WorldWideScience

Sample records for climate system model

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

    Institute of Scientific and Technical Information of China (English)

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

    2007-01-01

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

  2. Climate system model, numerical simulation and climate predictability

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

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

  3. 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

  4. The Community Climate System Model: CCSM3

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-12-27

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

  5. The Community Climate System Model, Version 2.

    Science.gov (United States)

    Kiehl, Jeffrey T.; Gent, Peter R.

    2004-10-01

    The Community Climate System Model, version 2 (CCSM2) is briefly described. A 1000-yr control simulation of the present day climate has been completed without flux adjustments. Minor modifications were made at year 350, which included all five components using the same physical constants. There are very small trends in the upper-ocean, sea ice, atmosphere, and land fields after year 150 of the control simulation. The deep ocean has small but significant trends; however, these are not large enough that the control simulation could not be continued much further. The equilibrium climate sensitivity of CCSM2 is 2.2 K, which is slightly larger than the Climate System Model, version 1 (CSM1) value of 2.0 K.Several aspects of the control simulation's mean climate and interannual variability are described, and good and bad properties of the control simulation are documented. In particular, several aspects of the simulation, especially in the Arctic region, are much improved over those obtained in CSM1. Other aspects, such as the tropical Pacific region simulation, have not been improved much compared to those in CSM1. Priorities for further model development are discussed in the conclusions section.HR ALIGN="center" WIDTH="30%">

  6. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

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

    2013-12-01

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

  7. A Regional Climate Model Evaluation System Project

    Data.gov (United States)

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

  8. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

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

    2014-12-01

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

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

    International Nuclear Information System (INIS)

    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 (C4MIP) 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

  10. Modeling Coupled Climate, Ecosystems, and Economic Systems

    OpenAIRE

    Brock, W.A.; Xepapadeas, A.

    2015-01-01

    Human economies and ecosystems form a coupled system coevolving in time and space, since human economies use ecosystems services and at the same time affect ecosystems through their production and consumption activities. The study of the interactions between human economies and ecosystems is fundamental for the efficient use of natural resources and the protection of the environment. This necessitates the development and use of models capa- ble of tracing the main interactions, links and feed...

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

    Institute of Scientific and Technical Information of China (English)

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

    2014-01-01

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

  12. Integrating Climate Model Data into Power System Planning

    OpenAIRE

    Chattopadhyay, Debabrata; Rhonda L. Jordan

    2015-01-01

    Significant multiyear and multi decade variations in intermittent renewable resources hold major implications for power system investments. They have been using extensive hydrology data for many years to represent hydrological risks in their planning. Climate model data are particularly suited for the assessment of longer-term variability. A good grasp of seasonal, multiyear, and multi dec...

  13. Big Data and Data Models for Climate System Energetics

    Science.gov (United States)

    Fillmore, D. W.; Habermann, T.; Goedecke, W. B.

    2015-12-01

    Multi-decade satellite missions, such as the NASA CERES mission designed to place observational constraints on the distribution of reflected solar radiation and emitted thermal radiation, present a significant challenge both in the analysis of heterogeneous Big Data and in data continuity. The NASA CERES EBAF dataset is a part of a broader effort to increase the usability of satellite observational data for the climate modeling community. Issues of accessibility, consistency, and reproducibility are paramount. Here we describe the transformation of CERES measurements from source to high level data products intended for direct use by the climate community. At each stage we examine data storage and processing patterns, metadata and potential challenges in reproducibility. The spatial distribution of net energy uptake and transport in the climate system, and its evolution over interannual and decadal time scales, is fundamental to the development of Earth system models. The workflow begins with the CERES footprint radiance seen by a polar orbiter, to the conversion of radiance to radiometric fluxes based on scene identification from MODIS and VIIRS imagery, followed by diurnal interpolation through the use of geostationary satellite imagery and eventually to the creation of high level gridded data products, the ultimate being the Energy Balanced and Filled flux product for direct comparison to climate models. Based on this CERES case study we try to anticipate future questions the may arise in the context of these massive satellite data collections, and what new data models may facilitate future data analysis.

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

    Directory of Open Access Journals (Sweden)

    K. A. Stone

    2015-07-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-02-01

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

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

    DEFF Research Database (Denmark)

    Butts, M.; Rasmussen, S.H.; Ridler, M.; Larsen, Morten Andreas Dahl; Drews, Martin; Lerer, Sara Maria; Overgaard, J.; Grooss, J.; Rosbjerg, Dan; Christensen, J.H.; Refsgaard, J. C.

    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....

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    , the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little......Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and...... continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20...

  18. 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.

  19. Study on the climate system and mass transport by a climate model

    International Nuclear Information System (INIS)

    The Center for Global Environmental Research (CGER), an organ of the National Institute for Environmental Studies of the Environment Agency of Japan, was established in October 1990 to contribute broadly to the scientific understanding of global change, and to the elucidation of and solution for our pressing environmental problems. CGER conducts environmental research from interdisciplinary, multiagency, and international perspective, provides research support facilities such as a supercomputer and databases, and offers its own data from long-term monitoring of the global environment. In March 1992, CGER installed a supercomputer system (NEC SX-3, Model 14) to facilitate research on global change. The system is open to environmental researchers worldwide. Proposed research programs are evaluated by the Supercomputer Steering Committee which consists of leading scientists in climate modeling, atmospheric chemistry, oceanic circulation, and computer science. After project approval, authorization for system usage is provided. In 1995 and 1996, several research proposals were designated as priority research and allocated larger shares of computer resources. The CGER supercomputer monograph report Vol. 3 is a report of priority research of CGER's supercomputer. The report covers the description of CCSR-NIES atmospheric general circulation model, lagragian general circulation based on the time-scale of particle motion, and ability of the CCSR-NIES atmospheric general circulation model in the stratosphere. The results obtained from these three studies are described in three chapters. We hope this report provides you with useful information on the global environmental research conducted on our supercomputer

  20. Integrated models of livestock systems for climate change studies. 1. Grazing systems.

    OpenAIRE

    Parsons, David J.; Armstrong, A. C.; Turnpenny, J. R.; Matthews, A M; Cooper, K. C.; Clark, J. A.

    2001-01-01

    The potential impact of climate change by the year 2050 on British grazing livestock systems is assessed through the use of simulation models of farming systems. The submodels, consisting of grass production, livestock feeding, livestock thermal balance, the thermal balance of naturally ventilated buildings and a stochastic weather generator, are described. These are integrated to form system models for sheep, beef calves and dairy cows. They are applied to scenarios represe...

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

    Directory of Open Access Journals (Sweden)

    M. Eby

    2013-05-01

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

  2. Computer Model for Automobile Climate Control System Simulation and Application

    Directory of Open Access Journals (Sweden)

    Emin Oker

    1999-06-01

    Full Text Available A software to simulate the dynamic operation of climate control system for a generic automobile has been developed. The transient nature of passenger cabin temperature and relative humidity are predicted using the principles of thermodynamics. Analysis include detailed simulations of every component of the automobile air conditioning network. The methodology is validated by comparing the simulation results with the experimental results.

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

    International Nuclear Information System (INIS)

    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.

  4. 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.

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

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

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

  6. Modelling the effects of climate change on the energy system-A case study of Norway

    International Nuclear Information System (INIS)

    The overall objective of this work is to identify the effects of climate change on the Norwegian energy system towards 2050. Changes in the future wind- and hydro-power resource potential, and changes in the heating and cooling demand are analysed to map the effects of climate change. The impact of climate change is evaluated with an energy system model, the MARKAL Norway model, to analyse the future cost optimal energy system. Ten climate experiments, based on five different global models and six emission scenarios, are used to cover the range of possible future climate scenarios and of these three experiments are used for detailed analyses. This study indicate that in Norway, climate change will reduce the heating demand, increase the cooling demand, have a limited impact on the wind power potential, and increase the hydro-power potential. The reduction of heating demand will be significantly higher than the increase of cooling demand, and thus the possible total direct consequence of climate change will be reduced energy system costs and lower electricity production costs. The investments in offshore wind and tidal power will be reduced and electric based vehicles will be profitable earlier. - Highlights: → Climate change will make an impact on the Norwegian energy system towards 2050. → An impact is lower Norwegian electricity production costs and increased electricity export. → Climate change gives earlier profitable investments in electric based vehicles. → Climate change reduces investments in offshore wind and tidal power.

  7. Progress Report 2008: A Scalable and Extensible Earth System Model for Climate Change Science

    Energy Technology Data Exchange (ETDEWEB)

    Drake, John B [ORNL; Worley, Patrick H [ORNL; Hoffman, Forrest M [ORNL; Jones, Phil [Los Alamos National Laboratory (LANL)

    2009-01-01

    This project employs multi-disciplinary teams to accelerate development of the Community Climate System Model (CCSM), based at the National Center for Atmospheric Research (NCAR). A consortium of eight Department of Energy (DOE) National Laboratories collaborate with NCAR and the NASA Global Modeling and Assimilation Office (GMAO). The laboratories are Argonne (ANL), Brookhaven (BNL) Los Alamos (LANL), Lawrence Berkeley (LBNL), Lawrence Livermore (LLNL), Oak Ridge (ORNL), Pacific Northwest (PNNL) and Sandia (SNL). The work plan focuses on scalablity for petascale computation and extensibility to a more comprehensive earth system model. Our stated goal is to support the DOE mission in climate change research by helping ... To determine the range of possible climate changes over the 21st century and beyond through simulations using a more accurate climate system model that includes the full range of human and natural climate feedbacks with increased realism and spatial resolution.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-06-30

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

  9. Evaluating synoptic systems in the CMIP5 climate models over the Australian region

    Science.gov (United States)

    Gibson, Peter B.; Uotila, Petteri; Perkins-Kirkpatrick, Sarah E.; Alexander, Lisa V.; Pitman, Andrew J.

    2016-01-01

    Climate models are our principal tool for generating the projections used to inform climate change policy. Our confidence in projections depends, in part, on how realistically they simulate present day climate and associated variability over a range of time scales. Traditionally, climate models are less commonly assessed at time scales relevant to daily weather systems. Here we explore the utility of a self-organizing maps (SOMs) procedure for evaluating the frequency, persistence and transitions of daily synoptic systems in the Australian region simulated by state-of-the-art global climate models. In terms of skill in simulating the climatological frequency of synoptic systems, large spread was observed between models. A positive association between all metrics was found, implying that relative skill in simulating the persistence and transitions of systems is related to skill in simulating the climatological frequency. Considering all models and metrics collectively, model performance was found to be related to model horizontal resolution but unrelated to vertical resolution or representation of the stratosphere. In terms of the SOM procedure, the timespan over which evaluation was performed had some influence on model performance skill measures, as did the number of circulation types examined. These findings have implications for selecting models most useful for future projections over the Australian region, particularly for projections related to synoptic scale processes and phenomena. More broadly, this study has demonstrated the utility of the SOMs procedure in providing a process-based evaluation of climate models.

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

    NARCIS (Netherlands)

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

    1994-01-01

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

  11. 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.

  12. 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.

  13. Modelling Interglacial Climate

    DEFF Research Database (Denmark)

    Pedersen, Rasmus Anker

    Past warm climate states could potentially provide information on future global warming. The past warming was driven by changed insolation rather than an increased greenhouse effect, and thus the warm climate states are expected to be different. Nonetheless, the response of the climate system...... involves some of the same mechanisms in the two climate states. This thesis aims to investigate these mechanisms through climate model experiments. This two-part study has a special focus on the Arctic region, and the main paleoclimate experiments are supplemented by idealized experiments detailing the...... impact of a changing sea ice cover. The first part focusses on the last interglacial climate (125,000 years before present) which was characterized by substantial warming at high northern latitudes due to an increased insolation during summer. The simulations reveal that the oceanic changes dominate the...

  14. 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...

  15. A multi-resolution method for climate system modeling: application of Spherical Centroidal A multi-resolution method for climate system modeling: Application of Spherical Centroidal Voroni Tessellations

    Energy Technology Data Exchange (ETDEWEB)

    Ringler, Todd D [Los Alamos National Laboratory; Gunzburger, Max [FLORIDA STATE UNIV; Ju, Lili [UNIV OF SOUTH CAROLINA

    2008-01-01

    During the next decade and beyond, climate system models will be challenged to resolve scales and processes that are far beyond their current scope. Each climate system component has its prototypical example of an unresolved process that may strongly influence the global climate system, ranging from eddy activity within ocean models, to ice streams within ice sheet models, to surface hydrological processes within land system models, to cloud processes within atmosphere models. These new demands will almost certainly result in the develop of multi-resolution schemes that are able, at least regional to faithfully simulate these fine-scale processes. Spherical Centroidal Voronoi Tessellations (SCVTs) offer one potential path toward the development of robust, multi-resolution climate system component models, SCVTs allow for the generation of high quality Voronoi diagrams and Delaunay triangulations through the use of an intuitive, user-defined density function, each of the examples provided, this method results in high-quality meshes where the quality measures are guaranteed to improve as the number of nodes is increased. Real-world examples are developed for the Greenland ice sheet and the North Atlantic ocean. Idealized examples are developed for ocean-ice shelf interaction and for regional atmospheric modeling. In addition to defining, developing and exhibiting SCVTs, we pair this mesh generation technique with a previously developed finite-volume method. Our numerical example is based on the nonlinear shallow-water equations spanning the entire surface of the sphere. This example is used to elucidate both the potential benefits of this multi-resolution method and the challenges ahead.

  16. An Intermediate Complexity Climate Model (ICCM based on the GFDL Flexible Modelling System

    Directory of Open Access Journals (Sweden)

    G. K. Vallis

    2009-04-01

    Full Text Available An intermediate complexity coupled ocean-atmosphere-land-ice model, based on the Geophysical Fluid Dynamics Laboratory (GFDL Flexible Modelling System (FMS, has been developed to study mechanisms of ocean-atmosphere interactions and natural climate variability at interannual to interdecadal and longer time scales. The model uses the three-dimensional primitive equations for both ocean and atmosphere, but is simplified from a "state of the art" coupled model in two respects: it uses simplified physics and parameterisation schemes, especially in the atmosphere, and idealised geometry and geography. These simplifications provide considerable savings in computational expense and, perhaps more importantly, allow mechanisms to be investigated more cleanly and thoroughly than with a more elaborate model. For example, the model allows integrations of several millennia as well as broad parameter studies. For the ocean, the model uses the free surface primitive equations Modular Ocean Model (MOM and the GFDL/FMS sea-ice model (SIS is coupled to the oceanic grid. The atmospheric component consists of the FMS B-grid moist primitive equations atmospheric dynamical core with highly simplified physical parameterisations. A simple bucket model is implemented for our idealised land following the GFDL/FMS Land model. Here we describe the model components and present a climatology of coupled simulations achieved with two different geometrical configurations. Throughout the paper, we give a flavour of the potential for this model to be a powerful tool for the climate modelling community by mentioning a wide range of studies that are currently being explored.

  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. Coupled water-energy modelling to assess climate change impacts on the Iberian Power System

    DEFF Research Database (Denmark)

    Pereira Cardenal, Silvio Javier; Madsen, H.; Riegels, N.;

    a temperature index method. The delta change approach was used to generate synthetic precipitation and temperature data based on observations (1961-1990) and three regional climate models (2036-2065, CLM, RACMO and REMO). Because modelling generation on 1000+ hydropower plants is intractable, the capacities......Water resources systems and power systems are strongly linked; water is needed for most power generation technologies, and electricity is required in every stage of water usage. In the Iberian Peninsula, climate change is expected to have a negative impact on the power system: changes in runoff...... the effects of climate change on the current Iberian power system. The Iberian power system is a competitive power market where power price is determined by power supply and demand, and which can be simulated by a market equilibrium model considering the power demand function and the installed capacities...

  19. Regional projections of climate change using an Earth system model of intermediate complexity

    Science.gov (United States)

    Sobie, S. R.; Murdock, T. Q.

    2011-12-01

    Earth system models of intermediate complexity have been generally employed in experiments studying global temperature changes, carbon-cycle responses and millennial-scale climate variability. Their reduced computational demands mean many different greenhouse gas emissions scenarios can be examined, including exploring thresholds of dangerous climate change and geo-engineering schemes. In response to requests from users for more information on regional climate change under both more optimistic and more pessimistic emissions scenarios than the range provided by SRES, EMICs are able to produce additional climate change projections relatively rapidly. However, as a result of their parameterizations and reduced complexity, EMICs have been generally avoided when examining sub-global spatial scales in favour of GCMs or RCMs. To investigate these concerns, we compare responses to changes in radiative forcing from both the University of Victoria Earth system climate model and an ensemble of CMIP3 global climate models at a variety of sub-global spatial scales. Temperature trends and anomalies from commonly used intervals in the 20th and 21st centuries (e.g. 1961-1990, 2046-2065) are evaluated for both model types under standard emissions scenarios. Results indicate that the UVIC model produces statistically similar regional temperature responses as those of the ensemble average of the IPCC AR4 global climate models. Precipitation anomalies display fewer statistical matches with rainfall increases underestimated and snowfall decreases overestimated by the UVIC model. The results suggest regional consequences of more varied emissions scenarios could be examined in certain cases using the UVIC model (and potentially other EMICs) instead of GCMs or RCMs. A selection of regional climate change responses comparing the UVIC model to the AR4 ensemble average will be presented for a variety of areas.

