WorldWideScience

Sample records for climate model results

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

    Science.gov (United States)

    Huebener, Heike; Hoffmann, Peter; Keuler, Klaus; Pfeifer, Susanne; Ramthun, Hans; Spekat, Arne; Steger, Christian; Warrach-Sagi, Kirsten

    2017-07-01

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

  2. 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.

  3. Reconstructing Holocene climate using a climate model: Model strategy and preliminary results

    Science.gov (United States)

    Haberkorn, K.; Blender, R.; Lunkeit, F.; Fraedrich, K.

    2009-04-01

    An Earth system model of intermediate complexity (Planet Simulator; PlaSim) is used to reconstruct Holocene climate based on proxy data. The Planet Simulator is a user friendly general circulation model (GCM) suitable for palaeoclimate research. Its easy handling and the modular structure allow for fast and problem dependent simulations. The spectral model is based on the moist primitive equations conserving momentum, mass, energy and moisture. Besides the atmospheric part, a mixed layer-ocean with sea ice and a land surface with biosphere are included. The present-day climate of PlaSim, based on an AMIP II control-run (T21/10L resolution), shows reasonable agreement with ERA-40 reanalysis data. Combining PlaSim with a socio-technological model (GLUES; DFG priority project INTERDYNAMIK) provides improved knowledge on the shift from hunting-gathering to agropastoral subsistence societies. This is achieved by a data assimilation approach, incorporating proxy time series into PlaSim to initialize palaeoclimate simulations during the Holocene. For this, the following strategy is applied: The sensitivities of the terrestrial PlaSim climate are determined with respect to sea surface temperature (SST) anomalies. Here, the focus is the impact of regionally varying SST both in the tropics and the Northern Hemisphere mid-latitudes. The inverse of these sensitivities is used to determine the SST conditions necessary for the nudging of land and coastal proxy climates. Preliminary results indicate the potential, the uncertainty and the limitations of the method.

  4. Increase of carbon cycle feedback with climate sensitivity: results from a coupled climate and carbon cycle model

    International Nuclear Information System (INIS)

    Govindasamy, B.; Thompson, S.; Mirin, A.; Wickett, M.; Caldeira, K.; Delire, C.

    2005-01-01

    Coupled climate and carbon cycle modelling studies have shown that the feedback between global warming and the carbon cycle, in particular the terrestrial carbon cycle, could accelerate climate change and result in greater warming. In this paper we investigate the sensitivity of this feedback for year 2100 global warming in the range of 0 to 8 K. Differing climate sensitivities to increased CO 2 content are imposed on the carbon cycle models for the same emissions. Emissions from the SRES A2 scenario are used. We use a fully coupled climate and carbon cycle model, the INtegrated Climate and CArbon model (INCCA), the NCAR/DOE Parallel Climate Model coupled to the IBIS terrestrial biosphere model and a modified OCMIP ocean biogeochemistry model. In our integrated model, for scenarios with year 2100 global warming increasing from 0 to 8 K, land uptake decreases from 47% to 29% of total CO 2 emissions. Due to competing effects, ocean uptake (16%) shows almost no change at all. Atmospheric CO 2 concentration increases are 48% higher in the run with 8 K global climate warming than in the case with no warming. Our results indicate that carbon cycle amplification of climate warming will be greater if there is higher climate sensitivity to increased atmospheric CO 2 content; the carbon cycle feedback factor increases from 1.13 to 1.48 when global warming increases from 3.2 to 8 K

  5. Regionalization of climate model results for the North Sea

    Energy Technology Data Exchange (ETDEWEB)

    Kauker, F.

    1999-07-01

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

  6. A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

    Science.gov (United States)

    Rummukainen, M.; Räisänen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willén, U.; Hansson, U.; Jones, C.

    This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results.

  7. A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

    Energy Technology Data Exchange (ETDEWEB)

    Rummukainen, M.; Raeisaenen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willen, U.; Hansson, U.; Jones, C. [Rossby Centre, Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden)

    2001-03-01

    This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results. (orig.)

  8. Impact of the choice of the precipitation reference data set on climate model selection and the resulting climate change signal

    Science.gov (United States)

    Gampe, D.; Ludwig, R.

    2017-12-01

    Regional Climate Models (RCMs) that downscale General Circulation Models (GCMs) are the primary tool to project future climate and serve as input to many impact models to assess the related changes and impacts under such climate conditions. Such RCMs are made available through the Coordinated Regional climate Downscaling Experiment (CORDEX). The ensemble of models provides a range of possible future climate changes around the ensemble mean climate change signal. The model outputs however are prone to biases compared to regional observations. A bias correction of these deviations is a crucial step in the impact modelling chain to allow the reproduction of historic conditions of i.e. river discharge. However, the detection and quantification of model biases are highly dependent on the selected regional reference data set. Additionally, in practice due to computational constraints it is usually not feasible to consider the entire ensembles of climate simulations with all members as input for impact models which provide information to support decision-making. Although more and more studies focus on model selection based on the preservation of the climate model spread, a selection based on validity, i.e. the representation of the historic conditions is still a widely applied approach. In this study, several available reference data sets for precipitation are selected to detect the model bias for the reference period 1989 - 2008 over the alpine catchment of the Adige River located in Northern Italy. The reference data sets originate from various sources, such as station data or reanalysis. These data sets are remapped to the common RCM grid at 0.11° resolution and several indicators, such as dry and wet spells, extreme precipitation and general climatology, are calculate to evaluate the capability of the RCMs to produce the historical conditions. The resulting RCM spread is compared against the spread of the reference data set to determine the related uncertainties and

  9. A comparison of simulation results from two terrestrial carbon cycle models using three climate data sets

    International Nuclear Information System (INIS)

    Ito, Akihiko; Sasai, Takahiro

    2006-01-01

    This study addressed how different climate data sets influence simulations of the global terrestrial carbon cycle. For the period 1982-2001, we compared the results of simulations based on three climate data sets (NCEP/NCAR, NCEP/DOE AMIP-II and ERA40) employed in meteorological, ecological and biogeochemical studies and two different models (BEAMS and Sim-CYCLE). The models differed in their parameterizations of photosynthetic and phenological processes but used the same surface climate (e.g. shortwave radiation, temperature and precipitation), vegetation, soil and topography data. The three data sets give different climatic conditions, especially for shortwave radiation, in terms of long-term means, linear trends and interannual variability. Consequently, the simulation results for global net primary productivity varied by 16%-43% only from differences in the climate data sets, especially in these regions where the shortwave radiation data differed markedly: differences in the climate data set can strongly influence simulation results. The differences among the climate data set and between the two models resulted in slightly different spatial distribution and interannual variability in the net ecosystem carbon budget. To minimize uncertainty, we should pay attention to the specific climate data used. We recommend developing an accurate standard climate data set for simulation studies

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-07-20

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

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  12. Vulnerability of hydropower generation to climate change in China: Results based on Grey forecasting model

    International Nuclear Information System (INIS)

    Wang, Bing; Liang, Xiao-Jie; Zhang, Hao; Wang, Lu; Wei, Yi-Ming

    2014-01-01

    This paper analyzes the long-term relationships between hydropower generation and climate factors (precipitation), hydropower generation capacity (installed capacity of hydropower station) to quantify the vulnerability of renewable energy production in China for the case of hydropower generation. Furthermore, this study applies Grey forecasting model to forecast precipitation in different provinces, and then sets up different scenarios for precipitation based on the IPCC Special Report on Emission Scenarios and results from PRECIS (Providing Regional Climate projections for Impacts Studies) model. The most important result found in this research is the increasing hydropower vulnerability of the poorest regions and the main hydropower generation provinces of China to climate change. Other main empirical results reveal that the impacts of climate change on the supply of hydropower generation in China will be noteworthy for the society. Different scenarios have different effects on hydropower generation, of which A2 scenario (pessimistic, high emission) has the largest. Meanwhile, the impacts of climate change on hydropower generation of every province are distinctly different, of which the Southwest part has the higher vulnerability than the average level while the central part lower. - Highlights: • The hydropower vulnerability will be enlarged with the rapid increase of hydropower capacity. • Modeling the vulnerability of hydropower in different scenarios and different provinces. • The increasing hydropower vulnerability of the poorest regions to climate change. • The increasing hydropower vulnerability of the main hydropower generation provinces. • Rainfall pattern caused by climate change would be the reason for the increasing vulnerability

  13. 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.)

  14. 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

  15. Confirmation of ACRU model results for applications in land use and climate change studies

    Directory of Open Access Journals (Sweden)

    G. P. W. Jewitt

    2010-12-01

    Full Text Available The hydrological responses of a catchment are sensitive to, and strongly coupled to, land use and climate, and changes thereof. The hydrological responses to the impacts of changing land use and climate will be the result of complex interactions, where the change in one may moderate or exacerbate the effects of the other. Further difficulties in assessing these interactions are that dominant drivers of the hydrological system may vary at different spatial and temporal scales. To assess these interactions, a process-based hydrological model, sensitive to land use and climate, and changes thereof, needs to be used. For this purpose the daily time step ACRU model was selected. However, to be able to use a hydrological model such as ACRU with confidence its representation of reality must be confirmed by comparing simulated output against observations across a range of climatic conditions. Comparison of simulated against observed streamflow was undertaken in three climatically diverse South African catchments, ranging from the semi-arid, sub-tropical Luvuvhu catchment, to the winter rainfall Upper Breede catchment and the sub-humid Mgeni catchment. Not only do the climates of the catchments differ, but their primary land uses also vary. In the upper areas of the Mgeni catchment commercial plantation forestry is dominant, while in the middle reaches there are significant areas of commercial plantation sugarcane and urban areas, while the lower reaches are dominated by urban areas. The Luvuvhu catchment has a large proportion of subsistence agriculture and informal residential areas. In the Upper Breede catchment in the Western Cape, commercial orchards and vineyards are the primary land uses. Overall the ACRU model was able to represent the high, low and total flows, with satisfactory Nash-Sutcliffe efficiency indexes obtained for the selected catchments. The study concluded that the ACRU model can be used with confidence to simulate the streamflows

  16. Confirmation of ACRU model results for applications in land use and climate change studies

    Science.gov (United States)

    Warburton, M. L.; Schulze, R. E.; Jewitt, G. P. W.

    2010-12-01

    The hydrological responses of a catchment are sensitive to, and strongly coupled to, land use and climate, and changes thereof. The hydrological responses to the impacts of changing land use and climate will be the result of complex interactions, where the change in one may moderate or exacerbate the effects of the other. Further difficulties in assessing these interactions are that dominant drivers of the hydrological system may vary at different spatial and temporal scales. To assess these interactions, a process-based hydrological model, sensitive to land use and climate, and changes thereof, needs to be used. For this purpose the daily time step ACRU model was selected. However, to be able to use a hydrological model such as ACRU with confidence its representation of reality must be confirmed by comparing simulated output against observations across a range of climatic conditions. Comparison of simulated against observed streamflow was undertaken in three climatically diverse South African catchments, ranging from the semi-arid, sub-tropical Luvuvhu catchment, to the winter rainfall Upper Breede catchment and the sub-humid Mgeni catchment. Not only do the climates of the catchments differ, but their primary land uses also vary. In the upper areas of the Mgeni catchment commercial plantation forestry is dominant, while in the middle reaches there are significant areas of commercial plantation sugarcane and urban areas, while the lower reaches are dominated by urban areas. The Luvuvhu catchment has a large proportion of subsistence agriculture and informal residential areas. In the Upper Breede catchment in the Western Cape, commercial orchards and vineyards are the primary land uses. Overall the ACRU model was able to represent the high, low and total flows, with satisfactory Nash-Sutcliffe efficiency indexes obtained for the selected catchments. The study concluded that the ACRU model can be used with confidence to simulate the streamflows of the three selected

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  19. 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.)

  20. The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate

    Energy Technology Data Exchange (ETDEWEB)

    Flato, G.M.; Boer, G.J.; Lee, W.G.; McFarlane, N.A.; Ramsden, D.; Reader, M.C. [Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); Weaver, A.J. [School of Earth and Ocean Sciences, University of Victoria, BC (Canada)

    2000-06-01

    A global, three-dimensional climate model, developed by coupling the CCCma second-generation atmospheric general circulation model (GCM2) to a version of the GFDL modular ocean model (MOM1), forms the basis for extended simulations of past, current and projected future climate. The spin-up and coupling procedures are described, as is the resulting climate based on a 200 year model simulation with constant atmospheric composition and external forcing. The simulated climate is systematically compared to available observations in terms of mean climate quantities and their spatial patterns, temporal variability, and regional behavior. Such comparison demonstrates a generally successful reproduction of the broad features of mean climate quantities, albeit with local discrepancies. Variability is generally well-simulated over land, but somewhat underestimated in the tropical ocean and the extratropical storm-track regions. The modelled climate state shows only small trends, indicating a reasonable level of balance at the surface, which is achieved in part by the use of heat and freshwater flux adjustments. The control simulation provides a basis against which to compare simulated climate change due to historical and projected greenhouse gas and aerosol forcing as described in companion publications. (orig.)

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

    Science.gov (United States)

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

    2012-04-01

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

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

    International Nuclear Information System (INIS)

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

    1992-08-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-10-01

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

  4. 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.

  5. Responses of the ocean carbon cycle to climate change: Results from an earth system climate model simulation

    Institute of Scientific and Technical Information of China (English)

    WANG Shuang-Jing; CAO Long; LI Na

    2014-01-01

    Based on simulations using the University of Victoria’s Earth System Climate Model, we analyzed the responses of the ocean carbon cycle to increasing atmospheric CO2 levels and climate change from 1800 to 2500 following the RCP 8.5 scenario and its extension. Compared to simulations without climate change, the simulation with a climate sensitivity of 3.0 K shows that in 2100, due to increased atmospheric CO2 concentrations, the simulated sea surface temperature increases by 2.7 K, the intensity of the North Atlantic deep water formation reduces by4.5 Sv, and the oceanic uptake of anthropogenic CO2 decreases by 0.8 Pg C. Climate change is also found to have a large effect on the North Atlantic’s ocean column inventory of anthropogenic CO2. Between the years 1800 and 2500, compared with the simulation with no climate change, the simulation with climate change causes a reduction in the total anthropogenic CO2 column inventory over the entire ocean and in North Atlantic by 23.1% and 32.0%, respectively. A set of simulations with climate sensitivity variations from 0.5 K to 4.5 K show that with greater climate sensitivity climate change would have a greater effect in reducing the ocean’s ability to absorb CO2 from the atmosphere.

  6. Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model

    Directory of Open Access Journals (Sweden)

    N. Mahowald

    2011-02-01

    Full Text Available Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climate feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.

  7. Paleoclimate validation of a numerical climate model

    International Nuclear Information System (INIS)

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

    1994-01-01

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

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

    Science.gov (United States)

    Boé, Julien

    2018-03-01

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

  9. Geospatial Analysis Tool Kit for Regional Climate Datasets (GATOR) : An Open-source Tool to Compute Climate Statistic GIS Layers from Argonne Climate Modeling Results

    Science.gov (United States)

    2017-08-01

    This large repository of climate model results for North America (Wang and Kotamarthi 2013, 2014, 2015) is stored in Network Common Data Form (NetCDF...Network Common Data Form (NetCDF). UCAR/Unidata Program Center, Boulder, CO. Available at: http://www.unidata.ucar.edu/software/netcdf. Accessed on 6/20...parametric approach. This introduces uncertainty, because the parametric models are only as good as the available observations that form the basis for

  10. 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.

  11. Validating predictions from climate envelope models.

    Directory of Open Access Journals (Sweden)

    James I Watling

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

  12. 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.

  13. Animating climate model data

    Science.gov (United States)

    DaPonte, John S.; Sadowski, Thomas; Thomas, Paul

    2006-05-01

    This paper describes a collaborative project conducted by the Computer Science Department at Southern Connecticut State University and NASA's Goddard Institute for Space Science (GISS). Animations of output from a climate simulation math model used at GISS to predict rainfall and circulation have been produced for West Africa from June to September 2002. These early results have assisted scientists at GISS in evaluating the accuracy of the RM3 climate model when compared to similar results obtained from satellite imagery. The results presented below will be refined to better meet the needs of GISS scientists and will be expanded to cover other geographic regions for a variety of time frames.

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

    Science.gov (United States)

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

    2017-04-01

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

  15. Spatial scale separation in regional climate modelling

    Energy Technology Data Exchange (ETDEWEB)

    Feser, F.

    2005-07-01

    In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter

  16. Safety climate and firefighting: Focus group results.

    Science.gov (United States)

    DeJoy, David M; Smith, Todd D; Dyal, Mari-Amanda

    2017-09-01

    Firefighting is a hazardous occupation and there have been numerous calls for fundamental changes in how fire service organizations approach safety and balance safety with other operational priorities. These calls, however, have yielded little systematic research. As part of a larger project to develop and test a model of safety climate for the fire service, focus groups were used to identify potentially important dimensions of safety climate pertinent to firefighting. Analyses revealed nine overarching themes. Competency/professionalism, physical/psychological readiness, and that positive traits sometimes produce negative consequences were themes at the individual level; cohesion and supervisor leadership/support at the workgroup level; and politics/bureaucracy, resources, leadership, and hiring/promotion at the organizational level. A multi-level perspective seems appropriate for examining safety climate in firefighting. Safety climate in firefighting appears to be multi-dimensional and some dimensions prominent in the general safety climate literature also seem relevant to firefighting. These results also suggest that the fire service may be undergoing transitions encompassing mission, personnel, and its fundamental approach to safety and risk. These results help point the way to the development of safety climate measures specific to firefighting and to interventions for improving safety performance. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

  17. 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...

  18. 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...

  19. Economy-Energy-Climate Interaction. The Model Wiagem

    International Nuclear Information System (INIS)

    Kemfert, C.

    2001-09-01

    This paper presents an integrated economy-energy-climate model WIAGEM (World Integrated Assessment General Equilibrium Model) which incorporates economic, energetic and climatic modules in an integrated assessment approach. In order to evaluate market and non-market costs and benefits of climate change WIAGEM combines an economic approach with a special focus on the international energy market and integrates climate interrelations by temperature changes and sea level variations. WIAGEM bases on 25 world regions which are aggregated to 11 trading regions and 14 sectors within each region. The representation of the economic relations is based on an intertemporal general equilibrium approach and contains the international markets for oil, coal and gas. The model incorporates all greenhouse gases (GHG) which influence the potential global temperature, the sea level variation and the assessed probable impacts in terms of costs and benefits of climate change. Market and non market damages are evaluated due to the damage costs approaches of Tol (2001). Additionally, this model includes net changes in GHG emissions from sources and removals by sinks resulting from land use change and forest activities. This paper describes the model structure in detail and outlines some general results, especially the impacts of climate change. As a result, climate change impacts do matter within the next 50 years, developing regions face high economic losses in terms of welfare and GDP losses. The inclusion of sinks and other GHG changes results significantly

  20. Investigating Impacts of Climate Change on Irrigation Water Demands and Its Resulting Consequences on Groundwater Using CMIP5 Models.

    Science.gov (United States)

    Goodarzi, Mustafa; Abedi-Koupai, Jahangir; Heidarpour, Manouchehr

    2018-04-15

    In this study, the impacts of climate change on crop water requirements and irrigation water requirements on the regional cropping pattern were evaluated using two climate change scenarios and combinations of 20 GCM models. Different models including CROPWAT, MODFLOW, and statistical models were used to evaluate the climate change impacts. The results showed that in the future period (2017 to 2046) the temperature in all months of the year will increase at all stations. The average annual precipitation decline in Isfahan, Tiran, Flavarjan, and Lenj stations for RCP 4.5 and RCP 8.5 scenarios are 18.6 and 27.6%, 15.2 and 18%, 22.5 and 31.5%, and 10.5 and 12.1%, respectively. The average increase in the evapotranspiration for RCP 4.5 and RCP 8.5 scenarios are about 2.5 and 4.1%, respectively. The irrigation water demands increases considerably and for some crops, on average 18%. Among the existing crops in the cropping pattern, barley, cumin, onion, wheat, and forage crops are more sensitive and their water demand will increase significantly. Results indicate that climate change could have a significant impact on water resources consumption. By considering irrigation efficiency in the region, climate change impacts will result in about 35 to 50 million m 3 /year, over-extraction from the aquifer. This additional exploitation causes an extra drop of 0.4 to 0.8 m in groundwater table per year in the aquifer. Therefore, with regard to the critical condition of the aquifer, management and preventive measures to deal with climate change in the future is absolutely necessary. © 2018, National Ground Water Association.

  1. 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

    1997-12-31

    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

  2. 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

  3. Climate and climate change sensitivity to model configuration in the Canadian RCM over North America

    Energy Technology Data Exchange (ETDEWEB)

    De Elia, Ramon [Ouranos Consortium on Regional Climate and Adaptation to Climate Change, Montreal (Canada); Centre ESCER, Univ. du Quebec a Montreal (Canada); Cote, Helene [Ouranos Consortium on Regional Climate and Adaptation to Climate Change, Montreal (Canada)

    2010-06-15

    Climate simulations performed with Regional Climate Models (RCMs) have been found to show sensitivity to parameter settings. The origin, consequences and interpretations of this sensitivity are varied, but it is generally accepted that sensitivity studies are very important for a better understanding and a more cautious manipulation of RCM results. In this work we present sensitivity experiments performed on the simulated climate produced by the Canadian Regional Climate Model (CRCM). In addition to climate sensitivity to parameter variation, we analyse the impact of the sensitivity on the climate change signal simulated by the CRCM. These studies are performed on 30-year long simulated present and future seasonal climates, and we have analysed the effect of seven kinds of configuration modifications: CRCM initial conditions, lateral boundary condition (LBC), nesting update interval, driving Global Climate Model (GCM), driving GCM member, large-scale spectral nudging, CRCM version, and domain size. Results show that large changes in both the driving model and the CRCM physics seem to be the main sources of sensitivity for the simulated climate and the climate change. Their effects dominate those of configuration issues, such as the use or not of large-scale nudging, domain size, or LBC update interval. Results suggest that in most cases, differences between simulated climates for different CRCM configurations are not transferred to the estimated climate change signal: in general, these tend to cancel each other out. (orig.)

  4. The use of the k - {epsilon} turbulence model within the Rossby Centre regional ocean climate model: parameterization development and results

    Energy Technology Data Exchange (ETDEWEB)

    Markus Meier, H.E. [Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden). Rossby Centre

    2000-09-01

    As mixing plays a dominant role for the physics of an estuary like the Baltic Sea (seasonal heat storage, mixing in channels, deep water mixing), different mixing parameterizations for use in 3D Baltic Sea models are discussed and compared. For this purpose two different OGCMs of the Baltic Sea are utilized. Within the Swedish regional climate modeling program, SWECLIM, a 3D coupled ice-ocean model for the Baltic Sea has been coupled with an improved version of the two-equation k - {epsilon} turbulence model with corrected dissipation term, flux boundary conditions to include the effect of a turbulence enhanced layer due to breaking surface gravity waves and a parameterization for breaking internal waves. Results of multi-year simulations are compared with observations. The seasonal thermocline is simulated satisfactory and erosion of the halocline is avoided. Unsolved problems are discussed. To replace the controversial equation for dissipation the performance of a hierarchy of k-models has been tested and compared with the k - {epsilon} model. In addition, it is shown that the results of the mixing parameterization depend very much on the choice of the ocean model. Finally, the impact of two mixing parameterizations on Baltic Sea climate is investigated. In this case the sensitivity of mean SST, vertical temperature and salinity profiles, ice season and seasonal cycle of heat fluxes is quite large.

  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. 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

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

    Science.gov (United States)

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

    2014-12-01

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

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

    Directory of Open Access Journals (Sweden)

    S. Hagemann

    2013-05-01

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

  9. Results from a 2 x CO2 simulation with the Canadian Climate Centre general circulation model

    International Nuclear Information System (INIS)

    Boer, G.J.

    1990-01-01

    The Canadian Climate Centre's general circulation model (GCM), GCMII, was used to simulate a doubling of atmospheric carbon dioxide concentration. The experiment was a standard greenhouse gas climate change study, using a three-dimensional atmospheric circulation model coupled to a simple 'slab' ocean and a thermodynamic ice model. This standard experiment retains the sophistication and generality of an atmospheric GCM, is straightforward in its use of simplified ocean and ice models, is comparatively economical of computer time, and permits comparison of results from different models. Features of the second generation GCMII include: higher resolution at T32L10 with a transform grid of 3.75 x 3.75 degree; full diurnal and annual cycles; ocean and sea ice treatment involving specification of ocean transports; modified treatment of land surface processes and hydrology; a parameterization of cloud optical feedback; and a retention of the special application data sets of surface parameters for North America and Europe. Results of the simulation were a globally averaged surface temperature increase of 3.5 degree C; a precipitation and evaporation increase of 3%; an average decrease in soil moisture of 6.6%; a decrease in cloud cover of 2.2%; a 66% decrease in mass of sea ice; and marked changes in other quantities in the polar region. 2 refs., 2 figs., 2 tabs

  10. 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/

  11. Assessing NARCCAP climate model effects using spatial confidence regions

    Directory of Open Access Journals (Sweden)

    J. P. French

    2017-07-01

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

  12. Key uncertainties in climate change policy: Results from ICAM-2

    Energy Technology Data Exchange (ETDEWEB)

    Dowlatabadi, H.; Kandlikar, M.

    1995-12-31

    A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to: inform decision makers about the likely outcome of policy initiatives; and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.0. This model includes demographics, economic activities, emissions, atmospheric chemistry, climate change, sea level rise and other impact modules and the numerous associated feedbacks. The model has over 700 objects of which over 1/3 are uncertain. These have been grouped into seven different classes of uncertain items. The impact of uncertainties in each of these items can be considered individually or in combinations with the others. In this paper we demonstrate the relative contribution of various sources of uncertainty to different outcomes in the model. The analysis shows that climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. Extreme uncertainties in indirect aerosol forcing and behavioral response to climate change (adaptation) were characterized by using bounding analyses; the results suggest that these extreme uncertainties can dominate the choice of policy outcomes.

  13. Agricultural drought in a future climate: results from 15 global climate models participating in the IPCC 4th assessment

    Science.gov (United States)

    Wang, Guiling

    2005-12-01

    This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June July August (JJA) season and the Asian monsoon region in the December January February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.

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

    International Nuclear Information System (INIS)

    Cubasch, Ulrich

    2007-01-01

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

  15. Climate Model Diagnostic Analyzer

    Science.gov (United States)

    Lee, Seungwon; Pan, Lei; Zhai, Chengxing; Tang, Benyang; Kubar, Terry; Zhang, Zia; Wang, Wei

    2015-01-01

    The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

  16. 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

  17. 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

    1996-12-31

    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

  18. 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

  19. 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.

  20. 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

  1. Modeling glacial climates

    Science.gov (United States)

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

    1984-01-01

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

  2. Modeling key processes causing climate change and variability

    Energy Technology Data Exchange (ETDEWEB)

    Henriksson, S.

    2013-09-01

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

  3. Improved Regional Climate Model Simulation of Precipitation by a Dynamical Coupling to a Hydrology Model

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Drews, Martin; Hesselbjerg Christensen, Jens

    convective precipitation systems. As a result climate model simulations let alone future projections of precipitation often exhibit substantial biases. Here we show that the dynamical coupling of a regional climate model to a detailed fully distributed hydrological model - including groundwater-, overland...... of local precipitation dynamics are seen for time scales of app. Seasonal duration and longer. We show that these results can be attributed to a more complete treatment of land surface feedbacks. The local scale effect on the atmosphere suggests that coupled high-resolution climate-hydrology models...... including a detailed 3D redistribution of sub- and land surface water have a significant potential for improving climate projections even diminishing the need for bias correction in climate-hydrology studies....

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

    Directory of Open Access Journals (Sweden)

    Xian-Ge Hu

    2017-12-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  7. 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.

  8. 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

  9. Climate model diversity in the Northern Hemisphere Polar vortex response to climate change.

    Science.gov (United States)

    Simpson, I.; Seager, R.; Hitchcock, P.; Cohen, N.

    2017-12-01

    Global climate models vary widely in their predictions of the future of the Northern Hemisphere stratospheric polar vortex, with some showing a significant strengthening of the vortex, some showing a significant weakening and others displaying a response that is not outside of the range expected from internal variability alone. This inter-model spread in stratospheric predictions may account for some inter-model spread in tropospheric predictions with important implications for the storm tracks and regional climate change, particularly for the North Atlantic sector. Here, our current state of understanding of this model spread and its tropospheric impacts will be reviewed. Previous studies have proposed relationships between a models polar vortex response to climate change and its present day vortex climatology while others have demonstrated links between a models polar vortex response and changing wave activity coming up from the troposphere below under a warming climate. The extent to which these mechanisms can account for the spread in polar vortex changes exhibited by the Coupled Model Intercomparison Project, phase 5 models will be assessed. In addition, preliminary results from a series of idealized experiments with the Community Atmosphere Model will be presented. In these experiments, nudging of the stratospheric zonal mean state has been imposed to mimic the inter-model spread in the polar vortex response to climate change so that the downward influence of the spread in zonal mean stratospheric responses on the tropospheric circulation can be assessed within one model.

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

    Science.gov (United States)

    Shabani, Farzin; Shafapour Tehrany, Mahyat; Solhjouy-Fard, Samaneh; Kumar, Lalit

    2018-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Farzin Shabani

    2018-03-01

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

  12. 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.

  13. On coupling global biome models with climate models

    International Nuclear Information System (INIS)

    Claussen, M.

    1994-01-01

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

  14. 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

  15. Modeling maize response to climate modification in Hungary

    OpenAIRE

    Angela Anda

    2006-01-01

    Modeling provides a tool for a better understanding of the modified plant behaviour that results from various climatic differences. The present study provides new information about the physiological processes in maize (Zea mays L.) in response to climatic changes. The aim was to help local farmers adapt to climate modifications in Hungary and mitigate the future consequences of these changes. A simulation model was applied to estimate the possible feedback on crop properties and elevated CO2....

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

    International Nuclear Information System (INIS)

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

    1993-09-01

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

  17. Oscillations in a simple climate-vegetation model

    Science.gov (United States)

    Rombouts, J.; Ghil, M.

    2015-05-01

    We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation off the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various timescales is discussed.

  18. 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.

  19. 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.

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

    Science.gov (United States)

    Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos

    2017-07-01

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

  1. Modeling U.S. water resources under climate change

    Science.gov (United States)

    Blanc, Elodie; Strzepek, Kenneth; Schlosser, Adam; Jacoby, Henry; Gueneau, Arthur; Fant, Charles; Rausch, Sebastian; Reilly, John

    2014-04-01

    Water is at the center of a complex and dynamic system involving climatic, biological, hydrological, physical, and human interactions. We demonstrate a new modeling system that integrates climatic and hydrological determinants of water supply with economic and biological drivers of sectoral and regional water requirement while taking into account constraints of engineered water storage and transport systems. This modeling system is an extension of the Massachusetts Institute of Technology (MIT) Integrated Global System Model framework and is unique in its consistent treatment of factors affecting water resources and water requirements. Irrigation demand, for example, is driven by the same climatic conditions that drive evapotranspiration in natural systems and runoff, and future scenarios of water demand for power plant cooling are consistent with energy scenarios driving climate change. To illustrate the modeling system we select "wet" and "dry" patterns of precipitation for the United States from general circulation models used in the Climate Model Intercomparison Project (CMIP3). Results suggest that population and economic growth alone would increase water stress in the United States through mid-century. Climate change generally increases water stress with the largest increases in the Southwest. By identifying areas of potential stress in the absence of specific adaptation responses, the modeling system can help direct attention to water planning that might then limit use or add storage in potentially stressed regions, while illustrating how avoiding climate change through mitigation could change likely outcomes.

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

    Science.gov (United States)

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

    2016-12-01

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

  3. Future flooding impacts on transportation infrastructure and traffic patterns resulting from climate change.

    Science.gov (United States)

    2011-11-01

    "This study investigated potential impacts of climate change on travel disruption resulting from road closures in two urban watersheds in the : Portland metropolitan area. We used ensemble climate change scenarios, a hydrologic model, stream channel ...

  4. On coupling global biome models with climate models

    OpenAIRE

    Claussen, M.

    1994-01-01

    The BIOME model of Prentice et al. (1992; J. Biogeogr. 19: 117-134), which predicts global vegetation patterns in equilibrium with climate, was coupled with the ECHAM climate model of the Max-Planck-Institut fiir Meteorologie, Hamburg, Germany. It was found that incorporation of the BIOME model into ECHAM, regardless at which frequency, does not enhance the simulated climate variability, expressed in terms of differences between global vegetation patterns. Strongest changes are seen only betw...

  5. 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.......01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be improved using an ensemble approach....

  6. Climate simulations for 1880-2003 with GISS modelE

    International Nuclear Information System (INIS)

    Hansen, J.; Lacis, A.; Miller, R.; Schmidt, G.A.; Russell, G.; Canuto, V.; Del Genio, A.; Hall, T.; Hansen, J.; Sato, M.; Kharecha, P.; Nazarenko, L.; Aleinov, I.; Bauer, S.; Chandler, M.; Faluvegi, G.; Jonas, J.; Ruedy, R.; Lo, K.; Cheng, Y.; Lacis, A.; Schmidt, G.A.; Del Genio, A.; Miller, R.; Cairns, B.; Hall, T.; Baum, E.; Cohen, A.; Fleming, E.; Jackman, C.; Friend, A.; Kelley, M.

    2007-01-01

    We carry out climate simulations for 1880-2003 with GISS modelE driven by ten measured or estimated climate forcing. 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 forcing, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcing are due to model deficiencies, inaccurate or incomplete forcing, 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 forcing, we aim to provide a benchmark against which the effect of improvements in the model, climate forcing, and observations can be tested. Principal model deficiencies include unrealistic weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. Greatest uncertainties in the forcing are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds. (authors)

  7. Response of permafrost to projected climate change: Results from global offline model simulations with JSBACH

    Science.gov (United States)

    Blome, Tanja; Ekici, Altug; Beer, Christian; Hagemann, Stefan

    2014-05-01

    Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) lacked the sufficient representation of permafrost physics in their land surface schemes. In order to assess the response of permafrost to projected climate change for the 21st century, the land surface scheme of the Max-Planck-Institute for Meteorology, JSBACH, has recently been equipped with the important physical processes for permafrost studies, and was driven globally with bias corrected climate data, thereby spanning a period from 1850 until 2100. The applied land surface scheme JSBACH now considers the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. To address the uncertainty range arising through different greenhouse gas concentrations as well as through different climate realisations when using various climate models, combinations of two Representative Concentration Pathways (RCPs) and two GCMs were used as driving data. In order to focus only on the climatic impact on permafrost, effects due to feedbacks between climate and permafrost (namely via carbon fluxes between land and atmosphere) are excluded in the experiments

  8. 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

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

    Science.gov (United States)

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

    2012-11-01

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

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

    Science.gov (United States)

    Bahari, Siti Fatimah; Clarke, Sharon

    2013-06-01

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

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

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  12. Coupling Climate Models and Forward-Looking Economic Models

    Science.gov (United States)

    Judd, K.; Brock, W. A.

    2010-12-01

    Authors: Dr. Kenneth L. Judd, Hoover Institution, and Prof. William A. Brock, University of Wisconsin Current climate models range from General Circulation Models (GCM’s) with millions of degrees of freedom to models with few degrees of freedom. Simple Energy Balance Climate Models (EBCM’s) help us understand the dynamics of GCM’s. The same is true in economics with Computable General Equilibrium Models (CGE’s) where some models are infinite-dimensional multidimensional differential equations but some are simple models. Nordhaus (2007, 2010) couples a simple EBCM with a simple economic model. One- and two- dimensional ECBM’s do better at approximating damages across the globe and positive and negative feedbacks from anthroprogenic forcing (North etal. (1981), Wu and North (2007)). A proper coupling of climate and economic systems is crucial for arriving at effective policies. Brock and Xepapadeas (2010) have used Fourier/Legendre based expansions to study the shape of socially optimal carbon taxes over time at the planetary level in the face of damages caused by polar ice cap melt (as discussed by Oppenheimer, 2005) but in only a “one dimensional” EBCM. Economists have used orthogonal polynomial expansions to solve dynamic, forward-looking economic models (Judd, 1992, 1998). This presentation will couple EBCM climate models with basic forward-looking economic models, and examine the effectiveness and scaling properties of alternative solution methods. We will use a two dimensional EBCM model on the sphere (Wu and North, 2007) and a multicountry, multisector regional model of the economic system. Our aim will be to gain insights into intertemporal shape of the optimal carbon tax schedule, and its impact on global food production, as modeled by Golub and Hertel (2009). We will initially have limited computing resources and will need to focus on highly aggregated models. However, this will be more complex than existing models with forward

  13. Development of ALARO-Climate regional climate model for a very high resolution

    Science.gov (United States)

    Skalak, Petr; Farda, Ales; Brozkova, Radmila; Masek, Jan

    2014-05-01

    ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main results of the RCM ALARO-Climate model simulations in 25 and 6.25 km resolutions on the longer time-scale (1961-1990). The model was driven by the ERA-40 re-analyses and run on the integration domain of ~ 2500 x 2500 km size covering the central Europe. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version dataset 8. Other simulated parameters (e.g., cloudiness, radiation or components of water cycle) were compared to the ERA-40 re-analyses. The validation of the first ERA-40 simulation in both, 25 km and 6.25 km resolutions, revealed significant cold biases in all seasons and overestimation of precipitation in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The differences between these simulations were small and thus revealed a robustness of the model's physical parameterization on the resolution change. The series of 25 km resolution simulations with several model adaptations was carried out to study their effect on the simulated properties of climate variables and thus possibly identify a source of major errors in the simulated climate. The current investigation suggests the main reason for biases is related to the model physic. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1

  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.; hide

    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. Simulated climate change during the last 1,000 years: comparing the ECHO-G general circulation model with the MAGICC simple climate model

    Energy Technology Data Exchange (ETDEWEB)

    Osborn, Timothy J.; Briffa, Keith R. [University of East Anglia, Climatic Research Unit, School of Environmental Sciences, Norwich (United Kingdom); Raper, Sarah C.B. [University of East Anglia, Climatic Research Unit, School of Environmental Sciences, Norwich (United Kingdom); Manchester Metropolitan University, Dalton Research Institute, Manchester (United Kingdom)

    2006-08-15

    An intercomparison of eight climate simulations, each driven with estimated natural and anthropogenic forcings for the last millennium, indicates that the so-called ''Erik'' simulation of the ECHO-G coupled ocean-atmosphere climate model exhibits atypical behaviour. The ECHO-G simulation has a much stronger cooling trend from 1000 to 1700 and a higher rate of warming since 1800 than the other simulations, with the result that the overall amplitude of millennial-scale temperature variations in the ECHO-G simulation is much greater than in the other models. The MAGICC (Model for the Assessment of Greenhouse-gas-Induced Climate Change) simple climate model is used to investigate possible causes of this atypical behaviour. It is shown that disequilibrium in the initial conditions probably contributes spuriously to the cooling trend in the early centuries of the simulation, and that the omission of tropospheric sulphate aerosol forcing is the likely explanation for the anomalously large recent warming. The simple climate model results are used to adjust the ECHO-G Erik simulation to mitigate these effects, which brings the simulation into better agreement with the other seven models considered here and greatly reduces the overall range of temperature variations during the last millennium simulated by ECHO-G. Smaller inter-model differences remain which can probably be explained by a combination of the particular forcing histories and model sensitivities of each experiment. These have not been investigated here, though we have diagnosed the effective climate sensitivity of ECHO-G to be 2.39{+-}0.11 K for a doubling of CO{sub 2}. (orig.)

