WorldWideScience

Sample records for climate model results

  1. Modelling rainfall erosion resulting from climate change

    Science.gov (United States)

    Kinnell, Peter

    2016-04-01

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

  2. Titan Chemistry: Results From A Global Climate Model

    Science.gov (United States)

    Wilson, Eric; West, R. A.; Friedson, A. J.; Oyafuso, F.

    2008-09-01

    We present results from a 3-dimesional global climate model of Titan's atmosphere and surface. This model, a modified version of NCAR's CAM-3 (Community Atmosphere Model), has been optimized for analysis of Titan's lower atmosphere and surface. With the inclusion of forcing from Saturn's gravitational tides, interaction from the surface, transfer of longwave and shortwave radiation, and parameterization of haze properties, constrained by Cassini observations, a dynamical field is generated, which serves to advect 14 long-lived species. The concentrations of these chemical tracers are also affected by 82 chemical reactions and the photolysis of 21 species, based on the Wilson and Atreya (2004) model, that provide sources and sinks for the advected species along with 23 additional non-advected radicals. In addition, the chemical contribution to haze conversion is parameterized along with the microphysical processes that serve to distribute haze opacity throughout the atmosphere. References Wilson, E.H. and S.K. Atreya, J. Geophys. Res., 109, E06002, 2004.

  3. Subsea Permafrost Climate Modeling - Challenges and First Results

    Science.gov (United States)

    Rodehacke, C. B.; Stendel, M.; Marchenko, S. S.; Christensen, J. H.; Romanovsky, V. E.; Nicolsky, D.

    2015-12-01

    Recent observations indicate that the East Siberian Arctic Shelf (ESAS) releases methane, which stems from shallow hydrate seabed reservoirs. The total amount of carbon within the ESAS is so large that release of only a small fraction, for example via taliks, which are columns of unfrozen sediment within the permafrost, could impact distinctly the global climate. Therefore it is crucial to simulate the future fate of ESAS' subsea permafrost with regard to changing atmospheric and oceanic conditions. However only very few attempts to address the vulnerability of subsea permafrost have been made, instead most studies have focused on the evolution of permafrost since the Late Pleistocene ocean transgression, approximately 14000 years ago.In contrast to land permafrost modeling, any attempt to model the future fate of subsea permafrost needs to consider several additional factors, in particular the dependence of freezing temperature on water depth and salt content and the differences in ground heat flux depending on the seabed properties. Also the amount of unfrozen water in the sediment needs to be taken into account. Using a system of coupled ocean, atmosphere and permafrost models will allow us to capture the complexity of the different parts of the system and evaluate the relative importance of different processes. Here we present the first results of a novel approach by means of dedicated permafrost model simulations. These have been driven by conditions of the Laptev Sea region in East Siberia. By exploiting the ensemble approach, we will show how uncertainties in boundary conditions and applied forcing scenarios control the future fate of the sub sea permafrost.

  4. What do model results tell us regarding Climate Intervention (Geoengineering) strategies to counter high latitude climate change.

    Science.gov (United States)

    Rasch, P. J.

    2015-12-01

    A number of modeling studies at various levels of complexity have taken place to explore consequences of climate intervention in countering climate change. I will review results from some of those studies, cover some new analysis, and identify areas where more study is needed, with a focus on high latitude climate.

  5. Regionalization of climate model results for the North Sea

    Energy Technology Data Exchange (ETDEWEB)

    Kauker, F. [Alfred-Wegener-Institut fuer Polar- und Meeresforschung, Bremerhaven (Germany); Storch, H. von [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

    2000-07-01

    A dynamical downscaling for the North Sea is presented. The numerical model used for the study is the coupled ice-ocean model OPYC. In a hindcast of the years 1979 to 1993 it was forced with atmospheric forcing of the ECMWF reanalysis. The models capability in simulating the observed mean state and variability in the North Sea is demonstrated by the hindcast. Two time scale ranges, from weekly to seasonal and the longer-than-seasonal time scales are investigated. Shorter time scales, for storm surges, are not captured by the model formulation. The main modes of variability of sea level, sea-surface circulation, sea-surface temperature, and sea-surface salinity are described and connections to atmospheric phenomena, like the NAO, are discussed. T106 ''time-slice'' simulations with a ''2 x CO{sub 2}'' horizon are used to estimate the effects of a changing climate on the shelf sea ''North Sea''. The ''2 x CO{sub 2}'' changes in the surface forcing are accompanied by changes in the lateral oceanic boundary conditions taken from a global coupled climate model. For ''2 x CO{sub 2}'' the time mean sea level increases up to 25 cm in the German Bight in the winter, where 15 cm are due to the surface forcing and 10 cm due to thermal expansion. This change is compared to the ''natural'' variability as simulated in the ECMWF integration and found to be not outside the range spanned by it. The variability of sea level on the weekly-to-seasonal time-scales is significantly reduced in the scenario integration. The variability on the longer-than-seasonal time-scales in the control and scenario runs is much smaller then in the ECMWF integration. This is traced back to the use of ''time-slice'' experiments. Discriminating between locally forced changes and changes induced at the lateral oceanic boundaries of the model in the circulation and

  6. Climate Models

    Science.gov (United States)

    Druyan, Leonard M.

    2012-01-01

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

  7. Modeling drifting snow in Antarctica with a regional climate model: 2. Results

    NARCIS (Netherlands)

    Lenaerts, J.T.M.; van den Broeke, M.R.

    2012-01-01

    This paper presents a model study of the impact of drifting snow on the lower atmosphere, surface snow characteristics, and surface mass balance of Antarctica. We use the regional atmospheric climate model RACMO2.1/ANT with a high horizontal resolution (27 km), equipped with a drifting snow routine

  8. Climate change impacts on hydrological processes in Norway based on two methods for transferring regional climate model results to meteorological station sites

    OpenAIRE

    Beldring, Stein; Engen-Skaugen, Torill; Førland, Eirik J.; Roald, Lars A.

    2008-01-01

    Climate change impacts on hydrological processes in Norway have been estimated through combination of results from the IPCC SRES A2 and B2 emission scenarios, global climate models from the Hadley Centre and the Max-Planck Institute, and dynamical downscaling using the RegClim HIRHAM regional climate model. Temperature and precipitation simulations from the regional climate model were transferred to meteorological station sites using two different approaches, the delta change or perturbation ...

  9. Large-scale features of Pliocene climate: results from the Pliocene Model Intercomparison Project

    OpenAIRE

    A. M. Haywood; D. J. Hill; Dolan, A. M.; B. L. Otto-Bliesner; F. Bragg; Chan, W.-L.; Chandler, M. A.; Contoux, C.; H. J. Dowsett; A. Jost; Y. Kamae; Lohmann, G.; Lunt, D. J.; Abe-Ouchi, A.; Pickering, S.J.

    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-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are cle...

  10. SAT-MAP-CLIMATE project results[SATellite base bio-geophysical parameter MAPping and aggregation modelling for CLIMATE models

    Energy Technology Data Exchange (ETDEWEB)

    Bay Hasager, C.; Woetmann Nielsen, N.; Soegaard, H.; Boegh, E.; Hesselbjerg Christensen, J.; Jensen, N.O.; Schultz Rasmussen, M.; Astrup, P.; Dellwik, E.

    2002-08-01

    Earth Observation (EO) data from imaging satellites are analysed with respect to albedo, land and sea surface temperatures, land cover types and vegetation parameters such as the Normalized Difference Vegetation Index (NDVI) and the leaf area index (LAI). The observed parameters are used in the DMI-HIRLAM-D05 weather prediction model in order to improve the forecasting. The effect of introducing actual sea surface temperatures from NOAA AVHHR compared to climatological mean values, shows a more pronounced land-sea breeze effect which is also observable in field observations. The albedo maps from NOAA AVHRR are rather similar to the climatological mean values so for the HIRLAM model this is insignicant, yet most likely of some importance in the HIRHAM regional climate model. Land cover type maps are assigned local roughness values determined from meteorological field observations. Only maps with a spatial resolution around 25 m can adequately map the roughness variations of the typical patch size distribution in Denmark. A roughness map covering Denmark is aggregated (ie area-average non-linearly) by a microscale aggregation model that takes the non-linear turbulent responses of each roughness step change between patches in an arbitrary pattern into account. The effective roughnesses are calculated into a 15 km by 15 km grid for the HIRLAM model. The effect of hedgerows is included as an added roughness effect as a function of hedge density mapped from a digital vector map. Introducing the new effective roughness maps into the HIRLAM model appears to remedy on the seasonal wind speed bias over land and sea in spring. A new parameterisation on the effective roughness for scalar surface fluxes is developed and tested on synthetic data. Further is a method for the estimation the evapotranspiration from albedo, surface temperatures and NDVI succesfully compared to field observations. The HIRLAM predictions of water vapour at 12 GMT are used for atmospheric correction of

  11. Intense precipitation extremes in a warmer climate: results from CMIP5 models

    Science.gov (United States)

    scoccimarro, enrico; gualdi, silvio; bellucci, alessio; zampieri, matteo; navarra, antonio

    2013-04-01

    In this work the authors investigate possible changes in the intensity of extreme precipitation events under a warmer climate, using the results of a set of 20 climate models taking part to the Coupled Model Intercomparison Project phase 5 effort (CMIP5). Future changes are evaluated as the epoch difference between the last four decades of the 21st and the 20th Century assuming the Representative Concentration Pathway RCP8.5 scenario. As a measure of the intensity associated with extreme precipitation events, we use the difference between the 99th and the 90th percentiles. Despite a slight tendency to underestimate the observed extreme precipitation intensity, the considered CMIP5 models well represent the observed patterns during both summer and winter seasons for the 1997-2005 period. Future changes in average precipitation are consistent with previous findings based on CMIP3 models. CMIP5 models show a projected increase for the end of the twenty-first century of the intensity of the extreme precipitations, particularly pronounced over India, South East Asia, Indonesia and Central Africa during boreal summer, as well as over South America and the southern Africa during boreal winter. These changes are consistent with a strong increase of the column integrated water content availability over the afore mentioned regions.

  12. Streamflow in the upper Mississippi river basin as simulated by SWAT driven by 20{sup th} century contemporary results of global climate models and NARCCAP regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Takle, Eugene S.; Jha, Manoj; Lu, Er; Arritt, Raymond W.; Gutowski, William J. [Iowa State Univ. Ames, IA (United States)

    2010-06-15

    We use Soil and Water Assessment Tool (SWAT) when driven by observations and results of climate models to evaluate hydrological quantities, including streamflow, in the Upper Mississippi River Basin (UMRB) for 1981-2003 in comparison to observed streamflow. Daily meteorological conditions used as input to SWAT are taken from (1) observations at weather stations in the basin, (2) daily meteorological conditions simulated by a collection of regional climate models (RCMs) driven by reanalysis boundary conditions, and (3) daily meteorological conditions simulated by a collection of global climate models (GCMs). Regional models used are those whose data are archived by the North American Regional Climate Change Assessment Program (NARCCAP). Results show that regional models correctly simulate the seasonal cycle of precipitation, temperature, and streamflow within the basin. Regional models also capture interannual extremes represented by the flood of 1993 and the dry conditions of 2000. The ensemble means of both the GCM-driven and RCM-driven simulations by SWAT capture both the timing and amplitude of the seasonal cycle of streamflow with neither demonstrating significant superiority at the basin level. (orig.)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-02-17

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

  14. Large-scale features of Pliocene climate: results from the Pliocene Model Intercomparison Project

    Directory of Open Access Journals (Sweden)

    A. M. Haywood

    2012-07-01

    Full Text Available Climate and environments of the mid-Pliocene Warm Period (3.264 to 3.025 Ma have been extensively studied. Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a co-ordinated multi-model and multi-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data/model comparison highlights the potential for models to underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Sensitivity tests exploring the "known unknowns" in modelling Pliocene climate specifically relevant to the high-latitudes are also essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses. Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS, suggest that ESS is greater than Climate Sensitivity (CS, and that the ratio of ESS to CS is between 1 and 2, with a best estimate of 1.5.

  15. Large-scale features of Pliocene climate: results from the Pliocene Model Intercomparison Project

    Directory of Open Access Journals (Sweden)

    A. M. Haywood

    2013-01-01

    Full Text Available Climate and environments of the mid-Pliocene warm period (3.264 to 3.025 Ma have been extensively studied. Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a coordinated multi-model and multi-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are clearly evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data/model comparison highlights that models potentially underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Furthermore, sensitivity tests exploring the known unknowns in modelling Pliocene climate specifically relevant to the high latitudes are essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses. Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS, support previous work suggesting that ESS is greater than Climate Sensitivity (CS, and suggest that the ratio of ESS to CS is between 1 and 2, with a "best" estimate of 1.5.

  16. 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.; Kamae, Y.; Lohmann, G.; Lunt, D. J.; Abe-Ouchi, A.; Pickering, S. J.; Ramstein, G.; Rosenbloom, N. A.; Salzmann, U.; Sohl, L.; Stepanek, C.; Ueda, H.; Yan, Q.; Zhang, Z.

    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.

  17. Climate change impacts on hydrological processes in Norway based on two methods for transferring regional climate model results to meteorological station sites

    Science.gov (United States)

    Beldring, Stein; Engen-Skaugen, Torill; Førland, Eirik J.; Roald, Lars A.

    2008-05-01

    Climate change impacts on hydrological processes in Norway have been estimated through combination of results from the IPCC SRES A2 and B2 emission scenarios, global climate models from the Hadley Centre and the Max-Planck Institute, and dynamical downscaling using the RegClim HIRHAM regional climate model. Temperature and precipitation simulations from the regional climate model were transferred to meteorological station sites using two different approaches, the delta change or perturbation method and an empirical adjustment procedure that reproduces observed monthly means and standard deviations for the control period. These climate scenarios were used for driving a spatially distributed version of the HBV hydrological model, yielding a set of simulations for the baseline period 1961-1990 and projections of climate change impacts on hydrological processes for the period 2071-2100. A comparison between the two methods used for transferring regional climate model results to meteorological station sites is provided by comparing the results from the hydrological model for basins located in different parts of Norway. Projected changes in runoff are linked to changes in the snow regime. Snow cover will be more unstable and the snowmelt flood will occur earlier in the year. Increased rainfall leads to higher runoff in the autumn and winter.

  18. Climate change impacts on hydrological processes in Norway based on two methods for transferring regional climate model results to meteorological station sites

    Energy Technology Data Exchange (ETDEWEB)

    Beldring, Stein; Roald, Lars A. (Norwegian Water Resources and Energy Directorate, PO Box 5091 Majorstua, 0301 Oslo (Norway)). e-mail: stein.beldring@nve.no; Engen-Skaugen, Torill; Foerland, Eirik J. (Norwegian Meteorological Inst., PO Box 43 Blindern, 0313 Oslo (Norway))

    2008-07-01

    Climate change impacts on hydrological processes in Norway have been estimated through combination of results from the IPCC SRES A2 and B2 emission scenarios, global climate models from the Hadley Centre and the Max- Planck Institute, and dynamical downscaling using the RegClim HIRHAM regional climate model. Temperature and precipitation simulations from the regional climate model were transferred to meteorological station sites using two different approaches, the delta change or perturbation method and an empirical adjustment procedure that reproduces observed monthly means and standard deviations for the control period. These climate scenarios were used for driving a spatially distributed version of the HBV hydrological model, yielding a set of simulations for the baseline period 1961- 1990 and projections of climate change impacts on hydrological processes for the period 2071-2100. A comparison between the two methods used for transferring regional climate model results to meteorological station sites is provided by comparing the results from the hydrological model for basins located in different parts of Norway. Projected changes in runoff are linked to changes in the snow regime. Snow cover will be more unstable and the snow melt flood will occur earlier in the year. Increased rainfall leads to higher runoff in the autumn and winter

  19. 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...

  20. Exploring students' epistemological knowledge of models and modelling in science: results from a teaching/learning experience on climate change

    Science.gov (United States)

    Tasquier, Giulia; Levrini, Olivia; Dillon, Justin

    2016-03-01

    The scientific community has been debating climate change for over two decades. In the light of certain arguments put forward by the aforesaid community, the EU has recommended a set of innovative reforms to science teaching such as incorporating environmental issues into the scientific curriculum, thereby helping to make schools a place of civic education. However, despite these European recommendations, relatively little emphasis is still given to climate change within science curricula. Climate change, although potentially engaging for students, is a complex topic that poses conceptual difficulties and emotional barriers, as well as epistemological challenges. Whilst the conceptual and emotional barriers have already been the object of several studies, students' reactions to the epistemological issues raised by climate changes have so far been rarely explored in science education research and thus are the main focus of this paper. This paper describes a study concerning the implementation of teaching materials designed to focus on the epistemological role of 'models and the game of modelling' in science and particularly when dealing with climate change. The materials were implemented in a course of 15 hours (five 3-hour lessons) for a class of Italian secondary-school students (grade 11; 16-17 years old). The purpose of the study is to investigate students' reactions to the epistemological dimension of the materials, and to explore if and how the material enabled them to develop their epistemological knowledge on models.

  1. Simulating Pacific Northwest Forest Response to Climate Change: How We Made Model Results Useful for Vulnerability Assessments

    Science.gov (United States)

    Kim, J. B.; Kerns, B. K.; Halofsky, J.

    2014-12-01

    GCM-based climate projections and downscaled climate data proliferate, and there are many climate-aware vegetation models in use by researchers. Yet application of fine-scale DGVM based simulation output in national forest vulnerability assessments is not common, because there are technical, administrative and social barriers for their use by managers and policy makers. As part of a science-management climate change adaptation partnership, we performed simulations of vegetation response to climate change for four national forests in the Blue Mountains of Oregon using the MC2 dynamic global vegetation model (DGVM) for use in vulnerability assessments. Our simulation results under business-as-usual scenarios suggest a starkly different future forest conditions for three out of the four national forests in the study area, making their adoption by forest managers a potential challenge. However, using DGVM output to structure discussion of potential vegetation changes provides a suitable framework to discuss the dynamic nature of vegetation change compared to using more commonly available model output (e.g. species distribution models). From the onset, we planned and coordinated our work with national forest managers to maximize the utility and the consideration of the simulation results in planning. Key lessons from this collaboration were: (1) structured and strategic selection of a small number climate change scenarios that capture the range of variability in future conditions simplified results; (2) collecting and integrating data from managers for use in simulations increased support and interest in applying output; (3) a structured, regionally focused, and hierarchical calibration of the DGVM produced well-validated results; (4) simple approaches to quantifying uncertainty in simulation results facilitated communication; and (5) interpretation of model results in a holistic context in relation to multiple lines of evidence produced balanced guidance. This latest

  2. Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results

    Energy Technology Data Exchange (ETDEWEB)

    Deque, M. [Centre National de Recherches Meteorologiques, Meteo-France, Toulouse Cedex 01 (France); Jones, R.G.; Hassell, D.C. [Hadley Centre for Climate Prediction and Research, Met Office, Devon (United Kingdom); Wild, M.; Vidale, P.L. [Swiss Federal Institute of Technology, Institute for Atmospheric and Climate Science, ETH, Zurich (Switzerland); Giorgi, F.; Kucharski, F. [Abdus Salam International Centre for Theoretical Physics, Trieste (Italy); Christensen, J.H. [Danish Meteorological Institute, Copenhagen (Denmark); Rockel, B. [Institute of Coastal Research, GKSS Forschungszentrum Geesthacht GmbH, Geesthacht (Germany); Jacob, D. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Kjellstroem, E. [Swedish Meteorological and Hydrological Institute, Norrkoeping (Sweden); Castro, M. de. [Universidad de Castilla La Mancha, Dept. de Ciencias Ambientales, Toledo (Spain); Hurk, B. van den [KNMI, Postbus 201, AE De Bilt (Netherlands)

    2005-11-01

    Four high resolution atmospheric general circulation models (GCMs) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre sea surface temperature and sea-ice extent. The response over Europe, calculated as the difference between the 2071-2100 and the 1961-1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs - in particular in terms of precipitation - is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes. The temperature response is larger than the systematic error. The situation is different for precipitation. The model bias is twice as large as the climate response. The confidence in PRUDENCE results comes from the fact that the models have a similar response to the IPCC-SRES A2 forcing, whereas their systematic errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs. (orig.)

  3. Plant functional type classification for earth system models: results from the European Space Agency's Land Cover Climate Change Initiative

    Science.gov (United States)

    Poulter, B.; MacBean, N.; Hartley, A.; Khlystova, I.; Arino, O.; Betts, R.; Bontemps, S.; Boettcher, M.; Brockmann, C.; Defourny, P.; Hagemann, S.; Herold, M.; Kirches, G.; Lamarche, C.; Lederer, D.; Ottlé, C.; Peters, M.; Peylin, P.

    2015-07-01

    Global land cover is a key variable in the earth system with feedbacks on climate, biodiversity and natural resources. However, global land cover data sets presently fall short of user needs in providing detailed spatial and thematic information that is consistently mapped over time and easily transferable to the requirements of earth system models. In 2009, the European Space Agency launched the Climate Change Initiative (CCI), with land cover (LC_CCI) as 1 of 13 essential climate variables targeted for research development. The LC_CCI was implemented in three phases: first responding to a survey of user needs; developing a global, moderate-resolution land cover data set for three time periods, or epochs (2000, 2005, and 2010); and the last phase resulting in a user tool for converting land cover to plant functional type equivalents. Here we present the results of the LC_CCI project with a focus on the mapping approach used to convert the United Nations Land Cover Classification System to plant functional types (PFTs). The translation was performed as part of consultative process among map producers and users, and resulted in an open-source conversion tool. A comparison with existing PFT maps used by three earth system modeling teams shows significant differences between the LC_CCI PFT data set and those currently used in earth system models with likely consequences for modeling terrestrial biogeochemistry and land-atmosphere interactions. The main difference between the new LC_CCI product and PFT data sets used currently by three different dynamic global vegetation modeling teams is a reduction in high-latitude grassland cover, a reduction in tropical tree cover and an expansion in temperate forest cover in Europe. The LC_CCI tool is flexible for users to modify land cover to PFT conversions and will evolve as phase 2 of the European Space Agency CCI program continues.

  4. Plant functional type classification for Earth System Models: results from the European Space Agency's Land Cover Climate Change Initiative

    Directory of Open Access Journals (Sweden)

    B. Poulter

    2015-01-01

    Full Text Available Global land cover is a key variable in the earth system with feedbacks on climate, biodiversity and natural resources. However, global land-cover datasets presently fall short of user needs in providing detailed spatial and thematic information that is consistently mapped over time and easily transferable to the requirements of earth system models. In 2009, the European Space Agency launched the Climate Change Initiative (CCI, with land cover (LC_CCI as one of thirteen Essential Climate Variables targeted for research development. The LC_CCI was implemented in three phases, first responding to a survey of user needs, then developing a global, moderate resolution, land-cover dataset for three time periods, or epochs, 2000, 2005, and 2010, and the last phase resulting in a user-tool for converting land cover to plant functional type equivalents. Here we present the results of the LC_CCI project with a focus on the mapping approach used to convert the United Nations Land Cover Classification System to plant functional types (PFT. The translation was performed as part of consultative process among map producers and users and resulted in an open-source conversion tool. A comparison with existing PFT maps used by three-earth system modeling teams shows significant differences between the LC_CCI PFT dataset and those currently used in earth system models with likely consequences for modeling terrestrial biogeochemistry and land–atmosphere interactions. The LC_CCI tool is flexible for users to modify land cover to PFT conversions and will evolve as Phase 2 of the European Space Agency CCI program continues.

  5. 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

  6. Modelling Interglacial Climate

    DEFF Research Database (Denmark)

    Pedersen, Rasmus Anker

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

  7. Estimates of Late Pleistocene Runoff in Estancia Drainage Basin, Central New Mexico: Climate Assumptions vs. Model Results

    Science.gov (United States)

    Menking, K. M.; Anderson, R. Y.; Syed, K. H.; Shafike, N. G.

    2002-12-01

    The climatic conditions leading to highstands of "pluvial" Lake Estancia in central New Mexico have been a matter of considerable debate, resulting in a wide range of estimates for Pleistocene precipitation and temperature in the southwestern United States. Using a simple hydrologic balance approach, Leopold (1951) calculated that precipitation was 50% greater than modern based on the assumption that summer temperatures were 9 ° C colder while winter temperatures were unchanged. In contrast, Galloway (1970) called on temperature decreases of 10-11 ° C throughout the year and a reduction in mean annual precipitation of 14% to raise Lake Estancia to its highstand. In still another study, Brakenridge suggested that highstands could be achieved through no change in precipitation if monthly temperatures were reduced by 7-8 ° C. Experiments with 3 physically-based, continuous-time models to simulate surface runoff (USDA Soil and Water Assessment Tool), groundwater flow (MODFLOW with LAK2 package), and lake evaporation (lake energy balance model of Hostetler and Bartlein, 1990) indicate that none of these proposed full glacial climate scenarios could have produced a highstand lake. In particular, previous workers appear to have overestimated the reduction in evaporation rates associated with their proposed temperature changes, suggesting that using empirical relationships between modern air temperature and evaporation to predict late Pleistocene evaporation is problematic. Furthermore, model-determined reductions in lake evaporation are insufficient to allow for lake expansion as suggested by Galloway and Brakenridge. Even under Leopold's assumption that precipitation increased by 50%, modeled runoff appears to be insufficient to raise Lake Estancia more than a few meters above the lake floor.

  8. 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

  9. Climate-sensitive subsea permafrost and related gas expulsions on the South Kara Sea shelf. Field studies and modeling results.

    Science.gov (United States)

    Portnov, Alexey; Mienert, Jurgen; Serov, Pavel

    2015-04-01

    Thawing subsea permafrost controls methane release bearing a considerable impact on the climate-sensitive Arctic environment. Significant expulsion of methane into shallow Russian shelf areas may continue to rise into the atmosphere on the Arctic shelves in response to intense degradation of relict subsea permafrost. The release of formerly trapped gas, essentially methane, is linked to the permafrost evolution. Modeling of the permafrost at the West Yamal shelf allowed describing its evolution from the Late Pleistocene to Holocene. During the previous work we detected extensive emissions of free gas into the water column at the boundary between today's shallow water permafrost and deeper water non-permafrost areas. These gas expulsions formed seismic and hydro-acoustic anomalies on the high-resolution seismic records. We supposed that in the water depths modeling results of relict permafrost distributions with these field data from the South Kara Sea. Modeling results suggest a highly-dynamic permafrost system that directly responds to even minor variations of lower and upper boundary conditions, e.g. heat flux from below and/or bottom water temperature changes from above. We present several scenarios of permafrost evolution and show that potentially minimal modern extent of the permafrost at the West Yamal shelf is limited by ~17 m isobaths, whereas maximal probable extent coincides with ~100 m isobaths. The model also predicts seaward tapering of relict permafrost with its maximal thickness 275-390 m near the shore line. We also present sensitivity analysis which define the wider range of modeling results depending on the changing input parameters (e.g. geothermal heat flux, bottom water temperature, porosity of the sediments). The model adapts well to corresponding field data, providing crucial information about the modern permafrost conditions, current location of the upper and lower permafrost boundaries and its possible impact on both the hydrosphere and

  10. Can a reduction of solar irradiance counteract CO2-induced climate change? – Results from four Earth system models

    Directory of Open Access Journals (Sweden)

    M. Lawrence

    2012-01-01

    Full Text Available In this study we compare the response of four state-of-the-art Earth system models to climate engineering under scenario G1 of the GeoMIP and IMPLICC model intercomparison projects. In G1, the radiative forcing from an instantaneous quadrupling of the CO2 concentration, starting from the preindustrial level, is balanced by a reduction of the solar constant. Model responses to the two counteracting forcings in G1 are compared to the preindustrial climate in terms of global means and regional patterns and their robustness. While the global mean surface air temperature in G1 remains almost unchanged, the meridional temperature gradient is reduced in all models compared to the control simulation. Another robust response is the global reduction of precipitation with strong effects in particular over North and South America and northern Eurasia. It is shown that this reduction is only partly compensated by a reduction in evaporation so that large continental regions are drier in the engineered climate. In comparison to the climate response to a quadrupling of CO2 alone the temperature responses are small in experiment G1. Precipitation responses are, however, of comparable magnitude but in many regions of opposite sign.

  11. Exploring Students' Epistemological Knowledge of Models and Modelling in Science: Results from a Teaching/Learning Experience on Climate Change

    Science.gov (United States)

    Tasquier, Giulia; Levrini, Olivia; Dillon, Justin

    2016-01-01

    The scientific community has been debating climate change for over two decades. In the light of certain arguments put forward by the aforesaid community, the EU has recommended a set of innovative reforms to science teaching such as incorporating environmental issues into the scientific curriculum, thereby helping to make schools a place of civic…

  12. Tests Results of the Electrostatic Accelerometer Flight Models for Gravity Recovery and Climate Experiment Follow-On Mission (GRACE FO)

    Science.gov (United States)

    Perrot, E.; Boulanger, D.; Christophe, B.; Foulon, B.; Lebat, V.; Huynh, P. A.; Liorzou, F.

    2015-12-01

    The GRACE FO mission, led by the JPL (Jet Propulsion Laboratory), is an Earth-orbiting gravity mission, continuation of the GRACE mission, which will produce an accurate model of the Earth's gravity field variation providing global climatic data during five years at least. The mission involves two satellites in a loosely controlled tandem formation, with a micro-wave link measuring the inter-satellites distance variation. Earth's mass distribution non-uniformities cause variations of the inter-satellite distance. This variation is measured to recover gravity, after subtracting the non-gravitational contributors, as the residual drag. ONERA (the French Aerospace Lab) is developing, manufacturing and testing electrostatic accelerometers measuring this residual drag applied on the satellites. The accelerometer is composed of two main parts: the Sensor Unit (including the Sensor Unit Mechanics - SUM - and the Front-End Electronic Unit - FEEU) and the Interface Control Unit - ICU. In the Accelerometer Core, located in the Sensor Unit Mechanics, the proof mass is levitated and maintained at the center of an electrode cage by electrostatic forces. Thus, any drag acceleration applied on the satellite involves a variation on the servo-controlled electrostatic suspension of the mass. The voltage on the electrodes providing this electrostatic force is the output measurement of the accelerometer. The impact of the accelerometer defaults (geometry, electronic and parasitic forces) leads to bias, misalignment and scale factor error, non-linearity and noise. Some of these accelerometer defaults are characterized by tests with micro-gravity pendulum bench on ground and with drops in ZARM catapult. The Critical Design Review was achieved successfully on September 2014. The Engineering Model (EM) was integrated and tested successfully, with ground levitation, drops, Electromagnetic Compatibility and thermal vacuum. The integration of the two Flight Models was done on July 2015. The

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

    Institute of Scientific and Technical Information of China (English)

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

    2007-01-01

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

  14. Assessing the relative effectiveness of statistical downscaling and distribution mapping in reproducing rainfall statistics based on climate model results

    Science.gov (United States)

    Langousis, Andreas; Mamalakis, Antonios; Deidda, Roberto; Marrocu, Marino

    2016-01-01

    To improve the level skill of climate models (CMs) in reproducing the statistics of daily rainfall at a basin level, two types of statistical approaches have been suggested. One is statistical correction of CM rainfall outputs based on historical series of precipitation. The other, usually referred to as statistical rainfall downscaling, is the use of stochastic models to conditionally simulate rainfall series, based on large-scale atmospheric forcing from CMs. While promising, the latter approach attracted reduced attention in recent years, since the developed downscaling schemes involved complex weather identification procedures, while demonstrating limited success in reproducing several statistical features of rainfall. In a recent effort, Langousis and Kaleris () developed a statistical framework for simulation of daily rainfall intensities conditional on upper-air variables, which is simpler to implement and more accurately reproduces several statistical properties of actual rainfall records. Here we study the relative performance of: (a) direct statistical correction of CM rainfall outputs using nonparametric distribution mapping, and (b) the statistical downscaling scheme of Langousis and Kaleris (), in reproducing the historical rainfall statistics, including rainfall extremes, at a regional level. This is done for an intermediate-sized catchment in Italy, i.e., the Flumendosa catchment, using rainfall and atmospheric data from four CMs of the ENSEMBLES project. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the CM used and the characteristics of the calibration period. This is particularly the case for yearly rainfall maxima.

  15. A Comparison of the Solar Cycle Signature in Vertical Ozone and Temperature Profiles Seen by SAGE II With Coupled Chemistry-Climate Model Results

    Science.gov (United States)

    Bodeker, G. E.; Austin, J.; Zawodny, J. M.

    2002-12-01

    Solar variability is known to affect the Earth's climate. However, the exact mechanisms whereby small changes in extra-terrestrial solar irradiance over the 11 year solar cycle affect the climate are poorly understood. One of the primary objectives of the SOLar Impacts on Climate and the Environment (SOLICE) project is to assess the impact of solar variability on stratospheric ozone, radiative forcing and surface UV using coupled chemistry-climate models. Comparisons of model results and observations are expected to advance understanding of the mechanisms of solar-climate links. Global vertical ozone profiles (version 6.1) from the Stratospheric Aerosol and Gas Experiment II (SAGE II), together with co-located NCEP/NCAR temperature profiles, have been examined for the solar cycle signature from October 1984 to June 2001 as a function of altitude/pressure and latitude. In addition to solar cycle forcing, ozone concentrations and temperatures may also be influenced by the Quasi-Biennial Oscillation (QBO), volcanic eruptions, the El Niño-Southern Oscillation (ENSO), tropopause height variations, and the solar zenith angle (time of day) at the measurement location [Bodeker et al., JGR, vol. 103, 28661-28681, 1998]. These confounding effects must be eliminated before the solar cycle signal can be quantitatively identified. Two different approaches have been used: 1) Outside of volcanically perturbed periods, the QBO is expected to be the largest source of variability. Ozone and temperature profiles are sorted according to the phase of the QBO before profile differences between solar maximum and minimum are calculated. 2) A regression model, incorporating all forcings as basis functions, is applied to the ozone and temperature profiles and the amplitude of the solar cycle basis function is extracted. These results are compared with output from the UMETRAC (Unified Model with Eulerian TRansport And Chemistry) coupled chemistry-climate model.

  16. 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.

  17. 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.

  18. Abrupt change in climate and climate models

    Directory of Open Access Journals (Sweden)

    A. J. Pitman

    2006-07-01

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

  19. An evaluation of Arctic cloud and radiation processes during the SHEBA year: simulation results from eight Arctic regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Wyser, K.; Willen, U. [Rossby Centre, SMHI, Norrkoeping (Sweden); Jones, C.G.; Du, P.; Girard, E.; Laprise, R. [Universite du Quebec a Montreal, Canadian Regional Climate Modelling and Diagnostics Network, Montreal (Canada); Cassano, J.; Serreze, M.; Shaw, M.J. [University of Colorado, Cooperative Institute for Research in Environmental Sciences and Department of Atmospheric and Oceanic Sciences, Boulder, CO (United States); Christensen, J.H. [Danish Meteorological Institute, Copenhagen (Denmark); Curry, J.A. [School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA (United States); Dethloff, K.; Rinke, A. [Alfred Wegener Institute for Polar and Marine Research, Research Unit, Potsdam (Germany); Haugen, J.-E.; Koeltzow, M. [Norwegian Meteorological Institute, Oslo (Norway); Jacob, D.; Pfeifer, S. [Max Planck Institute for Meteorology, Hamburg (Germany); Lynch, A. [Monash University, School of Geography and Environmental Science, Melbourne (Australia); Tjernstroem, M.; Zagar, M. [Stockholm University, Department of Meteorology, Stockholm (Sweden)

    2008-02-15

    Eight atmospheric regional climate models (RCMs) were run for the period September 1997 to October 1998 over the western Arctic Ocean. This period was coincident with the observational campaign of the Surface Heat Budget of the Arctic Ocean (SHEBA) project. The RCMs shared common domains, centred on the SHEBA observation camp, along with a common model horizontal resolution, but differed in their vertical structure and physical parameterizations. All RCMs used the same lateral and surface boundary conditions. Surface downwelling solar and terrestrial radiation, surface albedo, vertically integrated water vapour, liquid water path and cloud cover from each model are evaluated against the SHEBA observation data. Downwelling surface radiation, vertically integrated water vapour and liquid water path are reasonably well simulated at monthly and daily timescales in the model ensemble mean, but with considerable differences among individual models. Simulated surface albedos are relatively accurate in the winter season, but become increasingly inaccurate and variable in the melt season, thereby compromising the net surface radiation budget. Simulated cloud cover is more or less uncorrelated with observed values at the daily timescale. Even for monthly averages, many models do not reproduce the annual cycle correctly. The inter-model spread of simulated cloud-cover is very large, with no model appearing systematically superior. Analysis of the co-variability of terms controlling the surface radiation budget reveal some of the key processes requiring improved treatment in Arctic RCMs. Improvements in the parameterization of cloud amounts and surface albedo are most urgently needed to improve the overall performance of RCMs in the Arctic. (orig.)

  20. Do regional climate models represent regional climate?

    Science.gov (United States)

    Maraun, Douglas; Widmann, Martin

    2014-05-01

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

  1. High definition clouds and precipitation for climate prediction -results from a unified German research initiative on high resolution modeling and observations

    Science.gov (United States)

    Rauser, F.

