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. 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

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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...

  3. 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.

  4. 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

  5. Climate variability and change

    CERN Document Server

    Grassl, H

    1998-01-01

    Many factors influence climate. The present knowledge concerning the climate relevance of earth orbital parameters, solar luminosity, volcanoes, internal interactions, and human activities will be reported as well as the vulnerability of emission scenarios for given stabilization goals for greenhouse gas concentrations and the main points of the Kyoto Protocol

  6. 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)

  7. 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...

  8. 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...

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. Climate Project Screening Tool

    Science.gov (United States)

    Forest Service U.S. Department of Agriculture

    2011-01-01

    Climate change poses a challenge for resource managers as they review current management practices. Adaptation is a critical means of addressing climate change in the near future because, due to inherent time lags in climate impacts, the effects of increased atmospheric greenhouse gases will be felt for decades even if effective mitigation begins now. To address the...

  14. 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.

  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. 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;.

  17. 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.

  18. 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

  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. 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...

  1. 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)...

  2. 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.

  3. 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

  4. 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.

  5. 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...

  6. 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...

  7. 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

  8. 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.

  9. 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

  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. 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

  12. 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.

  13. 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

  14. 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.

  15. Climatic variability of east Malaysia

    International Nuclear Information System (INIS)

    Camerlengo, A.L.; Saadon, M.N.; Awang, M.; Somchit, H.; Rang, L.Y.

    2001-01-01

    The objective of this paper is to learn the variability of atmospheric pressure, relative humidity and insolation in East Malaysia. The main results of our study are: (1) a gentle pressure gradient is observed at the east coast in the boreal winter, (2) smaller atmospheric pressure values are noted during the first inter-monsoon period all across East Malaysia, (3) lesser insolation values are observed in Sarawak and at the east coast during the boreal winter as compared to the boreal summer, and (4) a poleward increase of insolation is registered. (author)

  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. 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.

  18. 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)

  19. 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:

  20. 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:

  1. 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.

  2. 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 ...

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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)

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  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. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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.

  9. Food Price Volatility and Decadal Climate Variability

    Science.gov (United States)

    Brown, M. E.

    2013-12-01

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

  10. Decadal climate prediction (project GCEP).

    Science.gov (United States)

    Haines, Keith; Hermanson, Leon; Liu, Chunlei; Putt, Debbie; Sutton, Rowan; Iwi, Alan; Smith, Doug

    2009-03-13

    Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.

  11. 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.

  12. 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

  13. 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.

  14. Detecting Climate Variability in Tropical Rainfall

    Science.gov (United States)

    Berg, W.

    2004-05-01

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

  15. 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 ...

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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.

  1. 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

  2. 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

  3. Societal Vulnerability to Climate Change and Variability

    International Nuclear Information System (INIS)

    Handmer, J.W.; Dovers, S.; Downing, T.E.

    1999-01-01

    Institutions in many wealthy industrialised countries are robust and their societies appear to be relatively well insulated against the impacts of climate variability, economic problems elsewhere and so on. However, many countries are not in this position, and there is a growing group of humanity which is not benefiting from the apparent global adaptive trends. Worst case scenarios reinforce the impact of this uneven distribution of adaptive capacity, both between and within countries. Nevertheless, at the broad global scale human societies are strongly adaptive and not threatened by climate change for many decades. At the local level the picture is quite different and the survival of some populations at their present locations is in doubt. In the absence of abatement, the longer term outlook is highly uncertain. Adaptation research needs to begin with an understanding of social and economic vulnerability. It requires a different approach to the traditional IPCC impacts assessment, as human behaviour, institutional capacity and culture are more important than biophysical impacts. This is consistent with the intellectual history of the IPCC which has gradually embraced an increasing range of disciplines. 32 refs

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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 ...

  14. 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.

  15. 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'.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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...

  1. 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.

  2. Climatic history - answers on the variability of weather and climate?

    International Nuclear Information System (INIS)

    Glaser, R.; Hagedorn, H.

    1994-01-01

    The paper is concerned with various aspects of climatic history. Emphasis is on the spectrum of data and methods used in historical climatology. The following section is devoted to an outline of the short- and long-range climatic changes since 1500 A.D. that show how much the climate has varied in space and time. It is pointed out that climatic extremes have been an ever-recurrent phenomenon throughout history. (orig.) [de

  3. 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.

  4. 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...

  5. 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.

  6. 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.

  7. 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.

  8. 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 ...

  9. 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.

  10. 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, ...

  11. 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

  12. 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...

  13. 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.

  14. 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...

  15. Climate variability and climate change vulnerability and adaptation. Workshop summary

    Energy Technology Data Exchange (ETDEWEB)

    Bhatti, N.; Cirillo, R.R. [Argonne National Lab., IL (United States); Dixon, R.K. [U.S. Country Studies Program, Washington, DC (United States)] [and others

    1995-12-31

    Representatives from fifteen countries met in Prague, Czech Republic, on September 11-15, 1995, to share results from the analysis of vulnerability and adaptation to global climate change. The workshop focused on the issues of global climate change and its impacts on various sectors of a national economy. The U.N. Framework Convention on Climate Change (FCCC), which has been signed by more than 150 governments worldwide, calls on signatory parties to develop and communicate measures they are implementing to respond to global climate change. An analysis of a country`s vulnerability to changes in the climate helps it identify suitable adaptation measures. These analyses are designed to determine the extent of the impacts of global climate change on sensitive sectors such as agricultural crops, forests, grasslands and livestock, water resources, and coastal areas. Once it is determined how vulnerable a country may be to climate change, it is possible to identify adaptation measures for ameliorating some or all of the effects.The objectives of the vulnerability and adaptation workshop were to: The objectives of the vulnerability and adaptation workshop were to: Provide an opportunity for countries to describe their study results; Encourage countries to learn from the experience of the more complete assessments and adjust their studies accordingly; Identify issues and analyses that require further investigation; and Summarize results and experiences for governmental and intergovernmental organizations.

  16. Climate variability and climate change vulnerability and adaptation. Workshop summary

    International Nuclear Information System (INIS)

    Bhatti, N.; Cirillo, R.R.; Dixon, R.K.

    1995-01-01

    Representatives from fifteen countries met in Prague, Czech Republic, on September 11-15, 1995, to share results from the analysis of vulnerability and adaptation to global climate change. The workshop focused on the issues of global climate change and its impacts on various sectors of a national economy. The U.N. Framework Convention on Climate Change (FCCC), which has been signed by more than 150 governments worldwide, calls on signatory parties to develop and communicate measures they are implementing to respond to global climate change. An analysis of a country's vulnerability to changes in the climate helps it identify suitable adaptation measures. These analyses are designed to determine the extent of the impacts of global climate change on sensitive sectors such as agricultural crops, forests, grasslands and livestock, water resources, and coastal areas. Once it is determined how vulnerable a country may be to climate change, it is possible to identify adaptation measures for ameliorating some or all of the effects.The objectives of the vulnerability and adaptation workshop were to: The objectives of the vulnerability and adaptation workshop were to: Provide an opportunity for countries to describe their study results; Encourage countries to learn from the experience of the more complete assessments and adjust their studies accordingly; Identify issues and analyses that require further investigation; and Summarize results and experiences for governmental and intergovernmental organizations

  17. 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.

  18. 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.

  19. 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)

  20. 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.

  1. "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.

  2. 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.

  3. 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.

  4. 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...

  5. 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

  6. 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.

  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. CLIMATE VARIABILITY, CHANGE, AND CONSEQUENCES IN ESTUARIES

    Science.gov (United States)

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

  9. 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 ...

  10. Impacts of Climate Variability and Climate Change on the Mangrove ...

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

    Already under threat from water pollution, deforestation and overfishing (black conch), ... local authorities and other stakeholders, will document the impact of climate ... Adaptation strategies for two Colombian cities were discussed at ADAPTO's ... International Water Resources Association, in close collaboration with IDRC, ...

  11. 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

  12. 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 ...

  13. 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 ...

  14. 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 ...

  15. 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 ...

  16. 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

  17. The Variable Climate Impact of Volcanic Eruptions

    Science.gov (United States)

    Graf, H.

    2011-12-01

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

  18. Climate Variability and Migration: Evidence from Tanzania

    OpenAIRE

    Mathilde MAUREL; Zaneta KUBIK

    2014-01-01

    We analyze whether Tanzanian households engage in internal migration as a response to weather-related shocks. Our findings confirm that climate shocks lead to a higher probability of migration by reducing agricultural yields, which in turn induces households to send their members away in order to spatially diversify their income. This effect is, however, low, since a 1% reduction in agricultural income induced by weather shock increases the probability of migration by 3% for an average househ...

  19. 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)

  20. 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

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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

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

    African Journals Online (AJOL)

    Normalized Difference Vegetation Index (NDVI) data derived from moderate resolution imaging spectroradiometer (MODIS) 250 m satellite imageries for 2000 to 2014 were used to determine the temporal dynamics of P. juliflora invasion in the study area. Both temperature and rainfall trends showed marked variability over ...

  7. 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 ...

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  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. 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.

  16. 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.

  17. Bangladesh Agro-Climatic Environmental Monitoring Project

    Science.gov (United States)

    Vermillion, C.; Maurer, H.; Williams, M.; Kamowski, J.; Moore, T.; Maksimovich, W.; Obler, H.; Gilbert, E.

