WorldWideScience

Sample records for models current climate

  1. Drought Duration Biases in Current Global Climate Models

    Science.gov (United States)

    Moon, Heewon; Gudmundsson, Lukas; Seneviratne, Sonia

    2016-04-01

    Several droughts in the recent past are characterized by their increased duration and intensity. In particular, substantially prolonged droughts have brought major societal and economic losses in certain regions, yet climate change projections of such droughts in terms of duration is subject to large uncertainties. This study analyzes the biases of drought duration in state-of-the-art global climate model (GCM) simulations from the 5th phase of Coupled Model Intercomparison Project (CMIP5). Drought durations are defined as negative precipitation anomalies and evaluated with three observation-based datasets in the period of 1901-2010. Large spread in biases of GCMs is commonly found in all regions, with particular strong biases in North East Brazil, Africa, Northern Australia, Central America, Central and Northern Europe, Sahel and Asia. Also in most regions, the interquartile range of bias lies below 0, meaning that the GCMs tend to underestimate drought durations. Meanwhile in some regions such as Western South America, the Amazon, Sahel, West and South Africa, and Asia, considerable inconsistency among the three observation-based datasets were found. These results indicate substantial uncertainties and errors in current GCMs for simulating drought durations as well as a large spread in observation-based datasets, both of which are found to be particularly strong in those regions that are often considered to be hot spots of projected future drying. The underlying sources of these uncertainties need to be identified in further study and will be applied to constrain GCM-based drought projections under climate change.

  2. Dust Composition in Climate Models: Current Status and Prospects

    Science.gov (United States)

    Pérez García-Pando, C.; Miller, R. L.; Perlwitz, J. P.; Kok, J. F.; Scanza, R.; Mahowald, N. M.

    2015-12-01

    Mineral dust created by wind erosion of soil particles is the dominant aerosol by mass in the atmosphere. It exerts significant effects on radiative fluxes, clouds, ocean biogeochemistry, and human health. Models that predict the lifecycle of mineral dust aerosols generally assume a globally uniform mineral composition. However, this simplification limits our understanding of the role of dust in the Earth system, since the effects of dust strongly depend on the particles' physical and chemical properties, which vary with their mineral composition. Hence, not only a detailed understanding of the processes determining the dust emission flux is needed, but also information about its size dependent mineral composition. Determining the mineral composition of dust aerosols is complicated. The largest uncertainty derives from the current atlases of soil mineral composition. These atlases provide global estimates of soil mineral fractions, but they are based upon massive extrapolation of a limited number of soil samples assuming that mineral composition is related to soil type. This disregards the potentially large variability of soil properties within each defined soil type. In addition, the analysis of these soil samples is based on wet sieving, a technique that breaks the aggregates found in the undisturbed parent soil. During wind erosion, these aggregates are subject to partial fragmentation, which generates differences on the size distribution and composition between the undisturbed parent soil and the emitted dust aerosols. We review recent progress on the representation of the mineral and chemical composition of dust in climate models. We discuss extensions of brittle fragmentation theory to prescribe the emitted size-resolved dust composition, and we identify key processes and uncertainties based upon model simulations and an unprecedented compilation of observations.

  3. Sensitivity analysis of a forest gap model concerning current and future climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Lasch, P.; Suckow, F.; Buerger, G.; Lindner, M.

    1998-07-01

    The ability of a forest gap model to simulate the effects of climate variability and extreme events depends on the temporal resolution of the weather data that are used and the internal processing of these data for growth, regeneration and mortality. The climatological driving forces of most current gap models are based on monthly means of weather data and their standard deviations, and long-term monthly means are used for calculating yearly aggregated response functions for ecological processes. In this study, the results of sensitivity analyses using the forest gap model FORSKA{sub -}P and involving climate data of different resolutions, from long-term monthly means to daily time series, including extreme events, are presented for the current climate and for a climate change scenario. The model was applied at two sites with differing soil conditions in the federal state of Brandenburg, Germany. The sensitivity of the model concerning climate variations and different climate input resolutions is analysed and evaluated. The climate variability used for the model investigations affected the behaviour of the model substantially. (orig.)

  4. Comparing snow models under current and future climates: Uncertainties and implications for hydrological impact studies

    Science.gov (United States)

    Troin, Magali; Poulin, Annie; Baraer, Michel; Brissette, François

    2016-09-01

    Projected climate change effects on snow hydrology are investigated for the 2041-2060 horizon following the SRES A2 emissions scenario over three snowmelt-dominated catchments in Quebec, Canada. A 16-member ensemble of eight snow models (SM) simulations, based on the high-resolution Canadian Regional Climate Model (CRCM-15 km) simulations driven by two realizations of the Canadian Global Climate Model (CGCM3), is established per catchment. This study aims to compare a range of SMs in their ability at simulating snow processes under current climate, and to evaluate how they affect the assessment of the climate change-induced snow impacts at the catchment scale. The variability of snowpack response caused by the use of different models within two different SM approaches (degree-day (DD) versus mixed degree-day/energy balance (DD/EB)) is also evaluated, as well as the uncertainty of natural climate variability. The simulations cover 1961-1990 in the present period and 2041-2060 in the future period. There is a general convergence in the ensemble spread of the climate change signals on snow water equivalent at the catchment scale, with an earlier peak and a decreased magnitude in all basins. The results of four snow indicators show that most of the uncertainty arises from natural climate variability (inter-member variability of the CRCM) followed by the snow model. Both the DD and DD/EB models provide comparable assessments of the impacts of climate change on snow hydrology at the catchment scale.

  5. Using climate model simulations to assess the current climate risk to maize production

    Science.gov (United States)

    Kent, Chris; Pope, Edward; Thompson, Vikki; Lewis, Kirsty; Scaife, Adam A.; Dunstone, Nick

    2017-05-01

    The relationship between the climate and agricultural production is of considerable importance to global food security. However, there has been relatively little exploration of climate-variability related yield shocks. The short observational yield record does not adequately sample natural inter-annual variability thereby limiting the accuracy of probability assessments. Focusing on the United States and China, we present an innovative use of initialised ensemble climate simulations and a new agro-climatic indicator, to calculate the risk of severe water stress. Combined, these regions provide 60% of the world’s maize, and therefore, are crucial to global food security. To probe a greater range of inter-annual variability, the indicator is applied to 1400 simulations of the present day climate. The probability of severe water stress in the major maize producing regions is quantified, and in many regions an increased risk is found compared to calculations from observed historical data. Analysis suggests that the present day climate is also capable of producing unprecedented severe water stress conditions. Therefore, adaptation plans and policies based solely on observed events from the recent past may considerably under-estimate the true risk of climate-related maize shocks. The probability of a major impact event occurring simultaneously across both regions—a multi-breadbasket failure—is estimated to be up to 6% per decade and arises from a physically plausible climate state. This novel approach highlights the significance of climate impacts on crop production shocks and provides a platform for considerably improving food security assessments, in the present day or under a changing climate, as well as development of new risk based climate services.

  6. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions

    NARCIS (Netherlands)

    Li, T.; Hasegawa, T.; Yin, X.; Zhu, Y.; Boote, K.; Adam, M.; Bregaglio, S.; Buis, S.; Confalonieri, R.; Fumoto, T.; Gaydon, D.; Marcaida III, M.; Nakagawa, H.; Oriol, P.; Ruane, A.C.; Ruget, F.; Singh, B.; Singh, U.; Tang, L.; Yoshida, H.; Zhang, Z.; Bouman, B.

    2015-01-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluat

  7. Modeling Hawaiian ecosystem degradation due to invasive plants under current and future climates

    Science.gov (United States)

    Vorsino, Adam E.; Fortini, Lucas B.; Amidon, Fred A.; Miller, Stephen E.; Jacobi, James D.; Price, Jonathan P.; `Ohukani`ohi`a Gon, Sam; Koob, Gregory A.

    2014-01-01

    Occupation of native ecosystems by invasive plant species alters their structure and/or function. In Hawaii, a subset of introduced plants is regarded as extremely harmful due to competitive ability, ecosystem modification, and biogeochemical habitat degradation. By controlling this subset of highly invasive ecosystem modifiers, conservation managers could significantly reduce native ecosystem degradation. To assess the invasibility of vulnerable native ecosystems, we selected a proxy subset of these invasive plants and developed robust ensemble species distribution models to define their respective potential distributions. The combinations of all species models using both binary and continuous habitat suitability projections resulted in estimates of species richness and diversity that were subsequently used to define an invasibility metric. The invasibility metric was defined from species distribution models with 0.8; True Skill Statistic >0.75) as evaluated per species. Invasibility was further projected onto a 2100 Hawaii regional climate change scenario to assess the change in potential habitat degradation. The distribution defined by the invasibility metric delineates areas of known and potential invasibility under current climate conditions and, when projected into the future, estimates potential reductions in native ecosystem extent due to climate-driven invasive incursion. We have provided the code used to develop these metrics to facilitate their wider use (Code S1). This work will help determine the vulnerability of native-dominated ecosystems to the combined threats of climate change and invasive species, and thus help prioritize ecosystem and species management actions.

  8. Modeling Hawaiian ecosystem degradation due to invasive plants under current and future climates.

    Directory of Open Access Journals (Sweden)

    Adam E Vorsino

    Full Text Available Occupation of native ecosystems by invasive plant species alters their structure and/or function. In Hawaii, a subset of introduced plants is regarded as extremely harmful due to competitive ability, ecosystem modification, and biogeochemical habitat degradation. By controlling this subset of highly invasive ecosystem modifiers, conservation managers could significantly reduce native ecosystem degradation. To assess the invasibility of vulnerable native ecosystems, we selected a proxy subset of these invasive plants and developed robust ensemble species distribution models to define their respective potential distributions. The combinations of all species models using both binary and continuous habitat suitability projections resulted in estimates of species richness and diversity that were subsequently used to define an invasibility metric. The invasibility metric was defined from species distribution models with 0.8; True Skill Statistic >0.75 as evaluated per species. Invasibility was further projected onto a 2100 Hawaii regional climate change scenario to assess the change in potential habitat degradation. The distribution defined by the invasibility metric delineates areas of known and potential invasibility under current climate conditions and, when projected into the future, estimates potential reductions in native ecosystem extent due to climate-driven invasive incursion. We have provided the code used to develop these metrics to facilitate their wider use (Code S1. This work will help determine the vulnerability of native-dominated ecosystems to the combined threats of climate change and invasive species, and thus help prioritize ecosystem and species management actions.

  9. Current models broadly neglect specific needs of biodiversity conservation in protected areas under climate change

    Directory of Open Access Journals (Sweden)

    Moloney Kirk A

    2011-05-01

    Full Text Available Abstract Background Protected areas are the most common and important instrument for the conservation of biological diversity and are called for under the United Nations' Convention on Biological Diversity. Growing human population densities, intensified land-use, invasive species and increasing habitat fragmentation threaten ecosystems worldwide and protected areas are often the only refuge for endangered species. Climate change is posing an additional threat that may also impact ecosystems currently under protection. Therefore, it is of crucial importance to include the potential impact of climate change when designing future nature conservation strategies and implementing protected area management. This approach would go beyond reactive crisis management and, by necessity, would include anticipatory risk assessments. One avenue for doing so is being provided by simulation models that take advantage of the increase in computing capacity and performance that has occurred over the last two decades. Here we review the literature to determine the state-of-the-art in modeling terrestrial protected areas under climate change, with the aim of evaluating and detecting trends and gaps in the current approaches being employed, as well as to provide a useful overview and guidelines for future research. Results Most studies apply statistical, bioclimatic envelope models and focus primarily on plant species as compared to other taxa. Very few studies utilize a mechanistic, process-based approach and none examine biotic interactions like predation and competition. Important factors like land-use, habitat fragmentation, invasion and dispersal are rarely incorporated, restricting the informative value of the resulting predictions considerably. Conclusion The general impression that emerges is that biodiversity conservation in protected areas could benefit from the application of modern modeling approaches to a greater extent than is currently reflected in the

  10. Climate-driven range extension of Amphistegina (protista, foraminiferida: models of current and predicted future ranges.

    Directory of Open Access Journals (Sweden)

    Martin R Langer

    Full Text Available Species-range expansions are a predicted and realized consequence of global climate change. Climate warming and the poleward widening of the tropical belt have induced range shifts in a variety of marine and terrestrial species. Range expansions may have broad implications on native biota and ecosystem functioning as shifting species may perturb recipient communities. Larger symbiont-bearing foraminifera constitute ubiquitous and prominent components of shallow water ecosystems, and range shifts of these important protists are likely to trigger changes in ecosystem functioning. We have used historical and newly acquired occurrence records to compute current range shifts of Amphistegina spp., a larger symbiont-bearing foraminifera, along the eastern coastline of Africa and compare them to analogous range shifts currently observed in the Mediterranean Sea. The study provides new evidence that amphisteginid foraminifera are rapidly progressing southwestward, closely approaching Port Edward (South Africa at 31°S. To project future species distributions, we applied a species distribution model (SDM based on ecological niche constraints of current distribution ranges. Our model indicates that further warming is likely to cause a continued range extension, and predicts dispersal along nearly the entire southeastern coast of Africa. The average rates of amphisteginid range shift were computed between 8 and 2.7 km year(-1, and are projected to lead to a total southward range expansion of 267 km, or 2.4° latitude, in the year 2100. Our results corroborate findings from the fossil record that some larger symbiont-bearing foraminifera cope well with rising water temperatures and are beneficiaries of global climate change.

  11. Climate-driven range extension of Amphistegina (protista, foraminiferida): models of current and predicted future ranges.

    Science.gov (United States)

    Langer, Martin R; Weinmann, Anna E; Lötters, Stefan; Bernhard, Joan M; Rödder, Dennis

    2013-01-01

    Species-range expansions are a predicted and realized consequence of global climate change. Climate warming and the poleward widening of the tropical belt have induced range shifts in a variety of marine and terrestrial species. Range expansions may have broad implications on native biota and ecosystem functioning as shifting species may perturb recipient communities. Larger symbiont-bearing foraminifera constitute ubiquitous and prominent components of shallow water ecosystems, and range shifts of these important protists are likely to trigger changes in ecosystem functioning. We have used historical and newly acquired occurrence records to compute current range shifts of Amphistegina spp., a larger symbiont-bearing foraminifera, along the eastern coastline of Africa and compare them to analogous range shifts currently observed in the Mediterranean Sea. The study provides new evidence that amphisteginid foraminifera are rapidly progressing southwestward, closely approaching Port Edward (South Africa) at 31°S. To project future species distributions, we applied a species distribution model (SDM) based on ecological niche constraints of current distribution ranges. Our model indicates that further warming is likely to cause a continued range extension, and predicts dispersal along nearly the entire southeastern coast of Africa. The average rates of amphisteginid range shift were computed between 8 and 2.7 km year(-1), and are projected to lead to a total southward range expansion of 267 km, or 2.4° latitude, in the year 2100. Our results corroborate findings from the fossil record that some larger symbiont-bearing foraminifera cope well with rising water temperatures and are beneficiaries of global climate change.

  12. Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

    Science.gov (United States)

    West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.

    2016-01-01

    Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

  13. Climate Models

    Science.gov (United States)

    Druyan, Leonard M.

    2012-01-01

    Climate models is a very broad topic, so a single volume can only offer a small sampling of relevant research activities. This volume of 14 chapters includes descriptions of a variety of modeling studies for a variety of geographic regions by an international roster of authors. The climate research community generally uses the rubric climate models to refer to organized sets of computer instructions that produce simulations of climate evolution. The code is based on physical relationships that describe the shared variability of meteorological parameters such as temperature, humidity, precipitation rate, circulation, radiation fluxes, etc. Three-dimensional climate models are integrated over time in order to compute the temporal and spatial variations of these parameters. Model domains can be global or regional and the horizontal and vertical resolutions of the computational grid vary from model to model. Considering the entire climate system requires accounting for interactions between solar insolation, atmospheric, oceanic and continental processes, the latter including land hydrology and vegetation. Model simulations may concentrate on one or more of these components, but the most sophisticated models will estimate the mutual interactions of all of these environments. Advances in computer technology have prompted investments in more complex model configurations that consider more phenomena interactions than were possible with yesterday s computers. However, not every attempt to add to the computational layers is rewarded by better model performance. Extensive research is required to test and document any advantages gained by greater sophistication in model formulation. One purpose for publishing climate model research results is to present purported advances for evaluation by the scientific community.

  14. The Impact of Different Absolute Solar Irradiance Values on Current Climate Model Simulations

    Science.gov (United States)

    Rind, David H.; Lean, Judith L.; Jonas, Jeffrey

    2014-01-01

    Simulations of the preindustrial and doubled CO2 climates are made with the GISS Global Climate Middle Atmosphere Model 3 using two different estimates of the absolute solar irradiance value: a higher value measured by solar radiometers in the 1990s and a lower value measured recently by the Solar Radiation and Climate Experiment. Each of the model simulations is adjusted to achieve global energy balance; without this adjustment the difference in irradiance produces a global temperature change of 0.48C, comparable to the cooling estimated for the Maunder Minimum. The results indicate that by altering cloud cover the model properly compensates for the different absolute solar irradiance values on a global level when simulating both preindustrial and doubled CO2 climates. On a regional level, the preindustrial climate simulations and the patterns of change with doubled CO2 concentrations are again remarkably similar, but there are some differences. Using a higher absolute solar irradiance value and the requisite cloud cover affects the model's depictions of high-latitude surface air temperature, sea level pressure, and stratospheric ozone, as well as tropical precipitation. In the climate change experiments it leads to an underestimation of North Atlantic warming, reduced precipitation in the tropical western Pacific, and smaller total ozone growth at high northern latitudes. Although significant, these differences are typically modest compared with the magnitude of the regional changes expected for doubled greenhouse gas concentrations. Nevertheless, the model simulations demonstrate that achieving the highest possible fidelity when simulating regional climate change requires that climate models use as input the most accurate (lower) solar irradiance value.

  15. Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

    Science.gov (United States)

    Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Adam, Myriam; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fumoto, Tamon; Gaydon, Donald; Marcaida, Manuel, III; Nakagawa, Hiroshi; Oriol, Philippe; Ruane, Alex C.; Ruget, Francoise; Singh, Balwinder; Singh, Upendra; Tang, Liang; Tao, Fulu; Wilkens, Paul; Yoshida, Hiroe; Zhang, Zhao; Bouman, Bas

    2014-01-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.

  16. Modeling the prospects for climatic change: current state-of-the-art and implications

    Energy Technology Data Exchange (ETDEWEB)

    Kellogg, W. M.

    1980-04-04

    It has been increasingly suggested that the world's climate is going to change in the next several decades, primarily as a result of anthropogenic perturbations to the global carbon cycle brought about by fossil fuel burning and large-scale deforestation. In order to cope with these future climatic changes, it is necessary that tools be developed to predict how complex systems respond to a given change of conditions. This report summarizes the status of our ability to model the planetary system that determines the climate. (ACR)

  17. Past and Current Climate Change

    Science.gov (United States)

    Mercedes Rodríguez Ruibal, Ma

    2014-05-01

    In 1837 the Swiss geologist and palaeontologist Louis Agassiz was the first scientist to propose the existence of an ice age in the Earth's past. Nearly two centuries after discussing global glacial periods... while the average global temperature is rising very quickly because of our economic and industrial model. In tribute to these pioneers, we have selected a major climate change of the past as the Snowball Earth and, through various activities in the classroom, compared to the current anthropogenic climate change. First, we include multiple geological processes that led to a global glaciation 750 million years ago as the decrease in the atmospheric concentration of greenhouse gases such as CO2 and CH4, the effect of climate variations in solar radiation due to emissions of volcanic dust and orbital changes (Milankovitch cycles), being an essential part of this model the feedback mechanism of the albedo of the ice on a geological scale. Moreover, from simple experiments and studies in the classroom this time we can compare the past with the current anthropogenic global warming we are experiencing and some of its consequences, highlighting that affect sea level rise, increased extreme and effects on health and the biosphere weather.

  18. Continental-scale convection-permitting modeling of the current and future climate of North America

    Science.gov (United States)

    Liu, Changhai; Ikeda, Kyoko; Rasmussen, Roy; Barlage, Mike; Newman, Andrew J.; Prein, Andreas F.; Chen, Fei; Chen, Liang; Clark, Martyn; Dai, Aiguo; Dudhia, Jimy; Eidhammer, Trude; Gochis, David; Gutmann, Ethan; Kurkute, Sopan; Li, Yanping; Thompson, Gregory; Yates, David

    2016-08-01

    Orographic precipitation and snowpack provide a vital water resource for the western U.S., while convective precipitation accounts for a significant part of annual precipitation in the eastern U.S. As a result, water managers are keenly interested in their fate under climate change. However, previous studies of water cycle changes in the U.S. have been conducted with climate models of relatively coarse resolution, leading to potential misrepresentation of key physical processes. This paper presents results from a high-resolution climate change simulation that permits convection and resolves mesoscale orography at 4-km grid spacing over much of North America using the Weather Research and Forecasting (WRF) model. Two 13-year simulations were performed, consisting of a retrospective simulation (October 2000-September 2013) with initial and boundary conditions from ERA-interim and a future climate sensitivity simulation with modified reanalysis-derived initial and boundary conditions through adding the CMIP5 ensemble-mean high-end emission scenario climate change. The retrospective simulation is evaluated by validating against Snowpack Telemetry (SNOTEL) and an ensemble of gridded observational datasets. It shows overall good performance capturing the annual/seasonal/sub-seasonal precipitation and surface temperature climatology except for a summer dry and warm bias in the central U.S. In particular, the WRF seasonal precipitation agrees with SNOTEL observations within a few percent over the mountain ranges, providing confidence in the model's estimation of western U.S. seasonal snowfall and snowpack. The future climate simulation forced with warmer and moister perturbed boundary conditions enhances annual and winter-spring-fall seasonal precipitation over most of the contiguous United States (CONUS), but suppresses summertime precipitation in the central U.S. The WRF-downscaled climate change simulations provide a high-resolution dataset (i.e., High-Resolution CONUS

  19. Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.

    Science.gov (United States)

    Mathewson, Paul D; Moyer-Horner, Lucas; Beever, Erik A; Briscoe, Natalie J; Kearney, Michael; Yahn, Jeremiah M; Porter, Warren P

    2017-03-01

    How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

  20. Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates

    Science.gov (United States)

    Mathewson, Paul; Moyer-Horner, Lucas; Beever, Erik; Briscoe, Natalie; Kearney, Michael T; Yahn, Jeremiah; Porter, Warren P.

    2017-01-01

    How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

  1. Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

    Science.gov (United States)

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

    2009-04-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

  2. Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments

    Science.gov (United States)

    Prestele, Reinhard; Arneth, Almut; Bondeau, Alberte; de Noblet-Ducoudré, Nathalie; Pugh, Thomas A. M.; Sitch, Stephen; Stehfest, Elke; Verburg, Peter H.

    2017-05-01

    Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs). The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC). Fully coupled models of climate, land use and biogeochemical cycles to explore land use-climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs) to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use-climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes (gross changes) across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest concentrating on the

  3. Changes in the Tsushima Warm Current and the Impact under a Global Warming Scenario in Coupled Climate Models

    Directory of Open Access Journals (Sweden)

    A-Ra Choi

    2013-06-01

    Full Text Available In this study we investigated changes in the Tsushima Warm Current (TWC under the global warming scenario RCP 4.5 by analysing the results from the World Climate Research Program’s (WCRP Coupled Model Intercomparison Project Phase 5 (CMIP5. Among the four models that had been employed to analyse the Tsushima Warm Current during the 20th Century, in the CSIRO-Mk3.6.0 and HadGEM2-CC models the transports of the Tsushima Warm Current were 2.8 Sv and 2.1 Sv, respectively, and comparable to observed transport, which is between 2.4 and 2.77 Sv. In the other two models the transports were much greater or smaller than the observed estimates. Using the two models that properly reproduced the transport of the Tsushima Warm Current we investigated the response of the current under the global warming scenario. In both models the volume transports and the temperature were greater in the future climate scenario. Warm advection into the East Sea was intensified to raise the temperature and consequently the heat loss to the air.

  4. Interannual Variability of Tropical Precipitation: How Well Do Climate Models Agree With Current Satellite Estimates?

    Science.gov (United States)

    Robertson, Franklin R.; Marshall, Susan; Roads, John; Oglesby, Robert J.; Fitzjarrald, Dan; Goodman, H. Michael (Technical Monitor)

    2001-01-01

    Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. Recent availability of the TRMM (Tropical Rainfall Measuring Mission) has further aided in narrowing uncertainties in rainfall over die tropics and subtropics. Although climate modeling efforts have long relied on space-based precipitation estimates for validation, we now are in a position to make more quantitative assessments of model performance, particularly in tropical regions. An integration of the CCM3 using observed SSTs as a lower boundary condition is used to examine how well this model responds to ENSO forcing in terms of anomalous precipitation. An integration of the NCEP spectral model used for the Reanalysis-H effort is also examined. This integration is run with specified SSTs, but with no data assimilation. Our analysis focuses on two aspects of inter-annual variability. First are the spatial anomalies that are indicative of dislocations in Hadley and Walker circulations. Second, we consider the ability of models to replicate observed increases in oceanic precipitation that are noted in satellite observations for large ENSO events. Finally, we consider a slab ocean version of the CCM3 model with prescribed ocean beat transports that mimic upwelling anomalies, but which still allows the surface energy balance to be predicted. This less restrictive experiment is used to understand why model experiments with specified SSTs seem to have noticeably less interannual variability in precipitation than do the satellite observations.

  5. Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments

    Directory of Open Access Journals (Sweden)

    R. Prestele

    2017-05-01

    Full Text Available Land-use and land-cover change (LULCC represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs. The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC. Fully coupled models of climate, land use and biogeochemical cycles to explore land use–climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use–climate interaction studies: (I provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II accounting for sub-grid processes and bidirectional changes (gross changes across spatial scales, and (III the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest

  6. CMIP5 model simulations of Ethiopian Kiremt-season precipitation: current climate and future changes

    Science.gov (United States)

    Li, Laifang; Li, Wenhong; Ballard, Tristan; Sun, Ge; Jeuland, Marc

    2016-05-01

    Kiremt-season (June-September) precipitation provides a significant water supply for Ethiopia, particularly in the central and northern regions. The response of Kiremt-season precipitation to climate change is thus of great concern to water resource managers. However, the complex processes that control Kiremt-season precipitation challenge the capability of general circulation models (GCMs) to accurately simulate precipitation amount and variability. This in turn raises questions about their utility for predicting future changes. This study assesses the impact of climate change on Kiremt-season precipitation using state-of-the-art GCMs participating in the Coupled Model Intercomparison Project Phase 5. Compared to models with a coarse resolution, high-resolution models (horizontal resolution RCP) 4.5 scenario, these high-resolution models project an increase in precipitation over central Highlands and northern Great Rift Valley in Ethiopia, but a decrease in precipitation over the southern part of the country. Such a dipole pattern is attributable to the intensification of the North Atlantic subtropical high (NASH) in a warmer climate, which influences Ethiopian Kiremt-season precipitation mainly by modulating atmospheric vertical motion. Diagnosis of the omega equation demonstrates that an intensified NASH increases (decreases) the advection of warm air and positive vorticity into the central Highlands and northern Great Rift Valley (southern part of the country), enhancing upward motion over the northern Rift Valley but decreasing elsewhere. Under the RCP 4.5 scenario, the high-resolution models project an intensification of the NASH by 15 (3 × 105 m2 s-2) geopotential meters (stream function) at the 850-hPa level, contributing to the projected precipitation change over Ethiopia. The influence of the NASH on Kiremt-season precipitation becomes more evident in the future due to the offsetting effects of two other major circulation systems: the East African Low

  7. Regional climate modeling of heat stress, frost, and water stress events in the agricultural region of Southwest Western Australia under the current climate and future climate scenarios.

    Science.gov (United States)

    Kala, Jatin; Lyons, Tom J.; Abbs, Deborah J.; Foster, Ian J.

    2010-05-01

    Heat stress, frost, and water stress events have significant impacts on grain quality and production within the agricultural region (wheat-belt) of Southwest Western Australia (SWWA) (Cramb, 2000) and understanding how the frequency and intensity of these events will change in the future is crucial for management purposes. Hence, the Regional Atmospheric Modeling System (Pielke et al, 1992) (RAMS Version 6.0) is used to simulate the past 10 years of the climate of SWWA at a 20 km grid resolution by down-scaling the 6-hourly 1.0 by 1.0 degree National Center for Environmental Prediction Final Analyses from December 1999 to Present. Daily minimum and maximum temperatures, as well as daily rainfall are validated against observations. Simulations of future climate are carried out by down-scaling the Commonwealth Scientific and Industrial Research Organization (CSIRO) Mark 3.5 General Circulation Model (Gordon et al, 2002) for 10 years (2046-2055) under the SRES A2 scenario using the Cubic Conformal Atmospheric Model (CCAM) (McGregor and Dix, 2008). The 6-hourly CCAM output is then downscaled to a 20 km resolution using RAMS. Changes in extreme events are discussed within the context of the continued viability of agriculture in SWWA. Cramb, J. (2000) Climate in relation to agriculture in south-western Australia. In: The Wheat Book (Eds W. K. Anderson and J. R. Garlinge). Bulletin 4443. Department of Agriculture, Western Australia. Gordon, H. B., Rotstayn, L. D., McGregor, J. L., Dix, M. R., Kowalczyk, E. A., O'Farrell, S. P., Waterman, L. J., Hirst, A. C., Wilson, S. G., Collier, M. A., Watterson, I. G., and Elliott, T. I. (2002). The CSIRO Mk3 Climate System Model [Electronic publication]. Aspendale: CSIRO Atmospheric Research. (CSIRO Atmospheric Research technical paper; no. 60). 130 p McGregor, J. L., and Dix, M. R., (2008) An updated description of the conformal-cubic atmospheric model. High Resolution Simulation of the Atmosphere and Ocean, Hamilton, K. and Ohfuchi

  8. Modeling Nitrogen Losses in Conventional and Advanced Soil-Based Onsite Wastewater Treatment Systems under Current and Changing Climate Conditions.

    Directory of Open Access Journals (Sweden)

    Ivan Morales

    Full Text Available Most of the non-point source nitrogen (N load in rural areas is attributed to onsite wastewater treatment systems (OWTS. Nitrogen compounds cause eutrophication, depleting the oxygen in marine ecosystems. OWTS rely on physical, chemical and biological soil processes to treat wastewater and these processes may be affected by climate change. We simulated the fate and transport of N in different types of OWTS drainfields, or soil treatment areas (STA under current and changing climate scenarios, using 2D/3D HYDRUS software. Experimental data from a mesocosm-scale study, including soil moisture content, and total N, ammonium (NH4+ and nitrate (NO3- concentrations, were used to calibrate the model. A water content-dependent function was used to compute the nitrification and denitrification rates. Three types of drainfields were simulated: (1 a pipe-and-stone (P&S, (2 advanced soil drainfields, pressurized shallow narrow drainfield (PSND and (3 Geomat (GEO, a variation of SND. The model was calibrated with acceptable goodness-of-fit between the observed and measured values. Average root mean square error (RSME ranged from 0.18 and 2.88 mg L-1 for NH4+ and 4.45 mg L-1 to 9.65 mg L-1 for NO3- in all drainfield types. The calibrated model was used to estimate N fluxes for both conventional and advanced STAs under current and changing climate conditions, i.e. increased soil temperature and higher water table. The model computed N losses from nitrification and denitrification differed little from measured losses in all STAs. The modeled N losses occurred mostly as NO3- in water outputs, accounting for more than 82% of N inputs in all drainfields. Losses as N2 were estimated to be 10.4% and 9.7% of total N input concentration for SND and Geo, respectively. The highest N2 losses, 17.6%, were estimated for P&S. Losses as N2 increased to 22%, 37% and 21% under changing climate conditions for Geo, PSND and P&S, respectively. These findings can provide

  9. Modeling Nitrogen Losses in Conventional and Advanced Soil-Based Onsite Wastewater Treatment Systems under Current and Changing Climate Conditions.

    Science.gov (United States)

    Morales, Ivan; Cooper, Jennifer; Amador, José A; Boving, Thomas B

    2016-01-01

    Most of the non-point source nitrogen (N) load in rural areas is attributed to onsite wastewater treatment systems (OWTS). Nitrogen compounds cause eutrophication, depleting the oxygen in marine ecosystems. OWTS rely on physical, chemical and biological soil processes to treat wastewater and these processes may be affected by climate change. We simulated the fate and transport of N in different types of OWTS drainfields, or soil treatment areas (STA) under current and changing climate scenarios, using 2D/3D HYDRUS software. Experimental data from a mesocosm-scale study, including soil moisture content, and total N, ammonium (NH4+) and nitrate (NO3-) concentrations, were used to calibrate the model. A water content-dependent function was used to compute the nitrification and denitrification rates. Three types of drainfields were simulated: (1) a pipe-and-stone (P&S), (2) advanced soil drainfields, pressurized shallow narrow drainfield (PSND) and (3) Geomat (GEO), a variation of SND. The model was calibrated with acceptable goodness-of-fit between the observed and measured values. Average root mean square error (RSME) ranged from 0.18 and 2.88 mg L-1 for NH4+ and 4.45 mg L-1 to 9.65 mg L-1 for NO3- in all drainfield types. The calibrated model was used to estimate N fluxes for both conventional and advanced STAs under current and changing climate conditions, i.e. increased soil temperature and higher water table. The model computed N losses from nitrification and denitrification differed little from measured losses in all STAs. The modeled N losses occurred mostly as NO3- in water outputs, accounting for more than 82% of N inputs in all drainfields. Losses as N2 were estimated to be 10.4% and 9.7% of total N input concentration for SND and Geo, respectively. The highest N2 losses, 17.6%, were estimated for P&S. Losses as N2 increased to 22%, 37% and 21% under changing climate conditions for Geo, PSND and P&S, respectively. These findings can provide practitioners

  10. TRACKING CLIMATE MODELS

    Data.gov (United States)

    National Aeronautics and Space Administration — CLAIRE MONTELEONI*, GAVIN SCHMIDT, AND SHAILESH SAROHA* Climate models are complex mathematical models designed by meteorologists, geophysicists, and climate...

  11. Abrupt change in climate and climate models

    Directory of Open Access Journals (Sweden)

    A. J. Pitman

    2006-01-01

    Full Text Available First, we review the evidence that abrupt climate changes have occurred in the past and then demonstrate that climate models have developing capacity to simulate many of these changes. In particular, the processes by which changes in the ocean circulation drive abrupt changes appear to be captured by climate models to a degree that is encouraging. The evidence that past changes in the ocean have driven abrupt change in terrestrial systems is also convincing, but these processes are only just beginning to be included in climate models. Second, we explore the likelihood that climate models can capture those abrupt changes in climate that may occur in the future due to the enhanced greenhouse effect. We note that existing evidence indicates that a major collapse of the thermohaline circulation seems unlikely in the 21st century, although very recent evidence suggests that a weakening may already be underway. We have confidence that current climate models can capture a weakening, but a collapse in the 21st century of the thermohaline circulation is not projected by climate models. Worrying evidence of instability in terrestrial carbon, from observations and modelling studies, is beginning to accumulate. Current climate models used by the Intergovernmental Panel on Climate Change for the 4th Assessment Report do not include these terrestrial carbon processes. We therefore can not make statements with any confidence regarding these changes. At present, the scale of the terrestrial carbon feedback is believed to be small enough that it does not significantly affect projections of warming during the first half of the 21st century. However, the uncertainties in how biological systems will respond to warming are sufficiently large to undermine confidence in this belief and point us to areas requiring significant additional work.

  12. Abrupt change in climate and climate models

    Directory of Open Access Journals (Sweden)

    A. J. Pitman

    2006-07-01

    Full Text Available First, we review the evidence that abrupt climate changes have occurred in the past and then demonstrate that climate models have developing capacity to simulate many of these changes. In particular, the processes by which changes in the ocean circulation drive abrupt changes appear to be captured by climate models to a degree that is encouraging. The evidence that past changes in the ocean have driven abrupt change in terrestrial systems is also convincing, but these processes are only just beginning to be included in climate models. Second, we explore the likelihood that climate models can capture those abrupt changes in climate that may occur in the future due to the enhanced greenhouse effect. We note that existing evidence indicates that a major collapse of the thermohaline circulate seems unlikely in the 21st century, although very recent evidence suggests that a weakening may already be underway. We have confidence that current climate models can capture a weakening, but a collapse of the thermohaline circulation in the 21st century is not projected by climate models. Worrying evidence of instability in terrestrial carbon, from observations and modelling studies, is beginning to accumulate. Current climate models used by the Intergovernmental Panel on Climate Change for the 4th Assessment Report do not include these terrestrial carbon processes. We therefore can not make statements with any confidence regarding these changes. At present, the scale of the terrestrial carbon feedback is believed to be small enough that it does not significantly affect projections of warming during the first half of the 21st century. However, the uncertainties in how biological systems will respond to warming are sufficiently large to undermine confidence in this belief and point us to areas requiring significant additional work.

  13. A Bayesian Hierarchical Modeling Scheme for Estimating Erosion Rates Under Current Climate Conditions

    Science.gov (United States)

    Lowman, L.; Barros, A. P.

    2014-12-01

    Computational modeling of surface erosion processes is inherently difficult because of the four-dimensional nature of the problem and the multiple temporal and spatial scales that govern individual mechanisms. Landscapes are modified via surface and fluvial erosion and exhumation, each of which takes place over a range of time scales. Traditional field measurements of erosion/exhumation rates are scale dependent, often valid for a single point-wise location or averaging over large aerial extents and periods with intense and mild erosion. We present a method of remotely estimating erosion rates using a Bayesian hierarchical model based upon the stream power erosion law (SPEL). A Bayesian approach allows for estimating erosion rates using the deterministic relationship given by the SPEL and data on channel slopes and precipitation at the basin and sub-basin scale. The spatial scale associated with this framework is the elevation class, where each class is characterized by distinct morphologic behavior observed through different modes in the distribution of basin outlet elevations. Interestingly, the distributions of first-order outlets are similar in shape and extent to the distribution of precipitation events (i.e. individual storms) over a 14-year period between 1998-2011. We demonstrate an application of the Bayesian hierarchical modeling framework for five basins and one intermontane basin located in the central Andes between 5S and 20S. Using remotely sensed data of current annual precipitation rates from the Tropical Rainfall Measuring Mission (TRMM) and topography from a high resolution (3 arc-seconds) digital elevation map (DEM), our erosion rate estimates are consistent with decadal-scale estimates based on landslide mapping and sediment flux observations and 1-2 orders of magnitude larger than most millennial and million year timescale estimates from thermochronology and cosmogenic nuclides.

  14. Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change

    Directory of Open Access Journals (Sweden)

    Tucker James R

    2009-06-01

    Full Text Available Abstract Background Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance. Results Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948 and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras. Conclusion Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources

  15. Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change.

    Science.gov (United States)

    Holt, Ashley C; Salkeld, Daniel J; Fritz, Curtis L; Tucker, James R; Gong, Peng

    2009-06-28

    Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance. Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948) and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras. Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources. In addition, Maxent model results were significantly

  16. Climate models and scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Fortelius, C.; Holopainen, E.; Kaurola, J.; Ruosteenoja, K.; Raeisaenen, J. [Helsinki Univ. (Finland). Dept. of Meteorology

    1996-12-31

    In recent years the modelling of interannual climate variability has been studied, the atmospheric energy and water cycles, and climate simulations with the ECHAM3 model. In addition, the climate simulations of several models have been compared with special emphasis in the area of northern Europe

  17. High-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale projections

    Science.gov (United States)

    Jacquemin, Ingrid; Henrot, Alexandra-Jane; Beckers, Veronique; Berckmans, Julie; Debusscher, Bos; Dury, Marie; Minet, Julien; Hamdi, Rafiq; Dendoncker, Nicolas; Tychon, Bernard; Hambuckers, Alain; François, Louis

    2016-04-01

    The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs

  18. Regionalizing global climate models

    NARCIS (Netherlands)

    Pitman, A.J.; Arneth, A.; Ganzeveld, L.N.

    2012-01-01

    Global climate models simulate the Earth's climate impressively at scales of continents and greater. At these scales, large-scale dynamics and physics largely define the climate. At spatial scales relevant to policy makers, and to impacts and adaptation, many other processes may affect regional and

  19. Regionalizing global climate models

    NARCIS (Netherlands)

    Pitman, A.J.; Arneth, A.; Ganzeveld, L.N.

    2012-01-01

    Global climate models simulate the Earth's climate impressively at scales of continents and greater. At these scales, large-scale dynamics and physics largely define the climate. At spatial scales relevant to policy makers, and to impacts and adaptation, many other processes may affect regional and

  20. Comparing modeled and observed changes in mineral dust transport and deposition to Antarctica between the Last Glacial Maximum and current climates

    Energy Technology Data Exchange (ETDEWEB)

    Albani, Samuel [University of Siena, Graduate School in Polar Sciences, Siena (Italy); University of Milano-Bicocca, Department of Environmental Sciences, Milano (Italy); Cornell University, Department of Earth and Atmospheric Sciences, Ithaca, NY (United States); Mahowald, Natalie M. [Cornell University, Department of Earth and Atmospheric Sciences, Ithaca, NY (United States); Delmonte, Barbara; Maggi, Valter [University of Milano-Bicocca, Department of Environmental Sciences, Milano (Italy); Winckler, Gisela [Columbia University, Lamont-Doherty Earth Observatory, Palisades, NY (United States); Columbia University, Department of Earth and Environmental Sciences, New York, NY (United States)

    2012-05-15

    Mineral dust aerosols represent an active component of the Earth's climate system, by interacting with radiation directly, and by modifying clouds and biogeochemistry. Mineral dust from polar ice cores over the last million years can be used as paleoclimate proxy, and provide unique information about climate variability, as changes in dust deposition at the core sites can be due to changes in sources, transport and/or deposition locally. Here we present results from a study based on climate model simulations using the Community Climate System Model. The focus of this work is to analyze simulated differences in the dust concentration, size distribution and sources in current climate conditions and during the Last Glacial Maximum at specific ice core locations in Antarctica, and compare with available paleodata. Model results suggest that South America is the most important source for dust deposited in Antarctica in current climate, but Australia is also a major contributor and there is spatial variability in the relative importance of the major dust sources. During the Last Glacial Maximum the dominant source in the model was South America, because of the increased activity of glaciogenic dust sources in Southern Patagonia-Tierra del Fuego and the Southernmost Pampas regions, as well as an increase in transport efficiency southward. Dust emitted from the Southern Hemisphere dust source areas usually follow zonal patterns, but southward flow towards Antarctica is located in specific areas characterized by southward displacement of air masses. Observations and model results consistently suggest a spatially variable shift in dust particle sizes. This is due to a combination of relatively reduced en route wet removal favouring a generalized shift towards smaller particles, and on the other hand to an enhanced relative contribution of dry coarse particle deposition in the Last Glacial Maximum. (orig.)

  1. Mitigation potential of horizontal ground coupled heat pumps for current and future climatic conditions: UK environmental modelling and monitoring studies

    Science.gov (United States)

    García González, Raquel; Verhoef, Anne; Vidale, Pier Luigi; Gan, Guohui; Wu, Yupeng; Hughes, Andrew; Mansour, Majdi; Blyth, Eleanor; Finch, Jon; Main, Bruce

    2010-05-01

    model predictions of soil moisture content and soil temperature with measurements at different GCHP locations over the UK. The combined effect of environment dynamics and horizontal GCHP technical properties on long-term GCHP performance will be assessed using a detailed land surface model (JULES: Joint UK Land Environment Simulator, Meteorological Office, UK) with additional equations embedded describing the interaction between GCHP heat exchangers and the surrounding soil. However, a number of key soil physical processes are currently not incorporated in JULES, such as groundwater flow, which, especially in lowland areas, can have an important effect on the heat flow between soil and HE. Furthermore, the interaction between HE and soil may also cause soil vapour and moisture fluxes. These will affect soil thermal conductivity and hence heat flow between the HE and the surrounding soil, which will in turn influence system performance. The project will address these issues. We propose to drive an improved version of JULES (with equations to simulate GCHP exchange embedded), with long-term gridded (1 km) atmospheric, soil and vegetation data (reflecting current and future environmental conditions) to reliably assess the mitigation potential of GCHPs over the entire domain of the UK, where uptake of GCHPs has been low traditionally. In this way we can identify areas that are most suitable for the installation of GCHPs. Only then recommendations can be made to local and regional governments, for example, on how to improve the mitigation potential in less suitable areas by adjusting GCHP configurations or design.

  2. Selecting global climate models for regional climate change studies

    OpenAIRE

    Pierce, David W.; Barnett, Tim P.; Santer, Benjamin D.; Gleckler, Peter J.

    2009-01-01

    Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simula...

  3. Modelling Interglacial Climate

    DEFF Research Database (Denmark)

    Pedersen, Rasmus Anker

    , with maximum warming occurring in winter. The three scenarios all affect the climate beyond the Arctic, especially the mid-latitude circulation which is sensitive to the location of the ice loss. Together, the results presented in this thesis illustrate that the changes in the Arctic sea ice cover......, while the insolation appears to be the dominant cause of the expected ice sheet reduction. The second part explores the atmospheric sensitivity to the location of sea ice loss. Three investigated sea ice scenarios with ice loss in different regions all exhibit substantial near-surface warming...... involves some of the same mechanisms in the two climate states. This thesis aims to investigate these mechanisms through climate model experiments. This two-part study has a special focus on the Arctic region, and the main paleoclimate experiments are supplemented by idealized experiments detailing...

  4. Current and future carbon budget at Takayama site, Japan, evaluated by a regional climate model and a process-based terrestrial ecosystem model

    Science.gov (United States)

    Kuribayashi, Masatoshi; Noh, Nam-Jin; Saitoh, Taku M.; Ito, Akihiko; Wakazuki, Yasutaka; Muraoka, Hiroyuki

    2016-12-01

    Accurate projection of carbon budget in forest ecosystems under future climate and atmospheric carbon dioxide (CO2) concentration is important to evaluate the function of terrestrial ecosystems, which serve as a major sink of atmospheric CO2. In this study, we examined the effects of spatial resolution of meteorological data on the accuracies of ecosystem model simulation for canopy phenology and carbon budget such as gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) of a deciduous forest in Japan. Then, we simulated the future (around 2085) changes in canopy phenology and carbon budget of the forest by incorporating high-resolution meteorological data downscaled by a regional climate model. The ecosystem model overestimated GPP and ER when we inputted low-resolution data, which have warming biases over mountainous landscape. But, it reproduced canopy phenology and carbon budget well, when we inputted high-resolution data. Under the future climate, earlier leaf expansion and delayed leaf fall by about 10 days compared with the present state was simulated, and also, GPP, ER and NEP were estimated to increase by 25.2%, 23.7% and 35.4%, respectively. Sensitivity analysis showed that the increase of NEP in June and October would be mainly caused by rising temperature, whereas that in July and August would be largely attributable to CO2 fertilization. This study suggests that the downscaling of future climate data enable us to project more reliable carbon budget of forest ecosystem in mountainous landscape than the low-resolution simulation due to the better predictions of leaf expansion and shedding.

  5. CMIP5 model-simulated onset, duration and intensity of the Asian summer monsoon in current and future climate

    Science.gov (United States)

    Dong, Guangtao; Zhang, H.; Moise, A.; Hanson, L.; Liang, P.; Ye, H.

    2016-01-01

    A number of significant weaknesses existed in our previous analysis of the changes in the Asian monsoon onset/retreat from coupled model intercomparison project phase 3 (CMIP3) models, including a lack of statistical significance tests, a small number of models analysed, and limited understanding of the causes of model uncertainties. Yet, the latest IPCC report acknowledges limited confidence for projected changes in monsoon onset/retreat. In this study we revisit the topic by expanding the analysis to a large number of CMIP5 models over much longer period and with more diagnoses. Daily 850 hPa wind, volumetric atmospheric precipitable water and rainfall data from 26 CMIP5 models over two sets of 50-year periods are used in this study. The overall model skill in reproducing the temporal and spatial patterns of the monsoon development is similar between CMIP3 and CMIP5 models. They are able to show distinct regional characteristics in the evolutions of Indian summer monsoon (ISM), East Asian summer monsoon (EASM) and West North Pacific summer monsoon (WNPSM). Nevertheless, the averaged onset dates vary significantly among the models. Large uncertainty exists in model-simulated changes in onset/retreat dates and the extent of uncertainty is comparable to that in CMIP3 models. Under global warming, a majority of the models tend to suggest delayed onset for the south Asian monsoon in the eastern part of tropical Indian Ocean and Indochina Peninsula and nearby region, primarily due to weakened tropical circulations and eastward shift of the Walker circulation. The earlier onset over the Arabian Sea and part of the Indian subcontinent in a number of the models are related to an enhanced southwesterly flow in the region. Weak changes in other domains are due to the offsetting results among the models, with some models showing earlier onsets but others showing delayed onsets. Different from the analysis of CMIP3 model results, this analysis highlights the importance of SST

  6. Hierarchical Climate Modeling for Cosmoclimatology

    Science.gov (United States)

    Ohfuchi, Wataru

    2010-05-01

    It has been reported that there are correlations among solar activity, amount of galactic cosmic ray, amount of low clouds and surface air temperature (Svensmark and Friis-Chistensen, 1997). These correlations seem to exist for current climate change, Little Ice Age, and geological time scale climate changes. Some hypothetic mechanisms have been argued for the correlations but it still needs quantitative studies to understand the mechanism. In order to decrease uncertainties, only first principles or laws very close to first principles should be used. Our group at Japan Agency for Marine-Earth Science and Technology has started modeling effort to tackle this problem. We are constructing models from galactic cosmic ray inducing ionization, to aerosol formation, to cloud formation, to global climate. In this talk, we introduce our modeling activities. For aerosol formation, we use molecular dynamics. For cloud formation, we use a new cloud microphysics model called "super droplet method". We also try to couple a nonhydrostatic atmospheric regional cloud resolving model and a hydrostatic atmospheric general circulation model.

  7. Comments on Current Space Systems Observing the Climate

    Science.gov (United States)

    Fisk, L. A.

    2016-07-01

    The Global Climate Observing System (GCOS), which was established in 1992, has been effective in specifying the observations needed for climate studies, and advocating that these observations be made. As a result, there are essential climate variables being observed, particularly from space, and these have formed the basis for our ever-improving models of how the Earth system functions and the human impact on it. We cannot conclude, however, that the current observing system in space is adequate. Climate change is accelerating, and we need to ensure that our observations capture, with completeness and with proper resolution and cadence, the most important changes. Perhaps of most significance, we need to use observations from space to guide the mitigation and adaptation strategies on which at last our civilization seems prepared to embark. And we need to use our observations to educate particularly policy makers on the reality of climate change, so that none deny the need to act. COSPAR is determined to play its part in highlighting the need to strengthen the climate observing system and notably its research component. This is being accomplished through events like the present roundtable, through the work of its Scientific Commission A, its Task Group on GEO (where COSPAR is serving as a member of its Program Board), and by promoting among space agencies and policy-makers the recently released scientific roadmap on Integrated Earth System Science for the period 2016-2025.

  8. Climate-induced boreal forest change: Predictions versus current observations

    Science.gov (United States)

    Soja, Amber J.; Tchebakova, Nadezda M.; French, Nancy H. F.; Flannigan, Michael D.; Shugart, Herman H.; Stocks, Brian J.; Sukhinin, Anatoly I.; Parfenova, E. I.; Chapin, F. Stuart; Stackhouse, Paul W.

    2007-04-01

    For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, 7 of the last 9 yr have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change.

  9. Climate-Induced Boreal Forest Change: Predictions versus Current Observations

    Science.gov (United States)

    Soja, Amber J.; Tchebakova, Nadezda M.; French, Nancy H. F.; Flannigan, Michael D.; Shugart, Herman H.; Stocks, Brian J.; Sukhinin, Anatoly I.; Parfenova, E. I.; Chapin, F. Stuart, III; Stackhouse, Paul W., Jr.

    2007-01-01

    For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change.

  10. Regional Wave Climates along Eastern Boundary Currents

    Science.gov (United States)

    Semedo, Alvaro; Soares, Pedro

    2016-04-01

    Two types of wind-generated gravity waves coexist at the ocean surface: wind sea and swell. Wind sea waves are waves under growing process. These young growing waves receive energy from the overlaying wind and are strongly coupled to the local wind field. Waves that propagate away from their generation area and no longer receive energy input from the local wind are called swell. Swell waves can travel long distances across entire ocean basins. A qualitative study of the ocean waves from a locally vs. remotely generation perspective is important, since the air sea interaction processes is strongly modulated by waves and vary accordingly to the prevalence of wind sea or swell waves in the area. A detailed climatology of wind sea and swell waves along eastern boundary currents (EBC; California Current, Canary Current, in the Northern Hemisphere, and Humboldt Current, Benguela Current, and Western Australia Current, in the Southern Hemisphere), based on the ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim reanalysis will be presented. The wind regime along EBC varies significantly from winter to summer. The high summer wind speeds along EBC generate higher locally generated wind sea waves, whereas lower winter wind speeds in these areas, along with stronger winter extratropical storms far away, lead to a predominance of swell waves there. In summer, the coast parallel winds also interact with coastal headlands, increasing the wind speed through a process called "expansion fan", which leads to an increase in the height of locally generated waves downwind of capes and points. Hence the spatial patterns of the wind sea or swell regional wave fields are shown to be different from the open ocean along EBC, due to coastal geometry and fetch dimensions. Swell waves will be shown to be considerably more prevalent and to carry more energy in winter along EBC, while in summer locally generated wind sea waves are either more comparable to swell waves or

  11. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

    2015-12-01

    Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the

  12. Selecting global climate models for regional climate change studies.

    Science.gov (United States)

    Pierce, David W; Barnett, Tim P; Santer, Benjamin D; Gleckler, Peter J

    2009-05-26

    Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures.

