in the basin could result if some scenarios for climate change come true . The results of model simulations of the basin streamflow demonstrate the difficulty in distinguishing the effects that climate change versus natural climate variability have on streamflow and water supply . The future direction of basin changes in most water resources, furthermore, cannot be precisely determined because of uncertainty in current projections of regional temperature and precipitation . This large uncertainty indicates that, for resource planning, information defining the sensitivities of water resources to a range of climate change is most relevant . The sensitivity analyses could be useful in developing contingency plans for evaluating and responding to changes, should they occur.

  7. Economic perspectives on the impact of climate variability and change: A summary report

    International Nuclear Information System (INIS)

    Timmerman, P.; Grima, A.P.

    1988-01-01

    A summary is presented of a collection of papers on the economic methodologies applicable to studies of the impact of global climate variability and change. The research was sponsored by the Canadian Climate program and was conducted as part of a project investigating the potential impacts on various sectors of the Canadian economy of climate warming due to the greenhouse effect. Topics of the papers include microeconomic analysis, benefit/cost analysis, input-output analysis, policy options regarding water levels in the Great Lakes, the scenario approach to assessing socio-economic sensitivities to climate change in the agri-food sector, and analysis of weather impacts. Several analytical tools are seen to be readily applicable to economic analyses of the effects of climate change, and issues of future water supply and demand are seen as central to climate impact assessment, and of particular concern to Canada

  8. Temporal relationship between climate variability, Prosopis juliflora ...

    African Journals Online (AJOL)

    Kyuma

    Key words: Climate, drylands, livestock, Prosopis juliflora, variability vegetation, trends, mesquite. ... climate change is costly and predictions are that both it and its cost will escalate ... Resilience Alliance, 2010; Tennigkeit and Wilkes, 2008;.

  9. THE EFFECTS OF CLIMATIC VARIABLES AND CROP AREA ON MAIZE YIELD AND VARIABILITY IN GHANA

    Directory of Open Access Journals (Sweden)

    Henry De-Graft Acquah

    2012-10-01

    Full Text Available Climate change tends to have negative effects on crop yield through its influence on crop production. Understanding the relationship between climatic variables and crop area on the mean and variance of crop yield will facilitate development of appropriate policies to cope with climate change. This paper examines the effects of climatic variables and crop area on the mean and variance of maize yield in Ghana. The Just and Pope stochastic production function using the Cobb-Douglas functional form was employed. The results show that average maize yield is positively related to crop area and negatively related to rainfall and temperature. Furthermore, increase in crop area and temperature will enlarge maize yield variability while rainfall increase will decrease the variability in maize yield.

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

    Science.gov (United States)

    Parsons, Luke Alexander

    Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall

  11. Climate variability and impacts on east African livestock herders: the ...

    African Journals Online (AJOL)

    Climate variability and impacts on east African livestock herders: the Maasai of ... and vulnerability to climate variability and climate change is assessed, using data ... Model results suggest that the ecosystem is quite resilient and suggests that ...

  12. A plant's perspective of extremes: terrestrial plant responses to changing climatic variability.

    Science.gov (United States)

    Reyer, Christopher P O; Leuzinger, Sebastian; Rammig, Anja; Wolf, Annett; Bartholomeus, Ruud P; Bonfante, Antonello; de Lorenzi, Francesca; Dury, Marie; Gloning, Philipp; Abou Jaoudé, Renée; Klein, Tamir; Kuster, Thomas M; Martins, Monica; Niedrist, Georg; Riccardi, Maria; Wohlfahrt, Georg; de Angelis, Paolo; de Dato, Giovanbattista; François, Louis; Menzel, Annette; Pereira, Marízia

    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, although potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heat-waves 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. © 2012 Blackwell Publishing Ltd.

  13. Response of the mean global vegetation distribution to interannual climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Notaro, Michael [University of Wisconsin-Madison, Center for Climatic Research, Madison, WI (United States)

    2008-06-15

    The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States' ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. (orig.)

  14. Role of resolution in regional climate change projections over China

    Science.gov (United States)

    Shi, Ying; Wang, Guiling; Gao, Xuejie

    2017-11-01

    This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days' total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to

  15. Impacts of climate variability and change on crop yield in sub-Sahara Africa

    Science.gov (United States)

    Pan, S.; Zhang, J.; Yang, J.; Chen, G.; Xu, R.; Zhang, B.; Lou, Y.

    2017-12-01

    Much concern has been raised about the impacts of climate change and climate extremes on Africa's food security. The impact of climate change on Africa's agriculture is likely to be severe compared to other continents due to high rain-fed agricultural dependence, and limited ability to mitigate and adapt to climate change. In recent decades, warming in Africa is more pronounced and faster than the global average and this trend is likely to continue in the future. However, quantitative assessment on impacts of climate extremes and climate change on crop yield has not been well investigated yet. By using an improved agricultural module of the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed impacts of historical climate variability and future climate change on food crop yield across the sub-Sahara Africa during1980-2016 and the rest of the 21st century (2017-2099). Our simulated results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Droughts have largely reduced crop yield in the most vulnerable regions of Sub-Sahara Africa. Future projections with DLEM-AG2 show that food crop production in Sub-Sahara Africa would be favored with limiting end-of-century warming to below 1.50 C.

  16. EVALUATING SHORT-TERM CLIMATE VARIABILITY IN THE LATE HOLOCENE OF THE NORTHERN GREAT PLAINS

    Energy Technology Data Exchange (ETDEWEB)

    Joseph H. Hartman

    1999-09-01

    This literature study investigated methods and areas to deduce climate change and climate patterns, looking for short-term cycle phenomena and the means to interpret them. Many groups are actively engaged in intensive climate-related research. Ongoing research might be (overly) simplified into three categories: (1) historic data on weather that can be used for trend analysis and modeling; (2) detailed geological, biological (subfossil), and analytical (geochemical, radiocarbon, etc.) studies covering the last 10,000 years (about since last glaciation); and (3) geological, paleontological, and analytical (geochemical, radiometric, etc.) studies over millions of years. Of importance is our ultimate ability to join these various lines of inquiry into an effective means of interpretation. At this point, the process of integration is fraught with methodological troubles and misconceptions about what each group can contribute. This project has met its goals to the extent that it provided an opportunity to study resource materials and consider options for future effort toward the goal of understanding the natural climate variation that has shaped our current civilization. A further outcome of this project is a proposed methodology based on ''climate sections'' that provides spatial and temporal correlation within a region. The method would integrate cultural and climate data to establish the climate history of a region with increasing accuracy with progressive study and scientific advancement (e. g., better integration of regional and global models). The goal of this project is to better understand natural climatic variations in the recent past (last 5000 years). The information generated by this work is intended to provide better context within which to examine global climate change. The ongoing project will help to establish a basis upon which to interpret late Holocene short-term climate variability as evidenced in various studies in the northern

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

    Science.gov (United States)

    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.

  18. A Robust Decision-Making Technique for Water Management under Decadal Scale Climate Variability

    Science.gov (United States)

    Callihan, L.; Zagona, E. A.; Rajagopalan, B.

    2013-12-01

    Robust decision making, a flexible and dynamic approach to managing water resources in light of deep uncertainties associated with climate variability at inter-annual to decadal time scales, is an analytical framework that detects when a system is in or approaching a vulnerable state. It provides decision makers the opportunity to implement strategies that both address the vulnerabilities and perform well over a wide range of plausible future scenarios. A strategy that performs acceptably over a wide range of possible future states is not likely to be optimal with respect to the actual future state. The degree of success--the ability to avoid vulnerable states and operate efficiently--thus depends on the skill in projecting future states and the ability to select the most efficient strategies to address vulnerabilities. This research develops a robust decision making framework that incorporates new methods of decadal scale projections with selection of efficient strategies. Previous approaches to water resources planning under inter-annual climate variability combining skillful seasonal flow forecasts with climatology for subsequent years are not skillful for medium term (i.e. decadal scale) projections as decision makers are not able to plan adequately to avoid vulnerabilities. We address this need by integrating skillful decadal scale streamflow projections into the robust decision making framework and making the probability distribution of this projection available to the decision making logic. The range of possible future hydrologic scenarios can be defined using a variety of nonparametric methods. Once defined, an ensemble projection of decadal flow scenarios are generated from a wavelet-based spectral K-nearest-neighbor resampling approach using historical and paleo-reconstructed data. This method has been shown to generate skillful medium term projections with a rich variety of natural variability. The current state of the system in combination with the

  19. Projecting Marine Mammal Distribution in a Changing Climate

    Directory of Open Access Journals (Sweden)

    Gregory K. Silber

    2017-12-01

    Full Text Available Climate-related shifts in marine mammal range and distribution have been observed in some populations; however, the nature and magnitude of future responses are uncertain in novel environments projected under climate change. This poses a challenge for agencies charged with management and conservation of these species. Specialized diets, restricted ranges, or reliance on specific substrates or sites (e.g., for pupping make many marine mammal populations particularly vulnerable to climate change. High-latitude, predominantly ice-obligate, species have experienced some of the largest changes in habitat and distribution and these are expected to continue. Efforts to predict and project marine mammal distributions to date have emphasized data-driven statistical habitat models. These have proven successful for short time-scale (e.g., seasonal management activities, but confidence that such relationships will hold for multi-decade projections and novel environments is limited. Recent advances in mechanistic modeling of marine mammals (i.e., models that rely on robust physiological and ecological principles expected to hold under climate change may address this limitation. The success of such approaches rests on continued advances in marine mammal ecology, behavior, and physiology together with improved regional climate projections. The broad scope of this challenge suggests initial priorities be placed on vulnerable species or populations (those already experiencing declines or projected to undergo ecological shifts resulting from climate changes that are consistent across climate projections and species or populations for which ample data already exist (with the hope that these may inform climate change sensitivities in less well observed species or populations elsewhere. The sustained monitoring networks, novel observations, and modeling advances required to more confidently project marine mammal distributions in a changing climate will ultimately

  20. Impacts of climate change and variability on transportation systems and infrastructure : Gulf Coast study, phase 2 : task 2 : climate variability and change in Mobile, Alabama.

    Science.gov (United States)

    2012-09-01

    Despite increasing confidence in global climate change projections in recent years, projections of : climate effects at local scales remains scarce. Location-specific risks to transportation systems : imposed by changes in climate are not yet well kn...

  1. Local Perceptions and Responses to Climate Change and Variability: The Case of Laikipia District, Kenya

    Directory of Open Access Journals (Sweden)

    Sarah Ayeri Ogalleh

    2012-12-01

    Full Text Available Agricultural policies in Kenya aim to improve farmers’ livelihoods. With projected climate change, these policies are short of mechanisms that promote farmers’ adaptation. As a result, smallholders are confronted with a variety of challenges including climate change, which hinders their agricultural production. Local knowledge can be instrumental in assisting smallholders to cope with climate change and variability. In this paper, we present empirical evidence that demonstrates local knowledge, perceptions and adaptations to climate change and variability amongst smallholders of Laikipia district of Kenya. A Palmer Drought Severity Index (PDSI calculated for one station is compared with smallholders’ perceptions. Data was collected using qualitative and quantitative methods in Umande and Muhonia sub-locations. Qualitative data included 46 transcripts from focus group discussions and key informant interviews. Quantitative data is derived from 206 interviewees. We analyzed qualitative and quantitative data using Atlas-ti and SPSS respectively. According to smallholders’ perceptions, climatic variability is increasingly changing. Local perceptions include decreasing rainfalls, increasing temperatures, increasing frosts and increasing hunger. The PDSI shows a trend towards severe droughts in the last four decades, which is in accordance with farmers’ perceptions. Smallholders use a combination of coping and adaptation strategies to respond to variability, including, among others, diversification of crop varieties, migration and sale of livestock. Significant relationships exist between drought perceptions and some adaptations such as migration and sale of livestock. Farmers have an in-depth knowledge of climatic variability, which they use to inform their coping and adaptation strategies. Knowledge of climatic perceptions and adaptations are vital entry points for decision makers and policy makers to learn how and where to enhance the

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

    Science.gov (United States)

    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

  3. Sensitivity of Climate Change Detection and Attribution to the Characterization of Internal Climate Variability

    KAUST Repository

    Imbers, Jara; Lopez, Ana; Huntingford, Chris; Allen, Myles

    2014-01-01

    The Intergovernmental Panel on Climate Change's (IPCC) "very likely" statement that anthropogenic emissions are affecting climate is based on a statistical detection and attribution methodology that strongly depends on the characterization of internal climate variability. In this paper, the authors test the robustness of this statement in the case of global mean surface air temperature, under different representations of such variability. The contributions of the different natural and anthropogenic forcings to the global mean surface air temperature response are computed using a box diffusion model. Representations of internal climate variability are explored using simple stochastic models that nevertheless span a representative range of plausible temporal autocorrelation structures, including the short-memory first-order autoregressive [AR(1)] process and the long-memory fractionally differencing process. The authors find that, independently of the representation chosen, the greenhouse gas signal remains statistically significant under the detection model employed in this paper. The results support the robustness of the IPCC detection and attribution statement for global mean temperature change under different characterizations of internal variability, but they also suggest that a wider variety of robustness tests, other than simple comparisons of residual variance, should be performed when dealing with other climate variables and/or different spatial scales. © 2014 American Meteorological Society.

  4. Sensitivity of Climate Change Detection and Attribution to the Characterization of Internal Climate Variability

    KAUST Repository

    Imbers, Jara

    2014-05-01

    The Intergovernmental Panel on Climate Change\\'s (IPCC) "very likely" statement that anthropogenic emissions are affecting climate is based on a statistical detection and attribution methodology that strongly depends on the characterization of internal climate variability. In this paper, the authors test the robustness of this statement in the case of global mean surface air temperature, under different representations of such variability. The contributions of the different natural and anthropogenic forcings to the global mean surface air temperature response are computed using a box diffusion model. Representations of internal climate variability are explored using simple stochastic models that nevertheless span a representative range of plausible temporal autocorrelation structures, including the short-memory first-order autoregressive [AR(1)] process and the long-memory fractionally differencing process. The authors find that, independently of the representation chosen, the greenhouse gas signal remains statistically significant under the detection model employed in this paper. The results support the robustness of the IPCC detection and attribution statement for global mean temperature change under different characterizations of internal variability, but they also suggest that a wider variety of robustness tests, other than simple comparisons of residual variance, should be performed when dealing with other climate variables and/or different spatial scales. © 2014 American Meteorological Society.

  5. Advances in Understanding Decadal Climate Variability

    Science.gov (United States)

    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.

  6. Toward a Unified Representation of Atmospheric Convection in Variable-Resolution Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Walko, Robert [Univ. of Miami, Coral Gables, FL (United States)

    2016-11-07

    The purpose of this project was to improve the representation of convection in atmospheric weather and climate models that employ computational grids with spatially-variable resolution. Specifically, our work targeted models whose grids are fine enough over selected regions that convection is resolved explicitly, while over other regions the grid is coarser and convection is represented as a subgrid-scale process. The working criterion for a successful scheme for representing convection over this range of grid resolution was that identical convective environments must produce very similar convective responses (i.e., the same precipitation amount, rate, and timing, and the same modification of the atmospheric profile) regardless of grid scale. The need for such a convective scheme has increased in recent years as more global weather and climate models have adopted variable resolution meshes that are often extended into the range of resolving convection in selected locations.

  7. Climate Projections and Drought: Verification for the Colorado River Basin

    Science.gov (United States)

    Santos, N. I.; Piechota, T. C.; Miller, W. P.; Ahmad, S.

    2017-12-01

    The Colorado River Basin has experienced the driest 17 year period (2000-2016) in over 100 years of historical record keeping. While the Colorado River reservoir system began the current drought at near 100% capacity, reservoir storage has fallen to just above 50% during the drought. Even though federal and state water agencies have worked together to mitigate the impact of the drought and have collaboratively sponsored conservation programs and drought contingency plans, the 17-years of observed data beg the question as to whether the most recent climate projections would have been able to project the current drought's severity. The objective of this study is to analyze observations and ensemble projections (e.g. temperature, precipitation, streamflow) from the CMIP3 and CMIP5 archive in the Colorado River Basin and compare metrics related to skill scores, the Palmer Drought Severity Index, and water supply sustainability index. Furthermore, a sub-ensemble of CMIP3/CMIP5 projections, developed using a teleconnection replication verification technique developed by the author, will also be compared to the observed record to assist in further validating the technique as a usable process to increase skill in climatological projections. In the end, this study will assist to better inform water resource managers about the ability of climate ensembles to project hydroclimatic variability and the appearance of decadal drought periods.

  8. Regional climate projection of the Maritime Continent using the MIT Regional Climate Model

    Science.gov (United States)

    IM, E. S.; Eltahir, E. A. B.

    2014-12-01

    Given that warming of the climate system is unequivocal (IPCC AR5), accurate assessment of future climate is essential to understand the impact of climate change due to global warming. Modelling the climate change of the Maritime Continent is particularly challenge, showing a high degree of uncertainty. Compared to other regions, model agreement of future projections in response to anthropogenic emission forcings is much less. Furthermore, the spatial and temporal behaviors of climate projections seem to vary significantly due to a complex geographical condition and a wide range of scale interactions. For the fine-scale climate information (27 km) suitable for representing the complexity of climate change over the Maritime Continent, dynamical downscaling is performed using the MIT regional climate model (MRCM) during two thirty-year period for reference (1970-1999) and future (2070-2099) climate. Initial and boundary conditions are provided by Community Earth System Model (CESM) simulations under the emission scenarios projected by MIT Integrated Global System Model (IGSM). Changes in mean climate as well as the frequency and intensity of extreme climate events are investigated at various temporal and spatial scales. Our analysis is primarily centered on the different behavior of changes in convective and large-scale precipitation over land vs. ocean during dry vs. wet season. In addition, we attempt to find the added value to downscaled results over the Maritime Continent through the comparison between MRCM and CESM projection. Acknowledgements.This research was supported by the National Research Foundation Singapore through the Singapore MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling interdisciplinary research program.

  9. Climate Variability, Social and Environmental Factors, and Ross River Virus Transmission: Research Development and Future Research Needs

    Science.gov (United States)

    Tong, Shilu; Dale, Pat; Nicholls, Neville; Mackenzie, John S.; Wolff, Rodney; McMichael, Anthony J.

    2008-01-01

    Background Arbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social, and environmental variability on the transmission of arbovirus diseases remains to be determined. Objective Our goal for this study was to provide an overview of research development and future research directions about the interrelationship between climate variability, social and environmental factors, and the transmission of Ross River virus (RRV), the most common and widespread arbovirus disease in Australia. Methods We conducted a systematic literature search on climatic, social, and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches. Results The body of evidence revealed that the transmission cycles of RRV disease appear to be sensitive to climate and tidal variability. Rainfall, temperature, and high tides were among major determinants of the transmission of RRV disease at the macro level. However, the nature and magnitude of the interrelationship between climate variability, mosquito density, and the transmission of RRV disease varied with geographic area and socioenvironmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections, and the key determinants of RRV transmission we have identified here may be useful in the development of an early warning system. Conclusions The analysis indicates that there is a complex relationship between climate variability, social and environmental factors, and RRV transmission. Different strategies may be needed for the control and prevention of RRV disease at different levels. These research findings could be used as an additional tool to support decision making in disease control/surveillance and risk management. PMID:19079707

  10. Risk variables in evaluation of transport projects

    Science.gov (United States)

    Vařbuchta, Petr; Kovářová, Hana; Hromádka, Vít; Vítková, Eva

    2017-09-01

    Depending on the constantly increasing demands on assessment of investment projects, especially assessment of large-scale projects in transport and important European projects with wide impacts, there is constantly increasing focus on risk management, whether to find mitigations, creating corrective measures or their implementation in assessment, especially in the context of Cost-Benefit analysis. To project assessment is often used implementation of certain risk variables, which can generate negative impacts of project outputs in framework of assess. Especially in case of transportation infrastructure projects is taken much emphasis on the influence of risk variables. However, currently in case of assessment of transportation projects is in Czech Republic used a few risk variables, which occur in the most projects. This leads to certain limitation in framework of impact assessment of risk variables. This papers aims to specify a new risk variables and process of applying them to already executed project assessment. Based on changes generated by new risk variables will be evaluated differences between original and adapted assessment.

  11. Means and extremes: building variability into community-level climate change experiments.

    Science.gov (United States)

    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.

  12. Marine assemblages respond rapidly to winter climate variability.

    Science.gov (United States)

    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.

  13. Investigating the Capacity of Hydrological Models to Project Impacts of Climate Change in the Context of Water Allocation

    Science.gov (United States)

    Velez, Carlos; Maroy, Edith; Rocabado, Ivan; Pereira, Fernando

    2017-04-01

    To analyse the impacts of climate changes, hydrological models are used to project the hydrology responds under future conditions that normally differ from those for which they were calibrated. The challenge is to assess the validity of the projected effects when there is not data to validate it. A framework for testing the ability of models to project climate change was proposed by Refsgaard et al., (2014). The authors recommend the use of the differential-split sample test (DSST) in order to build confidence in the model projections. The method follow three steps: 1. A small number of sub-periods are selected according to one climate characteristics, 2. The calibration - validation test is applied on these periods, 3. The validation performances are compered to evaluate whether they vary significantly when climatic characteristics differ between calibration and validation. DSST rely on the existing records of climate and hydrological variables; and performances are estimated based on indicators of error between observed and simulated variables. Other authors suggest that, since climate models are not able to reproduce single events but rather statistical properties describing the climate, this should be reflected when testing hydrological models. Thus, performance criteria such as RMSE should be replaced by for instance flow duration curves or other distribution functions. Using this type of performance criteria, Van Steenbergen and Willems, (2012) proposed a method to test the validity of hydrological models in a climate changing context. The method is based on the evaluation of peak flow increases due to different levels of rainfall increases. In contrast to DSST, this method use the projected climate variability and it is especially useful to compare different modelling tools. In the framework of a water allocation project for the region of Flanders (Belgium) we calibrated three hydrological models: NAM, PDM and VHM; for 67 gauged sub-catchments with approx

  14. Ensemble of regional climate model projections for Ireland

    Science.gov (United States)

    Nolan, Paul; McGrath, Ray

    2016-04-01

    The method of Regional Climate Modelling (RCM) was employed to assess the impacts of a warming climate on the mid-21st-century climate of Ireland. The RCM simulations were run at high spatial resolution, up to 4 km, thus allowing a better evaluation of the local effects of climate change. Simulations were run for a reference period 1981-2000 and future period 2041-2060. Differences between the two periods provide a measure of climate change. To address the issue of uncertainty, a multi-model ensemble approach was employed. Specifically, the future climate of Ireland was simulated using three different RCMs, driven by four Global Climate Models (GCMs). To account for the uncertainty in future emissions, a number of SRES (B1, A1B, A2) and RCP (4.5, 8.5) emission scenarios were used to simulate the future climate. Through the ensemble approach, the uncertainty in the RCM projections can be partially quantified, thus providing a measure of confidence in the predictions. In addition, likelihood values can be assigned to the projections. The RCMs used in this work are the COnsortium for Small-scale MOdeling-Climate Limited-area Modelling (COSMO-CLM, versions 3 and 4) model and the Weather Research and Forecasting (WRF) model. The GCMs used are the Max Planck Institute's ECHAM5, the UK Met Office's HadGEM2-ES, the CGCM3.1 model from the Canadian Centre for Climate Modelling and the EC-Earth consortium GCM. The projections for mid-century indicate an increase of 1-1.6°C in mean annual temperatures, with the largest increases seen in the east of the country. Warming is enhanced for the extremes (i.e. hot or cold days), with the warmest 5% of daily maximum summer temperatures projected to increase by 0.7-2.6°C. The coldest 5% of night-time temperatures in winter are projected to rise by 1.1-3.1°C. Averaged over the whole country, the number of frost days is projected to decrease by over 50%. The projections indicate an average increase in the length of the growing season

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

    Science.gov (United States)

    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

  16. Joint Applications Pilot of the National Climate Predictions and Projections Platform and the North Central Climate Science Center: Delivering climate projections on regional scales to support adaptation planning

    Science.gov (United States)

    Ray, A. J.; Ojima, D. S.; Morisette, J. T.

    2012-12-01

    The DOI North Central Climate Science Center (NC CSC) and the NOAA/NCAR National Climate Predictions and Projections (NCPP) Platform and have initiated a joint pilot study to collaboratively explore the "best available climate information" to support key land management questions and how to provide this information. NCPP's mission is to support state of the art approaches to develop and deliver comprehensive regional climate information and facilitate its use in decision making and adaptation planning. This presentation will describe the evolving joint pilot as a tangible, real-world demonstration of linkages between climate science, ecosystem science and resource management. Our joint pilot is developing a deliberate, ongoing interaction to prototype how NCPP will work with CSCs to develop and deliver needed climate information products, including translational information to support climate data understanding and use. This pilot also will build capacity in the North Central CSC by working with NCPP to use climate information used as input to ecological modeling. We will discuss lessons to date on developing and delivering needed climate information products based on this strategic partnership. Four projects have been funded to collaborate to incorporate climate information as part of an ecological modeling project, which in turn will address key DOI stakeholder priorities in the region: Riparian Corridors: Projecting climate change effects on cottonwood and willow seed dispersal phenology, flood timing, and seedling recruitment in western riparian forests. Sage Grouse & Habitats: Integrating climate and biological data into land management decision models to assess species and habitat vulnerability Grasslands & Forests: Projecting future effects of land management, natural disturbance, and CO2 on woody encroachment in the Northern Great Plains The value of climate information: Supporting management decisions in the Plains and Prairie Potholes LCC. NCCSC's role in

  17. The terroir of vineyards - climatic variability in an Austrian wine-growing region

    Science.gov (United States)

    Gerersdorfer, T.

    2010-09-01

    The description of a terroir is a concept in viticulture that relates the sensory attributes of wine to the environmental conditions in which the grapes grow. Many factors are involved including climate, soil, cultivar, human practices and all these factors interact manifold. The study area of Carnuntum is a small wine-growing region in the eastern part of Austria. It is rich of Roman remains which play a major role in tourism and the marketing strategies of the wines as well. An interdisciplinary study on the environmental characteristics particularly with regard to growing conditions of grapes was started in this region. The study is concerned with the description of the physiogeographic properties of the region and with the investigation of the dominating viticultural functions. Grape-vines depend on climatic conditions to a high extent. Compared to other influencing factors like soil, climate plays a significant role. In the framework of this interdisciplinary project climatic variability within the Carnuntum wine-growing region is investigated. On the one hand microclimatic variations are influenced by soil type and by canopy management. On the other hand the variability is a result of the topoclimate (altitude, aspect and slope) and therefore relief is a major terroir factor. Results of microclimatic measurements and variations are presented with focus on the interpretation of the relationship between relief, structure of the vineyards and the climatic conditions within the course of a full year period.

  18. Future Flows Climate: an ensemble of 1-km climate change projections for hydrological application in Great Britain

    Directory of Open Access Journals (Sweden)

    C. Prudhomme

    2012-11-01

    Full Text Available The dataset Future Flows Climate was developed as part of the project ''Future Flows and Groundwater Levels'' to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications, and to enable climate change uncertainty and climate variability to be accounted for in the assessment of their possible impacts on the environment.

    Future Flows Climate is derived from the Hadley Centre's ensemble projection HadRM3-PPE that is part of the basis of UKCP09 and includes projections in available precipitation (water available to hydrological processes after snow and ice storages have been accounted for and potential evapotranspiration. It corresponds to an 11-member ensemble of transient projections from January 1950 to December 2098, each a single realisation from a different variant of HadRM3. Data are provided on a 1-km grid over the HadRM3 land areas at a daily (available precipitation and monthly (PE time step as netCDF files.

    Because systematic biases in temperature and precipitation were found between HadRM3-PPE and gridded temperature and precipitation observations for the 1962–1991 period, a monthly bias correction procedure was undertaken, based on a linear correction for temperature and a quantile-mapping correction (using the gamma distribution for precipitation followed by a spatial downscaling. Available precipitation was derived from the bias-corrected precipitation and temperature time series using a simple elevation-dependant snow-melt model. Potential evapotranspiration time series were calculated for each month using the FAO-56 Penman-Monteith equations and bias-corrected temperature, cloud cover, relative humidity and wind speed from HadRM3-PPE along with latitude of the grid and the day of the year.

    Future Flows Climate is freely available for non-commercial use under certain licensing conditions. It is the

  19. Effects of climate variability and climate change on crop production in southern Mali

    NARCIS (Netherlands)

    Traore, B.; Corbeels, M.; Wijk, van M.T.; Rufino, M.C.; Giller, K.E.

    2013-01-01

    In West Africa predictions of future changes in climate and especially rainfall are highly uncertain, and up to now no long-term analyses are available of the effects of climate on crop production. This study analyses long-term trends in climate variability at N'Tarla and Sikasso in southern Mali

  20. Shift of biome patterns due to simulated climate variability and climate change

    International Nuclear Information System (INIS)

    Claussen, M.

    1993-01-01

    The variability of simulated equilibrium-response patterns of biomes caused by simulated climate variability and climate shift is analysed. This investigation is based on various realisations of simulated present-day climate and climate shift. It has been found that the difference between biomes computed from three 10-year climatologies and from the corresponding 30-year climatology, simulated by the Hamburg climate model at T21 resolution, amounts to approximately 6% of the total land area, Antarctica excluded. This difference is mainly due to differences in annual moisture availability and winter temperatures. When intercomparing biomes from the 10-year climatologies a 10% difference is seen, but there is no unique difference pattern. In contrast to the interdecadal variability, the shift of conditions favorable for biomes due to a shift in climate in the next 100 years, caused by an increase in sea-surface temperatures and atmospheric CO 2 , reveals a unique trend pattern. It turns out that the strongest and most significant signal is the north-east shift of conditions for boreal biomes. This signal is caused by an increase of annual temperature sums as well as mean temperatures of the coldest and warmest months. Trends in annual moisture availability are of secondary importance globally. Regionally, a decrease in water availability affects biomes in Central and East Europe and an increase of water availability leads to a potential increase in tropical rain forest. In total, all differences amount to roughly 30% of the total land surface, Antarctica excluded. (orig./KW)

  1. Potential increase in floods in California's Sierra Nevada under future climate projections

    Science.gov (United States)

    Das, T.; Dettinger, M.D.; Cayan, D.R.; Hidalgo, H.G.

    2011-01-01

    California's mountainous topography, exposure to occasional heavily moisture-laden storm systems, and varied communities and infrastructures in low lying areas make it highly vulnerable to floods. An important question facing the state-in terms of protecting the public and formulating water management responses to climate change-is "how might future climate changes affect flood characteristics in California?" To help address this, we simulate floods on the western slopes of the Sierra Nevada Mountains, the state's primary catchment, based on downscaled daily precipitation and temperature projections from three General Circulation Models (GCMs). These climate projections are fed into the Variable Infiltration Capacity (VIC) hydrologic model, and the VIC-simulated streamflows and hydrologic conditions, from historical and from projected climate change runs, allow us to evaluate possible changes in annual maximum 3-day flood magnitudes and frequencies of floods. By the end of the 21st Century, all projections yield larger-than-historical floods, for both the Northern Sierra Nevada (NSN) and for the Southern Sierra Nevada (SSN). The increases in flood magnitude are statistically significant (at p models, while under the third scenario, GFDL CM2. 1, frequencies remain constant or decline slightly, owing to an overall drying trend. These increases appear to derive jointly from increases in heavy precipitation amount, storm frequencies, and days with more precipitation falling as rain and less as snow. Increases in antecedent winter soil moisture also play a role in some areas. Thus, a complex, as-yet unpredictable interplay of several different climatic influences threatens to cause increased flood hazards in California's complex western Sierra landscapes. ?? 2011 Springer Science+Business Media B.V.

  2. Spatial uncertainty in bias corrected climate change projections and hydrogeological impacts

    DEFF Research Database (Denmark)

    Seaby, Lauren Paige; Refsgaard, Jens Christian; Sonnenborg, Torben

    2015-01-01

    Model pairing, this paper analyses the relationship between complexity and robustness of three distribution-based scaling (DBS) bias correction methods applied to daily precipitation at various spatial scales. Hydrological simulations are forced by CM inputs to assess the spatial uncertainty......The question of which climate model bias correction methods and spatial scales for correction are optimal for both projecting future hydrological changes as well as removing initial model bias has so far received little attention. For 11 climate models (CMs), or GCM/RCM – Global/Regional Climate...... signals. The magnitude of spatial bias seen in precipitation inputs does not necessarily correspond to the magnitude of biases seen in hydrological outputs. Variables that integrate basin responses over time and space are more sensitive to mean spatial biases and less so on extremes. Hydrological...

  3. Modeling key processes causing climate change and variability

    Energy Technology Data Exchange (ETDEWEB)

    Henriksson, S.

    2013-09-01

    Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are (1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, (2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, (3) identifying a power law shape S(f) {proportional_to} f-{alpha} for the spectrum of global mean temperature with {alpha} {approx} 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, (4) separating aerosol properties and climate effects in India by season and location (5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, (6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and (7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy

  4. Selection of climate change scenario data for impact modelling

    DEFF Research Database (Denmark)

    Sloth Madsen, M; Fox Maule, C; MacKellar, N

    2012-01-01

    Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study...... illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make...... the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented...

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

    Science.gov (United States)

    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.

  6. CLIMATE CHANGE, VARIABILITY AND SUSTAINABLE AGRICULTURE IN ZIMBABWE'S RURAL COMMUNITIES

    Directory of Open Access Journals (Sweden)

    Gukurume Simbarashe

    2013-02-01

    Full Text Available This article explores the impact of climate change and variability on agricultural productivity in the communal area of Bikita. The article further examines the adaptation and mitigation strategies devised by farmers to deal with the vagaries of climate change and variability. The sustainability of these is also interrogated in this article. This study juxtaposed qualitative and quantitative methodologies albeit with more bias on the former. A total of 40 farmers were sampled for unstructured interviews and focus group discussions. This article argues that the adverse impacts of climate change and variability are felt heavily by the poor communal farmers who are directly dependent on agriculture for livelihood. From the study, some of the widely reported signs of climate variability in Bikita included late and unpredictable rains, high temperatures (heat waves, successive drought, shortening rainfall seasons and seasonal changes in the timing of rainfall. The paper argues that climate change has compounded the vulnerability of peasant farmers in the drought - prone district of Bikita plunging them into food insecurity and abject poverty. It emerged in the study that some of effects of climate variability felt by communal farmers in Bikita included failure of crops, death of livestock and low crop yields, all of which have led to declining agricultural productivity. Findings in this study however established that communal farmers have not been passive victims of the vagaries of climate change and variability. They have rationally responded to it through various adaptation and mitigation strategies both individually and collectively.

  7. Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China

    Science.gov (United States)

    Li, Zhi; Jin, Jiming

    2017-11-01

    Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs) at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i) spatial downscaling of ESMs using a transfer function method, (ii) temporal downscaling of ESMs using a single-site weather generator, and (iii) reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011-2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT) for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011-2040 to 1961-2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its variance ratios of 2011-2040 to 1961-2005 increased

  8. The Mechanisms of Natural Variability and its Interaction with Anthropogenic Climate Change Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Vallis, Geoffrey K. [Princeton Univ., NJ (United States)

    2015-01-30

    The project had two main components. The first concerns estimating the climate sensitivity in the presence of forcing uncertainty and natural variability. Climate sensitivity is the increase in the average surface temperature for a given increase in greenhouse gases, for example a doubling of carbon dioxide. We have provided new, probabilistic estimates of climate sensitivity using a simple climate model an the observed warming in the 20th century, in conjunction with ideas in data assimilation and parameter estimation developed in the engineering community. The estimates combine the uncertainty in the anthropogenic aerosols with the uncertainty arising because of natural variability. The second component concerns how the atmospheric circulation itself might change with anthropogenic global warming. We have shown that GCMs robustly predict an increase in the length scale of eddies, and we have also explored the dynamical mechanisms whereby there might be a shift in the latitude of the jet stream associated with anthropogenic warming. Such shifts in the jet might cause large changes in regional climate, potentially larger than the globally-averaged signal itself. We have also shown that the tropopause robustly increases in height with global warming, and that the Hadley Cell expands, and that the expansion of the Hadley Cell is correlated with the polewards movement of the mid-latitude jet.