    1988-01-01

    The Agro-Climatic Environmental Monitoring Project (ACEMP) is based on a Participating Agency Service Agreement (PASA) between the Agency for International Development (AID) and the National Oceanic and Atmospheric Administration (NOAA). In FY80, the Asia Bureau and Office of Federal Disaster Assistance (OFDA), worked closely to develop a funding mechanism which would meet Bangladesh's needs both for flood and cyclone warning capability and for application of remote sensing data to development problems. In FY90, OFDA provided for a High Resolution Picture Transmission (HRPT) receiving capability to improve their forecasting accuracy for cyclones, flooding and storm surges. That equipment is primarily intended as a disaster prediction and preparedness measure. The ACEM Project was designed to focus on the development applications of remote sensing technology. Through this Project, AID provided to the Bangladesh Government (BDG) the equipment, technical assistance, and training necessary to collect and employ remote sensing data made available by satellites as well as hydrological data obtained from data collection platforms placed in major rivers. The data collected will enable the BDG to improve the management of its natural resources.

  18. Chaos, dynamical structure and climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, H.B. [Brookhaven National Lab., Upton, NY (United States). Dept. of Applied Science

    1995-09-01

    Deterministic chaos in dynamical systems offers a new paradigm for understanding irregular fluctuations. Techniques for identifying deterministic chaos from observed data, without recourse to mathematical models, are being developed. Powerful methods exist for reconstructing multidimensional phase space from an observed time series of a single scalar variable; these methods are invaluable when only a single scalar record of the dynamics is available. However, in some applications multiple concurrent time series may be available for consideration as phase space coordinates. Here the authors propose some basic analytical tools for such multichannel time series data, and illustrate them by applications to a simple synthetic model of chaos, to a low-order model of atmospheric circulation, and to two high-resolution paleoclimate proxy data series. The atmospheric circulation model, originally proposed by Lorenz, has 27 principal unknowns; they establish that the chaotic attractor can be embedded in a subspace of eight dimensions by exhibiting a specific subset of eight unknowns which pass multichannel tests for false nearest neighbors. They also show that one of the principal unknowns in the 27-variable model--the global mean sea surface temperature--is of no discernible usefulness in making short-term forecasts.

  19. 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

  20. 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.

  1. Natural climate variability in a coupled model

    International Nuclear Information System (INIS)

    Zebiak, S.E.; Cane, M.A.

    1990-01-01

    Multi-century simulations with a simplified coupled ocean-atmosphere model are described. These simulations reveal an impressive range of variability on decadal and longer time scales, in addition to the dominant interannual el Nino/Southern Oscillation signal that the model originally was designed to simulate. Based on a very large sample of century-long simulations, it is nonetheless possible to identify distinct model parameter sensitivities that are described here in terms of selected indices. Preliminary experiments motivated by general circulation model results for increasing greenhouse gases suggest a definite sensitivity to model global warming. While these results are not definitive, they strongly suggest that coupled air-sea dynamics figure prominently in global change and must be included in models for reliable predictions

  2. 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

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

    Science.gov (United States)

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

    2016-12-01

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

  4. 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.

  5. 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.

  6. 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)

  7. 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.

  8. 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.

  9. 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.

  10. 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...

  11. 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

  12. Climate change projections: past and future mysteries of climate science

    International Nuclear Information System (INIS)

    Meehl, Gerald A.

    2007-01-01

    Full text: Full text: The history of climate change has been wrapped in mysteries. Some have been solved, and we await the outcome of others. The major mystery of 20th century climate was why did temperatures rise in the early part of the century, level off, and then rise rapidly again after the 1970s? It has only been in the past seven years that advances in climate modelling have allowed us to deconstruct 20th century climate to pull apart the separate influences of natural and human-caused factors. This has allowed us to understand the subtle interplay between these various influences that produced the temperature time evolution. Another mystery has involved extreme weather and climate events. Again, climate models have allowed us to quantify how the small changes in average climate translate into much larger changes of regional extremes. The biggest remaining mysteries in climate science involve the future, and how the climate will evolve over the coming century. Up until now, various scenarios postulating different possible outcomes for 21st century climate, assuming different types of human activities, have been run in the climate models to provide a wide range of possible futures. However, more recently the outlook for global warming is being framed as a combination of mitigation and adaptation. If policy actions are taken to mitigate part of the problem of global warming, then climate models must be relied on to quantify the time-evolving picture of how much regional climate change we must adapt to. Solving this mystery will be the biggest and most important challenge ever taken on by the climate modelling community

  13. 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

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. 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...

  19. 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

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

    Science.gov (United States)

    USDA Forest Service

    2001-01-01

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

  1. 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 ...

  2. 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.

  3. 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.

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

    African Journals Online (AJOL)

    47% of the respondents perceived climatic variability as delayed in rainfall, 22% perceived it as high temperature, 6% says it is flood, 3% sees it as unusual rainfall while 22% perceived it as undefined season. Although both gender do not have the same adaptive capacity, women (100%) are more vulnerable to the impact ...

  5. 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

  6. 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.

  7. 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.

  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. 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

  10. 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.

  11. 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

  12. 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.

  13. Assessment of Variable Planting Date as an Agricultural Adaptation to Climate Variability in Sri Lanka

    Science.gov (United States)

    Rivera, A.; Gunda, T.; Hornberger, G. M.

    2016-12-01

    Agriculture accounts for approximately 70% of global freshwater withdrawals. Changes in precipitation patterns due to climate change as well as increasing demands for water necessitate an increased understanding of the water-­food intersection, notably at a local scale to inform farmer adaptations to improve water productivity, i.e., to get more food with less water. Local assessments of water-food security are particularly important for nations with self-sufficiency policies, which prioritize in-country production of certain resources. An ideal case study is the small island nation of Sri Lanka, which has a self-sufficiency policy for its staple food of rice. Because rice is a water-intensive crop, assessment of irrigation water requirements (IWRs) and the associated changes over time is especially important. Previous studies on IWRs of rice in Sri Lanka have failed to consider the Yala (dry) season, when water is scarcest.The goal of this study is to characterize the role that a human decision, setting the planting date, can play in buffering declines in rice yield against changes in precipitation patterns. Using four meteorological stations in the main rice-growing zones in Sri Lanka, we explore (1) general changes in IWRs over time during the Yala season and (2) the impact of the rice planting date. We use both historical data from meteorological stations as well as future projections from regional climate models. Our results indicate that gains can be achieved using a variable planting date relative to a fixed date, in accordance with a similar conclusion for the Maha (wet) season. This local scale assessment of Sri Lanka IWRs will contribute to the growing global literature on the impacts of water scarcity on agriculture and the role that one adaptation measure can play in mitigating deleterious impacts.

  14. 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.

  15. 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

  16. Climate variability and wine quality over Portuguese regions

    Science.gov (United States)

    Gouveia, Célia M.; Gani, Érico A.; Liberato, Margarida L. R.

    2015-04-01

    characterized in each region by high/low quality wines. Finally, we also investigated how climate variability is related to DOC wine quality for different regions using North Atlantic Oscillation (NAO) index. Results reveal a strong dependence of wine quality for all regions on maximum temperature and precipitation during spring and summer (the growing season) as expected. However the role of temperature on wine quality seems to be distinct among the diverse regions probably due to their different climate zoning. Moreover, it is shown that the differences associated with high/low quality wine are in agreement with different synoptic fields patterns. Our results suggest that this type of analysis may be used in developing a tool that may help anticipating a vintage/high quality year, based on already available seasonal climate outlooks. Santo F.E., de Lima M.I.P., Ramos A.M., Trigo R.M., Trends in seasonal surface air temperature in mainland Portugal, since 1941, International Journal Climatolology, 34: 1814-1837, doi: 10.1002/joc.3803 (2014) de Lima M.I.P., Santo F.E., Ramos A.M. , Trigo, R.M., Trends and correlations in annual extreme precipitation indices for mainland Portugal, 1941-2007, Theoretical and Applied Climatology, DOI:10.1007/s00704-013-1079-6 (2014) Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAGGLO/4155/2012).

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  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. 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.

  4. 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.

  5. 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)

  6. 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

  7. 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...

  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. 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.

  10. 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.

  11. 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)

  12. 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.

  13. 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...

  14. 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).

  15. 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)

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-06-01

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

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. Final Report for UW-Madison Portion of DE-SC0005301, "Collaborative Project: Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate"

    Energy Technology Data Exchange (ETDEWEB)

    Vimont, Daniel [University of Wisconsin - Madison

    2014-06-13

    This project funded two efforts at understanding the interactions between Central Pacific ENSO events, the mid-latitude atmosphere, and decadal variability in the Pacific. The first was an investigation of conditions that lead to Central Pacific (CP) and East Pacific (EP) ENSO events through the use of linear inverse modeling with defined norms. The second effort was a modeling study that combined output from the National Center for Atmospheric Research (NCAR) Community Atmospheric Model (CAM4) with the Battisti (1988) intermediate coupled model. The intent of the second activity was to investigate the relationship between the atmospheric North Pacific Oscillation (NPO), the Pacific Meridional Mode (PMM), and ENSO. These two activities are described herein.

  4. 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

  5. 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.

  6. 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....

  7. 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

  8. 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

  9. 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

  10. 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.

  11. 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

  12. 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.)

  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. 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

  15. 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 ...

  16. 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...

  17. 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

  18. Constrained variable projection method for blind deconvolution

    International Nuclear Information System (INIS)

    Cornelio, A; Piccolomini, E Loli; Nagy, J G

    2012-01-01

    This paper is focused on the solution of the blind deconvolution problem, here modeled as a separable nonlinear least squares problem. The well known ill-posedness, both on recovering the blurring operator and the true image, makes the problem really difficult to handle. We show that, by imposing appropriate constraints on the variables and with well chosen regularization parameters, it is possible to obtain an objective function that is fairly well behaved. Hence, the resulting nonlinear minimization problem can be effectively solved by classical methods, such as the Gauss-Newton algorithm.