  13. Selecting global climate models for regional climate change studies

    Science.gov (United States)

    Pierce, David W.; Barnett, Tim P.; Santer, Benjamin D.; Gleckler, Peter J.

    2009-01-01

    Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures. PMID:19439652

  14. Stochastic Climate Theory and Modelling

    CERN Document Server

    Franzke, Christian L E; Berner, Judith; Williams, Paul D; Lucarini, Valerio

    2014-01-01

    Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations as well as for model error representation, uncertainty quantification, data assimilation and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochast...

  15. Assessing the ability of current climate information to facilitate local climate services for the water sector.

    Science.gov (United States)

    Koutroulis, Aristeidis; Tsanis, Ioannis; Grillakis, Manolis; Jacob, Daniela

    2014-05-01

    In the frame of ECLISE EU FP6 project researchers, in close cooperation with local users of the water sector from the area of Crete, Greece, explored the ability of current climate information to develop and support local climate services water resources management and climate adaption policies. A wealth of climate modeling output ranging from event scale to decadal and centennial experiments, at temporal scales ranging from hourly to monthly, and at spatial scales from very high resolution regional climate models (2 km) to typical GCMs, were used in order to practically assess climate change impacts on water resources. Water resources availability issues analysed and facilitated within the project, focusing on estimates of the future water demands of the island, and comparing with seven "state of the art" CMIP5 simulations within COMBINE framework (under RCPs 2.6, 4.5 and 8.5) to estimate water resources availability, during 21st century. The ability of decadal GCM prediction experiments to reproduce basic hydrometeorological variables like precipitation and temperature for local impact studies, was also examined. Water availability for the whole island at basin scale until 2100 is estimated using the SAC-SMA rainfall-runoff model for a range of different scenarios of projected hydro-climatological regime, demand and supply potential. A robust signal of temperature increase and precipitation decrease is projected for all the pathways. Several messages could be extracted from this provider - user interaction such as the communication of basic concepts and uncertainties, user skepticism and feedback. The main user concern was the coarse spatial scale of climate information and in order to cope with this feedback a special case was framed in collaboration with the project modeling groups for demonstrating a high resolution climate modeling application of an extreme precipitation-flood event over the study area. This effort provided a realistic reproduction of the

  16. Models of current sintering

    Science.gov (United States)

    Angst, Sebastian; Engelke, Lukas; Winterer, Markus; Wolf, Dietrich E.

    2017-06-01

    Densification of (semi-)conducting particle agglomerates with the help of an electrical current is much faster and more energy efficient than traditional thermal sintering or powder compression. Therefore, this method becomes more and more common among experimentalists, engineers, and in industry. The mechanisms at work at the particle scale are highly complex because of the mutual feedback between current and pore structure. This paper extends previous modelling approaches in order to study mixtures of particles of two different materials. In addition to the delivery of Joule heat throughout the sample, especially in current bottlenecks, thermoelectric effects must be taken into account. They lead to segregation or spatial correlations in the particle arrangement. Various model extensions are possible and will be discussed.

  17. 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

  18. Modeling and assessing international climate financing

    Science.gov (United States)

    Wu, Jing; Tang, Lichun; Mohamed, Rayman; Zhu, Qianting; Wang, Zheng

    2016-06-01

    Climate financing is a key issue in current negotiations on climate protection. This study establishes a climate financing model based on a mechanism in which donor countries set up funds for climate financing and recipient countries use the funds exclusively for carbon emission reduction. The burden-sharing principles are based on GDP, historical emissions, and consumptionbased emissions. Using this model, we develop and analyze a series of scenario simulations, including a financing program negotiated at the Cancun Climate Change Conference (2010) and several subsequent programs. Results show that sustained climate financing can help to combat global climate change. However, the Cancun Agreements are projected to result in a reduction of only 0.01°C in global warming by 2100 compared to the scenario without climate financing. Longer-term climate financing programs should be established to achieve more significant benefits. Our model and simulations also show that climate financing has economic benefits for developing countries. Developed countries will suffer a slight GDP loss in the early stages of climate financing, but the longterm economic growth and the eventual benefits of climate mitigation will compensate for this slight loss. Different burden-sharing principles have very similar effects on global temperature change and economic growth of recipient countries, but they do result in differences in GDP changes for Japan and the FSU. The GDP-based principle results in a larger share of financial burden for Japan, while the historical emissions-based principle results in a larger share of financial burden for the FSU. A larger burden share leads to a greater GDP loss.

  19. Uncertainty Quantification in Climate Modeling and Projection

    Energy Technology Data Exchange (ETDEWEB)

    Qian, Yun; Jackson, Charles; Giorgi, Filippo; Booth, Ben; Duan, Qingyun; Forest, Chris; Higdon, Dave; Hou, Z. Jason; Huerta, Gabriel

    2016-05-01

    The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change information for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for

  20. Do regional climate models represent regional climate?

    Science.gov (United States)

    Maraun, Douglas; Widmann, Martin

    2014-05-01

    When using climate change scenarios - either from global climate models or further downscaled - to assess localised real world impacts, one has to ensure that the local simulation indeed correctly represents the real world local climate. Representativeness has so far mainly been discussed as a scale issue: simulated meteorological variables in general represent grid box averages, whereas real weather is often expressed by means of point values. As a result, in particular simulated extreme values are not directly comparable with observed local extreme values. Here we argue that the issue of representativeness is more general. To illustrate this point, assume the following situations: first, the (GCM or RCM) simulated large scale weather, e.g., the mid-latitude storm track, might be systematically distorted compared to observed weather. If such a distortion at the synoptic scale is strong, the simulated local climate might be completely different from the observed. Second, the orography even of high resolution RCMs is only a coarse model of true orography. In particular in mountain ranges the simulated mesoscale flow might therefore considerably deviate from the observed flow, leading to systematically displaced local weather. In both cases, the simulated local climate does not represent observed local climate. Thus, representativeness also encompasses representing a particular location. We propose to measure this aspect of representativeness for RCMs driven with perfect boundary conditions as the correlation between observations and simulations at the inter-annual scale. In doing so, random variability generated by the RCMs is largely averaged out. As an example, we assess how well KNMIs RACMO2 RCM at 25km horizontal resolution represents winter precipitation in the gridded E-OBS data set over the European domain. At a chosen grid box, RCM precipitation might not be representative of observed precipitation, in particular in the rain shadow of major moutain ranges

  1. Modelling Interglacial Climate

    DEFF Research Database (Denmark)

    Pedersen, Rasmus Anker

    Past warm climate states could potentially provide information on future global warming. The past warming was driven by changed insolation rather than an increased greenhouse effect, and thus the warm climate states are expected to be different. Nonetheless, the response of the climate system...... the impact of a changing sea ice cover. The first part focusses on the last interglacial climate (125,000 years before present) which was characterized by substantial warming at high northern latitudes due to an increased insolation during summer. The simulations reveal that the oceanic changes dominate...... the response at high northern latitudes, while the direct insolation impact is more dominant in the tropics. On Greenland, the simulated warming is low compared to the ice core reconstructions. Surface mass balance calculations indicate that the oceanic conditions favor increased accumulation in the southeast...

  2. Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models

    Directory of Open Access Journals (Sweden)

    E. Joetzjer

    2014-08-01

    Full Text Available While a majority of Global Climate Models project dryer and longer dry seasons over the Amazon under higher CO2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBACC Land Surface Model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent ThroughFall Exclusion (TFE experiments performed in the Amazon. We also explore the model sensitivity to different Water Stress Function (WSF and to an idealized increase in CO2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBACC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO2 concentration, the increased Water Use Efficiency (WUE mitigates the ISBACC's sensitivity to drought. While one of the proposed WSF formulation improves the response of most ISBACC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO2 concentration is clearly needed.

  3. Regional Climate Model Intercomparison Project for Asia.

    Science.gov (United States)

    Fu, Congbin; Wang, Shuyu; Xiong, Zhe; Gutowski, William J.; Lee, Dong-Kyou; McGregor, John L.; Sato, Yasuo; Kato, Hisashi; Kim, Jeong-Woo; Suh, Myoung-Seok

    2005-02-01

    Improving the simulation of regional climate change is one of the high-priority areas of climate study because regional information is needed for climate change impact assessments. Such information is especially important for the region covered by the East Asian monsoon where there is high variability in both space and time. To this end, the Regional Climate Model Intercomparison Project (RMIP) for Asia has been established to evaluate and improve regional climate model (RCM) simulations of the monsoon climate. RMIP operates under joint support of the Asia-Pacific Network for Global Change Research (APN), the Global Change System for Analysis, Research and Training (START), the Chinese Academy of Sciences, and several projects of participating nations. The project currently involves 10 research groups from Australia, China, Japan, South Korea, and the United States, as well as scientists from India, Italy, Mongolia, North Korea, and Russia.RMIP has three simulation phases: March 1997-August 1998, which covers a full annual cycle and extremes in monsoon behavior; January 1989-December 1998, which examines simulated climatology; and a regional climate change scenario, involving nesting with a global model. This paper is a brief report of RMIP goals, implementation design, and some initial results from the first phase studies.

  4. A physiological and biophysical model of coppice willow (Salix spp.) production yields for the contiguous USA in current and future climate scenarios.

    Science.gov (United States)

    Wang, Dan; Jaiswal, Deepak; LeBauer, David S; Wertin, Timothy M; Bollero, Germán A; Leakey, Andrew D B; Long, Stephen P

    2015-09-01

    High-performance computing has facilitated development of biomass production models that capture the key mechanisms underlying production at high spatial and temporal resolution. Direct responses to increasing [CO2 ] and temperature are important to long-lived emerging woody bioenergy crops. Fast-growing willow (Salix spp.) within short rotation coppice (SRC) has considerable potential as a renewable biomass source, but performance over wider environmental conditions and under climate change is uncertain. We extended the bioenergy crop modeling platform, BioCro, to SRC willow by adding coppicing and C3 photosynthesis subroutines, and modifying subroutines for perennation, allocation, morphology, phenology and development. Parameterization with measurements of leaf photosynthesis, allocation and phenology gave agreement of modeled with measured yield across 23 sites in Europe and North America. Predictions for the continental USA suggest yields of ≥17 Mg ha(-1)  year(-1) in a 4 year rotation. Rising temperature decreased predicted yields, an effect partially ameliorated by rising [CO2 ]. This model, based on over 100 equations describing the physiological and biophysical mechanisms underlying production, provides a new framework for utilizing mechanism of plant responses to the environment, including future climates. As an open-source tool, it is made available here as a community resource for further application, improvement and adaptation.

  5. Modeling of Past Climates: Some Perspectives

    Science.gov (United States)

    Kutzbach, J. E.

    2008-12-01

    Important new ideas related to modeling of past climates go hand in hand with new observations, with advances in our understanding and ability to represent physical and biogeochemical processes, and with advances in computer capacity and speed. Important first steps in quantitative climate modeling using energy balance models were underway in the early 20th century. Dynamical climate models began to be used to study past climates in the 1970s and 1980s, with a focus first on the atmosphere, and then on coupled models of atmosphere and upper ocean. In the past decades, coupled dynamical models include atmosphere, global ocean, vegetation, cryosphere and carbon cycle components. This astonishingly rapid development in modeling potential has been greatly facilitated by the rapid increase in computational power. Equally important is the rapid development of more diverse, accurate and worldwide observations of present and past environments from land, lakes, oceans and ice. The topics of early, more recent, and current research on modeling of past climates come from a diverse range of ideas about the mechanisms that might force fundamental changes in climate - for example: changes in greenhouse gases, changes in insolation caused by orbital changes, changes in land-sea distribution, changes in orography, and changes in ocean gateways. Past and current research on these topics, using climate models, illustrates the process and the progress. Certain fundamental principles of modeling and analysis have been important in the past, are important now, and most likely will continue to be important. These principles will be enumerated. Looking toward the future, new observations, improved models and even faster computers are to be expected. But there will also be new challenges: intermodel comparisons and analysis and correction of model bias, understanding feedback processes, understanding non-linear responses, understanding the response to combinations of forcing, and studying

  6. Western boundary currents and climate change

    Science.gov (United States)

    Seager, Richard; Simpson, Isla R.

    2016-09-01

    A recent paper in Journal of Geophysical Research-Oceans connects recent changes in atmospheric circulation to poleward movement and intensification of western boundary currents. Causes and characteristics of past and future trends in surface wind stress and western boundary currents are discussed here.

  7. Normal forms for reduced stochastic climate models

    NARCIS (Netherlands)

    Majda, A.J.; Franzke, C.; Crommelin, D.T.

    The systematic development of reduced low-dimensional stochastic climate models from observations or comprehensive highdimensional climate models is an important topic for atmospheric low-frequency variability, climate sensitivity, and improved extended range forecasting. Here techniques from

  8. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate...... and hydrology have used each model component in an offline mode where the models are run in sequential steps and one model serves as a boundary condition or data input source to the other. Within recent years a new field of research has emerged where efforts have been made to dynamically couple existing climate...... and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface...

  9. Large scale groundwater flow and hexavalent chromium transport modeling under current and future climatic conditions: the case of Asopos River Basin.

    Science.gov (United States)

    Dokou, Zoi; Karagiorgi, Vasiliki; Karatzas, George P; Nikolaidis, Nikolaos P; Kalogerakis, Nicolas

    2016-03-01

    In recent years, high concentrations of hexavalent chromium, Cr(VI), have been observed in the groundwater system of the Asopos River Basin, raising public concern regarding the quality of drinking and irrigation water. The work described herein focuses on the development of a groundwater flow and Cr(VI) transport model using hydrologic, geologic, and water quality data collected from various sources. An important dataset for this goal comprised an extensive time series of Cr(VI) concentrations at various locations that provided an indication of areas of high concentration and also served as model calibration locations. Two main sources of Cr(VI) contamination were considered in the area: anthropogenic contamination originating from Cr-rich industrial wastes buried or injected into the aquifer and geogenic contamination from the leaching process of ophiolitic rocks. The aquifer's response under climatic change scenario A2 was also investigated for the next two decades. Under this scenario, it is expected that rainfall, and thus infiltration, will decrease by 7.7 % during the winter and 15 % during the summer periods. The results for two sub-scenarios (linear and variable precipitation reduction) that were implemented based on A2 show that the impact on the study aquifer is moderate, resulting in a mean level decrease less than 1 m in both cases. The drier climatic conditions resulted in higher Cr(VI) concentrations, especially around the industrial areas.

  10. The Community Climate System Model: CCSM3

    Energy Technology Data Exchange (ETDEWEB)

    Collins, W D; Blackmon, M; Bitz, C; Bonan, G; Bretherton, C S; Carton, J A; Chang, P; Doney, S; Hack, J J; Kiehl, J T; Henderson, T; Large, W G; McKenna, D; Santer, B D; Smith, R D

    2004-12-27

    A new version of the Community Climate System Model (CCSM) has been developed and released to the climate community. CCSM3 is a coupled climate model with components representing the atmosphere, ocean, sea ice, and land surface connected by a flux coupler. CCSM3 is designed to produce realistic simulations over a wide range of spatial resolutions, enabling inexpensive simulations lasting several millennia or detailed studies of continental-scale climate change. This paper will show results from the configuration used for climate-change simulations with a T85 grid for atmosphere and land and a 1-degree grid for ocean and sea-ice. The new system incorporates several significant improvements in the scientific formulation. The enhancements in the model physics are designed to reduce or eliminate several systematic biases in the mean climate produced by previous editions of CCSM. These include new treatments of cloud processes, aerosol radiative forcing, land-atmosphere fluxes, ocean mixed-layer processes, and sea-ice dynamics. There are significant improvements in the sea-ice thickness, polar radiation budgets, equatorial sea-surface temperatures, ocean currents, cloud radiative effects, and ENSO teleconnections. CCSM3 can produce stable climate simulations of millenial duration without ad hoc adjustments to the fluxes exchanged among the component models. Nonetheless, there are still systematic biases in the ocean-atmosphere fluxes in western coastal regions, the spectrum of ENSO variability, the spatial distribution of precipitation in the Pacific and Indian Oceans, and the continental precipitation and surface air temperatures. We conclude with the prospects for extending CCSM to a more comprehensive model of the Earth's climate system.

  11. A Pedagogical "Toy" Climate Model

    CERN Document Server

    Katz, J I

    2010-01-01

    A "toy" model, simple and elementary enough for an undergraduate class, of the temperature dependence of the greenhouse (mid-IR) absorption by atmospheric water vapor implies a bistable climate system. The stable states are glaciation and warm interglacials, while intermediate states are unstable. This is in qualitative accord with the paleoclimatic data. The present climate may be unstable, with or without anthropogenic interventions such as CO$_2$ emission, unless there is additional stabilizing feedback such as "geoengineering".

  12. A Climate System Model, Numerical Simulation and Climate Predictability

    Institute of Scientific and Technical Information of China (English)

    ZENG Qingcun; WANG Huijun; LIN Zhaohui; ZHOU Guangqing; YU Yongqiang

    2007-01-01

    @@ The implementation of the project has lasted for more than 20 years. As a result, the following key innovative achievements have been obtained, ranging from the basic theory of climate dynamics, numerical model development and its related computational theory to the dynamical climate prediction using the climate system models:

  13. Modelling rainfall erosion resulting from climate change

    Science.gov (United States)

    Kinnell, Peter

    2016-04-01

    It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

  14. Multi-model assessment of linkages between eastern Arctic sea-ice variability and the Euro-Atlantic atmospheric circulation in current climate

    Science.gov (United States)

    García-Serrano, J.; Frankignoul, C.; King, M. P.; Arribas, A.; Gao, Y.; Guemas, V.; Matei, D.; Msadek, R.; Park, W.; Sanchez-Gomez, E.

    2016-11-01

    A set of ensemble integrations from the Coupled Model Intercomparison Project phase 5, with historical forcing plus RCP4.5 scenario, are used to explore if state-of-the-art climate models are able to simulate previously reported linkages between sea-ice concentration (SIC) anomalies over the eastern Arctic, namely in the Greenland-Barents-Kara Seas, and lagged atmospheric circulation that projects on the North Atlantic Oscillation (NAO)/Arctic Oscillation (AO). The study is focused on variability around the long-term trends, so that all anomalies are detrended prior to analysis; the period of study is 1979-2013. The model linkages are detected by applying maximum covariance analysis. As also found in observational data, all the models considered here show a statistically significant link with sea-ice reduction over the eastern Arctic followed by a negative NAO/AO-like pattern. If the simulated relationship is found at a lag of one month, the results suggest that a stratospheric pathway could be at play as the driving mechanism; in observations this is preferentially shown for SIC in November. The interference of a wave-like anomaly over Eurasia, accompanying SIC changes, with the climatological wave pattern appears to be key in setting the mediating role of the stratosphere. On the other hand, if the simulated relationship is found at a lag of two months, the results suggest that tropospheric dynamics are dominant, presumably due to transient eddy feedback; in observations this is preferentially shown for SIC in December. The results shown here and previous evidence from atmosphere-only experiments emphasize that there could be a detectable influence of eastern Arctic SIC variability on mid-latitude atmospheric circulation anomalies. Even if the mechanisms are robust among the models, the timing of the simulated linkages strongly depends on the model and does not generally mimic the observational ones. This implies that the atmospheric sensitivity to sea

  15. Model confirmation in climate economics.

    Science.gov (United States)

    Millner, Antony; McDermott, Thomas K J

    2016-08-01

    Benefit-cost integrated assessment models (BC-IAMs) inform climate policy debates by quantifying the trade-offs between alternative greenhouse gas abatement options. They achieve this by coupling simplified models of the climate system to models of the global economy and the costs and benefits of climate policy. Although these models have provided valuable qualitative insights into the sensitivity of policy trade-offs to different ethical and empirical assumptions, they are increasingly being used to inform the selection of policies in the real world. To the extent that BC-IAMs are used as inputs to policy selection, our confidence in their quantitative outputs must depend on the empirical validity of their modeling assumptions. We have a degree of confidence in climate models both because they have been tested on historical data in hindcasting experiments and because the physical principles they are based on have been empirically confirmed in closely related applications. By contrast, the economic components of BC-IAMs often rely on untestable scenarios, or on structural models that are comparatively untested on relevant time scales. Where possible, an approach to model confirmation similar to that used in climate science could help to build confidence in the economic components of BC-IAMs, or focus attention on which components might need refinement for policy applications. We illustrate the potential benefits of model confirmation exercises by performing a long-run hindcasting experiment with one of the leading BC-IAMs. We show that its model of long-run economic growth-one of its most important economic components-had questionable predictive power over the 20th century.

  16. Optimal adaptation to extreme rainfalls in current and future climate

    Science.gov (United States)

    Rosbjerg, Dan

    2017-01-01

    More intense and frequent rainfalls have increased the number of urban flooding events in recent years, prompting adaptation efforts. Economic optimization is considered an efficient tool to decide on the design level for adaptation. The costs associated with a flooding to the T-year level and the annual capital and operational costs of adapting to this level are described with log-linear relations. The total flooding costs are developed as the expected annual damage of flooding above the T-year level plus the annual capital and operational costs for ensuring no flooding below the T-year level. The value of the return period T that corresponds to the minimum of the sum of these costs will then be the optimal adaptation level. The change in climate, however, is expected to continue in the next century, which calls for expansion of the above model. The change can be expressed in terms of a climate factor (the ratio between the future and the current design level) which is assumed to increase in time. This implies increasing costs of flooding in the future for many places in the world. The optimal adaptation level is found for immediate as well as for delayed adaptation. In these cases, the optimum is determined by considering the net present value of the incurred costs during a sufficiently long time-span. Immediate as well as delayed adaptation is considered.

  17. Modeling plant species distributions under future climates: how fine scale do climate projections need to be?

    Science.gov (United States)

    Franklin, Janet; Davis, Frank W; Ikegami, Makihiko; Syphard, Alexandra D; Flint, Lorraine E; Flint, Alan L; Hannah, Lee

    2013-02-01

    Recent studies suggest that species distribution models (SDMs) based on fine-scale climate data may provide markedly different estimates of climate-change impacts than coarse-scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse-scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000-fold range of spatial scales (0.008-16 km(2) ). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate-data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine- and coarse-scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net

  18. High dimensional decision dilemmas in climate models

    Directory of Open Access Journals (Sweden)

    A. Bracco

    2013-10-01

    Full Text Available An important source of uncertainty in climate models is linked to the calibration of model parameters. Interest in systematic and automated parameter optimization procedures stems from the desire to improve the model climatology and to quantify the average sensitivity associated with potential changes in the climate system. Building upon on the smoothness of the response of an atmospheric circulation model (AGCM to changes of four adjustable parameters, Neelin et al. (2010 used a quadratic metamodel to objectively calibrate the AGCM. The metamodel accurately estimates global spatial averages of common fields of climatic interest, from precipitation, to low and high level winds, from temperature at various levels to sea level pressure and geopotential height, while providing a computationally cheap strategy to explore the influence of parameter settings. Here, guided by the metamodel, the ambiguities or dilemmas related to the decision making process in relation to model sensitivity and optimization are examined. Simulations of current climate are subject to considerable regional-scale biases. Those biases may vary substantially depending on the climate variable considered, and/or on the performance metric adopted. Common dilemmas are associated with model revisions yielding improvement in one field or regional pattern or season, but degradation in another, or improvement in the model climatology but degradation in the interannual variability representation. Challenges are posed to the modeler by the high dimensionality of the model output fields and by the large number of adjustable parameters. The use of the metamodel in the optimization strategy helps visualize trade-offs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional errors under minimization of global objective functions.

  19. High dimensional decision dilemmas in climate models

    Directory of Open Access Journals (Sweden)

    A. Bracco

    2013-05-01

    Full Text Available An important source of uncertainty in climate models is linked to the calibration of model parameters. Interest in systematic and automated parameter optimization procedures stems from the desire to improve the model climatology and to quantify the average sensitivity associated with potential changes in the climate system. Neelin et al. (2010 used a quadratic metamodel to objectively calibrate an atmospheric circulation model (AGCM around four adjustable parameters. The metamodel accurately estimates global spatial averages of common fields of climatic interest, from precipitation, to low and high level winds, from temperature at various levels to sea level pressure and geopotential height, while providing a computationally cheap strategy to explore the influence of parameter settings. Here, guided by the metamodel, the ambiguities or dilemmas related to the decision making process in relation to model sensitivity and optimization are examined. Simulations of current climate are subject to considerable regional-scale biases. Those biases may vary substantially depending on the climate variable considered, and/or on the performance metric adopted. Common dilemmas are associated with model revisions yielding improvement in one field or regional pattern or season, but degradation in another, or improvement in the model climatology but degradation in the interannual variability representation. Challenges are posed to the modeler by the high dimensionality of the model output fields and by the large number of adjustable parameters. The use of the metamodel in the optimization strategy helps visualize trade-offs at a regional level, e.g. how mismatches between sensitivity and error spatial fields yield regional errors under minimization of global objective functions.

  20. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate...... and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface...... to the LSM in HIRHAM. A wider range of processes are included at the land surface, subsurface flow is distributed in three dimensions and the temporal and spatial resolution is higher. Secondly, the feedback mechanisms of e.g. soil moisture and recipitation between the two models are included...

  1. Modelling the effect of climate change on species ranges

    NARCIS (Netherlands)

    Nagelkerke, C.J.; Alkemade, J.R.M.

    2003-01-01

    Three main types of models can be used to understand and predict climate-related range shifts. Equilibrium models predict potential future distributions from the current climate envelope of a species, but do not take migration constraints into account. They show that future range changes can be

  2. The VEMAP integrated dataset for simulation of ecological responses to global change: Current climate and climate change scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Kittel, T.G.F. [NCAR/UCAR, Boulder, CO (United States)]|[Colorado State Univ., Ft. Collins, CO (United States)

    1995-06-01

    The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) dataset consists of inputs for biogeochemical and biogeographical models, including current climate, climate scenarios, soils, and vegetation for the conterminous United States on a 0.5 deg lat./lon. grid. The set has daily and monthly representations of climate. Monthly temperature (T) and precipitation (PPT) were derived from station records or statistically-generated from nearby stations. These values were interpolated to the grid accounting for orographic effects in an effort to make the grid-scale climate representative of actual bioclimates within grid cells; this was crucial because ecosystem responses are nonlinearly related to climate. Daily T and PPT were stochastically simulated with WGEN, and daily solar radiation and humidity empirically estimated with CLIMSIM. Equilibrium climate change scenarios were selected to capture a range of potential change from GCM experiments. Transient scenario rates of change were based on atmosphere-ocean GCM results. Mean climate, equilibrium scenarios, vegetation, and soil data are available on CD-ROM.

  3. Climate system model, numerical simulation and climate predictability

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    @@ Thanks to its work of past more than 20 years,a research team led by Prof.ZENG Qingcun and Prof.WANG Huijun from the CAS Institute of Atmospheric Physics (IAP) has scored innovative achievements in their studies of basic theory of climate dynamics,numerical model development,its related computational theory,and the dynamical climate prediction using the climate system models.Their work received a second prize of the National Award for Natural Sciences in 2005.

  4. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Jiang, J. H.

    2013-12-01

    The latest Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with newly available global observations. The traditional approach to climate model evaluation, which compares a single parameter at a time, identifies symptomatic model biases and errors but fails to diagnose the model problems. The model diagnosis process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. To address these challenges, we are developing a parallel, distributed web-service system that enables the physics-based multi-variable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. We have developed a methodology to transform an existing science application code into a web service using a Python wrapper interface and Python web service frameworks (i.e., Flask, Gunicorn, and Tornado). The web-service system, called Climate Model Diagnostic Analyzer (CMDA), currently supports (1) all the datasets from Obs4MIPs and a few ocean datasets from NOAA and Argo, which can serve as observation-based reference data for model evaluation and (2) many of CMIP5 model outputs covering a broad range of atmosphere, ocean, and land variables from the CMIP5 specific historical runs and AMIP runs. Analysis capabilities currently supported by CMDA are (1) the calculation of annual and seasonal means of physical variables, (2) the calculation of time evolution of the means in any specified geographical region, (3) the calculation of correlation between two variables, and (4) the calculation of difference between two variables. A web user interface is chosen for CMDA because it not only lowers the learning curve and removes the adoption barrier of the tool but also enables instantaneous use

  5. Climate Change Modelling and Its Roles to Chinese Crops Yield

    Institute of Scientific and Technical Information of China (English)

    JU Hui; LIN Er-da; Tim Wheeler; Andrew Challinor; JIANG Shuai

    2013-01-01

    Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation. Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability. Understanding the interactions between climate change and agricultural production is essential for society stable development of China. The first mission is to fully understand how to predict future climate and link it with agriculture production system. In this paper, recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches. The methods for climate change scenarios construction are introduced. The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized. The study found that simulated productions of grain crop inherit uncertainty from using different climate models, emission scenarios and the crops simulation models. Moreover, studies have different spatial resolutions, and methods for general circulation model (GCM) downscaling which increase the uncertainty for regional impacts assessment. However, the magnitude of change in crop production due to climate change (at 700 ppm CO2 eq correct) appears within ±10%for China in these assessments. In most literatures, the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase. Finally, the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops. The uncertainty for crop yield projection is associated with climate change scenarios, CO2 fertilization effects and adaptation options. Therefore, more studies on the fields such as free air CO2 enrichment experiment and practical adaptations implemented need to be carried out.

  6. High-resolution simulations for Vietnam - methodology and evaluation of current climate

    Science.gov (United States)

    Katzfey, Jack; Nguyen, Kim; McGregor, John; Hoffmann, Peter; Ramasamy, Suppiah; Nguyen, Hiep Van; Khiem, Mai Van; Nguyen, Thang Van; Truong, Kien Ba; Vu, Thang Van; Nguyen, Hien Thuan; Thuc, Tran; Phong, Doan Ha; Nguyen, Bang Thanh; Phan-Van, Tan; Nguyen-Quang, Trung; Ngo-Duc, Thanh; Trinh-Tuan, Long

    2016-05-01

    To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO's variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (-60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.

  7. Uncertainty Quantification in Climate Modeling

    Science.gov (United States)

    Sargsyan, K.; Safta, C.; Berry, R.; Debusschere, B.; Najm, H.

    2011-12-01

    We address challenges that sensitivity analysis and uncertainty quantification methods face when dealing with complex computational models. In particular, climate models are computationally expensive and typically depend on a large number of input parameters. We consider the Community Land Model (CLM), which consists of a nested computational grid hierarchy designed to represent the spatial heterogeneity of the land surface. Each computational cell can be composed of multiple land types, and each land type can incorporate one or more sub-models describing the spatial and depth variability. Even for simulations at a regional scale, the computational cost of a single run is quite high and the number of parameters that control the model behavior is very large. Therefore, the parameter sensitivity analysis and uncertainty propagation face significant difficulties for climate models. This work employs several algorithmic avenues to address some of the challenges encountered by classical uncertainty quantification methodologies when dealing with expensive computational models, specifically focusing on the CLM as a primary application. First of all, since the available climate model predictions are extremely sparse due to the high computational cost of model runs, we adopt a Bayesian framework that effectively incorporates this lack-of-knowledge as a source of uncertainty, and produces robust predictions with quantified uncertainty even if the model runs are extremely sparse. In particular, we infer Polynomial Chaos spectral expansions that effectively encode the uncertain input-output relationship and allow efficient propagation of all sources of input uncertainties to outputs of interest. Secondly, the predictability analysis of climate models strongly suffers from the curse of dimensionality, i.e. the large number of input parameters. While single-parameter perturbation studies can be efficiently performed in a parallel fashion, the multivariate uncertainty analysis

  8. Modeling Impacts of Climate Change on Giant Panda Habitat

    Directory of Open Access Journals (Sweden)

    Melissa Songer

    2012-01-01

    Full Text Available Giant pandas (Ailuropoda melanoleuca are one of the most widely recognized endangered species globally. Habitat loss and fragmentation are the main threats, and climate change could significantly impact giant panda survival. We integrated giant panda habitat information with general climate models (GCMs to predict future geographic distribution and fragmentation of giant panda habitat. Results support a major general prediction of climate change—a shift of habitats towards higher elevation and higher latitudes. Our models predict climate change could reduce giant panda habitat by nearly 60% over 70 years. New areas may become suitable outside the current geographic range but much of these areas is far from the current giant panda range and only 15% fall within the current protected area system. Long-term survival of giant pandas will require the creation of new protected areas that are likely to support suitable habitat even if the climate changes.

  9. Little auks buffer the impact of current Arctic climate change

    DEFF Research Database (Denmark)

    Grémillet, David; Welcker, Jorg; Karnovsky, Nina J.

    2012-01-01

    Climate models predict a multi-degree warming of the North Atlantic in the 21st century. A research priority is to understand the impact of such changes upon marine organisms. With 40-80 million individuals, planktivorous little auks (Alle alle) are an essential component of pelagic food webs in ...

  10. Climate change and respiratory health: current evidence and knowledge gaps.

    Science.gov (United States)

    Takaro, Tim K; Knowlton, Kim; Balmes, John R

    2013-08-01

    Climate change is a key driver of the accelerating environmental change affecting populations around the world. Many of these changes and our response to them can affect respiratory health. This is an expert opinion review of recent peer-reviewed literature, focused on more recent medical journals and climate-health relevant modeling results from non-biomedical journals pertaining to climate interactions with air pollution. Global health impacts in low resource countries and migration precipitated by environmental change are addressed. The major findings are of respiratory health effects related to heat, air pollution, shifts in infectious diseases and allergens, flooding, water, food security and migration. The review concludes with knowledge gaps and research need that will support the evidence-base required to address the challenges ahead.

  11. Simulating malaria transmission in the current and future climate of West Africa

    Science.gov (United States)

    Yamana, T. K.; Bomblies, A.; Eltahir, E. A. B.

    2015-12-01

    Malaria transmission in West Africa is closely tied to climate, as rain fed water pools provide breeding habitat for the anopheles mosquito vector, and temperature affects the mosquito's ability to spread disease. We present results of a highly detailed, spatially explicit mechanistic modelling study exploring the relationships between the environment and malaria in the current and future climate of West Africa. A mechanistic model of human immunity was incorporated into an existing agent-based model of malaria transmission, allowing us to move beyond entomological measures such as mosquito density and vectorial capacity to analyzing the prevalence of the malaria parasite within human populations. The result is a novel modelling tool that mechanistically simulates all of the key processes linking environment to malaria transmission. Simulations were conducted across climate zones in West Africa, linking temperature and rainfall to entomological and epidemiological variables with a focus on nonlinearities due to threshold effects and interannual variability. Comparisons to observations from the region confirmed that the model provides a reasonable representation of the entomological and epidemiological conditions in this region. We used the predictions of future climate from the most credible CMIP5 climate models to predict the change in frequency and severity of malaria epidemics in West Africa as a result of climate change.

  12. Climate Sensitivity and Solar Cycle Response in Climate Models

    Science.gov (United States)

    Liang, M.; Lin, L.; Tung, K. K.; Yung, Y. L.

    2011-12-01

    Climate sensitivity, broadly defined, is a measure of the response of the climate system to the changes of external forcings such as anthropogenic greenhouse emissions and solar radiation, including climate feedback processes. General circulation models provide a means to quantitatively incorporate various feedback processes, such as water-vapor, cloud and albedo feedbacks. Less attention is devoted so far to the role of the oceans in significantly affecting these processes and hence the modelled transient climate sensitivity. Here we show that the oceanic mixing plays an important role in modifying the multi-decadal to centennial oscillations of the sea surface temperature, which in turn affect the derived climate sensitivity at various phases of the oscillations. The eleven-year solar cycle forcing is used to calibrate the response of the climate system. The GISS-EH coupled atmosphere-ocean model was run twice in coupled mode for more than 2000 model years, each with a different value for the ocean eddy mixing parameter. In both runs, there is a prominent low-frequency oscillation with a period of 300-500 years, and depending on the phase of such an oscillation, the derived climate gain factor varies by a factor of 2. The run with the value of the eddy ocean mixing parameter that is half that used in IPCC AR4 study has the more realistic low-frequency variability in SST and in the derived response to the known solar-cycle forcing.

  13. Modeling climate change impacts on water trading.

    Science.gov (United States)

    Luo, Bin; Maqsood, Imran; Gong, Yazhen

    2010-04-01

    This paper presents a new method of evaluating the impacts of climate change on the long-term performance of water trading programs, through designing an indicator to measure the mean of periodic water volume that can be released by trading through a water-use system. The indicator is computed with a stochastic optimization model which can reflect the random uncertainty of water availability. The developed method was demonstrated in the Swift Current Creek watershed of Prairie Canada under two future scenarios simulated by a Canadian Regional Climate Model, in which total water availabilities under future scenarios were estimated using a monthly water balance model. Frequency analysis was performed to obtain the best probability distributions for both observed and simulated water quantity data. Results from the case study indicate that the performance of a trading system is highly scenario-dependent in future climate, with trading effectiveness highly optimistic or undesirable under different future scenarios. Trading effectiveness also largely depends on trading costs, with high costs resulting in failure of the trading program.

  14. Climate modelling, uncertainty and responses to predictions of change

    Energy Technology Data Exchange (ETDEWEB)

    Henderson-Sellers, A. [Climatic Impacts Centre, Macquarie University, Sydney (Australia)

    1996-12-31

    Article 4.1(F) of the Framework Convention on Climate Change commits all parties to take climate change considerations into account, to the extent feasible, in relevant social, economic and environmental policies and actions and to employ methods such as impact assessments to minimize adverse effects of climate change. This could be achieved by, inter alia, incorporating climate change risk assessment into development planning processes, i.e. relating climatic change to issues of habitability and sustainability. Adaptation is an ubiquitous and beneficial natural and human strategy. Future adaptation (adjustment) to climate is inevitable at the least to decrease the vulnerability to current climatic impacts. An urgent issue is the mismatch between the predictions of global climatic change and the need for information on local to regional change in order to develop adaptation strategies. Mitigation efforts are essential since the more successful mitigation activities are, the less need there will be for adaptation responses. And, mitigation responses can be global (e.g. a uniform percentage reduction in greenhouse gas emissions) while adaptation responses will be local to regional in character and therefore depend upon confident predictions of regional climatic change. The dilemma facing policymakers is that scientists have considerable confidence in likely global climatic changes but virtually zero confidence in regional changes. Mitigation and adaptation strategies relevant to climatic change can most usefully be developed in the context of sound understanding of climate, especially the near-surface continental climate, permitting discussion of societally relevant issues. But, climate models can`t yet deliver this type of regionally and locationally specific prediction and some aspects of current research even seem to indicate increased uncertainty. These topics are explored in this paper using the specific example of the prediction of land-surface climate changes.

  15. Shifts of climate zones in multi-model climate change experiments using the Koeppen climate classification

    Energy Technology Data Exchange (ETDEWEB)

    Hanf, Franziska; Koerper, Janina; Spangehl, Thomas; Cubash, Ulrich [Freie Univ. Berlin (Germany). Inst. fuer Meteorologie

    2012-04-15

    This study investigates the future changes in the climate zones' distribution of the Earth's land area due to increasing atmospheric greenhouse gas concentrations in three IPCC SRES emissions scenarios (A1B, A2 and B1). The Koeppen climate classification is applied to climate simulations of seven atmosphere-ocean general circulation models (AOGCMs) and their multi-model mean. The evaluation of the skill of the individual climate models compared to an observation-reanalysis-based climate classification provides a first order estimate of relevant model uncertainties and serves as assessment for the confidence in the scenario projections. Uncertainties related to differences in simulation pathways of the future projections are estimated by both, the multi-model ensemble spread of the climate change signals for a given scenario and differences between different scenarios. For the recent climate the individual models fail to capture the exact Koeppen climate types in about 24-39 % of the global land area excluding Antarctica due to temperature and precipitation biases, while the multi-model ensemble mean simulates the present day observation-reanalysis-based distribution of the climate types more accurately. For the end of the 21{sup st} century compared to the present day climate the patterns of change are similar across the three scenarios, while the magnitude of change is largest for the highest emission scenario. Moreover, the temporal development of the climate shifts from the end of the 20st century and during the 21{sup st} century show that changes of the multi-model ensemble mean for the A2 and B1 scenario are generally within the ensemble spread of the individual models for the A1B scenario, illustrating that for the given range of scenarios the model uncertainty is even larger than the spread given by the different GHG concentration pathways. The multi-model ensemble mean's projections show climate shifts to dryer climates in the subtropics

  16. Vulnerability of Plantation Carbon Stocks to Defoliation under Current and Future Climates

    Directory of Open Access Journals (Sweden)

    Elizabeth A. Pinkard

    2014-06-01

    Full Text Available Plantation species globally are susceptible to a range of defoliating pests, but pest damage is rarely considered when estimating biomass C sequestered by these forests. We examined the impacts of defoliation on Eucalyptus globulus plantation C stocks under current and future climates using Mycospharella Leaf Disease (MLD as a case study, hypothesising that biomass C sequestered in plantations would decrease with a warming and drying climate, and that impacts of defoliation would be strongly site dependent. Six E. globulus plantation sites with varying productivity were selected for the study. Current (1961–2005 and future (2030 and 2070 severity and frequency of MLD were estimated for each site using the bioclimatic niche model CLIMEX, and used as inputs to the process-based forest productivity model CABALA. CABALA was used to develop annual estimates of total living and dead biomass for current, 2030 and 2070 climate scenarios. Averaged annual biomass outputs were used to initialise the carbon accounting model FullCAM for calculation of C sequestered in living and dead biomass over a growing cycle. E. globulus plantations were predicted to sequester between 4.8 and 13.4 Mg C·ha−1·year−1 over 10 years under current climatic conditions. While our estimates suggest that overall this is likely to increase slightly under future climates (up to a maximum of 17.2 Mg C·ha−1·year−1 in 2030, and a shift in minimum and maximum values to 7.6 and 17.6 respectively in 2070, we predict considerable between-site variation. Our results suggest that biomass C sequestration will not necessarily be enhanced by future climatic conditions in all locations. We predict that biomass C sequestration may be reduced considerably by defoliation meaning that any gains in C sequestration associated with changing climate may be substantially offset by defoliation. While defoliation has a generally small impact under current climatic conditions in these

  17. Advances in urban climate modeling.

    Science.gov (United States)

    Hidalgo, Julia; Masson, Valéry; Baklanov, Alexander; Pigeon, Grégoire; Gimeno, Luis

    2008-12-01

    Cities interact with the atmosphere over a wide range of scales from the large-scale processes, which have a direct impact on global climate change, to smaller scales, ranging from the conurbation itself to individual buildings. The review presented in this paper analyzes some of the ways in which cities influence atmospheric thermodynamics and airborne pollutant transport. We present the main physical processes that characterize the urban local meteorology (the urban microclimate) and air pollution. We focus on small-scale impacts, including the urban heat island and its causes. The impact on the lower atmosphere over conurbations, air pollution in cities, and the effect on meteorological processes are discussed. An overview of the recent principal advances in urban climatology and air quality modeling in atmospheric numerical models is also presented.

  18. Pleistocene climate, phylogeny, and climate envelope models: an integrative approach to better understand species' response to climate change.

    Directory of Open Access Journals (Sweden)

    A Michelle Lawing

    Full Text Available Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models, phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species, and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr than it has been on average for the past 320 ky (2.3 m/yr.

  19. Selecting representative climate models for climate change impact studies : An advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; ter Maat, Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.|info:eu-repo/dai/nl/290472113

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change

  20. Selecting representative climate models for climate change impact studies: an advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; Maat, ter Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change

  1. Selecting representative climate models for climate change impact studies : An advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; ter Maat, Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change impa

  2. Selecting representative climate models for climate change impact studies: an advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; Maat, ter Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change impa

  3. A Regional Climate Model Evaluation System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop a packaged data management infrastructure for the comparison of generated climate model output to existing observational datasets that includes capabilities...

  4. Economic costs of achieving current conservation goals in the future as climate changes.

    Science.gov (United States)

    Shaw, M Rebecca; Klausmeyer, Kirk; Cameron, D Richard; Mackenzie, Jason; Roehrdanz, Patrick

    2012-06-01

    Conservation of biologically diverse regions has thus far been accomplished largely through the establishment and maintenance of protected areas. Climate change is expected to shift climate space of many species outside existing reserve boundaries. We used climate-envelope models to examine shifts in climate space of 11 species that are representative of the Mount Hamilton Project area (MHPA) (California, U.S.A.), which includes areas within Alameda, Santa Clara, San Joaquin, Stanislaus, Merced, and San Benito counties and is in the state's Central Coast ecoregion. We used Marxan site-selection software to determine the minimum area required as climate changes to achieve a baseline conservation goal equal to 80% of existing climate space for all species in the MHPA through 2050 and 2100. Additionally, we assessed the costs associated with use of existing conservation strategies (land acquisition and management actions such as species translocation, monitoring, and captive breeding) necessary to meet current species-conservation goals as climate changes. Meeting conservation goals as climate changes through 2050 required an additional 256,000 ha (332%) of protected area, primarily to the south and west of the MHPA. Through 2050 the total cost of land acquisition and management was estimated at US$1.67-1.79 billion, or 139-149% of the cost of achieving the same conservation goals with no climate change. To maintain 80% of climate space through 2100 required nearly 380,000 additional hectares that would cost $2.46-2.62 billion, or 209-219% of the cost of achieving the same conservation goals with no climate change. Furthermore, maintaining 80% of existing climate space within California for 27% of the focal species was not possible by 2100 because climate space for these species did not exist in the state. The high costs of conserving species as the climate changes-that we found in an assessment of one conservation project-highlights the need for tools that will aid

  5. Optimal adaptation to extreme rainfalls in current and future climate

    DEFF Research Database (Denmark)

    Rosbjerg, Dan

    2017-01-01

    and the annual capital and operational costs of adapting to this level are described with log-linear relations. The total flooding costs are developed as the expected annual damage of flooding above the T-year level plus the annual capital and operational costs for ensuring no flooding below the T-year level......More intense and frequent rainfalls have increased the number of urban flooding events in recent years, prompting adaptation efforts. Economic optimization is considered an efficient tool to decide on the design level for adaptation. The costs associated with a flooding to the T-year level....... The value of the return period T that corresponds to the minimum of the sum of these costs will then be the optimal adaptation level. The change in climate, however, is expected to continue in the next century, which calls for expansion of the above model. The change can be expressed in terms of a climate...

  6. Climate model; Downscaling; Fars; GIS; Interpolation

    Directory of Open Access Journals (Sweden)

    Reza Deihimfard

    2016-03-01

    Full Text Available Introduction Today, Climate change issue is one of the main challenges for scientists and due to the critical role of water in human life, the study of climate change impacts on severity and frequency of drought in each region seems to be indispensable (Hulme et al., 1999. Drought is usually occurred over a period of water shortage owing to less rainfall, high evapotranspiration and pumping a huge amount of water from water tables. This issue could have extensive consequences on agriculture, ecosystems and communities. The objectives of this study were to predict meteorological parameters, calculation of drought index and its zoning under the changing climate in Fars province. Materials and methods In order to predict the future climate in nine districts of Fars province (including Shiraz, Eghlid, Fasa, Lar, Lamerd, Darab, Zarghan, Neiriz and Abadeh, two climate models (HadCM3 and IPCM4 was applied under three scenarios (B1, A1B and A2. LARS-WG software was applied to downscale climate parameters (Semenov and Barrow, 2002. To predict incident probability of drought in the all study locations, a drought index (Standardize Precipitation Index, SPI was calculated at a time scale of 12 months. SPI is the most commonly used drought index. SPI is calculated based upon the differences between monthly rainfall and average rainfall for a certain period of time according to the time scale (Mckee et al., 1995. In this study the SPI time series have been estimated for the historical base period 1980-1990 and for three future periods (2011-2030, 2046-2065, 2080-2099. Finally, drought maps and zoning were conducted in the whole province using GIS and based on IDW interpolation method. Results and discussion Results of climate models evaluation indicated that LARS-GW well predicted radiation, and maximum and minimum temperatures (RMSE of 0.51, 0.46 and 1.02%, respectively. However, the accuracy in prediction of rainfall was not as good as the other climatic

  7. Impact of future climate policy scenarios on air quality and aerosol-cloud interactions using an advanced version of CESM/CAM5: Part I. model evaluation for the current decadal simulations

    Science.gov (United States)

    Glotfelty, Timothy; He, Jian; Zhang, Yang

    2017-03-01

    A version of the Community Earth System Model modified at the North Carolina State University (CESM-NCSU) is used to simulate the current and future atmosphere following the representative concentration partway scenarios for stabilization of radiative forcing at 4.5 W m-2 (RCP4.5) and radiative forcing of 8.5 W m-2 (RCP8.5). Part I describes the results from a comprehensive evaluation of current decadal simulations. Radiation and most meteorological variables are well simulated in CESM-NCSU. Cloud parameters are not as well simulated due in part to the tuning of model radiation and general biases in cloud variables common to all global chemistry-climate models. The concentrations of most inorganic aerosol species (i.e., SO42-, NH4+, and NO3-) are well simulated with normalized mean biases (NMBs) typically less than 20%. However, some notable exceptions are European NH4+, which is overpredicted by 33.0-42.2% due to high NH3 emissions and irreversible coarse mode condensation, and Cl-, that is negatively impacted by errors in emissions driven by wind speed and overpredicted HNO3. Carbonaceous aerosols are largely underpredicted following the RCP scenarios due to low emissions of black carbon, organic carbon, and anthropogenic volatile compounds in the RCP inventory and efficient wet removal. This results in underpredictions of PM2.5 and PM10 by 6.4-55.7%. The column mass abundances are reasonably well simulated. Larger biases occur in surface mixing ratios of trace gases in CESM-NCSU, likely due to numerical diffusion from the coarse grid spacing of the CESM-NCSU simulations or errors in the magnitudes and vertical structure of emissions. This is especially true for SO2 and NO2. The mixing ratio of O3 is overpredicted by 38.9-76.0% due to the limitations in the O3 deposition scheme used in CESM and insufficient titration resulted from large underpredictions in NO2. Despite these limitations, CESM-NCSU reproduces reasonably well the current atmosphere in terms of

  8. Climate predictions: the chaos and complexity in climate models

    CERN Document Server

    Mihailović, Dragutin T; Arsenić, Ilija

    2013-01-01

    Some issues which are relevant for the recent state in climate modeling have been considered. A detailed overview of literature related to this subject is given. The concept in modeling of climate, as a complex system, seen through Godel's Theorem and Rosen's definition of complexity and predictability is discussed. It is pointed out to occurrence of chaos in computing the environmental interface temperature from the energy balance equation given in a difference form. A coupled system of equations, often used in climate models is analyzed. It is shown that the Lyapunov exponent mostly has positive values allowing presence of chaos in this systems. The horizontal energy exchange between environmental interfaces, which is described by the dynamics of driven coupled oscillators, is analyzed. Their behavior and synchronization, when a perturbation is introduced in the system, as a function of the coupling parameters, the logistic parameter and the parameter of exchange, was studied calculating the Lyapunov expone...

  9. Modeling lakes and reservoirs in the climate system

    Science.gov (United States)

    MacKay, M.D.; Neale, P.J.; Arp, C.D.; De Senerpont Domis, L. N.; Fang, X.; Gal, G.; Jo, K.D.; Kirillin, G.; Lenters, J.D.; Litchman, E.; MacIntyre, S.; Marsh, P.; Melack, J.; Mooij, W.M.; Peeters, F.; Quesada, A.; Schladow, S.G.; Schmid, M.; Spence, C.; Stokes, S.L.

    2009-01-01

    Modeling studies examining the effect of lakes on regional and global climate, as well as studies on the influence of climate variability and change on aquatic ecosystems, are surveyed. Fully coupled atmosphere-land surface-lake climate models that could be used for both of these types of study simultaneously do not presently exist, though there are many applications that would benefit from such models. It is argued here that current understanding of physical and biogeochemical processes in freshwater systems is sufficient to begin to construct such models, and a path forward is proposed. The largest impediment to fully representing lakes in the climate system lies in the handling of lakes that are too small to be explicitly resolved by the climate model, and that make up the majority of the lake-covered area at the resolutions currently used by global and regional climate models. Ongoing development within the hydrological sciences community and continual improvements in model resolution should help ameliorate this issue.