  9. Visualizing projected Climate Changes - the CMIP5 Multi-Model Ensemble

    Science.gov (United States)

    Böttinger, Michael; Eyring, Veronika; Lauer, Axel; Meier-Fleischer, Karin

    2017-04-01

    Large ensembles add an additional dimension to climate model simulations. Internal variability of the climate system can be assessed for example by multiple climate model simulations with small variations in the initial conditions or by analyzing the spread in large ensembles made by multiple climate models under common protocols. This spread is often used as a measure of uncertainty in climate projections. In the context of the fifth phase of the WCRP's Coupled Model Intercomparison Project (CMIP5), more than 40 different coupled climate models were employed to carry out a coordinated set of experiments. Time series of the development of integral quantities such as the global mean temperature change for all models visualize the spread in the multi-model ensemble. A similar approach can be applied to 2D-visualizations of projected climate changes such as latitude-longitude maps showing the multi-model mean of the ensemble by adding a graphical representation of the uncertainty information. This has been demonstrated for example with static figures in chapter 12 of the last IPCC report (AR5) using different so-called stippling and hatching techniques. In this work, we focus on animated visualizations of multi-model ensemble climate projections carried out within CMIP5 as a way of communicating climate change results to the scientific community as well as to the public. We take a closer look at measures of robustness or uncertainty used in recent publications suitable for animated visualizations. Specifically, we use the ESMValTool [1] to process and prepare the CMIP5 multi-model data in combination with standard visualization tools such as NCL and the commercial 3D visualization software Avizo to create the animations. We compare different visualization techniques such as height fields or shading with transparency for creating animated visualization of ensemble mean changes in temperature and precipitation including corresponding robustness measures. [1] Eyring, V

  10. Methodological principles for the evaluation of impact of the variability and the climatic change in the human health, a statistical focus

    International Nuclear Information System (INIS)

    Ortiz Bulto, Paulo Lazaro; Vladimir Guevara, Antonio; Ulloa, Jacqueline; Aparicio, Marilyn

    2001-01-01

    Signal detection of climate variability or change and the evaluation of its specific effects, requires an understanding of the variations in the observed data, which describe the natural climate variability and change signals. It is also necessary to understand the complex interactions that make up the climate system. In the present work, an unusual methodological approach is taken to evaluate the effects and impacts of climate variability and change on the behaviour of different diseases, on the basis of practical experience of its application in four countries of the Caribbean, Central and South America: Cuba, Panama, Bolivia and Paraguay. For the determination of the climate signal change multivariate analysis techniques (empirical orthogonal functions) were used, combined with robust methods of time series decomposition (decomposition by median). They allowed us to describe the changes observed in the seasonal patterns of climate and epidemiological diseases for the period 1991-1999, with respect to the period 1961-1990. These results were used to build an autoregressive model with non-constant variance, with a climate index based on the signals obtained from the decompositions, which enters the model as an exogenous variable in order to make projections of the diseases

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

    Science.gov (United States)

    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.

  12. Decomposing the uncertainty in climate impact projections of Dynamic Vegetation Models: a test with the forest models LANDCLIM and FORCLIM

    Science.gov (United States)

    Cailleret, Maxime; Snell, Rebecca; von Waldow, Harald; Kotlarski, Sven; Bugmann, Harald

    2015-04-01

    not so much at medium elevations. (ii) Considering climate change, the variability that is due to the GCM-RCM chains is much greater than the variability induced by the uncertainty in the initial climatic conditions. (iii) The uncertainties caused by the intrinsic stochasticity in the DVMs and by the random generation of the climate time-series are negligible. Overall, our results indicate that DVMs are quite sensitive to the climate data, highlighting particularly (1) the limitations of using one single multi-model average climate change scenario in climate impact studies and (2) the need to better consider the uncertainty in climate model outputs for projecting future vegetation changes.

  13. A Framework for Categorizing Important Project Variables

    Science.gov (United States)

    Parsons, Vickie S.

    2003-01-01

    While substantial research has led to theories concerning the variables that affect project success, no universal set of such variables has been acknowledged as the standard. The identification of a specific set of controllable variables is needed to minimize project failure. Much has been hypothesized about the need to match project controls and management processes to individual projects in order to increase the chance for success. However, an accepted taxonomy for facilitating this matching process does not exist. This paper surveyed existing literature on classification of project variables. After an analysis of those proposals, a simplified categorization is offered to encourage further research.

  14. Projected impacts of climate change on regional capacities for global plant species richness.

    Science.gov (United States)

    Sommer, Jan Henning; Kreft, Holger; Kier, Gerold; Jetz, Walter; Mutke, Jens; Barthlott, Wilhelm

    2010-08-07

    Climate change represents a major challenge to the maintenance of global biodiversity. To date, the direction and magnitude of net changes in the global distribution of plant diversity remain elusive. We use the empirical multi-variate relationships between contemporary water-energy dynamics and other non-climatic predictor variables to model the regional capacity for plant species richness (CSR) and its projected future changes. We find that across all analysed Intergovernmental Panel on Climate Change emission scenarios, relative changes in CSR increase with increased projected temperature rise. Between now and 2100, global average CSR is projected to remain similar to today (+0.3%) under the optimistic B1/+1.8 degrees C scenario, but to decrease significantly (-9.4%) under the 'business as usual' A1FI/+4.0 degrees C scenario. Across all modelled scenarios, the magnitude and direction of CSR change are geographically highly non-uniform. While in most temperate and arctic regions, a CSR increase is expected, the projections indicate a strong decline in most tropical and subtropical regions. Countries least responsible for past and present greenhouse gas emissions are likely to incur disproportionately large future losses in CSR, whereas industrialized countries have projected moderate increases. Independent of direction, we infer that all changes in regional CSR will probably induce on-site species turnover and thereby be a threat to native floras.

  15. Eyewitness Accounts on Climate Variability and the Responses: Perspectives from Farmers

    Directory of Open Access Journals (Sweden)

    Jiban Mani Poudel

    2012-06-01

    Full Text Available People with different socio-cultural arrangements havedifferent experiences and responses to climatic variability. The place specific experiences and responses at community level still remain a little explored issue in the discourse of climate change research. This paper deals with local experiences of climatic variability which have been monitoring by locals in their lifetime, on the one hand, and, on the other, explore their responses or coping mechanisms which they have been practicing to mitigate with climatic risks. Moreover, farmers’ experiences were documented in term of observed climatic variability in their lifetime focusing on qualitative data. I have used eyewitness accounts and hearsays to document their experiences of climatic variability. Moreover, farmers have developed various coping mechanisms such as indigenous knowledge, utilize kinship based social network, environment friendly cropping practices, and use of alternative sources of water (water-tanker, well-water for irrigation, arrange rain-making ritual to cope with climatic uncertainty in their lifetime.DOI: http://dx.doi.org/10.3126/dsaj.v5i0.6362Dhaulagiri Journal of Sociology and Anthropology Vol. 5, 2011: 171-90

  16. Climate change projections and stratosphere-troposphere interaction

    Energy Technology Data Exchange (ETDEWEB)

    Scaife, Adam A.; Fereday, David R.; Butchart, Neal; Hardiman, Steven C. [Met Office Hadley Centre, Exeter (United Kingdom); Spangehl, Thomas; Cubasch, Ulrich; Langematz, Ulrike [Freie Universitaet Berlin, Berlin (Germany); Akiyoshi, Hideharu [National Institute for Environmental Studies, Tsukuba (Japan); Bekki, Slimane [LATMOS-IPSL, UVSQ, UPMC, CNRS/INSU, Paris (France); Braesicke, Peter [University of Cambridge, Cambridge (United Kingdom); Chipperfield, Martyn P. [University of Leeds, School of Earth and Environment, Leeds (United Kingdom); Gettelman, Andrew [National Center for Atmospheric Research, Boulder, CO (United States); Michou, Martine [GAME/CNRM (Meteo France, CNRS), Toulouse (France); Rozanov, Eugene [PMOD/WRC and ETHZ, Davos (Switzerland); Shepherd, Theodore G. [University of Toronto, Toronto, ON (Canada)

    2012-05-15

    Climate change is expected to increase winter rainfall and flooding in many extratropical regions as evaporation and precipitation rates increase, storms become more intense and storm tracks move polewards. Here, we show how changes in stratospheric circulation could play a significant role in future climate change in the extratropics through an additional shift in the tropospheric circulation. This shift in the circulation alters climate change in regional winter rainfall by an amount large enough to significantly alter regional climate change projections. The changes are consistent with changes in stratospheric winds inducing a change in the baroclinic eddy growth rate across the depth of the troposphere. A change in mean wind structure and an equatorward shift of the tropospheric storm tracks relative to models with poor stratospheric resolution allows coupling with surface climate. Using the Atlantic storm track as an example, we show how this can double the predicted increase in extreme winter rainfall over Western and Central Europe compared to other current climate projections. (orig.)

  17. Simulation of climate variability and anthropogenic climate change

    International Nuclear Information System (INIS)

    Bengtsson, Lennart

    1999-01-01

    The climatic changes in the last century were discussed and focus was on the questions: 1) What are the causes of the rapid climate fluctuations and 2) Is the global warming, which is observed during the last century, caused by natural or anthropogenic effects. It is concluded that an understanding of climate based on the interpretation of observational data only is not feasible, unless supported by an adequate theoretical interpretation. The capabilities of climatic models were discussed and the importance of incorporating 1) calculations of the internal variability of the atmosphere when forced from an ocean with prescribed sea surface temperature as well as for a system consisting of an atmosphere and a mixed ocean of limited depth, 2) a fully coupled atmospheric and ocean model and finally, 3) a fully coupled system including transiently changing greenhouse gases and aerosols. A short summation of the results is presented. The pronounced warming during the last century is not reproduced under the assumption of constant forcing and pollution emissions have to be incorporated into the models in order to bring the simulated data in agreement with observations

  18. Projection of future runoff change using climate elasticity method derived from Budyko framework in major basins across China

    Science.gov (United States)

    Xing, Wanqiu; Wang, Weiguang; Zou, Shan; Deng, Chao

    2018-03-01

    This study established a climate elasticity method based on Budyko hypothesis and enhanced it by selecting the most effective Budyko-type formula to strengthen the runoff change prediction reliability. The spatiotemporal variations in hydrologic variables (i.e., runoff, precipitation and potential evaporation) during historical period were revealed first and the climate elasticities of runoff were investigated. The proposed climate elasticity method was also applied to project the spatiotemporal variations in future runoff and its key influencing factors in 35 watersheds across China. Wherein, the future climate series were retrieved by consulting the historical series, informed by four global climate models (GCMs) under representative concentration pathways from phase five of the Coupled Model Intercomparison Project. Wang-Tang equation was selected as the optimal Budyko-type equation for its best ability in reproducing the runoff change (with a coefficient of determination and mean absolute error of 0.998 and 1.36 mm, respectively). Observed runoff presents significant decreasing trends in the northern and increasing trends in the southern regions of China, and generally its change is identified to be more sensitive to climatic variables in Hai River Basin and lower Yellow River Basin. Compared to the runoff during the reference period, positive change rates in the north and negative change rates in the south of China in the mid-21st century can be practically generalized from the majority of GCMs projections. This maybe resulted from the increasing precipitation, especially in parts of northern basins. Meanwhile, GCMs project a consistently upward trend in potential evaporation although significant decreasing trends occur in the majority of catchments for the historical period. The results indicate that climate change will possibly bring some changes to the water resources over China in the mid-21st century and some countermeasures of water resources planning

  19. Regional climate projections for the MENA-CORDEX domain: analysis of projected temperature and precipitation changes

    Science.gov (United States)

    Hänsler, Andreas; Weber, Torsten; Eggert, Bastian; Saeed, Fahad; Jacob, Daniela

    2014-05-01

    Within the CORDEX initiative a multi-model suite of regionalized climate change information will be made available for several regions of the world. The German Climate Service Center (CSC) is taking part in this initiative by applying the regional climate model REMO to downscale global climate projections of different coupled general circulation models (GCMs) for several CORDEX domains. Also for the MENA-CORDEX domain, a set of regional climate change projections has been established at the CSC by downscaling CMIP5 projections of the Max-Planck-Institute Earth System Model (MPI-ESM) for the scenarios RCP4.5 and RCP8.5 with the regional model REMO for the time period from 1950 to 2100 to a horizontal resolution of 0.44 degree. In this study we investigate projected changes in future climate conditions over the domain towards the end of the 21st century. Focus in the analysis is given to projected changes in the temperature and rainfall characteristics and their differences for the two scenarios will be highlighted.

  20. Potential impacts of agricultural drought on crop yield variability under a changing climate in Texas

    Science.gov (United States)

    Lee, K.; Leng, G.; Huang, M.; Sheffield, J.; Zhao, G.; Gao, H.

    2017-12-01

    Texas has the largest farm area in the U.S, and its revenue from crop production ranks third overall. With the changing climate, hydrological extremes such as droughts are becoming more frequent and intensified, causing significant yield reduction in rainfed agricultural systems. The objective of this study is to investigate the potential impacts of agricultural drought on crop yields (corn, sorghum, and wheat) under a changing climate in Texas. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over 10 major Texas river basins during the historical period, is employed in this study.The model is forced by a set of statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four Representative Concentration Pathways (RCP) that represent different greenhouse gas concentration (4.5 and 8.5 w/m2 are selected in this study). To carry out the analysis, VIC simulations from 1950 to 2099 are first analyzed to investigate how the frequency and severity of agricultural droughts will be altered in Texas (under a changing climate). Second, future crop yields are projected using a statistical crop model. Third, the effects of agricultural drought on crop yields are quantitatively analyzed. The results are expected to contribute to future water resources planning, with a goal of mitigating the negative impacts of future droughts on agricultural production in Texas.

  1. RICE ice core: Black Carbon reflects climate variability at Roosevelt Island, West Antarctica

    Science.gov (United States)

    Ellis, Aja; Edwards, Ross; Bertler, Nancy; Winton, Holly; Goodwin, Ian; Neff, Peter; Tuohy, Andrea; Proemse, Bernadette; Hogan, Chad; Feiteng, Wang

    2015-04-01

    The Roosevelt Island Climate Evolution (RICE) project successfully drilled a deep ice core from Roosevelt Island during the 2011/2012 and 2012/2013 seasons. Located in the Ross Ice Shelf in West Antarctica, the site is an ideal location for investigating climate variability and the past stability of the Ross Ice Shelf. Black carbon (BC) aerosols are emitted by both biomass burning and fossil fuels, and BC particles emitted in the southern hemisphere are transported in the atmosphere and preserved in Antarctic ice. The past record of BC is expected to be sensitive to climate variability, as it is modulated by both emissions and transport. To investigate BC variability over the past 200 years, we developed a BC record from two overlapping ice cores (~1850-2012) and a high-resolution snow pit spanning 2010-2012 (cal. yr). Consistent results are found between the snow pit profiles and ice core records. Distinct decadal trends are found with respect to BC particle size, and the record indicates a steady rise in BC particle size over the last 100 years. Differences in emission sources and conditions may be a possible explanation for changes in BC size. These records also show a significant increase in BC concentration over the past decade with concentrations rising over 1.5 ppb (1.5*10^-9 ng/g), suggesting a fundamental shift in BC deposition to the site.

  2. European climate variability and human susceptibility over the past 2500 years

    Science.gov (United States)

    Buentgen, U.

    2010-09-01

    Climate variations including droughts in the western US and African Sahel, landfalls of Atlantic hurricanes, and shifts in the Asian monsoon have affected human societies throughout history mainly by modulating water supply and agricultural productivity, health risk and civil conflict. Yet, discriminations of environmental impacts from political, economical and technological drivers of societal shifts are may be hampered by the indirect effects of climate on society, but certainly by the paucity of high-resolution palaeoclimatic evidence. Here we present a tree-ring network of 7284 precipitation sensitive oak series from lower elevations in France and Germany, and a compilation of 1546 temperature responsive conifers from higher elevations in the Austrian Alps, both covering the past 2500 years. Temporal distribution of historical felling dates of construction timber refers to changes in settlement activity that mirror different stages of economic wealth. Variations in Central European summer precipitation and temperature are contrasted with societal benchmarks. Prolonged periods of generally wet and warm summers, favourable for cultural prosperity, appeared during the Roman epoch between ~200 BC and 200 AD and from ~700-1000 AD, with the latter facilitating the rapid economic, cultural and political growth of medieval Europe. Unprecedented climate variability from ~200-500 AD coincides with the demise of the Western Roman Empire and the subsequent Barbarian Migrations. This period was characterized by continental-scale political turmoil, cultural stagnation and socio-economic instability including settlement abandonment, population migration, and societal collapse. Driest and coldest summers of the Late Holocene concurred in the 6th century, during which regional consolidation began. The recent political, cultural and fiscal reluctance to adapt to and mitigate projected climate change reflects the common belief of societal insusceptibility to environmental

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

    Science.gov (United States)

    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

  4. Recognizing and exploring the right questions with climate data: An example of better understanding ENSO in climate projections

    Science.gov (United States)

    Ammann, C. M.; Brown, B.; Kalb, C. P.; Bullock, R.; Buja, L.; Gutowski, W. J., Jr.; Halley-Gotway, J.; Kaatz, L.; Yates, D. N.

    2017-12-01

    Coordinated, multi-model climate change projection archives have already led to a flourishing of new climate impact applications. Collections and online tools for the computation of derived indicators have attracted many non-specialist users and decision-makers and facilitated for them the exploration of potential future weather and climate changes on their systems. Guided by a set of standardized steps and analyses, many can now use model output and determine basic model-based changes. But because each application and decision-context is different, the question remains if such a small collection of standardized tools can faithfully and comprehensively represent the critical physical context of change? We use the example of the El Niño - Southern Oscillation, the largest and most broadly recognized mode of variability in the climate system, to explore the difference in impact contexts between a quasi-blind, protocol-bound and a flexible, scientifically guided use of climate information. More use oriented diagnostics of the model-data as well as different strategies for getting data into decision environments are explored.

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

    Science.gov (United States)

    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.

  6. Effects of Climatic Factors and Ecosystem Responses on the Inter-Annual Variability of Evapotranspiration in a Coniferous Plantation in Subtropical China

    Science.gov (United States)

    Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui

    2014-01-01

    Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003–2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003–2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May–June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation. PMID:24465610

  7. Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

    Science.gov (United States)

    Tao, F.; Rötter, R.

    2013-12-01

    Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for

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

    Science.gov (United States)

    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

  9. Long-Term Variability of Surface Albedo and Its Correlation with Climatic Variables over Antarctica

    Directory of Open Access Journals (Sweden)

    Minji Seo

    2016-11-01

    Full Text Available The cryosphere is an essential part of the earth system for understanding climate change. Components of the cryosphere, such as ice sheets and sea ice, are generally decreasing over time. However, previous studies have indicated differing trends between the Antarctic and the Arctic. The South Pole also shows internal differences in trends. These phenomena indicate the importance of continuous observation of the Polar Regions. Albedo is a main indicator for analyzing Antarctic climate change and is an important variable with regard to the radiation budget because it can provide positive feedback on polar warming and is related to net radiation and atmospheric heating in the mainly snow- and ice-covered Antarctic. Therefore, in this study, we analyzed long-term temporal and spatial variability of albedo and investigated the interrelationships between albedo and climatic variables over Antarctica. We used broadband surface albedo data from the Satellite Application Facility on Climate Monitoring and data for several climatic variables such as temperature and Antarctic oscillation index (AAO during the period of 1983 to 2009. Time series analysis and correlation analysis were performed through linear regression using albedo and climatic variables. The results of this research indicated that albedo shows two trends, west trend and an east trend, over Antarctica. Most of the western side of Antarctica showed a negative trend of albedo (about −0.0007 to −0.0015 year−1, but the other side showed a positive trend (about 0.0006 year−1. In addition, albedo and surface temperature had a negative correlation, but this relationship was weaker in west Antarctica than in east Antarctica. The correlation between albedo and AAO revealed different relationships in the two regions; west Antarctica had a negative correlation and east Antarctica showed a positive correlation. In addition, the correlation between albedo and AAO was weaker in the west. This

  10. Evolution of extreme temperature events in short term climate projection for Iberian Peninsula.

    Science.gov (United States)

    Rodriguez, Alfredo; Tarquis, Ana M.; Sanchez, Enrique; Dosio, Alessandro; Ruiz-Ramos, Margarita

    2014-05-01

    Extreme events of maximum and minimum temperatures are a main hazard for agricultural production in Iberian Peninsula. For this purpose, in this study we analyze projections of their evolution that could be valid for the next decade, represented in this study by the 30-year period 2004-2034 (target period). For this purpose two kinds of data were used in this study: 1) observations from the station network of AEMET (Spanish National Meteorological Agency) for five Spanish locations, and 2) simulated data at a resolution of 50 ×50 km horizontal grid derived from the outputs of twelve Regional Climate Models (RCMs) taken from project ENSEMBLES (van der Linden and Mitchell, 2009), with a bias correction (Dosio and Paruolo, 2011; Dosio et al., 2012) regarding the observational dataset Spain02 (Herrera et al., 2012). To validate the simulated climate, the available period of observations was compared to a baseline period (1964-1994) of simulated climate for all locations. Then, to analyze the changes for the present/very next future, probability of extreme temperature events for 2004-2034 were compared to that of the baseline period. Although only minor changes are expected, small variations in variability may have a significant impact in crop performance. The objective of the work is to evaluate the utility of these short term projections for potential users, as for instance insurance companies. References Dosio A. and Paruolo P., 2011. Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate. Journal of Geophysical Research, VOL. 116,D16106, doi:10.1029/2011JD015934 Dosio A., Paruolo P. and Rojas R., 2012. Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: Analysis of the climate change signal. Journal of Geophysical Research,Volume 117, D17, doi: 0.1029/2012JD017968 Herrera et. al. (2012) Development and Analysis of a 50 year high

  11. Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon

    Science.gov (United States)

    Waibel, Michael S.; Gannett, Marshall W.; Chang, Heejun; Hulbe, Christina L.

    2013-01-01

    We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect

  12. Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China

    Directory of Open Access Journals (Sweden)

    Z. Li

    2017-11-01

    Full Text Available Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i spatial downscaling of ESMs using a transfer function method, (ii temporal downscaling of ESMs using a single-site weather generator, and (iii reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011–2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011–2040 to 1961–2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its

  13. Interactions of Mineral Dust with Clouds, Sea Surface Temperature, and Climate Modes of Variability

    Science.gov (United States)

    DeFlorio, Michael J.

    Global climate models (GCMs) are a vital tool for ensuring the prosperity and security of modern society. They allow scientists to understand complex interactions between the air, ocean, and land, and are used by policymakers to project future changes in climate on regional and global scales. The previous generation of GCMs, represented by CMIP3 models, are shown to be deficient in their representation of precipitation over the western United States, a region that depends critically on wintertime orographically enhanced precipitation for drinking water. In addition, aerosol-cloud interactions were prescribed in CMIP3 models, which decreased the value of their representation of global aerosol, cloud, and precipitation features. This has potentially large impacts on global radiation budgets, since aerosol-cloud interactions affect the spatial extent and magnitude of clouds and precipitation. The newest suite of GCMs, the Coupled Model Intercomparison Project Phase 5 (CMIP5) models, includes state-of-the-art parameterizations of small-scale features such as aerosols, clouds, and precipitation, and is widely used by the scientific community to learn more about the climate system. The Community Earth System Model (CESM), in conjunction with observations, provides several simulations to investigate the role of aerosols, clouds, and precipitation in the climate system and how they interact with larger modes of climate variability. We show that CESM produces a realistic spatial distribution of precipitation extremes over the western U.S., and that teleconnected signals of ENSO and the Pacific Decadal Oscillation to large-scale circulation patterns and precipitation over the western U.S. are improved when compared to CCSM3. We also discover a new semi-direct effect between dust and stratocumulus clouds over the subtropical North Atlantic, whereby boundary layer inversion strength increases during the most dusty summers due to shortwave absorption of dust above the planetary

  14. Some aspects of climate variability in the north east Ethiopian ...

    African Journals Online (AJOL)

    This paper presents a review of climate variability in the northeast Ethiopian Highlands, particularly Wollo and Tigray, during the last 10000 years (the Holocene) and an analysis of rainfall variability during the historical period. To date little work has been done on climate reconstruction in Tigray and Wollo, however, ...

  15. Influence of climate variability on large rivers runoff

    Directory of Open Access Journals (Sweden)

    B. Nurtaev

    2015-06-01

    Full Text Available In accordance with IPCC Report the influence of climate change on the water cycle will increase hydrologic variability by means of changing of precipitation patterns, melting of ice and change of runoff. Precipitation has increased in high northern latitudes and decreased in southern latitudes. This study presents an analysis of river runoffs trends in different climatic zones of the world in condition of climate change.

  16. From Resistance to Receptiveness: Farmer Willingness to Participate in Extension Discussions About Climate Variability and Climate Change

    Directory of Open Access Journals (Sweden)

    David C. Diehl

    2016-10-01

    Full Text Available Identifying what Extension professionals believe are the critical elements of a communication strategy that is most likely to encourage agricultural producers to participate in discussions of climate variability and climate change is pivotal to providing timely solutions to issues facing farmers. The current study involved interviews with 50 Extension professionals from four southeastern states (Alabama, Florida, Georgia, and South Carolina who were engaged in ongoing work related to climate and agriculture. Respondents were asked to assess how best to engage farmers in conversations related to climate variability and climate change. Qualitative analysis showed that Extension professionals recommended avoiding content related to politics, attribution of climate change to human causes, and telling farmers what to do. Respondents recommended emphasizing adaptation strategies, climate variability over climate change, evidence that climate change exists, and the financial benefits for farmers. In addition, Extension professionals proposed several delivery methods they thought would be most effective with farmers, including delivery tailored to the characteristics of the audience, a positive overall tone, and an understanding that engagement should be viewed as a long-term process based on building relationships with farmers. The findings suggest that farmers are a potentially receptive audience on climate issues when properly approached.

  17. Cocoa farming households' vulnerability to climate variability in Ekiti ...

    African Journals Online (AJOL)

    BRO OKOJIE

    and protocols that control climate variability and change. Keywords: ... internal processes within the climate system. (internal ... adverse effects on the agricultural sector of the ... information and technology, social capital, ... Not accounting for.

  18. Climate variability, farmland value, and farmers’ perceptions of climate change

    NARCIS (Netherlands)

    Arshad, Muhammad; Kächele, Harald; Krupnik, Timothy J.; Amjath-Babu, T.S.; Aravindakshan, Sreejith; Abbas, Azhar; Mehmood, Yasir; Müller, Klaus

    2017-01-01

    Many studies have examined the impact of climatic variability on agricultural productivity, although an understanding of these effects on farmland values and their relationship to farmers’ decisions to adapt and modify their land-use practices remains nascent in developing nations. We estimated

  19. The effects of solar variability on climate

    International Nuclear Information System (INIS)

    Hoffert, M.I.

    1990-01-01

    It has been hypothesized for at least a century that some of the observed variance in global temperature records arises from variations in solar output. Theories of solar-variability effects on climate could not be tested directly prior to satellite measurements because uncertainties in ground-based measurements of solar irradiance were larger than the solar variations themselves. Measurements by the Active Cavity Radiometer (ACRIM) onboard the Solar Max satellite and by the Earth Radiation Budget (ERB) instrument onboard Nimbus 6 are now available which indicate solar-constant variations are positively correlated with solar activity over an 11-yr solar cycle, and are of order ± 1.0 W m -2 relative to a mean solar constant of S 0 = 1,367 W m -2 , ΔS/S 0 ∼ ± 0.07%. For a typical climate sensitivity parameter of β = S 0 ∂T/∂S ∼ 100 C, the corresponding variations in radiative equilibrium temperature at the Earth's surface are ΔT e ∼ ± 0.07 C. The realized temperature variations from solar forcing, ΔT, can be significantly smaller because of thermal damping by the ocean. The author considers effects of solar variability on the observed and projected history of the global temperature record in light of this data using an upwelling-diffusion ocean model to assess the effect of ocean thermal inertia on the thermal response. The response to harmonic variations of the 11-yr sunspot cycle is of order ΔT ∼ ± 0.02 C, though the coupling between response and forcing is stronger for long-term variations in the envelope of the solar cycle which more nearly match the thermal response time of the deep ocean

  20. Climate change and future wildfire in the western USA: what model projections do and don't tell us

    Science.gov (United States)

    Littell, J. S.; McKenzie, D.; Cushman, S. A.; Wan, H. Y.

    2017-12-01

    We developed statistical climate-fire models describing area burned for 70 ecosections in the western U.S. Historically, these ecosections collectively represent a gradient of climate-fire relationships from purely fuel limited (characterized by antecedent positive water balance anomalies and/or negative energy balance anomalies) to purely flammability limited (characterized by antecedent negative water balance anomalies and/or positive energy balance anomalies). Sixty-eight ecosection linear models included significant climate predictors, and 56 ecosections satisfied regression diagnostics, yielding acceptable climate-fire models. There is considerable diversity in seasonality, dominant variables, and prevalence of lagged climatic terms in the climate-fire regression models, indicating variation in mechanisms of climate-fire linkages across ecosystems. This diversity, however, is not random - there is a clear pattern in the fuzzy set membership of the relative dominance of regression predictor variables. This pattern defines a fuel-flammability gradient of limitations, with a tendency toward warm season drought on the flammability end and a tendency toward antecedent moisture on the fuel end. Projected area burned under a multi-model composite future climate scenarios varies, with increasing area burned in 41 ecosections in the West by 2030-2059 (median 132% among 10 purely flammability limited ecosections, median 240% among 25 flammability limited systems with a fuel limitation component, and median 43% among 6 systems with equal control) but decreasing (median -119% among 13 fuel limited systems with a flammability component). For the period 2070-2099, the projected area burned increases much more in the flammability (769%) and flammability-fuel hybrid (442%) systems than those with joint control (139%), and continues to decrease (-178%) in fuel-flammability hybrid systems. Filtering the projected results with fire rotation limits projections biased high by the

  1. Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections

    Science.gov (United States)

    Aryal, Anil; Shrestha, Sangam; Babel, Mukand S.

    2018-01-01

    The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by - 2.15% under RCP 4.5 and - 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and

  2. Hydrological Responses of Andean Lakes and Tropical Floodplains to Climate Variability and Human Intervention: an Integrative Modelling Framework

    Science.gov (United States)

    Hoyos, I. C.; González Morales, C.; Serna López, J. P.; Duque, C. L.; Canon Barriga, J. E.; Dominguez, F.

    2013-12-01

    Andean water bodies in tropical regions are significantly influenced by fluctuations associated with climatic and anthropogenic drivers, which implies long term changes in mountain snow peaks, land covers and ecosystems, among others. Our work aims at providing an integrative framework to realistically assess the possible future of natural water bodies with different degrees of human intervention. We are studying in particular the evolution of three water bodies in Colombia: two Andean lakes and a floodplain wetland. These natural reservoirs represent the accumulated effect of hydrological processes in their respective basins, which exhibit different patterns of climate variability and distinct human intervention and environmental histories. Modelling the hydrological responses of these local water bodies to climate variability and human intervention require an understanding of the strong linkage between geophysical and social factors. From the geophysical perspective, the challenge is how to downscale global climate projections in the local context: complex orography and relative lack of data. To overcome this challenge we combine the correlational and physically based analysis of several sources of spatially distributed biophysical and meteorological information to accurately determine aspects such as moisture sources and sinks and past, present and future local precipitation and temperature regimes. From the social perspective, the challenge is how to adequately represent and incorporate into the models the likely response of social agents whose water-related interests are diverse and usually conflictive. To deal with the complexity of these systems we develop interaction matrices, which are useful tools to holistically discuss and represent each environment as a complex system. Our goal is to assess partially the uncertainties of the hydrological balances in these intervened water bodies we establish climate/social scenarios, using hybrid models that combine

  3. Downscaling CESM1 climate change projections for the MENA-CORDEX domain using WRF

    Science.gov (United States)

    Zittis, George; Hadjinicolaou, Panos; Lelieveld, Jos

    2017-04-01

    According to analysis of observations and global climate model projections, the broader Middle East, North Africa and Mediterranean region is found to be a climate change hotspot. Substantial changes in precipitation amounts and patterns and strong summer warming (including an intensification of heat extremes) is a likely future scenario for the region, but a recent uncertainty analysis indicated good model agreement for temperature but much less for precipitation. Although the horizontal resolution of global models has increased over the last years, it is still not adequate for impact and adaptation assessments of regional or national level and further downscaling of the climate information is required. The region is now studied within the CORDEX initiative (Coordinated Regional Climate Downscaling Experiment) with the establishment of a domain covering the Middle East - North Africa (MENA-CORDEX) region (http://mena-cordex.cyi.ac.cy/). In this study, we present the first climate change projections for the MENA produced by dynamically downscaling a bias-corrected output of the CESM1 global earth system model. For the downscaling, we use a climate configuration of the Weather, Research and Forecasting model (WRF). Our simulations use a standard CORDEX Phase I 50-km grid in three simulations, a historical (1950-2005) and two scenario runs (2006-2100) with the greenhouse gas forcing following the RCP 4.5 and 8.5. We evaluate precipitation, temperature and other surface meteorological variables from the historical using gridded and station observational datasets. Maps of projected changes are constructed for different periods in the future as differences of the two scenarios model output against the data from the historical run. The main spatial and temporal patterns of change are discussed, especially in the context of the United Nations Framework Convention on Climate Change agreement in Paris to limit the global average temperature increase to 1.5 degrees above pre

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

    Directory of Open Access Journals (Sweden)

    Ploubidis George B

    2011-05-01

    Full Text Available Abstract 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

  5. Robustness of Ensemble Climate Projections Analyzed with Climate Signal Maps: Seasonal and Extreme Precipitation for Germany

    Directory of Open Access Journals (Sweden)

    Susanne Pfeifer

    2015-05-01

    Full Text Available Climate signal maps can be used to identify regions where robust climate changes can be derived from an ensemble of climate change simulations. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Climate signal maps do not show all information available from the model ensemble, but give a condensed view in order to be useful for non-climate scientists who have to assess climate change impact during the course of their work. Three different ensembles of regional climate projections have been analyzed regarding changes of seasonal mean and extreme precipitation (defined as the number of days exceeding the 95th percentile threshold of daily precipitation for Germany, using climate signal maps. Although the models used and the scenario assumptions differ for the three ensembles (representative concentration pathway (RCP 4.5 vs. RCP8.5 vs. A1B, some similarities in the projections of future seasonal and extreme precipitation can be seen. For the winter season, both mean and extreme precipitation are projected to increase. The strength, robustness and regional pattern of this increase, however, depends on the ensemble. For summer, a robust decrease of mean precipitation can be detected only for small regions in southwestern Germany and only from two of the three ensembles, whereas none of them projects a robust increase of summer extreme precipitation.

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

    Science.gov (United States)

    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. Near term climate projections for invasive species distributions

    Science.gov (United States)

    Jarnevich, C.S.; Stohlgren, T.J.

    2009-01-01

    Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas. ?? 2008 Springer Science+Business Media B.V.

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

    Science.gov (United States)

    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.

  9. Impacts of Present and Future Climate Change and Climate Variability on Agriculture in the Temperate Regions. North America

    International Nuclear Information System (INIS)

    Motha, Raymond P.; Baier, W.

    2005-01-01

    The potential impact of climate variability and climate change on agricultural production in the United States and Canada varies generally by latitude. Largest reductions are projected in southern crop areas due to increased temperatures and reduced water availability. A longer growing season and projected increases in CO2 may enhance crop yields in northern growing areas. Major factors in these scenarios analyzes are increased drought tendencies and more extreme weather events, both of which are detrimental to agriculture. Increasing competition for water between agriculture and non-agricultural users also focuses attention on water management issues. Agriculture also has impact on the greenhouse gas balance. Forests and soils are natural sinks for CO2. Removal of forests and changes in land use, associated with the conversion from rural to urban domains, alters these natural sinks. Agricultural livestock and rice cultivation are leading contributors to methane emission into the atmosphere. The application of fertilizers is also a significant contributor to nitrous oxide emission into the atmosphere. Thus, efficient management strategies in agriculture can play an important role in managing the sources and sinks of greenhouse gases. Forest and land management can be effective tools in mitigating the greenhouse effect

  10. Storm-tracks interannual variability and large-scale climate modes

    Science.gov (United States)

    Liberato, Margarida L. R.; Trigo, Isabel F.; Trigo, Ricardo M.