  19. 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.

  20. 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

  1. Saharan dust, climate variability, and asthma in Grenada, the Caribbean.

    Science.gov (United States)

    Akpinar-Elci, Muge; Martin, Francis E; Behr, Joshua G; Diaz, Rafael

    2015-11-01

    Saharan dust is transported across the Atlantic and interacts with the Caribbean seasonal climatic conditions, becoming respirable and contributing to asthma presentments at the emergency department. This study investigated the relationships among dust, climatic variables, and asthma-related visits to the emergency room in Grenada. All asthma visits to the emergency room (n = 4411) over 5 years (2001-2005) were compared to the dust cover and climatic variables for the corresponding period. Variation in asthma was associated with change in dust concentration (R(2) = 0.036, p asthma was positively correlated with rainfall (R(2) = 0.055, p asthma visits were inversely related to mean sea level pressure (R(2) = 0.123, p = 0.006) and positively correlated with relative humidity (R(2) = 0.593, p = 0.85). Saharan dust in conjunction with seasonal humidity allows for inhalable particulate matter that exacerbates asthma among residents in the Caribbean island of Grenada. These findings contribute evidence suggesting a broader public health impact from Saharan dust. Thus, this research may inform strategic planning of resource allocation among the Caribbean public health agencies.

  2. 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

  3. 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

  4. 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).

  5. An analysis of prediction skill of monthly mean climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Arun; Chen, Mingyue; Wang, Wanqiu [Climate Prediction Center, National Centers for Environmental Prediction (CPC/NCEP), Camp Springs, MD (United States)

    2011-09-15

    In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30-40 days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability. (orig.)

  6. 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.

  7. 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.

  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. 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.

  10. Orbital Forcing driving climate variability on Tropical South Atlantic

    Science.gov (United States)

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

    2017-12-01

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

  11. 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.

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

    Science.gov (United States)

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

    2017-12-01

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

  13. Rising climate variability and synchrony in North Pacific ecosystems

    Science.gov (United States)

    Black, Bryan

    2017-04-01

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

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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...

  20. Adapting to the impacts of climate change and variability

    International Nuclear Information System (INIS)

    Mortsch, L.; Koshida, G.; Tavares, D.

    1993-05-01

    A workshop was held to encourage awareness of the climate change impact issues and build collaboration among the Great Lakes/St. Lawrence basin (GLSLB) research, resource management, and policy-making community; to identify research opportunities to address the issues of water management, ecosystem health, human health, and land use and management; and to recommend directions and priority areas for future studies to develop an integrated climate impact assessment for the GLSLB. Presentations at the workshop were on topics including an overview of the GLSLB Project, the impacts of climate change on water supply and demand, and impacts on water quality, fisheries, wetlands, agriculture, shoreline management, and human health. Panel sessions were also convened to discuss information requirements that would assist in decision- and policy-making and to address the concept of integration. Working groups on water management, ecosystem health, land use and management, and human health were formed and made recommendations. A synthesis is presented of the reports from and recommendations of the four working groups as well as extended abstracts of the plenary presentations. A separate abstract has been prepared for one of the presentations from this workshop

  1. 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

  2. Regional climate change: Precipitation variability in mountainous part of Bulgaria

    Directory of Open Access Journals (Sweden)

    Nikolova Nina

    2007-01-01

    Full Text Available The aim of paper is to analyze temporal and spatial changes in monthly precipitation as well as extremely dry and wet months in mountainous part of Bulgaria. Study precipitation variability in mountainous part is very important because this part is the region where the rivers take its source from. Extreme values of monthly precipitation are important information for better understanding of the whole variability and trends in precipitation time series. The mean investigated period is 1951-2005 and the reference period is so called temporary climate - 1961- 1990. Extreme dry precipitation months are defined as a month whose monthly precipitation is lower than 10% of gamma distribution in the reference period 1961-1990. Extreme wet months are determined with respect to 90% percentiles of gamma distribution (monthly precipitation is higher than 90%. The result of the research show that in mountainous part of Bulgaria during 1950s and 1960s number of extremely wet months is higher than number of dry months. Decreasing of monthly precipitation is a feature for 1980s. This dry period continues till 2004. The years 2000 makes impression as driest year in high mountains with about 7 extremely dry months. The second dry year is 1993. The negative precipitation anomaly is most clearly determined during last decade at study area. The present research points out that fluctuation of precipitation in mountainous part of Bulgaria are coinciding with regional and global climate trends.

  3. 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

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

    Science.gov (United States)

    Galbraith, E.; Sarmiento, J.

    2008-12-01

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

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

    Science.gov (United States)

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

    2014-12-01

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

  6. 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

  7. 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.

  8. Changing project finance climate; Project finance wo meguru kankyo henka

    Energy Technology Data Exchange (ETDEWEB)

    Madono, S. [The Export-Import Bank of Japan, Tokyo (Japan)

    1998-03-01

    Development of conditions under which project financing (PF) functions is described. PF, a method with which funds are procured for a project on the security of the assets of and the cash flow involving the project, established its position as a popular financial means. Into the 1990, however, PF underwent a complete change, when it came to be actively employed as a means for the procurement of money for what is called `infrastructure building project for invigorating the private sector` in the developing countries. PF has now come to be utilized for the financing of projects in various fields besides the field of resources exploitation. In particular, PF is now utilized in schemes such as BOT (build, operate, transfer) in public enterprises, for instance, electric power utilities in developing countries. The gravest problem found in the private sector invigorating type PF is that the sponsor, operator, exporter, and lender on their respective levels are experiencing rising risks because of intensified competition in the presence of a great number of projects. Such risks involve the exchange rate, the completion of work, and the relations between the borrower and operator. 2 figs.

  9. 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

  10. Characterizing the impact of projected changes in climate and ...

    Science.gov (United States)

    The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O3) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O3 are much larger than the impacts of changing demographics.

  11. Adaptation to climatic variability and change. Report of the task force on climate adaptation

    International Nuclear Information System (INIS)

    Smit, B.

    1994-01-01

    A critique and interpretation is presented of what is known and available about adaptation to climate changes, not based on any particular climate scenario. It is assumed that variability is a fact of climate and that changes in climatic conditions are possible and are constantly occurring. Emphasis is on adaptation with regard to economic and social activities in Canada. A series of linked objectives are addressed, relating to demonstration of the significance of adaptation, consideration of case studies of adaptation (past and potential future) in Canada, clarification of the meaning of adaptation and the forms it takes, assessment of policy implications, and identification of research priorities. The basic facts on global climate change are reviewed, including long-term temperature variations, and adaptation is discussed as a public policy response. Examples of adaptation in Canada are given in the areas of Great Lakes property, power generation, and transportation; Atlantic Canada communities and fisheries; forestry; the construction industry; the energy industry; recreation and tourism; agriculture; urban areas; and national defense. Recommendations regarding adapation are made to governments, the private sector, and researchers. An inventory of adaptation strategies for agriculture, the Arctic, coastal areas, ecosystems and land use, energy supply, fisheries, forestry, urban infrastructure, and water resources is appended

  12. 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

  13. 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...

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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...

  19. 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.)

  20. 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.

  1. 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.

  2. 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.

  3. 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...

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

    Science.gov (United States)

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

    2017-04-01

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

  5. Climate variability in a coupled GCM. Pt. 2

    International Nuclear Information System (INIS)

    Latif, M.; Sterl, A.; Assenbaum, M.; Junge, M.M.; Maier-Reimer, E.

    1993-01-01

    The seasonal cycle and the interannual variability of the tropical Indian Ocean circulation are investigated and the Indian Summer Monsoon is simulated by a coupled ocean-atmosphere general circulation model in a 26 year integration. Although the model exhibits significant climate drift, it simulates realistically the seasonal changes in the tropical Indian Ocean and the onset and evolution of the Indian Summer Monsoon. The amplitudes of the seasonal changes, however, are somewhat underestimated. The coupled GCM also simulates considerable interannual variability in the tropical Indian Ocean circulation which is partly related to the El Nino/Southern Oscillation (ENSO) phenomenon and the associated changes in the Walker Circulation. Changes in the surface wind stress appear to be crucial in forcing interannual variations in the Indian Ocean SST. As in the Pacific Ocean, the net surface heat flux acts as a negative feedback on the SST anomalies. The interannual variability in Monsoon rainfall is simulated by the coupled GCM only about half as strongly as observed. (orig.)

  6. 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,

  7. 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.

  8. 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

  9. 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.