  20. 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.

  1. Climate Science: How Earth System Models are Reshaping the Science Policy Interface.

    Science.gov (United States)

    Ruane, Alex

    2015-01-01

    This talk is oriented at a general audience including the largest French utility company, and will describe the basics of climate change before moving into emissions scenarios and agricultural impacts that we can test with our earth system models and impacts models.

  2. 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

  3. A Bayesian approach for temporally scaling climate for modeling ecological systems.

    Science.gov (United States)

    Post van der Burg, Max; Anteau, Michael J; McCauley, Lisa A; Wiltermuth, Mark T

    2016-05-01

    With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre-1970] and contemporary [post-2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet-dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems. PMID:27217947

  4. A Bayesian approach for temporally scaling climate for modeling ecological systems

    Science.gov (United States)

    Post van der Burg, Max; Anteau, Michael J.; McCauley, Lisa A.; Wiltermuth, Mark T.

    2016-01-01

    With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre-1970] and contemporary [post-2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet–dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems.

  5. The Earth System Grid: Supporting the Next Generation of Climate Modeling Research

    CERN Document Server

    Bernholdt, David; Brown, David; Chanchio, Kasidit; Chen, Meili; Chervenak, Ann; Cinquini, Luca; Drach, Bob; Foster, Ian; Fox, Peter; Garcia, Jose; Kesselman, Carl; Markel, Rob; Middleton, Don; Nefedova, Veronika; Pouchard, Line; Shoshani, Arie; Sim, Alex; Strand, Gary; Williams, Dean

    2007-01-01

    Understanding the earth's climate system and how it might be changing is a preeminent scientific challenge. Global climate models are used to simulate past, present, and future climates, and experiments are executed continuously on an array of distributed supercomputers. The resulting data archive, spread over several sites, currently contains upwards of 100 TB of simulation data and is growing rapidly. Looking toward mid-decade and beyond, we must anticipate and prepare for distributed climate research data holdings of many petabytes. The Earth System Grid (ESG) is a collaborative interdisciplinary project aimed at addressing the challenge of enabling management, discovery, access, and analysis of these critically important datasets in a distributed and heterogeneous computational environment. The problem is fundamentally a Grid problem. Building upon the Globus toolkit and a variety of other technologies, ESG is developing an environment that addresses authentication, authorization for data access, large-sc...

  6. Validation of an ensemble modelling system for climate projections for the northwest European shelf seas

    Science.gov (United States)

    Tinker, Jonathan; Lowe, Jason; Holt, Jason; Pardaens, Anne; Wiltshire, Andy

    2015-11-01

    The aim of this study was to evaluate the performance of a modelling system used to represent the northwest European shelf seas. Variants of the coupled atmosphere-ocean global climate model, HadCM3, were run under conditions of historically varying concentrations of greenhouse gases and other radiatively active constituents. The atmospheric simulation for the shelf sea region and its surrounds was downscaled to finer spatial scales using a regional climate model (HadRM3); these simulations were then used to drive a river routing scheme (TRIP). Together, these provide the atmospheric, oceanic and riverine boundary conditions to drive the shelf seas model POLCOMS. Additionally, a shelf seas simulation was driven by the ERA-40 reanalysis in place of HadCM3. We compared the modelling systems output against a sea surface temperature satellite analysis product, a quality controlled ocean profile dataset and values of volume transport through particular ocean sections from the literature. In addition to assessing model drift with a pre-industrial control simulation the modelling system was evaluated against observations and the reanalysis driven simulation. We concluded that the modelling system provided an excellent (good) representation of the spatial patterns of temperature (salinity). It provided a good representation of the mean temperature climate, and a sufficient representation of the mean salinity and water column structure climate. The representation of the interannual variability was sufficient, while the overall shelf-wide circulation was qualitatively good. From this wide range of metrics we judged the modelling system fit for the purpose of providing centennial climate projections for the northwest European shelf seas.

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

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J.

    2013-02-07

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

  8. 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

  9. Implementation of the Stochastic Multicloud Model in the NCEP Climate Forecast System version 2 (CFSv2)

    Science.gov (United States)

    Goswami, B. B.; Krishna, R. P. M.; Khouider, B.; Mukhopadhyay, P.; Majda, A.

    2015-12-01

    We present here the implementation of the stochastic multicloud model (SMCM) (khouider et al 2010) in the NCEP Climate forecast system version 2 (CFSv2). The final goal of this effort is to improve the Indian Summer Monsoon weather and climate through better-organized tropical convection in CFSv2. The fidelity of CFSv2 in simulating the mean state of the global climate, particularly the Indian summer monsoon, relative to the CMIP5 models (Sabeer et al 2013) is the reason behind choosing CFSv2 as the GCM to implement SMCM. We expect to see an improved climate simulation in SMCM-CFSv2 because of the theoretically sound and tested design of the multicloud approach (Khouider and Majda 2006, and the relevant subsequent work thereafter). In order to implement SMCM in CFSv2, first we identify different climatic regions based on the mean state of the global climate (using the CFSR 20year monthly climatology). Then we initialize the climatological values (computed from the CFSR 20year monthly climatology) of the variables required in the multicloud parameterization scheme, for the different climatic zones. We input moisture, temperature and PBL height from the CFSv2 to the multicloud parameterization module and then compute the corresponding variables that were initialized from the mean state. Then we compute the deviation of those variables from the background state. Based on middle troposphere dryness, we compute the heating rates for the deep, congestus and stratiform convection from these deviations from the background (deterministic approach). The stochastic extension involves the evolution of the cloud area fractions, associated to each one of the three cloud types, which are represented by a stochastic lattice subgrid model whose random transitions depend on CAPE and large-scale tropospheric dryness. The stochastic model feedback, to the GCM dynamics, occurs through the modulation of the heating rates by the cloud area fractions.

  10. A multi-resolution method for climate system modeling: application of spherical centroidal Voronoi tessellations

    Energy Technology Data Exchange (ETDEWEB)

    Ringler, Todd [Los Alamos National Laboratory; Ju, Lili [University of South Carolina; Gunzburger, Max [Florida State University

    2008-01-01

    During the next decade and beyond, climate system models will be challenged to resolve scales and processes that are far beyond their current scope. Each climate system component has its prototypical example of an unresolved process that may strongly influence the global climate system, ranging from eddy activity within ocean models, to ice streams within ice sheet models, to surface hydrological processes within land system models, to cloud processes within atmosphere models. These new demands will almost certainly result in the develop of multiresolution schemes that are able, at least regionally, to faithfully simulate these fine-scale processes. Spherical centroidal Voronoi tessellations (SCVTs) offer one potential path toward the development of a robust, multiresolution climate system model components. SCVTs allow for the generation of high quality Voronoi diagrams and Delaunay triangulations through the use of an intuitive, user-defined density function. In each of the examples provided, this method results in high-quality meshes where the quality measures are guaranteed to improve as the number of nodes is increased. Real-world examples are developed for the Greenland ice sheet and the North Atlantic ocean. Idealized examples are developed for ocean–ice shelf interaction and for regional atmospheric modeling. In addition to defining, developing, and exhibiting SCVTs, we pair this mesh generation technique with a previously developed finite-volume method. Our numerical example is based on the nonlinear, shallow water equations spanning the entire surface of the sphere. This example is used to elucidate both the potential benefits of this multiresolution method and the challenges ahead.

  11. Modeling the impact of large-scale energy conversion systems on global climate

    International Nuclear Information System (INIS)

    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 CO2 concentration. State-of-the-art models estimate a surface temperature increase of 1.5-3.00C 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.)

  12. Modeling European ruminant production systems: Facing the challenges of climate change

    OpenAIRE

    Kipling, Richard P.; Bannink, André; Bellocchi, Gianni; Dalgaard, Tommy; Naomi J Fox; Hutchings, Nicholas J.; Kjeldsen, Chris; Lacetera, Nicola; Sinabell, Franz; Topp, Cairistiona F.E.; Oijen, Marcel van; Virkajärvi, Perttu; Nigel D Scollan

    2016-01-01

    Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute significantly to climate change through greenhouse gas (GHG) emissions, while intensification of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationshi...

  13. A NASA Climate Model Data Services (CDS) End-to-End System to Support Reanalysis Intercomparison

    Science.gov (United States)

    Carriere, L.; Potter, G. L.; McInerney, M.; Nadeau, D.; Shen, Y.; Duffy, D.; Schnase, J. L.; Maxwell, T. P.; Huffer, E.

    2014-12-01

    The NASA Climate Model Data Service (CDS) and the NASA Center for Climate Simulation (NCCS) are collaborating to provide an end-to-end system for the comparative study of the major Reanalysis projects, currently, ECMWF ERA-Interim, NASA/GMAO MERRA, NOAA/NCEP CFSR, NOAA/ESRL 20CR, and JMA JRA25. Components of the system include the full spectrum of Climate Model Data Services; Data, Compute Services, Data Services, Analytic Services and Knowledge Services. The Data includes standard Reanalysis model output, and will be expanded to include gridded observations, and gridded Innovations (O-A and O-F). The NCCS High Performance Science Cloud provides the compute environment (storage, servers, and network). Data Services are provided through an Earth System Grid Federation (ESGF) data node complete with Live Access Server (LAS), Web Map Service (WMS) and Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) for visualization, as well as a collaborative interface through the Earth System CoG. Analytic Services include UV-CDAT for analysis and MERRA/AS, accessed via the CDS API, for computation services, both part of the CDS Climate Analytics as a Service (CAaaS). Knowledge Services include access to an Ontology browser, ODISEES, for metadata search and data retrieval. The result is a system that provides the ability for both reanalysis scientists and those scientists in need of reanalysis output to identify the data of interest, compare, compute, visualize, and research without the need for transferring large volumes of data, performing time consuming format conversions, and writing code for frequently run computations and visualizations.

  14. Collaborative Proposal: Transforming How Climate System Models are Used: A Global, Multi-Resolution Approach

    Energy Technology Data Exchange (ETDEWEB)

    Estep, Donald

    2013-04-15

    Despite the great interest in regional modeling for both weather and climate applications, regional modeling is not yet at the stage that it can be used routinely and effectively for climate modeling of the ocean. The overarching goal of this project is to transform how climate models are used by developing and implementing a robust, efficient, and accurate global approach to regional ocean modeling. To achieve this goal, we will use theoretical and computational means to resolve several basic modeling and algorithmic issues. The first task is to develop techniques for transitioning between parameterized and high-fidelity regional ocean models as the discretization grid transitions from coarse to fine regions. The second task is to develop estimates for the error in scientifically relevant quantities of interest that provide a systematic way to automatically determine where refinement is needed in order to obtain accurate simulations of dynamic and tracer transport in regional ocean models. The third task is to develop efficient, accurate, and robust time-stepping schemes for variable spatial resolution discretizations used in regional ocean models of dynamics and tracer transport. The fourth task is to develop frequency-dependent eddy viscosity finite element and discontinuous Galerkin methods and study their performance and effectiveness for simulation of dynamics and tracer transport in regional ocean models. These four projects share common difficulties and will be approach using a common computational and mathematical toolbox. This is a multidisciplinary project involving faculty and postdocs from Colorado State University, Florida State University, and Penn State University along with scientists from Los Alamos National Laboratory. The completion of the tasks listed within the discussion of the four sub-projects will go a long way towards meeting our goal of developing superior regional ocean models that will transform how climate system models are used.

  15. Assessing climate change impacts on the Iberian power system using a coupled water-power model

    DEFF Research Database (Denmark)

    Cardenal, Silvio Javier Pereira; Madsen, Henrik; Arnbjerg-Nielsen, Karsten;

    2014-01-01

    Climate change is expected to have a negative impact on the power system of the Iberian Peninsula; changes in river runoff are expected to reduce hydropower generation, while higher temperatures are expected to increase summer electricity demand, when water resources are already limited. However......, these impacts have not yet been evaluated at the peninsular level. We coupled a hydrological model with a power market model to study three impacts of climate change on the current Iberian power system: changes in hydropower production caused by changes in precipitation and temperature, changes in...... temporal patterns of electricity demand caused by temperature changes, and changes in irrigation water use caused by temperature and precipitation changes. A stochastic dynamic programming approach was used to develop operating rules for the integrated system given hydrological uncertainty. We found that...

  16. Climate change induced transformations of agricultural systems: insights from a global model

    International Nuclear Information System (INIS)

    Climate change might impact crop yields considerably and anticipated transformations of agricultural systems are needed in the coming decades to sustain affordable food provision. However, decision-making on transformational shifts in agricultural systems is plagued by uncertainties concerning the nature and geography of climate change, its impacts, and adequate responses. Locking agricultural systems into inadequate transformations costly to adjust is a significant risk and this acts as an incentive to delay action. It is crucial to gain insight into how much transformation is required from agricultural systems, how robust such strategies are, and how we can defuse the associated challenge for decision-making. While implementing a definition related to large changes in resource use into a global impact assessment modelling framework, we find transformational adaptations to be required of agricultural systems in most regions by 2050s in order to cope with climate change. However, these transformations widely differ across climate change scenarios: uncertainties in large-scale development of irrigation span in all continents from 2030s on, and affect two-thirds of regions by 2050s. Meanwhile, significant but uncertain reduction of major agricultural areas affects the Northern Hemisphere’s temperate latitudes, while increases to non-agricultural zones could be large but uncertain in one-third of regions. To help reducing the associated challenge for decision-making, we propose a methodology exploring which, when, where and why transformations could be required and uncertain, by means of scenario analysis. (letter)

  17. Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

    Science.gov (United States)

    Loeb, Norman G.; Wielicki, Bruce A.; Doelling, David R.

    2008-01-01

    There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5

  18. Modelling sequential Biosphere systems under Climate change for radioactive waste disposal. Project BIOCLIM

    International Nuclear Information System (INIS)

    The BIOCLIM project (Modelling Sequential Biosphere systems under Climate change for Radioactive Waste Disposal) is part of the EURATOM fifth European framework programme. The project was launched in October 2000 for a three-year period. It is coordinated by ANDRA, the French national radioactive waste management agency. The project brings together a number of European radioactive waste management organisations that have national responsibilities for the safe disposal of radioactive wastes, and several highly experienced climate research teams. Waste management organisations involved are: NIREX (UK), GRS (Germany), ENRESA (Spain), NRI (Czech Republic) and ANDRA (France). Climate research teams involved are: LSCE (CEA/CNRS, France), CIEMAT (Spain), UPMETSIMM (Spain), UCL/ASTR (Belgium) and CRU (UEA, UK). The Environmental Agency for England and Wales provides a regulatory perspective. The consulting company Enviros Consulting (UK) assists ANDRA by contributing to both the administrative and scientific aspects of the project. This paper describes the project and progress to date. (authors)

  19. Modelling climate change effects on a Dutch coastal groundwater system using airborne electromagnetic measurements

    Directory of Open Access Journals (Sweden)

    M. Faneca Sànchez

    2012-12-01

    Full Text Available The forecast of climate change effects on the groundwater system in coastal areas is of key importance for policy makers. The Dutch water system has been deeply studied because of its complex system of low-lying areas, dunes, land won to the sea and dikes, but nowadays large efforts are still being done to find out the best techniques to describe complex fresh-brackish-saline groundwater dynamic systems. In this paper, we describe a methodology consisting of high-resolution airborne electromagnetic (EM measurements used in a 3-D variable-density transient groundwater model for a coastal area in the Netherlands. We used the airborne EM measurements in combination with borehole-logging data, electrical conductivity cone penetration tests and groundwater samples to create a 3-D fresh-brackish-saline groundwater distribution of the study area. The EM measurements proved to be an improvement compared to older techniques and provided quality input for the model. With the help of the built 3-D variable-density groundwater model, we removed the remaining inaccuracies of the 3-D chloride field and predicted the effects of three climate scenarios on the groundwater and surface water system. Results showed significant changes in the groundwater system, and gave direction for future water policy. Future research should provide more insight in the improvement of data collection for fresh-brackish-saline groundwater systems as it is of high importance to further improve the quality of the model.