    2013-04-01

    In this study we focus on the interannual variability and observed changes in northern hemisphere mid-latitude storm-tracks and relate them to large scale atmospheric circulation variability modes. Extratropical storminess, cyclones dominant paths, frequency and intensity have long been the object of climatological studies. The analysis of storm characteristics and historical trends presented here is based on the cyclone detecting and tracking algorithm first developed for the Mediterranean region (Trigo et al. 1999) and recently extended to a larger Euro-Atlantic region (Trigo 2006). The objective methodology, which identifies and follows individual lows as minima in SLP fields, fulfilling a set of conditions regarding the central pressure and the pressure gradient, is applied to the northern hemisphere 6-hourly geopotential data at 1000 hPa from the 20th Century Reanalyses (20CRv2) project and from reanalyses datasets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF): ERA-40 and ERA Interim reanalyses. First, we assess the interannual variability and cyclone frequency trends for each of the datasets, for the 20th century and for the period between 1958 and 2002 using the highest spatial resolution available (1.125° x 1.125°) from the ERA-40 data. Results show that winter variability of storm paths, cyclone frequency and travel times is in agreement with the reported variability in a number of large-scale climate patterns (including the North Atlantic Oscillation, the East Atlantic Pattern and the Scandinavian Pattern). In addition, three storm-track databases are built spanning the common available extended winter seasons from October 1979 to March 2002. Although relatively short, this common period allows a comparison of systems represented in reanalyses datasets with distinct horizontal resolutions. This exercise is mostly focused on the key areas of cyclogenesis and cyclolysis and main cyclone characteristics over the northern

  11. Impacts of Climate Variability on Latin American Small-scale Fisheries

    Directory of Open Access Journals (Sweden)

    Omar Defeo

    2013-12-01

    Full Text Available Small-scale fisheries (SSFs are social-ecological systems that play a critical role in terms of food security and poverty alleviation in Latin America. These fisheries are increasingly threatened by anthropogenic and climatic drivers acting at multiple scales. We review the effects of climate variability on Latin American SSFs, and discuss the combined effects of two additional human drivers: globalization of markets and governance. We show drastic long-term and large-scale effects of climate variability, e.g., sea surface temperature anomalies, wind intensity, sea level, and climatic indices, on SSFs. These variables, acting in concert with economic drivers, have exacerbated stock depletion rates in Latin American SSFs. The impact of these drivers varied according to the life cycle and latitudinal distribution of the target species, the characteristics of the oceanographic systems, and the inherent features of the social systems. Our review highlights the urgent need to improve management and governance systems to promote resilience as a way to cope with the increasing uncertainty about the impacts of climate and globalization of markets on Latin American SSFs.

  12. Projected response of an endangered marine turtle population to climate change

    Science.gov (United States)

    Saba, Vincent S.; Stock, Charles A.; Spotila, James R.; Paladino, Frank V.; Tomillo, Pilar Santidrián

    2012-11-01

    Assessing the potential impacts of climate change on individual species and populations is essential for the stewardship of ecosystems and biodiversity. Critically endangered leatherback turtles in the eastern Pacific Ocean are excellent candidates for such an assessment because their sensitivity to contemporary climate variability has been substantially studied. If incidental fisheries mortality is eliminated, this population still faces the challenge of recovery in a rapidly changing climate. Here we combined an Earth system model, climate model projections assessed by the Intergovernmental Panel on Climate Change and a population dynamics model to estimate a 7% per decade decline in the Costa Rica nesting population over the twenty-first century. Whereas changes in ocean conditions had a small effect on the population, the ~2.5°C warming of the nesting beach was the primary driver of the decline through reduced hatching success and hatchling emergence rate. Hatchling sex ratio did not substantially change. Adjusting nesting phenology or changing nesting sites may not entirely prevent the decline, but could offset the decline rate. However, if future observations show a long-term decline in hatching success and emergence rate, anthropogenic climate mitigation of nests (for example, shading, irrigation) may be able to preserve the nesting population.

  13. A New High Resolution Climate Dataset for Climate Change Impacts Assessments in New England

    Science.gov (United States)

    Komurcu, M.; Huber, M.

    2016-12-01

    Assessing regional impacts of climate change (such as changes in extreme events, land surface hydrology, water resources, energy, ecosystems and economy) requires much higher resolution climate variables than those available from global model projections. While it is possible to run global models in higher resolution, the high computational cost associated with these simulations prevent their use in such manner. To alleviate this problem, dynamical downscaling offers a method to deliver higher resolution climate variables. As part of an NSF EPSCoR funded interdisciplinary effort to assess climate change impacts on New Hampshire ecosystems, hydrology and economy (the New Hampshire Ecosystems and Society project), we create a unique high-resolution climate dataset for New England. We dynamically downscale global model projections under a high impact emissions scenario using the Weather Research and Forecasting model (WRF) with three nested grids of 27, 9 and 3 km horizontal resolution with the highest resolution innermost grid focusing over New England. We prefer dynamical downscaling over other methods such as statistical downscaling because it employs physical equations to progressively simulate climate variables as atmospheric processes interact with surface processes, emissions, radiation, clouds, precipitation and other model components, hence eliminates fix relationships between variables. In addition to simulating mean changes in regional climate, dynamical downscaling also allows for the simulation of climate extremes that significantly alter climate change impacts. We simulate three time slices: 2006-2015, 2040-2060 and 2080-2100. This new high-resolution climate dataset (with more than 200 variables saved in hourly (six hourly) intervals for the highest resolution domain (outer two domains)) along with model input and restart files used in our WRF simulations will be publicly available for use to the broader scientific community to support in-depth climate

  14. Assessing potential impacts of climate change on hydropower generation of three reservoirs in the Tagus River Basin under ensemble of climate projections

    Science.gov (United States)

    Lobanova, Anastasia; Koch, Hagen; Hattermann, Fred F.; Krysanova, Valentina

    2015-04-01

    The Tagus River basin is an important strategic water and energy source for Portugal and Spain. With an extensive network of 40 reservoirs with more than 15 hm3 capacity and numerous abstraction channels it is ensuring water supply for domestic and industrial usage, irrigation and hydropower production in Spain and Portugal. Growing electricity and water supply demands, over-regulation and construction of new dams, and large inter-basin water transfers aggravated by strong natural variability of climate and aridity of the catchment have already imposed significant pressures on the river. The substantial reduction of discharge, dropping during some months to zero in some parts of the catchment, is observed already now, and projected climatic change is expected to alter the water budget of the catchment further. As the water inflow is a fundamental defining factor in a reservoir operation and hydropower production, the latter are highly sensitive to shifts in water balance of the catchment, and hence to changes in climate. In this study we aim to investigate the effects of projected climate change on water inflows and hydropower generation of the three large reservoirs in the Tagus River Basin, and by that to assess their ability to cover electricity power demands and provide water supply under changed conditions, assuming present management strategies; hydropower and abstraction demands. The catchment scale, process-based eco-hydrological model SWIM was set up, calibrated and validated up to the Santarem gauge at the Tagus outlet, with the implementation of a reservoir module. The reservoir module is able to represent three reservoir operation management options, simulate water abstraction and provide rates of generated hydropower. In total, fifteen largest reservoirs in the Tagus River Basin were included in the model, calibrated and validated against observed inflow, stored water and outflow water volumes. The future climate projections were selected from the

  15. Analysis of the Relationship Between Climate and NDVI Variability at Global Scales

    Science.gov (United States)

    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

  16. Impacts of the Three Gorges Project on Local Climate

    Science.gov (United States)

    Song, Z.; Liang, S.; Feng, L.

    2015-12-01

    Three Gorges Project (TGP) is the largest hydroelectric project in the world and has led to significant land cover changes in Three Gorges Reservoir Area (TGRA). Since its construction the debates on its environmental and climatic impacts have never stopped, especially after the extreme drought and flood in Yangtze River Basin these years. TGP reached its final impounding water level in 2010. However, studies on systematically monitoring the long-term variations in surface and atmospheric parameters in TGRA are still lacking. In this study, three important surface parameters - surface albedo, land surface temperature (LST) and evapotranspiration (ET) and two climatic parameters - air temperature and precipitation were investigated from 2000 to 2013 by combining multiple remote sensing data and ground measurements. Results showed that along the reservoir albedo decreased significantly as a result of water impounding. Correspondingly, in the same region daytime LST decreased in spring and summer and nighttime LST increased in autumn and winter. In the western region of TGRA, albedo increased due to resettlement and LST also changed. The average ET increased by 20% in TGR but kept stable in the whole TGRA. In contrast to LST, air temperature showed less apparent spatial and temporal variability. Only in the region near the dam air temperature experienced a decrease at daytime and an increase at nighttime. Further analysis demonstrated precipitation revealed no apparent changes in TGRA and the precipitation anomaly in northwest of TGRA may not be connected with TGP. All of the findings provide a more substantial clues of local climate change caused by TGP.

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

    Science.gov (United States)

    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.

  18. Assessing the Impact of Climatic Variability and Change on Maize Production in the Midwestern USA

    Science.gov (United States)

    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.

  19. A modelling methodology for assessing the impact of climate variability and climatic change on hydroelectric generation

    International Nuclear Information System (INIS)

    Munoz, J.R.; Sailor, D.J.

    1998-01-01

    A new methodology relating basic climatic variables to hydroelectric generation was developed. The methodology can be implemented in large or small basins with any number of hydro plants. The method was applied to the Sacramento, Eel and Russian river basins in northern California where more than 100 hydroelectric plants are located. The final model predicts the availability of hydroelectric generation for the entire basin provided present and near past climate conditions, with about 90% accuracy. The results can be used for water management purposes or for analyzing the effect of climate variability on hydrogeneration availability in the basin. A wide range of results can be obtained depending on the climate change scenario used. (Author)

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

    Science.gov (United States)

    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.

  1. Climate variability and yields of major staple food crops in Northern ...

    African Journals Online (AJOL)

    Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we ...

  2. Atmospheric radiative feedbacks associated with transient climate change and climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Colman, Robert A.; Power, Scott B. [Bureau of Meteorology, Centre for Australian Weather and Climate Research, GPO Box 1289, Melbourne, VIC (Australia)

    2010-06-15

    to mid-latitude response seen under secular climate change. Surface albedo feedback is, however, slightly stronger under interannual variability - partly due to regions of extremely weak, or even negative, feedback over Antarctic sea ice in the transient experiment. Both long and shortwave global cloud feedbacks are essentially zero on interannual timescales, with the shortwave term also being very weak under climate change, although cloud fraction and optical property components show correlation with global temperature both under interannual variability and transient climate change. The results of this modelling study, although for a single model only, suggest that the analogues provided by interannual variability may provide some useful pointers to some aspects of climate change feedback strength, particularly for water vapour and surface albedo, but that structural differences will need to be heeded in such an analysis. (orig.)

  3. Changes in the world rivers' discharge projected from an updated high resolution dataset of current and future climate zones

    Science.gov (United States)

    Santini, Monia; di Paola, Arianna

    2015-12-01

    In this paper, an updated global map of the current climate zoning and of its projections, according to the Köppen-Geiger classification, is first provided. The map at high horizontal resolution (0.5° × 0.5°), representative of the current (i.e. 1961-2005) conditions, is based on the Climate Research Unit dataset holding gridded series of historical observed temperature and precipitation, while projected conditions rely on the simulated series, for the same variables, by the General Circulation Model CMCC-CM. Modeled variables were corrected for their bias and then projections of climate zoning were generated for the medium term (2006-2050) and long term (2056-2100) future periods, under RCP 4.5 and RCP 8.5 emission scenarios. Results show that Equatorial and Arid climates will spread at the expenses of Snow and Polar climates, with the Warm Temperate experiencing more moderate increase. Maps of climate zones are valuable for a wide range of studies on climate change and its impacts, especially those regarding the water cycle that is strongly regulated by the combined conditions of precipitation and temperature. As example of large scale hydrological applications, in this work we tested and implemented a spatial statistical procedure, the geographically weighted regression among climate zones' surface and mean annual discharge (MAD) at hydrographic basin level, to quantify likely changes in MAD for the main world rivers monitored through the Global Runoff Data Center database. The selected river basins are representative of more than half of both global superficial freshwater resources and world's land area. Globally, a decrease in MAD is projected both in the medium term and long term, while spatial differences highlight how some areas require efforts to avoid consequences of amplified water scarcity, while other areas call for strategies to take the opportunity from the expected increase in water availability. Also the fluctuations of trends between the

  4. Incorporating climate change projections into riparian restoration planning and design

    Science.gov (United States)

    Perry, Laura G.; Reynolds, Lindsay V.; Beechie, Timothy J.; Collins, Mathias J.; Shafroth, Patrick B.

    2015-01-01

    Climate change and associated changes in streamflow may alter riparian habitats substantially in coming decades. Riparian restoration provides opportunities to respond proactively to projected climate change effects, increase riparian ecosystem resilience to climate change, and simultaneously address effects of both climate change and other human disturbances. However, climate change may alter which restoration methods are most effective and which restoration goals can be achieved. Incorporating climate change into riparian restoration planning and design is critical to long-term restoration of desired community composition and ecosystem services. In this review, we discuss and provide examples of how climate change might be incorporated into restoration planning at the key stages of assessing the project context, establishing restoration goals and design criteria, evaluating design alternatives, and monitoring restoration outcomes. Restoration planners have access to numerous tools to predict future climate, streamflow, and riparian ecology at restoration sites. Planners can use those predictions to assess which species or ecosystem services will be most vulnerable under future conditions, and which sites will be most suitable for restoration. To accommodate future climate and streamflow change, planners may need to adjust methods for planting, invasive species control, channel and floodplain reconstruction, and water management. Given the considerable uncertainty in future climate and streamflow projections, riparian ecological responses, and effects on restoration outcomes, planners will need to consider multiple potential future scenarios, implement a variety of restoration methods, design projects with flexibility to adjust to future conditions, and plan to respond adaptively to unexpected change.

  5. Climate variability: Possible changes with climate change and impacts on crop yields

    International Nuclear Information System (INIS)

    Mearns, L.O.

    1991-01-01

    A pilot study was carried out of the sensitivity of the CERES wheat model, a deterministic crop-climate model, to changes in the interannual variability of temperature and precipitation. The study was designed to determine the effect of changed temperature variance on the mean and variance of the simulated yields, to compare the effect with the effect of mean temperature changes, and to determine the interacting effects of changes in mean and variance of temperature. The CERES model was applied to 29 cropping years (1952-1980), using three different soil types and two different management practices (fully irrigated and dryland). The coefficients of variation of the yields for irrigated and dryland conditions are plotted against variance change. It was found that in both management systems, the yield response is usually greater to increases rather than decreases in variance. The combined effect of mean and variance temperature changes are most striking under irrigated conditions, with a dramatic decrease in yield variability in the high mean climate change scenario with decreased temperature variance. This suggests that the variability decrease might mitigate the effect of a mean increase in temperature. This result is not found with the dryland case, where decreased temperature variability has little impact on yield variability. 12 refs., 4 figs

  6. Nature Relation Between Climatic Variables and Cotton Production

    Directory of Open Access Journals (Sweden)

    Zakaria M. Sawan

    2014-08-01

    Full Text Available This study investigated the effect of climatic variables on flower and boll production and retention in cotton (Gossypium barbadense. Also, this study investigated the relationship between climatic factors and production of flowers and bolls obtained during the development periods of the flowering and boll stage, and to determine the most representative period corresponding to the overall crop pattern. Evaporation, sunshine duration, relative humidity, surface soil temperature at 1800 h, and maximum air temperature, are the important climatic factors that significantly affect flower and boll production. The least important variables were found to be surface soil temperature at 0600 h and minimum temperature. There was a negative correlation between flower and boll production and either evaporation or sunshine duration, while that correlation with minimum relative humidity was positive. Higher minimum relative humidity, short period of sunshine duration, and low temperatures enhanced flower and boll formation.

  7. THE INFLUENCE OF EUROPEAN CLIMATE VARIABILITY MECHANISM ON AIR TEMPERATURE IN ROMANIA

    Directory of Open Access Journals (Sweden)

    M. MATEI

    2013-03-01

    Full Text Available The main objective of the present paper is to analyze the temporal and spatial variability of air-temperature in Romania, by using mean air-temperature values provided by the ECA&D project (http://eca.knmi.nl/. These data sets will be filtered by means of the EOF (Empirical Orthogonal Function analysis, which describes various modes of space variability and time coefficient series (PC series. The EOF analysis will also be used to identify the main way of action of the European climate variability mechanism, by using multiple variables in grid points, provided by the National Centre of Atmospheric Research (NCAR, USA. The variables considered here are: sea level pressure (SLP, geopotential height at 500 mb (H500 and air temperature at 850 mb (T850, for the summer and winter seasons. The linear trends and shift points of considered variables are then assessed by means of the Mann-Kendall and Pettitt non-parametric tests. By interpreting the results, we can infer that there is causal relationship between the large-scale analyzed parameters and temperature variability in Romania. These results are consistent with those presented by Busuioc et al., 2010, where the main variation trends of the principal European variables are shown.

  8. Global Climate Change Pilot Course Project

    Science.gov (United States)

    Schuenemann, K. C.; Wagner, R.

    2011-12-01

    In fall 2011 a pilot course on "Global Climate Change" is being offered, which has been proposed to educate urban, diverse, undergraduate students about climate change at the introductory level. The course has been approved to fulfill two general college requirements, a natural sciences requirement that focuses on the scientific method, as well as a global diversity requirement. This course presents the science behind global climate change from an Earth systems and atmospheric science perspective. These concepts then provide the basis to explore the effect of global warming on regions throughout the world. Climate change has been taught as a sub-topic in other courses in the past solely using scientific concepts, with little success in altering the climate change misconceptions of the students. This pilot course will see if new, innovative projects described below can make more of an impact on the students' views of climate change. Results of the successes or failures of these projects will be reported, as well as results of a pre- and post-course questionnaire on climate change given to students taking the course. Students in the class will pair off and choose a global region or country that they will research, write papers on, and then represent in four class discussions spaced throughout the semester. The first report will include details on the current climate of their region and how the climate shapes that region's society and culture. The second report will discuss how that region is contributing to climate change and/or sequestering greenhouse gases. Thirdly, students will discuss observed and predicted changes in that region's climate and what impact it has had, and could have, on their society. Lastly, students will report on what role their region has played in mitigating climate change, any policies their region may have implemented, and how their region can or cannot adapt to future climate changes. They will also try to get a feel for the region

  9. Vulnerability and adaptation to climate variability and change in smallholder farming systems in Zimbabwe

    NARCIS (Netherlands)

    Rurinda, J.

    2014-01-01

    Keywords: Climate change; Increased climate variability; Vulnerability; Smallholder farmers; Adaptation

    Climate change and increased climate variability are currently seen as the major constraints to the already stressed smallholder farming livelihood system in

  10. Potential impacts of climate change and variability on groundwater ...

    African Journals Online (AJOL)

    Potential impacts of climate change and variability on groundwater resources in Nigeria. ... African Journal of Environmental Science and Technology ... of climate change induced groundwater impacts due to largely multi-scale local and regional heterogeneity, there is need to evaluate groundwater resources, quality and ...

  11. Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide—a synthesis

    Science.gov (United States)

    Krysanova, Valentina; Vetter, Tobias; Eisner, Stephanie; Huang, Shaochun; Pechlivanidis, Ilias; Strauch, Michael; Gelfan, Alexander; Kumar, Rohini; Aich, Valentin; Arheimer, Berit; Chamorro, Alejandro; van Griensven, Ann; Kundu, Dipangkar; Lobanova, Anastasia; Mishra, Vimal; Plötner, Stefan; Reinhardt, Julia; Seidou, Ousmane; Wang, Xiaoyan; Wortmann, Michel; Zeng, Xiaofan; Hattermann, Fred F.

    2017-10-01

    An intercomparison of climate change impacts projected by nine regional-scale hydrological models for 12 large river basins on all continents was performed, and sources of uncertainty were quantified in the framework of the ISIMIP project. The models ECOMAG, HBV, HYMOD, HYPE, mHM, SWAT, SWIM, VIC and WaterGAP3 were applied in the following basins: Rhine and Tagus in Europe, Niger and Blue Nile in Africa, Ganges, Lena, Upper Yellow and Upper Yangtze in Asia, Upper Mississippi, MacKenzie and Upper Amazon in America, and Darling in Australia. The model calibration and validation was done using WATCH climate data for the period 1971-2000. The results, evaluated with 14 criteria, are mostly satisfactory, except for the low flow. Climate change impacts were analyzed using projections from five global climate models under four representative concentration pathways. Trends in the period 2070-2099 in relation to the reference period 1975-2004 were evaluated for three variables: the long-term mean annual flow and high and low flow percentiles Q 10 and Q 90, as well as for flows in three months high- and low-flow periods denoted as HF and LF. For three river basins: the Lena, MacKenzie and Tagus strong trends in all five variables were found (except for Q 10 in the MacKenzie); trends with moderate certainty for three to five variables were confirmed for the Rhine, Ganges and Upper Mississippi; and increases in HF and LF were found for the Upper Amazon, Upper Yangtze and Upper Yellow. The analysis of projected streamflow seasonality demonstrated increasing streamflow volumes during the high-flow period in four basins influenced by monsoonal precipitation (Ganges, Upper Amazon, Upper Yangtze and Upper Yellow), an amplification of the snowmelt flood peaks in the Lena and MacKenzie, and a substantial decrease of discharge in the Tagus (all months). The overall average fractions of uncertainty for the annual mean flow projections in the multi-model ensemble applied for all basins

  12. A Comprehensive Hydrologic Projections Resource to support Climate Change Vulnerability Assessments in the Western U.S

    Science.gov (United States)

    Brekke, L. D.; Pruitt, T.; Gangopadhyay, S.; Raff, D. A.

    2010-12-01

    The SECURE Water Act § 9503(b)(2) authorizes the U.S. Department of Interior's Bureau of Reclamation to assess climate change risks for water and environmental resources in eight "major Reclamation river basins" in the Western United States (i.e. Colorado, Columbia, Klamath, Missouri, Rio Grande, Sacramento, San Joaquin, and Truckee basins). The legislation calls for Reclamation to provide periodic reports on implications for water supplies, water deliveries, hydropower generation, fish and wildlife, water quality, flood control, ecological resiliency, and recreation. Reclamation's is developing a framework for consistently characterizing risks in Western U.S. river basins through the West-Wide Climate Risk Assessments, part of the Basin Study Program. One initial activity within this framework is focused on characterizing hydrologic and water supply implications of climate change. The centerpiece of this activity is the development of a west-wide ensemble of hydrologic projections, tiering from information in the online archive "Bias Corrected and Downscaled WCRP CMIP3 Climate Projections" (http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/dcpInterface.html) and utilizing a network of hydrologic model applications featured in the University of Washington and Princeton University's "Experimental National Hydrologic Prediction System" (http://www.hydro.washington.edu/forecast/westwide/index.shtml). The resulting hydrologic information has the same space and time attributes as the underlying downscaled climate information: 112 projections of monthly downscaled CMIP3 conditions from 1950-2099 at 1/8° resolution over the Western U.S. (nested within the underlying archive’s contiguous U.S. domain). Such attributes permit a time evolving risk-based portrayal of hydrologic conditions, which is useful for climate change adaptation discussions where the timing of impacts matters in relation the initiation and investment of adaptation or mitigation measures

  13. Potential impacts of projected climate change on vegetation management in Hawai`i Volcanoes National Park

    Science.gov (United States)

    Camp, Richard J.; Loh, Rhonda; Berkowitz, S. Paul; Brinck, Kevin W.; Jacobi, James D.; Price, Jonathan; McDaniel, Sierra; Fortini, Lucas B.

    2018-01-01

    Climate change will likely alter the seasonal and annual patterns of rainfall and temperature in Hawai`i. This is a major concern for resource managers at Hawai`i Volcanoes National Park where intensely managed Special Ecological Areas (SEAs), focal sites for managing rare and endangered plants, may no longer provide suitable habitat under future climate. Expanding invasive species’ distributions also may pose a threat to areas where native plants currently predominate. We combine recent climate modeling efforts for the state of Hawai`i with plant species distribution models to forecast changes in biodiversity in SEAs under future climate conditions. Based on this bioclimatic envelope model, we generated projected species range maps for four snapshots in time (2000, 2040, 2070, and 2090) to assess whether the range of 39 native and invasive species of management interest are expected to contract, expand, or remain the same under a moderately warmer and more variable precipitation scenario. Approximately two-thirds of the modeled native species were projected to contract in range, while one-third were shown to increase. Most of the park’s SEAs were projected to lose a majority of the native species modeled. Nine of the 10 modeled invasive species were projected to contract within the park; this trend occurred in most SEAs, including those at low, middle, and high elevations. There was good congruence in the current (2000) distribution of species richness and SEA configuration; however, the congruence between species richness hotspots and SEAs diminished by the end of this century. Over time the projected species-rich hotspots increasingly occurred outside of current SEA boundaries. Our research brought together managers and scientists to increase understanding of potential climate change impacts, and provide needed information to address how plants may respond under future conditions relative to current managed areas.

  14. Effect of climatic variability on malaria trends in Baringo County, Kenya.

    Science.gov (United States)

    Kipruto, Edwin K; Ochieng, Alfred O; Anyona, Douglas N; Mbalanya, Macrae; Mutua, Edna N; Onguru, Daniel; Nyamongo, Isaac K; Estambale, Benson B A

    2017-05-25

    Malaria transmission in arid and semi-arid regions of Kenya such as Baringo County, is seasonal and often influenced by climatic factors. Unravelling the relationship between climate variables and malaria transmission dynamics is therefore instrumental in developing effective malaria control strategies. The main aim of this study was to describe the effects of variability of rainfall, maximum temperature and vegetation indices on seasonal trends of malaria in selected health facilities within Baringo County, Kenya. Climate variables sourced from the International Research Institute (IRI)/Lamont-Doherty Earth Observatory (LDEO) climate database and malaria cases reported in 10 health facilities spread across four ecological zones (riverine, lowland, mid-altitude and highland) between 2004 and 2014 were subjected to a time series analysis. A negative binomial regression model with lagged climate variables was used to model long-term monthly malaria cases. The seasonal Mann-Kendall trend test was then used to detect overall monotonic trends in malaria cases. Malaria cases increased significantly in the highland and midland zones over the study period. Changes in malaria prevalence corresponded to variations in rainfall and maximum temperature. Rainfall at a time lag of 2 months resulted in an increase in malaria transmission across the four zones while an increase in temperature at time lags of 0 and 1 month resulted in an increase in malaria cases in the riverine and highland zones, respectively. Given the existence of a time lag between climatic variables more so rainfall and peak malaria transmission, appropriate control measures can be initiated at the onset of short and after long rains seasons.

  15. Expected impacts of climate change on extreme climate events

    International Nuclear Information System (INIS)

    Planton, S.; Deque, M.; Chauvin, F.; Terray, L.

    2008-01-01

    An overview of the expected change of climate extremes during this century due to greenhouse gases and aerosol anthropogenic emissions is presented. The most commonly used methodologies rely on the dynamical or statistical down-scaling of climate projections, performed with coupled atmosphere-ocean general circulation models. Either of dynamical or of statistical type, down-scaling methods present strengths and weaknesses, but neither their validation on present climate conditions, nor their potential ability to project the impact of climate change on extreme event statistics allows one to give a specific advantage to one of the two types. The results synthesized in the last IPCC report and more recent studies underline a convergence for a very likely increase in heat wave episodes over land surfaces, linked to the mean warming and the increase in temperature variability. In addition, the number of days of frost should decrease and the growing season length should increase. The projected increase in heavy precipitation events appears also as very likely over most areas and also seems linked to a change in the shape of the precipitation intensity distribution. The global trends for drought duration are less consistent between models and down-scaling methodologies, due to their regional variability. The change of wind-related extremes is also regionally dependent, and associated to a poleward displacement of the mid-latitude storm tracks. The specific study of extreme events over France reveals the high sensitivity of some statistics of climate extremes at the decadal time scale as a consequence of regional climate internal variability. (authors)

  16. Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease.

    Science.gov (United States)

    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.

  17. Climate Variability Structures Plant Community Dynamics in Mediterranean Restored and Reference Tidal Wetlands

    Directory of Open Access Journals (Sweden)

    Dylan E. Chapple

    2017-03-01

    Full Text Available In Mediterranean regions and other areas with variable climates, interannual weather variability may impact ecosystem dynamics, and by extension ecological restoration projects. Conditions at reference sites, which are often used to evaluate restoration projects, may also be influenced by weather variability, confounding interpretations of restoration outcomes. To better understand the influence of weather variability on plant community dynamics, we explore change in a vegetation dataset collected between 1990 and 2005 at a historic tidal wetland reference site and a nearby tidal wetland restoration project initiated in 1976 in California’s San Francisco (SF Bay. To determine the factors influencing reference and restoration trajectories, we examine changes in plant community identity in relation to annual salinity levels in the SF Bay, annual rainfall, and tidal channel structure. Over the entire study period, both sites experienced significant directional change away from the 1990 community. Community change was accelerated following low salinity conditions that resulted from strong El Niño events in 1994–1995 and 1997–1998. Overall rates of change were greater at the restoration site and driven by a combination of dominant and sub-dominant species, whereas change at the reference site was driven by sub-dominant species. Sub-dominant species first appeared at the restoration site in 1996 and incrementally increased during each subsequent year, whereas sub-dominant species cover at the reference site peaked in 1999 and subsequently declined. Our results show that frequent, long-term monitoring is needed to adequately capture plant community dynamics in variable Mediterranean ecosystems and demonstrate the need for expanding restoration monitoring and timing restoration actions to match weather conditions.

  18. Coping with climate variability and long-term climate trends for Nicaraguan maize-bean farmers (Invited)

    Science.gov (United States)

    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.

  19. Revealing Relationships among Relevant Climate Variables with Information Theory

    Science.gov (United States)

    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.

  20. Providing more informative projections of climate change impact on plant distribution in a mountain environment

    Science.gov (United States)

    Randin, C.; Engler, R.; Pearman, P.; Vittoz, P.; Guisan, A.

    2007-12-01

    Due to their conic shape and the reduction of area with increasing elevation, mountain ecosystems were early identified as potentially very sensitive to global warming. Moreover, mountain systems may experience unprecedented rates of warming during the next century, two or three times higher than that records of the 20th century. In this context, species distribution models (SDM) have become important tools for rapid assessment of the impact of accelerated land use and climate change on the distribution plant species. In this study, we developed and tested new predictor variables for species distribution models (SDM), specific to current and future geographic projections of plant species in a mountain system, using the Western Swiss Alps as model region. Since meso- and micro-topography are relevant to explain geographic patterns of plant species in mountain environments, we assessed the effect of scale on predictor variables and geographic projections of SDM. We also developed a methodological framework of space-for-time evaluation to test the robustness of SDM when projected in a future changing climate. Finally, we used a cellular automaton to run dynamic simulations of plant migration under climate change in a mountain landscape, including realistic distance of seed dispersal. Results of future projections for the 21st century were also discussed in perspective of vegetation changes monitored during the 20th century. Overall, we showed in this study that, based on the most severe A1 climate change scenario and realistic dispersal simulations of plant dispersal, species extinctions in the Western Swiss Alps could affect nearly one third (28.5%) of the 284 species modeled by 2100. With the less severe B1 scenario, only 4.6% of species are predicted to become extinct. However, even with B1, 54% (153 species) may still loose more than 80% of their initial surface. Results of monitoring of past vegetation changes suggested that plant species can react quickly to the

  1. Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

    Energy Technology Data Exchange (ETDEWEB)

    Deng, Yi [Georgia Inst. of Technology, Atlanta, GA (United States)

    2014-11-24

    DOE-GTRC-05596 11/24/2104 Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate PI: Dr. Yi Deng (PI) School of Earth and Atmospheric Sciences Georgia Institute of Technology 404-385-1821, yi.deng@eas.gatech.edu El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The projection of future changes in the ENSO and AM variability, however, remains highly uncertain with the state-of-the-science climate models. This project conducted a process-resolving, quantitative evaluations of the ENSO and AM variability in the modern reanalysis observations and in climate model simulations. The goal is to identify and understand the sources of uncertainty and biases in models’ representation of ENSO and AM variability. Using a feedback analysis method originally formulated by one of the collaborative PIs, we partitioned the 3D atmospheric temperature anomalies and surface temperature anomalies associated with ENSO and AM variability into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. In the past 4 years, the research conducted at Georgia Tech under the support of this project has led to 15 peer-reviewed publications and 9 conference/workshop presentations. Two graduate students and one postdoctoral fellow also received research training through participating the project activities. This final technical report summarizes key scientific discoveries we made and provides also a list of all publications and conference presentations resulted from research activities at Georgia Tech. The main findings include

  2. Climate variability from isotope records in precipitation

    International Nuclear Information System (INIS)

    Grassl, H.; Latif, M.; Schotterer, U.; Gourcy, L.

    2002-01-01

    Selected time series from the Global Network for Isotopes in Precipitation (GNIP) revealed a close relationship to climate variability phenomena like El Nino - Southern Oscillation (ENSO) or the North Atlantic Oscillation (NAO) although the precipitation anomaly in the case studies of Manaus (Brazil) and Groningen (The Netherlands) is rather weak. For a sound understanding of this relationship especially in the case of Manaus, the data should include major events like the 1997/98 El Nino, however, the time series are interrupted frequently or important stations are even closed. Improvements are only possible if existing key stations and new ones (placed at 'hot spots' derived from model experiments) are supported continuously. A close link of GNIP to important scientific programmes like CLIVAR, the Climate Variability and Predictability Programme seems to be indispensable for a successful continuation. (author)

  3. Coral based-ENSO/IOD related climate variability in Indonesia: a review

    Science.gov (United States)

    Yudawati Cahyarini, Sri; Henrizan, Marfasran

    2018-02-01

    Indonesia is located in the prominent site to study climate variability as it lies between Pacific and Indian Ocean. It has consequences to the regional climate in Indonesia that its climate variability is influenced by the climate events in the Pacific oceans (e.g. ENSO) and in the Indian ocean (e.g. IOD), and monsoon as well as Indonesian Throughflow (ITF). Northwestern monsoon causes rainfall in the region of Indonesia, while reversely Southwestern monsoon causes dry season around Indonesia. The ENSO warm phase called El Nino causes several droughts in Indonesian region, reversely the La Nina causes flooding in some regions in Indonesia. However, the impact of ENSO in Indonesia is different from one place to the others. Having better understanding on the climate phenomenon and its impact to the region requires long time series climate data. Paleoclimate study which provides climate data back into hundreds to thousands even to million years overcome this requirement. Coral Sr/Ca can provide information on past sea surface temperature (SST) and paired Sr/Ca and δ18O may be used to reconstruct variations in the precipitation balance (salinity) at monthly to annual interannual resolution. Several climate studies based on coral geochemical records in Indonesia show that coral Sr/Ca and δ18O from Indonesian records SST and salinity respectively. Coral Sr/Ca from inshore Seribu islands complex shows more air temperature rather than SST. Modern coral from Timor shows the impact of ENSO and IOD to the saliniy and SST is different at Timor sea. This result should be taken into account when interpreting Paleoclimate records over Indonesia. Timor coral also shows more pronounced low frequency SST variability compared to the SST reanalysis (model). The longer data of low frequency variability will improve the understanding of warming trend in this climatically important region.

  4. Linking models of human behaviour and climate alters projected climate change

    Science.gov (United States)

    Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; Carr, Eric; Metcalf, Sara S.; Winter, Jonathan M.; Howe, Peter D.; Fefferman, Nina; Franck, Travis; Zia, Asim; Kinzig, Ann; Hoffman, Forrest M.

    2018-01-01

    Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4-6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with the largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.

  5. Impacts of climate variability and change on beekeeping productivity ...

    African Journals Online (AJOL)

    This study investigated impacts of climate variability and change on Beekeeping productivity in Sunya, Kijungu and Olgira villages in Kiteto District in Manyara region in Tanzania. Specific objectives of the study were to identify the contribution of honey bees to community livelihoods, to identify climate related factors which ...

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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. Projected future wave climate in the NW Mediterranean Sea

    Science.gov (United States)

    Casas-Prat, M.; Sierra, J. P.

    2013-07-01

    Projected future regional wave climate scenarios at a high temporal-spatial scale were obtained for the NW Mediterranean Sea, using five combinations of regional-global circulation models. Changes in wave variables were analyzed and related to the variations of the forcing wind projections, while also evaluating the evolution of the presence of the different types of sea states. To assess the significance of the changes produced, a bootstrap-based method was proposed, which accounts for the autocorrelation of data and correctly reproduces the extremes. For the mean climate, relative changes of Hs up to ±10% were obtained, whereas they were around ±20% for the extreme climate. In mean terms, variations of Hs are similar to those associated with wind speed but are enhanced/attenuated, respectively, when fetch conditions are favorable/unfavorable. In general, most notable alterations are not in the Hs magnitude but rather in its direction. In this regard, during the winter season, it is interesting to note that the significant deviations between the results derived from the two global circulation models are larger than those between regional models. ECHAM5 simulated an enhanced west wind flow that is translated into more frequent W-NW waves, whereas the HadCM3Q3 global model gives rise to the east component, which contributes to a higher intensity and number of storms coming from such a direction and directly affects the wind-sea/swell distribution of coastal stretches that face east, like the Catalan coast. Different patterns of change were obtained during the summer when a common rise of NE-E waves was found.

  9. Joint effects of climate variability and socioecological factors on dengue transmission: epidemiological evidence.

    Science.gov (United States)

    Akter, Rokeya; Hu, Wenbiao; Naish, Suchithra; Banu, Shahera; Tong, Shilu

    2017-06-01

    To assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission. Following PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer-reviewed, freely available and full-text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review. Twenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors. Due to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems. © 2017 John Wiley & Sons Ltd.

  10. Water management to cope with and adapt to climate variability and change.

    Science.gov (United States)

    Hamdy, A.; Trisorio-Liuzzi, G.