  16. Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

    Science.gov (United States)

    Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

    2018-05-01

    Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

  17. 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.

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

    Science.gov (United States)

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

    2013-10-28

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

  19. Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

    Science.gov (United States)

    Tselioudis, G.; Bauer, M.; Rossow, W.

    2009-04-01

    Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

  20. Glacial climate sensitivity to different states of the Atlantic Meridional Overturning Circulation: results from the IPSL model

    Directory of Open Access Journals (Sweden)

    M. Kageyama

    2009-09-01

    Full Text Available Paleorecords from distant locations on the globe show rapid and large amplitude climate variations during the last glacial period. Here we study the global climatic response to different states of the Atlantic Meridional Overturning Circulation (AMOC as a potential explanation for these climate variations and their possible connections. We analyse three glacial simulations obtained with an atmosphere-ocean coupled general circulation model and characterised by different AMOC strengths (18, 15 and 2 Sv resulting from successive ~0.1 Sv freshwater perturbations in the North Atlantic. These AMOC states suggest the existence of a freshwater threshold for which the AMOC collapses. A weak (18 to 15 Sv AMOC decrease results in a North Atlantic and European cooling. This cooling is not homogeneous, with even a slight warming over the Norwegian Sea. Convection in this area is active in both experiments, but surprisingly stronger in the 15 Sv simulation, which appears to be related to interactions with the atmospheric circulation and sea-ice cover. Far from the North Atlantic, the climatic response is not significant. The climate differences for an AMOC collapse (15 to 2 Sv are much larger and of global extent. The timing of the climate response to this AMOC collapse suggests teleconnection mechanisms. Our analyses focus on the North Atlantic and surrounding regions, the tropical Atlantic and the Indian monsoon region. The North Atlantic cooling associated with the AMOC collapse induces a cyclonic atmospheric circulation anomaly centred over this region, which modulates the eastward advection of cold air over the Eurasian continent. This can explain why the cooling is not as strong over western Europe as over the North Atlantic. In the Tropics, the southward shift of the Inter-Tropical Convergence Zone appears to be strongest over the Atlantic and Eastern Pacific and results from an adjustment of the atmospheric and oceanic heat transports. Finally, the

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

    International Nuclear Information System (INIS)

    Stenchikov, G.L.

    1990-01-01

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

  2. 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

    2017-11-01

    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.

  3. Scale dependency of regional climate modeling of current and future climate extremes in Germany

    Science.gov (United States)

    Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

    2017-11-01

    A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

  4. 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.

  5. Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

    Science.gov (United States)

    Delgado, Juan; Moreno-Navas, Juan; Pulido, Antoine; García-Lafuente, Juan; Calero Quesada, Maria C.; García, Rodrigo

    2017-04-01

    Extreme climatic events, such as heat waves and severe storms are predicted to increase in frequency and magnitude as a consequence of global warming but their socio-ecological effects are poorly understood, particularly in estuarine ecosystems. The Guadalquivir Estuary has been anthropologically modified several times, the original salt marshes have been transformed to grow rice and cotton and approximately one-fourth of the total surface of the estuary is now part of two protected areas, one of them is a UNESCO, MAB Biosphere Reserve. The climatic events are most likely to affect Europe in forthcoming decades and a further understanding how these climatic disturbances drive abrupt changes in the Guadalquivir estuary is needed. A barotropic model has been developed to study how severe storm events affects the estuary by conducting paired control and climate-events simulations. The changes in the local wind and atmospheric pressure conditions in the estuary have been studied in detail and several scenarios are obtained by running the model under control and real storm conditions. The model output has been validated with in situ water elevation and good agreement between modelled and real measurements have been obtained. Our preliminary results show that the model demonstrated the capability describe of the tide-surge levels in the estuary, opening the possibility to study the interaction between climatic events and the port operations and food production activities. The barotropic hydrodynamic model provide spatially explicit information on the key variables governing the tide dynamics of estuarine areas under severe climatic scenarios . The numerical model will be a powerful tool in future climate change mitigation and adaptation programs in a complex socio-ecological system.

  6. Simulation of recent and future climates using CNRM and IPSL models

    International Nuclear Information System (INIS)

    Dufresne, J.L.; Bony, S.; Fairhead, L.; Grandpeix, J.Y.; Hourdin, F.; Idelkadi, A.; Musat, I.; Salas y Melia, D.; Tyteca, S.; Chauvin, F.; Deque, M.; Douville, H.; Gueremy, J.F.; Marquet, P.; Planton, S.; Royer, J.F.; Voldoire, A.; Denvil, S.; Cadule, P.; Foujols, M.A.; Arzel, O.; Fichefet, T.; Krinner, G.; Levy, C.; Madec, G.

    2006-01-01

    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)

  7. 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)

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

    NARCIS (Netherlands)

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

    2016-01-01

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

  9. 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

  10. Modeling climate change impacts on water trading.

    Science.gov (United States)

    Luo, Bin; Maqsood, Imran; Gong, Yazhen

    2010-04-01

    This paper presents a new method of evaluating the impacts of climate change on the long-term performance of water trading programs, through designing an indicator to measure the mean of periodic water volume that can be released by trading through a water-use system. The indicator is computed with a stochastic optimization model which can reflect the random uncertainty of water availability. The developed method was demonstrated in the Swift Current Creek watershed of Prairie Canada under two future scenarios simulated by a Canadian Regional Climate Model, in which total water availabilities under future scenarios were estimated using a monthly water balance model. Frequency analysis was performed to obtain the best probability distributions for both observed and simulated water quantity data. Results from the case study indicate that the performance of a trading system is highly scenario-dependent in future climate, with trading effectiveness highly optimistic or undesirable under different future scenarios. Trading effectiveness also largely depends on trading costs, with high costs resulting in failure of the trading program. (c) 2010 Elsevier B.V. All rights reserved.

  11. 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.

  12. Educational and Scientific Applications of Climate Model Diagnostic Analyzer

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Zhang, J.; Bao, Q.

    2016-12-01

    Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA infrastructure and technology have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences for three years since 2014. In the summer school, the students work on group research projects where CMDA provide datasets and analysis tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. A provenance management system for CMDA is developed to keep track of students' usages of CMDA, and to recommend datasets and analysis tools for their research topic. The provenance system also allows students to revisit their analysis results and share them with their group. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each use case developed is described and listed in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered from the use case, an analysis result such as output plots and data files, and a link to the exact analysis service call with all the input arguments filled. For example, one science use case is the evaluation of NCAR CAM5 model with MODIS total cloud fraction. The analysis service used is Difference Plot Service of

  13. 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.

  14. 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

    1996-12-31

    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)

  15. 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)

  16. 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.

  17. 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

  18. Climate Change: The Physical Basis and Latest Results

    CERN Multimedia

    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...

  19. Model confirmation in climate economics

    Science.gov (United States)

    Millner, Antony; McDermott, Thomas K. J.

    2016-01-01

    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. PMID:27432964

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

    International Nuclear Information System (INIS)

    Solow, A.R.

    1991-01-01

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

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

    International Nuclear Information System (INIS)

    Solow, A.R.

    1990-01-01

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

  2. Documenting Climate Models and Simulations: the ES-DOC Ecosystem in Support of CMIP

    Science.gov (United States)

    Pascoe, C. L.; Guilyardi, E.

    2017-12-01

    The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now non-specialists such as government officials, policy-makers, and the general public, all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. Here we describe the ES-DOC community-govern project to collect and make available documentation of climate models and their simulations for the internationally coordinated modeling activity CMIP6 (Coupled Model Intercomparison Project, Phase 6). An overview of the underlying standards, key properties and features, the evolution from CMIP5, the underlying tools and workflows as well as what modelling groups should expect and how they should engage with the documentation of their contribution to CMIP6 is also presented.

  3. Mediterranean climate modelling: variability and climate change scenarios

    International Nuclear Information System (INIS)

    Somot, S.

    2005-12-01

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

  4. Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

    Science.gov (United States)

    Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard

    2013-01-01

    Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

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

    NARCIS (Netherlands)

    van Wessem, J.M.|info:eu-repo/dai/nl/413533085

    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)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-06-28

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

  7. Evaluation of global climate models for Indian monsoon climatology

    International Nuclear Information System (INIS)

    Kodra, Evan; Ganguly, Auroop R; Ghosh, Subimal

    2012-01-01

    The viability of global climate models for forecasting the Indian monsoon is explored. Evaluation and intercomparison of model skills are employed to assess the reliability of individual models and to guide model selection strategies. Two dominant and unique patterns of Indian monsoon climatology are trends in maximum temperature and periodicity in total rainfall observed after 30 yr averaging over India. An examination of seven models and their ensembles reveals that no single model or model selection strategy outperforms the rest. The single-best model for the periodicity of Indian monsoon rainfall is the only model that captures a low-frequency natural climate oscillator thought to dictate the periodicity. The trend in maximum temperature, which most models are thought to handle relatively better, is best captured through a multimodel average compared to individual models. The results suggest a need to carefully evaluate individual models and model combinations, in addition to physical drivers where possible, for regional projections from global climate models. (letter)

  8. The North American Regional Climate Change Assessment Program (NARCCAP): Status and results

    Science.gov (United States)

    Arritt, R.

    2009-04-01

    NARCCAP is an international program that is generating projections of climate change for the U.S., Canada, and northern Mexico at decision-relevant regional scales. NARCCAP uses multiple limited-area regional climate models (RCMs) nested within multiple atmosphere-ocean general circulation models (AOGCMs). The use of multiple regional and global models allows us to investigate the uncertainty in model responses to future emissions (here, the A2 SRES scenario). The project also includes global time-slice experiments at the same discretization (50 km) using the GFDL atmospheric model (AM2.1) and the NCAR atmospheric model (CAM3). Phase I of the experiment uses the regional models nested within reanalysis in order to establish uncertainty attributable to the RCMs themselves. Phase II of the project then nests the RCMs within results from the current and future runs of the AOGCMs to explore the cascade of uncertainty from the global to the regional models. Phase I has been completed and the results to be shown include findings that spectral nudging is beneficial in some regions but not in others. Phase II is nearing completion and some preliminary results will be shown.

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  11. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

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

    2015-12-01

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

  12. Multi-model approach to assess the impact of climate change on runoff

    Science.gov (United States)

    Dams, J.; Nossent, J.; Senbeta, T. B.; Willems, P.; Batelaan, O.

    2015-10-01

    The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a

  13. Future directions in climate modeling: A climate impacts perspective

    International Nuclear Information System (INIS)

    Mearns, L.O.

    1990-01-01

    One of the most serious impediments to further progress on the determination of specific impacts of climate change on relevant earth systems is the lack of precise and accurate scenarios of regional change. Spatial resolution of models is generally coarse (5-10 degree, corresponding to 550-1,100 km), and the modeling of physical processes is quite crude. Three main areas in which improvements in the modeling of physical processes are being made are modeling of surface processes, modeling of oceans and coupling of oceans and atmospheric models, and modeling of clouds. Improvements are required in the modeling of surface hydrology and vegetative effects, which have significant impact on the albedo scheme used. Oceans are important in climate modeling for the following reasons: delay of warming due to oceanic heat absorption; effect of mean meridional circulation; control of regional patterns of sea surface temperatures and sea ice by wind driven currents; absorption of atmospheric carbon dioxide by the oceans; and determination of interannual climatic variability via variability in sea surface temperature. The effects of clouds on radiation balance is highly significant. Clouds both reflect shortwave radiation and trap longwave radiation. Most cloud properties are sub-grid scale and thus difficult to include explicitly in models. 25 refs., 1 tab

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

    Science.gov (United States)

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

    2018-04-01

    deep-water formation in the Labrador Sea, resulting in overestimated North Atlantic SST variability. Concerning the influence of locally (isotropically) increased resolution, the ENSO pattern and index statistics improve significantly with higher resolution around the equator, illustrating the potential of the novel unstructured-mesh method for global climate modeling.

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

    Energy Technology Data Exchange (ETDEWEB)

    Palma, J.H.N.

    2017-11-01

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

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

    International Nuclear Information System (INIS)

    Palma, J.H.N.

    2017-01-01

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

  17. Uncertainty in water resources availability in the Okavango River basin as a result of climate change

    Directory of Open Access Journals (Sweden)

    D. A. Hughes

    2011-03-01

    Full Text Available This paper assesses the hydrological response to scenarios of climate change in the Okavango River catchment in Southern Africa. Climate scenarios are constructed representing different changes in global mean temperature from an ensemble of 7 climate models assessed in the IPCC AR4. The results show a substantial change in mean flow associated with a global warming of 2 °C. However, there is considerable uncertainty in the sign and magnitude of the projected changes between different climate models, implying that the ensemble mean is not an appropriate generalised indicator of impact. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation. There is also a clear need to evaluate the physical mechanisms associated with the model projected changes in this region. The implications for water resource management policy are considered.

  18. Climate Ocean Modeling on Parallel Computers

    Science.gov (United States)

    Wang, P.; Cheng, B. N.; Chao, Y.

    1998-01-01

    Ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change. However, modeling the ocean circulation at various spatial and temporal scales is a very challenging computational task.

  19. 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.

  20. 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.

  1. Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models

    Science.gov (United States)

    Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby

    2018-06-01

    The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices.

  2. 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...

  3. 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.

  4. An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

    Science.gov (United States)

    Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

    2003-12-01

    Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

  5. Ecological Assimilation of Land and Climate Observations - the EALCO model

    Science.gov (United States)

    Wang, S.; Zhang, Y.; Trishchenko, A.

    2004-05-01

    Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net

  6. A comparison of metrics for assessing state-of-the-art climate models and implications for probabilistic projections of climate change

    Science.gov (United States)

    Ring, Christoph; Pollinger, Felix; Kaspar-Ott, Irena; Hertig, Elke; Jacobeit, Jucundus; Paeth, Heiko

    2018-03-01

    A major task of climate science are reliable projections of climate change for the future. To enable more solid statements and to decrease the range of uncertainty, global general circulation models and regional climate models are evaluated based on a 2 × 2 contingency table approach to generate model weights. These weights are compared among different methodologies and their impact on probabilistic projections of temperature and precipitation changes is investigated. Simulated seasonal precipitation and temperature for both 50-year trends and climatological means are assessed at two spatial scales: in seven study regions around the globe and in eight sub-regions of the Mediterranean area. Overall, 24 models of phase 3 and 38 models of phase 5 of the Coupled Model Intercomparison Project altogether 159 transient simulations of precipitation and 119 of temperature from four emissions scenarios are evaluated against the ERA-20C reanalysis over the 20th century. The results show high conformity with previous model evaluation studies. The metrics reveal that mean of precipitation and both temperature mean and trend agree well with the reference dataset and indicate improvement for the more recent ensemble mean, especially for temperature. The method is highly transferrable to a variety of further applications in climate science. Overall, there are regional differences of simulation quality, however, these are less pronounced than those between the results for 50-year mean and trend. The trend results are suitable for assigning weighting factors to climate models. Yet, the implications for probabilistic climate projections is strictly dependent on the region and season.

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

    KAUST Repository

    Merlis, Timothy M.; Held, Isaac M.; Stenchikov, Georgiy L.; Zeng, Fanrong; Horowitz, Larry W.

    2014-01-01

    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.

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

    KAUST Repository

    Merlis, Timothy M.

    2014-10-01

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

  9. High-resolution integration of water, energy, and climate models to assess electricity grid vulnerabilities to climate change

    Science.gov (United States)

    Meng, M.; Macknick, J.; Tidwell, V. C.; Zagona, E. A.; Magee, T. M.; Bennett, K.; Middleton, R. S.

    2017-12-01

    The U.S. electricity sector depends on large amounts of water for hydropower generation and cooling thermoelectric power plants. Variability in water quantity and temperature due to climate change could reduce the performance and reliability of individual power plants and of the electric grid as a system. While studies have modeled water usage in power systems planning, few have linked grid operations with physical water constraints or with climate-induced changes in water resources to capture the role of the energy-water nexus in power systems flexibility and adequacy. In addition, many hydrologic and hydropower models have a limited representation of power sector water demands and grid interaction opportunities of demand response and ancillary services. A multi-model framework was developed to integrate and harmonize electricity, water, and climate models, allowing for high-resolution simulation of the spatial, temporal, and physical dynamics of these interacting systems. The San Juan River basin in the Southwestern U.S., which contains thermoelectric power plants, hydropower facilities, and multiple non-energy water demands, was chosen as a case study. Downscaled data from three global climate models and predicted regional water demand changes were implemented in the simulations. The Variable Infiltration Capacity hydrologic model was used to project inflows, ambient air temperature, and humidity in the San Juan River Basin. Resulting river operations, water deliveries, water shortage sharing agreements, new water demands, and hydroelectricity generation at the basin-scale were estimated with RiverWare. The impacts of water availability and temperature on electric grid dispatch, curtailment, cooling water usage, and electricity generation cost were modeled in PLEXOS. Lack of water availability resulting from climate, new water demands, and shortage sharing agreements will require thermoelectric generators to drastically decrease power production, as much as 50

  10. 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

  11. A discrete-continuous choice model of climate change impacts on energy

    International Nuclear Information System (INIS)

    Morrison, W.N.; Mendelsohn, R.

    1998-01-01

    This paper estimates a discrete-continuous fuel choice model in order to explore climate impacts on the energy sector. The model is estimated on a national data set of firms and households. The results reveal that actors switch from oil in cold climates to electricity and natural gas in warm climates and that fuel-specific expenditures follow a U-shaped relationship with respect to temperature. The model implies that warming will increase American energy expenditures, reflecting a sizable welfare damage

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE...... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures...... the Medieval Climate Anomaly and the Little Ice Age estimated from paleoclimate reconstructions. This in turn could be a result of errors in the reconstructions of volcanic and/or solar radiative forcing used to drive the models or the incomplete representation of certain processes or variability within...

  13. Isotopes as validation tools for global climate models

    International Nuclear Information System (INIS)

    Henderson-Sellers, A.

    2001-01-01

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

  14. Towards a regional climate model coupled to a comprehensive hydrological model

    Science.gov (United States)

    Rasmussen, S. H.; Drews, M.; Christensen, J. H.; Butts, M. B.; Jensen, K. H.; Refsgaard, J.; Hydrological ModellingAssessing Climate Change Impacts At Different Scales (Hyacints)

    2010-12-01

    When planing new ground water abstractions wells, building areas, roads or other land use activities information about expected future groundwater table location for the lifetime of the construction may be critical. The life time of an abstraction well can be expected to be more than 50 years, while if for buildings may be up to 100 years or more. The construction of an abstraction well is expensive and it is important to know if clean groundwater is available for its expected life time. The future groundwater table is depending on the future climate. With climate change the hydrology is expected to change as well. Traditionally, this assessment has been done by driving hydrological models with output from a climate model. In this way feedback between the groundwater hydrology and the climate is neglected. Neglecting this feedback can lead to imprecise or wrong results. The goal of this work is to couple the regional climate model HIRHAM (Christensen et al. 2006) to the hydrological model MIKE SHE (Graham and Butts, 2006). The coupling exploits the new OpenMI technology that provides a standardized interface to define, describe and transfer data on a time step basis between software components that run simultaneously (Gregersen et al., 2007). HIRHAM runs on a UNIX platform whereas MIKE SHE and OpenMI are under WINDOWS. Therefore the first critical task has been to develop an effective communication link between the platforms. The first step towards assessing the coupled models performance are addressed by looking at simulated land-surface atmosphere feedback through variables such as evapotranspiration, sensible heat flux and soil moisture content. Christensen, O.B., Drews, M., Christensen, J.H., Dethloff, K., Ketelsen, K., Hebestadt, I. and Rinke, A. (2006) The HIRHAM Regional Climate Model. Version 5; DMI Scientific Report 0617. Danish Meteorological Institute. Graham, D.N. and Butts, M.B. (2005) Flexible, integrated watershed modelling with MIKE SHE, In

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

    International Nuclear Information System (INIS)

    Caneill, J.Y.; Hakkarinen, C.

    1992-01-01

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

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

    International Nuclear Information System (INIS)

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

    1998-01-01

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

  17. 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

  18. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2018-01-01

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

  20. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

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

  1. 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.

  2. 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

  3. Modeling climatic effects of anthropogenic CO2 emissions: Unknowns and uncertainties

    Science.gov (United States)

    Soon, W.; Baliunas, S.; Idso, S.; Kondratyev, K. Ya.; Posmentier, E. S.

    2001-12-01

    A likelihood of disastrous global environmental consequences has been surmised as a result of projected increases in anthropogenic greenhouse gas emissions. These estimates are based on computer climate modeling, a branch of science still in its infancy despite recent, substantial strides in knowledge. Because the expected anthropogenic climate forcings are relatively small compared to other background and forcing factors (internal and external), the credibility of the modeled global and regional responses rests on the validity of the models. We focus on this important question of climate model validation. Specifically, we review common deficiencies in general circulation model calculations of atmospheric temperature, surface temperature, precipitation and their spatial and temporal variability. These deficiencies arise from complex problems associated with parameterization of multiply-interacting climate components, forcings and feedbacks, involving especially clouds and oceans. We also review examples of expected climatic impacts from anthropogenic CO2 forcing. Given the host of uncertainties and unknowns in the difficult but important task of climate modeling, the unique attribution of observed current climate change to increased atmospheric CO2 concentration, including the relatively well-observed latest 20 years, is not possible. We further conclude that the incautious use of GCMs to make future climate projections from incomplete or unknown forcing scenarios is antithetical to the intrinsically heuristic value of models. Such uncritical application of climate models has led to the commonly-held but erroneous impression that modeling has proven or substantiated the hypothesis that CO2 added to the air has caused or will cause significant global warming. An assessment of the positive skills of GCMs and their use in suggesting a discernible human influence on global climate can be found in the joint World Meteorological Organisation and United Nations

  4. 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

  5. High Resolution Modeling of Hurricanes in a Climate Context

    Science.gov (United States)

    Knutson, T. R.

    2007-12-01

    Modeling of tropical cyclone activity in a climate context initially focused on simulation of relatively weak tropical storm-like disturbances as resolved by coarse grid (200 km) global models. As computing power has increased, multi-year simulations with global models of grid spacing 20-30 km have become feasible. Increased resolution also allowed for simulation storms of increasing intensity, and some global models generate storms of hurricane strength, depending on their resolution and other factors, although detailed hurricane structure is not simulated realistically. Results from some recent high resolution global model studies are reviewed. An alternative for hurricane simulation is regional downscaling. An early approach was to embed an operational (GFDL) hurricane prediction model within a global model solution, either for 5-day case studies of particular model storm cases, or for "idealized experiments" where an initial vortex is inserted into an idealized environments derived from global model statistics. Using this approach, hurricanes up to category five intensity can be simulated, owing to the model's relatively high resolution (9 km grid) and refined physics. Variants on this approach have been used to provide modeling support for theoretical predictions that greenhouse warming will increase the maximum intensities of hurricanes. These modeling studies also simulate increased hurricane rainfall rates in a warmer climate. The studies do not address hurricane frequency issues, and vertical shear is neglected in the idealized studies. A recent development is the use of regional model dynamical downscaling for extended (e.g., season-length) integrations of hurricane activity. In a study for the Atlantic basin, a non-hydrostatic model with grid spacing of 18km is run without convective parameterization, but with internal spectral nudging toward observed large-scale (basin wavenumbers 0-2) atmospheric conditions from reanalyses. Using this approach, our

  6. Climate change due to greenhouse effects in China as simulated by a regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Gao, X.J.; Zhao, Z.C.; Ding, Y.H.; Huang, R.H.; Giorgi, F. [National Climate Centre, Beijing (China)

    2001-07-01

    Impacts of greenhouse effects (2 x CO{sub 2}) upon climate change over China as simulated by a regional climate model over China (RegCM / China) have been investigated. The model was based on RegCM2 and was nested to a global coupled ocean-atmosphere model (CSIRO R21L9 AOGCM model). Results of the control run (1 x CO{sub 2}) indicated that simulations of surface air temperature and precipitation in China by RegCM are much better than that by the global coupled model because of a higher resolution. Results of sensitive experiment by RegCM with 2 x CO{sub 2} showed that the surface air temperature over China might increase remarkably due to greenhouse effect, especially in winter season and in North China. Precipitation might also increase in most parts of China due to the CO{sub 2} doubling.

  7. Climate change and watershed mercury export: a multiple projection and model analysis.

    Science.gov (United States)

    Golden, Heather E; Knightes, Christopher D; Conrads, Paul A; Feaster, Toby D; Davis, Gary M; Benedict, Stephen T; Bradley, Paul M

    2013-09-01

    Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling. Copyright © 2013 SETAC.

  8. Climate change and watershed mercury export: a multiple projection and model analysis

    Science.gov (United States)

    Golden, Heather E.; Knightes, Christopher D.; Conrads, Paul; Feaster, Toby D.; Davis, Gary M.; Benedict, Stephen T.; Bradley, Paul M.

    2013-01-01

    Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

  9. The regional aerosol-climate model REMO-HAM

    Directory of Open Access Journals (Sweden)

    J.-P. Pietikäinen

    2012-11-01

    Full Text Available REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes most of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM is coupled with a two-moment stratiform cloud scheme. On the other hand, REMO-HAM does not include an online coupled aerosol-radiation nor a secondary organic aerosol module. In this work, we evaluate the model and compare the results against ECHAM5-HAM and measurements. Four different measurement sites were chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50 × 50 km2 and 10 × 10 km2. Based on our simulations, REMO-HAM is in reasonable agreement with the measured values. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. Since we did not use activation nor kinetic nucleation for the boundary layer, the total number concentrations are somewhat underestimated. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we show that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.

  10. Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

    Science.gov (United States)

    Wanders, N.; Van Lanen, H. A. J.

    2015-03-01

    Hydrological drought characteristics (drought in groundwater and streamflow) likely will change in the 21st century as a result of climate change. The magnitude and directionality of these changes and their dependency on climatology and catchment characteristics, however, is uncertain. In this study a conceptual hydrological model was forced by downscaled and bias-corrected outcome from three general circulation models for the SRES A2 emission scenario (GCM forced models), and the WATCH Forcing Data set (reference model). The threshold level method was applied to investigate drought occurrence, duration and severity. Results for the control period (1971-2000) show that the drought characteristics of each GCM forced model reasonably agree with the reference model for most of the climate types, suggesting that the climate models' results after post-processing produce realistic outcomes for global drought analyses. For the near future (2021-2050) and far future (2071-2100) the GCM forced models show a decrease in drought occurrence for all major climates around the world and increase of both average drought duration and deficit volume of the remaining drought events. The largest decrease in hydrological drought occurrence is expected in cold (D) climates where global warming results in a decreased length of the snow season and an increased precipitation. In the dry (B) climates the smallest decrease in drought occurrence is expected to occur, which probably will lead to even more severe water scarcity. However, in the extreme climate regions (desert and polar), the drought analysis for the control period showed that projections of hydrological drought characteristics are most uncertain. On a global scale the increase in hydrological drought duration and severity in multiple regions will lead to a higher impact of drought events, which should motivate water resource managers to timely anticipate the increased risk of more severe drought in groundwater and streamflow

  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. 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

  13. 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.

  14. Modelling Interglacial Climate

    DEFF Research Database (Denmark)

    Pedersen, Rasmus Anker

    the impact of a changing sea ice cover. The first part focusses on the last interglacial climate (125,000 years before present) which was characterized by substantial warming at high northern latitudes due to an increased insolation during summer. The simulations reveal that the oceanic changes dominate......Past warm climate states could potentially provide information on future global warming. The past warming was driven by changed insolation rather than an increased greenhouse effect, and thus the warm climate states are expected to be different. Nonetheless, the response of the climate system......, 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...

  15. A flexible climate model for use in integrated assessments

    Science.gov (United States)

    Sokolov, A. P.; Stone, P. H.

    Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model's sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO2 are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM

  16. 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

  17. Regional model simulations of New Zealand climate

    Science.gov (United States)

    Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

    1998-03-01

    Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

  18. Bringing a Realistic Global Climate Modeling Experience to a Broader Audience

    Science.gov (United States)

    Sohl, L. E.; Chandler, M. A.; Zhou, J.

    2010-12-01

    EdGCM, the Educational Global Climate Model, was developed with the goal of helping students learn about climate change and climate modeling by giving them the ability to run a genuine NASA global climate model (GCM) on a desktop computer. Since EdGCM was first publicly released in January 2005, tens of thousands of users on seven continents have downloaded the software. EdGCM has been utilized by climate science educators from middle school through graduate school levels, and on occasion even by researchers who otherwise do not have ready access to climate model at national labs in the U.S. and elsewhere. The EdGCM software is designed to walk users through the same process a climate scientist would use in designing and running simulations, and analyzing and visualizing GCM output. Although the current interface design gives users a clear view of some of the complexities involved in using a climate model, it can be daunting for users whose main focus is on climate science rather than modeling per se. As part of the work funded by NASA’s Global Climate Change Education (GCCE) program, we will begin modifications to the user interface that will improve the accessibility of EdGCM to a wider array of users, especially at the middle school and high school levels, by: 1) Developing an automated approach (a “wizard”) to simplify the user experience in setting up new climate simulations; 2) Produce a catalog of “rediscovery experiments” that allow users to reproduce published climate model results, and in some cases compare model projections to real world data; and 3) Enhance distance learning and online learning opportunities through the development of a web-based interface. The prototypes for these modifications will then be presented to educators belonging to an EdGCM Users Group for feedback, so that we can further refine the EdGCM software, and thus deliver the tools and materials educators want and need across a wider range of learning environments.

  19. School climate, peer victimization, and academic achievement: results from a multi-informant study.

    Science.gov (United States)

    Wang, Weijun; Vaillancourt, Tracy; Brittain, Heather L; McDougall, Patricia; Krygsman, Amanda; Smith, David; Cunningham, Charles E; Haltigan, J D; Hymel, Shelley

    2014-09-01

    School-level school climate was examined in relation to self-reported peer victimization and teacher-rated academic achievement (grade point average; GPA). Participants included a sample of 1,023 fifth-grade children nested within 50 schools. Associations between peer victimization, school climate, and GPA were examined using multilevel modeling, with school climate as a contextual variable. Boys and girls reported no differences in victimization by their peers, although boys had lower GPAs than girls. Peer victimization was related to lower GPA and to a poorer perception of school climate (individual-level), which was also associated with lower GPA. Results of multilevel analyses revealed that peer victimization was again negatively associated with GPA, and that lower school-level climate was associated with lower GPA. Although no moderating effects of school-level school climate or sex were observed, the relation between peer victimization and GPA remained significant after taking into account (a) school-level climate scores, (b) individual variability in school-climate scores, and (c) several covariates--ethnicity, absenteeism, household income, parental education, percentage of minority students, type of school, and bullying perpetration. These findings underscore the importance of a positive school climate for academic success and viewing school climate as a fundamental collective school outcome. Results also speak to the importance of viewing peer victimization as being harmfully linked to students' academic performance. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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

    Science.gov (United States)

    Alexandru, Adelina; Sushama, Laxmi

    2015-08-01

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

  1. Estimating daily climatologies for climate indices derived from climate model data and observations

    Science.gov (United States)

    Mahlstein, Irina; Spirig, Christoph; Liniger, Mark A; Appenzeller, Christof

    2015-01-01

    Climate indices help to describe the past, present, and the future climate. They are usually closer related to possible impacts and are therefore more illustrative to users than simple climate means. Indices are often based on daily data series and thresholds. It is shown that the percentile-based thresholds are sensitive to the method of computation, and so are the climatological daily mean and the daily standard deviation, which are used for bias corrections of daily climate model data. Sample size issues of either the observed reference period or the model data lead to uncertainties in these estimations. A large number of past ensemble seasonal forecasts, called hindcasts, is used to explore these sampling uncertainties and to compare two different approaches. Based on a perfect model approach it is shown that a fitting approach can improve substantially the estimates of daily climatologies of percentile-based thresholds over land areas, as well as the mean and the variability. These improvements are relevant for bias removal in long-range forecasts or predictions of climate indices based on percentile thresholds. But also for climate change studies, the method shows potential for use. Key Points More robust estimates of daily climate characteristics Statistical fitting approach Based on a perfect model approach PMID:26042192

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

    Directory of Open Access Journals (Sweden)

    A Michelle Lawing

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

  3. Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

    Science.gov (United States)

    Erfanian, A.; Fomenko, L.; Wang, G.

    2016-12-01

    Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

  4. A piecewise modeling approach for climate sensitivity studies: Tests with a shallow-water model

    Science.gov (United States)

    Shao, Aimei; Qiu, Chongjian; Niu, Guo-Yue

    2015-10-01

    In model-based climate sensitivity studies, model errors may grow during continuous long-term integrations in both the "reference" and "perturbed" states and hence the climate sensitivity (defined as the difference between the two states). To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.

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

    Science.gov (United States)

    Flanagan, S.; Hurtt, G. C.; Fisk, J. P.; Rourke, O.

    2012-12-01

    A robust understanding of the sensitivity of the pattern, structure, and dynamics of ecosystems to climate, climate variability, and climate change is needed to predict ecosystem responses to current and projected climate change. We present results of a study designed to first quantify the sensitivity of ecosystems to climate through the use of climate and ecosystem data, and then use the results to test the sensitivity of the climate data in a state-of the art ecosystem model. A database of available ecosystem characteristics such as mean canopy height, above ground biomass, and basal area was constructed from sources like the National Biomass and Carbon Dataset (NBCD). The ecosystem characteristics were then paired by latitude and longitude with the corresponding climate characteristics temperature, precipitation, photosynthetically active radiation (PAR) and dew point that were retrieved from the North American Regional Reanalysis (NARR). The average yearly and seasonal means of the climate data, and their associated maximum and minimum values, over the 1979-2010 time frame provided by NARR were constructed and paired with the ecosystem data. The compiled results provide natural patterns of vegetation structure and distribution with regard to climate data. An advanced ecosystem model, the Ecosystem Demography model (ED), was then modified to allow yearly alterations to its mechanistic climate lookup table and used to predict the sensitivities of ecosystem pattern, structure, and dynamics to climate data. The combined ecosystem structure and climate data results were compared to ED's output to check the validity of the model. After verification, climate change scenarios such as those used in the last IPCC were run and future forest structure changes due to climate sensitivities were identified. The results of this study can be used to both quantify and test key relationships for next generation models. The sensitivity of ecosystem characteristics to climate data

  7. 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.

  8. The transferability of hydrological models under nonstationary climatic conditions

    Directory of Open Access Journals (Sweden)

    C. Z. Li

    2012-04-01

    Full Text Available This paper investigates issues involved in calibrating hydrological models against observed data when the aim of the modelling is to predict future runoff under different climatic conditions. To achieve this objective, we tested two hydrological models, DWBM and SIMHYD, using data from 30 unimpaired catchments in Australia which had at least 60 yr of daily precipitation, potential evapotranspiration (PET, and streamflow data. Nash-Sutcliffe efficiency (NSE, modified index of agreement (d1 and water balance error (WBE were used as performance criteria. We used a differential split-sample test to split up the data into 120 sub-periods and 4 different climatic sub-periods in order to assess how well the calibrated model could be transferred different periods. For each catchment, the models were calibrated for one sub-period and validated on the other three. Monte Carlo simulation was used to explore parameter stability compared to historic climatic variability. The chi-square test was used to measure the relationship between the distribution of the parameters and hydroclimatic variability. The results showed that the performance of the two hydrological models differed and depended on the model calibration. We found that if a hydrological model is set up to simulate runoff for a wet climate scenario then it should be calibrated on a wet segment of the historic record, and similarly a dry segment should be used for a dry climate scenario. The Monte Carlo simulation provides an effective and pragmatic approach to explore uncertainty and equifinality in hydrological model parameters. Some parameters of the hydrological models are shown to be significantly more sensitive to the choice of calibration periods. Our findings support the idea that when using conceptual hydrological models to assess future climate change impacts, a differential split-sample test and Monte Carlo simulation should be used to quantify uncertainties due to

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

    Directory of Open Access Journals (Sweden)

    Alvaro Sordo-Ward

    2017-11-01

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

  10. Generating synthetic wave climates for coastal modelling: a linear mixed modelling approach

    Science.gov (United States)

    Thomas, C.; Lark, R. M.

    2013-12-01

    Numerical coastline morphological evolution models require wave climate properties to drive morphological change through time. Wave climate properties (typically wave height, period and direction) may be temporally fixed, culled from real wave buoy data, or allowed to vary in some way defined by a Gaussian or other pdf. However, to examine sensitivity of coastline morphologies to wave climate change, it seems desirable to be able to modify wave climate time series from a current to some new state along a trajectory, but in a way consistent with, or initially conditioned by, the properties of existing data, or to generate fully synthetic data sets with realistic time series properties. For example, mean or significant wave height time series may have underlying periodicities, as revealed in numerous analyses of wave data. Our motivation is to develop a simple methodology to generate synthetic wave climate time series that can change in some stochastic way through time. We wish to use such time series in a coastline evolution model to test sensitivities of coastal landforms to changes in wave climate over decadal and centennial scales. We have worked initially on time series of significant wave height, based on data from a Waverider III buoy located off the coast of Yorkshire, England. The statistical framework for the simulation is the linear mixed model. The target variable, perhaps after transformation (Box-Cox), is modelled as a multivariate Gaussian, the mean modelled as a function of a fixed effect, and two random components, one of which is independently and identically distributed (iid) and the second of which is temporally correlated. The model was fitted to the data by likelihood methods. We considered the option of a periodic mean, the period either fixed (e.g. at 12 months) or estimated from the data. We considered two possible correlation structures for the second random effect. In one the correlation decays exponentially with time. In the second

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

    International Nuclear Information System (INIS)

    Husain, T.; Chowdhury, S.

    2009-01-01

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

  12. Developing climatic scenarios for pesticide fate modelling in Europe

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  13. Modeling the impact of climate change in Germany with biosphere models for long-term safety assessment of nuclear waste repositories

    International Nuclear Information System (INIS)

    Staudt, C.; Semiochkina, N.; Kaiser, J.C.; Pröhl, G.

    2013-01-01

    Biosphere models are used to evaluate the exposure of populations to radionuclides from a deep geological repository. Since the time frame for assessments of long-time disposal safety is 1 million years, potential future climate changes need to be accounted for. Potential future climate conditions were defined for northern Germany according to model results from the BIOCLIM project. Nine present day reference climate regions were defined to cover those future climate conditions. A biosphere model was developed according to the BIOMASS methodology of the IAEA and model parameters were adjusted to the conditions at the reference climate regions. The model includes exposure pathways common to those reference climate regions in a stylized biosphere and relevant to the exposure of a hypothetical self-sustaining population at the site of potential radionuclide contamination from a deep geological repository. The end points of the model are Biosphere Dose Conversion factors (BDCF) for a range of radionuclides and scenarios normalized for a constant radionuclide concentration in near-surface groundwater. Model results suggest an increased exposure of in dry climate regions with a high impact of drinking water consumption rates and the amount of irrigation water used for agriculture. - Highlights: ► We model Biosphere Dose Conversion Factors for a representative group exposed to radionuclides from a waste repository. ► The BDCF are modeled for different soil types. ► One model is used for the assessment of the influence of climate change during the disposal time frame.

  14. Climate Modeling and Causal Identification for Sea Ice Predictability

    Energy Technology Data Exchange (ETDEWEB)

    Hunke, Elizabeth Clare [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urrego Blanco, Jorge Rolando [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urban, Nathan Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-02-12

    This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments in which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.

  15. Global Climate Models for the Classroom: The Educational Impact of Student Work with a Key Tool of Climate Scientists

    Science.gov (United States)

    Bush, D. F.; Sieber, R.; Seiler, G.; Chandler, M. A.; Chmura, G. L.