  20. Stochastic Climate Theory and Modelling

    CERN Document Server

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

    2014-01-01

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

  1. 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

  2. A Fast Version of LASG/IAP Climate System Model and Its 1000-year Control Integration

    Institute of Scientific and Technical Information of China (English)

    ZHOU Tianjun; WU Bo; WEN Xinyu; LI Lijuan; WANG Bin

    2008-01-01

    A fast version of the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geo- physical Fluid Dynamics (LASG)/Institute of Atmospheric Physics (IAP) climate system model is briefly documented. The fast coupled model employs a low resolution version of the atmospheric component Grid Atmospheric Model of IAP/LASG (GAMIL), with the other parts of the model, namely an oceanic com- ponent LASG/IAP Climate Ocean Model (LICOM), land component Common Land Model (CLM), and sea ice component from National Center for Atmospheric Research Community Climate System Model (NCAR CCSM2), as the same as in the standard version of LASG/IAP Flexible Global Ocean Atmosphere Land System model (FGOALS_g). The parameterizatious of physical and dynamical processes of the at- mospheric component in the fast version are identical to the standard version, although some parameter values are different. However, by virtue of reduced horizontal resolution and increased time-step of the most time-consuming atmospheric component, it runs faster by a factor of 3 and can serve as a useful tool for long- term and large-ensemble integrations. A 1000-year control simulation of the present-day climate has been completed without flux adjustments. The final 600 years of this simulation has virtually no trends in global mean sea surface temperatures and is recommended for internal variability studies. Several aspects of the control simulation's mean climate and variability axe evaluated against the observational or reanalysis data. The strengths and weaknesses of the control simulation are evaluated. The mean atmospheric circulation is well simulated, except in high latitudes. The Asian-Australian monsoonal meridional cell shows realistic features, however, an artificial rainfall center is located to the eastern periphery of the Tibetan Plateau persists throughout the year. The mean bias of SST resembles that of the standard version, appearing as a "double ITCZ" (Inter

  3. Modeling of the climate system and of its response to a greenhouse effect increase

    International Nuclear Information System (INIS)

    The anthropic disturbance of the Earth's greenhouse effect is already visible and will enhance in the coming years or decades. In front of the rapidity and importance of the global warming effect, the socio-economical management of this change will rise problems and must be studied by the scientific community. At the modeling level, finding a direct strategy for the validation of climate models is not easy: many uncertainties exist because energy transformations take place at a low level and several processes take place at the same time. The variability observed at the seasonal, inter-annual or paleo- scales allows to validate the models at the process level but not the evolution of the whole system. The management of these uncertainties is an integral part of the global warming problem. Thus, several scenarios can be proposed and their risk of occurrence must be estimated. This paper presents first the greenhouse effect, the climatic changes during geologic times, the anthropic disturbance of the greenhouse effect, the modeling of climate and the forecasting of its evolution. (J.S.)

  4. Towards the Prediction of Decadal to Centennial Climate Processes in the Coupled Earth System Model

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Zhengyu [Univ. of Wisconsin, Madison, WI (United States); Kutzbach, J. [Univ. of Wisconsin, Madison, WI (United States); Jacob, R. [Argonne National Lab. (ANL), Argonne, IL (United States); Prentice, C. [Bristol Univ. (United Kingdom)

    2011-12-05

    In this proposal, we have made major advances in the understanding of decadal and long term climate variability. (a) We performed a systematic study of multidecadal climate variability in FOAM-LPJ and CCSM-T31, and are starting exploring decadal variability in the IPCC AR4 models. (b) We develop several novel methods for the assessment of climate feedbacks in the observation. (c) We also developed a new initialization scheme DAI (Dynamical Analogue Initialization) for ensemble decadal prediction. (d) We also studied climate-vegetation feedback in the observation and models. (e) Finally, we started a pilot program using Ensemble Kalman Filter in CGCM for decadal climate prediction.

  5. Improving Sea Ice Prediction in the NCEP Climate Forecast System Model

    Science.gov (United States)

    Collow, T. W.; Wang, W.; Kumar, A.

    2015-12-01

    Skillful prediction of Arctic sea ice is important for the wide variety of interests focused in that region. However, the current operational system used by the NOAA Climate Prediction Center does not adequately predict the seasonal climatology of sea ice extent and maintains too high sea ice coverage across the Arctic. It is thought that the primary reasoning for this lies in the initialization of sea ice thickness. Experiments are carried out using the Climate Forecast System (CFSv2) model with an improved sea ice thickness initialization from the Pan-Arctic Ice Ocean Analysis and Assimilation System (PIOMAS) rather than the default Climate Forecast System Reanalysis (CFSR) sea ice thickness data. All other variables are initialized from CFSR. In addition, physics parameterizations are adjusted to better simulate real world conditions. Here we focus on hindcasts initialized from 2005-2014. Although the seasonal cycle of sea ice is generally better captured in runs that use PIOMAS sea ice thickness initialization, local sea ice freeze in early winter in the Bering Strait and Chukchi Sea is delayed when both sea ice thickness configurations are used. In addition ice freeze in the North Atlantic is more pronounced than in the observations. This shows that simply changing initial sea ice thickness is not enough to improve forecasts for all locations. Modeled atmospheric and oceanic parameters are investigated including the radiation budget, land surface temperature advection, and sub-surface oceanic heat flow to diagnose possible reasons for the modeling deficiencies, and further modifications to the model will be discussed.

  6. The Impact of the Ocean Sulfur Cycle on Climate using the Community Earth System Model

    Science.gov (United States)

    Cameron-Smith, P. J.; Elliott, S. M.; Bergmann, D. J.; Branstetter, M. L.; Chuang, C.; Erickson, D. J.; Jacob, R. L.; Maltrud, M. E.; Mirin, A. A.

    2011-12-01

    Chemical cycling between the various Earth system components (atmosphere, biosphere, land, ocean, and sea-ice) can cause positive and negative feedbacks on the climate system. The long-standing CLAW/GAIA hypothesis proposed that global warming might stimulate increased production of dimethyl sulfide (DMS) by plankton in the ocean, which would then provide a negative climate feedback through atmospheric oxidation of the DMS to sulfate aerosols that reflect sunlight directly, and indirectly by affecting clouds. Our state-of-the-art earth system model (CESM with an ocean sulfur cycle and atmospheric chemistry) shows increased production of DMS over the 20th century by plankton, particularly in the Southern Ocean and Equatorial Pacific, which leads to modest cooling from direct reflection of sunlight in those regions. This suggests the possibility of local climate change mitigation by the plankton species that produce DMS. Part of this work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

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

    CERN Document Server

    Mitchell, Lewis

    2011-01-01

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

  8. Quantifying and Reducing Climate-Carbon Cycle Feedback Uncertainties: Analysis of CMIP5 Earth System Model Feedbacks

    Science.gov (United States)

    Hoffman, F. M.; Randerson, J. T.

    2011-12-01

    Increasing atmospheric carbon dioxide (CO2) concentrations, resulting from anthropogenic perturbation of the global carbon cycle, are altering the Earth's climate. Climate change is expected to induce feedbacks on future CO2 concentrations and on the climate system itself. These feedbacks are highly uncertain, potentially large, and difficult to predict using Earth System Models (ESMs). In order to reduce the range of uncertainty in climate predictions, model representation of feedbacks must be improved through comparisons with contemporary observations. In this study, we quantify the terrestrial and ocean carbon storage sensitivity to climate and atmospheric CO2 concentration of ESMs participating in the Climate Model Intercomparison Project Phase 5 (CMIP5) following the methodology of Friedlingstein et al. (2006). In order to evaluate the models' abilities to capture the 21st century carbon cycle and to offer possible constraints on the modeled feedback strengths, comparisons with contemporary observations will be made over three different time scales: seasonal to annual, interannual to decadal, and decadal to centennial. A conceptual framework for evaluating climate-carbon cycle feedbacks in global models--employing best-available observational data--will be presented, along with results from application of this framework to CMIP5 model output. Included in the analysis will be prototype model evaluation benchmarks of the carbon cycle being designed for the International Land Model Benchmarking (ILAMB) Project.

  9. Using the Climate Assessment Tool (CAT) in U.S. EPA BASINS integrated modeling system to assess watershed vulnerability to climate change.

    Science.gov (United States)

    Imhoff, J C; Kittle, J L; Gray, M R; Johnson, T E

    2007-01-01

    During the last century, much of the United States experienced warming temperatures and changes in amount and intensity of precipitation. Changes in future climate conditions present additional risk to water and watershed managers. The most recent release of U.S. EPA's BASINS watershed modeling system includes a Climate Assessment Tool (CAT) that provides new capabilities for assessing impacts of climate change on water resources. The BASINS CAT provides users with the ability to modify historical climate and conduct systematic sensitivity analyses of specific hydrologic and water quality endpoints to changes in climate using the BASINS models (Hydrologic Simulation Program - FORTRAN (HSPF)). These capabilities are well suited for addressing questions about the potential impacts of climate change on key hydrologic and water quality goals using the watershed scale at which most important planning decisions are made. This paper discusses the concepts that motivated the CAT development effort; the resulting capabilities incorporated into BASINS CAT; and the opportunities that result from integrating climate assessment capabilities into a comprehensive watershed water quality modeling system. PMID:17978432

  10. The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) – Part 1: Model description and pre-industrial simulation

    OpenAIRE

    R. M. Law; Ziehn, T.; Matear, R. J.; Lenton, A.; Chamberlain, M. A.; L. E. Stevens; Y. P. Wang; Srbinovsky, J.; Bi, D.; Yan, H; P. F. Vohralik

    2015-01-01

    Earth System Models (ESMs) that incorporate carbon-climate feedbacks represent the present state of the art in climate modelling. Here, we describe the Australian Community Climate and Earth System Simulator (ACCESS)-ESM1 that combines existing ocean and land carbon models into the physical climate model to simulate exchanges of carbon between the land, atmosphere and ocean. The land carbon model can optionally include both nitrogen and ...

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

    Science.gov (United States)

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

    2013-12-01

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

  12. Modeling the global society-biosphere-climate system. Part 2: computed scenarios

    International Nuclear Information System (INIS)

    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 concentrations of gases, temperature, precipitation, land cover and other indicators. Included are a 'Conventional Wisdom' scenario, and three variations of this scenario: (i) the Conventional Wisdom scenario is a reference case which is partly based on the input assumptions of the IPCC's IS92a scenario; (ii) the 'Biofuel Crops' scenario assumes that most biofuels will be derived from new cropland; (iii) the 'No Biofuels' scenario examines the sensitivity of the system to the use of biofuels; and (iv) the 'Ocean Realignment' scenario investigates the effect of a large-scale change in ocean circulation on the biosphere and climate. Results of the biofuel scenarios illustrate the importance of examining the impact of biofuels on the full range of greenhouse gases, rather than only CO2. These scenarios also indicate possible side effects of the land requirements for energy crops. The Ocean Realignment scenario shows that an unexpected, low probability event can both enhance the build-up of greenhouse gases, and at the same time cause a temporary cooling of surface air temperatures in the Northern Hemisphere. However, warming of the atmosphere is only delayed, not avoided. 26 refs., 16 figs., 7 tabs

  13. A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, Alexey V. [Yale University; Fedorov, Alexey

    2015-01-14

    The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth system models, to the stability and variability of the AMOC in past climates.

  14. Integrating components of the earth system to model global climate changes: implications for the simulation of the climate of the next million years

    International Nuclear Information System (INIS)

    The climate system is complex because it is made up of several components (atmosphere, ocean, sea ice, continental surface, ice sheets), each of which has its own response time. The paleo-climate record provides ample evidence that these components interact nonlinearly with each other and also with global biogeochemical cycles, which drive greenhouse gas concentration in the atmosphere. Forecasting the evolution of future climate is therefore an extremely complex problem. In addition, since the nineteenth century, human activities are releasing great quantities of greenhouse gases (CO2, CH4, CFC, etc.) into the atmosphere. As a consequence, the atmospheric content of these gases has tremendously increased. As they have a strong greenhouse effect, their concentration is now large enough to perturb the natural evolution of the earth's climate. In this paper, we shall review the strategy which has been used to develop and validate tools that would allow to simulate the future long-term behaviour of the Earth's climate. This strategy rests on two complementary approaches: developing numerical models of the climate system and validating them by comparing their output with present-day meteorological data and paleo-climatic reconstructions. We shall then evaluate the methods available to simulate climate at the regional scale and the major uncertainties that must be solved to reasonable estimate the long-term evolution of a region, which would receive a geological repository for nuclear wastes. (author)

  15. A parallel Atmosphere-Ocean Global Circulation Model of intermediate complexity for Earth system climate research

    Science.gov (United States)

    Silva, T. A.; Schmittner, A.

    2007-12-01

    We present the evolution of an Earth System model of intermediate complexity featuring an ocean global circulation model to include a fully coupled 3D primitive equations atmospheric model. The original Earth System climate model, UVic ESCM (Weaver et al. 2001), uses an ocean global circulation model coupled to a one layer atmospheric energy-moisture balance model. It also comprises a viscous-plastic rheology sea ice model, a mechanical land ice model, land surface, oceanic and terrestrial carbon models and a simple 3D marine ecosystem model (Schmittner et al. 2005). A spectral atmospheric, model, PUMA (Fraedrich et al. 2005), was coupled to the UVic ESCM to provide an atmosphere with nonlinear dynamics in target resolutions of T21, T31 and T42, as required. The coupling with the atmosphere, which involves data transfer, preprocessing and interpolation, is done through the OASIS3 coupler. During a run there are 2 + 2N parallel processes: the UVic ESCM, the Oasis3 coupler and the PUMA model with its domain split across 2N processes. The choice of N allows to balance more or less complex configurations of UVic model (e.g. higher level marine ecosystem model or number of biogeochemical tracers) with the atmospheric model at different resolutions, in order to maintain computational efficiency. The relatively simple parameterizations make this new atmosphere-ocean global circulation model much faster than a state-of-the-art Atmosphere-Ocean Global Circulation Model, and so optimally geared for decadal to millennial scale integrations. The latter require special care with the conservation of fluxes during coupling. A second order conservative interpolation method was applied (Jones 1999) and this is compared with the use of typical non-conservative methods.

  16. Modeling Multi-Reservoir Hydropower Systems in the Sierra Nevada with Environmental Requirements and Climate Warming

    Science.gov (United States)

    Rheinheimer, David Emmanuel

    Hydropower systems and other river regulation often harm instream ecosystems, partly by altering the natural flow and temperature regimes that ecosystems have historically depended on. These effects are compounded at regional scales. As hydropower and ecosystems are increasingly valued globally due to growing values for clean energy and native species as well as and new threats from climate warming, it is important to understand how climate warming might affect these systems, to identify tradeoffs between different water uses for different climate conditions, and to identify promising water management solutions. This research uses traditional simulation and optimization to explore these issues in California's upper west slope Sierra Nevada mountains. The Sierra Nevada provides most of the water for California's vast water supply system, supporting high-elevation hydropower generation, ecosystems, recreation, and some local municipal and agricultural water supply along the way. However, regional climate warming is expected to reduce snowmelt and shift runoff to earlier in the year, affecting all water uses. This dissertation begins by reviewing important literature related to the broader motivations of this study, including river regulation, freshwater conservation, and climate change. It then describes three substantial studies. First, a weekly time step water resources management model spanning the Feather River watershed in the north to the Kern River watershed in the south is developed. The model, which uses the Water Evaluation And Planning System (WEAP), includes reservoirs, run-of-river hydropower, variable head hydropower, water supply demand, and instream flow requirements. The model is applied with a runoff dataset that considers regional air temperature increases of 0, 2, 4 and 6 °C to represent historical, near-term, mid-term and far-term (end-of-century) warming. Most major hydropower turbine flows are simulated well. Reservoir storage is also

  17. Reservoir Systems in Changing Climate

    Science.gov (United States)

    Lien, W.; Tung, C.; Tai, C.

    2007-12-01

    Climate change may cause more climate variability and further results in more frequent extreme hydrological events which may greatly influence reservoir¡¦s abilities to provide service, such as water supply and flood mitigation, and even danger reservoir¡¦s safety. Some local studies have identified that climate change may cause more flood in wet period and less flow in dry period in Taiwan. To mitigate climate change impacts, more reservoir space, i.e. less storage, may be required to store higher flood in wet periods, while more reservoir storage may be required to supply water for dry periods. The goals to strengthen adaptive capacity of water supply and flood mitigation are conflict under climate change. This study will focus on evaluating the impacts of climate change on reservoir systems. The evaluation procedure includes hydrological models, a reservoir water balance model, and a water supply system dynamics model. The hydrological models are used to simulate reservoir inflows under different climate conditions. Future climate scenarios are derived from several GCMs. Then, the reservoir water balance model is developed to calculate reservoir¡¦s storage and outflows according to the simulated inflows and operational rules. The ability of flood mitigation is also evaluated. At last, those outflows are further input to the system dynamics model to assess whether the goal of water supply can still be met. To mitigate climate change impacts, the implementing adaptation strategies will be suggested with the principles of risk management. Besides, uncertainties of this study will also be analyzed. The Feitsui reservoir system in northern Taiwan is chosen as a case study.

  18. Impacts of Climate and Human-induced Changes on Stream Temperature in Large River Systems: An Earth System Modeling Perspective

    Science.gov (United States)

    Li, H. Y.; Leung, L. R.; Tesfa, T. K.; Voisin, N.; Yang, X.; Rice, J.