  10. The Taiwanese-American occultation survey project stellar variability. III. Detection of 58 new variable stars

    Energy Technology Data Exchange (ETDEWEB)

    Ishioka, R.; Wang, S.-Y.; Zhang, Z.-W.; Lehner, M. J.; Cook, K. H.; King, S.-K.; Lee, T.; Marshall, S. L.; Schwamb, M. E.; Wang, J.-H.; Wen, C.-Y. [Institute of Astronomy and Astrophysics, Academia Sinica, 11F of Astronomy-Mathematics Building, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan (China); Alcock, C.; Protopapas, P. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Axelrod, T. [Steward Observatory, 933 North Cherry Avenue, Room N204, Tucson, AZ 85721 (United States); Bianco, F. B. [Center for Cosmology and Particle Physics, New York University, 4 Washington Place, New York, NY 10003 (United States); Byun, Y.-I. [Department of Astronomy and University Observatory, Yonsei University, 134 Shinchon, Seoul 120-749 (Korea, Republic of); Chen, W. P.; Ngeow, C.-C. [Institute of Astronomy, National Central University, No. 300, Jhongda Road, Jhongli City, Taoyuan County 320, Taiwan (China); Kim, D.-W. [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany); Rice, J. A., E-mail: ishioka@asiaa.sinica.edu.tw [Department of Statistics, University of California Berkeley, 367 Evans Hall, Berkeley, CA 94720 (United States)

    2014-04-01

    The Taiwanese-American Occultation Survey project is designed for the detection of stellar occultations by small-size Kuiper Belt Objects, and it has monitored selected fields along the ecliptic plane by using four telescopes with a 3 deg{sup 2} field of view on the sky since 2005. We have analyzed data accumulated during 2005-2012 to detect variable stars. Sixteen fields with observations of more than 100 epochs were examined. We recovered 85 variables among a total of 158 known variable stars in these 16 fields. Most of the unrecovered variables are located in the fields observed less frequently. We also detected 58 variable stars which are not listed in the International Variable Star Index of the American Association of Variable Star Observers. These variable stars are classified as 3 RR Lyrae, 4 Cepheid, 1 δ Scuti, 5 Mira, 15 semi-regular, and 27 eclipsing binaries based on the periodicity and the profile of the light curves.

  11. 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.

  12. The Response of Ice Sheets to Climate Variability

    Science.gov (United States)

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

    2017-12-01

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

  13. 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...

  14. Trends and variability in climate parameters of peshawar district

    International Nuclear Information System (INIS)

    Shah, S.A.A.; Nisa, S.; Khan, A.; Rahman, Z.U.

    2012-01-01

    Rain fall pattern, daily minimum and maximum temperatures and humidity are the main factors that constitute the climate of an area. In Pakistan, consecutive positive anomalies have been observed in minimum, maximum and mean temperatures and rainfall since mid 1970s. The objective of the current study was to investigate the recent trends and variability of annual minimum, maximum and mean temperatures, relative humidity and rainfall of Peshawar. Annual meteorological parameters for 30-years (1981-2010) of Peshawar observatory have been analysed to determine indications of variations from long-term averages. Different statistical methods were used to analyse the data. For this purpose, Mann-Kendall test was applied to Meteorological data of Peshawar (1981-2010) to study any trend, which were revealed to be in a mixture. The final results show that rainfall is decreasing, minimum temperature, mean temperature and relative humidity are increasing and maximum temperature has no change. Various factors could be responsible for the contemporary trends in climate like rise in number of vehicles and industries from reviewing available literature, keeping in mind the nature of the study. Trends found may have negative implications for agriculture, health and socioeconomic conditions of the region that require the attention from relevant stakeholders. (author)

  15. Contribution of Temperature to Chilean Droughts Using Ensemble Climate Projections

    Science.gov (United States)

    Zambrano-Bigiarini, M.; Alfieri, L.; Naumann, G.; Garreaud, R. D.

    2017-12-01

    Precipitation deficit is traditionally considered as the main driver of drought events, however the evolution of drought conditions is also influenced by other variables such as temperature, wind speed and evapotranspiration. In view of global warming, the effect of rising temperatures may lead to increased socio-economic drought impacts, particularly in vulnerable developing countries. In this work, we used two drought indices to analyze the impacts of precipitation and temperature on the frequency, severity and duration of Chilean droughts (25°S-56°S) during the XXI century, using multi-model climate projections consistent with the high-end RCP 8.5 scenario. An ensemble of seven global CMIP5 simulations were used to drive the Earth System Model EC-EARTH3-HR v3.1 over the 1976-2100 period, in order to increase the spatial resolution from the original grid to 0.35°. The Standardized Precipitation Index (SPI) was used to describe the impact of precipitation on drought conditions, while the Standardized Precipitation-Evapotranspiration Index (SPEI) was used to assess the effect of temperature -throughout changes in potential evapotranspiration- on drought characteristics at different time scales. Drought indices along with duration, severity and frequency of drought events were computed for a 30-year baseline period (1976-2005) and then compared to three 30-year periods representing short, medium and long-term scenarios (2011-2040, 2041-2070 and 2071-2100). Indices obtained from climate simulations during the baseline period were compared against the corresponding values derived from ground observations. Results obtained with SPI-12 reveal a progressive decrease in precipitation in Chile, which is consistent through all climate models, though each of them shows a different spatial pattern. Simulations based on SPEI-12 show that the expected increase in evaporative demand (driven by the temperature increase) for the region is likely to exacerbate the severity and

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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

  1. Climate variability and change in Ethiopia : exploring impacts and adaptation options for cereal production

    NARCIS (Netherlands)

    Kassie, B.T.

    2014-01-01

    Key words: Climate change, Adaptation, Crop modelling, Uncertainty, Maize (Zea mays), Central Rift Valley.

    Smallholder farmers in Ethiopia have been facing severe climate related hazards, in particular highly variable rainfall and severe droughts that negativelyaffect their

  2. 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.

  3. 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

  4. 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.)

  5. 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

  6. Grazing and climatic variability in Sajama National Park, Bolivia

    Directory of Open Access Journals (Sweden)

    Yager, K.

    2008-12-01

    Full Text Available Sajama National Park, the first protected area in Bolivia, includes five indigenous communities with a primary production base of pastoralism. The semi-arid region of the Central Andes is one of the most extreme areas of human occupation at 4200 meters altitude and affected by high climatic variability. This paper studies the relations between climate variability, resilience, biodiversity of pastures and pastoral production in Sajama National Park. We present a botanical study of palatable pasture herbs between two years, one humid (2006 and the other dry (2007. Thirty vascular plants were recorded. The number of species and the cover of iro (Festuca ortophylla peak in areas of intermediate disturbance; areas that are at a medium distance from camelid corrals. On the other hand, the cover of ephemeral plants between tussocks increases in high disturbance areas. This is interpreted as a result of the tradeoff between the damage of grazing and the benefit of the fertilization produced by the herding animals. The local people clearly perceive strong impacts of climate change, combined with changes in management and human pressures. The social dynamics and production management, combined with climate warming, water reduction, and the increasing variability of surface water regimes create potential risks for the local sustainability of pastoralism.

    El Parque Nacional Sajama, la primer área protegida de Bolivia, incluye a cinco comunidades indígenas con una base de producción principalmente de ganadería. Esta región semi-árida de los Andes Centrales es una de las áreas más extremas de ocupación humana a 4200 metros de altura y es afectada por una alta variabilidad climática. Este trabajo considera las relaciones entre la variabilidad climática, resiliencia, biodiversidad de pastos y la producción ganadera en el Parque Nacional Sajama. Presentamos un estudio botánico de las comunidades de hierbas palatables a lo largo de dos a

  7. 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

  8. 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.)

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Henrick Berger

    2013-08-01

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

  11. 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.

  12. Variability in climatic productivity of paddy rice in japan

    OpenAIRE

    Sugihara, Yasuyuki

    1985-01-01

    The regionaliy of climatic productivity was examined from the viewpoints of seasonal variation and temperature characteristics of climatic productivity. The obtained climatic divisions are types A1 (coldest), A2 (cold), A3 (moderate), B (warmtransitional), C (warm), and D (warmest). The long-range changes of climatic productivity for 6 stations representative of each agro-climatic division were obtained. The productivities of Asahikawa, Morioka, and Saga clearly indicate maximum or minimum va...

  13. Projected future runoff of the Breede River under climate change ...

    African Journals Online (AJOL)

    The Breede River is the largest river in the Western Cape Province of South Africa, and as such, is a key resource for a variety of activities within the region. It is this significance of the river that prompted a study into the impact of climate change on future runoff in the river and hence, the potential impacts a projected change ...

  14. Projected impacts of climate change on Indian agriculture

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Projected impacts of climate change on Indian agriculture. Increase in CO2 to 550 ppm increases yields of rice, wheat, legumes and oilseeds by 10-20%. A 1oC increase in temperature may reduce yields of wheat, soybean, mustard, groundnut, and potato by 3-7%.

  15. Response of streamflow to projected climate change scenarios in an ...

    Indian Academy of Sciences (India)

    Snowmelt run-off model (SRM) based on degree-day approach has been employed to evaluate the change in snow-cover depletion and corresponding streamflow under different projected climatic scenarios foran eastern Himalayan catchment in India. Nuranang catchment located at Tawang district of ArunachalPradesh ...

  16. 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

  17. 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.

  18. 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

  19. 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

  20. Holocene Climate Variability on the Centennial and Millennial Time Scale

    Directory of Open Access Journals (Sweden)

    Eun Hee Lee

    2014-12-01

    Full Text Available There have been many suggestions and much debate about climate variability during the Holocene. However, their complex forcing factors and mechanisms have not yet been clearly identified. In this paper, we have examined the Holocene climate cycles and features based on the wavelet analyses of 14C, 10Be, and 18O records. The wavelet results of the 14C and 10Be data show that the cycles of ~2180-2310, ~970, ~500-520, ~350-360, and ~210-220 years are dominant, and the ~1720 and ~1500 year cycles are relatively weak and subdominant. In particular, the ~2180-2310 year periodicity corresponding to the Hallstatt cycle is constantly significant throughout the Holocene, while the ~970 year cycle corresponding to the Eddy cycle is mainly prominent in the early half of the Holocene. In addition, distinctive signals of the ~210-220 year period corresponding to the de Vries cycle appear recurrently in the wavelet distribution of 14C and 10Be, which coincide with the grand solar minima periods. These de Vries cycle events occurred every ~2270 years on average, implying a connection with the Hallstatt cycle. In contrast, the wavelet results of 18O data show that the cycles of ~1900-2000, ~900-1000, and ~550-560 years are dominant, while the ~2750 and ~2500 year cycles are subdominant. The periods of ~2750, ~2500, and ~1900 years being derived from the 18O records of NGRIP, GRIP and GISP2 ice cores, respectively, are rather longer or shorter than the Hallstatt cycle derived from the 14C and 10Be records. The records of these three sites all show the ~900-1000 year periodicity corresponding to the Eddy cycle in the early half of the Holocene.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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

  16. The response of land-falling tropical cyclone characteristics to projected climate change in northeast Australia

    Science.gov (United States)

    Parker, Chelsea L.; Bruyère, Cindy L.; Mooney, Priscilla A.; Lynch, Amanda H.