    2009-04-01

    In many parts of the world, variability in climatic conditions is already resulting in major impacts. These impacts are wide ranging and the link to water management problems is obvious and profound. The know-how and the available information undoubtedly indicate that climate change will lead to an intensification of the global hydrological cycle and can have major impacts on regional water resources, affecting both ground and surface water supply for sectorial water uses and, in particular, the irrigation field imposing notable negative effects on food security and poverty alleviation programs in most arid and semi-arid developing countries. At the United Nations Millennium Summit, in September 2000, world leaders adopted the Millennium Development Declaration. From this declaration, the IWRM was recognised as the key concept the water sector should be using for water related development and measures and, hence, for achieving the water related MDG's. However, the potential impacts of climate change and increasing climate variability are not sufficiently addressed in the IWRM plans. Indeed, only a very limited IWRM national plans have been prepared, coping with climate variability and changes. This is mainly due to the lack of operational instruments to deal with climate change and climate variability issues. This is particularly true in developing countries where the financial, human and ecological impacts are potentially greatest and where water resources may be already highly stressed, but the capacity to cope and adapt is weakest. Climate change has now brought realities including mainly rising temperatures and increasing frequency of floods and droughts that present new challenges to be addressed by the IWRM practice. There are already several regional and international initiatives underway that focus on various aspects of water resources management those to be linked with climate changes and vulnerability issues. This is the way where the water resources

  11. Impacts of climate change and variability on European agriculture

    DEFF Research Database (Denmark)

    Orlandini, Simone; Nejedlik, Pavol; Eitzinger, Josef

    2008-01-01

    susceptible to meteorological hazards. These hazards can modify environment-genotype interactions, which can affect the quality of production. The COST 734 Action (Impacts of Climate Change and Variability on European Agriculture), launched in 2006, is composed of 28 signature countries and is funded...... by the European Commission. The main objective of the Action is the evaluation of possible impacts arising from climate change and variability on agriculture and the assessment of critical thresholds for various European areas. The Action will concentrate on four different tasks: agroclimatic indices...... and simulation models, including review and assessment of tools used to relate climate and agricultural processes; evaluation of the current trends of agroclimatic indices and model outputs, including remote sensing; developing and assessing future regional and local scenarios of agroclimatic conditions...

  12. Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

    Energy Technology Data Exchange (ETDEWEB)

    Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Cassano, John J. [Univ. of Colorado, Boulder, CO (United States); Gutowski, Jr., William J. [Iowa State Univ., Ames, IA (United States); Lipscomb, William H. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nijssen, Bart [Univ. of Washington, Seattle, WA (United States); Roberts, Andrew [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Robertson, William [Univ. of Texas, El Paso, TX (United States); Tulaczyk, Slawek [Univ. of California, Santa Cruz, CA (United States); Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States)

    2011-05-15

    The primary outcome of the project was the development of the Regional Arctic System Model (RASM) and evaluation of its individual model components, coupling among them and fully coupled model results. Overall, we have demonstrated that RASM produces realistic mean and seasonal surface climate as well as its interannual and decadal variability and trends.

  13. Development of a database system for near-future climate change projections under the Japanese National Project SI-CAT

    Science.gov (United States)

    Nakagawa, Y.; Kawahara, S.; Araki, F.; Matsuoka, D.; Ishikawa, Y.; Fujita, M.; Sugimoto, S.; Okada, Y.; Kawazoe, S.; Watanabe, S.; Ishii, M.; Mizuta, R.; Murata, A.; Kawase, H.

    2017-12-01

    Analyses of large ensemble data are quite useful in order to produce probabilistic effect projection of climate change. Ensemble data of "+2K future climate simulations" are currently produced by Japanese national project "Social Implementation Program on Climate Change Adaptation Technology (SI-CAT)" as a part of a database for Policy Decision making for Future climate change (d4PDF; Mizuta et al. 2016) produced by Program for Risk Information on Climate Change. Those data consist of global warming simulations and regional downscaling simulations. Considering that those data volumes are too large (a few petabyte) to download to a local computer of users, a user-friendly system is required to search and download data which satisfy requests of the users. We develop "a database system for near-future climate change projections" for providing functions to find necessary data for the users under SI-CAT. The database system for near-future climate change projections mainly consists of a relational database, a data download function and user interface. The relational database using PostgreSQL is a key function among them. Temporally and spatially compressed data are registered on the relational database. As a first step, we develop the relational database for precipitation, temperature and track data of typhoon according to requests by SI-CAT members. The data download function using Open-source Project for a Network Data Access Protocol (OPeNDAP) provides a function to download temporally and spatially extracted data based on search results obtained by the relational database. We also develop the web-based user interface for using the relational database and the data download function. A prototype of the database system for near-future climate change projections are currently in operational test on our local server. The database system for near-future climate change projections will be released on Data Integration and Analysis System Program (DIAS) in fiscal year 2017

  14. Are the Projections of Future Climate Change Reliable in the IPCC Reports?

    Institute of Scientific and Technical Information of China (English)

    Zongci Zhao

    2011-01-01

    @@ As we know,the projections of future climate change including impacts and strategies in the IPCC Assessment Reports were based on global climate models with scenarios on various human activities.Global climate model simulations provide key inputs for climate change assessments. In this study,the main objective is to analyze if the projections of fu-ture climate change by global climate models are reli-able.Several workshops have been held on this issue,such as the IPCC expert meeting on assessing and combining multi-model climate projections in January of 2010 (presided by the co-chairs of the IPCC WGI and WGII AR5),and the workshop of the combined global climate model group held by NCAR in June of 2010.

  15. Creating Dynamically Downscaled Seasonal Climate Forecast and Climate Change Projection Information for the North American Monsoon Region Suitable for Decision Making Purposes

    Science.gov (United States)

    Castro, C. L.; Dominguez, F.; Chang, H.

    2010-12-01

    Current seasonal climate forecasts and climate change projections of the North American monsoon are based on the use of course-scale information from a general circulation model. The global models, however, have substantial difficulty in resolving the regional scale forcing mechanisms of precipitation. This is especially true during the period of the North American Monsoon in the warm season. Precipitation is driven primarily due to the diurnal cycle of convection, and this process cannot be resolve in coarse-resolution global models that have a relatively poor representation of terrain. Though statistical downscaling may offer a relatively expedient method to generate information more appropriate for the regional scale, and is already being used in the resource decision making processes in the Southwest U.S., its main drawback is that it cannot account for a non-stationary climate. Here we demonstrate the use of a regional climate model, specifically the Weather Research and Forecast (WRF) model, for dynamical downscaling of the North American Monsoon. To drive the WRF simulations, we use retrospective reforecasts from the Climate Forecast System (CFS) model, the operational model used at the U.S. National Center for Environmental Prediction, and three select “well performing” IPCC AR 4 models for the A2 emission scenario. Though relatively computationally expensive, the use of WRF as a regional climate model in this way adds substantial value in the representation of the North American Monsoon. In both cases, the regional climate model captures a fairly realistic and reasonable monsoon, where none exists in the driving global model, and captures the dominant modes of precipitation anomalies associated with ENSO and the Pacific Decadal Oscillation (PDO). Long-term precipitation variability and trends in these simulations is considered via the standardized precipitation index (SPI), a commonly used metric to characterize long-term drought. Dynamically

  16. (Tele)Connectivity in climate variability at different spatial/temporal scales in relation to solar and geomagnetic activity

    Czech Academy of Sciences Publication Activity Database

    Paluš, Milan; Hartman, David; Vejmelka, Martin; Novotná, Dagmar

    2011-01-01

    Roč. 13, - (2011), s. 9579 ISSN 1607-7962. [European Geosciences Union General Assembly 2011. 03.04.2011-08.04.2011, Vienna] R&D Projects: GA AV ČR IAA300420805 Institutional research plan: CEZ:AV0Z10300504; CEZ:AV0Z30420517 Keywords : climate variability * phase coherence * synchronization * North Atlantic Oscillation * solar activity Subject RIV: BB - Applied Statistics, Operational Research

  17. Cocoa farming households' vulnerability to climate variability in Ekiti ...

    African Journals Online (AJOL)

    Rural livelihoods in south western Nigeria are at risk to climate variability on the short run and climate change on the long run. This subjects agro ecological niches to high sensitivity and exposure thus reducing the adaptive capacity. Vulnerability results and the cocoa farming households, the major contributors to the ...

  18. Perception of Climate Variability on Agriculture and Food Security by ...

    African Journals Online (AJOL)

    Dr Osondu

    This paper focuses on how men and women farmers perceive climatic variability in Idanre ... Poor women and their ... Climate Change, Food Security and Poverty ..... 50. 8.3. Total. 180. 100. Marital status. Single. Married. Divorced. Widowed.

  19. Climate Change in Environmental Impact Assessment of Renewable Energy Projects

    DEFF Research Database (Denmark)

    Larsen, Sanne Vammen

    2012-01-01

    Many renewable energy projects are subject to EIA. However a question that surfaces is what use an impact assessment is when the project is ‘good for the environment’? One of the current topics receiving much attention in impact assessment is climate change and how this factor is integrated...... in impact assessments. This warrants the question: How do we assess the climate change related impacts of a project that inherently has a positive effect on climate? This paper is based on a document study of EIA reports from Denmark. The results show that climate change is included in most of the EIA...... reports reviewed, and that only climate change mitigation is in focus while adaptation is absent. Also the results point to focus on positive impacts, while the indirect negative impacts are less apparent. This leads to a discussion of the results in the light of the purpose of EIA....

  20. Hydroclimate variability in Scandinavia over the last millennium - insights from a climate model-proxy data comparison

    Science.gov (United States)

    Seftigen, Kristina; Goosse, Hugues; Klein, Francois; Chen, Deliang

    2017-12-01

    The integration of climate proxy information with general circulation model (GCM) results offers considerable potential for deriving greater understanding of the mechanisms underlying climate variability, as well as unique opportunities for out-of-sample evaluations of model performance. In this study, we combine insights from a new tree-ring hydroclimate reconstruction from Scandinavia with projections from a suite of forced transient simulations of the last millennium and historical intervals from the CMIP5 and PMIP3 archives. Model simulations and proxy reconstruction data are found to broadly agree on the modes of atmospheric variability that produce droughts-pluvials in the region. Despite these dynamical similarities, large differences between simulated and reconstructed hydroclimate time series remain. We find that the GCM-simulated multi-decadal and/or longer hydroclimate variability is systematically smaller than the proxy-based estimates, whereas the dominance of GCM-simulated high-frequency components of variability is not reflected in the proxy record. Furthermore, the paleoclimate evidence indicates in-phase coherencies between regional hydroclimate and temperature on decadal timescales, i.e., sustained wet periods have often been concurrent with warm periods and vice versa. The CMIP5-PMIP3 archive suggests, however, out-of-phase coherencies between the two variables in the last millennium. The lack of adequate understanding of mechanisms linking temperature and moisture supply on longer timescales has serious implications for attribution and prediction of regional hydroclimate changes. Our findings stress the need for further paleoclimate data-model intercomparison efforts to expand our understanding of the dynamics of hydroclimate variability and change, to enhance our ability to evaluate climate models, and to provide a more comprehensive view of future drought and pluvial risks.

  1. Climate Change Impacts at Department of Defense

    Energy Technology Data Exchange (ETDEWEB)

    Kotamarthi, Rao [Argonne National Lab. (ANL), Argonne, IL (United States); Wang, Jiali [Argonne National Lab. (ANL), Argonne, IL (United States); Zoebel, Zach [Univ. of Illinois, Urbana, IL (United States); Wuebbles, Don [Univ. of Illinois, Urbana, IL (United States); Hayhoe, Katharine [Texas Tech Univ., Lubbock, TX (United States); Stein, Michael [Univ. of Chicago, IL (United States); Changnon, David [Northern Illinois Univ., DeKalb, IL (United States)

    2017-06-16

    This project is aimed at providing the U.S. Department of Defense (DoD) with a comprehensive analysis of the uncertainty associated with generating climate projections at the regional scale that can be used by stakeholders and decision makers to quantify and plan for the impacts of future climate change at specific locations. The merits and limitations of commonly used downscaling models, ranging from simple to complex, are compared, and their appropriateness for application at installation scales is evaluated. Downscaled climate projections are generated at selected DoD installations using dynamic and statistical methods with an emphasis on generating probability distributions of climate variables and their associated uncertainties. The sites selection and selection of variables and parameters for downscaling was based on a comprehensive understanding of the current and projected roles that weather and climate play in operating, maintaining, and planning DoD facilities and installations.

  2. Climate variability in the subarctic area for the last 2 millennia

    Science.gov (United States)

    Nicolle, Marie; Debret, Maxime; Massei, Nicolas; Colin, Christophe; deVernal, Anne; Divine, Dmitry; Werner, Johannes P.; Hormes, Anne; Korhola, Atte; Linderholm, Hans W.

    2018-01-01

    To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA) was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A ˜ 16-30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas ˜ 20-30- and ˜ 50-90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice-temperature positive feedback.

  3. Working with Climate Projections to Estimate Disease Burden: Perspectives from Public Health

    Directory of Open Access Journals (Sweden)

    Kathryn C. Conlon

    2016-08-01

    Full Text Available There is interest among agencies and public health practitioners in the United States (USA to estimate the future burden of climate-related health outcomes. Calculating disease burden projections can be especially daunting, given the complexities of climate modeling and the multiple pathways by which climate influences public health. Interdisciplinary coordination between public health practitioners and climate scientists is necessary for scientifically derived estimates. We describe a unique partnership of state and regional climate scientists and public health practitioners assembled by the Florida Building Resilience Against Climate Effects (BRACE program. We provide a background on climate modeling and projections that has been developed specifically for public health practitioners, describe methodologies for combining climate and health data to project disease burden, and demonstrate three examples of this process used in Florida.

  4. Los Angeles County Metropolitan Transportation Authority climate change adaptation pilot project report.

    Science.gov (United States)

    2013-08-01

    This Climate Change Adaptation Pilot Project Report details the project background of the recently-completed Los Angeles County : Metropolitan Transportation Authority (Metro) Transit Climate Change Adaptation Pilot Project as well as the various wor...

  5. Assessment of projected climate change in the Carpathian Region using the Holdridge life zone system

    Science.gov (United States)

    Szelepcsényi, Zoltán; Breuer, Hajnalka; Kis, Anna; Pongrácz, Rita; Sümegi, Pál

    2018-01-01

    In this paper, expected changes in the spatial and altitudinal distribution patterns of Holdridge life zone (HLZ) types are analysed to assess the possible ecological impacts of future climate change for the Carpathian Region, by using 11 bias-corrected regional climate model simulations of temperature and precipitation. The distribution patterns of HLZ types are characterized by the relative extent, the mean centre and the altitudinal range. According to the applied projections, the following conclusions can be drawn: (a) the altitudinal ranges are likely to expand in the future, (b) the lower and upper altitudinal limits as well as the altitudinal midpoints may move to higher altitudes, (c) a northward shift is expected for most HLZ types and (d) the magnitudes of these shifts can even be multiples of those observed in the last century. Related to the northward shifts, the HLZ types warm temperate thorn steppe and subtropical dry forest can also appear in the southern segment of the target area. However, a large uncertainty in the estimated changes of precipitation patterns was indicated by the following: (a) the expected change in the coverage of the HLZ type cool temperate steppe is extremely uncertain because there is no consensus among the projections even in terms of the sign of the change (high inter-model variability) and (b) a significant trend in the westward/eastward shift is simulated just for some HLZ types (high temporal variability). Finally, it is important to emphasize that the uncertainty of our results is further enhanced by the fact that some important aspects (e.g. seasonality of climate variables, direct CO2 effect, etc.) cannot be considered in the estimating process.

  6. Women's role in adapting to climate change and variability

    Science.gov (United States)

    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.

  7. Future Changes in Surface Runoff over Korea Projected by a Regional Climate Model under A1B Scenario

    Directory of Open Access Journals (Sweden)

    Ji-Woo Lee

    2014-01-01

    Full Text Available This study assesses future change of surface runoff due to climate change over Korea using a regional climate model (RCM, namely, the Global/Regional Integrated Model System (GRIMs, Regional Model Program (RMP. The RMP is forced by future climate scenario, namely, A1B of Intergovernmental Panel on Climate Change (IPCC Fourth Assessment Report (AR4. The RMP satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation. The distribution of monsoonal precipitation-related runoff is adequately captured by the RMP. In the future (2040–2070 simulation, it is shown that the increasing trend of temperature has significant impacts on the intra-annual runoff variation. The variability of runoff is increased in summer; moreover, the strengthened possibility of extreme occurrence is detected in the future climate. This study indicates that future climate projection, including surface runoff and its variability over Korea, can be adequately addressed on the RMP testbed. Furthermore, this study reflects that global warming affects local hydrological cycle by changing major water budget components. This study adduces that the importance of runoff should not be overlooked in regional climate studies, and more elaborate presentation of fresh-water cycle is needed to close hydrological circulation in RCMs.

  8. Uncertainty in projected impacts of climate change on biodiversity

    DEFF Research Database (Denmark)

    Garcia, Raquel A.

    Evidence for shifts in the phenologies and distributions of species over recent decades has often been attributed to climate change. The prospect of greater and faster changes in climate during the 21st century has spurred a stream of studies anticipating future biodiversity impacts. Yet, uncerta......Evidence for shifts in the phenologies and distributions of species over recent decades has often been attributed to climate change. The prospect of greater and faster changes in climate during the 21st century has spurred a stream of studies anticipating future biodiversity impacts. Yet......, uncertainty is inherent to both projected climate changes and their effects on biodiversity, and needs to be understood before projections can be used. This thesis seeks to elucidate some of the uncertainties clouding assessments of biodiversity impacts from climate change, and explores ways to address them...... models, are shown to be affected by multiple uncertainties. Different model algorithms produce different outputs, as do alternative future climate models and scenarios of future emissions of greenhouse gases. Another uncertainty arises due to omission of species with small sample sizes, which...

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

    Science.gov (United States)

    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

  10. The NextData Project: a national Italian system for the retrieval, storage, access and diffusion of environmental and climate data from mountain and marine areas

    Science.gov (United States)

    Provenzale, Antonello

    2013-04-01

    Mountains are sentinels of climate and environmental change and many marine regions provide information on past climate variations. The Project of Interest NextData will favour the implementation of measurement networks in remote mountain and marine areas and will develop efficient web portals to access meteoclimatic and atmospheric composition data, past climate information from ice and sediment cores, biodiversity and ecosystem data, measurements of the hydrological cycle, marine reanalyses and climate projections at global and regional scale. New data on the present and past climatic variability and future climate projections in the Alps, the Himalaya-Karakoram, the Mediterranean region and other areas of interest will be obtained and made available. The pilot studies conducted during the project will allow for obtaining new estimates on the availability of water resources and on the effects of atmospheric aerosols on high-altitude environments, as well as new assessments of the impact of climate change on ecosystems, health and societies in mountain regions. The system of archives and the scientific results produced by the NextData project will provide a unique data base for research, for environmental management and for the estimate of climate change impacts, allowing for the development of knowledge-based environmental and climate adaptation policies.

  11. Hydrologic regime alteration of a Mediterranean catchment under climate change projection

    Science.gov (United States)

    Sellami, Haykel; Benabdallah, Sihem; La Jeunesse, Isabelle; Herrmann, Frank; Vanclooster, Marnik

    2014-05-01

    Most of the climate models projections for the Mediterranean basin have showed that the region will likely to experience a general tendency towards drier climate conditions with decreases in total precipitation, increases in temperature, alterations in the rainfall extreme events and droughts frequency (IPCC, 2007; Giorgi and Lionello, 2008; López-Moreno et al., 2011). The region is already suffering from water resources scarcity and vulnerability which are expected to amplify in the next century (Ludwig et al., 2011; Schneider et al., 2013). Therefore, assessing the impact of climate change on the hydrologic regime of Mediterranean catchments is with a major concern not only to scientist but also to water resources policy makers and general public. However, most of the climate change impact studies focus on the flow regime on global or regional scale rather than on the catchment scale which is more useful and more appropriate to guide practical mitigation and adaptation policy. This is because hydro-climate modeling at the local scale is confronted to the variability in climate, topography, geology, lack of observations and anthropogenic activities within the catchment. Furthermore, it is well recognized that hydrological and climate models forecasts are always affected with uncertainty making the assessment of climate change impact on Mediterranean catchment hydrology more challenging. This work aims to assess the impact of climate change on a Mediterranean catchment located in North Africa (the Chiba catchment in northeast Tunisia) through a conjunctive use of physically based hydrological model (SWAT) driven with four climate models*. Quantification of the impact of climate change has been conducted by means of the Indicators of Hydrologic Alteration (Richter et al., 1996) which are also ecologically meaningful. By comparing changes in these indicators in the reference period (1971-2000) to the projected ones in the future (2041-2070), it was possible to draw

  12. Final Progress Report submitted via the DOE Energy Link (E-Link) in June 2009 [Collaborative Research: Decadal-to-Centennial Climate & Climate Change Studies with Enhanced Variable and Uniform Resolution GCMs Using Advanced Numerical Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Fox-Rabinovitz, Michael S. [Univ. of Quebec (Canada); Cote, Jean [Univ. of Quebec (Canada)

    2009-10-09

    The joint U.S-Canadian project has been devoted to: (a) decadal climate studies using developed state-of-the-art GCMs (General Circulation Models) with enhanced variable and uniform resolution; (b) development and implementation of advanced numerical techniques; (c) research in parallel computing and associated numerical methods; (d) atmospheric chemistry experiments related to climate issues; (e) validation of regional climate modeling strategies for nested- and stretched-grid models. The variable-resolution stretched-grid (SG) GCMs produce accurate and cost-efficient regional climate simulations with mesoscale resolution. The advantage of the stretched grid approach is that it allows us to preserve the high quality of both global and regional circulations while providing consistent interactions between global and regional scales and phenomena. The major accomplishment for the project has been the successful international SGMIP-1 and SGMIP-2 (Stretched-Grid Model Intercomparison Project, phase-1 and phase-2) based on this research developments and activities. The SGMIP provides unique high-resolution regional and global multi-model ensembles beneficial for regional climate modeling and broader modeling community. The U.S SGMIP simulations have been produced using SciDAC ORNL supercomputers. The results of the successful SGMIP multi-model ensemble simulations of the U.S. climate are available at the SGMIP web site (http://essic.umd.edu/~foxrab/sgmip.html) and through the link to the WMO/WCRP/WGNE web site: http://collaboration.cmc.ec.gc.ca/science/wgne. Collaborations with other international participants M. Deque (Meteo-France) and J. McGregor (CSIRO, Australia) and their centers and groups have been beneficial for the strong joint effort, especially for the SGMIP activities. The WMO/WCRP/WGNE endorsed the SGMIP activities in 2004-2008. This project reflects a trend in the modeling and broader communities to move towards regional and sub-regional assessments and

  13. Terrestrial biosphere carbon storage under alternative climate projections

    Energy Technology Data Exchange (ETDEWEB)

    Schaphoff, S.; Lucht, W.; Gerten, D.; Sitch, S.; Cramer, W. [Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam (Germany); Prentice, I.C. [QUEST, Department of Earth Sciences, University of Bristol, Wills Memorial Building, Bristol, BS8 1RJ (United Kingdom)

    2006-01-15

    This study investigates commonalities and differences in projected land biosphere carbon storage among climate change projections derived from one emission scenario by five different general circulation models (GCMs). Carbon storage is studied using a global biogeochemical process model of vegetation and soil that includes dynamic treatment of changes in vegetation composition, a recently enhanced version of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM). Uncertainty in future terrestrial carbon storage due to differences in the climate projections is large. Changes by the end of the century range from -106 to +201 PgC, thus, even the sign of the response whether source or sink, is uncertain. Three out of five climate projections produce a land carbon source by the year 2100, one is approximately neutral and one a sink. A regional breakdown shows some robust qualitative features. Large areas of the boreal forest are shown as a future CO2 source, while a sink appears in the arctic. The sign of the response in tropical and sub-tropical ecosystems differs among models, due to the large variations in simulated precipitation patterns. The largest uncertainty is in the response of tropical rainforests of South America and Central Africa.

  14. Terrestrial biosphere carbon storage under alternative climate projections

    International Nuclear Information System (INIS)

    Schaphoff, S.; Lucht, W.; Gerten, D.; Sitch, S.; Cramer, W.; Prentice, I.C.

    2006-01-01

    This study investigates commonalities and differences in projected land biosphere carbon storage among climate change projections derived from one emission scenario by five different general circulation models (GCMs). Carbon storage is studied using a global biogeochemical process model of vegetation and soil that includes dynamic treatment of changes in vegetation composition, a recently enhanced version of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM). Uncertainty in future terrestrial carbon storage due to differences in the climate projections is large. Changes by the end of the century range from -106 to +201 PgC, thus, even the sign of the response whether source or sink, is uncertain. Three out of five climate projections produce a land carbon source by the year 2100, one is approximately neutral and one a sink. A regional breakdown shows some robust qualitative features. Large areas of the boreal forest are shown as a future CO2 source, while a sink appears in the arctic. The sign of the response in tropical and sub-tropical ecosystems differs among models, due to the large variations in simulated precipitation patterns. The largest uncertainty is in the response of tropical rainforests of South America and Central Africa

  15. Comparative response of Rangifer tarandus and other northern ungulates to climatic variability

    Directory of Open Access Journals (Sweden)

    Robert B. Weladji

    2002-06-01

    Full Text Available To understand the factors influencing life history traits and population dynamics, attention is increasingly being given to the importance of environmental stochasticity. In this paper, we review and discuss aspects of current knowledge concerning the effect of climatic variation (local and global on population parameters of northern ungu¬lates, with special emphasis on reindeer/caribou (Rangifer tarandus. We also restrict ourselves to indirect effects of climate through both forage availability and quality, and insect activity. Various authors have used different weather variables; with sometime opposite trends in resulting life history traits of ungulates, and few studies show consistent effects to the same climatic variables. There is thus little consensus about which weather variables play the most sig¬nificant role influencing ungulate population parameters. This may be because the effects of weather on ungulate pop¬ulation dynamics and life history traits are scale dependent and it is difficult to isolate climatic effects from density dependent factors. This confirms the complexity of the relationship between environment and ecosystem. We point out limits of comparability between systems and the difficulty of generalizing about the effect of climate change broadly across northern systems, across species and even within species. Furthermore, insect harassment appears to be a key climate-related factor for the ecology of reindeer/caribou that has been overlooked in the literature of climatic effects on large herbivores. In light of this, there is a need for further studies of long time series in assessing effects of climate variability on reindeer/caribou.

  16. Accounting for multiple climate components when estimating climate change exposure and velocity

    Science.gov (United States)

    Nadeau, Christopher P.; Fuller, Angela K.

    2015-01-01

    The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms.We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap.We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (using climate overlap compared to 1·4 km yr−1 when estimated using traditional methods.Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

  17. Surfing wave climate variability

    Science.gov (United States)

    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.

  18. Matching species traits to projected threats and opportunities from climate change

    Science.gov (United States)

    Garcia, Raquel A; Araújo, Miguel B; Burgess, Neil D; Foden, Wendy B; Gutsche, Alexander; Rahbek, Carsten; Cabeza, Mar

    2014-01-01

    Aim Climate change can lead to decreased climatic suitability within species' distributions, increased fragmentation of climatically suitable space, and/or emergence of newly suitable areas outside present distributions. Each of these extrinsic threats and opportunities potentially interacts with specific intrinsic traits of species, yet this specificity is seldom considered in risk assessments. We present an analytical framework for examining projections of climate change-induced threats and opportunities with reference to traits that are likely to mediate species' responses, and illustrate the applicability of the framework. Location Sub-Saharan Africa. Methods We applied the framework to 195 sub-Saharan African amphibians with both available bioclimatic envelope model projections for the mid-21st century and trait data. Excluded were 500 narrow-ranging species mainly from montane areas. For each of projected losses, increased fragmentation and gains of climate space, we selected potential response-mediating traits and examined the spatial overlap with vulnerability due to these traits. We examined the overlap for all species, and individually for groups of species with different combinations of threats and opportunities. Results In the Congo Basin and arid Southern Africa, projected losses for wide-ranging amphibians were compounded by sensitivity to climatic variation, and expected gains were precluded by poor dispersal ability. The spatial overlap between exposure and vulnerability was more pronounced for species projected to have their climate space contracting in situ or shifting to distant geographical areas. Our results exclude the potential exposure of narrow-ranging species to shrinking climates in the African tropical mountains. Main conclusions We illustrate the application of a framework combining spatial projections of climate change exposure with traits that are likely to mediate species' responses. Although the proposed framework carries several

  19. The CSAICLAWPS project: a multi-scalar, multi-data source approach to providing climate services for both modelling of climate change impacts on crop yields and development of community-level adaptive capacity for sustainable food security

    Science.gov (United States)

    Forsythe, N. D.; Fowler, H. J.

    2017-12-01

    The "Climate-smart agriculture implementation through community-focused pursuit of land and water productivity in South Asia" (CSAICLAWPS) project is a research initiative funded by the (UK) Royal Society through its Challenge Grants programme which is part of the broader UK Global Challenges Research Fund (GCRF). CSAICLAWPS has three objectives: a) development of "added-value" - bias assessed, statistically down-scaled - climate projections for selected case study sites across South Asia; b) investigation of crop failure modes under both present (observed) and future (projected) conditions; and c) facilitation of developing local adaptive capacity and resilience through stakeholder engagement. At AGU we will be presenting both next steps and progress to date toward these three objectives: [A] We have carried out bias assessments of a substantial multi-model RCM ensemble (MME) from the CORDEX South Asia (CORDEXdomain for case studies in three countries - Pakistan, India and Sri Lanka - and (stochastically) produced synthetic time-series for these sites from local observations using a Python-based implementation of the principles underlying the Climate Research Unit Weather Generator (CRU-WG) in order to enable probabilistic simulation of current crop yields. [B] We have characterised present response of local crop yields to climate variability in key case study sites using AquaCrop simulations parameterised based on input (agronomic practices, soil conditions, etc) from smallholder farmers. [C] We have implemented community-based hydro-climatological monitoring in several case study "revenue villages" (panchayats) in the Nainital District of Uttarakhand. The purpose of this is not only to increase availability of meteorological data, but also has the aspiration of, over time, leading to enhanced quantitative awareness of present climate variability and potential future conditions (as projected by RCMs). Next steps in our work will include: 1) future crop yield

  20. Benefit–cost analysis of non-marginal climate and energy projects

    International Nuclear Information System (INIS)

    Dietz, Simon; Hepburn, Cameron

    2013-01-01

    Conventional benefit–cost analysis incorporates the normally reasonable assumption that the policy or project under examination is marginal. Among the assumptions this entails is that the policy or project is small, so the underlying growth rate of the economy does not change. However, this assumption may be inappropriate in some important circumstances, including in climate-change and energy policy. One example is global targets for carbon emissions, while another is a large renewable energy project in a small economy, such as a hydropower dam. This paper develops some theory on the evaluation of non-marginal projects, with empirical applications to climate change and energy. We examine the conditions under which evaluation of a non-marginal project using marginal methods may be wrong, and in our empirical examples we show that both qualitative and large quantitative errors are plausible. - Highlights: • This paper develops the theory of the evaluation of non-marginal projects. • It also includes empirical applications to climate change and energy. • We show when evaluation of a non-marginal project using marginal methods is wrong

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  3. The impacts of future climate and carbon dioxide changes on the average and variability of US maize yields under two emission scenarios

    International Nuclear Information System (INIS)

    Urban, Daniel W; Lobell, David B; Sheffield, Justin

    2015-01-01

    The United States is the largest producer of maize in the world, a crop for which demand continues to rise rapidly. Past studies have projected that climate change will negatively impact mean maize yields in this region, while at the same time increasing yield variability. However, some have questioned the accuracy of these projections because they are often based on indirect measures of soil moisture, have failed to explicitly capture the potential interactions between temperature and soil moisture availability, and often omit the beneficial effects of elevated carbon dioxide (CO 2 ) on transpiration efficiency. Here we use a new detailed dataset on field-level yields in Iowa, Indiana, and Illinois, along with fine-resolution daily weather data and moisture reconstructions, to evaluate the combined effects of moisture and heat on maize yields in the region. Projected climate change scenarios over this region from a suite of CMIP5 models are then used to assess future impacts and the differences between two contrasting emissions scenarios (RCP 4.5 and RCP 8.5). We show that (i) statistical models which explicitly account for interactions between heat and moisture, which have not been represented in previous empirical models, lead to significant model improvement and significantly higher projected yield variability under warming and drying trends than when accounting for each factor independently; (ii) inclusion of the benefits of elevated CO 2 significantly reduces impacts, particularly for yield variability; and (iii) net damages from climate change and CO 2 become larger for the higher emission scenario in the latter half of the 21st century, and significantly so by the end of century. (paper)

  4. Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

    Science.gov (United States)

    Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

    2002-12-01

    The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).

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

    Science.gov (United States)

    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 (Pchanges in climatic 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.

  6. Changes in Southern Hemisphere circulation variability in climate change modelling experiments

    International Nuclear Information System (INIS)

    Grainger, Simon; Frederiksen, Carsten; Zheng, Xiaogu

    2007-01-01

    Full text: The seasonal mean of a climate variable can be considered as a statistical random variable, consisting of a signal and noise components (Madden 1976). The noise component consists of internal intraseasonal variability, and is not predictable on time-scales of a season or more ahead. The signal consists of slowly varying external and internal variability, and is potentially predictable on seasonal time-scales. The method of Zheng and Frederiksen (2004) has been applied to monthly time series of 500hPa Geopotential height from models submitted to the Coupled Model Intercomparison Project (CMIP3) experiment to obtain covariance matrices of the intraseasonal and slow components of covariability for summer and winter. The Empirical Orthogonal Functions (EOFs) of the intraseasonal and slow covariance matrices for the second half of the 20th century are compared with those observed by Frederiksen and Zheng (2007). The leading EOF in summer and winter for both the intraseasonal and slow components of covariability is the Southern Annular Mode (see, e.g. Kiladis and Mo 1998). This is generally reproduced by the CMIP3 models, although with different variance amounts. The observed secondary intraseasonal covariability modes of wave 4 patterns in summer and wave 3 or blocking in winter are also generally seen in the models, although the actual spatial pattern is different. For the slow covariabilty, the models are less successful in reproducing the two observed ENSO modes, with generally only one of them being represented among the leading EOFs. However, most models reproduce the observed South Pacific wave pattern. The intraseasonal and slow covariances matrices of 500hPa geopotential height under three climate change scenarios are also analysed and compared with those found for the second half of the 20th century. Through aggregating the results from a number of CMIP3 models, a consensus estimate of the changes in Southern Hemisphere variability, and their

  7. Enhancing STEM coursework at MSIs through the AMS Climate Studies Diversity Project

    Science.gov (United States)

    Abshire, W. E.; Mills, E. W.; Slough, S. W.; Brey, J. A.; Geer, I. W.; Nugnes, K. A.

    2017-12-01

    The AMS Education Program celebrates a successful completion to its AMS Climate Studies Diversity Project. The project was funded for 6 years (2011-2017) through the National Science Foundation (NSF). It introduced and enhanced geoscience and/or sustainability-focused course components at minority-serving institutions (MSIs) across the U.S., many of which are signatories to the President's Climate Leadership Commitments, administered by Second Nature, and/or members of the Louis Stokes Alliances for Minority Participation. The Project introduced AMS Climate Studies curriculum to approximately 130 faculty representing 113 MSIs. Each year a cohort of, on average, 25 faculty attended a course implementation workshop where they were immersed in the course materials, received presentations from high-level speakers, and trained as change agents for their local institutions. This workshop was held in the Washington, DC area in collaboration with Second Nature, NOAA, NASA Goddard Space Flight Center, Howard University, and other local climate educational and research institutions. Following, faculty introduced and enhanced geoscience curricula on their local campuses with AMS Climate Studies course materials, thereby bringing change from within. Faculty were then invited to the following AMS Annual Meeting to report on their AMS Climate Studies course implementation progress, reconnect with their colleagues, and learn new science presented at the meeting. A longitudinal survey was administered to all Climate Diversity Project faculty participants who attended the course implementation workshops. The survey goals were to assess the effectiveness of the Project in helping faculty implement/enhance their institutional climate science offering, share best practices in offering AMS Climate Studies, and analyze the usefulness of course materials. Results will be presented during this presentation. The AMS Climate Studies Diversity Project builds on highly successful, NSF

  8. Impacts of Present and Future Climate Variability on Agriculture and Forestry in the Temperate Regions. Europe

    International Nuclear Information System (INIS)

    Maracchi, G.; Sirotenko, O.; Bindi, M.