    2017-12-01

    Efforts to address climate change require public understanding of Earth and climate science. To meet this need, educators require instructional approaches and scientific technologies that overcome cultural barriers to impart conceptual understanding of the work of climate scientists. We compared student inquiry learning with now ubiquitous climate education toy models, data and tools against that which took place using a computational global climate model (GCM) from the National Aeronautics and Space Administration (NASA). Our study at McGill University and John Abbott College in Montreal, QC sheds light on how best to teach the research processes important to Earth and climate scientists studying atmospheric and Earth system processes but ill-understood by those outside the scientific community. We followed a pre/post, control/treatment experimental design that enabled detailed analysis and statistically significant results. Our research found more students succeed at understanding climate change when exposed to actual climate research processes and instruments. Inquiry-based education with a GCM resulted in significantly higher scores pre to post on diagnostic exams (quantitatively) and more complete conceptual understandings (qualitatively). We recognize the difficulty in planning and teaching inquiry with complex technology and we also found evidence that lectures support learning geared toward assessment exams.

  16. 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

  17. Tundra shrubification and tree-line advance amplify arctic climate warming: results from an individual-based dynamic vegetation model

    Science.gov (United States)

    Zhang, Wenxin; Miller, Paul A.; Smith, Benjamin; Wania, Rita; Koenigk, Torben; Döscher, Ralf

    2013-09-01

    One major challenge to the improvement of regional climate scenarios for the northern high latitudes is to understand land surface feedbacks associated with vegetation shifts and ecosystem biogeochemical cycling. We employed a customized, Arctic version of the individual-based dynamic vegetation model LPJ-GUESS to simulate the dynamics of upland and wetland ecosystems under a regional climate model-downscaled future climate projection for the Arctic and Subarctic. The simulated vegetation distribution (1961-1990) agreed well with a composite map of actual arctic vegetation. In the future (2051-2080), a poleward advance of the forest-tundra boundary, an expansion of tall shrub tundra, and a dominance shift from deciduous to evergreen boreal conifer forest over northern Eurasia were simulated. Ecosystems continued to sink carbon for the next few decades, although the size of these sinks diminished by the late 21st century. Hot spots of increased CH4 emission were identified in the peatlands near Hudson Bay and western Siberia. In terms of their net impact on regional climate forcing, positive feedbacks associated with the negative effects of tree-line, shrub cover and forest phenology changes on snow-season albedo, as well as the larger sources of CH4, may potentially dominate over negative feedbacks due to increased carbon sequestration and increased latent heat flux.

  18. Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

    Science.gov (United States)

    Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

    2012-01-01

    Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

  19. 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/).

  20. The Swedish Regional Climate Modelling Programme, SWECLIM: a review.

    Science.gov (United States)

    Rummukainen, Markku; Bergström, Sten; Persson, Gunn; Rodhe, Johan; Tjernström, Michael

    2004-06-01

    The Swedish Regional Climate Modelling Programme, SWECLIM, was a 6.5-year national research network for regional climate modeling, regional climate change projections and hydrological impact assessment and information to a wide range of stakeholders. Most of the program activities focussed on the regional climate system of Northern Europe. This led to the establishment of an advanced, coupled atmosphere-ocean-hydrology regional climate model system, a suite of regional climate change projections and progress on relevant data and process studies. These were, in turn, used for information and educational purposes, as a starting point for impact analyses on different societal sectors and provided contributions also to international climate research.

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

    CSIR Research Space (South Africa)

    Engelbrecht, FA

    2011-12-01

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

  2. ESCAPE: an integrated climate model for the EC

    International Nuclear Information System (INIS)

    Rotmans, J.

    1992-01-01

    A framework has been developed for the evaluation of policy options for climate change, called ESCAPE (Evaluation of Strategies to address Climate change by Adapting to and Preventing Emissions). ESCAPE consists of a suite of linked models which enables scenarios of greenhouse gas emissions to be constructed and their impact on global and regional climate and sea level and sectors of the European economy to be assessed. Conclusions resulting from simulations with the ESCAPE 1.1 model include: the major problem of a climate change for the EC is a sea level rise; Greece, Italy, Portugal and Spain will be faced with higher costs in the agricultural sector; worldwide implementation of an EC carbon tax leads to about 12% lower worldwide CO 2 emissions; to stabilize CO 2 emissions an Ecotax of 18 dollars per barrel would be required; and in all cases the rate of global temperature increase will be above the rate of 0.1 degree C per decade for the coming 40 years. 2 figs

  3. Modeling the impact of climate change in Germany with biosphere models for long-term safety assessment of nuclear waste repositories.

    Science.gov (United States)

    Staudt, C; Semiochkina, N; Kaiser, J C; Pröhl, G

    2013-01-01

    Biosphere models are used to evaluate the exposure of populations to radionuclides from a deep geological repository. Since the time frame for assessments of long-time disposal safety is 1 million years, potential future climate changes need to be accounted for. Potential future climate conditions were defined for northern Germany according to model results from the BIOCLIM project. Nine present day reference climate regions were defined to cover those future climate conditions. A biosphere model was developed according to the BIOMASS methodology of the IAEA and model parameters were adjusted to the conditions at the reference climate regions. The model includes exposure pathways common to those reference climate regions in a stylized biosphere and relevant to the exposure of a hypothetical self-sustaining population at the site of potential radionuclide contamination from a deep geological repository. The end points of the model are Biosphere Dose Conversion factors (BDCF) for a range of radionuclides and scenarios normalized for a constant radionuclide concentration in near-surface groundwater. Model results suggest an increased exposure of in dry climate regions with a high impact of drinking water consumption rates and the amount of irrigation water used for agriculture. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. The Importance of Considering the Temporal Distribution of Climate Variables for Ecological-Economic Modeling to Calculate the Consequences of Climate Change for Agriculture

    Science.gov (United States)

    Plegnière, Sabrina; Casper, Markus; Hecker, Benjamin; Müller-Fürstenberger, Georg

    2014-05-01

    The basis of many models to calculate and assess climate change and its consequences are annual means of temperature and precipitation. This method leads to many uncertainties especially at the regional or local level: the results are not realistic or too coarse. Particularly in agriculture, single events and the distribution of precipitation and temperature during the growing season have enormous influences on plant growth. Therefore, the temporal distribution of climate variables should not be ignored. To reach this goal, a high-resolution ecological-economic model was developed which combines a complex plant growth model (STICS) and an economic model. In this context, input data of the plant growth model are daily climate values for a specific climate station calculated by the statistical climate model (WETTREG). The economic model is deduced from the results of the plant growth model STICS. The chosen plant is corn because corn is often cultivated and used in many different ways. First of all, a sensitivity analysis showed that the plant growth model STICS is suitable to calculate the influences of different cultivation methods and climate on plant growth or yield as well as on soil fertility, e.g. by nitrate leaching, in a realistic way. Additional simulations helped to assess a production function that is the key element of the economic model. Thereby the problems when using mean values of temperature and precipitation in order to compute a production function by linear regression are pointed out. Several examples show why a linear regression to assess a production function based on mean climate values or smoothed natural distribution leads to imperfect results and why it is not possible to deduce a unique climate factor in the production function. One solution for this problem is the additional consideration of stress indices that show the impairment of plants by water or nitrate shortage. Thus, the resulting model takes into account not only the ecological

  5. Modelling the Impacts of Climate Change on Tropospheric Ozone over three Centuries

    Science.gov (United States)

    Brandt Hedegaard, Gitte; Brandt, Jørgen; Christensen, Jesper H.; Gross, Allan; May, Wihelm; Hansen, Kaj M.; Skjøth, Carsten A.

    2010-05-01

    So far reduction of the anthropogenic emissions of chemical species to the atmosphere has been profoundly investigated. However, new research indicates that climate change on its own also has a significant impact on the future air pollution levels. Climate Change and its impact on air pollution levels are currently studied by a number of research groups using, global, hemispherical and regional modelling systems. In the Department of Atmospheric Environment, National Environmental Research Institute (NERI), Aarhus University, in Denmark, we have developed a hemispherical model system which is based on the DEHM model (Christensen, 1997; Frohn et al., 2002a; Frohn et al., 2002b). In the DEHM modelling system an option for modelling the impacts of climate change has been included by using meteorological input from global climate models. Here we present results by using climate data that are provided by the ECHAM5/MPI-OM Atmosphere-Ocean General Circulation Model (May, 2008; Roeckner et al., 2003). In the current experiment the anthropogenic emissions in the chemistry model DEHM are kept constant on a 2000 level to separate out the signal of climate change on air pollutants while the meteorological drivers simulated by the ECHAM5/MPI-OM climate model is based on the IPCC SRES A1B Scenario. To save computing time the experiment is carried out in time-slices representing four centuries (1890s, 1990s, 2090s and the 2190s). The results show that the dominating impacts from climate change on a large number of the chemical species are related to the predicted temperature increase. This temperature affects chemistry as well as emissions from nature. The largest changes in both meteorology and air quality is found to happen in the 21st century. However, significant changes are also found in some parameters including tropospheric ozone in the following century. In general the background ozone concentrations is predicted to decrease at surface level however in the densely

  6. Understanding National Models for Climate Assessments

    Science.gov (United States)

    Dave, A.; Weingartner, K.

    2017-12-01

    National-level climate assessments have been produced or are underway in a number of countries. These efforts showcase a variety of approaches to mapping climate impacts onto human and natural systems, and involve a variety of development processes, organizational structures, and intended purposes. This presentation will provide a comparative overview of national `models' for climate assessments worldwide, drawing from a geographically diverse group of nations with varying capacities to conduct such assessments. Using an illustrative sampling of assessment models, the presentation will highlight the range of assessment mandates and requirements that drive this work, methodologies employed, focal areas, and the degree to which international dimensions are included for each nation's assessment. This not only allows the U.S. National Climate Assessment to be better understood within an international context, but provides the user with an entry point into other national climate assessments around the world, enabling a better understanding of the risks and vulnerabilities societies face.

  7. Modeling large-scale human alteration of land surface hydrology and climate

    Science.gov (United States)

    Pokhrel, Yadu N.; Felfelani, Farshid; Shin, Sanghoon; Yamada, Tomohito J.; Satoh, Yusuke

    2017-12-01

    Rapidly expanding human activities have profoundly affected various biophysical and biogeochemical processes of the Earth system over a broad range of scales, and freshwater systems are now amongst the most extensively altered ecosystems. In this study, we examine the human-induced changes in land surface water and energy balances and the associated climate impacts using a coupled hydrological-climate model framework which also simulates the impacts of human activities on the water cycle. We present three sets of analyses using the results from two model versions—one with and the other without considering human activities; both versions are run in offline and coupled mode resulting in a series of four experiments in total. First, we examine climate and human-induced changes in regional water balance focusing on the widely debated issue of the desiccation of the Aral Sea in central Asia. Then, we discuss the changes in surface temperature as a result of changes in land surface energy balance due to irrigation over global and regional scales. Finally, we examine the global and regional climate impacts of increased atmospheric water vapor content due to irrigation. Results indicate that the direct anthropogenic alteration of river flow in the Aral Sea basin resulted in the loss of 510 km3 of water during the latter half of the twentieth century which explains about half of the total loss of water from the sea. Results of irrigation-induced changes in surface energy balance suggest a significant surface cooling of up to 3.3 K over 1° grids in highly irrigated areas but a negligible change in land surface temperature when averaged over sufficiently large global regions. Results from the coupled model indicate a substantial change in 2 m air temperature and outgoing longwave radiation due to irrigation, highlighting the non-local (regional and global) implications of irrigation. These results provide important insights on the direct human alteration of land surface

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

    Science.gov (United States)

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

    2012-04-01

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

  9. Ensemble catchment hydrological modelling for climate change impact analysis

    Science.gov (United States)

    Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

    2014-05-01

    , more than in high flow conditions. Hence, the mechanism of the slow flow component simulation requires further attention. It is concluded that a multi-model ensemble approach where different plausible model structures are applied, is extremely useful. It improves the reliability of climate change impact results and allows decision making to be based on uncertainty assessment that includes model structure related uncertainties. References: Ntegeka, V., Baguis, P., Roulin, E., Willems, P., 2014. Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508C, 307-321 Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Willems, P., De Smedt, F., Batelaan, O., 2013. Climate change impact on river flows and catchment hydrology: a comparison of two spatially distributed models. Hydrological Processes, 27(25), 3649-3662. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Van Steenbergen, N., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation. Journal of Hydrology, in press. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of climate scenario impact predictions by a lumped and distributed model ensemble. Journal of Hydrology, in revision.

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

    Science.gov (United States)

    Parsons, Luke Alexander

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

  11. 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

    1996-12-31

    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)

  12. 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)

  13. Climate impact of transportation A model comparison

    NARCIS (Netherlands)

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

    2013-01-01

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

  14. Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific

    Science.gov (United States)

    Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B.

    2015-12-01

    Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study.

  15. Impact of climate changes on management plans for the St. Francois and Aylmer reservoirs : preliminary results

    International Nuclear Information System (INIS)

    Turcotte, R.; Fortin, L.G.; Pugin, S.; Cyr, J.F.; Picard, F.; Poirier, C.; Lacombe, P.

    2004-01-01

    Dams used for flood control, water supply, recreational activities and hydroelectricity in the province of Quebec are managed by the Centre d'Expertise Hydrique du Quebec (CEHQ). This paper addressed the issue of global warming and the changes that may occur in the hydrological regime within the next decades in response to predicted changes in climate. As a result of the changes in hydrological regime, there is a risk of losing the equilibrium between various objectives, identifiable through water management plans. The CEHQ is conducting a pilot study for the Saint-Francois and Aylmer reservoirs in order to develop a method to evaluate the adaptability of current management plans to climate change. The project is based on potential climate change scenarios as well as on deterministic and distributed hydrological models. Daily time steps are used to evaluate the hydrological impacts of climate change. CEHQ has developed a model that simulates the use of current management plans. The model makes it possible to evaluate and compare the occurrences where stream flows and water levels exceed critical values. The effectiveness of the management plans in both current and climate change scenarios can thereby be evaluated. Preliminary results suggest a possible increase in flood risk and fewer low water level occurrences. 18 refs., 4 tabs., 12 figs

  16. A prognostic pollen emissions model for climate models (PECM1.0

    Directory of Open Access Journals (Sweden)

    M. C. Wozniak

    2017-11-01

    Full Text Available We develop a prognostic model called Pollen Emissions for Climate Models (PECM for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus, evergreen needleleaf trees (Cupressaceae, Pinaceae, grasses (Poaceae; C3, C4, and ragweed (Ambrosia. This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4 over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1 a taxa-specific land cover database, phenology, and emission potential, and (2 a plant functional type (PFT land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions

  17. Intercomparison of four regional climate models for the German State of Saxonia

    Science.gov (United States)

    Kreienkamp, F.; Spekat, A.; Enke, W.

    2009-09-01

    Results from four regional climate models which focus on Central Europe are presented: CCLM, the climate version of the German Weather Service's Local Model - REMO, the regional dynamic model from the Max Planck Institute for Meteorology in Hamburg - STAR, the statistical model developed at the PIK Potsdam Institute and WETTREG, the statistic-dynamic model developed by the company CEC Potsdam. For the area of the German State of Saxonia a host of properties and indicators were analyzed aiming to show the models' abilities to reconstruct the current climate and compare climate model scenarios. These include a group of thermal indicators, such as the number of ice, frost, summer and hot days, the number of tropical nights; then there are hydrometeorological indicators such as the exceedance of low and high precipitation thresholds; humidity, cloudiness and wind indicators complement the array. A selection of them showing similarities and differences of the models investigated will be presented.

  18. 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.

  19. Overview of climate information needs for ecological effects models

    Energy Technology Data Exchange (ETDEWEB)

    Peer, R.L.

    1990-01-01

    Atmospheric scientists engaged in climate change research require a basic understanding of how ecological effects models incorporate climate. The report provides an overview of existing ecological models that might be used to model climate change effects on vegetation. Some agricultural models and statistical methods are also discussed. The weather input data requirements, weather simulation methods, and other model characteristics relevant to climate change research are described for a selected number of models. The ecological models are classified as biome, ecosystem, or tree models; the ecosystem models are further subdivided into species dynamics or process models. In general, ecological modelers have had to rely on readily available meteorological data such as temperature and rainfall. Although models are becoming more sophisticated in their treatment of weather and require more kinds of data (such as wind, solar radiation, or potential evapotranspiration), modelers are still hampered by a lack of data for many applications. Future directions of ecological effects models and the climate variables that will be required by the models are discussed.

  20. 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

  1. THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE.

    Science.gov (United States)

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

    2015-10-01

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

  2. Modeling forest dynamics along climate gradients in Bolivia

    Science.gov (United States)

    Seiler, C.; Hutjes, R. W. A.; Kruijt, B.; Quispe, J.; Añez, S.; Arora, V. K.; Melton, J. R.; Hickler, T.; Kabat, P.

    2014-05-01

    Dynamic vegetation models have been used to assess the resilience of tropical forests to climate change, but the global application of these modeling experiments often misrepresents carbon dynamics at a regional level, limiting the validity of future projections. Here a dynamic vegetation model (Lund Potsdam Jena General Ecosystem Simulator) was adapted to simulate present-day potential vegetation as a baseline for climate change impact assessments in the evergreen and deciduous forests of Bolivia. Results were compared to biomass measurements (819 plots) and remote sensing data. Using regional parameter values for allometric relations, specific leaf area, wood density, and disturbance interval, a realistic transition from the evergreen Amazon to the deciduous dry forest was simulated. This transition coincided with threshold values for precipitation (1400 mm yr-1) and water deficit (i.e., potential evapotranspiration minus precipitation) (-830 mm yr-1), beyond which leaf abscission became a competitive advantage. Significant correlations were found between modeled and observed values of seasonal leaf abscission (R2 = 0.6, p days. Decreasing rainfall trends were simulated to reduce GPP in the Amazon. The current model setup provides a baseline for assessing the potential impacts of climate change in the transition zone from wet to dry tropical forests in Bolivia.

  3. 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.

  4. Results from the BRACE 1.5 study: Climate change impacts of 1.5 C and 2 C warming

    Science.gov (United States)

    O'Neill, B. C.; Anderson, B.; Monaghan, A. J.; Ren, X.; Sanderson, B.; Tebaldi, C.

    2017-12-01

    In 2015, 195 countries negotiated the Paris Agreement on climate change, which set long-term goals of limiting global mean warming to well below 2 C and possibly 1.5 C. This event stimulated substantial scientific interest in climate outcomes and impacts on society associated with those levels of warming. Recently, the first set of global climate model simulations explicitly designed to meet those targets were undertaken with the Community Earth System Model (CESM) for use by the research community (Sanderson et al, accepted). The BRACE 1.5 project models societal impacts from these climate outcomes, combined with assumptions about future socioeconomic conditions according to the Shared Socioeconomic Pathways. These analyses build on a recently completed study of the Benefits of Reduced Anthropogenic Climate changE (BRACE), published as a set of 20 papers in Climatic Change, which examined the difference in impacts between two higher scenarios resulting in about 2.5 C and 3.7 C warming by late this century. BRACE 1.5 consists of a set of six papers to be submitted to a special collection in Environmental Research Letters that takes a similar approach but focuses on impacts at 1.5 and 2 C warming. We ask whether impacts differ substantially between the two climate scenarios, accounting for uncertainty in climate outcomes through the use of initial condition ensembles of CESM simulations, and in societal conditions by using alternative SSP-based development pathways. Impact assessment focuses on the health and agricultural sectors; modeling approaches include the use of a global mutli-region CGE model for economic analysis, both a process-based and an empirical crop model, a model of spatial population change, a model of climatic suitability for the aedes aegypti mosquito, and an epidemiological model of heat-related mortality. A methodological analysis also evaluates the use of climate model emulation techniques for providing climate information sufficient to

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

    International Nuclear Information System (INIS)

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

    1994-01-01

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

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

    Science.gov (United States)

    Stocker, T. F.

    2017-12-01

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

  7. 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 auch

  8. 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

  9. Ecological forecasting under climatic data uncertainty: a case study in phenological modeling

    International Nuclear Information System (INIS)

    Cook, Benjamin I; Terando, Adam; Steiner, Allison

    2010-01-01

    Forecasting ecological responses to climate change represents a challenge to the ecological community because models are often site-specific and climate data are lacking at appropriate spatial and temporal resolutions. We use a case study approach to demonstrate uncertainties in ecological predictions related to the driving climatic input data. We use observational records, derived observational datasets (e.g. interpolated observations from local weather stations and gridded data products) and output from general circulation models (GCM) in conjunction with site based phenology models to estimate the first flowering date (FFD) for three woody flowering species. Using derived observations over the modern time period, we find that cold biases and temperature trends lead to biased FFD simulations for all three species. Observational datasets resolved at the daily time step result in better FFD predictions compared to simulations using monthly resolution. Simulations using output from an ensemble of GCM and regional climate models over modern and future time periods have large intra-ensemble spreads and tend to underestimate observed FFD trends for the modern period. These results indicate that certain forcing datasets may be missing key features needed to generate accurate hindcasts at the local scale (e.g. trends, temporal resolution), and that standard modeling techniques (e.g. downscaling, ensemble mean, etc) may not necessarily improve the prediction of the ecological response. Studies attempting to simulate local ecological processes under modern and future climate forcing therefore need to quantify and propagate the climate data uncertainties in their simulations.

  10. 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

    2018-02-01

    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.

  11. Climate change impacts utilizing regional models for agriculture, hydrology and natural ecosystems

    Science.gov (United States)

    Kafatos, M.; Asrar, G. R.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Medvigy, D.; Prasad, A. K.; Smith, E.; Stack, D. H.; Tremback, C.; Walko, R. L.

    2012-12-01

    Climate change impacts the entire Earth but with crucial and often catastrophic impacts at local and regional levels. Extreme phenomena such as fires, dust storms, droughts and other natural hazards present immediate risks and challenges. Such phenomena will become more extreme as climate change and anthropogenic activities accelerate in the future. We describe a major project funded by NIFA (Grant # 2011-67004-30224), under the joint NSF-DOE-USDA Earth System Models (EaSM) program, to investigate the impacts of climate variability and change on the agricultural and natural (i.e. rangeland) ecosystems in the Southwest USA using a combination of historical and present observations together with climate, and ecosystem models, both in hind-cast and forecast modes. The applicability of the methodology to other regions is relevant (for similar geographic regions as well as other parts of the world with different agriculture and ecosystems) and should advance the state of knowledge for regional impacts of climate change. A combination of multi-model global climate projections from the decadal predictability simulations, to downscale dynamically these projections using three regional climate models, combined with remote sensing MODIS and other data, in order to obtain high-resolution climate data that can be used with hydrological and ecosystem models for impacts analysis, is described in this presentation. Such analysis is needed to assess the future risks and potential impacts of projected changes on these natural and managed ecosystems. The results from our analysis can be used by scientists to assist extended communities to determine agricultural coping strategies, and is, therefore, of interest to wide communities of stakeholders. In future work we will be including surface hydrologic modeling and water resources, extend modeling to higher resolutions and include significantly more crops and geographical regions with different weather and climate conditions

  12. A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence

    Directory of Open Access Journals (Sweden)

    Edlund Stefan

    2012-09-01

    Full Text Available Abstract Background The role of the Anopheles vector in malaria transmission and the effect of climate on Anopheles populations are well established. Models of the impact of climate change on the global malaria burden now have access to high-resolution climate data, but malaria surveillance data tends to be less precise, making model calibration problematic. Measurement of malaria response to fluctuations in climate variables offers a way to address these difficulties. Given the demonstrated sensitivity of malaria transmission to vector capacity, this work tests response functions to fluctuations in land surface temperature and precipitation. Methods This study of regional sensitivity of malaria incidence to year-to-year climate variations used an extended Macdonald Ross compartmental disease model (to compute malaria incidence built on top of a global Anopheles vector capacity model (based on 10 years of satellite climate data. The predicted incidence was compared with estimates from the World Health Organization and the Malaria Atlas. The models and denominator data used are freely available through the Eclipse Foundation’s Spatiotemporal Epidemiological Modeller (STEM. Results Although the absolute scale factor relating reported malaria to absolute incidence is uncertain, there is a positive correlation between predicted and reported year-to-year variation in malaria burden with an averaged root mean square (RMS error of 25% comparing normalized incidence across 86 countries. Based on this, the proposed measure of sensitivity of malaria to variations in climate variables indicates locations where malaria is most likely to increase or decrease in response to specific climate factors. Bootstrapping measures the increased uncertainty in predicting malaria sensitivity when reporting is restricted to national level and an annual basis. Results indicate a potential 20x improvement in accuracy if data were available at the level ISO 3166–2

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

    Science.gov (United States)

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

    2017-04-01

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

  14. Hydrological Modeling in Northern Tunisia with Regional Climate Model Outputs: Performance Evaluation and Bias-Correction in Present Climate Conditions

    Directory of Open Access Journals (Sweden)

    Asma Foughali

    2015-07-01

    Full Text Available This work aims to evaluate the performance of a hydrological balance model in a watershed located in northern Tunisia (wadi Sejnane, 378 km2 in present climate conditions using input variables provided by four regional climate models. A modified version (MBBH of the lumped and single layer surface model BBH (Bucket with Bottom Hole model, in which pedo-transfer parameters estimated using watershed physiographic characteristics are introduced is adopted to simulate the water balance components. Only two parameters representing respectively the water retention capacity of the soil and the vegetation resistance to evapotranspiration are calibrated using rainfall-runoff data. The evaluation criterions for the MBBH model calibration are: relative bias, mean square error and the ratio of mean actual evapotranspiration to mean potential evapotranspiration. Daily air temperature, rainfall and runoff observations are available from 1960 to 1984. The period 1960–1971 is selected for calibration while the period 1972–1984 is chosen for validation. Air temperature and precipitation series are provided by four regional climate models (DMI, ARP, SMH and ICT from the European program ENSEMBLES, forced by two global climate models (GCM: ECHAM and ARPEGE. The regional climate model outputs (precipitation and air temperature are compared to the observations in terms of statistical distribution. The analysis was performed at the seasonal scale for precipitation. We found out that RCM precipitation must be corrected before being introduced as MBBH inputs. Thus, a non-parametric quantile-quantile bias correction method together with a dry day correction is employed. Finally, simulated runoff generated using corrected precipitation from the regional climate model SMH is found the most acceptable by comparison with runoff simulated using observed precipitation data, to reproduce the temporal variability of mean monthly runoff. The SMH model is the most accurate to

  15. Palaeotemperature reconstructions of the European permafrost zone during Oxygen Isotope Stage 3 compared with climate model results.

    NARCIS (Netherlands)

    van Huissteden, J.; Vandenberghe, J.; Pollard, D.

    2003-01-01

    A palaeotemperature reconstruction based on periglacial phenomena in Europe north of approximately 51 °N, is compared with high-resolution regional climate model simulations of the marine oxygen isotope Stage 3 (Stage 3) palaeoclimate. The experiments represent Stage 3 warm (interstadial), Stage 3

  16. Climate vs grapevine pests and diseases worldwide: the first results of a global survey

    Directory of Open Access Journals (Sweden)

    Benjamin Bois

    2017-05-01

    Methods and results: Based on the answer of respondent about the main reported diseases/pests in their region, a severity index was calculated. Each region was geolocalised and data were compared to the WorldClim gridded climate database to document the range of climate conditions (growing season temperature and rainfall associated to the main diseases/pests. The potential climatic-induced changes of grapevine disease and pest geography by 2050 are assessed using agro-climate projections from the ARPEGE CNRM model, using the RCP 4.5 scenario. The preliminary results allow to determine the distribution of diseases as function of agroclimatic indicators. Conclusion: While the distribution of diseases differs according to the region of the world, the current analysis suggests that mildews remain the major phytosanitary threat in most of the regions. Powdery mildew, trunk diseases and viruses were reported in extremely diverse climatic conditions, including intermediate and wet regions.  Significance and impact of the study: This paper present an original methodology to address the relationship between grapevine disease and pest occurrences and climate. Such documentation is scarce in the current literature. Further analysis is currently being performed, including additional survey answers, climate indices and supplementary data collected (spatial extension, frequency of treatments… to better depict the challenges of grapevine phytosanitary management in a changing climate.

  17. GLOBAL CLIMATE MODEL:A COMPREHENSIVE TOOL IN CLIMATE CHANGE IMPACT STUDIES

    Directory of Open Access Journals (Sweden)

    Dharmaveer Singh

    2015-01-01

    Full Text Available There is growing concern, how and to what extent future changes in climate will affect human society and natural environments. Continuous emissions of Green House Gasses (GHGs at or above current rates will cause further warming. This, in turn, may modify global climate system during 21st century that very likely would have larger impacts than those observed during 20th century. At present, Global Climate Models (GCMs are only the most reliable tools available for studying behaviour of the climate system. This paper presents a comprehensive review of GCMs including their development and applications in climate change impacts studies. Following a discussion of the limitations of GCMs at regional and local scales, different approaches of downscaling are discussed in detail.

  18. An Investigation of Secondary Students' Mental Models of Climate Change and the Greenhouse Effect

    Science.gov (United States)

    Varela, Begoña; Sesto, Vanessa; García-Rodeja, Isabel

    2018-03-01

    There are several studies dealing with students' conceptions on climate change, but most of them refer to understanding before instruction. In contrast, this study investigates students' conceptions and describes the levels of sophistication of their mental models on climate change and the greenhouse effect. The participants were 40 secondary students (grade 7) in Spain. As a method of data collection, a questionnaire was designed with open-ended questions focusing on the mechanism, causes, and actions that could be useful in reducing climate change. Students completed the same questionnaire before and after instruction. The students' conceptions and mental models were identified by an inductive and iterative analysis of the participants' explanations. With regard to the students' conceptions, the results show that they usually link climate change to an increase in temperature, and they tend to mention, even after instruction, generic actions to mitigate climate change, such as not polluting. With regard to the students' mental models, the results show an evolution of models with little consistency and coherence, such as the models on level 1, towards higher levels of sophistication. The paper concludes with educational implications proposed for solving learning difficulties regarding the greenhouse effect and climate change.

  19. 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

  20. Modeling the effect of climate change on the indoor climate

    NARCIS (Netherlands)

    Schijndel, van A.W.M.; Schellen, H.L.

    2010-01-01

    Within the new EU project ‘Climate for Culture’ researchers are investigating climate change impacts on UNESCO World Heritage Sites. Simulation results are expected to give information on the possible impact of climate change on the built cultural heritage and its indoor environment. This paper

  1. Evaluating Impacts of climate and land use changes on streamflow using SWAT and land use models based CESM1-CAM5 Climate scenarios

    Science.gov (United States)

    Lin, Tzu Ping; Lin, Yu Pin; Lien, Wan Yu

    2015-04-01

    Climate change projects have various levels of impacts on hydrological cycles around the world. The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from the Coupled Model Intercomparison Project (CMIP5) which has been just be released in Taiwan, 2014. Since the streamflow run into ocean directly due to the steep terrain and the rainfall difference between wet and dry seasons is apparent; as a result, the allocation water resource reasonable is very challenge in Taiwan, particularly under climate change. The purpose of this study was to evaluate the impacts of climate and land use changes on a small watershed in Taiwan. The AR5 General Circulation Models(GCM) output data was adopted in this study and was downscaled from the monthly to the daily weather data as the input data of hydrological model such as Soil and Water Assessment Tool (SWAT) model in this study. The spatially explicit land uses change model, the Conservation of Land Use and its Effects at Small regional extent (CLUE-s), was applied to simulate land use scenarios in 2020-2039. Combined climate and land use change scenarios were adopted as input data of the hydrological model, the SWAT model, to estimate the future streamflows. With the increasing precipitation, increasing urban area and decreasing agricultural and grass land, the annual streamflow in the most of twenty-three subbasins were also increased. Besides, due to the increasing rainfall in wet season and decreasing rainfall in dry season, the difference of streamflow between wet season and dry season are also increased. This result indicates a more stringent challenge on the water resource management in future. Therefore, impacts on water resource caused by climate change and land use change should be considered in water resource planning for the Datuan river watershed. Keywords: SWAT, GCM, CLUE-s, streamflow, climate change, land use change

  2. Misleading prioritizations from modelling range shifts under climate change

    Science.gov (United States)

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

    2018-01-01

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

  3. Land use allocation model considering climate change impact

    Science.gov (United States)

    Lee, D. K.; Yoon, E. J.; Song, Y. I.

    2017-12-01

    In Korea, climate change adaptation plans are being developed for each administrative district based on impact assessments constructed in various fields. This climate change impact assessments are superimposed on the actual space, which causes problems in land use allocation because the spatial distribution of individual impacts may be different each other. This implies that trade-offs between climate change impacts can occur depending on the composition of land use. Moreover, the actual space is complexly intertwined with various factors such as required area, legal regulations, and socioeconomic values, so land use allocation in consideration of climate change can be very difficult problem to solve (Liu et al. 2012; Porta et al. 2013).Optimization techniques can generate a sufficiently good alternatives for land use allocation at the strategic level if only the fitness function of relationship between impact and land use composition are derived. It has also been noted that land use optimization model is more effective than the scenario-based prediction model in achieving the objectives for problem solving (Zhang et al. 2014). Therefore in this study, we developed a quantitative tool, MOGA (Multi Objective Genetic Algorithm), which can generate a comprehensive land use allocations considering various climate change impacts, and apply it to the Gangwon-do in Korea. Genetic Algorithms (GAs) are the most popular optimization technique to address multi-objective in land use allocation. Also, it allows for immediate feedback to stake holders because it can run a number of experiments with different parameter values. And it is expected that land use decision makers and planners can formulate a detailed spatial plan or perform additional analysis based on the result of optimization model. Acknowledgments: This work was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program (Project number: 2014001310006)"

  4. Modelling and observing urban climate in the Netherlands

    International Nuclear Information System (INIS)

    Van Hove, B.; Steeneveld, G.J.; Heusinkveld, B.; Holtslag, B.; Jacobs, C.; Ter Maat, H.; Elbers, J.; Moors, E.

    2011-06-01

    The main aims of the present study are: (1) to evaluate the performance of two well-known mesoscale NWP (numerical weather prediction) models coupled to a UCM (Urban Canopy Models), and (2) to develop a proper measurement strategy for obtaining meteorological data that can be used in model evaluation studies. We choose the mesoscale models WRF (Weather Research and Forecasting Model) and RAMS (Regional Atmospheric Modeling System), respectively, because the partners in the present project have a large expertise with respect to these models. In addition WRF and RAMS have been successfully used in the meteorology and climate research communities for various purposes, including weather prediction and land-atmosphere interaction research. Recently, state-of-the-art UCM's were embedded within the land surface scheme of the respective models, in order to better represent the exchange of heat, momentum, and water vapour in the urban environment. Key questions addressed here are: What is the general model performance with respect to the urban environment?; How can useful and observational data be obtained that allow sensible validation and further parameterization of the models?; and Can the models be easily modified to simulate the urban climate under Dutch climatic conditions, urban configuration and morphology? Chapter 2 reviews the available Urban Canopy Models; we discuss their theoretical basis, the different representations of the urban environment, the required input and the output. Much of the information was obtained from the Urban Surface Energy Balance: Land Surface Scheme Comparison project (PILPS URBAN, PILPS stands for Project for Inter-comparison of Land-Surface Parameterization Schemes). This project started in March 2008 and was coordinated by the Department of Geography, King's College London. In order to test the performance of our models we participated in this project. Chapter 3 discusses the main results of the first phase of PILPS URBAN. A first

  5. Evaluating the performance and utility of regional climate models

    DEFF Research Database (Denmark)

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

    2007-01-01

    This special issue of Climatic Change contains a series of research articles documenting co-ordinated work carried out within a 3-year European Union project 'Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects' (PRUDENCE). The main objective...... of the PRUDENCE project was to provide high resolution climate change scenarios for Europe at the end of the twenty-first century by means of dynamical downscaling (regional climate modelling) of global climate simulations. The first part of the issue comprises seven overarching PRUDENCE papers on: (1) the design...... of the model simulations and analyses of climate model performance, (2 and 3) evaluation and intercomparison of simulated climate changes, (4 and 5) specialised analyses of impacts on water resources and on other sectors including agriculture, ecosystems, energy, and transport, (6) investigation of extreme...

  6. 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 climate model COSMO-CLM is frequently applied for 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

  7. 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).

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

    Science.gov (United States)

    Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

    2015-12-01

    Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine

  9. Intercomparison of hydrological model structures and calibration approaches in climate scenario impact projections

    Science.gov (United States)

    Vansteenkiste, Thomas; Tavakoli, Mohsen; Ntegeka, Victor; De Smedt, Florimond; Batelaan, Okke; Pereira, Fernando; Willems, Patrick

    2014-11-01

    The objective of this paper is to investigate the effects of hydrological model structure and calibration on climate change impact results in hydrology. The uncertainty in the hydrological impact results is assessed by the relative change in runoff volumes and peak and low flow extremes from historical and future climate conditions. The effect of the hydrological model structure is examined through the use of five hydrological models with different spatial resolutions and process descriptions. These were applied to a medium sized catchment in Belgium. The models vary from the lumped conceptual NAM, PDM and VHM models over the intermediate detailed and distributed WetSpa model to the fully distributed MIKE SHE model. The latter model accounts for the 3D groundwater processes and interacts bi-directionally with a full hydrodynamic MIKE 11 river model. After careful and manual calibration of these models, accounting for the accuracy of the peak and low flow extremes and runoff subflows, and the changes in these extremes for changing rainfall conditions, the five models respond in a similar way to the climate scenarios over Belgium. Future projections on peak flows are highly uncertain with expected increases as well as decreases depending on the climate scenario. The projections on future low flows are more uniform; low flows decrease (up to 60%) for all models and for all climate scenarios. However, the uncertainties in the impact projections are high, mainly in the dry season. With respect to the model structural uncertainty, the PDM model simulates significantly higher runoff peak flows under future wet scenarios, which is explained by its specific model structure. For the low flow extremes, the MIKE SHE model projects significantly lower low flows in dry scenario conditions in comparison to the other models, probably due to its large difference in process descriptions for the groundwater component, the groundwater-river interactions. The effect of the model

  10. Can we trust climate models to realistically represent severe European windstorms?

    Science.gov (United States)

    Trzeciak, Tomasz M.; Knippertz, Peter; Owen, Jennifer S. R.