    2018-01-01

    Land-falling tropical cyclones along the Queensland coastline can result in serious and widespread damage. However, the effects of climate change on cyclone characteristics such as intensity, trajectory, rainfall, and especially translation speed and size are not well-understood. This study explores the relative change in the characteristics of three case studies by comparing the simulated tropical cyclones under current climate conditions with simulations of the same systems under future climate conditions. Simulations are performed with the Weather Research and Forecasting Model and environmental conditions for the future climate are obtained from the Community Earth System Model using a pseudo global warming technique. Results demonstrate a consistent response of increasing intensity through reduced central pressure (by up to 11 hPa), increased wind speeds (by 5-10% on average), and increased rainfall (by up to 27% for average hourly rainfall rates). The responses of other characteristics were variable and governed by either the location and trajectory of the current climate cyclone or the change in the steering flow. The cyclone that traveled furthest poleward encountered a larger climate perturbation, resulting in a larger proportional increase in size, rainfall rate, and wind speeds. The projected monthly average change in the 500 mb winds with climate change governed the alteration in the both the trajectory and translation speed for each case. The simulated changes have serious implications for damage to coastal settlements, infrastructure, and ecosystems through increased wind speeds, storm surge, rainfall, and potentially increased size of some systems.

  17. 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

  18. 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

  19. 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.

  20. Interdependency in Multimodel Climate Projections: Component Replication and Result Similarity

    Science.gov (United States)

    Boé, Julien

    2018-03-01

    Multimodel ensembles are the main way to deal with model uncertainties in climate projections. However, the interdependencies between models that often share entire components make it difficult to combine their results in a satisfactory way. In this study, how the replication of components (atmosphere, ocean, land, and sea ice) between climate models impacts the proximity of their results is quantified precisely, in terms of climatological means and future changes. A clear relationship exists between the number of components shared by climate models and the proximity of their results. Even the impact of a single shared component is generally visible. These conclusions are true at both the global and regional scales. Given available data, it cannot be robustly concluded that some components are more important than others. Those results provide ways to estimate model interdependencies a priori rather than a posteriori based on their results, in order to define independence weights.

  1. 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

  2. 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...

  3. 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.

  4. 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

  5. Bromus response to climate and projected changes with climate change [Chapter 9

    Science.gov (United States)

    Bethany A. Bradley; Caroline A. Curtis; Jeanne C. Chambers

    2016-01-01

    A prominent goal of invasive plant management is to prevent or reduce the spread of invasive species into uninvaded landscapes and regions. Monitoring and control efforts often rely on scientific knowledge of suitable habitat for the invasive species. However, rising temperatures and altered precipitation projected with climate change are likely to shift the...

  6. 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

  7. 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.

  8. 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 ...

  9. 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.

  10. 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

  11. 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

  12. Projecting the climatic effects of increasing carbon dioxide

    Energy Technology Data Exchange (ETDEWEB)

    MacCracken, M C; Luther, F M [eds.

    1985-12-01

    This report presents the current knowns, unknowns, and uncertainties regarding the projected climate changes that might occur as a result of an increasing atmospheric CO/sub 2/ concentration. Further, the volume describes what research is required to estimate the magnitude and rate of a CO/sub 2/-induced clamate change with regional and seasonal resolution. Separate abstracts have been prepared for the individual papers. (ACR)

  13. Climate and domestic projects CO2: why and how?

    International Nuclear Information System (INIS)

    2006-01-01

    In order to fight against the climatic change, the France decided to divide by four the greenhouse gases for 2050. With the emission trading, the industrialists and the energy producers progress in this way. But nothing is existing for the emission sectors as the transport, the agriculture, the building and for the greenhouse gases except the CO 2 . The domestic projects CO 2 approach aims to stimulate the realization of projects reducing the greenhouse gases emissions in these sectors, with a remuneration of these reductions. (A.L.B.)

  14. Adaptation to climate change and climate variability in European agriculture: The importance of farm level responses

    NARCIS (Netherlands)

    Reidsma, P.; Ewert, F.; Oude Lansink, A.G.J.M.; Leemans, R.

    2010-01-01

    Climatic conditions and hence climate change influence agriculture. Most studies that addressed the vulnerability of agriculture to climate change have focused on potential impacts without considering adaptation. When adaptation strategies are considered, socio-economic conditions and farm

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. Projections of climate potential for a touristic resort in Mallorca

    Science.gov (United States)

    Amengual Pou, Arnau; Homar Santaner, Victor; Romero March, Romualdo; Alonso Oroza, Sergio; Ramis Noguera, Climent

    2010-05-01

    Platja de Palma, in the Island of Mallorca, is one of the most popular touristic areas in the Mediterranean with more than 8 million tourist-nights spent per year. Socioeconomic activities undertaken in Platja de Palma are very closely linked with its climate. Therefore, optimization of residential and tourism opportunities in the medium term should necessarily take into account the close interdependence between the evolution of the main atmospheric parameters and the sea, sun and sand tourism (S3), the main tourist model exploited in the area and heavily dependent on the climate. We used the Climate Index for Tourism (CIT, Freitas et al. 2008) to estimate the satisfaction of the S3 tourist in terms of the environmental conditions of the day. The CIT integrates thermal aspects, aesthetic and physical parameters, and derive a measure of perceived satisfaction for the average tourists in terms of three thresholds: unacceptable conditions, acceptable, and ideal. In the first place, we analyzed the evolution of the CIT using data from the proximity weather station in Palma airport for the period 1973-2008. Then, the impact of climate change on the tourism potential of the resort was assessed by calculating the CIT for future climate scenarios. We used regional climate simulation results from the European project ENSEMBLES and for the period 2001-2050. In order to compute the CIT index, daily series of temperature, precipitation, relative humidity, cloudiness and wind near surface are necessary. Model output series are calibrated using observations from Palma airport. In addition, future CIT series are also calibrated using values directly derived from observations. The analysis of the observed period reveals an increase in the number of days per year of acceptable conditions for S3 tourism since 1973 but a decrease in the frequency of ideal conditions, mainly during summer and autumn. Also, ideal conditions in Platja de Palma have increased in frequency during spring

  20. 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...

  1. 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).

  2. 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

  3. 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.

  4. 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

  5. Climate Variability and Change in the Mediterranean Region

    Science.gov (United States)

    Lionello, Piero; Özsoy, Emin; Planton, Serge; Zanchetta, Giovanni

    2017-04-01

    This special issue collects new research results on the climate of the Mediterranean region. It covers traditional topics of the MedCLIVAR programme (www.medclivar.eu, Lionello et al. 2006, Lionello et al. 2012b) being devoted to papers addressing on-going and future climate changes in the Mediterranean region and their impacts on its environment.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. (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

  11. 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.

  12. 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

  13. 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

  14. Designing forestry projects for climate action plan implementation

    Energy Technology Data Exchange (ETDEWEB)

    Sampson, R.N. [American Forests, Washington, DC (United States)

    1995-11-01

    Forests play an important role in sequestering and storing carbon in terrestrial ecosystems, so countries considering ways to mitigate greenhouse gas emissions are looking at forestry projects as one option. Designing forestry projects that accomplish desired goals is no simple task however, as many past failures attest. This paper proposes that, to be successful, climate change mitigation forestry projects need to: (a) feature other socially, economically and environmentally desirable goals as primary motivators; (b) be designed in cooperation with, and in the interests of, local populations, and (c), feature cooperative efforts between government, industry, and volunteer associations. Volunteer associations can often be assisted in being a more capable partner through an organizational training and support process, and this is one of the services offered to cooperating countries through American Forests. 21 refs.

  15. Temporal and Spatial Trend of Climate Variability in Vietnam

    OpenAIRE

    Duc Luong Nguyen

    2014-01-01

    Vietnam’s long coastline, geographic location, and diverse topography and climates contribute to its being one of the most hazard-prone countries of the Asia-Pacific region. Given that a high proportion of the country’s population and economic assets are located in coastal lowlands and deltas, Vietnam has been ranked among the five countries likely to be most affected by global climate change. This paper aims at providing a short overview on the temporal and spatial trends of climate variabil...

  16. 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.

  17. 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.

  18. Subseasonal climate variability for North Carolina, United States

    Science.gov (United States)

    Sayemuzzaman, Mohammad; Jha, Manoj K.; Mekonnen, Ademe; Schimmel, Keith A.