  10. Climate Modeling: Ocean Cavities below Ice Shelves

    Energy Technology Data Exchange (ETDEWEB)

    Petersen, Mark Roger [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Computer, Computational, and Statistical Sciences Division

    2016-09-12

    The Accelerated Climate Model for Energy (ACME), a new initiative by the U.S. Department of Energy, includes unstructured-mesh ocean, land-ice, and sea-ice components using the Model for Prediction Across Scales (MPAS) framework. The ability to run coupled high-resolution global simulations efficiently on large, high-performance computers is a priority for ACME. Sub-ice shelf ocean cavities are a significant new capability in ACME, and will be used to better understand how changing ocean temperature and currents influence glacial melting and retreat. These simulations take advantage of the horizontal variable-resolution mesh and adaptive vertical coordinate in MPAS-Ocean, in order to place high resolution below ice shelves and near grounding lines.

  11. Wind climate from the regional climate model REMO

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Mann, Jakob; Berg, Jacob

    2010-01-01

    Selected outputs from simulations with the regional climate model REMO from the Max Planck Institute, Hamburg, Germany were studied in connection with wind energy resource assessment. It was found that the mean wind characteristics based on observations from six mid-latitude stations are well...

  12. An Appraisal of Coupled Climate Model Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Sperber, K; Gleckler, P; Covey, C; Taylor, K; Bader, D; Phillips, T; Fiorino, M; Achutarao, K

    2004-02-24

    In 2002, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) proposed the concept for a state-of-the-science appraisal of climate models to be performed approximately every two years. Motivation for this idea arose from the perceived needs of the international modeling groups and the broader climate research community to document progress more frequently than provided by the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports. A committee of external reviewers, which included senior researchers from four leading international modeling centers, supported the concept by stating in its review: ''The panel enthusiastically endorses the suggestion that PCMDI develop an independent appraisal of coupled model performance every 2-3 years. This would provide a useful 'mid-course' evaluation of modeling progress in the context of larger IPCC and national assessment activities, and should include both coupled and single-component model evaluations.''

  13. Climate Change Vulnerability and Resilience: Current Status and Trends for Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Ibarraran , Maria E.; Malone, Elizabeth L.; Brenkert, Antoinette L.

    2008-12-30

    Climate change alters different localities on the planet in different ways. The impact on each region depends mainly on the degree of vulnerability that natural ecosystems and human-made infrastructure have to changes in climate and extreme meteorological events, as well as on the coping and adaptation capacity towards new environmental conditions. This study assesses the current resilience of Mexico and Mexican states to such changes, as well as how this resilience will look in the future. In recent studies (Moss et al. 2000, Brenkert and Malone 2005, Malone and Brenket 2008, Ibarrarán et al. 2007), the Vulnerability-Resilience Indicators Model (VRIM) is used to integrate a set of proxy variables that determine the resilience of a region to climate change. Resilience, or the ability of a region to respond to climate variations and natural events that result from climate change, is given by its adaptation and coping capacity and its sensitivity. On the one hand, the sensitivity of a region to climate change is assessed, emphasizing its infrastructure, food security, water resources, and the health of the population and regional ecosystems. On the other hand, coping and adaptation capacity is based on the availability of human resources, economic capacity and environmental capacity.

  14. An Analog Earth Climate Model

    Science.gov (United States)

    Varekamp, J. C.

    2010-12-01

    The earth climate is broadly governed by the radiative power of the sun as well as the heat retention and convective cooling of the atmosphere. I have constructed an analog earth model for an undergraduate climate class that simulates mean climate using these three parameters. The ‘earth’ is a hollow, black, bronze sphere (4 cm diameter) mounted on a thin insulated rod, and illuminated by two opposite optic fibers, with light focused on the sphere by a set of lenses. The sphere is encased in a large double-walled aluminum cylinder (34 cm diameter by 26 cm high) with separate water cooling jackets at the top, bottom, and sides. The cylinder can be filled with a gas of choice at a variety of pressures or can be run in vacuum. The exterior is cladded with insulation, and the temperature of the sphere, atmosphere and walls is monitored with thermocouples. The temperature and waterflow of the three cooling jackets can be monitored to establish the energy output of the whole system; the energy input is the energy yield of the two optic fibers. A small IR transmissive lens at the top provides the opportunity to hook up the fiber of a hyper spectrometer to monitor the emission spectrum of the black ‘earth’ sphere. A pressure gauge and gas inlet-outlet system for flushing of the cell completes it. The heat yield of the cooling water at the top is the sum of the radiative and convective components, whereas the bottom jacket only carries off the radiative heat of the sphere. Undergraduate E&ES students at Wesleyan University have run experiments with dry air, pure CO2, N2 and Ar at 1 atmosphere, and a low vacuum run was accomplished to calibrate the energy input. For each experiment, the lights are flipped on, the temperature acquisition routine is activated, and the sphere starts to warm up until an equilibrium temperature has been reached. The lights are then flipped off and the cooling sequence towards ambient is registered. The energy input is constant for a given

  15. Observations that polar climate modelers use and want

    Science.gov (United States)

    Kay, J. E.; de Boer, G.; Hunke, E. C.; Bailey, D. A.; Schneider, D. P.

    2012-12-01

    Observations are essential for motivating and establishing improvement in the representation of polar processes within climate models. We believe that explicitly documenting the current methods used to develop and evaluate climate models with observations will help inform and improve collaborations between the observational and climate modeling communities. As such, we will present the current strategy of the Polar Climate Working Group (PCWG) to evaluate polar processes within Community Earth System Model (CESM) using observations. Our presentation will focus primarily on PCWG evaluation of atmospheric, sea ice, and surface oceanic processes. In the future, we hope to expand to include land surface, deep ocean, and biogeochemical observations. We hope our presentation, and a related working document developed by the PCWG (https://docs.google.com/document/d/1zt0xParsFeMYhlihfxVJhS3D5nEcKb8A41JH0G1Ic-E/edit) inspires new and useful interactions that lead to improved climate model representation of polar processes relevant to polar climate.

  16. COP21 climate negotiators' responses to climate model forecasts

    Science.gov (United States)

    Bosetti, Valentina; Weber, Elke; Berger, Loïc; Budescu, David V.; Liu, Ning; Tavoni, Massimo

    2017-02-01

    Policymakers involved in climate change negotiations are key users of climate science. It is therefore vital to understand how to communicate scientific information most effectively to this group. We tested how a unique sample of policymakers and negotiators at the Paris COP21 conference update their beliefs on year 2100 global mean temperature increases in response to a statistical summary of climate models' forecasts. We randomized the way information was provided across participants using three different formats similar to those used in Intergovernmental Panel on Climate Change reports. In spite of having received all available relevant scientific information, policymakers adopted such information very conservatively, assigning it less weight than their own prior beliefs. However, providing individual model estimates in addition to the statistical range was more effective in mitigating such inertia. The experiment was repeated with a population of European MBA students who, despite starting from similar priors, reported conditional probabilities closer to the provided models' forecasts than policymakers. There was also no effect of presentation format in the MBA sample. These results highlight the importance of testing visualization tools directly on the population of interest.

  17. Mixing parametrizations for ocean climate modelling

    Science.gov (United States)

    Gusev, Anatoly; Moshonkin, Sergey; Diansky, Nikolay; Zalesny, Vladimir

    2016-04-01

    The algorithm is presented of splitting the total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF), which is used to parameterize the viscosity and diffusion coefficients in ocean circulation models. The turbulence model equations are split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage, the following schemes are implemented: the explicit-implicit numerical scheme, analytical solution and the asymptotic behavior of the analytical solutions. The experiments were performed with different mixing parameterizations for the modelling of Arctic and the Atlantic climate decadal variability with the eddy-permitting circulation model INMOM (Institute of Numerical Mathematics Ocean Model) using vertical grid refinement in the zone of fully developed turbulence. The proposed model with the split equations for turbulence characteristics is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. Parameterizations with using the split turbulence model make it possible to obtain more adequate structure of temperature and salinity at decadal timescales, compared to the simpler Pacanowski-Philander (PP) turbulence parameterization. Parameterizations with using analytical solution or numerical scheme at the generation-dissipation step of the turbulence model leads to better representation of ocean climate than the faster parameterization using the asymptotic behavior of the analytical solution. At the same time, the computational efficiency left almost unchanged relative to the simple PP parameterization. Usage of PP parametrization in the circulation model leads to realistic simulation of density and circulation with violation of T,S-relationships. This error is majorly avoided with using the proposed parameterizations containing the split turbulence model

  18. Exploitation of Parallelism in Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Baer, F.; Tribbia, J.J.; Williamson, D.L.

    1999-03-01

    The US Department of Energy (DOE), through its CHAMMP initiative, hopes to develop the capability to make meaningful regional climate forecasts on time scales exceeding a decade, such capability to be based on numerical prediction type models. We propose research to contribute to each of the specific items enumerated in the CHAMMP announcement (Notice 91-3); i.e., to consider theoretical limits to prediction of climate and climate change on appropriate time scales, to develop new mathematical techniques to utilize massively parallel processors (MPP), to actually utilize MPPs as a research tool, and to develop improved representations of some processes essential to climate prediction. In particular, our goals are to: (1) Reconfigure the prediction equations such that the time iteration process can be compressed by use of MMP architecture, and to develop appropriate algorithms. (2) Develop local subgrid scale models which can provide time and space dependent parameterization for a state- of-the-art climate model to minimize the scale resolution necessary for a climate model, and to utilize MPP capability to simultaneously integrate those subgrid models and their statistics. (3) Capitalize on the MPP architecture to study the inherent ensemble nature of the climate problem. By careful choice of initial states, many realizations of the climate system can be determined concurrently and more realistic assessments of the climate prediction can be made in a realistic time frame. To explore these initiatives, we will exploit all available computing technology, and in particular MPP machines. We anticipate that significant improvements in modeling of climate on the decadal and longer time scales for regional space scales will result from our efforts.

  19. Validating predictions from climate envelope models

    Science.gov (United States)

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

    Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

  20. Global climate change model natural climate variation: Paleoclimate data base, probabilities and astronomic predictors

    Energy Technology Data Exchange (ETDEWEB)

    Kukla, G.; Gavin, J. [Columbia Univ., Palisades, NY (United States). Lamont-Doherty Geological Observatory

    1994-05-01

    This report was prepared at the Lamont-Doherty Geological Observatory of Columbia University at Palisades, New York, under subcontract to Pacific Northwest Laboratory it is a part of a larger project of global climate studies which supports site characterization work required for the selection of a potential high-level nuclear waste repository and forms part of the Performance Assessment Scientific Support (PASS) Program at PNL. The work under the PASS Program is currently focusing on the proposed site at Yucca Mountain, Nevada, and is under the overall direction of the Yucca Mountain Project Office US Department of Energy, Las Vegas, Nevada. The final results of the PNL project will provide input to global atmospheric models designed to test specific climate scenarios which will be used in the site specific modeling work of others. The primary purpose of the data bases compiled and of the astronomic predictive models is to aid in the estimation of the probabilities of future climate states. The results will be used by two other teams working on the global climate study under contract to PNL. They are located at and the University of Maine in Orono, Maine, and the Applied Research Corporation in College Station, Texas. This report presents the results of the third year`s work on the global climate change models and the data bases describing past climates.

  1. Global warming precipitation accumulation increases above the current-climate cutoff scale.

    Science.gov (United States)

    Neelin, J David; Sahany, Sandeep; Stechmann, Samuel N; Bernstein, Diana N

    2017-02-07

    Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.

  2. Global warming precipitation accumulation increases above the current-climate cutoff scale

    Science.gov (United States)

    Sahany, Sandeep; Stechmann, Samuel N.; Bernstein, Diana N.

    2017-01-01

    Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff. PMID:28115693

  3. Global warming precipitation accumulation increases above the current-climate cutoff scale

    Science.gov (United States)

    Neelin, J. David; Sahany, Sandeep; Stechmann, Samuel N.; Bernstein, Diana N.

    2017-02-01

    Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.

  4. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Jiang, J. H.

    2014-12-01

    We have developed a cloud-enabled web-service system that empowers physics-based, multi-variable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. We have developed a methodology to transform an existing science application code into a web service using a Python wrapper interface and Python web service frameworks. The web-service system, called Climate Model Diagnostic Analyzer (CMDA), currently supports (1) all the observational datasets from Obs4MIPs and a few ocean datasets from NOAA and Argo, which can serve as observation-based reference data for model evaluation, (2) many of CMIP5 model outputs covering a broad range of atmosphere, ocean, and land variables from the CMIP5 specific historical runs and AMIP runs, and (3) ECMWF reanalysis outputs for several environmental variables in order to supplement observational datasets. Analysis capabilities currently supported by CMDA are (1) the calculation of annual and seasonal means of physical variables, (2) the calculation of time evolution of the means in any specified geographical region, (3) the calculation of correlation between two variables, (4) the calculation of difference between two variables, and (5) the conditional sampling of one physical variable with respect to another variable. A web user interface is chosen for CMDA because it not only lowers the learning curve and removes the adoption barrier of the tool but also enables instantaneous use, avoiding the hassle of local software installation and environment incompatibility. CMDA will be used as an educational tool for the summer school organized by JPL's Center for Climate Science in 2014. In order to support 30+ simultaneous users during the school, we have deployed CMDA to the Amazon cloud environment. The cloud-enabled CMDA will provide each student with a virtual machine while the user interaction with the system will remain the same

  5. Land use effects on climate in China as simulated by a regional climate model

    Institute of Scientific and Technical Information of China (English)

    GAO XueJie; ZHANG DongFeng; CHEN ZhongXin; J.S.PAL; F. GIORGI

    2007-01-01

    A regional climate model (RegCM3)nested within ERA40 re-analyzed data is used to investigate the climate effects of land use change over China. Two 15-year simulations (1987-2001),one with current land use and the other with potential vegetation cover without human intervention, are conducted for a domain encompassing China. The climate impacts of land use change are assessed from the difference between the two simulations. Results show that the current land use (modified by anthropogenic activities) influences local climate as simulated by the model through the reinforcement of the monsoon circulation in both the winter and summer seasons and through changes of the surface energy budget. In winter. Land use change leads to reduced precipitation and decreased surface air temperature south of the Yangtze River, and increased precipitation north of the Yangtze River. Land use change significantly affects summer climate in southern China, yielding increased precipitation over the region, decreased temperature along the Yangtze River and increased temperature in the South China area (south-end of China).In summer, a reduction of precipitation over northern China and a temperature rise over Northwest China are also simulated. Both daily maximum and minimum temperatures are affected in the simulations. In general, the current land use in China leads to enhanced mean annual precipitation and decreased annual temperature over south China along with decreased precipitation over North China.

  6. Land use effects on climate in China as simulated by a regional climate model

    Institute of Scientific and Technical Information of China (English)

    J.S.PAL; F.GIORGI

    2007-01-01

    A regional climate model (RegCM3) nested within ERA40 re-analyzed data is used to investigate the climate effects of land use change over China. Two 15-year simulations (1987―2001), one with current land use and the other with potential vegetation cover without human intervention, are conducted for a domain encompassing China. The climate impacts of land use change are assessed from the difference between the two simulations. Results show that the current land use (modified by anthropogenic ac- tivities) influences local climate as simulated by the model through the reinforcement of the monsoon circulation in both the winter and summer seasons and through changes of the surface energy budget. In winter, land use change leads to reduced precipitation and decreased surface air temperature south of the Yangtze River, and increased precipitation north of the Yangtze River. Land use change signifi- cantly affects summer climate in southern China, yielding increased precipitation over the region, de- creased temperature along the Yangtze River and increased temperature in the South China area (south-end of China). In summer, a reduction of precipitation over northern China and a temperature rise over Northwest China are also simulated. Both daily maximum and minimum temperatures are affected in the simulations. In general, the current land use in China leads to enhanced mean annual precipitation and decreased annual temperature over south China along with decreased precipitation over North China.

  7. A Global Climate Model for Instruction.

    Science.gov (United States)

    Burt, James E.

    This paper describes a simple global climate model useful in a freshman or sophomore level course in climatology. There are three parts to the paper. The first part describes the model, which is a global model of surface air temperature averaged over latitude and longitude. Samples of the types of calculations performed in the model are provided.…

  8. A global map of suitability for coastal Vibrio cholerae under current and future climate conditions.

    Science.gov (United States)

    Escobar, Luis E; Ryan, Sadie J; Stewart-Ibarra, Anna M; Finkelstein, Julia L; King, Christine A; Qiao, Huijie; Polhemus, Mark E

    2015-09-01

    Vibrio cholerae is a globally distributed water-borne pathogen that causes severe diarrheal disease and mortality, with current outbreaks as part of the seventh pandemic. Further understanding of the role of environmental factors in potential pathogen distribution and corresponding V. cholerae disease transmission over time and space is urgently needed to target surveillance of cholera and other climate and water-sensitive diseases. We used an ecological niche model (ENM) to identify environmental variables associated with V. cholerae presence in marine environments, to project a global model of V. cholerae distribution in ocean waters under current and future climate scenarios. We generated an ENM using published reports of V. cholerae in seawater and freely available remotely sensed imagery. Models indicated that factors associated with V. cholerae presence included chlorophyll-a, pH, and sea surface temperature (SST), with chlorophyll-a demonstrating the greatest explanatory power from variables selected for model calibration. We identified specific geographic areas for potential V. cholerae distribution. Coastal Bangladesh, where cholera is endemic, was found to be environmentally similar to coastal areas in Latin America. In a conservative climate change scenario, we observed a predicted increase in areas with environmental conditions suitable for V. cholerae. Findings highlight the potential for vulnerability maps to inform cholera surveillance, early warning systems, and disease prevention and control.

  9. Modelling of anthropogenic and natural climate changes

    Energy Technology Data Exchange (ETDEWEB)

    Grassl, H.; Mikolajewicz, U.; Bakan, S. (Max Planck Institute of Meteorology, Hamburg (Germany))

    1993-06-01

    The delay of anthropogenic climate change caused by oceans and other slowly reacting climate system components forces us to numerical modeling as the basis of decisions. For three three-dimensional numerical examples, namely transient coupled ocean-atmosphere models for the additional greenhouse effect, internal ocean-atmosphere variability, and disturbance by soot particles from burning oil wells, the present-day status is described. From all anthropogenic impacts on the radiative balance, the contribution from trace gases is the most important.

  10. Regional and Global Climate Response to Anthropogenic SO2 Emissions from China in Three Climate Models

    Science.gov (United States)

    Kasoar, M.; Voulgarakis, Apostolos; Lamarque, Jean-Francois; Shindell, Drew T.; Bellouin, Nicholas; Collins, William J.; Faluvegi, Greg; Tsigaridis, Kostas

    2016-01-01

    We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against

  11. Regional and Global Climate Response to Anthropogenic SO2 Emissions from China in Three Climate Models

    Science.gov (United States)

    Kasoar, M.; Voulgarakis, Apostolos; Lamarque, Jean-Francois; Shindell, Drew T.; Bellouin, Nicholas; Collins, William J.; Faluvegi, Greg; Tsigaridis, Kostas

    2016-01-01

    We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against

  12. Potential effects of climate change on a marine invasion: The importance of current context

    Directory of Open Access Journals (Sweden)

    Isabelle M. CÔTÉ, Stephanie J. GREEN

    2012-02-01

    Full Text Available Species invasions threaten marine biodiversity globally. There is a concern that climate change is exacerbating this problem. Here, we examined some of the potential effects of warming water temperatures on the invasion of Western Atlantic habitats by a marine predator, the Indo-Pacific lionfish (Pterois volitans and P. miles. We focussed on two temperature-dependent aspects of lionfish life-history and behaviour: pelagic larval duration, because of its link to dispersal potential, and prey consumption rate, because it is an important determinant of the impacts of lionfish on native prey. Using models derived from fundamental metabolic theory, we predict that the length of time spent by lionfish in the plankton in early life should decrease with warming temperatures, with a concomitant reduction in potential dispersal distance. Although the uncertainty around change in dispersal distances is large, predicted reductions are, on average, more than an order of magnitude smaller than the current rate of range expansion of lionfish in the Caribbean. Nevertheless, because shorter pelagic larval duration has the potential to increase local retention of larvae, local lionfish management will become increasingly important under projected climate change. Increasing temperature is also expected to worsen the current imbalance between rates of prey consumption by lionfish and biomass production by their prey, leading to a heightened decline in native reef fish biomass. However, the magnitude of climate-induced decline is predicted to be minor compared to the effect of current rates of lionfish population increases (and hence overall prey consumption rates on invaded reefs. Placing the predicted effects of climate change in the current context thus reveals that, at least for the lionfish invasion, the threat is clear and present, rather than future [Current Zoology 58 (1: 1–8, 2012].

  13. Potential effects of climate change on a marine invasion: The importance of current context

    Institute of Scientific and Technical Information of China (English)

    Isabelle M. C(O)T(E); Stephanie J. GREEN

    2012-01-01

    Species invasions threaten marine biodiversity globally.There is a concern that climate change is exacerbating this problem.Here,we examined some of the potential effects of warming water temperatures on the invasion of Western Atlantic habitats by a marine predator,the lndo-Pacific lionfish (Pterois volitans and P.miles).We focussed on two temperature-dependent aspects of lionfish life-history and behaviour:pelagic larval duration,because of its link to dispersal potential,and prey consumption rate,because it is an important determinant of the impacts of lionfish on native prey.Using models derived from fundamental metabolic theory,we predict that the length of time spent by lionfish in the plankton in early life should decrease with warming temperatures,with a concomitant reduction in potential dispersal distance.Although the uncertainty around change in dispersal distances is large,predicted reductions are,on average,more than an order of magnitude smaller than the current rate of range expansion of lionfish in the Caribbean.Nevertheless,because shorter pelagic larval duration has the potential to increase local retention of larvae,local lionfish management will become increasingly important under projected climate change.Increasing temperature is also expected to worsen the current imbalance between rates of prey consumption by lionfish and biomass production by their prey,leading to a heightened decline in native reef fish biomass.However,the magnitude of climate-induced decline is predicted to be minor compared to the effect of current rates of lionfish population increases (and hence overall prey consumption rates) on invaded reefs.Placing the predicted effects of climate change in the current context thus reveals that,at least for the lionfish invasion,the threat is clear and present,rather than future [Current Zoology 58 (1):1-8,2012].

  14. Climate change and decadal shifts in the phenology of larval fishes in the California Current ecosystem.

    Science.gov (United States)

    Asch, Rebecca G

    2015-07-28

    Climate change has prompted an earlier arrival of spring in numerous ecosystems. It is uncertain whether such changes are occurring in Eastern Boundary Current Upwelling ecosystems, because these regions are subject to natural decadal climate variability, and regional climate models predict seasonal delays in upwelling. To answer this question, the phenology of 43 species of larval fishes was investigated between 1951 and 2008 off southern California. Ordination of the fish community showed earlier phenological progression in more recent years. Thirty-nine percent of seasonal peaks in larval abundance occurred earlier in the year, whereas 18% were delayed. The species whose phenology became earlier were characterized by an offshore, pelagic distribution, whereas species with delayed phenology were more likely to reside in coastal, demersal habitats. Phenological changes were more closely associated with a trend toward earlier warming of surface waters rather than decadal climate cycles, such as the Pacific Decadal Oscillation and North Pacific Gyre Oscillation. Species with long-term advances and delays in phenology reacted similarly to warming at the interannual time scale as demonstrated by responses to the El Niño Southern Oscillation. The trend toward earlier spawning was correlated with changes in sea surface temperature (SST) and mesozooplankton displacement volume, but not coastal upwelling. SST and upwelling were correlated with delays in fish phenology. For species with 20th century advances in phenology, future projections indicate that current trends will continue unabated. The fate of species with delayed phenology is less clear due to differences between Intergovernmental Panel on Climate Change models in projected upwelling trends.

  15. Climate change and decadal shifts in the phenology of larval fishes in the California Current ecosystem

    Science.gov (United States)

    Asch, Rebecca G.

    2015-01-01

    Climate change has prompted an earlier arrival of spring in numerous ecosystems. It is uncertain whether such changes are occurring in Eastern Boundary Current Upwelling ecosystems, because these regions are subject to natural decadal climate variability, and regional climate models predict seasonal delays in upwelling. To answer this question, the phenology of 43 species of larval fishes was investigated between 1951 and 2008 off southern California. Ordination of the fish community showed earlier phenological progression in more recent years. Thirty-nine percent of seasonal peaks in larval abundance occurred earlier in the year, whereas 18% were delayed. The species whose phenology became earlier were characterized by an offshore, pelagic distribution, whereas species with delayed phenology were more likely to reside in coastal, demersal habitats. Phenological changes were more closely associated with a trend toward earlier warming of surface waters rather than decadal climate cycles, such as the Pacific Decadal Oscillation and North Pacific Gyre Oscillation. Species with long-term advances and delays in phenology reacted similarly to warming at the interannual time scale as demonstrated by responses to the El Niño Southern Oscillation. The trend toward earlier spawning was correlated with changes in sea surface temperature (SST) and mesozooplankton displacement volume, but not coastal upwelling. SST and upwelling were correlated with delays in fish phenology. For species with 20th century advances in phenology, future projections indicate that current trends will continue unabated. The fate of species with delayed phenology is less clear due to differences between Intergovernmental Panel on Climate Change models in projected upwelling trends. PMID:26159416

  16. Climate Forcings and Climate Sensitivities Diagnosed from Coupled Climate Model Integrations

    Energy Technology Data Exchange (ETDEWEB)

    Forster, P M A F; Taylor, K E

    2006-07-25

    A simple technique is proposed for calculating global mean climate forcing from transient integrations of coupled Atmosphere Ocean General Circulation Models (AOGCMs). This 'climate forcing' differs from the conventionally defined radiative forcing as it includes semi-direct effects that account for certain short timescale responses in the troposphere. Firstly, we calculate a climate feedback term from reported values of 2 x CO{sub 2} radiative forcing and surface temperature time series from 70-year simulations by twenty AOGCMs. In these simulations carbon dioxide is increased by 1%/year. The derived climate feedback agrees well with values that we diagnose from equilibrium climate change experiments of slab-ocean versions of the same models. These climate feedback terms are associated with the fast, quasi-linear response of lapse rate, clouds, water vapor and albedo to global surface temperature changes. The importance of the feedbacks is gauged by their impact on the radiative fluxes at the top of the atmosphere. We find partial compensation between longwave and shortwave feedback terms that lessens the inter-model differences in the equilibrium climate sensitivity. There is also some indication that the AOGCMs overestimate the strength of the positive longwave feedback. These feedback terms are then used to infer the shortwave and longwave time series of climate forcing in 20th and 21st Century simulations in the AOGCMs. We validate the technique using conventionally calculated forcing time series from four AOGCMs. In these AOGCMs the shortwave and longwave climate forcings we diagnose agree with the conventional forcing time series within {approx}10%. The shortwave forcing time series exhibit order of magnitude variations between the AOGCMs, differences likely related to how both natural forcings and/or anthropogenic aerosol effects are included. There are also factor of two differences in the longwave climate forcing time series, which may indicate

  17. Interactive, process-oriented climate modeling with CLIMLAB

    Science.gov (United States)

    Rose, B. E. J.

    2016-12-01

    Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The Jupyter Notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields.

  18. Assessing Lebanon's wildfire potential in association with current and future climatic conditions

    Science.gov (United States)

    George H. Mitri; Mireille G. Jazi; David McWethy

    2015-01-01

    The increasing occurrence and extent of large-scale wildfires in the Mediterranean have been linked to extended periods of warm and dry weather. We set out to assess Lebanon's wildfire potential in association with current and future climatic conditions. The Keetch-Byram Drought Index (KBDI) was the primary climate variable used in our evaluation of climate/fire...

  19. Carbon and water cycling in a Bornean tropical rainforest under current and future climate scenarios

    Science.gov (United States)

    Kumagai, Tomo'omi; Katul, Gabriel G.; Porporato, Amilcare; Saitoh, Taku M.; Ohashi, Mizue; Ichie, Tomoaki; Suzuki, Masakazu

    2004-12-01

    We examined how the projected increase in atmospheric CO 2 and concomitant shifts in air temperature and precipitation affect water and carbon fluxes in an Asian tropical rainforest, using a combination of field measurements, simplified hydrological and carbon models, and Global Climate Model (GCM) projections. The model links the canopy photosynthetic flux with transpiration via a bulk canopy conductance and semi-empirical models of intercellular CO 2 concentration, with the transpiration rate determined from a hydrologic balance model. The primary forcing to the hydrologic model are current and projected rainfall statistics. A main novelty in this analysis is that the effect of increased air temperature on vapor pressure deficit ( D) and the effects of shifts in precipitation statistics on net radiation are explicitly considered. The model is validated against field measurements conducted in a tropical rainforest in Sarawak, Malaysia under current climate conditions. On the basis of this model and projected shifts in climatic statistics by GCM, we compute the probability distribution of soil moisture and other hydrologic fluxes. Regardless of projected and computed shifts in soil moisture, radiation and mean air temperature, transpiration was not appreciably altered. Despite increases in atmospheric CO 2 concentration ( Ca) and unchanged transpiration, canopy photosynthesis does not significantly increase if Ci/ Ca is assumed constant independent of D (where Ci is the bulk canopy intercellular CO 2 concentration). However, photosynthesis increased by a factor of 1.5 if Ci/ Ca decreased linearly with D as derived from Leuning stomatal conductance formulation [R. Leuning. Plant Cell Environ 1995;18:339-55]. How elevated atmospheric CO 2 alters the relationship between Ci/ Ca and D needs to be further investigated under elevated atmospheric CO 2 given its consequence on photosynthesis (and concomitant carbon sink) projections.

  20. Paladin Enterprises: Monolithic particle physics models global climate.

    CERN Multimedia

    2002-01-01

    Paladin Enterprises presents a monolithic particle model of the universe which will be used by them to build an economical fusion energy system. The model is an extension of the work done by James Clerk Maxwell. Essentially, gravity is unified with electro-magnetic forces and shown to be a product of a closed loop current system, i.e. a particle - monolithic or sub atomic. This discovery explains rapid global climate changes which are evident in the geological record and also provides an explanation for recent changes in the global climate.

  1. Assessing climate change impact by integrated hydrological modelling

    Science.gov (United States)

    Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

    2013-04-01

    showed some unexpected results, where climate models predicting the largest increase in net precipitation did not result in the largest increase in groundwater heads. This was found to be the result of different initial conditions (1990 - 2010) for the various climate models. In some areas a combination of a high initial groundwater head and an increase in precipitation towards 2021 - 2050 resulted in a groundwater head raise that reached the drainage or the surface water system. This will increase the exchange from the groundwater to the surface water system, but reduce the raise in groundwater heads. An alternative climate model, with a lower initial head can thus predict a higher increase in the groundwater head, although the increase in precipitation is lower. This illustrates an extra dimension in the uncertainty assessment, namely the climate models capability of simulating the current climatic conditions in a way that can reproduce the observed hydrological response. Højberg, AL, Troldborg, L, Stisen, S, et al. (2012) Stakeholder driven update and improvement of a national water resources model - http://www.sciencedirect.com/science/article/pii/S1364815212002423 Seaby, LP, Refsgaard, JC, Sonnenborg, TO, et al. (2012) Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections (submitted) Journal of Hydrology Stisen, S, Højberg, AL, Troldborg, L et al., (2012): On the importance of appropriate rain-gauge catch correction for hydrological modelling at mid to high latitudes - http://www.hydrol-earth-syst-sci.net/16/4157/2012/

  2. Modeling Past Abrupt Climate Changes

    DEFF Research Database (Denmark)

    Marchionne, Arianna

    According to Milankovitch theory of ice ages, glacial cycles are driven by variations in the insolation, i.e. the amount of the incoming solar radiation reaching the Earth. These variations are associated with variations of the Earth's orbit. Many attempts have been made to identify the in uence...... to the orbitally driven variations in insolation. However, the relationship is far from linear, and insolation alone can not explain the climatic variability seen in the records. In the rst part of this thesis, we discuss the possible dynamical mechanisms for linking the frequencies observed in the records...

  3. A climate robust integrated modelling framework for regional impact assessment of climate change

    Science.gov (United States)

    Janssen, Gijs; Bakker, Alexander; van Ek, Remco; Groot, Annemarie; Kroes, Joop; Kuiper, Marijn; Schipper, Peter; van Walsum, Paul; Wamelink, Wieger; Mol, Janet

    2013-04-01

    Decision making towards climate proofing the water management of regional catchments can benefit greatly from the availability of a climate robust integrated modelling framework, capable of a consistent assessment of climate change impacts on the various interests present in the catchments. In the Netherlands, much effort has been devoted to developing state-of-the-art regional dynamic groundwater models with a very high spatial resolution (25x25 m2). Still, these models are not completely satisfactory to decision makers because the modelling concepts do not take into account feedbacks between meteorology, vegetation/crop growth, and hydrology. This introduces uncertainties in forecasting the effects of climate change on groundwater, surface water, agricultural yields, and development of groundwater dependent terrestrial ecosystems. These uncertainties add to the uncertainties about the predictions on climate change itself. In order to create an integrated, climate robust modelling framework, we coupled existing model codes on hydrology, agriculture and nature that are currently in use at the different research institutes in the Netherlands. The modelling framework consists of the model codes MODFLOW (groundwater flow), MetaSWAP (vadose zone), WOFOST (crop growth), SMART2-SUMO2 (soil-vegetation) and NTM3 (nature valuation). MODFLOW, MetaSWAP and WOFOST are coupled online (i.e. exchange information on time step basis). Thus, changes in meteorology and CO2-concentrations affect crop growth and feedbacks between crop growth, vadose zone water movement and groundwater recharge are accounted for. The model chain WOFOST-MetaSWAP-MODFLOW generates hydrological input for the ecological prediction model combination SMART2-SUMO2-NTM3. The modelling framework was used to support the regional water management decision making process in the 267 km2 Baakse Beek-Veengoot catchment in the east of the Netherlands. Computations were performed for regionalized 30-year climate change

  4. Climatic Effects of Contrail Cirrus over the Western United States: A Regional Climate Model Investigation

    Science.gov (United States)

    Liou, K.; Ou, S. S.; Kim, J.; Gu, Y.; Yang, P.; Friedl, R. R.

    2009-12-01

    We investigate the impact of contrails and contrail induced cirrus clouds (CICC) on regional energy and water cycles over the Western United States (WUS), a region of both heavy air traffic and high climate sensitivity. Mountain snowpack in the WUS is a major source of warm-season water supply for Southern California and is highly sensitive to seasonal insolation variation, which can be significantly affected by the frequent presence of contrails/CICC. A regional climate model with an 18-km horizontal resolution based on the Weather Research and Forecast (WRF) model has been developed, which includes improved parameterizations of the optical properties of ice clouds and contrails in the Fu-Liou broadband radiative transfer model. The large-scale forcing data for driving regional climate simulations has been obtained from the NCEP/DOE re-analysis-2. We conduct multiple-year perpetual-spring climate runs to simulate the current climate conditions of the WUS and to investigate the climatic impact of contrails/CICC on radiative forcing, surface temperature, precipitation, and snowpack coverage. As a first approximation, we develop a linear correlation between available aviation emission data and contrail cover using the existing GCM results as proxy. Additionally, we use the ice crystal size spectrum and shape determined from the Subsonic Aircraft Contrail and Cloud Effects Special Study (SUCCESS) for calculations of the optical properties of contrails/CICC for input to the regional climate model. Preliminary simulation results and uncertainty analysis are presented in association with the effects of contrails/CICC cover and ice crystal size/shape on surface radiative forcing, surface temperature, and snow cover over the WUS in spring.

  5. A review on regional convection permitting climate modeling

    Science.gov (United States)

    van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin

    2016-04-01

    With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using CPMs to study climate change it is necessary that these deficiencies are addressed in future research. Coordinated

  6. Climate Change and Food Security in Tanzania: Analysis of Current ...

    African Journals Online (AJOL)

    ... economic and social effects. Keywords: climate change, food security, agriculture, adaptation, Tanzania ... According to the IPCC (2008) report, global warming is already .... health in the southern highlands of Tanzania. He concluded that ...

  7. Climate model uncertainty vs. conceptual geological uncertainty in hydrological modeling

    Directory of Open Access Journals (Sweden)

    T. O. Sonnenborg

    2015-04-01

    Full Text Available Projections of climate change impact are associated with a cascade of uncertainties including CO2 emission scenario, climate model, downscaling and impact model. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM-RCM model combination (from the ENSEMBLES project forced by the same CO2 scenario (A1B. The changes from the reference period (1991–2010 to the future period (2081–2100 in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty on the climate models is more important for groundwater hydraulic heads and stream flow.

  8. Potential climatic impacts of vegetation change: A regional modeling study

    Science.gov (United States)

    Copeland, J.H.; Pielke, R.A.; Kittel, T.G.F.

    1996-01-01

    The human species has been modifying the landscape long before the development of modern agrarian techniques. Much of the land area of the conterminous United States is currently used for agricultural production. In certain regions this change in vegetative cover from its natural state may have led to local climatic change. A regional climate version of the Colorado State University Regional Atmospheric Modeling System was used to assess the impact of a natural versus current vegetation distribution on the weather and climate of July 1989. The results indicate that coherent regions of substantial changes, of both positive and negative sign, in screen height temperature, humidity, wind speed, and precipitation are a possible consequence of land use change throughout the United States. The simulated changes in the screen height quantities were closely related to changes in the vegetation parameters of albedo, roughness length, leaf area index, and fractional coverage. Copyright 1996 by the American Geophysical Union.

  9. The Contribution of Soils to North America's Current and Future Climate

    Science.gov (United States)

    Mayes, M. A.; Reed, S.; Thornton, P. E.; Lajtha, K.; Bailey, V. L.; Shrestha, G.; Jastrow, J. D.; Torn, M. S.

    2015-12-01

    This presentation will cover key aspects of the terrestrial soil carbon cycle in North America and the US for the upcoming State of the Carbon Cycle Report (SOCCRII). SOCCRII seeks to summarize how natural processes and human interactions affect the global carbon cycle, how socio-economic trends affect greenhouse gas concentrations in the atmosphere, and how ecosystems are influenced by and respond to greenhouse gas emissions, management decisions, and concomitant climate effects. Here, we will summarize the contemporary understanding of carbon stocks, fluxes, and drivers in the soil ecosystem compartment. We will highlight recent advances in modeling the magnitude of soil carbon stocks and fluxes, as well as the importance of remaining uncertainties in predicting soil carbon cycling and its relationship with climate. Attention will be given to the role of uncertainties in predicting future fluxes from soils, and how those uncertainties vary by region and ecosystem. We will also address how climate feedbacks and management decisions can enhance or minimize future climatic effects based on current understanding and observations, and will highlight select research needs to improve our understanding of the balance of carbon in soils in North America.

  10. Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

    Science.gov (United States)

    Romanach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.

    2014-01-01

    Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

  11. Climate change in Central America and Mexico: regional climate model validation and climate change projections

    Science.gov (United States)

    Karmalkar, Ambarish V.; Bradley, Raymond S.; Diaz, Henry F.

    2011-08-01

    Central America has high biodiversity, it harbors high-value ecosystems and it's important to provide regional climate change information to assist in adaptation and mitigation work in the region. Here we study climate change projections for Central America and Mexico using a regional climate model. The model evaluation shows its success in simulating spatial and temporal variability of temperature and precipitation and also in capturing regional climate features such as the bimodal annual cycle of precipitation and the Caribbean low-level jet. A variety of climate regimes within the model domain are also better identified in the regional model simulation due to improved resolution of topographic features. Although, the model suffers from large precipitation biases, it shows improvements over the coarse-resolution driving model in simulating precipitation amounts. The model shows a dry bias in the wet season and a wet bias in the dry season suggesting that it's unable to capture the full range of precipitation variability. Projected warming under the A2 scenario is higher in the wet season than that in the dry season with the Yucatan Peninsula experiencing highest warming. A large reduction in precipitation in the wet season is projected for the region, whereas parts of Central America that receive a considerable amount of moisture in the form of orographic precipitation show significant decreases in precipitation in the dry season. Projected climatic changes can have detrimental impacts on biodiversity as they are spatially similar, but far greater in magnitude, than those observed during the El Niño events in recent decades that adversely affected species in the region.

  12. Climate change in Central America and Mexico: regional climate model validation and climate change projections

    Energy Technology Data Exchange (ETDEWEB)

    Karmalkar, Ambarish V. [University of Oxford, School of Geography and the Environment, Oxford (United Kingdom); Bradley, Raymond S. [University of Massachusetts, Department of Geosciences, Amherst, MA (United States); Diaz, Henry F. [NOAA/ESRL/CIRES, Boulder, CO (United States)

    2011-08-15

    Central America has high biodiversity, it harbors high-value ecosystems and it's important to provide regional climate change information to assist in adaptation and mitigation work in the region. Here we study climate change projections for Central America and Mexico using a regional climate model. The model evaluation shows its success in simulating spatial and temporal variability of temperature and precipitation and also in capturing regional climate features such as the bimodal annual cycle of precipitation and the Caribbean low-level jet. A variety of climate regimes within the model domain are also better identified in the regional model simulation due to improved resolution of topographic features. Although, the model suffers from large precipitation biases, it shows improvements over the coarse-resolution driving model in simulating precipitation amounts. The model shows a dry bias in the wet season and a wet bias in the dry season suggesting that it's unable to capture the full range of precipitation variability. Projected warming under the A2 scenario is higher in the wet season than that in the dry season with the Yucatan Peninsula experiencing highest warming. A large reduction in precipitation in the wet season is projected for the region, whereas parts of Central America that receive a considerable amount of moisture in the form of orographic precipitation show significant decreases in precipitation in the dry season. Projected climatic changes can have detrimental impacts on biodiversity as they are spatially similar, but far greater in magnitude, than those observed during the El Nino events in recent decades that adversely affected species in the region. (orig.)

  13. Modeling of Soybean under Present and Future Climates in Mozambique

    Directory of Open Access Journals (Sweden)

    Manuel António Dina Talacuece

    2016-06-01

    Full Text Available This study aims to calibrate and validate the generic crop model (CROPGRO-Soybean and estimate the soybean yield, considering simulations with different sowing times for the current period (1990–2013 and future climate scenario (2014–2030. The database used came from observed data, nine climate models of CORDEX (Coordinated Regional climate Downscaling Experiment-Africa framework and MERRA (Modern Era Retrospective-Analysis for Research and Applications reanalysis. The calibration and validation data for the model were acquired in field experiments, carried out in the 2009/2010 and 2010/2011 growing seasons in the experimental area of the International Institute of Tropical Agriculture (IITA in Angónia, Mozambique. The yield of two soybean cultivars: Tgx 1740-2F and Tgx 1908-8F was evaluated in the experiments and modeled for two distinct CO2 concentrations. Our model simulation results indicate that the fertilization effect leads to yield gains for both cultivars, ranging from 11.4% (Tgx 1908-8F to 15% (Tgx 1740-2Fm when compared to the performance of those cultivars under current CO2 atmospheric concentration. Moreover, our results show that MERRA, the RegCM4 (Regional Climatic Model version 4 and CNRM-CM5 (Centre National de Recherches Météorologiques – Climatic Model version 5 models provided more accurate estimates of yield, while others models underestimate yield as compared to observations, a fact that was demonstrated to be related to the model’s capability of reproducing the precipitation and the surface radiation amount.

  14. Modelling climate impacts on the aviation sector

    Science.gov (United States)

    Williams, Paul

    2017-04-01

    The climate is changing, not just where we live at ground level, but also where we fly at 35,000 feet. We have long known that air travel contributes to climate change through its emissions. However, we have only recently become aware that climate change could have significant consequences for air travel. This presentation will give an overview of the possible impacts of climate change on the aviation sector. The presentation will describe how the impacts are modelled and how their social and economic costs are estimated. The impacts are discussed in the International Civil Aviation Organization's (ICAO's) latest Environmental Report (Puempel and Williams 2016). Some of the possible impacts are as follows. Rising sea levels and storm surges threaten coastal airports, such as La Guardia in New York, which was flooded by the remnants of Hurricane Sandy in 2012. Warmer air at ground level reduces the lift force and makes it more difficult for planes to take-off (Coffel and Horton 2015). More extreme weather may cause flight disruptions and delays. Clear-air turbulence is expected to become up to 40% stronger and twice as common (Williams and Joshi 2013). Transatlantic flights may collectively be airborne for an extra 2,000 hours each year because of changes to the jet stream, burning an extra 7.2 million gallons of jet fuel at a cost of US 22 million, and emitting an extra 70 million kg of carbon dioxide (Williams 2016). These modelled impacts provide further evidence of the two-way interaction between aviation and climate change. References Coffel E and Horton R (2015) Climate change and the impact of extreme temperatures on aviation. Weather, Climate, and Society, 7, 94-102. http://dx.doi.org/10.1175/WCAS-D-14-00026.1 Puempel H and Williams PD (2016) The impacts of climate change on aviation: Scientific challenges and adaptation pathways. ICAO Environmental Report 2016: On Board A Sustainable Future, pp 205-207. http

  15. Decadal application of WRF/chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 2: Current vs. future simulations

    Science.gov (United States)

    Yahya, Khairunnisa; Campbell, Patrick; Zhang, Yang

    2017-03-01

    Following a comprehensive model evaluation, this Part II paper presents projected changes in future (2046-2055) climate, air quality, and their interactions under the RCP4.5 and RCP8.5 scenarios using the Weather, Research and Forecasting model with Chemistry (WRF/Chem). In general, both WRF/Chem RCP4.5 and RCP8.5 simulations predict similar increases on average (∼2 °C) for 2-m temperature (T2) but different spatial distributions of the projected changes in T2, 2-m relative humidity, 10-m wind speed, precipitation, and planetary boundary layer height, due to differences in the spatial distributions of projected emissions, and their feedbacks into climate. Future O3 mixing ratios will decrease for most parts of the U.S. under the RCP4.5 scenario but increase for all areas under the RCP8.5 scenario due to higher projected temperature, greenhouse gas concentrations and biogenic volatile organic compounds (VOC) emissions, higher O3 values for boundary conditions, and disbenefit of NOx reduction and decreased NO titration over VOC-limited O3 chemistry regions. Future PM2.5 concentrations will decrease for both RCP4.5 and RCP8.5 scenarios with different trends in projected concentrations of individual PM species. Total cloud amounts decrease under both scenarios in the future due to decreases in PM and cloud droplet number concentration thus increased radiation. Those results illustrate the impacts of carbon policies with different degrees of emission reductions on future climate and air quality. The WRF/Chem and WRF simulations show different spatial patterns for projected changes in T2 for future decade, indicating different impacts of prognostic and prescribed gas/aerosol concentrations, respectively, on climate change.

  16. The Current Policy of the European Parliament on Climate Change

    Directory of Open Access Journals (Sweden)

    TODEA Al.

    2010-12-01

    Full Text Available Approaches are presented to Parliament in order to take measures on climate change through suitable laws thataims to reduce bad habits that lead to greenhouse gas emissions, in order to reduce them by 20%, increase energyefficiency by 20% and use of resources renewable energy reaching 20% of all energy - with the deadline until 2020.

  17. Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment

    Science.gov (United States)

    Skiles, J. W.

    1995-01-01

    Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of particles, thermodynamics and radiation, and continuity of water vapor. Hydrology and heat balance are usually included for continents, and sea ice and heat balance are included for oceans. The current issue of this journal contains a paper by Van Blarcum et al. (1995) that predicts runoff from nine high-latitude rivers under a doubled CO2 atmosphere. The paper is important since river flow is an indicator variable for climate change. The authors show that precipitation will increase under the imposed perturbations and that owing to higher temperatures earlier in the year that cause the snow pack to melt sooner, runoff will also increase. They base their simulations on output from a GCM coupled with an interesting water routing scheme they have devised. Climate change models have been linked to other models to predict deforestation.

  18. Importance of Sea Ice for Validating Global Climate Models

    Science.gov (United States)

    Geiger, Cathleen A.

    1997-01-01

    Reproduction of current day large-scale physical features and processes is a critical test of global climate model performance. Without this benchmark, prognoses of future climate conditions are at best speculation. A fundamental question relevant to this issue is, which processes and observations are both robust and sensitive enough to be used for model validation and furthermore are they also indicators of the problem at hand? In the case of global climate, one of the problems at hand is to distinguish between anthropogenic and naturally occuring climate responses. The polar regions provide an excellent testing ground to examine this problem because few humans make their livelihood there, such that anthropogenic influences in the polar regions usually spawn from global redistribution of a source originating elsewhere. Concomitantly, polar regions are one of the few places where responses to climate are non-anthropogenic. Thus, if an anthropogenic effect has reached the polar regions (e.g. the case of upper atmospheric ozone sensitivity to CFCs), it has most likely had an impact globally but is more difficult to sort out from local effects in areas where anthropogenic activity is high. Within this context, sea ice has served as both a monitoring platform and sensitivity parameter of polar climate response since the time of Fridtjof Nansen. Sea ice resides in the polar regions at the air-sea interface such that changes in either the global atmospheric or oceanic circulation set up complex non-linear responses in sea ice which are uniquely determined. Sea ice currently covers a maximum of about 7% of the earth's surface but was completely absent during the Jurassic Period and far more extensive during the various ice ages. It is also geophysically very thin (typically global climate.

  19. Standard controlled vocabulary for climate models

    Science.gov (United States)

    Moine, Marie-Pierre; Pascoe, Charlotte; Guilyardi, Eric; Ford, Rupert

    2010-05-01

    The scope of climate modeling has grown tremendously in the last 10 years, resulting in a large variety of climate models, increasing complexity with more physical or chemical components and huge volumes of data sets (simulation outputs). While significant efforts to standardise the associated metadata (i.e. data describing data and models) have already been made in recent projects (e.g. CF standard names for CMIP3), detailed standards documentation of the models and experiments that created this data is still lacking. The EU METAFOR Project (http://metaforclimate.eu) is specifically addressing this issue by creating new metadata schemas in cooperation with existing standards in Earth System Modeling (Curator, GridSpec, CF convention, NumSim, etc.). Descriptions of climate simulations, of the data they produce, and of the numerical models used to perform these simulations are all within the scope of METAFOR and these descriptions are assembled in a common information model (the CIM). Of particular note is the metadata for numerical models that is found in the CIM. This paper presents the controlled vocabulary (CV) that has been collected by METAFOR to describe (in a common manner) the components of the numerical models developed by the different modeling centres. This vocabulary is used in the model part of the web-based questionnaire that METAFOR has developed in support of the upcoming IPCC exercise (the CMIP5 questionnaire). The methods to (1) establish standards for this vocabulary via interactions with climate scientists, (2) utilise the vocabulary in the web-based questionnaire and (3) process the vocabulary for ingestion in the Earth System Grid (ESG) portal, are described. Governance aspects of this new controlled vocabulary are also addressed.

  20. A New Method of Comparing Forcing Agents in Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Kravitz, Benjamin S.; MacMartin, Douglas; Rasch, Philip J.; Jarvis, Andrew

    2015-10-14

    We describe a new method of comparing different climate forcing agents (e.g., CO2, CH4, and solar irradiance) that avoids many of the ambiguities introduced by temperature-related climate feedbacks. This is achieved by introducing an explicit feedback loop external to the climate model that adjusts one forcing agent to balance another while keeping global mean surface temperature constant. Compared to current approaches, this method has two main advantages: (i) the need to define radiative forcing is bypassed and (ii) by maintaining roughly constant global mean temperature, the effects of state dependence on internal feedback strengths are minimized. We demonstrate this approach for several different forcing agents and derive the relationships between these forcing agents in two climate models; comparisons between forcing agents are highly linear in concordance with predicted functional forms. Transitivity of the relationships between the forcing agents appears to hold within a wide range of forcing. The relationships between the forcing agents obtained from this method are consistent across both models but differ from relationships that would be obtained from calculations of radiative forcing, highlighting the importance of controlling for surface temperature feedback effects when separating radiative forcing and climate response.

  1. Global Climate Models of the Terrestrial Planets

    Science.gov (United States)

    Forget, F.; Lebonnois, S.

    On the basis of the global climate models (GCMs) originally developed for Earth, several teams around the world have been able to develop GCMs for the atmospheres of the other terrestrial bodies in our solar system: Venus, Mars, Titan, Triton, and Pluto. In spite of the apparent complexity of climate systems and meteorology, GCMs are based on a limited number of equations. In practice, relatively complete climate simulators can be developed by combining a few components such as a dynamical core, a radiative transfer solver, a parameterization of turbulence and convection, a thermal ground model, and a volatile phase change code, possibly completed by a few specific schemes. It can be shown that many of these GCM components are "universal" so that we can envisage building realistic climate models for any kind of terrestrial planets and atmospheres that we can imagine. Such a tool is useful for conducting scientific investigations on the possible climates of terrestrial extrasolar planets, or to study past environments in the solar system. The ambition behind the development of GCMs is high: The ultimate goal is to build numerical simulators based only on universal physical or chemical equations, yet able to reproduce or predict all the available observations on a given planet, without any ad hoc forcing. In other words, we aim to virtually create in our computers planets that "behave" exactly like the actual planets themselves. In reality, of course, nature is always more complex than expected, but we learn a lot in the process. In this chapter we detail some lessons learned in the solar system: In many cases, GCMs work. They have been able to simulate many aspects of planetary climates without difficulty. In some cases, however, problems have been encountered, sometimes simply because a key process has been forgotten in the model or is not yet correctly parameterized, but also because sometimes the climate regime seems to be result of a subtle balance between

  2. Global comparison of three greenhouse climate models

    NARCIS (Netherlands)

    Bavel, van C.H.M.; Takakura, T.; Bot, G.P.A.