    2014-12-01

    Stream temperature plays an important role in closing the energy balance at local, regional and global scales, and exerts significant impacts on aquatic biodiversity, power plant operation and energy production. It is therefore a critical component for representing the energy-water nexus in earth system models. The stream temperature particularly in large river systems is very often regulated by human activities such as reservoir and power plant operations. This study is a first attempt to develop a physically based stream temperature model within the Community Earth System Model (CESM) framework. The Model for Scale Adaptive River Transport (MOSART) has been developed to represent riverine water dynamics and incorporated into CESM by coupling with the Community Land Model (CLM). Here we build upon CLM-MOSART to represent the riverine transport of heat along with water flux and the energy exchanges between river water and the atmosphere. More importantly, the impacts of reservoir and power plant operations are also explicitly parameterized within this new stream temperature model. This new stream temperature model will first be driven by historical forcing and validated against the observed stream temperature at a number of USGS gauges across the US. Then, driven by dynamically downscaled climate change scenarios, the relative contributions of climate change and reservoir and power-plant operation on the projected spatiotemporal changes in stream temperature will be systematically analyzed. Lastly the current limitations and future directions will be discussed.

  19. Assessment of Climate Change Impacts on Water Quality in a Tidal Estuarine System Using a Three-Dimensional Model

    OpenAIRE

    Wen-Cheng Liu; Wen-Ting Chan

    2016-01-01

    Climate change is one of the key factors affecting the future quality and quantity of water in rivers and tidal estuaries. A coupled three-dimensional hydrodynamic and water quality model has been developed and applied to the Danshuei River estuarine system in northern Taiwan to predict the influences of climate change on water quality. The water quality model considers state variables including nitrogen, phosphorus, organic carbon, and phytoplankton as well as dissolved oxygen, and is driven...

  20. Feedbacks between climate, CO2 and N2O quantified by a fully coupled Earth system model

    Science.gov (United States)

    Kracher, D.; Reick, C. H.

    2013-12-01

    Climate change is evoked by an anthropogenic increase of green house gases (GHG) in the atmosphere, induced by direct emissions from industrial processes or indirectly due to human impacts on ecosystems. Those indirect GHG emissions are strongly influenced by climatic conditions implying several feedback loops in the climate - carbon (C) - nitrogen (N) system. In our study we aim at quantifying the climate - nitrous oxide (N2O) feedback strength in comparison to other feedback mechanisms by applying an Earth system model with explicit representation of interactive N2O in the atmosphere-land-ocean system. Beside the feedbacks emerging due to the temperature sensitivity of biogenic CO2 and N2O emissions, another feedback addressed arises from additional inter-linkages between climate and C and N cycles. Future increased atmospheric CO2 leads to enhanced primary productivity ('CO2 fertilization') causing changes in N availability in the different land and ocean ecosystems. As N2O emissions are driven by availability of N, increased atmospheric CO2 concentrations will impact the climate system also via modifications in N2O emissions. Those changes in N2O emissions will feed back to the climate and will hence also modify the natural biogenic release of CO2 into the atmosphere. This and other associated feedbacks are quantified by applying MPI-ESM, the Earth system model of the Max Planck Institute for Meteorology in Hamburg. MPI-ESM is an atmosphere and ocean global circulation model with model components for land and ocean biogeochemistry. For both CO2 and N2O, land-atmosphere and ocean-atmosphere exchange as well as atmospheric transport are simulated explicitly. Hence, different feedback components in the climate-C-N system can be quantified by cutting artificially single feedback pathways in the model.

  1. Likelihood-Based Climate Model Evaluation

    Science.gov (United States)

    Braverman, Amy; Cressie, Noel; Teixeira, Joao

    2012-01-01

    Climate models are deterministic, mathematical descriptions of the physics of climate. Confidence in predictions of future climate is increased if the physics are verifiably correct. A necessary, (but not sufficient) condition is that past and present climate be simulated well. Quantify the likelihood that a (summary statistic computed from a) set of observations arises from a physical system with the characteristics captured by a model generated time series. Given a prior on models, we can go further: posterior distribution of model given observations.

  2. Evaluating the Representation and Impact of Convective Processes in the NCAR’s Community Climate System Model

    Energy Technology Data Exchange (ETDEWEB)

    Xiaoqing Wu

    2008-07-31

    Convection and clouds affect atmospheric temperature, moisture and wind fields through the heat of condensation and evaporation and through redistributions of heat, moisture and momentum. Individual clouds have a spatial scale of less than 10 km, much smaller than the grid size of several hundred kilometers used in climate models. Therefore the effects of clouds must be approximated in terms of variables that the model can resolve. Deriving such formulations for convection and clouds has been a major challenge for the climate modeling community due to the lack of observations of cloud and microphysical properties. The objective of our DOE CCPP project is to evaluate and improve the representation of convection schemes developed by PIs in the NCAR (National Center for Atmospheric Research) Community Climate System Model (CCSM) and study its impact on global climate simulations.

  3. Climate modeling at Manitoba Hydro

    International Nuclear Information System (INIS)

    This paper gives an outline of climate modeling at Manitoba Hydro. Manitoba Hydro is studying climate change because it affects water supply and energy demand. Hence climate change must be addressed in planning and operation of hydropower projects as well as regulatory and compliance issues. The study has developed a series of climate change scenarios based on the Global Climate Models

  4. A Pedagogical "Toy" Climate Model

    OpenAIRE

    Katz, J. I.

    2010-01-01

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

  5. A Pedagogical "Toy" Climate Model

    CERN Document Server

    Katz, J I

    2010-01-01

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

  6. Modeling Earth's Climate

    Science.gov (United States)

    Pallant, Amy; Lee, Hee-Sun; Pryputniewicz, Sara

    2012-01-01

    Systems thinking suggests that one can best understand a complex system by studying the interrelationships of its component parts rather than looking at the individual parts in isolation. With ongoing concern about the effects of climate change, using innovative materials to help students understand how Earth's systems connect with each other is…

  7. The climate in China over the past 2000 years in a global Earth System Model simulation

    Science.gov (United States)

    Zorita, Eduardo; Wagner, Sebastian; Luterbacher, Jürg; Zhang, Huan

    2016-04-01

    The climate in China over the past 2000 years is analysed based on a global simulation with the Earth System Model MPI-ESM-P. This model has been used for the past millennium simulations of the Climate Model Intercomparison Project version 5. The model includes an atmospheric sub-model (ECHAM6), the ocean and sea-ice submodel MPI-OM. The carbon cycle and vegetation submodels of MPI-ESM-P were switched-off in the version of the Earth System Model. The climate model was forced by reconstructions of past volcanic activity, solar irradiance, greenhouse gases and land-use changes. Over the second millennium, these forcings are the same those used in the past-millennium CMIP5 simulations with the model MPI-ESM-P. For the first millennium, reconstructions of these forcings have been implemented, as described below. The reconstruction of the volcanic forcing is based on the sulphate data set of Sigl et al. (2013) and applying the algorithm of Crowley and Unterman (2012). The sulphate records are scaled to the Crowley and Unterman (2012) reconstruction used within CMIP5 in the second millennium. The solar forcing is based on the reconstruction of Vieira et al. (2011). Long-term changes represent a 0.1% difference between the Maunder Minimum (1645-1715 AD) and present-day values (1950-2000 AD). Land-use changes have been prescribed according to the CMIP5 protocol from 800 onwards and kept constant before this period. This global simulation is currently analysed, thus the presentation will show preliminary results on the past climate variations over China for the Common Era. The spatially averaged annual mean temperature clearly displays the known phases of a relatively warm Roman period, followed by colder conditions during the 'Dark Ages', warmer temperatures again during the Mediaeval Warm Period (MWP; peaking at about 1100 AD). The period from 1300 to 1800 was characterised by below normal temperatures. with an ensuing strong warming trend over approximately the last 200

  8. A comprehensive view on climate change: coupling of earth system and integrated assessment models

    International Nuclear Information System (INIS)

    There are several reasons to strengthen the cooperation between the integrated assessment (IA) and earth system (ES) modeling teams in order to better understand the joint development of environmental and human systems. This cooperation can take many different forms, ranging from information exchange between research communities to fully coupled modeling approaches. Here, we discuss the strengths and weaknesses of different approaches and try to establish some guidelines for their applicability, based mainly on the type of interaction between the model components (including the role of feedback), possibilities for simplification and the importance of uncertainty. We also discuss several important areas of joint IA–ES research, such as land use/land cover dynamics and the interaction between climate change and air pollution, and indicate the type of collaboration that seems to be most appropriate in each case. We find that full coupling of IA–ES models might not always be the most desirable form of cooperation, since in some cases the direct feedbacks between IA and ES may be too weak or subject to considerable process or scenario uncertainty. However, when local processes are important, it could be important to consider full integration. By encouraging cooperation between the IA and ES communities in the future more consistent insights can be developed. (letter)

  9. A comprehensive view on climate change: coupling of earth system and integrated assessment models

    Science.gov (United States)

    van Vuuren, Detlef P.; Batlle Bayer, Laura; Chuwah, Clifford; Ganzeveld, Laurens; Hazeleger, Wilco; van den Hurk, Bart; van Noije, Twan; O'Neill, Brian; Strengers, Bart J.

    2012-06-01

    There are several reasons to strengthen the cooperation between the integrated assessment (IA) and earth system (ES) modeling teams in order to better understand the joint development of environmental and human systems. This cooperation can take many different forms, ranging from information exchange between research communities to fully coupled modeling approaches. Here, we discuss the strengths and weaknesses of different approaches and try to establish some guidelines for their applicability, based mainly on the type of interaction between the model components (including the role of feedback), possibilities for simplification and the importance of uncertainty. We also discuss several important areas of joint IA-ES research, such as land use/land cover dynamics and the interaction between climate change and air pollution, and indicate the type of collaboration that seems to be most appropriate in each case. We find that full coupling of IA-ES models might not always be the most desirable form of cooperation, since in some cases the direct feedbacks between IA and ES may be too weak or subject to considerable process or scenario uncertainty. However, when local processes are important, it could be important to consider full integration. By encouraging cooperation between the IA and ES communities in the future more consistent insights can be developed.

  10. Response of Soil Temperature to Climate Change in the CMIP5 Earth System Models

    Science.gov (United States)

    Phillips, C. L.; Torn, M. S.; Koven, C. D.

    2014-12-01

    Predictions of soil temperature changes are as critical to policy development and climate change adaptation as predictions of air temperature, but have received comparatively little attention. Soil temperature determines seed germination and growth of wild and agricultural plants, and impacts climate through both geophysical and carbon-cycle feedbacks. The Intergovernmental Panel on Climate Change 5th Assessment Report does not report soil temperature predictions, but focuses instead on surface air temperatures, despite the fact that mean annual soil temperatures and mean surface air temperatures are often different from each other. Here we aim to fill this important knowledge gap by reporting soil temperature and moisture predictions for 15 earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison 5 Project (CMIP5). Under the RCP 4.5 and 8.5 emissions scenarios, soil warming is predicted to almost keep pace with soil air warming, with about 10% less warming in soil than air, globally. The slower warming of soil compared to air is likely related to predictions of soil drying, with drier soils having reduced soil heat capacity and thermal conductivity. Mollisol soils, which are typically regarded as the most productive soil order for cultivating cereal crops, are anticipated to see warming in North America of 3.5 to 5.5 °C at the end of the 21st century (2080-2100) compared to 1986-2005. One impact of soil warming is likely to be an acceleration of germination timing, with the 3°C temperature threshold for wheat germination anticipated to advance by several weeks in Mollisol regions. Furthermore, soil warming at 1 m depth is predicted to be almost equivalent to warming at 1 cm depth in frost-free regions, indicating vulnerability of deep soil carbon pools to destabilization. To assess model performance we compare the models' predictions with observations of damping depth, and offsets between mean annual soil and air temperature

  11. Energy balance climate models

    Science.gov (United States)

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

    1981-01-01

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

  12. Pan-spectral observing system simulation experiments of shortwave reflectance and long-wave radiance for climate model evaluation

    Science.gov (United States)

    Feldman, D. R.; Collins, W. D.; Paige, J. L.

    2015-07-01

    Top-of-atmosphere (TOA) spectrally resolved shortwave reflectances and long-wave radiances describe the response of the Earth's surface and atmosphere to feedback processes and human-induced forcings. In order to evaluate proposed long-duration spectral measurements, we have projected 21st Century changes from the Community Climate System Model (CCSM3.0) conducted for the Intergovernmental Panel on Climate Change (IPCC) A2 Emissions Scenario onto shortwave reflectance spectra from 300 to 2500 nm and long-wave radiance spectra from 2000 to 200 cm-1 at 8 nm and 1 cm-1 resolution, respectively. The radiative transfer calculations have been rigorously validated against published standards and produce complementary signals describing the climate system forcings and feedbacks. Additional demonstration experiments were performed with the Model for Interdisciplinary Research on Climate (MIROC5) and Hadley Centre Global Environment Model version 2 Earth System (HadGEM2-ES) models for the Representative Concentration Pathway 8.5 (RCP8.5) scenario. The calculations contain readily distinguishable signatures of low clouds, snow/ice, aerosols, temperature gradients, and water vapour distributions. The goal of this effort is to understand both how climate change alters reflected solar and emitted infrared spectra of the Earth and determine whether spectral measurements enhance our detection and attribution of climate change. This effort also presents a path forward to understand the characteristics of hyperspectral observational records needed to confront models and inline instrument simulation. Such simulation will enable a diverse set of comparisons between model results from coupled model intercomparisons and existing and proposed satellite instrument measurement systems.

  13. Arctic Climate Systems Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ivey, Mark D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Robinson, David G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Boslough, Mark B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Backus, George A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Peterson, Kara J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); van Bloemen Waanders, Bart G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Desilets, Darin Maurice [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reinert, Rhonda Karen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    This study began with a challenge from program area managers at Sandia National Laboratories to technical staff in the energy, climate, and infrastructure security areas: apply a systems-level perspective to existing science and technology program areas in order to determine technology gaps, identify new technical capabilities at Sandia that could be applied to these areas, and identify opportunities for innovation. The Arctic was selected as one of these areas for systems level analyses, and this report documents the results. In this study, an emphasis was placed on the arctic atmosphere since Sandia has been active in atmospheric research in the Arctic since 1997. This study begins with a discussion of the challenges and benefits of analyzing the Arctic as a system. It goes on to discuss current and future needs of the defense, scientific, energy, and intelligence communities for more comprehensive data products related to the Arctic; assess the current state of atmospheric measurement resources available for the Arctic; and explain how the capabilities at Sandia National Laboratories can be used to address the identified technological, data, and modeling needs of the defense, scientific, energy, and intelligence communities for Arctic support.

  14. Modelling for water supply of irrigated cropping systems on climate change

    Directory of Open Access Journals (Sweden)

    Pasquale Campi

    2012-03-01

    Full Text Available The vulnerability of Mediterranean environment due to climatic changes makes necessary to define the effects of the increase of CO2 atmospheric concentration and the consequent alterations of temperature and precipitation variations upon the processes which regulate the plants’ water supply. The traditional research can not meet the needs of this information because of the difficulty of carrying out the experiments. Therefore, it is necessary to use models based upon mathematical representation of the processes and interactions between climatic scenarios, plant and soil, with which to simulate different agronomic situations. The integration of global circulation models with water balance models is a valid tool for studying the influence of climatic changes on water supply. This study took into account the influence of climatic changes on water supply of poly-annual (artichoke and asparagus and annual (potato and broccoli crops with the CRITERIA simulation model of water balance. The simulations were performed with two future climate scenarios (A2 and B1. The results of the simulations highlight how the A2 scenario gives a greater influence on cycle length of crops which develop in summer time determining a reduction of crop cycle from 15 to 20% compared to the observed data, and so, as a consequence in the future, the crops with a summer crop cycle will be subjected to reductions of water supply up to 25%.

  15. Embedding complex hydrology in the regional climate system – Dynamic coupling across different modelling domains

    DEFF Research Database (Denmark)

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

    2014-01-01

    impacts are assessed at the catchment scale, the most important scale for water management. Feedback between groundwater, the land surface and the atmosphere occurs across a range of scales. Recognising this, the coupling was developed to allow dynamic exchange of water and energy at the catchment scale......To improve our understanding of the impacts of feedback between the atmosphere and the terrestrial water cycle including groundwater and to improve the integration of water resource management modelling for climate adaption we have developed a dynamically coupled climate–hydrological modelling...... atmosphere and the groundwater via the land surface and can represent the lateral movement of water in both the surface and subsurface and their interactions, not normally accounted for in climate models. Meso-scale processes are important for climate in general and rainfall in particular. Hydrological...

  16. Effects of climate change on coastal groundwater systems: A modeling study in the Netherlands

    NARCIS (Netherlands)

    Oude Essink, Gualbert; Van Baaren, Esther S.; De Louw, Perry G.B.