    2014-05-01

    Despite the enormous advances made in climate change research, robust projections of the position and the strength of the North Atlantic stormtrack are not yet possible. In particular with respect to damaging windstorms, this incertitude bears enormous risks to European societies and the (re)insurance industry. Previous studies have addressed the problem of climate model uncertainty through statistical comparisons of simulations of the current climate with (re-)analysis data and found that there is large disagreement between different climate models, different ensemble members of the same model and observed climatologies of intense cyclones. One weakness of such statistical evaluations lies in the difficulty to separate influences of the climate model's basic state from the influence of fast processes on the development of the most intense storms. Compensating effects between the two might conceal errors and suggest higher reliability than there really is. A possible way to separate influences of fast and slow processes in climate projections is through a "seamless" approach of hindcasting historical, severe storms with climate models started from predefined initial conditions and run in a numerical weather prediction mode on the time scale of several days. Such a cost-effective case-study approach, which draws from and expands on the concepts from the Transpose-AMIP initiative, has recently been undertaken in the SEAMSEW project at the University of Leeds funded by the AXA Research Fund. Key results from this work focusing on 20 historical storms and using different lead times and horizontal and vertical resolutions include: (a) Tracks are represented reasonably well by most hindcasts. (b) Sensitivity to vertical resolution is low. (c) There is a systematic underprediction of cyclone depth for a coarse resolution of T63, but surprisingly no systematic bias is found for higher-resolution runs using T127, showing that climate models are in fact able to represent the

  11. New Gravity Wave Treatments for GISS Climate Models

    Science.gov (United States)

    Geller, Marvin A.; Zhou, Tiehan; Ruedy, Reto; Aleinov, Igor; Nazarenko, Larissa; Tausnev, Nikolai L.; Sun, Shan; Kelley, Maxwell; Cheng, Ye

    2011-01-01

    Previous versions of GISS climate models have either used formulations of Rayleigh drag to represent unresolved gravity wave interactions with the model-resolved flow or have included a rather complicated treatment of unresolved gravity waves that, while being climate interactive, involved the specification of a relatively large number of parameters that were not well constrained by observations and also was computationally very expensive. Here, the authors introduce a relatively simple and computationally efficient specification of unresolved orographic and nonorographic gravity waves and their interaction with the resolved flow. Comparisons of the GISS model winds and temperatures with no gravity wave parameterization; with only orographic gravity wave parameterization; and with both orographic and nonorographic gravity wave parameterizations are shown to illustrate how the zonal mean winds and temperatures converge toward observations. The authors also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. Then results are presented where the nonorographic gravity wave sources are specified to represent sources from convection in the intertropical convergence zone and spontaneous emission from jet imbalances. Finally, a strategy to include these effects in a climate-dependent manner is suggested.

  12. 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.

  13. Practice and philosophy of climate model tuning across six US modeling centers

    Directory of Open Access Journals (Sweden)

    G. A. Schmidt

    2017-09-01

    Full Text Available Model calibration (or tuning is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1995-12-31

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

  15. Bayesian hierarchical models for regional climate reconstructions of the last glacial maximum

    Science.gov (United States)

    Weitzel, Nils; Hense, Andreas; Ohlwein, Christian

    2017-04-01

    Spatio-temporal reconstructions of past climate are important for the understanding of the long term behavior of the climate system and the sensitivity to forcing changes. Unfortunately, they are subject to large uncertainties, have to deal with a complex proxy-climate structure, and a physically reasonable interpolation between the sparse proxy observations is difficult. Bayesian Hierarchical Models (BHMs) are a class of statistical models that is well suited for spatio-temporal reconstructions of past climate because they permit the inclusion of multiple sources of information (e.g. records from different proxy types, uncertain age information, output from climate simulations) and quantify uncertainties in a statistically rigorous way. BHMs in paleoclimatology typically consist of three stages which are modeled individually and are combined using Bayesian inference techniques. The data stage models the proxy-climate relation (often named transfer function), the process stage models the spatio-temporal distribution of the climate variables of interest, and the prior stage consists of prior distributions of the model parameters. For our BHMs, we translate well-known proxy-climate transfer functions for pollen to a Bayesian framework. In addition, we can include Gaussian distributed local climate information from preprocessed proxy records. The process stage combines physically reasonable spatial structures from prior distributions with proxy records which leads to a multivariate posterior probability distribution for the reconstructed climate variables. The prior distributions that constrain the possible spatial structure of the climate variables are calculated from climate simulation output. We present results from pseudoproxy tests as well as new regional reconstructions of temperatures for the last glacial maximum (LGM, ˜ 21,000 years BP). These reconstructions combine proxy data syntheses with information from climate simulations for the LGM that were

  16. Multilevel model of safety climate for furniture industries.

    Science.gov (United States)

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

    2015-01-01

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

  17. A multi-model assessment of regional climate disparities caused by solar geoengineering

    International Nuclear Information System (INIS)

    Kravitz, Ben; Rasch, Philip J; Singh, Balwinder; Yoon, Jin-Ho; MacMartin, Douglas G; Robock, Alan; Ricke, Katharine L; Cole, Jason N S; Curry, Charles L; Irvine, Peter J; Ji, Duoying; Moore, John C; Keith, David W; Egill Kristjánsson, Jón; Muri, Helene; Tilmes, Simone; Watanabe, Shingo; Yang, Shuting

    2014-01-01

    Global-scale solar geoengineering is the deliberate modification of the climate system to offset some amount of anthropogenic climate change by reducing the amount of incident solar radiation at the surface. These changes to the planetary energy budget result in differential regional climate effects. For the first time, we quantitatively evaluate the potential for regional disparities in a multi-model context using results from a model experiment that offsets the forcing from a quadrupling of CO 2 via reduction in solar irradiance. We evaluate temperature and precipitation changes in 22 geographic regions spanning most of Earth's continental area. Moderate amounts of solar reduction (up to 85% of the amount that returns global mean temperatures to preindustrial levels) result in regional temperature values that are closer to preindustrial levels than an un-geoengineered, high CO 2 world for all regions and all models. However, in all but one model, there is at least one region for which no amount of solar reduction can restore precipitation toward its preindustrial value. For most metrics considering simultaneous changes in both variables, temperature and precipitation values in all regions are closer to the preindustrial climate for a moderate amount of solar reduction than for no solar reduction. (letter)

  18. 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.

  19. Downscaling a global climate model to simulate climate change over the US and the implication on regional and urban air quality

    Directory of Open Access Journals (Sweden)

    M. Trail

    2013-09-01

    Full Text Available Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US, one region during summer (Texas, and one region where changes potentially would lead to better air quality during spring (Northeast. Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air

  20. A top-down bottom-up modeling approach to climate change policy analysis

    International Nuclear Information System (INIS)

    Tuladhar, Sugandha D.; Yuan, Mei; Bernstein, Paul; Montgomery, W. David; Smith, Anne

    2009-01-01

    This paper analyzes macroeconomic impacts of U.S. climate change policies for three different emissions pathways using a top-down bottom-up integrated model. The integrated model couples a technology-rich, bottom-up model of the U.S. electricity sector with a fully dynamic, forward-looking general equilibrium model of the U.S. economy. Our model provides a unique and consistent modeling framework for climate change analysis. Because of the model's detail and flexibility, we use it to examine additional scenarios to analyze many of the major uncertainties surrounding the implementation and impact of climate change policies - the role of command-and-control measures, loss in flexibility mechanisms such as banking, limits on low-emitting technology, and availability of offsets. The results consistently demonstrate that those policies that combine market-oriented abatement incentives with full flexibility are the most cost-effective. (author)

  1. Effect of model resolution on a regional climate model simulation over southeast Australia

    KAUST Repository

    Evans, J. P.; McCabe, Matthew

    2013-01-01

    Dynamically downscaling climate projections from global climate models (GCMs) for use in impacts and adaptation research has become a common practice in recent years. In this study, the CSIRO Mk3.5 GCM is downscaled using the Weather Research and Forecasting (WRF) regional climate model (RCM) to medium (50 km) and high (10 km) resolution over southeast Australia. The influence of model resolution on the present-day (1985 to 2009) modelled regional climate and projected future (2075 to 2099) changes are examined for both mean climate and extreme precipitation characteristics. Increasing model resolution tended to improve the simulation of present day climate, with larger improvements in areas affected by mountains and coastlines. Examination of circumstances under which increasing the resolution decreased performance revealed an error in the GCM circulation, the effects of which had been masked by the coarse GCM topography. Resolution modifications to projected changes were largest in regions with strong topographic and coastline influences, and can be large enough to change the sign of the climate change projected by the GCM. Known physical mechanisms for these changes included orographic uplift and low-level blocking of air-masses caused by mountains. In terms of precipitation extremes, the GCM projects increases in extremes even when the projected change in the mean was a decrease: but this was not always true for the higher resolution models. Thus, while the higher resolution RCM climate projections often concur with the GCM projections, there are times and places where they differ significantly due to their better representation of physical processes. It should also be noted that the model resolution can modify precipitation characteristics beyond just its mean value.

  2. Effect of model resolution on a regional climate model simulation over southeast Australia

    KAUST Repository

    Evans, J. P.

    2013-03-26

    Dynamically downscaling climate projections from global climate models (GCMs) for use in impacts and adaptation research has become a common practice in recent years. In this study, the CSIRO Mk3.5 GCM is downscaled using the Weather Research and Forecasting (WRF) regional climate model (RCM) to medium (50 km) and high (10 km) resolution over southeast Australia. The influence of model resolution on the present-day (1985 to 2009) modelled regional climate and projected future (2075 to 2099) changes are examined for both mean climate and extreme precipitation characteristics. Increasing model resolution tended to improve the simulation of present day climate, with larger improvements in areas affected by mountains and coastlines. Examination of circumstances under which increasing the resolution decreased performance revealed an error in the GCM circulation, the effects of which had been masked by the coarse GCM topography. Resolution modifications to projected changes were largest in regions with strong topographic and coastline influences, and can be large enough to change the sign of the climate change projected by the GCM. Known physical mechanisms for these changes included orographic uplift and low-level blocking of air-masses caused by mountains. In terms of precipitation extremes, the GCM projects increases in extremes even when the projected change in the mean was a decrease: but this was not always true for the higher resolution models. Thus, while the higher resolution RCM climate projections often concur with the GCM projections, there are times and places where they differ significantly due to their better representation of physical processes. It should also be noted that the model resolution can modify precipitation characteristics beyond just its mean value.

  3. Expected utility and catastrophic risk in a stochastic economy-climate model

    Energy Technology Data Exchange (ETDEWEB)

    Ikefuji, M. [Institute of Social and Economic Research, Osaka University, Osaka (Japan); Laeven, R.J.A.; Magnus, J.R. [Department of Econometrics and Operations Research, Tilburg University, Tilburg (Netherlands); Muris, C. [CentER, Tilburg University, Tilburg (Netherlands)

    2010-11-15

    In the context of extreme climate change, we ask how to conduct expected utility analysis in the presence of catastrophic risks. Economists typically model decision making under risk and uncertainty by expected utility with constant relative risk aversion (power utility); statisticians typically model economic catastrophes by probability distributions with heavy tails. Unfortunately, the expected utility framework is fragile with respect to heavy-tailed distributional assumptions. We specify a stochastic economy-climate model with power utility and explicitly demonstrate this fragility. We derive necessary and sufficient compatibility conditions on the utility function to avoid fragility and solve our stochastic economy-climate model for two examples of such compatible utility functions. We further develop and implement a procedure to learn the input parameters of our model and show that the model thus specified produces quite robust optimal policies. The numerical results indicate that higher levels of uncertainty (heavier tails) lead to less abatement and consumption, and to more investment, but this effect is not unlimited.

  4. Uncertainties in modelling CH4 emissions from northern wetlands in glacial climates: effect of hydrological model and CH4 model structure

    Directory of Open Access Journals (Sweden)

    J. van Huissteden

    2009-07-01

    Full Text Available Methane (CH4 fluxes from northern wetlands may have influenced atmospheric CH4 concentrations at climate warming phases during the last 800 000 years and during the present global warming. Including these CH4 fluxes in earth system models is essential to understand feedbacks between climate and atmospheric composition. Attempts to model CH4 fluxes from wetlands have previously been undertaken using various approaches. Here, we test a process-based wetland CH4 flux model (PEATLAND-VU which includes details of soil-atmosphere CH4 transport. The model has been used to simulate CH4 emissions from continental Europe in previous glacial climates and the current climate. This paper presents results regarding the sensitivity of modeling glacial terrestrial CH4 fluxes to (a basic tuning parameters of the model, (b different approaches in modeling of the water table, and (c model structure. In order to test the model structure, PEATLAND-VU was compared to a simpler modeling approach based on wetland primary production estimated from a vegetation model (BIOME 3.5. The tuning parameters are the CH4 production rate from labile organic carbon and its temperature sensitivity. The modelled fluxes prove comparatively insensitive to hydrology representation, while sensitive to microbial parameters and model structure. Glacial climate emissions are also highly sensitive to assumptions about the extent of ice cover and exposed seafloor. Wetland expansion over low relief exposed seafloor areas have compensated for a decrease of wetland area due to continental ice cover.

  5. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

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

  6. A characteristics of East Asian climate using high-resolution regional climate model

    Science.gov (United States)

    Yhang, Y.

    2013-12-01

    Climate research, particularly application studies for water, agriculture, forestry, fishery and energy management require fine scale multi-decadal information of meteorological, oceanographic and land states. Unfortunately, spatially and temporally homogeneous multi-decadal observations of these variables in high horizontal resolution are non-existent. Some long term surface records of temperature and precipitation exist, but the number of observation is very limited and the measurements are often contaminated by changes in instrumentation over time. Some climatologically important variables, such as soil moisture, surface evaporation, and radiation are not even measured over most of East Asia. Reanalysis is one approach to obtaining long term homogeneous analysis of needed variables. However, the horizontal resolution of global reanalysis is of the order of 100 to 200 km, too coarse for many application studies. Regional climate models (RCMs) are able to provide valuable regional finescale information, especially in regions where the climate variables are strongly regulated by the underlying topography and the surface heterogeneity. In this study, we will provide accurately downscaled regional climate over East Asia using the Global/Regional Integrated Model system [GRIMs; Hong et al. 2013]. A mixed layer model is embedded within the GRIMs in order to improve air-sea interaction. A detailed description of the characteristics of the East Asian summer and winter climate will be presented through the high-resolution numerical simulations. The increase in horizontal resolution is expected to provide the high-quality data that can be used in various application areas such as hydrology or environmental model forcing.

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

    Science.gov (United States)

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

    2011-12-01

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

  8. Terrestrial biogeochemistry in the community climate system model (CCSM)

    International Nuclear Information System (INIS)

    Hoffman, Forrest; Fung, Inez; Randerson, Jim; Thornton, Peter; Foley, Jon; Covey, Curtis; John, Jasmin; Levis, Samuel; Post, W Mac; Vertenstein, Mariana; Stoeckli, Reto; Running, Steve; Heinsch, Faith Ann; Erickson, David; Drake, John

    2006-01-01

    Described here is the formulation of the CASA ' biogeochemistry model of Fung, et al., which has recently been coupled to the Community Land Model Version 3 (CLM3) and the Community Climate System Model Version 3 (CCSM3). This model is presently being used for Coupled Climate/Carbon Cycle Model Intercomparison Project (C 4 MIP) Phase 1 experiments. In addition, CASA ' is one of three models - in addition to CN (Thornton, et al.) and IBIS (Thompson, et al.) - that are being run within CCSM to investigate their suitability for use in climate change predictions in a future version of CCSM. All of these biogeochemistry experiments are being performed on the Computational Climate Science End Station (Dr. Warren Washington, Principle Investigator) at the National Center for Computational Sciences at Oak Ridge National Laboratory

  9. 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.

  10. Simulated pre-industrial climate in Bergen Climate Model (version 2: model description and large-scale circulation features

    Directory of Open Access Journals (Sweden)

    O. H. Otterå

    2009-11-01

    Full Text Available The Bergen Climate Model (BCM is a fully-coupled atmosphere-ocean-sea-ice model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate. Here, a pre-industrial multi-century simulation with an updated version of BCM is described and compared to observational data. The model is run without any form of flux adjustments and is stable for several centuries. The simulated climate reproduces the general large-scale circulation in the atmosphere reasonably well, except for a positive bias in the high latitude sea level pressure distribution. Also, by introducing an updated turbulence scheme in the atmosphere model a persistent cold bias has been eliminated. For the ocean part, the model drifts in sea surface temperatures and salinities are considerably reduced compared to earlier versions of BCM. Improved conservation properties in the ocean model have contributed to this. Furthermore, by choosing a reference pressure at 2000 m and including thermobaric effects in the ocean model, a more realistic meridional overturning circulation is simulated in the Atlantic Ocean. The simulated sea-ice extent in the Northern Hemisphere is in general agreement with observational data except for summer where the extent is somewhat underestimated. In the Southern Hemisphere, large negative biases are found in the simulated sea-ice extent. This is partly related to problems with the mixed layer parametrization, causing the mixed layer in the Southern Ocean to be too deep, which in turn makes it hard to maintain a realistic sea-ice cover here. However, despite some problematic issues, the pre-industrial control simulation presented here should still be appropriate for climate change studies requiring multi-century simulations.

  11. 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

  12. Numerical Modeling of Climate-Chemistry Connections: Recent Developments and Future Challenges

    Directory of Open Access Journals (Sweden)

    Patrick Jöckel

    2013-05-01

    Full Text Available This paper reviews the current state and development of different numerical model classes that are used to simulate the global atmospheric system, particularly Earth’s climate and climate-chemistry connections. The focus is on Chemistry-Climate Models. In general, these serve to examine dynamical and chemical processes in the Earth atmosphere, their feedback, and interaction with climate. Such models have been established as helpful tools in addition to analyses of observational data. Definitions of the global model classes are given and their capabilities as well as weaknesses are discussed. Examples of scientific studies indicate how numerical exercises contribute to an improved understanding of atmospheric behavior. There, the focus is on synergistic investigations combining observations and model results. The possible future developments and challenges are presented, not only from the scientific point of view but also regarding the computer technology and respective consequences for numerical modeling of atmospheric processes. In the future, a stronger cross-linkage of subject-specific scientists is necessary, to tackle the looming challenges. It should link the specialist discipline and applied computer science.

  13. Automated parameter tuning applied to sea ice in a global climate model

    Science.gov (United States)

    Roach, Lettie A.; Tett, Simon F. B.; Mineter, Michael J.; Yamazaki, Kuniko; Rae, Cameron D.

    2018-01-01

    This study investigates the hypothesis that a significant portion of spread in climate model projections of sea ice is due to poorly-constrained model parameters. New automated methods for optimization are applied to historical sea ice in a global coupled climate model (HadCM3) in order to calculate the combination of parameters required to reduce the difference between simulation and observations to within the range of model noise. The optimized parameters result in a simulated sea-ice time series which is more consistent with Arctic observations throughout the satellite record (1980-present), particularly in the September minimum, than the standard configuration of HadCM3. Divergence from observed Antarctic trends and mean regional sea ice distribution reflects broader structural uncertainty in the climate model. We also find that the optimized parameters do not cause adverse effects on the model climatology. This simple approach provides evidence for the contribution of parameter uncertainty to spread in sea ice extent trends and could be customized to investigate uncertainties in other climate variables.

  14. Flexible global ocean-atmosphere-land system model. A modeling tool for the climate change research community

    International Nuclear Information System (INIS)

    Zhou, Tianjun; Yu, Yongqiang; Liu, Yimin; Wang, Bin

    2014-01-01

    First book available on systematic evaluations of the performance of the global climate model FGOALS. Covers the whole field, ranging from the development to the applications of this climate system model. Provide an outlook for the future development of the FGOALS model system. Offers brief introduction about how to run FGOALS. Coupled climate system models are of central importance for climate studies. A new model known as FGOALS (the Flexible Global Ocean-Atmosphere-Land System model), has been developed by the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP, CAS), a first-tier national geophysical laboratory. It serves as a powerful tool, both for deepening our understanding of fundamental mechanisms of the climate system and for making decadal prediction and scenario projections of future climate change. ''Flexible Global Ocean-Atmosphere-Land System Model: A Modeling Tool for the Climate Change Research Community'' is the first book to offer systematic evaluations of this model's performance. It is comprehensive in scope, covering both developmental and application-oriented aspects of this climate system model. It also provides an outlook of future development of FGOALS and offers an overview of how to employ the model. It represents a valuable reference work for researchers and professionals working within the related areas of climate variability and change.

  15. 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.

  16. Future Projections of Fire Occurrence in Brazil Using EC-Earth Climate Model

    Directory of Open Access Journals (Sweden)

    Patrícia Silva

    Full Text Available Abstract Fire has a fundamental role in the Earth system as it influences global and local ecosystem patterns and processes, such as vegetation distribution and structure, the carbon cycle and climate. Since, in the global context, Brazil is one of the regions with higher fire activity, an assessment is here performed of the sensitivity of the wildfire regime in Brazilian savanna and shrubland areas to changes in regional climate during the 21st Century, for an intermediate scenario (RCP4.5 of climate change. The assessment is based on a spatial and temporal analysis of a meteorological fire danger index specifically developed for Brazilian biomes, which was evaluated based on regional climate simulations of temperature, relative humidity and precipitation using the Rossby Centre Regional Climate Model (RCA4 forced by the EC-Earth earth system model. Results show a systematic increase in the extreme levels of fire danger throughout the 21st Century that mainly results from the increase in maximum daily temperature, which rises by about 2 °C between 2005 and 2100. This study provides new insights about projected fire activity in Brazilian woody savannas associated to climate change and is expected to benefit the user community, from governmental policies to land management and climate researches.

  17. Modeling transport of nutrients & sediment loads into Lake Tahoe under climate change

    Science.gov (United States)

    Riverson, John; Coats, Robert; Costa-Cabral, Mariza; Dettinger, Mike; Reuter, John; Sahoo, Goloka; Schladow, Geoffrey

    2013-01-01

    The outputs from two General Circulation Models (GCMs) with two emissions scenarios were downscaled and bias-corrected to develop regional climate change projections for the Tahoe Basin. For one model—the Geophysical Fluid Dynamics Laboratory or GFDL model—the daily model results were used to drive a distributed hydrologic model. The watershed model used an energy balance approach for computing evapotranspiration and snowpack dynamics so that the processes remain a function of the climate change projections. For this study, all other aspects of the model (i.e. land use distribution, routing configuration, and parameterization) were held constant to isolate impacts of climate change projections. The results indicate that (1) precipitation falling as rain rather than snow will increase, starting at the current mean snowline, and moving towards higher elevations over time; (2) annual accumulated snowpack will be reduced; (3) snowpack accumulation will start later; and (4) snowmelt will start earlier in the year. Certain changes were masked (or counter-balanced) when summarized as basin-wide averages; however, spatial evaluation added notable resolution. While rainfall runoff increased at higher elevations, a drop in total precipitation volume decreased runoff and fine sediment load from the lower elevation meadow areas and also decreased baseflow and nitrogen loads basin-wide. This finding also highlights the important role that the meadow areas could play as high-flow buffers under climatic change. Because the watershed model accounts for elevation change and variable meteorological patterns, it provided a robust platform for evaluating the impacts of projected climate change on hydrology and water quality.

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

    Science.gov (United States)

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

    2015-04-01

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

  19. Stress testing hydrologic models using bottom-up climate change assessment

    Science.gov (United States)

    Stephens, C.; Johnson, F.; Marshall, L. A.

    2017-12-01

    Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.

  20. Multivariate statistical assessments of greenhouse-gas-induced climatic change and comparison with results from general circulation models

    International Nuclear Information System (INIS)

    Schoenwiese, C.D.

    1990-01-01

    Based on univariate correction and coherence analyses, including techniques moving in time, and taking account of the physical basis of the relationships, a simple multivariate concept is presented which correlates observational climatic time series simultaneously with solar, volcanic, ENSO (El Nino/Souther Oscillation) and anthropogenic greenhouse-gas forcing. The climatic elements considered are air temperature (near the ground and stratosphere), sea surface temperature, sea level and precipitation, and cover at least the period 1881-1980 (stratospheric temperature only since 1960). The climate signal assessments which may be hypothetically attributed to the observed CO 2 or equivalent CO 2 (implying additional greenhouse gases) increase are compared with those resulting from GCM experiments. In case of the Northern hemisphere air temperature these comparisons are performed not only in respect to hemispheric and global means, but also in respect to the regional and seasonal patterns. Autocorrelations and phase shifts of the climate response to natural and anthropogenic forcing complicate the statistical assessments

  1. Terrestrial biogeochemistry in the community climate system model (CCSM)

    Energy Technology Data Exchange (ETDEWEB)

    Hoffman, Forrest [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6016 (United States); Fung, Inez [University of California at Berkeley, Berkeley, California (United States); Randerson, Jim [University of California at Irvine, Irvine, California (United States); Thornton, Peter [National Center for Atmospheric Research, Boulder, Colorado (United States); Foley, Jon [University of Wisconsin at Madison, Madison, Wisconsin (United States); Covey, Curtis [Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, California (United States); John, Jasmin [University of California at Berkeley, Berkeley, California (United States); Levis, Samuel [National Center for Atmospheric Research, Boulder, Colorado (United States); Post, W Mac [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6016 (United States); Vertenstein, Mariana [National Center for Atmospheric Research, Boulder, Colorado (United States); Stoeckli, Reto [Colorado State University, Ft. Collins, Colorado (United States); Running, Steve [University of Montana, Missoula, Montana (United States); Heinsch, Faith Ann [University of Montana, Missoula, Montana (United States); Erickson, David [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6016 (United States); Drake, John [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6016 (United States)

    2006-09-15

    Described here is the formulation of the CASA{sup '} biogeochemistry model of Fung, et al., which has recently been coupled to the Community Land Model Version 3 (CLM3) and the Community Climate System Model Version 3 (CCSM3). This model is presently being used for Coupled Climate/Carbon Cycle Model Intercomparison Project (C{sup 4}MIP) Phase 1 experiments. In addition, CASA{sup '} is one of three models - in addition to CN (Thornton, et al.) and IBIS (Thompson, et al.) - that are being run within CCSM to investigate their suitability for use in climate change predictions in a future version of CCSM. All of these biogeochemistry experiments are being performed on the Computational Climate Science End Station (Dr. Warren Washington, Principle Investigator) at the National Center for Computational Sciences at Oak Ridge National Laboratory.

  2. 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

  3. Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

    Science.gov (United States)

    Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

    2015-01-01

    Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

  4. Improving poverty and inequality modelling in climate research

    Science.gov (United States)

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

    2017-12-01

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

  5. The Software Architecture of Global Climate Models

    Science.gov (United States)

    Alexander, K. A.; Easterbrook, S. M.

    2011-12-01

    It has become common to compare and contrast the output of multiple global climate models (GCMs), such as in the Climate Model Intercomparison Project Phase 5 (CMIP5). However, intercomparisons of the software architecture of GCMs are almost nonexistent. In this qualitative study of seven GCMs from Canada, the United States, and Europe, we attempt to fill this gap in research. We describe the various representations of the climate system as computer programs, and account for architectural differences between models. Most GCMs now practice component-based software engineering, where Earth system components (such as the atmosphere or land surface) are present as highly encapsulated sub-models. This architecture facilitates a mix-and-match approach to climate modelling that allows for convenient sharing of model components between institutions, but it also leads to difficulty when choosing where to draw the lines between systems that are not encapsulated in the real world, such as sea ice. We also examine different styles of couplers in GCMs, which manage interaction and data flow between components. Finally, we pay particular attention to the varying levels of complexity in GCMs, both between and within models. Many GCMs have some components that are significantly more complex than others, a phenomenon which can be explained by the respective institution's research goals as well as the origin of the model components. In conclusion, although some features of software architecture have been adopted by every GCM we examined, other features show a wide range of different design choices and strategies. These architectural differences may provide new insights into variability and spread between models.

  6. Watershed sensitivity and hydrologic response to high-resolution climate model

    Science.gov (United States)

    Troin, M.; Caya, D.

    2012-12-01

    Global climate models (GCMs) are fundamental research tools to assess climate change impacts on water resources. Regional climate models (RCMs) are complementary to GCMs. The added benefit of RCMs for hydrological applications is still not well understood because watersheds respond differently to RCM experiments. It is expected that the new generation of RCMs improve the representation of climate processes making it more attractive for impact studies. Given the cost of RCMs, it is ascertain to identify whether high-resolution RCMs allow offering more details than what is simulated in GCMs or RCMs with coarser resolution to address impacts on water resources. This study aims to assess the added value of RCM with emphasis on using high-resolution climate models. More specifically is how the hydrological cycle is represented when the resolution in climate models is increased (45 vs 200km; 15 vs 45km). We used simulations from the Canadian RCM (CRCM) driven by reanalyses integrated on high-resolution domains (45 and 15km) and CRCM driven by multiple members of two GCMs (the Canadian CGCM3; the German ECHAM5) with a horizontal resolution of 45 km. CRCM data and data from their host GCMs are compared to observation over 1971-2000. Precipitation and temperature from CRCM and GCMs' simulations are inputted into the hydrological SWAT model to simulate streamflow in watersheds for the historical period. The selected watersheds are two basins in Quebec (QC) and one basin in British Columbia (BC), Canada. CRCM-45km driven by GCMs performs well in representing precipitation but shows a cold bias of 3.3°C. Such bias in temperature is more significant for the BC basin (4.5°C) due to the Rocky Mountains. For the CRCM-45km/GCM combination (CGCM3 or ECHAM5), comparable skills in reproducing the observed climate are identified even though CGCM3 analyzed alone provides more accurate indication of climatology in the basins than ECHAM5. When we compared to GCMs results, CRCM-45km

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

    Science.gov (United States)

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

    2014-08-01

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

  8. A probabilistic model of ecosystem response to climate change

    International Nuclear Information System (INIS)

    Shevliakova, E.; Dowlatabadi, H.

    1994-01-01

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

  9. Implementation of a parallel version of a regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Gerstengarbe, F.W. [ed.; Kuecken, M. [Potsdam-Institut fuer Klimafolgenforschung (PIK), Potsdam (Germany); Schaettler, U. [Deutscher Wetterdienst, Offenbach am Main (Germany). Geschaeftsbereich Forschung und Entwicklung

    1997-10-01

    A regional climate model developed by the Max Planck Institute for Meterology and the German Climate Computing Centre in Hamburg based on the `Europa` and `Deutschland` models of the German Weather Service has been parallelized and implemented on the IBM RS/6000 SP computer system of the Potsdam Institute for Climate Impact Research including parallel input/output processing, the explicit Eulerian time-step, the semi-implicit corrections, the normal-mode initialization and the physical parameterizations of the German Weather Service. The implementation utilizes Fortran 90 and the Message Passing Interface. The parallelization strategy used is a 2D domain decomposition. This report describes the parallelization strategy, the parallel I/O organization, the influence of different domain decomposition approaches for static and dynamic load imbalances and first numerical results. (orig.)

  10. The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

    Science.gov (United States)

    Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

    2013-10-01

    Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

  11. Decision-relevant evaluation of climate models: A case study of chill hours in California

    Science.gov (United States)

    Jagannathan, K. A.; Jones, A. D.; Kerr, A. C.

    2017-12-01

    The past decade has seen a proliferation of different climate datasets with over 60 climate models currently in use. Comparative evaluation and validation of models can assist practitioners chose the most appropriate models for adaptation planning. However, such assessments are usually conducted for `climate metrics' such as seasonal temperature, while sectoral decisions are often based on `decision-relevant outcome metrics' such as growing degree days or chill hours. Since climate models predict different metrics with varying skill, the goal of this research is to conduct a bottom-up evaluation of model skill for `outcome-based' metrics. Using chill hours (number of hours in winter months where temperature is lesser than 45 deg F) in Fresno, CA as a case, we assess how well different GCMs predict the historical mean and slope of chill hours, and whether and to what extent projections differ based on model selection. We then compare our results with other climate-based evaluations of the region, to identify similarities and differences. For the model skill evaluation, historically observed chill hours were compared with simulations from 27 GCMs (and multiple ensembles). Model skill scores were generated based on a statistical hypothesis test of the comparative assessment. Future projections from RCP 8.5 runs were evaluated, and a simple bias correction was also conducted. Our analysis indicates that model skill in predicting chill hour slope is dependent on its skill in predicting mean chill hours, which results from the non-linear nature of the chill metric. However, there was no clear relationship between the models that performed well for the chill hour metric and those that performed well in other temperature-based evaluations (such winter minimum temperature or diurnal temperature range). Further, contrary to conclusions from other studies, we also found that the multi-model mean or large ensemble mean results may not always be most appropriate for this

  12. A Scalable and Extensible Earth System Model for Climate Change Science

    Energy Technology Data Exchange (ETDEWEB)

    Gent, Peter; Lamarque, Jean-Francois; Conley, Andrew; Vertenstein, Mariana; Craig, Anthony

    2013-02-13

    The objective of this award was to build a scalable and extensible Earth System Model that can be used to study climate change science. That objective has been achieved with the public release of the Community Earth System Model, version 1 (CESM1). In particular, the development of the CESM1 atmospheric chemistry component was substantially funded by this award, as was the development of the significantly improved coupler component. The CESM1 allows new climate change science in areas such as future air quality in very large cities, the effects of recovery of the southern hemisphere ozone hole, and effects of runoff from ice melt in the Greenland and Antarctic ice sheets. Results from a whole series of future climate projections using the CESM1 are also freely available via the web from the CMIP5 archive at the Lawrence Livermore National Laboratory. Many research papers using these results have now been published, and will form part of the 5th Assessment Report of the United Nations Intergovernmental Panel on Climate Change, which is to be published late in 2013.

  13. Flexible global ocean-atmosphere-land system model. A modeling tool for the climate change research community

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Tianjun; Yu, Yongqiang; Liu, Yimin; Wang, Bin (eds.) [Chinese Academy of Sciences, Beijing, (China). Inst. of Atmospheric Physics

    2014-04-01

    First book available on systematic evaluations of the performance of the global climate model FGOALS. Covers the whole field, ranging from the development to the applications of this climate system model. Provide an outlook for the future development of the FGOALS model system. Offers brief introduction about how to run FGOALS. Coupled climate system models are of central importance for climate studies. A new model known as FGOALS (the Flexible Global Ocean-Atmosphere-Land System model), has been developed by the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP, CAS), a first-tier national geophysical laboratory. It serves as a powerful tool, both for deepening our understanding of fundamental mechanisms of the climate system and for making decadal prediction and scenario projections of future climate change. ''Flexible Global Ocean-Atmosphere-Land System Model: A Modeling Tool for the Climate Change Research Community'' is the first book to offer systematic evaluations of this model's performance. It is comprehensive in scope, covering both developmental and application-oriented aspects of this climate system model. It also provides an outlook of future development of FGOALS and offers an overview of how to employ the model. It represents a valuable reference work for researchers and professionals working within the related areas of climate variability and change.

  14. CORDEX - a treasure trove of open climate data for hydrological modelling

    Science.gov (United States)

    O'Rourke, Eleanor; Nikulin, Grigory; Kjellström, Erik

    2015-04-01

    The Coordinated Regional Downscaling Experiment (CORDEX) was initiated by the World Climate Research Programme (WCRP) to coordinate high-resolution Regional Climate Modelling and provide a set of regional climate projections for the majority of global land regions. Additionally making this data available, and importantly useable, to impact and adaptation communities was a fundamental goal. Phase I of CORDEX, which came to a close in November 2013, was successful in developing a framework in which scientists around the world adopted a common protocol to guide the development of high-resolution Regional Climate Model (RCM) and empirical statistical downscaling (ESD) projections, and the intercomparison of these projections, on each continent, with a particular focus on the African region. As a result of these intensive activities by groups across the globe more than 47000 quality checked open datasets are now freely available to users through the searchable Earth System Grid Federation (ESGF). The integration of this data into large scale hydrological modelling is in action within the Swedish Meteorological & Hydrological Institute (SMHI) exemplifying the great potential use of this resource to the hydrological community. The aim of CORDEX Phase II is to enhance the dialogue with end-users so as to meet the growing demand for tailored regional climate information. Here, greater interaction between the CORDEX and hydrological modelling community can only prove hugely beneficial leading to greater protection for those vulnerable to the impacts of a changing climate.

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

    International Nuclear Information System (INIS)

    Selroos, Jan-Olof; Follin, Sven

    2010-12-01

    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

  16. 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.

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

    International Nuclear Information System (INIS)

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

    2000-01-01

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

  18. 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.

  19. 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

  20. Parameter Estimation of Dynamic Multi-zone Models for Livestock Indoor Climate Control

    DEFF Research Database (Denmark)

    Wu, Zhuang; Stoustrup, Jakob; Heiselberg, Per

    2008-01-01

    , the livestock, the ventilation system and the building on the dynamic performance of indoor climate. Some significant parameters employed in the climate model as well as the airflow interaction between each conceptual zone are identified with the use of experimental time series data collected during spring......In this paper, a multi-zone modeling concept is proposed based on a simplified energy balance formulation to provide a better prediction of the indoor horizontal temperature variation inside the livestock building. The developed mathematical models reflect the influences from the weather...... and winter at a real scale livestock building in Denmark. The obtained comparative results between the measured data and the simulated output confirm that a very simple multi-zone model can capture the salient dynamical features of the climate dynamics which are needed for control purposes....

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

    International Nuclear Information System (INIS)

    Van der Werf, Edwin

    2008-01-01

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

  2. Climate models with delay differential equations.

    Science.gov (United States)

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

    2017-11-01

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

  3. Climate models with delay differential equations

    Science.gov (United States)

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

    2017-11-01

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

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

    Science.gov (United States)

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

    2002-12-01

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

  5. Identifying misbehaving models using baseline climate variance

    Science.gov (United States)

    Schultz, Colin

    2011-06-01

    The majority of projections made using general circulation models (GCMs) are conducted to help tease out the effects on a region, or on the climate system as a whole, of changing climate dynamics. Sun et al., however, used model runs from 20 different coupled atmosphere-ocean GCMs to try to understand a different aspect of climate projections: how bias correction, model selection, and other statistical techniques might affect the estimated outcomes. As a case study, the authors focused on predicting the potential change in precipitation for the Murray-Darling Basin (MDB), a 1-million- square- kilometer area in southeastern Australia that suffered a recent decade of drought that left many wondering about the potential impacts of climate change on this important agricultural region. The authors first compared the precipitation predictions made by the models with 107 years of observations, and they then made bias corrections to adjust the model projections to have the same statistical properties as the observations. They found that while the spread of the projected values was reduced, the average precipitation projection for the end of the 21st century barely changed. Further, the authors determined that interannual variations in precipitation for the MDB could be explained by random chance, where the precipitation in a given year was independent of that in previous years.

  6. Can phenological models predict tree phenology accurately under climate change conditions?

    Science.gov (United States)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  7. Climate Shocks and Migration: An Agent-Based Modeling Approach

    Science.gov (United States)

    Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

    2016-01-01

    This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725

  8. Tropical-extratropical climate interaction as revealed in idealized coupled climate model experiments

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Haijun [Peking University, Department of Atmospheric Science and Laboratory for Severe Storm and Flood Disasters, School of Physics, Beijing (China); Liu, Zhengyu [University of Wisconsin-Madison, Center for Climatic Research and Department of the Atmospheric and Oceanic Sciences, Madison, WI (United States)

    2005-06-01

    Tropical-extratropical climate interactions are studied by idealized experiments with a prescribed 2 C SST anomaly at different latitude bands in a coupled climate model. Instead of focusing on intrinsic climate variability, this work investigates the mean climate adjustment to remote external forcing. The extratropical impact on tropical climate can be as strong as the tropical impact on extratropical climate, with the remote sea surface temperature (SST) response being about half the magnitude of the imposed SST change in the forcing region. The equatorward impact of extratropical climate is accomplished by both the atmospheric bridge and the oceanic tunnel. About two-thirds of the tropical SST change comes from the atmospheric bridge, while the remaining one-third comes from the oceanic tunnel. The equatorial SST increase is first driven by the reduced latent heat flux and the weakened poleward surface Ekman transport, and then enhanced by the decrease in subtropical cells' strength and the equatorward subduction of warm anomalies. In contrast, the poleward impact of tropical climate is accomplished mainly by the atmospheric bridge, which is responsible for extratropical temperature changes in both the surface and subsurface. Sensitivity experiments also show the dominant role of the Southern Hemisphere oceans in the tropical climate change. (orig.)

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

    CSIR Research Space (South Africa)

    Landman, WA

    2009-12-01

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

  10. 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.