    2014-08-01

    Subseasonal trends in climate variability for maximum temperature (Tmax), minimum temperature (Tmin) and precipitation were evaluated for 249 ground-based stations in North Carolina for 1950-2009. The magnitude and significance of the trends at all stations were determined using the non-parametric Theil-Sen Approach (TSA) and the Mann-Kendall (MK) test, respectively. The Sequential Mann-Kendall (SQMK) test was also applied to find the initiation of abrupt trend changes. The lag-1 serial correlation and double mass curve were employed to address the data independency and homogeneity. Using the MK trend test, statistically significant (confidence level ≥ 95% in two-tailed test) decreasing (increasing) trends by 44% (45%) of stations were found in May (June). In general, trends were decreased in Tmax and increased in Tmin data series in subseasonal scale. Using the TSA method, the magnitude of lowest (highest) decreasing (increasing) trend in Tmax is - 0.050 °C/year (+ 0.052 °C/year) in the monthly series for May (March) and for Tmin is - 0.055 °C/year (+ 0.075 °C/year) in February (December). For the precipitation time series using the TSA method, it was found that the highest (lowest) magnitude of 1.00 mm/year (- 1.20 mm/year) is in September (February). The overall trends in precipitation data series were not significant at the 95% confidence level except that 17% of stations were found to have significant (confidence level ≥ 95% in two-tailed test) decreasing trends in February. The statistically significant trend test results were used to develop a spatial distribution of trends: May for Tmax, June for Tmin, and February for precipitation. A correlative analysis of significant temperature and precipitation trend results was examined with respect to large scale circulation modes (North Atlantic Oscillation (NAO) and Southern Oscillation Index (SOI). A negative NAO index (positive-El Niño Southern Oscillation (ENSO) index) was found to be associated with

  19. 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.

  20. Assessing Perceptions of Climate Variability and Change among ...

    African Journals Online (AJOL)

    ... data with the subjective recall and memory of change in climate from respondents. ... Also that rainfall data presented in this study represent a broad picture for the ... Key Words: Seasonality, rainfall pattern fluctuations, subsistence farmers, ...

  1. 630 understanding farmers' response to climate variability in nigeria

    African Journals Online (AJOL)

    Osondu

    Data were analyzed using descriptive statistics, and multinomial logit models. Farmers used multiple adaptation strategies; Crop Diversification (CD), Soil ... Increases in temperature, cloud ... and the effect of climate elements and their extreme ...

  2. Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan

    Science.gov (United States)

    Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

    2016-01-01

    This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (−) and one month ago (−)), and average relative humidity (current and 9 months ago (−)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future. PMID:26848675

  3. Solar variability and climate change: An historical perspective

    Science.gov (United States)

    Feldman, Theodore S.

    There is nothing new about the debate over the Sun's influence on terrestrial climate.As early as the late 18th century, widespread concern for the deterioration of the Earth's climate led to speculation about the Sun's role in climate change [Feldman, 1993; Fleming, 1990]. Drawing analogies with variations in the brightness of stars, the British astronomer William Herschel suggested that greater sunspot activity would result in warmer terrestrial climates. Herschel supported his hypothesis by referring to price series for wheat published in Adam Smiths Wealth of Nations [Hufbauer, 1991]. Later, the eminent American physicist Joseph Henry demonstrated by thermopile measurements that, contrary to Herschel's assumption, sunspots were cooler than the unblemished portions of the solar disk.

  4. Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan

    Directory of Open Access Journals (Sweden)

    Hsin-I Hsiao

    2016-02-01

    Full Text Available This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA models (including autoregression, seasonality, and a lag-time effect were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+, ocean temperature (+, ocean salinity of 6 months ago (+, maximum daily rainfall (current (− and one month ago (−, and average relative humidity (current and 9 months ago (− had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future.

  5. Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan.

    Science.gov (United States)

    Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

    2016-02-03

    This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (-) and one month ago (-)), and average relative humidity (current and 9 months ago (-)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future.

  6. 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.)

  7. Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan

    OpenAIRE

    Hsin-I Hsiao; Man-Ser Jan; Hui-Ju Chi

    2016-01-01

    This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 201...

  8. 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

  9. 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

  10. 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

  11. Climate variability and causes: from the perspective of the Tharaka people of eastern Kenya

    Science.gov (United States)

    Recha, Charles W.; Makokha, George L.; Shisanya, Chris A.

    2017-12-01

    The study assessed community understanding of climate variability in semi-arid Tharaka sub-county, Kenya. The study used four focus group discussions (FGD) ( N = 48) and a household survey ( N = 326) to obtain information from four agro-ecological zones (AEZs). The results were synthesized and descriptively presented. People in Tharaka sub-county are familiar with the term climate change and associate it with environmental degradation. There are, however, misconceptions and gaps in understanding the causes of climate change. There was a mismatch between community and individual perception of onset and cessation of rainfall—evidence that analysis of the impact of climate change should take into account the scale of interaction. To improve climate change knowledge, there is a need for climate change education by scientific institutions—to provide information on local climatic conditions and global and regional drivers of climate change to local communities.

  12. North atlantic multidecadal climate variability: An investigation of dominant time scales and processes

    NARCIS (Netherlands)

    Frankcombe, L.M.|info:eu-repo/dai/nl/304829838; von der Heydt, A.S.|info:eu-repo/dai/nl/245567526; Dijkstra, H.A.|info:eu-repo/dai/nl/073504467

    2010-01-01

    The issue of multidecadal variability in the North Atlantic has been an important topic of late. It is clear that there are multidecadal variations in several climate variables in the North Atlantic, such as sea surface temperature and sea level height. The details of this variability, in particular

  13. Projected impacts of climate change on hydropower potential in China

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Xingcai; Tang, Qiuhong; Voisin, Nathalie; Cui, Huijuan

    2016-01-01

    Hydropower is an important renewable energy source in China, but it is sensitive to climate change, because the changing climate may alter hydrological conditions (e.g., river flow and reservoir storage). Future changes and associated uncertainties in China's gross hydropower potential (GHP) and developed hydropower potential (DHP) are projected using simulations from eight global hydrological models (GHMs), including a large-scale reservoir regulation model, forced by five general circulation models (GCMs) with climate data under two representative concentration pathways (RCP2.6 and RCP8.5). Results show that the estimation of the present GHP of China is comparable to other studies; overall, the annual GHP is projected to change by −1.7 to 2 % in the near future (2020–2050) and increase by 3 to 6 % in the late 21st century (2070–2099). The annual DHP is projected to change by −2.2 to −5.4 % (0.7–1.7 % of the total installed hydropower capacity (IHC)) and −1.3 to −4 % (0.4–1.3 % of total IHC) for 2020–2050 and 2070–2099, respectively. Regional variations emerge: GHP will increase in northern China but decrease in southern China – mostly in south central China and eastern China – where numerous reservoirs and large IHCs currently are located. The area with the highest GHP in southwest China will have more GHP, while DHP will reduce in the regions with high IHC (e.g., Sichuan and Hubei) in the future. The largest decrease in DHP (in %) will occur in autumn or winter, when streamflow is relatively low and water use is competitive. Large ranges in hydropower estimates across GHMs and GCMs highlight the necessity of using multimodel assessments under climate change conditions. This study prompts the consideration of climate change in planning for hydropower development and operations in China, to be further combined with a socioeconomic analysis for strategic expansion.

  14. Importance of ensembles in projecting regional climate trends

    Science.gov (United States)

    Arritt, Raymond; Daniel, Ariele; Groisman, Pavel

    2016-04-01

    We have performed an ensemble of simulations using RegCM4 to examine the ability to reproduce observed trends in precipitation intensity and to project future changes through the 21st century for the central United States. We created a matrix of simulations over the CORDEX North America domain for 1950-2099 by driving the regional model with two different global models (HadGEM2-ES and GFDL-ESM2M, both for RCP8.5), by performing simulations at both 50 km and 25 km grid spacing, and by using three different convective parameterizations. The result is a set of 12 simulations (two GCMs by two resolutions by three convective parameterizations) that can be used to systematically evaluate the influence of simulation design on predicted precipitation. The two global models were selected to bracket the range of climate sensitivity in the CMIP5 models: HadGEM2-ES has the highest ECS of the CMIP5 models, while GFDL-ESM2M has one of the lowestt. Our evaluation metrics differ from many other RCM studies in that we focus on the skill of the models in reproducing past trends rather than the mean climate state. Trends in frequency of extreme precipitation (defined as amounts exceeding 76.2 mm/day) for most simulations are similar to the observed trend but with notable variations depending on RegCM4 configuration and on the driving GCM. There are complex interactions among resolution, choice of convective parameterization, and the driving GCM that carry over into the future climate projections. We also note that biases in the current climate do not correspond to biases in trends. As an example of these points the Emanuel scheme is consistently "wet" (positive bias in precipitation) yet it produced the smallest precipitation increase of the three convective parameterizations when used in simulations driven by HadGEM2-ES. However, it produced the largest increase when driven by GFDL-ESM2M. These findings reiterate that ensembles using multiple RCM configurations and driving GCMs are

  15. 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.