    2013-12-01

    We present results from the German BMBF initiative 'High Definition Cloud and Precipitation for advancing Climate Prediction -HD(CP)2'. This initiative addresses most of the problems that are discussed in this session in one, unified approach: cloud physics, convection, boundary layer development, radiation and subgrid variability are approached in one organizational framework. HD(CP)2 merges both observation and high performance computing / model development communities to tackle a shared problem: how to improve the understanding of the most important subgrid-scale processes of cloud and precipitation physics, and how to utilize this knowledge for improved climate predictions. HD(CP)2 is a coordinated initiative to: (i) realize; (ii) evaluate; and (iii) statistically characterize and exploit for the purpose of both parameterization development and cloud / precipitation feedback analysis; ultra-high resolution (100 m in the horizontal, 10-50 m in the vertical) regional hind-casts over time periods (3-15 y) and spatial scales (1000-1500 km) that are climatically meaningful. HD(CP)2 thus consists of three elements (the model development and simulations, their observational evaluation and exploitation/synthesis to advance CP prediction) and its first three-year phase has started on October 1st 2012. As a central part of HD(CP)2, the HD(CP)2 Observational Prototype Experiment (HOPE) has been carried out in spring 2013. In this campaign, high resolution measurements with a multitude of instruments from all major centers in Germany have been carried out in a limited domain, to allow for unprecedented resolution and precision in the observation of microphysics parameters on a resolution that will allow for evaluation and improvement of ultra-high resolution models. At the same time, a local area version of the new climate model ICON of the Max Planck Institute and the German weather service has been developed that allows for LES-type simulations on high resolutions on

  2. The North American Regional Climate Change Assessment Program: Overview of Climate Change Results

    Science.gov (United States)

    Mearns, L. O.

    2012-12-01

    The North American Regional Climate Change Assessment Program (NARCCAP) is an international program that is serving the climate scenario needs of the United States, Canada, and northern Mexico. We are systematically investigating the uncertainties in regional scale projections of future climate and producing high resolution climate change scenarios using multiple regional climate models (RCMs) and multiple global model responses by nesting the RCMs within atmosphere ocean general circulation models (AOGCMs) forced with a medium-high emissions scenario, over a domain covering the conterminous US, northern Mexico, and most of Canada. The project also includes a validation component through nesting the participating RCMs within the NCEP reanalysis R2. The basic spatial resolution of the RCM simulations is 50 km. This program includes six different RCMs that have been used in various intercomparison programs in Europe and the United States. Four different AOGCMs provide boundary conditions to drive the RCMS for 30 years in the current climate and 30 years for the mid 21st century. The resulting climate model simulations form the basis for multiple high resolution climate scenarios that can be used in climate change impacts and adaptation assessments over North America. All 12 sets of current and future simulations have been completed. Measures of uncertainty across the multiple simulations are being developed by geophysical statisticians. In this overview talk, results from the various climate change experiments for various subregions, along with measures of uncertainty, will be presented

  3. A sensitivity study to global desertification in cold and warm climates: results from the IPSL OAGCM model

    Energy Technology Data Exchange (ETDEWEB)

    Alkama, Ramdane [GAME/CNRM, CNRS/Meteo-France, Toulouse (France); Kageyama, Masa; Ramstein, Gilles [LSCE/IPSL UMR CEA-CNRS-UVSQ 8212, Gif sur Yvette (France)

    2012-04-15

    Many simulations have been devoted to study the impact of global desertification on climate, but very few have quantified this impact in very different climate contexts. Here, the climatic impacts of large-scale global desertification in warm (2100 under the SRES A2 scenario forcing), modern and cold (Last Glacial Maximum, 21 thousand years ago) climates are assessed by using the IPSL OAGCM. For each climate, two simulations have been performed, one in which the continents are covered by modern vegetation, the other in which global vegetation is changed to desert i.e. bare soil. The comparison between desert and present vegetation worlds reveals that the prevailing signal in terms of surface energy budget is dominated by the reduction of upward latent heat transfer. Replacing the vegetation by bare soil has similar impacts on surface air temperature South of 20 N in all three climatic contexts, with a warming over tropical forests and a slight cooling over semi-arid and arid areas, and these temperature changes are of the same order of magnitude. North of 20 N, the difference between the temperatures simulated with present day vegetation and in a desert world is mainly due to the change in net radiation related to the modulation of the snow albedo by vegetation, which is obviously absent in the desert world simulations. The enhanced albedo in the desert world simulations induces a large temperature decrease, especially during summer in the cold and modern climatic contexts, whereas the largest difference occurs during winter in the warm climate. This temperature difference requires a larger heat transport to the northern high latitudes. Part of this heat transport increase is achieved through an intensification of the Atlantic Meridional Overturning Circulation. This intensification reduces the sea-ice extent and causes a warming over the North Atlantic and Arctic oceans in the warm climate context. In contrast, the large cooling North of 20 N in both the modern

  4. Plant functional type classification for earth system models: results from the European Space Agency's Land Cover Climate Change Initiative

    NARCIS (Netherlands)

    Poulter, B.; MacBean, N.; Hartley, A.; Khlystova, I.; Arino, O.; Betts, R.; Bontemps, S.; Boettcher, M.; Brockmann, C.; Defourny, P.; Hagemann, S.; Herold, M.; Kirches, C.; Lamarche, C.; Lederer, D.; Ottlé, C.; Peters, M.; Peylin, P.

    2015-01-01

    Global land cover is a key variable in the earth system with feedbacks on climate, biodiversity and natural resources. However, global land cover data sets presently fall short of user needs in providing detailed spatial and thematic information that is consistently mapped over time and easily trans

  5. Geoengineering by stratospheric SO2 injection: results from the Met Office HadGEM2 climate model and comparison with the Goddard Institute for Space Studies ModelE

    Directory of Open Access Journals (Sweden)

    B. Kravitz

    2010-07-01

    Full Text Available We examine the response of the Met Office Hadley Centre's HadGEM2-AO climate model to simulated geoengineering by continuous injection of SO2 into the lower stratosphere, and compare the results with those from the Goddard Institute for Space Studies ModelE. Despite the differences between the models, we find a broadly similar geographic distribution of the response to geoengineering in both models in terms of near-surface air temperature and mean June–August precipitation. The simulations also suggest that significant changes in regional climate would be experienced even if geoengineering was successful in maintaining global-mean temperature near current values, and both models indicate rapid warming if geoengineering is not sustained.

  6. Synergy between Emissions Verification for Climate and Air Quality: Results from Modeling Analysis over the Contiguous US using CMAQ

    Science.gov (United States)

    Liu, Z.; Bambha, R.; Pinto, J. P.; Zeng, T.; Michelsen, H. A.

    2013-12-01

    The synergy between emissions-verification exercises for fossil-fuel CO2 and traditional air pollutants (TAPs, e.g., NOx, SO2, CO, and PM) stems from the common physical processes underlying the generation, transport, and perturbations of their emissions. Better understanding and characterizing such a synergetic relationship are of great interest and benefit for science and policy. To this end, we have been developing a modeling framework that allows for studying CO2 along with TAPs on regional-through-urban scales. The framework is based on the EPA Community Multi-Scale Air Quality (CMAQ) modeling system and has been implemented on a domain over the contiguous US, where abundant observational data and complete emissions information is available. In this presentation, we will show results from a comprehensive analysis of atmospheric CO2 and an array of TAPs observed from multiple networks and platforms (in situ and satellite observations) and those simulated by CMAQ over the contiguous US for a full year of 2007. We will first present the model configurations and input data used for CMAQ CO2 simulations and the results from model evaluations [1]. In light of the unique properties of CO2 compared to TAPs, we tested the sensitivity of model-simulated CO2 to different initial and boundary conditions, biosphere-atmosphere bidirectional fluxes and fossil-fuel emissions. We then examined the variability of CO2 and TAPs simulated by CMAQ and observed from the NOAA ESRL tall-tower network, the EPA AQS network, and satellites (e.g., SCIAMACHY and OMI) at various spatial and temporal scales. Finally, we diagnosed in CMAQ the roles of fluxes and transport in regulating the covariance between CO2 and TAPs manifested in both surface concentrations and column-integrated densities. We will discuss the implications from these results on how to understand trends and characteristics fossil-fuel emissions by exploiting and combining currently available observational and modeling

  7. Land use and climate change impacts on the hydrology of the upper Mara River Basin, Kenya: results of a modeling study to support better resource management

    Science.gov (United States)

    Mango, L. M.; Melesse, A. M.; McClain, M. E.; Gann, D.; Setegn, S. G.

    2011-07-01

    Some of the most valued natural and cultural landscapes on Earth lie in river basins that are poorly gauged and have incomplete historical climate and runoff records. The Mara River Basin of East Africa is such a basin. It hosts the internationally renowned Mara-Serengeti landscape as well as a rich mixture of indigenous cultures. The Mara River is the sole source of surface water to the landscape during the dry season and periods of drought. During recent years, the flow of the Mara River has become increasingly erratic, especially in the upper reaches, and resource managers are hampered by a lack of understanding of the relative influence of different sources of flow alteration. Uncertainties about the impacts of future climate change compound the challenges. We applied the Soil Water Assessment Tool (SWAT) to investigate the response of the headwater hydrology of the Mara River to scenarios of continued land use change and projected climate change. Under the data-scarce conditions of the basin, model performance was improved using satellite-based estimated rainfall data, which may also improve the usefulness of runoff models in other parts of East Africa. The results of the analysis indicate that any further conversion of forests to agriculture and grassland in the basin headwaters is likely to reduce dry season flows and increase peak flows, leading to greater water scarcity at critical times of the year and exacerbating erosion on hillslopes. Most climate change projections for the region call for modest and seasonally variable increases in precipitation (5-10 %) accompanied by increases in temperature (2.5-3.5 °C). Simulated runoff responses to climate change scenarios were non-linear and suggest the basin is highly vulnerable under low (-3 %) and high (+25 %) extremes of projected precipitation changes, but under median projections (+7 %) there is little impact on annual water yields or mean discharge. Modest increases in precipitation are partitioned

  8. Land use and climate change impacts on the hydrology of the upper Mara River Basin, Kenya: results of a modeling study to support better resource management

    Directory of Open Access Journals (Sweden)

    L. M. Mango

    2011-07-01

    Full Text Available Some of the most valued natural and cultural landscapes on Earth lie in river basins that are poorly gauged and have incomplete historical climate and runoff records. The Mara River Basin of East Africa is such a basin. It hosts the internationally renowned Mara-Serengeti landscape as well as a rich mixture of indigenous cultures. The Mara River is the sole source of surface water to the landscape during the dry season and periods of drought. During recent years, the flow of the Mara River has become increasingly erratic, especially in the upper reaches, and resource managers are hampered by a lack of understanding of the relative influence of different sources of flow alteration. Uncertainties about the impacts of future climate change compound the challenges. We applied the Soil Water Assessment Tool (SWAT to investigate the response of the headwater hydrology of the Mara River to scenarios of continued land use change and projected climate change. Under the data-scarce conditions of the basin, model performance was improved using satellite-based estimated rainfall data, which may also improve the usefulness of runoff models in other parts of East Africa. The results of the analysis indicate that any further conversion of forests to agriculture and grassland in the basin headwaters is likely to reduce dry season flows and increase peak flows, leading to greater water scarcity at critical times of the year and exacerbating erosion on hillslopes. Most climate change projections for the region call for modest and seasonally variable increases in precipitation (5–10 % accompanied by increases in temperature (2.5–3.5 °C. Simulated runoff responses to climate change scenarios were non-linear and suggest the basin is highly vulnerable under low (−3 % and high (+25 % extremes of projected precipitation changes, but under median projections (+7 % there is little impact on annual water yields or mean discharge. Modest increases in precipitation

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-04-15

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

  10. The spatial and temporal variability of the surface mass balance in Antarctica: results from a regional climate model

    NARCIS (Netherlands)

    Lipzig, N.P.M. van; Meijgaard, E. van; Oerlemans, J.

    2002-01-01

    A 14 year integration with a regional atmospheric model (RACMO) is used to obtain detailed information on the Antarctic surface mass balance and to understand the mechanisms that are responsible for the spatial and temporal distribution of the surface mass balance. The model (Δx = 55 km) uses the pa

  11. Stochastic Climate Theory and Modelling

    CERN Document Server

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

    2014-01-01

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

  12. Selecting global climate models for regional climate change studies

    Science.gov (United States)

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

    2009-01-01

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

  13. 32 questions concerning climate change (results of a questionnaire)

    Energy Technology Data Exchange (ETDEWEB)

    Auer, I.; Boehm, R. [Central Inst. for Meteorology and Geodynamics, Vienna (Austria); Steinacker, R. [Vienna Univ. (Austria).Inst. for Meteorology and Geophysics

    1995-12-31

    The intention of the inquiry was to investigate the opinion within the scientific community about climate change questions that are believed to be already well solved in the public opinion. 32 questions were formulated that deal with 12 main assumptions about the existence, the predictability and the impacts of climate changes due to an artificially enhanced greenhouse effect. The possibilities to answer reached from `sure yes`, over `guess yes`, `not answerable or no opinion` to `guess no` and `sure no`. There were additional questions about the way the answers were gained: `by own research`, `by studying scientific literature or discussion with colleagues` and `by mass media consumption`. In the following some of the key assumptions about climate change topics will be discussed as the predictability of future evolution of climate by climate models and the detectability of an artificially enhanced greenhouse effect in climate time series. The other assumptions can be shown here only in the form of a comprehensive overview. In a very comprehensive form the results of the inquiry could be described in the following: A weak majority of climatologists believe today`s climate models to be able to describe a greenhouse gas induced climate change in global scale - much less in regional scale and not in local scale. A majority of climatologists believe an anthropogenic greenhouse gas forced climate and its impacts to be developing in the future but not already at present. The shape of the opinion spectra is in most cases far from that of a scientifically solved problem - a lot of work still has to be done

  14. Analysis of the global free infra-gravity wave climate for the SWOT mission, and preliminary results of numerical modelling

    Science.gov (United States)

    Rawat, A.; Aucan, J.; Ardhuin, F.

    2012-12-01

    All sea level variations of the order of 1 cm at scales under 30 km are of great interest for the future Surface Water Ocean Topography (SWOT) satellite mission. That satellite should provide high-resolution maps of the sea surface height for analysis of meso to sub-mesoscale currents, but that will require a filtering of all gravity wave motions in the data. Free infragravity waves (FIGWs) are generated and radiate offshore when swells and/or wind seas and their associated bound infragravity waves impact exposed coastlines. Free infragravity waves have dominant periods comprised between 1 and 10 minutes and horizontal wavelengths of up to tens of kilometers. Given the length scales of the infragravity waves wavelength and amplitude, the infragravity wave field will can a significant fraction the signal measured by the future SWOT mission. In this study, we analyze the data from recovered bottom pressure recorders of the Deep-ocean Assessment and Reporting of Tsunami (DART) program. This analysis includes data spanning several years between 2006 and 2010, from stations at different latitudes in the North and South Pacific, the North Atlantic, the Gulf of Mexico and the Caribbean Sea. We present and discuss the following conclusions: (1) The amplitude of free infragravity waves can reach several centimeters, higher than the precision sought for the SWOT mission. (2) The free infragravity signal is higher in the Eastern North Pacific than in the Western North Pacific, possibly due to smaller incident swell and seas impacting the nearby coastlines. (3) Free infragravity waves are higher in the North Pacific than in the North Atlantic, possibly owing to different average continental shelves configurations in the two basins. (4) There is a clear seasonal cycle at the high latitudes North Atlantic and Pacific stations that is much less pronounced or absent at the tropical stations, consistent with the generation mechanism of free infragravity waves. Our numerical model

  15. 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.

  16. The North American Regional Climate Change Assessment Program (NARCCAP): Overview of Climate Change Results

    Science.gov (United States)

    Bukovsky, M. S.; Mearns, L. O.

    2012-04-01

    NARCCAP is an international program that is serving the climate scenario needs of the United States, Canada, and northern Mexico. We are systematically investigating the uncertainties in regional scale projections of future climate and producing high resolution climate change scenarios using six different regional climate models (RCMs ) and multiple global model responses to a future emission scenario, by nesting the RCMs within four atmosphere ocean general circulation models (AOGCMs) forced with the A2 SRES scenario, over a domain covering the conterminous US, northern Mexico, and most of Canada. The project also includes a validation component through nesting the participating RCMs within NCEP reanalyses. The spatial resolution of the RCM simulations is 50 km. This program includes RCMs that participated in the European PRUDENCE program (HadRM3 and RegCM), the Canadian regional climate model (CRCM) as well as the NCEP regional spectral model (RSM), the NCAR/PSU MM5, and NCAR WRF. AOGCMs include the Hadley Centre HadCM3, NCAR CCSM, the Canadian CGCM3 and the GFDL model. Insufficient funding was available to simulate all 24 combinations of RCMs and AOGCMs. Thus, we used a balanced fractional factorial statistical design to reduce the number of combinations of RCM-AOGCM pairs to twelve. High resolution (50 km) global time-slice experiments based on the GFDL atmospheric model and the NCAR atmospheric model (CAM3) have also been produced and will be compared with the simulations of the regional models. The geographic domain was regionalized into 29 subregions based on common climatological features, and summary climate change statistics for each of the subregions have been produced. In this overview talk, results from the RCM climate change simulations for select subregions of North America will be presented.

  17. First Results from The Last Millennium Climate Reanalysis Project

    Science.gov (United States)

    Hakim, G. J.; Steig, E. J.; Emile-Geay, J.; Noone, D. C.; Anderson, D. M.; Tardif, R.; Steiger, N. J.; Perkins, W. A.

    2015-12-01

    Paleoclimate proxies provide the only measured record of Earth's climate history, but they are noisy and sparse in space and time. Climate model simulations provide dynamically consistent spatial fields, but lack a direct connection to specific climate states prior to the instrumental record. Paleoclimate data assimilation (PDA) provides an optimally weighted estimate of the climate state from these two sources of information based on their error characteristics. The Last Millennium Climate Reanalysis Project (LMR) uses an ensemble-based PDA method and annually-resolved proxy records to reconstruct Earth's climate for the past 1000 years on a regular latitude--longitude grid. First results of the LMR project are reported here. Proxy records used in the first LMR reconstructions include: trees (ring width and wood density), corals (d18O and luminescence), ice cores (d18O), and a small number of sediment and speleothem records. A component of the data assimilation approach that distinguishes it from other techniques concerns the use of proxy system models to estimate the proxy from climate variables from a model simulation. Proxies are linearly related to 2-meter air temperature in a calibration dataset. Given a prior estimate of the climate from a model (here, a randomly sampled 1000-year control integration of CCSM4), we estimate the proxy value from the linear relationship (derived independently from the model). LMR analyses are compared against both existing gridded reanalysis records and withheld proxy records. Results show a cooling trend in global-mean air temperature during 1000-1900 CE, which derives primarily from cooling of the Northern Hemisphere extratropics, offset by weak tropical warming. There is no evidence of a Medieval Climate Anomaly. During the 20th century, the LMR estimate of the global-mean air temperature compares very closely with other reanalysis products. Skill appears insensitive to the calibration dataset used to derive the proxy system

  18. 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.

  19. 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.

  20. Advance in Application of Regional Climate Models in China

    Institute of Scientific and Technical Information of China (English)

    ZHANG Wei; YAN Minhua; CHEN Panqin; XU Helan

    2008-01-01

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

  1. A Pedagogical "Toy" Climate Model

    CERN Document Server

    Katz, J I

    2010-01-01

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

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

    OpenAIRE

    Diffenbaugh, Noah S; Giorgi, Filippo

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    T. O. Sonnenborg

    2015-04-01

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

  4. The last millennium climate reanalysis project: Framework and first results

    Science.gov (United States)

    Hakim, Gregory J.; Emile-Geay, Julien; Steig, Eric J.; Noone, David; Anderson, David M.; Tardif, Robert; Steiger, Nathan; Perkins, Walter A.

    2016-06-01

    An "offline" approach to DA is used, where static ensemble samples are drawn from existing CMIP climate-model simulations to serve as the prior estimate of climate variables. We use linear, univariate forward models ("proxy system models (PSMs)") that map climate variables to proxy measurements by fitting proxy data to 2 m air temperature from gridded instrumental temperature data; the linear PSMs are then used to predict proxy values from the prior estimate. Results for the LMR are compared against six gridded instrumental temperature data sets and 25% of the proxy records are withheld from assimilation for independent verification. Results show broad agreement with previous reconstructions of Northern Hemisphere mean 2 m air temperature, with millennial-scale cooling, a multicentennial warm period around 1000 C.E., and a cold period coincident with the Little Ice Age (circa 1450-1800 C.E.). Verification against gridded instrumental data sets during 1880-2000 C.E. reveals greatest skill in the tropics and lowest skill over Northern Hemisphere land areas. Verification against independent proxy records indicates substantial improvement relative to the model (prior) data without proxy assimilation. As an illustrative example, we present multivariate reconstructed fields for a singular event, the 1808/1809 "mystery" volcanic eruption, which reveal global cooling that is strongly enhanced locally due to the presence of the Pacific-North America wave pattern in the 500 hPa geopotential height field.

  5. Model confirmation in climate economics.

    Science.gov (United States)

    Millner, Antony; McDermott, Thomas K J

    2016-08-01

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

  6. Regional Climate Model Intercomparison Project for Asia.

    Science.gov (United States)

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

    2005-02-01

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

  7. 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.

  8. Ecologically relevant stress resistance: from microarrays and quantitative trait loci to candidate genes – A research plan and preliminary results using Drosophila as a model organism and climatic and genetic stress as model stresses

    Indian Academy of Sciences (India)

    Volker Loeschcke; Jesper G Sørensen; Torsten N Kristensen

    2004-12-01

    We aim at studying adaptation to genetic and environmental stress and its evolutionary implications at different levels of biological organization. Stress influences cellular processes, individual physiology, genetic variation at the population level, and the process of natural selection. To investigate these highly connected levels of stress effects, it is advisable – if not critical – to integrate approaches from ecology, evolution, physiology, molecular biology and genetics. To investigate the mechanisms of stress resistance, how resistance evolves, and what factors contribute to and constrain its evolution, we use the well-defined model systems of Drosophila species, representing both cosmopolitan species such as D. melanogaster with a known genome map, and more specialized and ecologically well described species such as the cactophilic D. buzzatii. Various climate-related stresses are used as model stresses including desiccation, starvation, cold and heat. Genetic stress or genetic load is modelled by studying the consequences of inbreeding, the accumulation of (slightly) deleterious mutations, hybridization or the loss of genetic variability. We present here a research plan and preliminary results combining various approaches: molecular techniques such as microarrays, quantitative trait loci (QTL) analyses, quantitative PCR, ELISA or Western blotting are combined with population studies of resistance to climatic and genetic stress in natural populations collected across climatic gradients as well as in selection lines maintained in the laboratory.

  9. The Community Climate System Model: CCSM3

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-12-27

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

  10. Climate Change: The Physical Basis and Latest Results

    CERN Document Server

    CERN. Geneva

    2009-01-01

    The 2007 Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) concludes: "Warming in the climate system is unequivocal." Without the contribution of Physics to climate science over many decades, such a statement would not have been possible. Experimental physics enables us to read climate archives such as polar ice cores and so provides the context for the current changes. For example, today the concentration of CO2 in the atmosphere, the second most important greenhouse gas, is 28% higher than any time during the last 800,000 years. Classical fluid mechanics and numerical mathematics are the basis of climate models from which estimates of future climate change are obtained. But major instabilities and surprises in the Earth System are still unknown. These are also to be considered when the climatic consequences of proposals for geo-engineering are estimated. Only Physics will permit us to further improve our understanding in order to provide the foundation for policy decisions facing the...

  11. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

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

  12. Hierarchical Climate Modeling for Cosmoclimatology

    Science.gov (United States)

    Ohfuchi, Wataru

    2010-05-01

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

  13. Climate system model, numerical simulation and climate predictability

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

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

  14. 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

  15. Climate change scenarios in Mexico from models results under the assumption of a doubling in the atmospheric CO{sub 2}

    Energy Technology Data Exchange (ETDEWEB)

    Mendoza, V.M.; Villanueva, E.E.; Garduno, R.; Adem, J. [Centro de Ciencias de la Atmosfera, Mexico (Mexico)

    1995-12-31

    General circulation models (GCMs) and energy balance models (EBMs) are the best way to simulate the complex large-scale dynamic and thermodynamic processes in the atmosphere. These models have been used to estimate the global warming due to an increase of atmospheric CO{sub 2}. In Japan Ohta with coworkers has developed a physical model based on the conservation of thermal energy applied to pounded shallow water, to compute the change in the water temperature, using the atmospheric warming and the precipitation due to the increase in the atmospheric CO{sub 2} computed by the GISS-GCM. In this work, a method similar to the Ohta`s one is used for computing the change in ground temperature, soil moisture, evaporation, runoff and dryness index in eleven hydrological zones, using in this case the surface air temperature and precipitation due to CO{sub 2} doubling, computed by the GFDLR30-GCM and the version of the Adem thermodynamic climate model (CTM-EBM), which contains the three feedbacks (cryosphere, clouds and water vapor), and does not include water vapor in the CO{sub 2} atmospheric spectral band (12-19{mu})

  16. Selecting global climate models for regional climate change studies

    OpenAIRE

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

    2009-01-01

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

  17. Uncertainty Quantification in Climate Modeling

    Science.gov (United States)

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

    2011-12-01

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

  18. Post-2020 climate agreements in the major economies assessed in the light of global models

    NARCIS (Netherlands)

    Tavoni, M.; Kriegler, E.; Riahi, K.; van Vuuren, D.F.; Aboumahboub, T.; Bowen, A.; Calvin, K.; Campiglio, E.; Kober, T.; Jewell, J.; Luderer, G.; Marangoni, G.; McCollum, D.; van Sluisveld, M.; Zimmer, A.; van der Zwaan, B.

    2014-01-01

    Integrated assessment models can help in quantifying the implications of international climate agreements and regional climate action. This paper reviews scenario results from model intercomparison projects to explore different possible outcomes of post-2020 climate negotiations, recently announced

  19. Post-2020 climate agreements in the major economies assessed in the light of global models

    NARCIS (Netherlands)

    Tavoni, Massimo; Kriegler, Elmar; Riahi, Keywan; Van Vuuren, Detlef P.; Aboumahboub, Tino; Bowen, Alex; Calvin, Katherine; Campiglio, Emanuele; Kober, Tom; Jewell, Jessica; Luderer, Gunnar; Marangoni, Giacomo; Mccollum, David; Van Sluisveld, Mariësse; Zimmer, Anne; Van Der Zwaan, Bob

    2015-01-01

    Integrated assessment models can help in quantifying the implications of international climate agreements and regional climate action. This paper reviews scenario results from model intercomparison projects to explore different possible outcomes of post-2020 climate negotiations, recently announced

  20. An Analog Earth Climate Model

    Science.gov (United States)

    Varekamp, J. C.

    2010-12-01

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

  1. SAT-MAP-CLIMATE project results

    DEFF Research Database (Denmark)

    Hasager, C.B.; Nielsen, N.W.; Soegaard, H.

    2002-01-01

    Earth Observation (EO) data from imaging satellites are analysed with respect to albedo, land and sea surface temperatures, land cover types and vegetation parameters such as the Normalized Difference Vegetation Index (NDVI) and the leaf area index (LAI).The observed parameters are used in the DMI...... from albedo, surface temperatures and NDVI succesfully compared to field observations. The HIRLAM predictions of water vapour at 12 GMT are used for atmospheric correction of the satellite parametersderived in the afternoon.......-HIRLAM-D05 weather prediction model in order to improve the forecasting. The effect of introducing actual sea surface temperatures from NOAA AVHHR compared to climatological mean values, shows a more pronouncedland-sea breeze effect which is also observable in field observations. The albedo maps from NOAA...

  2. Climate Sensitivity and Solar Cycle Response in Climate Models

    Science.gov (United States)

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

    2011-12-01

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

  3. Global Climate Models of the Terrestrial Planets

    Science.gov (United States)

    Forget, F.; Lebonnois, S.

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1991-10-01

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

  5. 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.

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

    Institute of Scientific and Technical Information of China (English)

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

    2013-01-01

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

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

    NARCIS (Netherlands)

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

    2016-01-01

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

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

    NARCIS (Netherlands)

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

    2016-01-01

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

  9. 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...

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

    Science.gov (United States)

    Holzkämper, Annelie; Honti, Mark; Fuhrer, Jürg

    2015-04-01

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

  11. Load-balancing algorithms for climate models

    Energy Technology Data Exchange (ETDEWEB)

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

    1994-06-01

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

  12. Load-balancing algorithms for climate models

    Science.gov (United States)

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

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

  13. Effects of sinking of salt rejected during formation of sea ice on results of an ocean-atmosphere-sea ice climate model

    Science.gov (United States)

    Duffy, P. B.; Eby, M.; Weaver, A. J.

    We show that results of an ocean-atmosphere-sea-ice model are sensitive to the treatment of salt rejected during formation of sea ice. In our Control simulation, we place all rejected salt in the top ocean-model level. In the Plume simulation, we instantaneously mix rejected salt into the subsurface ocean, to a maximum depth which depends on local density gradients. This mimics the effects of subgrid-scale convection of rejected salt. The results of the Plume simulation are more realistic than those of the Control simulation: the spatial pattern of simulated salinities (especially in the Southern Ocean), deep-ocean temperatures, simulated sea-ice extents and surface air temperatures all agree better with observations. A similar pair of simulations using horizontal tracer diffusion instead of the Gent-McWilliams eddy parameterization show similar changes due to instantaneous mixing of rejected salt.

  14. 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.

  15. 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.

  16. 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.

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

    CERN Document Server

    Mihailović, Dragutin T; Arsenić, Ilija

    2013-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-12-15

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

  19. Data assimilation experiments with MPIESM climate model

    Directory of Open Access Journals (Sweden)

    Belyaev Konstantin

    2016-01-01

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

  20. 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

  1. Application of HydroGeoSphere to model the response to anthropogenic climate change of three-dimensional hydrological processes in the geologically, geothermally, and topographically complex Valles Caldera super volcano, New Mexico: Preliminary results

    Science.gov (United States)

    Wine, M.; Cadol, D. D.

    2014-12-01

    Anthropogenic climate change is expected to reduce streamflow in the southwestern USA due to reduction in precipitation and increases in evaporative demand. Understanding the effects of climate change in this region is particularly important for mountainous areas since these are primary sources of recharge in arid and semi-arid environments. Therefore we undertook to model effects of climate change on the hydrological processes in Valles Caldera (448 km2), located in the Jemez Mountains of northern New Mexico. In Valles Caldera modeling the surficial, hydrogeological, and geothermal processes that influence hydrologic fluxes each present challenges. The surficial dynamics of evaporative demand and snowmelt both serve to control recharge dynamics, but are complicated by the complex topography and spatiotemporal vegetation dynamics. Complex factors affecting evaporative demand include leaf area index, temperature, albedo, and radiation affected by topographic shading; all of these factors vary in space and time. Snowmelt processes interact with evaporative demand and geology to serve as an important control on streamflow generation, but modeling the effects of spatiotemporal snow distributions on streamflow generation remains a challenge. The complexity of Valles Caldera's geology—and its associated hydraulic properties—rivals that of its surficial hydrologic forcings. Hydrologically important geologic features that have formed in the Valles Caldera are three-dimensionally intricate and include a dense system of faults, alluvium, landslides, lake deposits, and features associated with the eruption and collapse of this super volcano. Coupling geothermally-driven convection to the hydrologic cycle in this still-active geothermal system presents yet an additional challenge in modeling Valles Caldera. Preliminary results from applying the three-dimensional distributed hydrologic finite element model HydroGeoSphere to a sub-catchment of Valles Caldera will be

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  3. Towards Systematic Benchmarking of Climate Model Performance

    Science.gov (United States)

    Gleckler, P. J.

    2014-12-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

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

    Science.gov (United States)

    Zhang, Xianliang; Yan, Xiaodong

    2016-05-01

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

  6. An Appraisal of Coupled Climate Model Simulations

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-02-24

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

  7. 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

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

    Science.gov (United States)

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

    2011-12-01

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

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

    NARCIS (Netherlands)

    Dellink, R.B.

    2011-01-01

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

  10. 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.

  11. Observationally-Based Data/Model Metrics from the Southern Ocean Climate Model Atlas

    Science.gov (United States)

    Abell, J.; Russell, J. L.; Goodman, P. J.

    2015-12-01

    The Southern Ocean Climate Model Atlas makes available observationally-based standardized data/model metrics of the latest simulations of climate and projections of climate change from available climate models. Global climate model simulations differ greatly in the Southern Ocean, so the development of consistent, observationally-based metrics, by which to assess the fidelity of model simulations is essential. We will present metrics showing and quantifying the results of the modern day climate simulations over the Southern Ocean from models submitted as part of the CMIP5/IPCC-AR5 process. Our analysis will focus on the simulations of the temperature, salinity and carbon at various depths and along significant hydrographic sections. The models exhibit different skill levels with various metrics between models and also within individual models.

  12. 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.

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

    Science.gov (United States)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian; Trolle, Dennis; Børgesen, Christen Duus; Olesen, Jørgen E.; Jeppesen, Erik; Jensen, Karsten H.

    2016-04-01

    Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes on hydrology for a 486 km2 catchment in Denmark and to evaluate the sensitivity of the results to the choice of hydrological model. Three hydrological models, NAM, SWAT and MIKE SHE, were constructed and calibrated using similar methods. Each model was forced with results from four climate models and four land use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice remained the dominant factor for mean discharge, low and high flows as well as hydraulic head at the end of the century.

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

    NARCIS (Netherlands)

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

    2011-01-01

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

  15. 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

  16. Mixing parameterizations in ocean climate modeling

    Science.gov (United States)

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

    2016-03-01

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

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

    Directory of Open Access Journals (Sweden)

    J. Brandefelt

    2011-01-01

    variability of the simulated GS12 climate is dependent on the equilibration. The Atlantic Meridional Overturning Circulation (AMOC slows down by 50% in the GS12 climate as compared to the RP climate. This slowdown is attained without freshwater forcing in the North Atlantic region, a method used in other studies to force an AMOC shutdown. The results presented here suggest that stadial climate, rather that interstadial climate, should be interpreted as a near-equilibrium MIS 3 climate, in contradiction to an earlier modelling study.

  18. 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.

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

    Science.gov (United States)

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

    2016-03-31

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1994-05-01

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

  1. Modeling of Past Climates: Some Perspectives

    Science.gov (United States)

    Kutzbach, J. E.

    2008-12-01

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

  2. After the Data: Taking Action on ClimateQUAL® Results

    Directory of Open Access Journals (Sweden)

    Elizabeth Uzelac

    2013-06-01

    Full Text Available Objective – This paper discusses the actions taken by the staff development and training (SD&T team at the Sheridan Libraries and Johns Hopkins University Museums in response to results of a ClimateQUAL survey.Methods – The team administered the ClimateQUAL Organizational Climate and Diversity Assessment in March 2009 to the 150 staff members of the museums and libraries, and 80% responded. To get at the root of some of the results, the team conducted 23 focus group sessions over the course of two months. In each 90-minute session, 8 open-ended questions were used to probe the staff’s thoughts on the survey results and elicit concrete suggestions for moving forward. Participants were asked to discuss their personal experiences with six areas of concern: procedural justice, distributive justice, structural facilitation of teamwork, psychological safety, communication, and leadership. One year after the original ClimateQUAL survey, the team administered a one-question follow-up survey.Results – The team analyzed and coded the notes taken during the focus group sessions and developed three discrete written summaries for each session: a brief summary of themes, a list of specific actionable suggestions, and a general description of specific scenarios aired in the sessions. From these analyses, the team developed two types of recommendations: quick tactical actions and long-term strategic recommendations. Strategic recommendations were developed in three main areas: fostering a sense of global ownership of organizational issues, improving organizational communication, and improving leadership and facilitation of teamwork. With these recommendations, the team charged managers to take broad ownership of a plan for individual actions. The results of the one-year follow-up survey were mixed. Staff perceived positive change in communication, but indicated that the areas of procedural and distributive justice, psychological safety, and transparency

  3. 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.

  4. A Novel Method for Analyzing and Interpreting GCM Results Using Clustered Climate Regimes

    Science.gov (United States)

    Hoffman, F. M.; Hargrove, W. W.; Erickson, D. J.; Oglesby, R. J.

