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Sample records for models current climate

  1. Current climate and climate change over India as simulated by the Canadian Regional Climate Model

    Science.gov (United States)

    Alexandru, Adelina; Sushama, Laxmi

    2015-08-01

    The performance of the fifth generation of the Canadian Regional Climate Model (CRCM5) in reproducing the main climatic characteristics over India during the southwest (SW)-, post- and pre-monsoon seasons are presented in this article. To assess the performance of CRCM5, European Centre for Medium- Range Weather Forecasts (ECMWF) Re- Analysis (ERA- 40) and Interim re-analysis (ERA-Interim) driven CRCM5 simulation is compared against independent observations and reanalysis data for the 1971-2000 period. Projected changes for two future periods, 2041-2070 and 2071-2100, with respect to the 1971-2000 current period are assessed based on two transient climate change simulations of CRCM5 spanning the 1950-2100 period. These two simulations are driven by the Canadian Earth System Model version 2 (CanESM2) and the Max Planck Institute for Meteorology's Earth System Low Resolution Model (MPI-ESM-LR), respectively. The boundary forcing errors associated with errors in the driving global climate models are also studied by comparing the 1971-2000 period of the CanESM2 and MPI-ESM-LR driven simulations with that of the CRCM5 simulation driven by ERA-40/ERA-Interim. Results show that CRCM5 driven by ERA-40/ERA-Interim is in general able to capture well the temporal and spatial patterns of 2 m-temperature, precipitation, wind, sea level pressure, total runoff and soil moisture over India in comparison with available reanalysis and observations. However, some noticeable differences between the model and observational data were found during the SW-monsoon season within the domain of integration. CRCM5 driven by ERA-40/ERA-Interim is 1-2 °C colder than CRU observations and generates more precipitation over the Western Ghats and central regions of India, and not enough in the northern and north-eastern parts of India and along the Konkan west coast in comparison with the observed precipitation. The monsoon onset seems to be relatively well captured over the southwestern coast of

  2. Drought Duration Biases in Current Global Climate Models

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    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.

  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. Pest occurrence model in current climate – validation study for European domain

    Directory of Open Access Journals (Sweden)

    Eva Svobodová

    2013-01-01

    Full Text Available The present study yields detail validation of the pest occurrence models under current climate in wide European domain. Study organisms involve Cydia pomonella, Lobesia botrana, Ostrinia nubilalis, Leptinotarsa decemlineata, Oulema melanopus, Rhopalosiphum padi, and Sitobion avenae. Method used in this study belongs to the category climate matching (CLIMEX model allowing the estimation of areas climatically favourable for species persistence based on the climatic parameters characterising the species development. In the process of model validation parameters were iteratively tested and altered to truly describe the pest presence. The modelled pests presence was verified by comparison of the observed pests occurrence with the number of generations in given modelled area. The notable component of the model parameterization was the sensitivity analyses testing the reaction of species development on changing meteorological items. Parameterization of the factors causing distribution patterns of study species was successful and modelled potential distributions of species correspond well to known core distribution areas for all of these species. This validation study is intended as an initial for forthcoming studies focused on the estimation of geographical shifts of selected pests in the conditions of climate change within the Europe.

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

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    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

  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. 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.

  10. 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

  11. Water deficit effects on maize yields modeled under current and greenhouse climates

    International Nuclear Information System (INIS)

    Muchow, R.C.; Sinclair, T.R.

    1991-01-01

    The availability of water imposes one of the major limits on rainfed maize (Zea mays L.) productivity. This analysis was undertaken in an attempt to quantify the effects of limited water on maize growth and yield by extending a simple, mechanistic model in which temperature regulates crop development and intercepted solar radiation is used to calculate crop biomass accumulation. A soil water budget was incorporated into the model by accounting for inputs from rainfall and irrigation, and water use by soil evaporation and crop transpiration. The response functions of leaf area development and crop gas exchange to the soil water budget were developed from experimental studies. The model was used to interpret a range of field experiments using observed daily values of temperature, solar radiation, and rainfall or irrigation, where water deficits of varying durations developed at different stages of growth. The relative simplicity of the model and its robustness in simulating maize yields under a range of water-availability conditions allows the model to be readily used for studies of crop performance under alternate conditions. One such study, presented here, was a yield assessment for rainfed maize under possible greenhouse climates where temperature and atmospheric CO 2 concentration were increased. An increase in temperature combined with decreased rainfall lowered grain yield, although the increase in crop water use efficiency associated with elevated CO 2 concentration ameliorated the response to the greenhouse climate. Grain yields for the greenhouse climates as compared to current conditions increased, or decreased only slightly, except when the greenhouse climate was assumed to result in severly decreased rainfall

  12. ENSO dynamics in current climate models: an investigation using nonlinear dimensionality reduction

    Directory of Open Access Journals (Sweden)

    I. Ross

    2008-04-01

    Full Text Available Linear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality. These linear methods may not be appropriate for the analysis of data arising from nonlinear processes occurring in the climate system. Numerous techniques for nonlinear dimensionality reduction have been developed recently that may provide a potentially useful tool for the identification of low-dimensional manifolds in climate data sets arising from nonlinear dynamics. Here, we apply Isomap, one such technique, to the study of El Niño/Southern Oscillation variability in tropical Pacific sea surface temperatures, comparing observational data with simulations from a number of current coupled atmosphere-ocean general circulation models. We use Isomap to examine El Niño variability in the different datasets and assess the suitability of the Isomap approach for climate data analysis. We conclude that, for the application presented here, analysis using Isomap does not provide additional information beyond that already provided by principal component analysis.

  13. ENSO dynamics in current climate models: an investigation using nonlinear dimensionality reduction

    Science.gov (United States)

    Ross, I.; Valdes, P. J.; Wiggins, S.

    2008-04-01

    Linear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality. These linear methods may not be appropriate for the analysis of data arising from nonlinear processes occurring in the climate system. Numerous techniques for nonlinear dimensionality reduction have been developed recently that may provide a potentially useful tool for the identification of low-dimensional manifolds in climate data sets arising from nonlinear dynamics. Here, we apply Isomap, one such technique, to the study of El Niño/Southern Oscillation variability in tropical Pacific sea surface temperatures, comparing observational data with simulations from a number of current coupled atmosphere-ocean general circulation models. We use Isomap to examine El Niño variability in the different datasets and assess the suitability of the Isomap approach for climate data analysis. We conclude that, for the application presented here, analysis using Isomap does not provide additional information beyond that already provided by principal component analysis.

  14. 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.

  15. 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.

  16. Modeling the yield potential of dryland canola under current and future climates in California

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    George, N.; Kaffka, S.; Beeck, C.; Bucaram, S.; Zhang, J.

    2012-12-01

    -adapted canola varieties can be justified, and the potential value of a California canola industry both now and in the future. Winter annual crops like canola use rainfall in a Mediterranean climate like California more efficiently than spring or summer crops. Our results suggest that under current production costs and seed prices, dry farmed canola will have good potential in certain areas of the California. Canola yields decline with annual winter precipitation, however economically viable yields are still achieved at relatively precipitation levels (200 mm). Results from simulation, combined with related economic modeling (reported elsewhere) suggest that canola will be viable in a variety of production systems in the northern Sacramento Valley and some coastal locations, even under drier future climate scenarios. The in-field evaluation of Australian canola varieties should contribute to maintain or improving resource use efficiency and farm profitability.

  17. 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.

  18. 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.

  19. 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)

  20. Surface energy balances of three general circulation models: Current climate and response to increasing atmospheric CO2

    International Nuclear Information System (INIS)

    Gutowski, W.J.; Gutzler, D.S.; Portman, D.; Wang, W.C.

    1988-04-01

    The surface energy balance simulated by state-of-the-art general circulation models at GFDL, GISS and NCAR for climates with current levels of atmospheric CO 2 concentration (control climate) and with twice the current levels. The work is part of an effort sponsored by the US Department of Energy to assess climate simulations produced by these models. The surface energy balance enables us to diagnose differences between models in surface temperature climatology and sensitivity to doubling CO 2 in terms of the processes that control surface temperature. Our analysis compares the simulated balances by averaging the fields of interest over a hierarchy of spatial domains ranging from the entire globe down to regions a few hundred kilometers across

  1. 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

  2. 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.

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

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    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

  4. 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 African Low-level Jet (EALLJ) and the Tropical Easterly Jet (TEJ). The high-resolution models project a strengthening of the EALLJ, but a weakening of the TEJ. Future changes in the EALLJ and TEJ will drive this precipitation system in opposite directions, leading to small or no net changes in precipitation in Ethiopia.

  5. Modeling and mapping the current and future distribution of Pseudomonas syringae pv. actinidiae under climate change in China.

    Science.gov (United States)

    Wang, Rulin; Li, Qing; He, Shisong; Liu, Yuan; Wang, Mingtian; Jiang, Gan

    2018-01-01

    Bacterial canker of kiwifruit caused by Pseudomonas syringae pv. actinidiae (Psa) is a major threat to the kiwifruit industry throughout the world and accounts for substantial economic losses in China. The aim of the present study was to test and explore the possibility of using MaxEnt (maximum entropy models) to predict and analyze the future large-scale distribution of Psa in China. Based on the current environmental factors, three future climate scenarios, which were suggested by the fifth IPCC report, and the current distribution sites of Psa, MaxEnt combined with ArcGIS was applied to predict the potential suitable areas and the changing trend of Psa in China. The jackknife test and correlation analysis were used to choose dominant climatic factors. The receiver operating characteristic curve (ROC) drawn by MaxEnt was used to evaluate the accuracy of the simulation. The results showed that under current climatic conditions, the area from latitude 25° to 36°N and from longitude 101° to 122°E is the primary potential suitable area of Psa in China. The highly suitable area (with suitability between 66 and 100) was mainly concentrated in Northeast Sichuan, South Shaanxi, most of Chongqing, West Hubei and Southwest Gansu and occupied 4.94% of land in China. Under different future emission scenarios, both the areas and the centers of the suitable areas all showed differences compared with the current situation. Four climatic variables, i.e., maximum April temperature (19%), mean temperature of the coldest quarter (14%), precipitation in May (11.5%) and minimum temperature in October (10.8%), had the largest impact on the distribution of Psa. The MaxEnt model is potentially useful for forecasting the future adaptive distribution of Psa under climate change, and it provides important guidance for comprehensive management.

  6. Current state of aerosol nucleation parameterizations for air-quality and climate modeling

    Science.gov (United States)

    Semeniuk, Kirill; Dastoor, Ashu

    2018-04-01

    Aerosol nucleation parameterization models commonly used in 3-D air quality and climate models have serious limitations. This includes classical nucleation theory based variants, empirical models and other formulations. Recent work based on detailed and extensive laboratory measurements and improved quantum chemistry computation has substantially advanced the state of nucleation parameterizations. In terms of inorganic nucleation involving BHN and THN including ion effects these new models should be considered as worthwhile replacements for the old models. However, the contribution of organic species to nucleation remains poorly quantified. New particle formation consists of a distinct post-nucleation growth regime which is characterized by a strong Kelvin curvature effect and is thus dependent on availability of very low volatility organic species or sulfuric acid. There have been advances in the understanding of the multiphase chemistry of biogenic and anthropogenic organic compounds which facilitate to overcome the initial aerosol growth barrier. Implementation of processes influencing new particle formation is challenging in 3-D models and there is a lack of comprehensive parameterizations. This review considers the existing models and recent innovations.

  7. Current and future groundwater recharge in West Africa as estimated from a range of coupled climate model outputs

    Science.gov (United States)

    Verhoef, Anne; Cook, Peter; Black, Emily; Macdonald, David; Sorensen, James

    2017-04-01

    This research addresses the terrestrial water balance for West Africa. Emphasis is on the prediction of groundwater recharge and how this may change in the future, which has relevance to the management of surface and groundwater resources. The study was conducted as part of the BRAVE research project, "Building understanding of climate variability into planning of groundwater supplies from low storage aquifers in Africa - Second Phase", funded under the NERC/DFID/ESRC Programme, Unlocking the Potential of Groundwater for the Poor (UPGro). We used model output data of water balance components (precipitation, surface and subsurface run-off, evapotranspiration and soil moisture content) from ERA-Interim/ERA-LAND reanalysis, CMIP5, and high resolution model runs with HadGEM3 (UPSCALE; Mizielinski et al., 2014), for current and future time-periods. Water balance components varied widely between the different models; variation was particularly large for sub-surface runoff (defined as drainage from the bottom-most soil layer of each model). In-situ data for groundwater recharge obtained from the peer-reviewed literature were compared with the model outputs. Separate off-line model sensitivity studies with key land surface models were performed to gain understanding of the reasons behind the model differences. These analyses were centered on vegetation, and soil hydraulic parameters. The modelled current and future recharge time series that had the greatest degree of confidence were used to examine the spatiotemporal variability in groundwater storage. Finally, the implications for water supply planning were assessed. Mizielinski, M.S. et al., 2014. High-resolution global climate modelling: the UPSCALE project, a large-simulation campaign. Geoscientific Model Development, 7(4), pp.1629-1640.

  8. 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

  9. Prototyping global Earth System Models at high resolution: Representation of climate, ecosystems, and acidification in Eastern Boundary Currents

    Science.gov (United States)

    Dunne, J. P.; John, J. G.; Stock, C. A.

    2013-12-01

    The world's major Eastern Boundary Currents (EBC) such as the California Current Large Marine Ecosystem (CCLME) are critically important areas for global fisheries. Computational limitations have divided past EBC modeling into two types: high resolution regional approaches that resolve the strong meso-scale structures involved, and coarse global approaches that represent the large scale context for EBCs, but only crudely resolve only the largest scales of their manifestation. These latter global studies have illustrated the complex mechanisms involved in the climate change and acidification response in these regions, with the CCLME response dominated not by local adjustments but large scale reorganization of ocean circulation through remote forcing of water-mass supply pathways. While qualitatively illustrating the limitations of regional high resolution studies in long term projection, these studies lack the ability to robustly quantify change because of the inability of these models to represent the baseline meso-scale structures of EBCs. In the present work, we compare current generation coarse resolution (one degree) and a prototype next generation high resolution (1/10 degree) Earth System Models (ESMs) from NOAA's Geophysical Fluid Dynamics Laboratory in representing the four major EBCs. We review the long-known temperature biases that the coarse models suffer in being unable to represent the timing and intensity of upwelling-favorable winds, along with lack of representation of the observed high chlorophyll and biological productivity resulting from this upwelling. In promising contrast, we show that the high resolution prototype is capable of representing not only the overall meso-scale structure in physical and biogeochemical fields, but also the appropriate offshore extent of temperature anomalies and other EBC characteristics. Results for chlorophyll were mixed; while high resolution chlorophyll in EBCs were strongly enhanced over the coarse resolution

  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. Modeling fire-driven deforestation potential in Amazonia under current and projected climate conditions

    NARCIS (Netherlands)

    Le Page, Y.; van der Werf, G.R.; Morton, D.C.; Pereira, J.M.C.

    2010-01-01

    Fire is a widely used tool to prepare deforested areas for agricultural use in Amazonia. Deforestation is currently concentrated in seasonal forest types along the arc of deforestation, where dry-season conditions facilitate burning of clear-felled vegetation. Interior Amazon forests, however, are

  12. Modeling glacial climates

    Science.gov (United States)

    North, G. R.; Crowley, T. J.

    1984-01-01

    Mathematical climate modelling has matured as a discipline to the point that it is useful in paleoclimatology. As an example a new two dimensional energy balance model is described and applied to several problems of current interest. The model includes the seasonal cycle and the detailed land-sea geographical distribution. By examining the changes in the seasonal cycle when external perturbations are forced upon the climate system it is possible to construct hypotheses about the origin of midlatitude ice sheets and polar ice caps. In particular the model predicts a rather sudden potential for glaciation over large areas when the Earth's orbital elements are only slightly altered. Similarly, the drift of continents or the change of atmospheric carbon dioxide over geological time induces radical changes in continental ice cover. With the advance of computer technology and improved understanding of the individual components of the climate system, these ideas will be tested in far more realistic models in the near future.

  13. 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.

  14. Energy balance climate models

    Science.gov (United States)

    North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

    1981-01-01

    An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved, and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

  15. 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

  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. 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

  18. Analysis of Current and Future SPEI Droughts in the La Plata Basin Based on Results from the Regional Eta Climate Model

    Directory of Open Access Journals (Sweden)

    Alvaro Sordo-Ward

    2017-11-01

    Full Text Available We identified and analysed droughts in the La Plata Basin (divided into seven sub-basins for the current period (1961–2005 and estimated their expected evolution under future climate projections for the periods 2011–2040, 2041–2070, and 2071–2099. Future climate projections were analysed from results of the Eta Regional Climate Model (grid resolution of approximately 10 km forced by the global climate model HadGEM2-ES over the La Plata basin, and considering a RCP4.5 emission scenario. Within each sub-basin, we particularly focused our drought analyses on croplands and grasslands, due to their economic relevance. The three-month Standardized Precipitation Evapotranspiration Index (SPEI3 was used for drought identification and characterization. Droughts were evaluated in terms of time (percentage of time from the total length of each climate scenario, space (percentage of total area, and severity (SPEI3 values of cells characterized by cropland and grassland for each sub-basin and climate scenario. Drought-severity–area–frequency curves were developed to quantitatively relate the frequency distribution of drought occurrence to drought severity and area. For the period 2011–2040, droughts dominate the northern sub-basins, whereas alternating wet and short dry periods dominate the southern sub-basins. Wet climate spread from south to north within the La Plata Basin as more distant future scenarios were analysed, due to both a greater number of wet periods and fewer droughts. The area of each sub-basin affected by drought in all climate scenarios was highly varied temporally and spatially. The likelihood of the occurrence of droughts differed significantly between the studied cover types in the Lower Paraguay sub-basin, being higher for cropland than for grassland. Mainly in the Upper Paraguay and in the Upper Paraná basins the climate projections for all scenarios showed an increase of moderate and severe droughts over large regions

  19. Future local climate unlike currently observed anywhere

    Science.gov (United States)

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

    2017-08-01

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

  20. Electric climate-model

    Science.gov (United States)

    Koertvelyessy, L.

    Does the Sun heat variably by its varying magnetic fields? The main problem of all magnetic models is that SOHO found neither a "solar dynamo" nor "deep magnetic tubes". Also TRACE discovered too thin and straight filaments which could not have emerged through the boiling solar layers but grew out geyser-like from one foot-point. NASA stated some months ago that a "magnetic tube" would be unstable due to its own magnetic repulsion. A new, an electric climate-model is described based on the solar thermoelectric processes. TRACE- and LASCO-pictures show that solar filaments have an exact circular cross section i.e. they are electric direct currents shaped by the pinch-effect. Our climate is maximally correlated to the aa index of the magnetic storms which are the results of solar direct currents conducting by Earth. The burning out of the transformers of Hydro-Quebec (in 1989) is re-analysed on the base of these positive direct currents. The results are that the positive (active) Sun repulses the positive cosmic ray particles which are seeds of clouds. In addition, new movies show that this active Sun directly charges our clouds positively via red sprites during a proton storm. The hit clouds emit gamma rays and are perhaps diffused by this solar positive charge. Both effects could be responsible for the fact that the area of the clouds was found to be by 2-4.5 % lower in the middle magnetic latitudes during the last solar maximum. Parallel to both electric influences, the sunspots were re- discovered as "awesome solar hurricanes". ACRIM showed that their huge rotational energy can increase the solar irradiation . The present 88 year period will end in about 2045 probably with the highest irradiation of the last two millennia.

  1. Climate Analogues Suggest Limited Potential for Intensification of Production on Current Croplands Under Climate Change

    Science.gov (United States)

    Pugh, T. A. M.; Mueller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

    2016-01-01

    Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

  2. 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...... 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...... 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...

  3. 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

    2017-06-01

    Accurate projection of carbon budget in forest ecosystems under future climate and atmospheric carbon dioxide (CO 2 ) concentration is important to evaluate the function of terrestrial ecosystems, which serve as a major sink of atmospheric CO 2 . 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 CO 2 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.

  4. The Finer Details: Climate Modeling

    Science.gov (United States)

    2000-01-01

    If you want to know whether you will need sunscreen or an umbrella for tomorrow's picnic, you can simply read the local weather report. However, if you are calculating the impact of gas combustion on global temperatures, or anticipating next year's rainfall levels to set water conservation policy, you must conduct a more comprehensive investigation. Such complex matters require long-range modeling techniques that predict broad trends in climate development rather than day-to-day details. Climate models are built from equations that calculate the progression of weather-related conditions over time. Based on the laws of physics, climate model equations have been developed to predict a number of environmental factors, for example: 1. Amount of solar radiation that hits the Earth. 2. Varying proportions of gases that make up the air. 3. Temperature at the Earth's surface. 4. Circulation of ocean and wind currents. 5. Development of cloud cover. Numerical modeling of the climate can improve our understanding of both the past and, the future. A model can confirm the accuracy of environmental measurements taken. in, the past and can even fill in gaps in those records. In addition, by quantifying the relationship between different aspects of climate, scientists can estimate how a future change in one aspect may alter the rest of the world. For example, could an increase in the temperature of the Pacific Ocean somehow set off a drought on the other side of the world? A computer simulation could lead to an answer for this and other questions. Quantifying the chaotic, nonlinear activities that shape our climate is no easy matter. You cannot run these simulations on your desktop computer and expect results by the time you have finished checking your morning e-mail. Efficient and accurate climate modeling requires powerful computers that can process billions of mathematical calculations in a single second. The NCCS exists to provide this degree of vast computing capability.

  5. Energy-balance climate models

    Science.gov (United States)

    North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

    1980-01-01

    An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

  6. 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.

  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 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

  9. Response of O2 and pH to ENSO in the California Current System in a high-resolution global climate model

    Science.gov (United States)

    Turi, Giuliana; Alexander, Michael; Lovenduski, Nicole S.; Capotondi, Antonietta; Scott, James; Stock, Charles; Dunne, John; John, Jasmin; Jacox, Michael

    2018-02-01

    Coastal upwelling systems, such as the California Current System (CalCS), naturally experience a wide range of O2 concentrations and pH values due to the seasonality of upwelling. Nonetheless, changes in the El Niño-Southern Oscillation (ENSO) have been shown to measurably affect the biogeochemical and physical properties of coastal upwelling regions. In this study, we use a novel, high-resolution global climate model (GFDL-ESM2.6) to investigate the influence of warm and cold ENSO events on variations in the O2 concentration and the pH of the CalCS coastal waters. An assessment of the CalCS response to six El Niño and seven La Niña events in ESM2.6 reveals significant variations in the response between events. However, these variations overlay a consistent physical and biogeochemical (O2 and pH) response in the composite mean. Focusing on the mean response, our results demonstrate that O2 and pH are affected rather differently in the euphotic zone above ˜ 100 m. The strongest O2 response reaches up to several hundreds of kilometers offshore, whereas the pH signal occurs only within a ˜ 100 km wide band along the coast. By splitting the changes in O2 and pH into individual physical and biogeochemical components that are affected by ENSO variability, we found that O2 variability in the surface ocean is primarily driven by changes in surface temperature that affect the O2 solubility. In contrast, surface pH changes are predominantly driven by changes in dissolved inorganic carbon (DIC), which in turn is affected by upwelling, explaining the confined nature of the pH signal close to the coast. Below ˜ 100 m, we find conditions with anomalously low O2 and pH, and by extension also anomalously low aragonite saturation, during La Niña. This result is consistent with findings from previous studies and highlights the stress that the CalCS ecosystem could periodically undergo in addition to impacts due to climate change.

  10. Is the future blue-green? A review of the current model predictions of how climate change could affect pelagic freshwater cyanobacteria.

    Science.gov (United States)

    Elliott, J Alex

    2012-04-01

    There is increasing evidence that recent changes in climate have had an effect on lake phytoplankton communities and it has been suggested that it is likely that Cyanobacteria will increase in relative abundance under the predicted future climate. However, testing such a qualitative prediction is challenging and usually requires some form of numerical computer model. Therefore, the lake modelling literature was reviewed for studies that examined the impact of climate change upon Cyanobacteria. These studies, taken collectively, generally show an increase in relative Cyanobacteria abundance with increasing water temperature, decreased flushing rate and increased nutrient loads. Furthermore, they suggest that whilst the direct effects of climate change on the lakes can change the timing of bloom events and Cyanobacteria abundance, the amount of phytoplankton biomass produced over a year is not enhanced directly by these changes. Also, warmer waters in the spring increased nutrient consumption by the phytoplankton community which in some lakes caused nitrogen limitation later in the year to the advantage of some nitrogen-fixing Cyanobacteria. Finally, it is also possible that an increase in Cyanobacteria dominance of the phytoplankton biomass will lead to poorer energy flow to higher trophic levels due to their relatively poor edibility for zooplankton. Copyright © 2011 Elsevier Ltd. All rights reserved.

  11. 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.

  12. Model Democracy: Are All Climate Models Equally Good?

    Science.gov (United States)

    Shukla, J.

    2008-05-01

    We compare the ability of IPCC climate models to simulate present climate and their sensitivity to increased greenhouse gases. We find that models with higher fidelity in simulating the present climate produce higher values of global warming due to increased greenhouse gases. We also compare the forecast skill of dynamical seasonal prediction by coupled ocean-atmosphere models and their ability to simulate observed climate. Although all the current generation of coupled models have large error in simulating observed climate, yet the models with higher fidelity have higher skill. We conclude that there is a significant relationship between model fidelity and model sensitivity, and therefore, the IPCC assessments should not accept the concept of model democracy. We further conjecture that inaccuracy of climate models is the most dominant obstacle in both realizing the potential predictability of climate variations, and in providing reliable information on regional climate change. We make some proposals for the future pathways to improve the fidelity of climate models, and to harvest the realizable predictability.

  13. Improved regional climate modelling through dynamical downscaling

    International Nuclear Information System (INIS)

    Corney, Stuart; Grose, Michael; Holz, Greg; White, Chris; Bennett, James; Gaynor, Suzie; Bindoff, Nathan; Katzfey, Jack; McGregor, John

    2010-01-01

    Coupled Ocean-Atmosphere General Circulation Models (GCMs) provide the best estimates for assessing potential changes to our climate on a global scale out to the end of this century. Because coupled GCMs have a fairly coarse resolution they do not provide a detailed picture of climate (and climate change) at the local scale. Tasmania, due to its diverse geography and range of climate over a small area is a particularly difficult region for drawing conclusions regarding climate change when relying solely on GCMs. The foundation of the Climate Futures for Tasmania project is to take the output produced by multiple GCMs, using multiple climate change scenarios, and use this output as input into the Conformal Cubic Atmospheric Model (CCAM) to downscale the GCM output. CCAM is a full atmospheric global general circulation model, formulated using a conformal-cubic grid that covers the globe but can be stretched to provide higher resolution in the area of interest (Tasmania). By modelling the atmosphere at a much finer scale than is possible using a coupled GCM we can more accurately capture the processes that drive Tasmania's weather/climate, and thus can more clearly answer the question of how Tasmania's climate will change in the future. We present results that show the improvements in capturing the local-scale climate and climate drivers that can be achieved through downscaling, when compared to a gridded observational data set. The underlying assumption of this work is that a better simulated current climatology will also produce a more credible climate change signal.

  14. Land use change affecting our (modelled) climate

    Science.gov (United States)

    Weiß, M.; van den Hurk, B.

    2012-04-01

    Up until now, climate models often have used a static representation of land cover characteristics and only recently, the impact of a changing land surface on climate and climate simulations has attracted more attention. With climate scenarios to the fifth Assessment Report currently in preparation, this time considering different representative concentration pathways and associated land cover scenarios, we are still building up process-knowledge on the strength of land-atmosphere coupling. This study contributes to our understanding of the impact of land cover changes on the atmosphere by running global simulations with the EC-Earth climate model, using different historical land use data as well as two land use scenarios to analyse the following aspects in more detail: On the one hand the impact of land cover change via modified albedo, and on the other hand its impact via modified surface resistance, rooting depth and soil-moisture capacity on available energy, evapotranspiration, wind and temperature.

  15. 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

  16. 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

  17. 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.

  18. Climate Model Diagnostic Analyzer

    Data.gov (United States)

    National Aeronautics and Space Administration — Both the National Research Council (NRC) Decadal Survey and the latest Intergovernmental Panel on Climate Change (IPCC) Assessment Report stressed the need for the...

  19. 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.

  20. Large-Scale Control of the Probability Distribution Function of Precipitation over the Continental US in Observations and Models, in the Current and Future Climat

    Science.gov (United States)

    Straus, D. M.

    2016-12-01

    The goals of this research are to: (a) identify features of the probability distribution function (pdf) of pentad precipitation over the continental US (CONUS) that are controlled by the configuration of the large-scale fields, including both tails of the pdf, hence droughts and floods, and the overall shape of the pdf, e.g. skewness and kurtosis; (b) estimate the changes in the properties of the pdf controlled by the large-scale in a future climate. We first describe the significant dependence of the observed precipitation pdf conditioned on circulation regimes over CONUS. The regime states, and the number of regimes, are obtained by a method that assures a high degree of significance, and a high degree of pattern correlation between the states in a regime and its average. The regime-conditioned pdfs yield information on times scales from intra-seasonal to inter-annual. We then apply this method to atmospheric simulations run with the EC-Earth version 3 model for historical sea-surface temperatures (SST) and future (RCP8.5 CMIP5 scenario) estimates of SST, at resolutions T255 and T799, to understand what dynamically controlled changes in the precipitation pdf can be expected in a future climate.

  1. Which climatic modeling to assess climate change impacts on vineyards?

    OpenAIRE

    Quenol, Herve; Garcia De Cortazar Atauri, Inaki; Bois, Benjamin; Sturman, Andrew; Bonnardot, Valerie; Le Roux, Renan

    2017-01-01

    The impact of climatic change on viticulture is significant: main phenological stages appear earlier, wine characteristics are changing, ... This clearly illustrates the point that the adaptation of viticulture to climate change is crucial and should be based on simulations of future climate. Several types of models exist and are used to represent viticultural climates at various scales. In this paper, we propose a review of different types of climate models (methodology and uncertainties) an...

  2. The current macroeconomic climate in Denmark

    DEFF Research Database (Denmark)

    Gjerding, Allan Næs

    2005-01-01

    high-income economies the business cycles of which are not synchronised. At the same time, the Danish economy is characterised by a highly dynamic and flexible labour market sustaining the Danish economic position. However, the current growth of the Danish economy is driven by private consumption which...

  3. 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...

  4. 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.

  5. Model confirmation in climate economics.

    Science.gov (United States)

    Millner, Antony; McDermott, Thomas K J

    2016-08-02

    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.

  6. Mathematical Modelling of Turbidity Currents

    Science.gov (United States)

    Fay, G. L.; Fowler, A.; Howell, P.

    2011-12-01

    A turbidity current is a submarine sediment flow which propagates downslope through the ocean into the deep sea. Turbidity currents can occur randomly and without much warning and consequently are hard to observe and measure. The driving force in a turbidity current is the presence of sediment in the current - gravity acts on the sediment in suspension, causing it to move downstream through the ocean water. A phenomenon known as ignition or autosuspension has been observed in turbidity currents in submarine canyons, and it occurs when a current travelling downslope gathers speed as it erodes sediment from the sea floor in a self-reinforcing cycle. Using the turbidity current model of Parker et al. (Journal of Fluid Mechanics, 1986) we investigate the evolution of a 1-D turbidity current as it moves downstream. To seek a better understanding of the dynamics of flow as the current evolves in space and time, we present analytical results alongside computed numerical solutions, incorporating entrainment of water and erosion and deposition of sediment. We consider varying slope functions and inlet conditions and attempt to predict when the current will become extinct. We examine currents which are in both supercritical and subcritical flow regimes and consider the dynamics of the flow as the current switches regime.

  7. Predicting Future Seed Sourcing of Platycladus orientalis (L. for Future Climates Using Climate Niche Models

    Directory of Open Access Journals (Sweden)

    Xian-Ge Hu

    2017-12-01

    Full Text Available Climate niche modeling has been widely used to assess the impact of climate change on forest trees at the species level. However, geographically divergent tree populations are expected to respond differently to climate change. Considering intraspecific local adaptation in modeling species responses to climate change will thus improve the credibility and usefulness of climate niche models, particularly for genetic resources management. In this study, we used five Platycladus orientalis (L. seed zones (Northwestern; Northern; Central; Southern; and Subtropical covering the entire species range in China. A climate niche model was developed and used to project the suitable climatic conditions for each of the five seed zones for current and various future climate scenarios (Representative Concentration Pathways: RCP2.6, RCP4.5, RCP6.0, and RCP8.5. Our results indicated that the Subtropical seed zone would show consistent reduction for all climate change scenarios. The remaining seed zones, however, would experience various degrees of expansion in suitable habitat relative to their current geographic distributions. Most of the seed zones would gain suitable habitats at their northern distribution margins and higher latitudes. Thus, we recommend adjusting the current forest management strategies to mitigate the negative impacts of climate change.

  8. Climate change impacts in Iran: assessing our current knowledge

    Science.gov (United States)

    Rahimi, Jaber; Malekian, Arash; Khalili, Ali

    2018-02-01

    During recent years, various studies have focused on investigating the direct and indirect impacts of climate changes in Iran while the noteworthy fact is the achievement gained by these researches. Furthermore, what should be taken into consideration is whether these studies have been able to provide appropriate opportunities for improving further studies in this particular field or not. To address these questions, this study systematically reviewed and summarized the current available literature (n = 150) regarding the impacts of climate change on temperature and precipitation in Iran to assess our current state of knowledge. The results revealed that while all studies discuss the probable changes in temperature and precipitation over the next decades, serious contradictions could be seen in their results; also, the general pattern of changes was different in most of the cases. This matter may have a significant effect on public beliefs in climate change, which can be a serious warning for the activists in this realm.

  9. Western European cold spells in current and future climate

    NARCIS (Netherlands)

    Vries, de H.; Haarsma, R.; Hazeleger, W.

    2012-01-01

    This paper discusses western European cold spells (where temperature falls below the 10\\\\% quantile of the winter temperature distribution) in current and future climate. It is demonstrated that many of the projected future changes in cold-spell statistics (duration, return period, intensity) can be

  10. DBP formation and disinfection under current and future climates - slides

    Science.gov (United States)

    How to predict and monitoring DBP formation under current and future climate is a challenge and important to water plant operations and water supply security. This presentation summarizes a system approach being developed at the EPA Water Resources Adaptation Program (WRAP).