    1985-01-01

    Three dynamic simulation models for calculating the greenhouse climate and its energy requirements for both heating and cooling were compared by making detailed computations for each of seven sets of data. The data sets ranged from a cold winter day, requiring heating, to a hot summer day, requiring

  3. Modelling the wind climate of Ireland

    DEFF Research Database (Denmark)

    Frank, H.P.; Landberg, L.

    1997-01-01

    The wind climate of Ireland has been calculated using the Karlsruhe Atmospheric Mesoscale Model KAMM. The climatology is represented by 65 frequency classes of geostrophic wind that were selected as equiangular direction sectors and speed intervals with equal frequency in a sector. The results...

  4. Climate impact of transportation A model comparison

    NARCIS (Netherlands)

    Girod, B.; Vuuren, D.P. van; Grahn, M.; Kitous, A.; Kim, S.H.; Kyle, P.

    2013-01-01

    Transportation contributes to a significant and rising share of global energy use and GHG emissions. Therefore modeling future travel demand, its fuel use, and resulting CO2 emission is highly relevant for climate change mitigation. In this study we compare the baseline projections for global

  5. Climate impact of transportation A model comparison

    NARCIS (Netherlands)

    Girod, B.; Vuuren, D.P. van; Grahn, M.; Kitous, A.; Kim, S.H.; Kyle, P.

    2013-01-01

    Transportation contributes to a significant and rising share of global energy use and GHG emissions. Therefore modeling future travel demand, its fuel use, and resulting CO2 emission is highly relevant for climate change mitigation. In this study we compare the baseline projections for global servic

  6. Building an advanced climate model: Program plan for the CHAMMP (Computer Hardware, Advanced Mathematics, and Model Physics) Climate Modeling Program

    Energy Technology Data Exchange (ETDEWEB)

    1990-12-01

    The issue of global warming and related climatic changes from increasing concentrations of greenhouse gases in the atmosphere has received prominent attention during the past few years. The Computer Hardware, Advanced Mathematics, and Model Physics (CHAMMP) Climate Modeling Program is designed to contribute directly to this rapid improvement. The goal of the CHAMMP Climate Modeling Program is to develop, verify, and apply a new generation of climate models within a coordinated framework that incorporates the best available scientific and numerical approaches to represent physical, biogeochemical, and ecological processes, that fully utilizes the hardware and software capabilities of new computer architectures, that probes the limits of climate predictability, and finally that can be used to address the challenging problem of understanding the greenhouse climate issue through the ability of the models to simulate time-dependent climatic changes over extended times and with regional resolution.

  7. Climate change in the Himalayas : current state of knowledge

    OpenAIRE

    Gautam, Mahesh R.; Timilsina, Govinda R.; Acharya, Kumud

    2013-01-01

    This paper reviews the literature on the potential biophysical and economic impacts of climate change in the Himalayas. Existing observations indicate that the temperature is rising at a higher rate in Nepal and Chinese regions of the Himalayas compared with rest of the Himalayas. A declining trend of monsoon in the western Indian Himalayas and an increasing trend in the eastern Indian Himalayas have been observed, whereas increasing precipitation and stream flow in many parts of Tibetan Plat...

  8. Simulation of Effects of Land Use Change on Climate in China by a Regional Climate Model

    Institute of Scientific and Technical Information of China (English)

    高学杰; 罗勇; 林万涛; 赵宗慈; FilippoGIORGI

    2003-01-01

    Climate effects of land use change in China as simulated by a regional climate model (RegCM2)are investigated. The model is nested in one-way mode within a global coupled atmosphere-ocean model(CSIRO R21L9 AOGCM). Two multi-year simulations, one with current land use and the other with potential vegetation cover, are conducted. Statistically significant changes of precipitation, surface air temperature, and daily maximum and daily minimum temperature are analyzed based on the difference between the two simulations. The simulated effects of land use change over China include a decrease of mean annual precipitation over Northwest China, a region with a prevalence of arid and semi-arid areas;an increase of mean annual surfaoe air temperature over some areas; and a decrease of temperature along coastal areas. Summer mean daily maximum temperature increases in many locations, while winter mean daily minimum temperature decreases in East China and increases in Northwest China. The upper soil moisture decreases significantly across China. The results indicate that the same land use change may cause different climate effects in different regions depending on the surrounding environment and climate characteristics.

  9. Regional scale patterns of fine root lifespan and turnover under current and future climate.

    Science.gov (United States)

    McCormack, Luke M; Eissenstat, David M; Prasad, Anantha M; Smithwick, Erica A H

    2013-06-01

    Fine root dynamics control a dominant flux of carbon from plants and into soils and mediate potential uptake and cycling of nutrients and water in terrestrial ecosystems. Understanding of these patterns is needed to accurately describe critical processes like productivity and carbon storage from ecosystem to global scales. However, limited observations of root dynamics make it difficult to define and predict patterns of root dynamics across broad spatial scales. Here, we combine species-specific estimates of fine root dynamics with a model that predicts current distribution and future suitable habitat of temperate tree species across the eastern United States (US). Estimates of fine root lifespan and turnover are based on empirical observations and relationships with fine root and whole-plant traits and apply explicitly to the fine root pool that is relatively short-lived and most active in nutrient and water uptake. Results from the combined model identified patterns of faster root turnover rates in the North Central US and slower turnover rates in the Southeastern US. Portions of Minnesota, Ohio, and Pennsylvania were also predicted to experience >10% increases in root turnover rates given potential shifts in tree species composition under future climate scenarios while root turnover rates in other portions of the eastern US were predicted to decrease. Despite potential regional changes, the average estimates of root lifespan and turnover for the entire study area remained relatively stable between the current and future climate scenarios. Our combined model provides the first empirically based, spatially explicit, and spatially extensive estimates of fine root lifespan and turnover and is a potentially powerful tool allowing researchers to identify reasonable approximations of forest fine root turnover in areas where no direct observations are available. Future efforts should focus on reducing uncertainty in estimates of root dynamics by better understanding how

  10. FOAM: Expanding the horizons of climate modeling

    Energy Technology Data Exchange (ETDEWEB)

    Tobis, M.; Foster, I.T.; Schafer, C.M. [and others

    1997-10-01

    We report here on a project that expands the applicability of dynamic climate modeling to very long time scales. The Fast Ocean Atmosphere Model (FOAM) is a coupled ocean atmosphere model that incorporates physics of interest in understanding decade to century time scale variability. It addresses the high computational cost of this endeavor with a combination of improved ocean model formulation, low atmosphere resolution, and efficient coupling. It also uses message passing parallel processing techniques, allowing for the use of cost effective distributed memory platforms. The resulting model runs over 6000 times faster than real time with good fidelity, and has yielded significant results.

  11. Assessing the consistency between short-term global temperature trends in observations and climate model projections

    CERN Document Server

    Michaels, Patrick J; Christy, John R; Herman, Chad S; Liljegren, Lucia M; Annan, James D

    2013-01-01

    Assessing the consistency between short-term global temperature trends in observations and climate model projections is a challenging problem. While climate models capture many processes governing short-term climate fluctuations, they are not expected to simulate the specific timing of these somewhat random phenomena - the occurrence of which may impact the realized trend. Therefore, to assess model performance, we develop distributions of projected temperature trends from a collection of climate models running the IPCC A1B emissions scenario. We evaluate where observed trends of length 5 to 15 years fall within the distribution of model trends of the same length. We find that current trends lie near the lower limits of the model distributions, with cumulative probability-of-occurrence values typically between 5 percent and 20 percent, and probabilities below 5 percent not uncommon. Our results indicate cause for concern regarding the consistency between climate model projections and observed climate behavior...

  12. Modeling the climatic response to orbital variations.

    Science.gov (United States)

    Imbrie, J; Imbrie, J Z

    1980-02-29

    According to the astronomical theory of climate, variations in the earth's orbit are the fundamental cause of the succession of Pleistocene ice ages. This article summarizes how the theory has evolved since the pioneer studies of James Croll and Milutin Milankovitch, reviews recent evidence that supports the theory, and argues that a major opportunity is at hand to investigate the physical mechanisms by which the climate system responds to orbital forcing. After a survey of the kinds of models that have been applied to this problem, a strategy is suggested for building simple, physically motivated models, and a time-dependent model is developed that simulates the history of planetary glaciation for the past 500,000 years. Ignoring anthropogenic and other possible sources of variation acting at frequencies higher than one cycle per 19,000 years, this model predicts that the long-term cooling trend which began some 6000 years ago will continue for the next 23,000 years.

  13. Advance in Application of Regional Climate Models in China

    Institute of Scientific and Technical Information of China (English)

    ZHANG Wei; YAN Minhua; CHEN Panqin; XU Helan

    2008-01-01

    Regional climate models have become the powerful tools for simulating regional climate and its changeprocess and have been widely used in China. Using regional climate models, some research results have been obtainedon the following aspects: 1) the numerical simulation of East Asian monsoon climate, including exceptional monsoonprecipitation, summer precipitation distribution, East Asian circulation, multi-year climate average condition, summerrain belt and so on; 2) the simulation of arid climate of the western China, including thermal effect of the Qing-hai-Tibet Plateau, the plateau precipitation in the Qilian Mountains; and the impacts of greenhouse effects (CO2 dou-bling) upon climate in the western China; and 3) the simulation of the climate effect of underlying surface changes, in-cluding the effect of soil on climate formation, the influence of terrain on precipitation, the effect of regional soil deg-radation on regional climate, the effect of various underlying surfaces on regional climate, the effect of land-sea con-trast on the climate formulation, the influence of snow cover over the plateau regions on the regional climate, the effectof vegetation changes on the regional climate, etc. In the process of application of regional climate models, the prefer-ences of the models are improved so that better simulation results are gotten. At last, some suggestions are made aboutthe application of regional climate models in regional climate research in the future.

  14. Formulation of an ocean model for global climate simulations

    Directory of Open Access Journals (Sweden)

    S. M. Griffies

    2005-01-01

    Full Text Available This paper summarizes the formulation of the ocean component to the Geophysical Fluid Dynamics Laboratory's (GFDL climate model used for the 4th IPCC Assessment (AR4 of global climate change. In particular, it reviews the numerical schemes and physical parameterizations that make up an ocean climate model and how these schemes are pieced together for use in a state-of-the-art climate model. Features of the model described here include the following: (1 tripolar grid to resolve the Arctic Ocean without polar filtering, (2 partial bottom step representation of topography to better represent topographically influenced advective and wave processes, (3 more accurate equation of state, (4 three-dimensional flux limited tracer advection to reduce overshoots and undershoots, (5 incorporation of regional climatological variability in shortwave penetration, (6 neutral physics parameterization for representation of the pathways of tracer transport, (7 staggered time stepping for tracer conservation and numerical efficiency, (8 anisotropic horizontal viscosities for representation of equatorial currents, (9 parameterization of exchange with marginal seas, (10 incorporation of a free surface that accomodates a dynamic ice model and wave propagation, (11 transport of water across the ocean free surface to eliminate unphysical ``virtual tracer flux' methods, (12 parameterization of tidal mixing on continental shelves. We also present preliminary analyses of two particularly important sensitivities isolated during the development process, namely the details of how parameterized subgridscale eddies transport momentum and tracers.

  15. Climate Change and Cities in Africa: Current Dilemmas and Future Challenges

    Science.gov (United States)

    2014-10-01

    over time, whether due to natural variability or as a result of human activity.”7 A principal cause of climate change is the release of greenhouse ...What is causing the increase in greenhouse gas emissions? In recent decades, advancements in climate science have allowed for increasingly powerful...evidence that current patterns of climate change have been influenced by human activity.11 In particular, greenhouse emissions increased substantially

  16. A Practical Philosophy of Complex Climate Modelling

    Science.gov (United States)

    Schmidt, Gavin A.; Sherwood, Steven

    2014-01-01

    We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.

  17. A Practical Philosophy of Complex Climate Modelling

    Science.gov (United States)

    Schmidt, Gavin A.; Sherwood, Steven

    2014-01-01

    We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.

  18. Spatial and temporal variability of soil moisture-temperature coupling in current and future climate

    Science.gov (United States)

    Schwingshackl, Clemens; Hirschi, Martin; Seneviratne, Sonia Isabelle

    2017-04-01

    While climate models generally agree on a future global mean temperature increase, the exact rate of change is still uncertain. The uncertainty is even higher for regional temperature trends that can deviate substantially from the projected global temperature increase. Several studies tried to constrain these regional temperature projections. They found that over land areas soil moisture is an important factor that influences the regional response. Due to the limited knowledge of the influence of soil moisture on atmospheric conditions on global scale the constraint remains still weak, though. Here, we use a framework that is based on the dependence of evaporative fraction (i.e. the fraction of net radiation that goes into latent heat flux) on soil moisture to distinguish between different soil moisture regimes (Seneviratne et al., 2010). It allows to estimate the influence of soil moisture on near-surface air temperature in the current climate and in future projections. While in the wet soil moisture regime, atmospheric conditions and related land surface fluxes can be considered as mostly driven by available energy, in the transitional regime - where evaporative fraction and soil moisture are essentially linearly coupled - soil moisture has an impact on turbulent heat fluxes, air humidity and temperature: Decreasing soil moisture and concomitant decreasing evaporative fraction cause increasing sensible heat flux, which might further lead to higher surface air temperatures. We investigate the strength of the single couplings (soil moisture → latent heat flux → sensible heat flux → air temperature) in order to quantify the influence of soil moisture on surface air temperature in the transitional regime. Moreover, we take into account that the coupling strength can change in the course of the year due to seasonal climate variations. The relations between soil moisture, evaporative fraction and near-surface air temperature in re-analysis and observation

  19. Climate change hotspots in the CMIP5 global climate model ensemble

    OpenAIRE

    Diffenbaugh, Noah S; Giorgi, Filippo

    2012-01-01

    We use a statistical metric of multi-dimensional climate change to quantify the emergence of global climate change hotspots in the CMIP5 climate model ensemble. Our hotspot metric extends previous work through the inclusion of extreme seasonal temperature and precipitation, which exert critical influence on climate change impacts. The results identify areas of the Amazon, the Sahel and tropical West Africa, Indonesia, and the Tibetan Plateau as persistent regional climate change hotspots thro...

  20. Evaluating the effect of climate change on areal reduction factors using regional climate model projections

    Science.gov (United States)

    Li, Jingwan; Sharma, Ashish; Johnson, Fiona; Evans, Jason

    2015-09-01

    Areal reduction factors (ARFs) are commonly used to transform point design rainfall to represent the average design rainfall for a catchment area. While there has been considerable attention paid in the research and engineering communities to the likely changes in rainfall intensity in future climates, the issue of changes to design areal rainfall has been largely ignored. This paper investigates the impact of climate change on ARFs. A new methodology for estimating changes in ARFs is presented. This method is used to assess changes in ARFs in the greater Sydney region using a high-resolution regional climate model (RCM). ARFs under present (1990-2009) and future (2040-2059) climate conditions were derived and compared for annual exceedance probabilities (AEPs) from 50% to 5% for durations ranging from 1 h to 120 h. The analysis shows two main trends in the future changes in ARFs. For the shortest duration events (1-h) the ARFs are found to increase which implies that these events will tend to have a larger spatial structure in the future than the current climate. In contrast, storms with durations between 6 and 72 h are likely to have decreased ARFs in the future, suggesting a more restricted spatial coverage of storms under a warming climate. The extent of the decrease varies with event frequency and catchment size. The largest decreases are found for large catchments and rare events. Although the results here are based on a single RCM and need to be confirmed in future work with multiple models, the framework that is proposed will be useful for future studies considering changes in the areal extent of rainfall extremes.

  1. Extreme precipitation and temperature responses to circulation patterns in current climate: statistical approaches

    NARCIS (Netherlands)

    Photiadou, C.

    2015-01-01

    Climate change is likely to influence the frequency of extreme extremes - temperature, precipitation and hydrological extremes, which implies increasing risks for flood and drought events in Europe. In current climate, European countries were often not sufficiently prepared to deal with the great so

  2. Current Challenges in Dynamo Modeling

    Science.gov (United States)

    Glatzmaier, G. A.

    2001-12-01

    Three-dimensional, dynamically self-consistent, numerical simulations have been used for two decades to study the generation of global magnetic fields in the deep fluid interiors of planets and stars. In particular, the number of geodynamo models has increased significantly within the last five years. These simulations of magnetic field generation by laminar convection have provided considerable insight to the dynamo process and have produced large-scale fields similar to those observed. However, no global convective dynamo simulation has yet been able to afford the spatial resolution required to simulate turbulent convection, which surely must exist in these low-viscosity fluids. They have all employed greatly enhanced eddy diffusivities to stabilize the low resolution numerical solutions and crudely account for the transport and mixing by the unresolved turbulence. A grand challenge for the next generation of geodynamo models is to produce a simulation with the thermal and viscous (eddy) diffusivities set no larger than the actual magnetic diffusivity of the Earth's fluid core (2 m2/s), while using the core's dimensions, mass, rotation rate and heat flow. This would correspond to the Ekman and magnetic Ekman numbers both set to 10-9 and the Rayleigh number being many orders of magnitude greater than critical. Dynamo models for stars and planets present an additional complication: the large variation of density with radius. A grand challenge for the next generation of these models is to reach similarly low Ekman numbers and high Rayleigh numbers with a density that decreases by at least three orders of magnitude from the base of the convection zone to the model's outer boundary. The advances in numerical methods and massively parallel computing needed to meet these challenges will be discussed.

  3. Climate Modeling Computing Needs Assessment

    Science.gov (United States)

    Petraska, K. E.; McCabe, J. D.

    2011-12-01

    This paper discusses early findings of an assessment of computing needs for NASA science, engineering and flight communities. The purpose of this assessment is to document a comprehensive set of computing needs that will allow us to better evaluate whether our computing assets are adequately structured to meet evolving demand. The early results are interesting, already pointing out improvements we can make today to get more out of the computing capacity we have, as well as potential game changing innovations for the future in how we apply information technology to science computing. Our objective is to learn how to leverage our resources in the best way possible to do more science for less money. Our approach in this assessment is threefold: Development of use case studies for science workflows; Creating a taxonomy and structure for describing science computing requirements; and characterizing agency computing, analysis, and visualization resources. As projects evolve, science data sets increase in a number of ways: in size, scope, timelines, complexity, and fidelity. Generating, processing, moving, and analyzing these data sets places distinct and discernable requirements on underlying computing, analysis, storage, and visualization systems. The initial focus group for this assessment is the Earth Science modeling community within NASA's Science Mission Directorate (SMD). As the assessment evolves, this focus will expand to other science communities across the agency. We will discuss our use cases, our framework for requirements and our characterizations, as well as our interview process, what we learned and how we plan to improve our materials after using them in the first round of interviews in the Earth Science Modeling community. We will describe our plans for how to expand this assessment, first into the Earth Science data analysis and remote sensing communities, and then throughout the full community of science, engineering and flight at NASA.

  4. Selection of climate change scenario data for impact modelling

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  5. A Model for Climate Change Adaptation

    Science.gov (United States)

    Pasqualini, D.; Keating, G. N.

    2009-12-01

    Climate models predict serious impacts on the western U.S. in the next few decades, including increased temperatures and reduced precipitation. In combination, these changes are linked to profound impacts on fundamental systems, such as water and energy supplies, agriculture, population stability, and the economy. Global and national imperatives for climate change mitigation and adaptation are made actionable at the state level, for instance through greenhouse gas (GHG) emission regulations and incentives for renewable energy sources. However, adaptation occurs at the local level, where energy and water usage can be understood relative to local patterns of agriculture, industry, and culture. In response to the greenhouse gas emission reductions required by California’s Assembly Bill 32 (2006), Sonoma County has committed to sharp emissions reductions across several sectors, including water, energy, and transportation. To assist Sonoma County develop a renewable energy (RE) portfolio to achieve this goal we have developed an integrated assessment model, CLEAR (CLimate-Energy Assessment for Resiliency) model. Building on Sonoma County’s existing baseline studies of energy use, carbon emissions and potential RE sources, the CLEAR model simulates the complex interactions among technology deployment, economics and social behavior. This model enables assessment of these and other components with specific analysis of their coupling and feedbacks because, due to the complex nature of the problem, the interrelated sectors cannot be studied independently. The goal is an approach to climate change mitigation and adaptation that is replicable for use by other interested communities. The model user interfaces helps stakeholders and policymakers understand options for technology implementation.

  6. The ventilation and climate modelling of rapid development tunnel drivages

    Energy Technology Data Exchange (ETDEWEB)

    Lowndes, I.S.; Crossley, A.J.; Yang, Z.Y. [University of Nottingham, Nottingham (United Kingdom). School of Chemical Environmental & Mining Engineering

    2004-03-01

    The extraction of minerals and coal at greater depth, employing higher-powered machinery to increase production levels, has imposed an increased burden on ventilation systems to maintain an acceptable working environment. There may be an economic or practical limit to the climatic improvement that may be obtained by the sole use of ventilation air. Where this limit is identified, there may be the need to consider the selective application of air-cooling systems. This paper details the construction of a computer based climatic prediction tool developed at the University of Nottingham. The current model predicts the psychrometric and thermodynamic conditions within long rapid development single entry tunnel drivages. The model takes into account the mass and heat transfer between the strata, water, machinery and the ventilation air. The results produced by the model have been correlated against ventilation, climatic and operational data, obtained from a number of rapid tunnel developments within UK deep coalmines. The paper details the results of a series of correlation and validation studies conducted against the ventilation and climate survey data measured within 105s district Tail Gate tunnel development at Maltby Colliery, UK. The paper concludes by presenting the results of a case study that illustrate the application of the validated model to the design and operation of an integrated mine ventilation and cooling system. The case study illustrates the effect that an increased depth and hence increased virgin strata temperature has on the climate experienced within rapid tunnel developments. Further investigations were performed to identify the optimum cooling strategy that should be adopted to maintain a satisfactory climate at the head of the drivage.

  7. Supercomputing for weather and climate modelling: convenience or necessity

    CSIR Research Space (South Africa)

    Landman, WA

    2009-12-01

    Full Text Available Weather and climate modelling require dedicated computer infrastructure in order to generate high-resolution, large ensemble, various models with different configurations, etc. in order to optimise operational forecasts and climate projections. High...

  8. Climate science: Unexpected fix for ocean models

    Science.gov (United States)

    Kelly, Kathryn A.; Thompson, Luanne

    2016-07-01

    Computational models persistently underestimate strong currents that redistribute ocean heat. This problem is solved in models in which ocean eddies are damped by coupling of the atmosphere with the sea. See Letter p.533

  9. Drifting snow climate of the Greenland ice sheet: a study with a regional climate model

    NARCIS (Netherlands)

    Lenaerts, J.T.M.; van den Broeke, M.R.; van Angelen, J.H.; van Meijgaard, E.; Déry, S.J.

    2012-01-01

    This paper presents the drifting snow climate of the Greenland ice sheet, using output from a high-resolution ( 11 km) regional climate model. Because reliable direct observations of drifting snow do not exist, we evaluate the modeled near-surface climate instead, using automatic weather station (AW

  10. LINKING MICROBES TO CLIMATE: INCORPORATING MICROBIAL ACTIVITY INTO CLIMATE MODELS COLLOQUIUM

    Energy Technology Data Exchange (ETDEWEB)

    DeLong, Edward; Harwood, Caroline; Reid, Ann

    2011-01-01

    This report explains the connection between microbes and climate, discusses in general terms what modeling is and how it applied to climate, and discusses the need for knowledge in microbial physiology, evolution, and ecology to contribute to the determination of fluxes and rates in climate models. It recommends with a multi-pronged approach to address the gaps.

  11. Comparison of two potato simulation models under climate change. II Application of climate change scenarios.

    NARCIS (Netherlands)

    Wolf, J.

    2002-01-01

    The effects of climate change (for the year 2050 compared to ambient climate) and change in climatic variability on potato growth and production at 6 sites in Europe were calculated. These calculations were done with both a simple growth model, POTATOS, and a comprehensive model, NPOTATO. Comparison

  12. Comparison of two soya bean simulation models under climate change : II Application of climate change scenarios

    NARCIS (Netherlands)

    Wolf, J.

    2002-01-01

    The effects of climate change (for 2050 compared to ambient climate) and change in climatic variability on soya bean growth and production at 3 sites in the EU have been calculated. These calculations have been done with both a simple growth model, SOYBEANW, and a comprehensive model, CROPGRO.

  13. Drifting snow climate of the Greenland ice sheet: a study with a regional climate model

    NARCIS (Netherlands)

    Lenaerts, J.T.M.|info:eu-repo/dai/nl/314850163; van den Broeke, M.R.|info:eu-repo/dai/nl/073765643; van Angelen, J.H.; van Meijgaard, E.; Déry, S.J.

    2012-01-01

    This paper presents the drifting snow climate of the Greenland ice sheet, using output from a high-resolution ( 11 km) regional climate model. Because reliable direct observations of drifting snow do not exist, we evaluate the modeled near-surface climate instead, using automatic weather station (AW

  14. Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

    Science.gov (United States)

    Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; Araújo, Miguel B; Rebelo, Tony G

    2008-10-23

    Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.

  15. Modelling hydrological responses of Nerbioi River Basin to Climate Change

    Science.gov (United States)

    Mendizabal, Maddalen; Moncho, Roberto; Chust, Guillem; Torp, Peter

    2010-05-01

    basin (Basque Country, North of Spain). So that adaptation strategies can be defined. In order to fulfil this objective four subobjectives are defined: (1)selection of the future climate projections for the case study area from a wide spectrum of possibilities; (2) model the hydrological processes of the basin with a physically distributed complex hydrological model; (3) validation of the hydrological model with observation data; and (4) runoff simulation introducing regional climate model data selected. The analysis of climate models suggests that extreme precipitation in the Basque Country increased by about 10% during the twenty-first century. This increase of extreme precipitations raised discharge and water level in Nerbioi river basin. That is why in the 21st century it is expected that the flood-prone area will expand for precipitation with a return period of 50 years. In this context, it is necessary to define and evaluate different adaptation options which are already in practice or conceivable according to the current scientific knowledge. As well as evaluate the adaptation measures in terms of their ability to lower the vulnerability of water resources to climate change. For example, land use change could be a useful tool to adapt our basin systems. The land use plays an important role on the water balance of a river by varying the proportion of precipitation that runs off and the fraction that is lost by evapotranspiration. Therefore, both climate change and adaptation strategies will have an impact on the hydrodynamic conditions of rivers; particularly the changes in flow conditions will have a severe ecological, economical and social impact. As future work, adaptation measures will introduce in the future runoff simulation in order to evaluate the effectiveness and as a decision-making tool to operational organisations.

  16. Should we believe model predictions of future climate change? (Invited)

    Science.gov (United States)

    Knutti, R.

    2009-12-01

    As computers get faster and our understanding of the climate system improves, climate models to predict the future are getting more complex by including more and more processes, and they are run at higher and higher resolution to resolve more of the small scale processes. As a result, some of the simulated features and structures, e.g. ocean eddies or tropical cyclones look surprisingly real. But are these deceptive? A pattern can look perfectly real but be in the wrong place. So can the current global models really provide the kind of information on local scales and on the quantities (e.g. extreme events) that the decision maker would need to know to invest for example in adaptation? A closer look indicates that evaluating skill of climate models and quantifying uncertainties in predictions is very difficult. This presentation shows that while models are improving in simulating the climate features we observe (e.g. the present day mean state, or the El Nino Southern Oscillation), the spread from multiple models in predicting future changes is often not decreasing. The main problem is that (unlike with weather forecasts for example) we cannot evaluate the model on a prediction (for example for the year 2100) and we have to use the present, or past changes as metrics of skills. But there are infinite ways of testing a model, and many metrics used to test models do not clearly relate to the prediction. Therefore there is little agreement in the community on metrics to separate ‘good’ and ‘bad’ models, and there is a concern that model development, evaluation and posterior weighting or ranking of models are all using the same datasets. While models are continuously improving in representing what we believe to be the key processes, many models also share ideas, parameterizations or even pieces of model code. The current models can therefore not be considered independent. Robustness of a model simulated result is often interpreted as increasing the confidence

  17. Load-balancing algorithms for climate models

    Energy Technology Data Exchange (ETDEWEB)

    Foster, I.T.; Toonen, B.R.

    1994-06-01

    Implementations of climate models on scalable parallel computer systems can suffer from load imbalances due to temporal and spatial variations in the amount of computation required for physical parameterizations such as solar radiation and convective adjustment. We have developed specialized techniques for correcting such imbalances. These techniques are incorporated in a general-purpose, programmable load-balancing library that allows the mapping of computation to processors to be specified as a series of maps generated by a programmer-supplied load-balancing module. The communication required to move from one map to another is performed automatically by the library, without programmer intervention. In this paper, we de scribe the load-balancing problem and the techniques that we have developed to solve it. We also describe specific load-balancing algorithms that we have developed for PCCM2, a scalable parallel implementation of the community Climate Model, and present experimental results that demonstrate the effectiveness of these algorithms on parallel computers.

  18. Load-balancing algorithms for climate models

    Science.gov (United States)

    Foster, I. T.; Toonen, B. R.

    Implementations of climate models on scalable parallel computer systems can suffer from load imbalances due to temporal and spatial variations in the amount of computation required for physical parameterizations such as solar radiation and convective adjustment. We have developed specialized techniques for correcting such imbalances. These techniques are incorporated in a general-purpose, programmable load-balancing library that allows the mapping of computation to processors to be specified as a series of maps generated by a programmer-supplied load-balancing module. The communication required to move from one map to another is performed automatically by the library, without programmer intervention. In this paper, we describe the load-balancing problem and the techniques that we have developed to solve it. We also describe specific load-balancing algorithms that we have developed for PCCM2, a scalable parallel implementation of the community climate model, and present experimental results that demonstrate the effectiveness of these algorithms on parallel computers.

  19. Hurricane Footprints in Global Climate Models

    Directory of Open Access Journals (Sweden)

    Francisco J. Tapiador

    2008-11-01

    Full Text Available This paper addresses the identification of hurricanes in low-resolution global climate models (GCM. As hurricanes are not fully resolvable at the coarse resolution of the GCMs (typically 2.5 × 2.5 deg, indirect methods such as analyzing the environmental conditions favoring hurricane formation have to be sought. Nonetheless, the dynamical cores of the models have limitations in simulating hurricane formation, which is a far from fully understood process. Here, it is shown that variations in the specific entropy rather than in dynamical variables can be used as a proxy of the hurricane intensity as estimated by the Accumulated Cyclone Energy (ACE. The main application of this research is to ascertain the changes in the hurricane frequency and intensity in future climates.

  20. Precalibrating an intermediate complexity climate model

    Energy Technology Data Exchange (ETDEWEB)

    Edwards, Neil R. [The Open University, Earth and Environmental Sciences, Milton Keynes (United Kingdom); Cameron, David [Centre for Ecology and Hydrology, Edinburgh (United Kingdom); Rougier, Jonathan [University of Bristol, Department of Mathematics, Bristol (United Kingdom)

    2011-10-15

    Credible climate predictions require a rational quantification of uncertainty, but full Bayesian calibration requires detailed estimates of prior probability distributions and covariances, which are difficult to obtain in practice. We describe a simplified procedure, termed precalibration, which provides an approximate quantification of uncertainty in climate prediction, and requires only that uncontroversially implausible values of certain inputs and outputs are identified. The method is applied to intermediate-complexity model simulations of the Atlantic meridional overturning circulation (AMOC) and confirms the existence of a cliff-edge catastrophe in freshwater-forcing input space. When uncertainty in 14 further parameters is taken into account, an implausible, AMOC-off, region remains as a robust feature of the model dynamics, but its location is found to depend strongly on values of the other parameters. (orig.)

  1. Climate Modeling with a Linux Cluster

    Science.gov (United States)

    Renold, M.; Beyerle, U.; Raible, C. C.; Knutti, R.; Stocker, T. F.; Craig, T.

    2004-08-01

    Until recently, computationally intensive calculations in many scientific disciplines have been limited to institutions which have access to supercomputing centers. Today, the computing power of PC processors permits the assembly of inexpensive PC clusters that nearly approach the power of supercomputers. Moreover, the combination of inexpensive network cards and Open Source software provides an easy linking of standard computer equipment to enlarge such clusters. Universities and other institutions have taken this opportunity and built their own mini-supercomputers on site. Computing power is a particular issue for the climate modeling and impacts community. The purpose of this article is to make available a Linux cluster version of the Community Climate System Model developed by the National Center for Atmospheric Research (NCAR; http://www.cgd.ucar.edu/csm).

  2. Impact of urban WWTP and CSO fluxes on river peak flow extremes under current and future climate conditions.

    Science.gov (United States)

    Keupers, Ingrid; Willems, Patrick

    2013-01-01

    The impact of urban water fluxes on the river system outflow of the Grote Nete catchment (Belgium) was studied. First the impact of the Waste Water Treatment Plant (WWTP) and the Combined Sewer Overflow (CSO) outflows on the river system for the current climatic conditions was determined by simulating the urban fluxes as point sources in a detailed, hydrodynamic river model. Comparison was made of the simulation results on peak flow extremes with and without the urban point sources. In a second step, the impact of climate change scenarios on the urban fluxes and the consequent impacts on the river flow extremes were studied. It is shown that the change in the 10-year return period hourly peak flow discharge due to climate change (-14% to +45%) was in the same order of magnitude as the change due to the urban fluxes (+5%) in current climate conditions. Different climate change scenarios do not change the impact of the urban fluxes much except for the climate scenario that involves a strong increase in rainfall extremes in summer. This scenario leads to a strong increase of the impact of the urban fluxes on the river system.

  3. Assessment of mycotoxin risk on corn in the Philippines under current and future climate change conditions.

    Science.gov (United States)

    Salvacion, Arnold R; Pangga, Ireneo B; Cumagun, Christian Joseph R

    2015-01-01

    This study attempts to assess the risk of mycotoxins (aflatoxins and fumonisins) contamination on corn in the Philippines under current and projected climate change conditions using fuzzy logic methodology based on the published range of temperature and rainfall conditions that favor mycotoxin development. Based on the analysis, projected climatic change will reduce the risk of aflatoxin contamination in the country due to increased rainfall. In the case of fumonisin contamination, most parts of the country are at a very high risk both under current conditions and the projected climate change conditions.

  4. Assessing NARCCAP climate model effects using spatial confidence regions

    Science.gov (United States)

    French, Joshua P.; McGinnis, Seth; Schwartzman, Armin

    2017-07-01

    We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

  5. Assessing NARCCAP climate model effects using spatial confidence regions

    Directory of Open Access Journals (Sweden)

    J. P. French

    2017-07-01

    Full Text Available We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

  6. A Bayesian posterior predictive framework for weighting ensemble regional climate models

    Science.gov (United States)

    Fan, Yanan; Olson, Roman; Evans, Jason P.

    2017-06-01

    We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.

  7. Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms.

    Science.gov (United States)

    Vautard, Robert; Thais, Françoise; Tobin, Isabelle; Bréon, François-Marie; Devezeaux de Lavergne, Jean-Guy; Colette, Augustin; Yiou, Pascal; Ruti, Paolo Michele

    2014-01-01

    The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions.

  8. Modeling of Current Transformers Under Saturation Conditions

    Directory of Open Access Journals (Sweden)

    Martin Prochazka

    2006-01-01

    Full Text Available During a short circuit the input signal of the relay can be distort by the magnetic core saturation of the current transformer. It is useful to verify the behavior of CT by a mathematical model. The paper describes one phase and three phase models and it presents some methods of how to analyze and classify a deformed secondary current

  9. Model based climate information on drought risk in Africa

    Science.gov (United States)

    Calmanti, S.; Syroka, J.; Jones, C.; Carfagna, F.; Dell'Aquila, A.; Hoefsloot, P.; Kaffaf, S.; Nikulin, G.

    2012-04-01

    The United Nations World Food Programme (WFP) has embarked upon the endeavor of creating a sustainable Africa-wide natural disaster risk management system. A fundamental building block of this initiative is the setup of a drought impact modeling platform called Africa Risk-View that aims to quantify and monitor weather-related food security risk in Africa. The modeling approach is based the Water Requirement Satisfaction Index (WRSI), as the fundamental indicator of the performances of agriculture and uses historical records of food assistance operation to project future potential needs for livelihood protection. By using climate change scenarios as an input to Africa Risk-View it is possible, in principles, to evaluate the future impact of climate variability on critical issues such as food security and the overall performance of the envisaged risk management system. A necessary preliminary step to this challenging task is the exploration of the sources of uncertainties affecting the assessment based on modeled climate change scenarios. For this purpose, a limited set of climate models have been selected in order verify the relevance of using climate model output data with Africa Risk-View and to explore a minimal range of possible sources of uncertainty. This first evaluation exercise started before the setup of the CORDEX framework and has relied on model output available at the time. In particular only one regional downscaling was available for the entire African continent from the ENSEMBLES project. The analysis shows that current coarse resolution global climate models can not directly feed into the Africa RiskView risk-analysis tool. However, regional downscaling may help correcting the inherent biases observed in the datasets. Further analysis is performed by using the first data available under the CORDEX framework. In particular, we consider a set of simulation driven with boundary conditions from the reanalysis ERA-Interim to evaluate the skill drought

  10. Embedding complex hydrology in the climate system - towards fully coupled climate-hydrology models

    DEFF Research Database (Denmark)

    Butts, M.; Rasmussen, S.H.; Ridler, M.

    2013-01-01

    Motivated by the need to develop better tools to understand the impact of future management and climate change on water resources, we present a set of studies with the overall aim of developing a fully dynamic coupling between a comprehensive hydrological model, MIKE SHE, and a regional climate...... distributed parameters using satellite remote sensing. Secondly, field data are used to investigate the effects of model resolution and parameter scales for use in a coupled model. Finally, the development of the fully coupled climate-hydrology model is described and some of the challenges associated...... with coupling models for hydrological processes on sub-grid scales of the regional climate model are presented....

  11. Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method.

    Science.gov (United States)

    Kara, Fatih; Yucel, Ismail

    2015-09-01

    This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.

  12. Projecting hydropower production under future climates: a review of modelling challenges and open questions

    Science.gov (United States)

    Schaefli, Bettina

    2015-04-01

    Hydropower is a pillar for renewable electricity production in almost all world regions. The planning horizon of major hydropower infrastructure projects stretches over several decades and consideration of evolving climatic conditions plays an ever increasing role. This review of model-based climate change impact assessments provides a synthesis of the wealth of underlying modelling assumptions, highlights the importance of local factors and attempts to identify the most urgent open questions. Based on existing case studies, it critically discusses whether current hydro-climatic modelling frameworks are likely to provide narrow enough water scenario ranges to be included into economic analyses for end-to-end climate change impact assessments including electricity market models. This will be completed with an overview of not or indirectly climate-related boundary conditions, such as economic growth, legal constraints, national subsidy frameworks or growing competition for water, which might locally largely outweigh any climate change impacts.

  13. Data assimilation experiments with MPIESM climate model

    Directory of Open Access Journals (Sweden)

    Belyaev Konstantin

    2016-01-01

    Full Text Available Further development of data assimilation technique and its application in numerical experiments with state-of-the art Max Plank Institute Earth System model have been carried out. In particularly, the stability problem of assimilation is posed and discussed In the experiments the sea surface height data from archive Archiving, Validating and Interpolating Satellite Ocean have been used. All computations have been realized on cluster system of German Climate Computing Center. The results of numerical experiments with and without assimilation were recorded and analyzed. A special attention has been focused on the Arctic zone. It is shown that there is a good coincidence of model tendencies and independent data.

  14. Response of Mycorrhizal Diversity to Current Climatic Changes

    Directory of Open Access Journals (Sweden)

    Stephen E. Williams

    2011-01-01

    Full Text Available Form and function of mycorrhizas as well as tracing the presence of the mycorrhizal fungi through the geological time scale are herein first addressed. Then mycorrhizas and plant fitness, succession, mycorrhizas and ecosystem function, and mycorrhizal resiliency are introduced. From this, four hypotheses are drawn: (1 mycorrhizal diversity evolved in response to changes in Global Climate Change (GCC environmental drivers, (2 mycorrhizal diversity will be modified by present changes in GCC environmental drivers, (3 mycorrhizal changes in response to ecological drivers of GCC will in turn modify plant, community, and ecosystem responses to the same, and (4 Mycorrhizas will continue to evolve in response to present and future changes in GCC factors. The drivers of climate change examined here are: CO2 enrichment, temperature rise, altered precipitation, increased N-deposition, habitat fragmentation, and biotic invasion increase. These impact the soil-rhizosphere, plant and fungal physiology and/or ecosystem(s directly and indirectly. Direct effects include changes in resource availability and change in distribution of mycorrhizas. Indirect effects include changes in below ground allocation of C to roots and changes in plant species distribution. GCC ecological drivers have been partitioned into four putative time frames: (1 Immediate (1–2 years impacts, associated with ecosystem fragmentation and habitat loss realized through loss of plant-hosts and disturbance of the soil; (2 Short-term (3–10 year impacts, resultant of biotic invasions of exotic mycorrhizal fungi, plants and pests, diseases and other abiotic perturbations; (3 Intermediate-term (11–20 year impacts, of cumulative and additive effects of increased N (and S deposition, soil acidification and other pollutants; and (4 Long-term (21–50+ year impacts, where increased temperatures and CO2 will destabilize global rainfall patterns, soil properties and plant ecosystem resilience. Due

  15. Climate change impact on available water resources obtained using multiple global climate and hydrology models

    NARCIS (Netherlands)

    Hagemann, S.; Chen, Cui; Clark, D.B.; Folwell, S.; Gosling, S.; Haddeland, I.; Hanasaki, N.; Heinke, J.; Ludwig, F.

    2013-01-01

    Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological 5 models (eight) were used to systematically

  16. Climate change impact on available water resources obtained using multiple global climate and hydrology models

    NARCIS (Netherlands)

    Hagemann, S.; Chen, Cui; Clark, D.B.; Folwell, S.; Gosling, S.; Haddeland, I.; Hanasaki, N.; Heinke, J.; Ludwig, F.

    2013-01-01

    Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological 5 models (eight) were used to systematically

  17. Modeling the Current and Future Distribution of Treeline Species in the Nepal Himalaya

    Science.gov (United States)

    Chhetri, P. K.; Cairns, D. M.

    2015-12-01

    Knowledge of the current distribution of treeline species is important for predicting their future distribution in the landscape. Many studies have indicated that treeline will advance with climate change. Treeline advance will result in a loss of alpine biodiversity because the advancing treeline will fragment alpine ecosystems. A species distribution modeling approach using predicted climate data can increase our understanding of how treeline species will expand their range in the future. We used the Maxent model to predict the current and future distributions of three dominant treeline species, Abies spectabilis, Betula utilis, and Pinus wallichiana, of the Nepal Himalaya. The Maxent model predicted that the distribution of treeline species will change significantly under future climate change scenarios. The range of these treeline species will expand northward or upslope in response to future climate change. The model also indicated that temperature-related climatic variables are the most important determinants of the distribution of treeline species.

  18. Is the climate right for pleistocene rewilding? Using species distribution models to extrapolate climatic suitability for mammals across continents.

    Directory of Open Access Journals (Sweden)

    Orien M W Richmond

    Full Text Available Species distribution models (SDMs are increasingly used for extrapolation, or predicting suitable regions for species under new geographic or temporal scenarios. However, SDM predictions may be prone to errors if species are not at equilibrium with climatic conditions in the current range and if training samples are not representative. Here the controversial "Pleistocene rewilding" proposal was used as a novel example to address some of the challenges of extrapolating modeled species-climate relationships outside of current ranges. Climatic suitability for three proposed proxy species (Asian elephant, African cheetah and African lion was extrapolated to the American southwest and Great Plains using Maxent, a machine-learning species distribution model. Similar models were fit for Oryx gazella, a species native to Africa that has naturalized in North America, to test model predictions. To overcome biases introduced by contracted modern ranges and limited occurrence data, random pseudo-presence points generated from modern and historical ranges were used for model training. For all species except the oryx, models of climatic suitability fit to training data from historical ranges produced larger areas of predicted suitability in North America than models fit to training data from modern ranges. Four naturalized oryx populations in the American southwest were correctly predicted with a generous model threshold, but none of these locations were predicted with a more stringent threshold. In general, the northern Great Plains had low climatic suitability for all focal species and scenarios considered, while portions of the southern Great Plains and American southwest had low to intermediate suitability for some species in some scenarios. The results suggest that the use of historical, in addition to modern, range information and randomly sampled pseudo-presence points may improve model accuracy. This has implications for modeling range shifts of

  19. Is the climate right for pleistocene rewilding? Using species distribution models to extrapolate climatic suitability for mammals across continents.

    Science.gov (United States)

    Richmond, Orien M W; McEntee, Jay P; Hijmans, Robert J; Brashares, Justin S

    2010-09-22

    Species distribution models (SDMs) are increasingly used for extrapolation, or predicting suitable regions for species under new geographic or temporal scenarios. However, SDM predictions may be prone to errors if species are not at equilibrium with climatic conditions in the current range and if training samples are not representative. Here the controversial "Pleistocene rewilding" proposal was used as a novel example to address some of the challenges of extrapolating modeled species-climate relationships outside of current ranges. Climatic suitability for three proposed proxy species (Asian elephant, African cheetah and African lion) was extrapolated to the American southwest and Great Plains using Maxent, a machine-learning species distribution model. Similar models were fit for Oryx gazella, a species native to Africa that has naturalized in North America, to test model predictions. To overcome biases introduced by contracted modern ranges and limited occurrence data, random pseudo-presence points generated from modern and historical ranges were used for model training. For all species except the oryx, models of climatic suitability fit to training data from historical ranges produced larger areas of predicted suitability in North America than models fit to training data from modern ranges. Four naturalized oryx populations in the American southwest were correctly predicted with a generous model threshold, but none of these locations were predicted with a more stringent threshold. In general, the northern Great Plains had low climatic suitability for all focal species and scenarios considered, while portions of the southern Great Plains and American southwest had low to intermediate suitability for some species in some scenarios. The results suggest that the use of historical, in addition to modern, range information and randomly sampled pseudo-presence points may improve model accuracy. This has implications for modeling range shifts of organisms in response

  20. Abilities and limitations in the use of regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Koeltzov, Morten Andreas Oedegaard

    2012-11-01

    In order to say something about the effect of climate change at the regional level, one takes in use regional climate models. In these models the thesis introduce regional features, which are not included in the global climate models (which are basically in climate research). Regional models can provide good and useful climate projections that add more value than the global climate models, but also introduces an uncertainty in the calculations. How should this uncertainty affect the use of regional climate models?The most common methodology for calculating potential future climate developments are based on different scenarios of possible emissions of greenhouse gases. These scenarios operates as global climate models using physical laws and calculate possible future developments. This is considered mathematical complexed and processes with limited supercomputing capacity calculates the global models for the larger scale of the climate system. To study the effects of climate change are regional details required and the regional models used therefore in a limited area of the climate system. These regional models are driven by data from the global models and refines and improves these data. Impact studies can then use the data from the regional models or data which are further processed to provide more local details using geo-statistical methods. In the preparation of the climate projections is there a minimum of 4 sources of uncertainty. This uncertainty is related to the provision of emission scenarios of greenhouse gases, uncertainties related to the use of global climate models, uncertainty related to the use of regional climate models and the uncertainty of internal variability in the climate system. This thesis discusses the use of regional climate models, and illustrates how the regional climate model adds value to climate projections, and at the same time introduce uncertainty in the calculations. It discusses in particular the importance of the choice of

  1. Modeling lakes and reservoirs in the climate system

    NARCIS (Netherlands)

    MacKay, M.D.; Neale, P.J.; Arp, C.D.; De Senerpont Domis, L.N.; Fang, X.; Gal, G.; Jöhnk, K.D.; Kirillin, G.; Lenters, J.D.; Litchman, E.; MacIntyre, S.; Marsh, P.; Melack, J.; Mooij, W.M.; Peeters, F.; Quesada, A.; Schladow, S.G.; Schmid, M.; Spence, C.; Stokes, S.L.

    2009-01-01

    Modeling studies examining the effect of lakes on regional and global climate, as well as studies on the influence of climate variability and change on aquatic ecosystems, are surveyed. Fully coupled atmosphere–land surface–lake climate models that could be used for both of these types of study simu

  2. Hortisim: a model for greenhouse crops and greenhouse climate

    NARCIS (Netherlands)

    Gijzen, H.; Heuvelink, E.; Challa, H.; Dayan, E.; Marcelis, L.F.M.; Cohen, S.; Fuchs, M.

    1998-01-01

    A combined model for crop production and climate in greenhouses, HORTISIM, was developed. Existing models, developed by several research groups, of various aspects of crop growth and greenhouse climate have been integrated. HORTISIM contains 7 submodels (Weather, Greenhouse Climate, Soil, Crop, Gree

  3. Climate change, crop yields, and undernutrition: development of a model to quantify the impact of climate scenarios on child undernutrition.

    Science.gov (United States)

    Lloyd, Simon J; Kovats, R Sari; Chalabi, Zaid

    2011-12-01

    Global climate change is anticipated to reduce future cereal yields and threaten food security, thus potentially increasing the risk of undernutrition. The causation of undernutrition is complex, and there is a need to develop models that better quantify the potential impacts of climate change on population health. We developed a model for estimating future undernutrition that accounts for food and nonfood (socioeconomic) causes and can be linked to available regional scenario data. We estimated child stunting attributable to climate change in five regions in South Asia and sub-Saharan Africa (SSA) in 2050. We used current national food availability and undernutrition data to parameterize and validate a global model, using a process-driven approach based on estimations of the physiological relationship between a lack of food and stunting. We estimated stunting in 2050 using published modeled national calorie availability under two climate scenarios and a reference scenario (no climate change). We estimated that climate change will lead to a relative increase in moderate stunting of 1-29% in 2050 compared with a future without climate change. Climate change will have a greater impact on rates of severe stunting, which we estimated will increase by 23% (central SSA) to 62% (South Asia). Climate change is likely to impair future efforts to reduce child malnutrition in South Asia and SSA, even when economic growth is taken into account. Our model suggests that to reduce and prevent future undernutrition, it is necessary to both increase food access and improve socioeconomic conditions, as well as reduce greenhouse gas emissions.

  4. Development of a multi-year climate prediction model | Alexander ...

    African Journals Online (AJOL)

    Development of a multi-year climate prediction model. ... The available water resources in Southern Africa are rapidly approaching the limits of economic exploitation. ... that could be attributed to climate change arising from human activities.

  5. Interpolation of climate variables and temperature modeling

    Science.gov (United States)

    Samanta, Sailesh; Pal, Dilip Kumar; Lohar, Debasish; Pal, Babita

    2012-01-01

    Geographic Information Systems (GIS) and modeling are becoming powerful tools in agricultural research and natural resource management. This study proposes an empirical methodology for modeling and mapping of the monthly and annual air temperature using remote sensing and GIS techniques. The study area is Gangetic West Bengal and its neighborhood in the eastern India, where a number of weather systems occur throughout the year. Gangetic West Bengal is a region of strong heterogeneous surface with several weather disturbances. This paper also examines statistical approaches for interpolating climatic data over large regions, providing different interpolation techniques for climate variables' use in agricultural research. Three interpolation approaches, like inverse distance weighted averaging, thin-plate smoothing splines, and co-kriging are evaluated for 4° × 4° area, covering the eastern part of India. The land use/land cover, soil texture, and digital elevation model are used as the independent variables for temperature modeling. Multiple regression analysis with standard method is used to add dependent variables into regression equation. Prediction of mean temperature for monsoon season is better than winter season. Finally standard deviation errors are evaluated after comparing the predicted temperature and observed temperature of the area. For better improvement, distance from the coastline and seasonal wind pattern are stressed to be included as independent variables.