    2010-01-01

    Climate change in combination with increased anthropogenic activities will affect coastal groundwater systems throughout the world. In this paper, we focus on a coastal groundwater system that is already threatened by a relatively high seawater level: the low‐lying Dutch Delta. Nearly one third of t

  17. A National Strategy for Advancing Climate Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Dunlea, Edward; Elfring, Chris

    2012-12-04

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

  18. Implementation of an optimal stomatal conductance model in the Australian Community Climate Earth Systems Simulator (ACCESS1.3b

    Directory of Open Access Journals (Sweden)

    J. Kala

    2015-07-01

    Full Text Available We implement a new stomatal conductance model, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLE land surface model. Coupled land-atmosphere simulations are then performed using CABLE within the Australian Community Climate and Earth Systems Simulator (ACCESS with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway, but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5 to 1.0 mm day-1. This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology and improve existing biases by 10–20 %. The change in the surface energy balance also affects net primary productivity and the terrestrial carbon balance. We conclude that the improvements in the global climate model which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development of the ACCESS modelling system.

  19. How reliable are climate models?

    OpenAIRE

    Räisänen, Jouni

    2007-01-01

    How much can we trust model-based projections of future anthropogenic climate change? This review attempts to give an overview of this important but difficult topic by using three main lines of evidence: the skill of models in simulating present-day climate, intermodel agreement on future climate changes, and the ability of models to simulate climate changes that have already occurred. A comparison of simulated and observed present-day climates shows good agreement for many basic variables, p...

  20. Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

    Science.gov (United States)

    Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

    2014-12-01

    The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

  1. Testing the ability of RIEMS2.0 (Regional Integrated Environment Modeling System) on regional climate simulation in East Asia

    Science.gov (United States)

    Zhao, D.; Fu, C.; Yan, X.

    2010-12-01

    RIEMS1.0 (Regional Integrated Environmental Modeling System version 1.0) was developed by researchers from the START (Global change System for Analysis, Research, and Training) Regional Center for Temperate East Asia, IAP/CAS in 1998. The model was built on the thermodynamic frame of PSU/NCAR MM5V2, into which a land surface scheme (BATS1e) and radiative transfer scheme (the revised CCM3) are integrated. The model has been widely used in regional climate studies in the East Asia monsoon system and expresses excellent performance from RMIP (Regional Climate Model Inter-comparison Project). RIEMS2.0 is now being developed starting from RIEMS1.0 by the Key Laboratory of Regional Climate Environment Research for Temperate East Asia, IAP/CAS, and Nanjing University. The new version is built on the thermodynamic framework of nonhydrostatic approximation from MM5V3 with the same land surface model and radiation scheme as RIEMS1.0. To make it an integrated modeling system, the Princeton ocean mode (POM), Atmosphere-Vegetation interaction model (AVIM) and a chemical model are now being integrated. In order to test RIEMS2.0’s ability to simulate short-term climate, we perform ensemble simulations with different physics process schemes. The model will be used to perform ensemble simulations on two continuous extreme climate events, which is serve drought with high temperature in north China in the summer (June, July and August) of 1997 and serve flood in the Yangtze River valley in the summer of 1998. The results show that RIEMS2.0 can reproduce the spatial distribution of the precipitation and SAT from two continuous extreme climate events in the summer of 1997/1998, and disclose sub-regional characteristics. Though difference can be found among ensemble members, ensembles can decrease the model’s uncertainty and improve the simulation decision in a certain degree. In order to test RIEMS2.0’s ability to simulate long-term climate and climate change, we compare

  2. Modeling European ruminant prodcuction systems: facing the challenges of climate change

    DEFF Research Database (Denmark)

    Kipling, Richard Philip; Bannink, Andre; Bellocchi, Gianni;

    2016-01-01

    , yield and GHG emissions from mono-specific swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and...... changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, field and farm-scales and include assumptions which may not be valid under climate change conditions...... gas (GHG) emissions, while intensification of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of...

  3. Examination of a climate stabilization pathway via zero-emissions using Earth system models

    International Nuclear Information System (INIS)

    Long-term climate experiments up to the year 2300 have been conducted using two full-scale complex Earth system models (ESMs), CESM1(BGC) and MIROC-ESM, for a CO2 emissions reduction pathway, termed Z650, where annual CO2 emissions peak at 11 PgC in 2020, decline by 50% every 30 years, and reach zero in 2160. The results have been examined by focusing on the approximate linear relationship between the temperature increase and cumulative CO2 emissions. Although the temperature increase is nearly proportional to the cumulative CO2 emissions in both models, this relationship does not necessarily provide a robust basis for the restriction of CO2 emissions because it is substantially modulated by non-CO2 forcing. CO2-induced warming, estimated from the atmospheric CO2 concentrations in the models, indicates an approximate compensation of nonlinear changes between fast-mode responses to concentration changes at less than 10 years and slow-mode response at more than 100 years due to the thermal inertia of the ocean. In this estimate, CESM1(BGC) closely approximates a linear trend of 1.7 °C per 1000 PgC, whereas MIROC-ESM shows a deviation toward higher temperatures after the emissions peak, from 1.8 °C to 2.4 °C per 1000 PgC over the range of 400–850 PgC cumulative emissions corresponding to years 2000–2050. The evolution of temperature under zero emissions, 2160–2300, shows a slight decrease of about 0.1 °C per century in CESM1(BGC), but remains almost constant in MIROC-ESM. The fast-mode response toward the equilibrium state decreases with a decrease in the airborne fraction owing to continued CO2 uptake (carbon cycle inertia), whereas the slow-mode response results in more warming owing to continued heat uptake (thermal inertia). Several specific differences are noted between the two models regarding the degree of this compensation and in some key regional aspects associated with sustained warming and long-term climate risks. Overall, elevated temperatures

  4. Indian Ocean warming during 1958-2004 simulated by a climate system model and its mechanism

    Science.gov (United States)

    Dong, Lu; Zhou, Tianjun; Wu, Bo

    2014-01-01

    The mechanism responsible for Indian Ocean Sea surface temperature (SST) basin-wide warming trend during 1958-2004 is studied based on both observational data analysis and numerical experiments with a climate system model FGOALS-gl. To quantitatively estimate the relative contributions of external forcing (anthropogenic and natural forcing) and internal variability, three sets of numerical experiments are conducted, viz. an all forcing run forced by both anthropogenic forcing (greenhouse gases and sulfate aerosols) and natural forcing (solar constant and volcanic aerosols), a natural forcing run driven by only natural forcing, and a pre-industrial control run. The model results are compared to the observations. The results show that the observed warming trend during 1958-2004 (0.5 K (47-year)-1) is largely attributed to the external forcing (more than 90 % of the total trend), while the residual is attributed to the internal variability. Model results indicate that the anthropogenic forcing accounts for approximately 98.8 % contribution of the external forcing trend. Heat budget analysis shows that the surface latent heat flux due to atmosphere and surface longwave radiation, which are mainly associated with anthropogenic forcing, are in favor of the basin-wide warming trend. The basin-wide warming is not spatially uniform, but with an equatorial IOD-like pattern in climate model. The atmospheric processes, oceanic processes and climatological latent heat flux together form an equatorial IOD-like warming pattern, and the oceanic process is the most important in forming the zonal dipole pattern. Both the anthropogenic forcing and natural forcing result in easterly wind anomalies over the equator, which reduce the wind speed, thereby lead to less evaporation and warmer SST in the equatorial western basin. Based on Bjerknes feedback, the easterly wind anomalies uplift the thermocline, which is unfavorable to SST warming in the eastern basin, and contribute to SST

  5. Model confirmation in climate economics.

    Science.gov (United States)

    Millner, Antony; McDermott, Thomas K J

    2016-08-01

    Benefit-cost integrated assessment models (BC-IAMs) inform climate policy debates by quantifying the trade-offs between alternative greenhouse gas abatement options. They achieve this by coupling simplified models of the climate system to models of the global economy and the costs and benefits of climate policy. Although these models have provided valuable qualitative insights into the sensitivity of policy trade-offs to different ethical and empirical assumptions, they are increasingly being used to inform the selection of policies in the real world. To the extent that BC-IAMs are used as inputs to policy selection, our confidence in their quantitative outputs must depend on the empirical validity of their modeling assumptions. We have a degree of confidence in climate models both because they have been tested on historical data in hindcasting experiments and because the physical principles they are based on have been empirically confirmed in closely related applications. By contrast, the economic components of BC-IAMs often rely on untestable scenarios, or on structural models that are comparatively untested on relevant time scales. Where possible, an approach to model confirmation similar to that used in climate science could help to build confidence in the economic components of BC-IAMs, or focus attention on which components might need refinement for policy applications. We illustrate the potential benefits of model confirmation exercises by performing a long-run hindcasting experiment with one of the leading BC-IAMs. We show that its model of long-run economic growth-one of its most important economic components-had questionable predictive power over the 20th century. PMID:27432964

  6. Climate Observing Systems: Data System Challenges

    Science.gov (United States)

    Karl, T. R.

    2001-12-01

    Observing Systems) and GCOS. An international framework is vital. (2) A global telecommunications network and satellite data telemetry capacity to enable data and products to be disseminated. (3) A climate observations analysis capability that produces global and regional analyses of various products for the atmosphere, oceans, land surface and hydrology, and the cryosphere. (4) Four dimensional data assimilation capabilities that process the multivariate data in a physically consistent framework to enable production of the analyses, not just for the atmosphere but also for the oceans, land surface and so on. (5) Global climate models that encompass all parts of the climate system and which are utilized to design effective sampling strategies and evaluate observations. These improvements primarily relate to the data system, after the observation has been made, but they must be accompanied with a concerted effort to improve our instrumentation, platforms, and sampling resolutions for key climate variables. How much would such a data system cost? Practical experience has shown that an effective archive and access system can be designed for about 5 to 10 percent of the total cost of the observing system. Building on a solid investment in data management infrastructure and hardware (including data quality control, access, and long-term stewardship), a comparable investment would be required to address oversight, monitoring, data analysis, data assimilation, and adherence to the ten principles. An implementation time frame on the order of five to ten years is probably a realistic time frame, similar to the planning and implementation horizon of major new observing systems.

  7. The Norwegian Earth System Model, NorESM1-M - Part 1: Description and basic evaluation of the physical climate

    Science.gov (United States)

    Bentsen, M.; Bethke, I.; Debernard, J. B.; Iversen, T.; Kirkevåg, A.; Seland, Ø.; Drange, H.; Roelandt, C.; Seierstad, I. A.; Hoose, C.; Kristjánsson, J. E.

    2013-05-01

    The core version of the Norwegian Climate Center's Earth System Model, named NorESM1-M, is presented. The NorESM family of models are based on the Community Climate System Model version 4 (CCSM4) of the University Corporation for Atmospheric Research, but differs from the latter by, in particular, an isopycnic coordinate ocean model and advanced chemistry-aerosol-cloud-radiation interaction schemes. NorESM1-M has a horizontal resolution of approximately 2° for the atmosphere and land components and 1° for the ocean and ice components. NorESM is also available in a lower resolution version (NorESM1-L) and a version that includes prognostic biogeochemical cycling (NorESM1-ME). The latter two model configurations are not part of this paper. Here, a first-order assessment of the model stability, the mean model state and the internal variability based on the model experiments made available to CMIP5 are presented. Further analysis of the model performance is provided in an accompanying paper (Iversen et al., 2013), presenting the corresponding climate response and scenario projections made with NorESM1-M.

  8. A Drought Early Warning System Using System Dynamics Model and Seasonal Climate Forecasts: a case study in Hsinchu, Taiwan.

    Science.gov (United States)

    Tien, Yu-Chuan; Tung, Ching-Ping; Liu, Tzu-Ming; Lin, Chia-Yu

    2016-04-01

    In the last twenty years, Hsinchu, a county of Taiwan, has experienced a tremendous growth in water demand due to the development of Hsinchu Science Park. In order to fulfill the water demand, the government has built the new reservoir, Baoshan second reservoir. However, short term droughts still happen. One of the reasons is that the water level of the reservoirs in Hsinchu cannot be reasonably forecasted, which sometimes even underestimates the severity of drought. The purpose of this study is to build a drought early warning system that projects the water levels of two important reservoirs, Baoshan and Baoshan second reservoir, and also the spatial distribution of water shortagewith the lead time of three months. Furthermore, this study also attempts to assist the government to improve water resources management. Hence, a system dynamics model of Touchien River, which is the most important river for public water supply in Hsinchu, is developed. The model consists of several important subsystems, including two reservoirs, water treatment plants and agricultural irrigation districts. Using the upstream flow generated by seasonal weather forecasting data, the model is able to simulate the storage of the two reservoirs and the distribution of water shortage. Moreover, the model can also provide the information under certain emergency scenarios, such as the accident or failure of a water treatment plant. At last, the performance of the proposed method and the original water resource management method that the government used were also compared. Keyword: Water Resource Management, Hydrology, Seasonal Climate Forecast, Reservoir, Early Warning, Drought

  9. Simulating Climate Change in Central America Using PRECIS Regional Modeling System

    Science.gov (United States)

    Karmalkar, A. V.; Bradley, R. S.; Diaz, H. F.

    2006-12-01

    Highland tropical forests are rich in endemic species and crucial in maintaining freshwater resources in many regions. Much of their remarkable biodiversity is due to the steep climate gradients found on tropical mountains. These gradients are significantly altered due to warming, affecting many species living on the mountain slopes. Costa Rica's Monteverde Cloud Forest shows biological changes associated with changes in climatic patterns. Our goal is to understand climate change at areas of high relief in the tropics and its potential impacts on ecosystem dynamics. We address this question by focusing on Central America, which is considered to be a biodiversity hotspot. The model used is the UK Hadley Center PRECIS(Providing REgional Climates for Impact Studies) model. The model is based on HadAM3H, an improved version of the atmospheric component of the latest Hadley Center coupled AOGCM, HadCM3 and is forced at the lateral boundaries by HadAM3P GCM. The surface boundary conditions include observed SSTs and sea-ice. We carried out a baseline run (1961-1990) and a doubled CO2 run (SRES A2 2071-2100) at a resolution of 25 km (0.22°) over the region of Central America that includes several biodiversity hotspots. Model verification is performed by comparing control run results with observations and reanalysis data. Preliminary analysis shows that PRECIS has successfully captured present-day spatial and temporal climate variability that has been observed in Central America. Elevation dependency of temperature is one of the important results of this study and will be investigated in great detail. The SRES A2 run shows average warming of about 3K, with more warming at higher altitudes in general. Precipitation and relative humidity analysis shows drier conditions in the region in 2 × CO2 world. Additional techniques are being developed to better quantify model performance in areas of high relief. We plan to expand this project to other models, and to additional

  10. Modelling climate change effects on a Dutch coastal groundwater system using airborne Electro Magnetic measurements

    OpenAIRE

    M. Faneca Sànchez; J. L. Gunnink; E. S. van Baaren; Oude Essink, G.H.P.; B. Siemon; E. Auken; W. Elderhorst; de Louw, P.G.B.

    2012-01-01

    The forecast of climate change effects on the groundwater system in coastal areas is of key importance for policy makers. The Dutch water system has been deeply studied because of its complex system of low-lying areas, dunes, land won to the sea and dikes, but nowadays large efforts are still being done to find out the best techniques to describe complex fresh-brackish-saline groundwater dynamic systems. In this article, we describe a methodology consisting of high-resolution airborne Electro...

  11. Vegetation-climate feedback causes reduced precipitation in CMIP5 regional Earth system model simulation over Africa

    Science.gov (United States)

    Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick

    2013-04-01

    Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and

  12. Impact of stochastic parametrisation schemes on the climate of the Community Earth System Model

    Science.gov (United States)

    Christensen, Hannah; Berner, Judith; Coleman, Dani; Palmer, Tim

    2015-04-01

    Stochastic parametrisations have been used for more than a decade in atmospheric models. They provide a way to represent model uncertainty through representing the variability of unresolved sub-grid processes, and have been shown to have a beneficial effect on the spread and mean state for medium- and extended-range forecasts (Buizza et al. 1999, Palmer et al. 2009). There is also increasing evidence that stochastic parametrisation of unresolved processes could be beneficial for the climate of an atmospheric model. There is evidence that including stochastic physics can reduce model biases through noise-induced drift (nonlinear rectification) (Berner et al. 2008), and that including stochastic physics enables the climate simulator to explore other flow regimes (Christensen et al. 2014; Dawson and Palmer 2014). It is also possible that, through representing the variability of unresolved sub-grid processes, stochastic parametrisation schemes could improve the internal variability of a model's climate. We present results showing the impact of including the Stochastic Kinetic Energy Backscatter Scheme (SKEBS) and the Stochastically Perturbed Parametrisation Tendencies scheme (SPPT) in coupled runs of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4) with historical forcing. The impact of the schemes in the coupled runs is compared to the impact in a similar set of AMIP runs. Both schemes have a beneficial impact on the model climate. The SKEBS scheme significantly reduces mean biases in several fields whereas SPPT results in a significant improvement in the variability of the modeled climate. In particular, SPPT results in a significant improvement to the representation of the El Nino-Southern Oscillation in CAM4, improving the power spectrum, as well as both the inter- and intra-annual variability of tropical pacific sea surface temperatures. References: Berner, J., Doblas-Reyes, F. J., Palmer, T. N., Shutts, G. J

  13. Studying Uncertainties in Climate-Terrestrial Biogeochemical Feedbacks in the Northern High Latitudes using a Flexible Earth System Modeling Framework

    Science.gov (United States)

    Barman, R.; Hoffman, F. M.; Lawrence, D. M.; Song, Y.; Meiyappan, P.; Jain, A. K.; Jacob, R. L.; Vertenstein, M.