  11. Intervention model in organizational climate

    OpenAIRE

    Cárdenas Niño, Lucila; Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias de la Salud, Escuela de Psicología, Hospital Antiguo, Carrera 10 No 16ª05; Arciniegas Rodríguez, Yuly Cristina; Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias de la Salud, Escuela de Psicología, Hospital Antiguo, Carrera 10 No 16ª05; Barrera Cárdenas, Mónica; Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias de la Salud, Escuela de Psicología, Hospital Antiguo, Carrera 10 No 16ª05

    2015-01-01

    The aim of this study was to assess whether the intervention model in organizational climate PMCO, was effective in the Hospital of Yopal, Colombia. The following five phases, proposed by the model, were implemented: 1) problem analysis, 2) awareness, 3) strategies design and planning, at the individual, intergroup, and organizational levels, 4) implementation of the strategy, and 5) process evaluation. A design composed of two groups, experimental and control, was chosen, analyzing whether t...

  12. 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

  13. 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......To ensure optimal management and sustainable strategies for water resources, infrastructures, food production and ecosystems there is a need for an improved understanding of feedback and interaction mechanisms between the atmosphere and the land surface. This is especially true in light of expected...... 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...

  14. The Monash University Interactive Simple Climate Model

    Science.gov (United States)

    Dommenget, D.

    2013-12-01

    The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

  15. Optimal white spruce breeding zones for Ontario under current and future climates

    Energy Technology Data Exchange (ETDEWEB)

    Thomson, A.M.; Crowe, K.A.; Parker, W.H. [Lakehead Univ., Thunder Bay, ON (Canada). Faculty of Forestry and the Forest Environment

    2010-08-15

    Forest regeneration and tree improvement practices rely on the local adaptation of planted sources because maladaptation results in reduced growth and increased susceptibility to pests and pathogens. As such, the transfer of tree seed is usually regulated within seed and breeding zones to ensure that trees are planted within their environmental tolerance limits. The purpose of this study was to determine optimal adaptively based breeding zones of white spruce (Picea glauca (Moench) Voss) and to compare current zones with corresponding zones using a methodology for modeled future climates. Optimal breeding zones were developed for white spruce in Ontario under present and future climate conditions to examine potential shifts due to climate change. These zones were developed by determining candidate breeding zones based on the relationship between measured performance variables and climate and by using a decision support model to choose subsets of breeding zones that maximize geographic coverage. Current optimal breeding zones were based on 1961 to 1990 climate normals, and future breeding zones were based on 3 general circulation model predictions of 2041 to 2070 climate. The study showed that 14 zones were needed to cover the Ontario range of white spruce for the 1961 to 1990 data. The delimited current breeding zones for white spruce were found to be quite large, and can be used to ensure forest productivity by limiting the transfer of improved seeds to within areas where they can adapt adequately. 51 refs., 3 tabs., 6 figs.

  16. Model-based assessments of climate change effects on forests

    Energy Technology Data Exchange (ETDEWEB)

    Loehle, C.; LeBlanc, D.C. [Argonne National Lab., IL (United States)]|[Ball State Univ., Muncie, IN (United States)

    1995-06-01

    The potential effects of climate change on forests are of increasing concern. A number of studies based on forest simulation models predict substantial alteration of forest composition, forest dieback, or even loss of forest cover in response to increased temperatures associated with increasing atmospheric carbon dioxide concentrations. However, the structure of these computer models may cause them to overemphasize the role of climate in controlling tree growth and mortality. Model functions that represent the influence of climate on tree growth are based on the geographic range limits of a species, predicting maximal growth in the center of the range and zero growth (100% mortality) at the range limits and beyond. Many tree species can survive in climatic conditions outside their present range limits and can tolerate widely fluctuating climate regimes. Hence, there is reason to suspect that published projections of forest responses to climate change may exaggerate the direct impact of climate on tree growth and mortality. We propose that forest simulation models be reformulated with more realistic representations of growth responses to temperature, moisture, mortality and dispersal. We believe that only when these models more accurately reflect the physiological bases of the responses of tree species to climate variables can they be used to simulate responses of forests to rapid changes in climate. We argue that direct forest responses to climate change projected by such a reformulated model may be less traumatic and more gradual than those projected by current models.

  17. Evaluating Climate Models: Should We Use Weather or Climate Observations?

    Science.gov (United States)

    Oglesby, R. J.; Rowe, C. M.; Maasch, K. A.; Erickson, D. J.; Hays, C.

    2009-12-01

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

  18. 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.

  19. 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.

  20. A National Strategy for Advancing Climate Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Dunlea, Edward; Elfring, Chris

    2012-12-04

    Climate models are the foundation for understanding and projecting climate and climate-related changes and are thus critical tools for supporting climate-related decision making. This study developed a holistic strategy for improving the nation's capability to accurately simulate climate and related Earth system changes on decadal to centennial timescales. The committee's report is a high level analysis, providing a strategic framework to guide progress in the nation's climate modeling enterprise over the next 10-20 years. This study was supported by DOE, NSF, NASA, NOAA, and the intelligence community.

  1. 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. (c) 2010 Elsevier B.V. All rights reserved.

  2. Paleoclimate validation of a numerical climate model

    International Nuclear Information System (INIS)

    Schelling, F.J.; Church, H.W.; Zak, B.D.; Thompson, S.L.

    1994-01-01

    An analysis planned to validate regional climate model results for a past climate state at Yucca Mountain, Nevada, against paleoclimate evidence for the period is described. This analysis, which will use the GENESIS model of global climate nested with the RegCM2 regional climate model, is part of a larger study for DOE's Yucca Mountain Site Characterization Project that is evaluating the impacts of long term future climate change on performance of the potential high level nuclear waste repository at Yucca Mountain. The planned analysis and anticipated results are presented

  3. 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.

  4. The current investment climate for midstream gas processing assets

    International Nuclear Information System (INIS)

    Brouwer, R.J.

    1999-01-01

    Topics discussed in this paper dealing with the current investment climate for midstream gas processing assets include: (1) strategic reasons to retain or divest midstream assets, (2) available options for midstream asset divestment, (3) midstream market fundamentals, and (4) financial performance of midstream companies. There are some 700 gas plants in Alberta at present, of which about 20 per cent are owned by midstream companies . About one half of the plants are smaller than 12.5 MMCFD which represent inefficient use of resources; a clear indication that there are substantial opportunities for consolidation. 1 tab., 4 figs

  5. Predicting the potential distribution in China of Euwallacea fornicates (Eichhoff) under current and future climate conditions

    OpenAIRE

    Ge, Xuezhen; Jiang, Chao; Chen, Linghong; Qiu, Shuang; Zhao, Yuxiang; Wang, Tao; Zong, Shixiang

    2017-01-01

    Euwallacea fornicatus (Eichhoff) is an important forest pest that has caused serious damage in America and Vietnam. In 2014, it attacked forests of Acer trialatum in the Yunnan province of China, creating concern in China?s Forestry Bureau. We used the CLIMEX model to predict and compare the potential distribution for E. fornicates in China under current (1981?2010) and projected climate conditions (2011?2040) using one scenario (RCP8.5) and one global climate model (GCM), CSIRO-Mk3-6-0. Unde...

  6. 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

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

    International Nuclear Information System (INIS)

    Henderson-Sellers, A.

    1996-01-01

    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

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

    DEFF Research Database (Denmark)

    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 th...... 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........ 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...

  9. 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...... 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....... Both under 2010 and 2050 climatic conditions, four subscenarios were modelled, based on a combination of two soil types and two climates. Included in the assessment were seed production, soil preparation, fertilization, pesticide application, and harvest. When processes in the life cycle resulted in co...

  10. Predicting the potential distribution in China of Euwallacea fornicates (Eichhoff) under current and future climate conditions.

    Science.gov (United States)

    Ge, Xuezhen; Jiang, Chao; Chen, Linghong; Qiu, Shuang; Zhao, Yuxiang; Wang, Tao; Zong, Shixiang

    2017-04-19

    Euwallacea fornicatus (Eichhoff) is an important forest pest that has caused serious damage in America and Vietnam. In 2014, it attacked forests of Acer trialatum in the Yunnan province of China, creating concern in China's Forestry Bureau. We used the CLIMEX model to predict and compare the potential distribution for E. fornicates in China under current (1981-2010) and projected climate conditions (2011-2040) using one scenario (RCP8.5) and one global climate model (GCM), CSIRO-Mk3-6-0. Under both current and future climate conditions, the model predicted E. fornicates to be mainly distributed in the south of China. Comparing distributions under both climate conditions showed that the area of potential distribution was projected to increase (mainly because of an increase in favourable habitat) and shift to the north. Our results help clarify the potential effect of climate change on the range of this forest pest and provide a reference and guide to facilitate its control in China.

  11. Improving poverty and inequality modelling in climate research

    Science.gov (United States)

    Rao, Narasimha D.; van Ruijven, Bas J.; Riahi, Keywan; Bosetti, Valentina

    2017-12-01

    As climate change progresses, the risk of adverse impacts on vulnerable populations is growing. As governments seek increased and drastic action, policymakers are likely to seek quantification of climate-change impacts and the consequences of mitigation policies on these populations. Current models used in climate research have a limited ability to represent the poor and vulnerable, or the different dimensions along which they face these risks. Best practices need to be adopted more widely, and new model features that incorporate social heterogeneity and different policy mechanisms need to be developed. Increased collaboration between modellers, economists, and other social scientists could aid these developments.

  12. A Regional Climate Model Evaluation System

    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...

  13. 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...

  14. 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

  15. 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

  16. Usage of web-GIS platform Climate to prepare specialists in climate changes modeling and analysis

    Science.gov (United States)

    Gordova, Yulia; Martynova, Yulia; Shulgina, Tamara

    2014-05-01

    A web-GIS based platform "Climate" developed in our institute (http://climate.scert.ru/) has a set of tools and data bases to perform climate changes analysis on the selected territory. The platform is functioning and open for registration and all these tools are available. Besides that the platform has a potential to be used in education. It contains several educational courses followed by tests and trainings which are performed within the platform "Climate" using its web-gis tools. The main purpose of a new "Climatic and environmental modeling" module course is to enable students and graduates meteorological departments to improve their knowledge and skills in modern climatology. Although the emphasis is on climate science, the course is directly related to the part of the ecological science, which refers to the environment. This is due to the fact that the current global climate models have become models of the Earth system and include models of environment as well. The module includes a main course of lectures devoted to basic aspects of modern climatology , including analysis of the current climate change and its possible consequences , a special course on geophysical hydrodynamics, several on-line computing labs dedicated to specific monitoring and modeling of climate and climate change , as well as information kit , which not only includes the usual list of recommended reading, but also contains the files of many publications , the distribution of which is not limited by copyright law. Laboratory exercises are designed to consolidate students' knowledge of discipline, to instill in them the skills to work independently with large amounts of geophysical data using modern processing and analysis tools of web-GIS platform "Climate". The results obtained on laboratory work are presented as reports with the statement of the problem, the results of calculations and logically justified conclusion. Now the following labs are used to train and prepare young

  17. Probabilistic evaluation of competing climate models

    Directory of Open Access Journals (Sweden)

    A. Braverman

    2017-10-01

    Full Text Available Climate models produce output over decades or longer at high spatial and temporal resolution. Starting values, boundary conditions, greenhouse gas emissions, and so forth make the climate model an uncertain representation of the climate system. A standard paradigm for assessing the quality of climate model simulations is to compare what these models produce for past and present time periods, to observations of the past and present. Many of these comparisons are based on simple summary statistics called metrics. In this article, we propose an alternative: evaluation of competing climate models through probabilities derived from tests of the hypothesis that climate-model-simulated and observed time sequences share common climate-scale signals. The probabilities are based on the behavior of summary statistics of climate model output and observational data over ensembles of pseudo-realizations. These are obtained by partitioning the original time sequences into signal and noise components, and using a parametric bootstrap to create pseudo-realizations of the noise sequences. The statistics we choose come from working in the space of decorrelated and dimension-reduced wavelet coefficients. Here, we compare monthly sequences of CMIP5 model output of average global near-surface temperature anomalies to similar sequences obtained from the well-known HadCRUT4 data set as an illustration.

  18. Probabilistic evaluation of competing climate models

    Science.gov (United States)

    Braverman, Amy; Chatterjee, Snigdhansu; Heyman, Megan; Cressie, Noel

    2017-10-01

    Climate models produce output over decades or longer at high spatial and temporal resolution. Starting values, boundary conditions, greenhouse gas emissions, and so forth make the climate model an uncertain representation of the climate system. A standard paradigm for assessing the quality of climate model simulations is to compare what these models produce for past and present time periods, to observations of the past and present. Many of these comparisons are based on simple summary statistics called metrics. In this article, we propose an alternative: evaluation of competing climate models through probabilities derived from tests of the hypothesis that climate-model-simulated and observed time sequences share common climate-scale signals. The probabilities are based on the behavior of summary statistics of climate model output and observational data over ensembles of pseudo-realizations. These are obtained by partitioning the original time sequences into signal and noise components, and using a parametric bootstrap to create pseudo-realizations of the noise sequences. The statistics we choose come from working in the space of decorrelated and dimension-reduced wavelet coefficients. Here, we compare monthly sequences of CMIP5 model output of average global near-surface temperature anomalies to similar sequences obtained from the well-known HadCRUT4 data set as an illustration.

  19. Mediterranean climate modelling: variability and climate change scenarios

    International Nuclear Information System (INIS)

    Somot, S.

    2005-12-01

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

  20. 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.

  1. Influence of current climate, historical climate stability and topography on species richness and endemism in Mesoamerican geophyte plants

    Directory of Open Access Journals (Sweden)

    Victoria Sosa

    2017-10-01

    Full Text Available Background A number of biotic and abiotic factors have been proposed as drivers of geographic variation in species richness. As biotic elements, inter-specific interactions are the most widely recognized. Among abiotic factors, in particular for plants, climate and topographic variables as well as their historical variation have been correlated with species richness and endemism. In this study, we determine the extent to which the species richness and endemism of monocot geophyte species in Mesoamerica is predicted by current climate, historical climate stability and topography. Methods Using approximately 2,650 occurrence points representing 507 geophyte taxa, species richness (SR and weighted endemism (WE were estimated at a geographic scale using grids of 0.5 × 0.5 decimal degrees resolution using Mexico as the geographic extent. SR and WE were also estimated using species distributions inferred from ecological niche modeling for species with at least five spatially unique occurrence points. Current climate, current to Last Glacial Maximum temperature, precipitation stability and topographic features were used as predictor variables on multiple spatial regression analyses (i.e., spatial autoregressive models, SAR using the estimates of SR and WE as response variables. The standardized coefficients of the predictor variables that were significant in the regression models were utilized to understand the observed patterns of species richness and endemism. Results Our estimates of SR and WE based on direct occurrence data and distribution modeling generally yielded similar results, though estimates based on ecological niche modeling indicated broader distribution areas for SR and WE than when species richness was directly estimated using georeferenced coordinates. The SR and WE of monocot geophytes were highest along the Trans-Mexican Volcanic Belt, in both cases with higher levels in the central area of this mountain chain. Richness and

  2. Climate change and health modeling: horses for courses

    Directory of Open Access Journals (Sweden)

    Kristie L. Ebi

    2014-05-01

    Full Text Available Mathematical and statistical models are needed to understand the extent to which weather, climate variability, and climate change are affecting current and may affect future health burdens in the context of other risk factors and a range of possible development pathways, and the temporal and spatial patterns of any changes. Such understanding is needed to guide the design and the implementation of adaptation and mitigation measures. Because each model projection captures only a narrow range of possible futures, and because models serve different purposes, multiple models are needed for each health outcome (‘horses for courses’. Multiple modeling results can be used to bracket the ranges of when, where, and with what intensity negative health consequences could arise. This commentary explores some climate change and health modeling issues, particularly modeling exposure-response relationships, developing early warning systems, projecting health risks over coming decades, and modeling to inform decision-making. Research needs are also suggested.

  3. 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.

  4. Diurnal cloud cycle biases in climate models.

    Science.gov (United States)

    Yin, Jun; Porporato, Amilcare

    2017-12-22

    Clouds' efficiency at reflecting solar radiation and trapping the terrestrial radiation is strongly modulated by the diurnal cycle of clouds (DCC). Much attention has been paid to mean cloud properties due to their critical role in climate projections; however, less research has been devoted to the DCC. Here we quantify the mean, amplitude, and phase of the DCC in climate models and compare them with satellite observations and reanalysis data. While the mean appears to be reliable, the amplitude and phase of the DCC show marked inconsistencies, inducing overestimation of radiation in most climate models. In some models, DCC appears slightly shifted over the ocean, likely as a result of tuning and fortuitously compensating the large DCC errors over the land. While this model tuning does not seem to invalidate climate projections because of the limited DCC response to global warming, it may potentially increase the uncertainty of climate predictions.

  5. US Drought-Heat Wave Relationships in Past Versus Current Climates

    Science.gov (United States)

    Cheng, L.; Hoerling, M. P.; Eischeid, J.; Liu, Z.

    2017-12-01

    This study explores the relationship between droughts and heat waves over various regions of the contiguous United States that are distinguished by so-called energy-limited versus water-limited climatologies. We first examine the regional sensitivity of heat waves to soil moisture variability under 19th century climate conditions, and then compare to sensitivities under current climate that has been subjected to human-induced change. Our approach involves application of the conditional statistical framework of vine copula. Vine copula is known for its flexibility in reproducing various dependence structures exhibited by climate variables. Here we highlight its feature for evaluating the importance of conditional relationships between variables and processes that capture underlying physical factors involved in their interdependence during drought/heat waves. Of particular interest is identifying changes in coupling strength between heat waves and land surface conditions that may yield more extreme events as a result of land surface feedbacks. We diagnose two equilibrium experiments a coupled climate model (CESM1), one subjected to Year-1850 external forcing and the other to Year-2000 radiative forcing. We calculate joint heat wave/drought relationships for each climate state, and also calculate their change as a result of external radiative forcing changes across this 150-yr period. Our results reveal no material change in the dependency between heat waves and droughts, aside from small increases in coupling strength over the Great Plains. Overall, hot U.S. summer droughts of 1850-vintage do not become hotter in the current climate -- aside from the warming contribution of long-term climate change, in CESM1. The detectability of changes in hotter droughts as a consequence of anthropogenic forced changes in this single effect, i.e. coupling strength between soil moisture and hot summer temperature, is judged to be low at this time.

  6. Switzerland: current energy and climate policies. Political boundary conditions

    International Nuclear Information System (INIS)

    Previdoli, P.

    2006-01-01

    End use energy consumption in Switzerland has increased almost ninefold over the past 95 years, amounting to nearly 88 PJ in 2004. This figure breaks down as follows: coal 5%, oil-based fuels 29%, motor fuels 31%, electricity 22%, gas 11%, district heat, solid municipal and industrial waste as well as renewables (excluding electricity) approx. 1%. In 2004 alone, end use energy consumption rose by half a percent, thus reaching a new record high. This development is due, above all, to the population increase and to economic growth. To achieve its goals in energy and climate policies, and to initiate sustainable energy supply, the Swiss federal council in 2001 launched the 'EnergySwitzerland' Program. The new strategy of the Program focuses on these three goals: 'Climate', 'Electricity: Efficiency Goal', and 'Renewable Energies'. On the basis of perspectives of the development of the population and of the economy, the consequences of a number of policy variants for energy supply and demand and for the economy and the environment have been examined. Four scenarios (variants) are to help design energy policy on a medium and long term by showing energy policy options. For the area of electricity supply facing increasing requirements, 4 options and their pros and cons are distinguished: electricity imports, renewable energies, fossil- fired thermal plants (combined-cycle plants), and nuclear power. With a 40% share in domestic production, nuclear power continues to be a pillar of Swiss energy supply. The fundamental question about the future of nuclear power is not a question of technical or economic know-how, but a question of the system of political values. As the current legal system in the field of electricity supply does not meet requirements, it will have to be adapted. (orig.)

  7. 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.

  8. Modeling Past Abrupt Climate Changes

    DEFF Research Database (Denmark)

    Marchionne, Arianna

    of the orbital variations on Earth's climate; however, the knowledge and tools needed to complete a unied theory for ice ages have not been developed yet. Here, we focus on the climatic variations that have occurred over the last few million years. Paleoclimatic records show that the glacial cycles are linked...... 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...... discuss a third possible mechanism for the climate response to an external periodic forcing. In this scenario, the system is excitable: a small perturbation from the xed point may produce large excursions....

  9. 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.

  10. 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.

  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. Climate Predictions: The Chaos and Complexity in Climate Models

    Directory of Open Access Journals (Sweden)

    D. T. Mihailović

    2014-01-01

    Full Text Available 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 Gödel’s theorem and Rosen’s definition of complexity and predictability is discussed. Occurrence of chaos in computing the environmental interface temperature from the energy balance equation given in a difference form is pointed out. A coupled system of equations, often used in climate models, was analyzed. It is shown that the Lyapunov exponent mostly has positive values allowing presence of chaos in this system. The horizontal energy exchange between environmental interfaces, which is described by the dynamics of driven coupled oscillators, was analyzed. Their behavior and synchronization, when a perturbation is introduced in the system, as a function of the coupling parameter, the logistic parameter, and the parameter of exchange, were studied calculating the Lyapunov exponent under simulations with the closed contour of N=100 environmental interfaces. Finally, we have explored possible differences in complexities of two global and two regional climate models using their air temperature and precipitation output time series. The complexities were obtained with the algorithm for calculating the Kolmogorov complexity.

  13. The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yuying [Lawrence Livermore National Laboratory, Livermore, California; Xie, Shaocheng [Lawrence Livermore National Laboratory, Livermore, California; Klein, Stephen A. [Lawrence Livermore National Laboratory, Livermore, California; Marchand, Roger [University of Washington, Seattle, Washington; Kollias, Pavlos [Stony Brook University, Stony Brook, New York; Clothiaux, Eugene E. [The Pennsylvania State University, University Park, Pennsylvania; Lin, Wuyin [Brookhaven National Laboratory, Upton, New York; Johnson, Karen [Brookhaven National Laboratory, Upton, New York; Swales, Dustin [CIRES and NOAA/Earth System Research Laboratory, Boulder, Colorado; Bodas-Salcedo, Alejandro [Met Office Hadley Centre, Exeter, United Kingdom; Tang, Shuaiqi [Lawrence Livermore National Laboratory, Livermore, California; Haynes, John M. [Cooperative Institute for Research in the Atmosphere/Colorado State University, Fort Collins, Colorado; Collis, Scott [Argonne National Laboratory, Argonne, Illinois; Jensen, Michael [Brookhaven National Laboratory, Upton, New York; Bharadwaj, Nitin [Pacific Northwest National Laboratory, Richland, Washington; Hardin, Joseph [Pacific Northwest National Laboratory, Richland, Washington; Isom, Bradley [Pacific Northwest National Laboratory, Richland, Washington

    2018-01-01

    Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are

  14. 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.

  15. 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.

  16. Validating predictions from climate envelope models.

    Directory of Open Access Journals (Sweden)

    James I Watling

    Full Text Available 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

  17. 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. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  18. 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.

  19. 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

  20. Connecting Current Research on Climate and Snow with Individuals Who Care

    Science.gov (United States)

    Moore, C. E.; Denning, S.

    2015-12-01

    A growing body of research explores the effects of climate change on snow in the Southern Rocky Mountains. This research includes observing climate and weather patterns, modeling potential future winter climate and snowpack, and exploring how these changes will affect the ecosystems, people, and industries that rely on frozen reservoirs of seasonal snow. We review existing resources for non-scientists on this topic, and explain how climate and snow are changing in the Southern Rocky Mountains. The Southern Rockies urban corridor is home to a growing population of people who rely directly on snowmelt runoff for daily life, health, and prosperity. Many of these people also seek refuge from growing urbanization by escaping to the mountains. Meanwhile, high elevations in the Rockies are already experiencing noticeable effects of climate change. Individuals with personal connections to the mountains make a ready audience to receive accessible science communication grounded in current research. People who care about mountains may be inspired to join the conversation and take action in their own lives as they learn what is already changing and what they might expect to find in winters to come.

  1. 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.

  2. Wildfire Impacts Upon US Air Quality for Current and Future Climate Conditions

    Science.gov (United States)

    Gonzalez Abraham, R.; Chung, S. H.; Lamb, B. K.; Tao, I.; Avise, J. C.; Stavros, E. N.; Strand, T. T.; McKenzie, D.; Guenther, A. B.; Wiedinmyer, C.; Duhl, T.; Salathe, E. P.; Zhang, Y.

    2011-12-01

    Wildfires can have an important impact on regional air quality as they are large and intermittent sources of primary particulates, secondary aerosols, and ozone precursors. As part of an ongoing analysis on the effects of global change upon US air quality, we report results for current and future decade simulations of the inter-relationship among climate change, wildfires and air quality. The results are reported for the Northwest, Southwest, and Central Rockies regions of the US. Meteorological fields from the ECHAM5 global climate model for the IPCC A1B scenario were downscaled using the Weather Research Forecast (WRF) model to drive the MEGAN biogenic emissions model, a stochastic fire occurrence model, Fire Simulation Builder (FSB), and the CMAQ chemical transport model to predict ozone and aerosol concentrations. Simulations were completed for two nested domains covering most of the northern hemisphere from eastern Asia to North America at 220 km horizontal resolution (hemispheric domain) and covering the continental US at 36 km resolution (CONUS). Sensitivity studies were conducted for representative summer periods with fire occurrence generated from FSB within the current (1995-2004) and future decade (2045-2054) and using current decade historical fire data obtained from the Bureau of Land Management Database. Results are reported in terms of the effects of global change upon fire occurrence, fire plume transport and PM and ozone pollutant levels.

  3. Climate change and food security in Tanzania: analysis of current ...

    African Journals Online (AJOL)

    A review of literature was conducted in order to identify knowledge gaps in climate change and food security research in Tanzania. The review focused on published literature covering the past 20 years addressing climate change effects on various components of the food security. The review of literature reveals, among ...

  4. Stochastic Climate Forcing for Ice-Sheet Models

    Science.gov (United States)

    Nuterman, Roman; Jochum, Markus

    2017-04-01

    Climate oscillations from glacial periods, with large parts of the continents covered with ice, to warm interglacials like the present one, are observed in various paleoclimatic records over the past few million years. According to Milankovitch theory, which is commonly assumed, these glacial cycles are linked to changes in insolation due to periodic changes of external earth-orbital forcing. However, this relationship is far from understood, because the insolation variations are so small that enhancing feedbacks must be at play. Moreover, there are several shortcomings in the Milankovitch theory: first, the duration of the glacial cycles changed at the so-called Mid-Pleistocene transition from 41,000 years to approximately 100,000 years and second, the interglacial of 400,000 years ago should not have happened. Thus, the current phasing and magnitude of the glacial cycles are far from being well understood and the external perturbation might only play a minor role in comparison to internal stochastic variations or internal oscillations. Although modern Ice-Sheet Models (ISM) are able to simulate evolution of ice-sheets at the entire glacial or interglacial time scales, the state-of-the-art Earth System Models (ESM) are too computationally expensive for such long integrations. Therefore, a constant climate forcing is usually used in the ice-sheet models. However, this approach does not take into account the stochastic nature of climate. At the same time, ESM models provide valuable information on natural climate variability, which then can be used for building stochastic climate models able to generate both continuous and discrete climate variables with stochastic atmospheric processes. In this study, we present a stochastic climate model, built from large sets of Community Earth System Model (CESM) integrations with both internal and external climate forcing, and able to generate synthetic climate forcing (such as temperature and precipitation fields) of any

  5. 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].

  6. Climate change decision-making: Model & parameter uncertainties explored

    Energy Technology Data Exchange (ETDEWEB)

    Dowlatabadi, H.; Kandlikar, M.; Linville, C.

    1995-12-31

    A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.

  7. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

    A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    in this region that are potentially highly susceptible to climatic effects. Using an integrative study of their behaviour, physiology and fitness at three study sites, we evaluated the impact of ocean warming on little auks across the Greenland Sea in 2005-2007. Contrary to our hypothesis, the birds responded...... to a wide range of sea surface temperatures via plasticity of their foraging behaviour, allowing them to maintain their fitness levels unchanged. Predicted effects of climate change are significantly attenuated by such plasticity, confounding attempts to forecast future impacts of climate change by envelope...

  9. 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

  10. Modeling Uncertainty in Climate Change: A Multi-Model Comparison

    Energy Technology Data Exchange (ETDEWEB)

    Gillingham, Kenneth; Nordhaus, William; Anthoff, David; Blanford, Geoffrey J.; Bosetti, Valentina; Christensen, Peter; McJeon, Haewon C.; Reilly, J. M.; Sztorc, Paul

    2015-10-01

    The economics of climate change involves a vast array of uncertainties, complicating both the analysis and development of climate policy. This study presents the results of the first comprehensive study of uncertainty in climate change using multiple integrated assessment models. The study looks at model and parametric uncertainties for population, total factor productivity, and climate sensitivity and estimates the pdfs of key output variables, including CO2 concentrations, temperature, damages, and the social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting pdfs also provide insight on tail events.

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

    African Journals Online (AJOL)

    harvesting systems, weak research-extension- farmer linkages, rapid population growth, poor agricultural policies, inadequate application of agricultural technologies, poor agricultural practices, unreliable markets, crop pests and diseases, global energy demand, and climate change and variability (Ernhart and Twena,.

  12. Integrated assessment models of global climate change

    International Nuclear Information System (INIS)

    Parson, E.A.; Fisher-Vanden, K.

    1997-01-01

    The authors review recent work in the integrated assessment modeling of global climate change. This field has grown rapidly since 1990. Integrated assessment models seek to combine knowledge from multiple disciplines in formal integrated representations; inform policy-making, structure knowledge, and prioritize key uncertainties; and advance knowledge of broad system linkages and feedbacks, particularly between socio-economic and bio-physical processes. They may combine simplified representations of the socio-economic determinants of greenhouse gas emissions, the atmosphere and oceans, impacts on human activities and ecosystems, and potential policies and responses. The authors summarize current projects, grouping them according to whether they emphasize the dynamics of emissions control and optimal policy-making, uncertainty, or spatial detail. They review the few significant insights that have been claimed from work to date and identify important challenges for integrated assessment modeling in its relationships to disciplinary knowledge and to broader assessment seeking to inform policy- and decision-making. 192 refs., 2 figs

  13. Assessing Climate change impacts on river basins in New Zealand using model based downscaling, statistical downscaling and regional climate modelling

    Science.gov (United States)

    Zammit, C.; Diettrich, J.; Sood, A.

    2013-12-01

    Spatial resolution of General Circulation Models (GCMs) is too coarse to represent regional climate variations at the scales required for environmental impact assessments in New Zealand. Downscaling is necessary for climate change impact analyses that seek to constrain regional climate by information from global climate models. It is particularly important in the New Zealand context, as given maritime, topographic and convective climate processes. As a result local to regional scale variability is not always well represented by the broader global scale features simulated by GCMs. Three techniques are available to generate climate change information that can be used as input of environmental models: i) Downscaling to the New Zealand Virtual Climate Station Network grid (Tait et al, 2006); ii) Semi-empirical (statistical) downscaling (SDS) of GCM outputs; and iii) Regional climate models (RCMs) nested within a GCM. In this study, we compare the downstream impact of the three techniques for three different emission scenarios as characterised in the IPCC Fourth Assessment (B1-low emission, A1B- middle of the road, and A2-high emission scenario) and two of the 12 GCM models used in New Zealand (UKMO_HADCM3 and MPI_ECHAM5). Our study will focus on surface water hydrological responses (ie discharge, infiltration, evaporation, snow storage) for a number of river basins across the North and South Island of New Zealand. The analysis will compare the current situation (1980-1999) with two future time periods (2030-2049 and 2080-2099) and will draw recommendation regarding climate change impact uncertainty and its communication to decision makers.

  14. 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.

  15. A seasonal climate model for earth

    Science.gov (United States)

    North, G. R.; Coakley, J. A.

    1979-01-01

    A simple seasonal climate model for earth is developed on the basis of a few terms extracted from monthly and zonally averaged climatic data fields represented in latitude by Legendre polynomials and in time by Fourier series. This simple, physically motivated model accounts for the gross features of the present zonally averaged seasonal climate (root mean square error of two deg C). The sensitivities of the seasonal model and a corresponding mean annual model are approximately equal if ice and snow lines (for albedo purposes) are attached to certain mean-annual and instantaneous isotherms. More dynamics (in particular, cryospheric) are needed in the seasonal model to explain the relationship between glacial rhythms and changes in the earth's orbital elements.

  16. Influence of Regional Climate Model spatial resolution on wind climates

    Science.gov (United States)

    Pryor, S. C.; Barthelmie, R. J.; Nikulin, G.; Jones, C.

    2010-12-01

    Global and regional climate models are being run at increasingly fine horizontal and vertical resolution with the goal of increased skill. However, relatively few studies have quantified the change in modeled wind climates that derives from applying a Regional Climate Model (RCM) at varying resolutions, and the response to varying resolution may be highly non-linear since most models run in climate mode are hydrostatic. Thus, herein we examine the influence of grid-resolution on modelled wind speeds and gusts and derived extremes thereof over southern Scandinavia using output from the Rossby Centre (RCA3) RCM run at four different resolutions from 50 x 50 km to 6 x 6 km, and with two different vertical grid-spacings. Domain averaged fifty-year return period wind speeds and wind gusts derived using the method of moments approach to compute the Gumbel parameters, increase with resolution (Table 1), though the change is strongly mediated by the model grid-cell surface characteristics. Power spectra of the 3-hourly model time-step ‘instantaneous’ wind speeds and daily wind gusts at all four resolutions show clear peaks in the variance associated with bi-annual, annual, seasonal and synoptic frequencies. The variance associated with these peaks is enhanced with increased resolution, though not in a monotonic fashion, and is more marked in wind gusts than wind speeds. Relative to in situ observations, the model generally underestimates the variance, particularly associated with the synoptic time scale, even for the highest resolution simulations. There is some evidence to suggest that the change in the power spectra with horizontal resolution is less marked in the transition from 12.5 km to 6.25 km, than from 50 to 25 km, or 25 km to 12.5 km.Table 1. Domain averaged mean annual wind speed (U), 50-year return period extreme wind speed (U50yr) and wind gust (Gust50yr) (m/s) from the four RCA3 simulations at different resolution based on output from 1987-2008. The

  17. 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.