  11. Modeling the water balance of sloped vineyards under various climate change scenarios

    Directory of Open Access Journals (Sweden)

    Hofmann Marco

    2015-01-01

    Full Text Available Grapes for wine production are a highly climate sensitive crop and vineyard water budget is a decisive factor in quality formation. In order to conduct risk assessments for climate change effects in viticulture, models are needed which can be applied to complete growing regions. We first modified an existing simplified geometric vineyard model of radiation interception and resulting water use to incorporate numerical Monte Carlo simulations and the physical aspects of radiation interactions between canopy and vineyard slope and azimuth. We then used four regional climate models to assess for possible effects on the water budget of selected vineyard sites up to 2100. The model was developed to describe the partitioning of short-wave radiation between grapevine canopy and soil surface, respectively green cover, necessary to calculate vineyard evapotranspiration. Soil water storage was allocated to two sub reservoirs. The model was adopted for steep slope vineyards based on coordinate transformation and validated against measurements of grapevine sap flow and soil water content determined down to 1.6 m depth at three different sites over two years. The results showed good agreement of modelled and observed soil water dynamics of vineyards with large variations in site specific soil water holding capacity and viticultural management. Simulated sap flow was in overall good agreement with measured sap flow but site-specific responses of sap flow to potential evapotranspiration were observed. The analyses of climate change impacts on vineyard water budget demonstrated the importance of site-specific assessment due to natural variations in soil water holding capacity. The model was capable of describing seasonal and site-specific dynamics in soil water content and could be used in an amended version to estimate changes in the water budget of entire grape growing areas due to evolving climatic changes.

  12. Solar radiation modelling using ANNs for different climates in China

    International Nuclear Information System (INIS)

    Lam, Joseph C.; Wan, Kevin K.W.; Yang, Liu

    2008-01-01

    Artificial neural networks (ANNs) were used to develop prediction models for daily global solar radiation using measured sunshine duration for 40 cities covering nine major thermal climatic zones and sub-zones in China. Coefficients of determination (R 2 ) for all the 40 cities and nine climatic zones/sub-zones are 0.82 or higher, indicating reasonably strong correlation between daily solar radiation and the corresponding sunshine hours. Mean bias error (MBE) varies from -3.3 MJ/m 2 in Ruoqiang (cold climates) to 2.19 MJ/m 2 in Anyang (cold climates). Root mean square error (RMSE) ranges from 1.4 MJ/m 2 in Altay (severe cold climates) to 4.01 MJ/m 2 in Ruoqiang. The three principal statistics (i.e., R 2 , MBE and RMSE) of the climatic zone/sub-zone ANN models are very close to the corresponding zone/sub-zone averages of the individual city ANN models, suggesting that climatic zone ANN models could be used to estimate global solar radiation for locations within the respective zones/sub-zones where only measured sunshine duration data are available. (author)

  13. Consistency and Main Differences Between European Regional Climate Downscaling Intercomparison Results; From PRUDENCE and ENSEMBLES to CORDEX

    Science.gov (United States)

    Christensen, J. H.; Larsen, M. A. D.; Christensen, O. B.; Drews, M.

    2017-12-01

    For more than 20 years, coordinated efforts to apply regional climate models to downscale GCM simulations for Europe have been pursued by an ever increasing group of scientists. This endeavor showed its first results during EU framework supported projects such as RACCS and MERCURE. Here, the foundation for today's advanced worldwide CORDEX approach was laid out by a core of six research teams, who conducted some of the first coordinated RCM simulations with the aim to assess regional climate change for Europe. However, it was realized at this stage that model bias in GCMs as well as RCMs made this task very challenging. As an immediate outcome, the idea was conceived to make an even more coordinated effort by constructing a well-defined and structured set of common simulations; this lead to the PRUDENCE project (2001-2004). Additional coordinated efforts involving ever increasing numbers of GCMs and RCMs followed in ENSEMBLES (2004-2009) and the ongoing Euro-CORDEX (officially commenced 2011) efforts. Along with the overall coordination, simulations have increased their standard resolution from 50km (PRUDENCE) to about 12km (Euro-CORDEX) and from time slice simulations (PRUDENCE) to transient experiments (ENSEMBLES and CORDEX); from one driving model and emission scenario (PRUDENCE) to several (Euro-CORDEX). So far, this wealth of simulations have been used to assess the potential impacts of future climate change in Europe providing a baseline change as defined by a multi-model mean change with associated uncertainties calculated from model spread in the ensemble. But how has the overall picture of state-of-the-art regional climate change projections changed over this period of almost two decades? Here we compare across scenarios, model resolutions and model vintage the results from PRUDENCE, ENSEMBLES and Euro-CORDEX. By appropriate scaling we identify robust findings about the projected future of European climate expressed by temperature and precipitation changes

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

    Science.gov (United States)

    Badr, Hamada S.; Dezfuli, Amin K.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.

    2016-01-01

    Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios.

  15. 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

  16. An Online Approach for Training International Climate Scientists to Use Computer Models

    Science.gov (United States)

    Yarker, M. B.; Mesquita, M. D.; Veldore, V.

    2013-12-01

    With the mounting evidence by the work of IPCC (2007), climate change has been acknowledged as a significant challenge to Sustainable Development by the international community. It is important that scientists in developing countries have access to knowledge and tools so that well-informed decisions can be made about the mitigation and adaptation of climate change. However, training researchers to use climate modeling techniques and data analysis has become a challenge, because current capacity building approaches train researchers to use climate models through short-term workshops, which requires a large amount of funding. It has also been observed that many participants who recently completed capacity building courses still view climate and weather models as a metaphorical 'black box', where data goes in and results comes out; and there is evidence that these participants lack a basic understanding of the climate system. Both of these issues limit the ability of some scientists to go beyond running a model based on rote memorization of the process. As a result, they are unable to solve problems regarding run-time errors, thus cannot determine whether or not their model simulation is reasonable. Current research in the field of science education indicates that there are effective strategies to teach learners about science models. They involve having the learner work with, experiment with, modify, and apply models in a way that is significant and informative to the learner. It has also been noted that in the case of computational models, the installation and set up process alone can be time consuming and confusing for new users, which can hinder their ability to concentrate on using, experimenting with, and applying the model to real-world scenarios. Therefore, developing an online version of capacity building is an alternative approach to the workshop training programs, which makes use of new technologies and it allows for a long-term educational process in a way

  17. An evaluation of temperature and precipitation from global and regional climate models over Scandinavia

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-07-01

    Precipitation and temperature from global (GCMs) and regional (RCMs) climate models are compared with reanalysis and observations over Scandinavia. Also projections for the next 50-100 years are considered. The climate development is visualised as moving averages (1920-2100). Box plots are used to illuminate how well GCM runs capture the observed seasonal cycle. Maps show the seasonal difference between results from control runs (RCM) and observations (E-OBS dataset) for the reference period 1981-2000. Plots illustrate the RCM-representation of seasonal temperature and precipitations cycle for five locations in Norway and Sweden: Oslo, Bergen, Trondheim, Tromsoe and Oestersund. The results show rather large differences between control runs and observations, demonstrating the need for bias correction of results from climate models. To get an indicator of which GC M-RCM-combination give the best representation of present climate over Scandinavia, a model ranking is provided. The performance measure used is the root-mean-square deviation of mean monthly and seasonal values. The data is compared both in an area-weighted spatial average of the whole domain as well as for the selected locations. The results indicate that the regional models RACMO2 and RCA show the smallest deviations from observed climate. Among the top ranking GCM-RCM combinations, most were driven by the global model ECHAM5 and some by a version of HadCM3. These two GCMs are also present among the worst performing GCM-RCM combinations indicating that selection of RCMs is crucial. (Author)

  18. 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.

  19. 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.

  20. 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.

  1. A continuous latitudinal energy balance model to explore non-uniform climate engineering strategies

    Science.gov (United States)

    Bonetti, F.; McInnes, C. R.

    2016-12-01

    Current concentrations of atmospheric CO2 exceed measured historical levels in modern times, largely attributed to anthropogenic forcing since the industrial revolution. The required decline in emissions rates has never been achieved leading to recent interest in climate engineering for future risk-mitigation strategies. Climate engineering aims to offset human-driven climate change. It involves techniques developed both to reduce the concentration of CO2 in the atmosphere (Carbon Dioxide Removal (CDR) methods) and to counteract the radiative forcing that it generates (Solar Radiation Management (SRM) methods). In order to investigate effects of SRM technologies for climate engineering, an analytical model describing the main dynamics of the Earth's climate has been developed. The model is a time-dependent Energy Balance Model (EBM) with latitudinal resolution and allows for the evaluation of non-uniform climate engineering strategies. A significant disadvantage of climate engineering techniques involving the management of solar radiation is regional disparities in cooling. This model offers an analytical approach to design multi-objective strategies that counteract climate change on a regional basis: for example, to cool the Artic and restrict undesired impacts at mid-latitudes, or to control the equator-to-pole temperature gradient. Using the Green's function approach the resulting partial differential equation allows for the computation of the surface temperature as a function of time and latitude when a 1% per year increase in the CO2 concentration is considered. After the validation of the model through comparisons with high fidelity numerical models, it will be used to explore strategies for the injection of the aerosol precursors in the stratosphere. In particular, the model involves detailed description of the optical properties of the particles, the wash-out dynamics and the estimation of the radiative cooling they can generate.

  2. Assessment of the Impact of Climate Change on the Water Balances and Flooding Conditions of Peninsular Malaysia watersheds by a Coupled Numerical Climate Model - Watershed Hydrology Model

    Science.gov (United States)

    Ercan, A.; Kavvas, M. L.; Ishida, K.; Chen, Z. Q.; Amin, M. Z. M.; Shaaban, A. J.

    2017-12-01

    Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over various watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model that utilized an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century were dynamically downscaled to 6 km resolution over Peninsular Malaysia by a regional numerical climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over the selected watersheds of Peninsular Malaysia. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions at the selected watersheds during the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90 years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant at the selected watersheds. Furthermore, the flood frequency analyses for the selected watersheds indicate an overall increasing trend in the second half of the 21st century.

  3. Modelling of anthropogenic and natural climate changes

    Energy Technology Data Exchange (ETDEWEB)

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

    1993-06-01

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

  4. Can climate models be tuned to simulate the global mean absolute temperature correctly?

    Science.gov (United States)

    Duan, Q.; Shi, Y.; Gong, W.

    2016-12-01

    The Inter-government Panel on Climate Change (IPCC) has already issued five assessment reports (ARs), which include the simulation of the past climate and the projection of the future climate under various scenarios. The participating models can simulate reasonably well the trend in global mean temperature change, especially of the last 150 years. However, there is a large, constant discrepancy in terms of global mean absolute temperature simulations over this period. This discrepancy remained in the same range between IPCC-AR4 and IPCC-AR5, which amounts to about 3oC between the coldest model and the warmest model. This discrepancy has great implications to the land processes, particularly the processes related to the cryosphere, and casts doubts over if land-atmosphere-ocean interactions are correctly considered in those models. This presentation aims to explore if this discrepancy can be reduced through model tuning. We present an automatic model calibration strategy to tune the parameters of a climate model so the simulated global mean absolute temperature would match the observed data over the last 150 years. An intermediate complexity model known as LOVECLIM is used in the study. This presentation will show the preliminary results.

  5. Climate: Policy, Modeling, and Federal Priorities (Invited)

    Science.gov (United States)

    Koonin, S.; Department Of Energy Office Of The Under SecretaryScience

    2010-12-01

    The Administration has set ambitious national goals to reduce our dependence on fossil fuels and reduce anthropogenic greenhouse gas (GHG) emissions. The US and other countries involved in the U.N. Framework Convention on Climate Change continue to work toward a goal of establishing a viable treaty that would encompass limits on emissions and codify actions that nations would take to reduce emissions. These negotiations are informed by the science of climate change and by our understanding of how changes in technology and the economy might affect the overall climate in the future. I will describe the present efforts within the U.S. Department of Energy, and the federal government more generally, to address issues related to climate change. These include state-of-the-art climate modeling and uncertainty assessment, economic and climate scenario planning based on best estimates of different technology trajectories, adaption strategies for climate change, and monitoring and reporting for treaty verification.

  6. Climate stability and sensitivity in some simple conceptual models

    Energy Technology Data Exchange (ETDEWEB)

    Bates, J. Ray [University College Dublin, Meteorology and Climate Centre, School of Mathematical Sciences, Dublin (Ireland)

    2012-02-15

    A theoretical investigation of climate stability and sensitivity is carried out using three simple linearized models based on the top-of-the-atmosphere energy budget. The simplest is the zero-dimensional model (ZDM) commonly used as a conceptual basis for climate sensitivity and feedback studies. The others are two-zone models with tropics and extratropics of equal area; in the first of these (Model A), the dynamical heat transport (DHT) between the zones is implicit, in the second (Model B) it is explicitly parameterized. It is found that the stability and sensitivity properties of the ZDM and Model A are very similar, both depending only on the global-mean radiative response coefficient and the global-mean forcing. The corresponding properties of Model B are more complex, depending asymmetrically on the separate tropical and extratropical values of these quantities, as well as on the DHT coefficient. Adopting Model B as a benchmark, conditions are found under which the validity of the ZDM and Model A as climate sensitivity models holds. It is shown that parameter ranges of physical interest exist for which such validity may not hold. The 2 x CO{sub 2} sensitivities of the simple models are studied and compared. Possible implications of the results for sensitivities derived from GCMs and palaeoclimate data are suggested. Sensitivities for more general scenarios that include negative forcing in the tropics (due to aerosols, inadvertent or geoengineered) are also studied. Some unexpected outcomes are found in this case. These include the possibility of a negative global-mean temperature response to a positive global-mean forcing, and vice versa. (orig.)

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

    Czech Academy of Sciences Publication Activity Database

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

    2014-01-01

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

  8. 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...

  9. 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

  10. Impact of an observational time window on coupled data assimilation: simulation with a simple climate model

    Directory of Open Access Journals (Sweden)

    Y. Zhao

    2017-11-01

    Full Text Available Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.

  11. The upper end of climate model temperature projections is inconsistent with past warming

    International Nuclear Information System (INIS)

    Stott, Peter; Good, Peter; Jones, Gareth; Gillett, Nathan; Hawkins, Ed

    2013-01-01

    Climate models predict a large range of possible future temperatures for a particular scenario of future emissions of greenhouse gases and other anthropogenic forcings of climate. Given that further warming in coming decades could threaten increasing risks of climatic disruption, it is important to determine whether model projections are consistent with temperature changes already observed. This can be achieved by quantifying the extent to which increases in well mixed greenhouse gases and changes in other anthropogenic and natural forcings have already altered temperature patterns around the globe. Here, for the first time, we combine multiple climate models into a single synthesized estimate of future warming rates consistent with past temperature changes. We show that the observed evolution of near-surface temperatures appears to indicate lower ranges (5–95%) for warming (0.35–0.82 K and 0.45–0.93 K by the 2020s (2020–9) relative to 1986–2005 under the RCP4.5 and 8.5 scenarios respectively) than the equivalent ranges projected by the CMIP5 climate models (0.48–1.00 K and 0.51–1.16 K respectively). Our results indicate that for each RCP the upper end of the range of CMIP5 climate model projections is inconsistent with past warming. (letter)

  12. 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 Spain) a shift to more deep cyclones connected with an increasing number of strong wind events is found.

  13. 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. Copyright © 2016. Published by Elsevier B.V.

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

    Science.gov (United States)

    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

    2015-02-01

    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 highlight the distributional consequences of climate policies, and discuss the role of carbon markets for financing clean energy investments, and achieving efficiency and equity.

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

    International Nuclear Information System (INIS)

    Cantore, Nicola

    2011-01-01

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

  16. Study of tropical clouds feedback to a climate warming as simulated by climate models

    International Nuclear Information System (INIS)

    Brient, Florent

    2012-01-01

    The last IPCC report affirms the predominant role of low cloud-radiative feedbacks in the inter-model spread of climate sensitivity. Understanding the mechanisms that control the behavior of low-level clouds is thus crucial. However, the complexity of coupled ocean-atmosphere models and the large number of processes potentially involved make the analysis of this response difficult. To simplify the analysis and to identify the most critical controls of cloud feedbacks, we analyze the cloud response to climate change simulated by the IPSL-CM5A model in a hierarchy of configurations. A comparison between three model configurations (coupled, atmospheric and aqua-planet) using the same physical parametrizations shows that the cloud response to global warming is dominated by a decrease of low clouds in regimes of moderate subsidence. Using a Single Column Model, forced by weak subsidence large-scale forcing, allows us to reproduce the vertical cloud profile predicted in the 3D model, as well as its response to climate change (if a stochastic forcing is added on vertical velocity). We analyze the sensitivity of this low-cloud response to external forcing and also to uncertain parameters of physical parameterizations involved on the atmospheric model. Through a moist static energy (MSE) budget, we highlight several mechanisms: (1) Robust: Over weak subsidence regimes, the Clausius-Clapeyron relationship predicts that a warmer atmosphere leads to a increase of the vertical MSE gradient, resulting on a strengthening of the import of low-MSE from the free atmosphere into the cloudy boundary layer. The MSE budget links changes of vertical advection and cloud radiative effects. (2) Physics Model Dependent: The coupling between shallow convection, turbulence and cloud schemes allows the intensification of low-MSE transport so that cloud radiative cooling becomes 'less necessary' to balance the energy budget (Robust positive low cloud-radiative feedback for the model). The

  17. Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts

    Science.gov (United States)

    Irby, Isaac David

    Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research achieves that goal in three parts. First, a set of eight water quality models is used to establish a model mean and assess model skill. All models were found to exhibit similar skill in resolving dissolved oxygen concentrations as well as a number of dissolved oxygen-influencing variables (temperature, salinity, stratification, chlorophyll and nitrate) and the model mean exhibited the highest individual skill. The location of stratification within the water column was found to be a limiting factor in the models' ability to adequately simulate habitat compression resulting from low-oxygen conditions. Second, two of the previous models underwent the regulatory Chesapeake Bay pollution diet mandated by the Environmental Protection Agency. Both models exhibited a similar relative improvement in dissolved oxygen concentrations as a result of the reduction of nutrients stipulated in the pollution diet. A Confidence Index was developed to identify the locations of the Bay where the models are in agreement and disagreement regarding the impacts of the pollution diet. The models were least certain in the deep part of the upper main stem of the Bay and the uncertainty primarily stemmed from the post-processing methodology. Finally, by projecting the impacts of climate change in 2050 on the Bay, the potential success of the

  18. How realistic are air quality hindcasts driven by forcings from climate model simulations?

    Science.gov (United States)

    Lacressonnière, G.; Peuch, V.-H.; Arteta, J.; Josse, B.; Joly, M.; Marécal, V.; Saint Martin, D.; Déqué, M.; Watson, L.

    2012-12-01

    Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period; analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run results in a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 5-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure, etc.) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities, etc.). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O3, NOx, SO2 and, with some bias that can be explained by the set-up, PM10. We study how the simulations driven by climate

  19. Modelling Regional Climate Change Effects On Potential Natural Ecosystems in Sweden

    Energy Technology Data Exchange (ETDEWEB)

    Koca, D.; Smith, B.; Sykes, M.T. [Centre for GeoBiosphere Science, Department of Physical Geography and Ecosystems Analysis, Lund University, Soelvegatan 12, S-223 62 Lund (Sweden)

    2006-10-15

    This study aims to demonstrate the potential of a process-based regional ecosystem model, LPJ-GUESS, driven by climate scenarios generated by a regional climate model system (RCM) to generate predictions useful for assessing effects of climatic and CO2 change on the key ecosystem services of carbon uptake and storage. Scenarios compatible with the A2 and B2 greenhouse gas emission scenarios of the Special Report on Emission Scenarios (SRES) and with boundary conditions from two general circulation models (GCMs) - HadAM3H and ECHAM4/OPYC3 - were used in simulations to explore changes in tree species distributions, vegetation structure, productivity and ecosystem carbon stocks for the late 21st Century, thus accommodating a proportion of the GCM-based and emissions-based uncertainty in future climate development. The simulations represented in this study were of the potential natural vegetation ignoring direct anthropogenic effects. Results suggest that shifts in climatic zones may lead to changes in species distribution and community composition among seven major tree species of natural Swedish forests. All four climate scenarios were associated with an extension of the boreal forest treeline with respect to altitude and latitude. In the boreal and boreo-nemoral zones, the dominance of Norway spruce and to a lesser extent Scots pine was reduced in favour of deciduous broadleaved tree species. The model also predicted substantial increases in vegetation net primary productivity (NPP), especially in central Sweden. Expansion of forest cover and increased local biomass enhanced the net carbon sink over central and northern Sweden, despite increased carbon release through decomposition processes in the soil. In southern Sweden, reduced growing season soil moisture levels counterbalanced the positive effects of a longer growing season and increased carbon supply on NPP, with the result that many areas were converted from a sink to a source of carbon by the late 21st

  20. Modelling Regional Climate Change Effects On Potential Natural Ecosystems in Sweden

    International Nuclear Information System (INIS)

    Koca, D.; Smith, B.; Sykes, M.T.

    2006-01-01

    This study aims to demonstrate the potential of a process-based regional ecosystem model, LPJ-GUESS, driven by climate scenarios generated by a regional climate model system (RCM) to generate predictions useful for assessing effects of climatic and CO2 change on the key ecosystem services of carbon uptake and storage. Scenarios compatible with the A2 and B2 greenhouse gas emission scenarios of the Special Report on Emission Scenarios (SRES) and with boundary conditions from two general circulation models (GCMs) - HadAM3H and ECHAM4/OPYC3 - were used in simulations to explore changes in tree species distributions, vegetation structure, productivity and ecosystem carbon stocks for the late 21st Century, thus accommodating a proportion of the GCM-based and emissions-based uncertainty in future climate development. The simulations represented in this study were of the potential natural vegetation ignoring direct anthropogenic effects. Results suggest that shifts in climatic zones may lead to changes in species distribution and community composition among seven major tree species of natural Swedish forests. All four climate scenarios were associated with an extension of the boreal forest treeline with respect to altitude and latitude. In the boreal and boreo-nemoral zones, the dominance of Norway spruce and to a lesser extent Scots pine was reduced in favour of deciduous broadleaved tree species. The model also predicted substantial increases in vegetation net primary productivity (NPP), especially in central Sweden. Expansion of forest cover and increased local biomass enhanced the net carbon sink over central and northern Sweden, despite increased carbon release through decomposition processes in the soil. In southern Sweden, reduced growing season soil moisture levels counterbalanced the positive effects of a longer growing season and increased carbon supply on NPP, with the result that many areas were converted from a sink to a source of carbon by the late 21st

  1. Climate modelling on the GRID Experiences in the EU-project EELA

    Energy Technology Data Exchange (ETDEWEB)

    Fernandez-Quiruelas, V.; Fernandez, J.; Cofino, A. S.; Gutierrez, J. M.; Baeza Retamal, C.; Abarca del Rio, R.; Miguel San Martin, R.; Carrillo, M.

    2007-07-01

    Recent trends in climate modeling find in GRID computing a powerful way to achieve results by sharing computing and data distributed resources. In particular, ensemble prediction is based on the generation of multiple simulations from perturbed model conditions to sample the existing uncertainties. In this work, we present a GRID application consisting of a sequence of two state-of-the-art climate models (one global model and one regional model), operable through a web portal (based on Genius). The main goal of the application is providing ensemble-based regional predictions. This requires managing a complex work flow involving long-term jobs and job dependencies in a user-transparent way. In doing so, we identified the weaknesses of current middle ware tools and developed a robust work flow by merging the optimal existing applications with an underlying self-developed work flow application based on the communication with metadata catalogs (currently AMGA) storing application status and dynamic model output generation. As an illustrative scientific challenge, the application is applied to study the El Nino phenomenon, by simulating an El Nino year with different forcing conditions and analyzing the precipitation response over south-american countries subject to flooding risk. GRID computing; Climate models; CAM model; WRF model; Work flow. (Author)

  2. Climate modelling on the GRID Experiences in the EU-project EELA

    International Nuclear Information System (INIS)

    Fernandez-Quiruelas, V.; Fernandez, J.; Cofino, A. S.; Gutierrez, J. M.; Baeza Retamal, C.; Abarca del Rio, R.; Miguel San Martin, R.; Carrillo, M.

    2007-01-01

    Recent trends in climate modeling find in GRID computing a powerful way to achieve results by sharing computing and data distributed resources. In particular, ensemble prediction is based on the generation of multiple simulations from perturbed model conditions to sample the existing uncertainties. In this work, we present a GRID application consisting of a sequence of two state-of-the-art climate models (one global model and one regional model), operable through a web portal (based on Genius). The main goal of the application is providing ensemble-based regional predictions. This requires managing a complex work flow involving long-term jobs and job dependencies in a user-transparent way. In doing so, we identified the weaknesses of current middle ware tools and developed a robust work flow by merging the optimal existing applications with an underlying self-developed work flow application based on the communication with metadata catalogs (currently AMGA) storing application status and dynamic model output generation. As an illustrative scientific challenge, the application is applied to study the El Nino phenomenon, by simulating an El Nino year with different forcing conditions and analyzing the precipitation response over south-american countries subject to flooding risk. GRID computing; Climate models; CAM model; WRF model; Work flow. (Author)

  3. Manager personality, manager service quality orientation, and service climate: test of a model.

    Science.gov (United States)

    Salvaggio, Amy Nicole; Schneider, Benjamin; Nishii, Lisa H; Mayer, David M; Ramesh, Anuradha; Lyon, Julie S

    2007-11-01

    This article conceptually and empirically explores the relationships among manager personality, manager service quality orientation, and climate for customer service. Data were collected from 1,486 employees and 145 managers in grocery store departments (N = 145) to test the authors' theoretical model. Largely consistent with hypotheses, results revealed that core self-evaluations were positively related to managers' service quality orientation, even after dimensions of the Big Five model of personality were controlled, and that service quality orientation fully mediated the relationship between personality and global service climate. Implications for personality and organizational climate research are discussed. (c) 2007 APA

  4. Estimating uncertainty and its temporal variation related to global climate models in quantifying climate change impacts on hydrology

    Science.gov (United States)

    Shen, Mingxi; Chen, Jie; Zhuan, Meijia; Chen, Hua; Xu, Chong-Yu; Xiong, Lihua

    2018-01-01

    Uncertainty estimation of climate change impacts on hydrology has received much attention in the research community. The choice of a global climate model (GCM) is usually considered as the largest contributor to the uncertainty of climate change impacts. The temporal variation of GCM uncertainty needs to be investigated for making long-term decisions to deal with climate change. Accordingly, this study investigated the temporal variation (mainly long-term) of uncertainty related to the choice of a GCM in predicting climate change impacts on hydrology by using multi-GCMs over multiple continuous future periods. Specifically, twenty CMIP5 GCMs under RCP4.5 and RCP8.5 emission scenarios were adapted to adequately represent this uncertainty envelope, fifty-one 30-year future periods moving from 2021 to 2100 with 1-year interval were produced to express the temporal variation. Future climatic and hydrological regimes over all future periods were compared to those in the reference period (1971-2000) using a set of metrics, including mean and extremes. The periodicity of climatic and hydrological changes and their uncertainty were analyzed using wavelet analysis, while the trend was analyzed using Mann-Kendall trend test and regression analysis. The results showed that both future climate change (precipitation and temperature) and hydrological response predicted by the twenty GCMs were highly uncertain, and the uncertainty increased significantly over time. For example, the change of mean annual precipitation increased from 1.4% in 2021-2050 to 6.5% in 2071-2100 for RCP4.5 in terms of the median value of multi-models, but the projected uncertainty reached 21.7% in 2021-2050 and 25.1% in 2071-2100 for RCP4.5. The uncertainty under a high emission scenario (RCP8.5) was much larger than that under a relatively low emission scenario (RCP4.5). Almost all climatic and hydrological regimes and their uncertainty did not show significant periodicity at the P = .05 significance

  5. Estimating climate change impact on irrigation demand using integrated modelling

    International Nuclear Information System (INIS)

    Zupanc, Vesna; Pintar, Marina

    2004-01-01

    Water is basic element in agriculture, and along with the soil characteristics, it remains the essential for the growth and evolution of plants. Trends of air temperature and precipitation for Slovenia indicate the increase of the air temperature and reduction of precipitation during the vegetation period, which will have a substantial impact on rural economy in Slovenia. The impact of climate change will be substantial for soil the water balance. Distinctive drought periods in past years had great impact on rural plants in light soils. Climate change will most probably also result in drought in soils which otherwise provide optimal water supply for plants. Water balance in the cross section of the rooting depth is significant for the agriculture. Mathematical models enable smaller amount of measurements in a certain area by means of measurements carried out only in characteristic points serving for verification and calibration of the model. Combination of on site measurements and mathematical modelling proved to be an efficient method for understanding of processes in nature. Climate scenarios made for the estimation of the impact of climate change are based on the general circulation models. A study based on a hundred year set of monthly data showed that in Slovenia temperature would increase at min. by 2.3 o C, and by 5.6 o C at max and by 4.5 o C in average. Valid methodology for the estimate of the impact of climate change applies the model using a basic set of data for a thirty year period (1961-1990) and a changed set of climate input parameters on one hand, and, on the other, a comparison of output results of the model. Estimating climate change impact on irrigation demand for West Slovenia for peaches and nectarines grown on Cambisols and Fluvisols was made using computer model SWAP. SWAP is a precise and power too[ for the estimation of elements of soil water balance at the level of cross section of the monitored and studied profile from the soil surface

  6. Biogeophysical Impacts of Land-Use Change on Climate Extremes in Low-Emission Scenarios: Results From HAPPI-Land

    Science.gov (United States)

    Hirsch, Annette L.; Guillod, Benoit P.; Seneviratne, Sonia I.; Beyerle, Urs; Boysen, Lena R.; Brovkin, Victor; Davin, Edouard L.; Doelman, Jonathan C.; Kim, Hyungjun; Mitchell, Daniel M.; Nitta, Tomoko; Shiogama, Hideo; Sparrow, Sarah; Stehfest, Elke; van Vuuren, Detlef P.; Wilson, Simon

    2018-03-01

    The impacts of land use have been shown to have considerable influence on regional climate. With the recent international commitment to limit global warming to well below 2°C, emission reductions need to be ambitious and could involve major land-use change (LUC). Land-based mitigation efforts to curb emissions growth include increasing terrestrial carbon sequestration through reforestation, or the adoption of bioenergy crops. These activities influence local climate through biogeophysical feedbacks, however, it is uncertain how important they are for a 1.5° climate target. This was the motivation for HAPPI-Land: the half a degree additional warming, prognosis, and projected impacts—land-use scenario experiment. Using four Earth system models, we present the first multimodel results from HAPPI-Land and demonstrate the critical role of land use for understanding the characteristics of regional climate extremes in low-emission scenarios. In particular, our results show that changes in temperature extremes due to LUC are comparable in magnitude to changes arising from half a degree of global warming. We also demonstrate that LUC contributes to more than 20% of the change in temperature extremes for large land areas concentrated over the Northern Hemisphere. However, we also identify sources of uncertainty that influence the multimodel consensus of our results including how LUC is implemented and the corresponding biogeophysical feedbacks that perturb climate. Therefore, our results highlight the urgent need to resolve the challenges in implementing LUC across models to quantify the impacts and consider how LUC contributes to regional changes in extremes associated with sustainable development pathways.

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

    Directory of Open Access Journals (Sweden)

    Dirk Lauwaet

    2015-06-01

    Full Text Available A new dynamical downscaling methodology to analyze the impact of global climate change on the local climate of cities worldwide is presented. The urban boundary layer climate model UrbClim is coupled to 11 global climate models contained in the Coupled Model Intercomparison Project 5 archive, conducting 20-year simulations for present (1986–2005 and future (2081–2100 climate conditions, considering the Representative Concentration Pathway 8.5 climate scenario. The evolution of the urban heat island of eight different cities, located on three continents, is quantified and assessed, with an unprecedented horizontal resolution of a few hundred meters. For all cities, urban and rural air temperatures are found to increase strongly, up to 7 °C. However, the urban heat island intensity in most cases increases only slightly, often even below the range of uncertainty. A potential explanation, focusing on the role of increased incoming longwave radiation, is put forth. Finally, an alternative method for generating urban climate projections is proposed, combining the ensemble temperature change statistics and the results of the present-day urban climate.

  8. Tundra shrubification and tree-line advance amplify arctic climate warming: results from an individual-based dynamic vegetation model

    International Nuclear Information System (INIS)

    Zhang Wenxin; Miller, Paul A; Smith, Benjamin; Wania, Rita; Koenigk, Torben; Döscher, Ralf

    2013-01-01

    One major challenge to the improvement of regional climate scenarios for the northern high latitudes is to understand land surface feedbacks associated with vegetation shifts and ecosystem biogeochemical cycling. We employed a customized, Arctic version of the individual-based dynamic vegetation model LPJ-GUESS to simulate the dynamics of upland and wetland ecosystems under a regional climate model–downscaled future climate projection for the Arctic and Subarctic. The simulated vegetation distribution (1961–1990) agreed well with a composite map of actual arctic vegetation. In the future (2051–2080), a poleward advance of the forest–tundra boundary, an expansion of tall shrub tundra, and a dominance shift from deciduous to evergreen boreal conifer forest over northern Eurasia were simulated. Ecosystems continued to sink carbon for the next few decades, although the size of these sinks diminished by the late 21st century. Hot spots of increased CH 4 emission were identified in the peatlands near Hudson Bay and western Siberia. In terms of their net impact on regional climate forcing, positive feedbacks associated with the negative effects of tree-line, shrub cover and forest phenology changes on snow-season albedo, as well as the larger sources of CH 4 , may potentially dominate over negative feedbacks due to increased carbon sequestration and increased latent heat flux. (letter)

  9. The application of a dynamic OpenMI coupling between a regional climate model and a distributed surface water-groundwater model

    DEFF Research Database (Denmark)

    Butts, Michael; Drews, Martin; Larsen, Morten Andreas Dahl

    2014-01-01

    To support climate adaptation measures for water resources, we have developed and evaluated a dynamic coupling between a comprehensive distributed hydrological modelling system, MIKE SHE, and a regional climate modelling system, HIRHAM. The coupled model enables two-way interaction between the at......, including local measurements of energy fluxes. The results presented here suggest that there may be important differences in the simulated water balances for this catchment created by introducing an alternative hydrological model into the RCM....

  10. Lake Representations in Global Climate Models: An End-User Perspective

    Science.gov (United States)

    Rood, R. B.; Briley, L.; Steiner, A.; Wells, K.

    2017-12-01

    The weather and climate in the Great Lakes region of the United States and Canada are strongly influenced by the lakes. Within global climate models, lakes are incorporated in many ways. If one is interested in quantitative climate information for the Great Lakes, then it is a first principle requirement that end-users of climate model simulation data, whether scientists or practitioners, need to know if and how lakes are incorporated into models. We pose the basic question, how are lakes represented in CMIP models? Despite significant efforts by the climate community to document and publish basic information about climate models, it is unclear how to answer the question about lake representations? With significant knowledge of the practice of the field, then a reasonable starting point is to use the ES-DOC Comparator (https://compare.es-doc.org/ ). Once at this interface to model information, the end-user is faced with the need for more knowledge about the practice and culture of the discipline. For example, lakes are often categorized as a type of land, a counterintuitive concept. In some models, though, lakes are specified in ocean models. There is little evidence and little confidence that the information obtained through this process is complete or accurate. In fact, it is verifiably not accurate. This experience, then, motivates identifying and finding either human experts or technical documentation for each model. The conclusion from this exercise is that it can take months or longer to provide a defensible answer to if and how lakes are represented in climate models. Our experience with lake finding is that this is not a unique experience. This talk documents our experience and explores barriers we have identified and strategies for reducing those barriers.

  11. School climate and bullying victimization: a latent class growth model analysis.

    Science.gov (United States)

    Gage, Nicholas A; Prykanowski, Debra A; Larson, Alvin

    2014-09-01

    Researchers investigating school-level approaches for bullying prevention are beginning to discuss and target school climate as a construct that (a) may predict prevalence and (b) be an avenue for school-wide intervention efforts (i.e., increasing positive school climate). Although promising, research has not fully examined and established the social-ecological link between school climate factors and bullying/peer aggression. To address this gap, we examined the association between school climate factors and bullying victimization for 4,742 students in Grades 3-12 across 3 school years in a large, very diverse urban school district using latent class growth modeling. Across 3 different models (elementary, secondary, and transition to middle school), a 3-class model was identified, which included students at high-risk for bullying victimization. Results indicated that, for all students, respect for diversity and student differences (e.g., racial diversity) predicted within-class decreases in reports of bullying. High-risk elementary students reported that adult support in school was a significant predictor of within-class reduction of bullying, and high-risk secondary students report peer support as a significant predictor of within-class reduction of bullying. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  12. Ensembles modeling approach to study Climate Change impacts on Wheat

    Science.gov (United States)

    Ahmed, Mukhtar; Claudio, Stöckle O.; Nelson, Roger; Higgins, Stewart

    2017-04-01

    Simulations of crop yield under climate variability are subject to uncertainties, and quantification of such uncertainties is essential for effective use of projected results in adaptation and mitigation strategies. In this study we evaluated the uncertainties related to crop-climate models using five crop growth simulation models (CropSyst, APSIM, DSSAT, STICS and EPIC) and 14 general circulation models (GCMs) for 2 representative concentration pathways (RCP) of atmospheric CO2 (4.5 and 8.5 W m-2) in the Pacific Northwest (PNW), USA. The aim was to assess how different process-based crop models could be used accurately for estimation of winter wheat growth, development and yield. Firstly, all models were calibrated for high rainfall, medium rainfall, low rainfall and irrigated sites in the PNW using 1979-2010 as the baseline period. Response variables were related to farm management and soil properties, and included crop phenology, leaf area index (LAI), biomass and grain yield of winter wheat. All five models were run from 2000 to 2100 using the 14 GCMs and 2 RCPs to evaluate the effect of future climate (rainfall, temperature and CO2) on winter wheat phenology, LAI, biomass, grain yield and harvest index. Simulated time to flowering and maturity was reduced in all models except EPIC with some level of uncertainty. All models generally predicted an increase in biomass and grain yield under elevated CO2 but this effect was more prominent under rainfed conditions than irrigation. However, there was uncertainty in the simulation of crop phenology, biomass and grain yield under 14 GCMs during three prediction periods (2030, 2050 and 2070). We concluded that to improve accuracy and consistency in simulating wheat growth dynamics and yield under a changing climate, a multimodel ensemble approach should be used.

  13. Climate change and high-resolution whole-building numerical modelling

    NARCIS (Netherlands)

    Blocken, B.J.E.; Briggen, P.M.; Schellen, H.L.; Hensen, J.L.M.

    2010-01-01

    This paper briefly discusses the need of high-resolution whole-building numerical modelling in the context of climate change. High-resolution whole-building numerical modelling can be used for detailed analysis of the potential consequences of climate change on buildings and to evaluate remedial

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE......, 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... 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...

  15. Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment

    Science.gov (United States)

    Taner, M. U.; Wi, S.; Brown, C.

    2017-12-01

    The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.

  16. Modelling the wind climate of Ireland

    DEFF Research Database (Denmark)

    Frank, H.P.; Landberg, L.

    1997-01-01

    The wind climate of Ireland has been calculated using the Karlsruhe Atmospheric Mesoscale Model KAMM. The climatology is represented by 65 frequency classes of geostrophic wind that were selected as equiangular direction sectors and speed intervals with equal frequency in a sector. The results...... are compared with data from the European Wind Atlas which have been analyzed using the Wind Atlas Analysis and Application Program, WA(S)P. The prediction of the areas of higher wind power is fair. Stations with low power are overpredicted....

  17. A Web-Based Polar Firn Model to Motivate Interest in Climate Change

    Science.gov (United States)

    Harris, P. D.; Lundin, J.; Stevens, C.; Leahy, W.; Waddington, E. D.