    2011-12-01

    Uncertainties in the representation of terrestrial biogeochemistry in land surface models (LSMs), together with their long spin-up time requirements, contribute to the many challenges inherent in coupled Earth system models (ESMs). Here we present a recently developed ESM framework, designed to incorporate multiple LSMs into an existing ESM. This ISAM-CESM framework provides an alternative LSM, the Integrated Science Assessment Model (ISAM), coupled to the NCAR Community Earth System Model (CESM1). The purpose of this general modeling framework is to carry out equivalent climate simulations using multiple LSMs with the rest of the component models being the same, allowing a more direct comparison of the effects of different land surface representations on corresponding feedbacks to climate change. In this presentation, we will analyze the role of different biogeochemistry representations and the effects of different land surface processes on climate-carbon cycle feedbacks using the ISAM and the NCAR Community Land Model (CLM4), the two LSMs currently available in the ISAM-CESM framework. Both ISAM and CLM4 contain fully prognostic, coupled carbon-nitrogen models, integrated with detailed representation of terrestrial biogeophysics. Biogeophysical schemes in the ISAM have been adapted from the CLM4, its precursor CLM3.5, and the Common Land Model (CoLM); however, the representation of the biogeochemistry of carbon nitrogen cycles are structurally different in the two models, making them suitable for inter-comparison. The aim of this study is to understand those differences and better attribute their roles in varying responses of the land surface to future climate change. We will compare the 20th century predictions of gross primary productivity (GPP) and annual cycle of CO2 from offline land simulations of ISAM and CLM4, using the newly available CRU-NCEP climate forcing data, in the CESM1 modeling framework to study the response of alternate land surface models

  14. Modelling for water supply of irrigated cropping systems on climate change

    OpenAIRE

    Pasquale Campi; Alejandra Navarro; Luisa Giglio; Angelo D. Palumbo; Marcello Mastrorilli

    2012-01-01

    The vulnerability of Mediterranean environment due to climatic changes makes necessary to define the effects of the increase of CO2 atmospheric concentration and the consequent alterations of temperature and precipitation variations upon the processes which regulate the plants’ water supply. The traditional research can not meet the needs of this information because of the difficulty of carrying out the experiments. Therefore, it is necessary to use models based upon mathematical representati...

  15. Numerical climate modeling and verification of selected areas for heat waves of Pakistan using ensemble prediction system

    International Nuclear Information System (INIS)

    Depending upon the topography, there is an extreme variation in the temperature of Pakistan. Heat waves are the Weather-related events, having significant impact on the humans, including all socioeconomic activities and health issues as well which changes according to the climatic conditions of the area. The forecasting climate is of prime importance for being aware of future climatic changes, in order to mitigate them. The study used the Ensemble Prediction System (EPS) for the purpose of modeling seasonal weather hind-cast of three selected areas i.e., Islamabad, Jhelum and Muzaffarabad. This research was purposely carried out in order to suggest the most suitable climate model for Pakistan. Real time and simulated data of five General Circulation Models i.e., ECMWF, ERA-40, MPI, Meteo France and UKMO for selected areas was acquired from Pakistan Meteorological Department. Data incorporated constituted the statistical temperature records of 32 years for the months of June, July and August. This study was based on EPS to calculate probabilistic forecasts produced by single ensembles. Verification was done out to assess the quality of the forecast t by using standard probabilistic measures of Brier Score, Brier Skill Score, Cross Validation and Relative Operating Characteristic curve. The results showed ECMWF the most suitable model for Islamabad and Jhelum; and Meteo France for Muzaffarabad. Other models have significant results by omitting particular initial conditions.

  16. Philosophy of climate science part II: modelling climate change

    OpenAIRE

    Frigg, Roman; Thompson, Erica; Werndl, Charlotte

    2015-01-01

    This is the second of three parts of an introduction to the philosophy of climate science. In this second part about modelling climate change, the topics of climate modelling, confirmation of climate models, the limits of climate projections, uncertainty and finally model ensembles will be discussed.

  17. Final Report on Evaluating the Representation and Impact of Convective Processes in the NCAR Community Climate System Model

    Energy Technology Data Exchange (ETDEWEB)

    X. Wu, G. J. Zhang

    2008-04-23

    Convection and clouds affect atmospheric temperature, moisture and wind fields through the heat of condensation and evaporation and through redistributions of heat, moisture and momentum. Individual clouds have a spatial scale of less than 10 km, much smaller than the grid size of several hundred kilometers used in climate models. Therefore the effects of clouds must be approximated in terms of variables that the model can resolve. Deriving such formulations for convection and clouds has been a major challenge for the climate modeling community due to the lack of observations of cloud and microphysical properties. The objective of our DOE CCPP project is to evaluate and improve the representation of convection schemes developed by PIs in the NCAR (National Center for Atmospheric Research) Community Climate System Model (CCSM) and study its impact on global climate simulations. • The project resulted in nine peer-reviewed publications and numerous scientific presentations that directly address the CCPP’s scientific objective of improving climate models. • We developed a package of improved convection parameterization that includes improved closure, trigger condition for convection, and comprehensive treatment of convective momentum transport. • We implemented the new convection parameterization package into several versions of the NCAR models (both coupled and uncoupled). This has led to 1) Improved simulation of seasonal migration of ITCZ; 2) Improved shortwave cloud radiative forcing response to El Niño in CAM3; 3) Improved MJO simulation in both uncoupled and coupled model; and 4) Improved simulation of ENSO in coupled model. • Using the dynamic core of CCM3, we isolated the dynamic effects of convective momentum transport. • We implemented mosaic treatment of subgrid-scale cloud-radiation interaction in CCM3.

  18. Informing energy and climate policies using energy systems models insights from scenario analysis increasing the evidence base

    CERN Document Server

    Giannakidis, George; Ó Gallachóir, Brian; Tosato, GianCarlo

    2015-01-01

    This book highlights how energy-system models are used to underpin and support energy and climate mitigation policy decisions at national, multi-country and global levels. It brings together, for the first time in one volume, a range of methodological approaches and case studies of good modeling practice on a national and international scale from the IEA-ETSAP energy technology initiative. It provides insights for the reader into the rich and varied applications of energy-system models and the underlying methodologies and policy questions they can address. The book demonstrates how these mode

  19. Multi crop model climate risk country-level management design: case study on the Tanzanian maize production system

    Science.gov (United States)

    Chavez, E.

    2015-12-01

    Future climate projections indicate that a very serious consequence of post-industrial anthropogenic global warming is the likelihood of the greater frequency and intensity of extreme hydrometeorological events such as heat waves, droughts, storms, and floods. The design of national and international policies targeted at building more resilient and environmentally sustainable food systems needs to rely on access to robust and reliable data which is largely absent. In this context, the improvement of the modelling of current and future agricultural production losses using the unifying language of risk is paramount. In this study, we use a methodology that allows the integration of the current understanding of the various interacting systems of climate, agro-environment, crops, and the economy to determine short to long-term risk estimates of crop production loss, in different environmental, climate, and adaptation scenarios. This methodology is applied to Tanzania to assess optimum risk reduction and maize production increase paths in different climate scenarios. The simulations carried out use inputs from three different crop models (DSSAT, APSIM, WRSI) run in different technological scenarios and thus allowing to estimate crop model-driven risk exposure estimation bias. The results obtained also allow distinguishing different region-specific optimum climate risk reduction policies subject to historical as well as RCP2.5 and RCP8.5 climate scenarios. The region-specific risk profiles obtained provide a simple framework to determine cost-effective risk management policies for Tanzania and allow to optimally combine investments in risk reduction and risk transfer.

  20. The Med-CORDEX initiative: towards fully coupled Regional Climate System Models to study the Mediterranean climate variability, change and impact

    Science.gov (United States)

    Somot, S.; Ruti, P.

    2012-04-01

    The Mediterranean region is considered as particularly vulnerable to climate variability and change (Giorgi, 2006; IPCC, 2007), in particular, to changes in its regional water cycle. This climate vulnerability is a key issue for the 500 million inhabitants living in the 30 Mediterranean countries. In addition, the Mediterranean basin is a good case study for climate regionalization. It is indeed surrounded by various and complex topography channelling regional winds (Mistral, Tramontane, Bora, Etesian, Sirocco) than defined local climate. Many small-size islands limit the low-level air flow and its coastline is particularly complex. Strong land-sea contrast, land-atmosphere feedback, intense air-sea coupling and aerosol-radiation interaction are also among the regional characteristics to take into account when dealing with the Mediterranean climate modeling. What is true for the Mediterranean climate is also true for the Mediterranean Sea that show complex bathymetry including narrow and shallow straits, a strong eddy activity and various distinct and interacting water masses. For all these reasons, the Mediterranean area has been chosen as a CORDEX sub-domain (MED) leading to the Med-CORDEX initiative endorsed by Med-CLIVAR and HyMeX. In addition to the core CORDEX framework (Atmosphere-RCM, 50 km, ERA-Interim, RCP4.5, RCP8.5), two more tiers have been defined for Med-CORDEX. The first one would like to assess the added-value of higher-resolution RCMs pushing the horizontal resolution up to 10 km. The second one will serve to test new regional climate modeling tools called Regional Climate System Models (RCSM) including a high-resolution and coupled representation of all the physical components of the regional climate system: atmosphere, land surface, vegetation, surface hydrology, rivers and ocean. In addition, the Med-CORDEX initiative is strongly coordinated with the HyMeX program that plans large field campaigns within the area of interest, development of new

  1. Climate variability and predictability associated with the Indo-Pacific Oceanic Channel Dynamics in the CCSM4 Coupled System Model

    Science.gov (United States)

    Yuan, Dongliang; Xu, Peng; Xu, Tengfei

    2016-03-01

    An experiment using the Community Climate System Model (CCSM4), a participant of the Coupled Model Intercomparison Project phase-5 (CMIP5), is analyzed to assess the skills of this model in simulating and predicting the climate variabilities associated with the oceanic channel dynamics across the Indo-Pacific Oceans. The results of these analyses suggest that the model is able to reproduce the observed lag correlation between the oceanic anomalies in the southeastern tropical Indian Ocean and those in the cold tongue in the eastern equatorial Pacific Ocean at a time lag of 1 year. This success may be largely attributed to the successful simulation of the interannual variations of the Indonesian Throughflow, which carries the anomalies of the Indian Ocean Dipole (IOD) into the western equatorial Pacific Ocean to produce subsurface temperature anomalies, which in turn propagate to the eastern equatorial Pacific to generate ENSO. This connection is termed the "oceanic channel dynamics" and is shown to be consistent with the observational analyses. However, the model simulates a weaker connection between the IOD and the interannual variability of the Indonesian Throughflow transport than found in the observations. In addition, the model overestimates the westerly wind anomalies in the western-central equatorial Pacific in the year following the IOD, which forces unrealistic upwelling Rossby waves in the western equatorial Pacific and downwelling Kelvin waves in the east. This assessment suggests that the CCSM4 coupled climate system has underestimated the oceanic channel dynamics and overestimated the atmospheric bridge processes.

  2. It might take three: proxy system models as the missing link between proxies and climate models, and their potential for paleoclimate data assimilation

    Science.gov (United States)

    Dee, S. G.; Steiger, N. J.; Emile-Geay, J.; Hakim, G. J.

    2015-12-01

    In recent years, data assimilation (DA) has emerged as a competitive method for climate field reconstruction (CFR). DA blends information from climate models with proxy observations to estimate the most plausible climate state that could have given rise to a set of observations, together with uncertainties about this state. The DA framework allows one to explicitly represent proxy complexity via proxy system models (PSMs), which are physically-based, potentially nonlinear models of proxy systems. In contrast, most (regression-based) CFR approaches make a number of strong assumptions that may not be met in practice, including the use of linear temperature-proxy relationships, or ignoring the confounding effects of dating uncertainties in proxy data. In this study, we combine DA-based CFR techniques with proxy system modeling (PSM) to investigate uncertainties that arise as a result of these assumptions. We use PSM-generated pseudoproxy experiments to address three questions: (1) how much information is lost assuming proxies are linear, univariate responders to temperature? (2) does a misspecified proxy system contribute to poor climatic interpretations? and (3) given perfectly constrained proxy system parameters, what is the role of age uncertainties in blurring the retrieved climate signal? We find that employing linearized models for complex proxy systems contributes to substantial information loss in climate field reconstructions, while other complications (including age uncertainties) may not prove as problematic in a multi-proxy framework. We investigate the utility of embedding PSMs in DA techniques for paleoclimate state estimation, and use them to explore new uncertainties in paleodata-model comparison associated with linearity and nonstationarity. Implications for the potential of paleoclimate reanalyses are discussed.

  3. Simulations of Tornadoes, Tropical Cyclones, MJOs, and QBOs, using GFDL's multi-scale global climate modeling system

    Science.gov (United States)

    Lin, Shian-Jiann; Harris, Lucas; Chen, Jan-Huey; Zhao, Ming

    2014-05-01

    A multi-scale High-Resolution Atmosphere Model (HiRAM) is being developed at NOAA/Geophysical Fluid Dynamics Laboratory. The model's dynamical framework is the non-hydrostatic extension of the vertically Lagrangian finite-volume dynamical core (Lin 2004, Monthly Wea. Rev.) constructed on a stretchable (via Schmidt transformation) cubed-sphere grid. Physical parametrizations originally designed for IPCC-type climate predictions are in the process of being modified and made more "scale-aware", in an effort to make the model suitable for multi-scale weather-climate applications, with horizontal resolution ranging from 1 km (near the target high-resolution region) to as low as 400 km (near the antipodal point). One of the main goals of this development is to enable simulation of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously thought impossible. We will present preliminary results, covering a very wide spectrum of temporal-spatial scales, ranging from simulation of tornado genesis (hours), Madden-Julian Oscillations (intra-seasonal), topical cyclones (seasonal), to Quasi Biennial Oscillations (intra-decadal), using the same global multi-scale modeling system.

  4. Fully coupled ice sheet-earth system model: How does the Greenlandic ice sheet interact in a changing climate

    Science.gov (United States)

    Rodehacke, C.; Mikolajewicz, U.; Vizcaino, M.

    2012-04-01

    As ice sheets belong to the slowest climate components, they are usually not interactively coupled in current climate models. Therefore, long-term climate projections are incomplete and only the consideration of ice sheet interactions allows tackling fundamental questions, such as how do ice sheets modify the reaction of the climate systems under a strong CO2 forcing? The earth system model MPI-ESM, with the atmosphere model ECHAM6 and ocean model MPIOM, is coupled to the modified ice sheet model PISM. This ice sheet model, which is developed at the University of Fairbanks, represents the ice sheet of Greenland at a horizontal resolution of 10 km. The coupling is performed by calculating the surface mass balance based on 6-hourly atmospheric data to determine the boundary condition for the ice sheet model. The response of the ice sheet to this forcing, which includes orographic changes and fresh water fluxes, are passed back to the ESM. In contrast to commonly used strategies, we use a mass conserving scheme and do therefore neither apply flux corrections nor utilize anomaly coupling. Under a strong CO2 forcing a disintegrating Greenlandic ice sheet contributes to a rising sea level and has the potential to alter the formation of deep water masses in the adjacent formation sites Labrador Sea and Nordic Seas. We will present results for an idealized forcing with a growing atmospheric CO2 concentration that rises by 1% per year until four-times the pre-industrial level has been reached. We will discuss the reaction of the ice sheet and immediate responses of the ocean to ice loss.

  5. Variation of Surface Temperature during the Last Millennium in a Simulation with the FGOALS-g1 Climate System Model

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jie; Laurent LI; ZHOU Tianjun; XIN Xiaoge

    2013-01-01

    A reasonable past millennial climate simulation relies heavily on the specified external forcings,including both natural and anthropogenic forcing agents.In this paper,we examine the surface temperature responses to specified external forcing agents in a millennium-scale transient climate simulation with the fast version of LASG IAP Flexible Global Ocean-Atmosphere-Land System model (FGOALS-gl) developed in the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics (LASG/IAP).The model presents a reasonable performance in comparison with reconstructions of surface temperature.Differentiated from significant changes in the 20th century at the global scale,changes during the natural-forcing-dominant period are mainly manifested in the Northern Hemisphere.Seasonally,modeled significant changes are more pronounced during the wintertime at higher latitudes.This may be a manifestation of polar amplification associated with sea-ice-temperature positive feedback.The climate responses to total external forcings can explain about half of the climate variance during the whole millennium period,especially at decadal timescales.Surface temperature in the Antarctic shows heterogeneous and insignificant changes during the preindustrial period and the climate response to external forcings is undetectable due to the strong internal variability.The model response to specified external forcings is modulated by cloud radiative forcing (CRF).The CRF acts against the fluctuations of external forcings.Effects of clouds are manifested in shortwave radiation by changes in cloud water during the natural-forcing-dominant period,but mainly in longwave radiation by a decrease in cloud amount in the anthropogenic-forcing-dominant period.