  18. Past and current sediment dispersion pattern estimates through numerical modeling of wave climate: an example of the Holocene delta of the Doce River, Espírito Santo, Brazil

    Directory of Open Access Journals (Sweden)

    Abílio C.S.P. Bittencourt

    2007-06-01

    Full Text Available This paper presents a numerical modeling estimation of the sediment dispersion patterns caused by waves inciding through four distinct coastline contours of the delta plain of the Doce River during the Late Holocene. For this, a wave climate model based on the construction of wave refraction diagrams, as a function of current boundary conditions, was defined and was assumed to be valid for the four coastlines. The numerical modeling was carried out on basis of the refraction diagrams, taking into account the angle of approximation and the wave height along the coastline. The results are shown to be comparable with existing data regarding the directions of net longshore drift of sediments estimated from the integration of sediment cores, interpretation of aerial photographs and C14 datings. This fact apparently suggests that, on average, current boundary conditions appear to have remained with the same general characteristics since 5600 cal yr BP to the present. The used approach may prove useful to evaluate the sediment dispersion patterns during the Late Holocene in the Brazilian east-northeast coastal region.O presente trabalho apresenta uma estimativa, por modelagem numérica, dos padrões de dispersão de sedimentos causados por ondas ao longo de quatro distintos traçados da linha decosta durante o Holoceno Tardio na planície deltaica do Rio Doce. Para tanto, foi definido um modelo de clima de ondas baseado na construção de diagramas de refração de ondas, em função das condições de contorno atuais, que foi assumido como válido para as quatro linhas de costa. A modelagem numérica foi realizada a partir dos diagramas de refração, levando-se em conta o ângulo de aproximação e a altura da onda ao longo da linha de costa. Os resultados obtidos mostraram-se compatíveis com os dados existentes relativos aos sentidos da deriva litorânea efetiva de sedimentos estimados a partir da integração de testemunhos de vibra

  19. Global precipitation measurements for validating climate models

    Science.gov (United States)

    Tapiador, F. J.; Navarro, A.; Levizzani, V.; García-Ortega, E.; Huffman, G. J.; Kidd, C.; Kucera, P. A.; Kummerow, C. D.; Masunaga, H.; Petersen, W. A.; Roca, R.; Sánchez, J.-L.; Tao, W.-K.; Turk, F. J.

    2017-11-01

    The advent of global precipitation data sets with increasing temporal span has made it possible to use them for validating climate models. In order to fulfill the requirement of global coverage, existing products integrate satellite-derived retrievals from many sensors with direct ground observations (gauges, disdrometers, radars), which are used as reference for the satellites. While the resulting product can be deemed as the best-available source of quality validation data, awareness of the limitations of such data sets is important to avoid extracting wrong or unsubstantiated conclusions when assessing climate model abilities. This paper provides guidance on the use of precipitation data sets for climate research, including model validation and verification for improving physical parameterizations. The strengths and limitations of the data sets for climate modeling applications are presented, and a protocol for quality assurance of both observational databases and models is discussed. The paper helps elaborating the recent IPCC AR5 acknowledgment of large observational uncertainties in precipitation observations for climate model validation.

  20. Modelling climate change and malaria transmission.

    Science.gov (United States)

    Parham, Paul E; Michael, Edwin

    2010-01-01

    The impact of climate change on human health has received increasing attention in recent years, with potential impacts due to vector-borne diseases only now beginning to be understood. As the most severe vector-borne disease, with one million deaths globally in 2006, malaria is thought most likely to be affected by changes in climate variables due to the sensitivity of its transmission dynamics to environmental conditions. While considerable research has been carried out using statistical models to better assess the relationship between changes in environmental variables and malaria incidence, less progress has been made on developing process-based climate-driven mathematical models with greater explanatory power. Here, we develop a simple model of malaria transmission linked to climate which permits useful insights into the sensitivity of disease transmission to changes in rainfall and temperature variables. Both the impact of changes in the mean values of these key external variables and importantly temporal variation in these values are explored. We show that the development and analysis of such dynamic climate-driven transmission models will be crucial to understanding the rate at which P. falciparum and P. vivax may either infect, expand into or go extinct in populations as local environmental conditions change. Malaria becomes endemic in a population when the basic reproduction number R0 is greater than unity and we identify an optimum climate-driven transmission window for the disease, thus providing a useful indicator for determing how transmission risk may change as climate changes. Overall, our results indicate that considerable work is required to better understand ways in which global malaria incidence and distribution may alter with climate change. In particular, we show that the roles of seasonality, stochasticity and variability in environmental variables, as well as ultimately anthropogenic effects, require further study. The work presented here

  1. 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.

  2. 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

  3. Normal Forms for Reduced Stochastic Climate Models

    Science.gov (United States)

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

    2009-04-01

    The systematic development of reduced low-dimensional stochastic climate models from observations or comprehensive high-dimensional climate models is an important topic for low-frequency variability, climate sensitivity, and improved extended range forecasting. Here techniques from applied mathematics are utilized to systematically derive normal forms for reduced stochastic climate models for low-frequency variables. The use of a few Empirical Orthogonal Functions (EOF) depending on observational data to span the low-frequency subspace requires the assessment of dyad interactions besides the more familiar triads in the interaction between the low- and high-frequency subspaces of the dynamics. It will be shown that the dyad and multiplicative triad interactions combine with the climatological linear operator interactions to simultaneously produce both strong nonlinear dissipation and Correlated Additive and Multiplicative (CAM) stochastic noise. For a single low-frequency variable the dyad interactions and climatological linear operator alone produce a normal form with CAM noise from advection of the large-scales by the small scales and simultaneously strong cubic damping. This normal form should prove useful for developing systematic regression fitting strategies for stochastic models of climate data. The validity of the one and two dimensional normal forms will be presented. Also the analytical PDF form for one-dimensional reduced models will be derived. This PDF can exhibit power-law decay only over a limited range and its ultimate decay is determined by the cubic damping. This cubic damping produces a Gaussian tail.

  4. Climate-Induced Change in South Central Siberia: Predictions Versus Current Observations

    Science.gov (United States)

    Soja, A. J.; Tchebakova, N. M.; Parfenova, E. I.; Shishikin, A.; Kanzai, V.; Westberg, D. J.; Sukhinin, A. I.; Ivanova, G. A.; Stackhouse, P. W.

    2007-12-01

    Atmosphere Ocean General Circulations Models (AOGCM) are in agreement that Siberia is expected to experience warming in excess of 40% above global mean temperature increases by 2100. Moreover, it is predicted temperature increases will be evident in both the summer and winter. In association with changes in climate, the extent of the fire season, the amount of area burned and fire severity are predicted to increase. Fire regime increases are predicted to be the catalyst for ecosystem change, which will force ecosystems to move more rapidly towards equilibrium with the climate. Bioclimatic model results predict expansive changes in ecosystems, from a landscape dominated by taiga to a landscape dominated by steppe and forest-steppe. The focus of this investigation is on south, central Siberia in the Sayan Mountains and the Tyvan Republic, where one would expect to find the initial signs of climate change. The Sayan mountain range offers relatively abrupt change in ecosystems that are often defined by altitude, temperature and precipitation. Tyva is located at a vulnerable southern border, south of the Sayan, and contains 9 Biospheric Reserves, each representing distinct ecosystems. Additionally, Tyva is the home of several relic Pinus sylvestris forests. In these regions, January temperature increases have exceeded those predicted by the Hadley Centre scenario for 2090, and July temperatures are well below predictions. Predicted increases in rainfall are not apparent, and generally, precipitation change has been negative. The growing season length has already increased by about 6 to 12 days. Consequently, several of the relic pine forests have burned (some repeatedly), and natural regeneration is not visible at several sites, even one that had been re-planted on several occasions. In the last decades, these regions have experienced changes in climate and, potentially, initial signs of ecosystem change. In this report, we present a concentrated view of one region that

  5. On coupling global biome models with climate models

    International Nuclear Information System (INIS)

    Claussen, M.

    1994-01-01

    The BIOME model of Prentice et al. (1992), which predicts global vegetation patterns in equilibrium with climate, is coupled with the ECHAM climate model of the Max-Planck-Institut fuer Meteorologie, Hamburg. It is found that incorporation of the BIOME model into ECHAM, regardless at which frequency, does not enhance the simulated climate variability, expressed in terms of differences between global vegetation patterns. Strongest changes are seen only between the initial biome distribution and the biome distribution computed after the first simulation period, provided that the climate-biome model is started from a biome distribution that resembles the present-day distribution. After the first simulation period, there is no significant shrinking, expanding, or shifting of biomes. Likewise, no trend is seen in global averages of land-surface parameters and climate variables. (orig.)

  6. Integrated science model for assessment of climate change. Revision 1

    International Nuclear Information System (INIS)

    Jain, A.K.; Wuebbles, D.J.; Kheshgi, H.S.

    1994-04-01

    Past measurements show that greenhouse gas concentrations, many of which are affected by human related activities, are increasing in the atmosphere. There is wide consensus that this increase influences related activities, are increasing the earth's energy balance and concern that this will cause significant change in climate. Many different policies could be adopted in response to the prospects of greenhouse warming. Models are used by policy markers to analyze the range of possible policy options developed as a response to concerns about climate change. A fully integrated assessment model that spans the many aspects of climate change, including economics, energy options, effects of climate, and impacts of climate change, would be a useful tool. With this goal in mind, the science modules which estimate the effect of emissions of greenhouse gasses on global temperature and sea level are being developed. This is a report of the current characteristics and performance of an Integrated Science Model which consists of coupled modules for carbon cycle, atmospheric chemistry of other trace gases, radiative forcing by greenhouse gases, energy balance model for global temperature, and a model for sea level response

  7. 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.

  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. Multilevel model of safety climate for furniture industries.

    Science.gov (United States)

    Rodrigues, Matilde A; Arezes, Pedro M; Leão, Celina P

    2015-01-01

    Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies' safety conditions were also analyzed. Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies' safety conditions; the organizational scale is the one that best reflects the actual safety conditions. The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups' safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.

  10. Current State of Climate Education in the United States: Are Graduate Students being Adequately Prepared to Address Climate Issues?

    Science.gov (United States)

    Kuster, E.; Fox, G.

    2016-12-01

    Climate change is happening; scientists have already observed changes in sea level, increases in atmospheric carbon dioxide, and declining polar ice. The students of today are the leaders of tomorrow, and it is our duty to make sure they are well equipped and they understand the implications of climate change as part of their research and professional careers. Graduate students, in particular, are gaining valuable and necessary research, leadership, and critical thinking skills, but we need to ensure that they are receiving the appropriate climate education in their graduate training. Previous studies have primarily focused on capturing the K-12, college level, and general publics' knowledge of the climate system, concluding with recommendations on how to improve climate literacy in the classroom. While this is extremely important to study, very few studies have captured the current perception that graduate students hold regarding the amount of climate education being offered to them. This information is important to capture, as it can inform future curriculum development. We developed and distributed a nationwide survey (495 respondents) for graduate students to capture their perception on the level of climate system education being offered and their view on the importance of having climate education. We also investigated differences in the responses based on either geographic area or discipline. We compared how important graduate students felt it was to include climate education in their own discipline versus outside disciplines. The authors will discuss key findings from this ongoing research.

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

    Science.gov (United States)

    Romañach, 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.

  12. Greenhouse effect and climate warmup. The current situation (spring 1993)

    International Nuclear Information System (INIS)

    Leygonie, R.

    1993-01-01

    The present article first recalls the conclusions of the preceding one, essentially based on the IPCC study (Intergovernmental Panel on Climate Change). Recently several scientists expressed their disagreements on IPCC conclusions, which we summarize on the present article. Recent complementary studies by the IPCC team are briefly presented, which do not contradict previous conclusions but contain some amendments, the French programme ECLAT, closely tied to international research activities, is briefly summarized. Recent political facts are mentioned: - A directive proposal by the European Community which aims at a taxation of fossil carbon used as fuel and energy in general, in order to favour the reduction of CO 2 emissions. - The United Nations Convention on Climate Change signed at the Rio Conference (June 1992) by which 155 nations commit themselves to abate their emissions of greenhouse gases. No calendar and reduction figures are given, but subsequent texts specify relevant obligations. 1 tab

  13. Analytic modeling of axisymmetric disruption halo currents

    International Nuclear Information System (INIS)

    Humphreys, D.A.; Kellman, A.G.

    1999-01-01

    Currents which can flow in plasma facing components during disruptions pose a challenge to the design of next generation tokamaks. Induced toroidal eddy currents and both induced and conducted poloidal ''halo'' currents can produce design-limiting electromagnetic loads. While induction of toroidal and poloidal currents in passive structures is a well-understood phenomenon, the driving terms and scalings for poloidal currents flowing on open field lines during disruptions are less well established. A model of halo current evolution is presented in which the current is induced in the halo by decay of the plasma current and change in enclosed toroidal flux while being convected into the halo from the core by plasma motion. Fundamental physical processes and scalings are described in a simplified analytic version of the model. The peak axisymmetric halo current is found to depend on halo and core plasma characteristics during the current quench, including machine and plasma dimensions, resistivities, safety factor, and vertical stability growth rate. Two extreme regimes in poloidal halo current amplitude are identified depending on the minimum halo safety factor reached during the disruption. A 'type I' disruption is characterized by a minimum safety factor that remains relatively high (typically 2 - 3, comparable to the predisruption safety factor), and a relatively low poloidal halo current. A 'type II' disruption is characterized by a minimum safety factor comparable to unity and a relatively high poloidal halo current. Model predictions for these two regimes are found to agree well with halo current measurements from vertical displacement event disruptions in DIII-D [T. S. Taylor, K. H. Burrell, D. R. Baker, G. L. Jackson, R. J. La Haye, M. A. Mahdavi, R. Prater, T. C. Simonen, and A. D. Turnbull, open-quotes Results from the DIII-D Scientific Research Program,close quotes in Proceedings of the 17th IAEA Fusion Energy Conference, Yokohama, 1998, to be published in

  14. Impacts of weighting climate models for hydro-meteorological climate change studies

    Science.gov (United States)

    Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel

    2017-06-01

    Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.

  15. Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models

    Science.gov (United States)

    Pallant, Amy; Lee, Hee-Sun

    2015-04-01

    Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students ( N = 512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation tasks with three increasingly complex dynamic climate models. Each scientific argumentation task consisted of four parts: multiple-choice claim, openended explanation, five-point Likert scale uncertainty rating, and open-ended uncertainty rationale. We coded 1,294 scientific arguments in terms of a claim's consistency with current scientific consensus, whether explanations were model based or knowledge based and categorized the sources of uncertainty (personal vs. scientific). We used chi-square and ANOVA tests to identify significant patterns. Results indicate that (1) a majority of students incorporated models as evidence to support their claims, (2) most students used model output results shown on graphs to confirm their claim rather than to explain simulated molecular processes, (3) students' dependence on model results and their uncertainty rating diminished as the dynamic climate models became more and more complex, (4) some students' misconceptions interfered with observing and interpreting model results or simulated processes, and (5) students' uncertainty sources reflected more frequently on their assessment of personal knowledge or abilities related to the tasks than on their critical examination of scientific evidence resulting from models. These findings have implications for teaching and research related to the integration of scientific argumentation and modeling practices to address complex Earth systems.

  16. 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

  17. Eddy Current Model of Ball Lightning

    OpenAIRE

    Shelton, J. D.

    2011-01-01

    Eddy Current Model of Ball Lightning Calculations show that high-energy ball lightning may consist of a ball of plasma containing a large circular electric current arising as an eddy current generated by lightning. Synthetic ball lightning might serve as a method of plasma confinement for purposes of nuclear fusion. In this paper, three articles concerning ball lightning and the related phenomenon of large ball lightning are combined to provide insight into this rarely glimpsed occurrence.

  18. Modeling tokamak discharges with current holes

    International Nuclear Information System (INIS)

    Jensen, T.H.

    2002-01-01

    Tokamaks with current holes [T.S. Taylor, et al., Bull. Am. Phys. Soc. 43 (1998) 1783; N.C. Hawkes, et al., Phys. Rev. Lett. 87 (2001) 115001; T. Fujita, et al., Phys. Rev. Lett. 87 (2001) 245001] are interesting, in part, because discharges with true current holes do not consume poloidal flux. The modeling of this Letter suggests that under steady-state conditions their currents may be driven by radial flow of plasma resulting from neutral beam injection

  19. Lake heat content and stability variation due to climate change: coupled regional climate model (REMO-lake model (DYRESM analysis

    Directory of Open Access Journals (Sweden)

    Stefan Weinberger

    2014-02-01

    Full Text Available Climate change-derived higher air temperatures and the resulting increase in lake surface temperatures are known to influence the physical, biological and chemical processes of water bodies. By using hydrodynamic lake models coupled with regional climate models the potential future impact of a changing climate can be investigated. The present study hence elucidates limno-physical changes at the peri-Alpine, 83-m deep, currently dimictic Ammersee in southeastern Germany, both to underline the role of lakes as sentinels of climate change and provide a sound basis for further limnological investigations. This was realised by using water temperatures simulated with the hydrodynamic model DYRESM for the period 2041-2050, based on the results of the regional climate model REMO (IPCC A1B emission scenario. Modelling of future heat content resulted in a projected increase in the upper 3 m of the epilimnion from end of March to mid-November, whereas a decrease in future total heat content (January-December of the entire water column was simulated compared to that observed in 1997-2007. Lake thermal stability is projected to be higher in the period 2041-2050 than in 1985-2007. Stratification is expected to occur earlier and to last longer in the future than the pattern observed in 1985-2007. The future mean May-June depth of the thermocline is simulated to be situated above its past average vertical position, whereas an increase of mean thermocline depth is projected for the beginning of August to October. Furthermore, the mean May-October thickness of the metalimnion is simulated to increase. Additionally, we investigated the sensitivity of these limno-physical results to changes in the model parameter light extinction coefficient which determines how the solar radiation is absorbed by the lake water. The elucidation of physical changes at Ammersee by means of a regional climate model provides a sound basis on which to face the new challenges of lake

  20. 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.

  1. 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

  2. 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 ar...

  3. 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

  4. 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.

  5. 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

  6. Modeling of thermally stimulated depolarization current (TSDC ...

    Indian Academy of Sciences (India)

    Keywords. Dipole–dipole interaction; relaxation; modeling; TSDC; activation energy; PVC; ABS. Abstract. The study of thermally stimulated depolarization current (TSDC) using the dipole–dipole interaction model is described in this work. The dipole–dipole interactionmodel (DDIM) determines the TSDC peak successfully ...

  7. 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.

  8. 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.

  9. 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

  10. Dynamic-landscape metapopulation models predict complex response of wildlife populations to climate and landscape change

    Science.gov (United States)

    Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh

    2017-01-01

    The increasing need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. We used a comprehensive approach that combined recent advances in landscape and population modeling into dynamic-landscape metapopulation...

  11. 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.

  12. The Impact of Climate Change on Biodiversity in Nepal: Current Knowledge, Lacunae, and Opportunities

    Directory of Open Access Journals (Sweden)

    Aishwarya Bhattacharjee

    2017-10-01

    Full Text Available Nepal has an extreme altitudinal range from 60–8850 m with heterogeneous topography and distinct climatic zones. The country is considered a biodiversity hotspot, with nearly a quarter of the land area located in protected areas. Nepal and the surrounding Himalayan region are particularly vulnerable to climate change because of their abrupt ecological and climatic transitions. Tens of millions of people rely on the region’s ecosystem services, and observed and modeled warming trends predict increased climate extremes in the Himalayas. To study the ecological impacts of climate change in Nepal and inform adaptation planning, we review the literature on past, present, and predicted future climatic changes and their impacts on ecological diversity in Nepal. We found few studies focusing on organisms, while research on species and communities was more common. Most studies document or predict species range shifts and changes in community composition. Results of these few investigations highlight major lacunae in research regarding the effects of changing climate on species comprising the Himalayan biota. Further empirical work is needed at all levels of biological organization to build on information regarding direct ecological impacts of climatic changes in the region. Countries face an ever-increasing threat of climate change, and Nepal has strong physiographic, elevational, and climatic gradients that could provide a useful model for studying the effects of climate change on a mountainous, and highly biodiverse, area.

  13. Introducing an integrated climate change perspective in POPs modelling, monitoring and regulation

    International Nuclear Information System (INIS)

    Lamon, L.; Dalla Valle, M.; Critto, A.; Marcomini, A.

    2009-01-01

    This paper presents a review on the implications of climate change on the monitoring, modelling and regulation of persistent organic pollutants (POPs). Current research gaps are also identified and discussed. Long-term data sets are essential to identify relationships between climate fluctuations and changes in chemical species distribution. Reconstructing the influence of climatic changes on POPs environmental behaviour is very challenging in some local studies, and some insights can be obtained by the few available dated sediment cores or by studying POPs response to inter-annual climate fluctuations. Knowledge gaps and future projections can be studied by developing and applying various modelling tools, identifying compounds susceptibility to climate change, local and global effects, orienting international policies. Long-term monitoring strategies and modelling exercises taking into account climate change should be considered when devising new regulatory plans in chemicals management. - Climate change implications on POPs are addressed here with special attention to monitoring, modelling and regulation issues.

  14. High resolution experiments with the ALADIN-Climate regional climate model

    Science.gov (United States)

    Csima, G.

    2009-09-01

    The global climate models are able to describe the climate of the Earth at a rather coarse resolution providing realistic projections only for the synoptic scale characteristics of the climate. For this reason, they are insufficient for detailed regional or local scale estimations. However, impact studies and policy makers need simulations including all the effects caused by local features. Consequently, techniques for downscaling global climate model simulations - such as regional climate modelling - are essential. The ALADIN-Climate regional climate model (developed by Météo France on the basis of the internationally developed ALADIN modelling system) was adapted at the Hungarian Meteorological Service a few years ago. In the framework of the CECILIA project (www.cecilia-eu.org), the ALADIN-Climate regional climate model runs at high (10 km) horizontal resolution. Therefore, it is anticipated to give more realistic climate estimation for this century than either the global models or the lower resolution regional climate models. The ALADIN-Climate model was coupled to both ERA-40 re-analysis data and the ARPEGE/OPA global atmosphere-ocean general circulation model for the past - 1961-1990 - as the reference period. For the future time slices of 2021-2050 and 2071-2100, the lateral boundary conditions were provided by the same global model with the use of A1B SRES scenario. The results have been validated against different observational datasets for the past, and have been compared to the results of the ARPEGE-Climat global model in order to expose the added value of the regional climate model. The ALADIN-Climate model has also been evaluated for the future to give an estimation of climate change in the Carpathian Basin.

  15. Climate models with delay differential equations

    Science.gov (United States)

    Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M.

    2017-11-01

    A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

  16. Ensemble catchment hydrological modelling for climate change impact analysis

    Science.gov (United States)

    Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

    2014-05-01

    It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions

  17. 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...

  18. 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...

  19. 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.

  20. MASCOTTE: analytical model of eddy current signals

    International Nuclear Information System (INIS)

    Delsarte, G.; Levy, R.

    1992-01-01

    Tube examination is a major application of the eddy current technique in the nuclear and petrochemical industries. Such examination configurations being specially adapted to analytical modes, a physical model is developed on portable computers. It includes simple approximations made possible by the effective conditions of the examinations. The eddy current signal is described by an analytical formulation that takes into account the tube dimensions, the sensor conception, the physical characteristics of the defect and the examination parameters. Moreover, the model makes it possible to associate real signals and simulated signals

  1. 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

  2. OpenClimateGIS - A Web Service Providing Climate Model Data in Commonly Used Geospatial Formats

    Science.gov (United States)

    Erickson, T. A.; Koziol, B. W.; Rood, R. B.

    2011-12-01

    The goal of the OpenClimateGIS project is to make climate model datasets readily available in commonly used, modern geospatial formats used by GIS software, browser-based mapping tools, and virtual globes.The climate modeling community typically stores climate data in multidimensional gridded formats capable of efficiently storing large volumes of data (such as netCDF, grib) while the geospatial community typically uses flexible vector and raster formats that are capable of storing small volumes of data (relative to the multidimensional gridded formats). OpenClimateGIS seeks to address this difference in data formats by clipping climate data to user-specified vector geometries (i.e. areas of interest) and translating the gridded data on-the-fly into multiple vector formats. The OpenClimateGIS system does not store climate data archives locally, but rather works in conjunction with external climate archives that expose climate data via the OPeNDAP protocol. OpenClimateGIS provides a RESTful API web service for accessing climate data resources via HTTP, allowing a wide range of applications to access the climate data.The OpenClimateGIS system has been developed using open source development practices and the source code is publicly available. The project integrates libraries from several other open source projects (including Django, PostGIS, numpy, Shapely, and netcdf4-python).OpenClimateGIS development is supported by a grant from NOAA's Climate Program Office.

  3. Regional climate model performance and prediction of seasonal ...

    African Journals Online (AJOL)

    Knowledge about future climate provides valuable insights into how the challenges posed by climate change and variability can be addressed. ... Impacts Studies) in simulating rainfall and temperature over Uganda and also assess future impacts of climate when forced by an ensemble of two Global Climate Models (GCMs) ...

  4. 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.

  5. 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

  6. 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.

  7. Current definition and a generalized federbush model

    International Nuclear Information System (INIS)

    Singh, L.P.S.; Hagen, C.R.

    1978-01-01

    The Federbush model is studied, with particular attention being given to the definition of currents. Inasmuch as there is no a priori restriction of local gauge invariance, the currents in the interacting case can be defined more generally than in Q.E.D. It is found that two arbitrary parameters are thereby introduced into the theory. Lowest order perturbation calculations for the current correlation functions and the Fermion propagators indicate that the theory admits a whole class of solutions dependent upon these parameters with the closed solution of Federbush emerging as a special case. The theory is shown to be locally covariant, and a conserved energy--momentum tensor is displayed. One finds in addition that the generators of gauge transformations for the fields are conserved. Finally it is shown that the general theory yields the Federbush solution if suitable Thirring model type counterterms are added

  8. Models of Solar Irradiance Variations: Current Status

    Indian Academy of Sciences (India)

    2016-01-27

    Jan 27, 2016 ... Models of Solar Irradiance Variations: Current Status. Natalie A. ... Regular monitoring of solar irradiance has been carried out since 1978 to show that solar total and spectral irradiance varies at different time scales. Whereas ... Max Planck Institute for Solar System Research, Katlenburg-Lindau, Germany.

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

    Directory of Open Access Journals (Sweden)

    Y. Fan

    2017-06-01

    Full Text Available 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.

  10. Adaptive institutions? Peasant institutions and natural models facing climatic and economic changes in the Colombian Andes

    NARCIS (Netherlands)

    Feola, Giuseppe

    2017-01-01

    In the Colombian Andes, peasants have co-evolved with their environment for centuries, but it is uncertain whether traditional informal institutions and natural models are adapting to current and possibly unprecedented economic and climatic disturbances. This study investigated institutional

  11. Ocean currents modify the coupling between climate change and biogeographical shifts.

    Science.gov (United States)

    García Molinos, J; Burrows, M T; Poloczanska, E S

    2017-05-02

    Biogeographical shifts are a ubiquitous global response to climate change. However, observed shifts across taxa and geographical locations are highly variable and only partially attributable to climatic conditions. Such variable outcomes result from the interaction between local climatic changes and other abiotic and biotic factors operating across species ranges. Among them, external directional forces such as ocean and air currents influence the dispersal of nearly all marine and many terrestrial organisms. Here, using a global meta-dataset of observed range shifts of marine species, we show that incorporating directional agreement between flow and climate significantly increases the proportion of explained variance. We propose a simple metric that measures the degrees of directional agreement of ocean (or air) currents with thermal gradients and considers the effects of directional forces in predictions of climate-driven range shifts. Ocean flows are found to both facilitate and hinder shifts depending on their directional agreement with spatial gradients of temperature. Further, effects are shaped by the locations of shifts in the range (trailing, leading or centroid) and taxonomic identity of species. These results support the global effects of climatic changes on distribution shifts and stress the importance of framing climate expectations in reference to other non-climatic interacting factors.

  12. Silvicultural approaches to maintain forest health and productivity under current and future climates

    Science.gov (United States)

    Paul D. Anderson; Daniel J. Chmura

    2009-01-01

    Climate modeling based on a variety of scenarios for the Pacific Northwest suggests that over the next century temperatures may increase and that the abundance of summer precipitation may decline. Historically, climate changes at the century scale have been accompanied by adjustments in species population sizes and the composition of vegetation communities....

  13. 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

  14. 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.

  15. 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.

  16. A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus

    Directory of Open Access Journals (Sweden)

    Farzin Shabani

    2018-03-01

    Full Text Available Aedes albopictus, the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus? Our study used current Ae. albopictus distribution data to develop two independent models: (i regions with suitable non-climatic factors, and (ii regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF, together with six geographical conditioning factors (raster data layers, to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs, Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically

  17. 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.

  18. MECCA coordinated research program: analysis of climate models uncertainties used for climatic changes study

    International Nuclear Information System (INIS)

    Caneill, J.Y.; Hakkarinen, C.

    1992-01-01

    An international consortium, called MECCA, (Model Evaluation Consortium for Climate Assessment) has been created in 1991 by different partners including electric utilities, government and academic groups to make available to the international scientific community, a super-computer facility for climate evolution studies. The first phase of the program consists to assess uncertainties of climate model simulations in the framework of global climate change studies. Fourteen scientific projects have been accepted on an international basis in this first phase. The second phase of the program will consist in the evaluation of a set of long climate simulations realized with coupled ocean/atmosphere models, in order to study the transient aspects of climate changes and the associated uncertainties. A particular attention will be devoted, on the consequences of these assessments on climate impact studies, and on the regional aspects of climate changes

  19. Embedding complex hydrology in the climate system - Towards fully coupled climate-hydrology models

    DEFF Research Database (Denmark)

    Butts, Michael; Rasmussen, Søren H.; Ridler, Marc

    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....

  20. 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....

  1. 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.

  2. Megacity project: Liwa, climate and water balance modeling

    Science.gov (United States)

    Chamorro, Alejandro; Bardossy, Andras

    2010-05-01

    Megacity project: Liwa, climate and water balance modeling Peru uses to face different natural phenomena such as El Nino and La Nina phenomena and, like many cities around the word, the climate change effects. Its capital Lima, located in a region where annual precipitation is about 9 mm, has a high hydrological cycle vulnerability which is demonstrated in periods of drought and extreme drought. Accurate and reliable methodology is requiring studying the impact of all these problems in the water supply of Lima. A statistical downscaling scheme (Bardossy, 2002) will be used to generate time series of different local climate scenarios in order to be applied in hydrological models. The conceptual model HBV (Bergström, 1995) is used to simulate water discharges at certain points of the catchments under study, water balance groundwater and for the estimation of storage volume in different reservoirs. As already mentioned, El Nino and La Nina currents influence the hydrological cycle. Previous studies have shown that these phenomena have serious impacts in Peru. In order to quantify these impacts in the area of interest we have analyzed the magnitude of the precipitation in several stations in years in which El Nino occurred, and in years where El Nino did not occurred. The next step is to increase the temporal resolution by incorporating new data. Due to the high vulnerability of the water supply system in Lima, potential new water sources are required. In particular, the catchment of Mantaro (including existing lakes) on the other side of Los Andes Mountains provides potential new alternatives for adding water to the current system. Alternatives for water transportation include using existing long tunnels which connect Mantaro with Rimac, where the majority of the lakes are located. Finally, the global climate models simulations for the coming years, considering different scenarios, will be used as an indicator and to estimate water availability for human use (city

  3. Current algebra, statistical mechanics and quantum models

    Science.gov (United States)

    Vilela Mendes, R.

    2017-11-01

    Results obtained in the past for free boson systems at zero and nonzero temperatures are revisited to clarify the physical meaning of current algebra reducible functionals which are associated to systems with density fluctuations, leading to observable effects on phase transitions. To use current algebra as a tool for the formulation of quantum statistical mechanics amounts to the construction of unitary representations of diffeomorphism groups. Two mathematical equivalent procedures exist for this purpose. One searches for quasi-invariant measures on configuration spaces, the other for a cyclic vector in Hilbert space. Here, one argues that the second approach is closer to the physical intuition when modelling complex systems. An example of application of the current algebra methodology to the pairing phenomenon in two-dimensional fermion systems is discussed.

  4. Challenging the current climate change – migration nexus: exploring migrants’ perceptions of climate change in the hosting country

    Directory of Open Access Journals (Sweden)

    de Guttry, Corinna

    2016-06-01

    Full Text Available Along with the growing scientific and political concern on global warming, the relationship of climate and migration is framed as cause and consequence. Alarmist numbers of mass migration and related conflicts currently represent the main scientific narratives merging the issue of migration and climate change. This paper takes a different and explorative perspective: it suggests that scientific discourses on migration and climate change should be reframed by taking into consideration the diverse ‘knowledges’ offered by migrants. Employing an experimentalist approach, we aim at filling this gap in research and introduce an empirical perspective on climate framings among Italian and Chinese citizens in the local context of the city of Hamburg (Germany. Qualitatively analysing semi-structured interviews, the paper conveys an in-depth analysis of how Italian and Chinese migrants frame climate change and, furthermore, explores philosophical backgrounds informing them. We start with a theoretical and methodological outline on undertaking research with migrants and then turn to an empirical analysis in which we examine and discuss four prevailing categories found in the course of our investigation. The final section summarises the results and reflects upon the methodological and theoretical approach applied which refers to the relevance of migrants as active actors in local adaptation and mitigation processes of the hosting country.

  5. Basin-scale simulation of current and potential climate changed hydrologic conditions in the Lake Michigan Basin, United States

    Science.gov (United States)

    Christiansen, Daniel E.; Walker, John F.; Hunt, Randall J.

    2014-01-01

    The Great Lakes Restoration Initiative (GLRI) is the largest public investment in the Great Lakes in two decades. A task force of 11 Federal agencies developed an action plan to implement the initiative. The U.S. Department of the Interior was one of the 11 agencies that entered into an interagency agreement with the U.S. Environmental Protection Agency as part of the GLRI to complete scientific projects throughout the Great Lakes basin. The U.S. Geological Survey, a bureau within the Department of the Interior, is involved in the GLRI to provide scientific support to management decisions as well as measure progress of the Great Lakes basin restoration efforts. This report presents basin-scale simulated current and forecast climatic and hydrologic conditions in the Lake Michigan Basin. The forecasts were obtained by constructing and calibrating a Precipitation-Runoff Modeling System (PRMS) model of the Lake Michigan Basin; the PRMS model was calibrated using the parameter estimation and uncertainty analysis (PEST) software suite. The calibrated model was used to evaluate potential responses to climate change by using four simulated carbon emission scenarios from eight general circulation models released by the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3. Statistically downscaled datasets of these scenarios were used to project hydrologic response for the Lake Michigan Basin. In general, most of the observation sites in the Lake Michigan Basin indicated slight increases in annual streamflow in response to future climate change scenarios. Monthly streamflows indicated a general shift from the current (2014) winter-storage/snowmelt-pulse system to a system with a more equally distributed hydrograph throughout the year. Simulated soil moisture within the basin illustrates that conditions within the basin are also expected to change on a monthly timescale. One effect of increasing air temperature as a result of the changing

  6. 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

  7. Continental scale modelling of geomagnetically induced currents

    Directory of Open Access Journals (Sweden)

    Sakharov Yaroslav

    2012-09-01

    Full Text Available The EURISGIC project (European Risk from Geomagnetically Induced Currents aims at deriving statistics of geomagnetically induced currents (GIC in the European high-voltage power grids. Such a continent-wide system of more than 1500 substations and transmission lines requires updates of the previous modelling, which has dealt with national grids in fairly small geographic areas. We present here how GIC modelling can be conveniently performed on a spherical surface with minor changes in the previous technique. We derive the exact formulation to calculate geovoltages on the surface of a sphere and show its practical approximation in a fast vectorised form. Using the model of the old Finnish power grid and a much larger prototype model of European high-voltage power grids, we validate the new technique by comparing it to the old one. We also compare model results to measured data in the following cases: geoelectric field at the Nagycenk observatory, Hungary; GIC at a Russian transformer; GIC along the Finnish natural gas pipeline. In all cases, the new method works reasonably well.