  16. Projected climate change threatens pollinators and crop production in Brazil.

    Directory of Open Access Journals (Sweden)

    Tereza Cristina Giannini

    Full Text Available Animal pollination can impact food security since many crops depend on pollinators to produce fruits and seeds. However, the effects of projected climate change on crop pollinators and therefore on crop production are still unclear, especially for wild pollinators and aggregate community responses. Using species distributional modeling, we assessed the effects of climate change on the geographic distribution of 95 pollinator species of 13 Brazilian crops, and we estimated their relative impacts on crop production. We described these effects at the municipality level, and we assessed the crops that were grown, the gross production volume of these crops, the total crop production value, and the number of inhabitants. Overall, considering all crop species, we found that the projected climate change will reduce the probability of pollinator occurrence by almost 0.13 by 2050. Our models predict that almost 90% of the municipalities analyzed will face species loss. Decreases in the pollinator occurrence probability varied from 0.08 (persimmon to 0.25 (tomato and will potentially affect 9% (mandarin to 100% (sunflower of the municipalities that produce each crop. Municipalities in central and southern Brazil will potentially face relatively large impacts on crop production due to pollinator loss. In contrast, some municipalities in northern Brazil, particularly in the northwestern Amazon, could potentially benefit from climate change because pollinators of some crops may increase. The decline in the probability of pollinator occurrence is found in a large number of municipalities with the lowest GDP and will also likely affect some places where crop production is high (20% to 90% of the GDP and where the number of inhabitants is also high (more than 6 million people. Our study highlights key municipalities where crops are economically important and where pollinators will potentially face the worst conditions due to climate change. However, pollinators

  17. Chemistry and Climate in Asia - An Earth System Modeling Project

    Science.gov (United States)

    Barth, M. C.; Emmons, L. K.; Massie, S. T.; Pfister, G.; Romero Lankao, P.; Lamarque, J.; Carmichael, G. R.

    2011-12-01

    Asia is one of the most highly populated and economically dynamic regions in the world, with much of the population located in growing mega-cities. It is a region with significant emissions of greenhouse gases, aerosols and other pollutants, which pose high health risks to urban populations. Emissions of these aerosols and gases increased drastically over the last decade due to economic growth and urbanization and are expected to rise further in the near future. As such, the continent plays a role in influencing climate change via its effluent of aerosols and gaseous pollutants. Asia is also susceptible to adverse climate change through interactions between aerosols and clouds, which potentially can have serious implications for freshwater resources. We are developing an integrated inter-disciplinary program to focus on Asia, its climate, air quality, and impact on humans that will include connections with hydrology, ecosystems, extreme weather events, and human health. The primary goal of this project is to create a team to identify key scientific questions and establish networks of specialists to create a plan for future studies to address these questions. A second goal is to establish research facilities and a framework for investigating chemistry and climate over Asia. These facilities include producing high resolution Earth System Model simulations that have been evaluated with meteorological and chemical measurements, producing high-resolution emission inventories, analyzing satellite data, and analyzing the vulnerability of humans to air quality and extreme natural events. In this presentation we will describe in more detail these activities and discuss a future workshop on the impact of chemistry in climate on air quality and human health.

  18. Impacts of Climate Variability and Change on (Marine) Animals: Physiological Underpinnings and Evolutionary Consequences.

    Science.gov (United States)

    Pörtner, Hans O; Gutt, Julian

    2016-07-01

    variability throughout earth's history have influenced animal evolution and co-defined their success or failure from a bio-energetic point of view. Deepening such understanding may further reduce uncertainty about projected impacts of anthropogenic climate variability and change on the distribution, productivity and last not least, survival of aquatic and terrestrial species. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

  19. Projected climatic changes on drought conditions over Spain

    Science.gov (United States)

    García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

    2017-04-01

    In a context of global warming, the evapotranspiration processes will have a strong influence on drought severity. For this reason, the Standardized Precipitation Evapotranspiration Index (SPEI) was computed at different timescales in order to explore the projected drought changes for the main watersheds in Spain. For that, the Weather Research and Forecasting (WRF) model has been used in order to obtain current (1980-2010) and future (2021-2050 and 2071-2100) climate output fields. WRF model was used over a domain that spans the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser 0.44° EURO-CORDEX domain, and driving by the global bias-corrected climate model output data from version 1 of NCAR's Community Earth System Model (CESM1), using two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Besides, to examine the behavior of this drought index, a comparison with the Standardized Precipitation Index (SPI), which does not consider the evapotranspiration effects, was also performed. Additionally the relationship between the SPEI index and the soil moisture has also been analyzed. The results of this study suggest an increase in the severity and duration of drought, being larger when the SPEI index is used to define drought events. This fact confirms the relevance of taking into account the evapotranspiration processes to detect future drought events. The results also show a noticeable relationship between the SPEI and the simulated soil moisture content, which is more significant at higher timescales. Keywords: Drought, SPEI, SPI, Climatic change, Projections, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

  20. 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.

  1. 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.

  2. 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.

  3. Integrated variable projection approach (IVAPA) for parallel magnetic resonance imaging.

    Science.gov (United States)

    Zhang, Qiao; Sheng, Jinhua

    2012-10-01

    Parallel magnetic resonance imaging (pMRI) is a fast method which requires algorithms for the reconstructing image from a small number of measured k-space lines. The accurate estimation of the coil sensitivity functions is still a challenging problem in parallel imaging. The joint estimation of the coil sensitivity functions and the desired image has recently been proposed to improve the situation by iteratively optimizing both the coil sensitivity functions and the image reconstruction. It regards both the coil sensitivities and the desired images as unknowns to be solved for jointly. In this paper, we propose an integrated variable projection approach (IVAPA) for pMRI, which integrates two individual processing steps (coil sensitivity estimation and image reconstruction) into a single processing step to improve the accuracy of the coil sensitivity estimation using the variable projection approach. The method is demonstrated to be able to give an optimal solution with considerably reduced artifacts for high reduction factors and a low number of auto-calibration signal (ACS) lines, and our implementation has a fast convergence rate. The performance of the proposed method is evaluated using a set of in vivo experiment data. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. 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.

  5. 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)

  6. Role of climate variability in the heatstroke death rates of Kanto region in Japan

    Science.gov (United States)

    Akihiko, Takaya; Morioka, Yushi; Behera, Swadhin K.

    2014-07-01

    The death toll by heatstroke in Japan, especially in Kanto region, has sharply increased since 1994 together with large interannual variability. The surface air temperature and humidity observed during boreal summers of 1980-2010 were examined to understand the role of climate in the death toll. The extremely hot days, when the daily maximum temperature exceeds 35°C, are more strongly associated with the death toll than the conventional Wet Bulb Globe Temperature index. The extremely hot days tend to be associated with El Niño/Southern Oscillation or the Indian Ocean Dipole, suggesting a potential link with tropical climate variability to the heatstroke related deaths. Also, the influence of these climate modes on the death toll has strengthened since 1994 probably related to global warming. It is possible to develop early warning systems based on seasonal climate predictions since recent climate models show excellent predictability skills for those climate modes.

  7. 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...

  8. 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

  9. Agro-climate Projections for a Warming Alaska

    Science.gov (United States)

    Lader, R.; Walsh, J. E.; Bhatt, U. S.; Bieniek, P.

    2017-12-01

    In the context of greenhouse warming, agro-meteorological indices suggest widespread disruption to current food supply chains during the coming decades. Much of the western United States is projected to have more dry days, and the southern states are likely to experience greater plant heat stress. Considering these difficulties, it could become necessary for more northerly locations, including Alaska, to increase agricultural production to support local communities and offset supply shortages. This study employs multiple dynamically downscaled regional climate model simulations from the CMIP5 to investigate projected changes to agro-climate conditions across Alaska. The metric used here, the start-of-field operations index (SFO), identifies the date during which the sum of daily average temperature, starting from January 1st and excluding negative values, exceeds 200 ˚C. Using the current trajectory of greenhouse radiative forcing, RCP 8.5, this study indicates a doubling to 71,960 km2 of Alaska land area that meets the required thermal accumulation for crop production when comparing a historical period (1981-2010) to the future (2071-2100). The SFO shows a correlation coefficient of 0.91 with the independently produced green-up index for Fairbanks from 1981-2010. Among the land areas that currently reach the necessary thermal accumulation, there is a projected increase in growing season length (63-82 days), earlier date of last spring frost (28-48 days), and later date of first autumn frost (24-47 days) across the five USDA Census of Agriculture areas for Alaska. Both an average statewide decrease of annual frost days (71 fewer), and an increase in days with extreme warmth (28 more) are also projected.

  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. Uncovering effects of climate variables on global vegetation

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this project is to understand the causal relationships of how ecosystem dynamics, mostly characterized by vegetation changes, in different...

  12. Seasonal forecasts: communicating current climate variability in southern Africa

    CSIR Research Space (South Africa)

    Landman, WA

    2011-11-01

    Full Text Available seasonal time scale. Seasonal climate forecasts are defined as probabilistic predictions of how much rain is expected during the season and how warm or cool it will be, based primarily on the principle that the ocean (sea-surface temperatures) influences...

  13. Arctic Climate Variability and Trends from Satellite Observations

    Directory of Open Access Journals (Sweden)

    Xuanji Wang

    2012-01-01

    Full Text Available Arctic climate has been changing rapidly since the 1980s. This work shows distinctly different patterns of change in winter, spring, and summer for cloud fraction and surface temperature. Satellite observations over 1982–2004 have shown that the Arctic has warmed up and become cloudier in spring and summer, but cooled down and become less cloudy in winter. The annual mean surface temperature has increased at a rate of 0.34°C per decade. The decadal rates of cloud fraction trends are −3.4%, 2.3%, and 0.5% in winter, spring, and summer, respectively. Correspondingly, annually averaged surface albedo has decreased at a decadal rate of −3.2%. On the annual average, the trend of cloud forcing at the surface is −2.11 W/m2 per decade, indicating a damping effect on the surface warming by clouds. The decreasing sea ice albedo and surface warming tend to modulate cloud radiative cooling effect in spring and summer. Arctic sea ice has also declined substantially with decadal rates of −8%, −5%, and −15% in sea ice extent, thickness, and volume, respectively. Significant correlations between surface temperature anomalies and climate indices, especially the Arctic Oscillation (AO index, exist over some areas, implying linkages between global climate change and Arctic climate change.