    2005-01-01

    Agriculture and forestry will be particularly sensitive to changes in mean climate and climate variability in the northern and southern regions of Europe. Agriculture may be positively affected by climate change in the northern areas through the introduction of new crop species and varieties, higher crop production and expansion of suitable areas for crop cultivation. The disadvantages may be determined by an increase in need for plant protection, risk of nutrient leaching and accelerated breakdown of soil organic matter. In the southern areas the benefits of the projected climate change will be limited, while the disadvantages will be predominant. The increased water use efficiency caused by increasing CO2 will compensate for some of the negative effects of increasing water limitation and extreme weather events, but lower harvestable yields, higher yield variability and reduction in suitable areas of traditional crops are expected for these areas. Forestry in the Mediterranean region may be mainly affected by increases in drought and forest fires. In northern Europe, the increased precipitation is expected to be large enough to compensate for the increased evapotranspiration. On the other hand, however, increased precipitation, cloudiness and rain days and the reduced duration of snow cover and soil frost may negatively affect forest work and timber logging determining lower profitability of forest production and a decrease in recreational possibilities. Adaptation management strategies should be introduced, as effective tools, to reduce the negative impacts of climate change on agricultural and forestry sectors

  9. Quantitative assessment of drivers of recent climate variability

    DEFF Research Database (Denmark)

    Bhaskar, Ankush; Ramesh, Durbha Sai; Vichare, Geeta

    2016-01-01

    Identification and quantification of possible drivers of recent climate variability remain a challenging task. This important issue is addressed adopting a non-parametric information theory technique, the Transfer Entropy and its normalized variant. It distinctly quantifies actual information...... exchanged along with the directional flow of information between any two variables with no bearing on their common history or inputs, unlike correlation, mutual information etc. Measurements of greenhouse gases, CO2, CH4, and N2O; volcanic aerosols; solar activity: UV radiation, total solar irradiance (TSI...... ) and cosmic ray flux (CR); El Nino Southern Oscillation (ENSO) and Global Mean Temperature Anomaly (GMTA) made during 1984-2005 are utilized to distinguish driving and responding climate signals. Estimates of their relative contributions reveal that CO 2 (~24%), CH 4 (~19%) and volcanic aerosols (~23...

  10. Climate model performance and change projection for freshwater fluxes: Comparison for irrigated areas in Central and South Asia

    Directory of Open Access Journals (Sweden)

    Shilpa M. Asokan

    2016-03-01

    Full Text Available Study region: The large semi-arid Aral Region in Central Asia and the smaller tropical Mahanadi River Basin (MRB in India. Study focus: Few studies have so far evaluated the performance of the latest generation of global climate models on hydrological basin scales. We here investigate the performance and projections of the global climate models in the Coupled Model Intercomparison Project, Phase 5 (CMIP5 for freshwater fluxes and their changes in two regional hydrological basins, which are both irrigated but of different scale and with different climate. New hydrological insights for the region: For precipitation in both regions, model accuracy relative to observations has remained the same or decreased in successive climate model generations until and including CMIP5. No single climate model out-performs other models across all key freshwater variables in any of the investigated basins. Scale effects are not evident from global model application directly to freshwater assessment for the two basins of widely different size. Overall, model results are less accurate and more uncertain for freshwater fluxes than for temperature, and particularly so for model-implied water storage changes. Also, the monsoon-driven runoff seasonality in MRB is not accurately reproduced. Model projections agree on evapotranspiration increase in both regions until the climatic period 2070–2099. This increase is fed by precipitation increase in MRB and by runoff water (thereby decreasing runoff in the Aral Region. Keywords: CMIP5 global climate models, Hydro-climate, Freshwater change, Central Asia, South Asia, Monsoon driven seasonality

  11. The climate of the Eastern Seaboard of Australia: A challenging entity now and for future projections

    International Nuclear Information System (INIS)

    Timbal, Bertrand

    2010-01-01

    The Eastern SeaBoard (ESB) of Australia has long been recognised as a separate climate entity. Using the latest gridded observations from the Bureau of Meteorology, a definition of the spatial extent of the ESB is proposed. It appears that, while this area has recorded below average rainfall over the last 12 years, the ongoing deficiency is not record breaking in historic terms. This contrasts with record breaking droughts across large parts of inland, eastern Australia. The lesser severity of ongoing rainfall deficiencies in the ESB, compared to the rest of the region, is linked to the different impact of observed changes in regional surface pressure and, in particular, changes in the position of the sub-tropical ridge. It is also observed that while tropical modes of variability in the Pacific and Indian oceans are known to influence the climate of eastern Australia, that influence appears very weak and not statistically significant across the ESB. Finally, some issues relevant to future rainfall projections for the ESB are discussed. It is argued that providing reliable climate projections across this climatic region is a difficult challenge.

  12. Future extreme events in European climate: An exploration of regional climate model projections

    DEFF Research Database (Denmark)

    Beniston, M.; Stephenson, D.B.; Christensen, O.B.

    2007-01-01

    -90) and future (2071-2 100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves - Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first...

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

    Science.gov (United States)

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

    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...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  16. Interannual and spatial variability of maple syrup yield as related to climatic factors

    Science.gov (United States)

    Houle, Daniel

    2014-01-01

    Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

  17. Climate Variability and Yields of Major Staple Food Crops in Northern Ghana

    Science.gov (United States)

    Amikuzuno, J.

    2012-12-01

    Climate variability, the short-term fluctuations in average weather conditions, and agriculture affect each other. Climate variability affects the agroecological and growing conditions of crops and livestock, and is recently believed to be the greatest impediment to the realisation of the first Millennium Development Goal of reducing poverty and food insecurity in arid and semi-arid regions of developing countries. Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we provide some insight into the long run relationship between inter-annual variations in temperature and rainfall, and annual yields of the most important staple food crops in Northern Ghana. Applying pooled panel data of rainfall, temperature and yields of the selected crops from 1976 to 2010 to cointegration and Granger causality models, there is cogent evidence of cointegration between seasonal, total rainfall and crop yields; and causality from rainfall to crop yields in the Sudano-Guinea Savannah and Guinea Savannah zones of Northern Ghana. This suggests that inter-annual yields of the crops have been influenced by the total mounts of rainfall in the planting season. Temperature variability over the study period is however stationary, and is suspected to have minimal effect if any on crop yields. Overall, the results confirm the appropriateness of our attempt in modelling long-term relationships between the climate and crop yield variables.

  18. Climate variability and Great Plains agriculture

    International Nuclear Information System (INIS)

    Rosenberg, N.J.; Katz, L.A.

    1991-01-01

    The ways in which inhabitants of the Great Plains, including Indians, early settlers, and 20th century farmers, have adapted to climate changes on the Great Plains are explored. The climate of the Great Plains, because of its variability and extremes, can be very stressful to plants, animals and people. It is suggested that agriculture and society on the Great Plains have, during the last century, become less vulnerable to the stresses imposed by climate. Opinions as to the sustainability of agriculture on the Great Plains vary substantially. Lockeretz (1981) suggests that large scale, high cost technologies have stressed farmers by creating surpluses and by requiring large investments. Opie (1989) sees irrigation as a climate substitute, however he stresses that the Ogallala aquifer must inevitably become depleted. Deborah and Frank Popper (1987) believe that farming on the Plains is unsustainable, and destruction of shelterbelts, out-migration of the rural population and environmental problems will lead to total collapse. With global warming, water in the Great Plains is expected to become scarcer, and although improvements in irrigation efficiency may slow depletion of the Ogallala aquifer, ultimately the acreage under irrigation must decrease to levels that can be sustained by natural recharge and reliable surface flows. 23 refs., 2 figs

  19. Projecting Future Heat-Related Mortality under Climate Change Scenarios: A Systematic Review

    Science.gov (United States)

    Barnett, Adrian Gerard; Wang, Xiaoming; Vaneckova, Pavla; FitzGerald, Gerard; Tong, Shilu

    2011-01-01

    Background: Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality. Objectives: We conducted a systematic review of research and methods for projecting future heat-related mortality under climate change scenarios. Data sources and extraction: A literature search was conducted in August 2010, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 through July 2010. Data synthesis: Fourteen studies fulfilled the inclusion criteria. Most projections showed that climate change would result in a substantial increase in heat-related mortality. Projecting heat-related mortality requires understanding historical temperature–mortality relationships and considering the future changes in climate, population, and acclimatization. Further research is needed to provide a stronger theoretical framework for projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution, and mortality displacement. Conclusions: Scenario-based projection research will meaningfully contribute to assessing and managing the potential impacts of climate change on heat-related mortality. PMID:21816703

  20. Climate variability in the subarctic area for the last 2 millennia

    Directory of Open Access Journals (Sweden)

    M. Nicolle

    2018-01-01

    Full Text Available To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A ∼ 16–30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas ∼ 20–30- and ∼ 50–90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice–temperature positive feedback.

  1. Research on climate change and variability at the Ab dus Salam International Centre for Theoretical Physics

    International Nuclear Information System (INIS)

    Giorgi, F.; Molteni, F.

    2002-01-01

    The Physics of Weather and Climate Section at the Abdus Salam International Centre for Theoretical Physics, established in 1998, is currently performing research on different aspects of climate variability, dealing with both natural and anthropogenic aspects of climate changes. In addition to performing diagnostic work on multi-decadal observational datasets and climate simulations carried out in major research centres, the PWC section has been developing its own climate modeling capability, which is focused on three main areas: a) modeling of regional climate change; b) seasonal forecasting at global and regional scale; c) development of simplified models of the general circulation. On topic a), research on different aspects of anthropogenic climate change is being carried out using the Regional Climate (RegCM) developed by Giorgi and collaborators at the National Centre for Atmospheric Research. Time-slice experiments with a high-resolution atmospheric GCM, comparing current climate conditions with future climate scenarios in selected decades, are also planned for the near future. On topic b), a strategy based on ensembles of high-resolution simulations with atmospheric GCM's, using sea surface temperature anomalies predicted by lower-resolution coupled models from other institutions, is currently under experimentation. A one-way nesting of RegCM into the GCM simulations will also be tested. On item c), a 5-layer atmospheric GCM with simplified physical parameterizations has been developed. This model has a very small computational cost compared with state-of-the-art GCMs, and is suitable for studies of natural climate variability on inter-decadal and intercentennial time scales. It is planned to couple this model to simplified ocean models of different complexity, from a simple, static mixed layer model, to simplified models of the tropical Pacific circulation suited to the simulation of the El Nino phenomenon. A joint project with the IAEA-MEL Laboratory in

  2. Real-time monitoring of smallholder farmer responses to intra-seasonal climate variability in central Kenya

    Science.gov (United States)

    Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.

    2017-12-01

    While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.

  3. Collaborative Project: The problem of bias in defining uncertainty in computationally enabled strategies for data-driven climate model development. Final Technical Report.

    Energy Technology Data Exchange (ETDEWEB)

    Huerta, Gabriel [Univ. of New Mexico, Albuquerque, NM (United States)

    2016-05-10

    The objective of the project is to develop strategies for better representing scientific sensibilities within statistical measures of model skill that then can be used within a Bayesian statistical framework for data-driven climate model development and improved measures of model scientific uncertainty. One of the thorny issues in model evaluation is quantifying the effect of biases on climate projections. While any bias is not desirable, only those biases that affect feedbacks affect scatter in climate projections. The effort at the University of Texas is to analyze previously calculated ensembles of CAM3.1 with perturbed parameters to discover how biases affect projections of global warming. The hypothesis is that compensating errors in the control model can be identified by their effect on a combination of processes and that developing metrics that are sensitive to dependencies among state variables would provide a way to select version of climate models that may reduce scatter in climate projections. Gabriel Huerta at the University of New Mexico is responsible for developing statistical methods for evaluating these field dependencies. The UT effort will incorporate these developments into MECS, which is a set of python scripts being developed at the University of Texas for managing the workflow associated with data-driven climate model development over HPC resources. This report reflects the main activities at the University of New Mexico where the PI (Huerta) and the Postdocs (Nosedal, Hattab and Karki) worked on the project.

  4. Climate variability impacts on rice crop production in pakistan

    International Nuclear Information System (INIS)

    Shakoor, U.; Saboor, A.; Baig, I.

    2015-01-01

    The climate variability has affected the agriculture production all over the globe. This concern has motivated important changes in the field of research during the last decade. Climate changes are believed to have declining effects towards crop production in Pakistan. This study carries an empirical investigation of the effects of climate change on rice crop of Pakistan by employing Vector Auto Regression (VAR) model. Annual seasonal data of the climatic variables from 1980 to 2013 has been used. Results confirmed that rising mean maximum temperature would lead to reduction in rice production while increase in mean minimum temperature would be advantageous towards rice production. Variation in mean minimum temperature brought about seven percent increase in rice productivity as shown by Variance Decomposition. Mean precipitation and mean temperature would increase rice production but simulations scenarios for 2030 confirmed that much increase in rainfall and mean temperature in long run will negatively affect rice production in future. It is therefore important to follow adequate policy action to safeguard crop productions from disastrous effects. Development of varieties resistant to high temperatures as well as droughts will definitely enhance resilience of rice crop in Pakistan. (author)

  5. IN SITU COMPARISON OF TREE-RING RESPONSES TO CLIMATE AND POPULATION GENETICS: THE NEED TO CONTROL FOR LOCAL CLIMATE AND SITE VARIABLES

    Directory of Open Access Journals (Sweden)

    Johann Mathias Housset

    2016-10-01

    Full Text Available Tree species responses to climate change will be greatly influenced by their evolutionary potential and their phenotypic plasticity. Investigating tree-rings responses to climate and population genetics at the regional scale is therefore crucial in assessing the tree behaviour to climate change. This study combined in situ dendroclimatology and population genetics over a latitudinal gradient and compared the variations between the two at the intra- and inter-population levels. This approach was applied on the northern marginal populations of Thuja occidentalis (eastern white-cedar in the Canadian boreal forest. We aimed first to assess the radial growth variability (response functional trait within populations across the gradient and to compare it with the genetic diversity (microsatellites. Second, we investigated the variability in the growth response to climate at the regional scale through the radial growth-climate relationships, and tested its correlation with environmental variables and population genetic structure. Model selection based on the Akaike Information Criteria revealed that the growth synchronicity between pairs of trees of a population covariates with both the genetic diversity of this population and the amount of precipitation (inverse correlation, although these variables only explained a small fraction of the observed variance. At the regional scale, variance partitioning and partial redundancy analysis indicate that the growth response to climate was greatly modulated by stand environmental variables, suggesting predominant plastic variations in growth-response to climate. Combining in situ dendroclimatology and population genetics is a promising way to investigate species’ response capacity to climate change in natural stands. We stress the need to control for local climate and site conditions effects on dendroclimatic response to climate to avoid misleading conclusions regarding the associations with genetic variables.

  6. Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China

    Science.gov (United States)

    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

  7. Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China.

    Science.gov (United States)

    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.

  8. California Getting Wetter to the North, Drier to the South: Natural Variability or Climate Change?

    Directory of Open Access Journals (Sweden)

    Dan Killam

    2014-08-01

    Full Text Available Current climate change projections anticipate that global warming trends will lead to changes in the distribution and intensity of precipitation at a global level. However, few studies have corroborated these model-based results using historical precipitation records at a regional level, especially in our study region, California. In our analyses of 14 long-term precipitation records representing multiple climates throughout the state, we find northern and central regions increasing in precipitation while southern regions are drying. Winter precipitation is increasing in all regions, while other seasons show mixed results. Rain intensity has not changed since the 1920s. While Sacramento shows over 3 more days of rain per year, Los Angeles has almost 4 less days per year in the last century. Both the El Niño-Southern Oscillation (ENSO and the Pacific Decadal Oscillation (PDO greatly influence the California precipitation record. The climate change signal in the precipitation records remains unclear as annual variability overwhelms the precipitation trends.

  9. Come rain or shine: Multi-model Projections of Climate Hazards affecting Transportation in the South Central United States

    Science.gov (United States)

    Mullens, E.; Mcpherson, R. A.

    2016-12-01

    This work develops detailed trends in climate hazards affecting the Department of Transportation's Region 6, in the South Central U.S. Firstly, a survey was developed to gather information regarding weather and climate hazards in the region from the transportation community, identifying key phenomena and thresholds to evaluate. Statistically downscaled datasets were obtained from the Multivariate Adaptive Constructed Analogues (MACA) project, and the Asynchronous Regional Regression Model (ARRM), for a total of 21 model projections, two coupled model intercomparisons (CMIP3, and CMIP5), and four emissions pathways (A1Fi, B1, RCP8.5, RCP4.5). Specific hazards investigated include winter weather, freeze-thaw cycles, hot and cold extremes, and heavy precipitation. Projections for each of these variables were calculated for the region, utilizing spatial mapping, and time series analysis at the climate division level. The results indicate that cold-season phenomena such as winter weather, freeze-thaw, and cold extremes, decrease in intensity and frequency, particularly with the higher emissions pathways. Nonetheless, specific model and downscaling method yields variability in magnitudes, with the most notable decreasing trends late in the 21st century. Hot days show a pronounced increase, particularly with greater emissions, producing annual mean 100oF day frequencies by late 21st century analogous to the 2011 heatwave over the central Southern Plains. Heavy precipitation, evidenced by return period estimates and counts-over-thresholds, also show notable increasing trends, particularly between the recent past through mid-21st Century. Conversely, mean precipitation does not show significant trends and is regionally variable. Precipitation hazards (e.g., winter weather, extremes) diverge between downscaling methods and their associated model samples much more substantially than temperature, suggesting that the choice of global model and downscaled data is particularly

  10. Do projections from bioclimatic envelope models and climate change metrics match?

    DEFF Research Database (Denmark)

    Garcia, Raquel A.; Cabeza, Mar; Altwegg, Res

    2016-01-01

    as indicators of the exposure of species to climate change. Here, we investigate whether these two approaches provide qualitatively similar indications about where biodiversity is potentially most exposed to climate change. Location: Sub-Saharan Africa. Methods: We compared a range of climate change metrics...... for sub-Saharan Africa with ensembles of bioclimatic envelope models for 2723 species of amphibians, snakes, mammals and birds. For each taxonomic group, we performed three comparisons between the two approaches: (1) is projected change in local climatic suitability (models) greater in grid cells...... between the two approaches was found for all taxonomic groups, although it was stronger for species with a narrower climatic envelope breadth. Main conclusions: For sub-Saharan African vertebrates, projected patterns of exposure to climate change given by climate change metrics alone were qualitatively...

  11. Effects of temporal changes in climate variables on crop production ...

    African Journals Online (AJOL)

    Climate variability and change have been implicated to have significant impacts on global and regional food production particularly the common stable food crops performance in tropical sub-humid climatic zone. However, the extent and nature of these impacts still remain uncertain. In this study, records of crop yields and ...

  12. Building resilience to climate variability in Uganda's “cattle corridor ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    2016-04-27

    Apr 27, 2016 ... Extensive areas of sub-Saharan, particularly East Africa, are vulnerable to the long-term consequences of climate change and the short-term increase in climate variability. With IDRC support, researchers from the Africa Innovations Institute set out to find ways to enhance the resilience of poor rural ...

  13. Within-species digestive tract flexibility in rufous-collared sparrows and the climatic variability hypothesis.

    Science.gov (United States)

    Maldonado, Karin; Bozinovic, Francisco; Rojas, José M; Sabat, Pablo

    2011-01-01

    The climatic variability hypothesis (CVH) states that species are geographically more widespread at higher latitudes because individuals have a broader range of physiological tolerance or phenotypic flexibility as latitude and climatic variability increase. However, it remains unclear to what extent climatic variability or latitude, acting on the phenotype, account for any observed geographical gradient in mean range size. In this study, we analyzed the physiological flexibility within the CVH framework by using an intraspecific population experimental approach. We tested for a positive relationship between digestive-tract flexibility (i.e., morphology and enzyme activities) and latitude and climatic and natural diet variability in populations of rufous-collared sparrows (Zonotrichia capensis) captured in desert (27°S), Mediterranean (33°S), and cold-temperate (41°S) sites in Chile. In accordance with the CVH, we observed a positive relationship between the magnitude of digestive-tract flexibility and environmental variability but not latitude. The greatest digestive flexibility was observed in birds at middle latitudes, which experience the most environmental variability (a Mediterranean climate), whereas individuals from the most stable climates (desert and cold-temperate) exhibited little or no digestive-tract flexibility in response to experimental diets. Our findings support the idea that latitudinal gradients in geographical ranges may be strongly affected by the action of regional features, which makes it difficult to find general patterns in the distribution of species.

  14. Evaluating climate variables, indexes and thresholds governing Arctic urban sustainability: case study of Russian permafrost regions

    Science.gov (United States)

    Anisimov, O. A.; Kokorev, V.

    2013-12-01

    Addressing Arctic urban sustainability today forces planners to deal with the complex interplay of multiple factors, including governance and economic development, demography and migration, environmental changes and land use, changes in the ecosystems and their services, and climate change. While the latter can be seen as a factor that exacerbates the existing vulnerabilities to other stressors, changes in temperature, precipitation, snow, river and lake ice, and the hydrological regime also have direct implications for the cities in the North. Climate change leads to reduced demand for heating energy, on one hand, and heightened concerns about the fate of the infrastructure built upon thawing permafrost, on the other. Changes in snowfall are particularly important and have direct implications for the urban economy, as together with heating costs, expenses for snow removal from streets, airport runways, roofs and ventilation corridors underneath buildings erected on pile foundations on permafrost constitute the bulk of the city's maintenance budget. Many cities are located in river valleys and are prone to flooding that leads to enormous economic losses and casualties, including human deaths. The severity of the northern climate has direct implications for demographic changes governed by regional migration and labor flows. Climate could thus be viewed as an inexhaustible public resource that creates opportunities for sustainable urban development. Long-term trends show that climate as a resource is becoming more readily available in the Russian North, notwithstanding the general perception that globally climate change is one of the challenges facing humanity in the 21st century. In this study we explore the sustainability of the Arctic urban environment under changing climatic conditions. We identify key governing variables and indexes and study the thresholds beyond which changes in the governing climatic parameters have significant impact on the economy

  15. Modeling the Projected Changes of River Flow in Central Vietnam under Different Climate Change Scenarios

    Directory of Open Access Journals (Sweden)

    Tuan B. Le

    2015-07-01

    Full Text Available Recent studies by the United Nations Environment Programme (UNEP and the Intergovernmental Panel on Climate Change (IPCC indicate that Vietnam is one of the countries most affected by climate change. The variability of climate in this region, characterized by large fluctuations in precipitation and temperature, has caused significant changes in surface water resources. This study aims to project the impact of climate change on the seasonal availability of surface water of the Huong River in Central Vietnam in the twenty-first century through hydrologic simulations driven by climate model projections. To calibrate and validate the hydrologic model, the model was forced by the rain gage-based gridded Asian Precipitation–Highly Resolved Observational Data Integration Towards Evaluation of water resources (APHRODITE V1003R1 Monsoon Asia precipitation data along with observed temperature, humidity, wind speed, and solar radiation data from local weather stations. The simulated discharge was compared to observations for the period from 1951 until present. Three Global Climate Models (GCMs ECHAM5-OM, HadCM3 and GFDL-CM2.1 integrated into Long Ashton Research Station-Weather Generator (LARS-WG stochastic weather generator were run for three IPCC–Special Report on Emissions Scenarios (IPCC-SRES emissions scenarios A1B, A2, and B1 to simulate future climate conditions. The hydrologic model simulated the Huong River discharge for each IPCC-SRES scenario. Simulation results under the three GCMs generally indicate an increase in summer and fall river discharge during the twenty-first century in A2 and B1 scenarios. For A1B scenario, HadCM3 and GFDL-CM2.1 models project a decrease in river discharge from present to the 2051–2080 period and then increase until the 2071–2100 period while ECHAM5-OM model produces opposite projection that discharge will increase until the 2051–2080 period and then decrease for the rest of the century. Water management

  16. Climate variability and vulnerability to poverty in Nicaragua

    NARCIS (Netherlands)

    C. Herrera (Carlos); R. Ruben (Ruerd); A.G. Dijkstra (Geske)

    2018-01-01

    textabstractThis study considers the effect of climate variability on vulnerability to poverty in Nicaragua. It discusses how such vulnerability could be measured and which heterogeneous effects can be expected. A multilevel empirical framework is applied, linking per capita consumption

  17. The impact of climatic variability and climate change on arabic coffee crop in Brazil

    OpenAIRE

    Camargo,Marcelo Bento Paes de

    2010-01-01

    The climatic variability is the main factor responsible for the oscillations and frustrations of the coffee grain yield in Brazil. The relationships between the climatic parameters and the agricultural production are quite complex, because environmental factors affect the growth and the development of the plants under different forms during the growth stages of the coffee crop. Agrometeorological models related to the growth, development and productivity can supply information for the soil wa...

  18. Climate variability and change in southern Mali : Learning from farmer perceptions and on-farm trials

    NARCIS (Netherlands)

    Traore, B.; Wijk, van M.T.; Descheemaeker, K.K.E.; Corbeels, M.; Rufino, M.C.; Giller, K.E.

    2015-01-01

    Agricultural production in the Sudano–Sahelian zone of west Africa is highly vulnerable to the impacts of climate variability and climate change. The present study aimed to understand farmers’ perceptions of climate variability and change and to evaluate adaptation options together with farmers,

  19. Geocuration Lessons Learned from the Climate Data Initiative Project

    Science.gov (United States)

    Ramachandran, Rahul; Bugbee, Kaylin; Tilmes, Curt; Pinheiro Privette, Ana

    2015-01-01

    Curation is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest and typically occurs in museums, art galleries, and libraries. The task of organizing data around specific topics or themes is a vibrant and growing effort in the biological sciences but to date this effort has not been actively pursued in the Earth sciences. This presentation will introduce the concept of geocuration, which we define it as the act of searching, selecting, and synthesizing Earth science data/metadata and information from across disciplines and repositories into a single, cohesive, and useful compendium. We also present the Climate Data Initiative (CDI) project as an prototypical example. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. CDI is a broad multi-agency effort of the U.S. government and seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate change preparedness. The geocuration process used in the CDI project, key lessons learned, and suggestions to improve similar geocuration efforts in the future will be part of this presentation.

  20. Geocuration Lessons Learned from the Climate Data Initiative Project

    Science.gov (United States)

    Ramachandran, R.; Bugbee, K.; Tilmes, C.; Privette, A. P.

    2015-12-01

    Curation is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest and typically occurs in museums, art galleries, and libraries. The task of organizing data around specific topics or themes is a vibrant and growing effort in the biological sciences but to date this effort has not been actively pursued in the Earth sciences. This presentation will introduce the concept of geocuration, which we define it as the act of searching, selecting, and synthesizing Earth science data/metadata and information from across disciplines and repositories into a single, cohesive, and useful compendium.We also present the Climate Data Initiative (CDI) project as an exemplar example. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. CDI is a broad multi-agency effort of the U.S. government and seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate-change preparedness. The geocuration process used in CDI project, key lessons learned, and suggestions to improve similar geocuration efforts in the future will be part of this presentation.

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

    Science.gov (United States)

    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.

  2. Building resilience to climate variability in Uganda's “cattle corridor ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    2 déc. 2014 ... Extensive areas of sub-Saharan, particularly East Africa, are vulnerable to the long-term consequences of climate change and the short-term increase in climate variability. With IDRC support, researchers from the Africa Innovations Institute set out to find ways to enhance the resilience of poor rural ...

  3. Future Projection of Ocean Wave Climate: Analysis of SST Impacts on Wave Climate Changes in the Western North Pacific

    OpenAIRE

    Shimura, Tomoya; Mori, Nobuhito; Mase, Hajime

    2015-01-01

    Changes in ocean surface waves elicit a variety of impacts on coastal environments. To assess the future changes in the ocean surface wave climate, several future projections of global wave climate have been simulated in previous studies. However, previously there has been little discussion about the causes behind changes in the future wave climate and the differences between projections. The objective of this study is to estimate the future changes in mean wave climate and the sensitivity of...

  4. Supporting UK adaptation: building services for the next set of UK climate projections

    Science.gov (United States)

    Fung, Fai; Lowe, Jason

    2016-04-01

    As part of the Climate Change Act 2008, the UK Government sets out a national adaptation programme to address the risks and opportunities identified in a national climate change risk assessment (CCRA) every five years. The last risk assessment in 2012 was based on the probabilistic projections for the UK published in 2009 (UKCP09). The second risk assessment will also use information from UKCP09 alongside other evidence on climate projections. However, developments in the science of climate projeciton, and evolving user needs (based partly on what has been learnt about the diverse user requirements of the UK adaptation community from the seven years of delivering and managing UKCP09 products, market research and the peer-reviewed literature) suggest now is an appropriate time to update the projections and how they are delivered. A new set of UK climate projections are now being produced to upgrade UKCP09 to reflect the latest developments in climate science, the first phase of which will be delivered in 2018 to support the third CCRA. A major component of the work is the building of a tailored service to support users of the new projections during their development and to involve users in key decisions so that the projections are of most use. We will set out the plan for the new climate projections that seek to address the evolving user need. We will also present a framework which aims to (i) facilitate the dialogue between users, boundary organisations and producers, reflecting their different decision-making roles (ii) produce scientifically robust, user-relevant climate information (iii) provide the building blocks for developing further climate services to support adaptation activities in the UK.

  5. Climate change and the impact of increased rainfall variability on sediment transport and catchment scale water quality

    Science.gov (United States)

    Hancock, G. R.; Willgoose, G. R.; Cohen, S.

    2009-12-01

    Recently there has been recognition that changing climate will affect rainfall and storm patterns with research directed to examine how the global hydrological cycle will respond to climate change. This study investigates the effect of different rainfall patterns on erosion and resultant water quality for a well studied tropical monsoonal catchment that is undisturbed by Europeans in the Northern Territory, Australia. Water quality has a large affect on a range of aquatic flora and fauna and a significant change in sediment could have impacts on the aquatic ecosystems. There have been several studies of the effect of climate change on rainfall patterns in the study area with projections indicating a significant increase in storm activity. Therefore it is important that the impact of this variability be assessed in terms of catchment hydrology, sediment transport and water quality. Here a numerical model of erosion and hydrology (CAESAR) is used to assess several different rainfall scenarios over a 1000 year modelled period. The results show that that increased rainfall amount and intensity increases sediment transport rates but predicted water quality was variable and non-linear but within the range of measured field data for the catchment and region. Therefore an assessment of sediment transport and water quality is a significant and complex issue that requires further understandings of the role of biophysical feedbacks such as vegetation as well as the role of humans in managing landscapes (i.e. controlled and uncontrolled fire). The study provides a robust methodology for assessing the impact of enhanced climate variability on sediment transport and water quality.

  6. Worlding cities through their climate projects?

    DEFF Research Database (Denmark)

    Blok, Anders

    2014-01-01

    In recent years, the built environment has emerged as a critical target of climate change intervention for urban governments around the world, engaging developers, professionals, activists and communities in a range of new eco-urbanism projects. While important contributions have been made......, this paper suggests that critical academic and policy debates on urban climate politics have so far paid insufficient attention to the sheer divergence in urban experiences, concerns and public–professional responses elicited through such experiments worldwide. By juxtaposing architectural and other eco......-housing practices from diverse cities on three continents—Kyoto (Japan), Copenhagen (Denmark) and Surat (India)—this paper aims to conjure a more cosmopolitan research imagination on how climatic solidarities may emerge in the face of multiple urban differences and inequalities. Towards this end, the paper...

  7. Contributions of internal climate variability to mitigation of projected future regional sea level rise

    Science.gov (United States)

    Hu, A.; Bates, S. C.

    2017-12-01

    Observations indicate that the global mean surface temperature is rising, so does the global mean sea level. Sea level rise (SLR) can impose significant impacts on island and coastal communities, especially when SLR is compounded with storm surges. Here, via analyzing results from two sets of ensemble simulations from the Community Earth System Model version 1, we investigate how the potential SLR benefits through mitigating the future emission scenarios from business as usual to a mild-mitigation over the 21st Century would be affected by internal climate variability. Results show that there is almost no SLR benefit in the near term due to the large SLR variability due to the internal ocean dynamics. However, toward the end of the 21st century, the SLR benefit can be as much as a 26±1% reduction of the global mean SLR due to seawater thermal expansion. Regionally, the benefits from this mitigation for both near and long terms are heterogeneous. They vary from just a 11±5% SLR reduction in Melbourne, Australia to a 35±6% reduction in London. The processes contributing to these regional differences are the coupling of the wind-driven ocean circulation with the decadal scale sea surface temperature mode in the Pacific and Southern Oceans, and the changes of the thermohaline circulation and the mid-latitude air-sea coupling in the Atlantic.

  8. Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models.

    Science.gov (United States)

    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

  9. GC23G-1310: Investigation Into the Effects of Climate Variability and Land Cover Change on the Hydrologic System of the Lower Mekong Basin

    Science.gov (United States)

    Markert, Kel N.; Griffin, Robert; Limaye, Ashutosh S.; McNider, Richard T.; Anderson, Eric R.

    2016-01-01

    The Lower Mekong Basin (LMB) is an economically and ecologically important region that experiences hydrologic hazards such as floods and droughts, which can directly affect human well-being and limit economic growth and development. To effectively develop long-term plans for addressing hydrologic hazards, the regional hydrological response to climate variability and land cover change needs to be evaluated. This research aims to investigate how climate variability, specifically variations in the precipitation regime, and land cover change will affect hydrologic parameters both spatially and temporally within the LMB. The research goal is achieved by (1) modeling land cover change for a baseline land cover change scenario as well as changes in land cover with increases in forest or agriculture and (2) using projected climate variables and modeled land cover data as inputs into the Variable Infiltration Capacity (VIC) hydrologic model to simulate the changes to the hydrologic system. The VIC model outputs were analyzed against historic values to understand the relative contribution of climate variability and land cover to change, where these changes occur, and to what degree these changes affect the hydrology. This study found that the LMB hydrologic system is more sensitive to climate variability than land cover change. On average, climate variability was found to increase discharge and evapotranspiration (ET) while decreasing water storage. The change in land cover show that increasing forest area will slightly decrease discharge and increase ET while increasing agriculture area increases discharge and decreases ET. These findings will help the LMB by supporting individual country policy to plan for future hydrologic changes as well as policy for the basin as a whole.

  10. Tropical interannual variability in a global coupled GCM: Sensitivity to mean climate state

    Energy Technology Data Exchange (ETDEWEB)

    Moore, A.M. [Bureau of Meterology Research Centre, Melbourne, Victoria (Australia)

    1995-04-01

    A global coupled ocean-atmosphere-sea ice general circulation model is used to study interannual variability in the Tropics. Flux correction is used to control the mean climate of the coupled system, and in one configuration of the coupled model, interannual variability in the tropical Pacific is dominated by westward moving anomalies. Through a series of experiments in which the equatorial ocean wave speeds and ocean-atmosphere coupling strength are varied, it is demonstrated that these westward moving disturbances are probably some manifestation of what Neelin describes as an {open_quotes}SST mode.{close_quotes} By modifying the flux correction procedure, the mean climate of the coupled model can be changed. A fairly modest change in the mean climate is all that is required to excite eastward moving anomalies in place of the westward moving SST modes found previously. The apparent sensitivity of the nature of tropical interannual variability to the mean climate state in a coupled general circulation model such as that used here suggests that caution is advisable if we try to use such models to answer questions relating to changes in ENSO-like variability associated with global climate change. 41 refs., 23 figs., 1 tab.

  11. Projections of Climate Change over China for the 21st Century

    Institute of Scientific and Technical Information of China (English)

    LUO Yong; ZHAO Zongci; XU Ying; GAO Xuejie; DING Yihui

    2005-01-01

    The projections of climate changes in China for the 21st century by about 40 climate scenarios and multi-model ensembles have been investigated in this research. All the models with the different scenarios project a warming of 1.2℃ to 9.2℃ in China by the end of 21st century. Most of the projections point show the increasing of precipitation in China for the 21st century.

  12. Changes in atmospheric variability in a glacial climate and the impacts on proxy data: a model intercomparison

    Directory of Open Access Journals (Sweden)

    F. S. R. Pausata

    2009-09-01

    Full Text Available Using four different climate models, we investigate sea level pressure variability in the extratropical North Atlantic in the preindustrial climate (1750 AD and at the Last Glacial Maximum (LGM, 21 kyrs before present in order to understand how changes in atmospheric circulation can affect signals recorded in climate proxies.

    In general, the models exhibit a significant reduction in interannual variance of sea level pressure at the LGM compared to pre-industrial simulations and this reduction is concentrated in winter. For the preindustrial climate, all models feature a similar leading mode of sea level pressure variability that resembles the leading mode of variability in the instrumental record: the North Atlantic Oscillation (NAO. In contrast, the leading mode of sea level pressure variability at the LGM is model dependent, but in each model different from that in the preindustrial climate. In each model, the leading (NAO-like mode of variability explains a smaller fraction of the variance and also less absolute variance at the LGM than in the preindustrial climate.

    The models show that the relationship between atmospheric variability and surface climate (temperature and precipitation variability change in different climates. Results are model-specific, but indicate that proxy signals at the LGM may be misinterpreted if changes in the spatial pattern and seasonality of surface climate variability are not taken into account.

  13. Transient nature of late Pleistocene climate variability.

    Science.gov (United States)

    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.