  8. Probabilistic modeling of climate change impacts in permafrost regions

    Science.gov (United States)

    Anisimov, O.

    2009-04-01

    model reanalysis were used to characterize the baseline climate in Northern Eurasia and evaluate regional uncertainties resulting from the differences between the databases. Additional uncertainty in predictive calculations was associated with ensemble climatic projections for the mid-21st century. Another type of uncertainty is imposed by the small-scale stochastic variations of environmental parameters that govern the response of permafrost to climate variations. We simulated the effect it may have on the state of permafrost using the following approach. In different calculations snow depth varied in the range ± 50% from the mean climatological value; lower vegetation (moss) height varied between 5 and 10 cm, and organic layer thickness - in the range 5-20 cm. The range of variation for each of the environmental parameters has been selected using observational data. Performance of the stochastic model was evaluated using the two-step procedure. At the first step calculated for individual years statistics of the seasonal thaw depth was tested against observations at selected 1 x 1 km permafrost sites representing different bioclimatic conditions along the Russian Arctic coast. At each site the calculated ensemble was in good agreement with observations indicating that the model captures the component of small-scale variability associated with the spatial heterogeneity of environmental parameters. In the second test the model successfully reproduces the interannual variability of the ensemble-mean thaw depths at each site in the period 1990-2007. The ultimate result of our study is the set of predictive probabilistic permafrost maps for the Northern Eurasia. Aside from portraying the "average" or "typical" active-layer thickness for the current and projected for the mid-21st century climate, such maps depict the probability of thaw depth exceeding given thresholds within specified regions. Such information has important implication in cold region engineering and risk

  9. 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

  10. 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)

  11. Modeling Malaria Vector Distribution under Climate Change Scenarios in Kenya

    Science.gov (United States)

    Ngaina, J. N.

    2017-12-01

    Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control strategies for sustaining elimination and preventing reintroduction of malaria. However, in Kenya, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of future climate change on locally dominant Anopheles vectors including Anopheles gambiae, Anopheles arabiensis, Anopheles merus, Anopheles funestus, Anopheles pharoensis and Anopheles nili. Environmental data (Climate, Land cover and elevation) and primary empirical geo-located species-presence data were identified. The principle of maximum entropy (Maxent) was used to model the species' potential distribution area under paleoclimate, current and future climates. The Maxent model was highly accurate with a statistically significant AUC value. Simulation-based estimates suggest that the environmentally suitable area (ESA) for Anopheles gambiae, An. arabiensis, An. funestus and An. pharoensis would increase under all two scenarios for mid-century (2016-2045), but decrease for end century (2071-2100). An increase in ESA of An. Funestus was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios for mid-century. Our findings can be applied in various ways such as the identification of additional localities where Anopheles malaria vectors may already exist, but has not yet been detected and the recognition of localities where it is likely to spread to. Moreover, it will help guide future sampling location decisions, help with the planning of vector control suites nationally and encourage broader research inquiry into vector species niche modeling

  12. 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

  13. 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.

  14. 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.

  15. Understanding Hydroclimatic Extremes in Changing Monsoon Climates with Daily Bias Correction of CMIP5 Regional Climate Models over South Asia

    Science.gov (United States)

    Hasan, M. A.; Islam, A. S.; Akanda, A. S. S.

    2015-12-01

    The assessment of hydroclimatic and hydrometeorological extremes in changing climates has gathered special attention in the latest IPCC 5thAssessment Report (AR5). In monsoon regions such as South Asia, hydrologic modeling (i.e., stream flow assessment, water budget analysis, etc.) needs to incorporate such extremes to simulate retrospective and future scenarios. For information of past and future climate, Regional Climate Models (RCMs) are preferred over global models due to their higher resolution and dynamic downscaling capabilities. Although the models perform well in representing the mean climate, they still possess significant biases, especially in daily hydrometeorological extremes over monsoon regions. Therefore, modification and correction of RCM results while preserving the extremes are crucial for hydrologic modeling in changing monsoon climates such as in South Asia. In this context, we generate a gridded observed product that preserve the hydroclimatic and hydrometeorological extremes for the Ganges-Brahmaputra-Meghna (GBM) basin region in South Asia. A recent approach to bias correction is also proposed for correcting regional climate data in currently available future projections. The 30 year dataset (1971-2010) is used for comparing hydroclimatic and hydrometeorological extremes with APHRODITE and ERA-Interim Reanalysis products. The assessment has revealed that the new gridded data set provides much accurate maximum rainfall intensity, number of dry days, number of wet days and number of rainy days with greater than 500mm rainfall than any other available gridded data products. Using the gridded data sets, bias correctionis applied on CMIP5 multi-model historical datasets to evaluate RCM data performance over the region, which show great improvement in regional climate data for future hydrologic modeling scenarios and analyzing impacts of climate extremes.

  16. Advancing Climate Literacy through Investment in Science Education Faculty, and Future and Current Science Teachers: Providing Professional Learning, Instructional Materials, and a Model for Locally-Relevant and Culturally-Responsive Content

    Science.gov (United States)

    Halversen, C.; Apple, J. K.; McDonnell, J. D.; Weiss, E.

    2014-12-01

    The Next Generation Science Standards (NGSS) call for 5th grade students to "obtain and combine information about ways individual communities use science ideas to protect Earth's resources and environment". Achieving this, and other objectives in NGSS, will require changes in the educational system for both students and teachers. Teachers need access to high quality instructional materials and continuous professional learning opportunities starting in pre-service education. Students need highly engaging and authentic learning experiences focused on content that is strategically interwoven with science practices. Pre-service and early career teachers, even at the secondary level, often have relatively weak understandings of the complex Earth systems science required for understanding climate change and hold alternative ideas and naïve beliefs about the nature of science. These naïve understandings cause difficulties in portraying and teaching science, especially considering what is being called for in NGSS. The ACLIPSE program focuses on middle school pre-service science teachers and education faculty because: (1) the concepts that underlie climate change align well with the disciplinary core ideas and practices in NGSS for middle grades; and (2) middle school is a critical time for capturing students interest in science as student engagement by eighth grade is the most effective predictor of student pursuit of science in high school and college. Capturing student attention at this age is critical for recruitment to STEM careers and lifelong climate literacy. THE ACLIPSE program uses cutting edge research and technology in ocean observing systems to provide educators with new tools to engage students that will lead to deeper understanding of the interactions between the ocean and climate systems. Establishing authentic, meaningful connections between indigenous and place-based, and technological climate observations will help generate a more holistic perspective

  17. Evaluation of an ensemble of Arctic regional climate models

    DEFF Research Database (Denmark)

    Rinke, A.; Dethloff, K.; Cassano, J. J.

    2006-01-01

    Simulations of eight different regional climate models (RCMs) have been performed for the period September 1997-September 1998, which coincides with the Surface Heat Budget of the Arctic Ocean (SHEBA) project period. Each of the models employed approximately the same domain covering the western......, temperature, cloud cover, and long-/shortwave downward radiation between the individual model simulations are investigated. With this work, we quantify the scatter among the models and therefore the magnitude of disagreement and unreliability of current Arctic RCM simulations. Even with the relatively...... constrained experimental design we notice a considerable scatter among the different RCMs. We found the largest across-model scatter in the 2 m temperature over land, in the surface radiation fluxes, and in the cloud cover which implies a reduced confidence level for these variables....

  18. Toward an ultra-high resolution community climate system model for the BlueGene platform

    International Nuclear Information System (INIS)

    Dennis, John M; Jacob, Robert; Vertenstein, Mariana; Craig, Tony; Loy, Raymond

    2007-01-01

    Global climate models need to simulate several small, regional-scale processes which affect the global circulation in order to accurately simulate the climate. This is particularly important in the ocean where small scale features such as oceanic eddies are currently represented with adhoc parameterizations. There is also a need for higher resolution to provide climate predictions at small, regional scales. New high-performance computing platforms such as the IBM BlueGene can provide the necessary computational power to perform ultra-high resolution climate model integrations. We have begun to investigate the scaling of the individual components of the Community Climate System Model to prepare it for integrations on BlueGene and similar platforms. Our investigations show that it is possible to successfully utilize O(32K) processors. We describe the scalability of five models: the Parallel Ocean Program (POP), the Community Ice CodE (CICE), the Community Land Model (CLM), and the new CCSM sequential coupler (CPL7) which are components of the next generation Community Climate System Model (CCSM); as well as the High-Order Method Modeling Environment (HOMME) which is a dynamical core currently being evaluated within the Community Atmospheric Model. For our studies we concentrate on 1/10 0 resolution for CICE, POP, and CLM models and 1/4 0 resolution for HOMME. The ability to simulate high resolutions on the massively parallel petascale systems that will dominate high-performance computing for the foreseeable future is essential to the advancement of climate science

  19. Distributional aspects of emissions in climate change integrated assessment models

    International Nuclear Information System (INIS)

    Cantore, Nicola

    2011-01-01

    The recent failure of Copenhagen negotiations shows that concrete actions are needed to create the conditions for a consensus over global emission reduction policies. A wide coalition of countries in international climate change agreements could be facilitated by the perceived fairness of rich and poor countries of the abatement sharing at international level. In this paper I use two popular climate change integrated assessment models to investigate the path and decompose components and sources of future inequality in the emissions distribution. Results prove to be consistent with previous empirical studies and robust to model comparison and show that gaps in GDP across world regions will still play a crucial role in explaining different countries contributions to global warming. - Research highlights: → I implement a scenario analysis with two global climate change models. → I analyse inequality in the distribution of emissions. → I decompose emissions inequality components. → I find that GDP per capita is the main Kaya identity source of emissions inequality. → Current rich countries will mostly remain responsible for emissions inequality.

  20. 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

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

    International Nuclear Information System (INIS)

    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

  2. Prototype Mcs Parameterization for Global Climate Models

    Science.gov (United States)

    Moncrieff, M. W.

    2017-12-01

    Excellent progress has been made with observational, numerical and theoretical studies of MCS processes but the parameterization of those processes remain in a dire state and are missing from GCMs. The perceived complexity of the distribution, type, and intensity of organized precipitation systems has arguably daunted attention and stifled the development of adequate parameterizations. TRMM observations imply links between convective organization and large-scale meteorological features in the tropics and subtropics that are inadequately treated by GCMs. This calls for improved physical-dynamical treatment of organized convection to enable the next-generation of GCMs to reliably address a slew of challenges. The multiscale coherent structure parameterization (MCSP) paradigm is based on the fluid-dynamical concept of coherent structures in turbulent environments. The effects of vertical shear on MCS dynamics implemented as 2nd baroclinic convective heating and convective momentum transport is based on Lagrangian conservation principles, nonlinear dynamical models, and self-similarity. The prototype MCS parameterization, a minimalist proof-of-concept, is applied in the NCAR Community Climate Model, Version 5.5 (CAM 5.5). The MCSP generates convectively coupled tropical waves and large-scale precipitation features notably in the Indo-Pacific warm-pool and Maritime Continent region, a center-of-action for weather and climate variability around the globe.

  3. 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.

  4. 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/).

  5. Cross-validation of an employee safety climate model in Malaysia.

    Science.gov (United States)

    Bahari, Siti Fatimah; Clarke, Sharon

    2013-06-01

    Whilst substantial research has investigated the nature of safety climate, and its importance as a leading indicator of organisational safety, much of this research has been conducted with Western industrial samples. The current study focuses on the cross-validation of a safety climate model in the non-Western industrial context of Malaysian manufacturing. The first-order factorial validity of Cheyne et al.'s (1998) [Cheyne, A., Cox, S., Oliver, A., Tomas, J.M., 1998. Modelling safety climate in the prediction of levels of safety activity. Work and Stress, 12(3), 255-271] model was tested, using confirmatory factor analysis, in a Malaysian sample. Results showed that the model fit indices were below accepted levels, indicating that the original Cheyne et al. (1998) safety climate model was not supported. An alternative three-factor model was developed using exploratory factor analysis. Although these findings are not consistent with previously reported cross-validation studies, we argue that previous studies have focused on validation across Western samples, and that the current study demonstrates the need to take account of cultural factors in the development of safety climate models intended for use in non-Western contexts. The results have important implications for the transferability of existing safety climate models across cultures (for example, in global organisations) and highlight the need for future research to examine cross-cultural issues in relation to safety climate. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

  6. Climate, fishing, and fluctuations of sardine and anchovy in the California Current.

    Science.gov (United States)

    Lindegren, Martin; Checkley, David M; Rouyer, Tristan; MacCall, Alec D; Stenseth, Nils Chr

    2013-08-13

    Since the days of Elton, population cycles have challenged ecologists and resource managers. Although the underlying mechanisms remain debated, theory holds that both density-dependent and density-independent processes shape the dynamics. One striking example is the large-scale fluctuations of sardine and anchovy observed across the major upwelling areas of the world. Despite a long history of research, the causes of these fluctuations remain unresolved and heavily debated, with significant implications for fisheries management. We here model the underlying causes of these fluctuations, using the California Current Ecosystem as a case study, and show that the dynamics, accurately reproduced since A.D. 1661 onward, are explained by interacting density-dependent processes (i.e., through species-specific life-history traits) and climate forcing. Furthermore, we demonstrate how fishing modifies the dynamics and show that the sardine collapse of the 1950s was largely unavoidable given poor recruitment conditions. Our approach provides unique insight into the origin of sardine-anchovy fluctuations and a knowledge base for sustainable fisheries management in the California Current Ecosystem and beyond.

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we...... evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...

  8. 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.

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

    Science.gov (United States)

    Santini, Monia; di Paola, Arianna

    2015-12-01

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

  10. Modeling of Tsunami Currents in Harbors

    Science.gov (United States)

    Lynett, P. J.

    2010-12-01

    Extreme events, such as large wind waves and tsunamis, are well recognized as a damaging hazard to port and harbor facilities. Wind wave events, particularly those with long period spectral components or infragravity wave generation, can excite resonance inside harbors leading to both large vertical motions and strong currents. Tsunamis can cause great damage as well. The geometric amplification of these very long waves can create large vertical motions in the interior of a harbor. Additionally, if the tsunami is composed of a train of long waves, which it often is, resonance can be easily excited. These long wave motions create strong currents near the node locations of resonant motions, and when interacting with harbor structures such as breakwaters, can create intense turbulent rotational structures, typical in the form of large eddies or gyres. These gyres have tremendous transport potential, and have been observed to break mooring lines, and even cause ships to be trapped inside the rotation, moving helplessly with the flow until collision, grounding, or dissipation of the eddy (e.g. Okal et al., 2006). This presentation will introduce the traditional theory used to predict wave impacts on harbors, discussing both how these models are practically useful and in what types of situations require a more accurate tool. State-of-the-art numerical models will be introduced, with a focus on recent developments in Boussinesq-type modeling. The Boussinesq equations model can account the dispersive, turbulent and rotational flow properties frequently observed in nature. Also they have the ability to coupling currents and waves and can predict nonlinear wave propagation over uneven bottom from deep (or intermediate) water area to shallow water area. However, during the derivation of a 2D-horizontal equation set, some 3D flow features, such those driven by as the dispersive stresses and the effects of the unresolved small scale 3D turbulence, are excluded. Consequently

  11. Species distributions and climate change:current patterns and future scenarios for biodiversity

    DEFF Research Database (Denmark)

    Hof, Christian

    How does climate change affect biodiversity? - Answering this question is one of the most important tasks in current ecological research. Earth has been warming by 0.7°C during the last 100 years, and the consequences are already apparent in biotic systems. For example, species are responding...... by shifts of their distributional ranges, which affects the spatial patterns of species richness and turnover. Global temperatures are projected to rise by 1.8 - 4°C until the end of the century; hence climate change will most likely leave further imprints on species and ecosystems. This PhD thesis aims...... extinction, one might assume that most species may also be able to successfully cope with contemporary climate change. However, current ecosystems are heavily modified by humans. Among other factors, habitat destruction and fragmentation caused by anthropogenic land-use changes negatively affect species...

  12. 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

    2017-12-01

    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.

  13. 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.

  14. 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.

  15. Modeling the Earth: Climate on an Icosphere

    Science.gov (United States)

    Fouts, Stephanie; Cook, L. Jonathan

    The totally asymmetric simple exclusion process with Langmuir kinetics is a one-dimensional transport model used to study the motion of particles through a lattice. Its applications include systems in the fields of biology, climatology, mathematics, civil engineering, and physics. In our research, we examine the temporal dynamics through the power spectra, as well as the time-averaged particle distribution on the lattice via Monte Carlo simulations. We have applied our particle transport model to an icosahedron in an attempt to model Earth's changing climate. In our research, we examine the temporal dynamics of the particle distribution on the lattice, as they correspond to seasonal heat fluctuations in the polar and equatorial regions of the globe. Using Monte Carlos simulations, we alter the input parameters of the system to explore the resultant actions of the Earth-system model. Our findings include seasonal oscillations consistent with those seen in reality. We also built a mathematical framework for our model which, when solved numerically, matches the oscillations seen in our physical system.

  16. 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.

  17. 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

  18. Canadian RCM projected climate-change signal and its sensitivity to model errors

    Science.gov (United States)

    Sushama, L.; Laprise, R.; Caya, D.; Frigon, A.; Slivitzky, M.

    2006-12-01

    Climate change is commonly evaluated as the difference between simulated climates under future and current forcings, based on the assumption that systematic errors in the current-climate simulation do not affect the climate-change signal. In this paper, we investigate the Canadian Regional Climate Model (CRCM) projected climate changes in the climatological means and extremes of selected basin-scale surface fields and its sensitivity to model errors for Fraser, Mackenzie, Yukon, Nelson, Churchill and Mississippi basins, covering the major climate regions in North America, using current (1961-1990) and future climate simulations (2041-2070; A2 and IS92a scenarios) performed with two versions of CRCM.Assessment of errors in both model versions suggests the presence of nonnegligible biases in the surface fields, due primarily to the internal dynamics and physics of the regional model and to the errors in the driving data at the boundaries. In general, results demonstrate that, in spite of the errors in the two model versions, the simulated climate-change signals associated with the long-term monthly climatology of various surface water balance components (such as precipitation, evaporation, snow water equivalent (SWE), runoff and soil moisture) are consistent in sign, but differ in magnitude. The same is found for projected changes to the low-flow characteristics (frequency, timing and return levels) studied here. High-flow characteristics, particularly the seasonal distribution and return levels, appear to be more sensitive to the model version.CRCM climate-change projections indicate an increase in the average annual precipitation for all basins except Mississippi, while annual runoff increases in Fraser, Mackenzie and Yukon basins. A decrease in runoff is projected for Mississippi. A significant decrease in snow cover is projected for all basins, with maximum decrease in Fraser. Significant changes are also noted in the frequency, timing and return levels for low

  19. 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.

  20. 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).

  1. The Impact of ARM on Climate Modeling. Chapter 26

    Science.gov (United States)

    Randall, David A.; Del Genio, Anthony D.; Donner, Leo J.; Collins, William D.; Klein, Stephen A.

    2016-01-01

    Climate models are among humanity's most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability, and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of the Earth down to one hundred kilometers or smaller, and implicitly include the effects of processes on even smaller scales down to a micron or so. The atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM). In an AGCM, calculations are done on a three-dimensional grid, which in some of today's climate models consists of several million grid cells. For each grid cell, about a dozen variables are time-stepped as the model integrates forward from its initial conditions. These so-called prognostic variables have special importance because they are the only things that a model remembers from one time step to the next; everything else is recreated on each time step by starting from the prognostic variables and the boundary conditions. The prognostic variables typically include information about the mass of dry air, the temperature, the wind components, water vapor, various condensed-water species, and at least a few chemical species such as ozone. A good way to understand how climate models work is to consider the lengthy and complex process used to develop one. Lets imagine that a new AGCM is to be created, starting from a blank piece of paper. The model may be intended for a particular class of applications, e.g., high-resolution simulations on time scales of a few decades. Before a single line of code is written, the conceptual foundation of the model must be designed through a creative

  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. Examination of Satellite and Model Reanalysis Precipitation with Climate Oscillations

    Science.gov (United States)

    Donato, T. F.; Houser, P. R.

    2016-12-01

    The purpose of this study is to examine the efficacy of satellite and model reanalysis precipitation with climate oscillations. Specifically, we examine and compare the relationship between the Global Precipitation Climate Project (GPCP) with Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2) in regards to four climate indices: The North Atlantic Oscillation, Southern Oscillation Index, the Southern Annular Mode and Solar Activity. This analysis covers a 35-year observation period from 1980 through 2015. We ask two questions: How is global and regional precipitation changing over the observation period, and how are global and regional variations in precipitation related to global climate variation? We explore and compare global and regional precipitation trends between the two data sets. To do this, we constructed a total of 56 Regions of Interest (ROI). Nineteen of the ROIs were focused on geographic regions including continents, ocean basins, and marginal seas. Twelve ROIs examine hemispheric processes. The remaining 26 regions are derived from spatial-temporal classification analysis of GPCP data over a ten-year period (2001-2010). These regions include the primary wet and dry monsoon regions, regions influenced by western boundary currents, and orography. We investigate and interpret the monthly, seasonal and yearly global and regional response to the selected climate indices. Initial results indicate that no correlation exist between the GPCP data and Merra-2 data. Preliminary qualitative assessment between GCPC and solar activity suggest a possible relationship in intra-annual variability. This work is performed under the State of the Global Water and Energy Cycle (SWEC) project, a NASA-sponsored program in support of NASA's Energy and Water cycle Study (NEWS).

  4. On the construction of a regional atmospheric climate model

    DEFF Research Database (Denmark)

    Christensen, J. H.; Van Meijgaard, E.

    1992-01-01

    A Regional Atmospheric Climate Model which combines the physical parameterization package of the General Circulation or Climate Model (ECHAM) used at the Max Planck Institute for Meteorology in Hamburg, and the dynamics package of the Nordic - Dutch - Irish Limited Area Model (HIRLAM), has been...

  5. 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.

  6. 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.

  7. ARCAS (ACACIA Regional Climate-data Access System) -- a Web Access System for Climate Model Data Access, Visualization and Comparison

    Science.gov (United States)

    Hakkarinen, C.; Brown, D.; Callahan, J.; hankin, S.; de Koningh, M.; Middleton-Link, D.; Wigley, T.

    2001-05-01

    A Web-based access system to climate model output data sets for intercomparison and analysis has been produced, using the NOAA-PMEL developed Live Access Server software as host server and Ferret as the data serving and visualization engine. Called ARCAS ("ACACIA Regional Climate-data Access System"), and publicly accessible at http://dataserver.ucar.edu/arcas, the site currently serves climate model outputs from runs of the NCAR Climate System Model for the 21st century, for Business as Usual and Stabilization of Greenhouse Gas Emission scenarios. Users can select, download, and graphically display single variables or comparisons of two variables from either or both of the CSM model runs, averaged for monthly, seasonal, or annual time resolutions. The time length of the averaging period, and the geographical domain for download and display, are fully selectable by the user. A variety of arithmetic operations on the data variables can be computed "on-the-fly", as defined by the user. Expansions of the user-selectable options for defining analysis options, and for accessing other DOD-compatible ("Distributed Ocean Data System-compatible") data sets, residing at locations other than the NCAR hardware server on which ARCAS operates, are planned for this year. These expansions are designed to allow users quick and easy-to-operate web-based access to the largest possible selection of climate model output data sets available throughout the world.

  8. Developing climatic scenarios for pesticide fate modelling in Europe

    International Nuclear Information System (INIS)

    Blenkinsop, S.; Fowler, H.J.; Dubus, I.G.; Nolan, B.T.; Hollis, J.M.

    2008-01-01

    A climatic classification for Europe suitable for pesticide fate modelling was constructed using a 3-stage process involving the identification of key climatic variables, the extraction of the dominant modes of spatial variability in those variables and the use of k-means clustering to identify regions with similar climates. The procedure identified 16 coherent zones that reflect the variability of climate across Europe whilst maintaining a manageable number of zones for subsequent modelling studies. An analysis of basic climatic parameters for each zone demonstrates the success of the scheme in identifying distinct climatic regions. Objective criteria were used to identify one representative 26-year daily meteorological series from a European dataset for each zone. The representativeness of each series was then verified against the zonal classifications. These new FOOTPRINT climate zones provide a state-of-the-art objective classification of European climate complete with representative daily data that are suitable for use in pesticide fate modelling. - The FOOTPRINT climatic zones provide an objective climatic classification and daily climate series that may be used for the modelling of pesticide fate across Europe

  9. 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

  10. 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.

  11. 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.

  12. Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods

    Science.gov (United States)

    Teutschbein, Claudia; Seibert, Jan

    2012-08-01

    SummaryDespite the increasing use of regional climate model (RCM) simulations in hydrological climate-change impact studies, their application is challenging due to the risk of considerable biases. To deal with these biases, several bias correction methods have been developed recently, ranging from simple scaling to rather sophisticated approaches. This paper provides a review of available bias correction methods and demonstrates how they can be used to correct for deviations in an ensemble of 11 different RCM-simulated temperature and precipitation series. The performance of all methods was assessed in several ways: At first, differently corrected RCM data was compared to observed climate data. The second evaluation was based on the combined influence of corrected RCM-simulated temperature and precipitation on hydrological simulations of monthly mean streamflow as well as spring and autumn flood peaks for five catchments in Sweden under current (1961-1990) climate conditions. Finally, the impact on hydrological simulations based on projected future (2021-2050) climate conditions was compared for the different bias correction methods. Improvement of uncorrected RCM climate variables was achieved with all bias correction approaches. While all methods were able to correct the mean values, there were clear differences in their ability to correct other statistical properties such as standard deviation or percentiles. Simulated streamflow characteristics were sensitive to the quality of driving input data: Simulations driven with bias-corrected RCM variables fitted observed values better than simulations forced with uncorrected RCM climate variables and had more narrow variability bounds.

  13. 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).

  14. 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

  15. 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.

  16. Evaluation of the new EMAC-SWIFT chemistry climate model

    Science.gov (United States)

    Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Rex, Markus

    2016-04-01

    It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Including atmospheric ozone chemistry into climate simulations is usually done by prescribing a climatological ozone field, by including a fast linear ozone scheme into the model or by using a climate model with complex interactive chemistry. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. Although interactive chemistry provides a realistic representation of atmospheric chemistry such model simulations are computationally very expensive and hence not suitable for ensemble simulations or simulations with multiple climate change scenarios. A new approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has recently been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. Here, we show first results of EMAC-SWIFT simulations and validate these against EMAC simulations using the complex interactive chemistry scheme MECCA, and against observations.

  17. 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.

  18. [Lake eutrophication modeling in considering climatic factors change: a review].

    Science.gov (United States)

    Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

    2012-11-01

    Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

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

    Directory of Open Access Journals (Sweden)

    S. Hagemann

    2013-05-01

    Full Text Available 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 models (eight were used to systematically assess the hydrological response to climate change and project the future state of global water resources. This multi-model ensemble allows us to investigate how the hydrology models contribute to the uncertainty in projected hydrological changes compared to the climate models. Due to their systematic biases, GCM outputs cannot be used directly in hydrological impact studies, so a statistical bias correction has been applied. The results show a large spread in projected changes in water resources within the climate–hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change, and that the spread resulting from the choice of the hydrology model is larger than the spread originating from the climate models over many areas. But there are also areas showing a robust change signal, such as at high latitudes and in some midlatitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence in this ensemble mean signal. In many catchments an increase of available water resources is expected but there are some severe decreases in Central and Southern Europe, the Middle East, the Mississippi River basin, southern Africa, southern China and south-eastern Australia.

  20. On the statistical comparison of climate model output and climate data

    International Nuclear Information System (INIS)

    Solow, A.R.

    1991-01-01

    Some broad issues arising in the statistical comparison of the output of climate models with the corresponding climate data are reviewed. Particular attention is paid to the question of detecting climate change. The purpose of this paper is to review some statistical approaches to the comparison of the output of climate models with climate data. There are many statistical issues arising in such a comparison. The author will focus on some of the broader issues, although some specific methodological questions will arise along the way. One important potential application of the approaches discussed in this paper is the detection of climate change. Although much of the discussion will be fairly general, he will try to point out the appropriate connections to the detection question. 9 refs

  1. On the statistical comparison of climate model output and climate data

    International Nuclear Information System (INIS)

    Solow, A.R.

    1990-01-01

    Some broad issues arising in the statistical comparison of the output of climate models with the corresponding climate data are reviewed. Particular attention is paid to the question of detecting climate change. The purpose of this paper is to review some statistical approaches to the comparison of the output of climate models with climate data. There are many statistical issues arising in such a comparison. The author will focus on some of the broader issues, although some specific methodological questions will arise along the way. One important potential application of the approaches discussed in this paper is the detection of climate change. Although much of the discussion will be fairly general, he will try to point out the appropriate connections to the detection question

  2. 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.

  3. 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

  4. Estimation of climate change impact on water resources by using Bilan water balance model

    International Nuclear Information System (INIS)

    Horacek, Stanislav; Kasparek, Ladislav; Novicky, Oldrich

    2008-01-01

    Modelling of water balance under changed climate conditions has been carried out by T. G. Masaryk Water Research Institute in Prague for basins in the Czech Republic since 1990. The studies presently use climate change scenarios derived from simulations by regional climate models. Climate change scenarios are reflected in meteorological time-series for given catchment and subsequently used for simulation of water cycle components by using Bilan water balance model. Results of Bilan model simulations for input meteorological series not affected and affected by climate change scenarios give information for assessing the climate change impacts on output series of the model. The results of the studies generally show that annual runoff could largely decrease. The increased winter temperature could cause an increase in winter flows and a decrease in snow storage, and consequently, spring and summer outflows will decrease significantly, even to their current minimum values. The groundwater storage and base flow could also be highly reduced. The described method has been used in a number of research projects and operational applications. Its typical application is aimed at assessing possible impacts of climate change on surface water resources, whose availability can subsequently be analysed by using water management models of the individual basins. The Bilan model, particularly in combination with Modflow model, can also suitably be used for simulation and assessments of groundwater resources.

  5. 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.

  6. Current temporal trends in moth abundance are counter to predicted effects of climate change in an assemblage of subarctic forest moths.

    Science.gov (United States)

    Hunter, Mark D; Kozlov, Mikhail V; Itämies, Juhani; Pulliainen, Erkki; Bäck, Jaana; Kyrö, Ella-Maria; Niemelä, Pekka

    2014-06-01

    Changes in climate are influencing the distribution and abundance of the world's biota, with significant consequences for biological diversity and ecosystem processes. Recent work has raised concern that populations of moths and butterflies (Lepidoptera) may be particularly susceptible to population declines under environmental change. Moreover, effects of climate change may be especially pronounced in high latitude ecosystems. Here, we examine population dynamics in an assemblage of subarctic forest moths in Finnish Lapland to assess current trajectories of population change. Moth counts were made continuously over a period of 32 years using light traps. From 456 species recorded, 80 were sufficiently abundant for detailed analyses of their population dynamics. Climate records indicated rapid increases in temperature and winter precipitation at our study site during the sampling period. However, 90% of moth populations were stable (57%) or increasing (33%) over the same period of study. Nonetheless, current population trends do not appear to reflect positive responses to climate change. Rather, time-series models illustrated that the per capita rates of change of moth species were more frequently associated negatively than positively with climate change variables, even as their populations were increasing. For example, the per capita rates of change of 35% of microlepidoptera were associated negatively with climate change variables. Moth life-history traits were not generally strong predictors of current population change or associations with climate change variables. However, 60% of moth species that fed as larvae on resources other than living vascular plants (e.g. litter, lichen, mosses) were associated negatively with climate change variables in time-series models, suggesting that such species may be particularly vulnerable to climate change. Overall, populations of subarctic forest moths in Finland are performing better than expected, and their populations

  7. Ecological models and pesticide risk assessment: current modeling practice.

    Science.gov (United States)

    Schmolke, Amelie; Thorbek, Pernille; Chapman, Peter; Grimm, Volker

    2010-04-01

    Ecological risk assessments of pesticides usually focus on risk at the level of individuals, and are carried out by comparing exposure and toxicological endpoints. However, in most cases the protection goal is populations rather than individuals. On the population level, effects of pesticides depend not only on exposure and toxicity, but also on factors such as life history characteristics, population structure, timing of application, presence of refuges in time and space, and landscape structure. Ecological models can integrate such factors and have the potential to become important tools for the prediction of population-level effects of exposure to pesticides, thus allowing extrapolations, for example, from laboratory to field. Indeed, a broad range of ecological models have been applied to chemical risk assessment in the scientific literature, but so far such models have only rarely been used to support regulatory risk assessments of pesticides. To better understand the reasons for this situation, the current modeling practice in this field was assessed in the present study. The scientific literature was searched for relevant models and assessed according to nine characteristics: model type, model complexity, toxicity measure, exposure pattern, other factors, taxonomic group, risk assessment endpoint, parameterization, and model evaluation. The present study found that, although most models were of a high scientific standard, many of them would need modification before they are suitable for regulatory risk assessments. The main shortcomings of currently available models in the context of regulatory pesticide risk assessments were identified. When ecological models are applied to regulatory risk assessments, we recommend reviewing these models according to the nine characteristics evaluated here. (c) 2010 SETAC.

  8. 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

  9. Historical and idealized climate model experiments: an EMIC intercomparison

    DEFF Research Database (Denmark)

    Eby, M.; Weaver, A. J.; Alexander, K.

    2012-01-01

    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 c...

  10. 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...

  11. Evaluating the performance and utility of regional climate models

    DEFF Research Database (Denmark)

    Christensen, Jens H.; Carter, Timothy R.; Rummukainen, Markku

    2007-01-01

    This special issue of Climatic Change contains a series of research articles documenting co-ordinated work carried out within a 3-year European Union project 'Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects' (PRUDENCE). The main objective...... weather events and (7) implications of the results for policy. A paper summarising the related MICE (Modelling the Impact of Climate Extremes) project is also included. The second part of the issue contains 12 articles that focus in more detail on some of the themes summarised in the overarching papers....... The PRUDENCE results represent the first comprehensive, continental-scale intercomparison and evaluation of high resolution climate models and their applications, bringing together climate modelling, impact research and social sciences expertise on climate change....