  6. Downscaling GISS ModelE boreal summer climate over Africa

    Science.gov (United States)

    Druyan, Leonard M.; Fulakeza, Matthew

    2016-12-01

    The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June-September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2° latitude by 2.5° longitude and the RM3 grid spacing is 0.44°. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

  7. Downscaling GISS ModelE Boreal Summer Climate over Africa

    Science.gov (United States)

    Druyan, Leonard M.; Fulakeza, Matthew

    2015-01-01

    The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June- September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2deg latitude by 2.5deg longitude and the RM3 grid spacing is 0.44deg. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

  8. Downscaling GISS ModelE Boreal Summer Climate over Africa

    Science.gov (United States)

    Druyan, Leonard M.; Fulakeza, Matthew

    2015-01-01

    The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June- September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2deg latitude by 2.5deg longitude and the RM3 grid spacing is 0.44deg. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

  9. The international coordination of climate model validation and intercomparison

    Energy Technology Data Exchange (ETDEWEB)

    Gates, W.L. [Lawrence Livermore National Lab. Livermore, CA (United States). Program for Climate Model Diagnosis and Intercomparison

    1995-12-31

    Climate modeling, whereby basic physical laws are used to integrate the physics and dynamics of climate into a consistent system, plays a key role in climate research and is the medium through. Depending upon the portion(s) of the climate system being considered, climate models range from those concerned only with the equilibrium globally-averaged surface temperature to those depicting the 3-dimensional time-dependent evolution of the coupled atmosphere, ocean, sea ice and land surface. Here only the latter class of models are considered, which are commonly known as general circulation models (or GCMs). (author)

  10. Construction of a novel economy-climate model

    Institute of Scientific and Technical Information of China (English)

    CHOU JieMing; DONG WenJie; YE DuZheng

    2007-01-01

    An attempt has been made to construct a novel economy-climate model by combining climate change research with agricultural economy research to evaluate the influence of global climate change on grain yields. The insertion of a climate change factor into the economic C-D (Cobb-Dauglas) production function model yields a novel evaluation model, which connects the climate change factor to the economic variation factor, and the performance and reasonableness of the novel evaluation model are also preliminarily simulated and verified.

  11. Towards Systematic Benchmarking of Climate Model Performance

    Science.gov (United States)

    Gleckler, P. J.

    2014-12-01

    The process by which climate models are evaluated has evolved substantially over the past decade, with the Coupled Model Intercomparison Project (CMIP) serving as a centralizing activity for coordinating model experimentation and enabling research. Scientists with a broad spectrum of expertise have contributed to the CMIP model evaluation process, resulting in many hundreds of publications that have served as a key resource for the IPCC process. For several reasons, efforts are now underway to further systematize some aspects of the model evaluation process. First, some model evaluation can now be considered routine and should not require "re-inventing the wheel" or a journal publication simply to update results with newer models. Second, the benefit of CMIP research to model development has not been optimal because the publication of results generally takes several years and is usually not reproducible for benchmarking newer model versions. And third, there are now hundreds of model versions and many thousands of simulations, but there is no community-based mechanism for routinely monitoring model performance changes. An important change in the design of CMIP6 can help address these limitations. CMIP6 will include a small set standardized experiments as an ongoing exercise (CMIP "DECK": ongoing Diagnostic, Evaluation and Characterization of Klima), so that modeling groups can submit them at any time and not be overly constrained by deadlines. In this presentation, efforts to establish routine benchmarking of existing and future CMIP simulations will be described. To date, some benchmarking tools have been made available to all CMIP modeling groups to enable them to readily compare with CMIP5 simulations during the model development process. A natural extension of this effort is to make results from all CMIP simulations widely available, including the results from newer models as soon as the simulations become available for research. Making the results from routine

  12. Borehole climatology: a discussion based on contributions from climate modeling

    Directory of Open Access Journals (Sweden)

    J. F. González-Rouco

    2009-03-01

    Full Text Available Progress in understanding climate variability through the last millennium leans on simulation and reconstruction efforts. Exercises blending both approaches present a great potential for answering questions relevant both for the simulation and reconstruction of past climate, and depend on the specific peculiarities of proxies and methods involved in climate reconstructions, as well as on the realism and limitations of model simulations. This paper explores research specifically related to paleoclimate modeling and borehole climatology as a branch of climate reconstruction that has contributed significantly to our knowledge of the low frequency climate evolution during the last five centuries.

    The text flows around three main issues that group most of the interaction between model and geothermal efforts: the use of models as a validation tool for borehole climate reconstructions; comparison of geothermal information and model simulations as a means of either model validation or inference about past climate; and implications of the degree of realism on simulating subsurface climate on estimations of future climate change.

    The use of multi-centennial simulations as a surrogate reality for past climate suggests that within the simplified reality of climate models, methods and assumptions in borehole reconstructions deliver a consistent picture of past climate evolution at long time scales. Comparison of model simulations and borehole profiles indicate that borehole temperatures are responding to past external forcing and that more realism in the development of the soil model components in climate models is desirable. Such an improved degree of realism is important for the simulation of subsurface climate and air-ground interaction; results indicate it could also be crucial for simulating the adequate energy balance within climate change scenario experiments.

  13. Sensitivity of climate models: Comparison of simulated and observed patterns for past climates

    Energy Technology Data Exchange (ETDEWEB)

    Prell, W.L.; Webb, T. III.

    1992-08-01

    Predicting the potential climatic effects of increased concentrations of atmospheric carbon dioxide requires the continuing development of climate models. Confidence in the predictions will be much enhanced once the models are thoroughly tested in terms of their ability to simulate climates that differ significantly from today's climate. As one index of the magnitude of past climate change, the global mean temperature increase during the past 18,000 years is similar to that predicted for carbon dioxide--doubling. Simulating the climatic changes of the past 18,000 years, as well as the warmer-than-present climate of 6000 years ago and the climate of the last interglacial, around 126,000 years ago, provides an excellent opportunity to test the models that are being used in global climate change research. During the past several years, we have used paleoclimatic data to test the accuracy of the National Center for Atmospheric Research, Community Climate Model, Version 0, after changing its boundary conditions to those appropriate for past climates. We have assembled regional and near-global paleoclimatic data sets of pollen, lake level, and marine plankton data and calibrated many of the data in terms of climatic variables. We have also developed methods that permit direct quantitative comparisons between the data and model results. Our research has shown that comparing the model results with the data is an evolutionary process, because the models, the data, and the methods for comparison are continually being improved. During 1992, we have completed new modeling experiments, further analyzed previous model experiments, compiled new paleodata, made new comparisons between data and model results, and participated in workshops on paleoclimatic modeling.

  14. Mixing parameterizations in ocean climate modeling

    Science.gov (United States)

    Moshonkin, S. N.; Gusev, A. V.; Zalesny, V. B.; Byshev, V. I.

    2016-03-01

    Results of numerical experiments with an eddy-permitting ocean circulation model on the simulation of the climatic variability of the North Atlantic and the Arctic Ocean are analyzed. We compare the ocean simulation quality with using different subgrid mixing parameterizations. The circulation model is found to be sensitive to a mixing parametrization. The computation of viscosity and diffusivity coefficients by an original splitting algorithm of the evolution equations for turbulence characteristics is found to be as efficient as traditional Monin-Obukhov parameterizations. At the same time, however, the variability of ocean climate characteristics is simulated more adequately. The simulation of salinity fields in the entire study region improves most significantly. Turbulent processes have a large effect on the circulation in the long-term through changes in the density fields. The velocity fields in the Gulf Stream and in the entire North Atlantic Subpolar Cyclonic Gyre are reproduced more realistically. The surface level height in the Arctic Basin is simulated more faithfully, marking the Beaufort Gyre better. The use of the Prandtl number as a function of the Richardson number improves the quality of ocean modeling.

  15. The Whole Atmosphere Community Climate Model

    Science.gov (United States)

    Boville, B. A.; Garcia, R. R.; Sassi, F.; Kinnison, D.; Roble, R. G.

    The Whole Atmosphere Community Climate Model (WACCM) is an upward exten- sion of the National Center for Atmospheric Research Community Climate System Model. WACCM simulates the atmosphere from the surface to the lower thermosphere (140 km) and includes both dynamical and chemical components. The salient points of the model formulation will be summarized and several aspects of its performance will be discussed. Comparison with observations indicates that WACCM produces re- alistic temperature and zonal wind distributions. Both the mean state and interannual variability will be summarized. Temperature inversions in the midlatitude mesosphere have been reported by several authors and are also found in WACCM. These inver- sions are formed primarily by planetary wave forcing, but the background state on which they form also requires gravity wave forcing. The response to sea surface temperature (SST) anomalies will be examined by com- paring simulations with observed SSTs for 1950-1998 to a simulation with clima- tological annual cycle of SSTs. The response to ENSO events is found to extend though the winter stratosphere and mesosphere and a signal is also found at the sum- mer mesopause. The experimental framework allows the ENSO signal to be isolated, because no other forcings are included (e.g. solar variability and volcanic eruptions) which complicate the observational record. The temperature and wind variations asso- ciated with ENSO are large enough to generate significant perturbations in the chem- ical composition of the middle atmosphere, which will also be discussed.

  16. Numerical modeling of transformer inrush currents

    Science.gov (United States)

    Cardelli, E.; Faba, A.

    2014-02-01

    This paper presents an application of a vector hysteresis model to the prediction of the inrush current due the arbitrary initial excitation of a transformer after a fault. The approach proposed seems promising in order to predict the transient overshoot in current and the optimal time to close the circuit after the fault.

  17. Numerical modeling of transformer inrush currents

    Energy Technology Data Exchange (ETDEWEB)

    Cardelli, E. [Department of Industrial Engineering, University of Perugia, I-06125 Perugia (Italy); Center for Electric and Magnetic Applied Research (Italy); Faba, A., E-mail: faba@unipg.it [Department of Industrial Engineering, University of Perugia, I-06125 Perugia (Italy); Center for Electric and Magnetic Applied Research (Italy)

    2014-02-15

    This paper presents an application of a vector hysteresis model to the prediction of the inrush current due the arbitrary initial excitation of a transformer after a fault. The approach proposed seems promising in order to predict the transient overshoot in current and the optimal time to close the circuit after the fault.

  18. Regional climate simulations over Vietnam using the WRF model

    Science.gov (United States)

    Raghavan, S. V.; Vu, M. T.; Liong, S. Y.

    2016-10-01

    We present an analysis of the present-day (1961-1990) regional climate simulations over Vietnam. The regional climate model Weather Research and Forecasting (WRF) was driven by the global reanalysis ERA40. The performance of the regional climate model in simulating the observed climate is evaluated with a main focus on precipitation and temperature. The regional climate model was able to reproduce the observed spatial patterns of the climate, although with some biases. The model also performed better in reproducing the extreme precipitation and the interannual variability. Overall, the WRF model was able to simulate the main regional signatures of climate variables, seasonal cycles, and frequency distributions. This study is an evaluation of the present-day climate simulations of a regional climate model at a resolution of 25 km. Given that dynamical downscaling has become common for studying climate change and its impacts, the study highlights that much more improvements in modeling might be necessary to yield realistic simulations of climate at high resolutions before they can be used for impact studies at a local scale. The need for a dense network of observations is also realized as observations at high resolutions are needed when it comes to evaluations and validations of models at sub-regional and local scales.

  19. Model-based assessment of ecological adaptations of three forest tree species growing in Italy and impact on carbon and water balance at national scale under current and future climate scenarios

    Directory of Open Access Journals (Sweden)

    Vitale M

    2012-10-01

    Full Text Available A semi-empirical model has been used to estimate total net primary productivity, canopy transpiration and the water use efficiency under actual and future climate projections (B1 and A2 IPCC Scenarios of two deciduous (Fagus sylvatica, Quercus cerris and one evergreen tree species (Quercus ilex growing in Italy. In response to changes in the air temperature, the two deciduous species showed a strong reduction of NPP values, whereas the evergreen one showed very limited reductions. Under future warmer conditions, Q. ilex proved to be the best adapted species, probably for its drought-tolerant water-saving strategy, while Q. cerris suffered a reduction of transpiration, due to stomatal closure which was sensitive to the change of evaporative demand. Water Use Efficiency (WUE values did not increase in the B1 and A2 scenarios, indicating a non-conservative water-saving strategy, which likely affected the distribution pattern of Q. cerris under these conditions. Similar functional behaviour have been noted for F. sylvatica, although this species adopted a water spending strategy, typical of species growing in mesic environments, that could represent a risk for survival of beech population under extreme air temperature change. In this respect, the reduced suitable area for this species under the A2 scenario could reduce the possibilities of an upward shift toward higher altitudes.

  20. New Titan Saltation Threshold Experiments: Investigating Current and Past Climates

    Science.gov (United States)

    Bridges, N.; Burr, D. M.; Marshall, J.; Smith, J. K.; Emery, J. P.; Horst, S. M.; Nield, E.; Yu, X.

    2015-12-01

    Titan exhibits aeolian sand dunes that cover ~20% of its surface, attesting to significant sediment transport by the wind. Recent experiments in the Titan Wind Tunnel (TWT) at NASA Ames Research Center [1,2] found that the threshold friction speed needed to detach Titanian "sand" is about 50% higher than previous estimates based on theory alone [3], a result that might be explained by the low ratio of particle to fluid density on the body [1]. Following the successful completion of the initial Titan threshold tests, we are conducting new experiments that expand the pressure range above and below current Titan values. The basic experimental techniques are described in [1], with minor updates to the instrumentation as described in [2]. To reproduce the kinematic viscosity and particle friction Reynolds number equivalent to that expected for Titan's nitrogen atmosphere at 1.4 bars and 94 K requires that TWT be pressurized to 12.5 bars for air at 293K. In addition to running experiments at this pressure to reproduce previous results [1] and investigate low density (high density ratio) materials, TWT pressures of 3 and 8 bars are in the experimental matrix to understand threshold under past Titan conditions when the atmospheric pressure may have been lower [4]. Higher pressures, at 15 and 20 bars in TWT, are also being run to understand the putative effects of low density ratio conditions. Our experimental matrix for this follow-on work uses some of the same materials as previously used, including walnut shells, basalt, quartz, glass spheres, and various low density materials to better simulate the gravity-equivalent weight of Titan sand. For these experiments, the TWT is now equipped with a new high pressure Tavis transducer with sufficient sensitivity to measure freestream speeds of less than 0.5 m s-1 at 12.5 bars. New techniques include video documentation of the experiments. We are also investigating methods of measuring humidity of the wind tunnel environment and

  1. Holism, entrenchment, and the future of climate model pluralism

    Science.gov (United States)

    Lenhard, Johannes; Winsberg, Eric

    In this paper, we explore the extent to which issues of simulation model validation take on novel characteristics when the models in question become particularly complex. Our central claim is that complex simulation models in general, and global models of climate in particular, face a form of confirmation holism. This holism, moreover, makes analytic understanding of complex models of climate either extremely difficult or even impossible. We argue that this supports a position we call convergence skepticism: the belief that the existence of a plurality of different models making a plurality of different forecasts of future climate is likely to be a persistent feature of global climate science.

  2. Future meteorological drought: projections of regional climate models for Europe

    Science.gov (United States)

    Stagge, James; Tallaksen, Lena; Rizzi, Jonathan

    2015-04-01

    In response to the major European drought events of the last decade, projecting future drought frequency and severity in a non-stationary climate is a major concern for Europe. Prior drought studies have identified regional hotspots in the Mediterranean and Eastern European regions, but have otherwise produced conflicting results with regard to future drought severity. Some of this disagreement is likely related to the relatively coarse resolution of Global Climate Models (GCMs) and regional averaging, which tends to smooth extremes. This study makes use of the most current Regional Climate Models (RCMs) forced with CMIP5 climate projections to quantify the projected change in meteorological drought for Europe during the next century at a fine, gridded scale. Meteorological drought is quantified using the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI), which normalize accumulated precipitation and climatic water balance anomaly, respectively, for a specific location and time of year. By comparing projections for these two indices, the importance of precipitation deficits can be contrasted with the importance of evapotranspiration increases related to temperature changes. Climate projections are based on output from CORDEX (the Coordinated Regional Climate Downscaling Experiment), which provides high resolution regional downscaled climate scenarios that have been extensively tested for numerous regions around the globe, including Europe. SPI and SPEI are then calculated on a gridded scale at a spatial resolution of either 0.44 degrees (~50 km) or 0.11 degrees (~12.5km) for the three projected emission pathways (rcp26, rcp45, rcp85). Analysis is divided into two major sections: first validating the models with respect to observed historical trends in meteorological drought from 1970-2005 and then comparing drought severity and frequency during three future time periods (2011-2040, 2041-2070, 2071-2100) to the

  3. Modeling Bird Migration under Climate Change: A Mechanistic Approach

    Science.gov (United States)

    Smith, James A.

    2009-01-01

    behavior can be maintained over increasing and sustained environmental change. Also, the problem is much more complex than described by the current processes captured in our model. We have taken some important and interesting steps, and our model does demonstrate how local scale information about individual stop-over sites can be linked into the migratory flyway as a whole. We are incorporating additional, species specific, mechanistic processes to better reflect different climate change scenarios

  4. Modeling Bird Migration under Climate Change: A Mechanistic Approach

    Science.gov (United States)

    Smith, James A.

    2009-01-01

    behavior can be maintained over increasing and sustained environmental change. Also, the problem is much more complex than described by the current processes captured in our model. We have taken some important and interesting steps, and our model does demonstrate how local scale information about individual stop-over sites can be linked into the migratory flyway as a whole. We are incorporating additional, species specific, mechanistic processes to better reflect different climate change scenarios

  5. Conceptual Model of Climate Change Impacts at LANL

    Energy Technology Data Exchange (ETDEWEB)

    Dewart, Jean Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-17

    Goal 9 of the LANL FY15 Site Sustainability Plan (LANL 2014a) addresses Climate Change Adaptation. As part of Goal 9, the plan reviews many of the individual programs the Laboratory has initiated over the past 20 years to address climate change impacts to LANL (e.g. Wildland Fire Management Plan, Forest Management Plan, etc.). However, at that time, LANL did not yet have a comprehensive approach to climate change adaptation. To fill this gap, the FY15 Work Plan for the LANL Long Term Strategy for Environmental Stewardship and Sustainability (LANL 2015) included a goal of (1) establishing a comprehensive conceptual model of climate change impacts at LANL and (2) establishing specific climate change indices to measure climate change and impacts at Los Alamos. Establishing a conceptual model of climate change impacts will demonstrate that the Laboratory is addressing climate change impacts in a comprehensive manner. This paper fulfills the requirement of goal 1. The establishment of specific indices of climate change at Los Alamos (goal 2), will improve our ability to determine climate change vulnerabilities and assess risk. Future work will include prioritizing risks, evaluating options/technologies/costs, and where appropriate, taking actions. To develop a comprehensive conceptual model of climate change impacts, we selected the framework provided in the National Oceanic and Atmospheric Administration (NOAA) Climate Resilience Toolkit (http://toolkit.climate.gov/).

  6. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Auffhammer, M.; Hsiang, S. M.; Schlenker, W.; Sobel, A.

    2013-06-28

    Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

  7. On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa

    Science.gov (United States)

    Fotso-Nguemo, Thierry C.; Vondou, Derbetini A.; Pokam, Wilfried M.; Djomou, Zéphirin Yepdo; Diallo, Ismaïla; Haensler, Andreas; Tchotchou, Lucie A. Djiotang; Kamsu-Tamo, Pierre H.; Gaye, Amadou T.; Tchawoua, Clément

    2017-02-01

    In this paper, the regional climate model REMO is used to investigate the added value of downscaling low resolutions global climate models (GCMs) and the climate change projections over Central Africa. REMO was forced by two GCMs (EC-Earth and MPI-ESM), for the period from 1950 to 2100 under the Representative Concentration Pathway 8.5 scenario. The performance of the REMO simulations for current climate is compared first with REMO simulation driven by ERA-Interim reanalysis, then by the corresponding GCMs in order to determine whether REMO outputs are able to effectively lead to added value at local scale. We found that REMO is generally able to better represent some aspects of the rainfall inter-annual variability, the daily rainfall intensity distribution as well as the intra-seasonal variability of the Central African monsoon, though few biases are still evident. It is also found that the boundary conditions strongly influences the spatial distribution of seasonal 2-m temperature and rainfall. From the analysis of the climate change signal from the present period 1976-2005 to the future 2066-2095, we found that all models project a warming at the end of the twenty-first century although the details of the climate change differ between REMO and the driving GCMs, specifically in REMO where we observe a general decrease in rainfall. This rainfall decrease is associated with delayed onset and anticipated recession of the Central African monsoon and a shortening of the rainy season. Small-scales variability of the climate change signal for 2-m temperature are usually smaller than that of the large-scales climate change part. For rainfall however, small-scales induce change of about 70% compared to the present climate statistics.

  8. Nitrogen Controls on Climate Model Evapotranspiration.

    Science.gov (United States)

    Dickinson, Robert E.; Berry, Joseph A.; Bonan, Gordon B.; Collatz, G. James; Field, Christopher B.; Fung, Inez Y.; Goulden, Michael; Hoffmann, William A.; Jackson, Robert B.; Myneni, Ranga; Sellers, Piers J.; Shaikh, Muhammad

    2002-02-01

    Most evapotranspiration over land occurs through vegetation. The fraction of net radiation balanced by evapotranspiration depends on stomatal controls. Stomates transpire water for the leaf to assimilate carbon, depending on the canopy carbon demand, and on root uptake, if it is limiting. Canopy carbon demand in turn depends on the balancing between visible photon-driven and enzyme-driven steps in the leaf carbon physiology. The enzyme-driven component is here represented by a Rubisco-related nitrogen reservoir that interacts with plant-soil nitrogen cycling and other components of a climate model. Previous canopy carbon models included in GCMs have assumed either fixed leaf nitrogen, that is, prescribed photosynthetic capacities, or an optimization between leaf nitrogen and light levels so that in either case stomatal conductance varied only with light levels and temperature.A nitrogen model is coupled to a previously derived but here modified carbon model and includes, besides the enzyme reservoir, additional plant stores for leaf structure and roots. It also includes organic and mineral reservoirs in the soil; the latter are generated, exchanged, and lost by biological fixation, deposition and fertilization, mineralization, nitrification, root uptake, denitrification, and leaching. The root nutrient uptake model is a novel and simple, but rigorous, treatment of soil transport and root physiological uptake. The other soil components are largely derived from previously published parameterizations and global budget constraints.The feasibility of applying the derived biogeochemical cycling model to climate model calculations of evapotranspiration is demonstrated through its incorporation in the Biosphere-Atmosphere Transfer Scheme land model and a 17-yr Atmospheric Model Inter comparison Project II integration with the NCAR CCM3 GCM. The derived global budgets show land net primary production (NPP), fine root carbon, and various aspects of the nitrogen cycling are

  9. Climate model boundary conditions for four Cretaceous time slices

    NARCIS (Netherlands)

    Sewall, J.O.; Wal, R.S.W. van de; Zwan, C.J. van der; Oosterhout, C. van; Dijkstra, H.A.; Scotese, C.R.

    2007-01-01

    General circulation models (GCMs) are useful tools for investigating the characteristics and dynamics of past climates. Understanding of past climates contributes significantly to our overall understanding of Earth’s climate system. One of the most time consuming, and often daunting, tasks facing th

  10. Estimates of current debris from flux models

    Energy Technology Data Exchange (ETDEWEB)

    Canavan, G.H.

    1997-01-01

    Flux models that balance accuracy and simplicity are used to predict the growth of space debris to the present. Known and projected launch rates, decay models, and numerical integrations are used to predict distributions that closely resemble the current catalog-particularly in the regions containing most of the debris.

  11. Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Jaroslav Solc

    2009-06-01

    The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.

  12. Possible impact of climate change on meningitis in northwest Nigeria: an assessment using CMIP5 climate model simulations

    Science.gov (United States)

    Abdussalam, Auwal; Monaghan, Andrew; Steinhoff, Daniel; Dukic, Vanja; Hayden, Mary; Hopson, Thomas; Thornes, John; Leckebusch, Gregor

    2014-05-01

    Meningitis remains a major health burden throughout Sahelian Africa, especially in heavily-populated northwest Nigeria. Cases exhibit strong sensitivity to intra- and inter-annual climate variability, peaking during the hot and dry boreal spring months, raising concern that future climate change may increase the incidence of meningitis in the region. The impact of future climate change on meningitis risk in northwest Nigeria is assessed by forcing an empirical model of meningitis with monthly simulations from an ensemble of thirteen statistically downscaled global climate model projections from the Coupled Model Intercomparison Experiment Phase 5 (CMIP5) for RCPs 2.6, 6.0 and 8.5 scenarios. The results suggest future temperature increases due to climate change has the potential to significantly increase meningitis cases in both the early and late 21st century, and to increase the length of the meningitis season in the late century. March cases may increase from 23 per 100,000 people for present day (1990-2005), to 29-30 per 100,000 (p<0.01) in the early century (2020-2035) and 31-42 per 100,000 (p<0.01) in the late century (2060-2075), the range being dependent on the emissions scenario. It is noteworthy that these results represent the climatological potential for increased cases due to climate change, as we assume current prevention and treatment strategies remain similar in the future.

  13. A model for evaluating stream temperature response to climate change in Wisconsin

    Science.gov (United States)

    Stewart, Jana S.; Westenbroek, Stephen M.; Mitro, Matthew G.; Lyons, John D.; Kammel, Leah E.; Buchwald, Cheryl A.

    2015-01-01

    Expected climatic changes in air temperature and precipitation patterns across the State of Wisconsin may alter future stream temperature and flow regimes. As a consequence of flow and temperature changes, the composition and distribution of fish species assemblages are expected to change. In an effort to gain a better understanding of how climatic changes may affect stream temperature, an approach was developed to predict and project daily summertime stream temperature under current and future climate conditions for 94,341 stream kilometers across Wisconsin. The approach uses a combination of static landscape characteristics and dynamic time-series climatic variables as input for an Artificial Neural Network (ANN) Model integrated with a Soil-Water-Balance (SWB) Model. Future climate scenarios are based on output from downscaled General Circulation Models (GCMs). The SWB model provided a means to estimate the temporal variability in groundwater recharge and provided a mechanism to evaluate the effect of changing air temperature and precipitation on groundwater recharge and soil moisture. The Integrated Soil-Water-Balance and Artificial Neural Network version 1 (SWB-ANNv1) Model was used to simulate daily summertime stream temperature under current (1990–2008) climate and explained 76 percent of the variation in the daily mean based on validation at 67 independent sites. Results were summarized as July mean water temperature, and individual stream segments were classified by thermal class (cold, cold transition, warm transition, and warm) for comparison of current (1990–2008) with future climate conditions.

  14. Is a Universal Model for Loess Magnetism / Climate Connection Utopian?

    Science.gov (United States)

    Lagroix, F.; Banerjee, S. K.; Berquó, T. S.; Carvallo, C.; Guyodo, Y.

    2009-05-01

    Pleistocene loess deposition punctuated by periods of soil formation is observed, predominantly at mid- latitudes, over the Asian, European and North American continents. Geoscientists exercising in different disciplines have seized the opportunity handed by loess and paleosol deposits to study the climate of the past from a continental perspective. Paleomagnetists and mineral magnetists have already contributed significantly, most notably from Chinese Loess Plateau sequences. The former provided chronological constraints through the recovery of geomagnetic polarity changes and the latter discovered that roughly 30 nm ferrimagnetic particles were the source of magnetic susceptibility peak values in paleosol. Semi-quantitative models linking magnetic susceptibility to annual precipitation have been proposed but in all cases these are geographically restricted to local or regional models. How can we move forward, beyond the dominantly qualitative and regional models, towards a quantitative and a global model capable of inverting data from loess to paleoclimatic parameters? Is this utopian? The objective of this presentation is two-fold. First, we will take a wide angle look at the question/task at hand. Potential variables to be included are parent material (composition, grain size), post-depositional inputs (organic material, organisms), climate (temperature, moisture, etc.), physical parameters (slope, vegetation, pH, etc.), alteration (neoformation, dissolution, remobilization, recrystallisation). How do current magnetism based models address these different variables? What can we learn from the data, models and approaches of other disciplines such as elemental and isotope geochemistry, sedimentology and pedology? Secondly, we will explore, from the point of view of working with natural sample, the merits of different approaches such as physical and chemical separations. A comprehensive investigation, as outlined above, complemented by a similar systematic

  15. Analyzing the Response of Climate Perturbations to (Tropical) Cyclones using the WRF Model

    Science.gov (United States)

    Tewari, M.; Mittal, R.; Radhakrishnan, C.; Cipriani, J.; Watson, C.

    2015-12-01

    An analysis of global climate models shows considerable changes in the intensity and characteristics of future, warm climate cyclones. At regional scales, deviations in cyclone characteristics are often derived using idealized perturbations in the humidity, temperature and surface conditions. In this work, a more realistic approach is adopted by applying climate perturbations from the Community Climate System Model (CCSM4) to ERA-interim data to generate the initial and boundary conditions for future climate simulations. The climate signal perturbations are generated from the differences in 21 years of mean data from CCSM4 with representative concentration pathways (RCP8.5) for the periods: (a) 2070-2090 (future climate), (b) 2025-2045 (near-future climate) and (c) 1985-2005 (current climate). Four individual cyclone cases are simulated with and without climate perturbations using the Weather Research and Forecasting model with a nested configuration. Each cyclone is characterized by variations in intensity, landfall location, precipitation and societal damage. To calculate societal damage, we use the recently introduced Cyclone Damage Potential (CDP) index evolved from the Willis Hurricane Index (WHI). As CDP has been developed for general societal applications, this work should provide useful insights for resilience analyses and industry (e.g., re-insurance).

  16. Biodiversity in a changing climate: a synthesis of current and projected trends in the US

    Science.gov (United States)

    Staudinger, Michelle D.; Carter, Shawn L.; Cross, Molly S.; Dubois, Natalie S.; Duffy, J. Emmett; Enquist, Carolyn; Griffis, Roger; Hellmann, Jessica J.; Lawler, Joshua J.; O’Leary, John; Morrison, Scott A.; Sneddon, Lesley; Stein, Bruce A.; Thompson, Laura M.; Turner, Woody

    2013-01-01

    This paper provides a synthesis of the recent literature describing how global biodiversity is being affected by climate change and is projected to respond in the future. Current studies reinforce earlier findings of major climate-change-related impacts on biological systems and document new, more subtle after-effects. For example, many species are shifting their distributions and phenologies at faster rates than were recorded just a few years ago; however, responses are not uniform across species. Shifts have been idiosyncratic and in some cases counterintuitive, promoting new community compositions and altering biotic interactions. Although genetic diversity enhances species' potential to respond to variable conditions, climate change may outpace intrinsic adaptive capacities and increase the relative vulnerabilities of many organisms. Developing effective adaptation strategies for biodiversity conservation will not only require flexible decision-making and management approaches that account for uncertainties in climate projections and ecological responses but will also necessitate coordinated monitoring efforts.

  17. Assessing forest vulnerability and the potential distribution of pine beetles under current and future climate scenarios in the Interior West of the US

    Science.gov (United States)

    Evangelista, P.H.; Kumar, S.; Stohlgren, T.J.; Young, N.E.

    2011-01-01

    The aim of our study was to estimate forest vulnerability and potential distribution of three bark beetles (Curculionidae: Scolytinae) under current and projected climate conditions for 2020 and 2050. Our study focused on the mountain pine beetle (Dendroctonus ponderosae), western pine beetle (Dendroctonus brevicomis), and pine engraver (Ips pini). This study was conducted across eight states in the Interior West of the US covering approximately 2.2millionkm2 and encompassing about 95% of the Rocky Mountains in the contiguous US. Our analyses relied on aerial surveys of bark beetle outbreaks that occurred between 1991 and 2008. Occurrence points for each species were generated within polygons created from the aerial surveys. Current and projected climate scenarios were acquired from the WorldClim database and represented by 19 bioclimatic variables. We used Maxent modeling technique fit with occurrence points and current climate data to model potential beetle distributions and forest vulnerability. Three available climate models, each having two emission scenarios, were modeled independently and results averaged to produce two predictions for 2020 and two predictions for 2050 for each analysis. Environmental parameters defined by current climate models were then used to predict conditions under future climate scenarios, and changes in different species' ranges were calculated. Our results suggested that the potential distribution for bark beetles under current climate conditions is extensive, which coincides with infestation trends observed in the last decade. Our results predicted that suitable habitats for the mountain pine beetle and pine engraver beetle will stabilize or decrease under future climate conditions, while habitat for the western pine beetle will continue to increase over time. The greatest increase in habitat area was for the western pine beetle, where one climate model predicted a 27% increase by 2050. In contrast, the predicted habitat of the

  18. Behavioral modeling of Digitally Adjustable Current Amplifier

    OpenAIRE

    Josef Polak; Lukas Langhammer; Jan Jerabek

    2015-01-01

    This article presents the digitally adjustable current amplifier (DACA) and its analog behavioral model (ABM), which is suitable for both ideal and advanced analyses of the function block using DACA as active element. There are four levels of this model, each being suitable for simulation of a certain degree of electronic circuits design (e.g. filters, oscillators, generators). Each model is presented through a schematic wiring in the simulation program OrCAD, including a description of equat...

  19. Climate modelling: IPCC gazes into the future

    Science.gov (United States)

    Raper, Sarah

    2012-04-01

    In 2013, the Intergovernmental Panel on Climate Change will report on the next set of future greenhouse-gas emission scenarios, offering a rational alternative pathway for avoiding dangerous climate change.

  20. 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.

  1. Hybrid Surface Mesh Adaptation for Climate Modeling

    Institute of Scientific and Technical Information of China (English)

    Ahmed Khamayseh; Valmor de Almeida; Glen Hansen

    2008-01-01

    Solution-driven mesh adaptation is becoming quite popular for spatial error control in the numerical simulation of complex computational physics applications, such as climate modeling. Typically, spatial adaptation is achieved by element subdivision (h adaptation) with a primary goal of resolving the local length scales of interest. A second, lesspopular method of spatial adaptivity is called "mesh motion" (r adaptation); the smooth repositioning of mesh node points aimed at resizing existing elements to capture the local length scales. This paper proposes an adaptation method based on a combination of both element subdivision and node point repositioning (rh adaptation). By combining these two methods using the notion of a mobility function, the proposed approach seeks to increase the flexibility and extensibility of mesh motion algorithms while providing a somewhat smoother transition between refined regions than is pro-duced by element subdivision alone. Further, in an attempt to support the requirements of a very general class of climate simulation applications, the proposed method is de-signed to accommodate unstructured, polygonal mesh topologies in addition to the most popular mesh types.

  2. Measure the climate, model the city

    NARCIS (Netherlands)

    Boufidou, E.; Commandeur, T.J.F.; Nedkov, S.B.; Zlatanova, S.

    2011-01-01

    Modern large cities are characterized by a high building concentration, little aeration and lack of green spaces. Such characteristics create an urban climate which is different from the climate outside of cities. An example of an urban climate effect is the so-called Urban Heat Island: cities tend

  3. Sensitivity of climate models: Comparison of simulated and observed patterns for past climates

    Energy Technology Data Exchange (ETDEWEB)

    Prell, W.L.; Webb, T. III; Oglesby, R.J.

    1991-10-01

    Predicting the potential climatic effects of increased concentrations of atmospheric carbon dioxide requires the continuing development of climate models. As one index of the magnitude of past climates change, the global mean temperature increase during the past 18,000 years is similar to that predicted for carbon dioxide doubling. Simulating the climate changes of the past 18,000 years, as well as the warmer-than-present climate of 6000 years ago and the climate of the last interglacial, around 126,000 years ago, provides an excellent opportunity to test the models that are being used in global climate change research. During the past several years, we have used paleoclimatic data to test the accuracy of the NCAR CCMO (National Center for Atmospheric Research, Community Climate Model, Version 0), after changing its boundary conditions to those appropriate for past climates. We have assembled near-global paleoclimatic data sets of pollen, lake level, and marine plankton data and calibrated many of the data in terms of climatic variables. We have also developed methods that permit direct quantitative comparisons between the data and model results. Our comparisons have shown both some of the strengths and weaknesses of the model. The research so far has shown the feasibility of our methods for comparing paleoclimatic data and model results. Our research has also shown that comparing the model results with the data is an evolutionary process, because the models, the data, and the methods for comparison are continually being improved. During 1991, we have continued our studies and this Progress Report documents the results to date. During this year, we have completed new modeling experiments, compiled new data sets, made new comparisons between data and model results, and participated in workshops on paleoclimatic modeling. 37 refs.

  4. Simulation of Gravity Currents Using VOF Model

    Institute of Scientific and Technical Information of China (English)

    邹建锋; 黄钰期; 应新亚; 任安禄

    2002-01-01

    By the Volume of Fluid (VOF) multiphase flow model two-dimensional gravity currents with three phases including air are numerically simulated in this article. The necessity of consideration of turbulence effect for high Reynolds numbers is demonstrated quantitatively by LES (the Large Eddy Simulation) turbulence model. The gravity currents are simulated for h ≠ H as well as h = H, where h is the depth of the gravity current before the release and H is the depth of the intruded fluid. Uprising of swell occurs when a current flows horizontally into another lighter one for h ≠ H. The problems under what condition the uprising of swell occurs and how long it takes are considered in this article. All the simulated results are in reasonable agreement with the experimental results available.

  5. Comparing the effects of climate and impact model uncertainty on climate impacts estimates for grain maize

    Science.gov (United States)

    Holzkämper, Annelie; Honti, Mark; Fuhrer, Jürg

    2015-04-01

    Crop models are commonly applied to estimate impacts of projected climate change and to anticipate suitable adaptation measures. Thereby, uncertainties from global climate models, regional climate models, and impacts models cascade down to impact estimates. It is essential to quantify and understand uncertainties in impact assessments in order to provide informed guidance for decision making in adaptation planning. A question that has hardly been investigated in this context is how sensitive climate impact estimates are to the choice of the impact model approach. In a case study for Switzerland we compare results of three different crop modelling approaches to assess the relevance of impact model choice in relation to other uncertainty sources. The three approaches include an expert-based, a statistical and a process-based model. With each approach impact model parameter uncertainty and climate model uncertainty (originating from climate model chain and downscaling approach) are accounted for. ANOVA-based uncertainty partitioning is performed to quantify the relative importance of different uncertainty sources. Results suggest that uncertainty in estimated yield changes originating from the choice of the crop modelling approach can be greater than uncertainty from climate model chains. The uncertainty originating from crop model parameterization is small in comparison. While estimates of yield changes are highly uncertain, the directions of estimated changes in climatic limitations are largely consistent. This leads us to the conclusion that by focusing on estimated changes in climate limitations, more meaningful information can be provided to support decision making in adaptation planning - especially in cases where yield changes are highly uncertain.

  6. Empirical correction of a toy climate model

    CERN Document Server

    Allgaier, Nicholas A; Danforth, Christopher M

    2011-01-01

    Improving the accuracy of forecast models for physical systems such as the atmosphere is a crucial ongoing effort. Errors in state estimation for these often highly nonlinear systems has been the primary focus of recent research, but as that error has been successfully diminished, the role of model error in forecast uncertainty has duly increased. The present study is an investigation of a particular empirical correction procedure that is of special interest because it considers the model a "black box", and therefore can be applied widely with little modification. The procedure involves the comparison of short model forecasts with a reference "truth" system during a training period in order to calculate systematic (1) state-independent model bias and (2) state-dependent error patterns. An estimate of the likelihood of the latter error component is computed from the current state at every timestep of model integration. The effectiveness of this technique is explored in two experiments: (1) a perfect model scen...

  7. Regional climate modeling and development of climate adaptation decision aids for energy use in the Southwestern US

    Science.gov (United States)

    Higgins, G.; Darmenova, K.; Apling, D.; Kiley, H.

    2010-12-01

    There is currently a gap between the relatively coarse resolution science data that Global Climate Models (GCMs) produce and the high resolution tailored products that planners need to develop climate adaptation and mitigation strategies. Planners need to make decisions on infrastructure, budgets, policy, and programs related to their energy use and consumption and the impacts on the rest of the energy sector. We apply the Weather Research and Forecasting (WRF) model to conduct regional dynamical downscaling in the Southwestern US. The European Center/Hamburg Model (ECHAM5) GCM is used to provide initial and boundary conditions. Our methodology involves development of climatological indices of extreme weather and a variety of climate adaptation decision aids. We have further developed energy decision aids to translate the output from the WRF Regional Climate Model (RCM) into future electricity and natural gas demand for several sites in Colorado. These energy decision aids are developed using available energy consumption records from these sites over an historical period. These data are correlated with Heating Degree Days (HDD) and Cooling Degree Days (CCD) data from the RCM to develop models of energy use as a function of HDD/CDD. RCM estimates of HDD/CDD are presented for a current and future period along with projections of energy use. Additionally, derived statistical confidence bounds for these products are provided.

  8. Modelling Hydrological Consequences of Climate Change-Progress and Challenges

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps: (1) use of general circulation models (GCMs) to provide future global climate scenarios under the effect of increasing greenhouse gases,(2) use of downscaling techniques (both nested regional climate models, RCMs, and statistical methods)for "downscaling" the GCM output to the scales compatible with hydrological models, and (3) use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales.Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.

  9. Climate change and the potential global distribution of Aedes aegypti: spatial modelling using GIS and CLIMEX.

    Science.gov (United States)

    Khormi, Hassan M; Kumar, Lalit

    2014-05-01

    We examined the potential added risk posed by global climate change on the dengue vector Aedes aegypti abundance using CLIMEX, a powerful tool for exploring the relationship between the fundamental and realised niche of any species. After calibrating the model using data from several knowledge domains, including geographical distribution records, we estimated potential distributions of the mosquito under current and future potential scenarios. The impact of climate change on its potential distribution was assessed with two global climate models, the CSIRO-Mk3.0 and the MIROC-H, run with two potential, future emission scenarios (A1B and A2) published by the Intergovernmental Panel on Climate Change. We compared today's climate situation with two arbitrarily chosen future time points (2030 and 2070) to see the impact on the worldwide distribution of A. aegypti . The model for the current global climate indicated favourable areas for the mosquito within its known distribution in tropical and subtropical areas. However, even if much of the tropics and subtropics will continue to be suitable, the climatically favourable areas for A. aegypti globally are projected to contract under the future scenarios produced by these models, while currently unfavourable areas, such as inland Australia, the Arabian Peninsula, southern Iran and some parts of North America may become climatically favourable for this mosquito species. The climate models for the Aedes dengue vector presented here should be useful for management purposes as they can be adapted for decision/making regarding allocation of resources for dengue risk toward areas where risk infection remains and away from areas where climatic suitability is likely to decrease in the future.

  10. A potato model intercomparison across varying climates and productivity levels

    DEFF Research Database (Denmark)

    H. Fleisher, David; Condori, Bruno; Quiroz, Roberto

    2017-01-01

    A potato crop multi-model assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low- (Chinoli, Bolivia and Gisozi, Burundi) and high- (Jyndevad, Denmark and Washington, United States...

  11. Potato model uncertainty across common datasets and varying climate

    Science.gov (United States)

    A potato crop multi-model assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low- (Chinoli, Bolivia and Gisozi, Burundi) and high- (Jyndevad, Denmark and Washington, United States) ...

  12. Influence of Sea Ice on Arctic Marine Sulfur Biogeochemistry in the Community Climate System Model

    Energy Technology Data Exchange (ETDEWEB)

    Deal, Clara [Univ. of Alaska, Fairbanks, AL (United States); Jin, Meibing [Univ. of Alaska, Fairbanks, AL (United States)

    2013-06-30

    Global climate models (GCMs) have not effectively considered how responses of arctic marine ecosystems to a warming climate will influence the global climate system. A key response of arctic marine ecosystems that may substantially influence energy exchange in the Arctic is a change in dimethylsulfide (DMS) emissions, because DMS emissions influence cloud albedo. This response is closely tied to sea ice through its impacts on marine ecosystem carbon and sulfur cycling, and the ice-albedo feedback implicated in accelerated arctic warming. To reduce the uncertainty in predictions from coupled climate simulations, important model components of the climate system, such as feedbacks between arctic marine biogeochemistry and climate, need to be reasonably and realistically modeled. This research first involved model development to improve the representation of marine sulfur biogeochemistry simulations to understand/diagnose the control of sea-ice-related processes on the variability of DMS dynamics. This study will help build GCM predictions that quantify the relative current and possible future influences of arctic marine ecosystems on the global climate system. Our overall research objective was to improve arctic marine biogeochemistry in the Community Climate System Model (CCSM, now CESM). Working closely with the Climate Ocean Sea Ice Model (COSIM) team at Los Alamos National Laboratory (LANL), we added 1 sea-ice algae and arctic DMS production and related biogeochemistry to the global Parallel Ocean Program model (POP) coupled to the LANL sea ice model (CICE). Both CICE and POP are core components of CESM. Our specific research objectives were: 1) Develop a state-of-the-art ice-ocean DMS model for application in climate models, using observations to constrain the most crucial parameters; 2) Improve the global marine sulfur model used in CESM by including DMS biogeochemistry in the Arctic; and 3) Assess how sea ice influences DMS dynamics in the arctic marine

  13. The interaction of climate observation, parameter estimation, and mitigation decisions: Modeling climate policy under uncertainty with a partially observable Markov decision process

    Science.gov (United States)

    Fertig, E.; Webster, M.

    2013-12-01

    Though climate sensitivity remains poorly constrained, the trajectory of future greenhouse gas emissions and observable climate data could lead to improved estimates. Updated parameter estimates could alter decisions on greenhouse mitigation policy, which in turn influences future observed climate data and parameter estimation. Previous research on global climate mitigation policy neglects the cyclic nature of climate observation, parameter estimation, and policy action, instead treating uncertainty in climate sensitivity with scenario analysis or assuming that it will be resolved completely at some point in the future. This paper advances quantitative analysis of decision making under uncertainty (DMUU) in climate sensitivity by modeling the observation/parameter estimation/policy action cycle as a partially observable Markov decision process (POMDP). In a POMDP framework, an objective function is maximized while both observable parameters and probability distributions over unobservable parameters are retained as system states. As time progresses and more data are collected, the probability distributions are updated with Bayesian analysis. To model anthropogenic climate change as a POMDP, we maximize social welfare using a modified DICE model. Climate sensitivity is never directly observable; instead it is modeled with a distribution that is subject to Bayesian updating after observation of stochastic changes in global mean temperature. The maximization problem is posed as a stochastic Bellman equation, which expresses total social welfare as the sum of immediate social welfare resulting from a current mitigation decision under current knowledge of climate sensitivity and the expected cost-to-go, which is the discounted future social welfare in the subsequent time interval as a function of both global mean temperature and the consequent probability distribution over climate sensitivity. While similar, smaller stochastic dynamic programming problems can be solved

  14. Evidence of current impact of climate change on life : A walk from genes to the biosphere

    NARCIS (Netherlands)

    Penuelas, Josep; Sardans, Jordi; Estiarte, Marc; Ogaya, Roma; Carnicer, Jofre; Coll, Marta; Barbeta, Adria; Rivas-Ubach, Albert; Llusia, Joan; Garbulsky, Martin; Filella, Iolanda; Jump, Alistair S.

    We review the evidence of how organisms and populations are currently responding to climate change through phenotypic plasticity, genotypic evolution, changes in distribution and, in some cases, local extinction. Organisms alter their gene expression and metabolism to increase the concentrations of

  15. Updating Known Distribution Models for Forecasting Climate Change Impact on Endangered Species

    Science.gov (United States)

    Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo

    2013-01-01

    To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only. PMID:23840330

  16. Updating known distribution models for forecasting climate change impact on endangered species.

    Science.gov (United States)

    Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo

    2013-01-01

    To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only.

  17. Modelling Bambara Groundnut Yield in Southern Africa: Towards a Climate-Resilient Future

    Science.gov (United States)

    Karunaratne, A. S.; Walker, S.; Ruane, A. C.

    2015-01-01

    Current agriculture depends on a few major species grown as monocultures that are supported by global research underpinning current productivity. However, many hundreds of alternative crops have the potential to meet real world challenges by sustaining humanity, diversifying agricultural systems for food and nutritional security, and especially responding to climate change through their resilience to certain climate conditions. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilised African legume, is an exemplar crop for climate resilience. Predicted yield performances of Bambara groundnut by AquaCrop (a crop-water productivity model) were evaluated for baseline (1980-2009) and mid-century climates (2040-2069) under 20 downscaled Global Climate Models (CMIP5-RCP8.5), as well as for climate sensitivities (AgMIPC3MP) across 3 locations in Southern Africa (Botswana, South Africa, Namibia). Different land - races of Bambara groundnut originating from various semi-arid African locations showed diverse yield performances with diverse sensitivities to climate. S19 originating from hot-dry conditions in Namibia has greater future yield potential compared to the Swaziland landrace Uniswa Red-UN across study sites. South Africa has the lowest yield under the current climate, indicating positive future yield trends. Namibia reported the highest baseline yield at optimum current temperatures, indicating less yield potential in future climates. Bambara groundnut shows positive yield potential at temperatures of up to 31degC, with further warming pushing yields down. Thus, many regions in Southern Africa can utilize Bambara groundnut successfully in the coming decades. This modelling exercise supports decisions on genotypic suitability for present and future climates at specific locations.

  18. Modelling Bambara Groundnut Yield in Southern Africa: Towards a Climate-Resilient Future

    Science.gov (United States)

    Karunaratne, A. S.; Walker, S.; Ruane, A. C.

    2015-01-01

    Current agriculture depends on a few major species grown as monocultures that are supported by global research underpinning current productivity. However, many hundreds of alternative crops have the potential to meet real world challenges by sustaining humanity, diversifying agricultural systems for food and nutritional security, and especially responding to climate change through their resilience to certain climate conditions. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilised African legume, is an exemplar crop for climate resilience. Predicted yield performances of Bambara groundnut by AquaCrop (a crop-water productivity model) were evaluated for baseline (1980-2009) and mid-century climates (2040-2069) under 20 downscaled Global Climate Models (CMIP5-RCP8.5), as well as for climate sensitivities (AgMIPC3MP) across 3 locations in Southern Africa (Botswana, South Africa, Namibia). Different land - races of Bambara groundnut originating from various semi-arid African locations showed diverse yield performances with diverse sensitivities to climate. S19 originating from hot-dry conditions in Namibia has greater future yield potential compared to the Swaziland landrace Uniswa Red-UN across study sites. South Africa has the lowest yield under the current climate, indicating positive future yield trends. Namibia reported the highest baseline yield at optimum current temperatures, indicating less yield potential in future climates. Bambara groundnut shows positive yield potential at temperatures of up to 31degC, with further warming pushing yields down. Thus, many regions in Southern Africa can utilize Bambara groundnut successfully in the coming decades. This modelling exercise supports decisions on genotypic suitability for present and future climates at specific locations.

  19. Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

    Directory of Open Access Journals (Sweden)

    K. Steffens

    2013-08-01

    Full Text Available The assessment of climate change impacts on the risk for pesticide leaching needs careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in south-west Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM, greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO-model were generated by scaling a reference climate data set (1970–1999 for an important agricultural production area in south-west Sweden based on monthly change factors for 2070–2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios could provide robust probabilistic estimates of future pesticide losses and assessments of changes in pesticide leaching risks.

  20. Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

    Directory of Open Access Journals (Sweden)

    K. Steffens

    2014-02-01

    Full Text Available Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in south-western Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM, greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set (1970–1999 for an important agricultural production area in south-western Sweden based on monthly change factors for 2070–2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.

  1. Evidence of current impact of climate change on life: a walk from genes to the biosphere.

    Science.gov (United States)

    Peñuelas, Josep; Sardans, Jordi; Estiarte, Marc; Ogaya, Romà; Carnicer, Jofre; Coll, Marta; Barbeta, Adria; Rivas-Ubach, Albert; Llusià, Joan; Garbulsky, Martin; Filella, Iolanda; Jump, Alistair S

    2013-08-01

    We review the evidence of how organisms and populations are currently responding to climate change through phenotypic plasticity, genotypic evolution, changes in distribution and, in some cases, local extinction. Organisms alter their gene expression and metabolism to increase the concentrations of several antistress compounds and to change their physiology, phenology, growth and reproduction in response to climate change. Rapid adaptation and microevolution occur at the population level. Together with these phenotypic and genotypic adaptations, the movement of organisms and the turnover of populations can lead to migration toward habitats with better conditions unless hindered by barriers. Both migration and local extinction of populations have occurred. However, many unknowns for all these processes remain. The roles of phenotypic plasticity and genotypic evolution and their possible trade-offs and links with population structure warrant further research. The application of omic techniques to ecological studies will greatly favor this research. It remains poorly understood how climate change will result in asymmetrical responses of species and how it will interact with other increasing global impacts, such as N eutrophication, changes in environmental N : P ratios and species invasion, among many others. The biogeochemical and biophysical feedbacks on climate of all these changes in vegetation are also poorly understood. We here review the evidence of responses to climate change and discuss the perspectives for increasing our knowledge of the interactions between climate change and life.

  2. Crucial knowledge gaps in current understanding of climate change impacts on coral reef fishes

    KAUST Repository

    Wilson, S. K.

    2010-02-26

    Expert opinion was canvassed to identify crucial knowledge gaps in current understanding of climate change impacts on coral reef fishes. Scientists that had published three or more papers on the effects of climate and environmental factors on reef fishes were invited to submit five questions that, if addressed, would improve our understanding of climate change effects on coral reef fishes. Thirty-three scientists provided 155 questions, and 32 scientists scored these questions in terms of: (i) identifying a knowledge gap, (ii) achievability, (iii) applicability to a broad spectrum of species and reef habitats, and (iv) priority. Forty-two per cent of the questions related to habitat associations and community dynamics of fish, reflecting the established effects and immediate concern relating to climate-induced coral loss and habitat degradation. However, there were also questions on fish demographics, physiology, behaviour and management, all of which could be potentially affected by climate change. Irrespective of their individual expertise and background, scientists scored questions from different topics similarly, suggesting limited bias and recognition of a need for greater interdisciplinary and collaborative research. Presented here are the 53 highest-scoring unique questions. These questions should act as a guide for future research, providing a basis for better assessment and management of climate change impacts on coral reefs and associated fish communities.