    2003-12-01

    A high-performance parallel clustering algorithm has been developed for analyzing and comparing climate model results and long time series climate measurements. Designed to identify biases and detect trends in disparate climate change data sets, this tool combines and simplifies large temporally-varying data sets from atmospheric measurements to multi-century climate model output. Clustering is a statistical procedure which provides an objective method for grouping multivariate conditions into a set of states or regimes within a given level of statistical tolerance. The groups or clusters--statistically defined across space and through time--possess centroids which represent the synoptic conditions of observations or model results contained in each state no matter when or where they occurred. The clustering technique was applied to five business-as-usual (BAU) scenarios from the Parallel Climate Model (PCM). Three fields of significance (surface temperature, precipitation, and soil moisture) were clustered from 2000 through 2098. Our analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The same analysis subsequently applied to the ensemble as a whole demonstrates the consistency and variability of trends from each ensemble member. The patterns of cluster changes can be used to show predicted variability in climate on global and continental scales. Novel three-dimensional phase space representations of these climate regimes show the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time, and by incrementing time, that same spot will trace out a trajectory or orbit among these climate regimes in phase space. When a

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

    Energy Technology Data Exchange (ETDEWEB)

    Forster, P M A F; Taylor, K E

    2006-07-25

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

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

    Science.gov (United States)

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

    2010-12-01

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

  7. Emulation of MIROC5 with a simple climate model

    Science.gov (United States)

    Ishizaki, Yasuhiro; Emori, Seita; Shiogama, Hideo; Takahashi, Kiyoshi; Yokohata, Tokuta; Yoshimori, Masakazu

    2014-05-01

    We developed a simple climate model based on MAGICC6, and investigated the ability of the simple climate model to emulate global mean surface air temperature (SAT) changes of an atmosphere-ocean general circulation model (MIROC5) in the twenty-first century in representative concentration pathways (RCPs). Some previous research indicated that climate sensitivity, ocean vertical diffusion and forcing of anthropogenic aerosols (direct and indirect effects of sulfate aerosol, black carbon and organic carbon) are important factors to emulate global mean SAT changes of atmosphere-ocean general circulation models CMIP3. We therefore estimate these important parameters in the simple climate model using a Metropolis-Hastings Markov chain Monte Carlo (MCMC) approach. The estimated values of the important parameters by the MCMC are physically valid, and our simple climate model can successfully emulate global mean SAT changes of MIROC5 in RCPs with the estimated parameters by the MCMC approach. In addition, we estimated the relative contributions f each important parameter in sensitivity experiments, in which we change the value of an important parameter from the estimated one by the MCMC to the default value of MAGICC6. As a result, we found that the estimation of climate sensitivity is the most important factor for the emulation of the AOGCM, and the stimation of ocean vertical diffusion is also important factor. Although the estimations of the anthropogenic aerosols forcing are very important for the emulation of the AOGCM in the twenty century, the influence of them on the emulation of the AOGCM in the twenty first century is very small. This is because emissions of anthropogenic aerosols are projected to decrease in the twenty first century, and relative contributions of the forcing of anthropogenic aerosols also decrease. Carbon cycle models are not incorporated into our simple climate model yet. A sophisticated carbon cycle model is required to be incorporated into

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

    Directory of Open Access Journals (Sweden)

    M. Eby

    2012-08-01

    Full Text Available Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes seem to be underestimated. It is possible that recent modelled climate trends or climate-carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated.

    Several one thousand year long, idealized, 2x and 4x CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate-carbon feedbacks. The values from EMICs generally fall within the range given by General Circulation Models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows considerable synergy between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given

  9. Some GCM simulation results on present and possible future climate in northern Europe

    Energy Technology Data Exchange (ETDEWEB)

    Raeisaenen, J. [Helsinki Univ. (Finland). Dept. of Meteorology

    1995-12-31

    The Intergovernmental Panel on Climate Change initiated in 1993 a project entitled `Evaluation of Regional Climate Simulations`. The two basic aims of this project were to assess the skill of current general circulation models (GCMs) in simulating present climate at a regional level and to intercompare the regional response of various GCMs to increased greenhouse gas concentrations. The public data base established for the comparison included simulation results from several modelling centres, but most of the data were available in the form of time-averaged seasonal means only, and important quantities like precipitation were totally lacking in many cases. This presentation summarizes the intercomparison results for surface air temperature and sea level pressure in northern Europe. The quality of the control simulations and the response of the models to increased CO{sub 2} are addressed in both winter (December-February) and summer (June-August)

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

    Science.gov (United States)

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

    2016-01-01

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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...... common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 ≤ 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long...

  12. The Milankovitch theory and climate sensitivity. I - Equilibrium climate model solutions for the present surface conditions. II - Interaction between the Northern Hemisphere ice sheets and the climate system

    Science.gov (United States)

    Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

    1988-01-01

    A seasonal climate model was developed to test the climate sensitivity and, in particular, the Milankovitch (1941) theory. Four climate model versions were implemented to investigate the range of uncertainty in the parameterizations of three basic feedback mechanisms: the ice albedo-temperature, the outgoing long-wave radiation-temperature, and the eddy transport-meridional temperature gradient. It was found that the differences between the simulation of the present climate by the four versions were generally small, especially for annually averaged results. The climate model was also used to study the effect of growing/shrinking of a continental ice sheet, bedrock sinking/uplifting, and sea level changes on the climate system, taking also into account the feedback effects on the climate of the building of the ice caps.

  13. Assessing climate change impact by integrated hydrological modelling

    Science.gov (United States)

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

    2013-04-01

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

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

    Science.gov (United States)

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

    2013-04-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-08-15

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

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

    Science.gov (United States)

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

    2011-08-01

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

  18. Simulations of LGM climate of East Asia by regional climate model

    Institute of Scientific and Technical Information of China (English)

    郑益群; 于革; 王苏民; 薛滨; 刘华强; 曾新民

    2003-01-01

    Climate conditions in the Last Glacial Maximum (LGM) were remarkably different from the present ones. Adopting a regional climate model (RCM) which has included a detailed land surface scheme, LGM climate of East Asia has been simulated. The effects of vegetation changes on LGM climate have been diagnosed by adding forces of LGM paleovegetation reconstructed from the geological records. The results of the simulations by RCM indicate that large decreases in whole year temperature of East Asia continent caused strongly enhanced winter monsoon and weakened summer monsoon. The strengthening and westward-stretching of the Subtropical High of West-Pacific are the key reasons of decreases of LGM summer precipitation in eastern China. Precipitation and effective precipitation were increased in the Tibetan Plateau and Middle-Asia, while the humid condition in the Tibetan Plateau was mainly caused by increase of precipitation. Accumulated snow of LGM was also increased in the Tibetan Plateau, which was helpful to developing glacier and permafrost. This experiment has simulated that the frozen soil areas extend southward to 30°N. In LGM climate simulation, climate effects caused by external forces were amplified by added paleovegetation, therefore, decreases of temperature, changes of precipitation and snowfall, and other climatic parameters were further strengthened, making the simulation results more approach to geological evidences.

  19. Berry composition and climate: responses and empirical models

    Science.gov (United States)

    Barnuud, Nyamdorj N.; Zerihun, Ayalsew; Gibberd, Mark; Bates, Bryson

    2014-08-01

    Climate is a strong modulator of berry composition. Accordingly, the projected change in climate is expected to impact on the composition of berries and of the resultant wines. However, the direction and extent of climate change impact on fruit composition of winegrape cultivars are not fully known. This study utilised a climate gradient along a 700 km transect, covering all wine regions of Western Australia, to explore and empirically describe influences of climate on anthocyanins, pH and titratable acidity (TA) levels in two or three cultivars of Vitis vinifera (Cabernet Sauvignon, Chardonnay and Shiraz). The results showed that, at a common maturity of 22° Brix total soluble solids, berries from the warmer regions had low levels of anthocyanins and TA as well as high pH compared to berries from the cooler regions. Most of these regional variations in berry composition reflected the prevailing climatic conditions of the regions. Thus, depending on cultivar, 82-87 % of TA, 83 % of anthocyanins and about half of the pH variations across the gradient were explained by climate-variable-based empirical models. Some of the variables that were relevant in describing the variations in berry attributes included: diurnal ranges and ripening period temperature (TA), vapour pressure deficit in October and growing degree days (pH), and ripening period temperatures (anthocyanins). Further, the rates of change in these berry attributes in response to climate variables were cultivar dependent. Based on the observed patterns along the climate gradient, it is concluded that: (1) in a warming climate, all other things being equal, berry anthocyanins and TA levels will decline whereas pH levels will rise; and (2) despite variations in non-climatic factors (e.g. soil type and management) along the sampling transect, variations in TA and anthocyanins were satisfactorily described using climate-variable-based empirical models, indicating the overriding impact of climate on berry

  20. 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.

  1. 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.

  2. High dimensional decision dilemmas in climate models

    Directory of Open Access Journals (Sweden)

    A. Bracco

    2013-10-01

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

  3. High dimensional decision dilemmas in climate models

    Directory of Open Access Journals (Sweden)

    A. Bracco

    2013-05-01

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

  4. Model biases in rice phenology under warmer climates.

    Science.gov (United States)

    Zhang, Tianyi; Li, Tao; Yang, Xiaoguang; Simelton, Elisabeth

    2016-06-07

    Climate-induced crop yields model projections are constrained by the accuracy of the phenology simulation in crop models. Here, we use phenology observations from 775 trials with 19 rice cultivars in 5 Asian countries to compare the performance of four rice phenology models (growing-degree-day (GDD), exponential, beta and bilinear models) when applied to warmer climates. For a given cultivar, the difference in growing season temperature (GST) varied between 2.2 and 8.2 °C in different trials, which allowed us to calibrate the models for lower GST and validate under higher GST, with three calibration experiments. The results show that in warmer climates the bilinear and beta phenology models resulted in gradually increasing bias for phenology predication and double yield bias per percent increase in phenology simulation bias, while the GDD and exponential models maintained a comparatively constant bias. The phenology biases were primarily attributed to varying phenological patterns to temperature in models, rather than on the size of the calibration dataset. Additionally, results suggest that model simulations based on multiple cultivars provide better predictability than using one cultivar. Therefore, to accurately capture climate change impacts on rice phenology, we recommend simulations based on multiple cultivars using the GDD and exponential phenology models.

  5. Model biases in rice phenology under warmer climates

    Science.gov (United States)

    Zhang, Tianyi; Li, Tao; Yang, Xiaoguang; Simelton, Elisabeth

    2016-06-01

    Climate-induced crop yields model projections are constrained by the accuracy of the phenology simulation in crop models. Here, we use phenology observations from 775 trials with 19 rice cultivars in 5 Asian countries to compare the performance of four rice phenology models (growing-degree-day (GDD), exponential, beta and bilinear models) when applied to warmer climates. For a given cultivar, the difference in growing season temperature (GST) varied between 2.2 and 8.2 °C in different trials, which allowed us to calibrate the models for lower GST and validate under higher GST, with three calibration experiments. The results show that in warmer climates the bilinear and beta phenology models resulted in gradually increasing bias for phenology predication and double yield bias per percent increase in phenology simulation bias, while the GDD and exponential models maintained a comparatively constant bias. The phenology biases were primarily attributed to varying phenological patterns to temperature in models, rather than on the size of the calibration dataset. Additionally, results suggest that model simulations based on multiple cultivars provide better predictability than using one cultivar. Therefore, to accurately capture climate change impacts on rice phenology, we recommend simulations based on multiple cultivars using the GDD and exponential phenology models.

  6. Arctic climate changes in the 21st century: Ensemble model estimates accounting for realism in present-day climate simulation

    Science.gov (United States)

    Eliseev, A. V.; Semenov, V. A.

    2016-11-01

    In the course of forecasting future climate changes in the Arctic Region based on calculations and an ensemble of the state-of-the-art global climate models, the results depend on the method of construction the statistics from the models.

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

    Science.gov (United States)

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

    2009-12-01

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

  8. Diagnostic indicators for integrated assessment models of climate policy

    NARCIS (Netherlands)

    Kriegler, Elmar; Petermann, Nils; Krey, Volker; Schwanitz, Valeria Jana; Luderer, Gunnar; Ashina, Shuichi; Bosetti, Valentina; Eom, Jiyong; Kitous, Alban; Méjean, Aurélie; Paroussos, Leonidas; Sano, Fuminori; Turton, Hal; Wilson, Charlie; Van Vuuren, Detlef P.

    2015-01-01

    Integrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wid

  9. SIMULATION OF PRESENT CLIMATE OVER EAST ASIA BY A REGIONAL CLIMATE MODEL

    Institute of Scientific and Technical Information of China (English)

    ZHANG Dong-feng; GAO Xue-jie; OUYANG Li-cheng; DONG Wen-jie

    2008-01-01

    A 15-year simulation of climate over East Asia is conducted with the latest version of a regional climate model RegCM3 nested in one-way mode to the ERA40 Re-analysis data. The performance of themodel in simulating present climate over East Asia and China is investigated. Results show that RegCM3 can reproduce well the atmospheric circulation over East Asia. The simulation of the main distribution patterns of surface air temperature and precipitation over China and their seasonal cycle/evolution, are basically agree with that of the observation. Meanwhile a general cold bias is found in the simulation. AS for the precipitation, the model tends to overestimate the precipitation in northern China while underestimate it in southern China, particularly in winter. In general, the model has better performance in simulating temperature than precipitation.

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

    Science.gov (United States)

    Brandefelt, J.; Kjellström, E.; Näslund, J.-O.; Strandberg, G.; Voelker, A. H. L.; Wohlfarth, B.

    2011-06-01

    We present a coupled global climate model (CGCM) simulation, integrated for 1500 yr to quasi-equilibrium, of a stadial (cold period) within Marine Isotope Stage 3 (MIS 3). The simulated Greenland stadial 12 (GS12; ~44 ka BP) annual global mean surface temperature (Ts) is 5.5 °C lower than in the simulated recent past (RP) climate and 1.3 °C higher than in the simulated Last Glacial Maximum (LGM; 21 ka BP) climate. The simulated GS12 is evaluated against proxy data and previous modelling studies of MIS3 stadial climate. We show that the simulated MIS 3 climate, and hence conclusions drawn regarding the dynamics of this climate, is highly model-dependent. The main findings are: (i) Proxy sea surface temperatures (SSTs) are higher than simulated SSTs in the central North Atlantic, in contrast to earlier simulations of MIS 3 stadial climate in which proxy SSTs were found to be lower than simulated SST. (ii) The Atlantic Meridional Overturning Circulation (AMOC) slows down by 50 % in the GS12 climate as compared to the RP climate. This slowdown is attained without freshwater forcing in the North Atlantic region, a method used in other studies to force an AMOC shutdown. (iii) El-Niño-Southern Oscillation (ENSO) teleconnections in mean sea level pressure (MSLP) are significantly modified by GS12 and LGM forcing and boundary conditions. (iv) Both the mean state and variability of the simulated GS12 is dependent on the equilibration. The annual global mean Ts only changes by 0.10 °C from model years 500-599 to the last century of the simulation, indicating that the climate system may be close to equilibrium already after 500 yr of integration. However, significant regional differences between the last century of the simulation and model years 500-599 exist. Further, the difference between simulated and proxy SST is reduced from model years 500-599 to the last century of the simulation. The results of the ENSO variability analysis is also shown to depend on the

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

    Directory of Open Access Journals (Sweden)

    J. Brandefelt

    2011-06-01

    Full Text Available We present a coupled global climate model (CGCM simulation, integrated for 1500 yr to quasi-equilibrium, of a stadial (cold period within Marine Isotope Stage 3 (MIS 3. The simulated Greenland stadial 12 (GS12; ~44 ka BP annual global mean surface temperature (Ts is 5.5 °C lower than in the simulated recent past (RP climate and 1.3 °C higher than in the simulated Last Glacial Maximum (LGM; 21 ka BP climate. The simulated GS12 is evaluated against proxy data and previous modelling studies of MIS3 stadial climate. We show that the simulated MIS 3 climate, and hence conclusions drawn regarding the dynamics of this climate, is highly model-dependent. The main findings are: (i Proxy sea surface temperatures (SSTs are higher than simulated SSTs in the central North Atlantic, in contrast to earlier simulations of MIS 3 stadial climate in which proxy SSTs were found to be lower than simulated SST. (ii The Atlantic Meridional Overturning Circulation (AMOC slows down by 50 % in the GS12 climate as compared to the RP climate. This slowdown is attained without freshwater forcing in the North Atlantic region, a method used in other studies to force an AMOC shutdown. (iii El-Niño-Southern Oscillation (ENSO teleconnections in mean sea level pressure (MSLP are significantly modified by GS12 and LGM forcing and boundary conditions. (iv Both the mean state and variability of the simulated GS12 is dependent on the equilibration. The annual global mean Ts only changes by 0.10 °C from model years 500–599 to the last century of the simulation, indicating that the climate system may be close to equilibrium already after 500 yr of integration. However, significant regional differences between the last century of the simulation and model years 500–599 exist. Further, the difference between simulated and proxy SST is reduced from model years 500–599 to the last century of the simulation. The results of the ENSO variability

  12. Climatic Classification over Asia during the Middle Holocene Climatic Optimum Based on PMIP Models

    Institute of Scientific and Technical Information of China (English)

    Hyuntaik Oh; Ho-Jeong Shin

    2016-01-01

    ABSTRACT:When considering potential global warming projections, it is useful to understand the im-pact of each climate condition at 6 kyr before present. Asian paleoclimate was simulated by performing an integration of the multi-model ensemble with the paleoclimate modeling intercomparison project (PMIP) models. The reconstructed winter (summer) surface air temperature at 6 kyr before present was 0.85 ºC (0.21 ºC) lower (higher) than the present day over Asia, 60ºE–150ºE, 10ºN–60ºN. The seasonal variation and heating differences of land and ocean in summer at 6 kyr before present might be much larger than present day. The winter and summer precipitation of 6 kyr before present were 0.067 and 0.017 mm·day-1 larger than present day, respectively. The Group B climate, which means the dry climates based on Köppen climate classification, at 6 kyr before present decreased 17%compared to present day, but the Group D which means the continental and microthermal climates at 6 kyr before present increased over 7%. Comparison between the results from the model simulation and published paleo-proxy record agrees within the limited sparse paleo-proxy record data.

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

    Energy Technology Data Exchange (ETDEWEB)

    1990-12-01

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

  14. 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.

  15. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

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

    2013-12-01

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

  16. 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.

  17. A Practical Philosophy of Complex Climate Modelling

    Science.gov (United States)

    Schmidt, Gavin A.; Sherwood, Steven

    2014-01-01

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

  18. The research in climate system modeling, simulating and forecasting

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    @@ The major point of the World Climate Research Program (WCRP) is to predict the real-time climate change in seasons and years. Climate disasters in China occurred frequently, and resulted in a 200 billion RMB lost annually.

  19. The Validation of Climate Models: The Development of Essential Practice

    Science.gov (United States)

    Rood, R. B.

    2011-12-01

    It is possible from both a scientific and philosophical perspective to state that climate models cannot be validated. However, with the realization that the scientific investigation of climate change is as much a subject of politics as of science, maintaining this formal notion of "validation" has significant consequences. For example, it relegates the bulk of work of many climate scientists to an exercise of model evaluation that can be construed as ill-posed. Even within the science community this motivates criticism of climate modeling as an exercise of weak scientific practice. Stepping outside of the science community, statements that validation is impossible are used in political arguments to discredit the scientific investigation of climate, to maintain doubt about projections of climate change, and hence, to prohibit the development of public policy to regulate the emissions of greenhouse gases. With the acceptance of the impossibility of validation, scientists often state that the credibility of models can be established through an evaluation process. A robust evaluation process leads to the quantitative description of the modeling system against a standard set of measures. If this process is standardized as institutional practice, then this provides a measure of model performance from one modeling release to the next. It is argued, here, that such a robust and standardized evaluation of climate models can be structured and quantified as "validation." Arguments about the nuanced meaning of validation and evaluation are a subject about which the climate modeling community needs to develop a standard. It does injustice to a body of science-based knowledge to maintain that validation is "impossible." Rather than following such a premise, which immediately devalues the knowledge base, it is more useful to develop a systematic, standardized approach to robust, appropriate validation. This stands to represent the complexity of the Earth's climate and its

  20. 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...

  1. A Model for Climate Change Adaptation

    Science.gov (United States)

    Pasqualini, D.; Keating, G. N.

    2009-12-01

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

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

    Directory of Open Access Journals (Sweden)

    J. H. T. Williams

    2012-10-01

    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.

  3. 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.

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  5. Modeling stakeholder-defined climate risk on the Upper Great Lakes

    Science.gov (United States)

    Moody, Paul; Brown, Casey

    2012-10-01

    Climate change is believed to pose potential risks to the stakeholders of the Great Lakes due to changes in lake levels. This paper presents a model of stakeholder-defined risk as a function of climate change. It describes the development of a statistical model that links water resources system performance and climate changes developed for the Great Lakes of North America. The function is used in a process that links bottom-up water system vulnerability assessment to top-down climate change information. Vulnerabilities are defined based on input from stakeholders and resource experts and are used to determine system performance thresholds. These thresholds are used to measure performance over a wide range of climate changes mined from a large (55,590 year) stochastic data set. The performance and climate conditions are used to create a climate response function, a statistical model to predict lake performance based on climate statistics. This function facilitates exploration and analysis of performance over a wide range of climate conditions. It can also be used to estimate risk associated with change in climate mean and variability resulting from climate change. Problematic changes in climate can be identified and the probability of those conditions estimated using climate projections or other sources of climate information. The function can also be used to evaluate the robustness of a regulation plan and to compare performance of alternate plans. This paper demonstrates the utility of the climate response function as applied within the context of the International Upper Great Lakes Study.

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

    Institute of Scientific and Technical Information of China (English)

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

    2007-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    J.S.PAL; F.GIORGI

    2007-01-01

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

  8. Hurricane Footprints in Global Climate Models

    Directory of Open Access Journals (Sweden)

    Francisco J. Tapiador

    2008-11-01

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

  9. Climate Modeling with a Linux Cluster

    Science.gov (United States)

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

    2004-08-01

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

  10. Precalibrating an intermediate complexity climate model

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-10-15

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

  11. 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.

  12. Reconstructing the climate states of the Late Pleistocene with the MIROC climate model

    Science.gov (United States)

    Chan, Wing-Le; Abe-Ouchi, Ayako; O'ishi, Ryouta; Takahashi, Kunio

    2014-05-01

    the general features of the model-simulated climates and how model resolution can affect these results. We also compare our results with some available proxy data to elucidate where model simulations show good agreement.

  13. Notes of Numerical Simulation of Summer Rainfall in China with a Regional Climate Model REMO

    Institute of Scientific and Technical Information of China (English)

    CUI Xuefeng; HUANG Gang; CHEN Wen

    2008-01-01

    Regional climate models are major tools for regional climate simulation and their output are mostly used for climate impact studies. Notes are reported from a series of numerical simulations of summer rainfall in China with a regional climate model. Domain sizes and running modes are major foci. The results reveal that the model in forecast mode driven by "perfect" boundaries could reasonably represent the inter-annual differences: heavy rainfall along the Yangtze River in 1998 and dry conditions in 1997. Model simulation in climate mode differs to a greater extent from observation than that in forecast mode. This may be due to the fact that in climate mode it departs further from the driving fields and relies more on internal model dynamical processes. A smaller domain in climate mode outperforms a larger one. Further development of model parameterizations including dynamic vegetation are encouraged in future studies.

  14. Simulations of present and future climates in the western U.S. with four nested regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Duffy, P B; Arritt, R W; Coquard, J; Gutowski, W; Han, J; Iorio, J; Kim, J; Leung, L R; Roads, J; Zeledon, E

    2004-06-15

    We analyze simulations of present and future climates in the western U.S. performed with four regional climate models (RCMs) nested within two global ocean-atmosphere climate models. Our primary goal is to assess the range of regional climate responses to increased greenhouse gases in available RCM simulations. The four RCMs used different geographical domains, different increased greenhouse gas scenarios for future-climate simulations, and (in some cases) different lateral boundary conditions. For simulations of the present climate, we compare RCM results to observations and to results of the GCM that provided lateral boundary conditions to the RCM. For future-climate (increased greenhouse gas) simulations, we compare RCM results to each other and to results of the driving GCMs. When results are spatially averaged over the western U.S., we find that the results of each RCM closely follow those of the driving GCM in the same region, in both present and future climates. In present-climate simulations, the RCMs have biases in spatially-averaged simulated precipitation and near-surface temperature that seem to be very close to those of the driving GCMs. In future-climate simulations, the spatially-averaged RCM-projected responses in precipitation and near-surface temperature are also very close to those of the respective driving GCMs. Precipitation responses predicted by the RCMs are in many regions not statistically significant compared to interannual variability. Where the predicted precipitation responses are statistically significant, they are positive. The models agree that near-surface temperatures will increase, but do not agree on the spatial pattern of this increase. The four RCMs produce very different estimates of water content of snow in the present climate, and of the change in this water content in response to increased greenhouse gases.

  15. Shifts in climate suitability for wine production as a result of climate change in a temperate climate wine region of Romania

    Science.gov (United States)

    Irimia, Liviu Mihai; Patriche, Cristian Valeriu; Quenol, Hervé; Sfîcă, Lucian; Foss, Chris

    2017-01-01

    Climate change is causing important shifts in the suitability of regions for wine production. Fine scale mapping of these shifts helps us to understand the evolution of vineyard climates, and to find solutions through viticultural adaptation. The aim of this study is to identify and map the structural and spatial shifts that occurred in the climatic suitability for wine production of the Cotnari wine growing region (Romania) between 1961 and 2013. Discontinuities in trends of temperature were identified, and the averages and trends of 13 climatic parameters for the 1961 to 1980 and 1981 to 2013 time periods were analysed. Using the averages of these climatic parameters, climate suitability for wine production was calculated at a resolution of 30 m and mapped for each time period, and the changes analysed. The results indicate shifts in the area's historic climatic profile, due to an increase of heliothermal resources and precipitation constancy. The area's climate suitability for wine production was modified by the loss of climate suitability for white table wines, sparkling wines and wine for distillates; shifts in suitability to higher altitudes by about 67 m, and a 48.6% decrease in the area suitable for quality white wines; and the occurrence of suitable climates for red wines at lower altitudes. The study showed that climate suitability for wine production has a multi-level spatial structure, with classes requiring a cooler climate being located at a higher altitude than those requiring a warmer climate. Climate change has therefore resulted in the shift of climate suitability classes for wine production to higher altitudes.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-03-01

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

  17. The Eemian climate simulated by two models of different complexities

    Science.gov (United States)

    Nikolova, Irina; Yin, Qiuzhen; Berger, Andre; Singh, Umesh; Karami, Pasha

    2013-04-01

    The Eemian period, also known as MIS-5, experienced warmer than today climate, reduction in ice sheets and important sea-level rise. These interesting features have made the Eemian appropriate to evaluate climate models when forced with astronomical and greenhouse gas forcings different from today. In this work, we present the simulated Eemian climate by two climate models of different complexities, LOVECLIM (LLN Earth system model of intermediate complexity) and CCSM3 (NCAR atmosphere-ocean general circulation model). Feedbacks from sea ice, vegetation, monsoon and ENSO phenomena are discussed to explain the regional similarities/dissimilarities in both models with respect to the pre-industrial (PI) climate. Significant warming (cooling) over almost all the continents during boreal summer (winter) leads to a largely increased (reduced) seasonal contrast in the northern (southern) hemisphere, mainly due to the much higher (lower) insolation received by the whole Earth in boreal summer (winter). The arctic is warmer than at PI through the whole year, resulting from its much higher summer insolation and its remnant effect in the following fall-winter through the interactions between atmosphere, ocean and sea ice. Regional discrepancies exist in the sea-ice formation zones between the two models. Excessive sea-ice formation in CCSM3 results in intense regional cooling. In both models intensified African monsoon and vegetation feedback are responsible for the cooling during summer in North Africa and on the Arabian Peninsula. Over India precipitation maximum is found further west, while in Africa the precipitation maximum migrates further north. Trees and grassland expand north in Sahel/Sahara, trees being more abundant in the results from LOVECLIM than from CCSM3. A mix of forest and grassland occupies continents and expand deep in the high northern latitudes in line with proxy records. Desert areas reduce significantly in Northern Hemisphere, but increase in North

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

    Institute of Scientific and Technical Information of China (English)

    高学杰; 罗勇; 林万涛; 赵宗慈; FilippoGIORGI

    2003-01-01

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

  19. AUTH Regional Climate Model Contributions to EURO-CORDEX. Part II

    Science.gov (United States)

    Katragkou, E.; Gkotovou, I.; Kartsios, S.; Pavlidis, V.; Tsigaridis, K.; Trail, M.; Nazarenko, L.; Karacostas, Theodore S.

    2017-01-01

    Regional climate downscaling techniques are being increasingly used to provide higher-resolution climate information than is available directly from contemporary global climate models. The Coordinated Regional Climate Downscaling Experiment (CORDEX) initiative was build to foster communication and knowledge exchange between regional climate modelers. The Department of Meteorology and Climatology of the Aristotle University of Thessaloniki has been contributing to the CORDEX initiative since 2010, with regional climate model simulations over the European domain (EURO-CORDEX). Results of this work are presented here, including two hindcasts and a historical simulation with the Weather Research Forecasting model (WRF), driven by ERA-interim reanalysis and the NASA Earth System Goddard Institute for Space Studies (GISS) ModelE2, respectively. Model simulations are evaluated with the EOBS climatology and the model performance is assessed.

  20. The climate impact of energy peat utilisation - comparison and sensitivity analysis of Finnish and Swedish results

    Energy Technology Data Exchange (ETDEWEB)

    Holmgren, Kristina; Kirkinen, Johanna; Savolainen, Ilkka

    2006-06-15

    The climate impact of energy peat utilisation have been studied both in Finland by VTT Technical Research Centre and in Sweden by IVL Swedish Environmental Research Institute Ltd. The main objective of this study is to compare the results of earlier studies by VTT and IVL and to perform a sensitivity analysis of previous and new results. The scientific approach of the two studies is very similar. The climate impact of peat utilisation is considered from a life-cycle point of view by taking into account all phases of the peat utilisation chain. Peat reserves can be both sinks and sources of greenhouse gas emissions as well as there are both uptake and emissions of greenhouse gases during the utilisation chain. The net impact of the utilisation chain is assessed as the climate impact due to the utilisation chain minus the climate impact of non-utilisation chain. The instantaneous radiative forcing and accumulated radiative forcing are used in both studies as the indicator of the climate impact. Radiative forcing is calculated on the basis of the concentration changes due to emissions and uptake of greenhouse gases. The differences in the models for calculating concentrations and radiative forcing are minor. There are some differences in the definitions and boundaries of the considered peat utilisation chains, although the differences in the results due to differences in the chain definitions are small. The main reason for the differences in results between the two studies is differences in emission (and uptake) estimates for the after-treatment phase and the non-utilisation chain. Both Swedish and Finnish studies show that the use of cultivated peatland for energy peat utilisation results in lower climate impact than using coal (within 100 years). Both studies show that the use of pristine mires for peat production will result in larger climate impact than the use of already drained peatlands. The climate impact of peat utilisation chains where fens and forestry

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

    Energy Technology Data Exchange (ETDEWEB)

    Koeltzov, Morten Andreas Oedegaard

    2012-11-01

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

  2. Modeling lakes and reservoirs in the climate system

    NARCIS (Netherlands)

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

    2009-01-01

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

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

    NARCIS (Netherlands)

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

    1998-01-01

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

  4. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP: overview and description of models, simulations and climate diagnostics

    Directory of Open Access Journals (Sweden)

    J.-F. Lamarque

    2012-08-01

    Full Text Available The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP consists of a series of timeslice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting radiative forcing and the associated composition changes. Here we introduce the various simulations performed under ACCMIP and the associated model output. The ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions lead to a significant range in emissions, mostly for ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind reveals biases consistent with state-of-the-art climate models. The model-to-model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results, but with outliers different enough to possibly affect their representation of climate impact on chemistry.

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

    Science.gov (United States)

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

    2015-09-01

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

  6. Interpolation of climate variables and temperature modeling

    Science.gov (United States)

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

    2012-01-01

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

  7. 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)

  8. Construction of a novel economy-climate model

    Institute of Scientific and Technical Information of China (English)

    CHOU JieMing; DONG WenJie; YE DuZheng

    2007-01-01

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

  9. From Global Climate Model Projections to Local Impacts Assessments: Analyses in Support of Planning for Climate Change

    Science.gov (United States)

    Snover, A. K.; Littell, J. S.; Mantua, N. J.; Salathe, E. P.; Hamlet, A. F.; McGuire Elsner, M.; Tohver, I.; Lee, S.

    2010-12-01

    Assessing and planning for the impacts of climate change require regionally-specific information. Information is required not only about projected changes in climate but also the resultant changes in natural and human systems at the temporal and spatial scales of management and decision making. Therefore, climate impacts assessment typically results in a series of analyses, in which relatively coarse-resolution global climate model projections of changes in regional climate are downscaled to provide appropriate input to local impacts models. This talk will describe recent examples in which coarse-resolution (~150 to 300km) GCM output was “translated” into information requested by decision makers at relatively small (watershed) and large (multi-state) scales using regional climate modeling, statistical downscaling, hydrologic modeling, and sector-specific impacts modeling. Projected changes in local air temperature, precipitation, streamflow, and stream temperature were developed to support Seattle City Light’s assessment of climate change impacts on hydroelectric operations, future electricity load, and resident fish populations. A state-wide assessment of climate impacts on eight sectors (agriculture, coasts, energy, forests, human health, hydrology and water resources, salmon, and urban stormwater infrastructure) was developed for Washington State to aid adaptation planning. Hydro-climate change scenarios for approximately 300 streamflow locations in the Columbia River basin and selected coastal drainages west of the Cascades were developed in partnership with major water management agencies in the Pacific Northwest to allow planners to consider how hydrologic changes may affect management objectives. Treatment of uncertainty in these assessments included: using “bracketing” scenarios to describe a range of impacts, using ensemble averages to characterize the central estimate of future conditions (given an emissions scenario), and explicitly assessing

  10. Projected impact of climate change in the North and Baltic Sea. Results from dynamical downscaling of global CMIP climate scenarios

    Science.gov (United States)

    Gröger, Matthias; Maier-Reimer, Ernst; Mikolajewicz, Uwe; Sein, Dmitry

    2013-04-01

    Climate models have predicted strongest climate change impact for the mid/high lattiude areas. Despite their importance, shelves seas (which are supposed to account for more than 20% of global marine primary production and for up to 50% of total marine carbon uptake) are not adequately resolved in climate models. In this study, the global ocean general circulation and biogeochemistry model MPIOM/HAMOCC has been setup with an enhanced resolution over the NW European shelf (~10 km in the southern North Sea). For a realistic representation of atmosphere-ocean interactions the regional model REMO has been implemented. Thus, this model configuration allows a physically consistent simulation of climate signal propagation from the North Atlantic over the North Sea into the Baltic Sea since it interactively simulates mass and energy fluxes between the three basins. The results indicate substantial changes in hydrographic and biological conditions for the end of the 21st Century. A freshening by about 0.75 psu together with a surface warming of ~2.0 K and associated circulation changes in and outside the North Sea reduce biological production on the NW European shelf by ~35%. This reduction is twice as strong as the reduction in the open ocean. The underlying mechanism is a spatially well confined stratification feedback along the shelf break and the continental slope which reduces the winter mixed layer by locally more than 200 m compared to current conditions. As a consequence winter nutrient supply from the deep Atlantic declines between 40 and 50%. In addition to this, the volume transport of water and salt into the North Sea will slightly reduce (~10%) during summer. At the end of the 21st Century the North Sea appears nearly decoupled from the deep Atlantic. The projected decline in biological productivity and subsequent decrease of phytoplankton (by averaged 25%) will probably negatively affect the local fish stock in the North Sea. In the Baltic Sea the climate

  11. Integrated climate and hydrology modelling - Coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model

    Energy Technology Data Exchange (ETDEWEB)

    Dahl Larsen, M.A. [Technical Univ. of Denmark. DTU Management Engineering, DTU Risoe Campus, Roskilde (Denmark)

    2013-10-15

    location and resolution and of these the domain size was found to be the key parameter. For the inverse calibration of MIKE SHE the measured latent, sensible and soil heat fluxes lacked energy balance closure, requiring modifications based on different scenarios on the origin of the erroneous component. Also, the differing modelling platforms of Windows and Linux posed a great challenge in the development and testing of the coupling code. A primary task in the study was to assess the computational interaction between the two models in terms of scaling and simulation performance. Of six HIRHAM climatic output variables four showed an improvement with an increase in the data transfer frequency between the models alongside an increase in the computation time. In general however, the coupled runs were poorer than the uncoupled runs. This is not surprising and is attributed to each of the models having undergone substantial refinement and calibration in uncoupled modes to reproduce observations. By imposing a new LSM to HIRHAM and new driving data to MIKE SHE the coupled results are likely to be poorer. The feasibility and prospects of the coupled setup of HIRHAM and MIKE SHE are however clearly suggested by the simulations in the present PhD study. Further research is required to improve the simulations through coupled model calibration and other refinements are needed with respect to spatial and temporal scales, model processes and evaluation. (Author)

  12. Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

    Science.gov (United States)

    Gilligan, J. M.; John, N. J.; van der Linden, M.