  12. The influence of current and future climate on the spatial distribution of coccidioidomycosis in the southwestern United States

    Science.gov (United States)

    Gorris, M. E.; Hoffman, F. M.; Zender, C. S.; Treseder, K. K.; Randerson, J. T.

    2017-12-01

    Coccidioidomycosis, otherwise known as valley fever, is an infectious fungal disease currently endemic to the southwestern U.S. The magnitude, spatial distribution, and seasonality of valley fever incidence is shaped by variations in regional climate. As such, climate change may cause new communities to become at risk for contracting this disease. Humans contract valley fever by inhaling fungal spores of the genus Coccidioides. Coccidioides grow in the soil as a mycelium, and when stressed, autolyze into spores 2-5 µm in length. Spores can become airborne from any natural or anthropogenic soil disturbance, which can be exacerbated by dry soil conditions. Understanding the relationship between climate and valley fever incidence is critical for future disease risk management. We explored several multivariate techniques to create a predictive model of county-level valley fever incidence throughout the southwestern U.S., including Arizona, California, New Mexico, Nevada, and Utah. We incorporated surface air temperature, precipitation, soil moisture, surface dust concentrations, leaf area index, and the amount of agricultural land, all of which influence valley fever incidence. A log-linear regression model that incorporated surface air temperature, soil moisture, surface dust concentration, and the amount of agricultural land explained 34% of the county-level variance in annual average valley fever incidence. We used this model to predict valley fever incidence for the Representative Concentration Pathway 8.5 using simulation output from the Community Earth System Model. In our analysis, we describe how regional hotspots of valley fever incidence may shift with sustained warming and drying in the southwestern U.S. Our predictive model of valley fever incidence may help mitigate future health impacts of valley fever by informing health officials and policy makers of the climate conditions suitable for disease outbreak.

  13. 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.

  14. Global Climate Model Scenarios for Precipitation in North America

    Science.gov (United States)

    Ahlfeld, D.

    2005-12-01

    Global and regional climate models are valuable tools for assessing the impacts of alternate greenhouse emission scenarios on future climate. In recent years, the number of models available has increased and the sophistication of these models has generally improved. Recently, the Intergovernmental Panel on Climate Change has made model output from a range of global climate models available through the Program for Climate Model Diagnosis and Intercomparison at Lawrence Livermore National Laboratory. A comparison is made between observed and predicted precipitation from 18 global climate models for the period 1979 to 2000 in three regions of North America using monthly averaged output of the 20C3M experiment (climate of the 20th century) and the CPC Merged Analysis of Precipitation (CMAP) data. Precipitation averaged over monthly, seasonal and annual time periods is considered. The three regions encompass western, central and eastern North America excluding Alaska, northern Canada and Latin America. Most models compare well with observed precipitation for the central and eastern regions at all time scales. Discrepancies between model results and observed precipitation are generally smallest in summer and fall seasons. For the western region, models are less successful in comparison to observed precipitation. A subset of models, those deemed to be most successful at reproducing observed precipitation, are used to analyze the impact of various greenhouse gas emission scenarios (including the Commit and SRESB1 experiments) on precipitation in the mid- and late-21st century.

  15. The Climate-Agriculture-Modeling and Decision Tool (CAMDT) for Climate Risk Management in Agriculture

    Science.gov (United States)

    Ines, A. V. M.; Han, E.; Baethgen, W.

    2017-12-01

    Advances in seasonal climate forecasts (SCFs) during the past decades have brought great potential to improve agricultural climate risk managements associated with inter-annual climate variability. In spite of popular uses of crop simulation models in addressing climate risk problems, the models cannot readily take seasonal climate predictions issued in the format of tercile probabilities of most likely rainfall categories (i.e, below-, near- and above-normal). When a skillful SCF is linked with the crop simulation models, the informative climate information can be further translated into actionable agronomic terms and thus better support strategic and tactical decisions. In other words, crop modeling connected with a given SCF allows to simulate "what-if" scenarios with different crop choices or management practices and better inform the decision makers. In this paper, we present a decision support tool, called CAMDT (Climate Agriculture Modeling and Decision Tool), which seamlessly integrates probabilistic SCFs to DSSAT-CSM-Rice model to guide decision-makers in adopting appropriate crop and agricultural water management practices for given climatic conditions. The CAMDT has a functionality to disaggregate a probabilistic SCF into daily weather realizations (either a parametric or non-parametric disaggregation method) and to run DSSAT-CSM-Rice with the disaggregated weather realizations. The convenient graphical user-interface allows easy implementation of several "what-if" scenarios for non-technical users and visualize the results of the scenario runs. In addition, the CAMDT also translates crop model outputs to economic terms once the user provides expected crop price and cost. The CAMDT is a practical tool for real-world applications, specifically for agricultural climate risk management in the Bicol region, Philippines, having a great flexibility for being adapted to other crops or regions in the world. CAMDT GitHub: https://github.com/Agro-Climate/CAMDT

  16. Atlas : A library for numerical weather prediction and climate modelling

    Science.gov (United States)

    Deconinck, Willem; Bauer, Peter; Diamantakis, Michail; Hamrud, Mats; Kühnlein, Christian; Maciel, Pedro; Mengaldo, Gianmarco; Quintino, Tiago; Raoult, Baudouin; Smolarkiewicz, Piotr K.; Wedi, Nils P.

    2017-11-01

    The algorithms underlying numerical weather prediction (NWP) and climate models that have been developed in the past few decades face an increasing challenge caused by the paradigm shift imposed by hardware vendors towards more energy-efficient devices. In order to provide a sustainable path to exascale High Performance Computing (HPC), applications become increasingly restricted by energy consumption. As a result, the emerging diverse and complex hardware solutions have a large impact on the programming models traditionally used in NWP software, triggering a rethink of design choices for future massively parallel software frameworks. In this paper, we present Atlas, a new software library that is currently being developed at the European Centre for Medium-Range Weather Forecasts (ECMWF), with the scope of handling data structures required for NWP applications in a flexible and massively parallel way. Atlas provides a versatile framework for the future development of efficient NWP and climate applications on emerging HPC architectures. The applications range from full Earth system models, to specific tools required for post-processing weather forecast products. The Atlas library thus constitutes a step towards affordable exascale high-performance simulations by providing the necessary abstractions that facilitate the application in heterogeneous HPC environments by promoting the co-design of NWP algorithms with the underlying hardware.

  17. 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

  18. 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.

  19. Why inputs matter: Selection of climatic variables for species distribution modelling in the Himalayan region

    Science.gov (United States)

    Bobrowski, Maria; Schickhoff, Udo

    2017-04-01

    Betula utilis is a major constituent of alpine treeline ecotones in the western and central Himalayan region. The objective of this study is to provide first time analysis of the potential distribution of Betula utilis in the subalpine and alpine belts of the Himalayan region using species distribution modelling. Using Generalized Linear Models (GLM) we aim at examining climatic factors controlling the species distribution under current climate conditions. Furthermore we evaluate the prediction ability of climate data derived from different statistical methods. GLMs were created using least correlated bioclimatic variables derived from two different climate models: 1) interpolated climate data (i.e. Worldclim, Hijmans et al., 2005) and 2) quasi-mechanistical statistical downscaling (i.e. Chelsa; Karger et al., 2016). Model accuracy was evaluated by the ability to predict the potential species distribution range. We found that models based on variables of Chelsa climate data had higher predictive power, whereas models using Worldclim climate data consistently overpredicted the potential suitable habitat for Betula utilis. Although climatic variables of Worldclim are widely used in modelling species distribution, our results suggest to treat them with caution when remote regions like the Himalayan mountains are in focus. Unmindful usage of climatic variables for species distribution models potentially cause misleading projections and may lead to wrong implications and recommendations for nature conservation. References: Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978. Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N., Linder, H.P. & Kessler, M. (2016) Climatologies at high resolution for the earth land surface areas. arXiv:1607.00217 [physics].

  20. Deriving user-informed climate information from climate model ensemble results

    Directory of Open Access Journals (Sweden)

    H. Huebener

    2017-07-01

    Full Text Available Communication between providers and users of climate model simulation results still needs to be improved. In the German regional climate modeling project ReKliEs-De a midterm user workshop was conducted to allow the intended users of the project results to assess the preliminary results and to streamline the final project results to their needs. The user feedback highlighted, in particular, the still considerable gap between climate research output and user-tailored input for climate impact research. Two major requests from the user community addressed the selection of sub-ensembles and some condensed, easy to understand information on the strengths and weaknesses of the climate models involved in the project.

  1. The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

    Science.gov (United States)

    Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J

    2013-10-28

    Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.

  2. Current and future climate variability associated with wintertime precipitation in alpine Australia

    Science.gov (United States)

    Fiddes, Sonya Louise; Pezza, Alexandre Bernardes

    2015-05-01

    The Australian Alps, located in the southeast corner of the continent, are home to important ecologies and industries, including water supply, hydroelectricity and ski resorts. Sharp topography and prevailing westerly winds generate a unique microclimate with cool temperatures and abundant precipitation and is crucial to much of greater southeastern Australia's water supply. Here we study the western, high and eastern slopes separately, exploring the global climate drivers associated with wintertime precipitation variability. The results show that while total precipitation is significantly declining on the western and high slopes, the total rain is not significantly changing on the eastern side. These differing trends are thought be a result of the changing nature of the westerly storm track and the subtropical ridge. Interestingly, the west/high wintertime rainfall decline is seen primarily as a reduction in the intensity of events, as the number of rainfall days per season has remained relatively constant throughout the analysis. The synoptic patterns associated with extreme precipitation are identified and shown to be well correlated with the total seasonal precipitation, suggesting a great importance of the extreme weather signatures in modulating the longer term climate. This correlation is used to calculate a number of climate indices relying on dynamical indicators such as pressure and temperature gradients, helping simulate the rainfall variability within the area. By exploring contrasting Climate Model Intercomparison Project 3 models from the Commonwealth Scientific and Industry Research Organization's Representative Climate Futures Framework, we estimate using indices of the circulation dynamics that the west/high wintertime rainfall trend will continue to decline whilst rainfall in the eastern region will remain relatively stable. This result adds new light into future precipitation trends for the area, given the intrinsic difficulty of climate models

  3. Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change

    Science.gov (United States)

    Anantha M. Prasad; Judith D. Gardiner; Louis R. Iverson; Stephen N. Matthews; Matthew. Peters

    2013-01-01

    Climate change impacts tree species differentially by exerting unique pressures and altering their suitable habitats. We previously predicted these changes in suitable habitat for current and future climates using a species habitat model (DISTRIB) in the eastern United States. Based on the accuracy of the model, the species assemblages should eventually reflect the new...

  4. The effect of climate change on urban drainage: an evaluation based on regional climate model simulation.

    Science.gov (United States)

    Grum, M; Jørgensen, A T; Johansen, R M; Linde, J J

    2006-01-01

    That we are in a period of extraordinary rates of climate change is today evident. These climate changes are likely to impact local weather conditions with direct impacts on precipitation patterns and urban drainage. In recent years several studies have focused on revealing the nature, extent and consequences of climate change on urban drainage and urban runoff pollution issues. This study uses predictions from a regional climate model to look at the effects of climate change on extreme precipitation events. Results are presented in terms of point rainfall extremes. The analysis involves three steps: Firstly, hourly rainfall intensities from 16 point rain gauges are averaged to create a rain gauge equivalent intensity for a 25 x 25 km square corresponding to one grid cell in the climate model. Secondly, the differences between present and future in the climate model is used to project the hourly extreme statistics of the rain gauge surface into the future. Thirdly, the future extremes of the square surface area are downscaled to give point rainfall extremes of the future. The results and conclusions rely heavily on the regional model's suitability in describing extremes at timescales relevant to urban drainage. However, in spite of these uncertainties, and others raised in the discussion, the tendency is clear: extreme precipitation events effecting urban drainage and causing flooding will become more frequent as a result of climate change.

  5. Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

    Czech Academy of Sciences Publication Activity Database

    Gaál, Ľ.; Beranová, R.; Hlavčová, K.; Kyselý, Jan

    2014-01-01

    Roč. 2014, č. 943487 (2014), s. 1-14 ISSN 1687-9309 Institutional support: RVO:67179843 ; RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: EH - Ecology, Behaviour Impact factor: 0.946, year: 2014

  6. 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

    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......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...

  7. 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.

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

    Science.gov (United States)

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

    2018-01-01

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

  10. Climate driven crop planting date in the ACME Land Model (ALM): Impacts on productivity and yield

    Science.gov (United States)

    Drewniak, B.

    2017-12-01

    Climate is one of the key drivers of crop suitability and productivity in a region. The influence of climate and weather on the growing season determine the amount of time crops spend in each growth phase, which in turn impacts productivity and, more importantly, yields. Planting date can have a strong influence on yields with earlier planting generally resulting in higher yields, a sensitivity that is also present in some crop models. Furthermore, planting date is already changing and may continue, especially if longer growing seasons caused by future climate change drive early (or late) planting decisions. Crop models need an accurate method to predict plant date to allow these models to: 1) capture changes in crop management to adapt to climate change, 2) accurately model the timing of crop phenology, and 3) improve crop simulated influences on carbon, nutrient, energy, and water cycles. Previous studies have used climate as a predictor for planting date. Climate as a plant date predictor has more advantages than fixed plant dates. For example, crop expansion and other changes in land use (e.g., due to changing temperature conditions), can be accommodated without additional model inputs. As such, a new methodology to implement a predictive planting date based on climate inputs is added to the Accelerated Climate Model for Energy (ACME) Land Model (ALM). The model considers two main sources of climate data important for planting: precipitation and temperature. This method expands the current temperature threshold planting trigger and improves the estimated plant date in ALM. Furthermore, the precipitation metric for planting, which synchronizes the crop growing season with the wettest months, allows tropical crops to be introduced to the model. This presentation will demonstrate how the improved model enhances the ability of ALM to capture planting date compared with observations. More importantly, the impact of changing the planting date and introducing tropical

  11. Modeling of climate change impacts on agriculture, forestry and fishery

    International Nuclear Information System (INIS)

    Bala, B.K.; Munnaf, M.A.

    2014-01-01

    Changes in climate affect agriculture, forest and fisheries. This paper examines the climate change impact on crop production, fishery and forestry using state - of - the - art modeling technique. Crop growth model InfoCrop was used to predict the climate change impacts on the yields of rice, wheat and maize in Bangladesh. Historical climate change scenario has little or no negative impacts on rice and wheat yields in Mymensingh and Dinajpur but IPCC climate change scenario has higher negative impacts. There is almost no change in the yields of maize for the historical climate change scenario in the Chittagong, Hill Tracts of but there is a small decrease in the yields of rice and maize for IPCC climate change scenario. A new statistical model to forecast climate change impacts on fishery in the world oceans has been developed. Total climate change impact on fishery in the Indian Ocean is negative and the predictor power is 94.14% for eastern part and 98.59% for the western part. Two models are presented for the mangrove forests of the Sundarbans. To bole volumes of the pioneer, intermediate and climax are simulated for three different logging strategies and the results have been discussed in this paper. (author)

  12. Exploring the role of fire, succession, climate, and weather on landscape dynamics using comparative modeling

    Science.gov (United States)

    Robert E. Keane; Geoffrey J. Cary; Mike D. Flannigan; Russell A. Parsons; Ian D. Davies; Karen J. King; Chao Li; Ross A. Bradstock; Malcolm Gill

    2013-01-01

    An assessment of the relative importance of vegetation change and disturbance as agents of landscape change under current and future climates would (1) provide insight into the controls of landscape dynamics, (2) help inform the design and development of coarse scale spatially explicit ecosystem models such as Dynamic Global Vegetation Models (DGVMs), and (3) guide...

  13. 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.

  14. Assessment of climate change scenarios for Saudi Arabia using data from global climate models

    International Nuclear Information System (INIS)

    Husain, T.; Chowdhury, S.

    2009-01-01

    This study assesses available scientific information and data to predict changes in the climatic parameters in Saudi Arabia for understanding the impacts for mitigation and/or adaptation. Meteorological data from 26 synoptic stations were analyzed in this study. Various climatic change scenarios were reviewed and A 2 and B 2 climatic scenario families were selected. In order to assess long-term global impact, global climatic models were used to simulate changes in temperature, precipitation, relative humidity, solar radiation, and wind circulation. Using global climate model (GCM), monthly time series data was retrieved for Longitude 15 o N to 35 o N and 32.5 o E to 60 o E covering the Kingdom of Saudi Arabia from 1970 to 2100 for all grids. Taking averages of 1970 to 2003 as baseline, change in temperature, relative humidity and precipitation were estimated for the base period. A comparative evaluation was performed for predictive capabilities of these models for temperature, precipitation and relative humidity. Available meteorological data from 1970 to 2003 was used to determine trends. This paper discusses the inconsistency in these parameters for decision-making and recommends future studies by linking global climate models with a suitable regional climate modeling tool. (author)

  15. Regionalization of climate model results for the North Sea

    Energy Technology Data Exchange (ETDEWEB)

    Kauker, F.

    1999-07-01

    A dynamical downscaling is presented that allows an estimation of potential effects of climate change on the North Sea. Therefore, the ocean general circulation model OPYC is adapted for application on a shelf by adding a lateral boundary formulation and a tide model. In this set-up the model is forced, first, with data from the ECMWF reanalysis for model validation and the study of the natural variability, and, second, with data from climate change experiments to estimate the effects of climate change on the North Sea. (orig.)

  16. The Transition From the Present-Day Climate to a Snowball Earth Simulated With a Comprehensive Climate Model

    Science.gov (United States)

    Voigt, A.; Marotzke, J.

    2007-12-01

    Recently, Marotzke and Botzet (2007) have shown 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 greenhouse gas concentrations. By setting TSI to near-zero they were able to cause a transition from the present-day climate to the ice-covered state within 15 years [1]. In order to study the bifurcation point, we have repeated this experiment with the same model, i.e. the Max Planck Institute for Meteorology coupled atmosphere-ocean general circulation model ECHAM5/MPI-OM, at lower resolution (horizontally T31 in the atmosphere and 3.0 degrees in the ocean). We give estimates for the critical values of TSI and greenhouse gas concentrations needed to trigger the transition from the present-day to the ice- covered state. Starting from today's climate and setting TSI to 44% of today's value leads to a glaciation within 30 years. Furthermore, we investigate the degree of oceanic ice-cover needed for an unstoppable glaciation. We find that only an almost completely ice-covered ocean guarantees that the model does not return to the present-day climate when TSI is reset to its today's value. Our results indicate that a snowball Earth could, in principle, be triggered by a brief decrease of TSI. [1] Marotzke, J. and M. Botzet (2007), Present-day and ice-covered equilibrium states in a comprehensive climate model, Geophys. Res. Lett., Vol. 34, No. 16, L16704, doi:10.1029/2006GL028880

  17. Detection of anthropogenic climate change: a modeling study

    International Nuclear Information System (INIS)

    Duffy, P B; Eltgroth, P G.

    1998-01-01

    This project involved two related areas of research: (1) simulating natural climate variability using a global climate model, and (2) using the computer resources of the Accelerated Strategic Computing Initiative (ASCI) Blue computer for specific problems in atmospheric science and climate. Although originally scheduled to last two years, this ER project ended after one year; the work is begin continued under a larger (Strategic Initiative) project which started in FY99

  18. Modelling the economic impacts of addressing climate change

    International Nuclear Information System (INIS)

    2002-01-01

    This Power Point report presents highlights of the latest economic modelling of Canada's Kyoto commitment to address climate change. It presents framework assumptions and a snapshot under 4 scenarios. The objective of this report is to evaluate the national, sectoral, provincial and territorial impacts of the federal reference case policy package in which the emissions reduction target is 170 Mt from a business-as-usual scenario. The reference case policy package also includes 30 Mt of sinks from current packages of which 20 Mt are derived from the forestry sector and the remainder from agricultural sector. The report examined 4 scenarios based on 2 international carbon prices ($10 and $50) per tonne of carbon dioxide in 2010. The scenarios were also based on the fiscal assumptions that climate change initiatives and revenue losses would directly affect the governments' balances, or that the government balances are maintained by increasing personal income tax. A comparison of impacts under each of the 4 scenarios to 2010 was presented. The model presents impacts on GDP, employment, disposable income per household, and energy prices. 4 tabs., 4 figs

  19. 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.

  20. A Faculty Workshop Model to Integrate Climate Change across the Curriculum

    Science.gov (United States)

    Teranes, J. L.

    2017-12-01

    Much of the growing scientific certainty of human impacts on the climate system, and the implications of these impacts on current and future generations, have been discovered and documented in research labs in colleges and universities across the country. Often these institutions also take decisive action towards combatting climate change, by making significant reductions in greenhouse emissions and pledging to greater future reductions. Yet, there are still far too many students that graduate from these campuses without an adequate understanding of how climate change will impact them within their lifetimes and without adequate workforce preparation to implement solutions. It may be that where college and universities still have the largest influence on climate change adaption and mitigation is in the way that we educate students. Here I present a curriculum workshop model at UC San Diego that leverages faculty expertise to infuse climate change education across disciplines to enhance UC San Diego students' climate literacy, particularly for those students whose major focus is not in the geosciences. In this model, twenty faculty from a breadth of disciplines, including social sciences, humanities, arts, education, and natural sciences participated in workshops and developed curricula to infuse aspects of climate change into their existing undergraduate courses. We particularly encouraged development of climate change modules in courses in the humanities, social sciences and arts that are best positioned to address the important human and social dimensions of climate change. In this way, climate change content becomes embedded in current course offerings, including non-science courses, to increase climate literacy among a greater number and a broader cross-section of students.

  1. 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.

  2. Estimating the Health Impact of Climate Change with Calibrated Climate Model Output.

    Science.gov (United States)

    Zhou, Jingwen; Chang, Howard H; Fuentes, Montserrat

    2012-09-01

    Studies on the health impacts of climate change routinely use climate model output as future exposure projection. Uncertainty quantification, usually in the form of sensitivity analysis, has focused predominantly on the variability arise from different emission scenarios or multi-model ensembles. This paper describes a Bayesian spatial quantile regression approach to calibrate climate model output for examining to the risks of future temperature on adverse health outcomes. Specifically, we first estimate the spatial quantile process for climate model output using nonlinear monotonic regression during a historical period. The quantile process is then calibrated using the quantile functions estimated from the observed monitoring data. Our model also down-scales the gridded climate model output to the point-level for projecting future exposure over a specific geographical region. The quantile regression approach is motivated by the need to better characterize the tails of future temperature distribution where the greatest health impacts are likely to occur. We applied the methodology to calibrate temperature projections from a regional climate model for the period 2041 to 2050. Accounting for calibration uncertainty, we calculated the number of of excess deaths attributed to future temperature for three cities in the US state of Alabama.

  3. Current approaches to gene regulatory network modelling

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2007-09-01

    Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

  4. 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

  5. Modelling Monsoons: Understanding and Predicting Current and Future Behaviour

    Energy Technology Data Exchange (ETDEWEB)

    Turner, A; Sperber, K R; Slingo, J M; Meehl, G A; Mechoso, C R; Kimoto, M; Giannini, A

    2008-09-16

    including, but not limited to, the Mei-Yu/Baiu sudden onset and withdrawal, low-level jet orientation and variability, and orographic forced rainfall. Under anthropogenic climate change many competing factors complicate making robust projections of monsoon changes. Without aerosol effects, increased land-sea temperature contrast suggests strengthened monsoon circulation due to climate change. However, increased aerosol emissions will reflect more solar radiation back to space, which may temper or even reduce the strength of monsoon circulations compared to the present day. A more comprehensive assessment is needed of the impact of black carbon aerosols, which may modulate that of other anthropogenic greenhouse gases. Precipitation may behave independently from the circulation under warming conditions in which an increased atmospheric moisture loading, based purely on thermodynamic considerations, could result in increased monsoon rainfall under climate change. The challenge to improve model parameterizations and include more complex processes and feedbacks pushes computing resources to their limit, thus requiring continuous upgrades of computational infrastructure to ensure progress in understanding and predicting the current and future behavior of monsoons.

  6. Simulating Climate Change in Ireland using a Regional Climate Model Approach

    Science.gov (United States)

    Nolan, Paul; Lynch, Peter

    2010-05-01

    At the Meteorology & Climate Centre at University College Dublin, we are using the CLM-Community's COSMO-CLM Regional Climate Model (RCM) and the WRF RCM (developed at NCAR) to simulate the climate of Ireland at 7km resolution. The RCM models were validated by performing a 20-year simulation of the Irish climate (1981-2000), driven at the lateral boundaries by ECMWF ERA-40 global re-analysis data, and comparing the output to observations. Results confirm that the output of the RCM models exhibit reasonable and realistic features as documented in the historical data record. Validation results will be presented for wind, temperature and precipitation. Projections for the future Irish climate were generated by downscaling the Max Planck Institute's ECHAM5 global climate model data using the COSMO-CLM RCM. Simulations were run for a reference period 1961-2000 and future period 2021-2060. The future climate was simulated using the A1B & B1 greenhouse gas emission scenarios. Results for the downscaled simulations show a substantial overall increase in wind speeds for the future winter months and a decrease during the summer months. The projected changes for summer and winter were found to be statistically significant over most of Ireland. Future projections for temperature and precipitation will also be presented.

  7. Coupled Surface and Groundwater Hydrological Modeling in a Changing Climate.

    Science.gov (United States)

    Sridhar, Venkataramana; Billah, Mirza M; Hildreth, John W

    2017-11-09

    Many current watershed modeling efforts now incorporate surface water and groundwater for managing water resources since the exchanges between groundwater and surface water need a special focus considering the changing climate. The influence of groundwater dynamics on water and energy balance components is investigated in the Snake River Basin (SRB) by coupling the Variable Infiltration Capacity (VIC) and MODFLOW models (VIC-MF) for the period of 1986 through 2042. A 4.4% increase in base flows and a 10.3% decrease in peak flows are estimated by VIC-MF compared to the VIC model in SRB. The VIC-MF model shows significant improvement in the streamflow simulation (Nash-Sutcliffe efficiency [NSE] of 0.84) at King Hill, where the VIC model could not capture the effect of spring discharge in the streamflow simulation (NSE of -0.30); however, the streamflow estimates show an overall decreasing trend. Two climate scenarios representing median and high radiative-forcings such as representative concentration pathways 4.5 and 8.5 show an average increase in the water table elevations between 2.1 and 2.6 m (6.9 and 8.5 feet) through the year 2042. The spatial patterns of these exchanges show a higher groundwater elevation of 15 m (50 feet) in the downstream area and a lower elevation of up to 3 m (10 feet) in the upstream area. Broadly, this study supports results of previous work demonstrating that integrated assessment of groundwater-surface water enables stakeholders to balance pumping, recharge and base flow needs and to manage the watersheds that are subjected to human pressures more sustainably. © 2017, National Ground Water Association.

  8. Application of an integrated indoor climate, HVAC and showcase model for the indoor climate performance of a museum

    Energy Technology Data Exchange (ETDEWEB)

    Van Schijndel, A.W.M.; Schellen, H.L.; Wijffelaars, J.L.; Van Zundert, K. [Technische Universiteit Eindhoven, Department of Building and Architecture, Building Physics and Systems (BPS), VRT 6.29, P.O. Box 513, 5600 MB Eindhoven (Netherlands)

    2008-07-01

    This paper presents a case study on the performance based design of a HVAC system and controller of a museum. A famous museum in The Netherlands has reported possible damage to important preserved wallpaper fragments. The paper provides an evaluation of the current indoor climate by measurements, showing that the indoor climate performance does not satisfy the requirements for the preservation of old paper. To solve this problem we developed an integrated heat air and moisture (HAM) model consisting of models for respectively: the indoor climate, the HVAC system and controller and a showcase. The presented models are validated by a comparison of simulation and measurement results. The integrated model is used for the evaluation of a new HVAC controller design and the use of a showcase. It is concluded that it is not possible to satisfy the indoor climate within the recommended limits, exclusively by the use of a new control strategy. Furthermore in order to meet the recommendations, the wallpaper fragments should be placed in a showcase and a similar control strategy as presented in the paper, has to be implemented in order to limit the room air temperature change. (author)

  9. Understanding hydro-climatic drivers of infectious diarrheal diseases in South Asia and their projected risks from regional climate models

    Science.gov (United States)

    Hasan, M. A.; Akanda, A. S.; Jutla, A.; Huq, A.; Colwell, R. R.

    2017-12-01

    Diarrheal diseases remain a major threat to global public health and are the second largest cause of death for children under the age of five. Cholera and Rotavirus diarrhea together comprise more than two-thirds of the diarrheal morbidity in South Asia. Recent studies have shown strong influences of hydrologic processes and climatic variabilities on the onset, intensity, and seasonality of the outbreaks of these diseases. However, our understanding of the propagation and manifestation of these diseases in a changing climate in vulnerable regions of the world are still limited. In this study, we build on our understanding of the role of the hydro-climatic drivers of diarrheal diseases in South Asia in recent decades to project the probable risks of the diseases in this century using the climate projection scenarios from dynamically downscaled climate models. To build the current model, we conducted a multivariate logistic regression assessment using 34 climate indices to examine the role of temperature and rainfall extremes over the seasonality of rotavirus and cholera over a South Asian country, Bangladesh. We utilize the availability of long and reliable time-series of cholera and rotavirus from Bangladesh and conducted a temporal and spatial analysis derived from both ground and satellite observations. For projecting the future risks of the diseases, we used five bias-corrected Regional Climate Model (RCM) results of the CMIP5 series under the RCP 4.5 scenario. Cholera risk shows a significantly higher rate of increase compared to Rotavirus in Bangladesh in the 21st century. As the disease is significantly influenced by extreme rainfall, majority projections showed a significant increase in flood-driven cholera risk. Most RCMs suggest a warmer winter in future years, suggesting reduced risk for Rotavirus. However, as the dryness of the climate is also highly correlated with rotavirus epidemics, the incremental risk of the disease due to drier winters would

  10. Extracting climate memory using Fractional Integrated Statistical Model: A new perspective on climate prediction

    Science.gov (United States)

    Yuan, Naiming; Fu, Zuntao; Liu, Shida

    2014-01-01

    Long term memory (LTM) in climate variability is studied by means of fractional integral techniques. By using a recently developed model, Fractional Integral Statistical Model (FISM), we in this report proposed a new method, with which one can estimate the long-lasting influences of historical climate states on the present time quantitatively, and further extract the influence as climate memory signals. To show the usability of this method, two examples, the Northern Hemisphere monthly Temperature Anomalies (NHTA) and the Pacific Decadal Oscillation index (PDO), are analyzed in this study. We find the climate memory signals indeed can be extracted and the whole variations can be further decomposed into two parts: the cumulative climate memory (CCM) and the weather-scale excitation (WSE). The stronger LTM is, the larger proportion the climate memory signals will account for in the whole variations. With the climate memory signals extracted, one can at least determine on what basis the considered time series will continue to change. Therefore, this report provides a new perspective on climate prediction. PMID:25300777

  11. 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

  12. European Climate - Energy Security Nexus. A model based scenario analysis

    International Nuclear Information System (INIS)

    Criqui, Patrick; Mima, Silvana

    2011-01-01

    In this research, we have provided an overview of the climate-security nexus in the European sector through a model based scenario analysis with POLES model. The analysis underline that under stringent climate policies, Europe take advantage of a double dividend in its capacity to develop a new cleaner energy model and in lower vulnerability to potential shocks on the international energy markets. (authors)

  13. European Climate - Energy Security Nexus. A model based scenario analysis

    Energy Technology Data Exchange (ETDEWEB)

    Criqui, Patrick; Mima, Silvana

    2011-01-15

    In this research, we have provided an overview of the climate-security nexus in the European sector through a model based scenario analysis with POLES model. The analysis underline that under stringent climate policies, Europe take advantage of a double dividend in its capacity to develop a new cleaner energy model and in lower vulnerability to potential shocks on the international energy markets. (authors)

  14. 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

  15. Modeling productivity and transpiration of Pinus radiata: climatic effects

    Energy Technology Data Exchange (ETDEWEB)

    Sheriff, D. W.; Mattay, J. P. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Canberra, ACT (Australia). Div. of Forestry and Forest Products; McMurtrie, R. E. [New South Wales Univ., Sydney, NSW (Australia)

    1996-01-01

    Using a process-based forest growth model, BIOMASS, the climatic effect on annual net carbon gain, stem biomass and annual transpiration were simulated for Pinus radiata. Regional variation in climate between Canberra and Mt. Gambier resulted in a 20 per cent difference in simulated annual transpiration rate, but only a relatively small difference in simulated productivity. Simulated carbon gain values averaged about 1.4 per cent; this result was not consistent with the predicted 8 per cent annual carbon assimilation difference between the two sites, based on differences in climate. These results suggest that climatic differences do not account for differences in productivity. 12 refs., 3 tabs., 2 figs.

  16. 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.

  17. 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.

  18. Impact of climate change on large scale coastal currents of South Africa

    CSIR Research Space (South Africa)

    Meyer, A

    2010-09-01

    Full Text Available st century, that is: 1) a further intensification and southward shift of the mid-latitude westerlies with an affiliated increase in the antarctic circumpolar current transport; 2) a southwards migration and intensification of the Southern... Hemisphere sub-tropical gyre circulations; and 3) Stronger western boundary currents, that is, stronger agulhas current (along the east coast of South africa), and stronger Brazil and east australian current. figure 1: Map showing the model outputs...

  19. Computer experiments with a coarse-grid hydrodynamic climate model

    International Nuclear Information System (INIS)

    Stenchikov, G.L.

    1990-01-01

    A climate model is developed on the basis of the two-level Mintz-Arakawa general circulation model of the atmosphere and a bulk model of the upper layer of the ocean. A detailed model of the spectral transport of shortwave and longwave radiation is used to investigate the radiative effects of greenhouse gases. The radiative fluxes are calculated at the boundaries of five layers, each with a pressure thickness of about 200 mb. The results of the climate sensitivity calculations for mean-annual and perpetual seasonal regimes are discussed. The CCAS (Computer Center of the Academy of Sciences) climate model is used to investigate the climatic effects of anthropogenic changes of the optical properties of the atmosphere due to increasing CO 2 content and aerosol pollution, and to calculate the sensitivity to changes of land surface albedo and humidity

  20. 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...... a validation framework and guiding principles applicable across earth science disciplines for testing the capability of models to project future climate change and its impacts. Model test schemes comprising split-sample tests, differential split-sample tests and proxy site tests are discussed in relation...... 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...