  3. Crucial knowledge gaps in current understanding of climate change impacts on coral reef fishes.

    Science.gov (United States)

    Wilson, S K; Adjeroud, M; Bellwood, D R; Berumen, M L; Booth, D; Bozec, Y-Marie; Chabanet, P; Cheal, A; Cinner, J; Depczynski, M; Feary, D A; Gagliano, M; Graham, N A J; Halford, A R; Halpern, B S; Harborne, A R; Hoey, A S; Holbrook, S J; Jones, G P; Kulbiki, M; Letourneur, Y; De Loma, T L; McClanahan, T; McCormick, M I; Meekan, M G; Mumby, P J; Munday, P L; Ohman, M C; Pratchett, M S; Riegl, B; Sano, M; Schmitt, R J; Syms, C

    2010-03-15

    Expert opinion was canvassed to identify crucial knowledge gaps in current understanding of climate change impacts on coral reef fishes. Scientists that had published three or more papers on the effects of climate and environmental factors on reef fishes were invited to submit five questions that, if addressed, would improve our understanding of climate change effects on coral reef fishes. Thirty-three scientists provided 155 questions, and 32 scientists scored these questions in terms of: (i) identifying a knowledge gap, (ii) achievability, (iii) applicability to a broad spectrum of species and reef habitats, and (iv) priority. Forty-two per cent of the questions related to habitat associations and community dynamics of fish, reflecting the established effects and immediate concern relating to climate-induced coral loss and habitat degradation. However, there were also questions on fish demographics, physiology, behaviour and management, all of which could be potentially affected by climate change. Irrespective of their individual expertise and background, scientists scored questions from different topics similarly, suggesting limited bias and recognition of a need for greater interdisciplinary and collaborative research. Presented here are the 53 highest-scoring unique questions. These questions should act as a guide for future research, providing a basis for better assessment and management of climate change impacts on coral reefs and associated fish communities.

  4. Climatic modulation of recent trends in ocean acidification in the California Current System

    Science.gov (United States)

    Turi, G.; Lachkar, Z.; Gruber, N.; Münnich, M.

    2016-01-01

    We reconstruct the evolution of ocean acidification in the California Current System (CalCS) from 1979 through 2012 using hindcast simulations with an eddy-resolving ocean biogeochemical model forced with observation-based variations of wind and fluxes of heat and freshwater. We find that domain-wide pH and {{{Ω }}}{arag} in the top 60 m of the water column decreased significantly over these three decades by about -0.02 decade-1 and -0.12 decade-1, respectively. In the nearshore areas of northern California and Oregon, ocean acidification is reconstructed to have progressed much more rapidly, with rates up to 30% higher than the domain-wide trends. Furthermore, ocean acidification penetrated substantially into the thermocline, causing a significant domain-wide shoaling of the aragonite saturation depth of on average -33 m decade-1 and up to -50 m decade-1 in the nearshore area of northern California. This resulted in a coast-wide increase in nearly undersaturated waters and the appearance of waters with {{{Ω }}}{arag}\\lt 1, leading to a substantial reduction of habitat suitability. Averaged over the whole domain, the main driver of these trends is the oceanic uptake of anthropogenic CO2 from the atmosphere. However, recent changes in the climatic forcing have substantially modulated these trends regionally. This is particularly evident in the nearshore regions, where the total trends in pH are up to 50% larger and trends in {{{Ω }}}{arag} and in the aragonite saturation depth are even twice to three times larger than the purely atmospheric CO2-driven trends. This modulation in the nearshore regions is a result of the recent marked increase in alongshore wind stress, which brought elevated levels of dissolved inorganic carbon to the surface via upwelling. Our results demonstrate that changes in the climatic forcing need to be taken into consideration in future projections of the progression of ocean acidification in coastal upwelling regions.

  5. The Future of Planetary Climate Modeling and Weather Prediction

    Science.gov (United States)

    Del Genio, A. D.; Domagal-Goldman, S. D.; Kiang, N. Y.; Kopparapu, R. K.; Schmidt, G. A.; Sohl, L. E.

    2017-01-01

    Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.

  6. Climatic suitability of Aedes albopictus in Europe referring to climate change projections: comparison of mechanistic and correlative niche modelling approaches.

    Science.gov (United States)

    Fischer, D; Thomas, S M; Neteler, M; Tjaden, N B; Beierkuhnlein, C

    2014-02-13

    The Asian tiger mosquito, Aedes albopictus, is capable of transmitting a broad range of viruses to humans. Since its introduction at the end of the 20th century, it has become well established in large parts of southern Europe. As future expansion as a result of climate change can be expected, determining the current and projected future climatic suitability of this invasive mosquito in Europe is of interest. Several studies have tried to detect the potential habitats for this species, but differing data sources and modelling approaches must be considered when interpreting the findings. Here, various modelling methodologies are compared with special emphasis on model set-up and study design. Basic approaches and model algorithms for the projection of spatio-temporal trends within the 21st century differ substantially. Applied methods range from mechanistic models (e.g. overlay of climatic constraints based on geographic information systems or rather process-based approaches) to correlative niche models. We conclude that spatial characteristics such as introduction gateways and dispersal pathways need to be considered. Laboratory experiments addressing the climatic constraints of the mosquito are required for improved modelling results. However, the main source of uncertainty remains the insufficient knowledge about the species' ability to adapt to novel environments.

  7. COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J.

    2013-02-07

    The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

  8. Climatic and thermodynamic modelling of rapid development drivages

    Energy Technology Data Exchange (ETDEWEB)

    Crossley, A.J.; Lowndes, I.S. [University of Nottingham (United Kingdom). School of Chemical, Environmental and Mining Engineering

    2001-07-01

    This paper details the construction of a computer based climatic prediction tool currently being developed at the University of Nottingham. The model predicts the psychrometric and thermodynamic conditions within single entry drivages, taking into account the effects of the strata and the machinery on the ventilation air. The interaction between the air travelling through the forced ventilation ducting and back down the drivage is considered, through a series of leakage and heat transfer calculations. It is intended that the model may be further developed to include procedures to investigate the effects of applying localized cooling systems. Preliminary results obtained from the model are shown and compared against measurements collected from within a UK rapid development drivage. 14 refs., 4 figs.

  9. Unpacking the mechanisms captured by a correlative species distribution model to improve predictions of climate refugia.

    Science.gov (United States)

    Briscoe, Natalie J; Kearney, Michael R; Taylor, Chris A; Wintle, Brendan A

    2016-07-01

    Climate refugia are regions that animals can retreat to, persist in and potentially then expand from under changing environmental conditions. Most forecasts of climate change refugia for species are based on correlative species distribution models (SDMs) using long-term climate averages, projected to future climate scenarios. Limitations of such methods include the need to extrapolate into novel environments and uncertainty regarding the extent to which proximate variables included in the model capture processes driving distribution limits (and thus can be assumed to provide reliable predictions under new conditions). These limitations are well documented; however, their impact on the quality of climate refugia predictions is difficult to quantify. Here, we develop a detailed bioenergetics model for the koala. It indicates that range limits are driven by heat-induced water stress, with the timing of rainfall and heat waves limiting the koala in the warmer parts of its range. We compare refugia predictions from the bioenergetics model with predictions from a suite of competing correlative SDMs under a range of future climate scenarios. SDMs were fitted using combinations of long-term climate and weather extremes variables, to test how well each set of predictions captures the knowledge embedded in the bioenergetics model. Correlative models produced broadly similar predictions to the bioenergetics model across much of the species' current range - with SDMs that included weather extremes showing highest congruence. However, predictions in some regions diverged significantly when projecting to future climates due to the breakdown in correlation between climate variables. We provide unique insight into the mechanisms driving koala distribution and illustrate the importance of subtle relationships between the timing of weather events, particularly rain relative to hot-spells, in driving species-climate relationships and distributions. By unpacking the mechanisms

  10. Climate change impact on the establishment and seasonal abundance of Invasive Mosquito Species: current state and future risk maps over southeast Europe

    Science.gov (United States)

    Tagaris, Efthimios; -Eleni Sotiropoulou, Rafaella; Sotiropoulos, Andreas; Spanos, Ioannis; Milonas, Panayiotis; Michaelakis, Antonios

    2017-04-01

    Establishment and seasonal abundance of a region for Invasive Mosquito Species (IMS) are related to climatic parameters such as temperature and precipitation. In this work the current state is assessed using data from the European Climate Assessment and Dataset (ECA&D) project over Greece and Italy for the development of current spatial risk databases of IMS. Results are validated from the installation of a prototype IMS monitoring device that has been designed and developed in the framework of the LIFE CONOPS project at key points across the two countries. Since climate models suggest changes in future temperature and precipitation rates, the future potentiality of IMS establishment and spread over Greece and Italy is assessed using the climatic parameters in 2050's provided by the NASA GISS GCM ModelE under the IPCC-A1B emissions scenarios. The need for regional climate projections in a finer grid size is assessed using the Weather Research and Forecasting (WRF) model to dynamically downscale GCM simulations. The estimated changes in the future meteorological parameters are combined with the observation data in order to estimate the future levels of the climatic parameters of interest. The final product includes spatial distribution maps presenting the future suitability of a region for the establishment and seasonal abundance of the IMS over Greece and Italy. Acknowledgement: LIFE CONOPS project "Development & demonstration of management plans against - the climate change enhanced - invasive mosquitoes in S. Europe" (LIFE12 ENV/GR/000466).

  11. Deficiencies in the simulation of the geographic distribution of climate types by global climate models

    Science.gov (United States)

    Zhang, Xianliang; Yan, Xiaodong

    2016-05-01

    The performances of General Circulation Models (GCMs) when checked with conventional methods (i.e. correlation, bias, root-mean-square error) can only be evaluated for each variable individually. The geographic distribution of climate type in GCM simulations, which reflects the spatial attributes of models and is related closely to the terrestrial biosphere, has not yet been evaluated. Thus, whether the geographic distribution of climate types was well simulated by GCMs was evaluated in this study for nine GCMs. The results showed that large areas of climate zones classified by the GCMs were allocated incorrectly when compared to the basic climate zones established by observed data. The percentages of wrong areas covered approximately 30-50 % of the total land area for most models. In addition, the temporal shift in the distribution of climate zones according to the GCMs was found to be inaccurate. Not only were the locations of shifts poorly simulated, but also the areas of shift in climate zones. Overall, the geographic distribution of climate types was not simulated well by the GCMs, nor was the temporal shift in the distribution of climate zones. Thus, a new method on how to evaluate the simulated distribution of climate types for GCMs was provided in this study.

  12. Quantifying Greenland freshwater flux underestimates in climate models

    Science.gov (United States)

    Little, Christopher M.; Piecuch, Christopher G.; Chaudhuri, Ayan H.

    2016-05-01

    Key processes regulating the mass balance of the Greenland Ice Sheet (GIS) are not represented in current-generation climate models. Here using output from 19 different climate models forced with a high-end business-as-usual emissions pathway, we compare modeled freshwater fluxes (FWF) to a parameterization based on midtropospheric temperature. By the mid 21st century, parameterized GIS FWF is 478 ± 215 km3 yr-1 larger than modeled—over 3 times the 1992-2011 rate of GIS mass loss. By the late 21st century, ensemble mean parameterized GIS FWF anomalies are comparable to FWF anomalies over the northern North Atlantic Ocean, equivalent to approximately 11 cm of global mean sea level rise. The magnitude and spread of these underestimates underscores the need for assessments of the coupled response of the ocean to increased FWF that recognize: (1) the widely varying freshwater budgets of each model and (2) uncertainty in the relationship between GIS FWF and atmospheric temperature.

  13. Climate suitability for European ticks: assessing species distribution models against null models and projection under AR5 climate.

    Science.gov (United States)

    Williams, Hefin Wyn; Cross, Dónall Eoin; Crump, Heather Louise; Drost, Cornelis Jan; Thomas, Christopher James

    2015-08-28

    There is increasing evidence that the geographic distribution of tick species is changing. Whilst correlative Species Distribution Models (SDMs) have been used to predict areas that are potentially suitable for ticks, models have often been assessed without due consideration for spatial patterns in the data that may inflate the influence of predictor variables on species distributions. This study used null models to rigorously evaluate the role of climate and the potential for climate change to affect future climate suitability for eight European tick species, including several important disease vectors. We undertook a comparative assessment of the performance of Maxent and Mahalanobis Distance SDMs based on observed data against those of null models based on null species distributions or null climate data. This enabled the identification of species whose distributions demonstrate a significant association with climate variables. Latest generation (AR5) climate projections were subsequently used to project future climate suitability under four Representative Concentration Pathways (RCPs). Seven out of eight tick species exhibited strong climatic signals within their observed distributions. Future projections intimate varying degrees of northward shift in climate suitability for these tick species, with the greatest shifts forecasted under the most extreme RCPs. Despite the high performance measure obtained for the observed model of Hyalomma lusitanicum, it did not perform significantly better than null models; this may result from the effects of non-climatic factors on its distribution. By comparing observed SDMs with null models, our results allow confidence that we have identified climate signals in tick distributions that are not simply a consequence of spatial patterns in the data. Observed climate-driven SDMs for seven out of eight species performed significantly better than null models, demonstrating the vulnerability of these tick species to the effects of

  14. The climate4impact platform: Providing, tailoring and facilitating climate model data access

    Science.gov (United States)

    Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael

    2017-04-01

    One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European

  15. Geospatial Issues in Energy-Climate Modeling: Implications for Modelers, Economists, Climate Scientists and Policy Makers

    Science.gov (United States)

    Newmark, R. L.; Arent, D.; Sullivan, P.; Short, W.

    2010-12-01

    Accurate characterizations of renewable energy technologies, particularly wind, solar, geothermal, and biomass, require an increasingly sophisticated understanding of location-specific attributes, including generation or production costs and the cost of transmission or transportation to a point of use, and climate induced changes to the resource base. Capturing these site-specific characteristics in national and global models presents both unique opportunities and challenges. National and global decisions, ideally, should be informed by geospatially rich data and analysis. Here we describe issues related to and initial advances in representing renewable energy technologies in global models, and the resulting implications for climate stabilization analysis and global assessments, including IPCC’s Assessment Round 5 and IEA’s World Energy Outlook.

  16. Improved Analysis of Earth System Models and Observations using Simple Climate Models

    Science.gov (United States)

    Nadiga, B. T.; Urban, N. M.

    2016-12-01

    Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using

  17. Multivariate probabilistic projections using imperfect climate models. Part II: robustness of methodological choices and consequences for climate sensitivity

    Science.gov (United States)

    Sexton, David M. H.; Murphy, James M.

    2012-06-01

    A method for providing probabilistic climate projections, which applies a Bayesian framework to information from a perturbed physics ensemble, a multimodel ensemble and observations, was demonstrated in an accompanying paper. This information allows us to account for the combined effects of more sources of uncertainty than in any previous study of the equilibrium response to doubled CO2 concentrations, namely parametric and structural modelling uncertainty, internal variability, and observational uncertainty. Such probabilistic projections are dependent on the climate models and observations used but also contain an element of expert judgement. Two expert choices in the methodology involve the amount of information used to (a) specify the effects of structural modelling uncertainty and (b) represent the observational metrics that constrain the probabilistic climate projections. These choices, effected by selecting how many multivariate eigenvectors of a large set of climate variables to retain in our analysis, are investigated in more detail. We also show sensitivity tests that explore a range of key expert choices. For changes in annual global mean temperature and regional changes over England and Wales and Northern Europe, the variations in the projections across the sensitivity studies are small compared to the overall uncertainty, demonstrating that the projections are robust to reasonable variations in key assumptions. We are therefore confident that, despite sampling sources of uncertainty more comprehensively than previously, the improved multivariate treatment of observational metrics has narrowed the probability distribution of climate sensitivity consistent with evidence currently available. Our 5th, 50th, and 95th percentiles are in the range 2.2-2.4, 3.2-3.3, and 4.1-4.5K, respectively. The main caveat is that the handling of structural uncertainty does not account for systematic errors common to the current set of climate models and finding methods to

  18. Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios

    Science.gov (United States)

    Goderniaux, Pascal; BrouyèRe, Serge; Blenkinsop, Stephen; Burton, Aidan; Fowler, Hayley J.; Orban, Philippe; Dassargues, Alain

    2011-12-01

    Several studies have highlighted the potential negative impact of climate change on groundwater reserves, but additional work is required to help water managers plan for future changes. In particular, existing studies provide projections for a stationary climate representative of the end of the century, although information is demanded for the near future. Such time-slice experiments fail to account for the transient nature of climatic changes over the century. Moreover, uncertainty linked to natural climate variability is not explicitly considered in previous studies. In this study we substantially improve upon the state-of-the-art by using a sophisticated transient weather generator in combination with an integrated surface-subsurface hydrological model (Geer basin, Belgium) developed with the finite element modeling software "HydroGeoSphere." This version of the weather generator enables the stochastic generation of large numbers of equiprobable climatic time series, representing transient climate change, and used to assess impacts in a probabilistic way. For the Geer basin, 30 equiprobable climate change scenarios from 2010 to 2085 have been generated for each of six different regional climate models (RCMs). Results show that although the 95% confidence intervals calculated around projected groundwater levels remain large, the climate change signal becomes stronger than that of natural climate variability by 2085. Additionally, the weather generator's ability to simulate transient climate change enabled the assessment of the likely time scale and associated uncertainty of a specific impact, providing managers with additional information when planning further investment. This methodology constitutes a real improvement in the field of groundwater projections under climate change conditions.

  19. An Overview of BCC Climate System Model Development and Application for Climate Change Studies

    Institute of Scientific and Technical Information of China (English)

    WU Tongwen; WU Fanghua; LIU Yiming; ZHANG Fang; SHI Xueli; CHU Min; ZHANG Jie; FANG Yongjie; WANG Fang; LU Yixiong; LIU Xiangwen; SONG Lianchun; WEI Min; LIU Qianxia; ZHOU Wenyan; DONG Min; ZHAO Qigeng; JI Jinjun; Laurent LI; ZHOU Mingyu; LI Weiping; WANG Zaizhi; ZHANG Hua; XIN Xiaoge; ZHANG Yanwu; ZHANG Li; LI Jianglong

    2014-01-01

    This paper reviews recent progress in the development of the Beijing Climate Center Climate System Model (BCC-CSM) and its four component models (atmosphere, land surface, ocean, and sea ice). Two recent versions are described: BCC-CSM1.1 with coarse resolution (approximately 2.8125◦×2.8125◦) and BCC-CSM1.1(m) with moderate resolution (approximately 1.125◦×1.125◦). Both versions are fully cou-pled climate-carbon cycle models that simulate the global terrestrial and oceanic carbon cycles and include dynamic vegetation. Both models well simulate the concentration and temporal evolution of atmospheric CO2 during the 20th century with anthropogenic CO2 emissions prescribed. Simulations using these two versions of the BCC-CSM model have been contributed to the Coupled Model Intercomparison Project phase fi ve (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). These simulations are available for use by both national and international communities for investigating global climate change and for future climate pro jections. Simulations of the 20th century climate using BCC-CSM1.1 and BCC-CSM1.1(m) are presented and validated, with particular focus on the spatial pattern and seasonal evolution of precipitation and surface air temperature on global and continental scales. Simulations of climate during the last millennium and pro jections of climate change during the next century are also presented and discussed. Both BCC-CSM1.1 and BCC-CSM1.1(m) perform well when compared with other CMIP5 models. Preliminary analyses in-dicate that the higher resolution in BCC-CSM1.1(m) improves the simulation of mean climate relative to BCC-CSM1.1, particularly on regional scales.

  20. Use of a crop climate modeling system to evaluate climate change adaptation practices: maize yield in East Africa

    Science.gov (United States)

    Moore, N. J.; Alagarswamy, G.; Andresen, J.; Olson, J.; Thornton, P.

    2013-12-01

    Sub Saharan African agriculture is dominated by small-scale farmers and is heavily depend on growing season precipitation. Recent studies indicate that anthropogenic- induced warming including the Indian Ocean sea surface significantly influences precipitation in East Africa. East Africa is a useful region to assess impacts of future climate because of its large rainfall gradient, large percentage of its area being sub-humid or semi-arid, complex climatology and topography, varied soils, and because the population is particularly vulnerable to shifts in climate. Agronomic adaptation practices most commonly being considered include include a shift to short season, drought resistant maize varieties, better management practices especially fertilizer use, and irrigation. The effectiveness of these practices with climate change had not previously been tested. We used the WorldClim data set to represent current climate and compared the current and future climate scenarios of 4 Global Climate Models (GCMs) including a wetter (CCSM) and drier (HadCM3) GCM downscaled to 6 km resolution. The climate data was then used in the process-based CERES maize crop model to simulate the current period (representing 1960- 1990) and change in future maize production (from 2000 to 2050s). The effectiveness of agronomic practices, including short duration maize variety, fertilizer use and irrigation, to reduce projected future yield losses due to climate change were simulated. The GCMs project an increase in maximum temperature during growing season ranging from 1.5 to 3°C. Changes in precipitation were dependent on the GCM, with high variability across different topographies land cover types and elevations. Projected warmer temperatures in the future scenarios accelerated plant development and led to a reduction in growing season length and yields even where moisture was sufficient Maize yield changes in 2050 relative to the historical period were highly varied, in excess of +/- 500 kg

  1. Evaluation of climate extremes in the CMIP5 model simulations

    Science.gov (United States)

    Sillmann, J.; Kharin, S.; Zhang, X.; Zwiers, F. W.

    2011-12-01

    Climate extremes manifest an important aspect of natural climate variability and anthropogenic climate change. To minimize human and financial losses caused by extreme events it is important to have reliable projections of their occurrence and intensity. State-of-the-art global climate models represented by the CMIP5 model ensemble are widely used as tools to simulate the present and project the future climate. Thus, it is crucial to get an understanding of how well climate extremes are simulated by these models in the present climate to be able to appraise their usefulness for future projections. We calculated a global set of well-defined indices for climate extremes based on daily temperature and precipitation data with the available CMIP5 models and use the indices to present a first-order evaluation of the model performance in comparison with re-analysis and a gridded observational dataset. We also focus our analysis on regional aspects of the model performance. Some of the indices are based on threshold exceedance, i.e. percentage of days below the 10th or above the 90th percentile of the maximum and minimum temperature. These indices require special attention for model evaluation as by definition the threshold exceedance is approximately 10% for individual models, re-analysis, and observations. We introduce a novel method to evaluate the model performance particular for these indices.

  2. Behavioral modeling of Digitally Adjustable Current Amplifier

    Directory of Open Access Journals (Sweden)

    Josef Polak

    2015-03-01

    Full Text Available This article presents the digitally adjustable current amplifier (DACA and its analog behavioral model (ABM, which is suitable for both ideal and advanced analyses of the function block using DACA as active element. There are four levels of this model, each being suitable for simulation of a certain degree of electronic circuits design (e.g. filters, oscillators, generators. Each model is presented through a schematic wiring in the simulation program OrCAD, including a description of equations representing specific functions in the given level of the simulation model. The design of individual levels is always verified using PSpice simulations. The ABM model has been developed based on practically measured values of a number of DACA amplifier samples. The simulation results for proposed levels of the ABM model are shown and compared with the results of the real easurements of the active element DACA.

  3. Assessment of rainfall-runoff modelling for climate change mitigation

    Science.gov (United States)

    Otieno, Hesbon; Han, Dawei; Woods, Ross

    2015-04-01

    Sustainable water resources management requires reliable methods for quantification of hydrological variables. This is a big challenge in developing countries, due to the problem of inadequate data as a result of sparse gauge networks. Successive occurrence of both abundance and shortage of water can arise in a catchment within the same year, with deficit situations becoming an increasingly occurring phenomenon in Kenya. This work compares the performance of two models in the Tana River catchment in Kenya, in generation of synthetic flow data. One of the models is the simpler USGS Thornthwaite monthly water balance model that uses a monthly time step and has three parameters. In order to explore alternative modelling schemes, the more complex Pitman model with 19 parameters was also applied in the catchment. It is uncertain whether the complex model (Pitman) will do better than the simple model, because a model with a large number of parameters may do well in the current system but poorly in future. To check this we have used old data (1970-1985) to calibrate the models and to validate with recent data (after 1985) to see which model is robust over time. This study is relevant and useful to water resources managers in scenario analysis for water resources management, planning and development in African countries with similar climates and catchment conditions.

  4. THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE.

    Science.gov (United States)

    Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

    2015-10-01

    The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran's universities. This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran's public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran's libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries.

  5. THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE

    Science.gov (United States)

    Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

    2015-01-01

    Background: The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran’s universities. Methods: This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran’s public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. Results: of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran’s libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Conclusions: Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries. PMID:26622203

  6. Present-day and ice-covered equilibrium states in a comprehensive climate model

    OpenAIRE

    J. Marotzke; Botzet, M.

    2007-01-01

    We show that in a comprehensive climate model both the current climate and a completely ice-covered Earth are stable states under today's total solar irradiance (TSI) and CO2 level. We employ the Max Planck Institute for Meteorology coupled atmosphere-ocean general circulation model ECHAM5/MPI-OM, at relatively high resolution (horizontally T63 in the atmosphere and 1.5 degrees in the ocean). Setting TSI to near-zero causes a transition from realistic present-day climate to a completely ice-c...

  7. Potential climate effect of mineral aerosols over West Africa. Part I: model validation and contemporary climate evaluation

    Science.gov (United States)

    Ji, Zhenming; Wang, Guiling; Pal, Jeremy S.; Yu, Miao

    2016-02-01

    Mineral dusts present in the atmosphere can play an important role in climate over West Africa and surrounding regions. However, current understanding regarding how dust aerosols influence climate of West Africa is very limited. In this study, a regional climate model is used to investigate the potential climatic impacts of dust aerosols. Two sets of simulations driven by reanalysis and Earth System Model boundary conditions are performed with and without the representation of dust processes. The model, regardless of the boundary forcing, captures the spatial and temporal variability of the aerosol optical depth and surface concentration. The shortwave radiative forcing of dust is negative at the surface and positive in the atmosphere, with greater changes in the spring and summer. The presence of mineral dusts causes surface cooling and lower troposphere heating, resulting in a stabilization effect and reduction in precipitation in the northern portion of the monsoon close to the dust emissions region. This results in an enhancement of precipitation to the south. While dusts cause the lower troposphere to stabilize, upper tropospheric cooling makes the region more prone to intense deep convection as is evident by a simulated increase in extreme precipitation. In a companion paper, the impacts of dust emissions on future West African climate are investigated.

  8. Constraining Transient Climate Sensitivity Using Coupled Climate Model Simulations of Volcanic Eruptions

    KAUST Repository

    Merlis, Timothy M.

    2014-10-01

    Coupled climate model simulations of volcanic eruptions and abrupt changes in CO2 concentration are compared in multiple realizations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1). The change in global-mean surface temperature (GMST) is analyzed to determine whether a fast component of the climate sensitivity of relevance to the transient climate response (TCR; defined with the 1%yr-1 CO2-increase scenario) can be estimated from shorter-time-scale climate changes. The fast component of the climate sensitivity estimated from the response of the climate model to volcanic forcing is similar to that of the simulations forced by abrupt CO2 changes but is 5%-15% smaller than the TCR. In addition, the partition between the top-of-atmosphere radiative restoring and ocean heat uptake is similar across radiative forcing agents. The possible asymmetry between warming and cooling climate perturbations, which may affect the utility of volcanic eruptions for estimating the TCR, is assessed by comparing simulations of abrupt CO2 doubling to abrupt CO2 halving. There is slightly less (~5%) GMST change in 0.5 × CO2 simulations than in 2 × CO2 simulations on the short (~10 yr) time scales relevant to the fast component of the volcanic signal. However, inferring the TCR from volcanic eruptions is more sensitive to uncertainties from internal climate variability and the estimation procedure. The response of the GMST to volcanic eruptions is similar in GFDL CM2.1 and GFDL Climate Model, version 3 (CM3), even though the latter has a higher TCR associated with a multidecadal time scale in its response. This is consistent with the expectation that the fast component of the climate sensitivity inferred from volcanic eruptions is a lower bound for the TCR.

  9. Climate forcings and climate sensitivities diagnosed from atmospheric global circulation models

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Bruce T. [Boston University, Department of Geography and Environment, Boston, MA (United States); Knight, Jeff R.; Ringer, Mark A. [Met Office Hadley Centre, Exeter (United Kingdom); Deser, Clara; Phillips, Adam S. [National Center for Atmospheric Research, Boulder, CO (United States); Yoon, Jin-Ho [University of Maryland, Cooperative Institute for Climate and Satellites, Earth System Science Interdisciplinary Center, College Park, MD (United States); Cherchi, Annalisa [Centro Euro-Mediterraneo per i Cambiamenti Climatici, and Istituto Nazionale di Geofisica e Vulcanologia, Bologna (Italy)

    2010-12-15

    Understanding the historical and future response of the global climate system to anthropogenic emissions of radiatively active atmospheric constituents has become a timely and compelling concern. At present, however, there are uncertainties in: the total radiative forcing associated with changes in the chemical composition of the atmosphere; the effective forcing applied to the climate system resulting from a (temporary) reduction via ocean-heat uptake; and the strength of the climate feedbacks that subsequently modify this forcing. Here a set of analyses derived from atmospheric general circulation model simulations are used to estimate the effective and total radiative forcing of the observed climate system due to anthropogenic emissions over the last 50 years of the twentieth century. They are also used to estimate the sensitivity of the observed climate system to these emissions, as well as the expected change in global surface temperatures once the climate system returns to radiative equilibrium. Results indicate that estimates of the effective radiative forcing and total radiative forcing associated with historical anthropogenic emissions differ across models. In addition estimates of the historical sensitivity of the climate to these emissions differ across models. However, results suggest that the variations in climate sensitivity and total climate forcing are not independent, and that the two vary inversely with respect to one another. As such, expected equilibrium temperature changes, which are given by the product of the total radiative forcing and the climate sensitivity, are relatively constant between models, particularly in comparison to results in which the total radiative forcing is assumed constant. Implications of these results for projected future climate forcings and subsequent responses are also discussed. (orig.)

  10. CONSTABLE: A Global Climate Model for Classroom Use.

    Science.gov (United States)

    Cerveny, Randall S.; And Others

    1985-01-01

    Described is the global climate model CONSTABLE (Climatic One-Dimensional Numerical Simulation of the Annual Balance of Latitudinal Energy), which can be used in undergraduate and graduate level climatology courses. Classroom exercises that can be used with the model are also included. (RM)

  11. A potato model intercomparison across varying climates and productivity levels

    NARCIS (Netherlands)

    Fleisher, David H.; Condori, Bruno; Quiroz, Roberto; Alva, Ashok; Asseng, Senthold; Barreda, Carolina; Bindi, Marco; Boote, Kenneth J.; Ferrise, Roberto; Franke, Angelinus C.; Govindakrishnan, Panamanna M.; Harahagazwe, Dieudonne; Hoogenboom, Gerrit; Naresh Kumar, Soora; Merante, Paolo; Nendel, Claas; Olesen, Jorgen E.; Parker, Phillip S.; Raes, Dirk; Raymundo, Rubi; Ruane, Alex C.; Stockle, Claudio; Supit, Iwan; Vanuytrecht, Eline; Wolf, Joost; Woli, Prem

    2016-01-01

    A potato crop multimodel assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low-input (Chinoli, Bolivia and Gisozi, Burundi)- and high-input (Jyndevad, Denmark and Washington, United

  12. Storm Water Management Model Climate Adjustment Tool (SWMM-CAT)

    Science.gov (United States)

    The US EPA’s newest tool, the Stormwater Management Model (SWMM) – Climate Adjustment Tool (CAT) is meant to help municipal stormwater utilities better address potential climate change impacts affecting their operations. SWMM, first released in 1971, models hydrology and hydrauli...

  13. The Application of Geobiocoenological Landscape Typology in The Modelling of Climate Change Implications

    Directory of Open Access Journals (Sweden)

    Vlčková Veronika

    2015-11-01

    Full Text Available Geobiocoenological landscape typology, which is used in landscape planning in the Czech Republic, includes vegetation zonation of the landscape. Vegetation zones are determined by climatic conditions. Changes in climatic conditions will probably be manifested in the shift of vegetation zones in the landscape. Mathematical geobiocoenological model of vegetation zonation of the landscape is based on the general ecological relationship between the current vegetation zonation and present climatic conditions and the assumption that this general relationship will be maintained in the future. The paper presents the application of the model using the example of the prediction of changes in climatic conditions for the Norway spruce (the first-generation of the model and grapevine (the second-generation of the model in the Czech Republic. In the case of the Norway spruce example, the model shows that the predicted changes in climatic conditions will prevent the cultivation of the spruce in the Czech Republic outside its natural range in mountainous areas. The results of the presented model for grapevine show significant enlargement of areas climatically suitable for growing grapes within the studied area.These examples demonstrate the potential for the application of geobiocoenological landscape typology in the modeling of the effects of climate change in the landscape.

  14. High Resolution Simulation of a Colorado Rockies Extreme Snow and Rain Event in both a Current and Future Climate

    Science.gov (United States)

    Rasmussen, Roy; Ikeda, Kyoko; Liu, Changhai; Gutmann, Ethan; Gochis, David

    2016-04-01

    Modeling of extreme weather events often require very finely resolved treatment of atmospheric circulation structures in order to produce and localize the large moisture fluxes that result in extreme precipitation. This is particularly true for cool season orographic precipitation processes where the representation of the landform can significantly impact vertical velocity profiles and cloud moisture entrainment rates. This study presents results for high resolution regional climate modeling study of the Colorado Headwaters region using an updated version of the Weather Research and Forecasting (WRF) model run at 4 km horizontal resolution and a hydrological extension package called WRF-Hydro. Previous work has shown that the WRF modeling system can produce credible depictions of winter orographic precipitation over the Colorado Rockies if run at horizontal resolutions warming on total precipitation, snow-rain partitioning and surface hydrological fluxes (evapotranspiration and runoff) will be discussed in the context of how potential changes in temperature impact the amount of precipitation, the phase of precipitation (rain vs. snow) and the timing and amplitude of streamflow responses. The results show using the Pseudo Global Warming technique that intense precipitation rates significantly increased during the event and a significant fraction of the snowfall converts to rain which significantly amplifies the runoff response from one where runoff is produced gradually to one in which runoff is rapidly translated into streamflow values that approach significant flooding risks. Results from a new, CONUS scale high resolution climate simulation of extreme events in a current and future climate will be presented as time permits.

  15. Regional-Scale Climate Change: Observations and Model Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, Raymond S; Diaz, Henry F

    2010-12-14

    This collaborative proposal addressed key issues in understanding the Earth's climate system, as highlighted by the U.S. Climate Science Program. The research focused on documenting past climatic changes and on assessing future climatic changes based on suites of global and regional climate models. Geographically, our emphasis was on the mountainous regions of the world, with a particular focus on the Neotropics of Central America and the Hawaiian Islands. Mountain regions are zones where large variations in ecosystems occur due to the strong climate zonation forced by the topography. These areas are particularly susceptible to changes in critical ecological thresholds, and we conducted studies of changes in phonological indicators based on various climatic thresholds.

  16. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    DEFF Research Database (Denmark)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian;

    2016-01-01

    Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes...... use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared...... to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice...

  17. Climate Change Hotspots Identification in China through the CMIP5 Global Climate Model Ensemble

    Directory of Open Access Journals (Sweden)

    Huanghe Gu

    2014-01-01

    Full Text Available China is one of the countries vulnerable to adverse climate changes. The potential climate change hotspots in China throughout the 21st century are identified in this study by using a multimodel, multiscenario climate model ensemble that includes Phase Five of the Coupled Model Intercomparison Project (CMIP5 atmosphere-ocean general circulation models. Both high (RCP8.5 and low (RCP4.5 greenhouse gas emission trajectories are tested, and both the mean and extreme seasonal temperature and precipitation are considered in identifying regional climate change hotspots. Tarim basin and Tibetan Plateau in West China are identified as persistent regional climate change hotspots in both the RCP4.5 and RCP8.5 scenarios. The aggregate impacts of climate change increase throughout the 21st century and are more significant in RCP8.5 than in RCP4.5. Extreme hot event and mean temperature are two climate variables that greatly contribute to the hotspots calculation in all regions. The contribution of other climate variables exhibits a notable subregional variability. South China is identified as another hotspot based on the change of extreme dry event, especially in SON and DJF, which indicates that such event will frequently occur in the future. Our results can contribute to the designing of national and cross-national adaptation and mitigation policies.

  18. Incorporating vegetation feedbacks in regional climate modeling over West Africa

    Science.gov (United States)

    Erfanian, A.; Wang, G.; Yu, M.; Ahmed, K. F.; Anyah, R. O.

    2015-12-01

    Despite major advancements in modeling of the climate system, incorporating vegetation dynamics into climate models is still at the initial stages making it an ongoing research topic. Only few of GCMs participating in CMIP5 simulations included the vegetation dynamics component. Consideration for vegetation dynamics is even less common in RCMs. In this study, RegCM4.3.4-CLM4-CN-DV, a regional climate model synchronously coupled with a land surface component that includes both Carbon-Nitrogen (CN) and Dynamic-Vegetation (DV) processes is used to simulate and project regional climate over West Africa. Due to its unique regional features, West Africa climate is known for being susceptible to land-atmosphere interactions, enhancing the importance of including vegetation dynamics in modeling climate over this region. In this study the model is integrated for two scenarios (present-day and future) using outputs from four GCMs participating in CMIP5 (MIROC, CESM, GFDL and CCSM4) as lateral boundary conditions, which form the basis of a multi-model ensemble. Results of model validation indicates that ensemble of all models outperforms each of individual models in simulating present-day temperature and precipitation. Therefore, the ensemble set is used to analyze the impact of including vegetation dynamics in the RCM on future projection of West Africa's climate. Results from the ensemble analysis will be presented, together with comparison among individual models.

  19. Improving Understanding of the Agulhas Current and Its Global Climate Impacts

    Science.gov (United States)

    Beal, Lisa; Biastoch, Arne

    2010-05-01

    Working Group on the Climatic Importance of the Greater Agulhas System; Portland, Oregon, 20-21 February 2010; The first meeting of the new Scientific Committee on Oceanic Research (SCOR) Working Group 136 was held to discuss recent developments in understanding the greater Agulhas Current system and future research directions. The overarching goal of the working group is to improve understanding and awareness of the regional and global climate impacts of the Agulhas Current, a major western boundary current that flows along the east coast of Africa, and its interocean leakage. In addition to studying modern circulation, the working group is motivated by recent paleodata that suggest that through the currents' southern influence on the Atlantic meridional overturning circulation (AMOC), changes in the leakage of warm and salty Agulhas waters into the Atlantic may have triggered the end of ice ages. In terms of global climate, this arguably puts the importance of the greater Agulhas system on a par with Heinrich (land-ice release) events and high-latitude deepwater formation.

  20. Modeling the influence of climate change on watershed systems: Adaptation through targeted practices

    Science.gov (United States)

    Dudula, John; Randhir, Timothy O.

    2016-10-01

    Climate change may influence hydrologic processes of watersheds (IPCC, 2013) and increased runoff may cause flooding, eroded stream banks, widening of stream channels, increased pollutant loading, and consequently impairment of aquatic life. The goal of this study was to quantify the potential impacts of climate change on watershed hydrologic processes and to evaluate scale and effectiveness of management practices for adaptation. We simulate baseline watershed conditions using the Hydrological Simulation Program Fortran (HSPF) simulation model to examine the possible effects of changing climate on watershed processes. We also simulate the effects of adaptation and mitigation through specific best management strategies for various climatic scenarios. With continuing low-flow conditions and vulnerability to climate change, the Ipswich watershed is the focus of this study. We quantify fluxes in runoff, evapotranspiration, infiltration, sediment load, and nutrient concentrations under baseline and climate change scenarios (near and far future). We model adaptation options for mitigating climate effects on watershed processes using bioretention/raingarden Best Management Practices (BMPs). It was observed that climate change has a significant impact on watershed runoff and carefully designed and maintained BMPs at subwatershed scale can be effective in mitigating some of the problems related to stormwater runoff. Policy options include implementation of BMPs through education and incentives for scale-dependent and site specific bioretention units/raingardens to increase the resilience of the watershed system to current and future climate change.

  1. Circulation patterns related to debris-flow triggering in the Zermatt valley in current and future climates

    Science.gov (United States)

    van den Heuvel, Floor; Goyette, Stéphane; Rahman, Kazi; Stoffel, Markus

    2016-11-01

    The principal objective of this study was to investigate the types of large-scale meteorological situations that are conducive to the precipitation and temperature conditions most likely to trigger debris flows in the Zermatt valley, Switzerland, under current and future climates. A two-dimensional Bayesian probability calculation was applied to take account of uncertainties in debris-flow triggering. Precipitation quantities exceeding the 95th percentile of daily precipitation amounts were found to have a significantly higher probability to coincide with observed debris flows. A different relationship exists for extreme temperatures, however. Southerly air flows, weak horizontal pressure gradients over Europe, and westerly flows are mostly associated with observed debris flows and 95th precipitation percentile exceedances. These principal flow directions are well represented in the regional climate model (RCM) HIRHAM control simulations for events exceeding the 95th precipitation percentile and the 30th temperature percentile. Under the IPCC A2 emission scenario, westerly and southerly flows are mostly responsible for these precipitation and temperature conditions under the hypothesis of slow adaptation to climate change (HS1/HC1). Under the hypothesis of rapid adaptation to climate change (HS1/HS1), southerly flows and weak horizontal pressure gradients are likely to gain in importance. In both scenarios for the future, southeasterly flows are among the principal flow directions responsible for the joint exceedance of the 95th precipitation percentile and the 30th temperature percentile, while these were absent in observations and the control simulation.

  2. The impact of iceberg calving on climate: a model study with a fully coupled ice-sheet - climate model

    Science.gov (United States)

    Bugelmayer, Marianne; Roche, Didier; Renssen, Hans

    2013-04-01

    In the current period of climate change the understanding of the interactions between different parts of the climate system gets more and more important. The ice-sheets and ice-shelves, an important part of this system, experienced strong changes in the geological past, ranging from fully ice free to ice covered - thereby altering the whole climate. In the present climate, thousands of icebergs are released every year from Greenland and Antarctica, acting as a moving source of freshwater and a sink of latent heat. As a consequence, these icebergs alter the oceans' stratification and facilitate the formation of sea ice, thus influencing the state of the ocean and of the atmosphere. Up to now, the impact of icebergs on climate has been addressed in different studies which utilize climate models using freshwater and latent heat fluxes to parameterize icebergs. Mostly these fluxes were equally distributed around the coast. However, more recently iceberg modules were integrated into climate models to take into account the temporal and spatial distribution of the iceberg melting. In the presented study, an earth system model of intermediate complexity - iLOVECLIM - that includes a 3D dynamic - thermodynamic iceberg module (Jongma et al., 2008) is coupled to the Grenoble ice shelves and land ice model - GRISLI (Ritz et al., 1997, 2001). In GRISLI, ice sheets evolve according to the precipitation and temperature received from iLOVECLIM. In turn, GRISLI provides its topography and the ice mask to the atmospheric component of iLOVECLIM and all freshwater fluxes (ablation and calving) to its oceanic component. The ablation is directly put into the uppermost layer of the ocean, whereas the calving is used to generate icebergs at the calving sites following the size distribution of Bigg et al. (1997). Using this model set-up we analyse the evolution and the equilibrium state of the Greenland ice-sheet under pre-industrial conditions within three different coupling methods. All

  3. Production and use of regional climate model projections - A Swedish perspective on building climate services.

    Science.gov (United States)

    Kjellström, Erik; Bärring, Lars; Nikulin, Grigory; Nilsson, Carin; Persson, Gunn; Strandberg, Gustav

    2016-09-01

    We describe the process of building a climate service centred on regional climate model results from the Rossby Centre regional climate model RCA4. The climate service has as its central facility a web service provided by the Swedish Meteorological and Hydrological Institute where users can get an idea of various aspects of climate change from a suite of maps, diagrams, explaining texts and user guides. Here we present the contents of the web service and how this has been designed and developed in collaboration with users of the service in a dialogue reaching over more than a decade. We also present the ensemble of climate projections with RCA4 that provides the fundamental climate information presented at the web service. In this context, RCA4 has been used to downscale nine different coupled atmosphere-ocean general circulation models (AOGCMs) from the 5th Coupled Model Intercomparison Project (CMIP5) to 0.44° (c. 50 km) horizontal resolution over Europe. Further, we investigate how this ensemble relates to the CMIP5 ensemble. We find that the iterative approach involving the users of the climate service has been successful as the service is widely used and is an important source of information for work on climate adaptation in Sweden. The RCA4 ensemble samples a large degree of the spread in the CMIP5 ensemble implying that it can be used to illustrate uncertainties and robustness in future climate change in Sweden. The results also show that RCA4 changes results compared to the underlying AOGCMs, sometimes in a systematic way.

  4. Multi-century Changes to Global Climate and Carbon Cycle: Results from a Coupled Climate and Carbon Cycle Model

    Energy Technology Data Exchange (ETDEWEB)

    Bala, G; Caldeira, K; Mirin, A; Wickett, M; Delire, C

    2005-02-17

    In this paper, we use a coupled climate and carbon cycle model to investigate the global climate and carbon cycle changes out to year 2300 that would occur if CO{sub 2} emissions from all the currently estimated fossil fuel resources were released to the atmosphere. By year 2300, the global climate warms by about 8 K and atmospheric CO{sub 2} reaches 1423 ppmv. The warming is higher than anticipated because the sensitivity to radiative forcing increases as the simulation progresses. In our simulation, the rate of emissions peak at over 30 PgC yr{sup -1} early in the 22nd century. Even at year 2300, nearly 50% of cumulative emissions remain in the atmosphere. In our simulations both soils and living biomass are net carbon sinks throughout the simulation. Despite having relatively low climate sensitivity and strong carbon uptake by the land biosphere, our model projections suggest severe long-term consequences for global climate if all the fossil-fuel carbon is ultimately released to the atmosphere.

  5. Multi-century Changes to Global Climate and Carbon Cycle: Results from a Coupled Climate and Carbon Cycle Model

    Energy Technology Data Exchange (ETDEWEB)

    Bala, G; Caldeira, K; Mirin, A; Wickett, M; Delire, C

    2005-02-17

    In this paper, we use a coupled climate and carbon cycle model to investigate the global climate and carbon cycle changes out to year 2300 that would occur if CO{sub 2} emissions from all the currently estimated fossil fuel resources were released to the atmosphere. By year 2300, the global climate warms by about 8 K and atmospheric CO{sub 2} reaches 1423 ppmv. The warming is higher than anticipated because the sensitivity to radiative forcing increases as the simulation progresses. In our simulation, the rate of emissions peak at over 30 PgC yr{sup -1} early in the 22nd century. Even at year 2300, nearly 50% of cumulative emissions remain in the atmosphere. In our simulations both soils and living biomass are net carbon sinks throughout the simulation. Despite having relatively low climate sensitivity and strong carbon uptake by the land biosphere, our model projections suggest severe long-term consequences for global climate if all the fossil-fuel carbon is ultimately released to the atmosphere.

  6. Climate change impacts on the future distribution of date palms: a modeling exercise using CLIMEX.

    Directory of Open Access Journals (Sweden)

    Farzin Shabani

    Full Text Available Climate is changing and, as a consequence, some areas that are climatically suitable for date palm (Phoenix dactylifera L. cultivation at the present time will become unsuitable in the future. In contrast, some areas that are unsuitable under the current climate will become suitable in the future. Consequently, countries that are dependent on date fruit export will experience economic decline, while other countries' economies could improve. Knowledge of the likely potential distribution of this economically important crop under current and future climate scenarios will be useful in planning better strategies to manage such issues. This study used CLIMEX to estimate potential date palm distribution under current and future climate models by using one emission scenario (A2 with two different global climate models (GCMs, CSIRO-Mk3.0 (CS and MIROC-H (MR. The results indicate that in North Africa, many areas with a suitable climate for this species are projected to become climatically unsuitable by 2100. In North and South America, locations such as south-eastern Bolivia and northern Venezuela will become climatically more suitable. By 2070, Saudi Arabia, Iraq and western Iran are projected to have a reduction in climate suitability. The results indicate that cold and dry stresses will play an important role in date palm distribution in the future. These results can inform strategic planning by government and agricultural organizations by identifying new areas in which to cultivate this economically important crop in the future and those areas that will need greater attention due to becoming marginal regions for continued date palm cultivation.

  7. Climate change impacts on the future distribution of date palms: a modeling exercise using CLIMEX.

    Science.gov (United States)

    Shabani, Farzin; Kumar, Lalit; Taylor, Subhashni

    2012-01-01

    Climate is changing and, as a consequence, some areas that are climatically suitable for date palm (Phoenix dactylifera L.) cultivation at the present time will become unsuitable in the future. In contrast, some areas that are unsuitable under the current climate will become suitable in the future. Consequently, countries that are dependent on date fruit export will experience economic decline, while other countries' economies could improve. Knowledge of the likely potential distribution of this economically important crop under current and future climate scenarios will be useful in planning better strategies to manage such issues. This study used CLIMEX to estimate potential date palm distribution under current and future climate models by using one emission scenario (A2) with two different global climate models (GCMs), CSIRO-Mk3.0 (CS) and MIROC-H (MR). The results indicate that in North Africa, many areas with a suitable climate for this species are projected to become climatically unsuitable by 2100. In North and South America, locations such as south-eastern Bolivia and northern Venezuela will become climatically more suitable. By 2070, Saudi Arabia, Iraq and western Iran are projected to have a reduction in climate suitability. The results indicate that cold and dry stresses will play an important role in date palm distribution in the future. These results can inform strategic planning by government and agricultural organizations by identifying new areas in which to cultivate this economically important crop in the future and those areas that will need greater attention due to becoming marginal regions for continued date palm cultivation.

  8. Elements of change 1994. Climate-radiation feedbacks: The current state of the science

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-09-01

    This report presents the details of the Climate-Radiation Feedback summer seminar. Topics include: radiative transfer; radiative properties of clouds; absorption of radiation in the atmosphere due to clouds; global cloud climatology; aerosols; general circulation models; and convection. Individual papers have been indexed separately for the database.

  9. A coupled climate model simulation of Marine Isotope Stage 3 stadial climate

    Directory of Open Access Journals (Sweden)

    J. Brandefelt

    2011-01-01

    Full Text Available We present a coupled global climate model (CGCM simulation, integrated for 1500 years to quasi-equilibrium, of a stadial (cold period within Marine Isotope Stage 3 (MIS 3. The simulated Greenland stadial 12 (GS12; ~44 ka BP annual global mean surface temperature (Ts is 5.5 °C higher than in the simulated recent past (RP climate and 1.3 °C lower than in the simulated Last Glacial Maximum (LGM; 21 ka BP climate. The simulated GS12 climate is evaluated against proxy data of sea surface temperature (SST. Simulated SSTs fall within the uncertainty range of the proxy SSTs for 30–50% of the sites depending on season. Proxy SSTs are higher than simulated SSTs in the Central North Atlantic, in contrast to earlier simulations of MIS 3 stadial climate in which proxy SSTs were found to be lower than simulated SST. The annual global mean Ts only changes by 0.10 °C from model years 500–599 to the last century of the simulation, indicating that the climate system may be close to equilibrium already after 500 years of integration. However, significant regional differences between the last century of the simulation and model years 500–599, with a maximum of 8 °C in temperature and 65% in precipitation in Southeastern Greenland in boreal winter, exist. Further, the agreement between simulated and proxy SST is improved from model years 500–599 to the last century of the simulation. El-Niño-Southern Oscillation (ENSO teleconnections in mean sea level pressure (MSLP are analysed for the last 300 years of the GS12, LGM and RP climate simulations. In agreement with an earlier study, we find that GS12 and LGM forcing and boundary conditions induce major modifications to ENSO teleconnections. However, significant differences in the teleconnection patterns are found between a 300-year time-slice starting after 195 model years and the last 300 years of the simulation. Thus we conclude that both the mean state and the

  10. The hydrological response of the Ourthe catchment to climate change as modelled by the HBV model

    Directory of Open Access Journals (Sweden)

    T. L. A. Driessen

    2009-11-01

    Full Text Available The Meuse is an important river in western Europe, and almost exclusively rain-fed. Projected changes in precipitation characteristics due to climate change, therefore, are expected to have a considerable effect on the hydrological regime of the river Meuse. We focus on an important tributary of the Meuse, the Ourthe, measuring about 1600 km2. The well-known hydrological model HBV is forced with three high-resolution (0.088° regional climate scenarios, each based on one of three different IPCC CO2 emission scenarios: A1B, A2 and B1. To represent the current climate, a reference model run at the same resolution is used. Prior to running the hydrological model, the biases in the climate model output are investigated and corrected for. Different approaches to correct the distributed climate model output using single-site observations are compared. Correcting the spatially averaged temperature and precipitation is found to give the best results, but still large differences exist between observations and simulations. The bias corrected data are then used to force HBV. Results indicate a small increase in overall discharge for especially the B1 scenario during the beginning of the 21st century. Towards the end of the century, all scenarios show a decrease in summer discharge, partially because of the diminished buffering effect by the snow pack, and an increased discharge in winter. It should be stressed, however, that we used results from only one GCM (the only one available at such a high resolution. It would be interesting to repeat the analysis with multiple models.