    2015-12-01

    Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

  13. Modelling oxygen isotopes in the University of Victoria Earth System Climate Model

    Directory of Open Access Journals (Sweden)

    C. E. Brennan

    2011-09-01

    Full Text Available Implementing oxygen isotopes (H218O, H216O in coupled climate models provides both an important test of the individual model's hydrological cycle, and a powerful tool to mechanistically explore past climate changes while producing results directly comparable to isotope proxy records. Here we describe the addition of oxygen isotopes in the University of Victoria Earth System Climate Model (UVic ESCM. Equilibrium simulations are performed for preindustrial and Last Glacial Maximum conditions. The oxygen isotope content in the model preindustrial climate is compared against observations for precipitation and seawater. The distribution of oxygen isotopes during the LGM is compared against available paleo-reconstructions.

  14. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Overview and Description of Models, Simulations and Climate Diagnostics

    Science.gov (United States)

    Lamarque, J.-F.; Shindell, D. T.; Naik, V.; Plummer, D.; Josse, B.; Righi, M.; Rumbold, S. T.; Schulz, M.; Skeie, R. B.; Strode, S.; Young, P. J.; Cionni, I.; Dalsoren, S.; Eyring, V.; Bergmann, D.; Cameron-Smith, P.; Collins, W. J.; Doherty, R.; Faluvegi, G.; Folberth, G.; Ghan, S. J.; Horowitz, L. W.; Lee, Y. H.; MacKenzie, I. A.; Nagashima, T.

    2013-01-01

    The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.

  15. General and Partial Equilibrium Modeling of Sectoral Policies to Address Climate Change in the United States

    Energy Technology Data Exchange (ETDEWEB)

    Pizer, William; Burtraw, Dallas; Harrington, Winston; Newell, Richard; Sanchirico, James; Toman, Michael

    2003-03-31

    This document provides technical documentation for work using detailed sectoral models to calibrate a general equilibrium analysis of market and non-market sectoral policies to address climate change. Results of this work can be found in the companion paper, "Modeling Costs of Economy-wide versus Sectoral Climate Policies Using Combined Aggregate-Sectoral Model".

  16. Climate simulations for the last interglacial period by means of climate models of different complexity

    Energy Technology Data Exchange (ETDEWEB)

    Montoya, M.L. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

    1999-07-01

    Climatic conditions during the lst interglacial (125,000 years before present) are investigated with two climate models of different complexity: The atmosphere-ocean general circulation model ECHAM-1/LSG and the climate system model of intermediate complexity CLIMBER-2. In particular the role of vegetation at the last interglacial maximum, and its importance for a consistent simulation of the Mid-Holocene climate, has been investigated (EU project ASPEN: Air-Sea Wave Processes in Climate Change Models). Comparison of the results of the two models reveals a broad agreement in most large-scale features. Nevertheless, discrepancies are also detected. Essentially, the models differ in their ocean circulation responses. Profiting of the fast turnaround time of CLIMBER-2, a number of sensitivity experiments have been performed to try to explain the possible reasons for these differences, and to analyze additional effects not included in the previous simulations. In particular, the role of vegetation at the last interglacial maximum has been investigated. Comparison of the simulated responses against CLIMAP reconstructed SSTs for Marine Isotope Stage 5e shows a satisfactory agreement within the data uncertainties. (orig.) [German] Die klimatischen Bedingungen waehrend der letzten interglazialen Periode (vor 125 000 Jahren) werden anhand zweier Klimamodelle unterschiedlicher Komplexitaet untersucht: Dem Ozean-Atmosphaere gekoppelten allgemeinen Zirkulationsmodell ECHAM-1/LSG und dem Klimasystemmodell mittlerer Komplexitaet CLIMBER-2. Inbesondere wurde die Rolle der Vegetation in der letzten interglazialen Periode und ihre Bedeutung fuer eine konsistente Simulation des mittelholozaenischen Klimas untersucht (EU-Projekt ASPEN: Air-Sea Wave Processes in Climate Change Models - 'Klimavariationen in historischen Zeiten'). Der Vergleich der Ergebnisse beider Modelle zeigt eine gute Uebereinstimmung der meisten der grossskaligen Eigenschaften, allerdings zeigen sich

  17. Regional climate simulations over Vietnam using the WRF model

    Science.gov (United States)

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

    2016-10-01

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

  18. Mixing parametrizations for ocean climate modelling

    Science.gov (United States)

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

    2016-04-01

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

  19. 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.

  20. A Tool for Sharing Empirical Models of Climate Impacts

    Science.gov (United States)

    Rising, J.; Kopp, R. E.; Hsiang, S. M.

    2013-12-01

    Scientists, policy advisors, and the public struggle to synthesize the quickly evolving empirical work on climate change impacts. The Integrated Assessment Models (IAMs) used to estimate the impacts of climate change and the effects of adaptation and mitigation policies can also benefit greatly from recent empirical results (Kopp, Hsiang & Oppenheimer, Impacts World 2013 discussion paper). This paper details a new online tool for exploring, analyzing, combining, and communicating a wide range of impact results, and supporting their integration into IAMs. The tool uses a new database of statistical results, which researchers can expand both in depth (by providing additional results that describing existing relationships) and breadth (by adding new relationships). Scientists can use the tool to quickly perform meta-analyses of related results, using Bayesian techniques to produce pooled and partially-pooled posterior distributions. Policy advisors can apply the statistical results to particular contexts, and combine different kinds of results in a cost-benefit framework. For example, models of the impact of temperature changes on agricultural yields can be first aggregated to build a best-estimate of the effect under given assumptions, then compared across countries using different temperature scenarios, and finally combined to estimate a social cost of carbon. The general public can better understand the many estimates of climate impacts and their range of uncertainty by exploring these results dynamically, with maps, bar charts, and dose-response-style plots. Front page of the climate impacts tool website. Sample "collections" of models, within which all results are estimates of the same fundamental relationship, are shown on the right. Simple pooled result for Gelman's "8 schools" example. Pooled results are calculated analytically, while partial-pooling (Bayesian hierarchical estimation) uses posterior simulations.

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

    Science.gov (United States)

    Lenhard, Johannes; Winsberg, Eric

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

  2. Uncertainty of the hydrological response to climate change conditions; 605 basins, 3 hydrological models, 5 climate models, 5 hydrological variables

    Science.gov (United States)

    Melsen, Lieke; Mizukami, Naoki; Newman, Andrew; Clark, Martyn; Teuling, Adriaan

    2016-04-01

    Many studies investigated the effect of a changing climate on the hydrological response of a catchment and uncertainty of the effect coming from hydrologic modelling (e.g., forcing, hydrologic model structures, and parameters). However, most past studies used only a single or a small number of catchments. To go beyond the case-study, and to assess the uncertainty involved in modelling the hydrological impact of climate change more comprehensively, we studied 605 basins over a wide range of climate regimes throughout the contiguous USA. We used three different widely-used hydrological models (VIC, HBV, SAC), which we forced with five distinct climate model outputs. The hydrological models have been run for a base period (1986-2008) for which observations were available, and for a future period (2070-2099). Instead of calibrating each hydrological model for each basin, the model has been run with a parameter sample (varying from 1600 to 1900 samples dependent on the number of free parameters in the model). Five hydrological states and fluxes were stored; discharge, evapotranspiration, soil moisture, SWE and snow melt, and 15 different metrics and signatures have been obtained for each model run. With the results, we conduct a sensitivity analysis over the change in signatures from the future period compared to the base period. In this way, we can identify the parameters that are responsible for certain projected changes, and identify the processes responsible for this change. By using three different models, in which VIC is most distinctive in including explicit vegetation parameters, we can compare different process representations and the effect on the projected hydrological change.

  3. The North American Regional Climate Change Assessment Program: Overview of Phase I Results

    Energy Technology Data Exchange (ETDEWEB)

    Mearns, L. O.; Arritt, R.; Biner, S.; Bukovsky, Melissa; McGinnis, Seth; Sain, Steve; Caya, Daniel; Correia Jr., James; Flory, Dave; Gutowski, William; Takle, Gene; Jones, Richard; Leung, Lai-Yung R.; Moufouma-Okia, Wilfran; McDaniel, Larry; Nunes, A.; Qian, Yun; Roads, J.; Sloan, Lisa; Snyder, Mark A.

    2012-09-20

    The North American Regional Climate Change Assessment Program is an international effort designed to systematically investigate the uncertainties in regional scale projections of future climate and produce high resolution climate change scenarios using multiple regional climate models (RCMs) nested within atmosphere ocean general circulation models (AOGCMs) forced with the A2 SRES scenario, with a common domain covering the conterminous US, northern Mexico, and most of Canada. The program also includes an evaluation component (Phase I) wherein the participating RCMs are nested within 25 years of NCEP/DOE global reanalysis II. The grid spacing of the RCM simulations is 50 km.

  4. 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.

  5. Conceptual Model of Climate Change Impacts at LANL

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-05-17

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

  6. New proofs of the recent climate warming over the Tibetan Plateau as a result of the increasing greenhouse gases emissions

    Institute of Scientific and Technical Information of China (English)

    DUAN Anmin; WU Guoxiong; ZHANG Qiong; LIU Yimin

    2006-01-01

    A striking climate warming over the Tibetan Plateau during the last decades has been revealed by many studies, but evidence linking it to human activity is insufficient. By using historical observations, here we show that the in situ climate warming is accompanied by a distinct decreasing trend of the diurnal range of surface air temperature. The ERA40 reanalysis further indicates that there seems to be a coherent warming trend near the tropopause but a cooling trend in the lower stratosphere. Moreover, all these features can be reproduced in two coupled climate models forced by observed CO2 concentration of the 20th century but cannot be produced by the fixed external conditions before the industrial revolution. These suggest that the recent climate warming over the Tibetan Plateau primarily results from the increasing anthropogenic greenhouse gases emissions, and impacts of the increased greenhouse gases emissions upon the climate change in the plateau are probably more serious than the rest of the world.

  7. Application and impacts of the GlobeLand30 land cover dataset on the Beijing Climate Center Climate Model

    Science.gov (United States)

    Shi, X.; Nie, S.; Ju, W.; Yu, L.

    2016-04-01

    Land cover (LC) is a necessary and important input variable of the land surface and climate model, and has significant impacts on climate and climate changes. In this paper, the new higher-resolution global LC dataset, GlobeLand30, was employed in the Beijing Climate Center Climate System Model (BCC_CSM) to investigate LC impacts on the land surface and climate via simulation experiments. The strategy for connecting the new LC dataset and model was to merge the GlobeLand30 data with other satellite remote sensing datasets to enlarge the plant function types (PFT) fitted for the BCC_CSM. The area-weighted up-scaling approach was used to aggregate the 30m-resolution GlobeLand30 data onto the coarser model grids and derive PFT as well as percentage information. The LC datasets of GlobeLand30 and the original BCC_CSM had generally consistent spatial features but with significant differences. Numerical simulations with these two LC datasets were conducted and compared to present the effects of the new GlobeLand30 data on the climate. Results show that with the new LC data products, several model biases between simulations and observations in the BCC climate model with original LC datasets were effectively reduced, including the positive bias of precipitation in the mid-high latitude of the northern hemisphere and the negative bias in the Amazon, as well as the negative bias of air temperature in part of the southern hemisphere. Therefore, the GlobeLand30 data are suitable for use in the BCC_CSM component models and can improve the performance of climate simulations.

  8. The consistency evaluation of the climate version of the Eta regional forecast model developed for regional climate downscaling

    CERN Document Server

    Pisnichenko, I A

    2007-01-01

    The regional climate model prepared from Eta WS (workstation) forecast model has been integrated over South America with the horizontal resolution of 40 km for the period of 1961-1977. The model was forced at its lateral boundaries by the outputs of HadAMP. The data of HadAMP represent the simulation of modern climate with the resolution about150 km. In order to prepare climate regional model from the Eta forecast model was added new blocks and multiple modifications and corrections was made in the original model. The running of climate Eta model was made on the supercomputer SX-6. The detailed analysis of the results of dynamical downscaling experiment includes an investigation of a consistency between the regional and AGCM models as well as of ability of the regional model to resolve important features of climate fields on the finer scale than that resolved by AGCM. In this work we show the results of our investigation of the consistency of the output fields of the Eta model and HadAMP. We have analysed geo...

  9. Nitrogen Controls on Climate Model Evapotranspiration.

    Science.gov (United States)

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

    2002-02-01

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

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

    Science.gov (United States)

    Knutti, R.

    2009-12-01

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

  11. Climate model boundary conditions for four Cretaceous time slices

    Directory of Open Access Journals (Sweden)

    J. O. Sewall

    2007-06-01

    Full Text Available General circulation models (GCMs are useful tools for investigating the characteristics and dynamics of past climates. Understanding of past climates contributes significantly to our overall understanding of Earth's climate system. One of the most time consuming, and often daunting, tasks facing the paleoclimate modeler, particularly those without a geological background, is the production of surface boundary conditions for past time periods. These boundary conditions consist of, at a minimum, continental configurations derived from plate tectonic modeling, topography, bathymetry, and a vegetation distribution. Typically, each researcher develops a unique set of boundary conditions for use in their simulations. Thus, unlike simulations of modern climate, basic assumptions in paleo surface boundary conditions can vary from researcher to researcher. This makes comparisons between results from multiple researchers difficult and, thus, hinders the integration of studies across the broader community. Unless special changes to surface conditions are warranted, researcher dependent boundary conditions are not the most efficient way to proceed in paleoclimate investigations. Here we present surface boundary conditions (land-sea distribution, paleotopography, paleobathymetry, and paleovegetation distribution for four Cretaceous time slices (120 Ma, 110 Ma, 90 Ma, and 70 Ma. These boundary conditions are modified from base datasets to be appropriate for incorporation into numerical studies of Earth's climate and are available in NetCDF format upon request from the lead author. The land-sea distribution, bathymetry, and topography are based on the 1°×1° (latitude x longitude paleo Digital Elevation Models (paleoDEMs of Christopher Scotese. Those paleoDEMs were adjusted using the paleogeographical reconstructions of Ronald Blakey (Northern Arizona University and published literature and were then modified for use in GCMs. The paleovegetation

  12. Climate model boundary conditions for four Cretaceous time slices

    Directory of Open Access Journals (Sweden)

    J. O. Sewall

    2007-11-01

    Full Text Available General circulation models (GCMs are useful tools for investigating the characteristics and dynamics of past climates. Understanding of past climates contributes significantly to our overall understanding of Earth's climate system. One of the most time consuming, and often daunting, tasks facing the paleoclimate modeler, particularly those without a geological background, is the production of surface boundary conditions for past time periods. These boundary conditions consist of, at a minimum, continental configurations derived from plate tectonic modeling, topography, bathymetry, and a vegetation distribution. Typically, each researcher develops a unique set of boundary conditions for use in their simulations. Thus, unlike simulations of modern climate, basic assumptions in paleo surface boundary conditions can vary from researcher to researcher. This makes comparisons between results from multiple researchers difficult and, thus, hinders the integration of studies across the broader community. Unless special changes to surface conditions are warranted, researcher dependent boundary conditions are not the most efficient way to proceed in paleoclimate investigations. Here we present surface boundary conditions (land-sea distribution, paleotopography, paleobathymetry, and paleovegetation distribution for four Cretaceous time slices (120 Ma, 110 Ma, 90 Ma, and 70 Ma. These boundary conditions are modified from base datasets to be appropriate for incorporation into numerical studies of Earth's climate and are available in NetCDF format upon request from the lead author. The land-sea distribution, bathymetry, and topography are based on the 1°×1° (latitude × longitude paleo Digital Elevation Models (paleoDEMs of Christopher Scotese. Those paleoDEMs were adjusted using the paleogeographical reconstructions of Ronald Blakey (Northern Arizona University and published literature and were then modified for use in GCMs. The paleovegetation

  13. Ensemble of regional climate model projections for Ireland

    Science.gov (United States)

    Nolan, Paul; McGrath, Ray

    2016-04-01

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

  14. Sensitivity of ecosystem models to the spatial resolution of the NCAR Community Climate Model CCM2

    Energy Technology Data Exchange (ETDEWEB)

    Ciret, C. [Macquarie Univ., Sydney (Australia). Climate Impacts Centre; Henderson-Sellers, A. [Royal Melbourne Institute of Technology, Melbourne (Australia)

    1998-06-01

    This study evaluates the sensitivity of ecosystem models to changes in the horizontal resolution of version 2 of the national centre for atmospheric research community climate model (CCM2). A previous study has shown that the distributions of natural ecosystems predicted by vegetation models using coarse resolution present-day climate simulations are poorly simulated. It is usually assumed that increasing the spatial resolution of general circulation models (GCMs) will improve the simulation of climate, and hence will increase our level of confidence in the use of GCM output for impacts studies. The principal goals of this study is to investigate this hypothesis and to identify which biomes are more affected by the changes in spatial resolution of the forcing climate. The ecosystem models used are the BIOME-1 model and a version of the Holdridge scheme. The climate simulations come from a set of experiments in which CCM2 was run with increasing horizontal resolutions. The biome distributions predicted using CCM2 climates are compared against biome distributions predicted using observed climate datasets. Results show that increasing the resolution of CCM2 produces a significant improvement of the global-scale vegetation prediction, indicating that a higher level of confidence can be vested in the global-scale prediction of natural ecosystems using medium and high resolution GCMs. However, not all biomes are equally affected by the increased spatial resolution, and although certain biome distributions are improved (e.g. hot desert, tropical seasonal forest), others remain globally poorly predicted even at high resolution (e.g. grasses and xerophytic woods). In addition, these results show that some climatic biases are enhanced with increasing resolution (e.g. in mountain ranges), resulting in the inadequate prediction of biomes. (orig.) With 16 figs., 5 tabs., 37 refs.

  15. Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

    Science.gov (United States)

    Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

    2016-09-01

    Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize (Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

  16. Climate model boundary conditions for four Cretaceous time slices

    NARCIS (Netherlands)

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

    2007-01-01

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

  17. 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.

  18. Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

    Science.gov (United States)

    Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

    2011-12-01

    Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling

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

    Science.gov (United States)

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

    2008-10-23

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

  20. Climate model forecast biases assessed with a perturbed physics ensemble

    Science.gov (United States)

    Mulholland, David P.; Haines, Keith; Sparrow, Sarah N.; Wallom, David

    2016-10-01

    Perturbed physics ensembles have often been used to analyse long-timescale climate model behaviour, but have been used less often to study model processes on shorter timescales. We combine a transient perturbed physics ensemble with a set of initialised forecasts to deduce regional process errors present in the standard HadCM3 model, which cause the model to drift in the early stages of the forecast. First, it is shown that the transient drifts in the perturbed physics ensembles can be used to recover quantitatively the parameters that were perturbed. The parameters which exert most influence on the drifts vary regionally, but upper ocean mixing and atmospheric convective processes are particularly important on the 1-month timescale. Drifts in the initialised forecasts are then used to recover the `equivalent parameter perturbations', which allow identification of the physical processes that may be at fault in the HadCM3 representation of the real world. Most parameters show positive and negative adjustments in different regions, indicating that standard HadCM3 values represent a global compromise. The method is verified by correcting an unusually widespread positive bias in the strength of wind-driven ocean mixing, with forecast drifts reduced in a large number of areas as a result. This method could therefore be used to improve the skill of initialised climate model forecasts by reducing model biases through regional adjustments to physical processes, either by tuning or targeted parametrisation refinement. Further, such regionally tuned models might also significantly outperform standard climate models, with global parameter configurations, in longer-term climate studies.

  1. The climate impact of energy peat utilisation - comparison and sensitivity analysis of Finnish and Swedish results

    Energy Technology Data Exchange (ETDEWEB)

    Holmgren, Kristina; Kirkinen, Johanna; Savolainen, Ilkka

    2006-06-15

    The climate impact of energy peat utilisation have been studied both in Finland by VTT Technical Research Centre and in Sweden by IVL Swedish Environmental Research Institute Ltd. The main objective of this study is to compare the results of earlier studies by VTT and IVL and to perform a sensitivity analysis of previous and new results. The scientific approach of the two studies is very similar. The climate impact of peat utilisation is considered from a life-cycle point of view by taking into account all phases of the peat utilisation chain. Peat reserves can be both sinks and sources of greenhouse gas emissions as well as there are both uptake and emissions of greenhouse gases during the utilisation chain. The net impact of the utilisation chain is assessed as the climate impact due to the utilisation chain minus the climate impact of non-utilisation chain. The instantaneous radiative forcing and accumulated radiative forcing are used in both studies as the indicator of the climate impact. Radiative forcing is calculated on the basis of the concentration changes due to emissions and uptake of greenhouse gases. The differences in the models for calculating concentrations and radiative forcing are minor. There are some differences in the definitions and boundaries of the considered peat utilisation chains, although the differences in the results due to differences in the chain definitions are small. The main reason for the differences in results between the two studies is differences in emission (and uptake) estimates for the after-treatment phase and the non-utilisation chain. Both Swedish and Finnish studies show that the use of cultivated peatland for energy peat utilisation results in lower climate impact than using coal (within 100 years). Both studies show that the use of pristine mires for peat production will result in larger climate impact than the use of already drained peatlands. The climate impact of peat utilisation chains where fens and forestry

  2. Cyclones and extreme windstorm events over Europe under climate change: Global and regional climate model diagnostics

    Science.gov (United States)

    Leckebusch, G. C.; Ulbrich, U.

    2003-04-01

    More than any changes of the climate system mean state conditions, the development of extreme events may influence social, economic and legal aspects of our society. This linkage results from the impact of extreme climate events (natural hazards) on environmental systems which again are directly linked to human activities. Prominent examples from the recent past are the record breaking rainfall amounts of August 2002 in central Europe which produced widespread floodings or the wind storm Lothar of December 1999. Within the MICE (Modelling the Impact of Climate Extremes) project framework an assessment of the impact of changes in extremes will be done. The investigation is carried out for several different impact categories as agriculture, energy use and property damage. Focus is laid on the diagnostics of GCM and RCM simulations under different climate change scenarios. In this study we concentrate on extreme windstorms and their relationship to cyclone activity in the global HADCM3 as well as in the regional HADRM3 model under two climate change scenarios (SRESA2a, B2a). In order to identify cyclones we used an objective algorithm from Murry and Simmonds which was widely tested under several different conditions. A slight increase in the occurrence of systems is identified above northern parts of central Europe for both scenarios. For more severe systems (core pressure wind events can be defined via different percentile values of the windspeed (e.g. above the 95 percentile). By this means the relationship between strong wind events and cyclones is also investigated. For several regions (e.g. Germany, France, Spain) a shift to more deep cyclones connected with an increasing number of strong wind events is found.

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

    Science.gov (United States)

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

    2014-01-01

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

  4. Dynamics of the coupled human-climate system resulting from closed-loop control of solar geoengineering

    Science.gov (United States)

    MacMartin, Douglas G.; Kravitz, Ben; Keith, David W.; Jarvis, Andrew

    2014-07-01

    If solar radiation management (SRM) were ever implemented, feedback of the observed climate state might be used to adjust the radiative forcing of SRM in order to compensate for uncertainty in either the forcing or the climate response. Feedback might also compensate for unexpected changes in the system, e.g. a nonlinear change in climate sensitivity. However, in addition to the intended response to greenhouse-gas induced changes, the use of feedback would also result in a geoengineering response to natural climate variability. We use a box-diffusion dynamic model of the climate system to understand how changing the properties of the feedback control affect the emergent dynamics of this coupled human-climate system, and evaluate these predictions using the HadCM3L general circulation model. In particular, some amplification of natural variability is unavoidable; any time delay (e.g., to average out natural variability, or due to decision-making) exacerbates this amplification, with oscillatory behavior possible if there is a desire for rapid correction (high feedback gain). This is a challenge for policy as a delayed response is needed for decision making. Conversely, the need for feedback to compensate for uncertainty, combined with a desire to avoid excessive amplification of natural variability, results in a limit on how rapidly SRM could respond to changes in the observed state of the climate system.

  5. Simulation of recent and future climates using CNRM and IPSL models; Simulation du climat recent et futur par les modeles du CNRM et de l'IPSL

    Energy Technology Data Exchange (ETDEWEB)

    Dufresne, J.L.; Bony, S.; Fairhead, L.; Grandpeix, J.Y.; Hourdin, F.; Idelkadi, A.; Musat, I. [Universite Pierre et Marie Curie, Lab. de Meteorologie Dynamique (LMD-IPSL), CNRS, 75 - Paris (France); Salas y Melia, D.; Tyteca, S.; Chauvin, F.; Deque, M.; Douville, H.; Gueremy, J.F.; Marquet, P.; Planton, S.; Royer, J.F.; Voldoire, A. [Meteo France Centre National de Recherches Meteorologiques, 31 - Toulouse (France); Denvil, S.; Cadule, P.; Foujols, M.A. [Universite Pierre et Marie Curie, Institut Pierre-Simon Laplace, CNRS, 75 - Paris (France); Arzel, O.; Fichefet, T. [Universite Catholique de Louvain (UCL), Louvain-la-Neuve (Belgium). Inst. d' Astronomie et de Geophysique G. Lemaitre; Braconnot, P.; Brockmann, P.; Caubel, A.; Friedlingstein, P.; Marti, O.; Swingedouw, D. [Laboratoire des Sciences du Climat et de l' Environnement, Domaine du CNRS, 91 - Gif Sur Yvette (France); Krinner, G. [Universite Joseph-Fourier, Grenoble I, Lab. de Glaciologie et Geophysique de l' Environnement (LGGE), CNRS, 38 - Saint Martin d' Heres (France); Levy, C.; Madec, G. [Universite Pierre et Marie Curie, Lab. d' Oceanographie et Climat (Locean-IPLS), CNRS, 75 - Paris (France)

    2006-11-15

    In support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) that should appear in early 2007, modelling groups world-wide have performed a huge coordinated exercise of climate change runs for the 20. and 21. centuries. In this paper we present the results of the two French climate models, CNRM and IPSL. In particular we emphasize the progress made since the previous IPCC report and we identify which results are comparable among models and which strongly differ. (authors)

  6. Forest cover change in the upper Midwestern United States results from both climate and land use change following European settlement: Historical survey and weather records provide robust support for modeling applications

    Science.gov (United States)

    Goring, S. J.; Williams, J. W.; McLachlan, J. S.; Dawson, A.; Dietze, M.; Paciorek, C. J.; Mladenoff, D. J.; Record, S.; Cogbill, C. V.; Hooten, M.; Ruid, M.; Jackson, S. T.

    2013-12-01

    Since European settlement, both climate and human land use have acted on forests in the upper Midwestern United States resulting in changes in forest structure and composition. The extent of these changes has been examined locally and at the state level by examining forest records from the Public Lands Survey System (PLSS), but here we bring together records of changing forest composition with weather records from the mid to late 19th century from the 19th Century Forts and Observer's Database. We are able to assign attribution for taxon range and composition shifts in the region to either land use, climate or both. We see that much of the range contraction in the region seen when comparing Forest Inventory and Analysis data with Public Land Survey System data occurs along the prairie margin, with northern forests showing greater stability in both range and composition suggesting a dominant role for land use in structuring regional vegetation. Modern forests are often less diverse than PLSS forests and the mean minimum dissimilarity between modern and PLSS-era forests is significantly higher than the minimum dissimilarity within either the PLSS-era forests or the modern (FIA) forests, indicating the possiblity that our modern forests have already become 'no-analogue' ecosystems.

  7. Model Interpretation of Climate Signals: Application to the Asian Monsoon Climate

    Science.gov (United States)

    Lau, William K. M.

    2002-01-01

    This is an invited review paper intended to be published as a Chapter in a book entitled "The Global Climate System: Patterns, Processes and Teleconnections" Cambridge University Press. The author begins with an introduction followed by a primer of climate models, including a description of various modeling strategies and methodologies used for climate diagnostics and predictability studies. Results from the CLIVAR Monsoon Model Intercomparison Project (MMIP) were used to illustrate the application of the strategies to modeling the Asian monsoon. It is shown that state-of-the art atmospheric GCMs have reasonable capability in simulating the seasonal mean large scale monsoon circulation, and response to El Nino. However, most models fail to capture the climatological as well as interannual anomalies of regional scale features of the Asian monsoon. These include in general over-estimating the intensity and/or misplacing the locations of the monsoon convection over the Bay of Bengal, and the zones of heavy rainfall near steep topography of the Indian subcontinent, Indonesia, and Indo-China and the Philippines. The intensity of convection in the equatorial Indian Ocean is generally weaker in models compared to observations. Most important, an endemic problem in all models is the weakness and the lack of definition of the Mei-yu rainbelt of the East Asia, in particular the part of the Mei-yu rainbelt over the East China Sea and southern Japan are under-represented. All models seem to possess certain amount of intraseasonal variability, but the monsoon transitions, such as the onset and breaks are less defined compared with the observed. Evidences are provided that a better simulation of the annual cycle and intraseasonal variability is a pre-requisite for better simulation and better prediction of interannual anomalies.

  8. Climate modelling: IPCC gazes into the future

    Science.gov (United States)

    Raper, Sarah

    2012-04-01

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

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

    Science.gov (United States)

    Stagge, James; Tallaksen, Lena; Rizzi, Jonathan

    2015-04-01

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

  10. Hybrid Surface Mesh Adaptation for Climate Modeling

    Institute of Scientific and Technical Information of China (English)

    Ahmed Khamayseh; Valmor de Almeida; Glen Hansen

    2008-01-01

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

  11. Land-atmosphere interactions and climate change: Recent results and new perspectives (Invited)

    Science.gov (United States)

    Seneviratne, S. I.; Davin, E. L.; Greve, P.; Gudmundsson, L.; Guillod, B.; Hirschi, M.; Mittelbach, H.; Mueller, B.; Mystakidis, S.; Orlowsky, B.; Orth, R.; Wilhelm, M.

    2013-12-01

    Land-atmosphere interactions play a key role in the climate system. In particular, soil moisture-climate interactions have been shown to affect the occurrence of extreme events in both present and future (e.g. Seneviratne et al. 2006, 2010). This presentation will provide an overview on recent results highlighting the impact of soil moisture-temperature feedbacks on hot extremes (e.g. Hirschi et al. 2010, Mueller and Seneviratne 2012, Seneviratne et al. 2013). Furthermore, it will also address new findings in the area of soil moisture-precipitation and land albedo-climate feedbacks (Guillod et al. 2013, Davin et al. 2013). The representation of these feedbacks in current climate models will be discussed, based on analyses of CMIP5 simulations. We will especially highlight systematic biases found in some key relationships underlying these feedbacks (e.g. Mueller and Seneviratne 2013). Finally, we will address the question of terrestrial climate engineering through targeted modifications of the land surface. References: Davin, E.L., S.I. Seneviratne, P. Ciais, A. Olioso, and T. Wang, 2013: Preferential cooling of hot extremes from cropland albedo management. Submitted. Guillod, B., et al., 2013: Land surface controls on afternoon precipitation diagnosed from observational data: Uncertainties, confounding factors and the possible role of interception storage. Manuscript in preparation. Hirschi, M., S.I. Seneviratne, V. Alexandrov, F. Boberg, C. Boroneant, O.B. Christensen, H. Formayer, B. Orlowsky, and P. Stepanek, 2011: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nature Geoscience, 4, 17-21, doi:10.1038/ngeo1032. Mueller, B., and S.I. Seneviratne, 2012: Hot days induced by precipitation deficits at the global scale. Proceedings of the National Academy of Sciences, 109 (31), 12398-12403, doi: 10.1073/pnas.1204330109. Mueller, B., and S.I. Seneviratne 2013: Systematic land climate and evapotranspiration biases in CMIP5

  12. 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

  13. Spatial scale dependency of the modelled climatic response to deforestation

    OpenAIRE

    Longobardi, P.; Montenegro, A.; H. Beltrami; M. Eby

    2012-01-01

    Deforestation is associated with increased atmospheric CO2 and alterations to the surface energy and mass balances that can lead to local and global climate changes. Previous modelling studies show that the global surface air temperature (SAT) response to deforestation depends on latitude, with most simulations showing that high latitude deforestation results in cooling, low latitude deforestation causes warming and that the mid latitude response is mixed. T...

  14. Post-2020 climate agreements in the major economies assessed in the light of global models

    OpenAIRE

    Tavoni, Massimo; Kriegler, Elmar; Riahi, Keywan (Prof. Dr. ); van Vuuren, Detlef P.; Aboumahboub, Tino; Bowen, Alex; Calvin, Katherine; Campiglio, Emanuele; Kober, Tom; Jewell, Jessica; Luderer, Gunnar; Marangoni, Giacomo; McCollum, David; van Sluisveld, Mariësse; Zimmer, Anne

    2014-01-01

    Integrated assessment models can help in quantifying the implications of international climate agreements and regional climate action. This paper reviews scenario results from model intercomparison projects to explore different possible outcomes of post-2020 climate negotiations, recently announced pledges and their relation to the 2 °C target. We provide key information for all the major economies, such as the year of emission peaking, regional carbon budgets and emissions allowances. We hig...

  15. Modelling middle pliocene warm climates of the USA

    Science.gov (United States)

    Haywood, A.M.; Valdes, P.J.; Sellwood, B.W.; Kaplan, J.O.; Dowsett, H.J.

    2001-01-01

    The middle Pliocene warm period represents a unique time slice in which to model and understand climatic processes operating under a warm climatic regime. Palaeoclimatic model simulations, focussed on the United States of America (USA), for the middle Pliocene (ca 3 Ma) were generated using the USGS PRISM2 2?? ?? 2?? data set of boundary conditions and the UK Meteorological Office's HadAMS General Circulation Model (GCM). Model results suggest that conditions in the USA during the middle Pliocene can be characterised as annually warmer (by 2?? to 4??C), less seasonal, wetter (by a maximum of 4 to 8 mm/day) and with an absence of freezing winters over the central and southern Great Plains. A sensitivity experiment suggests that the main forcing mechanisms for surface temperature changes in near coastal areas are the imposed Pliocene sea surface temperatures (SST's). In interior regions, reduced Northern Hemisphere terrestrial ice, combined with less snow cover and a reduction in the elevation of the western cordillera of North America, generate atmospheric circulation changes and positive albedo feedbacks that raise surface temperatures. A complex set of climatic feedback mechanisms cause an enhancement of the hydrological cycle magnifying the moisture bearing westerly wind belt during the winter season (Dec., Jan., Feb.). Predictions produced by the model are in broad agreement with available geological evidence. However, the GCM appears to underestimate precipitation levels in the interior and central regions of the southern USA. Copyright: Palaeontological Association, 22 June 2001.

  16. Climate stability for a Sellers-type model. [atmospheric diffusive energy balance model

    Science.gov (United States)

    Ghil, M.

    1976-01-01

    We study a diffusive energy-balance climate model governed by a nonlinear parabolic partial differential equation. Three positive steady-state solutions of this equation are found; they correspond to three possible climates of our planet: an interglacial (nearly identical to the present climate), a glacial, and a completely ice-covered earth. We consider also models similar to the main one studied, and determine the number of their steady states. All the models have albedo continuously varying with latitude and temperature, and entirely diffusive horizontal heat transfer. The diffusion is taken to be nonlinear as well as linear. We investigate the stability under small perturbations of the main model's climates. A stability criterion is derived, and its application shows that the 'present climate' and the 'deep freeze' are stable, whereas the model's glacial is unstable. A variational principle is introduced to confirm the results of this stability analysis. For a sufficient decrease in solar radiation (about 2%) the glacial and interglacial solutions disappear, leaving the ice-covered earth as the only possible climate.

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

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

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

  18. Diagnostic indicators for integrated assessment models of climate policy

    Energy Technology Data Exchange (ETDEWEB)

    Kriegler, Elmar; Petermann, Nils; Krey, Volker; Schwanitz, Jana; Luderer, Gunnar; Ashina, Shuichi; Bosetti, Valentina; Eom, Jiyong; Kitous, Alban; Mejean, Aurelie; Paroussos, Leonidas; Sano, Fuminori; Turton, Hal; Wilson, Charlie; Van Vuuren, Detlef

    2015-01-01

    Integrated assessments of how climate policy interacts with energy-economic systems can be performed by a variety of models with different functional structures. This article proposes a diagnostic scheme that can be applied to a wide range of integrated assessment models to classify differences among models based on their carbon price responses. Model diagnostics can uncover patterns and provide insights into why, under a given scenario, certain types of models behave in observed ways. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study with 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to more easily explain variations among policy-relevant model results.

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  20. Potato model uncertainty across common datasets and varying climate

    Science.gov (United States)

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

  1. Testing alternative models of climate-mediated extirpations

    Science.gov (United States)

    Beever, E.A.; Chris, R.A.Y.; Mote, P.W.; Wilkening, J.L.