  1. Multi-observation integrated model of troposphere - current status

    Science.gov (United States)

    Wilgan, Karina; Rohm, Witold; Bosy, Jarosław; Sierny, Jan; Kapłon, Jan; Hadaś, Tomasz; Hordyniec, Paweł

    2014-05-01

    The Global Navigation Satellite Systems (GNSS) and meteorological observation systems in the past decades were developed to address separate challenges and were used by different communities. Currently, the inter-dependence between meteorology and GNSS processing is growing up, providing both communities incentives, data and research challenges. The GNSS community uses meteorological observations as well as Numerical Weather Prediction (NWP) models to reduce the troposphere impact on the signal propagation (i.e. eliminate tropospheric delay). On the other hand, meteorology community is assimilating the GNSS observations into weather forecasting, nowcasting or climate studies. To seamlessly use observations from both sides of the GNSS and meteorology spectra, the data have to be interoperable. In this study we present a current status of establishing an integrated model of troposphere. We investigated and compared a number of meteorological and GNSS data sources that are going to be integrated into the troposphere model with high temporal and spatial resolution. The integrated model will provide values of meteorological and GNSS parameters at any point and any time with known accuracy. First step in building this model is to inter-compare all available data sources and to establish the accuracy of parameters. Three main data sources were compared: ground-based GNSS products on ASG-EUPOS stations, NWP model COAMPS (Coupled Ocean/ Atmosphere Mesoscale Prediction System) and meteorological parameters from three kinds of stations - EUREF Permanent Network (EPN) stations, meteorological sensors at airports and synoptic Institute of Meteorology and Water Management. Data was provided with different temporal and spatial resolution, so it had to be interpolated prior to inter-comparison. Afterwards, the quality of the data was established. The results show that NWP model data quality is: 4hPa in terms of air pressure, 2hPa in terms of water vapor partial pressure, and 6K in

  2. 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.

  3. Regional climate model downscaling may improve the prediction of alien plant species distributions

    Science.gov (United States)

    Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

    2014-12-01

    Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

  4. Heat waves in Portugal: Current regime, changes in future climate and impacts on extreme wildfires.

    Science.gov (United States)

    Parente, J; Pereira, M G; Amraoui, M; Fischer, E M

    2018-03-09

    Heat waves (HW) can have devastating social, economic and environmental impacts. Together with long-term drought, they are the main factors contributing to wildfires. Surprisingly, the quantitative and objective analysis leading to the identification and characterization of HW in current and future climate conditions as well as its influence on the occurrence of extreme wildfires (EW) has never been performed for Portugal and are the main objectives of this study. For this reason, we assess HW in recent past and future climate based on a consistent high resolution meteorological database and have compared their occurrence with long and reliable, precise and detailed information about Portuguese fire events. Results include the characterization of HW frequency, duration, seasonality and intensity for current and different future climate conditions and their relationship with EW occurrence. We detected 130 HW between 1981 and 2010, concentrated between May and October and highest values in July and August. The highest HW number and duration is found over the Northeast corner and the south of the country while highest amplitudes are typically located in central area. HW characteristics present high inter-annual variability but are clearly associated to the temporal and spatial distribution of EW: 97% of total number of EW were active during an HW, 90% of total EW days were also HW days; 82% of the EW had duration completely contained in the duration of an HW; and, 83% of EW occurred during and in the area affected by HW. Our results also show that HW should increase in number, duration and amplitude, more significantly for RCP 8.5, and for the 30-year periods near the end of the 21st century. Findings of this study will support the definition of climate change adaptation strategies for fire danger and risk management. Copyright © 2018. Published by Elsevier B.V.

  5. Current and Evolving Models of Peer Review

    OpenAIRE

    Fresco Santalla, Ana; Hernández Pérez, Antonio

    2014-01-01

    New models of scientific publishing and new ways of practicing peer review have injected a recent dynamism into the scholarly communication system. In this article, we delineate the context of the traditional peer review model, reflect upon some of the first experiences with open peer review and forecast some of the challenges that new models for peer review will have to meet. Our findings suggest that the peer review function has the potential to be divorced from the journal system, so that ...

  6. Towards Measures to Establish the Relevance of Climate Model Output for Decision Support

    Science.gov (United States)

    Clarke, L.; Smith, L. A.

    2007-12-01

    How exactly can decision-support and policy making benefit from the use of multiple climate model experiments in terms of coping with the uncertainties on climate change projections? Climate modelling faces challenges beyond those of weather forecasting or even seasonal forecasting, as with climate we are now (and will probably always be) required to extrapolate to regimes in which we have no relevant forecast-verification archive. This suggests a very different approach from traditional methods of mixing models and skill based weighting to gain profitable probabilistic information when a large forecast-verification archive is in hand. In the case of climate, it may prove more rational to search for agreement between our models (in distribution), the aim being to determine the space and timescales on which, given our current understanding, the details of the simulation models are unimportant. This suggestion and others from Smith (2002, Proc. National Acad. Sci. USA 4 (99): 2487-2492) are interpreted in the light of recent advances. Climate models are large nonlinear dynamical systems which insightfully but imperfectly reflect the evolving weather patterns of the Earth. Their use in policy making and decision support assumes both that they contain sufficient information regarding reality to inform the decision, and that this information can be effectively communicated to the decision makers. There is nothing unique about climate modeling and these constraints, they apply in all cases where scientific modeling is applied to real-word actions (other than, perhaps, the action of improving our models). Starting with the issue of communication, figures from the 2007 IPCC Summary for Policy Makers will be constructively criticized from the perspective of decision makers, specifically those of the energy sector and the insurance/reinsurance sector. More information on basic questions of reliability and robustness would be of significant value when determining how heavily

  7. A model, and the fidelity of climate reconstructions from speleothems

    Science.gov (United States)

    Fischer, M. J.; Treble, P. C.

    2009-04-01

    The use of multiple tracers to provide quantitative estimates of environment variables is well-known from other paleoclimate archives eg. in corals Mg, Sr, 13C and 18O are used jointly to separate and provide quantitative estimates for variables such as SST, salinity and precipitation amount. From speleothems, however, high-resolution quantitative climate reconstructions over the last millennia are still rare. There is no well-established theory on how to use multiple proxies to separate distinct environmental signals (precipitation, temperature, water balance), and it is not understood how the joint stochastic properties of climate variables- for a range of climate conditions- affect the fidelity of specific climate variable reconstructions from speleothems. In this presentation, a preliminary model of an environment+speleothem system is introduced, and investigated using modern statistical techniques. A soil+hydrology model is forced using gridded observed climate data (with a high spatial and temporal resolution) for Australia for the last century. Precipitation isotopes are reconstructed for the pre-1960 period using climate-isotope transfer functions. Soil carbon isotope variation is reconstructed using a recent hydrobiotic parameterisation. A speleothem is simulated using a growth rate model, and trace elements (Ba, Mg) are simulated based on growth-rate plus hydrological effects. All these parameterisations are linked together to form a speleothem multi-proxy model, that is forced by real climate data. Using the statistical method of canonical correlations with a split validation scheme, we show how climate signal reconstruction, and its fidelity, differs under different regional climates in Australia. This model provides a tool for understanding the science of regional climate reconstructions from speleothems over the last few millennia.

  8. Is wartime mobilisation a suitable policy model for rapid national climate mitigation?

    International Nuclear Information System (INIS)

    Delina, Laurence L.; Diesendorf, Mark

    2013-01-01

    Climate science suggests that, to have a high probability of limiting global warming to an average temperature increase of 2 °C, global greenhouse gas emissions must peak by 2020 and be reduced to close to zero by 2040. However, the current trend is heading towards at least 4 °C by 2100 and little effective action is being taken. This paper commences the process of developing contingency plans for a scenario in which a sudden major global climate impact galvanises governments to implement emergency climate mitigation targets and programs. Climate activists assert that rapid mitigation is feasible, invoking the scale and scope of wartime mobilisation strategies. This paper draws upon historical accounts of social, technological and economic restructurings in several countries during World War 2 in order to investigate potential applications of wartime experience to radical, rigorous and rapid climate mitigation strategies. We focus on the energy sector, the biggest single contributor to global climate change, in developed and rapidly developing countries. We find that, while wartime experience suggests some potential strategies for rapid climate mitigation in the areas of finance and labour, it also has severe limitations, resulting from its lack of democratic processes. - Highlights: • The paper explores the strengths and weaknesses of using wartime experience as a model for rapid climate mitigation. • Wartime experience suggests some potential strategies for rapid climate mitigation in the areas of finance and labour. • Wartime experience also has severe limitations, resulting from its lack of democratic processes

  9. 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.

  10. 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.

  11. 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

  12. Ecosystem size structure response to 21st century climate projection: large fish abundance decreases in the central North Pacific and increases in the California Current.

    Science.gov (United States)

    Woodworth-Jefcoats, Phoebe A; Polovina, Jeffrey J; Dunne, John P; Blanchard, Julia L

    2013-03-01

    Output from an earth system model is paired with a size-based food web model to investigate the effects of climate change on the abundance of large fish over the 21st century. The earth system model, forced by the Intergovernmental Panel on Climate Change (IPCC) Special report on emission scenario A2, combines a coupled climate model with a biogeochemical model including major nutrients, three phytoplankton functional groups, and zooplankton grazing. The size-based food web model includes linkages between two size-structured pelagic communities: primary producers and consumers. Our investigation focuses on seven sites in the North Pacific, each highlighting a specific aspect of projected climate change, and includes top-down ecosystem depletion through fishing. We project declines in large fish abundance ranging from 0 to 75.8% in the central North Pacific and increases of up to 43.0% in the California Current (CC) region over the 21st century in response to change in phytoplankton size structure and direct physiological effects. We find that fish abundance is especially sensitive to projected changes in large phytoplankton density and our model projects changes in the abundance of large fish being of the same order of magnitude as changes in the abundance of large phytoplankton. Thus, studies that address only climate-induced impacts to primary production without including changes to phytoplankton size structure may not adequately project ecosystem responses. © 2012 Blackwell Publishing Ltd.

  13. Particle Models with Self Sustained Current

    Science.gov (United States)

    Colangeli, M.; De Masi, A.; Presutti, E.

    2017-06-01

    We present some computer simulations run on a stochastic cellular automaton (CA). The CA simulates a gas of particles which are in a channel,the interval [1, L] in Z, but also in "reservoirs" R_1 and R_2. The evolution in the channel simulates a lattice gas with Kawasaki dynamics with attractive Kac interactions; the temperature is chosen smaller than the mean field critical one. There are also exchanges of particles between the channel and the reservoirs and among reservoirs. When the rate of exchanges among reservoirs is in a suitable interval the CA reaches an apparently stationary state with a non zero current; for different choices of the initial condition the current changes sign. We have a quite satisfactory theory of the phenomenon but we miss a full mathematical proof.

  14. A probabilistic model of ecosystem response to climate change

    International Nuclear Information System (INIS)

    Shevliakova, E.; Dowlatabadi, H.

    1994-01-01

    Anthropogenic activities are leading to rapid changes in land cover and emissions of greenhouse gases into the atmosphere. These changes can bring about climate change typified by average global temperatures rising by 1--5 C over the next century. Climate change of this magnitude is likely to alter the distribution of terrestrial ecosystems on a large scale. Options available for dealing with such change are abatement of emissions, adaptation, and geoengineering. The integrated assessment of climate change demands that frameworks be developed where all the elements of the climate problem are present (from economic activity to climate change and its impacts on market and non-market goods and services). Integrated climate assessment requires multiple impact metrics and multi-attribute utility functions to simulate the response of different key actors/decision-makers to the actual physical impacts (rather than a dollar value) of the climate-damage vs. policy-cost debate. This necessitates direct modeling of ecosystem impacts of climate change. The authors have developed a probabilistic model of ecosystem response to global change. This model differs from previous efforts in that it is statistically estimated using actual ecosystem and climate data yielding a joint multivariate probability of prevalence for each ecosystem, given climatic conditions. The authors expect this approach to permit simulation of inertia and competition which have, so far, been absent in transfer models of continental-scale ecosystem response to global change. Thus, although the probability of one ecotype will dominate others at a given point, others would have the possibility of establishing an early foothold

  15. Reconstructing Climate Change: The Model-Data Ping-Pong

    Science.gov (United States)

    Stocker, T. F.

    2017-12-01

    When Cesare Emiliani, the father of paleoceanography, made the first attempts at a quantitative reconstruction of Pleistocene climate change in the early 1950s, climate models were not yet conceived. The understanding of paleoceanographic records was therefore limited, and scientists had to resort to plausibility arguments to interpret their data. With the advent of coupled climate models in the early 1970s, for the first time hypotheses about climate processes and climate change could be tested in a dynamically consistent framework. However, only a model hierarchy can cope with the long time scales and the multi-component physical-biogeochemical Earth System. There are many examples how climate models have inspired the interpretation of paleoclimate data on the one hand, and conversely, how data have questioned long-held concepts and models. In this lecture I critically revisit a few examples of this model-data ping-pong, such as the bipolar seesaw, the mid-Holocene greenhouse gas increase, millennial and rapid CO2 changes reconstructed from polar ice cores, and the interpretation of novel paleoceanographic tracers. These examples also highlight many of the still unsolved questions and provide guidance for future research. The combination of high-resolution paleoceanographic data and modeling has never been more relevant than today. It will be the key for an appropriate risk assessment of impacts on the Earth System that are already underway in the Anthropocene.

  16. Environmental sub models for a macroeconomic model: Agricultural contribution to climate change and acidification in Denmark

    DEFF Research Database (Denmark)

    Jensen, T.S.; Jensen, J.D.; Hasler, B.

    2007-01-01

    economic model, environmental satellite models of energy and waste related emissions contributing to climate change and acidification. The model extension allows the main Danish contribution to climate change and acidification to be modelled. The existing model system is extended by environmental satellite...... for changes in the husbandry sector within the agricultural sector....

  17. 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...... modelling with policy and strategies for sustainable management. In this paper we give a brief overview of different ecosystem modelling methods, discuss how to include ecological and management aspects, and highlight the importance of science–stakeholder communication. By this, we hope to stimulate...

  18. Twenty first century climate change as simulated by European climate models

    International Nuclear Information System (INIS)

    Cubasch, Ulrich

    2007-01-01

    Full text: Climate change simulation results for seven European state-of-the-art climate models, participating in the European research project ENSEMBLES (ENSEMBLE-based Predictions of Climate Changes and their Impacts), will be presented. Models from Norway, France, Germany, Denmark, and Great Britain, representing a sub-ensemble of the models contributing to the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4), are included. Climate simulations are conducted with all the models for present-day climate and for future climate under the SRES A1B, A2, and B1 scenarios. The design of the simulations follows the guidelines of the IPCC AR4. The 21st century projections are compared to the corresponding present-day simulations. The ensemble mean global mean near surface temperature rise for the year 2099 compared to the 1961-1990 period amounts to 3.2Kforthe A1B scenario, to 4.1 K for the A2 scenario, and to 2.1 K for the B1 scenario. The spatial patterns of temperature change are robust among the contributing models with the largest temperature increase over the Arctic in boreal winter, stronger warming overland than over ocean, and little warming over the southern oceans. The ensemble mean globally averaged precipitation increases for the three scenarios (5.6%, 5.7%, and 3.8% for scenarios A1B, A2, and B1, respectively). The precipitation signals of the different models display a larger spread than the temperature signals. In general, precipitation increases in the Intertropical Convergence Zone and the mid- to high latitudes (most pronounced during the hemispheric winter) and decreases in the subtropics. Sea-level pressure decreases over the polar regions in all models and all scenarios, which is mainly compensated by a pressure increase in the subtropical highs. These changes imply an intensification of the Southern and Northern Annular Modes

  19. Modelization of the Current and Future Habitat Suitability of Rhododendron ferrugineum Using Potential Snow Accumulation.

    Directory of Open Access Journals (Sweden)

    Benjamin Komac

    Full Text Available Mountain areas are particularly sensitive to climate change. Species distribution models predict important extinctions in these areas whose magnitude will depend on a number of different factors. Here we examine the possible impact of climate change on the Rhododendron ferrugineum (alpenrose niche in Andorra (Pyrenees. This species currently occupies 14.6 km2 of this country and relies on the protection afforded by snow cover in winter. We used high-resolution climatic data, potential snow accumulation and a combined forecasting method to obtain the realized niche model of this species. Subsequently, we used data from the high-resolution Scampei project climate change projection for the A2, A1B and B1 scenarios to model its future realized niche model. The modelization performed well when predicting the species's distribution, which improved when we considered the potential snow accumulation, the most important variable influencing its distribution. We thus obtained a potential extent of about 70.7 km(2 or 15.1% of the country. We observed an elevation lag distribution between the current and potential distribution of the species, probably due to its slow colonization rate and the small-scale survey of seedlings. Under the three climatic scenarios, the realized niche model of the species will be reduced by 37.9-70.1 km(2 by the end of the century and it will become confined to what are today screes and rocky hillside habitats. The particular effects of climate change on seedling establishment, as well as on the species' plasticity and sensitivity in the event of a reduction of the snow cover, could worsen these predictions.

  20. Modelization of the Current and Future Habitat Suitability of Rhododendron ferrugineum Using Potential Snow Accumulation.

    Science.gov (United States)

    Komac, Benjamin; Esteban, Pere; Trapero, Laura; Caritg, Roger

    2016-01-01

    Mountain areas are particularly sensitive to climate change. Species distribution models predict important extinctions in these areas whose magnitude will depend on a number of different factors. Here we examine the possible impact of climate change on the Rhododendron ferrugineum (alpenrose) niche in Andorra (Pyrenees). This species currently occupies 14.6 km2 of this country and relies on the protection afforded by snow cover in winter. We used high-resolution climatic data, potential snow accumulation and a combined forecasting method to obtain the realized niche model of this species. Subsequently, we used data from the high-resolution Scampei project climate change projection for the A2, A1B and B1 scenarios to model its future realized niche model. The modelization performed well when predicting the species's distribution, which improved when we considered the potential snow accumulation, the most important variable influencing its distribution. We thus obtained a potential extent of about 70.7 km(2) or 15.1% of the country. We observed an elevation lag distribution between the current and potential distribution of the species, probably due to its slow colonization rate and the small-scale survey of seedlings. Under the three climatic scenarios, the realized niche model of the species will be reduced by 37.9-70.1 km(2) by the end of the century and it will become confined to what are today screes and rocky hillside habitats. The particular effects of climate change on seedling establishment, as well as on the species' plasticity and sensitivity in the event of a reduction of the snow cover, could worsen these predictions.

  1. An observational and modeling study of the August 2017 Florida climate extreme event.

    Science.gov (United States)

    Konduru, R.; Singh, V.; Routray, A.

    2017-12-01

    A special report on the climate extremes by the Intergovernmental Panel on Climate Change (IPCC) elucidates that the sole cause of disasters is due to the exposure and vulnerability of the human and natural system to the climate extremes. The cause of such a climate extreme could be anthropogenic or non-anthropogenic. Therefore, it is challenging to discern the critical factor of influence for a particular climate extreme. Such kind of perceptive study with reasonable confidence on climate extreme events is possible only if there exist any past case studies. A similar rarest climate extreme problem encountered in the case of Houston floods and extreme rainfall over Florida in August 2017. A continuum of hurricanes like Harvey and Irma targeted the Florida region and caused catastrophe. Due to the rarity of August 2017 Florida climate extreme event, it requires the in-depth study on this case. To understand the multi-faceted nature of the event, a study on the development of the Harvey hurricane and its progression and dynamics is significant. Current article focus on the observational and modeling study on the Harvey hurricane. A global model named as NCUM (The global UK Met office Unified Model (UM) operational at National Center for Medium Range Weather Forecasting, India, was utilized to simulate the Harvey hurricane. The simulated rainfall and wind fields were compared with the observational datasets like Tropical Rainfall Measuring Mission rainfall datasets and Era-Interim wind fields. The National Centre for Environmental Prediction (NCEP) automated tracking system was utilized to track the Harvey hurricane, and the tracks were analyzed statistically for different forecasts concerning the Harvey hurricane track of Joint Typhon Warning Centre. Further, the current study will be continued to investigate the atmospheric processes involved in the August 2017 Florida climate extreme event.

  2. Review of models on energy and climate change

    International Nuclear Information System (INIS)

    Weyant, J.

    1991-01-01

    The Energy Modeling Forum recently has initiated a global climate change project. The purpose of the project is to summarize the work which has already been done on this topic and to evaluate the quality of the work. Several critical issues arise in any effort to make credible estimates of the cost of greenhouse control strategies. First, a worldwide modeling framework must be developed because carbon emissions from particular regions affect the global atmosphere. Because the data available on developing countries is quite poor at present, future efforts should focus on new data collection and modeling efforts in these regions. Second, all the major greenhouse gases - CO 2 , CFCs, methane and N 2 O - and not just carbon dioxide must be considered in future analyses. It is the overall concentration of all these different greenhouse gases in the atmosphere that ultimately will lead to global climate change. Third, an effective means for analyzing the various greenhouse gas control strategies must be developed. In order to successfully carry out the final task, a method must be developed which integrates a top-down macro-economic approach with a bottom-up process engineering approach. When implementing the macro-economic approach, one must choose plausible ranges for future economic and population growth rates. The reason for this is that even small changes in these driving factors can have huge impacts on emissions projections over the 100 or more year time frames required to address the greenhouse gas problem. The implementation of the process engineering approach requires: an accurate characterization of the costs, performance and availability of current and likely future technologies; an assessment of the likely barriers to technology transfer of both existing and new technologies, particularly from the developed to the developing countries; and an evaluation of the impact of energy prices and greenhouse gas policies on new technological development

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America

    Science.gov (United States)

    Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.

    2005-12-01

    Central America covers a relatively small area, but is topographically very complex, has long coast-lines, large inland bodies of water, and very diverse land cover which is both natural and human-induced. As a result, Central America is plagued by hydrologic extremes, especially major flooding and drought events, in a region where many people still barely manage to eke out a living through subsistence. Therefore, considerable concern exists about whether these extreme events will change, either in magnitude or in number, as climate changes in the future. To address this concern, we have used global climate model simulations of future climate change to drive a regional climate model centered on Central America. We use the IPCC `business as usual' scenario 21st century run made with the NCAR CCSM3 global model to drive the regional model MM5 at 12 km resolution. We chose the `business as usual' scenario to focus on the largest possible changes that are likely to occur. Because we are most interested in near-term changes, our simulations are for the years 2010, 2015, and 2025. A long `present-day run (for 2005) allows us to distinguish between climate variability and any signal due to climate change. Furthermore, a multi-year run with MM5 forced by NCEP reanalyses allows an assessment of how well the coupled global-regional model performs over Central America. Our analyses suggest that the coupled model does a credible job simulating the current climate and hydrologic regime, though lack of sufficient observations strongly complicates this comparison. The suite of model runs for the future years is currently nearing completion, and key results will be presented at the meeting.

  8. The Impact of School Climate and School Identification on Academic Achievement: Multilevel Modeling with Student and Teacher Data

    OpenAIRE

    Maxwell, Sophie; Reynolds, Katherine J.; Lee, Eunro; Subasic, Emina; Bromhead, David

    2017-01-01

    School climate is a leading factor in explaining student learning and achievement. Less work has explored the impact of both staff and student perceptions of school climate raising interesting questions about whether staff school climate experiences can add “value” to students' achievement. In the current research, multiple sources were integrated into a multilevel model, including staff self-reports, student self-reports, objective school records of academic achievement, and socio-economic d...

  9. 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.

  10. Surface CUrrents from a Diagnostic model (SCUD): Pacific

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The SCUD data product is an estimate of upper-ocean velocities computed from a diagnostic model (Surface CUrrents from a Diagnostic model). This model makes daily...

  11. Modeling of thermally stimulated depolarization current (TSDC ...

    Indian Academy of Sciences (India)

    2007-08-02

    Aug 2, 2007 ... and acrylonitrile-butadiene-styrene (ABS) using the thermal sampling technique were used. Furthermore, to compare the model, calculated peak parameters (i.e. the energy (E) and pre-exponential factor (τ0)), two known peak shape me- thods were used: (i) the initial rise method (IR) (Garlick and Gibson ...

  12. Current Density and Continuity in Discretized Models

    Science.gov (United States)

    Boykin, Timothy B.; Luisier, Mathieu; Klimeck, Gerhard

    2010-01-01

    Discrete approaches have long been used in numerical modelling of physical systems in both research and teaching. Discrete versions of the Schrodinger equation employing either one or several basis functions per mesh point are often used by senior undergraduates and beginning graduate students in computational physics projects. In studying…

  13. Models of Solar Irradiance Variations: Current Status

    Indian Academy of Sciences (India)

    2016-01-27

    Jan 27, 2016 ... Whereas variations on time scales of minutes to hours are due to solar oscillations and granulation, variations on longer time scales are driven by the evolution of the solar surface magnetic field. Here the most recent advances in modelling of solar irradiance variations on time scales longer than a day are ...

  14. The hydroclimatic and ecophysiological basis of cloud forest distributions under current and projected climates.

    Science.gov (United States)

    Oliveira, Rafael S; Eller, Cleiton B; Bittencourt, Paulo R L; Mulligan, Mark

    2014-05-01

    Tropical montane cloud forests (TMCFs) are characterized by a unique set of biological and hydroclimatic features, including frequent and/or persistent fog, cool temperatures, and high biodiversity and endemism. These forests are one of the most vulnerable ecosystems to climate change given their small geographic range, high endemism and dependence on a rare microclimatic envelope. The frequency of atmospheric water deficits for some TMCFs is likely to increase in the future, but the consequences for the integrity and distribution of these ecosystems are uncertain. In order to investigate plant and ecosystem responses to climate change, we need to know how TMCF species function in response to current climate, which factors shape function and ecology most and how these will change into the future. This review focuses on recent advances in ecophysiological research of TMCF plants to establish a link between TMCF hydrometeorological conditions and vegetation distribution, functioning and survival. The hydraulic characteristics of TMCF trees are discussed, together with the prevalence and ecological consequences of foliar uptake of fog water (FWU) in TMCFs, a key process that allows efficient acquisition of water during cloud immersion periods, minimizing water deficits and favouring survival of species prone to drought-induced hydraulic failure. Fog occurrence is the single most important microclimatic feature affecting the distribution and function of TMCF plants. Plants in TMCFs are very vulnerable to drought (possessing a small hydraulic safety margin), and the presence of fog and FWU minimizes the occurrence of tree water deficits and thus favours the survival of TMCF trees where such deficits may occur. Characterizing the interplay between microclimatic dynamics and plant water relations is key to foster more realistic projections about climate change effects on TMCF functioning and distribution.

  15. 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.

  16. 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.

  17. Spontaneous abrupt climate change due to an atmospheric blocking-sea-ice-ocean feedback in an unforced climate model simulation.

    Science.gov (United States)

    Drijfhout, Sybren; Gleeson, Emily; Dijkstra, Henk A; Livina, Valerie

    2013-12-03

    Abrupt climate change is abundant in geological records, but climate models rarely have been able to simulate such events in response to realistic forcing. Here we report on a spontaneous abrupt cooling event, lasting for more than a century, with a temperature anomaly similar to that of the Little Ice Age. The event was simulated in the preindustrial control run of a high-resolution climate model, without imposing external perturbations. Initial cooling started with a period of enhanced atmospheric blocking over the eastern subpolar gyre. In response, a southward progression of the sea-ice margin occurred, and the sea-level pressure anomaly was locked to the sea-ice margin through thermal forcing. The cold-core high steered more cold air to the area, reinforcing the sea-ice concentration anomaly east of Greenland. The sea-ice surplus was carried southward by ocean currents around the tip of Greenland. South of 70 °N, sea ice already started melting and the associated freshwater anomaly was carried to the Labrador Sea, shutting off deep convection. There, surface waters were exposed longer to atmospheric cooling and sea surface temperature dropped, causing an even larger thermally forced high above the Labrador Sea. In consequence, east of Greenland, anomalous winds changed from north to south, terminating the event with similar abruptness to its onset. Our results imply that only climate models that possess sufficient resolution to correctly represent atmospheric blocking, in combination with a sensitive sea-ice model, are able to simulate this kind of abrupt climate change.

  18. Fixing Climate: What Past Climate Changes Reveal About the Current Threat-And How to Counter It

    Science.gov (United States)

    McKinley, Galen A.

    2008-10-01

    The Earth's climate is changing due to human activities. Recent polls suggest that the U.S. public generally recognizes this fact, and the efforts that led the Intergovernmental Panel on Climate Change (IPCC) and former U.S. vice president Al Gore to win the 2007 Nobel Peace Prize have played no small role in bringing most of the public to realize what scientists have been discussing for years. Yet aside from distorted Hollywood movie accounts such as The Day After Tomorrow, the public knows little about the potential for abrupt change in the climate system. With support from climate science philanthropist Gary Comer, climate scientist Wally Broecker has teamed with science writer Robert Kunzig in this book to bring abrupt climate change into public view. They do this elegantly and convincingly, making the first 12 chapters quite enjoyable.

  19. Historical and idealized climate model experiments: an EMIC intercomparison

    DEFF Research Database (Denmark)

    Eby, M.; Weaver, A. J.; Alexander, K.

    2012-01-01

    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......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......, 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

  20. Assessment of Salinity Distributions and Residual Currents at the Northern Bay of Bengal considering Climate Change Impacts

    Directory of Open Access Journals (Sweden)

    Mohammad Asad Hussain

    2012-09-01

    Full Text Available The overall objective of the study is to investigate the future salinity distributions and residual flow scenarios in the northern Bay of Bengal taking into consideration of the change in hydrological and meteorological parameters. Observed and projected meteorological data are employed to generate present and future scenarios in the Northern Bay of Bengal. Numerical experiments through a 3D hydrodynamic model show that both during the monsoon as well as during winter periods, residual currents in the Northern Bay of Bengal display an anti-clockwise circulation concentrating at the eastern part of the bay. The Swatch of No Ground appears to have an important influence on the circulation patterns. Future salinity distributions are calculated through employment of projected meteorological data from regional climate model (RCM experiments. It shows considerable increase in salinity level which may hamper the freshwater availability and ecological balance in the region in future.

  1. Modeling potential climate change impacts on the trees of the northeastern United States

    Science.gov (United States)

    Louis Iverson; Anantha Prasad; Stephen Matthews

    2008-01-01

    We evaluated 134 tree species from the eastern United States for potential response to several scenarios of climate change, and summarized those responses for nine northeastern United States. We modeled and mapped each species individually and show current and potential future distributions for two emission scenarios (A1fi [higher emission] and B1 [lower emission]) and...

  2. Comparative Climates of the Trappist-1 Planetary System: Results from a Simple Climate-vegetation Model

    Science.gov (United States)

    Alberti, Tommaso; Carbone, Vincenzo; Lepreti, Fabio; Vecchio, Antonio

    2017-07-01

    The recent discovery of the planetary system hosted by the ultracool dwarf star TRAPPIST-1 could open new paths for investigations of the planetary climates of Earth-sized exoplanets, their atmospheres, and their possible habitability. In this paper, we use a simple climate-vegetation energy-balance model to study the climate of the seven TRAPPIST-1 planets and the climate dependence on various factors: the global albedo, the fraction of vegetation that could cover their surfaces, and the different greenhouse conditions. The model allows us to investigate whether liquid water could be maintained on the planetary surfaces (I.e., by defining a “surface water zone (SWZ)”) in different planetary conditions, with or without the presence of a greenhouse effect. It is shown that planet TRAPPIST-1d seems to be the most stable from an Earth-like perspective, since it resides in the SWZ for a wide range of reasonable values of the model parameters. Moreover, according to the model, outer planets (f, g, and h) cannot host liquid water on their surfaces, even with Earth-like conditions, entering a snowball state. Although very simple, the model allows us to extract the main features of the TRAPPIST-1 planetary climates.

  3. Comparative Climates of the Trappist-1 Planetary System: Results from a Simple Climate-vegetation Model

    Energy Technology Data Exchange (ETDEWEB)

    Alberti, Tommaso; Carbone, Vincenzo; Lepreti, Fabio [Dipartimento di Fisica, Università della Calabria, Ponte P. Bucci, Cubo 31C, I-87036, Rende (CS) (Italy); Vecchio, Antonio, E-mail: tommaso.alberti@unical.it, E-mail: tommasoalberti89@gmail.com [LESIA—Observatoire de Paris, PSL Research University, 5 place Jules Janssen, F-92190, Meudon (France)

    2017-07-20

    The recent discovery of the planetary system hosted by the ultracool dwarf star TRAPPIST-1 could open new paths for investigations of the planetary climates of Earth-sized exoplanets, their atmospheres, and their possible habitability. In this paper, we use a simple climate-vegetation energy-balance model to study the climate of the seven TRAPPIST-1 planets and the climate dependence on various factors: the global albedo, the fraction of vegetation that could cover their surfaces, and the different greenhouse conditions. The model allows us to investigate whether liquid water could be maintained on the planetary surfaces (i.e., by defining a “surface water zone (SWZ)”) in different planetary conditions, with or without the presence of a greenhouse effect. It is shown that planet TRAPPIST-1d seems to be the most stable from an Earth-like perspective, since it resides in the SWZ for a wide range of reasonable values of the model parameters. Moreover, according to the model, outer planets (f, g, and h) cannot host liquid water on their surfaces, even with Earth-like conditions, entering a snowball state. Although very simple, the model allows us to extract the main features of the TRAPPIST-1 planetary climates.

  4. Climate change adaptation: Comparing climate model projections of flooding against flood estimation by continuous simulation

    Science.gov (United States)

    Smith, A.; Bates, P. D.; Freer, J. E.

    2012-12-01

    Modelled assessments of climate change impacts on flooding are now increasingly used to inform adaptation and mitigation policy. These modelled assessments are typically driven by Global and Regional Climate Models (GCM/RCM). However, opinion is divided on how best to proceed, particularly with regards to the feasibility and practicality of using climate model outputs to inform management strategies. Here RCM driven projections of extreme discharges are compared against the uncertainty present in the observed record. The run-off model HBV_light is applied, within the Generalised Likelihood Uncertainty Estimation (GLUE) framework, to the Upper Avon catchment in the Midlands of England, in the U.K. A 48 year observational record of rainfall and discharge was used, with non-behavioural parameter sets being rejected through an evaluation of continuous hydrograph simulation and annual maximum discharge. The output of an RCM ensemble was used, with differing ensemble approaches, to assess climate change impacts on extreme discharge. A daily stochastic rainfall generator was then applied to the observational record and used to simulate 2000 years of discharge. RCM driven changes in extreme discharge could then be compared against the variability present in the observed record. The results suggest that coping with present uncertainty in the observed record is already a significant challenge, with the range of uncertainty in a 1 in 100 year event eclipsing the uncertainty present in climate projections.

  5. Development of BMD-1 model standard pulse current generator

    International Nuclear Information System (INIS)

    Lai Bingquan

    1998-12-01

    The BMD-1 Model Standard Pulse Current Generator is a pulse current calibration instrument. It is used to calibrate current probe, amplifier of current probe and other current measurement instruments. The standard pulse current generator uses a perfect current switch to transfer the standard direct current into the standard pulse current. It provides a variable output current ranges from 1 mA to 1 A, current accuracy is +-(0.25% + 2μA). The standard pulse generator provides three work modes of output current: DC, signal pulse and variable frequencies from 10 Hz to 1 MHz, and provides a variable pulse current widths from 0.5 to 50 μs

  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. Informing Public Perceptions About Climate Change: A 'Mental Models' Approach.