    2013-12-01

    How long would you have to dig straight down in Greenland before you reached solid ice? This is one of many questions that could be answered by a typical high school student using our online firn model. Firn is fallen snow that compacts under its own weight and eventually turns into glacial ice. The Herron and Langway (1980) firn model describes this process. An important component of predicting future climate change is researching past climate change. Some details of our past climate are discovered by analyzing polar ice and the firn process. Firn research can also be useful for understanding how changes in ice surface levels reflect changes in the ice mass. We have produced an online version of the Herron and Langway model that provides a simple way for students to learn how polar snow turns into ice. As a user, you can enter some climatic conditions (accumulation rate, temperature, and surface density) into our graphical user interface and press 'Submit'. We take the numbers you enter in your internet browser, send them to the model written in Python that is running on our server, and provide links to your results, all within seconds. The model produces firn depth, density, and age data. The results appear on the webpage in both text and graphical format. We have developed an example lesson plan appropriate for a high-school physics or environmental science class. The online model offers students an opportunity to apply their scientific knowledge in order to understand real-world physical processes. Additionally, students learn about scientific research and the tools scientists use to conduct it. The model can be used as a standalone lesson or as a part of a larger climate-science unit. The online model was created with funding from the Washington NASA Space Grant Consortium and the National Science Foundation's Partnerships for International Research and Education program.

  18. Climate Model Diagnostic and Evaluation: With a Focus on Satellite Observations

    Science.gov (United States)

    Waliser, Duane

    2011-01-01

    Each year, we host a summer school that brings together the next generation of climate scientists - about 30 graduate students and postdocs from around the world - to engage with premier climate scientists from the Jet Propulsion Laboratory and elsewhere. Our yearly summer school focuses on topics on the leading edge of climate science research. Our inaugural summer school, held in 2011, was on the topic of "Using Satellite Observations to Advance Climate Models," and enabled students to explore how satellite observations can be used to evaluate and improve climate models. Speakers included climate experts from both NASA and the National Oceanic and Atmospheric Administration (NOAA), who provided updates on climate model diagnostics and evaluation and remote sensing of the planet. Details of the next summer school will be posted here in due course.

  19. The Co-evolution of Climate Models and the Intergovernmental Panel on Climate Change

    Science.gov (United States)

    Somerville, R. C.

    2010-12-01

    As recently as the 1950s, global climate models, or GCMs, did not exist, and the notion that man-made carbon dioxide might lead to significant climate change was not regarded as a serious possibility by most experts. Today, of course, the prospect or threat of exactly this type of climate change dominates the science and ranks among the most pressing issues confronting all mankind. Indeed, the prevailing scientific view throughout the first half of the twentieth century was that adding carbon dioxide to the atmosphere would have only a negligible effect on climate. The science of climate change caused by atmospheric carbon dioxide changes has thus undergone a genuine revolution. An extraordinarily rapid development of global climate models has also characterized this period, especially in the three decades since about 1980. In these three decades, the number of GCMs has greatly increased, and their physical and computational aspects have both markedly improved. Modeling progress has been enabled by many scientific advances, of course, but especially by a massive increase in available computer power, with supercomputer speeds increasing by roughly a factor of a million in the three decades from about 1980 to 2010. This technological advance has permitted a rapid increase in the physical comprehensiveness of GCMs as well as in spatial computational resolution. In short, GCMs have dramatically evolved over time, in exactly the same recent period as popular interest and scientific concern about anthropogenic climate change have markedly increased. In parallel, a unique international organization, the Intergovernmental Panel on Climate Change, or IPCC, has also recently come into being and also evolved rapidly. Today, the IPCC has become widely respected and globally influential. The IPCC was founded in 1988, and its history is thus even shorter than that of GCMs. Yet, its stature today is such that a series of IPCC reports assessing climate change science has already

  20. A structural equation modelling approach examining the pathways between safety climate, behaviour performance and workplace slipping

    Science.gov (United States)

    Swedler, David I; Verma, Santosh K; Huang, Yueng-Hsiang; Lombardi, David A; Chang, Wen-Ruey; Brennan, Melayne; Courtney, Theodore K

    2015-01-01

    Objective Safety climate has previously been associated with increasing safe workplace behaviours and decreasing occupational injuries. This study seeks to understand the structural relationship between employees’ perceptions of safety climate, performing a safety behaviour (ie, wearing slip-resistant shoes) and risk of slipping in the setting of limited-service restaurants. Methods At baseline, we surveyed 349 employees at 30 restaurants for their perceptions of their safety training and management commitment to safety as well as demographic data. Safety performance was identified as wearing slip-resistant shoes, as measured by direct observation by the study team. We then prospectively collected participants’ hours worked and number of slips weekly for the next 12 weeks. Using a confirmatory factor analysis, we modelled safety climate as a higher order factor composed of previously identified training and management commitment factors. Results The 349 study participants experienced 1075 slips during the 12-week follow-up. Confirmatory factor analysis supported modelling safety climate as a higher order factor composed of safety training and management commitment. In a structural equation model, safety climate indirectly affected prospective risk of slipping through safety performance, but no direct relationship between safety climate and slips was evident. Conclusions Results suggest that safety climate can reduce workplace slips through performance of a safety behaviour as well as suggesting a potential causal mechanism through which safety climate can reduce workplace injuries. Safety climate can be modelled as a higher order factor composed of safety training and management commitment. PMID:25710968

  1. Characterizing and Addressing the Need for Statistical Adjustment of Global Climate Model Data

    Science.gov (United States)

    White, K. D.; Baker, B.; Mueller, C.; Villarini, G.; Foley, P.; Friedman, D.

    2017-12-01

    As part of its mission to research and measure the effects of the changing climate, the U. S. Army Corps of Engineers (USACE) regularly uses the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset. However, these data are generated at a global level and are not fine-tuned for specific watersheds. This often causes CMIP5 output to vary from locally observed patterns in the climate. Several downscaling methods have been developed to increase the resolution of the CMIP5 data and decrease systemic differences to support decision-makers as they evaluate results at the watershed scale. Evaluating preliminary comparisons of observed and projected flow frequency curves over the US revealed a simple framework for water resources decision makers to plan and design water resources management measures under changing conditions using standard tools. Using this framework as a basis, USACE has begun to explore to use of statistical adjustment to alter global climate model data to better match the locally observed patterns while preserving the general structure and behavior of the model data. When paired with careful measurement and hypothesis testing, statistical adjustment can be particularly effective at navigating the compromise between the locally observed patterns and the global climate model structures for decision makers.

  2. Climate models on massively parallel computers

    International Nuclear Information System (INIS)

    Vitart, F.; Rouvillois, P.

    1993-01-01

    First results got on massively parallel computers (Multiple Instruction Multiple Data and Simple Instruction Multiple Data) allow to consider building of coupled models with high resolutions. This would make possible simulation of thermoaline circulation and other interaction phenomena between atmosphere and ocean. The increasing of computers powers, and then the improvement of resolution will go us to revise our approximations. Then hydrostatic approximation (in ocean circulation) will not be valid when the grid mesh will be of a dimension lower than a few kilometers: We shall have to find other models. The expert appraisement got in numerical analysis at the Center of Limeil-Valenton (CEL-V) will be used again to imagine global models taking in account atmosphere, ocean, ice floe and biosphere, allowing climate simulation until a regional scale

  3. Modelling relationships between lichen bioindicators, air quality and climate on a national scale: Results from the UK OPAL air survey

    International Nuclear Information System (INIS)

    Seed, Lindsay; Wolseley, Pat; Gosling, Laura; Davies, Linda; Power, Sally A.

    2013-01-01

    Air pollution has many negative effects on the natural environment, from changes in plant growth patterns to loss of ecosystem function. This study uses citizen science to investigate national-scale patterns in the distribution and abundance of selected lichen species on tree trunks and branches, and to relate these to air pollution and climate. Volunteers collected data for nine lichen indicators on 19,334 deciduous trees. Submitted data provided information on species-level patterns, and were used to derive composite lichen indices. Multiple linear regression and ANCOVA were used to model the relationships between lichen response variables on Quercus spp. and pollution, climate and location. The study demonstrated significant relationships between patterns in indicator lichens and levels of N- and S-containing pollutants on trunks and twigs. The derived lichen indices show great potential as a tool to provide information on local, site-specific levels of air quality. -- Highlights: •Data on presence and abundance of selected lichens were collected by members of the public. •Indicator species and indices were modelled against air pollution and climate data. •Lichens and indices show significant relationships with nitrogenous air pollution. •Lichen indices are useful tools for providing information on local air quality. -- Data on selected lichen taxa collected by members of the public in England is used to show the relationship of indicator taxa and pollution indices to air pollution and climate data

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

    Science.gov (United States)

    Horton, Radley M.

    during El Nino events. Based on the results from Chapter One, the analysis is expanded in several ways in Chapter Two. To gain a more complete and statistically meaningful understanding of ENSO, a 25 year time period is used instead of a single event. To gain a fuller understanding of climate variability, additional patterns are analyzed. Finally analysis is conducted at the regional scales that are of interest to farmers and agricultural planners. Key findings are that GISS ModelE can reproduce: (1) the spatial pattern associated with two additional related modes, the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO); (2) rainfall patterns in Indonesia; and (3) dynamical features such as sea level pressure (SLP) gradients and wind in the study regions. When run in coupled mode, the same model reproduces similar modes spatially but with reduced variance and weak teleconnections. Since Chapter Two identified Western Indonesia as the region where GCMs hold the most promise for agricultural applications, in Chapter Three a finer spatial and temporal scale analysis of ENSO's effects is presented. Agricultural decision-making is also linked to ENSO's climate effects. Early rainy season precipitation and circulation, and same-season planting and harvesting dates, are shown to be sensitive to ENSO. The locus of ENSO convergence and rainfall anomalies is shown to be near the axis of rainy season establishment, defined as the 6--8 mm/day isohyet, an approximate threshold for irrigated rice cultivation. As the axis tracks south and east between October and January, so do ENSO anomalies. Circulation anomalies associated with ENSO are shown to be similar to those associated with rainfall anomalies, suggesting that long lead-time ENSO forecasts may allow more adaptation than 'wait and see' methods, with little loss of forecast skill. Additional findings include: (1) rice and corn yields are lower (higher) during dry (wet) trimesters and El Nino (La Nina) years; and (2

  5. Coupling a global climatic model with insurance impact models for flood and drought: an estimation of the financial impact of climate change

    Directory of Open Access Journals (Sweden)

    Tinard Pierre

    2016-01-01

    Full Text Available CCR, a French reinsurance company mostly involved in natural disasters coverage in France, has been developing tools for the estimation of its exposure to climatic risks for many years. Both a flood and a drought models were developed and calibrated on a large policies and claims database supplied every year with insurers’ data. More recently, CCR has been developing a stochastic approach in order to evaluate its financial exposure to extreme events. A large and realistic event set has been generated by applying extreme value statistic tools to simulate hazard and to estimate, using our impact models, the average annual losses and losses related to different return periods. These event sets have been simulated separately for flood and drought, with a hypothesis of independence, consistent with recent annual damage data. The newest development presented here consists in the use of the ARPEGE–Climat model performed by Météo-France to simulate two 200-years sets of hourly atmospheric time series reflecting both the current climate and the RCP 4.5 climate conditions circa year 2050. These climatic data constitute the input data for the flood and drought impact models to detect events and simulate the associated hazard and damages. Our two main goals are (1 to simulate simultaneously flood and drought events for the same simulated years and (2 to evaluate the financial impact of climate change.

  6. Modeling Past Abrupt Climate Changes

    DEFF Research Database (Denmark)

    Marchionne, Arianna

    of the orbital variations on Earth's climate; however, the knowledge and tools needed to complete a unied theory for ice ages have not been developed yet. Here, we focus on the climatic variations that have occurred over the last few million years. Paleoclimatic records show that the glacial cycles are linked...... to those present in the astronomical forcing. We shall do this in terms of a general framework of conceptual dynamical models, which may or may not exhibit internal self-sustained oscillations. We introduce and discuss two distinct mechanisms for a periodic response at a dierent period to a periodic...

  7. The origins of computer weather prediction and climate modeling

    International Nuclear Information System (INIS)

    Lynch, Peter

    2008-01-01

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

  8. Model based climate information on drought risk in Africa

    Science.gov (United States)

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

    2012-04-01

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

  9. What’s Needed from Climate Modeling to Advance Actionable Science for Water Utilities?

    Science.gov (United States)

    Barsugli, J. J.; Anderson, C. J.; Smith, J. B.; Vogel, J. M.

    2009-12-01

    “…perfect information on climate change is neither available today nor likely to be available in the future, but … over time, as the threats climate change poses to our systems grow more real, predicting those effects with greater certainty is non-discretionary. We’re not yet at a level at which climate change projections can drive climate change adaptation.” (Testimony of WUCA Staff Chair David Behar to the House Committee on Science and Technology, May 5, 2009) To respond to this challenge, the Water Utility Climate Alliance (WUCA) has sponsored a white paper titled “Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. ” This report concerns how investments in the science of climate change, and in particular climate modeling and downscaling, can best be directed to help make climate projections more actionable. The meaning of “model improvement” can be very different depending on whether one is talking to a climate model developer or to a water manager trying to incorporate climate projections in to planning. We first surveyed the WUCA members on present and potential uses of climate model projections and on climate inputs to their various system models. Based on those surveys and on subsequent discussions, we identified four dimensions along which improvement in modeling would make the science more “actionable”: improved model agreement on change in key parameters; narrowing the range of model projections; providing projections at spatial and temporal scales that match water utilities system models; providing projections that water utility planning horizons. With these goals in mind we developed four options for improving global-scale climate modeling and three options for improving downscaling that will be discussed. However, there does not seem to be a single investment - the proverbial “magic bullet” -- which will substantially reduce the range of model projections at the scales at which utility

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

    Science.gov (United States)

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

    2013-12-03

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

  11. Tuning the climate sensitivity of a global model to match 20th Century warming

    Science.gov (United States)

    Mauritsen, T.; Roeckner, E.

    2015-12-01

    A climate models ability to reproduce observed historical warming is sometimes viewed as a measure of quality. Yet, for practical reasons historical warming cannot be considered a purely empirical result of the modelling efforts because the desired result is known in advance and so is a potential target of tuning. Here we explain how the latest edition of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2) atmospheric model (ECHAM6.3) had its climate sensitivity systematically tuned to about 3 K; the MPI model to be used during CMIP6. This was deliberately done in order to improve the match to observed 20th Century warming over the previous model generation (MPI-ESM, ECHAM6.1) which warmed too much and had a sensitivity of 3.5 K. In the process we identified several controls on model cloud feedback that confirm recently proposed hypotheses concerning trade-wind cumulus and high-latitude mixed-phase clouds. We then evaluate the model fidelity with centennial global warming and discuss the relative importance of climate sensitivity, forcing and ocean heat uptake efficiency in determining the response as well as possible systematic biases. The activity of targeting historical warming during model development is polarizing the modeling community with 35 percent of modelers stating that 20th Century warming was rated very important to decisive, whereas 30 percent would not consider it at all. Likewise, opinions diverge as to which measures are legitimate means for improving the model match to observed warming. These results are from a survey conducted in conjunction with the first WCRP Workshop on Model Tuning in fall 2014 answered by 23 modelers. We argue that tuning or constructing models to match observed warming to some extent is practically unavoidable, and as such, in many cases might as well be done explicitly. For modeling groups that have the capability to tune both their aerosol forcing and climate sensitivity there is now a unique

  12. Modelling Climate change influence on runoff and soil losses in a rainfed catchment with Mediterranean climate

    Science.gov (United States)

    Concepción Ramos, Maria; Martínez-Casasnovas, José A.

    2015-04-01

    The magnitude of erosion processes, widespread throughout the Mediterranean areas, may be enhanced due to changes in seasonal precipitation regimes and an increase of extreme events. The present research shows the results of possible effects of climate change on runoff and soil loss in a rainfed catchment located in the Barcelona province (NE Spain).In the study area, vines are the main land use, cultivated under the Penedès designation of origin. The present research shows the results of runoff and soil loss simulated using SWAT for a small basin with vines as main land use. Input data included detailed soil and land use maps, and daily climate data of the period 1998-2012. The analysis compared simulated results for years with different climatic conditions during that period and the average with predictions for the scenario 2020, 2050 and 2080 based on the HadCM3 GCM under A2 scenario and the trends observed in the area related to maximum rainfall intensity. The model was calibrated and validated using data recorded at different subbasins, using soil water and runoff samples. Taking into account the predicted changes in temperature and precipitation, the model simulated a decrease in soil loss associated with a decrease in runoff, mainly driven by an increase in evapotranspiration. However, the trend in soil losses varied when the changes in precipitation could balance the increase of evapotranspiration and also due to the increase of rainfall intensity. An increase in maximum rainfall intensity in spring and autumn (main rainy seasons) produced significant increases in soil loss: by up to 12% for the 2020 scenario and up to 57% for the 2050 scenario, although high differences may exists depending on rainfall characteristics. The research confirmed the difficulty of predicting future soil loss in this region, which has a very high climate inter-annual variability.

  13. Comparison of Predictive Models for Photovoltaic Module Performance under Sudanese-Sahelian Climate

    Directory of Open Access Journals (Sweden)

    Njomo Donatien

    2012-06-01

    Full Text Available This paper investigates various approaches to the modeling of photovoltaic systems and tests their accuracy under tropical climate. Particularly the single diode model is used to estimate the electrical behavior of the cell with respect changes on environmental parameter of temperature and irradiance. A particular typical MXS60 solar panel is used for models evaluation and results are comparing with points taken directly from the experience made on the same panel in tropical climate of the Sudan type . The accuracy of models was computed and the better model was determined for local conditions. The analysis of the curves shows that the single diode model has the better accuracy whereas the Photovoltaic geographical information system (PVGIS approach seems to be not appropriate for the region.

  14. What Can Human Geography Offer Climate Change Modelling?

    DEFF Research Database (Denmark)

    Grindsted, Thomas Skou

    2014-01-01

    behaviour to economic rationality when construed in sophisticated climate models and sometimes in nongeographical representations. The need to comprehensively take into consideration methodological approaches concerning the interface of society-environment interactions seems highly relevant to contemporary...... regularities, rationalities, and pre-analytic assumptions. Lastly we discuss challenges of constructing nature(s) and how we better understand the (geo) politics of climate change modeling.......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...

  15. Climate Change Impacts on US Water Quality using two Models: HAWQS and US Basins

    Science.gov (United States)

    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 Hydr...

  16. IIASA's climate-vegetation-biogeochemical cycle module as a part of an integrated model for climate change

    International Nuclear Information System (INIS)

    Ganopolski, A.V.; Jonas, M.; Krabec, J.; Olendrzynski, K.; Petoukhov, V.K.; Venevsky, S.V.

    1994-01-01

    The main objective of this study is the development of a hierarchy of coupled climate biosphere models with a full description of the global biogeochemical cycles. These models are planned for use as the core of a set of integrated models of climate change and they will incorporate the main elements of the Earth system (atmosphere, hydrosphere, pedosphere and biosphere) linked with each other (and eventually with the antroposphere) through the fluxes of heat, momentum, water and through the global biogeochemical cycles of carbon and nitrogen. This set of integrated models can be considered to fill the gap between highly simplified integrated models of climate change and very sophisticated and computationally expensive coupled models, developed on the basis of general circulation models (GCMs). It is anticipated that this range of integrated models will be an effective tool for investigating the broad spectrum of problems connected with the coexistence of human society and biosphere

  17. Learning About Climate and Atmospheric Models Through Machine Learning

    Science.gov (United States)

    Lucas, D. D.

    2017-12-01

    From the analysis of ensemble variability to improving simulation performance, machine learning algorithms can play a powerful role in understanding the behavior of atmospheric and climate models. To learn about model behavior, we create training and testing data sets through ensemble techniques that sample different model configurations and values of input parameters, and then use supervised machine learning to map the relationships between the inputs and outputs. Following this procedure, we have used support vector machines, random forests, gradient boosting and other methods to investigate a variety of atmospheric and climate model phenomena. We have used machine learning to predict simulation crashes, estimate the probability density function of climate sensitivity, optimize simulations of the Madden Julian oscillation, assess the impacts of weather and emissions uncertainty on atmospheric dispersion, and quantify the effects of model resolution changes on precipitation. This presentation highlights recent examples of our applications of machine learning to improve the understanding of climate and atmospheric models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  18. Weather regimes in past climate atmospheric general circulation model simulations

    Energy Technology Data Exchange (ETDEWEB)

    Kageyama, M.; Ramstein, G. [CEA Saclay, Gif-sur-Yvette (France). Lab. des Sci. du Climat et de l' Environnement; D' Andrea, F.; Vautard, R. [Laboratoire de Meteorologie Dynamique, Ecole Normale Superieure, Paris (France); Valdes, P.J. [Department of Meteorology, University of Reading (United Kingdom)

    1999-10-01

    We investigate the climates of the present-day, inception of the last glaciation (115000 y ago) and last glacial maximum (21000 y ago) in the extratropical north Atlantic and Europe, as simulated by the laboratoire de Meteorologie dynamique atmospheric general circulation model. We use these simulations to investigate the low-frequency variability of the model in different climates. The aim is to evaluate whether changes in the intraseasonal variability, which we characterize using weather regimes, can help describe the impact of different boundary conditions on climate and give a better understanding of climate change processes. Weather regimes are defined as the most recurrent patterns in the 500 hPa geopotential height, using a clustering algorithm method. The regimes found in the climate simulations of the present-day and inception of the last glaciation are similar in their number and their structure. It is the regimes' populations which are found to be different for these climates, with an increase of the model's blocked regime and a decrease in the zonal regime at the inception of the last glaciation. This description reinforces the conclusions from a study of the differences between the climatological averages of the different runs and confirms the northeastward shift to the tail of the Atlantic storm-track, which would favour more precipitation over the site of growth of the Fennoscandian ice-sheet. On the other hand, the last glacial maximum results over this sector are not found to be classifiable, showing that the change in boundary conditions can be responsible for severe changes in the weather regime and low-frequency dynamics. The LGM Atlantic low-frequency variability appears to be dominated by a large-scale retrogressing wave with a period 40 to 50 days. (orig.)

  19. Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs*

    KAUST Repository

    Castruccio, Stefano

    2014-03-01

    The authors describe a new approach for emulating the output of a fully coupled climate model under arbitrary forcing scenarios that is based on a small set of precomputed runs from the model. Temperature and precipitation are expressed as simple functions of the past trajectory of atmospheric CO2 concentrations, and a statistical model is fit using a limited set of training runs. The approach is demonstrated to be a useful and computationally efficient alternative to pattern scaling and captures the nonlinear evolution of spatial patterns of climate anomalies inherent in transient climates. The approach does as well as pattern scaling in all circumstances and substantially better in many; it is not computationally demanding; and, once the statistical model is fit, it produces emulated climate output effectively instantaneously. It may therefore find wide application in climate impacts assessments and other policy analyses requiring rapid climate projections.

  20. 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

  1. Simulation and Modelling of Climate Change Effects on River Awara Flow Discharge using WEAP Model

    Directory of Open Access Journals (Sweden)

    Oyati E.N.

    2017-11-01

    Full Text Available Modelling of stream flow and discharge of river Awara under changed climate conditions using CLIMGEN for stochastic weather generation and WEAP model was used to simulate reserviour storage volume, water demand and river discharges at high spatial resolution (0.5°×0.5°, total 66,420 grid cells. Results of CLM-Based flow measurement shows a linear regression with R 2 = 0.99 for IFPRI-MNP- IGSM_WRS calibration. Sensitivity simulation of ambient long-term shows an increase in temperature with 0.5 o c thus the results of the studies generally show that annual runoff and river discharges could largely decrease. The projection of water demand 150 million m 3 by 2020 against the reservoir storage volume 60 million m 3 and decrease in rainfall depth by -5.7 mm. The output of the combined models used in this study is veritable to create robust water management system under different climate change scenarios.

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

    Directory of Open Access Journals (Sweden)

    F. S. R. Pausata

    2009-09-01

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

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

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

  3. Statistical surrogate models for prediction of high-consequence climate change.

    Energy Technology Data Exchange (ETDEWEB)

    Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

    2011-09-01

    In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.

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

    NARCIS (Netherlands)

    Möller, M.; Obleitner, F.; Reijmer, C.H.; Pohjola, V.A.; Glowacki, P.; Kohler, J.

    2016-01-01

    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

  5. Global Water Cycle Agreement in the Climate Models Assessed in the IPCC AR4

    Science.gov (United States)

    Waliser, D.; Seo, K. -W.; Schubert, S.; Njoku, E.

    2007-01-01

    This study examines the fidelity of the global water cycle in the climate model simulations assessed in the IPCC Fourth Assessment Report. The results demonstrate good model agreement in quantities that have had a robust global observational basis and that are physically unambiguous. The worst agreement occurs for quantities that have both poor observational constraints and whose model representations can be physically ambiguous. In addition, components involving water vapor (frozen water) typically exhibit the best (worst) agreement, and fluxes typically exhibit better agreement than reservoirs. These results are discussed in relation to the importance of obtaining accurate model representation of the water cycle and its role in climate change. Recommendations are also given for facilitating the needed model improvements.

  6. Using isotopes to improve impact and hydrological predictions of land-surface schemes in global climate models

    International Nuclear Information System (INIS)

    McGuffie, K.; Henderson-Sellers, A.

    2002-01-01

    Global climate model (GCM) predictions of the impact of large-scale land-use change date back to 1984 as do the earliest isotopic studies of large-basin hydrology. Despite this coincidence in interest and geography, with both papers focussed on the Amazon, there have been few studies that have tried to exploit isotopic information with the goal of improving climate model simulations of the land-surface. In this paper we analyze isotopic results from the IAEA global data base specifically with the goal of identifying signatures of potential value for improving global and regional climate model simulations of the land-surface. Evaluation of climate model predictions of the impacts of deforestation of the Amazon has been shown to be of significance by recent results which indicate impacts occurring distant from the Amazon i.e. tele-connections causing climate change elsewhere around the globe. It is suggested that these could be similar in magnitude and extent to the global impacts of ENSO events. Validation of GCM predictions associated with Amazonian deforestation are increasingly urgently required because of the additional effects of other aspects of climate change, particularly synergies occurring between forest removal and greenhouse gas increases, especially CO 2 . Here we examine three decades distributions of deuterium excess across the Amazon and use the results to evaluate the relative importance of the fractionating (partial evaporation) and non-fractionating (transpiration) processes. These results illuminate GCM scenarios of importance to the regional climate and hydrology: (i) the possible impact of increased stomatal resistance in the rainforest caused by higher levels of atmospheric CO2 [4]; and (ii) the consequences of the combined effects of deforestation and global warming on the regions climate and hydrology

  7. A Regional Climate Model Evaluation System

    Data.gov (United States)

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

  8. Diagnosis and Quantification of Climatic Sensitivity of Carbon Fluxes in Ensemble Global Ecosystem Models

    Science.gov (United States)

    Wang, W.; Hashimoto, H.; Milesi, C.; Nemani, R. R.; Myneni, R.

    2011-12-01

    Terrestrial ecosystem models are primary scientific tools to extrapolate our understanding of ecosystem functioning from point observations to global scales as well as from the past climatic conditions into the future. However, no model is nearly perfect and there are often considerable structural uncertainties existing between different models. Ensemble model experiments thus become a mainstream approach in evaluating the current status of global carbon cycle and predicting its future changes. A key task in such applications is to quantify the sensitivity of the simulated carbon fluxes to climate variations and changes. Here we develop a systematic framework to address this question solely by analyzing the inputs and the outputs from the models. The principle of our approach is to assume the long-term (~30 years) average of the inputs/outputs as a quasi-equlibrium of the climate-vegetation system while treat the anomalies of carbon fluxes as responses to climatic disturbances. In this way, the corresponding relationships can be largely linearized and analyzed using conventional time-series techniques. This method is used to characterize three major aspects of the vegetation models that are mostly important to global carbon cycle, namely the primary production, the biomass dynamics, and the ecosystem respiration. We apply this analytical framework to quantify the climatic sensitivity of an ensemble of models including CASA, Biome-BGC, LPJ as well as several other DGVMs from previous studies, all driven by the CRU-NCEP climate dataset. The detailed analysis results are reported in this study.

  9. Cluster-based analysis of multi-model climate ensembles

    Science.gov (United States)

    Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

    2018-06-01

    Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and

  10. Drought Persistence Errors in Global Climate Models

    Science.gov (United States)

    Moon, H.; Gudmundsson, L.; Seneviratne, S. I.

    2018-04-01

    The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, but the capability of current global climate models (GCMs) to simulate such events is subject to large uncertainties. In this study, the representation of drought persistence in GCMs is assessed by comparing state-of-the-art GCM model simulations to observation-based data sets. For doing so, we consider dry-to-dry transition probabilities at monthly and annual scales as estimates for drought persistence, where a dry status is defined as negative precipitation anomaly. Though there is a substantial spread in the drought persistence bias, most of the simulations show systematic underestimation of drought persistence at global scale. Subsequently, we analyzed to which degree (i) inaccurate observations, (ii) differences among models, (iii) internal climate variability, and (iv) uncertainty of the employed statistical methods contribute to the spread in drought persistence errors using an analysis of variance approach. The results show that at monthly scale, model uncertainty and observational uncertainty dominate, while the contribution from internal variability is small in most cases. At annual scale, the spread of the drought persistence error is dominated by the statistical estimation error of drought persistence, indicating that the partitioning of the error is impaired by the limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current GCMs and suggest directions for further model improvement.

  11. A Reusable Framework for Regional Climate Model Evaluation

    Science.gov (United States)

    Hart, A. F.; Goodale, C. E.; Mattmann, C. A.; Lean, P.; Kim, J.; Zimdars, P.; Waliser, D. E.; Crichton, D. J.

    2011-12-01

    Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and

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

    Science.gov (United States)

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

    2016-01-01

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

  13. Errors and uncertainties introduced by a regional climate model in climate impact assessments: example of crop yield simulations in West Africa

    International Nuclear Information System (INIS)

    Ramarohetra, Johanna; Pohl, Benjamin; Sultan, Benjamin

    2015-01-01

    The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting (WRF) regional climate model to downscale ERA-Interim (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model (LSM) is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments. (letter)

  14. Significance of Bias Correction in Drought Frequency and Scenario Analysis Based on Climate Models

    Science.gov (United States)

    Aryal, Y.; Zhu, J.

    2015-12-01

    Assessment of future drought characteristics is difficult as climate models usually have bias in simulating precipitation frequency and intensity. To overcome this limitation, output from climate models need to be bias corrected based on the specific purpose of applications. In this study, we examine the significance of bias correction in the context of drought frequency and scenario analysis using output from climate models. In particular, we investigate the performance of three widely used bias correction techniques: (1) monthly bias correction (MBC), (2) nested bias correction (NBC), and (3) equidistance quantile mapping (EQM) The effect of bias correction in future scenario of drought frequency is also analyzed. The characteristics of drought are investigated in terms of frequency and severity in nine representative locations in different climatic regions across the United States using regional climate model (RCM) output from the North American Regional Climate Change Assessment Program (NARCCAP). The Standardized Precipitation Index (SPI) is used as the means to compare and forecast drought characteristics at different timescales. Systematic biases in the RCM precipitation output are corrected against the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data. The results demonstrate that bias correction significantly decreases the RCM errors in reproducing drought frequency derived from the NARR data. Preserving mean and standard deviation is essential for climate models in drought frequency analysis. RCM biases both have regional and timescale dependence. Different timescale of input precipitation in the bias corrections show similar results. Drought frequency obtained from the RCM future (2040-2070) scenarios is compared with that from the historical simulations. The changes in drought characteristics occur in all climatic regions. The relative changes in drought frequency in future scenario in relation to

  15. Impact of whole-building hygrothermal modelling on the assessment of indoor climate in a library building

    Energy Technology Data Exchange (ETDEWEB)

    Steeman, M.; Janssens, A. [Ghent University, Department of Architecture and Urban Planning, Jozef Plateaustraat 22, B-9000 Gent (Belgium); De Paepe, M. [Ghent University, Department of Flow, Heat and Combustion Mechanics, Sint-Pietersnieuwstraat 41, B-9000 Gent (Belgium)

    2010-07-15

    This paper focuses on the importance of accurately modelling the hygrothermal interaction between the building and its hygroscopic content for the assessment of the indoor climate. Libraries contain a large amount of stored books which require a stable relative humidity to guarantee their preservation. On the other hand, visitors and staff must be comfortable with the indoor climate. The indoor climate of a new library building is evaluated by means of measurements and simulations. Complaints of the staff are confirmed by measured data during the winter and summer of 2007-2008. For the evaluation of the indoor climate, a building simulation model is used in which the porous books are either described by a HAM model or by a simplified isothermal model. Calculations demonstrate that the HAM model predicts a more stable indoor climate regarding both temperature and relative humidity variations in comparison to the estimations by the simplified model. This is attributed to the ability of the HAM model to account for the effect of temperature variations on moisture storage. Moreover, by applying the HAM model, a good agreement with the measured indoor climate is found. As expected, a larger exposed book surface ameliorates the indoor climate because a more stable indoor relative humidity is obtained. Finally, the building simulation model is used to improve the indoor climate with respect to the preservation of valuable books. Results demonstrate that more stringent interventions on the air handling unit are expected when a simplified approach is used to model the hygroscopic books. (author)

  16. Uncertainty and endogenous technical change in climate policy models

    International Nuclear Information System (INIS)

    Baker, Erin; Shittu, Ekundayo

    2008-01-01

    Until recently endogenous technical change and uncertainty have been modeled separately in climate policy models. In this paper, we review the emerging literature that considers both these elements together. Taken as a whole the literature indicates that explicitly including uncertainty has important quantitative and qualitative impacts on optimal climate change technology policy. (author)

  17. Development and application of an interactive climate-ecosystem model system

    Institute of Scientific and Technical Information of China (English)

    CHEN Ming; D. Pollard

    2003-01-01

    A regional climate-ecosystem model system is developed in this study. It overcomes the weakness in traditional one-way coupling models and enables detailed description of interactive process between climate and natural ecosystem. It is applied to interaction study between monsoon climate and ecosystem in East Asia, with emphasis on future climate and ecosystem change scenario forced by doubled CO2. The climate tends to be warmer and wetter under doubled CO2 in Jianghuai and the Yangzi River valley, but it becomes warmer and drier in inland areas of northern and northwestern China. The largest changes and feedbacks between vegetation and climate occur in northern China. Northern inland ecosystems experience considerable degradation and desertification, indicating a marked sensitivity and vulnerability to climatic change. The strongest vegetation response to climate change occurs in northern China and the weakest in southern China. Vegetation feedbacks intensify warming and reduce drying due to increased CO2 during summer in northern China. Generally, vegetation-climate interactions are much stronger in northern China than in southern China.

  18. Vulnerability of sandy coasts to climate change and anthropic pressures: methodology and preliminary results

    Science.gov (United States)

    Idier, D.; Poumadère, M.; Vinchon, C.; Romieu, E.; Oliveros, C.

    2009-04-01

    medium-term (decades), whereas the space scales range from several tens of meters to several tens of kilometers. The project is based on the study of representative coastal units: 4 sites characterised by low-lying linear sandy beaches but different, representative, hydrodynamic and socio-economic environments. These sites are located in: Mediterranean Sea (Lido of Sète), Atlantic coast (Truc Vert beach and Noirmoutier island) and English channel coast (Est of Dunkerque). Each of these sites is studied following the same methodology, on both the physical and socio-economic dimensions, the aim being to identify vulnerability indicators regarding climate change and anthropic pressure. 2 - METHODOLOGY The work is based on the following methodology, for every site: 1) The compartments of the unit are defined: shoreface, coastline, backshore, hinterland, from a physical and socio-economical point of view. 2) The available data are analysed in order to provide some information on the present trend of the coastal unit, regarding climate change and anthropic pressure, but also to support the model validation. 3) The vulnerability is studied. On one hand, the socio-economic dimension is assessed and, in a risk governance perspective, stake holders are identified and involved. This part of the project combines the study of social perceptions of dangers along with a deliberative workshop. On the other hand, numerical models of the physical behaviour of shoreface and coastline are applied. The selected models cover a time scale from short-term (storm time scale) to long-term (decades). Then, vulnerability can be studied: the vulnerability of coast/beach is defined and studied based on in-situ observations and model results. Most of these models needs some forcing conditions (waves at the boundary of the computational domains for instance). The present day conditions can be potentially modified by climate change. However, the model and literature review on climate change show that

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

    Science.gov (United States)

    Hakala, Kirsti; Addor, Nans; Seibert, Jan

    2017-04-01

    streamflow under the climate scenarios RCP4.5 and RCP8.5. We utilize two techniques for correcting biases in the climate model output: quantile mapping and a new method, frequency bias correction. The FBC method matches the frequencies between observed and GCM-RCM data. In this way, it can be used to correct for all time scales, which is a known limitation of quantile mapping. A novel approach for the evaluation of the climate simulations and bias correction methods was then applied. Streamflow can be thought of as the "great integrator" of uncertainties. The ability, or the lack thereof, to correctly simulate streamflow is a way to assess the realism of the bias-corrected climate simulations. Long-term monthly mean as well as high and low flow metrics are used to evaluate the realism of the simulations under current climate and to gauge the impacts of climate change on streamflow. Preliminary results show that under present climate, calibration of the hydrological model comprises of a much smaller band of uncertainty in the modeling chain as compared to the bias correction of the GCM-RCMs. Therefore, for future time periods, we expect the bias correction of climate model data to have a greater influence on projected changes in streamflow than the calibration of the hydrological model.

  20. Observational uncertainty and regional climate model evaluation: A pan-European perspective

    Science.gov (United States)

    Kotlarski, Sven; Szabó, Péter; Herrera, Sixto; Räty, Olle; Keuler, Klaus; Soares, Pedro M.; Cardoso, Rita M.; Bosshard, Thomas; Pagé, Christian; Boberg, Fredrik; Gutiérrez, José M.; Jaczewski, Adam; Kreienkamp, Frank; Liniger, Mark. A.; Lussana, Cristian; Szepszo, Gabriella

    2017-04-01

    Local and regional climate change assessments based on downscaling methods crucially depend on the existence of accurate and reliable observational reference data. In dynamical downscaling via regional climate models (RCMs) observational data can influence model development itself and, later on, model evaluation, parameter calibration and added value assessment. In empirical-statistical downscaling, observations serve as predictand data and directly influence model calibration with corresponding effects on downscaled climate change projections. Focusing on the evaluation of RCMs, we here analyze the influence of uncertainties in observational reference data on evaluation results in a well-defined performance assessment framework and on a European scale. For this purpose we employ three different gridded observational reference grids, namely (1) the well-established EOBS dataset (2) the recently developed EURO4M-MESAN regional re-analysis, and (3) several national high-resolution and quality-controlled gridded datasets that recently became available. In terms of climate models five reanalysis-driven experiments carried out by five different RCMs within the EURO-CORDEX framework are used. Two variables (temperature and precipitation) and a range of evaluation metrics that reflect different aspects of RCM performance are considered. We furthermore include an illustrative model ranking exercise and relate observational spread to RCM spread. The results obtained indicate a varying influence of observational uncertainty on model evaluation depending on the variable, the season, the region and the specific performance metric considered. Over most parts of the continent, the influence of the choice of the reference dataset for temperature is rather small for seasonal mean values and inter-annual variability. Here, model uncertainty (as measured by the spread between the five RCM simulations considered) is typically much larger than reference data uncertainty. For

  1. Sensitivity of Hydrologic Response to Climate Model Debiasing Procedures

    Science.gov (United States)

    Channell, K.; Gronewold, A.; Rood, R. B.; Xiao, C.; Lofgren, B. M.; Hunter, T.