  11. Climate change projections for Greek viticulture as simulated by a regional climate model

    Science.gov (United States)

    Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos

    2017-07-01

    Viticulture represents an important economic activity for Greek agriculture. Winegrapes are cultivated in many areas covering the whole Greek territory, due to the favorable soil and climatic conditions. Given the dependence of viticulture on climate, the vitivinicultural sector is expected to be affected by possible climatic changes. The present study is set out to investigate the impacts of climatic change in Greek viticulture, using nine bioclimatic indices for the period 1981-2100. For this purpose, reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the regional climatic model Regional Climate Model Version 3 (RegCM3) are used. It was found that the examined regional climate model estimates satisfactorily these bioclimatic indices. The results of the study show that the increasing trend of temperature and drought will affect all wine-producing regions in Greece. In vineyards in mountainous regions, the impact is positive, while in islands and coastal regions, it is negative. Overall, it should be highlighted that for the first time that Greece is classified into common climatic characteristic categories, according to the international Geoviticulture Multicriteria Climatic Classification System (MCC system). According to the proposed classification, Greek viticulture regions are estimated to have similar climatic characteristics with the warmer wine-producing regions of the world up to the end of twenty-first century. Wine growers and winemakers should take the findings of the study under consideration in order to take measures for Greek wine sector adaptation and the continuation of high-quality wine production.

  12. Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods

    Science.gov (United States)

    Hakala, Kirsti; Addor, Nans; Seibert, Jan

    2017-04-01

    Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of

  13. The Urgent Need for Improved Climate Models and Predictions

    Science.gov (United States)

    Goddard, Lisa; Baethgen, Walter; Kirtman, Ben; Meehl, Gerald

    2009-09-01

    An investment over the next 10 years of the order of US$2 billion for developing improved climate models was recommended in a report (http://wcrp.wmo.int/documents/WCRP_WorldModellingSummit_Jan2009.pdf) from the May 2008 World Modelling Summit for Climate Prediction, held in Reading, United Kingdom, and presented by the World Climate Research Programme. The report indicated that “climate models will, as in the past, play an important, and perhaps central, role in guiding the trillion dollar decisions that the peoples, governments and industries of the world will be making to cope with the consequences of changing climate.” If trillions of dollars are going to be invested in making decisions related to climate impacts, an investment of $2 billion, which is less than 0.1% of that amount, to provide better climate information seems prudent. One example of investment in adaptation is the World Bank's Climate Investment Fund, which has drawn contributions of more than $6 billion for work on clean technologies and adaptation efforts in nine pilot countries and two pilot regions. This is just the beginning of expenditures on adaptation efforts by the World Bank and other mechanisms, focusing on only a small fraction of the nations of the world and primarily aimed at anticipated anthropogenic climate change. Moreover, decisions are being made now, all around the world—by individuals, companies, and governments—that affect people and their livelihoods today, not just 50 or more years in the future. Climate risk management, whether related to projects of the scope of the World Bank's or to the planning and decisions of municipalities, will be best guided by meaningful climate information derived from observations of the past and model predictions of the future.

  14. The new climate data record of total and spectral solar irradiance: Current progress and future steps

    Science.gov (United States)

    Coddington, Odele; Lean, Judith; Rottman, Gary; Pilewskie, Peter; Snow, Martin; Lindholm, Doug

    2016-04-01

    We present a climate data record of Total Solar Irradiance (TSI) and Solar Spectral Irradiance (SSI), with associated time and wavelength dependent uncertainties, from 1610 to the present. The data record was developed jointly by the Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado Boulder and the Naval Research Laboratory (NRL) as part of the National Oceanographic and Atmospheric Administration's (NOAA) National Centers for Environmental Information (NCEI) Climate Data Record (CDR) Program, where the data record, source code, and supporting documentation are archived. TSI and SSI are constructed from models that determine the changes from quiet Sun conditions arising from bright faculae and dark sunspots on the solar disk using linear regression of proxies of solar magnetic activity with observations from the SOlar Radiation and Climate Experiment (SORCE) Total Irradiance Monitor (TIM), Spectral Irradiance Monitor (SIM), and SOlar Stellar Irradiance Comparison Experiment (SOLSTICE). We show that TSI can be separately modeled to within TIM's measurement accuracy from solar rotational to solar cycle time scales and we assume that SSI measurements are reliable on solar rotational time scales. We discuss the model formulation, uncertainty estimates, and operational implementation and present comparisons of the modeled TSI and SSI with the measurement record and with other solar irradiance models. We also discuss ongoing work to assess the sensitivity of the modeled irradiances to model assumptions, namely, the scaling of solar variability from rotational-to-cycle time scales and the representation of the sunspot darkening index.

  15. Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

    Science.gov (United States)

    Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

    2014-08-01

    Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

  16. Can a regional climate model reproduce observed extreme temperatures?

    Directory of Open Access Journals (Sweden)

    Peter F. Craigmile

    2013-10-01

    Full Text Available Using output from a regional Swedish climate model and observations from the Swedish synoptic observational network, we compare seasonal minimum temperatures from model output and observations using marginal extreme value modeling techniques. We make seasonal comparisons using generalized extreme value models and empirically estimate the shift in the distribution as a function of the regional climate model values, using the Doksum shift function. Spatial and temporal comparisons over south central Sweden are made by building hierarchical Bayesian generalized extreme value models for the observed minima and regional climate model output. Generally speaking the regional model is surprisingly well calibrated for minimum temperatures. We do detect a problem in the regional model to produce minimum temperatures close to 0◦C. The seasonal spatial effects are quite similar between data and regional model. The observations indicate relatively strong warming, especially in the northern region. This signal is present in the regional model, but is not as strong.

  17. Using Transport Diagnostics to Understand Chemistry Climate Model Ozone Simulations

    Science.gov (United States)

    Strahan, S. E.; Douglass, A. R.; Stolarski, R. S.; Akiyoshi, H.; Bekki, S.; Braesicke, P.; Butchart, N.; Chipperfield, M. P.; Cugnet, D.; Dhomse, S.; Frith, S. M.; Gettleman, A.; Hardiman, S. C.; Kinnison, D. E.; Lamarque, J.-F.; Mancini, E.; Marchand, M.; Michou, M.; Morgenstern, O.; Nakamura, T.; Olivie, D.; Pawson, S.; Pitari, G.; Plummer, D. A.; Pyle, J. A.

    2010-01-01

    We demonstrate how observations of N2O and mean age in the tropical and midlatitude lower stratosphere (LS) can be used to identify realistic transport in models. The results are applied to 15 Chemistry Climate Models (CCMs) participating in the 2010 WMO assessment. Comparison of the observed and simulated N2O/mean age relationship identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. The use of this process-oriented N2O/mean age diagnostic identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. We compare the diagnosed model transport behavior with a model's ability to produce realistic LS O3 profiles in the tropics and midlatitudes. Models with the greatest tropical transport problems show the poorest agreement with observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the SPARC CCMVal Report (2010) to explain the range of CCM predictions for the return-to-1980 dates for global (60 S-60 N) and Antarctic column ozone. Later (earlier) Antarctic return dates are generally correlated to higher (lower) vortex Cl(sub y) levels in the LS, and vortex Cl(sub y) is generally correlated with the model's circulation although model Cl(sub y) chemistry or Cl(sub y) conservation can have a significant effect. In both regions, models that have good LS transport produce a smaller range of predictions for the return-to-1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily large due to identifiable model transport deficiencies.

  18. The use of multi-model ensembles from global climate models for impact assessment of climate change

    Science.gov (United States)

    Semenov, M. A.

    2009-04-01

    The IPCC 4th Assessment Report was based on large datasets of projections of future climate produced by eighteen modelling groups worldwide who performed a set of coordinated climate experiments in which numerous global climate models (GCMs) have been run for a common set of experiments and various emission scenarios. These datasets are freely available form the IPCC Data Distribution Centre (www.ipcc-data.org) and can be used by the research community to assess the impact of changing climate on various systems of interest including impacts on agricultural crops and natural ecosystems, biodiversity and plant diseases. Multi-model ensembles (MME) emphasize the uncertainty in climate predictions resulting from structural differences in the global climate model design as well as uncertainty to variations of initial conditions or model parameters. This paper describes a methodology based on a stochastic weather generator for linking MME of predictions from GCMs with process-based impact models to assess impacts of climate change on biological or ecological systems. The latest version of the LARS-WG weather generator is described which allows seamlessly generating daily site-specific climate scenarios worldwide by utilising local daily weather and MME from GCMs. Examples of impacts on wheat in Europe, based on MME, are discussed, including changes in severity of drought and heat stress around flowering.

  19. Climate Change Adaption Measures in the Coastal City of Semarang, Indonesia: Current Practices and Performance

    Directory of Open Access Journals (Sweden)

    Nurrohman Wijaya

    2015-04-01

    Full Text Available Abstrak. Indonesia merupakan salah satu negara yang sangat rawan terhadap perubahan iklim dikarenakan oleh garis pantainya yang panjang, adanya konsentrasi penduduk dan kegiatan ekonomi di kawasan pesisir. Selain itu, dampak perubahan iklim telah memberikan akibat yang serius terhadap aspek lingkungan, sosial dan ekonomi. Untuk mengurangi dampak yang terjadi, maka diperlukan suatu proses dan intervensi tambahan melalui beberapa tindakan adaptasi. Beberapa upaya adaptasi terhadap perubahan iklim telah dilaksanakan di kota-kota pesisir di Indonesia. Artikel ini bertujuan untuk mengkaji praktik dan kinerja dari tindakan adaptasi perubahan iklim pada tingkat lokal di kota pesisir Semarang. Tindakan adaptasi tersebut yaitu integrasi strategi ketahanan iklim dengan perencanaan kota, serta strategi adaptasi fisik dalam penanggulangan bencana banjir. Temuan studi ini menyatakan bahwa kinerja tiap tindakan adaptasi memberikan hasil yang berbeda tergantung pada tipologi adaptasi. Kerjasama dan komitmen yang kuat di antara pemangku kepentingan serta peningkatan kapasitas adaptasi masyarakat lokal adalah hal yang dibutuhkan.Kata kunci. Tindakan adaptasi, perubahan iklim, kota pesisir, SemarangAbstract. Indonesia is among the most vulnerable countries to climate change due to its coastlines, high concentration of population and economic activity in coastal areas. In addition, the impacts of climate change have had severe environmental and socio-economic consequences. Adaptation measures are required to minimize the impacts. Some climate change adaptation measures have been practiced in the coastal cities of Indonesia. This article aims to examine the current practices and performance of local adaptation measures in the coastal city of Semarang City. The current adaptation practices include an integration of climate resilience strategy into city planning and a physical adaptation strategy for the tidal flood hazard. It is found that the performance of each

  20. Regional Climate Modeling over South America: A Review

    Directory of Open Access Journals (Sweden)

    Silvina A. Solman

    2013-01-01

    Full Text Available This review summarizes the progress achieved on regional climate modeling activities over South America since the early efforts at the beginning of the 2000s until now. During the last 10 years, simulations with regional climate models (RCMs have been performed for several purposes over the region. Early efforts were mainly focused on sensitivity studies to both physical mechanisms and technical aspects of RCMs. The last developments were focused mainly on providing high-resolution information on regional climate change. This paper describes the most outstanding contributions from the isolated efforts to the ongoing coordinated RCM activities in the framework of the CORDEX initiative, which represents a major endeavor to produce ensemble climate change projections at regional scales and allows exploring the associated range of uncertainties. The remaining challenges in modeling South American climate features are also discussed.

  1. A framework for testing the ability of models to project climate change and its impacts

    DEFF Research Database (Denmark)

    Refsgaard, J. C.; Madsen, H.; Andréassian, V.

    2014-01-01

    Models used for climate change impact projections are typically not tested for simulation beyond current climate conditions. Since we have no data truly reflecting future conditions, a key challenge in this respect is to rigorously test models using proxies of future conditions. This paper presents...... to their application for projections by use of single models, ensemble modelling and space-time-substitution and in relation to use of different data from historical time series, paleo data and controlled experiments. We recommend that differential-split sample tests should be performed with best available proxy data...

  2. Agricultural climate impacts assessment for economic modeling and decision support

    Science.gov (United States)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  3. A framework for modeling uncertainty in regional climate change

    Science.gov (United States)

    In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the United States associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework ...

  4. Modelling faba bean production in an uncertain future climate

    NARCIS (Netherlands)

    Crawford, J.W.; Yiqun Gu,; Peiris, D.R.; Grashoff, C.; McNicol, J.W.; Marschall, B.

    1996-01-01

    Future climate change may bring risk or benefit to crop production. In this paper, the possible impact of climate change on faba bean production in Scotland is examined. Instead of conventional simulation modelling techniques, the belief network approach is applied to deal with the uncertain

  5. Drivers of stability of climate coalitions in the STACO model

    NARCIS (Netherlands)

    Dellink, R.B.

    2011-01-01

    This paper investigates which drivers affect the formation and stability of international climate agreements (ICAs). The applied model STACO is used to project costs and benefits of an international agreement on climate change mitigation activities. The simulation results show that an incentive-base

  6. Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

    Energy Technology Data Exchange (ETDEWEB)

    Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

    2015-07-14

    demonstrate significant advances in all six research areas. The major conclusions are that statically-adaptive variable-resolution modeling is currently becoming mature in the climate sciences, and that AMR holds outstanding promise for future-generation weather and climate models on high-performance computing architectures.

  7. Improving assessment and modelling of climate change impacts on global terrestrial biodiversity.

    Science.gov (United States)

    McMahon, Sean M; Harrison, Sandy P; Armbruster, W Scott; Bartlein, Patrick J; Beale, Colin M; Edwards, Mary E; Kattge, Jens; Midgley, Guy; Morin, Xavier; Prentice, I Colin

    2011-05-01

    Understanding how species and ecosystems respond to climate change has become a major focus of ecology and conservation biology. Modelling approaches provide important tools for making future projections, but current models of the climate-biosphere interface remain overly simplistic, undermining the credibility of projections. We identify five ways in which substantial advances could be made in the next few years: (i) improving the accessibility and efficiency of biodiversity monitoring data, (ii) quantifying the main determinants of the sensitivity of species to climate change, (iii) incorporating community dynamics into projections of biodiversity responses, (iv) accounting for the influence of evolutionary processes on the response of species to climate change, and (v) improving the biophysical rule sets that define functional groupings of species in global models. Published by Elsevier Ltd.

  8. Enhanced science-stakeholder communication to improve ecosystem model performances for climate change impact assessments

    DEFF Research Database (Denmark)

    Jonsson, Anna Maria; Anderbrant, Olle; Holmer, Jennie;

    2015-01-01

    In recent years, climate impact assessments of relevance to the agricultural and forestry sectors have received considerable attention. Current ecosystem models commonly capture the effect of a warmer climate on biomass production, but they rarely sufficiently capture potential losses caused...... a discussion among the science–stakeholder communities on how to quantify the potential for climate change adaptation by improving the realism in the models....... by pests, pathogens and extreme weather events. In addition, alternative management regimes may not be integrated in the models. A way to improve the quality of climate impact assessments is to increase the science–stakeholder collaboration, and in a two-way dialog link empirical experience and impact...

  9. Benchmarking an Unstructured-Grid Model for Tsunami Current Modeling

    Science.gov (United States)

    Zhang, Yinglong J.; Priest, George; Allan, Jonathan; Stimely, Laura

    2016-12-01

    We present model results derived from a tsunami current benchmarking workshop held by the NTHMP (National Tsunami Hazard Mitigation Program) in February 2015. Modeling was undertaken using our own 3D unstructured-grid model that has been previously certified by the NTHMP for tsunami inundation. Results for two benchmark tests are described here, including: (1) vortex structure in the wake of a submerged shoal and (2) impact of tsunami waves on Hilo Harbor in the 2011 Tohoku event. The modeled current velocities are compared with available lab and field data. We demonstrate that the model is able to accurately capture the velocity field in the two benchmark tests; in particular, the 3D model gives a much more accurate wake structure than the 2D model for the first test, with the root-mean-square error and mean bias no more than 2 cm s-1 and 8 mm s-1, respectively, for the modeled velocity.

  10. Detecting Warming Hiatus Periods in CMIP5 Climate Model Projections

    OpenAIRE

    Li, Tony W.; Noel C. Baker

    2016-01-01

    The observed slow-down in the global-mean surface temperature (GST) warming from 1998 to 2012 has been called a “warming hiatus.” Certain climate models, operating under experiments which simulate warming by increasing radiative forcing, have been shown to reproduce periods which resemble the observed hiatus. The present study provides a comprehensive analysis of 38 CMIP5 climate models to provide further evidence that models produce warming hiatus periods during warming experiments. GST rate...

  11. Climate change and dengue: a critical and systematic review of quantitative modelling approaches.

    Science.gov (United States)

    Naish, Suchithra; Dale, Pat; Mackenzie, John S; McBride, John; Mengersen, Kerrie; Tong, Shilu

    2014-03-26

    Many studies have found associations between climatic conditions and dengue transmission. However, there is a debate about the future impacts of climate change on dengue transmission. This paper reviewed epidemiological evidence on the relationship between climate and dengue with a focus on quantitative methods for assessing the potential impacts of climate change on global dengue transmission. A literature search was conducted in October 2012, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search focused on peer-reviewed journal articles published in English from January 1991 through October 2012. Sixteen studies met the inclusion criteria and most studies showed that the transmission of dengue is highly sensitive to climatic conditions, especially temperature, rainfall and relative humidity. Studies on the potential impacts of climate change on dengue indicate increased climatic suitability for transmission and an expansion of the geographic regions at risk during this century. A variety of quantitative modelling approaches were used in the studies. Several key methodological issues and current knowledge gaps were identified through this review. It is important to assemble spatio-temporal patterns of dengue transmission compatible with long-term data on climate and other socio-ecological changes and this would advance projections of dengue risks associated with climate change.

  12. A dynamic, climate-driven model of Rift Valley fever.

    Science.gov (United States)

    Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P

    2016-03-31

    Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

  13. A dynamic, climate-driven model of Rift Valley fever

    Directory of Open Access Journals (Sweden)

    Joseph Leedale

    2016-03-01

    Full Text Available Outbreaks of Rift Valley fever (RVF in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

  14. Developing the next-generation climate system models: challenges and achievements.

    Science.gov (United States)

    Slingo, Julia; Bates, Kevin; Nikiforakis, Nikos; Piggott, Matthew; Roberts, Malcolm; Shaffrey, Len; Stevens, Ian; Vidale, Pier Luigi; Weller, Hilary

    2009-03-13

    Although climate models have been improving in accuracy and efficiency over the past few decades, it now seems that these incremental improvements may be slowing. As tera/petascale computing becomes massively parallel, our legacy codes are less suitable, and even with the increased resolution that we are now beginning to use, these models cannot represent the multiscale nature of the climate system. This paper argues that it may be time to reconsider the use of adaptive mesh refinement for weather and climate forecasting in order to achieve good scaling and representation of the wide range of spatial scales in the atmosphere and ocean. Furthermore, the challenge of introducing living organisms and human responses into climate system models is only just beginning to be tackled. We do not yet have a clear framework in which to approach the problem, but it is likely to cover such a huge number of different scales and processes that radically different methods may have to be considered. The challenges of multiscale modelling and petascale computing provide an opportunity to consider a fresh approach to numerical modelling of the climate (or Earth) system, which takes advantage of the computational fluid dynamics developments in other fields and brings new perspectives on how to incorporate Earth system processes. This paper reviews some of the current issues in climate (and, by implication, Earth) system modelling, and asks the question whether a new generation of models is needed to tackle these problems.

  15. Soil moisture and root water uptake in climate models. Research Programme Climate Changes Spatial Planning

    NARCIS (Netherlands)

    Dam, van J.C.; Metselaar, K.; Wipfler, E.L.; Feddes, R.A.; Meijgaard, van E.; Hurk, van den B.

    2011-01-01

    More accurate simulation of the energy and water balance near the Earth surface is important to improve the performance of regional climate models. We used a detailed ecohydrological model to rank the importance of vegetation and soil factors with respect to evapotranspiration modeling. The results

  16. Soil moisture and root water uptake in climate models. Research Programme Climate Changes Spatial Planning

    NARCIS (Netherlands)

    Dam, van J.C.; Metselaar, K.; Wipfler, E.L.; Feddes, R.A.; Meijgaard, van E.; Hurk, van den B.

    2011-01-01

    More accurate simulation of the energy and water balance near the Earth surface is important to improve the performance of regional climate models. We used a detailed ecohydrological model to rank the importance of vegetation and soil factors with respect to evapotranspiration modeling. The results

  17. Forest fire risk assessment in Sweden using climate model data: bias correction and future changes

    Directory of Open Access Journals (Sweden)

    W. Yang

    2015-01-01

    Full Text Available As the risk for a forest fire is largely influenced by weather, evaluating its tendency under a changing climate becomes important for management and decision making. Currently, biases in climate models make it difficult to realistically estimate the future climate and consequent impact on fire risk. A distribution-based scaling (DBS approach was developed as a post-processing tool that intends to correct systematic biases in climate modelling outputs. In this study, we used two projections, one driven by historical reanalysis (ERA40 and one from a global climate model (ECHAM5 for future projection, both having been dynamically downscaled by a regional climate model (RCA3. The effects of the post-processing tool on relative humidity and wind speed were studied in addition to the primary variables precipitation and temperature. Finally, the Canadian Fire Weather Index system was used to evaluate the influence of changing meteorological conditions on the moisture content in fuel layers and the fire-spread risk. The forest fire risk results using DBS are proven to better reflect risk using observations than that using raw climate outputs. For future periods, southern Sweden is likely to have a higher fire risk than today, whereas northern Sweden will have a lower risk of forest fire.

  18. Methodology Aspects of Quantifying Stochastic Climate Variability with Dynamic Models

    Science.gov (United States)

    Nuterman, Roman; Jochum, Markus; Solgaard, Anna

    2015-04-01

    The paleoclimatic records show that climate has changed dramatically through time. For the past few millions of years it has been oscillating between ice ages, with large parts of the continents covered with ice, and warm interglacial periods like the present one. It is commonly assumed that these glacial cycles are related to changes in insolation due to periodic changes in Earth's orbit around Sun (Milankovitch theory). However, this relationship is far from understood. The insolation changes are so small that enhancing feedbacks must be at play. It might even be that the external perturbation only plays a minor role in comparison to internal stochastic variations or internal oscillations. This claim is based on several shortcomings in the Milankovitch theory: Prior to one million years ago, the duration of the glacial cycles was indeed 41,000 years, in line with the obliquity cycle of Earth's orbit. This duration changed at the so-called Mid-Pleistocene transition to approximately 100,000 years. Moreover, according to Milankovitch's theory the interglacial of 400,000 years ago should not have happened. Thus, while prior to one million years ago the pacing of these glacial cycles may be tied to changes in Earth's orbit, we do not understand the current magnitude and phasing of the glacial cycles. In principle it is possible that the glacial/interglacial cycles are not due to variations in Earth's orbit, but due to stochastic forcing or internal modes of variability. We present a new method and preliminary results for a unified framework using a fully coupled Earth System Model (ESM), in which the leading three ice age hypotheses will be investigated together. Was the waxing and waning of ice sheets due to an internal mode of variability, due to variations in Earth's orbit, or simply due to a low-order auto-regressive process (i.e., noise integrated by system with memory)? The central idea is to use the Generalized Linear Models (GLM), which can handle both

  19. A methodology for model-based greenhouse design: Part 1, a greenhouse climate model for a broad range of designs and climates

    NARCIS (Netherlands)

    Vanthoor, B.H.E.; Stanghellini, C.; Henten, van E.J.; Visser, de P.H.B.

    2011-01-01

    With the aim of developing a model-based method to design greenhouses for a broad range of climatic and economic conditions, a greenhouse climate model has been developed and validated. This model describes the effects of the outdoor climate and greenhouse design on the indoor greenhouse climate. Fo

  20. Assessing potential modifications of landslide triggering probability based on hydromechanical modelling and regional climate model projections

    Science.gov (United States)

    Peres, David Johnny; Cancelliere, Antonino

    2017-04-01

    Climate change related to uncontrolled greenhouse gas emissions is expected to modify climate characteristics in a harmful way, increasing the frequency of many precipitation-triggered natural hazards, landslides included. In our study we analyse regional climate model (RCM) projections with the aim of assessing the potential future modifications of rainfall event characteristics linked to shallow landslide triggering, such as: event duration, total depth, and inter-arrival time. Factor of changes of the mean and the variance of these rainfall-event characteristics are exploited to adjust a stochastic rainfall generator aimed at simulating precipitation series likely to occur in the future. Then Monte Carlo simulations - where the stochastic rainfall generator and a physically based hydromechanical model are coupled - are carried out to estimate the probability of landslide triggering for future time horizons, and its changes respect to the current climate conditions. The proposed methodology is applied to the Peloritani region in Sicily, Italy, an area that in the past two decades has experienced several catastrophic shallow and rapidly moving landslide events. Different RCM simulations from the Coordinated regional Climate Downscaling Experiment (CORDEX) initiative are considered in the application, as well as two different emission scenarios, known as Representative Concentration Pathways: intermediate (RCP 4.5) and high-emissions (RCP 8.5). The estimated rainfall event characteristics modifications differ significantly both in magnitude and in direction (increase/decrease) from one model to another. RCMs are concordant only in predicting an increase of the mean of inter-event dry intervals. The variance of rainfall depth exhibits maximum changes (increase or decrease depending on the RCM), and it is the characteristic to which landslide triggering seems to be more sensitive. Some RCMs indicate significant variations of landslide probability due to climate

  1. Translating Climate-Change Probabilities into Impact Risks - Overcoming the Impact- Model Bottleneck

    Science.gov (United States)

    Dettinger, M.

    2008-12-01

    Projections of climate change in response to increasing greenhouse-gas concentrations are uncertain and likely to remain so for the foreseeable future. As more projections become available for analysts, we are increasingly able to characterize the probabilities of obtaining various levels of climate change in current projections. However, the probabilities of most interest in impact assessments are not the probabilities of climate changes, but rather the probabilities (or risks) of various levels and kinds of climate-change impact. These risks can be difficult to estimate even if the climate-change probabilities are well known. The difficulty arises because, frequently, impact models and assessments are computationally demanding or time consuming of hands-on, human expert analyses, so that severe limits are placed on the numbers of climate- change scenarios from which detailed impacts can be assessed. Estimation of risks of various impacts is generally difficult with the few resulting examples. However, real-world examples from the water-resources sector will be used to show that, by applying several different "derived distributions" approaches for estimating the risks of various impacts from known climate-change probabilities to just a few impact-model simulations, risks can be estimated along with indications of how accurate are the impact-risk estimates. The prospects for a priori selection of a few climate-change scenarios (from a larger ensemble of available projections) that will allow the best, most economical estimates of impact risks will be explored with a simple but real-world example.

  2. Emulation of MIROC5 with a simple climate model

    Science.gov (United States)

    Ishizaki, Yasuhiro; Emori, Seita; Shiogama, Hideo; Takahashi, Kiyoshi; Yokohata, Tokuta; Yoshimori, Masakazu

    2014-05-01

    We developed a simple climate model based on MAGICC6, and investigated the ability of the simple climate model to emulate global mean surface air temperature (SAT) changes of an atmosphere-ocean general circulation model (MIROC5) in the twenty-first century in representative concentration pathways (RCPs). Some previous research indicated that climate sensitivity, ocean vertical diffusion and forcing of anthropogenic aerosols (direct and indirect effects of sulfate aerosol, black carbon and organic carbon) are important factors to emulate global mean SAT changes of atmosphere-ocean general circulation models CMIP3. We therefore estimate these important parameters in the simple climate model using a Metropolis-Hastings Markov chain Monte Carlo (MCMC) approach. The estimated values of the important parameters by the MCMC are physically valid, and our simple climate model can successfully emulate global mean SAT changes of MIROC5 in RCPs with the estimated parameters by the MCMC approach. In addition, we estimated the relative contributions f each important parameter in sensitivity experiments, in which we change the value of an important parameter from the estimated one by the MCMC to the default value of MAGICC6. As a result, we found that the estimation of climate sensitivity is the most important factor for the emulation of the AOGCM, and the stimation of ocean vertical diffusion is also important factor. Although the estimations of the anthropogenic aerosols forcing are very important for the emulation of the AOGCM in the twenty century, the influence of them on the emulation of the AOGCM in the twenty first century is very small. This is because emissions of anthropogenic aerosols are projected to decrease in the twenty first century, and relative contributions of the forcing of anthropogenic aerosols also decrease. Carbon cycle models are not incorporated into our simple climate model yet. A sophisticated carbon cycle model is required to be incorporated into

  3. Key challenges and priorities for modelling European grasslands under climate change.

    Science.gov (United States)

    Kipling, Richard P; Virkajärvi, Perttu; Breitsameter, Laura; Curnel, Yannick; De Swaef, Tom; Gustavsson, Anne-Maj; Hennart, Sylvain; Höglind, Mats; Järvenranta, Kirsi; Minet, Julien; Nendel, Claas; Persson, Tomas; Picon-Cochard, Catherine; Rolinski, Susanne; Sandars, Daniel L; Scollan, Nigel D; Sebek, Leon; Seddaiu, Giovanna; Topp, Cairistiona F E; Twardy, Stanislaw; Van Middelkoop, Jantine; Wu, Lianhai; Bellocchi, Gianni

    2016-10-01

    Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research

  4. Climate sensitivity runs and regional hydrologic modeling for predicting the response of the greater Florida Everglades ecosystem to climate change.

    Science.gov (United States)

    Obeysekera, Jayantha; Barnes, Jenifer; Nungesser, Martha

    2015-04-01

    It is important to understand the vulnerability of the water management system in south Florida and to determine the resilience and robustness of greater Everglades restoration plans under future climate change. The current climate models, at both global and regional scales, are not ready to deliver specific climatic datasets for water resources investigations involving future plans and therefore a scenario based approach was adopted for this first study in restoration planning. We focused on the general implications of potential changes in future temperature and associated changes in evapotranspiration, precipitation, and sea levels at the regional boundary. From these, we developed a set of six climate and sea level scenarios, used them to simulate the hydrologic response of the greater Everglades region including agricultural, urban, and natural areas, and compared the results to those from a base run of current conditions. The scenarios included a 1.5 °C increase in temperature, ±10 % change in precipitation, and a 0.46 m (1.5 feet) increase in sea level for the 50-year planning horizon. The results suggested that, depending on the rainfall and temperature scenario, there would be significant changes in water budgets, ecosystem performance, and in water supply demands met. The increased sea level scenarios also show that the ground water levels would increase significantly with associated implications for flood protection in the urbanized areas of southeastern Florida.

  5. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    Science.gov (United States)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian; Trolle, Dennis; Børgesen, Christen Duus; Olesen, Jørgen E.; Jeppesen, Erik; Jensen, Karsten H.

    2016-04-01

    Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes on hydrology for a 486 km2 catchment in Denmark and to evaluate the sensitivity of the results to the choice of hydrological model. Three hydrological models, NAM, SWAT and MIKE SHE, were constructed and calibrated using similar methods. Each model was forced with results from four climate models and four land use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice remained the dominant factor for mean discharge, low and high flows as well as hydraulic head at the end of the century.

  6. A study of model bivalve siphonal currents

    Science.gov (United States)

    Monismith, Stephen G.; Koseff, Jeffrey R.; Thompson, Janet K.; O'Riordan, Catherine A.; Nepf, Heidi M.

    1990-01-01

    We carried out experiments studying the hydrodynamics of bivalve siphonal currents in a laboratory flume. Rather than use living animals, we devised a simple, model siphon pair connected to a pump. Fluorescence-based flow visualization was used to characterize siphon-jet flows for several geometric configurations and flow speeds. These measurements show that the boundary-layer velocity profile, siphon height, siphon pair orientation, and size of siphon structure all affect the vertical distribution of the excurrent flow downstream of the siphon pair and the fraction of excurrent that is refiltered. The observed flows may effect both the clearance rate of an entire population of siphonate bivalves as well as the efficiency of feeding of any individual. Our results imply that field conditions are properly represented in laboratory flume studies of phytoplankton biomass losses to benthic bivalves when the shear velocity and bottom roughness are matched to values found in the field. Numerical models of feeding by a bivalve population should include an effective sink distribution which is created by the combined incurrent-excurrent flow field. Near-bed flows need to be accounted for to properly represent these benthic-pelagic exchanges. We also present velocity measurements made with a laser-Doppler anemometer (LDA) for a single configuration (siphons flush with bed, inlet downstream) that show that the siphonal currents have a significant local effect on the properties of a turbulent boundary layer.

  7. Climate change hotspots in the CMIP5 global climate model ensemble.

    Science.gov (United States)

    Diffenbaugh, Noah S; Giorgi, Filippo

    2012-01-10

    We use a statistical metric of multi-dimensional climate change to quantify the emergence of global climate change hotspots in the CMIP5 climate model ensemble. Our hotspot metric extends previous work through the inclusion of extreme seasonal temperature and precipitation, which exert critical influence on climate change impacts. The results identify areas of the Amazon, the Sahel and tropical West Africa, Indonesia, and the Tibetan Plateau as persistent regional climate change hotspots throughout the 21(st) century of the RCP8.5 and RCP4.5 forcing pathways. In addition, areas of southern Africa, the Mediterranean, the Arctic, and Central America/western North America also emerge as prominent regional climate change hotspots in response to intermediate and high levels of forcing. Comparisons of different periods of the two forcing pathways suggest that the pattern of aggregate change is fairly robust to the level of global warming below approximately 2°C of global warming (relative to the late-20(th)-century baseline), but not at the higher levels of global warming that occur in the late-21(st)-century period of the RCP8.5 pathway, with areas of southern Africa, the Mediterranean, and the Arctic exhibiting particular intensification of relative aggregate climate change in response to high levels of forcing. Although specific impacts will clearly be shaped by the interaction of climate change with human and biological vulnerabilities, our identification of climate change hotspots can help to inform mitigation and adaptation decisions by quantifying the rate, magnitude and causes of the aggregate climate response in different parts of the world.

  8. Historical and idealized climate model experiments: an EMIC intercomparison

    Directory of Open Access Journals (Sweden)

    M. Eby

    2012-08-01

    Full Text Available Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes seem to be underestimated. It is possible that recent modelled climate trends or climate-carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated.

    Several one thousand year long, idealized, 2x and 4x CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate-carbon feedbacks. The values from EMICs generally fall within the range given by General Circulation Models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows considerable synergy between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given

  9. Characterizing droughts under current and future climates in the Jordan River region

    Directory of Open Access Journals (Sweden)

    T. Törnros

    2013-05-01

    Full Text Available The Standardized Precipitation Index (SPI was applied in order to address the characteristics of current and future agricultural droughts in the Jordan River region located in the southeastern Mediterranean area. In the first step, the SPI was applied on spatially interpolated monthly precipitation data at multiple timescales, i.e. accumulated precipitation was considered over a number of timescales, for example: 1, 3, and 6 months. To investigate the performance of the drought index, correlation analyses were conducted with the Normalized Difference Vegetation Index (NDVI obtained from remote sensing. The results show that the 6 month SPI best explains the inter-annual variation of the NDVI. Hence, a timescale of 6 months is the most appropriate when addressing agricultural drought in the semi-arid region. In the second step, the 6 month SPI was applied to three climate projections based on the IPCC emission scenario A1B. When comparing the period 2031–2060 with 1961–1990, it is shown that the mean drought duration is projected to increase. Furthermore, the droughts are expected to become more severe because the frequency of severe and extreme droughts is projected to increase and the frequency of moderate drought is projected to decrease. To address the impact of drought on the agricultural sector, the irrigation water demand during drought was simulated with a hydrological model on a spatial resolution of 1 km. A large increase in the demand for irrigation water was simulated, showing that the agricultural sector is expected to become even more vulnerable to drought in the future.

  10. Synchronicity of Kuroshio Current and climate system variability since the Last Glacial Maximum

    Science.gov (United States)

    Zheng, Xufeng; Li, Anchun; Kao, ShuhJi; Gong, Xun; Frank, Martin; Kuhn, Gerhard; Cai, Wenju; Yan, Hong; Wan, Shiming; Zhang, Honghai; Jiang, Fuqing; Hathorne, Edmund; Chen, Zhong; Hu, Bangqi

    2016-10-01

    The Kuroshio Current (KC) is the northward branch of the North Pacific subtropical gyre (NPG) and exerts influence on the exchange of physical, chemical, and biological properties of downstream regions in the Pacific Ocean. Resolving long-term changes in the flow of the KC water masses is, therefore, crucial for advancing our understanding of the Pacific's role in global ocean and climate variability. Here, we reconstruct changes in KC dynamics over the past 20 ka based on grain-size spectra, clay mineral, and Sr-Nd isotope constraints of sediments from the northern Okinawa Trough. Combined with published sediment records surrounding the NPG, we suggest that the KC remained in the Okinawa Trough throughout the Last Glacial Maximum. Together with Earth-System-Model simulations, our results additionally indicate that KC intensified considerably during the early Holocene (EH). The synchronous establishment of the KC "water barrier" and the modern circulation pattern during the EH highstand shaped the sediment transport patterns. This is ascribed to the precession-induced increase in the occurrence of La Niña-like state and the strength of the East Asian summer monsoon. The synchronicity of the shifts in the intensity of the KC, Kuroshio extension, and El Niño/La Niña-Southern Oscillation (ENSO) variability may further indicate that the western branch of the NPG has been subject to basin-scale changes in wind stress curl over the North Pacific in response to low-latitude insolation. Superimposed on this long-term trend are high-amplitude, large century, and millennial-scale variations during last 5 ka, which are ascribed to the advent of modern ENSO when the equatorial oceans experienced stronger insolation during the boreal winter.

  11. Eliciting climate experts' knowledge to address model uncertainties in regional climate projections: a case study of Guanacaste, Northwest Costa Rica

    Science.gov (United States)

    Grossmann, I.; Steyn, D. G.

    2014-12-01

    Global general circulation models typically cannot provide the detailed and accurate regional climate information required by stakeholders for climate adaptation efforts, given their limited capacity to resolve the regional topography and changes in local sea surface temperature, wind and circulation patterns. The study region in Northwest Costa Rica has a tropical wet-dry climate with a double-peak wet season. During the dry season the central Costa Rican mountains prevent tropical Atlantic moisture from reaching the region. Most of the annual precipitation is received following the northward migration of the ITCZ in May that allows the region to benefit from moist southwesterly flow from the tropical Pacific. The wet season begins with a short period of "early rains" and is interrupted by the mid-summer drought associated with the intensification and westward expansion of the North Atlantic subtropical high in late June. Model projections for the 21st century indicate a lengthening and intensification of the mid-summer drought and a weakening of the early rains on which current crop cultivation practices rely. We developed an expert elicitation to systematically address uncertainties in the available model projections of changes in the seasonal precipitation pattern. Our approach extends an elicitation approach developed previously at Carnegie Mellon University. Experts in the climate of the study region or Central American climate were asked to assess the mechanisms driving precipitation during each part of the season, uncertainties regarding these mechanisms, expected changes in each mechanism in a warming climate, and the capacity of current models to reproduce these processes. To avoid overconfidence bias, a step-by-step procedure was followed to estimate changes in the timing and intensity of precipitation during each part of the season. The questions drew upon interviews conducted with the regions stakeholders to assess their climate information needs. This

  12. Environmental impacts of barley cultivation under current and future climatic conditions

    DEFF Research Database (Denmark)

    Dijkman, Teunis Johannes; Birkved, Morten; Saxe, Henrik

    2017-01-01

    The purpose of this work is to compare the environmental impacts of spring barley cultivation in Denmark under current (year 2010) and future (year 2050) climatic conditions. Therefore, a Life Cycle Assessment was carried out for the production of 1 kg of spring barley in Denmark, at farm gate......-products, the resulting environmental impacts were allocated between the main product and their respective by-products using economic allocation. Impact assessment was done using the ReCiPe (H) methodology, except for toxicity impacts, which were assessed using USEtox. The results show that the impacts for all impact...... for the increased impacts. This finding was confirmed by the sensitivity analysis. Because this study focused solely on the impacts of climate change, technological improvements and political measures to reduce impacts in the 2050 scenario are not taken into account. Options to mitigate the environmental impacts...

  13. Assessing climate model software quality: a defect density analysis of three models

    Directory of Open Access Journals (Sweden)

    J. Pipitone

    2012-08-01

    Full Text Available A climate model is an executable theory of the climate; the model encapsulates climatological theories in software so that they can be simulated and their implications investigated. Thus, in order to trust a climate model, one must trust that the software it is built from is built correctly. Our study explores the nature of software quality in the context of climate modelling. We performed an analysis of defect reports and defect fixes in several versions of leading global climate models by collecting defect data from bug tracking systems and version control repository comments. We found that the climate models all have very low defect densities compared to well-known, similarly sized open-source projects. We discuss the implications of our findings for the assessment of climate model software trustworthiness.

  14. California Basin Characterization Model Downscaled Climate and Hydrology

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The California Basin Characterization Model (CA-BCM 2014) dataset provides historical and projected climate and hydrologic surfaces for the region that encompasses...

  15. Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

    Science.gov (United States)

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

    2007-12-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

  16. Modelling impacts of changes in nitrogen deposition and climate on ecosystem services in the period 1900-2050

    NARCIS (Netherlands)

    Vries, de W.; Posch, M.

    2010-01-01

    We modelled the combined effects of past and expected future changes in climate and nitrogen deposition on tree carbon sequestration by European forests for the period 1900-2050. Two scenarios for deposition (current legislation and maximum technically feasible reductions) and two climate scenarios

  17. Modeling Surgery: A New Way Toward Understanding Earth Climate Variability

    Institute of Scientific and Technical Information of China (English)

    WU Lixin; LIU Zhengyu; Robert Gallimore; Michael Notaro; Robert Jacob

    2005-01-01

    A new modeling concept, referred to as Modeling Surgery, has been recently developed at University of Wisconsin-Madison. It is specifically designed to diagnose coupled feedbacks between different climate components as well as climatic teleconnections within a specific component through systematically modifying the coupling configurations and teleconnective pathways. It thus provides a powerful means for identifying the causes and mechanisms of low-frequency variability in the Earth's climate system. In this paper, we will give a short review of our recent progress in this new area.

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

    Science.gov (United States)

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

    2009-04-01

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

  19. Climate simulations for 1880-2003 with GISS modelE

    CERN Document Server

    Hansen, J; Bauer, S; Baum, E; Cairns, B; Canuto, V; Chandler, M; Cheng, Y; Cohen, A; Faluvegi, G; Fleming, E; Friend, A; Genio, A D; Hall, T; Jackman, C; Jonas, J; Kelley, M; Kharecha, P; Kiang, N Y; Koch, D; Labow, G; Lacis, A; Lerner, J; Lo, K; Menon, S; Miller, R; Nazarenko, L; Novakov, T; Oinas, V; Perlwitz, J; Rind, D; Romanou, A; Ruedy, R; Russell, G; Sato, M; Schmidt, G A; Schmunk, R; Shindell, D; Stone, P; Streets, D; Sun, S; Tausnev, N; Thresher, D; Unger, N; Yao, M; Zhang, S; Perlwitz, Ja.; Perlwitz, Ju.

    2006-01-01

    We carry out climate simulations for 1880-2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880-2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies...

  20. Hydrological Modelling of Mountainous and Glacierised regions under Changing Climate

    OpenAIRE

    Li, Hong

    2015-01-01

    Climate change is one of the most serious environmental threats that humanity has ever been confronted to. Hydrological models are vital tools to asses its impacts on the water cycle and water resources. The goal of this project is to evaluate and improve the capacity of the HBV model (Hydrologiska Byr°ans Vattenbalansavdelning) in simulating hydrological processes in mountainous and glacierised regions under both the present and future climate. This goal is achieved in two steps: (1) impleme...

  1. Parameterization of clouds and radiation in climate models

    Energy Technology Data Exchange (ETDEWEB)

    Roeckner, E. [Max Planck Institute for Meterology, Hamburg (Germany)

    1995-09-01

    Clouds are a very important, yet poorly modeled element in the climate system. There are many potential cloud feedbacks, including those related to cloud cover, height, water content, phase change, and droplet concentration and size distribution. As a prerequisite to studying the cloud feedback issue, this research reports on the simulation and validation of cloud radiative forcing under present climate conditions using the ECHAM general circulation model and ERBE top-of-atmosphere radiative fluxes.

  2. Modeling climate change impacts on overwintering bald eagles

    OpenAIRE

    Chris J. Harvey; Moriarty, Pamela E.; Salathé Jr, Eric P

    2012-01-01

    Bald eagles (Haliaeetus leucocephalus) are recovering from severe population declines, and are exerting pressure on food resources in some areas. Thousands of bald eagles overwinter near Puget Sound, primarily to feed on chum salmon (Oncorhynchus keta) carcasses. We used modeling techniques to examine how anticipated climate changes will affect energetic demands of overwintering bald eagles. We applied a regional downscaling method to two global climate change models to obtain hourly temperat...

  3. Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model

    Directory of Open Access Journals (Sweden)

    N. Mahowald

    2011-02-01

    Full Text Available Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climate feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.

  4. Modelling climate change impacts on mycotoxin contamination

    NARCIS (Netherlands)

    Fels, van der Ine; Liu, C.; Battilani, P.

    2016-01-01

    Projected climate change effects will influence primary agricultural systems and thus food security, directly via impacts on yields, and indirectly via impacts on its safety, with mycotoxins considered as crucial hazards. Mycotoxins are produced by a wide variety of fungal species, each having their

  5. Modelling climate change impacts on mycotoxin contamination

    NARCIS (Netherlands)

    Fels, van der Ine; Liu, C.; Battilani, P.

    2016-01-01

    Projected climate change effects will influence primary agricultural systems and thus food security, directly via impacts on yields, and indirectly via impacts on its safety, with mycotoxins considered as crucial hazards. Mycotoxins are produced by a wide variety of fungal species, each having their

  6. Genetic and physiological bases for phenological responses to current and predicted climates

    OpenAIRE

    Wilczek, A. M.; Burghardt, L. T.; Cobb, A. R.; Cooper, M D; Welch, S. M.; Schmitt, J

    2010-01-01

    We are now reaching the stage at which specific genetic factors with known physiological effects can be tied directly and quantitatively to variation in phenology. With such a mechanistic understanding, scientists can better predict phenological responses to novel seasonal climates. Using the widespread model species Arabidopsis thaliana, we explore how variation in different genetic pathways can be linked to phenology and life-history variation across geographical regions and seasons. We sho...

  7. A coupled climate model simulation of Marine Isotope Stage 3 stadial climate

    Science.gov (United States)

    Brandefelt, J.; Kjellström, E.; Näslund, J.-O.; Strandberg, G.; Voelker, A. H. L.; Wohlfarth, B.

    2011-06-01

    We present a coupled global climate model (CGCM) simulation, integrated for 1500 yr to quasi-equilibrium, of a stadial (cold period) within Marine Isotope Stage 3 (MIS 3). The simulated Greenland stadial 12 (GS12; ~44 ka BP) annual global mean surface temperature (Ts) is 5.5 °C lower than in the simulated recent past (RP) climate and 1.3 °C higher than in the simulated Last Glacial Maximum (LGM; 21 ka BP) climate. The simulated GS12 is evaluated against proxy data and previous modelling studies of MIS3 stadial climate. We show that the simulated MIS 3 climate, and hence conclusions drawn regarding the dynamics of this climate, is highly model-dependent. The main findings are: (i) Proxy sea surface temperatures (SSTs) are higher than simulated SSTs in the central North Atlantic, in contrast to earlier simulations of MIS 3 stadial climate in which proxy SSTs were found to be lower than simulated SST. (ii) The Atlantic Meridional Overturning Circulation (AMOC) slows down by 50 % in the GS12 climate as compared to the RP climate. This slowdown is attained without freshwater forcing in the North Atlantic region, a method used in other studies to force an AMOC shutdown. (iii) El-Niño-Southern Oscillation (ENSO) teleconnections in mean sea level pressure (MSLP) are significantly modified by GS12 and LGM forcing and boundary conditions. (iv) Both the mean state and variability of the simulated GS12 is dependent on the equilibration. The annual global mean Ts only changes by 0.10 °C from model years 500-599 to the last century of the simulation, indicating that the climate system may be close to equilibrium already after 500 yr of integration. However, significant regional differences between the last century of the simulation and model years 500-599 exist. Further, the difference between simulated and proxy SST is reduced from model years 500-599 to the last century of the simulation. The results of the ENSO variability analysis is also shown to depend on the

  8. A coupled climate model simulation of Marine Isotope Stage 3 stadial climate

    Directory of Open Access Journals (Sweden)

    J. Brandefelt

    2011-06-01

    Full Text Available We present a coupled global climate model (CGCM simulation, integrated for 1500 yr to quasi-equilibrium, of a stadial (cold period within Marine Isotope Stage 3 (MIS 3. The simulated Greenland stadial 12 (GS12; ~44 ka BP annual global mean surface temperature (Ts is 5.5 °C lower than in the simulated recent past (RP climate and 1.3 °C higher than in the simulated Last Glacial Maximum (LGM; 21 ka BP climate. The simulated GS12 is evaluated against proxy data and previous modelling studies of MIS3 stadial climate. We show that the simulated MIS 3 climate, and hence conclusions drawn regarding the dynamics of this climate, is highly model-dependent. The main findings are: (i Proxy sea surface temperatures (SSTs are higher than simulated SSTs in the central North Atlantic, in contrast to earlier simulations of MIS 3 stadial climate in which proxy SSTs were found to be lower than simulated SST. (ii The Atlantic Meridional Overturning Circulation (AMOC slows down by 50 % in the GS12 climate as compared to the RP climate. This slowdown is attained without freshwater forcing in the North Atlantic region, a method used in other studies to force an AMOC shutdown. (iii El-Niño-Southern Oscillation (ENSO teleconnections in mean sea level pressure (MSLP are significantly modified by GS12 and LGM forcing and boundary conditions. (iv Both the mean state and variability of the simulated GS12 is dependent on the equilibration. The annual global mean Ts only changes by 0.10 °C from model years 500–599 to the last century of the simulation, indicating that the climate system may be close to equilibrium already after 500 yr of integration. However, significant regional differences between the last century of the simulation and model years 500–599 exist. Further, the difference between simulated and proxy SST is reduced from model years 500–599 to the last century of the simulation. The results of the ENSO variability

  9. Simulations of LGM climate of East Asia by regional climate model

    Institute of Scientific and Technical Information of China (English)

    郑益群; 于革; 王苏民; 薛滨; 刘华强; 曾新民

    2003-01-01

    Climate conditions in the Last Glacial Maximum (LGM) were remarkably different from the present ones. Adopting a regional climate model (RCM) which has included a detailed land surface scheme, LGM climate of East Asia has been simulated. The effects of vegetation changes on LGM climate have been diagnosed by adding forces of LGM paleovegetation reconstructed from the geological records. The results of the simulations by RCM indicate that large decreases in whole year temperature of East Asia continent caused strongly enhanced winter monsoon and weakened summer monsoon. The strengthening and westward-stretching of the Subtropical High of West-Pacific are the key reasons of decreases of LGM summer precipitation in eastern China. Precipitation and effective precipitation were increased in the Tibetan Plateau and Middle-Asia, while the humid condition in the Tibetan Plateau was mainly caused by increase of precipitation. Accumulated snow of LGM was also increased in the Tibetan Plateau, which was helpful to developing glacier and permafrost. This experiment has simulated that the frozen soil areas extend southward to 30°N. In LGM climate simulation, climate effects caused by external forces were amplified by added paleovegetation, therefore, decreases of temperature, changes of precipitation and snowfall, and other climatic parameters were further strengthened, making the simulation results more approach to geological evidences.

  10. Reconciled climate response estimates from climate models and the energy budget of Earth

    Science.gov (United States)

    Richardson, Mark; Cowtan, Kevin; Hawkins, Ed; Stolpe, Martin B.