    Science.gov (United States)

    Wong-Parodi, Gabrielle; Bruine de Bruin, Wändi

    2017-10-01

    As the specter of climate change looms on the horizon, people will face complex decisions about whether to support climate change policies and how to cope with climate change impacts on their lives. Without some grasp of the relevant science, they may find it hard to make informed decisions. Climate experts therefore face the ethical need to effectively communicate to non-expert audiences. Unfortunately, climate experts may inadvertently violate the maxims of effective communication, which require sharing communications that are truthful, brief, relevant, clear, and tested for effectiveness. Here, we discuss the 'mental models' approach towards developing communications, which aims to help experts to meet the maxims of effective communications, and to better inform the judgments and decisions of non-expert audiences.

  8. Climate policies for road transport revisited (I): Evaluation of the current framework

    International Nuclear Information System (INIS)

    Creutzig, Felix; McGlynn, Emily; Minx, Jan; Edenhofer, Ottmar

    2011-01-01

    The global rise of greenhouse gas (GHG) emissions and its potentially devastating consequences require a comprehensive regulatory framework for reducing emissions, including those from the transport sector. Alternative fuels and technologies have been promoted as a means for reducing the carbon intensity of the transport sector. However, the overall transport policy framework in major world economies is geared towards the use of conventional fossil fuels. This paper evaluates the effectiveness and efficiency of current climate policies for road transport that (1) target fuel producers and/or car manufacturers, and (2) influence use of alternative fuels and technologies. With diversifying fuel supply chains, carbon intensity of fuels and energy efficiency of vehicles cannot be regulated by a single instrument. We demonstrate that vehicles are best regulated across all fuels in terms of energy per distance. We conclude that price-based policies and a cap on total emissions are essential for alleviating rebound effects and perverse incentives of fuel efficiency standards and low carbon fuel standards. In tandem with existing policy tools, cap and price signal policies incentivize all emissions reduction options. Design and effects of cap and trade in the transport sector are investigated in the companion article (). - Research highlights: → We review how alternative fuels and technologies impact climate policies in the transport sector. → Future fuel efficiency standards are best measured in units of energy intensity (MJ/km). → Fuel efficiency standards should not be attribute-based. → Renewable and low carbon fuel standards are ineffective climate policies. → Cap-and-trade in the transport sector can remedy some flaws of the current framework.

  9. 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.

  10. Bioclimatic predictions of habitat suitability for the biofuel switchgrass in North America under current and future climate scenarios

    International Nuclear Information System (INIS)

    Barney, Jacob N.; DiTomaso, Joseph M.

    2010-01-01

    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 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)

  11. Monitoring changes in precipitation and radiative energy using satellite data and climate models

    OpenAIRE

    Allan, R.P.; John, V.O.

    2009-01-01

    Current changes in the tropical hydrological cycle, including water vapour and precipitation, are\\ud presented over the period 1979-2008 based on a diverse suite of observational datasets and\\ud atmosphere-only climate models. Models capture the observed variability in tropical moisture while\\ud reanalyses cannot. Observed variability in precipitation is highly dependent upon the satellite\\ud instruments employed and only cursory agreement with model simulations, primarily relating to the\\ud ...

  12. Evaluation of the Australian Community Climate and Earth-System Simulator Chemistry-Climate Model

    Science.gov (United States)

    Stone, K. A.; Morgenstern, O.; Karoly, D. J.; Klekociuk, A. R.; French, W. J. R.; Abraham, N. L.; Schofield, R.

    2015-07-01

    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 these

  13. Validity of Differently Bias-Corrected Regional Climate Model Simulations for Streamflow Simulations under Changing Climate Conditions

    Science.gov (United States)

    Teutschbein, C.; Seibert, J.

    2012-04-01

    The direct application of Regional Climate Model (RCM) simulations in hydrological climate-change impact studies can be questionable due to the potential risk for considerable biases. Several bias correction approaches - ranging from simple scaling to rather sophisticated methods - have been developed to help impact modelers coping with the various problems linked to biased RCM output. The main disadvantage of any of these correction procedures is their underlying assumption of stationarity: the correction algorithm and its parameterization for current climate are expected to also be valid for future climate conditions. Whether or not this presupposition is actually fulfilled for future conditions cannot be evaluated - given our lack of time machines. Nevertheless, systematic testing of how well bias correction procedures perform for conditions different from those used for calibration can be done by applying a differential split-sample as proposed by Klemeš ["Operational testing of hydrological simulation models", Hydrological Sciences Journal 31, no. 1 (1986): 13-24]. This contribution summarizes shortly available bias correction methods and demonstrates their application using the example of an ensemble of 11 different RCM-simulated temperature and precipitation series. We then applied a differential split-sample test which enabled us to evaluate the performance of different bias correction procedures under changing climate conditions with only a limited amount of data (30-year records). Furthermore, we evaluated the different correction methods based on their combined influence on hydrological simulations of monthly mean streamflow as well as spring and autumn flood peaks for five meso-scale catchments in Sweden under current (1961-1990) and future (2021-2050) climate conditions. This differential split-sample test resulted in a large spread and a clear bias for some of the correction methods during validation based on an independent data set. More

  14. Modelling shifts in agroclimate and crop cultivar response under climate change.

    Science.gov (United States)

    Rötter, Reimund P; Höhn, Jukka; Trnka, Mirek; Fronzek, Stefan; Carter, Timothy R; Kahiluoto, Helena

    2013-10-01

    (i) to identify at national scale areas where crop yield formation is currently most prone to climate-induced stresses, (ii) to evaluate how the severity of these stresses is likely to develop in time and space, and (iii) to appraise and quantify the performance of two strategies for adapting crop cultivation to a wide range of (uncertain) climate change projections. To this end we made use of extensive climate, crop, and soil data, and of two modelling tools: N-AgriCLIM and the WOFOST crop simulation model. N-AgriCLIM was developed for the automatic generation of indicators describing basic agroclimatic conditions and was applied over the whole of Finland. WOFOST was used to simulate detailed crop responses at four representative locations. N-AgriCLIM calculations have been performed nationally for 3829 grid boxes at a 10 × 10 km resolution and for 32 climate scenarios. Ranges of projected shifts in indicator values for heat, drought and other crop-relevant stresses across the scenarios vary widely - so do the spatial patterns of change. Overall, under reference climate the most risk-prone areas for spring cereals are found in south-west Finland, shifting to south-east Finland towards the end of this century. Conditions for grass are likely to improve. WOFOST simulation results suggest that CO2 fertilization and adjusted sowing combined can lead to small yield increases of current barley cultivars under most climate scenarios on favourable soils, but not under extreme climate scenarios and poor soils. This information can be valuable for appraising alternative adaptation strategies. It facilitates the identification of regions in which climatic changes might be rapid or otherwise notable for crop production, requiring a more detailed evaluation of adaptation measures. The results also suggest that utilizing the diversity of cultivar responses seems beneficial given the high uncertainty in climate change projections.

  15. High resolution climate simulations with the AWI Climate Model (AWI-CM)

    Science.gov (United States)

    Sein, Dmitry; Semmler, Tido; Danilov, Sergey; Rackow, Thomas; Sidorenko, Dmitry; Jung, Thomas

    2017-04-01

    ResMIP protocol. The ocean model was initialized with 1950-1954 mean winter EN4 data. Afterwards, 50 years of coupled spin-up with constant 1950 forcing was performed. After the spin-up, both LR and HR were run with CMIP5 20th century forcing from 1950 till 2005, followed by the CMIP5 RCP8.5 scenario from 2006 till 2100. The results clearly demonstrate the added value of HR simulations for both the ocean and atmospheric climate. Biases are strongly reduced almost over the entire globe. The most remarkable reduction in 2m temperature can be seen in the equatorial Pacific, in the Kuroshio current region, and over Southeast Asia.

  16. Model for the resistive critical current transition in composite superconductors

    International Nuclear Information System (INIS)

    Warnes, W.H.

    1988-01-01

    Much of the research investigating technological type-II superconducting composites relies on the measurement of the resistive critical current transition. We have developed a model for the resistive transition which improves on older models by allowing for the very different nature of monofilamentary and multifilamentary composite structures. The monofilamentary model allows for axial current flow around critical current weak links in the superconducting filament. The multifilamentary model incorporates an additional radial current transfer between neighboring filaments. The development of both models is presented. It is shown that the models are useful for extracting more information from the experimental data than was formerly possible. Specific information obtainable from the experimental voltage-current characteristic includes the distribution of critical currents in the composite, the average critical current of the distribution, the range of critical currents in the composite, the field and temperature dependence of the distribution, and the fraction of the composite dissipating energy in flux flow at any current. This additional information about the distribution of critical currents may be helpful in leading toward a better understanding of flux pinning in technological superconductors. Comparison of the models with several experiments is given and shown to be in reasonable agreement. Implications of the models for the measurement of critical currents in technological composites is presented and discussed with reference to basic flux pinning studies in such composites

  17. 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.

  18. Climatic Calibration of Paleoecological Data and Data/Model Comparisons

    Science.gov (United States)

    Webb, T.; Bartlein, P. J.; Shuman, B.; Williams, J. W.

    2004-12-01

    When accurately and precisely dated, paleoecological data along with geochemical data and geomorphological features indicate past changes in climate. Calibrating these data in terms of standard climatic (e.g. July mean temperature) or bioclimatic (e.g. winter extreme temperatures) variables has allowed construction of paleoclimatic maps and time series that not only show the magnitude and extent of the difference in past climates but also can be compared to the output from global climate and earth-system models. Key to judging the reliability of the derived paleoclimatic estimates is the qualitative and quantitative comparison of estimates from different paleoclimatic indicators to show whether consistent or discrepant patterns exist. Here "multi-proxy" studies of independent paleoclimatic indicators from single cores, single basins, and multiple sites are providing many new opportunities to test calibration methods and results. The multi-proxy studies are also allowing researchers to develop a multivariate view of climate because different types of data, whether paleoecological or geochemical, often are sensitive to different aspects of climate change. These can be temperature changes and/or moisture changes as well as changes in seasonality or climatic extremes. Recent research mapping late Quaternary pollen, geochemical, and lake-level data across eastern North America in 1000-yr intervals illustrates some the advances gained from this multi-proxy approach to the reconstruction of past climates since the last glacial maximum 21,000 years ago.

  19. Optimization of Water Management of Cranberry Fields under Current and Future Climate Conditions

    Science.gov (United States)

    Létourneau, G.; Gumiere, S.; Mailhot, E.; Rousseau, A. N.

    2016-12-01

    In North America, cranberry production is on the rise. Since 2005, land area dedicated to cranberry doubled, principally in Canada. Recent studies have shown that sub-irrigation could lead to improvements in yield, water use efficiency and pumping energy requirements compared to conventional sprinkler irrigation. However, the experimental determination of the optimal water table level of each production site may be expensiveand time-consuming. The primary objective of this study is to optimize the water table level as a function of typical soil properties, and climatic conditions observed in major production areas using a numerical modeling approach. The second objective is to evaluate the impacts of projected climatic conditions on water management of cranberry fields. To that end, cranberry-specific management operations such as harvest flooding, rapid drainage following heavy rainfall, or hydric stress management during dry weather conditions were simulated with the HYDRUS 2D software. Results have shown that maintaining the water table approximately at 60 cm provides optimal results for most of the studied soils. However, under certain extreme climatic conditions, the drainage system design may not allow maintaining optimal hydric conditions for cranberry growth. The long-term benefit of this study has potential to advance the design of drainage/sub-irrigation systems.

  20. 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

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

    International Nuclear Information System (INIS)

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

    1998-01-01

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

  2. Consistency and discrepancy in the atmospheric response to Arctic sea-ice loss across climate models

    Science.gov (United States)

    Screen, James A.; Deser, Clara; Smith, Doug M.; Zhang, Xiangdong; Blackport, Russell; Kushner, Paul J.; Oudar, Thomas; McCusker, Kelly E.; Sun, Lantao

    2018-02-01

    The decline of Arctic sea ice is an integral part of anthropogenic climate change. Sea-ice loss is already having a significant impact on Arctic communities and ecosystems. Its role as a cause of climate changes outside of the Arctic has also attracted much scientific interest. Evidence is mounting that Arctic sea-ice loss can affect weather and climate throughout the Northern Hemisphere. The remote impacts of Arctic sea-ice loss can only be properly represented using models that simulate interactions among the ocean, sea ice, land and atmosphere. A synthesis of six such experiments with different models shows consistent hemispheric-wide atmospheric warming, strongest in the mid-to-high-latitude lower troposphere; an intensification of the wintertime Aleutian Low and, in most cases, the Siberian High; a weakening of the Icelandic Low; and a reduction in strength and southward shift of the mid-latitude westerly winds in winter. The atmospheric circulation response seems to be sensitive to the magnitude and geographic pattern of sea-ice loss and, in some cases, to the background climate state. However, it is unclear whether current-generation climate models respond too weakly to sea-ice change. We advocate for coordinated experiments that use different models and observational constraints to quantify the climate response to Arctic sea-ice loss.

  3. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model

    International Nuclear Information System (INIS)

    Cox, P.M.; Betts, R.A.; Jones, C.D.; Spall, S.A.; Totterdell, I.J.

    2000-01-01

    The continued increase in the atmospheric concentration of carbon dioxide due to anthropogenic emissions is predicted to lead to significant changes in climate. About half of the current emissions are being absorbed by the ocean and by land ecosystems, but this absorption is sensitive to climate as well as to atmospheric carbon dioxide concentrations, creating a feedback loop. General circulation models have generally excluded the feedback between climate and the biosphere, using static vegetation distributions and CO 2 concentrations from simple carbon-cycle models that do not include climate change. Here we present results from a fully coupled, three-dimensional carbon-climate model, indicating that carbon-cycle feedbacks could significantly accelerate climate change over the twenty-first century. We find that under a 'business as usual' scenario, the terrestrial biosphere acts as an overall carbon sink until about 2050, but turns into a source thereafter. By 2100, the ocean uptake rate of 5 Gt C yr -1 is balanced by the terrestrial carbon source, and atmospheric CO 2 concentrations are 250 p.p.m.v. higher in our fully coupled simulation than in uncoupled carbon models, resulting in a global-mean warming of 5.5 K, as compared to 4 K without the carbon-cycle feedback. (author)

  4. Determining the response of African biota to climate change: using the past to model the future

    Science.gov (United States)

    Willis, K. J.; Bennett, K. D.; Burrough, S. L.; Macias-Fauria, M.; Tovar, C.

    2013-01-01

    Prediction of biotic responses to future climate change in tropical Africa tends to be based on two modelling approaches: bioclimatic species envelope models and dynamic vegetation models. Another complementary but underused approach is to examine biotic responses to similar climatic changes in the past as evidenced in fossil and historical records. This paper reviews these records and highlights the information that they provide in terms of understanding the local- and regional-scale responses of African vegetation to future climate change. A key point that emerges is that a move to warmer and wetter conditions in the past resulted in a large increase in biomass and a range distribution of woody plants up to 400–500 km north of its present location, the so-called greening of the Sahara. By contrast, a transition to warmer and drier conditions resulted in a reduction in woody vegetation in many regions and an increase in grass/savanna-dominated landscapes. The rapid rate of climate warming coming into the current interglacial resulted in a dramatic increase in community turnover, but there is little evidence for widespread extinctions. However, huge variation in biotic response in both space and time is apparent with, in some cases, totally different responses to the same climatic driver. This highlights the importance of local features such as soils, topography and also internal biotic factors in determining responses and resilience of the African biota to climate change, information that is difficult to obtain from modelling but is abundant in palaeoecological records. PMID:23878343

  5. Determining the response of African biota to climate change: using the past to model the future.

    Science.gov (United States)

    Willis, K J; Bennett, K D; Burrough, S L; Macias-Fauria, M; Tovar, C

    2013-01-01

    Prediction of biotic responses to future climate change in tropical Africa tends to be based on two modelling approaches: bioclimatic species envelope models and dynamic vegetation models. Another complementary but underused approach is to examine biotic responses to similar climatic changes in the past as evidenced in fossil and historical records. This paper reviews these records and highlights the information that they provide in terms of understanding the local- and regional-scale responses of African vegetation to future climate change. A key point that emerges is that a move to warmer and wetter conditions in the past resulted in a large increase in biomass and a range distribution of woody plants up to 400-500 km north of its present location, the so-called greening of the Sahara. By contrast, a transition to warmer and drier conditions resulted in a reduction in woody vegetation in many regions and an increase in grass/savanna-dominated landscapes. The rapid rate of climate warming coming into the current interglacial resulted in a dramatic increase in community turnover, but there is little evidence for widespread extinctions. However, huge variation in biotic response in both space and time is apparent with, in some cases, totally different responses to the same climatic driver. This highlights the importance of local features such as soils, topography and also internal biotic factors in determining responses and resilience of the African biota to climate change, information that is difficult to obtain from modelling but is abundant in palaeoecological records.

  6. The origins of computer weather prediction and climate modeling

    Science.gov (United States)

    Lynch, Peter

    2008-03-01

    Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

  7. The origins of computer weather prediction and climate modeling

    International Nuclear Information System (INIS)

    Lynch, Peter

    2008-01-01

    Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed

  8. Impact of surface waves in a Regional Climate Model

    DEFF Research Database (Denmark)

    Rutgersson, Anna; Sætra, Oyvind; Semedo, Alvaro

    2010-01-01

    A coupled regional atmosphere-wave model system is developed with the purpose of investigating the impact of climate changes on the wave field, as well as feed-back effects of the wave field on the atmospheric parameters. This study focuses on the effects of introducing a two-way atmosphere......-wave coupling on the atmosphere as well as on wave parameters. The model components are the regional climate model RCA, and the third generation wave model WAM. Two different methods are used for the coupling, using the roughness length and only including the effect of growing sea, and using the wave age...... in climate models for a realistic description of processes over sea....

  9. Aerosols and clouds in chemical transport models and climate models.

    Energy Technology Data Exchange (ETDEWEB)

    Lohmann,U.; Schwartz, S. E.

    2008-03-02

    Clouds exert major influences on both shortwave and longwave radiation as well as on the hydrological cycle. Accurate representation of clouds in climate models is a major unsolved problem because of high sensitivity of radiation and hydrology to cloud properties and processes, incomplete understanding of these processes, and the wide range of length scales over which these processes occur. Small changes in the amount, altitude, physical thickness, and/or microphysical properties of clouds due to human influences can exert changes in Earth's radiation budget that are comparable to the radiative forcing by anthropogenic greenhouse gases, thus either partly offsetting or enhancing the warming due to these gases. Because clouds form on aerosol particles, changes in the amount and/or composition of aerosols affect clouds in a variety of ways. The forcing of the radiation balance due to aerosol-cloud interactions (indirect aerosol effect) has large uncertainties because a variety of important processes are not well understood precluding their accurate representation in models.

  10. 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.

  11. An Improved Model Predictive Current Controller of Switched Reluctance Machines Using Time-Multiplexed Current Sensor.

    Science.gov (United States)

    Li, Bingchu; Ling, Xiao; Huang, Yixiang; Gong, Liang; Liu, Chengliang

    2017-05-17

    This paper presents a fixed-switching-frequency model predictive current controller using multiplexed current sensor for switched reluctance machine (SRM) drives. The converter was modified to distinguish currents from simultaneously excited phases during the sampling period. The only current sensor installed in the converter was time division multiplexing for phase current sampling. During the commutation stage, the control steps of adjacent phases were shifted so that sampling time was staggered. The maximum and minimum duty ratio of pulse width modulation (PWM) was limited to keep enough sampling time for analog-to-digital (A/D) conversion. Current sensor multiplexing was realized without complex adjustment of either driver circuit nor control algorithms, while it helps to reduce the cost and errors introduced in current sampling due to inconsistency between sensors. The proposed controller is validated by both simulation and experimental results with a 1.5 kW three-phase 12/8 SRM. Satisfied current sampling is received with little difference compared with independent phase current sensors for each phase. The proposed controller tracks the reference current profile as accurately as the model predictive current controller with independent phase current sensors, while having minor tracking errors compared with a hysteresis current controller.

  12. 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...... regularities, rationalities, and pre-analytic assumptions. Lastly we discuss challenges of constructing nature(s) and how we better understand the (geo) politics of climate change modeling....

  13. On the Baltic Sea Response to Climate Change: Model Implications

    International Nuclear Information System (INIS)

    Omstedt, Anders; Leppaeranta, Matti

    1999-01-01

    The sensitivity of the Baltic Sea to climate change is reviewed on the basis of recent model studies. In general, the presently available models indicate that the Baltic Sea is a most sensitive system to climate change, particularly in air temperature, wind, fresh water inflow and the barotropic forcing in the entrance area. Available scenarios for ice conditions and climate warming around year 2100 show 2-3 months' shortening of the ice season in the Bothnian Bay and about 0.4 m decrease in the maximum annual ice thickness. Corresponding scenarios for climate cooling show 1-2 months' longer ice season in the Bothnian Bay and 0.2 - 0.5 m increase in the maximum annual ice thickness

  14. Isotopes as validation tools for global climate models

    International Nuclear Information System (INIS)

    Henderson-Sellers, A.

    2001-01-01

    Global Climate Models (GCMs) are the predominant tool with which we predict the future climate. In order that people can have confidence in such predictions, GCMs require validation. As almost every available item of meteorological data has been exploited in the construction and tuning of GCMs to date, independent validation is very difficult. This paper explores the use of isotopes as a novel and fully independent means of evaluating GCMs. The focus is the Amazon Basin which has a long history of isotope collection and analysis and also of climate modelling: both having been reported for over thirty years. Careful consideration of the results of GCM simulations of Amazonian deforestation and climate change suggests that the recent stable isotope record is more consistent with the predicted effects of greenhouse warming, possibly combined with forest removal, than with GCM predictions of the effects of deforestation alone

  15. A Bayesian hierarchical model for climate change detection and attribution

    Science.gov (United States)

    Katzfuss, Matthias; Hammerling, Dorit; Smith, Richard L.

    2017-06-01

    Regression-based detection and attribution methods continue to take a central role in the study of climate change and its causes. Here we propose a novel Bayesian hierarchical approach to this problem, which allows us to address several open methodological questions. Specifically, we take into account the uncertainties in the true temperature change due to imperfect measurements, the uncertainty in the true climate signal under different forcing scenarios due to the availability of only a small number of climate model simulations, and the uncertainty associated with estimating the climate variability covariance matrix, including the truncation of the number of empirical orthogonal functions (EOFs) in this covariance matrix. We apply Bayesian model averaging to assign optimal probabilistic weights to different possible truncations and incorporate all uncertainties into the inference on the regression coefficients. We provide an efficient implementation of our method in a software package and illustrate its use with a realistic application.

  16. 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.

  17. Large-Scale Features of Pliocene Climate: Results from the Pliocene Model Intercomparison Project

    Science.gov (United States)

    Haywood, A. M.; Hill, D.J.; Dolan, A. M.; Otto-Bliesner, B. L.; Bragg, F.; Chan, W.-L.; Chandler, M. A.; Contoux, C.; Dowsett, H. J.; Jost, A.; hide

    2013-01-01

    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-mode 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.

  18. The Perils of Modelling How Migration Responds to Climate Change

    OpenAIRE

    Feng, Bo; Partridge, Mark; Rembert, Mark

    2016-01-01

    The impact of climate change has drawn growing interests from both researchers and policymakers. Yet, relatively little is known with respect to its influence on interregional migration. The surge of extreme weather conditions could lead to the increase of forced migration from coastal to inland regions, which normally follows different patterns than voluntary migration. However, recent migration models tend to predict unrealistic migration trends under climate change in that migration would ...

  19. Multisite bias correction of precipitation data from regional climate models

    Czech Academy of Sciences Publication Activity Database

    Hnilica, Jan; Hanel, M.; Puš, V.

    2017-01-01

    Roč. 37, č. 6 (2017), s. 2934-2946 ISSN 0899-8418 R&D Projects: GA ČR GA16-05665S Grant - others:Grantová agentura ČR - GA ČR(CZ) 16-16549S Institutional support: RVO:67985874 Keywords : bias correction * regional climate model * correlation * covariance * multivariate data * multisite correction * principal components * precipitation Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Climatic research Impact factor: 3.760, year: 2016

  20. Current models of positive mental health

    Directory of Open Access Journals (Sweden)

    Stanojević Dragana Z.

    2012-01-01

    Full Text Available The concept of positive mental health represents not merely the absence of mental disease but presence of high level of happiness and well-being. In this paper we mentioned shortly the earliest concept of mental health, presented by Marie Jahoda in the mid-twentieth century. After that, we described two traditions in understanding and researching of subjective well-being: hedonic and eudaimonic approach. First approach focuses on investigation of positive affects and happiness as emotional and life satisfaction as cognitive component of subjective well-being. Second tradition emphasizes potentials and competences that person develops to the highest level, in personal and social area. Both psychological and social well-being are core concept of positive mental health psychology, designated together as positive functioning. The psychological well-being comprises six dimensions: self-acceptance, positive relations with others, environmental mastery, autonomy, purpose of life and personal growth. Social well-being consists of five dimensions: social integration, social acceptance, social contribution, social actualization and social coherence. By integrating hedonic and eudaimonic well-being as well as absence of mental disease, Corey Keyes introduced concept of complete mental health. People with complete mental health have reported absence of disease during past year and presence of high level of emotional, psychological and social well-being (flourishing. People with incomplete mental health have also reported absence of mental disease but low level of positive functioning (languishing. Keyes thought there are people with complete and incomplete mental illness; both groups report presence of mental disease, but second group has high level of positive functioning. Models of positive mental health are widely used in research studies as well as in programs for prevention and promotion of mental health. .

  1. Plant physiological models of heat, water and photoinhibition stress for climate change modelling and agricultural prediction

    Science.gov (United States)

    Nicolas, B.; Gilbert, M. E.; Paw U, K. T.

    2015-12-01

    Soil-Vegetation-Atmosphere Transfer (SVAT) models are based upon well understood steady state photosynthetic physiology - the Farquhar-von Caemmerer-Berry model (FvCB). However, representations of physiological stress and damage have not been successfully integrated into SVAT models. Generally, it has been assumed that plants will strive to conserve water at higher temperatures by reducing stomatal conductance or adjusting osmotic balance, until potentially damaging temperatures and the need for evaporative cooling become more important than water conservation. A key point is that damage is the result of combined stresses: drought leads to stomatal closure, less evaporative cooling, high leaf temperature, less photosynthetic dissipation of absorbed energy, all coupled with high light (photosynthetic photon flux density; PPFD). This leads to excess absorbed energy by Photosystem II (PSII) and results in photoinhibition and damage, neither are included in SVAT models. Current representations of photoinhibition are treated as a function of PPFD, not as a function of constrained photosynthesis under heat or water. Thus, it seems unlikely that current models can predict responses of vegetation to climate variability and change. We propose a dynamic model of damage to Rubisco and RuBP-regeneration that accounts, mechanistically, for the interactions between high temperature, light, and constrained photosynthesis under drought. Further, these predictions are illustrated by key experiments allowing model validation. We also integrated this new framework within the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA). Preliminary results show that our approach can be used to predict reasonable photosynthetic dynamics. For instances, a leaf undergoing one day of drought stress will quickly decrease its maximum quantum yield of PSII (Fv/Fm), but it won't recover to unstressed levels for several days. Consequently, cumulative effect of photoinhibition on photosynthesis can cause

  2. Modeling transient response of forests to climate change.

    Science.gov (United States)

    Dale, Virginia H; Tharp, M Lynn; Lannom, Karen O; Hodges, Donald G

    2010-03-15

    Our hypothesis is that a high diversity of dominant life forms in Tennessee forests conveys resilience to disturbance such as climate change. Because of uncertainty in climate change and their effects, three climate change scenarios for 2030 and 2080 from three General Circulation Models (GCMs) were used to simulate a range of potential climate conditions for the state. These climate changes derive from the Intergovernmental Panel on Climate Change (IPCC) "A1B" storyline that assumes rapid global economic growth. The precipitation and temperature projections from the three GCMs for 2030 and 2080 were related to changes in five ecological provinces using the monthly record of temperature and precipitation from 1980 to 1997 for each 1km cell across the state as aggregated into the provinces. Temperatures are projected to increase in all ecological provinces in all months for all three GCMs for both 2030 and 2080. Precipitation differences from the long-term average are more complex but less striking. The forest ecosystem model LINKAGES was used to simulate conditions for five ecological provinces from 1989 to 2300. Average output projects changes in tree diversity and species composition in all ecological provinces in Tennessee with the greatest changes in the Southern Mixed Forest province. Projected declines in total tree biomass are followed by biomass recovery as species replacement occurs in stands. The Southern Mixed Forest province results in less diversity in dominant trees as well as lower overall biomass than projections for the other four provinces. The biomass and composition changes projected in this study differ from forest dynamics expected without climate change. These results suggest that biomass recovery following climate change is linked to dominant tree diversity in the southeastern forest of the US. The generality of this observation warrants further investigation, for it relates to ways that forest management may influence climate change effects.

  3. Considerations for building climate-based species distribution models

    Science.gov (United States)

    Bucklin, David N.; Basille, Mathieu; Romañach, Stephanie; Brandt, Laura A.; Mazzotti, Frank J.; Watling, James I.

    2016-01-01

    Climate plays an important role in the distribution of species. A given species may adjust to new conditions in-place, move to new areas with suitable climates, or go extinct. Scientists and conservation practitioners use mathematical models to predict the effects of future climate change on wildlife and plan for a biodiverse future. This 8-page fact sheet written by David N. Bucklin, Mathieu Basille, Stephanie S. Romañach, Laura A. Brandt, Frank J. Mazzotti, and James I. Watling and published by the Department of Wildlife Ecology and Conservation explains how, with a better understanding of species distribution models, we can predict how species may respond to climate change. The models alone cannot tell us how a certain species will actually respond to changes in climate, but they can inform conservation planning that aims to allow species to both adapt in place and (for those that are able to) move to newly suitable areas. Such planning will likely minimize loss of biodiversity due to climate change.

  4. CLIMBER-2: a climate system model of intermediate complexity. Pt. 1. Model description and performance for present climate

    Energy Technology Data Exchange (ETDEWEB)

    Petoukhov, V.; Ganopolski, A.; Brovkin, V.; Claussen, M.; Eliseev, A.; Kubatzki, C.; Rahmstorf, S.

    1998-02-01

    A 2.5-dimensional climate system model of intermediate complexity CLIMBER-2 and its performance for present climate conditions are presented. The model consists of modules describing atmosphere, ocean, sea ice, land surface processes, terrestrial vegetation cover, and global carbon cycle. The modules interact (on-line) through the fluxes of momentum, energy, water and carbon. The model has a coarse spatial resolution, allowing nevertheless to capture the major features of the Earth`s geography. The model describes temporal variability of the system on seasonal and longer time scales. Due to the fact that the model does not employ any type of flux adjustment and has fast turnaround time, it can be used for study of climates significantly different from the present one and allows to perform long-term (multimillennia) simulations. The constraints for coupling the atmosphere and ocean without flux adjustment are discussed. The results of a model validation against present climate data show that the model successfully describes the seasonal variability of a large set of characteristics of the climate system, including radiative balance, temperature, precipitation, ocean circulation and cryosphere. (orig.) 62 refs.

  5. Historical and idealized climate model experiments: an EMIC intercomparison

    DEFF Research Database (Denmark)

    Eby, M.; Weaver, A. J.; Alexander, K.

    2012-01-01

    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...... the Medieval Climate Anomaly and the Little Ice Age estimated from paleoclimate reconstructions. This in turn could be a result of errors in the reconstructions of volcanic and/or solar radiative forcing used to drive the models or the incomplete representation of certain processes or variability within...

  6. Production functions for climate policy modeling. An empirical analysis

    International Nuclear Information System (INIS)

    Van der Werf, Edwin

    2008-01-01

    Quantitative models for climate policy modeling differ in the production structure used and in the sizes of the elasticities of substitution. The empirical foundation for both is generally lacking. This paper estimates the parameters of 2-level CES production functions with capital, labour and energy as inputs, and is the first to systematically compare all nesting structures. Using industry-level data from 12 OECD countries, we find that the nesting structure where capital and labour are combined first, fits the data best, but for most countries and industries we cannot reject that all three inputs can be put into one single nest. These two nesting structures are used by most climate models. However, while several climate policy models use a Cobb-Douglas function for (part of the) production function, we reject elasticities equal to one, in favour of considerably smaller values. Finally we find evidence for factor-specific technological change. With lower elasticities and with factor-specific technological change, some climate policy models may find a bigger effect of endogenous technological change on mitigating the costs of climate policy. (author)

  7. Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models.

    Science.gov (United States)

    Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Barbraud, Christophe; Weimerskirch, Henri; Serreze, Mark; Caswell, Hal

    2012-09-01

    Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa , because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SICa , which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor

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

    DEFF Research Database (Denmark)

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

    2017-01-01

    unknown among models. Using median model ensemble values, yield increased on average 6% per 100-ppm C, declined 4.6% per °C, and declined 2% for every 10% decrease in rainfall (for non-irrigated sites). Differences in predictions due to model representation of light utilization were significant (p ...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......) input management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield...

  9. Detailed Urban Heat Island Projections for Cities Worldwide: Dynamical Downscaling CMIP5 Global Climate Models

    OpenAIRE

    Lauwaet, Dirk; Hooyberghs, Hans; Maiheu, Bino; Lefebvre, Wouter; Driesen, Guy; Looy, Stijn Van; Ridder, Koen De

    2015-01-01

    A new dynamical downscaling methodology to analyze the impact of global climate change on the local climate of cities worldwide is presented. The urban boundary layer climate model UrbClim is coupled to 11 global climate models contained in the Coupled Model Intercomparison Project 5 archive, conducting 20-year simulations for present (1986–2005) and future (2081–2100) climate conditions, considering the Representative Concentration Pathway 8.5 climate scenario. The evolution of the urban hea...

  10. Classical Ecological Restoration and its Current Challenges: Assisted Migration as an Adaptation Strategy to Climate Change

    Directory of Open Access Journals (Sweden)

    Pilar A. Gómez-Ruiz

    2017-06-01

    Full Text Available Ecological restoration is a very active area in ecology and of great importance for ecosystems management. Despite of being a relatively young discipline, the classical concepts of restoration seem, at present, impractical considering the great challenges generated by modification and destruction of ecosystems. This is due to anthropic activities (deforestation, change of land use, pollution and global climate change. In the classic definition of restoration, the objective is to recover the degraded ecosystem to the same conditions of a historical reference state. However, nowadays the ecosystems return to a state prior to the disturbances seems unviable, because the thresholds of resilience have already been overcome. Additionally, climate change is causing environmental changes at an unprecedented rate. For this reason, ecological restoration needs to unite efforts of diverse actors to recover ecosystems that can be sustainable and functional in the future, where the species could be able to tolerate the environmental conditions that will exist in the long term. Assisted migration has been proposed as a conservation strategy; it is defined as the translocation of species to new locations outside their known range of distribution. In the current context of loss of diversity and ecosystems, this strategy could be fundamental for the formation of new communities that can later become novel ecosystems where species that are fundamental to the dynamics of ecosystems can persist and, at the same time, recover function, structure and resilience.