  14. Effect of climate variables on cocoa black pod incidence in Sabah using ARIMAX model

    Science.gov (United States)

    Ling Sheng Chang, Albert; Ramba, Haya; Mohd. Jaaffar, Ahmad Kamil; Kim Phin, Chong; Chong Mun, Ho

    2016-06-01

    Cocoa black pod disease is one of the major diseases affecting the cocoa production in Malaysia and also around the world. Studies have shown that the climate variables have influenced the cocoa black pod disease incidence and it is important to quantify the black pod disease variation due to the effect of climate variables. Application of time series analysis especially auto-regressive moving average (ARIMA) model has been widely used in economics study and can be used to quantify the effect of climate variables on black pod incidence to forecast the right time to control the incidence. However, ARIMA model does not capture some turning points in cocoa black pod incidence. In order to improve forecasting performance, other explanatory variables such as climate variables should be included into ARIMA model as ARIMAX model. Therefore, this paper is to study the effect of climate variables on the cocoa black pod disease incidence using ARIMAX model. The findings of the study showed ARIMAX model using MA(1) and relative humidity at lag 7 days, RHt - 7 gave better R square value compared to ARIMA model using MA(1) which could be used to forecast the black pod incidence to assist the farmers determine timely application of fungicide spraying and culture practices to control the black pod incidence.

  15. Catchments' hedging strategy on evapotranspiration for climatic variability

    Science.gov (United States)

    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.

  16. Climate change in Australia: technical report 2007

    International Nuclear Information System (INIS)

    2007-01-01

    The purpose of this report is to provide an up-to-date assessment of observed climate change over Australia, the likely causes, and projections of future changes to Australia's climate. It also provides information on how to apply the projections in impact studies and in risk assessments. The two main strategies for managing climate risk are mitigation (net reductions in greenhouse gas emissions) to slow climate change and adaptation to climate impacts that are unavoidable. A number of major advances have been made since the last report on climate change projections in Australia (CSIRO 2001) including: a much larger number of climate and ocean variables are projected (21 and 6 respectively); a much larger number (23) of climate models are used; the provision of probabilistic information on some of the projections, including the probability of exceeding the 10th, 50th and 90th percentiles; greater emphasis on projections from models that are better able to simulate observed Australian climate; a detailed assessment of observed changes in Australian climate and likely causes; and information on risk assessment, to provide guidance for using climate projections in impact studies

  17. Projected impacts of climate change on marine fish and fisheries

    DEFF Research Database (Denmark)

    Hollowed, Anne B.; Barange, Manuel; Beamish, Richard J.

    2013-01-01

    This paper reviews current literature on the projected effects of climate change on marine fish and shellfish, their fisheries, and fishery-dependent communities throughout the northern hemisphere. The review addresses the following issues: (i) expected impacts on ecosystem productivity and habitat......) implications for food security and associated changes; and (v) uncertainty and modelling skill assessment. Climate change will impact fish and shellfish, their fisheries, and fishery-dependent communities through a complex suite of linked processes. Integrated interdisciplinary research teams are forming...... in many regions to project these complex responses. National and international marine research organizations serve a key role in the coordination and integration of research to accelerate the production of projections of the effects of climate change on marine ecosystems and to move towards a future where...

  18. Inflated Uncertainty in Multimodel-Based Regional Climate Projections

    Science.gov (United States)

    Madsen, Marianne Sloth; Langen, Peter L.; Boberg, Fredrik; Christensen, Jens Hesselbjerg

    2017-11-01

    Multimodel ensembles are widely analyzed to estimate the range of future regional climate change projections. For an ensemble of climate models, the result is often portrayed by showing maps of the geographical distribution of the multimodel mean results and associated uncertainties represented by model spread at the grid point scale. Here we use a set of CMIP5 models to show that presenting statistics this way results in an overestimation of the projected range leading to physically implausible patterns of change on global but also on regional scales. We point out that similar inconsistencies occur in impact analyses relying on multimodel information extracted using statistics at the regional scale, for example, when a subset of CMIP models is selected to represent regional model spread. Consequently, the risk of unwanted impacts may be overestimated at larger scales as climate change impacts will never be realized as the worst (or best) case everywhere.

  19. Understanding surface-water availability in the Central Valley as a means to projecting future groundwater storage with climate variability

    Science.gov (United States)

    Goodrich, J. P.; Cayan, D. R.

    2017-12-01

    California's Central Valley (CV) relies heavily on diverted surface water and groundwater pumping to supply irrigated agriculture. However, understanding the spatiotemporal character of water availability in the CV is difficult because of the number of individual farms and local, state, and federal agencies involved in using and managing water. Here we use the Central Valley Hydrologic Model (CVHM), developed by the USGS, to understand the relationships between climatic variability, surface water inputs, and resulting groundwater use over the historical period 1970-2013. We analyzed monthly surface water diversion data from >500 CV locations. Principle components analyses were applied to drivers constructed from meteorological data, surface reservoir storage, ET, land use cover, and upstream inflows, to feed multiple regressions and identify factors most important in predicting surface water diversions. Two thirds of the diversion locations ( 80% of total diverted water) can be predicted to within 15%. Along with monthly inputs, representations of cumulative precipitation over the previous 3 to 36 months can explain an additional 10% of variance, depending on location, compared to results that excluded this information. Diversions in the southern CV are highly sensitive to inter-annual variability in precipitation (R2 = 0.8), whereby more surface water is used during wet years. Until recently, this was not the case in the northern and mid-CV, where diversions were relatively constant annually, suggesting relative insensitivity to drought. In contrast, this has important implications for drought response in southern regions (eg. Tulare Basin) where extended dry conditions can severely limit surface water supplies and lead to excess groundwater pumping, storage loss, and subsidence. In addition to fueling our understanding of spatiotemporal variability in diversions, our ability to predict these water balance components allows us to update CVHM predictions before

  20. Coral Reef Habitat Suitability in Future Climate Scenarios from NCAR CESM1 considering a Suite of Biogeochemical Variables

    Science.gov (United States)

    Freeman, L. A.; Kleypas, J. A.; Miller, A. J.

    2013-12-01

    A maximum entropy species distribution model (Maxent) is used to describe coral reef habitat in current climate conditions and to predict changes to that habitat during the 21st century. Two climate change scenarios (RCP4.5 and RCP8.5) from the National Center for Atmospheric Research's Community Earth System Model version 1 (CESM1) were used with Maxent to determine environmental suitability for the family of corals Scleractina in 1° by 1° cells. Input environmental variables most suitable for representing coral habitat limitation are isolated using a principal component analysis and include cumulative thermal stress, salinity, light availability, current speed, phosphate levels and aragonite saturation state. Considering a suite of environmental variables allows for a more synergistic view of future habitat suitability, although individual variables are found to be limiting in certain areas- for example, aragonite saturation state is limiting at higher latitudes. Climate-driven coral reef habitat changes depend strongly on the oceanic region of interest and the region of corals used to train the niche model. Increased global coral habitat loss occurred in both RCP4.5 and RCP8.5 climate projections as time progressed through the 21th century. Maximum suitable habitat loss was 82% by 2100 for RCP8.5. When only Caribbean/Atlantic coral reef environmental data is applied globally, 88% of global habitat was lost by 2100 for RCP8.5. The global runs utilizing only Pacific Ocean reefs' ability to survive showed the most significant worldwide loss, 90% by 2100 for RCP8.5. When Maxent was trained with Indian Ocean reefs, an increase in suitable habitat worldwide was estimated. Habitat suitability was found to increase by 38% in RCP4.5 by 2100 and 28% in RCP8.5 by 2050. This suggests that shallow tropical sites in the Indian Ocean basin experience conditions today that are most similar to future worldwide climate projections. Indian Ocean reefs may be ideal candidate

  1. Projected climate change impacts in rainfall erosivity over Brazil

    Science.gov (United States)

    Climate change projections and historical analyses have shown alterations in global precipitation dynamics, and therefore, it is also expected that there will be associated changes to soil erosion rates. The impacts of climate change on soil erosion may bring serious economic, social, and environmen...

  2. Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

    Science.gov (United States)

    Wang, Weile; Nemani, Ramakrishna R.; Michaelis, Andrew; Hashimoto, Hirofumi; Dungan, Jennifer L.; Thrasher, Bridget L.; Dixon, Keith W.

    2016-01-01

    The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km x 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

  3. Causes of decadal climate variability over the North Pacific and North America

    International Nuclear Information System (INIS)

    Latif, M.; Barnett, T.P.

    1994-01-01

    The cause of decadal climate variability over the North Pacific and North America is investigated by analyzing data from a multi-decadal integration with a state of the art coupled ocean-atmosphere model and observations. About one third of the low-frequency climate variability in the region of interest can be attributed to a cycle involving unstable air-sea interactions between the subtropical gyre circulation in the North Pacific and the Aleutian low pressure system. The existence of this cycle provides a basis for long-range climate forecasting over the western United States at decadal time scales. (orig.)

  4. Millennial- to century-scale variability in Gulf of Mexico Holocene climate records

    Science.gov (United States)

    Poore, R.Z.; Dowsett, H.J.; Verardo, S.; Quinn, T.M.

    2003-01-01

    Proxy records from two piston cores in the Gulf of Mexico (GOM) provide a detailed (50-100 year resolution) record of climate variability over the last 14,000 years. Long-term (millennial-scale) trends and changes are related to the transition from glacial to interglacial conditions and movement of the average position of the Intertropical Convergence Zone (ITCZ) related to orbital forcing. The ??18O of the surface-dwelling planktic foraminifer Globigerinoides ruber show negative excursions between 14 and 10.2 ka (radiocarbon years) that reflect influx of meltwater into the western GOM during melting of the Laurentide Ice Sheet. The relative abundance of the planktic foraminifer Globigerinoides sacculifer is related to transport of Caribbean water into the GOM. Maximum transport of Caribbean surface waters and moisture into the GOM associated with a northward migration of the average position of the ITCZ occurs between about 6.5 and 4.5 ka. In addition, abundance variations of G. sacculifer show century-scale variability throughout most of the Holocene. The GOM record is consistent with records from other areas, suggesting that century-scale variability is a pervasive feature of Holocene climate. The frequency of several cycles in the climate records is similar to cycles identified in proxy records of solar variability, indicating that at least some of the century-scale climate variability during the Holocene is due to external (solar) forcing.

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

    Science.gov (United States)

    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...

  6. Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda, Northwest Ethiopia

    Directory of Open Access Journals (Sweden)

    Menberu Teshome

    2018-04-01

    Full Text Available Climate variability is the fluctuation of climatic elements from the normal or baseline values. Agrarian communities are the most sensitive social groups to climate variability and associate extreme weather-induced hazards due to the fact that climate variability affects the two most important direct agricultural production inputs, such as rainfall and temperature. As Ethiopia is heavily dependent on agriculture its economic development is being hindered by climate variability coupled with many other deriving forces. Therefore, the objective of this study is to examine climate variability, local communities’ perceptions and land management strategies to reduce the adverse impact of climate variability in Lay Gayint Woreda, Ethiopia. Both primary and secondary data were used to complete this study. Primary data were collected and analyzed from a total of 200 randomly selected respondents reside in different agro-ecological areas. Metrology data were gathered from Nefas Mewcha Station from the years 1979 to 2010. Standardized rainfall anomaly index (SRAI, crop diversification index (CDI and other descriptive statistical techniques were used to analyze the data. The results obtained from the climate data revealed an increase in temperature, and decrease and/or erratic in rainfall distribution. Time series SRAI from 1979 to 2010 indicates that 2002 and 2008 were characterized by extreme and severe dry conditions in order of importance with high impact on crop yields whist only 1984 and 1990 received near normal rainfall amount. Similarly, the survey result reveals that out of the total household heads, 87.5 % perceived that there was an increase in temperature over the last 20 years. The survey result also disclosed that significant numbers of households are more likely to adopt different land management strategies to reduce the negative impact of climate variability. Constructing terraces and check dams as well as planting trees were the major

  7. Spatial variability in growth-increment chronologies of long-lived freshwater mussels: Implications for climate impacts and reconstructions

    Science.gov (United States)

    Black, Bryan A.; Dunham, Jason B.; Blundon, Brett W.; Raggon, Mark F.; Zima, Daniela

    2010-01-01

    Estimates of historical variability in river ecosystems are often lacking, but long-lived freshwater mussels could provide unique opportunities to understand past conditions in these environments. We applied dendrochronology techniques to quantify historical variability in growth-increment widths in valves (shells) of western pearlshell freshwater mussels (Margaritifera falcata). A total of 3 growth-increment chronologies, spanning 19 to 26 y in length, were developed. Growth was highly synchronous among individuals within each site, and to a lesser extent, chronologies were synchronous among sites. All 3 chronologies negatively related to instrumental records of stream discharge, while correlations with measures of water temperature were consistently positive but weaker. A reconstruction of stream discharge was performed using linear regressions based on a mussel growth chronology and the regional Palmer Drought Severity Index (PDSI). Models based on mussel growth and PDSI yielded similar coefficients of prediction (R2Pred) of 0.73 and 0.77, respectively, for predicting out-ofsample observations. From an ecological perspective, we found that mussel chronologies provided a rich source of information for understanding climate impacts. Responses of mussels to changes in climate and stream ecosystems can be very site- and process-specific, underscoring the complex nature of biotic responses to climate change and the need to understand both regional and local processes in projecting climate impacts on freshwater species.

  8. The World Climate Project: Bringing the UN Climate Negotiations to Classrooms, Boardrooms, and Living Rooms Near You

    Science.gov (United States)

    Rath, K.; Rooney-varga, J. N.; Jones, A.; Johnston, E.; Sterman, J.

    2015-12-01

    As a simulation-based role-playing exercise, World Climate provides an opportunity for participants to have an immersive experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the geophysical dynamics of the climate system, through an interactive computer simulation. In June 2015, we launched the World Climate Project with the intent of bringing this powerful tool to students, citizens, and decision-makers across government, NGO, and private sectors around the world. Within a period of six weeks from the launch date, 440 educators from 36 states and 56 countries have enrolled in the initiative, offering the potential to reach tens of thousands of participants around the world. While this project is clearly in its infancy, we see several characteristics that may be contributing to widespread interest in it. These factors include the ease-of-use, real-world relevance, and scientific rigor of the decision-support simulation, C-ROADS, that frames the World Climate Exercise. Other characteristics of World Climate include its potential to evoke an emotional response that is arousing and inspirational and its use of positive framing and a call to action. Similarly, the World Climate Project takes a collaborative approach, enabling educators to be innovators and valued contributors and regularly communicating with people who join the initiative through webinars, social media, and resources.

  9. The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate

    Energy Technology Data Exchange (ETDEWEB)

    Flato, G.M.; Boer, G.J.; Lee, W.G.; McFarlane, N.A.; Ramsden, D.; Reader, M.C. [Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); Weaver, A.J. [School of Earth and Ocean Sciences, University of Victoria, BC (Canada)

    2000-06-01

    A global, three-dimensional climate model, developed by coupling the CCCma second-generation atmospheric general circulation model (GCM2) to a version of the GFDL modular ocean model (MOM1), forms the basis for extended simulations of past, current and projected future climate. The spin-up and coupling procedures are described, as is the resulting climate based on a 200 year model simulation with constant atmospheric composition and external forcing. The simulated climate is systematically compared to available observations in terms of mean climate quantities and their spatial patterns, temporal variability, and regional behavior. Such comparison demonstrates a generally successful reproduction of the broad features of mean climate quantities, albeit with local discrepancies. Variability is generally well-simulated over land, but somewhat underestimated in the tropical ocean and the extratropical storm-track regions. The modelled climate state shows only small trends, indicating a reasonable level of balance at the surface, which is achieved in part by the use of heat and freshwater flux adjustments. The control simulation provides a basis against which to compare simulated climate change due to historical and projected greenhouse gas and aerosol forcing as described in companion publications. (orig.)

  10. Towards implementing climate services in Peru – The project CLIMANDES

    Directory of Open Access Journals (Sweden)

    G. Rosas

    2016-12-01

    The efforts accomplished within CLIMANDES improved the quality of the climate services provided by SENAMHI. The project hence contributed successfully to higher awareness and higher confidence in the climate information by SENAMHI.

  11. Climate variability and vadose zone controls on damping of transient recharge

    Science.gov (United States)

    Corona, Claudia R.; Gurdak, Jason J.; Dickinson, Jesse; Ferré, T.P.A.; Maurer, Edwin P.

    2017-01-01

    Increasing demand on groundwater resources motivates understanding of the controls on recharge dynamics so model predictions under current and future climate may improve. Here we address questions about the nonlinear behavior of flux variability in the vadose zone that may explain previously reported teleconnections between global-scale climate variability and fluctuations in groundwater levels. We use hundreds of HYDRUS-1D simulations in a sensitivity analysis approach to evaluate the damping depth of transient recharge over a range of periodic boundary conditions and vadose zone geometries and hydraulic parameters that are representative of aquifer systems of the conterminous United States (U.S). Although the models were parameterized based on U.S. aquifers, findings from this study are applicable elsewhere that have mean recharge rates between 3.65 and 730 mm yr–1. We find that mean infiltration flux, period of time varying infiltration, and hydraulic conductivity are statistically significant predictors of damping depth. The resulting framework explains why some periodic infiltration fluxes associated with climate variability dampen with depth in the vadose zone, resulting in steady-state recharge, while other periodic surface fluxes do not dampen with depth, resulting in transient recharge. We find that transient recharge in response to the climate variability patterns could be detected at the depths of water levels in most U.S. aquifers. Our findings indicate that the damping behavior of transient infiltration fluxes is linear across soil layers for a range of texture combinations. The implications are that relatively simple, homogeneous models of the vadose zone may provide reasonable estimates of the damping depth of climate-varying transient recharge in some complex, layered vadose zone profiles.

  12. The double tragedy of agriculture vulnerability to climate variability in Africa: How vulnerable is smallholder agriculture to rainfall variability in Ghana?

    Directory of Open Access Journals (Sweden)

    Emmanuel K. Derbile

    2016-04-01

    Full Text Available This article analysed vulnerability of smallholder agriculture to climate variability, particularly the alternating incidences of drought and heavy precipitation events in Ghana. Although there is an unmet need for understanding the linkages between climate change and livelihoods, the urgent need for climate change adaptation planning (CCAP in response to climate change makes vulnerability assessment even more compelling in development research. The data for analysis were collected from two complementary studies. These included a regional survey in the Upper West Region and an in-depth study in three selected communities in the Sissala East District. The results showed that smallholder agriculture is significantly vulnerable to climate variability in the region and that three layers of vulnerability can be identified in a ladder of vulnerability. Firstly, farmers are confronted with the double tragedy of droughts and heavy precipitation events, which adversely affect both crops and livestock. Secondly, farmers have to decide on crops for adaptation, but each option – whether indigenous crops, new early-maturing crops or genetically modified crops – predisposes farmers to a different set of risks. Finally, the overall impact is a higher-level vulnerability, namely the risk of total livelihood failure and food insecurity. The article recommended CCAP and an endogenous development (ED approach to addressing agriculture vulnerability to climate variability within the framework of decentralisation and local governance in Ghana. Keywords: Climate variability; agriculture; vulnerability; endogenous development; Ghana

  13. Improving Climate Projections by Understanding How Cloud Phase affects Radiation

    Science.gov (United States)

    Cesana, Gregory; Storelvmo, Trude

    2017-01-01

    Whether a cloud is predominantly water or ice strongly influences interactions between clouds and radiation coming down from the Sun or up from the Earth. Being able to simulate cloud phase transitions accurately in climate models based on observational data sets is critical in order to improve confidence in climate projections, because this uncertainty contributes greatly to the overall uncertainty associated with cloud-climate feedbacks. Ultimately, it translates into uncertainties in Earth's sensitivity to higher CO2 levels. While a lot of effort has recently been made toward constraining cloud phase in climate models, more remains to be done to document the radiative properties of clouds according to their phase. Here we discuss the added value of a new satellite data set that advances the field by providing estimates of the cloud radiative effect as a function of cloud phase and the implications for climate projections.

  14. Examining the impact of climate change and variability on sweet potatoes in East Africa

    Science.gov (United States)

    Ddumba, S. D.; Andresen, J.; Moore, N. J.; Olson, J.; Snapp, S.; Winkler, J. A.

    2013-12-01

    Climate change is one of the biggest challenges to food security for the rapidly increasing population of East Africa. Rainfall is becoming more variable and temperatures are rising, consequently leading to increased occurrence of droughts and floods, and, changes in the timing and length of growing seasons. These changes have serious implications on crop production with the greatest impact likely to be on C4 crops such as cereals compared to C3 crops such as root tubers. Sweet potatoes is one the four most important food crops in East Africa owing to its high nutrition and calorie content, and, high tolerance to heat and drought, but little is known about how the crop will be affected by climate change. This study identifies the major climatic constraints to sweet potato production and examines the impact of projected future climates on sweet potato production in East Africa during the next 10 to 30 years. A process-based Sweet POTato COMputer Simulation (SPOTCOMS) model is used to assess four sweet potato cultivars; Naspot 1, Naspot 10, Naspot 11 and SPK 004-Ejumula. This is work in progress but preliminary results from the crop modeling experiments and the strength and weakness of the crop model will be presented.

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

    DEFF Research Database (Denmark)

    Fountoulakis, Konstantinos N; Chatzikosta, Isaia; Pastiadis, Konstantinos

    2016-01-01

    BACKGROUND: 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. METHODS: 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. RESULTS......: 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...

  16. Climatic Action Plan Project for the state of Veracruz (Mexico)

    Science.gov (United States)

    Tejeda, A.; Ochoa, C.

    2007-05-01

    power stations (Tuxpan and Laguna Verde) will be affected directly if they're still operating within half century. The lagoons of Alvarado and Tamiahua will be part of the sea. In heavy numbers, more than six hundred kilometers of beaches will be lost (and, of course, good part of the tourist infrastructure including Costa Esmeralda and Veracruz Boca del Río), along with more than two hundred kilometers of routes and around twenty kilometers of seaports. More than three thousand urban hectares will become floodable as two hundred thousand fields and agriculture. Because of all this, a study is proposed that considers a revision of the state's variability and climatic change in Veracruz; an inventory of GEI emissions and its respective scenes; data bases with quality control and analysis of climatic variability; regional climatic scenes (years 2025, 2050 and 2075), and scenes of vulnerability and adaptation measures, mitigation in coast affectations and coastal infrastructure, water availability, biodiversity, agriculture, human establishments and energy consumption by air conditioning of houses. Approaches of the study will be discussed and advances during the first semester of the project will appear in this presentation.

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

    Science.gov (United States)

    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

  18. Present and Future Projections of Habitat Suitability of the Asian Tiger Mosquito, a Vector of Viral Pathogens, from Global Climate Simulations.

    Science.gov (United States)

    Proestos, Y.; Christophides, G.; Erguler, K.; Tanarhte, M.; Waldock, J.; Lelieveld, J.

    2014-12-01

    Climate change can influence the transmission of vector borne diseases (VBDs) through altering the habitat suitability of insect vectors. Here we present global climate model simulations and evaluate the associated uncertainties in view of the main meteorological factors that may affect the distribution of the Asian Tiger mosquito (Aedes albopictus), which can transmit pathogens that cause Chikungunya, Dengue fever, yellow fever and various encephalitides. Using a general circulation model (GCM) at 50 km horizontal resolution to simulate mosquito survival variables including temperature, precipitation and relative humidity, we present both global and regional projections of the habitat suitability up to the middle of the 21st century. The model resolution of 50 km allows evaluation against previous projections for Europe and provides a basis for comparative analyses with other regions. Model uncertainties and performance are addressed in light of the recent CMIP5 ensemble climate model simulations for the RCP8.5 concentration pathway and using meteorological re-analysis data (ERA-Interim/ECMWF) for the recent past. Uncertainty ranges associated with the thresholds of meteorological variables that may affect the distribution of Ae. albopictus are diagnosed using fuzzy-logic methodology, notably to assess the influence of selected meteorological criteria and combinations of criteria that influence mosquito habitat suitability. From the climate projections for 2050, and adopting a habitat suitability index larger than 70%, we estimate that about 2.4 billion individuals in a land area of nearly 20 million square kilometres will potentially be exposed to Ae. albopictus. The synthesis of fuzzy-logic based on mosquito biology and climate change analysis provides new insights into the regional and global spreading of VBDs to support disease control and policy making.

  19. Development of Joint Climate and Discharge Projections for the International Rhine River Basin - the CHR RheinBlick2050 Project

    Science.gov (United States)

    Görgen, K.; Pfister, L.

    2008-12-01

    The anticipated climate change will lead to modified hydro-meteorological regimes that influence discharge behaviour and hydraulics of rivers. This has variable impacts on managed (anthropogenic) and unmanaged (natural) systems, depending on their sensitivity and vulnerability (ecology, economy, infrastructure, transport, energy production, water management, etc.). Decision makers in these contexts need adequate adaptation strategies to minimize adverse effects of climate change, i.e. an improved knowledge on the potential impacts including uncertainties means an extension of the informed options open to users. The goal of the highly applied study presented here is the development of joint, consistent climate and discharge projections for the international Rhine River catchments (Switzerland, France, Germany, Netherlands) in order to assess future changes of hydro-meteorological regimes in the meso- and macroscale Rhine River catchments and to derive and improve the understanding of such impacts on hydrologic and hydraulic processes. The RheinBlick2050 project is an international effort initiated by the International Commission for the Hydrology of the Rhine Basin (CHR) in close cooperation with the International Commission for the Protection of the Rhine. The core experiment design foresees a data-synthesis, multi-model approach where (transient) (bias- corrected) regional climate change projections are used as forcing data for existing calibrated hydrological (and hydraulic) models at a daily temporal resolution over mesoscale catchments of the Rhine River. Mainly for validation purposes, hydro-meteorological observations from national weather services are compiled into a new consistent 5 km x 5 km reference dataset from 1961 to 2005. RCM data are mainly used from the ENSEMBLES project and other existing dynamical downscaling model runs to derive probabilistic ensembles and thereby also access uncertainties on a regional scale. A benchmarking is helping to

  20. Climate change and watershed mercury export: a multiple projection and model analysis.

    Science.gov (United States)

    Golden, Heather E; Knightes, Christopher D; Conrads, Paul A; Feaster, Toby D; Davis, Gary M; Benedict, Stephen T; Bradley, Paul M

    2013-09-01

    Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling. Copyright © 2013 SETAC.

  1. Climate change and watershed mercury export: a multiple projection and model analysis

    Science.gov (United States)

    Golden, Heather E.; Knightes, Christopher D.; Conrads, Paul; Feaster, Toby D.; Davis, Gary M.; Benedict, Stephen T.; Bradley, Paul M.

    2013-01-01

    Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

  2. Matching species traits to projected threats and opportunities from climate change

    DEFF Research Database (Denmark)

    Garcia, Raquel A.; Bastos, Miguel; Burgess, Neil David

    2014-01-01

    Aim Climate change can lead to decreased climatic suitability within species' distributions, increased fragmentation of climatically suitable space, and/or emergence of newly suitable areas outside present distributions. Each of these extrinsic threats and opportunities potentially interacts...... with specific intrinsic traits of species, yet this specificity is seldom considered in risk assessments. We present an analytical framework for examining projections of climate change-induced threats and opportunities with reference to traits that are likely to mediate species' responses, and illustrate...... of a framework combining spatial projections of climate change exposure with traits that are likely to mediate species' responses. Although the proposed framework carries several assumptions that require further scrutiny, its application adds a degree of realism to familiar assessments that consider all species...

  3. High Variability Is a Defining Component of Mediterranean-Climate Rivers and Their Biota

    Directory of Open Access Journals (Sweden)

    Núria Cid

    2017-01-01

    Full Text Available Variability in flow as a result of seasonal precipitation patterns is a defining element of streams and rivers in Mediterranean-climate regions of the world and strongly influences the biota of these unique systems. Mediterranean-climate areas include the Mediterranean Basin and parts of Australia, California, Chile, and South Africa. Mediterranean streams and rivers can experience wet winters and consequent floods to severe droughts, when intermittency in otherwise perennial systems can occur. Inter-annual variation in precipitation can include multi-year droughts or consecutive wet years. Spatial variation in patterns of precipitation (rain vs. snow combined with topographic variability lead to spatial variability in hydrologic patterns that influence populations and communities. Mediterranean streams and rivers are global biodiversity hotspots and are particularly vulnerable to human impacts. Biomonitoring, conservation efforts, and management responses to climate change require approaches that account for spatial and temporal variability (including both intra- and inter-annual. The importance of long-term data sets for understanding and managing these systems highlights the need for sustained and coordinated research efforts in Mediterranean-climate streams and rivers.

  4. Sustainable Relations in International Development Cooperation Projects: The Role of Organizational Climate

    Directory of Open Access Journals (Sweden)

    Cosimo Rota

    2011-10-01

    Full Text Available  The importance of the human side of project management to assess the success of international development project has not been fully considered yet. An analysis of the literature on the project success definition, focused on the success criteria and success factors, was carried out. The organization’s effectiveness, in terms of Relations Sustainability, emerged as a criteria integrating the "time, cost, performance" approach to define a project success. Based on previous research contributions on the factors influencing the organization’s effectiveness, the paper expands the analysis of the influence of Organizational Climate on the Relation Sustainability between project manager and project team involved in international cooperation for development. The statistical methods used include confirmatory factors analysis and structural equation modeling. The results carry implications for project management identifying five dimensions of Organizational Climate (trust, innovation, social cohesion, communication and job challenge influencing Relations Sustainability. This finding suggests that Organizational Climate contributes to project success by creating trust, stimulating commitment and generating satisfaction to overcome conflicts between project manager and project team.

  5. Can model weighting improve probabilistic projections of climate change?

    Energy Technology Data Exchange (ETDEWEB)

    Raeisaenen, Jouni; Ylhaeisi, Jussi S. [Department of Physics, P.O. Box 48, University of Helsinki (Finland)

    2012-10-15

    Recently, Raeisaenen and co-authors proposed a weighting scheme in which the relationship between observable climate and climate change within a multi-model ensemble determines to what extent agreement with observations affects model weights in climate change projection. Within the Third Coupled Model Intercomparison Project (CMIP3) dataset, this scheme slightly improved the cross-validated accuracy of deterministic projections of temperature change. Here the same scheme is applied to probabilistic temperature change projection, under the strong limiting assumption that the CMIP3 ensemble spans the actual modeling uncertainty. Cross-validation suggests that probabilistic temperature change projections may also be improved by this weighting scheme. However, the improvement relative to uniform weighting is smaller in the tail-sensitive logarithmic score than in the continuous ranked probability score. The impact of the weighting on projection of real-world twenty-first century temperature change is modest in most parts of the world. However, in some areas mainly over the high-latitude oceans, the mean of the distribution is substantially changed and/or the distribution is considerably narrowed. The weights of individual models vary strongly with location, so that a model that receives nearly zero weight in some area may still get a large weight elsewhere. Although the details of this variation are method-specific, it suggests that the relative strengths of different models may be difficult to harness by weighting schemes that use spatially uniform model weights. (orig.)

  6. How ocean lateral mixing changes Southern Ocean variability in coupled climate models

    Science.gov (United States)

    Pradal, M. A. S.; Gnanadesikan, A.; Thomas, J. L.

    2016-02-01

    The lateral mixing of tracers represents a major uncertainty in the formulation of coupled climate models. The mixing of tracers along density surfaces in the interior and horizontally within the mixed layer is often parameterized using a mixing coefficient ARedi. The models used in the Coupled Model Intercomparison Project 5 exhibit more than an order of magnitude range in the values of this coefficient used within the Southern Ocean. The impacts of such uncertainty on Southern Ocean variability have remained unclear, even as recent work has shown that this variability differs between different models. In this poster, we change the lateral mixing coefficient within GFDL ESM2Mc, a coarse-resolution Earth System model that nonetheless has a reasonable circulation within the Southern Ocean. As the coefficient varies from 400 to 2400 m2/s the amplitude of the variability varies significantly. The low-mixing case shows strong decadal variability with an annual mean RMS temperature variability exceeding 1C in the Circumpolar Current. The highest-mixing case shows a very similar spatial pattern of variability, but with amplitudes only about 60% as large. The suppression of mixing is larger in the Atlantic Sector of the Southern Ocean relatively to the Pacific sector. We examine the salinity budgets of convective regions, paying particular attention to the extent to which high mixing prevents the buildup of low-saline waters that are capable of shutting off deep convection entirely.

  7. Climate change impacts on projections of excess mortality at ...

    Science.gov (United States)

    We project the change in ozone-related mortality burden attributable to changes in climate between a historical (1995-2005) and near-future (2025-2035) time period while incorporating a non-linear and synergistic effect of ozone and temperature on mortality. We simulate air quality from climate projections varying only biogenic emissions and holding anthropogenic emissions constant, thus attributing changes in ozone only to changes in climate and independent of changes in air pollutant emissions. We estimate non-linear, spatially varying, ozone-temperature risk surfaces for 94 US urban areas using observeddata. Using the risk surfaces and climate projections we estimate daily mortality attributable to ozone exceeding 40 p.p.b. (moderate level) and 75 p.p.b. (US ozone NAAQS) for each time period. The average increases in city-specific median April-October ozone and temperature between time periods are 1.02 p.p.b. and 1.94 °F; however, the results variedby region . Increases in ozone because of climate change result in an increase in ozone mortality burden. Mortality attributed to ozone exceeding 40 p.p.b. increases by 7.7% (1 .6-14.2%). Mortality attributed to ozone exceeding 75 p.p.b. increases by 14.2% (1.628.9%). The absolute increase in excess ozone mortality is larger for changes in moderate ozone levels, reflecting the larger number of days with moderate ozone levels. In this study we evaluate changes in ozone related mortality due to changes in biogenic f

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

    Science.gov (United States)

    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

  9. Future changes in peak river flows across northern Eurasia as inferred from an ensemble of regional climate projections under the IPCC RCP8.5 scenario

    Science.gov (United States)

    Shkolnik, Igor; Pavlova, Tatiana; Efimov, Sergey; Zhuravlev, Sergey

    2018-01-01

    Climate change simulation based on 30-member ensemble of Voeikov Main Geophysical Observatory RCM (resolution 25 km) for northern Eurasia is used to drive hydrological model CaMa-Flood. Using this modeling framework, we evaluate the uncertainties in the future projection of the peak river discharge and flood hazard by 2050-2059 relative to 1990-1999 under IPCC RCP8.5 scenario. Large ensemble size, along with reasonably high modeling resolution, allows one to efficiently sample natural climate variability and increase our ability to predict future changes in the hydrological extremes. It has been shown that the annual maximum river discharge can almost double by the mid-XXI century in the outlets of major Siberian rivers. In the western regions, there is a weak signal in the river discharge and flood hazard, hardly discernible above climate variability. Annual maximum flood area is projected to increase across Siberia mostly by 2-5% relative to the baseline period. A contribution of natural climate variability at different temporal scales to the uncertainty of ensemble prediction is discussed. The analysis shows that there expected considerable changes in the extreme river discharge probability at locations of the key hydropower facilities. This suggests that the extensive impact studies are required to develop recommendations for maintaining regional energy security.

  10. Food Prices and Climate Extremes: A Model of Global Grain Price Variability with Storage

    Science.gov (United States)

    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.

  11. Impact of climate variability on runoff in the north-central United States

    Science.gov (United States)

    Ryberg, Karen R.; Lin, Wei; Vecchia, Aldo V.

    2014-01-01

    Large changes in runoff in the north-central United States have occurred during the past century, with larger floods and increases in runoff tending to occur from the 1970s to the present. The attribution of these changes is a subject of much interest. Long-term precipitation, temperature, and streamflow records were used to compare changes in precipitation and potential evapotranspiration (PET) to changes in runoff within 25 stream basins. The basins studied were organized into four groups, each one representing basins similar in topography, climate, and historic patterns of runoff. Precipitation, PET, and runoff data were adjusted for near-decadal scale variability to examine longer-term changes. A nonlinear water-balance analysis shows that changes in precipitation and PET explain the majority of multidecadal spatial/temporal variability of runoff and flood magnitudes, with precipitation being the dominant driver. Historical changes in climate and runoff in the region appear to be more consistent with complex transient shifts in seasonal climatic conditions than with gradual climate change. A portion of the unexplained variability likely stems from land-use change.

  12. Climate Change Communicators: The C3E3 Project

    Science.gov (United States)

    Sharif, H. O.; Joseph, J.

    2013-12-01

    The University of Texas at San Antonio (UTSA), San Antonio College (SAC), and the University of North Dakota (UND) have partnered with NASA to provide underrepresented undergraduates from UTSA, SAC, and other community colleges climate-related research and education experiences through the Climate Change Communication: Engineer, Environmental science, and Education (C3E3) project. The program aims to develop a robust response to climate change by providing K-16 climate change education; enhance the effectiveness of K-16 education particularly in engineering and other STEM disciplines by use of new instructional technologies; increase the enrollment in engineering programs and the number of engineering degrees awarded by showing engineering's usefulness in relation to the much-discussed contemporary issue of climate change; increase persistence in STEM degrees by providing student research opportunities; and increase the ethnic diversity of those receiving engineering degrees and help ensure an ethnically diverse response to climate change. Students participated in the second summer internship funded by the project. More than 60 students participated in guided research experiences aligned with NASA Science Plan objectives for climate and Earth system science and the educational objectives of the three institutions. The students went through training in modern media technology (webcasts), and in using this technology to communicate the information on climate change to others, especially high school students, culminating in production of webcasts on investigating the aspects of climate change using NASA data. Content developed is leveraged by NASA Earth observation data and NASA Earth system models and tools. Several departments are involved in the educational program.