    2010-01-01

    Biotic responses to climate change will vary among taxa and across latitudes, elevational gradients, and degrees of insularity. However, due to factors such as phenotypic plasticity, ecotypic variation, and evolved tolerance to thermal stress, it remains poorly understood whether losses should be greatest in populations experiencing the greatest climatic change or living in places where the prevailing climate is closest to the edge of the species' bioclimatic envelope (e.g., at the hottest, driest sites). Research on American pikas (Ochotona princeps) in montane areas of the Great Basin during 1994-1999 suggested that 20th-century population extirpations were predicted by a combination of biogeographic, anthropogenic, and especially climatic factors. Surveys during 2005-2007 documented additional extirpations and within-site shifts of pika distributions at remaining sites. To evaluate the evidence in support of alternative hypotheses involving effects of thermal stress on pikas, we placed temperature sensors at 156 locations within pika habitats in the vicinity of 25 sites with historical records of pikas in the Basin. We related these time series of sensor data to data on ambient temperature from weather stations within the Historical Climate Network. We then used these highly correlated relationships, combined with long-term data from the same weather stations, to hindcast temperatures within pika habitats from 1945 through 2006. To explain patterns of loss, we posited three alternative classes of direct thermal stress: (1) acute cold stress (number of days below a threshold temperature); (2) acute heat stress (number of days above a threshold, temperature); and. (3) chronic heat stress (average summer temperature). Climate change was defined as change in our thermal metrics between two 31-y.r periods: 1945-1975 and 1976-2006. We found that patterns of persistence were well predicted by metrics of climate. Our best models suggest some effects of climate change

  2. Physical-Socio-Economic Modeling of Climate Change

    Science.gov (United States)

    Chamberlain, R. G.; Vatan, F.

    2008-12-01

    Because of the global nature of climate change, any assessment of the effects of plans, policies, and response to climate change demands a model that encompasses the entire Earth System, including socio- economic factors. Physics-based climate models of the factors that drive global temperatures, rainfall patterns, and sea level are necessary but not sufficient to guide decision making. Actions taken by farmers, industrialists, environmentalists, politicians, and other policy makers may result in large changes to economic factors, international relations, food production, disease vectors, and beyond. These consequences will not be felt uniformly around the globe or even across a given region. Policy models must comprehend all of these considerations. Combining physics-based models of the Earth's climate and biosphere with societal models of population dynamics, economics, and politics is a grand challenge with high stakes. We propose to leverage our recent advances in modeling and simulation of military stability and reconstruction operations to models that address all these areas of concern. Following over twenty years' experience of successful combat simulation, JPL has started developing Minerva, which will add demographic, economic, political, and media/information models to capabilities that already exist. With these new models, for which we have design concepts, it will be possible to address a very wide range of potential national and international problems that were previously inaccessible. Our climate change model builds on Minerva and expands the geographical horizon from playboxes containing regions and neighborhoods to the entire globe. This system consists of a collection of interacting simulation models that specialize in different aspects of the global situation. They will each contribute to and draw from a pool of shared data. The basic models are: the physical model; the demographic model; the political model; the economic model; and the media

  3. A climate model intercomparison for the Antarctic region: present and past

    NARCIS (Netherlands)

    Maris, M.N.A.; de Boer, B.; Oerlemans, J.

    2012-01-01

    Eighteen General Circulation Models (GCMs) are compared to reference data for the present, the Mid-Holocene (MH) and the Last Glacial Maximum (LGM) for the Antarctic region. The climatology produced by a regional climate model is taken as a reference climate for the present. GCM results for the past

  4. High-resolution climate modelling of Antarctica and the Antarctic Peninsula

    NARCIS (Netherlands)

    van Wessem, J.M.

    2016-01-01

    In this thesis we have used a high-resolution regional atmospheric climate model (RACMO2.3) to simulate the present-day climate (1979-2014) of Antarctica and the Antarctic Peninsula. We have evaluated the model results with several observations, such as in situ surface energy balance (SEB) observati

  5. 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

    This paper presents an overview of changes in the extreme events that are most likely to affect Europe in forthcoming decades. A variety of diagnostic methods are used to determine how heat waves, heavy precipitation, drought, wind storms, and storm surges change between present (1961......-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...... century, countries in central Europe will experience the same number of hot days as are currently experienced in southern Europe. The intensity of extreme temperatures increases more rapidly than the intensity of more moderate temperatures over the continental interior due to increases in temperature...

  6. How Does a Regional Climate Model Modify the Projected Climate Change Signal of the Driving GCM: A Study over Different CORDEX Regions Using REMO

    Directory of Open Access Journals (Sweden)

    Claas Teichmann

    2013-06-01

    Full Text Available Global and regional climate model simulations are frequently used for regional climate change assessments and in climate impact modeling studies. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations from different global and regional climate model combinations. To interpret the spread of simulated results, it is useful to understand how the climate change signal is modified in the GCM-RCM modelmodelgeneral circulation model-regional climate model (GCM-RCM chain. This kind of information can also be useful for impact modelers; for the process of experiment design and when interpreting model results. In this study, we investigate how the simulated historical and future climate of the Max-Planck-Institute earth system model (MPI-ESM is modified by dynamic downscaling with the regional model REMO in different world regions. The historical climate simulations for 1950–2005 are driven by observed anthropogenic forcing. The climate projections are driven by projected anthropogenic forcing according to different Representative Concentration Pathways (RCPs. The global simulations are downscaled with REMO over the Coordinated Regional Climate Downscaling Experiment (CORDEX domains Africa, Europe, South America and West Asia from 2006–2100. This unique set of simulations allows for climate type specific analysis across multiple world regions and for multi-scenarios. We used a classification of climate types by Köppen-Trewartha to define evaluation regions with certain climate conditions. A systematic comparison of near-surface temperature and precipitation simulated by the regional and the global model is done. In general, the historical time period is well represented by the GCM and the RCM. Some different biases occur in the RCM compared to the GCM as in the Amazon Basin, northern Africa and the West Asian domain. Both models project similar warming

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

    Science.gov (United States)

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

    2016-08-01

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

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

    Directory of Open Access Journals (Sweden)

    K. Steffens

    2013-08-01

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

  9. 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.

  10. Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

    Directory of Open Access Journals (Sweden)

    M. Eby

    2013-05-01

    Full Text Available Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there

  11. Data assimilation in slow-fast systems using homogenized climate models

    CERN Document Server

    Mitchell, Lewis

    2011-01-01

    A deterministic multiscale toy model is studied in which a chaotic fast subsystem triggers rare transitions between slow regimes, akin to weather or climate regimes. Using homogenization techniques, a reduced stochastic parametrization model is derived for the slow dynamics. The reliability of this reduced climate model in reproducing the statistics of the slow dynamics of the full deterministic model for finite values of the time scale separation is numerically established. The statistics however is sensitive to uncertainties in the parameters of the stochastic model. It is investigated whether the stochastic climate model can be beneficial as a forecast model in an ensemble data assimilation setting, in particular in the realistic setting when observations are only available for the slow variables. The main result is that reduced stochastic models can indeed improve the analysis skill, when used as forecast models instead of the perfect full deterministic model. The stochastic climate model is far superior ...

  12. Updated cloud physics improve the modelled near surface climate of Antarctica of a regional atmospheric climate model

    Directory of Open Access Journals (Sweden)

    J. M. van Wessem

    2013-07-01

    Full Text Available The physics package of the polar version of the regional atmospheric climate model RACMO2 has been updated from RACMO2.1 to RACMO2.3. The update constitutes, amongst others, the inclusion of a parameterization for cloud ice super-saturation, an improved turbulent and radiative flux scheme and a changed cloud scheme. In this study the effects of these changes on the modelled near-surface climate of Antarctica are presented. Significant biases remain, but overall RACMO2.3 better represents the near-surface climate in terms of the modelled surface energy balance, based on a comparison with > 750 months of data from nine automatic weather stations located in East Antarctica. Especially the representation of the sensible heat flux and net longwave radiative flux has improved with a decrease in biases of up to 40 %. These improvements are mainly caused by the inclusion of ice super-saturation, which has led to more moisture being transported onto the continent, resulting in more and optically thicker clouds and more downward longwave radiation. As a result, modelled surface temperatures have increased and the bias, when compared to 10 m snow temperatures from 64 ice core observations, has decreased from −2.3 K to −1.3 K. The weaker surface temperature inversion consequently improves the representation of the sensible heat flux, whereas wind speed remains unchanged.

  13. Accelerate Climate Models with the IBM Cell Processor

    Science.gov (United States)

    Zhou, S.; Duffy, D.; Clune, T.; Williams, S.; Suarez, M.; Halem, M.

    2008-12-01

    Ever increasing model resolutions and physical processes in climate models demand continual computing power increases. The IBM Cell processor's order-of- magnitude peak performance increase over conventional processors makes it very attractive for fulfilling this requirement. However, the Cell's characteristics: 256KB local memory per SPE and the new low-level communication mechanism, make it very challenging to port an application. We selected the solar radiation component of the NASA GEOS-5 climate model, which: (1) is representative of column physics components (~50% total computation time), (2) has a high computational load relative to data traffic to/from main memory, and (3) performs independent calculations across multiple columns. We converted the baseline code (single-precision, Fortran code) to C and ported it to an IBM BladeCenter QS20, manually SIMDizing 4 independent columns, and found that a Cell with 8 SPEs can process more than 3000 columns per second. Compared with the baseline results, the Cell is ~6.76x, ~8.91x, ~9.85x faster than a core on Intel's Xeon Woodcrest, Dempsey, and Itanium2 respectively. Our analysis shows that the Cell could also speed up the dynamics component (~25% total computation time). We believe this dramatic performance improvement makes the Cell processor very competitive, at least as an accelerator. We will report our experience in porting both the C and Fortran codes and will discuss our work in porting other climate model components.

  14. Catastrophe model of the accident process, safety climate, and anxiety.

    Science.gov (United States)

    Guastello, Stephen J; Lynn, Mark

    2014-04-01

    This study aimed (a) to address the evidence for situational specificity in the connection between safety climate to occupational accidents, (b) to resolve similar issues between anxiety and accidents, (c) to expand and develop the concept of safety climate to include a wider range of organizational constructs, (d) to assess a cusp catastrophe model for occupational accidents where safety climate and anxiety are treated as bifurcation variables, and environ-mental hazards are asymmetry variables. Bifurcation, or trigger variables can have a positive or negative effect on outcomes, depending on the levels of asymmetry, or background variables. The participants were 1262 production employees of two steel manufacturing facilities who completed a survey that measured safety management, anxiety, subjective danger, dysregulation, stressors and hazards. Nonlinear regression analyses showed, for this industry, that the accident process was explained by a cusp catastrophe model in which safety management and anxiety were bifurcation variables, and hazards, age and experience were asymmetry variables. The accuracy of the cusp model (R2 = .72) exceeded that of the next best log-linear model (R2 = .08) composed from the same survey variables. The results are thought to generalize to any industry where serious injuries could occur, although situationally specific effects should be anticipated as well.

  15. 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

  16. Load-balancing algorithms for the parallel community climate model

    Energy Technology Data Exchange (ETDEWEB)

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

    1995-01-01

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

  17. Landscape reorganization under changing climatic forcing: Results from an experimental landscape

    Science.gov (United States)

    Singh, Arvind; Reinhardt, Liam; Foufoula-Georgiou, Efi

    2015-06-01

    Understanding how landscapes respond to climate dynamics in terms of macroscale (average topographic features) and microscale (landform reorganization) is of interest both for deciphering past climates from today's landscapes and for predicting future landscapes in view of recent climatic trends. Although several studies have addressed macro-scale response, only a few have focused on quantifying smaller-scale basin reorganization. To that goal, a series of controlled laboratory experiments were conducted where a self-organized complete drainage network emerged under constant precipitation and uplift dynamics. Once steady state was achieved, the landscape was subjected to a fivefold increase in precipitation (transient state). Throughout the evolution, high-resolution spatiotemporal topographic data in the form of digital elevation models were collected. The steady state landscape was shown to possess three distinct geomorphic regimes (unchannelized hillslopes, debris-dominated channels, and fluvially dominated channels). During transient state, landscape reorganization was observed to be driven by hillslopes via accelerated erosion, ridge lowering, channel widening, and reduction of basin relief as opposed to channel base-level reduction. Quantitative metrics on which these conclusions were based included slope-area curve, correlation analysis of spatial and temporal elevation increments, and wavelet spectral analysis of the evolving landscapes. Our results highlight that landscape reorganization in response to increased precipitation seems to follow "an arrow of scale": major elevation change initiates at the hillslope scale driving erosional regime change at intermediate scales and further cascading to geomorphic changes at the channel scale as time evolves.

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

    Science.gov (United States)

    Smith, James A.

    2009-01-01

    How will migrating birds respond to changes in the environment under climate change? What are the implications for migratory success under the various accelerated climate change scenarios as forecast by the Intergovernmental Panel on Climate Change? How will reductions or increased variability in the number or quality of wetland stop-over sites affect migratory bird species? The answers to these questions have important ramifications for conservation biology and wildlife management. Here, we describe the use of continental scale simulation modeling to explore how spatio-temporal changes along migratory flyways affect en-route migration success. We use an individually based, biophysical, mechanistic, bird migration model to simulate the movement of shorebirds in North America as a tool to study how such factors as drought and wetland loss may impact migratory success and modify migration patterns. Our model is driven by remote sensing and climate data and incorporates important landscape variables. The energy budget components of the model include resting, foraging, and flight, but presently predation is ignored. Results/Conclusions We illustrate our model by studying the spring migration of sandpipers through the Great Plains to their Arctic breeding grounds. Why many species of shorebirds have shown significant declines remains a puzzle. Shorebirds are sensitive to stop-over quality and spacing because of their need for frequent refueling stops and their opportunistic feeding patterns. We predict bird "hydrographs that is, stop-over frequency with latitude, that are in agreement with the literature. Mean stop-over durations predicted from our model for nominal cases also are consistent with the limited, but available data. For the shorebird species simulated, our model predicts that shorebirds exhibit significant plasticity and are able to shift their migration patterns in response to changing drought conditions. However, the question remains as to whether this

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

    Institute of Scientific and Technical Information of China (English)

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

    2014-01-01

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

  20. Evaluation of climate extremes in the CMIP5 model simulations

    Science.gov (United States)

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

    2011-12-01

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

  1. Feedbacks, climate sensitivity, and the limits of linear models

    Science.gov (United States)

    Rugenstein, M.; Knutti, R.

    2015-12-01

    The term "feedback" is used ubiquitously in climate research, but implies varied meanings in different contexts. From a specific process that locally affects a quantity, to a formal framework that attempts to determine a global response to a forcing, researchers use this term to separate, simplify, and quantify parts of the complex Earth system. We combine large (>120 member) ensemble GCM and EMIC step forcing simulations over a broad range of forcing levels with a historical and educational perspective to organize existing ideas around feedbacks and linear forcing-feedback models. With a new method overcoming internal variability and initial condition problems we quantify the non-constancy of the climate feedback parameter. Our results suggest a strong state- and forcing-dependency of feedbacks, which is not considered appropriately in many studies. A non-constant feedback factor likely explains some of the differences in estimates of equilibrium climate sensitivity from different methods and types of data. We discuss implications for the definition of the forcing term and its various adjustments. Clarifying the value and applicability of the linear forcing feedback framework and a better quantification of feedbacks on various timescales and spatial scales remains a high priority in order to better understand past and predict future changes in the climate system.

  2. Influence of climate model variability on projected Arctic shipping futures

    Science.gov (United States)

    Stephenson, Scott R.; Smith, Laurence C.

    2015-11-01

    Though climate models exhibit broadly similar agreement on key long-term trends, they have significant temporal and spatial differences due to intermodel variability. Such variability should be considered when using climate models to project the future marine Arctic. Here we present multiple scenarios of 21st-century Arctic marine access as driven by sea ice output from 10 CMIP5 models known to represent well the historical trend and climatology of Arctic sea ice. Optimal vessel transits from North America and Europe to the Bering Strait are estimated for two periods representing early-century (2011-2035) and mid-century (2036-2060) conditions under two forcing scenarios (RCP 4.5/8.5), assuming Polar Class 6 and open-water vessels with medium and no ice-breaking capability, respectively. Results illustrate that projected shipping viability of the Northern Sea Route (NSR) and Northwest Passage (NWP) depends critically on model choice. The eastern Arctic will remain the most reliably accessible marine space for trans-Arctic shipping by mid-century, while outcomes for the NWP are particularly model-dependent. Omitting three models (GFDL-CM3, MIROC-ESM-CHEM, and MPI-ESM-MR), our results would indicate minimal NWP potential even for routes from North America. Furthermore, the relative importance of the NSR will diminish over time as the number of viable central Arctic routes increases gradually toward mid-century. Compared to vessel class, climate forcing plays a minor role. These findings reveal the importance of model choice in devising projections for strategic planning by governments, environmental agencies, and the global maritime industry.

  3. Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents

    OpenAIRE

    Vetter, T.; Huang, S.; Aich, V.; Yang, T; X. Wang; Krysanova, V.; Hattermann, F.

    2015-01-01

    Climate change impacts on hydrological processes should be simulated for river basins using validated models and multiple climate scenarios in order to provide reliable results for stakeholders. In the last 10–15 years, climate impact assessment has been performed for many river basins worldwide using different climate scenarios and models. However, their results are hardly comparable, and do not allow one to create a full picture of impacts and uncertainties. Therefore, a s...

  4. 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.

  5. 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.

  6. 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...

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

    NARCIS (Netherlands)

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

    2016-01-01

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

  8. Post-impact climate conditions on early Mars: preliminary results from GCM simulations

    Science.gov (United States)

    Steakley, Kathryn; Murphy, Jim; Kahre, Melinda A.; Haberle, Robert

    2016-10-01

    Observations imply that liquid water was stable on Mars' surface during the late Noachian/early Hesperian era, with valley networks forming roughly 3.5-3.75 billion years ago, possibly from precipitation and runoff (Fassett & Head 2008, Icarus 195, 61; Hynek et al., 2010, JGR Planets, 115, E09008). Climate models, however, struggle to reproduce such warm conditions (Forget et al., 2013, Icarus 21, 81). Volcanism and impacts have been suggested as mechanisms of either inducing a warm and wet environment or causing local melting in a cold and wet environment. Comets and asteroids are capable of injecting into the atmosphere both kinetic energy from the impact and water from the object itself and from vaporized surface and subsurface ice. Segura et al. (2008, JGR Planets 113, E11007) find using a 1-D atmospheric model that significant rainfall and periods of above-freezing temperatures lasting months to years can follow impacts of objects between 30 and 100 km in diameter. We revisit this work utilizing a 3-D global climate model (GCM) to consider the effects of dynamics, topography, global surface ice variations, etc. We present preliminary results from the NASA ARC Mars GCM investigating global temperature and precipitation behavior in a post-impact, early Mars environment.

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

    Science.gov (United States)

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

    2010-09-22

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

  10. 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

  11. Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

    Directory of Open Access Journals (Sweden)

    B. Schneider

    2008-04-01

    Full Text Available Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP and export production (EP of particulate organic carbon (POC. Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation. Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006 with stronger stratification (higher sea surface temperature; SST being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL also reproduces the inverse relationship between stratification (SST and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

  12. Spatial scale dependency of the modelled climatic response to deforestation

    Directory of Open Access Journals (Sweden)

    P. Longobardi

    2012-10-01

    Full Text Available Deforestation is associated with increased atmospheric CO2 and alterations to the surface energy and mass balances that can lead to local and global climate changes. Previous modelling studies show that the global surface air temperature (SAT response to deforestation depends on latitude, with most simulations showing that high latitude deforestation results in cooling, low latitude deforestation causes warming and that the mid latitude response is mixed. These earlier conclusions are based on simulated large scale land cover change, with complete removal of trees from whole latitude bands. Using a global climate model we determine effects of removing fractions of 5% to 100% of forested areas in the high, mid and low latitudes. All high latitude deforestation scenarios reduce mean global SAT, the opposite occurring for low latitude deforestation, although a decrease in SAT is registered over low latitude deforested areas. Mid latitude SAT response is mixed. For all simulations deforested areas tend to become drier and have lower surface air temperature, although soil temperatures increase over deforested mid and low latitude grid cells. For high latitude deforestation fractions of 45% and above, larger net primary productivity, in conjunction with colder and drier conditions after deforestation, cause an increase in soil carbon large enough to generate a previously not reported net drawdown of CO2 from the atmosphere. Our results support previous indications of the importance of changes in cloud cover in the modelled temperature response to deforestation at low latitudes. They also show the complex interaction between soil carbon dynamics and climate and the role this plays on the climatic response to land cover change.

  13. Thermohaline feedbacks in ocean-climate models of varying complexity

    Science.gov (United States)

    den Toom, M.

    2013-03-01

    The Atlantic Meridional Overturning Circulation (AMOC) is considered an important component of the climate system, because of its significant contribution to the heat budget of the Northern Hemisphere. Theoretical models indicate that the AMOC has non-linear dynamics, which result in a strong sensitivity to high latitude freshwater forcing. These models suggest that, as a result of the presence of multiple equilibria, the AMOC may drive large, abrupt shifts of the climate when a certain threshold is exceeded. There is no direct observational evidence that such AMOC related climate variations occur in reality, but the available data are too short and sparse to be conclusive in this case. Therefore, numerical models provide the main source of information regarding the nonlinear behavior of the AMOC. Because numerical models are necessarily incomplete, not in the least because of a lack of computational resources, their results must always be tested for robustness. This thesis presents four studies that examine how the representation of a certain unresolved process affects the behavior of the simulated AMOC The study in chapter 2 deals with the representation of horizontal mixing by mesoscale eddies. It is shown that a simple horizontal tracer mixing scheme is only a reasonable alternative to the more realistic isoneutral / Gent-McWilliams parameterization, provided that no wind forcing is imposed. In chapter 3, it is demonstrated that the use of a stability-dependent tracer diffusivity, which is commonly used to parameterize convection, leads to the occurrence of artificial multiple equilibria. In chapter 4, the representation of ocean-atmosphere interaction is considered. It is found that the sensitivity to anomalous freshwater forcing is only slightly modified if an interactive (sea surface temperature-dependent) atmosphere model is used, instead of a static atmosphere model. In chapter 5, the simulated sensitivity of the AMOC is compared between a model that

  14. Using Different Spatial Scales of Climate Data for Regional Climate Impact Assessment: Effect on Crop Modeling Analysis

    Science.gov (United States)

    Mereu, V.; Gallo, A.; Trabucco, A.; Montesarchio, M.; Mercogliano, P.; Spano, D.

    2015-12-01

    The high vulnerability of the agricultural sector to climate conditions causes serious concern regarding climate change impacts on crop development and production, particularly in vulnerable areas like the Mediterranean Basin. Crop simulation models are the most common tools applied for the assessment of such impacts on crop development and yields, both at local and regional scales. However, the use of these models in regional impact studies requires spatial input data for weather, soil, management, etc, whose resolution could affect simulation results. Indeed, the uncertainty in projecting climate change impacts on crop phenology and yield at the regional scale is affected not only by the uncertainty related to climate models and scenarios, but also by the downscaling methods and the resolution of climate data. The aim of this study was the evaluation of the effects of spatial resolutions of climate projections in estimating maturity date and grain yield for different varieties of durum wheat, common wheat and maize in Italy. The simulations were carried out using the CSM-CERES-Wheat and CSM-CERES-Maize crop models included in the DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, parameterized and evaluated in different experimental sites located in Italy. Dynamically downscaled climate data at different resolutions and different RCP scenarios were used as input in the crop models. A spatial platform, DSSAT-CSM based, developed in R programming language was applied to perform the simulation of maturity date and grain yield for durum wheat, common wheat and maize in each grid cell. Results, analyzed at the national and regional level, will be discussed.

  15. Modelling the Spatial Distribution of Culicoides imicola: Climatic versus Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Jasper Van Doninck

    2014-07-01

    Full Text Available Culicoides imicola is the main vector of the bluetongue virus in the Mediterranean Basin. Spatial distribution models for this species traditionally employ either climatic data or remotely sensed data, or a combination of both. Until now, however, no studies compared the accuracies of C. imicola distribution models based on climatic versus remote sensing data, even though remotely sensed datasets may offer advantages over climatic datasets with respect to spatial and temporal resolution. This study performs such an analysis for datasets over the peninsula of Calabria, Italy. Spatial distribution modelling based on climatic data using the random forests machine learning technique resulted in a percentage of correctly classified C. imicola trapping sites of nearly 88%, thereby outperforming the linear discriminant analysis and logistic regression modelling techniques. When replacing climatic data by remote sensing data, random forests modelling accuracies decreased only slightly. Assessment of the different variables’ importance showed that precipitation during late spring was the most important amongst 48 climatic variables. The dominant remotely sensed variables could be linked to climatic variables. Notwithstanding the slight decrease in predictive performance in this study, remotely sensed datasets could be preferred over climatic datasets for the modelling of C. imicola. Unlike climatic observations, remote sensing provides an equally high spatial resolution globally. Additionally, its high temporal resolution allows for investigating changes in species’ presence and changing environment.

  16. 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.

  17. 'Initial' Soil Moisture Effects on the Climate in China——A Regional Climate Model Study

    Institute of Scientific and Technical Information of China (English)

    SHI Xueli

    2009-01-01

    In this study, the effects of 'initial' soil moisture (SM) in arid and semi-arid Northwestern China on subsequent climate were investigated with a regional climate model. Besides the control simulations (denoted as CTL), a series of sensitivity experi-ments were conducted, including the DRY and WET experiments, in which the simulated 'initial' SM over the region 30-50°N, 75 -105°E was only 5% and 50%, and up to 150% and 200% of the simulated value in the CTL, respectively. The results show that SM change can modify the subsequent climate in not only the SM-change region proper but also the far downstream regions in Eastern and even Northeastern China. The SM-change effects are generally more prominent in the WET than in the DRY experiments. After the SM is initially increased, the SM in the SM-change region is always higher than that in the CTL, the latent (sensible) heat flux there increases (decreases), and the surface air temperature decreases. Spatially, the most prominent changes in the WET experiments are surface air temperature decrease, geopotential height decrease and corresponding abnormal changes of cyclonic wind vectors at the mid-upper troposphere levels. Generally opposite effects exist in the DRY experiments but with much weaker intensity. In addi-tion, the differences between the results obtained from the two sets of sensitivity experiments and those of the CTL are not always consistent with the variation of the initial SM. Being different from the variation of temperature, the rainfall modifications caused by initial SM change are not so distinct and in fact they show some common features in the WET and DRY experiments. This might imply that SM is only one of the factors that impact the subsequent climate, and its effect is involved in complex processes within the atmosphere, which needs further investigation.

  18. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models.

    Science.gov (United States)

    Ramírez-Albores, Jorge E; Bustamante, Ramiro O; Badano, Ernesto I

    2016-01-01

    Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of

  19. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models.

    Directory of Open Access Journals (Sweden)

    Jorge E Ramírez-Albores

    Full Text Available Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile nor the origin of individuals (naturally established or man-planted, the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle, a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model. The second model only included occurrence records of naturally established mature individuals (adult niche model, while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model. When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with

  20. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models

    Science.gov (United States)

    Ramírez-Albores, Jorge E.; Bustamante, Ramiro O.

    2016-01-01

    Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of

  1. The relationship between team climate and interprofessional collaboration: Preliminary results of a mixed methods study.

    Science.gov (United States)

    Agreli, Heloise F; Peduzzi, Marina; Bailey, Christopher

    2017-03-01

    Relational and organisational factors are key elements of interprofessional collaboration (IPC) and team climate. Few studies have explored the relationship between IPC and team climate. This article presents a study that aimed to explore IPC in primary healthcare teams and understand how the assessment of team climate may provide insights into IPC. A mixed methods study design was adopted. In Stage 1 of the study, team climate was assessed using the Team Climate Inventory with 159 professionals in 18 interprofessional teams based in São Paulo, Brazil. In Stage 2, data were collected through in-depth interviews with a sample of team members who participated in the first stage of the study. Results from Stage 1 provided an overview of factors relevant to teamwork, which in turn informed our exploration of the relationship between team climate and IPC. Preliminary findings from Stage 2 indicated that teams with a more positive team climate (in particular, greater participative safety) also reported more effective communication and mutual support. In conclusion, team climate provided insights into IPC, especially regarding aspects of communication and interaction in teams. Further research will provide a better understanding of differences and areas of overlap between team climate and IPC. It will potentially contribute for an innovative theoretical approach to explore interprofessional work in primary care settings.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1996-12-31

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

  3. Last Interglacial climate and sea-level evolution from a coupled ice sheet-climate model

    Science.gov (United States)

    Goelzer, Heiko; Huybrechts, Philippe; Loutre, Marie-France; Fichefet, Thierry

    2016-12-01

    As the most recent warm period in Earth's history with a sea-level stand higher than present, the Last Interglacial (LIG, ˜ 130 to 115 kyr BP) is often considered a prime example to study the impact of a warmer climate on the two polar ice sheets remaining today. Here we simulate the Last Interglacial climate, ice sheet, and sea-level evolution with the Earth system model of intermediate complexity LOVECLIM v.1.3, which includes dynamic and fully coupled components representing the atmosphere, the ocean and sea ice, the terrestrial biosphere, and the Greenland and Antarctic ice sheets. In this setup, sea-level evolution and climate-ice sheet interactions are modelled in a consistent framework.Surface mass balance change governed by changes in surface meltwater runoff is the dominant forcing for the Greenland ice sheet, which shows a peak sea-level contribution of 1.4 m at 123 kyr BP in the reference experiment. Our results indicate that ice sheet-climate feedbacks play an important role to amplify climate and sea-level changes in the Northern Hemisphere. The sensitivity of the Greenland ice sheet to surface temperature changes considerably increases when interactive albedo changes are considered. Southern Hemisphere polar and sub-polar ocean warming is limited throughout the Last Interglacial, and surface and sub-shelf melting exerts only a minor control on the Antarctic sea-level contribution with a peak of 4.4 m at 125 kyr BP. Retreat of the Antarctic ice sheet at the onset of the LIG is mainly forced by rising sea level and to a lesser extent by reduced ice shelf viscosity as the surface temperature increases. Global sea level shows a peak of 5.3 m at 124.5 kyr BP, which includes a minor contribution of 0.35 m from oceanic thermal expansion. Neither the individual contributions nor the total modelled sea-level stand show fast multi-millennial timescale variations as indicated by some reconstructions.

  4. The Development in modeling Tibetan Plateau Land/Climate Interaction

    Science.gov (United States)

    Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio

    2015-04-01

    Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP

  5. 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.

  6. Uncertainties in climate responses to past land cover change: First results from the LUCID intercomparison study

    NARCIS (Netherlands)

    Pitman, A.J.; Noblet-Ducoudré, de N.; Cruz, F.T.; Davin, E.L.; Bonan, G.B.; Brovkin, V.; Claussen, M.; Delire, C.; Ganzeveld, L.N.; Gayler, V.; Hurk, van den B.J.J.M.; Lawrence, P.J.; Molen, van der M.K.; Müller, C.; Reick, C.H.; Senevirantne, S.I.; Strengers, B.J.; Voldoire, A.

    2009-01-01

    Seven climate models were used to explore the biogeophysical impacts of human-induced land cover change (LCC) at regional and global scales. The imposed LCC led to statistically significant decreases in the northern hemisphere summer latent heat flux in three models, and increases in three models. F

  7. Parametrization of contrails in a comprehensive climate model

    Energy Technology Data Exchange (ETDEWEB)

    Ponater, M.; Brinkop, S.; Sausen, R.; Schumann, U. [Deutsche Forschungs- und Versuchsanstalt fuer Luft- und Raumfahrt e.V., Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere

    1997-12-31

    A contrail parametrization scheme for a general circulation model (GCM) is presented. Guidelines for its development were that it should be based on the thermodynamic theory of contrail formation and that it should be consistent with the cloud parametrization scheme of the GCM. Results of a six-year test integration indicate reasonable results concerning the spatial and temporal development of both contrail coverage and contrail optical properties. Hence, the scheme forms a promising basis for the quantitative estimation of the contrail climatic impact. (author) 9 refs.

  8. A climate distribution model of malaria transmission in Sudan.

    Science.gov (United States)

    Musa, Mohammed I; Shohaimi, Shamarina; Hashim, Nor R; Krishnarajah, Isthrinayagy

    2012-11-01

    Malaria remains a major health problem in Sudan. With a population exceeding 39 million, there are around 7.5 million cases and 35,000 deaths every year. The predicted distribution of malaria derived from climate factors such as maximum and minimum temperatures, rainfall and relative humidity was compared with the actual number of malaria cases in Sudan for the period 2004 to 2010. The predictive calculations were done by fuzzy logic suitability (FLS) applied to the numerical distribution of malaria transmission based on the life cycle characteristics of the Anopheles mosquito accounting for the impact of climate factors on malaria transmission. This information is visualized as a series of maps (presented in video format) using a geographical information systems (GIS) approach. The climate factors were found to be suitable for malaria transmission in the period of May to October, whereas the actual case rates of malaria were high from June to November indicating a positive correlation. While comparisons between the prediction model for June and the case rate model for July did not show a high degree of association (18%), the results later in the year were better, reaching the highest level (55%) for October prediction and November case rate.

  9. Model for Predicting Climatic Yield of Sugarcane in Nanning City

    Institute of Scientific and Technical Information of China (English)

    Zhanggui; LAN; Guanghai; LI; Yulian; LIANG; Yuhong; YANG; Xiaoping; LI

    2014-01-01

    According to spatial distribution of climate disasters in Nanning City and physiological and ecological indicator demands of sugarcane,with the aid of HJ- 1 CCD satellite remote sensing images,basic meteorological data and geographic information data,this paper established the model for predicting climatic yield of sugarcane in Nanning City,to predict total yield of sugarcane in Nanning City. Results indicated that the distribution of sugarcane in Nanning City is greatly influenced by drought. In 2010,regions suffered from drought had sugarcane planting area of 346. 20 km2,accounting for 18.88% of the total sugarcane planting area. The influence of frost disaster on distribution of sugarcane in Nanning City is limited. Regions suffered from frost had sugarcane planting area of only 67. 1 km2,taking up 3.75% of the total sugarcane planting area. In 2010,the climatic yield of sugarcane in Nanning City was 8. 8446 million tons. It proved that the prediction accuracy of the model is up to 90%.

  10. A regional dynamic vegetation-climate model for Central America

    Science.gov (United States)

    Snell, R. S.; Cowling, S. A.; Smith, B.

    2009-12-01

    Global vegetation models simulate the distribution of vegetation as a function of climate. Dynamic global vegetation models (DGVMs) are also able to simulate the vegetation shifts in response to climate change, which makes them particularly useful for addressing questions about past and future climate scenarios. However, DGVMs have been criticized for using generic plant functional types (PFTs) and running the models at a coarse grid cell resolution. Regional dynamic vegetation models are able to simulate important landscape variation, since they use a finer resolution and specific PFTs for their region. Regional studies have typically focused on boreal or temperate ecosystems in North America and Europe. We will be presenting the results of applying a dynamic regional vegetation-climate model (LPJ-GUESS) for Central America. Initially, the model was run with the described global PFTs. However, several biomes were very poorly represented. Two PFTs were added: a Tropical Needleleaf Evergreen Tree to improve the simulation of the Mixed Pine-Oak biome, and a Desert Shrub to capture the Xeric Shrublands. The overall distribution of biomes was visually similar, however the Kappa statistic indicated a poor agreement with the potential biome map (overall Kappa = 0.301). The Kappa statistic did improve as we aggregated cell sizes and simplified the biomes (overall Kappa = 0.728). Compared to remote sensing data, the model showed a strong correlation with total LAI (r = 0.75). The poor Kappa statistic is likely due to a combination of factors. The way in which biomes are defined by the author can have a large influence on the level of agreement between simulated and potential vegetation. The Kappa statistic is also limited to comparing individual grid cells and thus, cannot detect overall patterns. Examining those areas which are poorly represented will help to identify future work and improve the representation of vegetation in these ecological models. In particular, the

  11. Climate in Sweden during the past millennium - Evidence from proxy data, instrumental data and model simulations

    Energy Technology Data Exchange (ETDEWEB)

    Moberg, Anders; Gouirand, Isabelle; Schoning, Kristian; Wohlfarth, Barbara [Stockholm Univ. (Sweden). Dept. of Physical Geography and Quaternary Geology; Kjellstroem, Erik; Rummukainen, Markku [Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden). Rossby Centre; Jong, Rixt de [Lund Univ. (Sweden). Dept. of Quaternary Geology; Linderholm, Hans [Goeteborg Univ. (Sweden). Dept. of Earth Sciences; Zorita, Eduardo [GKSS Research Centre, Geesthacht (Germany)

    2006-12-15

    last millennium. Models, however, cannot be used to deduce the exact time evolution of climate variations, but they can provide relevant information in a statistical sense, for example by defining the limits within which climate naturally has varied. Uncertainties - and also advantages - of both empirical climate data and model simulations are discussed. A main conclusion is that there have been both relatively warm and cold past periods, as well as some relatively wet and dry periods during the past 1,000 to 2,000 years. It appears that the last 70-year period in Sweden was the warmest period over at least the last 500 years. Exactly how unusual the past few decades were can, however, not yet be established due to limitations of the proxy data. There are also indications that significant past changes in precipitation, river runoff and storminess have occurred, although available proxy data do not yet allow accurate quantitative estimations. The results of the present report will be used by SKB, along with other information, in the process of defining and describing future climate scenarios. They will also be used in evaluating the impact of climate on various processes related to repository safety, for example biosphere processes. To increase knowledge of past climate variations in Sweden for the last millennium, it seems necessary to develop additional climate proxy records with annual or at least decadal resolution. Long simulations with climate models may also be used in this context.