    2016-10-01

    Climate risks increase with mean global temperature, so knowledge about the amount of future global warming should better inform risk assessments for policymakers. Expected near-term warming is encapsulated by the transient climate response (TCR), formally defined as the warming following 70 years of 1% per year increases in atmospheric CO2 concentration, by which point atmospheric CO2 has doubled. Studies based on Earth's historical energy budget have typically estimated lower values of TCR than climate models, suggesting that some models could overestimate future warming. However, energy-budget estimates rely on historical temperature records that are geographically incomplete and blend air temperatures over land and sea ice with water temperatures over open oceans. We show that there is no evidence that climate models overestimate TCR when their output is processed in the same way as the HadCRUT4 observation-based temperature record. Models suggest that air-temperature warming is 24% greater than observed by HadCRUT4 over 1861-2009 because slower-warming regions are preferentially sampled and water warms less than air. Correcting for these biases and accounting for wider uncertainties in radiative forcing based on recent evidence, we infer an observation-based best estimate for TCR of 1.66 °C, with a 5-95% range of 1.0-3.3 °C, consistent with the climate models considered in the IPCC 5th Assessment Report.

  11. Improving NASA's Multiscale Modeling Framework for Tropical Cyclone Climate Study

    Science.gov (United States)

    Shen, Bo-Wen; Nelson, Bron; Cheung, Samson; Tao, Wei-Kuo

    2013-01-01

    One of the current challenges in tropical cyclone (TC) research is how to improve our understanding of TC interannual variability and the impact of climate change on TCs. Recent advances in global modeling, visualization, and supercomputing technologies at NASA show potential for such studies. In this article, the authors discuss recent scalability improvement to the multiscale modeling framework (MMF) that makes it feasible to perform long-term TC-resolving simulations. The MMF consists of the finite-volume general circulation model (fvGCM), supplemented by a copy of the Goddard cumulus ensemble model (GCE) at each of the fvGCM grid points, giving 13,104 GCE copies. The original fvGCM implementation has a 1D data decomposition; the revised MMF implementation retains the 1D decomposition for most of the code, but uses a 2D decomposition for the massive copies of GCEs. Because the vast majority of computation time in the MMF is spent computing the GCEs, this approach can achieve excellent speedup without incurring the cost of modifying the entire code. Intelligent process mapping allows differing numbers of processes to be assigned to each domain for load balancing. The revised parallel implementation shows highly promising scalability, obtaining a nearly 80-fold speedup by increasing the number of cores from 30 to 3,335.

  12. A continuous latitudinal energy balance model to explore non-uniform climate engineering strategies

    Science.gov (United States)

    Bonetti, F.; McInnes, C. R.

    2016-12-01

    Current concentrations of atmospheric CO2 exceed measured historical levels in modern times, largely attributed to anthropogenic forcing since the industrial revolution. The required decline in emissions rates has never been achieved leading to recent interest in climate engineering for future risk-mitigation strategies. Climate engineering aims to offset human-driven climate change. It involves techniques developed both to reduce the concentration of CO2 in the atmosphere (Carbon Dioxide Removal (CDR) methods) and to counteract the radiative forcing that it generates (Solar Radiation Management (SRM) methods). In order to investigate effects of SRM technologies for climate engineering, an analytical model describing the main dynamics of the Earth's climate has been developed. The model is a time-dependent Energy Balance Model (EBM) with latitudinal resolution and allows for the evaluation of non-uniform climate engineering strategies. A significant disadvantage of climate engineering techniques involving the management of solar radiation is regional disparities in cooling. This model offers an analytical approach to design multi-objective strategies that counteract climate change on a regional basis: for example, to cool the Artic and restrict undesired impacts at mid-latitudes, or to control the equator-to-pole temperature gradient. Using the Green's function approach the resulting partial differential equation allows for the computation of the surface temperature as a function of time and latitude when a 1% per year increase in the CO2 concentration is considered. After the validation of the model through comparisons with high fidelity numerical models, it will be used to explore strategies for the injection of the aerosol precursors in the stratosphere. In particular, the model involves detailed description of the optical properties of the particles, the wash-out dynamics and the estimation of the radiative cooling they can generate.

  13. Evaluation of the Australian Community Climate and Earth-System Simulator Chemistry-Climate Model

    Directory of Open Access Journals (Sweden)

    K. A. Stone

    2015-07-01

    Full Text Available Chemistry climate models are important tools for addressing interactions of composition and climate in the Earth System. In particular, they are used for assessing the combined roles of greenhouse gases and ozone in Southern Hemisphere climate and weather. Here we present an evaluation of the Australian Community Climate and Earth System Simulator-Chemistry Climate Model, focusing on the Southern Hemisphere and the Australian region. This model is used for the Australian contribution to the international Chemistry-Climate Model Initiative, which is soliciting hindcast, future projection and sensitivity simulations. The model simulates global total column ozone (TCO distributions accurately, with a slight delay in the onset and recovery of springtime Antarctic ozone depletion, and consistently higher ozone values. However, October averaged Antarctic TCO from 1960 to 2010 show a similar amount of depletion compared to observations. A significant innovation is the evaluation of simulated vertical profiles of ozone and temperature with ozonesonde data from Australia, New Zealand and Antarctica from 38 to 90° S. Excess ozone concentrations (up to 26.4 % at Davis during winter and stratospheric cold biases (up to 10.1 K at the South Pole outside the period of perturbed springtime ozone depletion are seen during all seasons compared to ozonesondes. A disparity in the vertical location of ozone depletion is seen: centered around 100 hPa in ozonesonde data compared to above 50 hPa in the model. Analysis of vertical chlorine monoxide profiles indicates that colder Antarctic stratospheric temperatures (possibly due to reduced mid-latitude heat flux are artificially enhancing polar stratospheric cloud formation at high altitudes. The models inability to explicitly simulated supercooled ternary solution may also explain the lack of depletion at lower altitudes. The simulated Southern Annular Mode (SAM index compares well with ERA-Interim data. Accompanying

  14. Modeling human-induced climatic change: A summary for environmental managers

    Energy Technology Data Exchange (ETDEWEB)

    Sulzman, E.W. [National Biological Survey, Washington, DC (United States)]|[University Corporation for Atmospheric Research, Boulder, CO (United States); Poiani, K.A. [Cornell Univ., Ithaca, NY (United States); Kittel, T.G.F. [University Corporation for Atmospheric Research, Boulder, CO (United States)]|[Colorado State Univ., Fort Collins, CO (United States)

    1995-03-01

    The rapid increase in atmospheric concentrations of greenhouse gases has caused concern because of their potential to alter the earth`s radiation budget and disrupt current climate patterns. While there are many uncertainties associated with use of general circulation models (GCMs), GCMs are currently the best available technology to project changes in climate associated with elevated gas concentrations. Results indicate increases in global temperature and changes in global precipitation patterns are likely as a result of doubled CO{sub 2}. GCMs are not reliable for use at the regional scale because local scale processes and geography are not taken into account. Comparison of results from five GCMs in three regions of the United States indicate high variability across regions and among models depending on season and climate variable. Statistical methods of scaling model output and nesting finer resolution models in global models are two techniques that may improve projections. Despite the many limitations in GCMs, they are useful tools to explore climate-earth system dynamics when used in conjunction with water resource and ecosystem models. A variety of water resource models showed significant alteration of region hydrology when run with both GCM-generated and hypothetical climate scenarios, regardless of region or model complexity. Similarly, ecological models demonstrate the sensitivity of ecosystem production, nutrient dynamics, and distribution to changes in climate and CO{sub 2} levels. We recommend the use of GCM-based scenarios in conjunction with water resource and ecosystem models to guide environmental management and policy in a {open_quotes}no-regrets{close_quotes} framework or as part of a precautionary approach to natural resource protection. 174 refs., 4 figs., 5 tabs.

  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

    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...

  16. Observationally-Based Data/Model Metrics from the Southern Ocean Climate Model Atlas

    Science.gov (United States)

    Abell, J.; Russell, J. L.; Goodman, P. J.

    2015-12-01

    The Southern Ocean Climate Model Atlas makes available observationally-based standardized data/model metrics of the latest simulations of climate and projections of climate change from available climate models. Global climate model simulations differ greatly in the Southern Ocean, so the development of consistent, observationally-based metrics, by which to assess the fidelity of model simulations is essential. We will present metrics showing and quantifying the results of the modern day climate simulations over the Southern Ocean from models submitted as part of the CMIP5/IPCC-AR5 process. Our analysis will focus on the simulations of the temperature, salinity and carbon at various depths and along significant hydrographic sections. The models exhibit different skill levels with various metrics between models and also within individual models.

  17. Web Service Based Approach to Link Heterogeneous Climate-Energy-Economy Models for Climate Change Mitigation Analysis

    NARCIS (Netherlands)

    Belete, Getachew F.; Voinov, Alexey; Bulavskaya, Tatyana; Niamir, Leila; Dhavala, Kishore

    2016-01-01

    Climate change mitigation analysis requires understanding the causes and identifying the possible alternative actions that could be taken. We linked heterogeneous models that focus on climate, energy, and economy for the purpose of climate change mitigation. The models were originally developed to s

  18. Web Service Based Approach to Link Heterogeneous Climate-Energy-Economy Models for Climate Change Mitigation Analysis

    NARCIS (Netherlands)

    Belete, G.F.; Voinov, A.; Bulavskaya, Tatyana; Niamir, Leila; Dhavala, Kishore

    2016-01-01

    Climate change mitigation analysis requires understanding the causes and identifying the possible alternative actions that could be taken. We linked heterogeneous models that focus on climate, energy, and economy for the purpose of climate change mitigation. The models were originally developed to

  19. CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

    Science.gov (United States)

    Rose, B. E. J.

    2015-12-01

    Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

  20. Post-2020 climate agreements in the major economies assessed in the light of global models

    NARCIS (Netherlands)

    Tavoni, M.; Kriegler, E.; Riahi, K.; van Vuuren, D.F.; Aboumahboub, T.; Bowen, A.; Calvin, K.; Campiglio, E.; Kober, T.; Jewell, J.; Luderer, G.; Marangoni, G.; McCollum, D.; van Sluisveld, M.; Zimmer, A.; van der Zwaan, B.

    2014-01-01

    Integrated assessment models can help in quantifying the implications of international climate agreements and regional climate action. This paper reviews scenario results from model intercomparison projects to explore different possible outcomes of post-2020 climate negotiations, recently announced

  1. Post-2020 climate agreements in the major economies assessed in the light of global models

    NARCIS (Netherlands)

    Tavoni, Massimo; Kriegler, Elmar; Riahi, Keywan; Van Vuuren, Detlef P.|info:eu-repo/dai/nl/11522016X; Aboumahboub, Tino; Bowen, Alex; Calvin, Katherine; Campiglio, Emanuele; Kober, Tom; Jewell, Jessica; Luderer, Gunnar; Marangoni, Giacomo; Mccollum, David; Van Sluisveld, Mariësse; Zimmer, Anne; Van Der Zwaan, Bob

    2015-01-01

    Integrated assessment models can help in quantifying the implications of international climate agreements and regional climate action. This paper reviews scenario results from model intercomparison projects to explore different possible outcomes of post-2020 climate negotiations, recently announced

  2. Post-2020 climate agreements in the major economies assessed in the light of global models

    NARCIS (Netherlands)

    Tavoni, M.; Kriegler, E.; Riahi, K.; van Vuuren, D.F.; Aboumahboub, T.; Bowen, A.; Calvin, K.; Campiglio, E.; Kober, T.; Jewell, J.; Luderer, G.; Marangoni, G.; McCollum, D.; van Sluisveld, M.; Zimmer, A.; van der Zwaan, B.

    2014-01-01

    Integrated assessment models can help in quantifying the implications of international climate agreements and regional climate action. This paper reviews scenario results from model intercomparison projects to explore different possible outcomes of post-2020 climate negotiations, recently announced

  3. Post-2020 climate agreements in the major economies assessed in the light of global models

    NARCIS (Netherlands)

    Tavoni, Massimo; Kriegler, Elmar; Riahi, Keywan; Van Vuuren, Detlef P.; Aboumahboub, Tino; Bowen, Alex; Calvin, Katherine; Campiglio, Emanuele; Kober, Tom; Jewell, Jessica; Luderer, Gunnar; Marangoni, Giacomo; Mccollum, David; Van Sluisveld, Mariësse; Zimmer, Anne; Van Der Zwaan, Bob

    2015-01-01

    Integrated assessment models can help in quantifying the implications of international climate agreements and regional climate action. This paper reviews scenario results from model intercomparison projects to explore different possible outcomes of post-2020 climate negotiations, recently announced

  4. Using a Global Climate Model in an On-line Climate Change Course

    Science.gov (United States)

    Randle, D. E.; Chandler, M. A.; Sohl, L. E.

    2012-12-01

    Seminars on Science: Climate Change is an on-line, graduate-level teacher professional development course offered by the American Museum of Natural History. It is an intensive 6-week course covering a broad range of global climate topics, from the fundamentals of the climate system, to the causes of climate change, the role of paleoclimate investigations, and a discussion of potential consequences and risks. The instructional method blends essays, videos, textbooks, and linked websites, with required participation in electronic discussion forums that are moderated by an experienced educator and a course scientist. Most weeks include additional assignments. Three of these assignments employ computer models, including two weeks spent working with a full-fledged 3D global climate model (GCM). The global climate modeling environment is supplied through a partnership with Columbia University's Educational Global Climate Modeling Project (EdGCM). The objective is to have participants gain hands-on experience with one of the most important, yet misunderstood, aspects of climate change research. Participants in the course are supplied with a USB drive that includes installers for the software and sample data. The EdGCM software includes a version of NASA's global climate model fitted with a graphical user interface and pre-loaded with several climate change simulations. Step-by-step assignments and video tutorials help walk people through these challenging exercises and the course incorporates a special assignment discussion forum to help with technical problems and questions about the NASA GCM. There are several takeaways from our first year and a half of offering this course, which has become one of the most popular out of the twelve courses offered by the Museum. Participants report a high level of satisfaction in using EdGCM. Some report frustration at the initial steps, but overwhelmingly claim that the assignments are worth the effort. Many of the difficulties that

  5. Biases in simulation of the rice phenology models when applied in warmer climates

    Science.gov (United States)

    Zhang, T.; Li, T.; Yang, X.; Simelton, E.

    2015-12-01

    The current model inter-comparison studies highlight the difference in projections between crop models when they are applied to warmer climates, but these studies do not provide results on how the accuracy of the models would change in these projections because the adequate observations under largely diverse growing season temperature (GST) are often unavailable. Here, we investigate the potential changes in the accuracy of rice phenology models when these models were applied to a significantly warmer climate. We collected phenology data from 775 trials with 19 cultivars in 5 Asian countries (China, India, Philippines, Bangladesh and Thailand). Each cultivar encompasses the phenology observations under diverse GST regimes. For a given rice cultivar in different trials, the GST difference reaches 2.2 to 8.2°C, which allows us to calibrate the models under lower GST and validate under higher GST (i.e., warmer climates). Four common phenology models representing major algorithms on simulations of rice phenology, and three model calibration experiments were conducted. The results suggest that the bilinear and beta models resulted in gradually increasing phenology bias (Figure) and double yield bias per percent increase in phenology bias, whereas the growing-degree-day (GDD) and exponential models maintained a comparatively constant bias when applied in warmer climates (Figure). Moreover, the bias of phenology estimated by the bilinear and beta models did not reduce with increase in GST when all data were used to calibrate models. These suggest that variations in phenology bias are primarily attributed to intrinsic properties of the respective phenology model rather than on the calibration dataset. Therefore we conclude that using the GDD and exponential models has more chances of predicting rice phenology correctly and thus, production under warmer climates, and result in effective agricultural strategic adaptation to and mitigation of climate change.

  6. Investigations of the Climate System Response to Climate Engineering in a Hierarchy of Models

    Science.gov (United States)

    McCusker, Kelly E.

    Global warming due to anthropogenic emissions of greenhouse gases is causing negative impacts on diverse ecological and human systems around the globe, and these impacts are projected to worsen as climate continues to warm. In the absence of meaningful greenhouse gas emissions reductions, new strategies have been proposed to engineer the climate, with the aim of preventing further warming and avoiding associated climate impacts. We investigate one such strategy here, falling under the umbrella of `solar radiation management', in which sulfate aerosols are injected into the stratosphere. We use a global climate model with a coupled mixed-layer depth ocean and with a fully-coupled ocean general circulation model to simulate the stabilization of climate by balancing increasing carbon dioxide with increasing stratospheric sulfate concentrations. We evaluate whether or not severe climate impacts, such as melting Arctic sea ice, tropical crop failure, or destabilization of the West Antarctic ice sheet, could be avoided. We find that while tropical climate emergencies might be avoided by use of stratospheric aerosol injections, avoiding polar emergencies cannot be guaranteed due to large residual climate changes in those regions, which are in part due to residual atmospheric circulation anomalies. We also find that the inclusion of a fully-coupled ocean is important for determining the regional climate response because of its dynamical feedbacks. The efficacy of stratospheric sulfate aerosol injections, and solar radiation management more generally, depends on its ability to be maintained indefinitely, without interruption from a variety of possible sources, such as technological failure, a breakdown in global cooperation, lack of funding, or negative unintended consequences. We next consider the scenario in which stratospheric sulfate injections are abruptly terminated after a multi- decadal period of implementation while greenhouse gas emissions have continued unabated

  7. Groundwater flow modelling of periods with temperate climate conditions - Laxemar

    Energy Technology Data Exchange (ETDEWEB)

    Joyce, Steven; Simpson, Trevor; Hartley, Lee; Applegate, David; Hoek, Jaap; Jackson, Peter; Roberts, David; Swan, David (Serco Technical Consulting Services (United Kingdom)); Gylling, Bjoern; Marsic, Niko (Kemakta Konsult AB, Stockholm (Sweden)); Rhen, Ingvar (SWECO Environment AB, Falun (Sweden))

    2010-12-15

    As a part of the license application for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different hydraulic conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. This report concerns the modelling of a repository at the Laxemar-Simpevarp site during temperate climate conditions as a comparison to corresponding modelling carried out for Forsmark /Joyce et al. 2010/. The collation and implementation of onsite hydrogeological and hydrogeochemical data from previous reports are used in the construction of a Hydrogeological base case (reference case conceptualisation) and then an examination of various areas of uncertainty within the current understanding by a series of model variants. The Hydrogeological base case models at three different scales, 'repository', 'site' and 'regional' make use of a discrete fracture network (DFN) and equivalent continuous porous medium (ECPM) models. The use of hydrogeological models allow for the investigation of the groundwater flow from a deep disposal facility to the biosphere and for the calculation of performance measures that will provide an input to the site performance assessment. The focus of the study described in this report has been to perform numerical simulations of the hydrogeological system from post-closure and throughout the temperate period up until the receding shoreline leaves the modelling domain at around 15,000 AD. Besides providing quantitative results for the immediate temperate period following post-closure, these results are also intended to give a qualitative indication of the evolution of the groundwater system during future temperate periods within an ongoing cycle of glacial/inter-glacial events

  8. Climatic Classification over Asia during the Middle Holocene Climatic Optimum Based on PMIP Models

    Institute of Scientific and Technical Information of China (English)

    Hyuntaik Oh; Ho-Jeong Shin

    2016-01-01

    ABSTRACT:When considering potential global warming projections, it is useful to understand the im-pact of each climate condition at 6 kyr before present. Asian paleoclimate was simulated by performing an integration of the multi-model ensemble with the paleoclimate modeling intercomparison project (PMIP) models. The reconstructed winter (summer) surface air temperature at 6 kyr before present was 0.85 ºC (0.21 ºC) lower (higher) than the present day over Asia, 60ºE–150ºE, 10ºN–60ºN. The seasonal variation and heating differences of land and ocean in summer at 6 kyr before present might be much larger than present day. The winter and summer precipitation of 6 kyr before present were 0.067 and 0.017 mm·day-1 larger than present day, respectively. The Group B climate, which means the dry climates based on Köppen climate classification, at 6 kyr before present decreased 17%compared to present day, but the Group D which means the continental and microthermal climates at 6 kyr before present increased over 7%. Comparison between the results from the model simulation and published paleo-proxy record agrees within the limited sparse paleo-proxy record data.

  9. Assessing model uncertainties in climate projections of severe, mid-latitude windstorms using seamless approach

    Science.gov (United States)

    Trzeciak, T. M.; Knippertz, P.; Owen, J. S. R.

    2012-04-01

    Despite the enormous advances made in climate change research, robust projections of the position and the strength of the North Atlantic stormtrack are not yet possible. In particular with respect to damaging windstorms, this incertitude bears enormous risks to European societies and the (re-)insurance industry. Previous studies have addressed the problem of climate model uncertainty through statistical comparisons of simulations of the current climate with (re-)analysis data and found that there is large disagreement between different climate models, different ensemble members of the same model and observed climatologies of intense cyclones. The use of different horizontal and vertical resolutions, as well as different approaches to measure storminess further complicate comparison between the results from different studies. One weakness of such statistical evaluations lies in the difficulty to separate influences of the climate model's basic state, which will be governed by slow processes such as ocean circulations or sea-ice transport, from the influence of fast processes such as energy fluxes from the ocean or latent heating on the development of the most intense storms. The former might generate a bias in storm counts through an incorrect occurrence frequency of storm-prone initial conditions, while the latter could generate a similar bias due to the lack of crucial dynamics of extreme cyclone intensification due to over-simplistic model physics or insufficient horizontal resolution. Compensating effects between the two might conceal errors and suggest higher reliability than there really is. Therefore, separating sources of uncertainty is an important step towards a more reliable interpretation of climate projections and towards targeted improvements of future model generations. A possible way to separate influences of fast and slow processes in climate projections is through a "seamless" approach of hindcasting historical, severe storms with climate models

  10. Current Progresses in Study of Impacts of the Tibetan Plateau on Asian Summer Climate

    Institute of Scientific and Technical Information of China (English)

    WU Guoxiong; MAO Jiangyu; DUAN Anmin; ZHANG Qiong

    2006-01-01

    The current progresses in the study of impacts of the Tibetan Plateau on Asian summer climate in the last decade are reviewed. By analyzing evolution of the transitional zone between westerly to the north and easterly to the south (WEB), it is shown that due to the strong heating over the Tibetan Plateau in spring, the overturning in the prevailing wind direction from easterly in winter to westerly in summer occurs firstly over the eastern Bay of Bengal (BOB), accompanied with vigorous convective precipitation to its east. The area between eastern BOB and western Indo-China Peninsula thus becomes the area with the earliest onset of Asian monsoon, which may be referred as BOB monsoon in short. It is shown that the summertime circulations triggered by the thermal forcing of the Iranian Plateau and the Tibetan Plateau are embedded in phase with the continental-scale circulation forced by the diabatic heating over the Eurasian Continent. As a result, the East Asian summer monsoon is intensified and the drought climate over the western and central Asian areas is enhanced. Together with perturbations triggered by the Tibetan Plateau,the above scenarios and the associated heating have important influences on the climate patterns over Asia.Furthermore, the characteristics of the Tibetan mode of the summertime South Asian high are compared with those of Iranian mode. Results demonstrate that corresponding to each of the bimodality of the South Asian high, the rainfall anomaly distributions over Asia exhibit different patterns.

  11. SIMULATION OF PRESENT CLIMATE OVER EAST ASIA BY A REGIONAL CLIMATE MODEL

    Institute of Scientific and Technical Information of China (English)

    ZHANG Dong-feng; GAO Xue-jie; OUYANG Li-cheng; DONG Wen-jie

    2008-01-01

    A 15-year simulation of climate over East Asia is conducted with the latest version of a regional climate model RegCM3 nested in one-way mode to the ERA40 Re-analysis data. The performance of themodel in simulating present climate over East Asia and China is investigated. Results show that RegCM3 can reproduce well the atmospheric circulation over East Asia. The simulation of the main distribution patterns of surface air temperature and precipitation over China and their seasonal cycle/evolution, are basically agree with that of the observation. Meanwhile a general cold bias is found in the simulation. AS for the precipitation, the model tends to overestimate the precipitation in northern China while underestimate it in southern China, particularly in winter. In general, the model has better performance in simulating temperature than precipitation.

  12. Exploitation of parallelism in climate models. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Baer, Ferdinand; Tribbia, Joseph J.; Williamson, David L.

    2001-02-05

    This final report includes details on the research accomplished by the grant entitled 'Exploitation of Parallelism in Climate Models' to the University of Maryland. The purpose of the grant was to shed light on (a) how to reconfigure the atmospheric prediction equations such that the time iteration process could be compressed by use of MPP architecture; (b) how to develop local subgrid scale models which can provide time and space dependent parameterization for a state-of-the-art climate model to minimize the scale resolution necessary for a climate model, and to utilize MPP capability to simultaneously integrate those subgrid models and their statistics; and (c) how to capitalize on the MPP architecture to study the inherent ensemble nature of the climate problem. In the process of addressing these issues, we created parallel algorithms with spectral accuracy; we developed a process for concurrent climate simulations; we established suitable model reconstructions to speed up computation; we identified and tested optimum realization statistics; we undertook a number of parameterization studies to better understand model physics; and we studied the impact of subgrid scale motions and their parameterization in atmospheric models.

  13. Advances in ocean modeling for climate change research

    Science.gov (United States)

    Holland, William R.; Capotondi, Antonietta; Holland, Marika M.

    1995-07-01

    An adequate understanding of climate variability and the eventual prediction of climate change are among the most urgent and far-reaching efforts of the scientific community. The climate system is in an ever-changing state with vast impact on mankind in all his activities. Both short and long-term aspects of climate variability are of concern, and the unravelling of "natural" variability from "man-induced" climate change is required to prepare for and ameliorate, if possible, the potentially devastating aspects of such change. In terms of scientific effort, the climate community can be thought of as the union of the disciplinary sciences of meteorology, oceanography, sea ice and glaciology, and land surface processes. Since models are based upon mathematical and numerical constructs, mathematics and computer sciences are also directly involved. In addition, some of the problems of man-induced climate change (release of greenhouse gases, the ozone-hole problem, etc.) are basically chemical in nature, and the expertise of the atmospheric and oceanic chemist is also required. In addition, some part of the response to climate perturbations will arise in the biological world, due to upsetting the balance in the great food web that binds communities together on both the land and the sea. Thus, the problems to be solved are extraordinarily complex and require the efforts of many kinds of scientist.

  14. [Current distribution of Schisandra chinensis in China and its predicted responses to climate change].

    Science.gov (United States)

    Hu, Li-Le; Zhang, Hai-Ying; Qin, Ling; Yan, Bo-Qian

    2012-09-01

    With integration of literature data, specimens records, and field surveys, the current distribution map of Schisandra chinensis in China was drawn, and, based on this map and considering 21 environmental factors, the future distribution of S. chinensis in China in the 2050s and 2080s under the IPCC A2 and A1B climate change scenarios was predicted by using Maxent software. Currently, the S. chinensis in China occurred in 15 provinces, involving 151 counties, and its distribution area decreased with decreasing latitude and longitude. The main distribution area included Heilongjiang, Liaoning, Inner Mongolia, and Jilin. The potential distribution area of S. chinensis in China was 145.12 x 10(4) km2, 48.6% of which were the favorable habitat area, mainly distributed in Changbai Mountains, Xiaoxing'anling Mountains, Daxing'anling Mountains, and the regions between Hebei and Liaoning provinces. The most favorable habitat area only accounted for 0.3%, and was mainly in the Kuandian Manchu Autonomous County, Benxi Manchu Autonomous County, and Huanren Manchu Autonomous County of Liaoning Province, the Antu County and Helong County of Jilin Province, and the Yakeshi City of Inner Mongolia. Under the two climate change scenarios, the potential future distribution area of S. chinensis in China would have a gradual decrease, and the decrement would be larger under A2 than under A1B scenario. By 2050, the distribution area of the S. chinensis under A1B and A2 scenarios would be moderately decreased to 84.0% and 81.5% of the current distribution area, respectively; by 2080, the distribution of S. chinensis under A2 scenario would be dramatically decreased to only 0.5% of the current range, and that under A1B scenario would be decreased to 1/2 of the current range.

  15. Biotic Interactions in the Face of Climate Change: A Comparison of Three Modelling Approaches

    Science.gov (United States)

    Jaeschke, Anja; Bittner, Torsten; Jentsch, Anke; Reineking, Björn; Schlumprecht, Helmut; Beierkuhnlein, Carl

    2012-01-01

    Climate change is expected to alter biotic interactions, and may lead to temporal and spatial mismatches of interacting species. Although the importance of interactions for climate change risk assessments is increasingly acknowledged in observational and experimental studies, biotic interactions are still rarely incorporated in species distribution models. We assessed the potential impacts of climate change on the obligate interaction between Aeshna viridis and its egg-laying plant Stratiotes aloides in Europe, based on an ensemble modelling technique. We compared three different approaches for incorporating biotic interactions in distribution models: (1) We separately modelled each species based on climatic information, and intersected the future range overlap (‘overlap approach’). (2) We modelled the potential future distribution of A. viridis with the projected occurrence probability of S. aloides as further predictor in addition to climate (‘explanatory variable approach’). (3) We calibrated the model of A. viridis in the current range of S. aloides and multiplied the future occurrence probabilities of both species (‘reference area approach’). Subsequently, all approaches were compared to a single species model of A. viridis without interactions. All approaches projected a range expansion for A. viridis. Model performance on test data and amount of range gain differed depending on the biotic interaction approach. All interaction approaches yielded lower range gains (up to 667% lower) than the model without interaction. Regarding the contribution of algorithm and approach to the overall uncertainty, the main part of explained variation stems from the modelling algorithm, and only a small part is attributed to the modelling approach. The comparison of the no-interaction model with the three interaction approaches emphasizes the importance of including obligate biotic interactions in projective species distribution modelling. We recommend the use of

  16. Multi-wheat-model ensemble responses to interannual climate variability

    NARCIS (Netherlands)

    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; Basso, Bruno; Bertuzzi, Patrick; Biernath, Christian; Brisson, Nadine; Challinor, Andrew J.; Doltra, Jordi; Gayler, Sebastian; Goldberg, Richard; Grant, Robert F.; Heng, Lee; Hooker, Josh; Hunt, Leslie A.; Ingwersen, Joachim; Izaurralde, Roberto C.; Kersebaum, Kurt Christian; Kumar, Soora Naresh; Müller, Christoph; Nendel, Claas; O'Leary, Garry; Olesen, Jørgen E.; Osborne, Tom M.; Palosuo, Taru; Priesack, Eckart; Ripoche, Dominique; Rötter, Reimund P.; Semenov, Mikhail A.; Shcherbak, Iurii; Steduto, Pasquale; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Travasso, Maria; Waha, Katharina; Wallach, Daniel; White, Jeffrey W.; Wolf, Joost

    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

  17. A Modeling Tool for Evaluating Climate Change Impacts on Water Supply System

    Science.gov (United States)

    Chuang, L.; Tung, C.; Liu, T.

    2009-12-01

    Climate change may exacerbate short-term climate variability and more extreme hydrological events, and then may impact on human society and natural environment. Socioeconomic development is dependent on adequate water resources, but climate change may impact on such supply system, including available streamflow, groundwater, irrigation water demand. The purpose of this study is to apply an integrated modeling tool to assess the climate change impacts on regional water supply systems and then to propose response strategies to strengthen adaptive capacity to achieve sustainable water uses. The modeling tool integrates the functions of downscaling, weather generation, hydrological modeling, and an interface for linking system dynamics models. The Touchien river basin in Taiwan is chosen as a study area, which has a high-tech industry park. The vulnerability of the water supply system was evaluated for present and future conditions. The results demonstrated that the water supply system could meet current water demand, but might be subjected to serious water shortage due to future climate change and increasing water demand. At last, this study provides suggestions to government agency to develop better water resources management strategies to mitigate the impacts of changing climate.

  18. A description of persistent climatic anomalies in a 1000-year climatic model simulation

    Science.gov (United States)

    Hunt, B. G.

    The Mark 2 version of the CSIRO coupled global climatic model has been used to generate a 1000-year simulation of natural (i.e. unforced) climatic variability representative of ``present conditions''. The annual mean output from the simulation has been used to investigate the occurrence of decadal and longer trends over the globe for a number of climatic variables. Here trends are defined to be periods of years with a climatic anomaly of a given sign. The analysis reveals substantial differences between the trend characteristics of the various climatic variables. Trends longer than 12years duration were unusual for rainfall. Such trends were fairly uniformly distributed over the globe and had an asymmetry in the rate of occurrence for wet or dry conditions. On the other hand, trends in surface wind stress, and especially the atmospheric screen temperature, were of longer duration but primarily confined to oceanic regions. The trends in the atmospheric screen temperature could be traced deep into the oceanic mixed layer, implying large changes in oceanic thermal inertia. This thermal inertia then constituted an important component of the `memory' of the climatic system. While the geographic region associated with a given trend could be identified over several adjacent grid boxes of the model, regional plots for individual years of the trend revealed a range of variations, suggesting that a consistent forcing mechanism may not be responsible for a trend at a given location. Typical return periods for 12-year rainfall trends were once in 1000years, highlighting the rarity of such events. Using a looser definition of a trend revealed that drying trends up to 50 years duration were also possible, attributable solely to natural climatic variability. Significant ( 20% to 40%) rainfall reductions per year can be associated with a long-term drying trend, hence such events are of considerable climatic significance. It can take more than 100years for the hydrologic losses

  19. A Distributed, Cross-Agency Software Architecture for Sharing Climate Models and Observational Data Sets (Invited)

    Science.gov (United States)

    Crichton, D. J.; Mattmann, C. A.; Braverman, A. J.; Cinquini, L.

    2010-12-01

    The Jet Propulsion Laboratory (JPL) has been developing a distributed infrastructure to supporting access and sharing of Earth Science observational data sets with climate models to support model-to-data intercomparison for climate research. The Climate Data Exchange (CDX), a framework for linking distributed repositories coupled with tailored distributed services to support the intercomparison, provides mechanisms to discover, access, transform and share observational and model output data [2]. These services are critical to allowing data to remain distributed, but be pulled together to support analysis. The architecture itself provides a services-based approach allowing for integrating and working with other computing infrastructures through well-defined software interfaces. Specifically, JPL has worked very closely with the Earth System Grid (ESG) and the Program for Climate Model Diagnostics and Intercomparisons (PCMDI) at Lawrence Livermore National Laboratory (LLNL) to integrate NASA science data systems with the Earth System Grid to support federation across organizational and agency boundaries [1]. Of particular interest near-term is enabling access to NASA observational data along-side climate models for the Coupled Model Intercomparison Project known as CMIP5. CMIP5 is the protocol that will be used for the next International Panel for Climate Change (IPCC) Assessment Report (AR5) on climate change. JPL and NASA are currently engaged in a project to ensure that observational data are available to the climate research community through the Earth System Grid. By both developing a software architecture and working with the key architects for the ESG, JPL has been successful at building a prototype for AR5. This presentation will review the software architecture including core principles, models and interfaces, the Climate Data Exchange project and specific goals to support access to both observational data and models for AR5. It will highlight the progress

  20. The aerosol-climate model ECHAM5-HAM

    Directory of Open Access Journals (Sweden)

    P. Stier

    2005-01-01

    Full Text Available The aerosol-climate modelling system ECHAM5-HAM is introduced. It is based on a flexible microphysical approach and, as the number of externally imposed parameters is minimised, allows the application in a wide range of climate regimes. ECHAM5-HAM predicts the evolution of an ensemble of microphysically interacting internally- and externally-mixed aerosol populations as well as their size-distribution and composition. The size-distribution is represented by a superposition of log-normal modes. In the current setup, the major global aerosol compounds sulfate (SU, black carbon (BC, particulate organic matter (POM, sea salt (SS, and mineral dust (DU are included. The simulated global annual mean aerosol burdens (lifetimes for the year 2000 are for SU: 0.80 Tg(S (3.9 days, for BC: 0.11 Tg (5.4 days, for POM: 0.99 Tg (5.4 days, for SS: 10.5 Tg (0.8 days, and for DU: 8.28 Tg (4.6 days. An extensive evaluation with in-situ and remote sensing measurements underscores that the model results are generally in good agreement with observations of the global aerosol system. The simulated global annual mean aerosol optical depth (AOD is with 0.14 in excellent agreement with an estimate derived from AERONET measurements (0.14 and a composite derived from MODIS-MISR satellite retrievals (0.16. Regionally, the deviations are not negligible. However, the main patterns of AOD attributable to anthropogenic activity are reproduced.

  1. Groundwater flow modelling of periods with temperate climate conditions - Forsmark

    Energy Technology Data Exchange (ETDEWEB)

    Joyce, Steven; Simpson, Trevor; Hartley, Lee; Applegate, David; Hoek, Jaap; Jackson, Peter; Swan, David (Serco Technical Consulting Services (United Kingdom)); Marsic, Niko (Kemakta Konsult AB (Sweden)); Follin, Sven (SF GeoLogic AB (Sweden))

    2010-11-15

    As a part of the license application for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different climate conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. This report concerns the modelling of a repository at the Forsmark site during temperate conditions; i.e. from post-closure and throughout the temperate period up until the receding shoreline leaves the modelling domain at around 12,000 AD. The collation and implementation of onsite hydrogeological and hydrogeochemical data from previous reports are used in the construction of a hydrogeological base case (reference case conceptualisation) and then in an examination of various areas of uncertainty within the current understanding by a series of model variants. The hydrogeological base case models at three different scales, 'repository', 'site' and 'regional', make use of continuous porous medium (CPM), equivalent continuous porous medium (ECPM) and discrete fracture network (DFN) models. The use of hydrogeological models allow for the investigation of the groundwater flow from a deep disposal facility to the biosphere and for the calculation of performance measures that will provide an input to the site performance assessment. The focus of the study described in this report has been to perform numerical simulations of the hydrogeological system from post-closure and throughout the temperate period. Besides providing quantitative results for the immediate temperate period following post-closure, these results are also intended to give a qualitative indication of the evolution of the groundwater system during future temperate periods within an ongoing cycle of glacial/inter-glacial events

  2. Large-scale features of Pliocene climate: results from the Pliocene Model Intercomparison Project

    Directory of Open Access Journals (Sweden)

    A. M. Haywood

    2012-07-01

    Full Text Available Climate and environments of the mid-Pliocene Warm Period (3.264 to 3.025 Ma have been extensively studied. Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a co-ordinated multi-model and multi-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data/model comparison highlights the potential for models to underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Sensitivity tests exploring the "known unknowns" in modelling Pliocene climate specifically relevant to the high-latitudes are also essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses. Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS, suggest that ESS is greater than Climate Sensitivity (CS, and that the ratio of ESS to CS is between 1 and 2, with a best estimate of 1.5.

  3. Large-scale features of Pliocene climate: results from the Pliocene Model Intercomparison Project

    Directory of Open Access Journals (Sweden)

    A. M. Haywood

    2013-01-01

    Full Text Available Climate and environments of the mid-Pliocene warm period (3.264 to 3.025 Ma have been extensively studied. Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a coordinated multi-model and multi-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are clearly evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data/model comparison highlights that models potentially underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Furthermore, sensitivity tests exploring the known unknowns in modelling Pliocene climate specifically relevant to the high latitudes are essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses. Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS, support previous work suggesting that ESS is greater than Climate Sensitivity (CS, and suggest that the ratio of ESS to CS is between 1 and 2, with a "best" estimate of 1.5.

  4. Embedding complex hydrology in the climate system - towards fully coupled climate-hydrology models

    DEFF Research Database (Denmark)

    Butts, M.; Rasmussen, S.H.; Ridler, M.

    2013-01-01

    model, HIRHAM. The physics of the coupling is formulated using an energy-based SVAT (land surface) model while the numerical coupling exploits the OpenMI modelling interface. First, some investigations of the applicability of the SVAT model are presented, including our ability to characterise...... distributed parameters using satellite remote sensing. Secondly, field data are used to investigate the effects of model resolution and parameter scales for use in a coupled model. Finally, the development of the fully coupled climate-hydrology model is described and some of the challenges associated...

  5. What Can Human Geography Offer Climate Change Modelling?

    DEFF Research Database (Denmark)

    Grindsted, Thomas Skou

    2014-01-01

    The discipline of Geography may be one of the most prominent and oldest disciplines in the conceptualization of human–environment interactions that integrates elements from both natural and social sciences. Yet, much research on society–environment interactions on climate change reduces human...... conceptual modelling of climate change adaption and mitigation. In other words, geographical representations do matter. In the following we will first reflect upon what I shall call spatio-temporal tides and waves of the human environment theme to examine the methodological grounds on which climate change...

  6. Terrestrial hydro-climatic change, lake shrinkage and water resource deterioration: Analysis of current to future drivers across Asia

    Science.gov (United States)

    Jarsjo, J.; Beygi, H.; Thorslund, J.

    2016-12-01

    Due to overlapping effects of different anthropogenic pressures and natural variability, main drivers behind on-going changes in the water cycle have in many cases not been identified, which complicates management of water resources. For instance, in many parts of the world, and not least in semi-arid and arid parts of Asia, lowered groundwater levels and shrinkage of surface water bodies with associated salinization and water quality deterioration constitute great challenges. With the aim to identify main drivers and mechanisms behind such changes, we here combine (i) historical observations of long-term, large scale change, (ii) ensemble projections of expected future change from the climate models of the Coupled Model Intercomparison Project Phase 5 (CMIP 5) and (iii) output from water balance modelling. Our particular focus is on regions near shrinking lakes. For the principal Lake Urmia in Iran, results show that agricultural intensification including irrigation expansion has clearly contributed to the surprisingly rapid water quality deterioration and lake shrinkage, from 10% lake area reduction in 2002 to the current value of about 75% (leaving billion of tons of salt exposed in its basin). Nevertheless, runoff decrease due to climate change has had an even larger effect. For the Aral Sea in Central Asia, where problems accelerated much earlier (in the 1990's), land-use change and irrigation expansion can fully explain the disastrous surface water deficits and water quality problems in the extensive low-lying parts of the basin. However, projections show that climate-driven runoff decrease in the headwaters of the Aral Sea basin may become a dominant driver of continued change in the near-future. More generally, present results illustrate that mitigation measures that compensate only for land-use driven effects may not reverse current trends of decreasing water availability, due to increasingly strong impacts of climate-driven runoff decrease. This has

  7. Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

    Science.gov (United States)

    Delgado, Juan; Moreno-Navas, Juan; Pulido, Antoine; García-Lafuente, Juan; Calero Quesada, Maria C.; García, Rodrigo

    2017-04-01

    Extreme climatic events, such as heat waves and severe storms are predicted to increase in frequency and magnitude as a consequence of global warming but their socio-ecological effects are poorly understood, particularly in estuarine ecosystems. The Guadalquivir Estuary has been anthropologically modified several times, the original salt marshes have been transformed to grow rice and cotton and approximately one-fourth of the total surface of the estuary is now part of two protected areas, one of them is a UNESCO, MAB Biosphere Reserve. The climatic events are most likely to affect Europe in forthcoming decades and a further understanding how these climatic disturbances drive abrupt changes in the Guadalquivir estuary is needed. A barotropic model has been developed to study how severe storm events affects the estuary by conducting paired control and climate-events simulations. The changes in the local wind and atmospheric pressure conditions in the estuary have been studied in detail and several scenarios are obtained by running the model under control and real storm conditions. The model output has been validated with in situ water elevation and good agreement between modelled and real measurements have been obtained. Our preliminary results show that the model demonstrated the capability describe of the tide-surge levels in the estuary, opening the possibility to study the interaction between climatic events and the port operations and food production activities. The barotropic hydrodynamic model provide spatially explicit information on the key variables governing the tide dynamics of estuarine areas under severe climatic scenarios . The numerical model will be a powerful tool in future climate change mitigation and adaptation programs in a complex socio-ecological system.

  8. Bioclimatic predictions of habitat suitability for the biofuel switchgrass in North America under current and future climate scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Barney, Jacob N.; DiTomaso, Joseph M. [One Shields Ave, Mailstop 4, Department of Plant Sciences, University of California, Davis, CA 95616 (United States)

    2010-01-15

    Dedicated biofuel crops, while providing economic and other benefits, may adversely impact biodiversity directly via land use conversion, or indirectly via creation of novel invasive species. To mitigate negative impacts bioclimatic envelope models (BEM) can be used to estimate the potential distribution and suitable habitat based on the climate and distribution in the native range. We used CLIMEX to evaluate the regions of North America suitable for agronomic production, as well as regions potentially susceptible to an invasion of switchgrass (Panicum virgatum) under both current and future climate scenarios. Model results show that >8.7 million km{sup 2} of North America has suitable to very favorable habitat, most of which occurs east of the Rocky Mountains. The non-native range of western North America is largely unsuitable to switchgrass as a crop or potential weed unless irrigation or permanent water is available. Under both the CGCM2 and HadCM3 climate models and A2 and B2 emissions scenarios, an overall increase in suitable habitat is predicted over the coming century, although the western US remains unsuitable. Our results suggest that much of North America is suitable for switchgrass cultivation, although this is likely to shift north in the coming century. Our results also agree with field collections of switchgrass outside its native range, which indicate that switchgrass is unlikely to establish unless it has access to water throughout the year (e.g., along a stream). Thus, it is the potential invasion of switchgrass into riparian habitats in the West that requires further investigation. (author)

  9. Systematic review of current efforts to quantify the impacts of climate change on undernutrition.

    Science.gov (United States)

    Phalkey, Revati K; Aranda-Jan, Clara; Marx, Sabrina; Höfle, Bernhard; Sauerborn, Rainer

    2015-08-18

    Malnutrition is a challenge to the health and productivity of populations and is viewed as one of the five largest adverse health impacts of climate change. Nonetheless, systematic evidence quantifying these impacts is currently limited. Our aim was to assess the scientific evidence base for the impact of climate change on childhood undernutrition (particularly stunting) in subsistence farmers in low- and middle-income countries. A systematic review was conducted to identify peer-reviewed and gray full-text documents in English with no limits for year of publication or study design. Fifteen manuscripts were reviewed. Few studies use primary data to investigate the proportion of stunting that can be attributed to climate/weather variability. Although scattered and limited, current evidence suggests a significant but variable link between weather variables, e.g., rainfall, extreme weather events (floods/droughts), seasonality, and temperature, and childhood stunting at the household level (12 of 15 studies, 80%). In addition, we note that agricultural, socioeconomic, and demographic factors at the household and individual levels also play substantial roles in mediating the nutritional impacts. Comparable interdisciplinary studies based on primary data at a household level are urgently required to guide effective adaptation, particularly for rural subsistence farmers. Systemization of data collection at the global level is indispensable and urgent. We need to assimilate data from long-term, high-quality agricultural, environmental, socioeconomic, health, and demographic surveillance systems and develop robust statistical methods to establish and validate causal links, quantify impacts, and make reliable predictions that can guide evidence-based health interventions in the future.

  10. Impact modelling of water resources development and climate scenarios on Zambezi River discharge

    Directory of Open Access Journals (Sweden)

    Harald Kling

    2014-07-01

    New hydrological insights for the region: Comparisons between historical and future scenarios show that the biggest changes have already occurred. Construction of Kariba and CahoraBassa dams in the mid 1900s altered the seasonality and flow duration curves. Future irrigation development will cause decreases of a similar magnitude to those caused by current reservoir evaporation losses. The discharge is highly sensitive to small precipitation changes and the two climate models used give different signs for future precipitation change, suggestive of large uncertainty. The river basin model and database are available as anopen-online Decision Support System to facilitate impact assessments of additional climate or development scenarios.

  11. Global Modeling and Projection of Short-Lived Climate Pollutants in an Earth System Model

    Science.gov (United States)

    Sudo, K.; Takemura, T.; Klimont, Z.; Kurokawa, J.; Akimoto, H.

    2013-12-01

    in the maximal feasible reduction (MFR) scenario, contributing to global mean temperature reduction by about -0.25 oC after 2030. This heating-SLCPs-induced warming mitigation in MFR is, however, largely cancelled out by the temperature increase due to decreases in cooling aerosols (SO42-, NO3-, and organics), resulting in temperature projection which is not quite different from the other scenarios like CLE (current legislation for air quality) or 450ppm climate stabilization (intermediate reduction) scenario. References Bond et al. (2013): Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res., 118, 5380-5552, doi:10.1002/jgrd.50171, 2013. Cofala et al. (2007): Scenarios of global anthropogenic emissions of air pollutants and methane until 2030, Atmos. Environ., 41, 8486-8499. Kerr et al. (2013): Soot is warming the world even more than thought, Science, 339, 382, doi: 10.1126/science.339.6118.382. Klimont, Z., Brink, C. (2006): Modelling of Emissions of Air Pollutants and Greenhouse Gases from Agricultural Sources in Europe. International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria. Shindell et al. (2012): Simultaneously Mitigating Near-Term Climate Change and Improving Human Health and Food Security, Science, 335, 183-189, doi: 10.1126/science.1210026.

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

    DEFF Research Database (Denmark)

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

    2007-01-01

    -90) and future (2071-2 100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves - Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first......, and the detailed patterns of these changes are sensitive to the choice of the driving global model. In the case of precipitation, variation between models can exceed both internal variability and variability between different emissions scenarios....... regions of Holland, Germany and Denmark, in particular. These results are found to depend to different degrees on model formulation. While the responses of heat waves are robust to model formulation, the magnitudes of changes in precipitation and wind speed are sensitive to the choice of regional model...

  13. Spatial-temporal assessment of climate model drifts

    Science.gov (United States)

    Zanchettin, Davide; Woldeyes Arisido, Maeregu; Gaetan, Carlo; Rubino, Angelo

    2016-04-01

    Decadal climate forecasts with full-field initialized coupled climate models are affected by a growing error signal that develops due to the adjustment of the simulations from the assimilated state consistent with observations to the state consistent with the biased model's climatology. Sea-surface temperature (SST) drifts and biases are a major concern due to the central role of SST properties for the dynamical coupling between the atmosphere and the ocean, and for the associated variability. Therefore, strong SST drifts complicate the initialization and assessment of decadal climate prediction experiments, and can be detrimental for their overall quality. We propose a dynamic linear model based on a state-space approach and developed within a Bayesian hierarchical framework for probabilistic assessment of spatial and temporal characteristics of SST drifts in ensemble climate simulations. The state-space approach uses unobservable state variables to directly model the processes generating the observed variability. The statistical model is based on a sequential definition of the process having a conditional dependency only on the previous time step, which therefore corresponds to the Kalman filter formulas. In our formulation, the statistical model distinguishes between seasonal and longer-term drift components, and between large-scale and local drifts. We apply the Bayesian method to make inferences on the variance components of the Gaussian errors in both the observation and system equations of the state-space model. To this purpose, we draw samples from their posterior distributions using a Monte Carlo Markov Chain simulation technique with a Gibbs sampler. In this contribution we illustrate a first application of the model using the MiKlip prototype system for decadal climate predictions. We focus on the tropical Atlantic Ocean - a region where climate models are typically affected by a severe warm SST bias - to demonstrate how our approach allows for a more

  14. Model biases in rice phenology under warmer climates.

    Science.gov (United States)

    Zhang, Tianyi; Li, Tao; Yang, Xiaoguang; Simelton, Elisabeth

    2016-06-07

    Climate-induced crop yields model projections are constrained by the accuracy of the phenology simulation in crop models. Here, we use phenology observations from 775 trials with 19 rice cultivars in 5 Asian countries to compare the performance of four rice phenology models (growing-degree-day (GDD), exponential, beta and bilinear models) when applied to warmer climates. For a given cultivar, the difference in growing season temperature (GST) varied between 2.2 and 8.2 °C in different trials, which allowed us to calibrate the models for lower GST and validate under higher GST, with three calibration experiments. The results show that in warmer climates the bilinear and beta phenology models resulted in gradually increasing bias for phenology predication and double yield bias per percent increase in phenology simulation bias, while the GDD and exponential models maintained a comparatively constant bias. The phenology biases were primarily attributed to varying phenological patterns to temperature in models, rather than on the size of the calibration dataset. Additionally, results suggest that model simulations based on multiple cultivars provide better predictability than using one cultivar. Therefore, to accurately capture climate change impacts on rice phenology, we recommend simulations based on multiple cultivars using the GDD and exponential phenology models.

  15. Model biases in rice phenology under warmer climates

    Science.gov (United States)

    Zhang, Tianyi; Li, Tao; Yang, Xiaoguang; Simelton, Elisabeth

    2016-06-01

    Climate-induced crop yields model projections are constrained by the accuracy of the phenology simulation in crop models. Here, we use phenology observations from 775 trials with 19 rice cultivars in 5 Asian countries to compare the performance of four rice phenology models (growing-degree-day (GDD), exponential, beta and bilinear models) when applied to warmer climates. For a given cultivar, the difference in growing season temperature (GST) varied between 2.2 and 8.2 °C in different trials, which allowed us to calibrate the models for lower GST and validate under higher GST, with three calibration experiments. The results show that in warmer climates the bilinear and beta phenology models resulted in gradually increasing bias for phenology predication and double yield bias per percent increase in phenology simulation bias, while the GDD and exponential models maintained a comparatively constant bias. The phenology biases were primarily attributed to varying phenological patterns to temperature in models, rather than on the size of the calibration dataset. Additionally, results suggest that model simulations based on multiple cultivars provide better predictability than using one cultivar. Therefore, to accurately capture climate change impacts on rice phenology, we recommend simulations based on multiple cultivars using the GDD and exponential phenology models.

  16. Large-Scale Features of Pliocene Climate: Results from the Pliocene Model Intercomparison Project

    Science.gov (United States)

    Haywood, A.