    2017-12-01

    Climate change is already having a profound impact on the global hydrologic cycle. In the Laurentian Great Lakes, changes in long-term evaporation and precipitation can lead to rapid water level fluctuations in the lakes, as evidenced by unprecedented change in water levels seen in the last two decades. These fluctuations often have an adverse impact on the region's human, environmental, and economic well-being, making accurate long-term water level projections invaluable to regional water resources management planning. Here we use hydrological components from a downscaled climate model (GFDL-CM3/WRF), to obtain future water supplies for the Great Lakes. We then apply a suite of bias correction procedures before propagating these water supplies through a routing model to produce lake water levels. Results using conventional bias correction methods suggest that water levels will decline by several feet in the coming century. However, methods that reflect the seasonal water cycle and explicitly debias individual hydrological components (overlake precipitation, overlake evaporation, runoff) imply that future water levels may be closer to their historical average. This discrepancy between debiased results indicates that water level forecasts are highly influenced by the bias correction method, a source of sensitivity that is commonly overlooked. Debiasing, however, does not remedy misrepresentation of the underlying physical processes in the climate model that produce these biases and contribute uncertainty to the hydrological projections. This uncertainty coupled with the differences in water level forecasts from varying bias correction methods are important for water management and long term planning in the Great Lakes region.

  2. 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

  3. Agent-Based Modelling of Agricultural Water Abstraction in Response to Climate, Policy, and Demand Changes: Results from East Anglia, UK

    Science.gov (United States)

    Swinscoe, T. H. A.; Knoeri, C.; Fleskens, L.; Barrett, J.

    2014-12-01

    Freshwater is a vital natural resource for multiple needs, such as drinking water for the public, industrial processes, hydropower for energy companies, and irrigation for agriculture. In the UK, crop production is the largest in East Anglia, while at the same time the region is also the driest, with average annual rainfall between 560 and 720 mm (1971 to 2000). Many water catchments of East Anglia are reported as over licensed or over abstracted. Therefore, freshwater available for agricultural irrigation abstraction in this region is becoming both increasingly scarce due to competing demands, and increasingly variable and uncertain due to climate and policy changes. It is vital for water users and policy makers to understand how these factors will affect individual abstractors and water resource management at the system level. We present first results of an Agent-based Model that captures the complexity of this system as individual abstractors interact, learn and adapt to these internal and external changes. The purpose of this model is to simulate what patterns of water resource management emerge on the system level based on local interactions, adaptations and behaviours, and what policies lead to a sustainable water resource management system. The model is based on an irrigation abstractor typology derived from a survey in the study area, to capture individual behavioural intentions under a range of water availability scenarios, in addition to farm attributes, and demographics. Regional climate change scenarios, current and new abstraction licence reforms by the UK regulator, such as water trading and water shares, and estimated demand increases from other sectors were used as additional input data. Findings from the integrated model provide new understanding of the patterns of water resource management likely to emerge at the system level.

  4. The Agricultural Model Intercomparison and Improvement Project (AgMIP): Progress and Preliminary Results

    Science.gov (United States)

    Rosenzweig, C.

    2011-12-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Recent progress and the current status of AgMIP will be presented, highlighting three areas of activity: preliminary results from crop pilot studies, outcomes from regional workshops, and emerging scientific challenges. AgMIP crop modeling efforts are being led by pilot studies, which have been established for wheat, maize, rice, and sugarcane. These crop-specific initiatives have proven instrumental in testing and contributing to AgMIP protocols, as well as creating preliminary results for aggregation and input to agricultural trade models. Regional workshops are being held to encourage collaborations and set research activities in motion for key agricultural areas. The first of these workshops was hosted by Embrapa and UNICAMP and held in Campinas, Brazil. Outcomes from this meeting have informed crop modeling research activities within South America, AgMIP protocols, and future regional workshops. Several scientific challenges have emerged and are currently being addressed by AgMIP researchers. Areas of particular interest include geospatial weather generation, ensemble methods for climate scenarios and crop models, spatial aggregation of field-scale yields to regional and global production, and characterization of future changes in climate variability.

  5. Climatic features of the Red Sea from a regional assimilative model

    KAUST Repository

    Viswanadhapalli, Yesubabu

    2016-08-16

    The Advanced Research version of Weather Research and Forecasting (WRF-ARW) model was used to generate a downscaled, 10-km resolution regional climate dataset over the Red Sea and adjacent region. The model simulations are performed based on two, two-way nested domains of 30- and 10-km resolutions assimilating all conventional observations using a cyclic three-dimensional variational approach over an initial 12-h period. The improved initial conditions are then used to generate regional climate products for the following 24 h. We combined the resulting daily 24-h datasets to construct a 15-year Red Sea atmospheric downscaled product from 2000 to 2014. This 15-year downscaled dataset is evaluated via comparisons with various in situ and gridded datasets. Our analysis indicates that the assimilated model successfully reproduced the spatial and temporal variability of temperature, wind, rainfall, relative humidity and sea level pressure over the Red Sea region. The model also efficiently simulated the seasonal and monthly variability of wind patterns, the Red Sea Convergence Zone and associated rainfall. Our results suggest that dynamical downscaling and assimilation of available observations improve the representation of regional atmospheric features over the Red Sea compared to global analysis data from the National Centers for Environmental Prediction. We use the dataset to describe the atmospheric climatic conditions over the Red Sea region. © 2016 Royal Meteorological Society.

  6. Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

    Science.gov (United States)

    Hanson, D. A.; Kotamarthi, V. R.; Foster, I. T.; Franklin, M.; Zhu, E.; Patel, D. M.

    2008-12-01

    Here, we compare two scenarios based on Stanford University's Energy Modeling Forum Study 22 on global cooperative and non-cooperative climate policies. In the former, efficient transition paths are implemented including technology Research and Development effort, energy conservation programs, and price signals for greenhouse gas (GHG) emissions. In the non-cooperative case, some countries try to relax their regulations and be free riders. Total emissions and costs are higher in the non-cooperative scenario. The simulations, including climate impacts, run to the year 2100. We use the Argonne AMIGA-MARS economic-energy systems model, the Texas AM University's Forest and Agricultural Sector Optimization Model (FASOM), and the University of Illinois's Integrated Science Assessment Model (ISAM), with offline coupling between the FASOM and AMIGA-MARS and an online coupling between AMIGA-MARS and ISAM. This set of models captures the interaction of terrestrial systems, land use, crops and forests, climate change, human activity, and energy systems. Our scenario simulations represent dynamic paths over which all the climate, terrestrial, economic, and energy technology equations are solved simultaneously Special attention is paid to biofuels and how they interact with conventional gasoline/diesel fuel markets. Possible low-carbon penetration paths are based on estimated costs for new technologies, including cellulosic biomass, coal-to-liquids, plug-in electric vehicles, solar and nuclear energy. We explicitly explore key uncertainties that affect mitigation and adaptation scenarios.

  7. 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.

  8. A commentary on the Atlantic meridional overturning circulation stability in climate models

    Science.gov (United States)

    Gent, Peter R.

    2018-02-01

    The stability of the Atlantic meridional overturning circulation (AMOC) in ocean models depends quite strongly on the model formulation, especially the vertical mixing, and whether it is coupled to an atmosphere model. A hysteresis loop in AMOC strength with respect to freshwater forcing has been found in several intermediate complexity climate models and in one fully coupled climate model that has very coarse resolution. Over 40% of modern climate models are in a bistable AMOC state according to the very frequently used simple stability criterion which is based solely on the sign of the AMOC freshwater transport across 33° S. In a recent freshwater hosing experiment in a climate model with an eddy-permitting ocean component, the change in the gyre freshwater transport across 33° S is larger than the AMOC freshwater transport change. This casts very strong doubt on the usefulness of this simple AMOC stability criterion. If a climate model uses large surface flux adjustments, then these adjustments can interfere with the atmosphere-ocean feedbacks, and strongly change the AMOC stability properties. AMOC can be shut off for many hundreds of years in modern fully coupled climate models if the hosing or carbon dioxide forcing is strong enough. However, in one climate model the AMOC recovers after between 1000 and 1400 years. Recent 1% increasing carbon dioxide runs and RCP8.5 future scenario runs have shown that the AMOC reduction is smaller using an eddy-resolving ocean component than in the comparable standard 1° ocean climate models.

  9. Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

    Energy Technology Data Exchange (ETDEWEB)

    Bhatt, Uma S. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Atmospheric Sciences; Wackerbauer, Renate [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Physics; Polyakov, Igor V. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Atmospheric Sciences; Newman, David E. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Physics; Sanchez, Raul E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Fusion Energy Division; Univ. Carlos III de Madrid (Spain)

    2015-11-13

    The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were applied to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.

  10. Atmospheric sulfur and climate changes: a modelling study at mid and high-southern latitudes

    International Nuclear Information System (INIS)

    Castebrunet, H.

    2007-09-01

    The mid and high-southern latitudes are still marginally affected by anthropogenic sulfur emissions. They are the only regions in the world where the natural cycle of the atmospheric sulfur may still be observed. Sulfur aerosols are well-known for their radiative impact, and thus interact with climate. Climate can in turn affect atmospheric sulfur sources, distribution and chemistry. Antarctic ice cores provide information on the evolution of climate and sulfur deposition at the surface of the ice sheet at glacial-interglacial time scales. The aim of this thesis is to develop and use modeling towards a better understanding of the atmospheric sulfur cycle in antarctic and sub-antarctic regions. Ice core data are used to validate model results under glacial climate conditions. An Atmospheric General Circulation Model (AGCM) coupled to a sulfur chemistry module is used: the LMD-ZTSulfur model, version 4. An update of both the physical and chemical parts of the model. The model was first performed. The impact of there changes on modelled sulfur cycle are evaluated for modern climate. Further, boundary conditions are adapted to simulate the atmospheric circulation and sulfur cycle at the Last Glacial Maximum, approximately 20,000 years ago. In the model, sulfur is found to be highly sensitive to antarctic sea-ice coverage, which is still poorly known during the ice age. An original dataset of ice-age sea-ice coverage was developed. Its impact on the oceanic emissions of dimethyl sulfide, main precursor of sulfur aerosols at high-southern latitudes, is discussed. Using the same oceanic sulfur reservoirs as for present day climate, the model broadly reproduces the glacial deposits of sulfur aerosols on the Antarctic plateau, suggesting little impact of climate on oceanic sulfur production in the Antarctic region. Sensitivity tests were carried out to draw an up-to-date status of major uncertainties and difficulties facing future progress in understanding atmospheric

  11. Chapter 7: Developing climate-informed state-and-transition models

    Science.gov (United States)

    Miles A. Hemstrom; Jessica E. Halofsky; David R. Conklin; Joshua S. Halofsky; Dominique Bachelet; Becky K. Kerns

    2014-01-01

    Land managers and others need ways to understand the potential effects of climate change on local vegetation types and how management activities might be impacted by climate change. To date, climate change impact models have not included localized vegetation communities or the integrated effects of vegetation development dynamics, natural disturbances, and management...

  12. Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change

    Science.gov (United States)

    Reese, Gordon; Skagen, Susan K.

    2017-01-01

    To identify areas on the landscape that may contribute to a robust network of conservation areas, we modeled the probabilities of occurrence of several en route migratory shorebirds and wintering waterfowl in the southern Great Plains of North America, including responses to changing climate. We predominantly used data from the eBird citizen-science project to model probabilities of occurrence relative to land-use patterns, spatial distribution of wetlands, and climate. We projected models to potential future climate conditions using five representative general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5). We used Random Forests to model probabilities of occurrence and compared the time periods 1981–2010 (hindcast) and 2041–2070 (forecast) in “model space.” Projected changes in shorebird probabilities of occurrence varied with species-specific general distribution pattern, migration distance, and spatial extent. Species using the western and northern portion of the study area exhibited the greatest likelihoods of decline, whereas species with more easterly occurrences, mostly long-distance migrants, had the greatest projected increases in probability of occurrence. At an ecoregional extent, differences in probabilities of shorebird occurrence ranged from −0.015 to 0.045 when averaged across climate models, with the largest increases occurring early in migration. Spatial shifts are predicted for several shorebird species. Probabilities of occurrence of wintering Mallards and Northern Pintail are predicted to increase by 0.046 and 0.061, respectively, with northward shifts projected for both species. When incorporated into partner land management decision tools, results at ecoregional extents can be used to identify wetland complexes with the greatest potential to support birds in the nonbreeding season under a wide range of future climate scenarios.

  13. Sensitivity of hydrological modeling to meteorological data and implications for climate change studies

    International Nuclear Information System (INIS)

    Roy, L.G.; Roy, R.; Desrochers, G.E.; Vaillancourt, C.; Chartier, I.

    2008-01-01

    There are uncertainties associated with the use of hydrological models. This study aims to analyse one source of uncertainty associated with hydrological modeling, particularly in the context of climate change studies on water resources. Additional intent of this study is to compare the ability of some meteorological data sources, used in conjunction with an hydrological model, to reproduce the hydrologic regime of a watershed. A case study on a watershed of south-western Quebec, Canada using five different sources of meteorological data as input to an offline hydrological model are presented in this paper. Data used came from weather stations, NCEP reanalysis, ERA40 reanalysis and two Canadian Regional Climate Model (CRCM) runs driven by NCEP and ERA40 reanalysis, providing atmospheric driving boundary conditions to this limited-area climate model. To investigate the sensitivity of simulated streamflow to different sources of meteorological data, we first calibrated the hydrological model with each of the meteorological data sets over the 1961-1980 period. The five different sets of parameters of the hydrological model were then used to simulate streamflow of the 1981-2000 validation period with the five meteorological data sets as inputs. The 25 simulated streamflow series have been compared to the observed streamflow of the watershed. The five meteorological data sets do not have the same ability, when used with the hydrological model, to reproduce streamflow. Our results show also that the hydrological model parameters used may have an important influence on results such as water balance, but it is linked with the differences that may have in the characteristics of the meteorological data used. For climate change impacts assessments on water resources, we have found that there is an uncertainty associated with the meteorological data used to calibrate the model. For expected changes on mean annual flows of the Chateauguay River, our results vary from a small

  14. A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

    Directory of Open Access Journals (Sweden)

    Rachel D. Cavanagh

    2017-09-01

    Full Text Available Increasing concern about the impacts of climate change on ecosystems is prompting ecologists and ecosystem managers to seek reliable projections of physical drivers of change. The use of global climate models in ecology is growing, although drawing ecologically meaningful conclusions can be problematic. The expertise required to access and interpret output from climate and earth system models is hampering progress in utilizing them most effectively to determine the wider implications of climate change. To address this issue, we present a joint approach between climate scientists and ecologists that explores key challenges and opportunities for progress. As an exemplar, our focus is the Southern Ocean, notable for significant change with global implications, and on sea ice, given its crucial role in this dynamic ecosystem. We combined perspectives to evaluate the representation of sea ice in global climate models. With an emphasis on ecologically-relevant criteria (sea ice extent and seasonality we selected a subset of eight models that reliably reproduce extant sea ice distributions. While the model subset shows a similar mean change to the full ensemble in sea ice extent (approximately 50% decline in winter and 30% decline in summer, there is a marked reduction in the range. This improved the precision of projected future sea ice distributions by approximately one third, and means they are more amenable to ecological interpretation. We conclude that careful multidisciplinary evaluation of climate models, in conjunction with ongoing modeling advances, should form an integral part of utilizing model output.

  15. 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

  16. Global climate model performance over Alaska and Greenland

    DEFF Research Database (Denmark)

    Walsh, John E.; Chapman, William L.; Romanovsky, Vladimir

    2008-01-01

    The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958...... to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic....... of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic...

  17. A report on workshops: General circulation model study of climate- chemistry interaction

    International Nuclear Information System (INIS)

    Wei-Chyung, Wang; Isaksen, I.S.A.

    1993-01-01

    This report summarizes the discussion on General Circulation Model Study of Climate-Chemistry Interaction from two workshops, the first held 19--21 August 1992 at Oslo, Norway and the second 26--27 May 1993 at Albany, New York, USA. The workshops are the IAMAP activities under the Trace Constituent Working Group. The main objective of the two workshops was to recommend specific general circulation model (GCM) studies of the ozone distribution and the climatic effect of its changes. The workshops also discussed the climatic implications of increasing sulfate aerosols because of its importance to regional climate. The workshops were organized into four working groups: observation of atmospheric O 3 ; modeling of atmospheric chemical composition; modeling of sulfate aerosols; and aspects of climate modeling

  18. Climate engineering and the risk of rapid climate change

    International Nuclear Information System (INIS)

    Ross, Andrew; Damon Matthews, H

    2009-01-01

    Recent research has highlighted risks associated with the use of climate engineering as a method of stabilizing global temperatures, including the possibility of rapid climate warming in the case of abrupt removal of engineered radiative forcing. In this study, we have used a simple climate model to estimate the likely range of temperature changes associated with implementation and removal of climate engineering. In the absence of climate engineering, maximum annual rates of warming ranged from 0.015 to 0.07 deg. C/year, depending on the model's climate sensitivity. Climate engineering resulted in much higher rates of warming, with the temperature change in the year following the removal of climate engineering ranging from 0.13 to 0.76 deg. C. High rates of temperature change were sustained for two decades following the removal of climate engineering; rates of change of 0.5 (0.3,0.1) deg. C/decade were exceeded over a 20 year period with 15% (75%, 100%) likelihood. Many ecosystems could be negatively affected by these rates of temperature change; our results suggest that climate engineering in the absence of deep emissions cuts could arguably constitute increased risk of dangerous anthropogenic interference in the climate system under the criteria laid out in the United Nations Framework Convention on Climate Change.

  19. Prospects for future climate: A special US/USSR report on climate and climate change

    International Nuclear Information System (INIS)

    MacCracken, M.C.; Budyko, M.I.; Hecht, A.D.; Izrael, Y.A.

    1990-01-01

    Starting with the US-USSR Agreement on Protection of the Environment signed in 1972, the two nations have cooperated in joint research on atmospheric and environmental problems. The result of these efforts has been an innovative approach to projecting future climate change based on what has been learned about past warm periods and what can be learned from models. The chapters in this document explore the following: past changes in climate, both paleoclimatology and changes in the recent past; changes in atmospheric composition; estimates of greenhouse-induced change including the use of both empirical methods and climate models; impacts of climate change on water resources and agriculture in the two countries; and prospects for future climate changes

  20. Daily precipitation statistics in regional climate models

    DEFF Research Database (Denmark)

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

    2003-01-01

    An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...

  1. Modelling and Mapping Oxygen-18 Isotope Composition of Precipitation in Spain for Hydrologic and Climatic Applications

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez-Arevalo, J.; Diaz-Teijeiro, M. F. [Centro de Estudios y Experimentacion de Obras Publicas (CEDEX), Madrid (Spain); Castano, S. [Geological Survey of Spain (IGME), Madrid (Spain)

    2013-07-15

    A simple multiple regression model based on two geographic factors (latitude and elevation) has been developed that reproduces reasonably well the spatial distribution of the current mean oxygen-18 isotope composition in precipitation over spain. In a preliminary analysis, additional geographic and climatic factors do not improve the performance of the model. A continuous digital map of oxygen-18 isotope composition in precipitation has been produced by combining the polynomial model with a digital elevation model using GIS tools. Application of the resulting map to several groundwater case studies in spain has shown it to be useful as a reference of the input function to recharge. Further validation of the model, and further testing of its usefulness in surface hydrology and climatic studies, is ongoing through comparison of model results with isotope data from the GNIP database and from isotope studies in hydrogeology and climate change taking place in spain. (author)

  2. Hydrologic response to multimodel climate output using a physically based model of groundwater/surface water interactions

    Science.gov (United States)

    Sulis, M.; Paniconi, C.; Marrocu, M.; Huard, D.; Chaumont, D.

    2012-12-01

    General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability.

  3. Intervention model in organizational climate

    OpenAIRE

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

    2015-01-01

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

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  5. Modelling coffee leaf rust risk in Colombia with climate reanalysis data.

    Science.gov (United States)

    Bebber, Daniel P; Castillo, Ángela Delgado; Gurr, Sarah J

    2016-12-05

    Many fungal plant diseases are strongly controlled by weather, and global climate change is thus likely to have affected fungal pathogen distributions and impacts. Modelling the response of plant diseases to climate change is hampered by the difficulty of estimating pathogen-relevant microclimatic variables from standard meteorological data. The availability of increasingly sophisticated high-resolution climate reanalyses may help overcome this challenge. We illustrate the use of climate reanalyses by testing the hypothesis that climate change increased the likelihood of the 2008-2011 outbreak of Coffee Leaf Rust (CLR, Hemileia vastatrix) in Colombia. We develop a model of germination and infection risk, and drive this model using estimates of leaf wetness duration and canopy temperature from the Japanese 55-Year Reanalysis (JRA-55). We model germination and infection as Weibull functions with different temperature optima, based upon existing experimental data. We find no evidence for an overall trend in disease risk in coffee-growing regions of Colombia from 1990 to 2015, therefore, we reject the climate change hypothesis. There was a significant elevation in predicted CLR infection risk from 2008 to 2011 compared with other years. JRA-55 data suggest a decrease in canopy surface water after 2008, which may have helped terminate the outbreak. The spatial resolution and accuracy of climate reanalyses are continually improving, increasing their utility for biological modelling. Confronting disease models with data requires not only accurate climate data, but also disease observations at high spatio-temporal resolution. Investment in monitoring, storage and accessibility of plant disease observation data are needed to match the quality of the climate data now available.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Authors.

  6. Projecting regional climate and cropland changes using a linked biogeophysical-socioeconomic modeling framework: 1. Model description and an equilibrium application over West Africa

    Science.gov (United States)

    Wang, Guiling; Ahmed, Kazi Farzan; You, Liangzhi; Yu, Miao; Pal, Jeremy; Ji, Zhenming

    2017-03-01

    Agricultural land use alters regional climate through modifying the surface mass, energy, and momentum fluxes; climate influences agricultural land use through their impact on crop yields. These interactions are not well understood and have not been adequately considered in climate projections. This study tackles the critical linkages within the coupled natural-human system of West Africa in a changing climate based on an equilibrium application of a modeling framework that asynchronously couples models of regional climate, crop yield, multimarket agricultural economics, and cropland expansion. Using this regional modeling framework driven with two global climate models, we assess the contributions of land use change (LUC) and greenhouse gas (GHGs) concentration changes to regional climate changes and assess the contribution of climate change and socioeconomic factors to agricultural land use changes. For future cropland expansion in West Africa, our results suggest that socioeconomic development would be the dominant driver in the east (where current cropland coverage is already high) and climate changes would be the primary driver in the west (where future yield drop is severe). For future climate, it is found that agricultural expansion would cause a dry signal in the west and a wet signal in the east downwind, with an east-west contrast similar to the GHG-induced changes. Over a substantial portion of West Africa, the strength of the LUC-induced climate signals is comparable to the GHG-induced changes. Uncertainties originating from the driving global models are small; human decision making related to land use and international trade is a major source of uncertainty.

  7. Climate versus carbon dioxide controls on biomass burning: a model analysis of the glacial-interglacial contrast

    Science.gov (United States)

    Calvo, M. Martin; Prentice, I. C.; Harrison, S. P.

    2014-11-01

    Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness. CO2 concentration constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence on CO2 concentration, the quantitative relationship between atmospheric CO2 concentration and biomass burning is not well understood. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial-interglacial changes in biomass burning to an increase in CO2, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided last glacial maximum (LGM) climate anomalies - that is, differences from the pre-industrial (PI) control climate - from the Palaeoclimate Modelling Intercomparison Project Phase~2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes from biomass burning were corrected for the model's observed prediction biases in contemporary regional average values for biomes. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux at the LGM was in the range of 1.0-1.4 Pg C year-1, about a third less than that modelled for PI time. LGM climate with pre-industrial CO2 (280 ppm) yielded unrealistic results, with global biomass burning fluxes similar to or even greater than in the pre-industrial climate. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on primary production and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to project future fire risks.

  8. Modeling the impact of large-scale energy conversion systems on global climate

    International Nuclear Information System (INIS)

    Williams, J.

    There are three energy options which could satisfy a projected energy requirement of about 30 TW and these are the solar, nuclear and (to a lesser extent) coal options. Climate models can be used to assess the impact of large scale deployment of these options. The impact of waste heat has been assessed using energy balance models and general circulation models (GCMs). Results suggest that the impacts are significant when the heat imput is very high and studies of more realistic scenarios are required. Energy balance models, radiative-convective models and a GCM have been used to study the impact of doubling the atmospheric CO 2 concentration. State-of-the-art models estimate a surface temperature increase of 1.5-3.0 0 C with large amplification near the poles, but much uncertainty remains. Very few model studies have been made of the impact of particles on global climate, more information on the characteristics of particle input are required. The impact of large-scale deployment of solar energy conversion systems has received little attention but model studies suggest that large scale changes in surface characteristics associated with such systems (surface heat balance, roughness and hydrological characteristics and ocean surface temperature) could have significant global climatic effects. (Auth.)

  9. Modelling Snowmelt Runoff under Climate Change Scenarios in an Ungauged Mountainous Watershed, Northwest China

    Directory of Open Access Journals (Sweden)

    Yonggang Ma

    2013-01-01

    Full Text Available An integrated modeling system has been developed for analyzing the impact of climate change on snowmelt runoff in Kaidu Watershed, Northwest China. The system couples Hadley Centre Coupled Model version 3 (HadCM3 outputs with Snowmelt Runoff Model (SRM. The SRM was verified against observed discharge for outlet hydrological station of the watershed during the period from April to September in 2001 and generally performed well for Nash-Sutcliffe coefficient (EF and water balance coefficient (RE. The EF is approximately over 0.8, and the water balance error is lower than ± 10%, indicating reasonable prediction accuracy. The Statistical Downscaling Model (SDSM was used to downscale coarse outputs of HadCM3, and then the downscaled future climate data were used as inputs of the SRM. Four scenarios were considered for analyzing the climate change impact on snowmelt flow in the Kaidu Watershed. And the results indicated that watershed hydrology would alter under different climate change scenarios. The stream flow in spring is likely to increase with the increased mean temperature; the discharge and peck flow in summer decrease with the decreased precipitation under Scenarios 1 and 2. Moreover, the consideration of the change in cryosphere area would intensify the variability of stream flow under Scenarios 3 and 4. The modeling results provide useful decision support for water resources management.

  10. Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

    Science.gov (United States)

    Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

    2013-12-01

    Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

  11. Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

    Science.gov (United States)

    Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

    2013-01-01

    Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

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

    Science.gov (United States)

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

    2013-12-01

    /ha in many areas. The simulated yield changes in the future were both spatially explicit and dependent on the GCM used. The effectiveness of agronomic practices was highly varied across the region depending on soil type, agro-ecological zone and projected climate change. The results have critical implications for agronomic research and policy. The study challenges using a ';one size fits all' approach in the identification of potential adaptation strategies. The goal is to use models to target local, optimized solutions as part of the broader need for impact assessments at coarser scales.

  13. "On Clocks and Clouds:" Confirming and Interpreting Climate Models as Scientific Hypotheses (Invited)

    Science.gov (United States)

    Donner, L.

    2009-12-01

    The certainty of climate change projected under various scenarios of emissions using general circulation models is an issue of vast societal importance. Unlike numerical weather prediction, a problem to which general circulation models are also applied, projected climate changes usually lie outside of the range of external forcings for which the models generating these changes have been directly evaluated. This presentation views climate models as complex scientific hypotheses and thereby frames these models within a well-defined process of both advancing scientific knowledge and recognizing its limitations. Karl Popper's Logik der Forschung (The Logic of Scientific Discovery, 1934) and 1965 essay “On Clocks and Clouds” capture well the methodologies and challenges associated with constructing climate models. Indeed, the process of a problem situation generating tentative theories, refined by error elimination, characterizes aptly the routine of general circulation model development. Limitations on certainty arise from the distinction Popper perceived in types of natural processes, which he exemplified by clocks, capable of exact measurement, and clouds, subject only to statistical approximation. Remarkably, the representation of clouds in general circulation models remains the key uncertainty in understanding atmospheric aspects of climate change. The asymmetry of hypothesis falsification by negation and much vaguer development of confidence in hypotheses consistent with some of their implications is an important practical challenge to confirming climate models. The presentation will discuss the ways in which predictions made by climate models for observable aspects of the present and past climate can be regarded as falsifiable hypotheses. The presentation will also include reasons why “passing” these tests does not provide complete confidence in predictions about the future by climate models. Finally, I will suggest that a “reductionist” view, in

  14. What is the role of historical anthropogenically-induced land-cover change on the surface climate of West Africa? Results from the LUCID intercomparison project

    Science.gov (United States)

    Souleymane, S.

    2015-12-01

    West Africa has been highlighted as a hot spot of land surface-atmosphere interactions. This study analyses the outputs of the project Land-Use and Climate, IDentification of Robust Impacts (LUCID) over West Africa. LUCID used seven atmosphere-land models with a common experimental design to explore the impacts of Land Use induced Land Cover Change (LULCC) that are robust and consistent across the climate models. Focusing the analysis on Sahel and Guinea, this study shows that, even though the seven climate models use the same atmospheric and land cover forcing, there are significant differences of West African Monsoon variability across the climate models. The magnitude of that variability differs significantly from model to model resulting two major "features": (1) atmosphere dynamics models; (2) how the land-surface functioning is parameterized in the Land surface Model, in particular regarding the evapotranspiration partitioning within the different land-cover types, as well as the role of leaf area index (LAI) in the flux calculations and how strongly the surface is coupled to the atmosphere. The major role that the models'sensitivity to land-cover perturbations plays in the resulting climate impacts of LULCC has been analysed in this study. The climate models show, however, significant differences in the magnitude and the seasonal partitioning of the temperature change. The LULCC induced cooling is directed by decreases in net shortwave radiation that reduced the available energy (QA) (related to changes in land-cover properties other than albedo, such as LAI and surface roughness), which decreases during most part of the year. The biophysical impacts of LULCC were compared to the impact of elevated greenhouse gases resulting changes in sea surface temperatures and sea ice extent (CO2SST). The results show that the surface cooling (related a decrease in QA) induced by the biophysical effects of LULCC are insignificant compared to surface warming (related an

  15. Climate vs. carbon dioxide controls on biomass burning: a model analysis of the glacial-interglacial contrast

    Science.gov (United States)

    Calvo, M. Martin; Prentice, I. C.; Harrison, S. P.

    2014-02-01

    Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness; CO2 availability, in turn, constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence CO2 availability, the links between atmospheric CO2 and biomass burning are not well known. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial-interglacial changes in biomass burning to CO2 increase, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided Last Glacial Maximum (LGM) climate anomalies - that is, differences from the pre-industrial (PI) control climate - from the Palaeoclimate Modelling Intercomparison Project Phase 2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes in biomass burning were corrected for the model's observed biases in contemporary biome-average values. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux was 70 to 80% lower at the LGM than in PI time. LGM climate with pre-industrial CO2 (280 ppm) however yielded unrealistic results, with global and Northern Hemisphere biomass burning fluxes greater than in the pre-industrial climate. Using the PI CO2 concentration increased the modelled LGM biomass burning fluxes for all climate models and latitudinal bands to between four and ten times their values under LGM CO2 concentration. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on productivity and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to

  16. Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change

    Science.gov (United States)

    1997-01-01

    This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the Goddard Institute for Space Studies (GISS) 8 deg x lO deg atmospheric General Circulation Model (GCM) to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2.

  17. Use of regional climate models data for groundwater recharge modelling in Baltic artesian basin

    Science.gov (United States)

    Timuhins, A.; Klints, I.; Sennikovs, J.; Virbulis, J.

    2012-04-01

    Baltic artesian basin (BAB) covers about 480000 square kilometres. BAB includes territory of Latvia, Lithuania, Estonia, parts of Poland, Russia, Belarus and Baltic Sea. The closed hydrogeological mathematical model for the BAB is developed in University of Latvia and reference calculations made in steady state mode. No-flow boundary condition is applied on the bottom and side boundaries of BAB. Hydraulic head is fixed on the seabed and largest lakes, and along the main river lines. Main water supply wells also are presented in the model as a pointwise water extraction. Precipitation is the main source of the groundwater recharge in the BAB region. Infiltration parameterization is responsible for this water source in BAB model. During the early stage of calibration of BAB hydrogeological model an automatic calibration for the hydraulic conductivities of permeable layers and single infiltration rate was attempted. Performing BAB model calibration it was noted that the differences of calculated and observed hydraulic heads (used for calculating the calibration penalty function) can be reduced by introducing a spatially distributed infiltration model. The aim of the present study is improving of the infiltration model, as well as preserving a short computation time (several minutes) for the piezometric head. Direct solution of improvement of the infiltration would be a usage of the advanced hydrological models. However, an accurate hydrological model requires a lot of computational power. It should couple meteorological and hydrological parameters and requires additional calibration. The regional climate model (KNMI-RACMO2 25 km resolution) results from ENSEMBLES project are used for the spatially distributed infiltration field calculation. The infiltration field is constructed as weighted difference of 30 year averaged precipitation and evaporation fields. The weight value is calibrated and a considerable decrease of the value of penalty function of the groundwater

  18. Technical Note: On the use of nudging for aerosol-climate model intercomparison studies

    Science.gov (United States)

    Zhang, K.; Wan, H.; Liu, X.; Ghan, S. J.; Kooperman, G. J.; Ma, P.-L.; Rasch, P. J.; Neubauer, D.; Lohmann, U.

    2014-08-01

    Nudging as an assimilation technique has seen increased use in recent years in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5 (CAM5), due to the systematic temperature bias in the standard model and the sensitivity of simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on long-wave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations, and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. Results from both CAM5 and a second aerosol-climate model ECHAM6-HAM2 also indicate that compared to the wind-and-temperature nudging, constraining only winds leads to better agreement with the free-running model in terms of the estimated shortwave cloud forcing and the simulated convective activities. This suggests nudging the horizontal winds but not temperature is a

  19. Technical Note: On the use of nudging for aerosol–climate model intercomparison studies

    Directory of Open Access Journals (Sweden)

    K. Zhang

    2014-08-01

    Full Text Available Nudging as an assimilation technique has seen increased use in recent years in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5 (CAM5, due to the systematic temperature bias in the standard model and the sensitivity of simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on long-wave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations, and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. Results from both CAM5 and a second aerosol–climate model ECHAM6-HAM2 also indicate that compared to the wind-and-temperature nudging, constraining only winds leads to better agreement with the free-running model in terms of the estimated shortwave cloud forcing and the simulated convective activities. This suggests nudging the horizontal winds but

  20. Adjoint-Based Climate Model Tuning: Application to the Planet Simulator

    Science.gov (United States)

    Lyu, Guokun; Köhl, Armin; Matei, Ion; Stammer, Detlef

    2018-01-01

    The adjoint method is used to calibrate the medium complexity climate model "Planet Simulator" through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA-Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models.

  1. Increase in flood risk resulting from climate change in a developed urban watershed - the role of storm temporal patterns

    Science.gov (United States)

    Hettiarachchi, Suresh; Wasko, Conrad; Sharma, Ashish

    2018-03-01

    The effects of climate change are causing more frequent extreme rainfall events and an increased risk of flooding in developed areas. Quantifying this increased risk is of critical importance for the protection of life and property as well as for infrastructure planning and design. The updated National Oceanic and Atmospheric Administration (NOAA) Atlas 14 intensity-duration-frequency (IDF) relationships and temporal patterns are widely used in hydrologic and hydraulic modeling for design and planning in the United States. Current literature shows that rising temperatures as a result of climate change will result in an intensification of rainfall. These impacts are not explicitly included in the NOAA temporal patterns, which can have consequences on the design and planning of adaptation and flood mitigation measures. In addition there is a lack of detailed hydraulic modeling when assessing climate change impacts on flooding. The study presented in this paper uses a comprehensive hydrologic and hydraulic model of a fully developed urban/suburban catchment to explore two primary questions related to climate change impacts on flood risk. (1) How do climate change effects on storm temporal patterns and rainfall volumes impact flooding in a developed complex watershed? (2) Is the storm temporal pattern as critical as the total volume of rainfall when evaluating urban flood risk? We use the NOAA Atlas 14 temporal patterns, along with the expected increase in temperature for the RCP8.5 scenario for 2081-2100, to project temporal patterns and rainfall volumes to reflect future climatic change. The model results show that different rainfall patterns cause variability in flood depths during a storm event. The changes in the projected temporal patterns alone increase the risk of flood magnitude up to 35 %, with the cumulative impacts of temperature rise on temporal patterns and the storm volume increasing flood risk from 10 to 170 %. The results also show that regional

  2. Predicting climate-induced range shifts: model differences and model reliability.

    Science.gov (United States)

    Joshua J. Lawler; Denis White; Ronald P. Neilson; Andrew R. Blaustein

    2006-01-01

    Predicted changes in the global climate are likely to cause large shifts in the geographic ranges of many plant and animal species. To date, predictions of future range shifts have relied on a variety of modeling approaches with different levels of model accuracy. Using a common data set, we investigated the potential implications of alternative modeling approaches for...

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  4. How do the methodological choices of your climate change study affect your results? A hydrologic case study across the Pacific Northwest

    Science.gov (United States)

    Chegwidden, O.; Nijssen, B.; Rupp, D. E.; Kao, S. C.; Clark, M. P.

    2017-12-01

    We describe results from a large hydrologic climate change dataset developed across the Pacific Northwestern United States and discuss how the analysis of those results can be seen as a framework for other large hydrologic ensemble investigations. This investigation will better inform future modeling efforts and large ensemble analyses across domains within and beyond the Pacific Northwest. Using outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we provide projections of hydrologic change for the domain through the end of the 21st century. The dataset is based upon permutations of four methodological choices: (1) ten global climate models (2) two representative concentration pathways (3) three meteorological downscaling methods and (4) four unique hydrologic model set-ups (three of which entail the same hydrologic model using independently calibrated parameter sets). All simulations were conducted across the Columbia River Basin and Pacific coastal drainages at a 1/16th ( 6 km) resolution and at a daily timestep. In total, the 172 distinct simulations offer an updated, comprehensive view of climate change projections through the end of the 21st century. The results consist of routed streamflow at 400 sites throughout the domain as well as distributed spatial fields of relevant hydrologic variables like snow water equivalent and soil moisture. In this presentation, we discuss the level of agreement with previous hydrologic projections for the study area and how these projections differ with specific methodological choices. By controlling for some methodological choices we can show how each choice affects key climatic change metrics. We discuss how the spread in results varies across hydroclimatic regimes. We will use this large dataset as a case study for distilling a wide range of hydroclimatological projections into useful climate change assessments.

  5. The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

    Science.gov (United States)

    Shukla, Sonali P.; Ruane, Alexander Clark

    2014-01-01

    Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, and water (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models' responses to CTW changes (Rotter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012). To fulfill this need, the Coordinated Climate-Crop Modeling Project (C3MP) (Ruane et al., 2014) was initiated within the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013). The submitted results from C3MP Phase 1 (February 15, 2013-December 31, 2013) are currently being analyzed. This chapter serves to present and update the C3MP protocols, discuss the initial participation and general findings, comment on needed adjustments, and describe continued and future development. AgMIP aims to improve

  6. School Climate, Peer Victimization, and Academic Achievement: Results from a Multi-Informant Study

    Science.gov (United States)

    Wang, Weijun; Vaillancourt, Tracy; Brittain, Heather L.; McDougall, Patricia; Krygsman, Amanda; Smith, David; Cunningham, Charles E.; Haltigan, J. D.; Hymel, Shelley

    2014-01-01

    School-level school climate was examined in relation to self-reported peer victimization and teacher-rated academic achievement (grade point average; GPA). Participants included a sample of 1,023 fifth-grade children nested within 50 schools. Associations between peer victimization, school climate, and GPA were examined using multilevel modeling,…

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

    Directory of Open Access Journals (Sweden)

    Y. Fan

    2017-06-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  9. 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

    1998-12-31

    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.