  6. The CSIRO Mk3L climate system model version 1.0 – Part 2: Response to external forcings

    Directory of Open Access Journals (Sweden)

    S. J. Phipps

    2012-05-01

    Full Text Available The CSIRO Mk3L climate system model is a coupled general circulation model, designed primarily for millennial-scale climate simulation and palaeoclimate research. Mk3L includes components which describe the atmosphere, ocean, sea ice and land surface, and combines computational efficiency with a stable and realistic control climatology. It is freely available to the research community. This paper evaluates the response of the model to external forcings which correspond to past and future changes in the climate system.

    A simulation of the mid-Holocene climate is performed, in which changes in the seasonal and meridional distribution of incoming solar radiation are imposed. Mk3L correctly simulates increased summer temperatures at northern mid-latitudes and cooling in the tropics. However, it is unable to capture some of the regional-scale features of the mid-Holocene climate, with the precipitation over Northern Africa being deficient. The model simulates a reduction of between 7 and 15% in the amplitude of El Niño-Southern Oscillation, a smaller decrease than that implied by the palaeoclimate record. However, the realism of the simulated ENSO is limited by the model's relatively coarse spatial resolution.

    Transient simulations of the late Holocene climate are then performed. The evolving distribution of insolation is imposed, and an acceleration technique is applied and assessed. The model successfully captures the temperature changes in each hemisphere and the upward trend in ENSO variability. However, the lack of a dynamic vegetation scheme does not allow it to simulate an abrupt desertification of the Sahara.

    To assess the response of Mk3L to other forcings, transient simulations of the last millennium are performed. Changes in solar irradiance, atmospheric greenhouse gas concentrations and volcanic emissions are applied to the model. The model is again broadly successful at simulating larger-scale changes in the

  7. The CSIRO Mk3L climate system model version 1.0 – Part 2: Response to external forcings

    Directory of Open Access Journals (Sweden)

    A. C. Hirst

    2011-12-01

    Full Text Available The CSIRO Mk3L climate system model is a coupled general circulation model, designed primarily for millennial-scale climate simulation and palaeoclimate research. Mk3L includes components which describe the atmosphere, ocean, sea ice and land surface, and combines computational efficiency with a stable and realistic control climatology. It is freely available to the research community. This paper evaluates the response of the model to external forcings which correspond to past and future changes in the climate system. A simulation of the mid-Holocene climate is performed, in which changes in the seasonal and meridional distribution of incoming solar radiation are imposed. Mk3L correctly simulates increased summer temperatures at northern mid-latitudes and cooling in the tropics. However, it is unable to capture some of the regional-scale features of the mid-Holocene climate, with the precipitation over Northern Africa being deficient. The model simulates a reduction of between 7 and 15% in the amplitude of El Niño-Southern Oscillation, a smaller decrease than that implied by the palaeoclimate record. However, the realism of the simulated ENSO is limited by the model's relatively coarse spatial resolution. Transient simulations of the late Holocene climate are then performed. The evolving distribution of insolation is imposed, and an acceleration technique is applied and assessed. The model successfully captures the temperature changes in each hemisphere and the upward trend in ENSO variability. However, the lack of a dynamic vegetation scheme does not allow it to simulate an abrupt desertification of the Sahara. To assess the response of Mk3L to other forcings, transient simulations of the last millennium are performed. Changes in solar irradiance, atmospheric greenhouse gas concentrations and volcanic emissions are applied to the model. The model is again broadly successful at simulating larger-scale changes in the climate system. Both the

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

    CERN Document Server

    Mihailović, Dragutin T; Arsenić, Ilija

    2013-01-01

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

  9. Applying a System Dynamics Approach for Modeling Groundwater Dynamics to Depletion under Different Economical and Climate Change Scenarios

    Directory of Open Access Journals (Sweden)

    Hamid Balali

    2015-09-01

    Full Text Available In the recent decades, due to many different factors, including climate change effects towards be warming and lower precipitation, as well as some structural policies such as more intensive harvesting of groundwater and low price of irrigation water, the level of groundwater has decreased in most plains of Iran. The objective of this study is to model groundwater dynamics to depletion under different economic policies and climate change by using a system dynamics approach. For this purpose a dynamic hydro-economic model which simultaneously simulates the farmer’s economic behavior, groundwater aquifer dynamics, studied area climatology factors and government economical policies related to groundwater, is developed using STELLA 10.0.6. The vulnerability of groundwater balance is forecasted under three scenarios of climate including the Dry, Nor and Wet and also, different scenarios of irrigation water and energy pricing policies. Results show that implementation of some economic policies on irrigation water and energy pricing can significantly affect on groundwater exploitation and its volume balance. By increasing of irrigation water price along with energy price, exploitation of groundwater will improve, in so far as in scenarios S15 and S16, studied area’s aquifer groundwater balance is positive at the end of planning horizon, even in Dry condition of precipitation. Also, results indicate that climate change can affect groundwater recharge. It can generally be expected that increases in precipitation would produce greater aquifer recharge rates.

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

    Science.gov (United States)

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

    2015-07-01

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

  11. An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

    Science.gov (United States)

    Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

    2015-07-15

    The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. PMID:25829290

  12. Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil

    Science.gov (United States)

    Lowe, Rachel; Bailey, Trevor C.; Stephenson, David B.; Graham, Richard J.; Coelho, Caio A. S.; Sá Carvalho, Marilia; Barcellos, Christovam

    2011-03-01

    This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a 2.5°×2.5° longitude-latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil.

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

    Directory of Open Access Journals (Sweden)

    B. Poulter

    2015-01-01

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

  14. Application of global weather and climate model output to the design and operation of wind-energy systems

    Energy Technology Data Exchange (ETDEWEB)

    Curry, Judith [Climate Forecast Applications Network, Atlanta, GA (United States)

    2015-05-21

    This project addressed the challenge of providing weather and climate information to support the operation, management and planning for wind-energy systems. The need for forecast information is extending to longer projection windows with increasing penetration of wind power into the grid and also with diminishing reserve margins to meet peak loads during significant weather events. Maintenance planning and natural gas trading is being influenced increasingly by anticipation of wind generation on timescales of weeks to months. Future scenarios on decadal time scales are needed to support assessment of wind farm siting, government planning, long-term wind purchase agreements and the regulatory environment. The challenge of making wind forecasts on these longer time scales is associated with a wide range of uncertainties in general circulation and regional climate models that make them unsuitable for direct use in the design and planning of wind-energy systems. To address this challenge, CFAN has developed a hybrid statistical/dynamical forecasting scheme for delivering probabilistic forecasts on time scales from one day to seven months using what is arguably the best forecasting system in the world (European Centre for Medium Range Weather Forecasting, ECMWF). The project also provided a framework to assess future wind power through developing scenarios of interannual to decadal climate variability and change. The Phase II research has successfully developed an operational wind power forecasting system for the U.S., which is being extended to Europe and possibly Asia.

  15. Integrated numerical modeling of a landslide early warning system in a context of adaptation to future climatic pressures

    Science.gov (United States)

    Khabarov, Nikolay; Huggel, Christian; Obersteiner, Michael; Ramírez, Juan Manuel

    2010-05-01

    Mountain regions are typically characterized by rugged terrain which is susceptible to different types of landslides during high-intensity precipitation. Landslides account for billions of dollars of damage and many casualties, and are expected to increase in frequency in the future due to a projected increase of precipitation intensity. Early warning systems (EWS) are thought to be a primary tool for related disaster risk reduction and climate change adaptation to extreme climatic events and hydro-meteorological hazards, including landslides. An EWS for hazards such as landslides consist of different components, including environmental monitoring instruments (e.g. rainfall or flow sensors), physical or empirical process models to support decision-making (warnings, evacuation), data and voice communication, organization and logistics-related procedures, and population response. Considering this broad range, EWS are highly complex systems, and it is therefore difficult to understand the effect of the different components and changing conditions on the overall performance, ultimately being expressed as human lives saved or structural damage reduced. In this contribution we present a further development of our approach to assess a landslide EWS in an integral way, both at the system and component level. We utilize a numerical model using 6 hour rainfall data as basic input. A threshold function based on a rainfall-intensity/duration relation was applied as a decision criterion for evacuation. Damage to infrastructure and human lives was defined as a linear function of landslide magnitude, with the magnitude modelled using a power function of landslide frequency. Correct evacuation was assessed with a ‘true' reference rainfall dataset versus a dataset of artificially reduced quality imitating the observation system component. Performance of the EWS using these rainfall datasets was expressed in monetary terms (i.e. damage related to false and correct evacuation). We

  16. GEOCLIM reloaded (v 1.0): a new coupled earth system model for past climate change

    OpenAIRE

    S. Arndt; Regnier, P.; Y. Goddéris; Y. Donnadieu

    2011-01-01

    We present a new version of the coupled Earth system model GEOCLIM. The new release, GEOCLIM reloaded (v 1.0), links the existing atmosphere and weathering modules to a novel, temporally and spatially resolved model of the global ocean circulation, which provides a physical framework for a mechanistic description of the marine biogeochemical dynamics of carbon, nitrogen, phosphorus and oxygen. The ocean model is also coupled to a fully formulated, vertically resolved diagenetic model. GEOCLIM...

  17. Modelling nitrous oxide emissions from organic and conventional cereal-based cropping systems under different management, soil and climate factors

    DEFF Research Database (Denmark)

    Doltra, J; Olesen, Jørgen E; Báez, D;

    2015-01-01

    Mitigation of greenhouse gas emissions from agriculture should be assessed across cropping systems and agroclimatic regions. In this study, we investigate the ability of the FASSET model to analyze differences in the magnitude of N2O emissions due to soil, climate and management factors in cereal......-based cropping systems. Forage maize was grown in a conventional dairy system at Mabegondo (NW Spain) and wheat and barley in organic and conventional crop rotations at Foulum (NW Denmark). These two European sites represent agricultural areas with high and low to moderate emission levels, respectively. Field...... static chamber method with more frequent measurements post-fertilization and biweekly measurements when high fluxes were not expected. All cropping systems were simulated with the FASSET version 2.5 simulation model. Cumulative soil seasonal N2O emissions were about ten-fold higher at Mabegondo than at...

  18. Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system

    International Nuclear Information System (INIS)

    This study is the first evaluation of dynamical downscaling using the Weather Research and Forecasting (WRF) Model on a 4 km × 4 km high resolution scale in the eastern US driven by the new Community Earth System Model version 1.0 (CESM v1.0). First we examined the global and regional climate model results, and corrected an inconsistency in skin temperature during the downscaling process by modifying the land/sea mask. In comparison with observations, WRF shows statistically significant improvement over CESM in reproducing extreme weather events, with improvement for heat wave frequency estimation as high as 98%. The fossil fuel intensive scenario Representative Concentration Pathway (RCP) 8.5 was used to study a possible future mid-century climate extreme in 2057–9. Both the heat waves and the extreme precipitation in 2057–9 are more severe than the present climate in the Eastern US. The Northeastern US shows large increases in both heat wave intensity (3.05 °C higher) and annual extreme precipitation (107.3 mm more per year). (letter)

  19. Role of the hydrological cycle in regulating the planetary climate system of a simple nonlinear dynamical model

    Directory of Open Access Journals (Sweden)

    K. M. Nordstrom

    2005-01-01

    Full Text Available We present the construction of a dynamic area fraction model (DAFM, representing a new class of models for an earth-like planet. The model presented here has no spatial dimensions, but contains coupled parameterizations for all the major components of the hydrological cycle involving liquid, solid and vapor phases. We investigate the nature of feedback processes with this model in regulating Earth's climate as a highly nonlinear coupled system. The model includes solar radiation, evapotranspiration from dynamically competing trees and grasses, an ocean, an ice cap, precipitation, dynamic clouds, and a static carbon greenhouse effect. This model therefore shares some of the characteristics of an Earth System Model of Intermediate complexity. We perform two experiments with this model to determine the potential effects of positive and negative feedbacks due to a dynamic hydrological cycle, and due to the relative distribution of trees and grasses, in regulating global mean temperature. In the first experiment, we vary the intensity of insolation on the model's surface both with and without an active (fully coupled water cycle. In the second, we test the strength of feedbacks with biota in a fully coupled model by varying the optimal growing temperature for our two plant species (trees and grasses. We find that the negative feedbacks associated with the water cycle are far more powerful than those associated with the biota, but that the biota still play a significant role in shaping the model climate. third experiment, we vary the heat and moisture transport coefficient in an attempt to represent changing atmospheric circulations.

  20. Assessment of malaria transmission changes in Africa, due to the climate impact of land use change using Coupled Model Intercomparison Project Phase 5 earth system models.

    Science.gov (United States)

    Tompkins, Adrian M; Caporaso, Luca

    2016-01-01

    Using mathematical modelling tools, we assessed the potential for land use change (LUC) associated with the Intergovernmental Panel on Climate Change low- and high-end emission scenarios (RCP2.6 and RCP8.5) to impact malaria transmission in Africa. To drive a spatially explicit, dynamical malaria model, data from the four available earth system models (ESMs) that contributed to the LUC experiment of the Fifth Climate Model Intercomparison Project are used. Despite the limited size of the ESM ensemble, stark differences in the assessment of how LUC can impact climate are revealed. In three out of four ESMs, the impact of LUC on precipitation and temperature over the next century is limited, resulting in no significant change in malaria transmission. However, in one ESM, LUC leads to increases in precipitation under scenario RCP2.6, and increases in temperature in areas of land use conversion to farmland under both scenarios. The result is a more intense transmission and longer transmission seasons in the southeast of the continent, most notably in Mozambique and southern Tanzania. In contrast, warming associated with LUC in the Sahel region reduces risk in this model, as temperatures are already above the 25-30°C threshold at which transmission peaks. The differences between the ESMs emphasise the uncertainty in such assessments. It is also recalled that the modelling framework is unable to adequately represent local-scale changes in climate due to LUC, which some field studies indicate could be significant. PMID:27063732

  1. An experimental seasonal hydrological forecasting system over the Yellow River basin - Part 2: The added value from climate forecast models

    Science.gov (United States)

    Yuan, Xing

    2016-06-01

    This is the second paper of a two-part series on introducing an experimental seasonal hydrological forecasting system over the Yellow River basin in northern China. While the natural hydrological predictability in terms of initial hydrological conditions (ICs) is investigated in a companion paper, the added value from eight North American Multimodel Ensemble (NMME) climate forecast models with a grand ensemble of 99 members is assessed in this paper, with an implicit consideration of human-induced uncertainty in the hydrological models through a post-processing procedure. The forecast skill in terms of anomaly correlation (AC) for 2 m air temperature and precipitation does not necessarily decrease over leads but is dependent on the target month due to a strong seasonality for the climate over the Yellow River basin. As there is more diversity in the model performance for the temperature forecasts than the precipitation forecasts, the grand NMME ensemble mean forecast has consistently higher skill than the best single model up to 6 months for the temperature but up to 2 months for the precipitation. The NMME climate predictions are downscaled to drive the variable infiltration capacity (VIC) land surface hydrological model and a global routing model regionalized over the Yellow River basin to produce forecasts of soil moisture, runoff and streamflow. And the NMME/VIC forecasts are compared with the Ensemble Streamflow Prediction method (ESP/VIC) through 6-month hindcast experiments for each calendar month during 1982-2010. As verified by the VIC offline simulations, the NMME/VIC is comparable to the ESP/VIC for the soil moisture forecasts, and the former has higher skill than the latter only for the forecasts at long leads and for those initialized in the rainy season. The forecast skill for runoff is lower for both forecast approaches, but the added value from NMME/VIC is more obvious, with an increase of the average AC by 0.08-0.2. To compare with the observed

  2. Ragweed pollen production and dispersion modelling within a regional climate system, calibration and application over Europe

    Science.gov (United States)

    Liu, Li; Solmon, Fabien; Vautard, Robert; Hamaoui-Laguel, Lynda; Zsolt Torma, Csaba; Giorgi, Filippo