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

    Science.gov (United States)

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

    2014-02-13

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

  13. Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?

    Science.gov (United States)

    Tabari, Hossein; De Troch, Rozemien; Giot, Olivier; Hamdi, Rafiq; Termonia, Piet; Saeed, Sajjad; Brisson, Erwan; Van Lipzig, Nicole; Willems, Patrick

    2016-09-01

    This study explores whether climate models with higher spatial resolutions provide higher accuracy for precipitation simulations and/or different climate change signals. The outputs from two convection-permitting climate models (ALARO and CCLM) with a spatial resolution of 3-4 km are compared with those from the coarse-scale driving models or reanalysis data for simulating/projecting daily and sub-daily precipitation quantiles. Validation of historical design precipitation statistics derived from intensity-duration-frequency (IDF) curves shows a better match of the convection-permitting model results with the observations-based IDF statistics compared to the driving GCMs and reanalysis data. This is the case for simulation of local sub-daily precipitation extremes during the summer season, while the convection-permitting models do not appear to bring added value to simulation of daily precipitation extremes. Results moreover indicate that one has to be careful in assuming spatial-scale independency of climate change signals for the delta change downscaling method, as high-resolution models may show larger changes in extreme precipitation. These larger changes appear to be dependent on the timescale, since such intensification is not observed for daily timescales for both the ALARO and CCLM models.

  14. The treatment of climate science in Integrated Assessment Modelling: integration of climate step function response in an energy system integrated assessment model.

    Science.gov (United States)

    Dessens, Olivier

    2016-04-01

    Integrated Assessment Models (IAMs) are used as crucial inputs to policy-making on climate change. These models simulate aspect of the economy and climate system to deliver future projections and to explore the impact of mitigation and adaptation policies. The IAMs' climate representation is extremely important as it can have great influence on future political action. The step-function-response is a simple climate model recently developed by the UK Met Office and is an alternate method of estimating the climate response to an emission trajectory directly from global climate model step simulations. Good et al., (2013) have formulated a method of reconstructing general circulation models (GCMs) climate response to emission trajectories through an idealized experiment. This method is called the "step-response approach" after and is based on an idealized abrupt CO2 step experiment results. TIAM-UCL is a technology-rich model that belongs to the family of, partial-equilibrium, bottom-up models, developed at University College London to represent a wide spectrum of energy systems in 16 regions of the globe (Anandarajah et al. 2011). The model uses optimisation functions to obtain cost-efficient solutions, in meeting an exogenously defined set of energy-service demands, given certain technological and environmental constraints. Furthermore, it employs linear programming techniques making the step function representation of the climate change response adapted to the model mathematical formulation. For the first time, we have introduced the "step-response approach" method developed at the UK Met Office in an IAM, the TIAM-UCL energy system, and we investigate the main consequences of this modification on the results of the model in term of climate and energy system responses. The main advantage of this approach (apart from the low computational cost it entails) is that its results are directly traceable to the GCM involved and closely connected to well-known methods of

  15. Clouds and Precipitation Simulated by the US DOE Accelerated Climate Modeling for Energy (ACME)

    Science.gov (United States)

    Xie, S.; Lin, W.; Yoon, J. H.; Ma, P. L.; Rasch, P. J.; Ghan, S.; Zhang, K.; Zhang, Y.; Zhang, C.; Bogenschutz, P.; Gettelman, A.; Larson, V. E.; Neale, R. B.; Park, S.; Zhang, G. J.

    2015-12-01

    A new US Department of Energy (DOE) climate modeling effort is to develop an Accelerated Climate Model for Energy (ACME) to accelerate the development and application of fully coupled, state-of-the-art Earth system models for scientific and energy application. ACME is a high-resolution climate model with a 0.25 degree in horizontal and more than 60 levels in the vertical. It starts from the Community Earth System Model (CESM) with notable changes to its physical parameterizations and other components. This presentation provides an overview on the ACME model's capability in simulating clouds and precipitation and its sensitivity to convection schemes. Results with using several state-of-the-art cumulus convection schemes, including those unified parameterizations that are being developed in the climate community, will be presented. These convection schemes are evaluated in a multi-scale framework including both short-range hindcasts and free-running climate simulations with both satellite data and ground-based measurements. Running climate model in short-range hindcasts has been proven to be an efficient way to understand model deficiencies. The analysis is focused on those systematic errors in clouds and precipitation simulations that are shared in many climate models. The goal is to understand what model deficiencies might be primarily responsible for these systematic errors.

  16. The Urgent Need for Improved Climate Models and Predictions

    Science.gov (United States)

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

    2009-09-01

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

  17. A global climate model based, Bayesian climate projection for northern extra-tropical land areas

    Science.gov (United States)

    Arzhanov, Maxim M.; Eliseev, Alexey V.; Mokhov, Igor I.

    2012-04-01

    Projections with contemporary global climate models (GCMs) still markedly deviate from each other on magnitude of climate changes, in particular, in middle to subpolar latitudes. In this work, a climate projection based on the ensemble of 18 CMIP3 GCM models forced by SRES A1B scenario is performed for the northern extra-tropical land. To assess the change of soil state, off-line simulations are performed with the Deep Soil Simulator (DSS) developed at the A.M.Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS). This model is forced by output of the above-mentioned GCM simulations. Ensemble mean and ensemble standard deviation for any variable are calculated by using Bayesian averaging which allows to enhance a contribution from more realistic models and diminish that from less realistic models. As a result, uncertainty for soil and permafrost variables become substantially narrower. The Bayesian weights for each model are calculated based on their performance for the present-day surface air temperature (SAT) and permafrost distributions, and for SAT trend during the 20th century. The results, except for intra-ensemble standard deviations, are not very sensitive to particular choice of Bayesian traits. Averaged over the northern extra-tropical land, annual mean surface air temperature in the ensemble increases by 3.1 ± 1.4 K (ensemble mean±intra-ensemble standard deviation) during the 21st century. Precipitation robustly increases in the pan-Arctic and decreases in the Mediterranean/Black Sea region. The models agree on near-surface permafrost degradation during the 21st century. The area underlain by near-surface permafrost decreases from the contemporary value 20 ± 3 mln sq. km to 14 ± 3 mln sq. km in the late 21st century. This leads to risk for geocryological hazard due to soil subsidence. This risk is classified as moderate to high in the southern and western parts of Siberia and Tibet in Eurasia, and in the region from Alaska

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

    Directory of Open Access Journals (Sweden)

    Peter F. Craigmile

    2013-10-01

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

  19. Modeling the global society-biosphere-climate system : Part 2: Computed scenarios

    NARCIS (Netherlands)

    Alcamo, J.; Van Den Born, G.J.; Bouwman, A.F.; De Haan, B.J.; Klein Goldewijk, K.; Klepper, O.; Krabec, J.; Leemans, R.; Olivier, J.G.J.; Toet, A.M.C.; De Vries, H.J.M.; Van Der Woerd, H.J.

    1994-01-01

    This paper presents scenarios computed with IMAGE 2.0, an integrated model of the global environment and climate change. Results are presented for selected aspects of the society-biosphere-climate system including primary energy consumption, emissions of various greenhouse gases, atmospheric concent

  20. Le changement climatique d'origine humaine. Rappel de quelques résultats générauxAnthropogenic climate change: general results

    Science.gov (United States)

    Petit, Michel

    1999-02-01

    The IPCC (International Panel on Climate Change) reports have highlighted major results, which constitute a relevant framework for the specific papers in this issue. Both facts established with large confidence level and models results are presented.

  1. Effect of Flux Adjustments on Temperature Variability in Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Duffy, P.; Bell, J.; Covey, C.; Sloan, L.

    1999-12-27

    It has been suggested that ''flux adjustments'' in climate models suppress simulated temperature variability. If true, this might invalidate the conclusion that at least some of observed temperature increases since 1860 are anthropogenic, since this conclusion is based in part on estimates of natural temperature variability derived from flux-adjusted models. We assess variability of surface air temperatures in 17 simulations of internal temperature variability submitted to the Coupled Model Intercomparison Project. By comparing variability in flux-adjusted vs. non-flux adjusted simulations, we find no evidence that flux adjustments suppress temperature variability in climate models; other, largely unknown, factors are much more important in determining simulated temperature variability. Therefore the conclusion that at least some of observed temperature increases are anthropogenic cannot be questioned on the grounds that it is based in part on results of flux-adjusted models. Also, reducing or eliminating flux adjustments would probably do little to improve simulations of temperature variability.

  2. Regional Climate Modeling over South America: A Review

    Directory of Open Access Journals (Sweden)

    Silvina A. Solman

    2013-01-01

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

  3. Considerations for parameter optimization and sensitivity in climate models.

    Science.gov (United States)

    Neelin, J David; Bracco, Annalisa; Luo, Hao; McWilliams, James C; Meyerson, Joyce E

    2010-12-14

    Climate models exhibit high sensitivity in some respects, such as for differences in predicted precipitation changes under global warming. Despite successful large-scale simulations, regional climatology features prove difficult to constrain toward observations, with challenges including high-dimensionality, computationally expensive simulations, and ambiguity in the choice of objective function. In an atmospheric General Circulation Model forced by observed sea surface temperature or coupled to a mixed-layer ocean, many climatic variables yield rms-error objective functions that vary smoothly through the feasible parameter range. This smoothness occurs despite nonlinearity strong enough to reverse the curvature of the objective function in some parameters, and to imply limitations on multimodel ensemble means as an estimator of global warming precipitation changes. Low-order polynomial fits to the model output spatial fields as a function of parameter (quadratic in model field, fourth-order in objective function) yield surprisingly successful metamodels for many quantities and facilitate a multiobjective optimization approach. Tradeoffs arise as optima for different variables occur at different parameter values, but with agreement in certain directions. Optima often occur at the limit of the feasible parameter range, identifying key parameterization aspects warranting attention--here the interaction of convection with free tropospheric water vapor. Analytic results for spatial fields of leading contributions to the optimization help to visualize tradeoffs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional error under minimization of global objective functions. The approach is sufficiently simple to guide parameter choices and to aid intercomparison of sensitivity properties among climate models.

  4. Ontological and Epistemological Issues Regarding Climate Models and Computer Experiments

    Science.gov (United States)

    Vezer, M. A.

    2010-12-01

    Recent philosophical discussions (Parker 2009; Frigg and Reiss 2009; Winsberg, 2009; Morgon 2002, 2003, 2005; Gula 2002) about the ontology of computer simulation experiments and the epistemology of inferences drawn from them are of particular relevance to climate science as computer modeling and analysis are instrumental in understanding climatic systems. How do computer simulation experiments compare with traditional experiments? Is there an ontological difference between these two methods of inquiry? Are there epistemological considerations that result in one type of inference being more reliable than the other? What are the implications of these questions with respect to climate studies that rely on computer simulation analysis? In this paper, I examine these philosophical questions within the context of climate science, instantiating concerns in the philosophical literature with examples found in analysis of global climate change. I concentrate on Wendy Parker’s (2009) account of computer simulation studies, which offers a treatment of these and other questions relevant to investigations of climate change involving such modelling. Two theses at the center of Parker’s account will be the focus of this paper. The first is that computer simulation experiments ought to be regarded as straightforward material experiments; which is to say, there is no significant ontological difference between computer and traditional experimentation. Parker’s second thesis is that some of the emphasis on the epistemological importance of materiality has been misplaced. I examine both of these claims. First, I inquire as to whether viewing computer and traditional experiments as ontologically similar in the way she does implies that there is no proper distinction between abstract experiments (such as ‘thought experiments’ as well as computer experiments) and traditional ‘concrete’ ones. Second, I examine the notion of materiality (i.e., the material commonality between

  5. Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

    Science.gov (United States)

    Ruane, Alex C.; Goldberg, Richard; Chryssanthacopoulos, James

    2014-01-01

    The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

  6. A framework for modeling uncertainty in regional climate change

    Science.gov (United States)

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

  7. Integrated modelling of climate, water, soil, agricultural and socio-economic processes: a general introduction of the methodology and some exemplary results from the semi-rid Northeast of Brazil

    NARCIS (Netherlands)

    Krol, Maarten; Jaeger, Annekathrin; Bronstert, Axel; Güntner, Andreas

    2006-01-01

    Many semi-arid regions are characterised by water scarcity and vulnerability of natural resources, pronounced climatic variability and social stress. Integrated studies including climatology, hydrology, and socio-economic studies are required both for analysing the dynamic natural conditions and to

  8. A Joint Approach to the Study of S-Type and P-Type Habitable Zones in Binary Systems: New Results in the View of 3-D Planetary Climate Models

    Science.gov (United States)

    Cuntz, Manfred

    2015-01-01

    In two previous papers, given by Cuntz (2014a,b) [ApJ 780, A14 (19 pages); arXiv:1409.3796], a comprehensive approach has been provided for the study of S-type and P-type habitable zones in stellar binary systems, P-type orbits occur when the planet orbits both binary components, whereas in case of S-type orbits, the planet orbits only one of the binary components with the second component considered a perturbator. The selected approach considers a variety of aspects, including (1) the consideration of a joint constraint including orbital stability and a habitable region for a possible system planet through the stellar radiative energy fluxes; (2) the treatment of conservative (CHZ), general (GHZ) and extended zones of habitability (EHZ) [see Paper I for definitions] for the systems as previously defined for the Solar System; (3) the provision of a combined formalism for the assessment of both S-type and P-type habitability; in particular, mathematical criteria are devised for which kind of system S-type and P-type habitability is realized; and (4) the applications of the theoretical approach to systems with the stars in different kinds of orbits, including elliptical orbits (the most expected case). Particularly, an algebraic formalism for the assessment of both S-type and P-type habitability is given based on a higher-order polynomial expression. Thus, an a prior specification for the presence or absence of S-type or P-type radiative habitable zones is - from a mathematical point of view - neither necessary nor possible, as those are determined by the adopted formalism. Previously, numerous applications of the method have been given encompassing theoretical star-panet systems and and observations. Most recently, this method has been upgraded to include recent studies of 3-D planetary climate models. Originally, this type of work affects the extent and position of habitable zones around single stars; however, it has also profound consequence for the habitable

  9. Dynamics of the Coupled Human-climate System Resulting from Closed-loop Control of Solar Geoengineering

    Energy Technology Data Exchange (ETDEWEB)

    MacMartin, Douglas; Kravitz, Benjamin S.; Keith, David; Jarvis, Andrew

    2014-07-08

    If solar radiation management (SRM) were ever implemented, feedback of the observed climate state might be used to adjust the radiative forcing of SRM, in order to compensate for uncertainty in either the forcing or the climate response; this would also compensate for unexpected changes in the system, e.g. a nonlinear change in climate sensitivity. This feedback creates an emergent coupled human-climate system, with entirely new dynamics. In addition to the intended response to greenhouse-gas induced changes, the use of feedback would also result in a geoengineering response to natural climate variability. We use a simple box-diffusion dynamic model to understand how changing feedback-control parameters and time delay affect the behavior of this coupled natural-human system, and verify these predictions using the HadCM3L general circulation model. In particular, some amplification of natural variability is unavoidable; any time delay (e.g., to average out natural variability, or due to decision-making) exacerbates this amplification, with oscillatory behavior possible if there is a desire for rapid correction (high feedback gain), but a delayed response needed for decision making. Conversely, the need for feedback to compensate for uncertainty, combined with a desire to avoid excessive amplification, results in a limit on how rapidly SRM could respond to uncertain changes.

  10. Precipitation extremes over La Plata Basin - Review and new results from observations and climate simulations

    Science.gov (United States)

    Cavalcanti, I. F. A.; Carril, A. F.; Penalba, O. C.; Grimm, A. M.; Menéndez, C. G.; Sanchez, E.; Cherchi, A.; Sörensson, A.; Robledo, F.; Rivera, J.; Pántano, V.; Bettolli, L. M.; Zaninelli, P.; Zamboni, L.; Tedeschi, R. G.; Dominguez, M.; Ruscica, R.; Flach, R.

    2015-04-01

    Monthly and daily precipitation extremes over La Plata Basin (LPB) are analyzed in the framework of the CLARIS-LPB Project. A review of the studies developed during the project and results of additional research are presented and discussed. Specific aspects of analysis are focused on large-scale versus local processes impacts on the intensity and frequency of precipitation extremes over LPB, and on the assessment of specific wet and dry spell indices and their changed characteristics in future climate scenarios. The analysis is shown for both available observations of precipitation in the region and ad-hoc global and regional models experiments. The Pacific, Indian and Atlantic Oceans can all impact precipitation intensity and frequency over LPB. In particular, considering the Pacific sector, different types of ENSO events (i.e. canonical vs Modoki or East vs Central) have different influences. Moreover, model projections indicate an increase in the frequency of precipitation extremes over LPB during El Niño and La Ninã events in future climate. Local forcings can also be important for precipitation extremes. Here, the feedbacks between soil moisture and extreme precipitation in LPB are discussed based on hydric conditions in the region and model sensitivity experiments. Concerning droughts, it was found that they were more frequent in the western than in the eastern sector of LPB during the period of 1962-2008. On the other hand, observations and model experiments agree in that the monthly wet extremes were more frequent than the dry extremes in the northern and southern LPB sectors during the period 1979-2001, with higher frequency in the south.

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

    Science.gov (United States)

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

    2016-02-01

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

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

    NARCIS (Netherlands)

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

    2011-01-01

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

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

    Science.gov (United States)

    Bugelmayer, Marianne; Roche, Didier; Renssen, Hans

    2013-04-01

    methods share that GRISLI is coupled to iLOVECLIM on a yearly basis with exchange of accumulation/temperature and albedo /topography fields. They differ in the method used to provide the freshwater feedback to the ocean component. The first method assumes no water-feedback, this implies that there is no influence of calving and runoff from GRISLI on iLOVECLIM. In the second set-up, the freshwater-feedback (ablation and calving) is included but only in the form of liquid water: the thermal and distribution effect of icebergs is ignored and calving is given as a simple freshwater flux at the calving site to the oceanic component. In the third coupling procedure, calving is used to generate icebergs. By comparing these three experiments we are able to identify the influence of the water feedback on the climate. Moreover, the impact of the icebergs compared to direct freshwater fluxes is displayed by the fact that the resulting ocean cooling in the first few hundred years is relatively weak and is located close to Greenland, while it becomes stronger and more wide-spread later on. These differences in response to the forcing (icebergs/liquid runoff at the calving site) seem to decrease with time. These findings reveal that parameterizing icebergs using freshwater fluxes is a useful approach under constant forcing, yet, when investigating extreme events it will lead to a different timing of the climatic response. References Bigg, G., WADLEY, M. R., STEVENS, D. P., & Johnson, J. V. (1997). Modelling the dynamics and thermodynamics of icebergs. Cold Regions Science and Technology, 26(2), 113-135. doi:10.1016/S0165-232X(97)00012-8 Jongma, J., Driesschaert, E., Fichefet, T., Goosse, H., & Renssen, H. (2008). The effect of dynamic-thermodynamic icebergs on the Southern Ocean climate in a three-dimensional model. Ocean Modelling, 26(1-2), 104-113. Elsevier Ltd. doi:10.1016/j.ocemod.2008.09.007 Ritz, C., Fabre, A., and Letréguilly, A. (1997). Sensitivity of a Greenland ice sheet

  14. Nonhydrostatic adaptive mesh dynamics for multiscale climate models (Invited)

    Science.gov (United States)

    Collins, W.; Johansen, H.; McCorquodale, P.; Colella, P.; Ullrich, P. A.

    2013-12-01

    Many of the atmospheric phenomena with the greatest potential impact in future warmer climates are inherently multiscale. Such meteorological systems include hurricanes and tropical cyclones, atmospheric rivers, and other types of hydrometeorological extremes. These phenomena are challenging to simulate in conventional climate models due to the relatively coarse uniform model resolutions relative to the native nonhydrostatic scales of the phenomonological dynamics. To enable studies of these systems with sufficient local resolution for the multiscale dynamics yet with sufficient speed for climate-change studies, we have adapted existing adaptive mesh dynamics for the DOE-NSF Community Atmosphere Model (CAM). In this talk, we present an adaptive, conservative finite volume approach for moist non-hydrostatic atmospheric dynamics. The approach is based on the compressible Euler equations on 3D thin spherical shells, where the radial direction is treated implicitly (using a fourth-order Runga-Kutta IMEX scheme) to eliminate time step constraints from vertical acoustic waves. Refinement is performed only in the horizontal directions. The spatial discretization is the equiangular cubed-sphere mapping, with a fourth-order accurate discretization to compute flux averages on faces. By using both space-and time-adaptive mesh refinement, the solver allocates computational effort only where greater accuracy is needed. The resulting method is demonstrated to be fourth-order accurate for model problems, and robust at solution discontinuities and stable for large aspect ratios. We present comparisons using a simplified physics package for dycore comparisons of moist physics. Hadley cell lifting an advected tracer into upper atmosphere, with horizontal adaptivity

  15. Results of an Institutional LGBT Climate Survey at an Academic Medical Center.

    Science.gov (United States)

    Chester, Sean D; Ehrenfeld, Jesse M; Eckstrand, Kristen L

    2014-12-01

    The purpose of this study was to characterize the climate and culture experienced by lesbian, gay, bisexual, and transgender (LGBT) employees and students at one large academic medical center. An anonymous, online institutional climate survey was used to assess the attitudes and experiences of LGBT employees and students. There were 42 LGBT and 14 non-LGBT survey participants. Results revealed that a surprisingly large percentage of LGBT individuals experienced pressure to remain "closeted" and were harassed despite medical center policies of non-discrimination. Continuing training, inclusive policies and practices, and the development of mechanisms to address LGBT-specific harassment are necessary for improving institutional climate.

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

    Directory of Open Access Journals (Sweden)

    T. L. A. Driessen

    2009-11-01

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

  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. Modeling of Arctic Climate: Fairbanks-Barrow Top of the World Summer School

    Science.gov (United States)

    Alexeev, V. A.; Walsh, J. E.; Sparrow, E. B.

    2009-04-01

    Arctic climate is the result of a complex interplay between the atmosphere, the ocean, sea ice and a terrestrial component in which freezing and thawing are critical to variations over a range of timescales. In view of the delicate balances between these components and their poorly documented sensitivities, it is not surprising that global climate models show the largest disagreement among themselves, and also the strongest greenhouse-induced changes, in the polar regions. Since changes in the Arctic may well have global implications, it is essential that Arctic climate simulations be enhanced in order to reduce the uncertainties in projections of climate change. Given the challenges and opportunities in Arctic modeling, the International Arctic Research Center's (IARC) 2008 summer school at the University of Alaska Fairbanks (UAF), was designed to bring the next generation of climate modelers to the Arctic. The two-week summer school brought together a group of 16 graduate students and young scientists, as well as specialists in Arctic climate and climate modeling, for two weeks, the first week in Fairbanks (May 27-31) and the second in Barrow (June 1-6). The young scientists gained a perspective on the key issues in Arctic climate from observational, diagnostic and modeling perspectives and received hands-on experience in the analysis of climate model output or in climate model experimentation at a level consistent with the students' expertise. The summer school consisted of background pedagogical lectures in the mornings, and mini-projects and informal discussions in the afternoons. The mini-projects have been performed in collaboration with lecturers, and utilized existing databases and available models. The second week was spent observing and experiencing Arctic research first-hand in Barrow, Alaska in coordination with the Barrow Arctic Sciences Consortium (BASC). The summer school and IARC are supported by the NSF, NOAA and JAMSTEC.

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

    Science.gov (United States)

    Fertig, E.; Webster, M.

    2013-12-01

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

  20. California Basin Characterization Model Downscaled Climate and Hydrology

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The California Basin Characterization Model (CA-BCM 2014) dataset provides historical and projected climate and hydrologic surfaces for the region that encompasses...

  1. Modeling lakes and reservoirs in the climate system

    Science.gov (United States)

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

    2009-01-01

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

  2. 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.

  3. Climatic and thermodynamic modelling of rapid development drivages

    Energy Technology Data Exchange (ETDEWEB)

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

    2001-07-01

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

  4. Climate Model Dependency and Understanding the Antarctic Ice Sheet during the Warm Late Pliocene

    Science.gov (United States)

    Dolan, Aisling; de Boer, Bas; Bernales, Jorge; Hunter, Stephen; Haywood, Alan

    2016-04-01

    In the context of future climate change, understanding the nature and behaviour of ice sheets during warm intervals of Earth history is fundamentally important. A warm period in the Late Pliocene (3.264 to 3.025 million years before present) can serve as a potential analogue for projected future climates. Although Pliocene ice locations and extents are still poorly constrained, a significant contribution to sea-level rise should be expected from both the Greenland ice sheet and the West and East Antarctic ice sheets based on palaeo sea-level reconstructions and geological evidence. Following a five year international project PLISMIP (Pliocene Ice Sheet Modeling Intercomparison Project) we present the final set of results which quantify uncertainty in climate model-based predictions of the Antarctic ice sheet. In this study we use an ensemble of climate model forcings within a multi-ice sheet model framework to assess the climate (model) dependency of large scale features of the Antarctic ice sheet. Seven coupled atmosphere-ocean climate models are used to derive surface temperature, precipitation and oceanic forcing that drive three ice sheet models (over the grounded and floating domain). Similar to results presented over Greenland, we show that the reconstruction of the Antarctic ice sheet is sensitive to which climate model is used to provide the forcing field. Key areas of uncertainty include West Antarctica, the large subglacial basins of East Antarctica and the overall thickness of the continental interior of East Antarctica. We relate the results back to geological proxy data, such as those relating to exposure rates which provide information on potential ice sheet thickness. Finally we discuss as to whether the choice of modelling framework (i.e. climate model and ice sheet model used) or the choice of boundary conditions causes the greatest uncertainty in ice sheet reconstructions of the warm Pliocene.

  5. 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.

  6. Adjustment of regional climate model output for modeling the climatic mass balance of all glaciers on Svalbard.

    Science.gov (United States)

    Möller, Marco; Obleitner, Friedrich; Reijmer, Carleen H; Pohjola, Veijo A; Głowacki, Piotr; Kohler, Jack

    2016-05-27

    Large-scale modeling of glacier mass balance relies often on the output from regional climate models (RCMs). However, the limited accuracy and spatial resolution of RCM output pose limitations on mass balance simulations at subregional or local scales. Moreover, RCM output is still rarely available over larger regions or for longer time periods. This study evaluates the extent to which it is possible to derive reliable region-wide glacier mass balance estimates, using coarse resolution (10 km) RCM output for model forcing. Our data cover the entire Svalbard archipelago over one decade. To calculate mass balance, we use an index-based model. Model parameters are not calibrated, but the RCM air temperature and precipitation fields are adjusted using in situ mass balance measurements as reference. We compare two different calibration methods: root mean square error minimization and regression optimization. The obtained air temperature shifts (+1.43°C versus +2.22°C) and precipitation scaling factors (1.23 versus 1.86) differ considerably between the two methods, which we attribute to inhomogeneities in the spatiotemporal distribution of the reference data. Our modeling suggests a mean annual climatic mass balance of -0.05 ± 0.40 m w.e. a(-1) for Svalbard over 2000-2011 and a mean equilibrium line altitude of 452 ± 200 m  above sea level. We find that the limited spatial resolution of the RCM forcing with respect to real surface topography and the usage of spatially homogeneous RCM output adjustments and mass balance model parameters are responsible for much of the modeling uncertainty. Sensitivity of the results to model parameter uncertainty is comparably small and of minor importance.

  7. Modeling Surgery: A New Way Toward Understanding Earth Climate Variability

    Institute of Scientific and Technical Information of China (English)

    WU Lixin; LIU Zhengyu; Robert Gallimore; Michael Notaro; Robert Jacob

    2005-01-01

    A new modeling concept, referred to as Modeling Surgery, has been recently developed at University of Wisconsin-Madison. It is specifically designed to diagnose coupled feedbacks between different climate components as well as climatic teleconnections within a specific component through systematically modifying the coupling configurations and teleconnective pathways. It thus provides a powerful means for identifying the causes and mechanisms of low-frequency variability in the Earth's climate system. In this paper, we will give a short review of our recent progress in this new area.

  8. Climate simulations for 1880-2003 with GISS modelE

    CERN Document Server

    Hansen, J; Bauer, S; Baum, E; Cairns, B; Canuto, V; Chandler, M; Cheng, Y; Cohen, A; Faluvegi, G; Fleming, E; Friend, A; Genio, A D; Hall, T; Jackman, C; Jonas, J; Kelley, M; Kharecha, P; Kiang, N Y; Koch, D; Labow, G; Lacis, A; Lerner, J; Lo, K; Menon, S; Miller, R; Nazarenko, L; Novakov, T; Oinas, V; Perlwitz, J; Rind, D; Romanou, A; Ruedy, R; Russell, G; Sato, M; Schmidt, G A; Schmunk, R; Shindell, D; Stone, P; Streets, D; Sun, S; Tausnev, N; Thresher, D; Unger, N; Yao, M; Zhang, S; Perlwitz, Ja.; Perlwitz, Ju.

    2006-01-01

    We carry out climate simulations for 1880-2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880-2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies...

  9. Hydrological Modelling of Mountainous and Glacierised regions under Changing Climate

    OpenAIRE

    Li, Hong

    2015-01-01

    Climate change is one of the most serious environmental threats that humanity has ever been confronted to. Hydrological models are vital tools to asses its impacts on the water cycle and water resources. The goal of this project is to evaluate and improve the capacity of the HBV model (Hydrologiska Byr°ans Vattenbalansavdelning) in simulating hydrological processes in mountainous and glacierised regions under both the present and future climate. This goal is achieved in two steps: (1) impleme...

  10. Modeling climate change impacts on overwintering bald eagles

    OpenAIRE

    Chris J. Harvey; Moriarty, Pamela E.; Salathé Jr, Eric P

    2012-01-01

    Bald eagles (Haliaeetus leucocephalus) are recovering from severe population declines, and are exerting pressure on food resources in some areas. Thousands of bald eagles overwinter near Puget Sound, primarily to feed on chum salmon (Oncorhynchus keta) carcasses. We used modeling techniques to examine how anticipated climate changes will affect energetic demands of overwintering bald eagles. We applied a regional downscaling method to two global climate change models to obtain hourly temperat...

  11. Parameterization of clouds and radiation in climate models

    Energy Technology Data Exchange (ETDEWEB)

    Roeckner, E. [Max Planck Institute for Meterology, Hamburg (Germany)

    1995-09-01

    Clouds are a very important, yet poorly modeled element in the climate system. There are many potential cloud feedbacks, including those related to cloud cover, height, water content, phase change, and droplet concentration and size distribution. As a prerequisite to studying the cloud feedback issue, this research reports on the simulation and validation of cloud radiative forcing under present climate conditions using the ECHAM general circulation model and ERBE top-of-atmosphere radiative fluxes.

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

    Directory of Open Access Journals (Sweden)

    Vlčková Veronika

    2015-11-01

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

  13. 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.)

  14. Artificial snowmaking possibilities and climate change based on regional climate modeling in the Southern Black Forest

    Energy Technology Data Exchange (ETDEWEB)

    Schmidt, Philipp; Matzarakis, Andreas [Freiburg Univ. (Germany). Meteorological Inst.; Steiger, Robert [alpS - Centre for Climate Change Adaptation Technologies, Innsbruck (Austria)

    2012-04-15

    Winter sport, especially ski tourism - is one of those sectors of tourism that will be affected by climate change. Ski resorts across the Alps and in the adjacent low mountain ranges react to warm winter seasons by investing in artificial snowmaking. But snowmaking in warm winter seasons is fraught with risk, because sufficiently low air temperature will become less frequent in the future. The present study deals with the ski resort Feldberg, which has 14 ski lifts and 16 ski slopes which is the biggest ski resort in the German Federal state Baden-Wuerttemberg. The impact of climate change in this region is extraordinary important because winter tourism is the main source of revenue for the whole area around the ski resort. The study area is in altitudinal range of 850 to 1450 meters above sea level. At the moment, it is possible to supply one third of the whole area with artificial snow, but there is plan for artificial snowmaking of the whole Feldberg area by the year 2020. Based on this, more detailed investigations of season length and the needed volume of produced snow are necessary. A ski season simulation model (SkiSim 2.0) was applied in order to assess potential impacts of climate change on the Feldberg ski area for the A1B and B1 emission scenarios based on the ECHAM5 GCM downscaled by the REMO RCM. SkiSim 2.0 calculates daily snow depth (natural and technically produced snow) and the required amount of artificial snow for 100 m altitudinal bands. Analysing the development of the number of potential skiing days, it can be assessed whether ski operation is cost covering or not. Model results of the study show a more pronounced and rapid shortening of the ski season in the lower ranges until the year 2100 in each climate scenario. In both the A1B and B1 scenario runs of REMO, a cost-covering ski season of 100 days cannot be guaranteed in every altitudinal range even if snowmaking is considered. In this context, the obtained high-resolution snow data can

  15. Modelling climate change impacts on mycotoxin contamination

    NARCIS (Netherlands)

    Fels, van der Ine; Liu, C.; Battilani, P.

    2016-01-01

    Projected climate change effects will influence primary agricultural systems and thus food security, directly via impacts on yields, and indirectly via impacts on its safety, with mycotoxins considered as crucial hazards. Mycotoxins are produced by a wide variety of fungal species, each having their

  16. Reconciled climate response estimates from climate models and the energy budget of Earth

    Science.gov (United States)

    Richardson, Mark; Cowtan, Kevin; Hawkins, Ed; Stolpe, Martin B.

    2016-10-01

    Climate risks increase with mean global temperature, so knowledge about the amount of future global warming should better inform risk assessments for policymakers. Expected near-term warming is encapsulated by the transient climate response (TCR), formally defined as the warming following 70 years of 1% per year increases in atmospheric CO2 concentration, by which point atmospheric CO2 has doubled. Studies based on Earth's historical energy budget have typically estimated lower values of TCR than climate models, suggesting that some models could overestimate future warming. However, energy-budget estimates rely on historical temperature records that are geographically incomplete and blend air temperatures over land and sea ice with water temperatures over open oceans. We show that there is no evidence that climate models overestimate TCR when their output is processed in the same way as the HadCRUT4 observation-based temperature record. Models suggest that air-temperature warming is 24% greater than observed by HadCRUT4 over 1861-2009 because slower-warming regions are preferentially sampled and water warms less than air. Correcting for these biases and accounting for wider uncertainties in radiative forcing based on recent evidence, we infer an observation-based best estimate for TCR of 1.66 °C, with a 5-95% range of 1.0-3.3 °C, consistent with the climate models considered in the IPCC 5th Assessment Report.

  17. Climate Change under aggressive mitigation: The ENSEMBLES multi-model experiment

    NARCIS (Netherlands)

    Johns, T.C.; Royer, J.F.; Hoeschel, I.; Huebener, H.; Roeckner, E.; Manzini, E.; May, W.; Dufresne, J.L.; Ottera, O.H.; van Vuuren, D.P.; Salas y Melia, D.; Giorgetta, M.A.; Denvil, S.; Yang, S.; Fogli, P.G.; Koerper, J.; Tjiputra, J.F.; Stehfest, E.; Hewitt, C.D.

    2011-01-01

    We present results from multiple comprehensive models used to simulate an aggressive mitigation scenario based on detailed results of an Integrated Assessment Model. The experiment employs ten global climate and Earth System models (GCMs and ESMs) and pioneers elements of the long-term experimental

  18. The Alpine snow-albedo feedback in regional climate models

    Science.gov (United States)

    Winter, Kevin J.-P. M.; Kotlarski, Sven; Scherrer, Simon C.; Schär, Christoph

    2017-02-01

    The effect of the snow-albedo feedback (SAF) on 2m temperatures and their future changes in the European Alps is investigated in the ENSEMBLES regional climate models (RCMs) with a focus on the spring season. A total of 14 re-analysis-driven RCM experiments covering the period 1961-2000 and 10 GCM-driven transient climate change projections for 1950-2099 are analysed. A positive springtime SAF is found in all RCMs, but the range of the diagnosed SAF is large. Results are compared against an observation-based SAF estimate. For some RCMs, values very close to this estimate are found; other models show a considerable overestimation of the SAF. Net shortwave radiation has the largest influence of all components of the energy balance on the diagnosed SAF and can partly explain its spatial variability. Model deficiencies in reproducing 2m temperatures above snow and ice and associated cold temperature biases at high elevations seem to contribute to a SAF overestimation in several RCMs. The diagnosed SAF in the observational period strongly influences the estimated SAF contribution to twenty first century temperature changes in the European Alps. This contribution is subject to a clear elevation dependency that is governed by the elevation-dependent change in the number of snow days. Elevations of maximum SAF contribution range from 1500 to 2000 m in spring and are found above 2000 m in summer. Here, a SAF contribution to the total simulated temperature change between 0 and 0.5 °C until 2099 (multi-model mean in spring: 0.26 °C) or 0 and 14 % (multi-model mean in spring: 8 %) is obtained for models showing a realistic SAF. These numbers represent a well-funded but only approximate estimate of the SAF contribution to future warming, and a remaining contribution of model-specific SAF misrepresentations cannot be ruled out.