  13. Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models.

    Directory of Open Access Journals (Sweden)

    Frieda Beauregard

    Full Text Available 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

  14. Ecological response of Cedrus atlantica to climate variability in the Massif of Guetiane (Algeria

    Directory of Open Access Journals (Sweden)

    Said Slimani

    2014-12-01

    Full Text Available Aim of the study: The study analyzes the long-term response of Atlas cedar, Cedrus atlantica (Manneti, to climate variability. Area of study: Atlas cedar forest of Guetiane (Batna, Algeria.Material and methods: The dendrochronological approach was adopted. An Atlas cedar tree-ring chronology was established from twenty trees. The response of the species to climate variability was assessed through the pointer years (PYs, the common climate signal among the individual chronologies, expressed by the first component (PC1, the mean sensitivity (msx, and response function and correlations analysis involving the tree-ring index and climate data (monthly mean temperature and total precipitation.Results: The highest growth variability was registered from the second half of the 20th century. The lower than the mean PYs, the PC1, and the msx increased markedly during the studied period. Dramatic increases in the PC1 and msx were detected at the end of the 1970s, reflecting a shift towards drier conditions enhancing an increasing trend towards more synchronous response of trees to climate conditions. The response function and correlations analysis showed that tree growth was mainly influenced by precipitation variability.Research highlights: Our findings provide baseline knowledge concerning the ecological response of Atlas cedar to climate variability in in its southern distribution limit, where a high level of tree mortality has been observed during recent decades, coinciding with the driest period Algeria has ever experienced. This information is vital to support ongoing ecosystem management efforts in the region. Keywords: Atlas cedar; annual growth variability; dieback; dendrochronology. 

  15. Climate variability and land cover change over the North American monsoon region (Invited)

    Science.gov (United States)

    Zeng, X.; Scheftic, W. D.; Broxton, P. D.

    2013-12-01

    The North American Monsoon System over Mexico and southwestern United States represents a weather/climate and ecosystem coupled "macrosystem". The weather and climate affect the seasonal and interannual variability of ecosystem, while the ecosystem change affects surface energy, water, and carbon fluxes that, in turn, affect weather and climate. Furthermore, long-term weather/climate data have a much coarser horizontal resolution than the satellite land cover data. Here the North American Regional Reanalysis (NARR) data at 32 km grid spacing will be combined with various satellite remote sensing products at 1 km and/or 8 km resolution from AVHRR, MODIS, and SPOT for the period of 1982 to present. Our analysis includes: a) precipitation, wind, and precipitable water data from NARR to characterize the North American monsoon; b) land cover type, normalized difference vegetation index (NDVI), green vegetation fraction, and leaf-area index (LAI) data to characterize the seasonal and interannual variability of ecosystem; c) assessing the consistency of various satellite products; and d) testing the coherence in the weather/climate and ecosystem variability.

  16. Adapting to climate variability and change: experiences from cereal-based farming in the central rift and Kobo Valleys, Ethiopia.

    Science.gov (United States)

    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

  17. Adapting to Climate Variability and Change: Experiences from Cereal-Based Farming in the Central Rift and Kobo Valleys, Ethiopia

    Science.gov (United States)

    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

  18. Partitioning inter annual variability in net ecosystem exchange between climatic variability and functional change

    International Nuclear Information System (INIS)

    Hui, D.; Luo, Y.; Katul, G.

    2003-01-01

    Inter annual variability in net ecosystem exchange of carbon is investigated using a homogeneity-of-slopes model to identify the function change contributing to inter annual variability, net ecosystem carbon exchange, and night-time ecosystem respiration. Results of employing this statistical approach to a data set collected at the Duke Forest AmeriFlux site from August 1997 to December 2001 are discussed. The results demonstrate that it is feasible to partition the variation in ecosystem carbon fluxes into direct effects of seasonal and inter annual climatic variability and functional change. 51 refs., 4 tabs., 5 figs

  19. Responses of Montane Forest to Climate Variability in the Central Himalayas of Nepal

    Directory of Open Access Journals (Sweden)

    Janardan Mainali

    2015-02-01

    Full Text Available Climate changes are having dramatic ecological impacts in mid- to high-latitude mountain ranges where growth conditions are limited by climatic variables such as duration of growing season, moisture, and ambient temperature. We document patterns of forest vegetative response for 5 major alpine forest communities to current climate variability in the central Himalayas of Nepal to provide a baseline for assessment of future changes, as well as offer some insight into the trajectory of these changes over time. We used mean monthly surface air temperature and rainfall and the monthly averaged normalized difference vegetation index (NDVI to compare relative vegetation productivity among forest types and in relation to both climatic variables. Because changes in temperature and precipitation are directly manifested as changes in phenology, we examined current vegetative responses to climate variability in an effort to determine which climate variable is most critical for different alpine forest types. Our results show that correlations differ according to vegetation type and confirm that both precipitation and temperature affect monthly NDVI values, though more significant correlations were found with temperature data. The temperature response was more consistent because at the maximum increased temperatures, there was still an ongoing increase in vegetative vigor. This indicates that temperature is still the major limiting factor for plant growth at higher-elevation sites. This part of the Himalayas has abundant moisture, and some forest types are already saturated in terms of growth in relation to precipitation. Clear increases in productivity are documented on the upper treeline ecotones, and these systems are likely to continue to have increasing growth rates.

  20. Climate variability and demand growth as drivers of water scarcity in the Turkwel river basin: a bottom-up risk assessment of a data-sparse basin in Kenya

    Science.gov (United States)

    Hirpa, F. A.; Dyer, E.; Hope, R.; Dadson, S. J.

    2017-12-01

    Sustainable water management and allocation are essential for maintaining human well-being, sustaining healthy ecosystems, and supporting steady economic growth. The Turkwel river basin, located in north-western Kenya, experiences a high level of water scarcity due to its arid climate, high rainfall variability, and rapidly growing water demand. However, due to sparse hydro-climatic data and limited literature, the water resources system of the basin has been poorly understood. Here we apply a bottom-up climate risk assessment method to estimate the resilience of the basin's water resources system to growing demand and climate stressors. First, using a water resource system model and historical climate data, we construct a climate risk map that depicts the way in which the system responds to climate change and variability. Then we develop a set of water demand scenarios to identify the conditions that potentially lead to the risk of unmet water demand and groundwater depletion. Finally, we investigate the impact of climate change and variability by stress testing these development scenarios against historically strong El Niño/Southern Oscillation (ENSO) years and future climate projections from multiple Global Circulation Models (GCMs). The results reveal that climate variability and increased water demand are the main drivers of water scarcity in the basin. Our findings show that increases in water demand due to expanded irrigation and population growth exert the strongest influence on the ability of the system to meet water resource supply requirements, and in all cases considered increase the impacts of droughts caused by future climate variability. Our analysis illustrates the importance of combining analysis of future climate risks with other development decisions that affect water resources planning. Policy and investment decisions which maximise water use efficiency in the present day are likely to impart resilience to climate change and variability under a

  1. The role of land-climate interactions for the regional amplification of temperature extremes in climate projections

    Science.gov (United States)

    Seneviratne, S. I.; Vogel, M.; Zscheischler, J.; Schwingshackl, C.; Davin, E.; Gudmundsson, L.; Guillod, B.; Hauser, M.; Hirsch, A.; Hirschi, M.; Humphrey, V.; Thiery, W.

    2017-12-01

    Regional hot extremes are projected to increase more strongly than the global mean temperature, with substantially larger changes than 2°C even if global warming is limited to this level (Seneviratne et al. 2016). This presentation will highlight the processes underlying this behavior, which is strongly related to land-climate feedbacks (Vogel et al. 2017). The identified feedbacks are also affecting the occurrence probability of compound drought and heat events (Zscheischler and Seneviratne 2017), with high relevance for impacts on forest fire and agriculture production. Moreover, the responsible land processes strongly contribute to the inter-model spread in the projections, and can thus be used to derive observations-based constraints to reduce the uncertainty of projected changes in climate extremes. Finally, we will also discuss the role of soil moisture effects on carbon uptake and their relevance for projections, as well as the role of land use changes in affecting the identified feedbacks and projected changes in climate extremes. References: Seneviratne, S.I., M. Donat, A.J. Pitman, R. Knutti, and R.L. Wilby, 2016: Allowable CO2 emissions based on regional and impact-related climate targets. Nature, 529, 477-483, doi:10.1038/nature16542. Vogel, M.M., R. Orth, F. Cheruy, S. Hagemann, R. Lorenz, B.J.J.M. Hurk, and S.I. Seneviratne, 2017: Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks. Geophysical Research Letters, 44(3), 1511-1519, doi:10.1002/2016GL071235. Zscheischler, J., and S.I. Seneviratne, 2017: Dependence of drivers affects risks associated with compound events. Science Advances, 3(6), doi: 10.1126/sciadv.1700263

  2. Impact of projected climate change on agricultural production in ...

    African Journals Online (AJOL)

    The climate change projections data from global climate models were downscaled using self-organising maps technique. Under the conventional practices, results show that during long rainy season (from March to May) there is yield decline of 13% for cultivar Situka, no change for cultivar Kito and increase of 10% and ...

  3. Climate Trends and Impacts in China

    OpenAIRE

    Chris Sall

    2013-01-01

    This discussion paper summarizes observed and projected trends in extreme weather events, present-day climate variability, and future climate change and their impacts on China's different regions. Findings are presented from China's national assessment report on climate change (2007) and second national assessment report on climate change (2011) as well as other studies by Chinese and inte...

  4. Exploiting temporal variability to understand tree recruitment response to climate change

    Science.gov (United States)

    Ines Ibanez; James S. Clark; Shannon LaDeau; Janneke Hill Ris Lambers

    2007-01-01

    Predicting vegetation shifts under climate change is a challenging endeavor, given the complex interactions between biotic and abiotic variables that influence demographic rates. To determine how current trends and variation in climate change affect seedling establishment, we analyzed demographic responses to spatiotemporal variation to temperature and soil moisture in...

  5. Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.

    Directory of Open Access Journals (Sweden)

    Valerie Steen

    Full Text Available The Prairie Pothole Region (PPR of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs. We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971-2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981-2000 and projected future distributions to climate scenarios for 2040-2049. Species were projected to, on average, lose almost half their current habitat (-46%. However, individual species projections varied widely, from +8% (Upland Sandpiper to -100% (Wilson's Snipe. Variable importance ranks indicated that land cover (wetland and upland variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.

  6. Selecting sagebrush seed sources for restoration in a variable climate: ecophysiological variation among genotypes

    Science.gov (United States)

    Germino, Matthew J.

    2012-01-01

    Big sagebrush (Artemisia tridentata) communities dominate a large fraction of the United States and provide critical habitat for a number of wildlife species of concern. Loss of big sagebrush due to fire followed by poor restoration success continues to reduce ecological potential of this ecosystem type, particularly in the Great Basin. Choice of appropriate seed sources for restoration efforts is currently unguided due to knowledge gaps on genetic variation and local adaptation as they relate to a changing landscape. We are assessing ecophysiological responses of big sagebrush to climate variation, comparing plants that germinated from ~20 geographically distinct populations of each of the three subspecies of big sagebrush. Seedlings were previously planted into common gardens by US Forest Service collaborators Drs. B. Richardson and N. Shaw, (USFS Rocky Mountain Research Station, Provo, Utah and Boise, Idaho) as part of the Great Basin Native Plant Selection and Increase Project. Seed sources spanned all states in the conterminous Western United States. Germination, establishment, growth and ecophysiological responses are being linked to genomics and foliar palatability. New information is being produced to aid choice of appropriate seed sources by Bureau of Land Management and USFS field offices when they are planning seed acquisitions for emergency post-fire rehabilitation projects while considering climate variability and wildlife needs.

  7. Study on Variations in Climatic Variables and Their Influence on Runoff in the Manas River Basin, China

    Directory of Open Access Journals (Sweden)

    Lei Ren

    2017-04-01

    Full Text Available Climate change in Northwest China could lead to the change of the hydrological cycle and water resources. This paper assessed the influence of climate change on runoff in the Manas River basin as follows. First, the temporal trends and abrupt change points of runoff, precipitation, and mean, lowest and highest temperature in yearly scale during the period of 1961–2015 were analyzed using the Mann-Kendall (MK test. Then the correlation between runoff and climatic variables was characterized in a monthly, seasonal and yearly scale using the partial correlation method. Furthermore, three global climate models (GCMs from Coupled Model Inter-comparison Project Phase 5 (CMIP5 were bias-corrected using Equidistant Cumulative Distribution Functions (EDCDF method to reveal the future climate change during the period from 2021 to 2060 compared with the baseline period of 1961–2000. The influence of climate change on runoff was studied by simulating the runoff with the GCMs using a modified TOPMODEL considering the future snowmelt during the period from 2021 to 2060. The results showed that the runoff, precipitation, and mean, lowest and highest temperature all presented an increasing trend in yearly scale during the period of 1961–2015, and their abrupt change points were at a similar time; the runoff series was more strongly related to temperature than to precipitation in the spring, autumn and yearly scales, and the opposite was true in winter. All GCMs projected precipitation and temperature, and the runoff simulated with these GCMs were predicted to increase in the period from 2021 to 2060 compared with the baseline period of 1961–2000. These findings provide valuable information for assessing the influence of climate change on water resources in the Manas River basin, and references for water management in such regions.

  8. Assessing the vulnerability of economic sectors to climate variability to improve the usability of seasonal to decadal climate forecasts in Europe - a preliminary concept

    Science.gov (United States)

    Funk, Daniel

    2015-04-01

    Climate variability poses major challenges for decision-makers in climate-sensitive sectors. Seasonal to decadal (S2D) forecasts provide potential value for management decisions especially in the context of climate change where information from present or past climatology loses significance. However, usable and decision-relevant tailored climate forecasts are still sparse for Europe and successful examples of application require elaborate and individual producer-user interaction. The assessment of sector-specific vulnerabilities to critical climate conditions at specific temporal scale will be a great step forward to increase the usability and efficiency of climate forecasts. A concept for a sector-specific vulnerability assessment (VA) to climate variability is presented. The focus of this VA is on the provision of usable vulnerability information which can be directly incorporated in decision-making processes. This is done by developing sector-specific climate-impact-decision-pathways and the identification of their specific time frames using data from both bottom-up and top-down approaches. The structure of common VA's for climate change related issues is adopted which envisages the determination of exposure, sensitivity and coping capacity. However, the application of the common vulnerability components within the context of climate service application poses some fundamental considerations: Exposure - the effect of climate events on the system of concern may be modified and delayed due to interconnected systems (e.g. catchment). The critical time-frame of a climate event or event sequence is dependent on system-internal thresholds and initial conditions. But also on decision-making processes which require specific lead times of climate information to initiate respective coping measures. Sensitivity - in organizational systems climate may pose only one of many factors relevant for decision making. The scope of "sensitivity" in this concept comprises both the

  9. Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

    Science.gov (United States)

    Verrot, Lucile; Destouni, Georgia

    2015-01-01

    Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

  10. Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa

    Directory of Open Access Journals (Sweden)

    Osadolor Ebhuoma

    2016-06-01

    Full Text Available Malaria is a serious public health threat in Sub-Saharan Africa (SSA, and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI Web of KnowledgeSM databases (PubMed, Web of Science and ScienceDirect was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI derived from either the National Oceanic and Atmospheric Administration (NOAA Advanced Very High Resolution Radiometer (AVHRR or Moderate-resolution Imaging Spectrometer (MODIS satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic

  11. Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa.

    Science.gov (United States)

    Ebhuoma, Osadolor; Gebreslasie, Michael

    2016-06-14

    Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of Knowledge(SM) databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic

  12. Assessing Shifts of Mediterranean and Arid Climates Under RCP4.5 and RCP8.5 Climate Projections in Europe

    Science.gov (United States)

    Barredo, José I.; Mauri, Achille; Caudullo, Giovanni; Dosio, Alessandro

    2018-04-01

    The Mediterranean basin is the richest biodiversity region in Europe and a global hotspot of biological diversity. In spite of that, anthropogenic climate change is one of the most serious concerns for nature conservation in this region. One of the climatic threats is represented by shifts of the Mediterranean climate and expansion of the arid climate. In this paper, we present an assessment of changes in the spatial range of the Mediterranean climate in Europe and the conversion into arid climate under different greenhouse gas forcings, namely RCP4.5 and RCP8.5. We used 11 simulations in two future 30-year periods of state-of-the-art regional climate models from EURO-CORDEX. Our results indicate that by the end of the century under RCP8.5 the present Mediterranean climate zone is projected to contract by 16%, i.e. an area ( 157,000 km2) equivalent to half the size of Italy. This compares with the less severe scenario RCP4.5 that projected only a 3% reduction. In addition, the Mediterranean climate zone is projected to expand to other zones by an area equivalent to 24 and 50% of its present extent under RCP4.5 and RCP8.5, respectively. Our study indicates that expansion of the arid zone is almost always the cause for contraction of the Mediterranean zone. Under RCP8.5 the arid zone is projected to increase by more than twice its present extent, equivalent to three times the size of Greece. Results of this study are useful for identifying (1) priority zones for biodiversity conservation, i.e. stable Mediterranean climate zones, (2) zones requiring assisted adaptation, such as establishment of new protected areas, implementation of buffer zones around protected areas and creating ecological corridors connecting stable Mediterranean zones.

  13. Understanding Farmers' Response to Climate Variability in Nigeria ...

    African Journals Online (AJOL)

    In this study, farmers 'response to climate variability was examined. Primary and secondary data were used. A multi-stage sampling procedure was adopted in the collection of the primary data using structured questionnaires. Four vegetation zones out of seven where farming is mainly carried out were selected for the study.

  14. Climate variability and sustainable food production: Insights from ...

    African Journals Online (AJOL)

    They are integrated and balance the ... implement resilient agricultural practices that increase productivity and production; that help maintain ecosystems ... other forms of life, the manner in which human beings respond to climate variability is critical not ..... work for longer hours and at the same time its effect on their health.

  15. Climate variability and extremes, interacting with nitrogen storage, amplify eutrophication risk

    Science.gov (United States)

    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.

  16. Impacts of Present and Future Climate Variability and Change on Agriculture and Forestry in the Arid and Semi-Arid Tropics

    Energy Technology Data Exchange (ETDEWEB)

    Sivakumar, M.V.K. [World Meteorological Organization WMO, 7bis Avenue de la Paix, 1211 Geneva 2 (Switzerland); Das, H.P. [India Meteorological Department, Shivaji Nagar, Pune, 411005 (India); Brunini, O. [Center for Ecology and Biophysics, 13.020-430-Campinas, Sao Paulo (Brazil)

    2005-05-01

    The arid and semi-arid regions account for approximately 30% of the world total area and are inhabited by approximately 20% of the total world population. Issues of present and future climate variability and change on agriculture and forestry in the arid and semi-arid tropics of the world were examined and discussion under each of these issues had been presented separately for Asia, Africa and Latin America. Several countries in tropical Asia have reported increasing surface temperature trends in recent decades. Although, there is no definite trend discernible in the long-term mean for precipitation for the tropical Asian region, many countries have shown a decreasing trend in rainfall in the past three decades. African rainfall has changed substantially over the last 60 yr and a number of theoretical, modelling and empirical analyses have suggested that noticeable changes in the frequency and intensity of extreme events, including floods may occur when there are only small changes in climate. Climate in Latin America is affected by the El Nino-southern oscillation (ENSO) phases and there is a close relationship between the increase and decrease of rainfall depending upon the warm or cold phases of the phenomenon. Over land regions of Asia, the projected area-averaged annual mean warming is likely to be 1.6 {+-} 0.2C in the 2020s, 3.1 {+-} 0.3C in the 2050s, and 4.6 {+-} 0.4C in the 2080s and the models show high uncertainty in projections of future winter and summer precipitation. Future annual warming across Africa is projected to range from 0.2C per decade to more than 0.5C per decade, while future changes in mean seasonal rainfall in Africa are less well defined. In Latin America, projections indicate a slight increase in temperature and changes in precipitation. Impacts of climate variability and changes are discussed with suitable examples. Agricultural productivity in tropical Asia is sensitive not only to temperature increases, but also to changes in the

  17. Impacts of Present and Future Climate Variability and Change on Agriculture and Forestry in the Arid and Semi-Arid Tropics

    International Nuclear Information System (INIS)

    Sivakumar, M.V.K.; Das, H.P.; Brunini, O.

    2005-01-01

    The arid and semi-arid regions account for approximately 30% of the world total area and are inhabited by approximately 20% of the total world population. Issues of present and future climate variability and change on agriculture and forestry in the arid and semi-arid tropics of the world were examined and discussion under each of these issues had been presented separately for Asia, Africa and Latin America. Several countries in tropical Asia have reported increasing surface temperature trends in recent decades. Although, there is no definite trend discernible in the long-term mean for precipitation for the tropical Asian region, many countries have shown a decreasing trend in rainfall in the past three decades. African rainfall has changed substantially over the last 60 yr and a number of theoretical, modelling and empirical analyses have suggested that noticeable changes in the frequency and intensity of extreme events, including floods may occur when there are only small changes in climate. Climate in Latin America is affected by the El Nino-southern oscillation (ENSO) phases and there is a close relationship between the increase and decrease of rainfall depending upon the warm or cold phases of the phenomenon. Over land regions of Asia, the projected area-averaged annual mean warming is likely to be 1.6 ± 0.2C in the 2020s, 3.1 ± 0.3C in the 2050s, and 4.6 ± 0.4C in the 2080s and the models show high uncertainty in projections of future winter and summer precipitation. Future annual warming across Africa is projected to range from 0.2C per decade to more than 0.5C per decade, while future changes in mean seasonal rainfall in Africa are less well defined. In Latin America, projections indicate a slight increase in temperature and changes in precipitation. Impacts of climate variability and changes are discussed with suitable examples. Agricultural productivity in tropical Asia is sensitive not only to temperature increases, but also to changes in the nature

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

    Science.gov (United States)

    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. The Polar WRF Downscaled Historical and Projected Twenty-First Century Climate for the Coast and Foothills of Arctic Alaska

    Directory of Open Access Journals (Sweden)

    Lei Cai

    2018-01-01

    Full Text Available Climate change is most pronounced in the northern high latitude region. Yet, climate observations are unable to fully capture regional-scale dynamics due to the sparse weather station coverage, which limits our ability to make reliable climate-based assessments. A set of simulated data products was therefore developed for the North Slope of Alaska through a dynamical downscaling approach. The polar-optimized Weather Research and Forecast (Polar WRF model was forced by three sources: The ERA-interim reanalysis data (for 1979–2014, the Community Earth System Model 1.0 (CESM1.0 historical simulation (for 1950–2005, and the CESM1.0 projected (for 2006–2100 simulations in two Representative Concentration Pathways (RCP4.5 and RCP8.5 scenarios. Climatic variables were produced in a 10-km grid spacing and a 3-h interval. The ERA-interim forced WRF (ERA-WRF proves the value of dynamical downscaling, which yields more realistic topographical-induced precipitation and air temperature, as well as corrects underestimations in observed precipitation. In summary, dry and cold biases to the north of the Brooks Range are presented in ERA-WRF, while CESM forced WRF (CESM-WRF holds wet and warm biases in its historical period. A linear scaling method allowed for an adjustment of the biases, while keeping the majority of the variability and extreme values of modeled precipitation and air temperature. CESM-WRF under RCP 4.5 scenario projects smaller increase in precipitation and air temperature than observed in the historical CESM-WRF product, while the CESM-WRF under RCP 8.5 scenario shows larger changes. The fine spatial and temporal resolution, long temporal coverage, and multi-scenario projections jointly make the dataset appropriate to address a myriad of physical and biological changes occurring on the North Slope of Alaska.

  20. The polar WRF downscaled historical and projected 21st century climate for the coast and foothills of Arctic Alaska

    Science.gov (United States)

    Cai, Lei; Alexeev, Vladimir A.; Arp, Christopher D.; Jones, Benjamin M.; Liljedahl, Anna K.; Gädeke, Anne

    2018-01-01

    Climate change is most pronounced in the northern high latitude region. Yet, climate observations are unable to fully capture regional-scale dynamics due to the sparse weather station coverage, which limits our ability to make reliable climate-based assessments. A set of simulated data products was therefore developed for the North Slope of Alaska through a dynamical downscaling approach. The polar-optimized Weather Research & Forecast (Polar WRF) model was forced by three sources: The ERA-interim reanalysis data (for 1979-2014), the Community Earth System Model 1.0 (CESM1.0) historical simulation (for 1950-2005), and the CESM1.0 projected (for 2006-2100) simulations in two Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios. Climatic variables were produced in a 10-km grid spacing and a 3-hour interval. The ERA-interim forced WRF (ERA-WRF) proves the value of dynamical downscaling, which yields more realistic topographical-induced precipitation and air temperature, as well as corrects underestimations in observed precipitation. In summary, dry and cold biases to the north of the Brooks Range are presented in ERA-WRF, while CESM forced WRF (CESM-WRF) holds wet and warm biases in its historical period. A linear scaling method allowed for an adjustment of the biases, while keeping the majority of the variability and extreme values of modeled precipitation and air temperature. CESM-WRF under RCP 4.5 scenario projects smaller increase in precipitation and air temperature than observed in the historical CESM-WRF product, while the CESM-WRF under RCP8.5 scenario shows larger changes. The fine spatial and temporal resolution, long temporal coverage, and multi-scenario projections jointly make the dataset appropriate to address a myriad of physical and biological changes occurring on the North Slope of Alaska.

  1. High-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale projections

    Science.gov (United States)

    Jacquemin, Ingrid; Henrot, Alexandra-Jane; Beckers, Veronique; Berckmans, Julie; Debusscher, Bos; Dury, Marie; Minet, Julien; Hamdi, Rafiq; Dendoncker, Nicolas; Tychon, Bernard; Hambuckers, Alain; François, Louis

    2016-04-01

    The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs

  2. Climate change and water table fluctuation: Implications for raised bog surface variability

    Science.gov (United States)

    Taminskas, Julius; Linkevičienė, Rita; Šimanauskienė, Rasa; Jukna, Laurynas; Kibirkštis, Gintautas; Tamkevičiūtė, Marija

    2018-03-01

    Cyclic peatland surface variability is influenced by hydrological conditions that highly depend on climate and/or anthropogenic activities. A low water level leads to a decrease of peatland surface and an increase of C emissions into the atmosphere, whereas a high water level leads to an increase of peatland surface and carbon sequestration in peatlands. The main aim of this article is to evaluate the influence of hydrometeorological conditions toward the peatland surface and its feedback toward the water regime. A regional survey of the raised bog water table fluctuation and surface variability was made in one of the largest peatlands in Lithuania. Two appropriate indicators for different peatland surface variability periods (increase and decrease) were detected. The first one is an 200 mm y- 1 average net rainfall over a three-year range. The second one is an average annual water depth of 25-30 cm. The application of these indicators enabled the reconstruction of Čepkeliai peatland surface variability during a 100 year period. Processes of peatland surface variability differ in time and in separate parts of peatland. Therefore, internal subbasins in peatland are formed. Subbasins involve autogenic processes that can later affect their internal hydrology, nutrient status, and vegetation succession. Internal hydrological conditions, surface fluctuation, and vegetation succession in peatland subbasins should be taken into account during evaluation of their state, nature management projects, and other peatland research works.

  3. The Cloud Project Climate Research with Accelerators

    CERN Document Server

    Kirkby, Jasper

    2010-01-01

    The current understanding of climate change in the in- dustrial age is that it is predominantly caused by anthro- pogenic greenhouse gases, with relatively small natural contributions due to solar irradiance and volcanoes. How- ever, palaeoclimatic reconstructions show that the climate has frequently varied on 100-year time scales during the Holocene (last 10 kyr) by amounts comparable to the present warming—and yet the mechanism is not under- stood. Estimated changes of solar irradiance on these time scales are too small to account for the climate observations. This raises the question of whether cosmic rays, which are modulated by the solar wind, may be directly affect- ing the climate, providing an effective indirect solar forcing mechanism. Indeed recent satellite observations—although disputed—suggest that cosmic rays may affect clouds un- der certain conditions. However, given the many sources of variability in the atmosphere and the lack of control of the cosmic ray flux, demonstrating overall ca...

  4. Response of permafrost to projected climate change: Results from global offline model simulations with JSBACH

    Science.gov (United States)

    Blome, Tanja; Ekici, Altug; Beer, Christian; Hagemann, Stefan

    2014-05-01

    . Differences between future time slices and today's climate are analysed. The effect in relevant variables, such as permafrost extent, depth of the Active Layer, ground temperature, and amount of soil carbon, is investigated. The experiments (as well as the development of JSBACH with respect to permafrost soil physics) are part of the European project PAGE21, where a focus is set on interactions between the changing climate and its impact on permafrost, especially for the 21st century.

  5. Rainfall variability and drought characteristics in two agro-climatic zones: An assessment of climate change challenges in Africa.

    Science.gov (United States)

    Ayanlade, Ayansina; Radeny, Maren; Morton, John F; Muchaba, Tabitha

    2018-07-15

    This paper examines drought characteristics as an evidence of climate change in two agro-climatic zones of Nigeria and farmers' climate change perceptions of impacts and adaptation strategies. The results show high spatial and temporal rainfall variability for the stations. Consequently, there are several anomalies in rainfall in recent years but much more in the locations around the Guinea savanna. The inter-station and seasonality statistics reveal less variable and wetter early growing seasons and late growing seasons in the Rainforest zone, and more variable and drier growing seasons in other stations. The probability (p) of dry spells exceeding 3, 5 and 10 consecutive days is very high with 0.62≤p≥0.8 in all the stations, though, the p-values for 10day spells drop below 0.6 in Ibadan and Osogbo. The results further show that rainfall is much more reliable from the month of May until July with the coefficient of variance for rainy days 0.30), though CV-RD appears higher in the month of August for all the stations. It is apparent that farmers' perceptions of drought fundamentally mirror climatic patterns from historical weather data. The study concludes that the adaptation facilities and equipment, hybrids of crops and animals are to be provided to farmers, at a subsidized price by the government, for them to cope with the current condition of climate change. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  6. High-resolution multi-model projections of onshore wind resources over Portugal under a changing climate

    Science.gov (United States)

    Nogueira, Miguel; Soares, Pedro M. M.; Tomé, Ricardo; Cardoso, Rita M.

    2018-05-01

    We present a detailed evaluation of wind energy density (WED) over Portugal, based on the EURO-CORDEX database of high-resolution regional climate model (RCM) simulations. Most RCMs showed reasonable accuracy in reproducing the observed near-surface wind speed. The climatological patterns of WED displayed large sub-regional heterogeneity, with higher values over coastal regions and steep orography. Subsequently, we investigated the future changes of WED throughout the twenty-first century, considering mid- and end-century periods, and two emission scenarios (RCP4.5 and RCP8.5). On the yearly average, the multi-model ensemble WED changes were below 10% (15%) under RCP4.5 (RCP8.5). However, the projected WED anomalies displayed strong seasonality, dominated by low positive values in summer (< 10% for both scenarios), negative values in winter and spring (up to - 10% (- 20%) under RCP4.5 (RCP8.5)), and stronger negative anomalies in autumn (up to - 25% (- 35%) under RCP4.5 (RCP8.5)). These projected WED anomalies displayed large sub-regional variability. The largest reductions (and lowest increases) are linked to the northern and central-eastern elevated terrain, and the southwestern coast. In contrast, the largest increases (and lowest reductions) are linked to the central-western orographic features of moderate elevation. The projections also showed changes in inter-annual variability of WED, with small increases for annual averages, but with distinct behavior when considering year-to-year variability over a specific season: small increases in winter, larger increases in summer, slight decrease in autumn, and no relevant change in spring. The changes in inter-annual variability also displayed strong dependence on the underlying terrain. Finally, we found significant model spread in the magnitude of projected WED anomalies and inter-annual variability, affecting even the signal of the changes.

  7. Historical versus contemporary climate forcing on the annual nesting variability of loggerhead sea turtles in the Northwest Atlantic Ocean.

    Directory of Open Access Journals (Sweden)

    Michael D Arendt

    Full Text Available A recent analysis suggested that historical climate forcing on the oceanic habitat of neonate sea turtles explained two-thirds of interannual variability in contemporary loggerhead (Caretta caretta sea turtle nest counts in Florida, where nearly 90% of all nesting by this species in the Northwest Atlantic Ocean occurs. Here, we show that associations between annual nest counts and climate conditions decades prior to nest counts and those conditions one year prior to nest counts were not significantly different. Examination of annual nest count and climate data revealed that statistical artifacts influenced the reported 31-year lag association with nest counts. The projected importance of age 31 neophytes to annual nest counts between 2020 and 2043 was modeled using observed nest counts between 1989 and 2012. Assuming consistent survival rates among cohorts for a 5% population growth trajectory and that one third of the mature female population nests annually, the 41% decline in annual nest counts observed during 1998-2007 was not projected for 2029-2038. This finding suggests that annual nest count trends are more influenced by remigrants than neophytes. Projections under the 5% population growth scenario also suggest that the Peninsular Recovery Unit could attain the demographic recovery criteria of 106,100 annual nests by 2027 if nest counts in 2019 are at least comparable to 2012. Because the first year of life represents only 4% of the time elapsed through age 31, cumulative survival at sea across decades explains most cohort variability, and thus, remigrant population size. Pursuant to the U.S. Endangered Species Act, staggered implementation of protection measures for all loggerhead life stages has taken place since the 1970s. We suggest that the 1998-2007 nesting decline represented a lagged perturbation response to historical anthropogenic impacts, and that subsequent nest count increases since 2008 reflect a potential recovery response.

  8. Projected range contractions of European protected oceanic montane plant communities: focus on climate change impacts is essential for their future conservation.

    Science.gov (United States)

    Hodd, Rory L; Bourke, David; Skeffington, Micheline Sheehy

    2014-01-01

    Global climate is rapidly changing and while many studies have investigated the potential impacts of this on the distribution of montane plant species and communities, few have focused on those with oceanic montane affinities. In Europe, highly sensitive bryophyte species reach their optimum occurrence, highest diversity and abundance in the north-west hyperoceanic regions, while a number of montane vascular plant species occur here at the edge of their range. This study evaluates the potential impact of climate change on the distribution of these species and assesses the implications for EU Habitats Directive-protected oceanic montane plant communities. We applied an ensemble of species distribution modelling techniques, using atlas data of 30 vascular plant and bryophyte species, to calculate range changes under projected future climate change. The future effectiveness of the protected area network to conserve these species was evaluated using gap analysis. We found that the majority of these montane species are projected to lose suitable climate space, primarily at lower altitudes, or that areas of suitable climate will principally shift northwards. In particular, rare oceanic montane bryophytes have poor dispersal capacity and are likely to be especially vulnerable to contractions in their current climate space. Significantly different projected range change responses were found between 1) oceanic montane bryophytes and vascular plants; 2) species belonging to different montane plant communities; 3) species categorised according to different biomes and eastern limit classifications. The inclusion of topographical variables in addition to climate, significantly improved the statistical and spatial performance of models. The current protected area network is projected to become less effective, especially for specialised arctic-montane species, posing a challenge to conserving oceanic montane plant communities. Conservation management plans need significantly

  9. Projected range contractions of European protected oceanic montane plant communities: focus on climate change impacts is essential for their future conservation.

    Directory of Open Access Journals (Sweden)

    Rory L Hodd

    Full Text Available Global climate is rapidly changing and while many studies have investigated the potential impacts of this on the distribution of montane plant species and communities, few have focused on those with oceanic montane affinities. In Europe, highly sensitive bryophyte species reach their optimum occurrence, highest diversity and abundance in the north-west hyperoceanic regions, while a number of montane vascular plant species occur here at the edge of their range. This study evaluates the potential impact of climate change on the distribution of these species and assesses the implications for EU Habitats Directive-protected oceanic montane plant communities. We applied an ensemble of species distribution modelling techniques, using atlas data of 30 vascular plant and bryophyte species, to calculate range changes under projected future climate change. The future effectiveness of the protected area network to conserve these species was evaluated using gap analysis. We found that the majority of these montane species are projected to lose suitable climate space, primarily at lower altitudes, or that areas of suitable climate will principally shift northwards. In particular, rare oceanic montane bryophytes have poor dispersal capacity and are likely to be especially vulnerable to contractions in their current climate space. Significantly different projected range change responses were found between 1 oceanic montane bryophytes and vascular plants; 2 species belonging to different montane plant communities; 3 species categorised according to different biomes and eastern limit classifications. The inclusion of topographical variables in addition to climate, significantly improved the statistical and spatial performance of models. The current protected area network is projected to become less effective, especially for specialised arctic-montane species, posing a challenge to conserving oceanic montane plant communities. Conservation management plans need

  10. Trend analysis of hydro-climatic variables in the north of Iran

    Science.gov (United States)

    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 basin decreased by 14% significantly, but the annual maximum daily flow increased by 118%. Results for the trend analysis of streamflow and climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value 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.