  10. 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.

  11. Water-Constrained Electric Sector Capacity Expansion Modeling Under Climate Change Scenarios

    Science.gov (United States)

    Cohen, S. M.; Macknick, J.; Miara, A.; Vorosmarty, C. J.; Averyt, K.; Meldrum, J.; Corsi, F.; Prousevitch, A.; Rangwala, I.

    2015-12-01

    Over 80% of U.S. electricity generation uses a thermoelectric process, which requires significant quantities of water for power plant cooling. This water requirement exposes the electric sector to vulnerabilities related to shifts in water availability driven by climate change as well as reductions in power plant efficiencies. Electricity demand is also sensitive to climate change, which in most of the United States leads to warming temperatures that increase total cooling-degree days. The resulting demand increase is typically greater for peak demand periods. This work examines the sensitivity of the development and operations of the U.S. electric sector to the impacts of climate change using an electric sector capacity expansion model that endogenously represents seasonal and local water resource availability as well as climate impacts on water availability, electricity demand, and electricity system performance. Capacity expansion portfolios and water resource implications from 2010 to 2050 are shown at high spatial resolution under a series of climate scenarios. Results demonstrate the importance of water availability for future electric sector capacity planning and operations, especially under more extreme hotter and drier climate scenarios. In addition, region-specific changes in electricity demand and water resources require region-specific responses that depend on local renewable resource availability and electricity market conditions. Climate change and the associated impacts on water availability and temperature can affect the types of power plants that are built, their location, and their impact on regional water resources.

  12. Future bloom and blossom frost risk for Malus domestica considering climate model and impact model uncertainties.

    Science.gov (United States)

    Hoffmann, Holger; Rath, Thomas

    2013-01-01

    The future bloom and risk of blossom frosts for Malus domestica were projected using regional climate realizations and phenological ( = impact) models. As climate impact projections are susceptible to uncertainties of climate and impact models and model concatenation, the significant horizon of the climate impact signal was analyzed by applying 7 impact models, including two new developments, on 13 climate realizations of the IPCC emission scenario A1B. Advancement of phenophases and a decrease in blossom frost risk for Lower Saxony (Germany) for early and late ripeners was determined by six out of seven phenological models. Single model/single grid point time series of bloom showed significant trends by 2021-2050 compared to 1971-2000, whereas the joint signal of all climate and impact models did not stabilize until 2043. Regarding blossom frost risk, joint projection variability exceeded the projected signal. Thus, blossom frost risk cannot be stated to be lower by the end of the 21st century despite a negative trend. As a consequence it is however unlikely to increase. Uncertainty of temperature, blooming date and blossom frost risk projection reached a minimum at 2078-2087. The projected phenophases advanced by 5.5 d K(-1), showing partial compensation of delayed fulfillment of the winter chill requirement and faster completion of the following forcing phase in spring. Finally, phenological model performance was improved by considering the length of day.

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

    Science.gov (United States)

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

    2011-12-01

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

  14. A paradigm shift toward a consistent modeling framework to assess climate impacts

    Science.gov (United States)

    Monier, E.; Paltsev, S.; Sokolov, A. P.; Fant, C.; Chen, H.; Gao, X.; Schlosser, C. A.; Scott, J. R.; Dutkiewicz, S.; Ejaz, Q.; Couzo, E. A.; Prinn, R. G.; Haigh, M.

    2017-12-01

    Estimates of physical and economic impacts of future climate change are subject to substantial challenges. To enrich the currently popular approaches of assessing climate impacts by evaluating a damage function or by multi-model comparisons based on the Representative Concentration Pathways (RCPs), we focus here on integrating impacts into a self-consistent coupled human and Earth system modeling framework that includes modules that represent multiple physical impacts. In a sample application we show that this framework is capable of investigating the physical impacts of climate change and socio-economic stressors. The projected climate impacts vary dramatically across the globe in a set of scenarios with global mean warming ranging between 2.4°C and 3.6°C above pre-industrial by 2100. Unabated emissions lead to substantial sea level rise, acidification that impacts the base of the oceanic food chain, air pollution that exceeds health standards by tenfold, water stress that impacts an additional 1 to 2 billion people globally and agricultural productivity that decreases substantially in many parts of the world. We compare the outcomes from these forward-looking scenarios against the common goal described by the target-driven scenario of 2°C, which results in much smaller impacts. It is challenging for large internationally coordinated exercises to respond quickly to new policy targets. We propose that a paradigm shift toward a self-consistent modeling framework to assess climate impacts is needed to produce information relevant to evolving global climate policy and mitigation strategies in a timely way.

  15. Biodiversity and Climate Modeling Workshop Series: Identifying gaps and needs for improving large-scale biodiversity models

    Science.gov (United States)

    Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.

    2017-12-01

    At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.

  16. Climate modeling - a tool for the assessment of the paleodistribution of source and reservoir rocks

    Energy Technology Data Exchange (ETDEWEB)

    Roscher, M.; Schneider, J.W. [Technische Univ. Bergakademie Freiberg (Germany). Inst. fuer Geologie; Berner, U. [Bundesanstalt fuer Geowissenschaften und Rohstoffe, Hannover (Germany). Referat Organische Geochemie/Kohlenwasserstoff-Forschung

    2008-10-23

    In an on-going project of BGR and TU Bergakademie Freiberg, numeric paleo-climate modeling is used as a tool for the assessment of the paleo-distribution of organic rich deposits as well as of reservoir rocks. This modeling approach is based on new ideas concerning the formation of the Pangea supercontinent. The new plate tectonic concept is supported by paleo- magnetic data as it fits the 95% confidence interval of published data. Six Permocarboniferous time slices (340, 320, 300, 290, 270, 255 Ma) were chosen within a first paleo-climate modeling approach as they represent the most important changes of the Late Paleozoic climate development. The digital maps have a resolution of 2.8 x 2.8 (T42), suitable for high-resolution climate modeling, using the PLASIM model. CO{sub 2} concentrations of the paleo-atmosphere and paleo-insolation values have been estimated by published methods. For the purpose of validation, quantitative model output, had to be transformed into qualitative parameters in order to be able to compare digital data with qualitative data of geologic indicators. The model output of surface temperatures and precipitation was therefore converted into climate zones. The reconstructed occurrences of geological indicators like aeolian sands, evaporites, reefs, coals, oil source rocks, tillites, phosphorites and cherts were then compared to the computed paleo-climate zones. Examples of the Permian Pangea show a very good agreement between model results and geological indicators. From the modeling approach we are able to identify climatic processes which lead to the deposition of hydrocarbon source and reservoir rocks. The regional assessment of such atmospheric processes may be used for the identification of the paleo-distribution of organic rich deposits or rock types suitable to form hydrocarbon reservoirs. (orig.)

  17. The impact of structural error on parameter constraint in a climate model

    Science.gov (United States)

    McNeall, Doug; Williams, Jonny; Booth, Ben; Betts, Richard; Challenor, Peter; Wiltshire, Andy; Sexton, David

    2016-11-01

    Uncertainty in the simulation of the carbon cycle contributes significantly to uncertainty in the projections of future climate change. We use observations of forest fraction to constrain carbon cycle and land surface input parameters of the global climate model FAMOUS, in the presence of an uncertain structural error. Using an ensemble of climate model runs to build a computationally cheap statistical proxy (emulator) of the climate model, we use history matching to rule out input parameter settings where the corresponding climate model output is judged sufficiently different from observations, even allowing for uncertainty. Regions of parameter space where FAMOUS best simulates the Amazon forest fraction are incompatible with the regions where FAMOUS best simulates other forests, indicating a structural error in the model. We use the emulator to simulate the forest fraction at the best set of parameters implied by matching the model to the Amazon, Central African, South East Asian, and North American forests in turn. We can find parameters that lead to a realistic forest fraction in the Amazon, but that using the Amazon alone to tune the simulator would result in a significant overestimate of forest fraction in the other forests. Conversely, using the other forests to tune the simulator leads to a larger underestimate of the Amazon forest fraction. We use sensitivity analysis to find the parameters which have the most impact on simulator output and perform a history-matching exercise using credible estimates for simulator discrepancy and observational uncertainty terms. We are unable to constrain the parameters individually, but we rule out just under half of joint parameter space as being incompatible with forest observations. We discuss the possible sources of the discrepancy in the simulated Amazon, including missing processes in the land surface component and a bias in the climatology of the Amazon.

  18. Web-based Data Visualization of the MGClimDeX Climate Model Output: An Integrated Perspective of Climate Change Impact on Natural Resources in Highly Vulnerable Regions.

    Science.gov (United States)

    Martinez-Rey, J.; Brockmann, P.; Cadule, P.; Nangini, C.

    2016-12-01

    Earth System Models allow us to understand the interactions between climate and biogeological processes. These models generate a very large amount of data. These data are usually reduced to a few number of static figures shown in highly specialized scientific publications. However, the potential impacts of climate change demand a broader perspective regarding the ways in which climate model results of this kind are disseminated, particularly in the amount and variety of data, and the target audience. This issue is of great importance particularly for scientific projects that seek a large broadcast with different audiences on their key results. The MGClimDeX project, which assesses the climate change impact on La Martinique island in the Lesser Antilles, will provide tools and means to help the key stakeholders -responsible for addressing the critical social, economic, and environmental issues- to take the appropriate adaptation and mitigation measures in order to prevent future risks associated with climate variability and change, and its role on human activities. The MGClimDeX project will do so by using model output and data visualization techniques within the next year, showing the cross-connected impacts of climate change on various sectors (agriculture, forestry, ecosystems, water resources and fisheries). To address this challenge of representing large sets of data from model output, we use back-end data processing and front-end web-based visualization techniques, going from the conventional netCDF model output stored on hub servers to highly interactive web-based data-powered visualizations on browsers. We use the well-known javascript library D3.js extended with DC.js -a dimensional charting library for all the front-end interactive filtering-, in combination with Bokeh, a Python library to synthesize the data, all framed in the essential HTML+CSS scripts. The resulting websites exist as standalone information units or embedded into journals or scientific

  19. Integration of climatic indices in an objective probabilistic model for establishing and mapping viticultural climatic zones in a region

    Science.gov (United States)

    Moral, Francisco J.; Rebollo, Francisco J.; Paniagua, Luis L.; García, Abelardo; Honorio, Fulgencio

    2016-05-01

    Different climatic indices have been proposed to determine the wine suitability in a region. Some of them are related to the air temperature, but the hydric component of climate should also be considered which, in turn, is influenced by the precipitation during the different stages of the grapevine growing and ripening periods. In this study, we propose using the information obtained from ten climatic indices [heliothermal index (HI), cool night index (CI), dryness index (DI), growing season temperature (GST), the Winkler index (WI), September mean thermal amplitude (MTA), annual precipitation (AP), precipitation during flowering (PDF), precipitation before flowering (PBF), and summer precipitation (SP)] as inputs in an objective and probabilistic model, the Rasch model, with the aim of integrating the individual effects of them, obtaining the climate data that summarize all main climatic indices, which could influence on wine suitability from a climate viewpoint, and utilizing the Rasch measures to generate homogeneous climatic zones. The use of the Rasch model to estimate viticultural climatic suitability constitutes a new application of great practical importance, enabling to rationally determine locations in a region where high viticultural potential exists and establishing a ranking of the climatic indices which exerts an important influence on wine suitability in a region. Furthermore, from the measures of viticultural climatic suitability at some locations, estimates can be computed using a geostatistical algorithm, and these estimates can be utilized to map viticultural climatic zones in a region. To illustrate the process, an application to Extremadura, southwestern Spain, is shown.

  20. Tropical convection regimes in climate models: evaluation with satellite observations

    Directory of Open Access Journals (Sweden)

    A. K. Steiner

    2018-04-01

    Full Text Available High-quality observations are powerful tools for the evaluation of climate models towards improvement and reduction of uncertainty. Particularly at low latitudes, the most uncertain aspect lies in the representation of moist convection and interaction with dynamics, where rising motion is tied to deep convection and sinking motion to dry regimes. Since humidity is closely coupled with temperature feedbacks in the tropical troposphere, a proper representation of this region is essential. Here we demonstrate the evaluation of atmospheric climate models with satellite-based observations from Global Positioning System (GPS radio occultation (RO, which feature high vertical resolution and accuracy in the troposphere to lower stratosphere. We focus on the representation of the vertical atmospheric structure in tropical convection regimes, defined by high updraft velocity over warm surfaces, and investigate atmospheric temperature and humidity profiles. Results reveal that some models do not fully capture convection regions, particularly over land, and only partly represent strong vertical wind classes. Models show large biases in tropical mean temperature of more than 4 K in the tropopause region and the lower stratosphere. Reasonable agreement with observations is given in mean specific humidity in the lower to mid-troposphere. In moist convection regions, models tend to underestimate moisture by 10 to 40 % over oceans, whereas in dry downdraft regions they overestimate moisture by 100 %. Our findings provide evidence that RO observations are a unique source of information, with a range of further atmospheric variables to be exploited, for the evaluation and advancement of next-generation climate models.

  1. Tropical convection regimes in climate models: evaluation with satellite observations

    Science.gov (United States)

    Steiner, Andrea K.; Lackner, Bettina C.; Ringer, Mark A.

    2018-04-01

    High-quality observations are powerful tools for the evaluation of climate models towards improvement and reduction of uncertainty. Particularly at low latitudes, the most uncertain aspect lies in the representation of moist convection and interaction with dynamics, where rising motion is tied to deep convection and sinking motion to dry regimes. Since humidity is closely coupled with temperature feedbacks in the tropical troposphere, a proper representation of this region is essential. Here we demonstrate the evaluation of atmospheric climate models with satellite-based observations from Global Positioning System (GPS) radio occultation (RO), which feature high vertical resolution and accuracy in the troposphere to lower stratosphere. We focus on the representation of the vertical atmospheric structure in tropical convection regimes, defined by high updraft velocity over warm surfaces, and investigate atmospheric temperature and humidity profiles. Results reveal that some models do not fully capture convection regions, particularly over land, and only partly represent strong vertical wind classes. Models show large biases in tropical mean temperature of more than 4 K in the tropopause region and the lower stratosphere. Reasonable agreement with observations is given in mean specific humidity in the lower to mid-troposphere. In moist convection regions, models tend to underestimate moisture by 10 to 40 % over oceans, whereas in dry downdraft regions they overestimate moisture by 100 %. Our findings provide evidence that RO observations are a unique source of information, with a range of further atmospheric variables to be exploited, for the evaluation and advancement of next-generation climate models.

  2. Using Models to Teach about Climate Change: A look at NGSS Expectations and Teacher Perceptions

    Science.gov (United States)

    Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

    2013-12-01

    The Next Generation Science Standards have been updated from the previous version of the standards with some much needed emphasis on topics in climate and climate change. In particular, the standards have focused on K-12 students learning about science models, which is extremely important when discussing climate change. The NGSS suggest that students be able to 1) develop and use science models (not just use them to explain a concept) because this is how scientists actually use models during the scientific process; and 2) understand systems and system models across all science concepts and all age levels because it leads to further understanding about a more complex natural system (like climate change). To summarize, the NGSS expects that K-12 students should develop and use system models across disciplines and age groups in a way that is similar to how scientists use them in practice, which is to make predictions about unanswered questions. Research indicates that students who learn about science content using an approach that aligns more authentically with the way real science inquiry is done have a better understanding of the content, better understanding of the nature of science, improved critical thinking skills, and improved problem solving skills. Research also indicates that most teachers are aware of this method to teach science content, but sometimes have trouble implementing it into the classroom effectively for many reasons. If accepted, this presentation will share an approach to incorporate modeling into the classroom effectively as well as report the results from a study that qualitatively look at three teacher's perspectives on using models in the classroom while teaching units about climate change, in order to identify how/why teachers struggle to teach about models involved in content related to climate change. Preliminary results indicate that the teachers in this study view models as an effective way to explain a concept to their students, but

  3. Modelling the regional effects of climate change on air quality

    International Nuclear Information System (INIS)

    Giorgi, F.; Meleux, F.

    2007-01-01

    The life cycle of pollutants is affected by chemical as well as meteorological factors, such as wind, temperature, precipitation, solar radiation. Therefore, climatic changes induced by anthropogenic emissions of greenhouse gases may be expected to have significant effects on air quality. Because of the spatial variability of the pollutant emissions and climate-change signals, these effects are particularly relevant at the regional to local scales. This paper first briefly reviews modelling tools and methodologies used to study regional climate-change impacts on air quality. Patterns of regional precipitation, temperature, and sea-level changes emerging from the latest set of general circulation model projections are then discussed. Finally, the specific case of climate-change effects on summer ozone concentrations over Europe is presented to illustrate the potential impacts of climate change on pollutant amounts. It is concluded that climate change is an important factor that needs to be taken into account when designing future pollution-reduction policies. (authors)

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

    Science.gov (United States)

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

    2016-01-01

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

  5. Toward a consistent modeling framework to assess multi-sectoral climate impacts.

    Science.gov (United States)

    Monier, Erwan; Paltsev, Sergey; Sokolov, Andrei; Chen, Y-H Henry; Gao, Xiang; Ejaz, Qudsia; Couzo, Evan; Schlosser, C Adam; Dutkiewicz, Stephanie; Fant, Charles; Scott, Jeffery; Kicklighter, David; Morris, Jennifer; Jacoby, Henry; Prinn, Ronald; Haigh, Martin

    2018-02-13

    Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.

  6. Controlled comparison of species- and community-level models across novel climates and communities

    Science.gov (United States)

    Maguire, Kaitlin C.; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.; Ferrier, Simon; Lorenz, David J.

    2016-01-01

    Species distribution models (SDMs) assume species exist in isolation and do not influence one another's distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa. PMID:26962143

  7. 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

  8. Cpl6: The New Extensible, High-Performance Parallel Coupler forthe Community Climate System Model

    Energy Technology Data Exchange (ETDEWEB)

    Craig, Anthony P.; Jacob, Robert L.; Kauffman, Brain; Bettge,Tom; Larson, Jay; Ong, Everest; Ding, Chris; He, Yun

    2005-03-24

    Coupled climate models are large, multiphysics applications designed to simulate the Earth's climate and predict the response of the climate to any changes in the forcing or boundary conditions. The Community Climate System Model (CCSM) is a widely used state-of-art climate model that has released several versions to the climate community over the past ten years. Like many climate models, CCSM employs a coupler, a functional unit that coordinates the exchange of data between parts of climate system such as the atmosphere and ocean. This paper describes the new coupler, cpl6, contained in the latest version of CCSM,CCSM3. Cpl6 introduces distributed-memory parallelism to the coupler, a class library for important coupler functions, and a standardized interface for component models. Cpl6 is implemented entirely in Fortran90 and uses Model Coupling Toolkit as the base for most of its classes. Cpl6 gives improved performance over previous versions and scales well on multiple platforms.

  9. Modelling the effects of climate change on streamflow in a sub-basin of the lower Churchill River

    International Nuclear Information System (INIS)

    Pryse-Phillips, Amy; Snelgrove, Ken

    2010-01-01

    Climate change is likely to affect extreme flows as well as average flows. This is an important consideration for hydroelectric power producers. This paper presented the development of an approach to assess the impact of climate changes on seasonal and average annual river flows. The main goal was to investigate how climate change will affect the hydroelectric potential of the Lower Churchill Project using different combinations of emissions scenarios, climate model output and downscaling techniques. The setup and calibration of the numerical hydrological model, WATFLOOD, were performed as preliminary work for the Pinus River basin selected as study basin. Downscaled climate data from the North America change assessment program for both current and future climate periods were analysed. The calibrated model was used to simulate the current and future period streamflow scenarios. The results showed a 13 percent increase in mean annual flows concentrated in the winter and spring seasons.

  10. Modelling the effects of climate change on streamflow in a sub-basin of the lower Churchill River

    Energy Technology Data Exchange (ETDEWEB)

    Pryse-Phillips, Amy [Hatch Ltd., St John' s, (Canada); Snelgrove, Ken [Memorial University of Newfoundland, St John' s, (Canada)

    2010-07-01

    Climate change is likely to affect extreme flows as well as average flows. This is an important consideration for hydroelectric power producers. This paper presented the development of an approach to assess the impact of climate changes on seasonal and average annual river flows. The main goal was to investigate how climate change will affect the hydroelectric potential of the Lower Churchill Project using different combinations of emissions scenarios, climate model output and downscaling techniques. The setup and calibration of the numerical hydrological model, WATFLOOD, were performed as preliminary work for the Pinus River basin selected as study basin. Downscaled climate data from the North America change assessment program for both current and future climate periods were analysed. The calibrated model was used to simulate the current and future period streamflow scenarios. The results showed a 13 percent increase in mean annual flows concentrated in the winter and spring seasons.

  11. The Bern Simple Climate Model (BernSCM) v1.0: an extensible and fully documented open-source re-implementation of the Bern reduced-form model for global carbon cycle-climate simulations

    Science.gov (United States)

    Strassmann, Kuno M.; Joos, Fortunat

    2018-05-01

    The Bern Simple Climate Model (BernSCM) is a free open-source re-implementation of a reduced-form carbon cycle-climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRFs). The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near-linear behavior. Illustrative simulations of scenarios from previous multimodel studies show that BernSCM is broadly representative of the range of the climate-carbon cycle response simulated by more complex and detailed models. Model code (in Fortran) was written from scratch with transparency and extensibility in mind, and is provided open source. BernSCM makes scientifically sound carbon cycle-climate modeling available for many applications. Supporting up to decadal time steps with high accuracy, it is suitable for studies with high computational load and for coupling with integrated assessment models (IAMs), for example. Further applications include climate risk assessment in a business, public, or educational context and the estimation of CO2 and climate benefits of emission mitigation options.

  12. Amazon collapse in the next century: exploring the sensitivity to climate and model formulation uncertainties

    Science.gov (United States)

    Booth, B.; Collins, M.; Harris, G.; Chris, H.; Jones, C.

    2007-12-01

    A number of recent studies have highlighted the risk of abrupt dieback of the Amazon Rain Forest as the result of climate changes over the next century. The recent 2005 Amazon drought brought wider acceptance of the idea that that climate drivers will play a significant role in future rain forest stability, yet that stability is still subject to considerable degree of uncertainty. We present a study which seeks to explore some of the underlying uncertainties both in the climate drivers of dieback and in the terrestrial land surface formulation used in GCMs. We adopt a perturbed physics approach which forms part of a wider project which is covered in an accompanying abstract submitted to the multi-model ensembles session. We first couple the same interactive land surface model to a number of different versions of the Hadley Centre atmosphere-ocean model that exhibit a wide range of different physical climate responses in the future. The rainforest extent is shown to collapse in all model cases but the timing of the collapse is dependent on the magnitude of the climate drivers. In the second part, we explore uncertainties in the terrestrial land surface model using the perturbed physics ensemble approach, perturbing uncertain parameters which have an important role in the vegetation and soil response. Contrasting the two approaches enables a greater understanding of the relative importance of climatic and land surface model uncertainties in Amazon dieback.

  13. Connecting today's climates to future climate analogs to facilitate movement of species under climate change.

    Science.gov (United States)

    Littlefield, Caitlin E; McRae, Brad H; Michalak, Julia L; Lawler, Joshua J; Carroll, Carlos

    2017-12-01

    Increasing connectivity is an important strategy for facilitating species range shifts and maintaining biodiversity in the face of climate change. To date, however, few researchers have included future climate projections in efforts to prioritize areas for increasing connectivity. We identified key areas likely to facilitate climate-induced species' movement across western North America. Using historical climate data sets and future climate projections, we mapped potential species' movement routes that link current climate conditions to analogous climate conditions in the future (i.e., future climate analogs) with a novel moving-window analysis based on electrical circuit theory. In addition to tracing shifting climates, the approach accounted for landscape permeability and empirically derived species' dispersal capabilities. We compared connectivity maps generated with our climate-change-informed approach with maps of connectivity based solely on the degree of human modification of the landscape. Including future climate projections in connectivity models substantially shifted and constrained priority areas for movement to a smaller proportion of the landscape than when climate projections were not considered. Potential movement, measured as current flow, decreased in all ecoregions when climate projections were included, particularly when dispersal was limited, which made climate analogs inaccessible. Many areas emerged as important for connectivity only when climate change was modeled in 2 time steps rather than in a single time step. Our results illustrate that movement routes needed to track changing climatic conditions may differ from those that connect present-day landscapes. Incorporating future climate projections into connectivity modeling is an important step toward facilitating successful species movement and population persistence in a changing climate. © 2017 Society for Conservation Biology.

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

    International Nuclear Information System (INIS)

    Criqui, Patrick; Mima, Silvana

    2011-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Kellogg, W. M.

    1980-04-04

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

  16. On the importance of paleoclimate modelling for improving predictions of future climate change

    Directory of Open Access Journals (Sweden)

    J. C. Hargreaves

    2009-12-01

    Full Text Available We use an ensemble of runs from the MIROC3.2 AGCM with slab-ocean to explore the extent to which mid-Holocene simulations are relevant to predictions of future climate change. The results are compared with similar analyses for the Last Glacial Maximum (LGM and pre-industrial control climate. We suggest that the paleoclimate epochs can provide some independent validation of the models that is also relevant for future predictions. Considering the paleoclimate epochs, we find that the stronger global forcing and hence larger climate change at the LGM makes this likely to be the more powerful one for estimating the large-scale changes that are anticipated due to anthropogenic forcing. The phenomena in the mid-Holocene simulations which are most strongly correlated with future changes (i.e., the mid to high northern latitude land temperature and monsoon precipitation do, however, coincide with areas where the LGM results are not correlated with future changes, and these are also areas where the paleodata indicate significant climate changes have occurred. Thus, these regions and phenomena for the mid-Holocene may be useful for model improvement and validation.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-09-06

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

  18. 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.

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

    International Nuclear Information System (INIS)

    Moberg, Anders; Gouirand, Isabelle; Schoning, Kristian; Wohlfarth, Barbara

    2006-12-01

    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

  20. Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada

    Science.gov (United States)

    Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

    2014-07-01

    Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

  1. Eocene climate and Arctic paleobathymetry: A tectonic sensitivity study using GISS ModelE-R

    Science.gov (United States)

    Roberts, C. D.; Legrande, A. N.; Tripati, A. K.

    2009-12-01

    The early Paleogene (65-45 million years ago, Ma) was a ‘greenhouse’ interval with global temperatures warmer than any other time in the last 65 Ma. This period was characterized by high levels of CO2, warm high-latitudes, warm surface-and-deep oceans, and an intensified hydrological cycle. Sediments from the Arctic suggest that the Eocene surface Arctic Ocean was warm, brackish, and episodically enabled the freshwater fern Azolla to bloom. The precise mechanisms responsible for the development of these conditions remain uncertain. We present equilibrium climate conditions derived from a fully-coupled, water-isotope enabled, general circulation model (GISS ModelE-R) configured for the early Eocene. We also present model-data comparison plots for key climatic variables (SST and δ18O) and analyses of the leading modes of variability in the tropical Pacific and North Atlantic regions. Our tectonic sensitivity study indicates that Northern Hemisphere climate would have been very sensitive to the degree of oceanic exchange through the seaways connecting the Arctic to the Atlantic and Tethys. By restricting these seaways, we simulate freshening of the surface Arctic Ocean to ~6 psu and warming of sea-surface temperatures by 2°C in the North Atlantic and 5-10°C in the Labrador Sea. Our results may help explain the occurrence of low-salinity tolerant taxa in the Arctic Ocean during the Eocene and provide a mechanism for enhanced warmth in the north western Atlantic. We also suggest that the formation of a volcanic land-bridge between Greenland and Europe could have caused increased ocean convection and warming of intermediate waters in the Atlantic. If true, this result is consistent with the theory that bathymetry changes may have caused thermal destabilisation of methane clathrates in the Atlantic.

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

    International Nuclear Information System (INIS)

    Omstedt, Anders; Leppaeranta, Matti

    1999-01-01

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

  3. Agent Model Development for Assessing Climate-Induced Geopolitical Instability.

    Energy Technology Data Exchange (ETDEWEB)

    Boslough, Mark B.; Backus, George A.

    2005-12-01

    We present the initial stages of development of new agent-based computational methods to generate and test hypotheses about linkages between environmental change and international instability. This report summarizes the first year's effort of an originally proposed three-year Laboratory Directed Research and Development (LDRD) project. The preliminary work focused on a set of simple agent-based models and benefited from lessons learned in previous related projects and case studies of human response to climate change and environmental scarcity. Our approach was to define a qualitative model using extremely simple cellular agent models akin to Lovelock's Daisyworld and Schelling's segregation model. Such models do not require significant computing resources, and users can modify behavior rules to gain insights. One of the difficulties in agent-based modeling is finding the right balance between model simplicity and real-world representation. Our approach was to keep agent behaviors as simple as possible during the development stage (described herein) and to ground them with a realistic geospatial Earth system model in subsequent years. This work is directed toward incorporating projected climate data--including various C02 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report--and ultimately toward coupling a useful agent-based model to a general circulation model.3

  4. A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

    Science.gov (United States)

    Pan, Yang; Archer, Cristina L.

    2018-04-01

    To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

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

    CERN Multimedia

    2002-01-01

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

  6. 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.

  7. Modelling of oceanic gas hydrate instability and methane release in response to climate change

    International Nuclear Information System (INIS)

    Reagan, M.T.; Moridis, G.J.

    2008-01-01

    Methane releases from oceanic hydrates are thought to have played a significant role in climatic changes that have occurred in the past. In this study, gas hydrate accumulations subjected to temperature changes were modelled in order to assess their potential for future methane releases into the ocean. Recent ocean and atmospheric chemistry studies were used to model 2 climate scenarios. Two types of hydrate accumulations were used to represent dispersed, low-saturation deposits. The 1-D multiphase thermodynamic-hydrological model considered the properties of benthic sediments; ocean depth; sea floor temperature; the saturation and distribution of the hydrates; and the effect of benthic biogeochemical activity. Results of the simulations showed that shallow deposits undergo rapid dissociation and are capable of producing methane fluxes of 2 to 13 mol m 3 per year over a period of decades. The fluxes exceed the ability of the anaerobic sea floor environment to sequester or consume the methane. A large proportion of the methane released in the scenarios emerged in the gas phase. Arctic hydrates may pose a threat to regional and global ecological systems. It was concluded that results of the study will be coupled with global climate models in order to assess the impact of the methane releases in relation to global climatic change. 39 refs., 5 figs

  8. Evaluation of Aerosol Mixing State Classes in the GISS Modele-matrix Climate Model Using Single-particle Mass Spectrometry Measurements

    Science.gov (United States)

    Bauer, Susanne E.; Ault, Andrew; Prather, Kimberly A.

    2013-01-01

    Aerosol particles in the atmosphere are composed of multiple chemical species. The aerosol mixing state, which describes how chemical species are mixed at the single-particle level, provides critical information on microphysical characteristics that determine the interaction of aerosols with the climate system. The evaluation of mixing state has become the next challenge. This study uses aerosol time-of-flight mass spectrometry (ATOFMS) data and compares the results to those of the Goddard Institute for Space Studies modelE-MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) model, a global climate model that includes a detailed aerosol microphysical scheme. We use data from field campaigns that examine a variety of air mass regimens (urban, rural, and maritime). At all locations, polluted areas in California (Riverside, La Jolla, and Long Beach), a remote location in the Sierra Nevada Mountains (Sugar Pine) and observations from Jeju (South Korea), the majority of aerosol species are internally mixed. Coarse aerosol particles, those above 1 micron, are typically aged, such as coated dust or reacted sea-salt particles. Particles below 1 micron contain large fractions of organic material, internally-mixed with sulfate and black carbon, and few external mixtures. We conclude that observations taken over multiple weeks characterize typical air mass types at a given location well; however, due to the instrumentation, we could not evaluate mass budgets. These results represent the first detailed comparison of single-particle mixing states in a global climate model with real-time single-particle mass spectrometry data, an important step in improving the representation of mixing state in global climate models.

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

    Directory of Open Access Journals (Sweden)

    Shilpa M. Asokan

    2016-03-01

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

  10. Software Testing and Verification in Climate Model Development

    Science.gov (United States)

    Clune, Thomas L.; Rood, RIchard B.

    2011-01-01

    Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

  11. Do downscaled general circulation models reliably simulate historical climatic conditions?

    Science.gov (United States)

    Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

    2018-01-01

    The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

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

    Science.gov (United States)

    Beauregard, Frieda; de Blois, Sylvie

    2014-01-01

    Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential

  13. Climate Sensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Lindzen, Richard [M.I.T.

    2011-11-09

    Warming observed thus far is entirely consistent with low climate sensitivity. However, the result is ambiguous because the sources of climate change are numerous and poorly specified. Model predictions of substantial warming aredependent on positive feedbacks associated with upper level water vapor and clouds, but models are notably inadequate in dealing with clouds and the impacts of clouds and water vapor are intimately intertwined. Various approaches to measuring sensitivity based on the physics of the feedbacks will be described. The results thus far point to negative feedbacks. Problems with these approaches as well as problems with the concept of climate sensitivity will be described.

  14. Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change

    Science.gov (United States)

    1998-01-01

    This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the GISS 8 deg x lO deg atmospheric GCM to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2.

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

    International Nuclear Information System (INIS)

    Delina, Laurence L.; Diesendorf, Mark

    2013-01-01

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

  16. Tropical climate and vegetation changes during Heinrich Event 1: a model-data comparison

    Directory of Open Access Journals (Sweden)

    D. Handiani

    2012-01-01

    Full Text Available Abrupt climate changes from 18 to 15 thousand years before present (kyr BP associated with Heinrich Event 1 (HE1 had a strong impact on vegetation patterns not only at high latitudes of the Northern Hemisphere, but also in the tropical regions around the Atlantic Ocean. To gain a better understanding of the linkage between high and low latitudes, we used the University of Victoria (UVic Earth System-Climate Model (ESCM with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era, the Last Glacial Maximum (LGM, and a Heinrich-like event with two different climate backgrounds (interglacial and glacial. We calculated mega-biomes from the plant-functional types (PFTs generated by the model to allow for a direct comparison between model results and palynological vegetation reconstructions.

    Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well with biome reconstructions of the modern and LGM time slices, respectively, except that our pre-industrial simulation predicted the dominance of grassland in southern Europe and our LGM simulation resulted in more forest cover in tropical and sub-tropical South America.

    The HE1-like simulation with a glacial climate background produced sea-surface temperature patterns and enhanced inter-hemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. We found that the cooling of the Northern Hemisphere caused a southward shift of those PFTs that are indicative of an increased desertification and a retreat of broadleaf forests in West Africa and northern South America. The mega-biomes from our HE1 simulation agreed well with paleovegetation data from tropical Africa and northern South America. Thus, according to our model-data comparison, the reconstructed vegetation changes for the tropical regions around the Atlantic Ocean were physically consistent with the remote

  17. Hydro-climatic conditions and thermoelectric electricity generation – Part I: Development of models

    International Nuclear Information System (INIS)

    Koch, Hagen; Vögele, Stefan

    2013-01-01

    In recent years there have been several heat waves affecting the use of thermoelectric power plants, e.g. in Europe and the U.S. In this paper the linkage between hydro-climatic conditions and possible electricity generation restrictions is described. The coupling of hydrological models and a power plant model is presented. In this approach each power plant is considered separately with its technical specifications. Also environmental regulations, e.g. permissible rise in the cooling water temperature, are considered for the respective power plant. The hydrological models developed to simulate river runoff and water temperature are also site specific. The approach presented is applied to Krümmel nuclear power plant in Germany. Analysed are the uncertainties with regard to electricity generation restrictions on account of climatic developments and corresponding higher water temperatures and low flows. Overall, increased water temperatures and declining river runoff lead to more frequent and more severe generation restrictions. It is concluded that the site-specific approach is necessary to reliably simulate power plants water demand, river runoff and water temperature. Using a simulation time step of one day, electricity generation restrictions are significantly higher than for simulations at monthly time step. - Highlights: • An approach to assess climate effects on electricity generation is presented. • Site specific models for power plants, water temperature and discharge are used. • Monthly and daily simulation time-steps give different results. • Climate change effects on generation depend on cooling system and climate scenario

  18. Basis of a formal language for facilitating communication among climate modelers

    Energy Technology Data Exchange (ETDEWEB)

    Elia, Ramon de [Climate Analysis Team, Consortium Ouranos, Montreal, QC (Canada); Universite du Quebec a Montreal, Centre ESCER, Montreal, QC (Canada)

    2012-08-15

    The objective of this work is to present the basis for a formal language that aims to express in a concise way some fundamental beliefs held within the climate research community. The expression of this set of beliefs takes the form of relations, conjectures or propositions that describe characteristics of different aspects of climate modeling. Examples are constructed using topics that are much discussed within the climate modeling community. The article first introduces, as elements of this formal language, models considered a priori (the model as a code or algorithm) or a posteriori (the model as output), and then presents different relations between these elements. The most important relation is that of dominance, which helps to define the superiority of one model over another based on which model a rational agent will choose. Various kinds of dominance are considered. Also presented in a formal language are propositions and conjectures relating to model development, model calibration and climate change ensemble projections, each of which are held with diverse levels of acceptance within the climate modeling community. In addition, the relevance of defining elements - models - whose existence is improbable, such as bug-free model versions, is discussed. Although the potential value of this language is shown, there remains a need to improve the definitions presented here, as some of them remain unsatisfying. Still, we believe that this attempt may help us not only communicate more clearly but also to better distinguish different schools of thought that currently exist within the community. (orig.)

  19. Parameterization of a bucket model for soil-vegetation-atmosphere modeling under seasonal climatic regimes

    Directory of Open Access Journals (Sweden)

    N. Romano

    2011-12-01

    Full Text Available We investigate the potential impact of accounting for seasonal variations in the climatic forcing and using different methods to parameterize the soil water content at field capacity on the water balance components computed by a bucket model (BM. The single-layer BM of Guswa et al. (2002 is employed, whereas the Richards equation (RE based Soil Water Atmosphere Plant (SWAP model is used as a benchmark model. The results are analyzed for two differently-textured soils and for some synthetic runs under real-like seasonal weather conditions, using stochastically-generated daily rainfall data for a period of 100 years. Since transient soil-moisture dynamics and climatic seasonality play a key role in certain zones of the World, such as in Mediterranean land areas, a specific feature of this study is to test the prediction capability of the bucket model under a condition where seasonal variations in rainfall are not in phase with the variations in plant transpiration. Reference is made to a hydrologic year in which we have a rainy period (starting 1 November and lasting 151 days where vegetation is basically assumed in a dormant stage, followed by a drier and rainless period with a vegetation regrowth phase. Better agreement between BM and RE-SWAP intercomparison results are obtained when BM is parameterized by a field capacity value determined through the drainage method proposed by Romano and Santini (2002. Depending on the vegetation regrowth or dormant seasons, rainfall variability within a season results in transpiration regimes and soil moisture fluctuations with distinctive features. During the vegetation regrowth season, transpiration exerts a key control on soil water budget with respect to rainfall. During the dormant season of vegetation, the precipitation regime becomes an important climate forcing. Simulations also highlight the occurrence of bimodality in the probability distribution of soil moisture during the season when plants are

  20. 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