  19. Integrated hydrological SVAT model for climate change studies in Denmark

    Science.gov (United States)

    Mollerup, M.; Refsgaard, J.; Sonnenborg, T. O.

    2010-12-01

    In a major Danish funded research project (www.hyacints.dk) a coupling is being established between the HIRHAM regional climate model code from Danish Meteorological Institute and the MIKE SHE distributed hydrological model code from DHI. The linkage between those two codes is a soil vegetation atmosphere transfer scheme, which is a module of MIKE SHE. The coupled model will be established for the entire country of Denmark (43,000 km2 land area) where a MIKE SHE based hydrological model already exists (Henriksen et al., 2003, 2008). The present paper presents the MIKE SHE SVAT module and the methodology used for parameterising and calibrating the MIKE SHE SVAT module for use throughout the country. As SVAT models previously typically have been tested for research field sites with comprehensive data on energy fluxes, soil and vegetation data, the major challenge lies in parameterisation of the model when only ordinary data exist. For this purpose annual variations of vegetation characteristics (Leaf Area Index (LAI), Crop height, Root depth and the surface albedo) for different combinations of soil profiles and vegetation types have been simulated by use of the soil plant atmosphere model Daisy (Hansen et al., 1990; Abrahamsen and Hansen, 2000) has been applied. The MIKE SHE SVAT using Daisy generated surface/soil properties model has been calibrated against existing data on groundwater heads and river discharges. Simulation results in form of evapotranspiration and percolation are compared to the existing MIKE SHE model and to observations. To analyse the use of the SVAT model in climate change impact assessments data from the ENSEMBLES project (http://ensembles-eu.metoffice.com/) have been analysed to assess the impacts on reference evapotranspiration (calculated by the Makkink and the Penmann-Monteith equations) as well as on the individual elements in the Penmann-Monteith equation (radiation, wind speed, humidity and temperature). The differences on the

  20. Cross-validation analysis of bias models in Bayesian multi-model projections of climate

    Science.gov (United States)

    Huttunen, J. M. J.; Räisänen, J.; Nissinen, A.; Lipponen, A.; Kolehmainen, V.

    2017-03-01

    Climate change projections are commonly based on multi-model ensembles of climate simulations. In this paper we consider the choice of bias models in Bayesian multimodel predictions. Buser et al. (Clim Res 44(2-3):227-241, 2010a) introduced a hybrid bias model which combines commonly used constant bias and constant relation bias assumptions. The hybrid model includes a weighting parameter which balances these bias models. In this study, we use a cross-validation approach to study which bias model or bias parameter leads to, in a specific sense, optimal climate change projections. The analysis is carried out for summer and winter season means of 2 m-temperatures spatially averaged over the IPCC SREX regions, using 19 model runs from the CMIP5 data set. The cross-validation approach is applied to calculate optimal bias parameters (in the specific sense) for projecting the temperature change from the control period (1961-2005) to the scenario period (2046-2090). The results are compared to the results of the Buser et al. (Clim Res 44(2-3):227-241, 2010a) method which includes the bias parameter as one of the unknown parameters to be estimated from the data.

  1. Assessment of climate change impacts on rainfall using large scale climate variables and downscaling models – A case study

    Indian Academy of Sciences (India)

    Azadeh Ahmadi; Ali Moridi; Elham Kakaei Lafdani; Ghasem Kianpisheh

    2014-10-01

    Many of the applied techniques in water resources management can be directly or indirectly influenced by hydro-climatology predictions. In recent decades, utilizing the large scale climate variables as predictors of hydrological phenomena and downscaling numerical weather ensemble forecasts has revolutionized the long-lead predictions. In this study, two types of rainfall prediction models are developed to predict the rainfall of the Zayandehrood dam basin located in the central part of Iran. The first seasonal model is based on large scale climate signals data around the world. In order to determine the inputs of the seasonal rainfall prediction model, the correlation coefficient analysis and the new Gamma Test (GT) method are utilized. Comparison of modelling results shows that the Gamma test method improves the Nash–Sutcliffe efficiency coefficient of modelling performance as 8% and 10% for dry and wet seasons, respectively. In this study, Support Vector Machine (SVM) model for predicting rainfall in the region has been used and its results are compared with the benchmark models such as K-nearest neighbours (KNN) and Artificial Neural Network (ANN). The results show better performance of the SVM model at testing stage. In the second model, statistical downscaling model (SDSM) as a popular downscaling tool has been used. In this model, using the outputs from GCM, the rainfall of Zayandehrood dam is projected under two climate change scenarios. Most effective variables have been identified among 26 predictor variables. Comparison of the results of the two models shows that the developed SVM model has lesser errors in monthly rainfall estimation. The results show that the rainfall in the future wet periods are more than historical values and it is lower than historical values in the dry periods. The highest monthly uncertainty of future rainfall occurs in March and the lowest in July.

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

    Science.gov (United States)

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

    2010-01-01

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

  3. Assessing the Transferability of the Regional Climate Model REMO to Different COordinated Regional Climate Downscaling EXperiment (CORDEX Regions

    Directory of Open Access Journals (Sweden)

    Claas Teichmann

    2012-02-01

    mountainous regions and East Africa, respectively. The temperature over South America and precipitation over the tundra and highland climate of West Asia are misrepresented. The probable causes leading to these biases are discussed and ideas for improvements are suggested. The annual cycle of precipitation and temperature of major catchments in each domain are also well represented by REMO. The model has performed well in simulating the inter- and intra-seasonal characteristics of different climate types in different regions. Moreover, the model has a high ability in representing the general characteristics of different climate types as measured by the probability density function (PDF skill score method. Although REMO seems to perform best over its home domain in Europe (domain of development and testing, the model has simulated quite well the climate characteristics of other regions with the same set of parameterization options. Therefore, these results lead us to the conclusion that REMO is well suited for long-term climate change simulations to examine projected future changes in all these regions.

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

    Directory of Open Access Journals (Sweden)

    K. A. Stone

    2015-07-01

    Full Text Available Chemistry climate models are important tools for addressing interactions of composition and climate in the Earth System. In particular, they are used for assessing the combined roles of greenhouse gases and ozone in Southern Hemisphere climate and weather. Here we present an evaluation of the Australian Community Climate and Earth System Simulator-Chemistry Climate Model, focusing on the Southern Hemisphere and the Australian region. This model is used for the Australian contribution to the international Chemistry-Climate Model Initiative, which is soliciting hindcast, future projection and sensitivity simulations. The model simulates global total column ozone (TCO distributions accurately, with a slight delay in the onset and recovery of springtime Antarctic ozone depletion, and consistently higher ozone values. However, October averaged Antarctic TCO from 1960 to 2010 show a similar amount of depletion compared to observations. A significant innovation is the evaluation of simulated vertical profiles of ozone and temperature with ozonesonde data from Australia, New Zealand and Antarctica from 38 to 90° S. Excess ozone concentrations (up to 26.4 % at Davis during winter and stratospheric cold biases (up to 10.1 K at the South Pole outside the period of perturbed springtime ozone depletion are seen during all seasons compared to ozonesondes. A disparity in the vertical location of ozone depletion is seen: centered around 100 hPa in ozonesonde data compared to above 50 hPa in the model. Analysis of vertical chlorine monoxide profiles indicates that colder Antarctic stratospheric temperatures (possibly due to reduced mid-latitude heat flux are artificially enhancing polar stratospheric cloud formation at high altitudes. The models inability to explicitly simulated supercooled ternary solution may also explain the lack of depletion at lower altitudes. The simulated Southern Annular Mode (SAM index compares well with ERA-Interim data. Accompanying

  5. Web Service Based Approach to Link Heterogeneous Climate-Energy-Economy Models for Climate Change Mitigation Analysis

    NARCIS (Netherlands)

    Belete, Getachew F.; Voinov, Alexey; Bulavskaya, Tatyana; Niamir, Leila; Dhavala, Kishore

    2016-01-01

    Climate change mitigation analysis requires understanding the causes and identifying the possible alternative actions that could be taken. We linked heterogeneous models that focus on climate, energy, and economy for the purpose of climate change mitigation. The models were originally developed to s

  6. Effects of climate model interdependency on the uncertainty quantification of extreme reinfall projections

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Madsen, H.; Rosbjerg, Dan;

    The inherent uncertainty in climate models is one of the most important uncertainties in climate change impact studies. In recent years, several uncertainty quantification methods based on multi-model ensembles have been suggested. Most of these methods assume that the climate models...... are independent. This study investigates the validity of this assumption and its effects on the estimated probabilistic projections of the changes in the 95% quantile of wet days. The methodology is divided in two main parts. First, the interdependency of the ENSEMBLES RCMs is estimated using the methodology...... developed by Pennell and Reichler (2011). The results show that the projections from the ENSEMBLES RCMs cannot be assumed independent. This result is then used to estimate the uncertainty in climate model projections. A Bayesian approach has been developed using the procedure suggested by Tebaldi et al...

  7. Climate Change Challenges of Managing Quality of Drinking Water: Survey Results from Utilities in California

    Science.gov (United States)

    Ekstrom, J.; Bedsworth, L. W.

    2015-12-01

    Scientists have established that climate change threatens sources of drinking water through many different pathways, both in terms of quantity and quality. Recognizing water utilities will face the brunt of these impacts, this study seeks to better understand the disconnect between the projections produced and the needs of utilities on-the-ground. As part of the first stage of the three-year study, this presentation reports results of a statewide survey evaluating how far along water utilities in California are along in preparing for the projected climate change impacts on water quality, the range in respondents' perspectives (and concerns) of climate change on water quality, and how the state's four-year drought is already presenting treatment challenges. On-going case studies are investigating the needs and capacity of utilities to prepare for and adapt to the projected water quality impacts from increasing extreme events and how or whether climate scientists can help meet these needs.

  8. Using a Global Climate Model in an On-line Climate Change Course

    Science.gov (United States)

    Randle, D. E.; Chandler, M. A.; Sohl, L. E.

    2012-12-01

    Seminars on Science: Climate Change is an on-line, graduate-level teacher professional development course offered by the American Museum of Natural History. It is an intensive 6-week course covering a broad range of global climate topics, from the fundamentals of the climate system, to the causes of climate change, the role of paleoclimate investigations, and a discussion of potential consequences and risks. The instructional method blends essays, videos, textbooks, and linked websites, with required participation in electronic discussion forums that are moderated by an experienced educator and a course scientist. Most weeks include additional assignments. Three of these assignments employ computer models, including two weeks spent working with a full-fledged 3D global climate model (GCM). The global climate modeling environment is supplied through a partnership with Columbia University's Educational Global Climate Modeling Project (EdGCM). The objective is to have participants gain hands-on experience with one of the most important, yet misunderstood, aspects of climate change research. Participants in the course are supplied with a USB drive that includes installers for the software and sample data. The EdGCM software includes a version of NASA's global climate model fitted with a graphical user interface and pre-loaded with several climate change simulations. Step-by-step assignments and video tutorials help walk people through these challenging exercises and the course incorporates a special assignment discussion forum to help with technical problems and questions about the NASA GCM. There are several takeaways from our first year and a half of offering this course, which has become one of the most popular out of the twelve courses offered by the Museum. Participants report a high level of satisfaction in using EdGCM. Some report frustration at the initial steps, but overwhelmingly claim that the assignments are worth the effort. Many of the difficulties that

  9. Modelling mid-Pliocene climate with COSMOS

    Directory of Open Access Journals (Sweden)

    C. Stepanek

    2012-10-01

    Full Text Available In this manuscript we describe the experimental procedure employed at the Alfred Wegener Institute in Germany in the preparation of the simulations for the Pliocene Model Intercomparison Project (PlioMIP. We present a description of the utilized Community Earth System Models (COSMOS, version: COSMOS-landveg r2413, 2009 and document the procedures that we applied to transfer the Pliocene Research, Interpretation and Synoptic Mapping (PRISM Project mid-Pliocene reconstruction into model forcing fields. The model setup and spin-up procedure are described for both the paleo- and preindustrial (PI time slices of PlioMIP experiments 1 and 2, and general results that depict the performance of our model setup for mid-Pliocene conditions are presented. The mid-Pliocene, as simulated with our COSMOS setup and PRISM boundary conditions, is both warmer and wetter in the global mean than the PI. The globally averaged annual mean surface air temperature in the mid-Pliocene standalone atmosphere (fully coupled atmosphere-ocean simulation is 17.35 °C (17.82 °C, which implies a warming of 2.23 °C (3.40 °C relative to the respective PI control simulation.

  10. An improved dust emission model with insights into the global dust cycle's climate sensitivity

    Science.gov (United States)

    Kok, J. F.; Mahowald, N. M.; Albani, S.; Fratini, G.; Gillies, J. A.; Ishizuka, M.; Leys, J. F.; Mikami, M.; Park, M.-S.; Park, S.-U.; Van Pelt, R. S.; Ward, D. S.; Zobeck, T. M.

    2014-03-01

    Simulations of the global dust cycle and its interactions with a changing Earth system are hindered by the empirical nature of dust emission parameterizations in climate models. Here we take a step towards improving global dust cycle simulations by presenting a physically-based dust emission model. The resulting dust flux parameterization depends only on the wind friction speed and the soil's threshold friction speed, and can therefore be readily implemented into climate models. We show that our parameterization's functional form is supported by a compilation of quality-controlled vertical dust flux measurements, and that it better reproduces these measurements than existing parameterizations. Both our theory and measurements indicate that many climate models underestimate the dust flux's sensitivity to soil erodibility. This finding can explain why dust cycle simulations in many models are improved by using an empirical preferential sources function that shifts dust emissions towards the most erodible regions. In fact, implementing our parameterization in a climate model produces even better agreement against aerosol optical depth measurements than simulations that use such a source function. These results indicate that the need to use a source function is at least partially eliminated by the additional physics accounted for by our parameterization. Since soil erodibility is affected by climate changes, our results further suggest that many models have underestimated the climate sensitivity of the global dust cycle.

  11. Climate Model Response from the Geoengineering Model Intercomparison Project (GeoMIP)

    Energy Technology Data Exchange (ETDEWEB)

    Kravitz, Benjamin S.; Caldeira, Ken; Boucher, Olivier; Robock, Alan; Rasch, Philip J.; Alterskjaer, Kari; Bou Karam, Diana; Cole, Jason N.; Curry, Charles L.; Haywood, J.; Irvine, Peter; Ji, Duoying; Jones, A.; Kristjansson, J. E.; Lunt, Daniel; Moore, John; Niemeier, Ulrike; Schmidt, Hauke; Schulz, M.; Singh, Balwinder; Tilmes, S.; Watanabe, Shingo; Yang, Shuting; Yoon, Jin-Ho

    2013-08-09

    Solar geoengineering—deliberate reduction in the amount of solar radiation retained by the Earth—has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwise occur under high CO2 levels but, compared to the preindustrial climate, leaves the tropics cooler (-0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2mmday-1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO2 fertilization, but also in part due to reduced plant heat stress compared to a high CO2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels.

  12. 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

  13. Building Energy Use Modeling at the U.S. State Level Under Climate Change

    Science.gov (United States)

    Zhou, Y.; Eom, J.; Clarke, L.; Kyle, P.

    2012-12-01

    Climate change plays an important role in building energy use for heating and cooling. As global building energy use accounts for as much as about 32% of global final energy consumption in 2005, the impact of climate change on greenhouse gas emissions may also be significant. As long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate impact on building energy use at the sub-national level will offer useful insights into regional energy system planning. In this study, we have developed a detailed building energy model with U.S. 50-state representation, embedded in an integrated assessment framework (Global Change Assessment Model). The climate change impact on heating and cooling demand is measured through estimating heating and cooling degree days (HDD/CDDs) derived from MIT Integrated Global System Model (IGSM) climate data and linking the estimates to the building energy model. Having the model calibrated against historical data at the U.S. state level, we estimated the building energy use in the 21st century at the U.S. state level and analyzed its spatial pattern. We have found that the total building energy use (heating and cooling) in U.S. states is over- or under-estimated without having climate feedback taken into account, and that the difference with and without climate feedback at the state level varies from -25% to 25% in reference scenario and -15% to 10% in climate mitigation scenario. The result not only confirms earlier finding that global warming leads to increased cooling and decreased heating energy use, it also indicates that climate change has a different impact on total building energy use at national and state level, exhibiting large spatial heterogeneity across states (Figure 1). The scale impact in building energy use modeling emphasizes the importance of developing a building energy model that represents socioeconomic development, energy service expansion, and

  14. The GEOS Chemistry Climate Model: Implications of Climate Feedbacks on Ozone Depletion and Recovery

    Science.gov (United States)

    Stolarski, Richard S.; Pawson, Steven; Douglass, Anne R.; Newman, Paul A.; Kawa, S. Randy; Nielsen, J. Eric; Rodriquez, Jose; Strahan, Susan; Oman, Luke; Waugh, Darryn

    2008-01-01

    The Goddard Earth Observing System Chemistry Climate Model (GEOS CCM) has been developed by combining the atmospheric chemistry and transport modules developed over the years at Goddard and the GEOS general circulation model, also developed at Goddard. The first version of the model was used in the CCMVal intercomparison exercises that contributed to the 2006 WMO/UNEP Ozone Assessment. The second version incorporates the updated version of the GCM (GEOS 5) and will be used for the next round of CCMVal evaluations and the 2010 Ozone Assessment. The third version, now under development, incorporates the combined stratosphere and troposphere chemistry package developed under the Global Modeling Initiative (GMI). We will show comparison to past observations that indicate that we represent the ozone trends over the past 30 years. We will also show the basic temperature, composition, and dynamical structure of the simulations. We will further show projections into the future. We will show results from an ensemble of transient and time-slice simulations, including simulations with fixed 1960 chlorine, simulations with a best guess scenario (Al), and simulations with extremely high chlorine loadings. We will discuss planned extensions of the model to include emission-based boundary conditions for both anthropogenic and biogenic compounds.

  15. Observations that polar climate modelers use and want

    Science.gov (United States)

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

    2012-12-01

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

  16. Examining the Fidelity of Climate model via Shadowing Time

    Science.gov (United States)

    Du, H.; Smith, L. A.

    2015-12-01

    Fully fledged climate models provide the best available simulations for reflecting the future, yet we have scant insight into their fidelity, in particular as to the duration into the future at which the real world should be expected to evolve in a manner today's models cannot foresee. We know now that our best available models are not adequate for many sought after purposes. To throw some light on the maximum fidelity expected from a given generation of models, and thereby aid both policy making and model development, we can test the weaknesses of a model as a dynamical system to get an informed idea of its potential applicability at various lead times. Shadowing times reflect the duration on which a GCM reflects the observations; extracting the shortcomings of the model which limit shadowing times allows informed speculation regarding the fidelity of the model in the future. More specifically, the relevant phenomena limiting model fidelity can be learned by identifying the reasons models cannot shadow; the time scales on which feedbacks on the system (which are not active in the model) are likely to result in model irrelevance can be discerned. The methodology is developed in the "low dimensional laboratory" of relatively simple dynamical systems, for example Lorenz 95 systems. The results are presented in Lorenz 95 systems, high dimensional fluid dynamical simulations of rotating annulus and GCMs. There are severe limits on the light shadowing experiments can shine on GCM predictions. Never the less, they appear to be one of the brightest lights we can shine to illuminate the likely fidelity of GCM extrapolations into the future.

  17. Impacts of Sea Surface Salinity Bias Correction on North Atlantic Ocean Circulation and Climate Variability in the Kiel Climate Model

    Science.gov (United States)

    Park, Taewook; Park, Wonsun; Latif, Mojib

    2016-04-01

    We investigated impacts of correcting North Atlantic sea surface salinity (SSS) biases on the ocean circulation of the North Atlantic and on North Atlantic sector mean climate and climate variability in the Kiel Climate Model (KCM). Bias reduction was achieved by applying a freshwater flux correction over the North Atlantic to the model. The quality of simulating the mean circulation of the North Atlantic Ocean, North Atlantic sector mean climate and decadal variability is greatly enhanced in the freshwater flux-corrected integration which, by definition, depicts relatively small North Atlantic SSS biases. In particular, a large reduction in the North Atlantic cold sea surface temperature (SST) bias is observed and a more realistic Atlantic Multidecadal Variability (AMV) simulated. Improvements relative to the non-flux corrected integration also comprise a more realistic representation of deep convection sites, sea ice, gyre circulation and Atlantic Meridional Overturning Circulation (AMOC). The results suggest that simulations of North Atlantic sector mean climate and decadal variability could strongly benefit from alleviating sea surface salinity biases in the North Atlantic, which may enhance the skill of decadal predictions in that region.

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

    Science.gov (United States)

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

    2013-01-01

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

  19. 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.

  20. Using an ensemble of regional climate models to assess climate change impacts on water scarcity in European river basins.

    Science.gov (United States)

    Gampe, David; Nikulin, Grigory; Ludwig, Ralf

    2016-12-15

    Climate change will likely increase pressure on the water balances of Mediterranean basins due to decreasing precipitation and rising temperatures. To overcome the issue of data scarcity the hydrological relevant variables total runoff, surface evaporation, precipitation and air temperature are taken from climate model simulations. The ensemble applied in this study consists of 22 simulations, derived from different combinations of four General Circulation Models (GCMs) forcing different Regional Climate Models (RCMs) and two Representative Concentration Pathways (RCPs) at ~12km horizontal resolution provided through the EURO-CORDEX initiative. Four river basins (Adige, Ebro, Evrotas and Sava) are selected and climate change signals for the future period 2035-2065 as compared to the reference period 1981-2010 are investigated. Decreased runoff and evaporation indicate increased water scarcity over the Ebro and the Evrotas, as well as the southern parts of the Adige and the Sava, resulting from a temperature increase of 1-3° and precipitation decrease of up to 30%. Most severe changes are projected for the summer months indicating further pressure on the river basins already at least partly characterized by flow intermittency. The widely used Falkenmark indicator is presented and confirms this tendency and shows the necessity for spatially distributed analysis and high resolution projections. Related uncertainties are addressed by the means of a variance decomposition and model agreement to determine the robustness of the projections. The study highlights the importance of high resolution climate projections and represents a feasible approach to assess climate impacts on water scarcity also in regions that suffer from data scarcity.

  1. Multi-wheat-model ensemble responses to interannual climate variability

    NARCIS (Netherlands)

    Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos; Basso, Bruno; Bertuzzi, Patrick; Biernath, Christian; Brisson, Nadine; Challinor, Andrew J.; Doltra, Jordi; Gayler, Sebastian; Goldberg, Richard; Grant, Robert F.; Heng, Lee; Hooker, Josh; Hunt, Leslie A.; Ingwersen, Joachim; Izaurralde, Roberto C.; Kersebaum, Kurt Christian; Kumar, Soora Naresh; Müller, Christoph; Nendel, Claas; O'Leary, Garry; Olesen, Jørgen E.; Osborne, Tom M.; Palosuo, Taru; Priesack, Eckart; Ripoche, Dominique; Rötter, Reimund P.; Semenov, Mikhail A.; Shcherbak, Iurii; Steduto, Pasquale; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Travasso, Maria; Waha, Katharina; Wallach, Daniel; White, Jeffrey W.; Wolf, Joost

    2016-01-01

    We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981-2010 grain yield, and

  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

    The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project

  3. Drought Duration Biases in Current Global Climate Models

    Science.gov (United States)

    Moon, Heewon; Gudmundsson, Lukas; Seneviratne, Sonia

    2016-04-01

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

  4. Cuckoo Search Optimization for Reduction of a Greenhouse Climate Model

    Directory of Open Access Journals (Sweden)

    Hasni Abdelhafid

    2016-07-01

    Full Text Available Greenhouse climate and crop models and specially reduced models are necessary for bettering environmental management and control ability. In this paper, we present a new metaheuristic method, called Cuckoo Search (CS algorithm, established on the life of a bird family for selecting the parameters of a reduced model which optimizes their choice by minimizing a cost function. The reduced model was already developed for control purposes and published in the literature. The proposed models target at simulating and predicting the greenhouse environment. [?]. This study focuses on the dynamical behaviors of the inside air temperature and pressure using ventilation. Some experimental results are used for model validation, the greenhouse being automated with actuators and sensors connected to a greenhouse control system on the cuckoo search methods to determine the best set of parameters allowing for the convergence of a criteria based on the difference between calculated and observed state variables (inside air temperature and water vapour pressure content. The results shown that the tested Cuckoo Search algorithm allows for a faster convergence towards the optimal solution than classical optimization methods.

  5. SR-Site groundwater flow modelling methodology, setup and results

    Energy Technology Data Exchange (ETDEWEB)

    Selroos, Jan-Olof (Swedish Nuclear Fuel and Waste Management Co., Stockholm (Sweden)); Follin, Sven (SF GeoLogic AB, Taeby (Sweden))

    2010-12-15

    As a part of the license application for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken three groundwater flow modelling studies. These are performed within the SR-Site project and represent time periods with different climate conditions. The simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. Three time periods are addressed; the Excavation and operational phases, the Initial period of temperate climate after closure, and the Remaining part of the reference glacial cycle. The present report is a synthesis of the background reports describing the modelling methodology, setup, and results. It is the primary reference for the conclusions drawn in a SR-Site specific context concerning groundwater flow during the three climate periods. These conclusions are not necessarily provided explicitly in the background reports, but are based on the results provided in these reports. The main results and comparisons presented in the present report are summarised in the SR-Site Main report.

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    model, HIRHAM. The physics of the coupling is formulated using an energy-based SVAT (land surface) model while the numerical coupling exploits the OpenMI modelling interface. First, some investigations of the applicability of the SVAT model are presented, including our ability to characterise...... distributed parameters using satellite remote sensing. Secondly, field data are used to investigate the effects of model resolution and parameter scales for use in a coupled model. Finally, the development of the fully coupled climate-hydrology model is described and some of the challenges associated...

  7. Modeling Climate Change Impacts on the US Agricultural Exports

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yu-quan; CAI Yong-xia; Beach Robert H; McCARL Bruce A

    2014-01-01

    Climate change is expected to have substantial effects on agricultural productivity worldwide. However, these impacts will differ across commodities, locations and time periods. As a result, landowners will see changes in relative returns that are likely to induce modiifcations in production practices and land allocation. In addition, regional variations in impacts can alter relative competitiveness across countries and lead to adjustments in international trade patterns. Thus in climate change impact studies it is likely useful to account for worldwide productivity effects. In this study, we investigate the implications of considering rest of world climate impacts on projections of the US agricultural exports. We chose to focus on the US because it is one of the largest agricultural exporters. To conduct our analyses, we consider four alternative climate scenarios, both with and without rest of world climate change impacts. Our results show that considering/ignoring rest of world climate impacts causes signiifcant changes in the US production and exports projections. Thus we feel climate change impact studies should account not only for climate impacts in the country of focus but also on productivity in the rest of the world in order to capture effects on commodity markets and trade potential.

  8. 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...

  9. Local control on precipitation in a fully coupled climate-hydrology model.

    Science.gov (United States)

    Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

    2016-03-10

    The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

  10. 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.

  11. Correction of biased climate simulated by biased physics through parameter estimation in an intermediate coupled model

    Science.gov (United States)

    Zhang, Xuefeng; Zhang, Shaoqing; Liu, Zhengyu; Wu, Xinrong; Han, Guijun

    2016-09-01

    Imperfect physical parameterization schemes are an important source of model bias in a coupled model and adversely impact the performance of model simulation. With a coupled ocean-atmosphere-land model of intermediate complexity, the impact of imperfect parameter estimation on model simulation with biased physics has been studied. Here, the biased physics is induced by using different outgoing longwave radiation schemes in the assimilation and "truth" models. To mitigate model bias, the parameters employed in the biased longwave radiation scheme are optimized using three different methods: least-squares parameter fitting (LSPF), single-valued parameter estimation and geography-dependent parameter optimization (GPO), the last two of which belong to the coupled model parameter estimation (CMPE) method. While the traditional LSPF method is able to improve the performance of coupled model simulations, the optimized parameter values from the CMPE, which uses the coupled model dynamics to project observational information onto the parameters, further reduce the bias of the simulated climate arising from biased physics. Further, parameters estimated by the GPO method can properly capture the climate-scale signal to improve the simulation of climate variability. These results suggest that the physical parameter estimation via the CMPE scheme is an effective approach to restrain the model climate drift during decadal climate predictions using coupled general circulation models.

  12. 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.

  13. Simulation of black carbon in snow and its climate impact in the Canadian Global Climate Model

    Science.gov (United States)

    Namazi, M.; von Salzen, K.; Cole, J. N. S.

    2015-09-01

    A new physically based parameterisation of black carbon (BC) in snow was developed and implemented in the Canadian Atmospheric Global Climate Model (CanAM4.2). Simulated BC snow mixing ratios and BC snow radiative forcings are in good agreement with measurements and results from other models. Simulations with the improved model yield considerable trends in regional BC concentrations in snow and BC snow radiative forcings during the time period from 1950-1959 to 2000-2009. Increases in radiative forcings for Asia and decreases for Europe and North America are found to be associated with changes in BC emissions. Additional sensitivity simulations were performed in order to study the impact of BC emission changes between 1950-1959 and 2000-2009 on surface albedo, snow cover fraction, and surface air temperature. Results from these simulations indicate that impacts of BC emission changes on snow albedos between these 2 decades are small and not significant. Overall, changes in BC concentrations in snow have much smaller impacts on the cryosphere than the net warming surface air temperatures during the second half of the 20th century.

  14. Simulation of black carbon in snow and its climate impact in the Canadian Global Climate Model

    Directory of Open Access Journals (Sweden)

    M. Namazi

    2015-07-01

    Full Text Available A new physically-based parameterization of black carbon (BC in snow was developed and implemented in the Canadian Atmospheric Global Climate Model (CanAM4.2. Simulated BC snow mixing ratios and BC snow radiative forcings are in good agreement with measurements and results from other models. Simulations with the improved model yield considerable trends in regional BC concentrations in snow and BC snow radiative forcings during the time period from 1950–1959 to 2000–2009. Increases in radiative forcings for Asia and decreases for Europe and North America are found to be associated with changes in BC emissions. Additional sensitivity simulations were performed in order to study the impact of BC emission changes between 1950–1959 and 2000–2009 on surface albedo, snow cover fraction, and surface air temperature. Results from these simulations indicate that impacts of BC emission changes on snow albedos between these two decades are small and not significant. Overall, changes in BC concentrations in snow have much smaller impacts on the cryosphere than the net warming surface air temperatures during the second half of the 20th century.

  15. Moisture Flux Convergence in Regional and Global Climate Models: Implications for Droughts in the Southwestern United States Under Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Yanhong; Leung, Lai-Yung R.; Salathe, E.; Dominguez, Francina; Nijssen, Bart; Lettenmaier, D. P.

    2012-05-10

    The water cycle of the southwestern United States (SW) is dominated by winter storms that maintain a positive annual net precipitation. Analysis of the control and future climate from four pairs of regional and global climate models (RCMs and GCMs) shows that the RCMs simulate a higher fraction of transient eddy moisture fluxes because the hydrodynamic instabilities associated with flow over complex terrain are better resolved. Under global warming, this enables the RCMs to capture the response of transient eddies to increased atmospheric stability that allows more moisture to converge on the windward side of the mountains by blocking. As a result, RCMs simulate enhanced transient eddy moisture convergence in the SW compared to GCMs, although both robustly simulate drying due to enhanced moisture divergence by the divergent mean flow in a warmer climate. This enhanced convergence leads to reduced susceptibility to hydrological change in the RCMs compared to GCMs.

  16. Integrated Modelling of Climate Change Impacts in an Irrigated, Semi-arid Catchment

    Science.gov (United States)

    Haslauer, C. P.; von Gunten, D.; Wöhling, T.; Rudolph, D. L.; Cirpka, O. A.

    2015-12-01

    Predicting the impacts of climate change on hydrological processes is a central challenge for water management. Commonly, studies on climate-change effects focus on surface flow and feed-backs between surface and subsurface flows are neglected frequently. Furthermore, changes in hydrological processes are generally not distributed realistically. Integrated catchment models, based on partial-differential-equations, have the potential of overcoming these difficulties. However, these models are complicated to use in realistic settings, notably because of their long simulation time. In this presentation, we demonstrate a successful application of an integrated catchment model (HydroGeoSphere) in a semi-arid catchment in north-east Spain. The study area recently underwent a transition to irrigated agriculture, which is reflected in our model evaluations conducted under varying irrigation conditions. To accelerate model calibration, we developed a novel calibration method based on a hierarchy of computational grids. The climate scenarios for the region are based on four regional climate models, which are downscaled using a weather generator. These scenarios are used to estimate climate change impacts on hydrologic parameters in different irrigation settings. The effects of climate change strongly depend on the presence of irrigation. Water table depth and low flows are more sensitive to climate change when irrigation is present, while peak flows exhibit a more pronounced response to climate in scenarios without irrigation. In addition to the climatic means, we examined the impacts of changes in drought conditions. We compare the outcomes of droughts predicted by our hydrological model with simpler approaches based on drought indices. We show that drought indices oversimplify future hydrological impacts of droughts and can result in biased estimation of drought impacts, especially if drought indices do not take temperature changes into account.

  17. Spatial-temporal assessment of climate model drifts

    Science.gov (United States)

    Zanchettin, Davide; Woldeyes Arisido, Maeregu; Gaetan, Carlo; Rubino, Angelo

    2016-04-01

    Decadal climate forecasts with full-field initialized coupled climate models are affected by a growing error signal that develops due to the adjustment of the simulations from the assimilated state consistent with observations to the state consistent with the biased model's climatology. Sea-surface temperature (SST) drifts and biases are a major concern due to the central role of SST properties for the dynamical coupling between the atmosphere and the ocean, and for the associated variability. Therefore, strong SST drifts complicate the initialization and assessment of decadal climate prediction experiments, and can be detrimental for their overall quality. We propose a dynamic linear model based on a state-space approach and developed within a Bayesian hierarchical framework for probabilistic assessment of spatial and temporal characteristics of SST drifts in ensemble climate simulations. The state-space approach uses unobservable state variables to directly model the processes generating the observed variability. The statistical model is based on a sequential definition of the process having a conditional dependency only on the previous time step, which therefore corresponds to the Kalman filter formulas. In our formulation, the statistical model distinguishes between seasonal and longer-term drift components, and between large-scale and local drifts. We apply the Bayesian method to make inferences on the variance components of the Gaussian errors in both the observation and system equations of the state-space model. To this purpose, we draw samples from their posterior distributions using a Monte Carlo Markov Chain simulation technique with a Gibbs sampler. In this contribution we illustrate a first application of the model using the MiKlip prototype system for decadal climate predictions. We focus on the tropical Atlantic Ocean - a region where climate models are typically affected by a severe warm SST bias - to demonstrate how our approach allows for a more

  18. 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

  19. Uncertainty vs. learning in climate policy: Some classical results and new directions

    Energy Technology Data Exchange (ETDEWEB)

    Lange, A. [Univ. of Maryland (United States); Treich, N. [Univ. of Toulouse (France)

    2007-07-01

    Climate policy decisions today have to be made under substantial uncertainty: the impact of accumulating greenhouse gases in the atmosphere is not perfectly known, the future economic and social consequences of climate change, in particular the valuation of possible damages, are uncertain. However, learning will change the basis of making future decisions on abatement policies. These important issues of uncertainty and learning are often presented in a colloquial sense. Two opposing effects are typically put forward: First, uncertainty about future climate damage, which is often associated with the possibility of a catastrophic scenario is said to give a premium to slow down global warming and therefore to increase abatement efforts today. Second learning opportunities will reduce scientific undertainty about climate damage over time. This is often used as an argument to postpone abatement efforts until new information is received. The effects of uncertainty and learning on the optimal design of current climate policy are still much debated both in the academic and the political arena. In this paper, the authors study and contrast the effect of uncertainty and learning in a two-decision model that encompasses most existing microeconomics models of climate change. They first consider the common expected utility framework: While uncertainty has generally no or a negative effect on welfare, learning has always a positive, and thus opposite, effect. The effects of both uncertainty and learning on decisions are less clear. Neither uncertainty nor learning can be used as an argument to increase or reduce emissions today, independently on the degree of risk aversion of the decision-marker and on the nature of irreversibility constraints. The authors then deviate from the expected utility framework and consider a model with ambiguity aversion. The model accounts well for situations of imprecise or multiple probability distributions, as present in the context of climate

  20. Considerations for building climate-based species distribution models

    Science.gov (United States)

    Bucklin, David N; Basille, Mathieu; Romanach, 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.