  14. Climate Variability and Access to and Utilization of Water Resources ...

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

    The team will collect climate and hydrological data, and conduct household surveys in three informal neighborhoods (Nonghin, Polesgo, Nioko II) in Ougadougou, covering approximately 35 000 people. The methods used to analyze and interpret the quantitative data gathered on the availability and quality of water will be ...

  15. Rainfall Variability and the Recent Climate Extremes in Nigeria ...

    African Journals Online (AJOL)

    Recently, large and extended weather and climate extremes were recorded in different parts of the country, causing significant socio-economic impacts. Weather patterns affecting the country are driven by the northward and southward movement of the Inter-Tropical Discontinuity (ITD) as well as developments within the ...

  16. Climate Change and Variability: Implications for Household Food ...

    African Journals Online (AJOL)

    These are drought, low annual rainfall, high temperature, and water shortage. The econometric model estimation result revealed the important factors determining household food security. These are household perception of climate change, use of soil and water conservation practices, use of livestock feed management ...

  17. Climate Variability and Household Adaptation Strategies in Southern Ethiopia

    Directory of Open Access Journals (Sweden)

    Wassie Berhanu

    2015-05-01

    Full Text Available This paper examines the determinants and implied economic impacts of climate change adaptation strategies in the context of traditional pastoralism. It is based on econometric analysis of survey data generated from household level interviews in southern Ethiopian rangelands. Pastoralists’ perception of climate change in the region is found to be very consistent with the actually recorded trends of increased temperature and the evident secular declines in precipitation. Not only long-term declines, trends in the region’s rainfall also appear to have taken a shift towards the direction of more unpredictability. Pastoralist adaptation response strategies broadly involve adjustments in pastoral practices and shifts to non-pastoral livelihoods. Results of the estimated models confirm that pastoral mobility is still quite essential in the present context of climate-induced household vulnerabilities. Increased mobility and diversification of pastoral herd portfolios in favor of a drought-tolerant species (camel are found to be positively associated with pastoral household net income. A policy stance that ignores the detrimental impacts of the currently pervasive private rangeland enclosures or intends to hasten pastoralist sedentarization in the area is simply untenable in the present context of climate-induced risks and pastoral livelihood vulnerability.

  18. Climate change/variability science and adaptive strategies for state and regional transportation decision making.

    Science.gov (United States)

    2010-04-01

    The objective of this study was to generate a baseline understanding of current policy responses to climate : change/variability at the state and regional transportation-planning and -decision levels. Specifically, : researchers were interested in th...

  19. Using traditional methods and indigenous technologies for coping with climate variability

    NARCIS (Netherlands)

    Stigter, C.J.; Zheng Dawei,; Onyewotu, L.O.Z.; Mei Xurong,

    2005-01-01

    In agrometeorology and management of meteorology related natural resources, many traditional methods and indigenous technologies are still in use or being revived for managing low external inputs sustainable agriculture (LEISA) under conditions of climate variability. This paper starts with the

  20. Changes of extreme precipitation and nonlinear influence of climate variables over monsoon region in China

    KAUST Repository

    Gao, Tao; Wang, Huixia Judy; Zhou, Tianjun

    2017-01-01

    of precipitation extremes over monsoon regions in China (MRC). However, research on monsoon extremes in China and their associations with climate variables is limited. In this study, we examine the space-time variations of extreme precipitation across the MRC

  1. Forests and trees for social adaptation to climate variability and change

    NARCIS (Netherlands)

    Pramova, E.; Locatelli, B.; Djoudi, H.; Somorin, O.A.

    2012-01-01

    Ecosystems provide important services that can help people adapt to climate variability and change. Recognizing this role of ecosystems, several international and nongovernmental organizations have promoted an ecosystem-based approach to adaptation. We review the scientific literature related to

  2. 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 ...

  3. Long-term streamflow response to climatic variability in the Loess Plateau, China

    Science.gov (United States)

    Shenping Wang; Zhiqiang Zhang; Ge Sun; Steven G. McNulty; Huayong Zhang; Jianlao Li; Manliang Zhang

    2008-01-01

    The Loess Plateau region in northwestern China has experienced severe water resource shortages due to the combined impacts of climate and land use changes and water resource exploitation during the past decades. This study was designed to examine the impacts of climatic variability on streamflow characteristics of a 12-km2 watershed near Tianshui City, Gansu Province...

  4. 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...

  5. 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

  6. Impacts of Climate Change and Variability on Water Resources in the Southeast USA

    Science.gov (United States)

    Ge Sun; Peter V. Caldwell; Steven G. McNulty; Aris P. Georgakakos; Sankar Arumugam; James Cruise; Richard T. McNider; Adam Terando; Paul A. Conrads; John Feldt; Vasu Misra; Luigi Romolo; Todd C. Rasmussen; Daniel A. Marion

    2013-01-01

    Key FindingsClimate change is affecting the southeastern USA, particularly increases in rainfall variability and air temperature, which have resulted in more frequent hydrologic extremes, such as high‐intensity storms (tropical storms and hurricanes), flooding, and drought events.Future climate warming likely will...

  7. 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 ...

  8. Capturing subregional variability in regional-scale climate change vulnerability assessments of natural resources

    Science.gov (United States)

    Polly C. Buotte; David L. Peterson; Kevin S. McKelvey; Jeffrey A. Hicke

    2016-01-01

    Natural resource vulnerability to climate change can depend on the climatology and ecological conditions at a particular site. Here we present a conceptual framework for incorporating spatial variability in natural resource vulnerability to climate change in a regional-scale assessment. The framework was implemented in the first regional-scale vulnerability...

  9. 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...

  10. Effects of climate variability on freshwater fisheries in Cambodia's rice field fisheries: a longitudinal cohort study

    Directory of Open Access Journals (Sweden)

    Kathryn J Fiorella, PhD

    2018-05-01

    Full Text Available Background: Projections suggest that by 2050, climate change will reduce global fish catch by 3–13%, with fish catch falling by as much as 30% in some tropical marine systems. Freshwater fisheries are particularly susceptible to the warming effects of climate change because shallower, hydrologically distinct water bodies are easily affected by atmospheric temperatures and less easily accommodate fish migrations. Damage to freshwater fisheries is a problem particularly for poor and undernourished human populations, which are especially dependent on them. Despite the severity of projected climate change effects on fish catch and the risk to human health, few empirical studies have examined how fish catch is already responding to climate variability, the ways fishers are adapting to these changes, and how it affects people's consumption of fish, which are rich in micronutrients and fatty acids. We aim here to account for behavioural responses among fishers to identify the ecological effect of flood and weather on fish catch in Cambodian rice field fisheries, and patterns of fish consumption and nutrition in the local communities. Methods: In this longitudinal cohort study, we use a panel dataset collected by WorldFish of 400 households dependent on rice field fisheries over 3 years (19 distinct timepoints to examine how changing flood patterns and temperature alter households' fish catch and whether fishing families respond by either adapting the effort put into fishing (ie, hours, time of day, or number of family members involved or fish consumption. We analyse the net effect of biophysical changes on household fish catch, the effect of biophysical changes (flood, temperature, and rainfall on household fish catch and fish consumption with the addition of controls for fishing effort, a key way that fishers might adapt to ecological changes, and the direct effect of biophysical changes on fishing effort and fish consumption. Findings: Preliminary

  11. A projected decrease in lightning under climate change

    Science.gov (United States)

    Finney, Declan L.; Doherty, Ruth M.; Wild, Oliver; Stevenson, David S.; MacKenzie, Ian A.; Blyth, Alan M.

    2018-03-01

    Lightning strongly influences atmospheric chemistry1-3, and impacts the frequency of natural wildfires4. Most previous studies project an increase in global lightning with climate change over the coming century1,5-7, but these typically use parameterizations of lightning that neglect cloud ice fluxes, a component generally considered to be fundamental to thunderstorm charging8. As such, the response of lightning to climate change is uncertain. Here, we compare lightning projections for 2100 using two parameterizations: the widely used cloud-top height (CTH) approach9, and a new upward cloud ice flux (IFLUX) approach10 that overcomes previous limitations. In contrast to the previously reported global increase in lightning based on CTH, we find a 15% decrease in total lightning flash rate with IFLUX in 2100 under a strong global warming scenario. Differences are largest in the tropics, where most lightning occurs, with implications for the estimation of future changes in tropospheric ozone and methane, as well as differences in their radiative forcings. These results suggest that lightning schemes more closely related to cloud ice and microphysical processes are needed to robustly estimate future changes in lightning and atmospheric composition.

  12. Antarctic climate variability on regional and continental scales over the last 2000 years

    Directory of Open Access Journals (Sweden)

    B. Stenni

    2017-11-01

    Antarctic Peninsula regions, and these trends are robust across the distribution of records that contribute to the unweighted isotopic composites and also significant in the weighted temperature reconstructions. Only for the Antarctic Peninsula is this most recent century-scale trend unusual in the context of natural variability over the last 2000 years. However, projected warming of the Antarctic continent during the 21st century may soon see significant and unusual warming develop across other parts of the Antarctic continent. The extended Antarctica2k ice core isotope database developed by this working group opens up many avenues for developing a deeper understanding of the response of Antarctic climate to natural and anthropogenic climate forcings. The first long-term quantification of regional climate in Antarctica presented herein is a basis for data–model comparison and assessments of past, present and future driving factors of Antarctic climate.

  13. 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.

  14. 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.

  15. 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 im