  11. How Useful Are Species Distribution Models for Managing Biodiversity under Future Climates?

    Directory of Open Access Journals (Sweden)

    Steve J. Sinclair

    2010-03-01

    Full Text Available Climate change presents unprecedented challenges for biological conservation. Agencies are increasingly looking to modeled projections of species' distributions under future climates to inform management strategies. As government scientists with a responsibility to communicate the best available science to our policy colleagues, we question whether current modeling approaches and outputs are practically useful. Here, we synthesize conceptual problems with species distribution models (SDMs associated with interspecific interactions, dispersal, ecological equilibria and time lags, evolution, and the sampling of niche space. Although projected SDMs have undoubtedly been critical in alerting us to the magnitude of climate change impacts, we conclude that until they offer insights that are more precise than what we can derive from basic ecological theory, we question their utility in deciding how to allocate scarce funds to large-scale conservation projects.

  12. Quantification of key parameters for treating contrails in a large scale climate model

    Energy Technology Data Exchange (ETDEWEB)

    Ponater, M.; Gierens, K. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Wessling (Germany). Inst. fuer Physik der Atmosphaere

    1997-12-01

    The general objective of this project, to determine contrail key parameters with respect to their climate effect, has been approached by three tasks: (1) quantification of microphysical key parameters, (2) development of a contrail coverage parametrization for climate models, and (3) determination of the worldwide coverage with persistent contrails due to present day air traffic. The microphysical key parameters are determined using microphysical box model simulations. The contrail parametrization was achieved by deriving (from aircraft measurements) the instantaneous fluctuations of temperature and relative humidity that occur on spatial scales beyond the resolution of climate models. The global and annual mean coverage by persistent contrails was calculated from ECMWF numerical analyses and from actual air traffic density. It was found to be currently about 0.1%, though the atmosphere has the potential to form persistent contrails over a much larger area. (orig.) 144 figs., 42 tabs., 497 refs.

  13. Modeling Climate Change Impacts on Landscape Evolution, Fire, and Hydrology

    Science.gov (United States)

    Sheppard, B. S.; O Connor, C.; Falk, D. A.; Garfin, G. M.

    2015-12-01

    Landscape disturbances such as wildfire interact with climate variability to influence hydrologic regimes. We coupled landscape, fire, and hydrologic models and forced them using projected climate to demonstrate climate change impacts anticipated at Fort Huachuca in southeastern Arizona, USA. The US Department of Defense (DoD) recognizes climate change as a trend that has implications for military installations, national security and global instability. The goal of this DoD Strategic Environmental Research and Development Program (SERDP) project (RC-2232) is to provide decision making tools for military installations in the southwestern US to help them adapt to the operational realities associated with climate change. For this study we coupled the spatially explicit fire and vegetation dynamics model FireBGCv2 with the Automated Geospatial Watershed Assessment tool (AGWA) to evaluate landscape vegetation change, fire disturbance, and surface runoff in response to projected climate forcing. A projected climate stream for the years 2005-2055 was developed from the Multivariate Adaptive Constructed Analogs (MACA) 4 km statistical downscaling of the CanESM2 GCM using Representative Concentration Pathway (RCP) 8.5. AGWA, an ArcGIS add-in tool, was used to automate the parameterization and execution of the Soil Water Assessment Tool (SWAT) and the KINematic runoff and EROSion2 (KINEROS2) models based on GIS layers. Landscape raster data generated by FireBGCv2 project an increase in fire and drought associated tree mortality and a decrease in vegetative basal area over the years of simulation. Preliminary results from SWAT modeling efforts show an increase to surface runoff during years following a fire, and for future winter rainy seasons. Initial results from KINEROS2 model runs show that peak runoff rates are expected to increase 10-100 fold as a result of intense rainfall falling on burned areas.

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

    Science.gov (United States)

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

    2018-04-01

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

  15. Modelling interactions of carbon dioxide, forests, and climate

    International Nuclear Information System (INIS)

    Luxmoore, R.J.; Baldocchi, D.D.

    1994-01-01

    Atmospheric carbon dioxide is rising and forests and climate is changing exclamation point This combination of fact and premise may be evaluated at a range of temporal and spatial scales with the aid of computer simulators describing the interrelationships between forest vegetation, litter and soil characteristics, and appropriate meteorological variables. Some insights on the effects of climate on the transfers of carbon and the converse effect of carbon transfer on climate are discussed as a basis for assessing the significance of feedbacks between vegetation and climate under conditions of rising atmospheric carbon dioxide. Three main classes of forest models are reviewed. These are physiologically-based models, forest succession simulators based on the JABOWA model, and ecosystem-carbon budget models that use compartment transfer rates with empirically estimated coefficients. Some regression modeling approaches are also outlined. Energy budget models applied to forests and grasslands are also reviewed. This review presents examples of forest models; a comprehensive discussion of all available models is not undertaken

  16. Wind climate modeling using Weibull and extreme value distribution ...

    African Journals Online (AJOL)

    The expected number of stress cycles in the projected working life of a structure is related to the expected number of hours in the critical wind speed range and wind climate modelling is required to know this. The most popular model for this purpose is Weibull distribution. Again, wind energy is proportional to the cube of the ...

  17. Optimising the FAMOUS climate model: inclusion of global carbon cycling

    Directory of Open Access Journals (Sweden)

    J. H. T. Williams

    2013-01-01

    Full Text Available FAMOUS fills an important role in the hierarchy of climate models, both explicitly resolving atmospheric and oceanic dynamics yet being sufficiently computationally efficient that either very long simulations or large ensembles are possible. An improved set of carbon cycle parameters for this model has been found using a perturbed physics ensemble technique. This is an important step towards building the "Earth System" modelling capability of FAMOUS, which is a reduced resolution, and hence faster running, version of the Hadley Centre Climate model, HadCM3. Two separate 100 member perturbed parameter ensembles were performed; one for the land surface and one for the ocean. The land surface scheme was tested against present-day and past representations of vegetation and the ocean ensemble was tested against observations of nitrate. An advantage of using a relatively fast climate model is that a large number of simulations can be run and hence the model parameter space (a large source of climate model uncertainty can be more thoroughly sampled. This has the associated benefit of being able to assess the sensitivity of model results to changes in each parameter. The climatologies of surface and tropospheric air temperature and precipitation are improved relative to previous versions of FAMOUS. The improved representation of upper atmosphere temperatures is driven by improved ozone concentrations near the tropopause and better upper level winds.

  18. Model prediction of maize yield responses to climate change in ...

    African Journals Online (AJOL)

    Observed data of the last three decades (1971 to 2000) from several climatological stations in north-eastern Zimbabwe and outputs from several global climate models were used. The downscaled model simulations consistently predicted a warming of between 1 and 2 ºC above the baseline period (1971-2000) at most of ...

  19. Climate effects of anthropogenic sulfate: Simulations from a coupled chemistry/climate model

    International Nuclear Information System (INIS)

    Chuang, C.C.; Penner, J.E.; Taylor, K.E.; Walton, J.J.

    1993-09-01

    In this paper, we use a more comprehensive approach by coupling a climate model with a 3-D global chemistry model to investigate the forcing by anthropogenic aerosol sulfate. The chemistry model treats the global-scale transport, transformation, and removal of SO 2 , DMS and H 2 SO 4 species in the atmosphere. The mass concentration of anthropogenic sulfate from fossil fuel combustion and biomass burning is calculated in the chemistry model and provided to the climate model where it affects the shortwave radiation. We also investigate the effect, with cloud nucleation parameterized in terms of local aerosol number, sulfate mass concentration and updraft velocity. Our simulations indicate that anthropogenic sulfate may result in important increases in reflected solar radiation, which would mask locally the radiative forcing from increased greenhouse gases. Uncertainties in these results will be discussed

  20. Climate effects of anthropogenic sulfate: Simulations from a coupled chemistry/climate model

    Energy Technology Data Exchange (ETDEWEB)

    Chuang, C.C.; Penner, J.E.; Taylor, K.E.; Walton, J.J.

    1993-09-01

    In this paper, we use a more comprehensive approach by coupling a climate model with a 3-D global chemistry model to investigate the forcing by anthropogenic aerosol sulfate. The chemistry model treats the global-scale transport, transformation, and removal of SO{sub 2}, DMS and H{sub 2}SO{sub 4} species in the atmosphere. The mass concentration of anthropogenic sulfate from fossil fuel combustion and biomass burning is calculated in the chemistry model and provided to the climate model where it affects the shortwave radiation. We also investigate the effect, with cloud nucleation parameterized in terms of local aerosol number, sulfate mass concentration and updraft velocity. Our simulations indicate that anthropogenic sulfate may result in important increases in reflected solar radiation, which would mask locally the radiative forcing from increased greenhouse gases. Uncertainties in these results will be discussed.

  1. Current-voltage model of LED light sources

    DEFF Research Database (Denmark)

    Beczkowski, Szymon; Munk-Nielsen, Stig

    2012-01-01

    Amplitude modulation is rarely used for dimming light-emitting diodes in polychromatic luminaires due to big color shifts caused by varying magnitude of LED driving current and nonlinear relationship between intensity of a diode and driving current. Current-voltage empirical model of light...

  2. Modelling of diurnal cycle under climate change

    Energy Technology Data Exchange (ETDEWEB)

    Eliseev, A.V.; Bezmenov, K.V.; Demchenko, P.F.; Mokhov, I.I.; Petoukhov, V.K. [Russian Academy of Sciences, Moscow (Russian Federation). Inst. of Atmospheric Physics

    1995-12-31

    The observed diurnal temperature range (DTR) displays remarkable change during last 30 years. Land air DTR generally decreases under global climate warming due to more significant night minimum temperature increase in comparison with day maximum temperature increase. Atmosphere hydrological cycle characteristics change under global warming and possible background aerosol atmosphere content change may cause essential errors in the estimation of DTR tendencies of change under global warming. The result of this study is the investigation of cloudiness effect on the DTR and blackbody radiative emissivity diurnal range. It is shown that in some cases (particularly in cold seasons) it results in opposite change in DTR and BD at doubled CO{sub 2} atmosphere content. The influence of background aerosol is the same as the cloudiness one

  3. Climate Informatics

    Science.gov (United States)

    Monteleoni, Claire; Schmidt, Gavin A.; Alexander, Francis J.; Niculescu-Mizil, Alexandru; Steinhaeuser, Karsten; Tippett, Michael; Banerjee, Arindam; Blumenthal, M. Benno; Ganguly, Auroop R.; Smerdon, Jason E.; hide

    2013-01-01

    The impacts of present and potential future climate change will be one of the most important scientific and societal challenges in the 21st century. Given observed changes in temperature, sea ice, and sea level, improving our understanding of the climate system is an international priority. This system is characterized by complex phenomena that are imperfectly observed and even more imperfectly simulated. But with an ever-growing supply of climate data from satellites and environmental sensors, the magnitude of data and climate model output is beginning to overwhelm the relatively simple tools currently used to analyze them. A computational approach will therefore be indispensable for these analysis challenges. This chapter introduces the fledgling research discipline climate informatics: collaborations between climate scientists and machine learning researchers in order to bridge this gap between data and understanding. We hope that the study of climate informatics will accelerate discovery in answering pressing questions in climate science.

  4. Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies

    Directory of Open Access Journals (Sweden)

    A. Loew

    2013-09-01

    Full Text Available Soil moisture is an essential climate variable (ECV of major importance for land–atmosphere interactions and global hydrology. An appropriate representation of soil moisture dynamics in global climate models is therefore important. Recently, a first multidecadal, observation-based soil moisture dataset has become available that provides information on soil moisture dynamics from satellite observations (ECVSM, essential climate variable soil moisture. The present study investigates the potential and limitations of this new dataset for several applications in climate model evaluation. We compare soil moisture data from satellite observations, reanalysis and simulations from a state-of-the-art land surface model and analyze relationships between soil moisture and precipitation anomalies in the different dataset. Other potential applications like model parameter optimization or model initialization are not investigated in the present study. In a detailed regional study, we show that ECVSM is capable to capture well the interannual and intraannual soil moisture and precipitation dynamics in the Sahelian region. Current deficits of the new dataset are critically discussed and summarized at the end of the paper to provide guidance for an appropriate usage of the ECVSM dataset for climate studies.

  5. Estimating climate model systematic errors in a climate change impact study of the Okavango River basin, southwestern Africa using a mesoscale model

    Science.gov (United States)

    Raghavan, S. V.; Todd, M.

    2007-12-01

    Simulating the impact of future climate variability and change on hydrological systems requires estimates of climate at high spatial resolution compatible with hydrological models. Here we present initial results of a project to simulate future climate over the Okavango River basin and delta in Southwestern Africa. Given the significance of the delta to biodiversity and as a resource to the local population, there is considerable concern regarding the sensitivity of the system to future climate change. An important component of climate variability/change impact studies is an assessment of errors in the modeling suite. Here, we attempt to quantify errors and uncertainties involved in regional climate modelling that will impact on hydrological simulations. The study determines the ability of the MM5 Regional Climate Model to simulate the present day regional climate at the high resolution required by the hydrological models and the effectiveness of the RCM in downscaling GCM outputs to study regional climate change and impacts.

  6. Current practices and future opportunities for policy on climate change and invasive species.

    Science.gov (United States)

    Pyke, Christopher R; Thomas, Roxanne; Porter, Read D; Hellmann, Jessica J; Dukes, Jeffrey S; Lodge, David M; Chavarria, Gabriela

    2008-06-01

    Climate change and invasive species are often treated as important, but independent, issues. Nevertheless, they have strong connections: changes in climate and societal responses to climate change may exacerbate the impacts of invasive species, whereas invasive species may affect the magnitude, rate, and impact of climate change. We argue that the design and implementation of climate-change policy in the United States should specifically consider the implications for invasive species; conversely, invasive-species policy should address consequences for climate change. The development of such policies should be based on (1) characterization of interactions between invasive species and climate change, (2) identification of areas where climate-change policies could negatively affect invasive-species management, and (3) identification of areas where policies could benefit from synergies between climate change and invasive-species management.

  7. Climate Modeling and Analysis with Decision Makers in Mind

    Science.gov (United States)

    Jones, A. D.; Jagannathan, K.; Calvin, K. V.; Lamarque, J. F.; Ullrich, P. A.

    2016-12-01

    There is a growing need for information about future climate conditions to support adaptation planning across a wide range of sectors and stakeholder communities. However, our principal tools for understanding future climate - global Earth system models - were not developed with these user needs in mind, nor have we developed transparent methods for evaluating and communicating the credibility of various climate information products with respect to the climate characteristics that matter most to decision-makers. Several recent community engagements have identified a need for "co-production" of knowledge among stakeholders and scientists. Here we highlight some of the barriers to communication and collaboration that must be overcome to improve the dialogue among researchers and climate adaptation practitioners in a meaningful way. Solutions to this challenge are two-fold: 1) new institutional arrangements and collaborative mechanisms designed to improve coordination and understanding among communities, and 2) a research agenda that explicitly incorporates stakeholder needs into model evaluation, development, and experimental design. We contrast the information content in global-scale model evaluation exercises with that required for in specific decision contexts, such as long-term agricultural management decisions. Finally, we present a vision for advancing the science of model evaluation in the context of predicting decision-relevant hydroclimate regime shifts in North America.

  8. Modeled impact of anthropogenic land cover change on climate

    Science.gov (United States)

    Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J.

    2007-01-01

    Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.

  9. A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

    Science.gov (United States)

    Ashraf, M Irfan; Meng, Fan-Rui; Bourque, Charles P-A; MacLean, David A

    2015-01-01

    Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2) 5-year(-1) and volume: 0.0008 m(3) 5-year(-1)). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm(2) 5-year(-1) and 0.0393 m(3) 5-year(-1) in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology

  10. A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

    Directory of Open Access Journals (Sweden)

    M Irfan Ashraf

    Full Text Available Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model. Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2 5-year(-1 and volume: 0.0008 m(3 5-year(-1. Model variability described by root mean squared error (RMSE in basal area prediction was 40.53 cm(2 5-year(-1 and 0.0393 m(3 5-year(-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence

  11. Online-coupled meteorology and chemistry models: history, current status, and outlook

    Directory of Open Access Journals (Sweden)

    Y. Zhang

    2008-06-01

    Full Text Available The climate-chemistry-aerosol-cloud-radiation feedbacks are important processes occurring in the atmosphere. Accurately simulating those feedbacks requires fully-coupled meteorology, climate, and chemistry models and presents significant challenges in terms of both scientific understanding and computational demand. This paper reviews the history and current status of the development and application of online-coupled meteorology and chemistry models, with a focus on five representative models developed in the US including GATOR-GCMOM, WRF/Chem, CAM3, MIRAGE, and Caltech unified GCM. These models represent the current status and/or the state-of-the science treatments of online-coupled models worldwide. Their major model features, typical applications, and physical/chemical treatments are compared with a focus on model treatments of aerosol and cloud microphysics and aerosol-cloud interactions. Aerosol feedbacks to planetary boundary layer meteorology and aerosol indirect effects are illustrated with case studies for some of these models. Future research needs for model development, improvement, application, as well as major challenges for online-coupled models are discussed.

  12. Misleading prioritizations from modelling range shifts under climate change

    Science.gov (United States)

    Sofaer, Helen R.; Jarnevich, Catherine S.; Flather, Curtis H.

    2018-01-01

    AimConservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change.LocationConterminous U.S.A.Time period1977–2014.Major taxa studiedPasserine birds.MethodsWe estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c. 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size.ResultsSpecies distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species.Main conclusionsModels failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and

  13. High Resolution Modelling of Crop Response to Climate Change

    Science.gov (United States)

    Mirmasoudi, S. S.; Byrne, J. M.; MacDonald, R. J.; Lewis, D.

    2014-12-01

    Crop production is one of the most vulnerable sectors to climatic variability and change. Increasing atmospheric CO2 concentration and other greenhouse gases are causing increases in global temperature. In western North America, water supply is largely derived from mountain snowmelt. Climate change will have a significant impact on mountain snowpack and subsequently, the snow-derived water supply. This will strain water supplies and increase water demand in areas with substantial irrigation agriculture. Increasing temperatures may create heat stress for some crops regardless of soil water supply, and increasing surface O3 and other pollutants may damage crops and ecosystems. CO2 fertilization may or may not be an advantage in future. This work is part of a larger study that will address a series of questions based on a range of future climate scenarios for several watersheds in western North America. The key questions are: (1) how will snowmelt and rainfall runoff vary in future; (2) how will seasonal and inter-annual soil water supply vary, and how might that impacts food supplies; (3) how might heat stress impact (some) crops even with adequate soil water; (4) will CO2 fertilization alter crop yields; and (5) will pollution loads, particularly O3, cause meaningful changes to crop yields? The Generate Earth Systems Science (GENESYS) Spatial Hydrometeorological Model is an innovative, efficient, high-resolution model designed to assess climate driven changes in mountain snowpack derived water supplies. We will link GENESYS to the CROPWAT crop model system to assess climate driven changes in water requirement and associated crop productivity for a range of future climate scenarios. Literature bases studies will be utilised to develop approximate crop response functions for heat stress, CO2 fertilization and for O3 damages. The overall objective is to create modeling systems that allows meaningful assessment of agricultural productivity at a watershed scale under a

  14. Evaluating the impacts of climate change on diurnal wind power cycles using multiple regional climate models

    KAUST Repository

    Goddard, Scott D.

    2015-05-01

    Electrical utility system operators must plan resources so that electricity supply matches demand throughout the day. As the proportion of wind-generated electricity in the US grows, changes in daily wind patterns have the potential either to disrupt the utility or increase the value of wind to the system over time. Wind power projects are designed to last many years, so at this timescale, climate change may become an influential factor on wind patterns. We examine the potential effects of climate change on the average diurnal power production cycles at 12 locations in North America by analyzing averaged and individual output from nine high-resolution regional climate models comprising historical (1971–1999) and future (2041–2069) periods. A semi-parametric mixed model is fit using cubic B-splines, and model diagnostics are checked. Then, a likelihood ratio test is applied to test for differences between the time periods in the seasonal daily averaged cycles, and agreement among the individual regional climate models is assessed. We investigate the significant changes by combining boxplots with a differencing approach and identify broad categories of changes in the amplitude, shape, and position of the average daily cycles. We then discuss the potential impact of these changes on wind power production.

  15. Managing uncertainty in climate-driven ecological models to inform adaptation to climate change

    Science.gov (United States)

    Jeremy S. Littell; Donald McKenzie; Becky K. Kerns; Samuel Cushman; Charles G. Shaw

    2011-01-01

    The impacts of climate change on forest ecosystems are likely to require changes in forest planning and natural resource management. Changes in tree growth, disturbance extent and intensity, and eventually species distributions are expected. In natural resource management and planning, ecosystem models are typically used to provide a "best estimate" about how...

  16. Peformance Tuning and Evaluation of a Parallel Community Climate Model

    Energy Technology Data Exchange (ETDEWEB)

    Drake, J.B.; Worley, P.H.; Hammond, S.

    1999-11-13

    The Parallel Community Climate Model (PCCM) is a message-passing parallelization of version 2.1 of the Community Climate Model (CCM) developed by researchers at Argonne and Oak Ridge National Laboratories and at the National Center for Atmospheric Research in the early to mid 1990s. In preparation for use in the Department of Energy's Parallel Climate Model (PCM), PCCM has recently been updated with new physics routines from version 3.2 of the CCM, improvements to the parallel implementation, and ports to the SGIKray Research T3E and Origin 2000. We describe our experience in porting and tuning PCCM on these new platforms, evaluating the performance of different parallel algorithm options and comparing performance between the T3E and Origin 2000.

  17. Interactions of landscape disturbances and climate change dictate ecological pattern and process: spatial modeling of wildfire, insect, and disease dynamics under future climates

    Science.gov (United States)

    Loehman, Rachel A.; Keane, Robert E.; Holsinger, Lisa M.; Wu, Zhiwei

    2016-01-01

    ContextInteractions among disturbances, climate, and vegetation influence landscape patterns and ecosystem processes. Climate changes, exotic invasions, beetle outbreaks, altered fire regimes, and human activities may interact to produce landscapes that appear and function beyond historical analogs.ObjectivesWe used the mechanistic ecosystem-fire process model FireBGCv2 to model interactions of wildland fire, mountain pine beetle (Dendroctonus ponderosae), and white pine blister rust (Cronartium ribicola) under current and future climates, across three diverse study areas.MethodsWe assessed changes in tree basal area as a measure of landscape response over a 300-year simulation period for the Crown of the Continent in north-central Montana, East Fork of the Bitterroot River in western Montana, and Yellowstone Central Plateau in western Wyoming, USA.ResultsInteracting disturbances reduced overall basal area via increased tree mortality of host species. Wildfire decreased basal area more than beetles or rust, and disturbance interactions modeled under future climate significantly altered landscape basal area as compared with no-disturbance and current climate scenarios. Responses varied among landscapes depending on species composition, sensitivity to fire, and pathogen and beetle suitability and susceptibility.ConclusionsUnderstanding disturbance interactions is critical for managing landscapes because forest responses to wildfires, pathogens, and beetle attacks may offset or exacerbate climate influences, with consequences for wildlife, carbon, and biodiversity.

  18. EcoClimate: a database of climate data from multiple models for past, present, and future for macroecologists and biogeographers

    Directory of Open Access Journals (Sweden)

    Matheus Souza Lima-Ribeiro

    2015-08-01

    Full Text Available Studies in biogeography and macroecology have been increasing massively since climate and biodiversity databases became easily accessible. Climate simulations for past, present, and future have enabled macroecologists and biogeographers to combine data on species’ occurrences with detailed information on climatic conditions through time to predict biological responses across large spatial and temporal scales. Here we present and describe ecoClimate, a free and open data repository developed to serve useful climate data to macroecologists and biogeographers. ecoClimate arose from the need for climate layers with which to build ecological niche models and test macroecological and biogeographic hypotheses in the past, present, and future. ecoClimate offers a suite of processed, multi-temporal climate data sets from the most recent multi-model ensembles developed by the Coupled Modeling Intercomparison Projects (CMIP5 and Paleoclimate Modeling Intercomparison Projects (PMIP3 across past, present, and future time frames, at global extents and 0.5° spatial resolution, in convenient formats for analysis and manipulation. A priority of ecoClimate is consistency across these diverse data, but retaining information on uncertainties among model predictions. The ecoClimate research group intends to maintain the web repository updated continuously as new model outputs become available, as well as software that makes our workflows broadly accessible.

  19. A Model for Collaborative Learning in Undergraduate Climate Change Courses

    Science.gov (United States)

    Teranes, J. L.

    2008-12-01

    Like several colleges and universities across the nation, the University of California, San Diego, has introduced climate change topics into many existing and new undergraduate courses. I have administered a program in this area at UCSD and have also developed and taught a new lower-division UCSD course entitled "Climate Change and Society", a general education course for non-majors. This class covers the basics of climate change, such as the science that explains it, the causes of climate change, climate change impacts, and mitigation strategies. The teaching methods for this course stress interdisciplinary approaches. I find that inquiry-based and collaborative modes of learning are particularly effective when applied to science-based climate, environmental and sustainability topics. Undergraduate education is often dominated by a competitive and individualistic approach to learning. In this approach, individual success is frequently perceived as contingent on others being less successful. Such a model is at odds with commonly stated goals of teaching climate change and sustainability, which are to equip students to contribute to the debate on global environmental change and societal adaptation strategies; and to help students become better informed citizens and decision makers. I present classroom-tested strategies for developing collaborative forms of learning in climate change and environmental courses, including team projects, group presentations and group assessment exercises. I show how critical thinking skills and long-term retention of information can benefit in the collaborative mode of learning. I find that a collaborative learning model is especially appropriate to general education courses in which the enrolled student body represents a wide diversity of majors, class level and expertise. I also connect collaborative coursework in interdisciplinary environmental topics directly to applications in the field, where so much "real-world" achievement in

  20. Extending to seasonal scales the current usage of short range weather forecasts and climate projections for water management in Spain

    Science.gov (United States)

    Rodriguez-Camino, Ernesto; Voces, José; Sánchez, Eroteida; Navascues, Beatriz; Pouget, Laurent; Roldan, Tamara; Gómez, Manuel; Cabello, Angels; Comas, Pau; Pastor, Fernando; Concepción García-Gómez, M.°; José Gil, Juan; Gil, Delfina; Galván, Rogelio; Solera, Abel

    2016-04-01

    This presentation, first, briefly describes the current use of weather forecasts and climate projections delivered by AEMET for water management in Spain. The potential use of seasonal climate predictions for water -in particular dams- management is then discussed more in-depth, using a pilot experience carried out by a multidisciplinary group coordinated by AEMET and DG for Water of Spain. This initiative is being developed in the framework of the national implementation of the GFCS and the European project, EUPORIAS. Among the main components of this experience there are meteorological and hydrological observations, and an empirical seasonal forecasting technique that provides an ensemble of water reservoir inflows. These forecasted inflows feed a prediction model for the dam state that has been adapted for this purpose. The full system is being tested retrospectively, over several decades, for selected water reservoirs located in different Spanish river basins. The assessment includes an objective verification of the probabilistic seasonal forecasts using standard metrics, and the evaluation of the potential social and economic benefits, with special attention to drought and flooding conditions. The methodology of implementation of these seasonal predictions in the decision making process is being developed in close collaboration with final users participating in this pilot experience.

  1. Climate change web picker. A tool bridging daily climate needs in process based modelling in forestry and agriculture

    International Nuclear Information System (INIS)

    Palma, J.H.N.

    2017-01-01

    Aim of study: Climate data is a need for different types of modeling assessments, especially those involving process based modeling focusing on climate change impacts. However, there is a scarcity of tools delivering easy access to climate datasets to use in biological related modeling. This study aimed at the development of a tool that could provide an user-friendly interface to facilitate access to climate datasets, that are used to supply climate scenarios for the International Panel on Climate Change. Area of study: The tool provides daily datasets across Europe, and also parts of northern Africa Material and Methods: The tool uses climatic datasets generated from third party sources (IPCC related) while a web based interface was developed in JavaScript to ease the access to the datasets Main Results: The interface delivers daily (or monthly) climate data from a user-defined location in Europe for 7 climate variables: minimum and maximum temperature, precipitation, radiation, minimum and maximum relative humidity and wind speed). The time frame ranges from 1951 to 2100, providing the basis to use the data for climate change impact assessments. The tool is free and publicly available at http://www.isa.ulisboa.pt/proj/clipick/. Research Highlights: A new and easy-to-use tool is suggested that will promote the use of climate change scenarios across Europe, especially when daily time steps are needed. CliPick eases the communication between climatic and modelling communities such as agriculture and forestry.

  2. Climate change web picker. A tool bridging daily climate needs in process based modelling in forestry and agriculture

    Energy Technology Data Exchange (ETDEWEB)

    Palma, J.H.N.

    2017-11-01

    Aim of study: Climate data is a need for different types of modeling assessments, especially those involving process based modeling focusing on climate change impacts. However, there is a scarcity of tools delivering easy access to climate datasets to use in biological related modeling. This study aimed at the development of a tool that could provide an user-friendly interface to facilitate access to climate datasets, that are used to supply climate scenarios for the International Panel on Climate Change. Area of study: The tool provides daily datasets across Europe, and also parts of northern Africa Material and Methods: The tool uses climatic datasets generated from third party sources (IPCC related) while a web based interface was developed in JavaScript to ease the access to the datasets Main Results: The interface delivers daily (or monthly) climate data from a user-defined location in Europe for 7 climate variables: minimum and maximum temperature, precipitation, radiation, minimum and maximum relative humidity and wind speed). The time frame ranges from 1951 to 2100, providing the basis to use the data for climate change impact assessments. The tool is free and publicly available at http://www.isa.ulisboa.pt/proj/clipick/. Research Highlights: A new and easy-to-use tool is suggested that will promote the use of climate change scenarios across Europe, especially when daily time steps are needed. CliPick eases the communication between climatic and modelling communities such as agriculture and forestry.

  3. Climate change scenarios experiments predict a future reduction in small pelagic fish recruitment in the Humboldt Current system.

    Science.gov (United States)

    Brochier, Timothée; Echevin, Vincent; Tam, Jorge; Chaigneau, Alexis; Goubanova, Katerina; Bertrand, Arnaud

    2013-06-01

    The Humboldt Current System (HCS) sustains the world's largest small pelagic fishery. While a cooling of this system has been observed during recent decades, there is debate about the potential impacts of rising atmospheric CO2 concentrations on upwelling dynamics and productivity. Recent studies suggest that under increased atmospheric CO2 scenarios the oceanic stratification may strongly increase and upwelling-favorable winds may remain nearly constant off Peru and increase off Chile. Here we investigate the impact of such climatic conditions on egg and larval dispersal phases, a key stage of small pelagic fish reproduction. We used larval retention rate in a predefined nursery area to provide a proxy for the recruitment level. Numerical experiments are based on hydrodynamics downscaled to the HCS from global simulations forced by pre-industrial (PI), 2 × CO2 and 4 × CO2 scenarios. A biogeochemical model is applied to the PI and 4 × CO2 scenarios to define a time-variable nursery area where larval survival is optimum. We test two distinct values of the oxycline depth that limits larval vertical distribution: One corresponding to the present-day situation and the other corresponding to a shallower oxycline potentially produced by climate change. It appeared that larval retention over the continental shelf increases with enhanced stratification due to regional warming. However, this increase in retention is largely compensated for by a decrease of the nursery area and the shoaling of the oxycline. The underlying dynamics are explained by a combination of stratification effects and mesoscale activity changes. Our results therefore show that future climate change may significantly reduce fish capacity in the HCS with strong ecological, economic and social consequences. © 2013 Blackwell Publishing Ltd.

  4. Natural climate variability in a coupled model

    International Nuclear Information System (INIS)

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

    1990-01-01

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

  5. pyhector: A Python interface for the simple climate model Hector

    Energy Technology Data Exchange (ETDEWEB)

    N Willner, Sven; Hartin, Corinne; Gieseke, Robert

    2017-04-01

    Pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary production and respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system (Hartin et al. 2016). The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2. These were developed to cover the range of baseline and mitigation emissions scenarios and are widely used in climate change research and model intercomparison projects. Using DataFrames from the Python library Pandas (McKinney 2010) as a data structure for the scenarios simplifies generating and adapting scenarios. Other parameters of the Hector model can easily be modified when running the model. Pyhector can be installed using pip from the Python Package Index.3 Source code and issue tracker are available in Pyhector's GitHub repository4. Documentation is provided through Readthedocs5. Usage examples are also contained in the repository as a Jupyter Notebook (Pérez and Granger 2007; Kluyver et al. 2016). Courtesy of the Mybinder project6, the example Notebook can also be executed and modified without installing Pyhector locally.

  6. Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

    Czech Academy of Sciences Publication Activity Database

    Kyselý, Jan; Gaál, Ladislav; Beranová, Romana; Plavcová, Eva

    2011-01-01

    Roč. 104, 3-4 (2011), s. 529-542 ISSN 0177-798X R&D Projects: GA ČR GAP209/10/2265 Grant - others:European Commission(XE) 505539 Program:FP6 Institutional research plan: CEZ:AV0Z30420517 Keywords : precipitation extremes * regional climate models * ENSEMBLES * climate change * region-of-influence method Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.942, year: 2011 http://www.springerlink.com/content/95wj1140307nu5k7/fulltext.pdf

  7. 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...... variability. Precipitation - Heavy winter precipitation increases in central and northern Europe and decreases in the south; heavy summer precipitation increases in north-eastern Europe and decreases in the south. Mediterranean droughts start earlier in the year and last longer. Winter storms - Extreme wind...... 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...

  8. Daily precipitation statistics in regional climate models

    DEFF Research Database (Denmark)

    Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel

    2003-01-01

    . The 15-year integrations were forced from reanalyses and observed sea surface temperature and sea ice (global model from sea surface only). The observational reference is based on 6400 rain gauge records (10-50 stations per grid box). Evaluation statistics encompass mean precipitation, wet-day frequency...... for other statistics. In summer, all models underestimate precipitation intensity (by 16-42%) and there is a too low frequency of heavy events. This bias reflects too dry summer mean conditions in three of the models, while it is partly compensated by too many low-intensity events in the other two models...

  9. Influence Processes in Climate Change Negotiations. Modelling the Rounds