  1. The large influence of climate model bias on terrestrial carbon cycle simulations

    Science.gov (United States)

    Ahlström, Anders; Schurgers, Guy; Smith, Benjamin

    2017-01-01

    Global vegetation models and terrestrial carbon cycle models are widely used for projecting the carbon balance of terrestrial ecosystems. Ensembles of such models show a large spread in carbon balance predictions, ranging from a large uptake to a release of carbon by the terrestrial biosphere, constituting a large uncertainty in the associated feedback to atmospheric CO2 concentrations under global climate change. Errors and biases that may contribute to such uncertainty include ecosystem model structure, parameters and forcing by climate output from general circulation models (GCMs) or the atmospheric components of Earth system models (ESMs), e.g. as prepared for use in IPCC climate change assessments. The relative importance of these contributing factors to the overall uncertainty in carbon cycle projections is not well characterised. Here we investigate the role of climate model-derived biases by forcing a single global ecosystem-carbon cycle model, with original climate outputs from 15 ESMs and GCMs from the CMIP5 ensemble. We show that variation among the resulting ensemble of present and future carbon cycle simulations propagates from biases in annual means of temperature, precipitation and incoming shortwave radiation. Future changes in carbon pools, and thus land carbon sink trends, are also affected by climate biases, although to a smaller extent than the absolute size of carbon pools. Our results suggest that climate biases could be responsible for a considerable fraction of the large uncertainties in ESM simulations of land carbon fluxes and pools, amounting to about 40% of the range reported for ESMs. We conclude that climate bias-induced uncertainties must be decreased to make accurate coupled atmosphere-carbon cycle projections.

  2. Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

    Science.gov (United States)

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

    2007-12-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

  3. The influence of HBV model calibration on flood predictions for future climate

    Science.gov (United States)

    Osuch, Marzena; Romanowicz, Renata

    2014-05-01

    The temporal variability of HBV rainfall-runoff model parameters was tested to address the influence of climate characteristics on the values of model optimal parameters. HBV is a conceptual model with a physically-based structure that takes into account soil moisture, snow-melt and dynamic runoff components. The model parameters were optimized by the DEGL method (Differential Evolution with Global and Local neighbours) for a set of catchments located in Poland. The methodology consisted of the calibration and cross-validation of the HBV models on a series of five-year periods within a moving window. The optimal parameter values show large temporal variability and dependence on climatic conditions described by the mean and standard deviation of precipitation, air temperature and PET. Derived regressions models between parameters and climatic indices were statistically significant at the 0.05 level. The set of model optimal values was applied to simulate future flows in a changed climate. We used the precipitation and temperature series from 6 RCM/GCM models for 2071-2100 following the A1B climate change scenario. The climatic variables were obtained from the KLIMADA project. The resulting flow series for the future climate scenario were used to derive flow indices, including the flood quantiles. Results indicate a large influence of climatic variability on flow indices. This work was partly supported by the project "Stochastic flood forecasting system (The River Vistula reach from Zawichost to Warsaw)" carried out by the Institute of Geophysics, Polish Academy of Sciences by order of the National Science Centre (contract No. 2011/01/B/ST10/06866). The rainfall and flow data were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

  4. Reconstructing glacier-based climates of LGM Europe and Russia – Part 2: A dataset of LGM climates derived from degree-day modelling of palaeo glaciers

    Directory of Open Access Journals (Sweden)

    A. J. Payne

    2007-10-01

    Full Text Available The study of European and Russian Quaternary glacial-geological evidence during the last 15 years has generated sufficient to data to use former glacial extent as a proxy for Last Glacial Maximum (LGM climate at a continental scale. Utilisation of such data is relevant for two reasons. First, continental to global scale proxy reconstructions of past climate are an important tool in the assessment of retrospective general circulation model (GCM simulations. Second, the development of a multi-proxy approach will result in a more robust proxy based climate signal. A new and independent dataset of 36 LGM climate estimates derived from European and Russian mountain regions is presented in this paper. A simple glacier-climate model was used to establish the optimum LGM climate conditions for each region from a suite of over 4000 model climates using the principle of zero cumulative mass balance. Clear regional trends are present in the reconstructed LGM climates; temperature anomalies north of the Alps are 2°C and 5°C larger than those in the western and eastern Mediterranean, respectively. In Russia the model results suggest that both the Arctic Urals and Puterana Plateau were probably glaciated by small mountain glaciers during the LGM.

  5. Climate change impacts on the vegetation carbon cycle of the Iberian Peninsula—Intercomparison of CMIP5 results

    Science.gov (United States)

    Aparício, Sara; Carvalhais, Nuno; Seixas, Júlia

    2015-04-01

    The vulnerability of a water-limited region like the Iberian Peninsula (IP) to climate changes drives a great concern and interest in understanding its impacts on the carbon cycle, namely, in terms of biomass production. This study assesses the effects of climate change and rising CO2 on forest growth, carbon sequestration, and water-use efficiency on the IP by late 21st century using 12 models from the CMIP5 project (Coupled Model Intercomparison Project Phase 5). We find a strong agreement among the models under representative concentration pathway 4.5 (RCP4.5) scenario, mostly regarding projected forest growth and increased primary production (13, 9% of gross primary production (GPP) increase projected by the models ensemble). Under RCP8.5 scenario, the results are less conclusive, as seven models project both GPP and net primary production to increase (up to 83% and 69%, respectively), while the remaining four models project the IP as a potential carbon source by late century. Divergences in carbon mass in wood predictions could be attributed to model structures, such as the N cycle, land model component, land cover data and parameterization, and distinct clusters of Earth System Models (ESMs). ESMs divergences in carbon feedbacks are likely being highly impacted by parameterization divergences and susceptibility to climate change and CO2 fertilization effect. Despite projected rainfall reductions, we observe a strong agreement between models regarding the increase of water-use efficiency (by 21% and 34%) under RCP4.5 and RCP8.5, respectively. Results suggest that rising CO2 has the potential to partially alleviate the adverse effects of drought.

  6. Significance of hydrological model choice and land use changes when doing climate change impact assessment

    Science.gov (United States)

    Bjørnholt Karlsson, Ida; Obel Sonnenborg, Torben; Refsgaard, Jens Christian; Høgh Jensen, Karsten

    2014-05-01

    Uncertainty in impact studies arises both from Global Climate Models (GCM), emission projections, statistical downscaling, Regional Climate Models (RCM), hydrological models and calibration techniques (Refsgaard et al. 2013). Some of these uncertainties have been evaluated several times in the literature; however few studies have investigated the effect of hydrological model choice on the assessment results (Boorman & Sefton 1997; Jiang et al. 2007; Bastola et al. 2011). These studies have found that model choice results in large differences, up to 70%, in the predicted discharge changes depending on the climate input. The objective of the study is to investigate the impact of climate change on hydrology of the Odense catchment, Denmark both in response to (a) different climate projections (GCM-RCM combinations); (b) different hydrological models and (c) different land use scenarios. This includes: 1. Separation of the climate model signal; the hydrological model signal and the land use signal 2. How do the different hydrological components react under different climate and land use conditions for the different models 3. What land use scenario seems to provide the best adaptation for the challenges of the different future climate change scenarios from a hydrological perspective? Four climate models from the ENSEMBLES project (Hewitt & Griggs 2004): ECHAM5 - HIRHAM5, ECHAM5 - RCA3, ARPEGE - RM5.1 and HadCM3 - HadRM3 are used, assessing the climate change impact in three periods: 1991-2010 (present), 2041-2060 (near future) and 2081-2100 (far future). The four climate models are used in combination with three hydrological models with different conceptual layout: NAM, SWAT and MIKE SHE. Bastola, S., C. Murphy and J. Sweeney (2011). "The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments." Advances in Water Resources 34: 562-576. Boorman, D. B. and C. E. M. Sefton (1997). "Recognising the uncertainty in the

  7. Effects of climate model interdependency on the uncertainty quantification of extreme rainfall projections

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Madsen, H.; Rosbjerg, Dan;

    Changes in rainfall extremes under climate change conditions are subject to numerous uncertainties. One of the most important uncertainties arises from the inherent uncertainty in climate models. In recent years, many efforts have been made in creating large multi-model ensembles of both Regional...... Climate Models (RCMs) and General Circulation Models (GCMs). These multi-model ensembles provide the information needed to estimate probabilistic climate change projections. Several probabilistic methods have been suggested. One common assumption in most of these methods is that the climate models...... of accounting for the climate model interdependency when estimating the uncertainty of climate change projections....

  8. Climate model validation and selection for hydrological applications in representative Mediterranean catchments

    Directory of Open Access Journals (Sweden)

    R. Deidda

    2013-07-01

    Full Text Available This paper discusses the relative performance of several climate models in providing reliable forcing for hydrological modeling in six representative catchments in the Mediterranean region. We consider 14 Regional Climate Models (RCMs, from the EU-FP6 ENSEMBLES project, run for the A1B emission scenario on a common 0.22-degree (about 24 km rotated grid over Europe and the Mediterranean. In the validation period (1951 to 2010 we consider daily precipitation and surface temperatures from the E-OBS dataset, available from the ENSEMBLES project and the data providers in the ECA&D project. Our primary objective is to rank the 14 RCMs for each catchment and select the four best performing ones to use as common forcing for hydrological models in the six Mediterranean basins considered in the EU-FP7 CLIMB project. Using a common suite of 4 RCMs for all studied catchments reduces the (epistemic uncertainty when evaluating trends and climate change impacts in the XXI century. We present and discuss the validation setting, as well as the obtained results and, to some detail, the difficulties we experienced when processing the data. In doing so we also provide useful information and hint for an audience of researchers not directly involved in climate modeling, but interested in the use of climate model outputs for hydrological modeling and, more in general, climate change impact studies in the Mediterranean.

  9. Climate Change Impacts on US Water Quality Using Two Models: HAWQS and US Basins

    Directory of Open Access Journals (Sweden)

    Charles Fant

    2017-02-01

    Full Text Available Climate change and freshwater quality are well-linked. Changes in climate result in changes in streamflow and rising water temperatures, which impact biochemical reaction rates and increase stratification in lakes and reservoirs. Using two water quality modeling systems (the Hydrologic and Water Quality System; HAWQS and US Basins, five climate models, and two greenhouse gas (GHG mitigation policies, we assess future water quality in the continental U.S. to 2100 considering four water quality parameters: water temperature, dissolved oxygen, total nitrogen, and total phosphorus. Once these parameters are aggregated into a water quality index, we find that, while the water quality models differ under the baseline, there is more agreement between future projections. In addition, we find that the difference in national-scale economic benefits across climate models is generally larger than the difference between the two water quality models. Both water quality models find that water quality will more likely worsen in the East than in the West. Under the business-as-usual emissions scenario, we find that climate change is likely to cause economic impacts ranging from 1.2 to 2.3 (2005 billion USD/year in 2050 and 2.7 to 4.8 in 2090 across all climate and water quality models.

  10. Regional climate models' performance in representing precipitation and temperature over selected Mediterranean areas

    Directory of Open Access Journals (Sweden)

    R. Deidda

    2013-12-01

    Full Text Available This paper discusses the relative performance of several climate models in providing reliable forcing for hydrological modeling in six representative catchments in the Mediterranean region. We consider 14 Regional Climate Models (RCMs, from the EU-FP6 ENSEMBLES project, run for the A1B emission scenario on a common 0.22° (about 24 km rotated grid over Europe and the Mediterranean region. In the validation period (1951 to 2010 we consider daily precipitation and surface temperatures from the observed data fields (E-OBS data set, available from the ENSEMBLES project and the data providers in the ECA&D project. Our primary objective is to rank the 14 RCMs for each catchment and select the four best-performing ones to use as common forcing for hydrological models in the six Mediterranean basins considered in the EU-FP7 CLIMB project. Using a common suite of four RCMs for all studied catchments reduces the (epistemic uncertainty when evaluating trends and climate change impacts in the 21st century. We present and discuss the validation setting, as well as the obtained results and, in some detail, the difficulties we experienced when processing the data. In doing so we also provide useful information and advice for researchers not directly involved in climate modeling, but interested in the use of climate model outputs for hydrological modeling and, more generally, climate change impact studies in the Mediterranean region.

  11. Contributions to Future Stratospheric Climate Change: An Idealized Chemistry-Climate Model Sensitivity Study

    Science.gov (United States)

    Hurwitz, M. M.; Braesicke, P.; Pyle, J. A.

    2010-01-01

    Within the framework of an idealized model sensitivity study, three of the main contributors to future stratospheric climate change are evaluated: increases in greenhouse gas concentrations, ozone recovery, and changing sea surface temperatures (SSTs). These three contributors are explored in combination and separately, to test the interactions between ozone and climate; the linearity of their contributions to stratospheric climate change is also assessed. In a simplified chemistry-climate model, stratospheric global mean temperature is most sensitive to CO2 doubling, followed by ozone depletion, then by increased SSTs. At polar latitudes, the Northern Hemisphere (NH) stratosphere is more sensitive to changes in CO2, SSTs and O3 than is the Southern Hemisphere (SH); the opposing responses to ozone depletion under low or high background CO2 concentrations, as seen with present-day SSTs, are much weaker and are not statistically significant under enhanced SSTs. Consistent with previous studies, the strength of the Brewer-Dobson circulation is found to increase in an idealized future climate; SSTs contribute most to this increase in the upper troposphere/lower stratosphere (UT/LS) region, while CO2 and ozone changes contribute most in the stratosphere and mesosphere.

  12. A review on regional convection permitting climate modeling

    Science.gov (United States)

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

    2016-04-01

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

  13. A Review on Evaluation Methods of Climate Modeling

    Institute of Scientific and Technical Information of China (English)

    ZHAO; Zong-Ci; LUO; Yong; HUANG; Jian-Bin

    2013-01-01

    There is scientific progress in the evaluation methods of recent Earth system models(ESMs).Methods range from single variable to multi-variables,multi-processes,multi-phenomena quantitative evaluations in five layers(spheres)of the Earth system,from climatic mean assessment to climate change(such as trends,periodicity,interdecadal variability),extreme values,abnormal characters and quantitative evaluations of phenomena,from qualitative assessment to quantitative calculation of reliability and uncertainty for model simulations.Researchers started considering independence and similarity between models in multi-model use,as well as the quantitative evaluation of climate prediction and projection efect and the quantitative uncertainty contribution analysis.In this manuscript,the simulations and projections by both CMIP5 and CMIP3 that have been published after 2007 are reviewed and summarized.

  14. Climate-based risk models for Fasciola hepatica in Colombia

    Directory of Open Access Journals (Sweden)

    Natalia Valencia-López

    2012-09-01

    Full Text Available A predictive Fasciola hepatica model, based on the growing degree day-water budget (GDD-WB concept and the known biological requirements of the parasite, was developed within a geographical information system (GIS in Colombia. Climate-based forecast index (CFI values were calculated and represented in a national-scale, climate grid (18 x 18 km using ArcGIS 9.3. A mask overlay was used to exclude unsuitable areas where mean annual temperature exceeded 25 °C, the upper threshold for development and propagation of the F. hepatica life cycle. The model was then validated and further developed by studies limited to one department in northwest Colombia. F. hepatica prevalence data was obtained from a 2008-2010 survey in 10 municipalities of 6,016 dairy cattle at 673 herd study sites, for which global positioning system coordinates were recorded. The CFI map results were compared to F. hepatica environmental risk models for the survey data points that had over 5% prevalence (231 of the 673 sites at the 1 km2 scale using two independent approaches: (i a GIS map query based on satellite data parameters including elevation, enhanced vegetation index and land surface temperature day-night difference; and (ii an ecological niche model (MaxEnt, for which geographic point coordinates of F. hepatica survey farms were used with BioClim data as environmental variables to develop a probability map. The predicted risk pattern of both approaches was similar to that seen in the forecast index grid. The temporal risk, evaluated by the monthly CFIs and a daily GDD-WB forecast software for 2007 and 2008, revealed a major July-August to January transmission period with considerable inter-annual differences.

  15. 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...

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

    Science.gov (United States)

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

    2016-09-01

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

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

    Directory of Open Access Journals (Sweden)

    W. Yang

    2015-01-01

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

  18. Ensemble data assimilation in the Whole Atmosphere Community Climate Model

    Science.gov (United States)

    Pedatella, N. M.; Raeder, K.; Anderson, J. L.; Liu, H.-L.

    2014-08-01

    We present results pertaining to the assimilation of real lower, middle, and upper atmosphere observations in the Whole Atmosphere Community Climate Model (WACCM) using the Data Assimilation Research Testbed (DART) ensemble adjustment Kalman filter. The ability to assimilate lower atmosphere observations of aircraft and radiosonde temperature and winds, satellite drift winds, and Constellation Observing System for Meteorology, Ionosphere, and Climate refractivity along with middle/upper atmosphere temperature observations from SABER and Aura MLS is demonstrated. The WACCM+DART data assimilation system is shown to be able to reproduce the salient features, and variability, of the troposphere present in the National Centers for Environmental Prediction/National Center for Atmospheric Research Re-Analysis. In the mesosphere, the fit of WACCM+DART to observations is found to be slightly worse when only lower atmosphere observations are assimilated compared to a control experiment that is reflective of the model climatological variability. This differs from previous results which found that assimilation of lower atmosphere observations improves the fit to mesospheric observations. This discrepancy is attributed to the fact that due to the gravity wave drag parameterizations, the model climatology differs significantly from the observations in the mesosphere, and this is not corrected by the assimilation of lower atmosphere observations. The fit of WACCM+DART to mesospheric observations is, however, significantly improved compared to the control experiment when middle/upper atmosphere observations are assimilated. We find that assimilating SABER observations reduces the root-mean-square error and bias of WACCM+DART relative to the independent Aura MLS observations by ˜50%, demonstrating that assimilation of middle/upper atmosphere observations is essential for accurate specification of the mesosphere and lower thermosphere region in WACCM+DART. Last, we demonstrate that

  19. Climate change hotspots over South America: from CMIP3 to CMIP5 multi-model datasets

    Science.gov (United States)

    Torres, Roger Rodrigues; Marengo, Jose Antonio

    2014-08-01

    This study identifies possible hotspots of climate change in South America through an examination of the spatial pattern of the Regional Climate Change Index (RCCI) over the region by the end of the twenty-first century. The RCCI is a qualitative index that can synthesize a large number of climate model projections, and it is suitable for identifying those regions where climate change could be more pronounced in a warmer climate. The reliability and uncertainties of the results are evaluated by using numerous state-of-the-art general circulation models (GCMs) and forcing scenarios from the Coupled Model Intercomparison Project phases 3 and 5. The results show that southern Amazonia and the central-western region and western portion of Minas Gerais state in Brazil are persistent climate change hotspots through different forcing scenarios and GCM datasets. In general, as the scenarios vary from low- to high-level forcing, the area of high values of RCCI increase and the magnitude intensify from central-western and southeast Brazil to northwest South America. In general, the climatic hotspots identified in this study are characterized by an increase of mean surface air temperature, mainly in the austral winter; by an increase of interannual temperature variability, predominantly in the austral summer; and by a change in the mean and interannual variability of precipitation during the austral winter.

  20. 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.

  1. Climate of the Greenland ice sheet using a high-resolution climate model - Part 1: Evaluation

    NARCIS (Netherlands)

    Ettema, J.; van den Broeke, M.R.; van Meijgaard, E.; van de Berg, W.J.; Box, J.E.; Steffen, K.

    2010-01-01

    A simulation of 51 years (1957-2008) has been performed over Greenland using the regional atmospheric climate model (RACMO2/GR) at a horizontal grid spacing of 11 km and forced by ECMWF re-analysis products. To better represent processes affecting ice sheet surface mass balance, such as meltwater re

  2. 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.

  3. Future projection of Indian summer monsoon variability under climate change scenario: An assessment from CMIP5 climate models

    Science.gov (United States)

    Sharmila, S.; Joseph, S.; Sahai, A. K.; Abhilash, S.; Chattopadhyay, R.

    2015-01-01

    may notably modulate the ISM rainfall in future climate. Both extreme wet and dry episodes are likely to intensify and regionally extend in future climate with enhanced propensity of short active and long break spells. The SM (WM) could also be more wet (dry) in future due to the increment in longer active (break) spells. However, future changes in the spatial pattern during active/break phase of SM and WM are geographically inconsistent among the models. The results point out the growing climate-related vulnerability over Indian subcontinent, and further suggest the requisite of profound adaptation measures and better policy making in future.

  4. Uncertainties in the regional climate models simulations of South-Asian summer monsoon and climate change

    Science.gov (United States)

    Syed, F. S.; Iqbal, Waheed; Syed, Ahsan Ali Bukhari; Rasul, G.

    2014-04-01

    The uncertainties in the regional climate models (RCMs) are evaluated by analyzing the driving global data of ERA40 reanalysis and ECHAM5 general circulation models, and the downscaled data of two RCMs (RegCM4 and PRECIS) over South-Asia for the present day simulation (1971-2000) of South-Asian summer monsoon. The differences between the observational datasets over South-Asia are also analyzed. The spatial and the quantitative analysis over the selected climatic regions of South-Asia for the mean climate and the inter-annual variability of temperature, precipitation and circulation show that the RCMs have systematic biases which are independent from different driving datasets and seems to come from the physics parameterization of the RCMs. The spatial gradients and topographically-induced structure of climate are generally captured and simulated values are within a few degrees of the observed values. The biases in the RCMs are not consistent with the biases in the driving fields and the models show similar spatial patterns after downscaling different global datasets. The annual cycle of temperature and rainfall is well simulated by the RCMs, however the RCMs are not able to capture the inter-annual variability. ECHAM5 is also downscaled for the future (2071-2100) climate under A1B emission scenario. The climate change signal is consistent between ECHAM5 and RCMs. There is warming over all the regions of South-Asia associated with increasing greenhouse gas concentrations and the increase in summer mean surface air temperature by the end of the century ranges from 2.5 to 5 °C, with maximum warming over north western parts of the domain and 30 % increase in rainfall over north eastern India, Bangladesh and Myanmar.

  5. Coupling of climate models and ice sheet models by surface mass balance gradients: application to the Greenland Ice Sheet

    Directory of Open Access Journals (Sweden)

    M. M. Helsen

    2012-03-01

    Full Text Available It is notoriously difficult to couple surface mass balance (SMB results from climate models to the changing geometry of an ice sheet model. This problem is traditionally avoided by using only accumulation from a climate model, and parameterizing the meltwater run-off as a function of temperature, which is often related to surface elevation (Hs. In this study, we propose a new strategy to calculate SMB, to allow a direct adjustment of SMB to a change in ice sheet topography and/or a change in climate forcing. This method is based on elevational gradients in the SMB field as computed by a regional climate model. Separate linear relations are derived for ablation and accumulation, using pairs of Hs and SMB within a minimum search radius. The continuously adjusting SMB forcing is consistent with climate model forcing fields, also for initially non-glaciated areas in the peripheral areas of an ice sheet. When applied to an asynchronous coupled ice sheet – climate model setup, this method circumvents traditional temperature lapse rate assumptions. Here we apply it to the Greenland Ice Sheet (GrIS. Experiments using both steady-state forcing and glacial-interglacial forcing result in realistic ice sheet reconstructions.

  6. Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model

    Science.gov (United States)

    Swain, Eric; Stefanova, Lydia; Smith, Thomas

    2014-01-01

    Precipitation data from Global Climate Models have been downscaled to smaller regions. Adapting this downscaled precipitation data to a coupled hydrodynamic surface-water/groundwater model of southern Florida allows an examination of future conditions and their effect on groundwater levels, inundation patterns, surface-water stage and flows, and salinity. The downscaled rainfall data include the 1996-2001 time series from the European Center for Medium-Range Weather Forecasting ERA-40 simulation and both the 1996-1999 and 2038-2057 time series from two global climate models: the Community Climate System Model (CCSM) and the Geophysical Fluid Dynamic Laboratory (GFDL). Synthesized surface-water inflow datasets were developed for the 2038-2057 simulations. The resulting hydrologic simulations, with and without a 30-cm sea-level rise, were compared with each other and field data to analyze a range of projected conditions. Simulations predicted generally higher future stage and groundwater levels and surface-water flows, with sea-level rise inducing higher coastal salinities. A coincident rise in sea level, precipitation and surface-water flows resulted in a narrower inland saline/fresh transition zone. The inland areas were affected more by the rainfall difference than the sea-level rise, and the rainfall differences make little difference in coastal inundation, but a larger difference in coastal salinities.

  7. 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.

  8. Response of a Grassland Ecosystem to Climate Change in a Theoretical Model

    Institute of Scientific and Technical Information of China (English)

    SUN Guodong; MU Mu

    2011-01-01

    The response of a grassland ecosystem to climate change is discussed within the context of a theoretical model.An optimization approach,a conditional nonlinear optimal perturbation related to parameter (CNOP-P) approach,was employed in this study.The CNOP-P,a perturbation of moisture index in the theoretical model,represents a nonlinear climate perturbation.Two kinds of linear climate perturbations were also used to study the response of the grassland ecosystem to different types of climate changes.The results show that the extent of grassland ecosystem variation caused by the CNOP-P-type climate change is greater than that caused by the two linear types of climate change.In addition,the grassland ecosystem affected by the CNOP-P-type climate change evolved into a desert ecosystem,and the two linear types of climate changes failed within a specific amplitude range when the moisture index recovered to its reference state. Therefore,the grassland ecosystem response to climate change was nonlinear. This study yielded similar results for a desert ecosystem seeded with both living and wilted biomass litter.The quantitative analysis performed in this study also accounted for the role of soil moisture in the root zone and the shading effect of wilted biomass on the grassland ecosystem through nonlinear interactions between soil and vegetation.The results of this study imply that the CNOP-P approach is a potentially effective tool for assessing the impact of nonlinear climate change on grassland ecosystems.

  9. Local control on precipitation in a fully coupled climate-hydrology model

    DEFF Research Database (Denmark)

    Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin;

    2016-01-01

    simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface......, plant coverand the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub......-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact...

  10. Stochastic Parameterization: Towards a new view of Weather and Climate Models

    CERN Document Server

    Berner, Judith; Batte, Lauriane; De La Camara, Alvaro; Crommelin, Daan; Christensen, Hannah; Colangeli, Matteo; Dolaptchiev, Stamen; Franzke, Christian L E; Friederichs, Petra; Imkeller, Peter; Jarvinen, Heikki; Juricke, Stephan; Kitsios, Vassili; Lott, Franois; Lucarini, Valerio; Mahajan, Salil; Palmer, Timothy N; Penland, Cecile; Von Storch, Jin-Song; Sakradzija, Mirjana; Weniger, Michael; Weisheimer, Antje; Williams, Paul D; Yano, Jun-Ichi

    2015-01-01

    The last decade has seen the success of stochastic parameterizations in short-term, medium-range and seasonal ensembles: operational weather centers now routinely use stochastic parameterization schemes to better represent model inadequacy and improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides more skillful estimates of uncertainty, but is also extremely promising for reducing longstanding climate biases and relevant for determining the climate response to forcings such as e.g., an increase of CO2. This article highlights recent results from different research groups which show that the stochastic representation of unresolved processes in the atmosphere, oceans, land surface and cryosphere of comprehensive weather and climate models a) gives rise to more reliable probabilistic forecasts of weather and climate and b) reduces systematic model bias. We make a case that the use of mathematically ...

  11. Groundwater flow modelling of periods with temperate climate conditions - Laxemar

    Energy Technology Data Exchange (ETDEWEB)

    Joyce, Steven; Simpson, Trevor; Hartley, Lee; Applegate, David; Hoek, Jaap; Jackson, Peter; Roberts, David; Swan, David (Serco Technical Consulting Services (United Kingdom)); Gylling, Bjoern; Marsic, Niko (Kemakta Konsult AB, Stockholm (Sweden)); Rhen, Ingvar (SWECO Environment AB, Falun (Sweden))

    2010-12-15

    As a part of the license application for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different hydraulic conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. This report concerns the modelling of a repository at the Laxemar-Simpevarp site during temperate climate conditions as a comparison to corresponding modelling carried out for Forsmark /Joyce et al. 2010/. The collation and implementation of onsite hydrogeological and hydrogeochemical data from previous reports are used in the construction of a Hydrogeological base case (reference case conceptualisation) and then an examination of various areas of uncertainty within the current understanding by a series of model variants. The Hydrogeological base case models at three different scales, 'repository', 'site' and 'regional' make use of a discrete fracture network (DFN) and equivalent continuous porous medium (ECPM) models. The use of hydrogeological models allow for the investigation of the groundwater flow from a deep disposal facility to the biosphere and for the calculation of performance measures that will provide an input to the site performance assessment. The focus of the study described in this report has been to perform numerical simulations of the hydrogeological system from post-closure and throughout the temperate period up until the receding shoreline leaves the modelling domain at around 15,000 AD. Besides providing quantitative results for the immediate temperate period following post-closure, these results are also intended to give a qualitative indication of the evolution of the groundwater system during future temperate periods within an ongoing cycle of glacial/inter-glacial events

  12. The DSET Tool Library: A software approach to enable data exchange between climate system models

    Energy Technology Data Exchange (ETDEWEB)

    McCormick, J. [Lawrence Livermore National Lab., CA (United States)

    1994-12-01

    Climate modeling is a computationally intensive process. Until recently computers were not powerful enough to perform the complex calculations required to simulate the earth`s climate. As a result standalone programs were created that represent components of the earth`s climate (e.g., Atmospheric Circulation Model). However, recent advances in computing, including massively parallel computing, make it possible to couple the components forming a complete earth climate simulation. The ability to couple different climate model components will significantly improve our ability to predict climate accurately and reliably. Historically each major component of the coupled earth simulation is a standalone program designed independently with different coordinate systems and data representations. In order for two component models to be coupled, the data of one model must be mapped to the coordinate system of the second model. The focus of this project is to provide a general tool to facilitate the mapping of data between simulation components, with an emphasis on using object-oriented programming techniques to provide polynomial interpolation, line and area weighting, and aggregation services.

  13. 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.

  14. 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

  15. An energy balance model of carbon's effect on climate change

    CERN Document Server

    Benney, Lucas

    2015-01-01

    Due to climate change, the interest of studying our climatic system using mathematical modeling has become tremendous in recent years. One well-known model is Budyko's system, which represents the coupled evolution of two variables, the ice-line and the average earth surface temperature. The system depends on natural parameters, such as the earth albedo, and the amount A of carbon in the atmosphere. We introduce a 3-dimensional extension of this model in which we regard A as the third coupled variable of the system. We analyze the phase space and dependence on parameters, looking for Hopf bifurcations and the birth of cycling behavior. We interpret the cycles as climatic oscillations triggered by the sensitivity in our regulation of carbon emissions at extreme temperatures.

  16. Climate change and permafrost stability in the eastern Canada Cordillera:The results of 33 years of measurements

    Institute of Scientific and Technical Information of China (English)

    Stuart; A.Harris

    2009-01-01

    Over the last 33 years,a network of climate stations has been set up at high altitude mountain permafrost sites from Plateau Mountain near Claresholm,Alberta,north to Sheldon Lake on the North Canol Road in the Yukon.Taken together with the data from the US National Weather Service and the Canadian Atmospheric Environment Service,the results indicate a cooling of mean annual air temperature south of Calgary,no significant change in Calgary,a slight warming at Jasper,and a major warming at Summit Lake,west of Fort Nelson.In contrast,the south eastern and central Yukon show only a minor warming trend that lies well within the limits of a sixty-year record measured by the Canadian Atmospheric Environment Service.Along the Mackenzie valley and on the North Slope of Alaska,the mean annual air temperature is rising.Permafrost is aggrading on Plateau Mountain,degrading at Summit Lake,and appears to be stable in southern Yukon and southern Alaska.This is in contrast to the warming occurring on the Arctic coastal plain and along the Mackenzie valley.It therefore appears that changes in climate vary considera-bly from place to place,and even where warming may occur,it may not continue indefinitely.There has been a northward shift of the arctic front due to a weakening of air pressure in the Yukon and Alaska relative to the continental tropical(cT) and maritime polar(mT) air masses to the south.Any actual changes that may be occurring appear to undergo amplification along the Mackenzie valley and Arctic coastal plain and reduction by buffering in the interior Yukon and Alaskan mountains,a result of mi-cro-environmental factors.Continued,careful monitoring of the climate is required and needs to be expanded in the National Parks in the mountains in order to provide data on the changes that may be taking place.Such measurements can provide a sound basis for interpreting ecological and other climate-related data.The existing climate models are not working satisfactorily because

  17. Climate change and permafrost stability in the eastern Canada Cordillera: The results of 33 years of measurements

    Institute of Scientific and Technical Information of China (English)

    Stuart A. Harris

    2009-01-01

    Over the last 33 years, a network of climate stations has been set up at high altitude mountain permafrost sites from Plateau Mountain near Claresholm, Alberta, north to Sheldon Lake on the North Canol Road in the Yukon. Taken together with the data from the US National Weather Service and the Canadian Atmospheric Environment Service, the results indicate a cooling of mean annual air temperature south of Calgary, no significant change in Calgary, a slight warming at Jasper, and a major warming at Summit Lake, west of Fort Nelson. In contrast, the south eastern and central Yukon show only a minor warming trend that lies well within the limits of a sixty-year record measured by the Canadian Atmospheric Environment Service. Along the Mackenzie valley and on the North Slope of Alaska, the mean annual air temperature is rising. Permafrost is aggrading on Plateau Mountain,degrading at Summit Lake, and appears to be stable in southern Yukon and southern Alaska. This is in contrast to the warming occurring on the Arctic coastal plain and along the Mackenzie valley. It therefore appears that changes in climate vary considerably from place to place, and even where warming may occur, it may not continue indefinitely. There has been a northward shift of the arctic front due to a weakening of air pressure in the Yukon and Alaska relative to the continental tropical (cT) and maritime polar (mT) air masses to the south. Any actual changes that may be occurring appear to undergo amplification along the Mackenzie valley and Arctic coastal plain and reduction by buffering in the interior Yukon and Alaskan mountains, a result of micro-environmental factors. Continued, careful monitoring of the climate is required and needs to be expanded in the National Parks in the mountains in order to provide data on the changes that may be taking place. Such measurements can provide a sound basis for interpreting ecological and other climate-related data. The existing climate models are not

  18. Bias correction of temperature and precipitation data for regional climate model application to the Rhine basin

    Science.gov (United States)

    Terink, W.; Hurkmans, R. T. W. L.; Uijlenhoet, R.; Torfs, P. J. J. F.; Warmerdam, P. M. M.

    2009-04-01

    The Hydrology and Quantitative Water Management group of Wageningen University is involved in the EU research project NeWater. The objective of this project is to develop tools which provide medium range hydrological predictions by coupling catchment-scale water balance models and ensembles from mesoscale climate models. The catchment-scale distributed hydrological model used in this study is the Variable Infiltration Capacity (VIC) model. This hydrological model in combination with an ensemble from the climate model ECHAM5 (developed by Max Plank Institute für Meteorologie (MPI-M), Hamburg) is being used to evaluate the effects of climate change on the hydrological regime of the Rhine basin and to assess the uncertainties involved in the ensembles from the climate model used in this study. Three future scenarios (2001-2100) are used in this study, which are downscaled ECHAM5 runs which were forced by the IPCC carbon emission scenarios B1, A1B and A2. A downscaled ECHAM5 "Climate of the 20th Century" run (1951-2000) is used as the reference climate. Downscaled ERA15 data is used to calibrate the VIC model. Downscaling of both the ECHAM5 and ERA15 model was carried out with the regional climate model REMO at MPI-M to a resolution of 0.088 degrees. The assessment of uncertainties involved in the climate model ensembles is performed by comparing the model (ECHAM5-REMO and ERA15-REMO) ensemble precipitation and temperature data with observations. This resulted in the detection of a bias in both the downscaled reference climate data and downscaled ERA15 data. A bias-correction has been applied to both the downscaled ERA15 data and the reference climate data. This bias-correction corrects for the mean and coefficient of variation for precipitation and the mean and standard deviation for temperature. The results of the applied bias-correction are analyzed spatially and temporally. Despite the fact that the bias-correction only uses two parameters, the coefficient of

  19. Climate Change Resulting from Lunar Impact in the Year 1178 AD

    Directory of Open Access Journals (Sweden)

    Chapman D. W.

    2014-10-01

    Full Text Available In June of the year 1178, an impact was observed on the Moon. Within a few years, Europe experienced a climatic event known as the Little Ice Age. Calculations of the reduction in sunlight due to dust in high earth orbit are consistent with the historical temperature decrease. Other past temperature reductions may have resulted from similar impacts on the Moon.

  20. Parameterization of FAO's AquaCrop Model by Integrating a Hydrological Model and Climate Indices

    Science.gov (United States)

    Langhorn, C.; Kienzle, S. W.; Doria, R.; Jiskoot, H.; Cheng, H.

    2014-12-01

    One of the greatest global challenges is to meet growing food demand under rapidly changing climate conditions. Continued global population growth increases the pressure on the agriculture sector to produce enough food to feed the world. In 2013, the province of Alberta, Canada, set a record high for principal field crop production of 34.5 million tonnes (Matejovsky, 2014). AquaCrop, a crop yield and water productivity model developed by the Land and Water Division of the Food and Agriculture Organization of the United Nations (FAO), attempts to balance the accuracy, simplicity and robustness of crop modelling (Steduto et al., 2009). The model is focused on the three components of the soil-plant-atmosphere continuum. AquaCrop is applied in this study for simulating hard red spring wheat and durum wheat yields, and simulated yields are verified against observed yields available from a crop insurer. One of the challenges of crop yield modelling is the selection of a realistic seeding date, which can vary by four to five weeks (end of March to end of April). In order to enable realistic simulation for the historical period 1950-2010 as well the future period 2041-