  11. Southern hemisphere climate variability as represented by an ocean-atmosphere coupled model

    CSIR Research Space (South Africa)

    Beraki, A

    2012-09-01

    Full Text Available in the atmospheric circulation. The ability of predicting these modes of climate variability on longer timescales is vital. Potential predictability is usually measured as a signal-to-noise contrast between the slowly evolving and chaotic components of the climate...

  12. Climate and dengue transmission: evidence and implications.

    Science.gov (United States)

    Morin, Cory W; Comrie, Andrew C; Ernst, Kacey

    2013-01-01

    Climate influences dengue ecology by affecting vector dynamics, agent development, and mosquito/human interactions. Although these relationships are known, the impact climate change will have on transmission is unclear. Climate-driven statistical and process-based models are being used to refine our knowledge of these relationships and predict the effects of projected climate change on dengue fever occurrence, but results have been inconsistent. We sought to identify major climatic influences on dengue virus ecology and to evaluate the ability of climate-based dengue models to describe associations between climate and dengue, simulate outbreaks, and project the impacts of climate change. We reviewed the evidence for direct and indirect relationships between climate and dengue generated from laboratory studies, field studies, and statistical analyses of associations between vectors, dengue fever incidence, and climate conditions. We assessed the potential contribution of climate-driven, process-based dengue models and provide suggestions to improve their performance. Relationships between climate variables and factors that influence dengue transmission are complex. A climate variable may increase dengue transmission potential through one aspect of the system while simultaneously decreasing transmission potential through another. This complexity may at least partly explain inconsistencies in statistical associations between dengue and climate. Process-based models can account for the complex dynamics but often omit important aspects of dengue ecology, notably virus development and host-species interactions. Synthesizing and applying current knowledge of climatic effects on all aspects of dengue virus ecology will help direct future research and enable better projections of climate change effects on dengue incidence.

  13. Consequences of an uncertain mass mortality regime triggered by climate variability on giant clam population management in the Pacific Ocean.

    Science.gov (United States)

    Van Wynsberge, Simon; Andréfouët, Serge; Gaertner-Mazouni, Nabila; Remoissenet, Georges

    2018-02-01

    Despite actions to manage sustainably tropical Pacific Ocean reef fisheries, managers have faced failures and frustrations because of unpredicted mass mortality events triggered by climate variability. The consequences of these events on the long-term population dynamics of living resources need to be better understood for better management decisions. Here, we use a giant clam (Tridacna maxima) spatially explicit population model to compare the efficiency of several management strategies under various scenarios of natural mortality, including mass mortality due to climatic anomalies. The model was parameterized by in situ estimations of growth and mortality and fishing effort, and was validated by historical and new in situ surveys of giant clam stocks in two French Polynesia lagoons. Projections on the long run (100 years) suggested that the best management strategy was a decrease of fishing pressure through quota implementation, regardless of the mortality regime considered. In contrast, increasing the minimum legal size of catch and closing areas to fishing were less efficient. When high mortality occurred due to climate variability, the efficiency of all management scenarios decreased markedly. Simulating El Niño Southern Oscillation event by adding temporal autocorrelation in natural mortality rates increased the natural variability of stocks, and also decreased the efficiency of management. These results highlight the difficulties that managers in small Pacific islands can expect in the future in the face of global warming, climate anomalies and new mass mortalities. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Climate change and climate variability impacts on rainfed agricultural activities and possible adaptation measures. A Mexican case study

    Energy Technology Data Exchange (ETDEWEB)

    Conde, C.; Ferrer, R. [Centro de Ciencias de la Atmosfera, Universidad Nacional Autonoma de Mexico Circuito Exterior, Mexico, D.F. (Mexico)]. E-mail: e-mail: conde@servidor.unam.mx; Orozco, S. [Escuela de Agrobiologia, Universidad Autonoma de Tlaxcala, Tlaxcala (Mexico)

    2006-07-15

    Climate extreme events (such as those associated to strong El Nino events) highly affect Mexican agriculture, since more than sixty percent of it is rainfed. The basic crop cultivated is maize, which is still the main source of nutrients for a large portion of the rural population in the country. Within the project Capacity Building for Stage II Adaptation to Climate Change in Central America, Mexico and Cuba, we analyze the strategies developed by maize producers in the central region of the country to cope with climatic adverse events. Impact on rainfed maize due to climate variability and climate change conditions are studied using a crop simulation model. Several adaptation measures can be evaluated using that model. However, the effect of other stressors must be considered in an assessment of the adaptive capacity of small farmers to climate variability and change. Key stakeholders' involvement in the region helped us to decide which of the adaptive measures could be viable under the current conditions and under future climatic conditions. The construction of greenhouses, the use of compost, and dripping irrigation, were some of the techniques selected with the participation of the stakeholders. The enthusiastic responses to these measures allow us to consider that they can prevail in the future, under climate change conditions. However, the adaptation to climate change includes -besides the stated techniques- the generation of the capacities to cope with climatic adverse events, that is, to enhance the adaptive capacities to climate change among the key stakeholders. [Spanish] Los eventos climaticos extremos (como los asociados con eventos fuertes de El Nino) afectan de manera importante a la agricultura mexicana, ya que mas del sesenta por ciento de ella es de temporal, esto es, depende fundamentalmente de una buena temporada de lluvias para producir. El cultivo que se siembra es basicamente maiz, que todavia es la principal fuente de nutrientes para

  15. Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

    Science.gov (United States)

    Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

    2018-06-04

    A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

  16. Essential climatic variables estimation with satellite imagery

    Science.gov (United States)

    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.

  17. Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S.

    Energy Technology Data Exchange (ETDEWEB)

    Wagener, Thorsten [Univ. of Bristol (United Kingdom); Mann, Michael [Pennsylvania State Univ., State College, PA (United States); Crane, Robert [Pennsylvania State Univ., State College, PA (United States)

    2014-04-29

    This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach to establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.

  18. Mediterranean climate modelling: variability and climate change scenarios; Modelisation climatique du Bassin mediterraneen: variabilite et scenarios de changement climatique

    Energy Technology Data Exchange (ETDEWEB)

    Somot, S

    2005-12-15

    Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)

  19. Greenhouse gas observations from space: The GHG-CCI project of ESA's Climate Change Initiative

    Science.gov (United States)

    Buchwitz, Michael; Noël, Stefan; Bergamaschi, Peter; Boesch, Hartmut; Bovensmann, Heinrich; Notholt, Justus; Schneising, Oliver; Hasekamp, Otto; Reuter, Maximilian; Parker, Robert; Dils, Bart; Chevallier, Frederic; Zehner, Claus; Burrows, John

    2012-07-01

    The GHG-CCI project (http://www.esa-ghg-cci.org) is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs). The goal of GHG-CCI is to deliver global satellite-derived data sets of the two most important anthropogenic greenhouse gases (GHGs) carbon dioxide (CO2) and methane (CH4) suitable to obtain information on regional CO2 and CH4 surface sources and sinks as needed for better climate prediction. The GHG-CCI core ECV data products are column-averaged mole fractions of CO2 and CH4, XCO2 and XCH4, retrieved from SCIAMACHY on ENVISAT and TANSO on GOSAT. Other satellite instruments will be used to provide constraints in upper layers such as IASI, MIPAS, and ACE-FTS. Which of the advanced algorithms, which are under development, will be the best for a given data product still needs to be determined. For each of the 4 GHG-CCI core data products - XCO2 and XCH4 from SCIAMACHY and GOSAT - several algorithms are being further developed and the corresponding data products are inter-compared to identify which data product is the most appropriate. This includes comparisons with corresponding data products generated elsewhere, most notably with the operational data products of GOSAT generated at NIES and the NASA/ACOS GOSAT XCO2 product. This activity, the so-called "Round Robin exercise", will be performed in the first two years of this project. At the end of the 2 year Round Robin phase (end of August 2012) a decision will be made which of the algorithms performs best. The selected algorithms will be used to generate the first version of the ECV GHG. In the last six months of this 3 year project the resulting data products will be validated and made available to all interested users. In the presentation and overview about this project will be given focussing on the latest results.

  20. Climate change projections for Tamil Nadu, India: deriving high-resolution climate data by a downscaling approach using PRECIS

    Science.gov (United States)

    Bal, Prasanta Kumar; Ramachandran, A.; Geetha, R.; Bhaskaran, B.; Thirumurugan, P.; Indumathi, J.; Jayanthi, N.

    2016-02-01

    In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments.

  1. Societal Impacts of Natural Decadal Climate Variability - The Pacemakers of Civilizations

    Science.gov (United States)

    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

  2. Integrating ecophysiology and forest landscape models to improve projections of drought effects under climate change.

    Science.gov (United States)

    Gustafson, Eric J; De Bruijn, Arjan M G; Pangle, Robert E; Limousin, Jean-Marc; McDowell, Nate G; Pockman, William T; Sturtevant, Brian R; Muss, Jordan D; Kubiske, Mark E

    2015-02-01

    Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy-makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and projected responses are weak and indirect, limiting their reliability for projecting the impacts of climate change. We developed and tested a relatively mechanistic method to simulate the effects of changing precipitation on species competition within the LANDIS-II FLM. Using data from a field precipitation manipulation experiment in a piñon pine (Pinus edulis) and juniper (Juniperus monosperma) ecosystem in New Mexico (USA), we calibrated our model to measurements from ambient control plots and tested predictions under the drought and irrigation treatments against empirical measurements. The model successfully predicted behavior of physiological variables under the treatments. Discrepancies between model output and empirical data occurred when the monthly time step of the model failed to capture the short-term dynamics of the ecosystem as recorded by instantaneous field measurements. We applied the model to heuristically assess the effect of alternative climate scenarios on the piñon-juniper ecosystem and found that warmer and drier climate reduced productivity and increased the risk of drought-induced mortality, especially for piñon. We concluded that the direct links between fundamental drivers and growth rates in our model hold great promise to improve our understanding of ecosystem processes under climate change and improve management decisions because of its greater reliance on first principles. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

  3. General technical comments on climate change - comment 1: Answers to five questions posed at the conference

    International Nuclear Information System (INIS)

    Firor, J.

    1992-01-01

    An attempt is made to answer the following five questions: (1) what are the projections of global average temperature increase? (2) What are the prospects for projecting regional climate change? (3) Do the climate models produce outlooks for a group of climate variables closely related to sociatal impacts? (4) What is the feasibility and what are the costs of proposed geoengineering options for responding to climate change? (5) What climate variables co-vary with global average temperature

  4. Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

    Science.gov (United States)

    van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

    2015-05-01

    Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    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 Change and Climate Variability in the Latin American Region

    Science.gov (United States)

    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

  7. Internal variability in a regional climate model over West Africa

    Energy Technology Data Exchange (ETDEWEB)

    Vanvyve, Emilie; Ypersele, Jean-Pascal van [Universite catholique de Louvain, Institut d' astronomie et de geophysique Georges Lemaitre, Louvain-la-Neuve (Belgium); Hall, Nicholas [Laboratoire d' Etudes en Geophysique et Oceanographie Spatiales/Centre National d' Etudes Spatiales, Toulouse Cedex 9 (France); Messager, Christophe [University of Leeds, Institute for Atmospheric Science, Environment, School of Earth and Environment, Leeds (United Kingdom); Leroux, Stephanie [Universite Joseph Fourier, Laboratoire d' etude des Transferts en Hydrologie et Environnement, BP53, Grenoble Cedex 9 (France)

    2008-02-15

    Sensitivity studies with regional climate models are often performed on the basis of a few simulations for which the difference is analysed and the statistical significance is often taken for granted. In this study we present some simple measures of the confidence limits for these types of experiments by analysing the internal variability of a regional climate model run over West Africa. Two 1-year long simulations, differing only in their initial conditions, are compared. The difference between the two runs gives a measure of the internal variability of the model and an indication of which timescales are reliable for analysis. The results are analysed for a range of timescales and spatial scales, and quantitative measures of the confidence limits for regional model simulations are diagnosed for a selection of study areas for rainfall, low level temperature and wind. As the averaging period or spatial scale is increased, the signal due to internal variability gets smaller and confidence in the simulations increases. This occurs more rapidly for variations in precipitation, which appear essentially random, than for dynamical variables, which show some organisation on larger scales. (orig.)

  8. Effect of Climate Variability on Crop Income in Central Ethiopia

    Directory of Open Access Journals (Sweden)

    Arega Shumetie Ademe

    2017-12-01

    Full Text Available Ethiopian agriculture is a vulnerable sector from effects of climate variability. This study identified how strong is the effect of climate variability on smallholders’ crop income in Central highlands and Arssi grain plough farming systems of the country. The unbalanced panel data (1994-2014 of the study collected for eight rounds analysed through fixed effect regression. The model result shows that successive increment of crop season rainfall keeping the temperature constant has negative and significant effect on households’ crop income in the study area. The crop income responds similarly for temperature increment if the rainfall remains constant. Given this, simultaneous increment of the two climate related inputs has positive and significant effect on crop income. Other variables like flood, frost, storm, and rainfall inconsistency in the onset and cessation time affected households’ crop income negatively and significantly. Similarly, draught power and human labour, which are critical inputs in the crop production of Ethiopian smallholders, have positive and significant effect on crop income as to the model result. Thus, this study recommended that there should be supplementing the rainfall through irrigation, check dam and other activities to have consistent water supply for the crop production that enable smallholders to collect better income. Additionally, negative effect of temperature increment should be curved through adopting long lasting strategies like afforestation.

  9. Air Pollution and Climate Change Health Impact Assessment. The ACHIA Project

    International Nuclear Information System (INIS)

    Kinney, P.L.

    2013-01-01

    Climate change may affect human health via interactions with air pollutants such as ozone and PM 2.5 . These air pollutants are linked to climate because they can be both affected by and have effects on climate. In coming decades, substantial, cost-effective improvements in public health may be achieved with well-planned strategies to mitigate climate impacts while also reducing health effects of ozone and PM 2.5 . Climate mitigation actions affect greenhouse pollutant emissions, including methane and black carbon, but also may affect other key air pollution precursors such as NOx, CO, and SOx. To better understand the potential of such strategies, studies are needed that assess possible future health impacts under alternative assumptions about future emissions and climate across multiple spatial scales. The overall objective of this project is to apply state of the art climate, air quality, and health modelling tools to assess future health impacts of ozone and PM 2.5 under different IPCCs scenario of climate change, focusing specifically on pollution-related health co-benefits which could be achieved under alternative climate mitigation pathways in the period 2030-2050. This question will be explored at three spatial scales: global, regional (Europe), and urban (Paris). ACHIA is comprised of an integrated set of four work packages: WP1. Global Climate and Air Pollution Impacts of Alternative Emissions Pathways; WP2. Climate and Air Quality at Regional and Urban Scales: Results for Europe and Paris; WP3. Health Impact Assessment; WP4. Dissemination, Evaluation, Management. ACHIA is designed to create an interdisciplinary approach to the impacts of climate change on health through air quality changes, and to start longer-term collaborations between communities. We expect the project to advance state of art across all WPs, with important implications for research groups around the world. A particular innovation of the project is the multi-scale aspect, i.e., the

  10. Climate Analogues for agricultural impact projection and adaptation – a reliability test

    Directory of Open Access Journals (Sweden)

    Swen P.M. Bos

    2015-10-01

    Full Text Available The climate analogue approach is often considered a valuable tool for climate change impact projection and adaptation planning, especially for complex systems that cannot be modelled reliably. Important examples are smallholder farming systems using agroforestry or other mixed-cropping approaches. For the projected climate at a particular site of interest, the analogue approach identifies locations where the current climate is similar to these projected conditions. By comparing baseline-analogue site pairs, information on climate impacts and opportunities for adaptation can be obtained. However, the climate analogue approach is only meaningful, if climate is a dominant driver of differences between baseline and analogue site pairs. For a smallholder farming setting on Mt. Elgon in Kenya, we tested this requirement by comparing yield potentials of maize and coffee (obtained from the IIASA Global Agro-ecological Zones dataset among 50 close analogue sites for different future climate scenarios and models, and by comparing local ecological knowledge and farm characteristics for one baseline-analogue pair.Yield potentials among the 50 closest analogue locations varied strongly within all climate scenarios, hinting at factors other than climate as major drivers of what the analogue approach might interpret as climate effects. However, on average future climatic conditions seemed more favourable to maize and coffee cultivation than current conditions. The detailed site comparison revealed substantial differences between farms in important characteristics, such as farm size and presence of cash crops, casting doubt on the usefulness of the comparison for climate change analysis. Climatic constraints were similar between sites, so that no apparent lessons for adaptation could be derived. Pests and diseases were also similar, indicating that climate change may not lead to strong changes in biotic constraints at the baseline site in the near future. From

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

    Science.gov (United States)

    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.

  12. Climatic variability and trends in the surface waters of coastal British Columbia

    Science.gov (United States)

    Cummins, Patrick F.; Masson, Diane

    2014-01-01

    Multi-decadal records of monthly sea surface temperature (SST) and sea surface salinity (SSS) collected at a set of lighthouse stations are used to examine climatic variability and trends in the coastal waters of British Columbia. Particular attention is given to relations between the water property anomalies and variability in coastal freshwater discharge and alongshore wind stress. Within the Strait of Georgia, SSS anomalies are closely related to Fraser River discharge anomalies. Along the Pacific coast, anomalies in alongshore wind stress and freshwater runoff have the characteristics of white noise processes. A cross-correlation analysis demonstrates that SST and SSS variability along the open west coast is consistent with the response of a first-order autoregressive process driven by anomalous alongshore wind stress and coastal freshwater discharge, respectively. Thus climatic variability of SST and SSS along the Pacific coast of British Columbia occurs, in part, through the integration of noisy atmospheric forcing and coastal precipitation. Seasonal correlations show that SST is strongly related to wind stress during winter and fall. Conversely, SSS is relatively weakly related to the alongshore wind during spring, suggesting that variability in upwelling makes only a modest contribution to variability of SSS in the nearshore environment. Consistent with previous studies, secular trends indicate long-term warming and freshening of the coastal ocean at most stations. It is shown that long-term SST trends can be obscured by the pronounced climatic variability of these waters, requiring that time series extend for several decades to be reliably detected.

  13. Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

    Directory of Open Access Journals (Sweden)

    B. Schneider

    2008-04-01

    Full Text Available Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP and export production (EP of particulate organic carbon (POC. Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation. Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006 with stronger stratification (higher sea surface temperature; SST being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL also reproduces the inverse relationship between stratification (SST and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

  14. Climate variability and Port wine quality

    Science.gov (United States)

    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

  15. Influence of Climate Variability on US Regional Homicide Rates

    Science.gov (United States)

    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

  16. Internal and external North Atlantic Sector variability in the Kiel climate model

    Energy Technology Data Exchange (ETDEWEB)

    Latif, Mojib; Park, Wonsun; Ding, Hui; Keenlyside, Noel S. [Leibniz-Inst. fuer Meereswissenschaften, Kiel (Germany)

    2009-08-15

    The internal and external North Atlantic Sector variability is investigated by means of a multimillennial control run and forced experiments with the Kiel Climate Model (KCM). The internal variability is studied by analyzing the control run. The externally forced variability is investigated in a run with periodic millennial solar forcing and in greenhouse warming experiments with enhanced carbon dioxide concentrations. The surface air temperature (SAT) averaged over the Northern Hemisphere simulated in the control run displays enhanced variability relative to the red background at decadal, centennial, and millennial timescales. Special emphasis is given to the variability of the Meridional Overturning Circulation (MOC). The MOC plays an important role in the generation of internal climate modes. Furthermore, the MOC provides a strong negative feedback on the Northern Hemisphere SAT in both the solar and greenhouse warming experiments, thereby moderating the direct effects of the external forcing in the North Atlantic. The implications of the results for decadal predictability are discussed. (orig.)

  17. Climatically driven yield variability of major crops in Khakassia (South Siberia)

    Science.gov (United States)

    Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

    2017-12-01

    We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

  18. Projected heat-related mortality under climate change in the metropolitan area of Skopje

    Directory of Open Access Journals (Sweden)

    Gerardo Sanchez Martinez

    2016-05-01

    Full Text Available Abstract Background Excessive summer heat is a serious environmental health problem in Skopje, the capital and largest city of the former Yugoslav Republic of Macedonia. This paper attempts to forecast the impact of heat on mortality in Skopje in two future periods under climate change and compare it with a historical baseline period. Methods After ascertaining the relationship between daily mean ambient air temperature and daily mortality in Skopje, we modelled the evolution of ambient temperatures in the city under a Representative Concentration Pathway scenario (RCP8.5 and the evolution of the city population in two future time periods: 2026–2045 and 2081–2100, and in a past time period (1986–2005 to serve as baseline for comparison. We then calculated the projected average annual mortality attributable to heat in the absence of adaptation or acclimatization during those time windows, and evaluated the contribution of each source of uncertainty on the final impact. Results Our estimates suggest that, compared to the baseline period (1986–2005, heat-related mortality in Skopje would more than double in 2026–2045, and more than quadruple in 2081–2100. When considering the impact in 2081–2100, sampling variability around the heat–mortality relationship and climate model explained 40.3 and 46.6 % of total variability. Conclusion These results highlight the importance of a long-term perspective in the public health prevention of heat exposure, particularly in the context of a changing climate.

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

    Science.gov (United States)

    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.

  20. Uncertainty in projected climate change arising from uncertain fossil-fuel emission factors

    Science.gov (United States)

    Quilcaille, Y.; Gasser, T.; Ciais, P.; Lecocq, F.; Janssens-Maenhout, G.; Mohr, S.

    2018-04-01

    Emission inventories are widely used by the climate community, but their uncertainties are rarely accounted for. In this study, we evaluate the uncertainty in projected climate change induced by uncertainties in fossil-fuel emissions, accounting for non-CO2 species co-emitted with the combustion of fossil-fuels and their use in industrial processes. Using consistent historical reconstructions and three contrasted future projections of fossil-fuel extraction from Mohr et al we calculate CO2 emissions and their uncertainties stemming from estimates of fuel carbon content, net calorific value and oxidation fraction. Our historical reconstructions of fossil-fuel CO2 emissions are consistent with other inventories in terms of average and range. The uncertainties sum up to a ±15% relative uncertainty in cumulative CO2 emissions by 2300. Uncertainties in the emissions of non-CO2 species associated with the use of fossil fuels are estimated using co-emission ratios varying with time. Using these inputs, we use the compact Earth system model OSCAR v2.2 and a Monte Carlo setup, in order to attribute the uncertainty in projected global surface temperature change (ΔT) to three sources of uncertainty, namely on the Earth system’s response, on fossil-fuel CO2 emission and on non-CO2 co-emissions. Under the three future fuel extraction scenarios, we simulate the median ΔT to be 1.9, 2.7 or 4.0 °C in 2300, with an associated 90% confidence interval of about 65%, 52% and 42%. We show that virtually all of the total uncertainty is attributable to the uncertainty in the future Earth system’s response to the anthropogenic perturbation. We conclude that the uncertainty in emission estimates can be neglected for global temperature projections in the face of the large uncertainty in the Earth system response to the forcing of emissions. We show that this result does not hold for all variables of the climate system, such as the atmospheric partial pressure of CO2 and the

  1. Potential impacts of climate change and variability on groundwater ...

    African Journals Online (AJOL)

    Aizebeokhai

    largely mimic the projected changes in precipitation. Increased precipitation intensity and variability is projected to increase the risks of flooding in many coastal areas, and drought in many arid and semi-arid regions. Higher water temperatures and changes in extremes, including floods and droughts, are projected to affect.

  2. An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

    Science.gov (United States)

    Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

    2003-12-01

    Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

  3. Improving preparedness of farmers to Climate Variability: A case study of Vidarbha region of Maharashtra, India

    Science.gov (United States)

    Swami, D.; Parthasarathy, D.; Dave, P.

    2016-12-01

    A key objective of the ongoing research is to understand the risk and vulnerability of agriculture and farming communities with respect to multiple climate change attributes, particularly monsoon variability and hydrology such as ground water availability. Climate Variability has always been a feature affecting Indian agriculture but the nature and characteristics of this variability is not well understood. Indian monsoon patterns are highly variable and most of the studies focus on larger domain such as Central India or Western coast (Ghosh et al., 2009) but district level analysis is missing i.e. the linkage between agriculture and climate variables at finer scale has not been investigated comprehensively. For example, Eastern Vidarbha region in Maharashtra is considered as one of the most agriculturally sensitive region in India, where every year a large number of farmers commit suicide. The main reasons for large number of suicides are climate related stressors such as droughts, hail storms, and monsoon variability aggravated with poor socio-economic conditions. Present study has tried to explore the areas in Vidarbha region of Maharashtra where famers and crop productivity, specifically cotton, sorghum, is highly vulnerable to monsoon variability, hydrological and socio-economic variables which are further modelled to determine the maximal contributing factor towards crops and farmers' vulnerability. After analysis using primary and secondary data, it will aid in decision making regarding field operations such as time of sowing, harvesting and irrigation requirements by optimizing the cropping pattern with climatic, hydrological and socio-economic variables. It also suggests the adaptation strategies to farmers regarding different types of cropping and water harvesting practices, optimized dates and timings for harvesting, sowing, water and nutrient requirements of particular crops according to the specific region. Primarily along with secondary analysis

  4. Multi-model Ensemble Regional Climate Projection of the Maritime Continent using the MIT Regional Climate Model

    Science.gov (United States)

    Kang, S.; IM, E. S.; Eltahir, E. A. B.

    2016-12-01

    In this study, the future change in precipitation due to global warming is investigated over the Maritime Continent using the MIT Regional Climate Model (MRCM). A total of nine 30-year projections under multi-GCMs (CCSM, MPI, ACCESS) and multi-scenarios of emissions (Control, RCP4.5, RCP8.5) are dynamically downscaled using the MRCM with 12km horizontal resolution. Since downscaled results tend to systematically overestimate the precipitation regardless of GCM used as lateral boundary conditions, the Parametric Quantile Mapping (PQM) is applied to reduce this wet bias. The cross validation for the control simulation shows that the PQM method seems to retain the spatial pattern and temporal variability of raw simulation, however it effectively reduce the wet bias. Based on ensemble projections produced by dynamical downscaling and statistical bias correction, a reduction of future precipitation is discernible, in particular during dry season (June-July-August). For example, intense precipitation in Singapore is expected to be reduced in RCP8.5 projection compared to control simulation. However, the geographical patterns and magnitude of changes still remain uncertain, suffering from statistical insignificance and a lack of model agreement. Acknowledgements This research is supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise programme. The Center for Environmental Sensing and Modeling is an interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology

  5. Climate Change Adaptation

    DEFF Research Database (Denmark)

    Hudecz, Adriána

    The European Union ROADEX Project 1998 – 2012 was a trans-national roads co-operation aimed at developing ways for interactive and innovative management of low traffic volume roads throughout the cold climate regions of the Northern Periphery Area of Europe. Its goals were to facilitate co......-operation and research into the common problems of the Northern Periphery. This report is an output of the ROADEX “Implementing Accessibility” project (2009-2012). It gives a summary of the results of research into adaptation measures to combat climate change effects on low volume roads in the Northern Periphery...... causes changes in other climatic variables such as rainfall, humidity and wind speed that impact on the functioning of infrastructure such road networks. This paper discusses the climate changes predicted by the world’s meteorological organisations and considers how these may impact on the public...

  6. Association of genetic and phenotypic variability with geography and climate in three southern California oaks.

    Science.gov (United States)

    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.

  7. Projecting temperature-related years of life lost under different climate change scenarios in one temperate megacity, China.

    Science.gov (United States)

    Li, Yixue; Li, Guoxing; Zeng, Qiang; Liang, Fengchao; Pan, Xiaochuan

    2018-02-01

    Temperature has been associated with population health, but few studies have projected the future temperature-related years of life lost attributable to climate change. To project future temperature-related disease burden in Tianjin, we selected years of life lost (YLL) as the dependent variable to explore YLL attributable to climate change. A generalized linear model (GLM) and distributed lag non-linear model were combined to assess the non-linear and delayed effects of temperature on the YLL of non-accidental mortality. Then, we calculated the YLL changes attributable to future climate scenarios in 2055 and 2090. The relationships of daily mean temperature with the YLL of non-accident mortality were basically U-shaped. Both the daily mean temperature increase on high-temperature days and its drop on low-temperature days caused an increase of YLL and non-accidental deaths. The temperature-related YLL will worsen if future climate change exceeds 2 °C. In addition, the adverse effects of extreme temperature on YLL occurred more quickly than that of the overall temperature. The impact of low temperature was greater than that of high temperature. Men were vulnerable to high temperature compared with women. This analysis highlights that the government should formulate environmental policies to reach the Paris Agreement goal. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Final Project Report

    Energy Technology Data Exchange (ETDEWEB)

    Small, R. Justin [Woods Hole Oceanographic Institution, MA (United States); Bryan, Frank [Woods Hole Oceanographic Institution, MA (United States); Tribbia, Joseph [Woods Hole Oceanographic Institution, MA (United States); Park, Sungsu [Woods Hole Oceanographic Institution, MA (United States); Dennis, John [Woods Hole Oceanographic Institution, MA (United States); Saravanan, R. [Woods Hole Oceanographic Institution, MA (United States); Schneider, Niklas [Woods Hole Oceanographic Institution, MA (United States); Kwon, Young-Oh [Woods Hole Oceanographic Institution, MA (United States)

    2015-06-01

    Most climate models are currently run with grid spacings of around 100km, which, with today’s computing power, allows for long (up to 1000 year) simulations, or ensembles of simulations to explore climate change and variability. However this grid spacing does not resolve important components of the weather/climate system such as atmospheric fronts and mesoscale systems, and ocean boundary currents and eddies. The overall aim of this project has been to look at the effect of these small-scale features on the weather/climate system using a suite of high and low resolution climate models, idealized models and observations. This project was only possible due to the highly scalable aspect of the CAM Spectral Element dynamical core, and the significant resources allocated at Yellowstone and NERSC for which we are grateful.

  9. Data Requirements for Developing Adaptations to Climate Variability and Change

    International Nuclear Information System (INIS)

    Basher, Reid E.

    1999-01-01

    An extensive foundation of high quality data and information on the climate and on the biological, environmental and social systems affected by climate is required in order to understand the climate impact processes involved, to develop new adaptation practices, and to subsequently implement these practices. Experience of the impacts of current and past variability of climate and sea level is a prime source of information. Many practices are in use to reduce climate impacts, for example in engineering design, agricultural risk management and climate prediction services, though their roles as adaptations to climate change are not widely appreciated. While there are good data sets on some factors and in some regions, in many cases the databases are inadequate and there are few data sets on adaptation-specific quantities such as vulnerability, resilience and adaptation effectiveness. Current international action under the United Nations Framework Convention on Climate Change (UNFCCC) pays little attention to adaptation and its information requirements. Furthermore there are trends toward reduced data gathering and to restrictions on access to data sets, especially arising from cost and commercialisation pressures. To effectively respond to the changes in climate that are now inevitable, governments will need to more clearly identify adaptation as a central feature of climate change policy and make a renewed shared commitment to collecting and freely exchanging the necessary data. 12 refs

  10. Evidence for a climate signal in trends of global crop yield variability over the past 50 years

    International Nuclear Information System (INIS)

    Osborne, T M; Wheeler, T R

    2013-01-01

    Low variability of crop production from year to year is desirable for many reasons, including reduced income risk and stability of supplies. Therefore, it is important to understand the nature of yield variability, whether it is changing through time, and how it varies between crops and regions. Previous studies have shown that national crop yield variability has changed in the past, with the direction and magnitude dependent on crop type and location. Whilst such studies acknowledge the importance of climate variability in determining yield variability, it has been assumed that its magnitude and its effect on crop production have not changed through time and, hence, that changes to yield variability have been due to non-climatic factors. We address this assumption by jointly examining yield and climate variability for three major crops (rice, wheat and maize) over the past 50 years. National yield time series and growing season temperature and precipitation were de-trended and related using multiple linear regression. Yield variability changed significantly in half of the crop–country combinations examined. For several crop–country combinations, changes in yield variability were related to changes in climate variability. (letter)

  11. Description of the default climate scenario for impact projects in NRP-II

    NARCIS (Netherlands)

    Verweij W; Viner D; NOP

    2001-01-01

    The Dutch National Research Programme on Climate Change (NRP) is funding strategic research on climate change. One of the central research themes focuses on potential impacts of climate change. In general, results of impact projects may differ markedly, depending on input of scenario data for

  12. Effects of temporal changes in climate variables on crop production ...

    African Journals Online (AJOL)

    Administrator

    comprehensive study of the impacts of climate variability on some common classes of food crops. (tubers, grains ... erosion, incidents of pests and diseases, and sea level rise (Onyekwelu et .... calamities and human sufferings. The productivity ...

  13. Impacts of climate change, variability and adaptation strategies on ...

    African Journals Online (AJOL)

    Impacts of climate change, variability and adaptation strategies on agriculture in semi arid areas of Tanzania: The case of Manyoni District in Singida Region, Tanzania. ... The changes have affected crops and livestock in a number of ways resulting in reduced productivity. Empirical analysis of rainfall suggest decreasing ...

  14. ENSO related decadal scale climate variability from the Indo-Pacific Warm Pool

    NARCIS (Netherlands)

    Brijker, J.M.; Jung, S.J.A.; Ganssen, G.M.; Bickert, T.; Kroon, D.

    2006-01-01

    The El Niño-Southern Oscillation (ENSO) is a climatic phenomenon that affects socio-economical welfare in vast areas in the world. A continuous record of Holocene ENSO related climate variability of the Indo-Pacific Warm pool (IPWP) is constructed on the basis of stable oxygen isotopes in shells of

  15. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

    Science.gov (United States)

    Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

    2017-09-01

    High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

  16. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

    Science.gov (United States)

    Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

    2018-06-01

    High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

  17. Impact of climate variability on tropospheric ozone

    International Nuclear Information System (INIS)

    Grewe, Volker

    2007-01-01

    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 Nino), 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

  18. Projections of temperature-related excess mortality under climate change scenarios

    Czech Academy of Sciences Publication Activity Database

    Gasparrini, A.; Guo, Y.; Sera, F.; Vicedo-Cabrera, A.M.; Huber, V.; Tong, S.; Coelho, M. S. Z. S.; Saldiva, P. H. N.; Lavigne, E.; Correa, P.M.; Ortega, N. V.; Kan, H.; Osorio, S.; Kyselý, Jan; Urban, Aleš; Jaakkola, J.J.K.; Ryti, N.R.I.; Pascal, M.; Goodman, P.G.; Zeka, A.; Michelozzi, P.; Scortichini, M.; Hashizume, M.; Honda, Y.; Hurtado-Diaz, M.; Cruz, J.C.; Seposo, X.; Kim, H.; Tobias, A.; Iñiguez, C.; Forsberg, B.; Åström, D.O.; Ragettli, M.S.; Guo, Y.L.; Wu, Ch.; Zanobetti, A.; Schwartz, J.; Bell, M.L.; Dang, T.N.; Van, D.D.; Heaviside, C.; Vardoulakis, S.; Hajat, S.; Haines, A.; Armstrong, B.

    2017-01-01

    Roč. 1, č. 9 (2017), e360-e367 ISSN 2542-5196 R&D Projects: GA ČR(CZ) GA16-22000S Institutional support: RVO:68378289 Keywords : climate change scenarios * mortality Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Climatic research https://www.sciencedirect.com/science/article/pii/S2542519617301560#!

  19. Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data.

    Science.gov (United States)

    Bateman, Brooke L; Pidgeon, Anna M; Radeloff, Volker C; Flather, Curtis H; VanDerWal, Jeremy; Akçakaya, H Resit; Thogmartin, Wayne E; Albright, Thomas P; Vavrus, Stephen J; Heglund, Patricia J

    2016-12-01

    Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate

  20. Impacts of Present and Future Climate Variability On Agriculture and Forestry in the Humid and Sub-Humid Tropics

    International Nuclear Information System (INIS)

    Zhao, Y.; Wang, C.; Wang, S.; Tibig, Lourdes V.

    2005-01-01

    Although there are different results from different studies, most assessments indicate that climate variability would have negative effects on agriculture and forestry in the humid and sub-humid tropics. Cereal crop yields would decrease generally with even minimal increases in temperature. For commercial crops, extreme events such as cyclones, droughts and floods lead to larger damages than only changes of mean climate. Impacts of climate variability on livestock mainly include two aspects; impacts on animals such as increase of heat and disease stress-related death, and impacts on pasture. As to forestry, climate variability would have negative as well as some positive impacts on forests of humid and sub-humid tropics. However, in most tropical regions, the impacts of human activities such as deforestation will be more important than climate variability and climate change in determining natural forest cover