    2016-05-01

    Common ragweed (Ambrosia artemisiifolia L.) is a highly allergenic and invasive plant in Europe. Its pollen can be transported over large distances and has been recognized as a significant cause of hay fever and asthma (D'Amato et al., 2007; Burbach et al., 2009). To simulate production and dispersion of common ragweed pollen, we implement a pollen emission and transport module in the Regional Climate Model (RegCM) version 4 using the framework of the Community Land Model (CLM) version 4.5. In this online approach pollen emissions are calculated based on the modelling of plant distribution, pollen production, species-specific phenology, flowering probability, and flux response to meteorological conditions. A pollen tracer model is used to describe pollen advective transport, turbulent mixing, dry and wet deposition. The model is then applied and evaluated on a European domain for the period 2000-2010. To reduce the large uncertainties notably due to the lack of information on ragweed density distribution, a calibration based on airborne pollen observations is used. Accordingly a cross validation is conducted and shows reasonable error and sensitivity of the calibration. Resulting simulations show that the model captures the gross features of the pollen concentrations found in Europe, and reproduce reasonably both the spatial and temporal patterns of flowering season and associated pollen concentrations measured over Europe. The model can explain 68.6, 39.2, and 34.3 % of the observed variance in starting, central, and ending dates of the pollen season with associated root mean square error (RMSE) equal to 4.7, 3.9, and 7.0 days, respectively. The correlation between simulated and observed daily concentrations time series reaches 0.69. Statistical scores show that the model performs better over the central Europe source region where pollen loads are larger and the model is better constrained. From these simulations health risks associated to common ragweed pollen

  3. Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis

    Directory of Open Access Journals (Sweden)

    L. M. Verheijen

    2013-08-01

    Full Text Available In many current dynamic global vegetation models (DGVMs, including those incorporated into Earth system models (ESMs, terrestrial vegetation is represented by a small number of plant functional types (PFTs, each with fixed properties irrespective of their predicted occurrence. This contrasts with natural vegetation, in which many plant traits vary systematically along geographic and environmental gradients. In the JSBACH DGVM, which is part of the MPI-ESM, we allowed three traits (specific leaf area (SLA, maximum carboxylation rate at 25 °C (Vcmax25 and maximum electron transport rate at 25 °C (Jmax25 to vary within PFTs via trait–climate relationships based on a large trait database. The R2adjusted of these relationships were up to 0.83 and 0.71 for Vcmax25 and Jmax25, respectively. For SLA, more variance remained unexplained, with a maximum R2adjusted of 0.40. Compared to the default simulation, allowing trait variation within PFTs resulted in gross primary productivity differences of up to 50% in the tropics, in > 35% different dominant vegetation cover, and a closer match with a natural vegetation map. The discrepancy between default trait values and natural trait variation, combined with the substantial changes in simulated vegetation properties, together emphasize that incorporating climate-driven trait variation, calibrated on observational data and based on ecological concepts, allows more variation in vegetation responses in DGVMs and as such is likely to enable more reliable projections in unknown climates.

  4. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate...... existing climate and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and...... the land surface. The modelling tool consists of a fully dynamic two-way coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model. The expected gain is twofold. Firstly, HIRHAM utilizes the land surface component of the combined MIKE SHE/SWET hydrology and land surface model...

  5. Do regional climate models represent regional climate?

    Science.gov (United States)

    Maraun, Douglas; Widmann, Martin

    2014-05-01

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

  6. Formulation of a reduced order model of the climatic system by combining classical simulation methods with artificial intelligence techniques

    Science.gov (United States)

    Bounceur, Nabila; Crucifix, Michel

    2010-05-01

    The climate is a multivariable dynamic complex system, governed by equations which are strongly nonlinear. The space-time modes of climatic variability extend on a very broad scale and constitute a major difficulty to represent this variability over long time-scales. It is generally decided to separate the dynamics of the slow components (ice sheets, carbon cycle, deep oceans) which have a time scale of about thousand of years and more, from those of the fast components (atmosphere, mixed layer, earth and ice surface) for which the time scale is for about some years. In this framework, the time-evolution of the slow components depends on the statistics of the fast components, and the latter are controlled by the slow components and the external forcing particularly astronomical ones characterised by the variation of the orbital parameters: Obliquity, precession and eccentricity. The statistics of the fast components of the climate could in principle be estimated with a general circulation model of the atmosphere and ocean. However, the demand on computing resources would be far too excessive. Given the complexity of the climatic system, the great number of dynamic equations which govern it and its degree of nonlinearity we are interested in the statistical reduction rather than an analytical one. The order reduction problem is equivalent to approximator construction. We will focus on neural networks because they constitute very powerful estimators in presence of non-linearity. The training of this network would be done using the output of the climate model of intermediate complexity "LoveClim" developed and available in the Institute of Astronomy and Geophysics G.Lemaître in Belgium as a first step of statistical reduction. The output of the model are first reduced using different methods of reduction order going from linear ones as principal component analysis (PCA) and empirical orthogonal functions (EOF) to non linear ones as Non Linear Principal component

  7. Tropical climate and vegetation simulations during the Heinrich event 1 using an Earth System Model of Intermediate Complexity (EMIC) - the University of Victoria Earth System-Climate Model (UVic ESCM)

    OpenAIRE

    Handiani, Dian; André, Paul; Dupont, Lydie

    2012-01-01

    data supplementary to Handiani, Dian; Paul, André; Dupont, Lydie (2012): Tropical climate and vegetation changes during Heinrich Event 1: a model-data comparison. Climate of the Past, 8(1), 1-21, doi:10.5194/cp-8-1-2012

  8. Utilizing Cloud Computing to Improve Climate Modeling and Studies

    Science.gov (United States)

    Li, Z.; Yang, C.; Liu, K.; Sun, M.; XIA, J.; Huang, Q.

    2013-12-01

    Climate studies have become increasingly important due to the global climate change, one of the biggest challenges for the human in the 21st century. Climate data, not only observations data collected from various sensors but also simulated data generated from diverse climate models, are essential for scientists to explore the potential climate change patterns and analyze the complex climate dynamics. Climate modeling and simulation, a critical methodology for simulating the past and predicting the future climate conditions, can produce huge amount of data that contains potentially valuable information for climate studies. However, using modeling method in climate studies poses at least two challenges for scientists. First, running climate models is a computing intensive process, which requires large amounts of computation resources. Second, running climate models is also a data intensive process generating Big geospatial Data (model output), which demands large storage for managing the data and large computing power to process and analyze these data. This presentation introduces a novel framework to tackle the two challenges by 1) running climate models in a cloud environment in an automated fashion, and 2) managing and parallel processing Big model output Data by leveraging cloud computing technologies. A prototype system is developed based on the framework using ModelE as the climate model. Experiment results show that this framework can improve climate modeling in the research cycle by accelerating big data generation (model simulation), big data management (storage and processing) and on demand big data analytics.

  9. Present-day and future Antarctic ice sheet climate and surface mass balance in the Community Earth System Model

    Science.gov (United States)

    Lenaerts, Jan T. M.; Vizcaino, Miren; Fyke, Jeremy; van Kampenhout, Leo; van den Broeke, Michiel R.

    2016-02-01

    We present climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS) as simulated by the global, coupled ocean-atmosphere-land Community Earth System Model (CESM) with a horizontal resolution of ˜1° in the past, present and future (1850-2100). CESM correctly simulates present-day Antarctic sea ice extent, large-scale atmospheric circulation and near-surface climate, but fails to simulate the recent expansion of Antarctic sea ice. The present-day Antarctic ice sheet SMB equals 2280 ± 131 {Gt year^{-1}} , which concurs with existing independent estimates of AIS SMB. When forced by two CMIP5 climate change scenarios (high mitigation scenario RCP2.6 and high-emission scenario RCP8.5), CESM projects an increase of Antarctic ice sheet SMB of about 70 {Gt year^{-1}} per degree warming. This increase is driven by enhanced snowfall, which is partially counteracted by more surface melt and runoff along the ice sheet's edges. This intensifying hydrological cycle is predominantly driven by atmospheric warming, which increases (1) the moisture-carrying capacity of the atmosphere, (2) oceanic source region evaporation, and (3) summer AIS cloud liquid water content.

  10. Modelling adaptation to climate change of Ecuadorian agriculture and associated water resources: uncertainties in coastal and highland cropping systems

    Science.gov (United States)

    Ruiz-Ramos, Margarita; Bastidas, Wellington; Cóndor, Amparo; Villacís, Marcos; Calderón, Marco; Herrera, Mario; Zambrano, José Luis; Lizaso, Jon; Hernández, Carlos; Rodríguez, Alfredo; Capa-Morocho, Mirian

    2016-04-01

    Climate change threatens sustainability of farms and associated water resources in Ecuador. Although the last IPCC report (AR5) provides a general framework for adaptation, , impact assessment and especially adaptation analysis should be site-specific, taking into account both biophysical and social aspects. The objective of this study is to analyse the climate change impacts and to sustainable adaptations to optimize the crop yield. Furthermore is also aimed to weave agronomical and hydrometeorological aspects, to improve the modelling of the coastal ("costa") and highland ("sierra") cropping systems in Ecuador, from the agricultural production and water resources points of view. The final aim is to support decision makers, at national and local institutions, for technological implementation of structural adaptation strategies, and to support farmers for their autonomous adaptation actions to cope with the climate change impacts and that allow equal access to resources and appropriate technologies. . A diagnosis of the current situation in terms of data availability and reliability was previously done, and the main sources of uncertainty for agricultural projections have been identified: weather data, especially precipitation projections, soil data below the upper 30 cm, and equivalent experimental protocol for ecophysiological crop field measurements. For reducing these uncertainties, several methodologies are being discussed. This study was funded by PROMETEO program from Ecuador through SENESCYT (M. Ruiz-Ramos contract), and by the project COOP-XV-25 funded by Universidad Politécnica de Madrid.

  11. The EC BIOCLIM Project (2000-2003), 5. Euratom Framework Programme - Modelling sequential biosphere systems under climate change for radioactive waste disposal

    International Nuclear Information System (INIS)

    Marianne Calvez (ANDRA, France) presented the new EC BIOCLIM project that started in 2001. Its main objective is to provide a scientific basis and practical methodology for assessing the possible long-term impacts on the safety of radioactive waste repositories in deep formations due to climate driven changes. She explained that BIOCLIM objective is not to predict what will be the future but will correspond to an illustration of how people could use the knowledge. The BIOCLIM project will use the outcomes from the Biomass project. Where Biomass considered discrete biospheres, the BIOCLIM project will consider the evolution of climate with a focus on the European climate for three regions in the United Kingdom, France and Spain. The consortium of BIOCLIM participants consists of various experts in climate modelling and various experts and organisations in performance assessment. The intent is to build an integrated dynamic climate model that represents all the important mechanisms for long-term climate evolution. The modelling will primarily address the next 200000 years. The final outcome will be an enhancement of the state-of-the-art treatment of biosphere system change over long periods of time through the use of a number of innovative climate modelling approaches and the application of the climate model outputs in performance assessments

  12. Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

    Science.gov (United States)

    Tao, W.-K.; Wang, Y.; Qian, J.-H.; Shie, C.-L.; Lau, W. K.-M.; Kakar, R.; Starr, David (Technical Monitor)

    2002-01-01

    The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, ships, wind profilers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional scale model (with grid size of 20 km) and Goddard Cumulus Ensemble (GCE) model (with 1 km grid size) are used to perform multi-day integration to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during SCSMEX Sensitivity tests on various land surface models, sea surface temperature (SST) variations, and cloud processes are performed to understand the precipitation processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. Cloud processes can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. The GCE-model results captured many observed precipitation characteristics because it used a fine grid size. For example, the model simulated rainfall temporal variation compared quite well to the sounding-estimated rainfall. The

  13. Fine-Resolution Modeling of the Santa Cruz and San Pedro River Basins for Climate Change and Riparian System Studies

    Science.gov (United States)

    Robles-Morua, A.; Vivoni, E. R.; Volo, T. J.; Rivera, E. R.; Dominguez, F.; Meixner, T.

    2011-12-01

    This project is part of a multidisciplinary effort aimed at understanding the impacts of climate variability and change on the ecological services provided by riparian ecosystems in semiarid watersheds of the southwestern United States. Valuing the environmental and recreational services provided by these ecosystems in the future requires a numerical simulation approach to estimate streamflow in ungauged tributaries as well as diffuse and direct recharge to groundwater basins. In this work, we utilize a distributed hydrologic model known as the TIN-based Real-time Integrated Basin Simulator (tRIBS) in the upper Santa Cruz and San Pedro basins with the goal of generating simulated hydrological fields that will be coupled to a riparian groundwater model. With the distributed model, we will evaluate a set of climate change and population scenarios to quantify future conditions in these two river systems and their impacts on flood peaks, recharge events and low flows. Here, we present a model confidence building exercise based on high performance computing (HPC) runs of the tRIBS model in both basins during the period of 1990-2000. Distributed model simulations utilize best-available data across the US-Mexico border on topography, land cover and soils obtained from analysis of remotely-sensed imagery and government databases. Meteorological forcing over the historical period is obtained from a combination of sparse ground networks and weather radar rainfall estimates. We then focus on a comparison between simulation runs using ground-based forcing to cases where the Weather Research Forecast (WRF) model is used to specify the historical conditions. Two spatial resolutions are considered from the WRF model fields - a coarse (35-km) and a downscaled (10- km) forcing. Comparisons will focus on the distribution of precipitation, soil moisture, runoff generation and recharge and assess the value of the WRF coarse and downscaled products. These results provide confidence in

  14. Economic impact of climate change : simulations with a regionalized climate-economy model

    OpenAIRE

    Deke, Oliver; Hooss, Kurt Georg; Kasten, Christiane; Klepper, Gernot; Springer, Katrin

    2001-01-01

    Climate change affects the physical and biological system in many regions of the world. The extent to which human systems will suffer economically from climate change depends on the adaptive capabilities within a region as well as across regions. We use an economic General-Equilibrium model and an Ocean-Atmosphere model in a regionally and sectorally disaggregated framework to analyze adaptation to climate change in different regions of the world. It turns out that vulnerability to climate im...

  15. Climate change and the potential global distribution of Aedes aegypti: spatial modelling using geographical information system and CLIMEX

    Directory of Open Access Journals (Sweden)

    Hassan M. Khormi

    2014-05-01

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

  16. A simple object-oriented and open-source model for scientific and policy analyses of the global climate system - Hector v1.0

    Science.gov (United States)

    Hartin, C. A.; Patel, P.; Schwarber, A.; Link, R. P.; Bond-Lamberty, B. P.

    2015-04-01

    Simple climate models play an integral role in the policy and scientific communities. They are used for climate mitigation scenarios within integrated assessment models, complex climate model emulation, and uncertainty analyses. Here we describe Hector v1.0, an open source, object-oriented, simple global climate carbon-cycle model. This model runs essentially instantaneously while still representing the most critical global-scale earth system processes. Hector has a three-part main carbon cycle: a one-pool atmosphere, land, and ocean. The model's terrestrial carbon cycle includes primary production and respiration fluxes, accommodating arbitrary geographic divisions into, e.g., ecological biomes or political units. Hector actively solves the inorganic carbon system in the surface ocean, directly calculating air-sea fluxes of carbon and ocean pH. Hector reproduces the global historical trends of atmospheric [CO2], radiative forcing, and surface temperatures. The model simulates all four Representative Concentration Pathways (RCPs) with equivalent rates of change of key variables over time compared to current observations, MAGICC (a well-known simple climate model), and models from the 5th Coupled Model Intercomparison Project. Hector's flexibility, open-source nature, and modular design will facilitate a broad range of research in various areas.

  17. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    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

  18. Modelling the impacts of challenging 2050 European climate mitigation targets on Ireland’s energy system

    International Nuclear Information System (INIS)

    The Copenhagen Accord established political consensus on the 2 °C limit (in global temperature increase) and for deep cuts in greenhouse gas (GHG) emissions levels to achieve this goal. The European Union has set ambitious GHG targets for the year 2050 (80–95% below 1990 levels), with each Member State developing strategies to contribute to these targets. This paper focuses on mitigation targets for one Member State, Ireland, an interesting case study due to the growth in GHG emissions (24% increase between 1990 and 2005) and the high share of emissions from agriculture (30% of total GHG emissions). We use the Irish TIMES energy systems modelling tool to build a number of scenarios delivering an 80% emissions reduction target by 2050, including accounting for the limited options for agriculture GHG abatement by increasing the emissions reduction target for the energy system. We then compare the scenario results in terms of changes in energy technology, the role of energy efficiency and renewable energy. We also quantify the economic impacts of the mitigation scenarios in terms of marginal CO2 abatement costs and energy system costs. The paper also sheds light on the impacts of short term targets and policies on long term mitigation pathways. - Highlights: ► We developed a techno-economic energy model of Ireland to the year 2050. ► Reductions between 80% and 95% of GHG emissions can be technically achieved. ► A 50% emissions cut in agriculture requires a 95% reductions from the energy system. ► Extending current policies implies greater electrification and efficiency measures. ► The additional cost to achieve mitigation remain less than 2% of GDP levels in 2050.

  19. 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.

  20. An Assessment of Indo-Pacific Oceanic Channel Dynamics in the FGOALS-g2 Coupled Climate System Model

    Institute of Scientific and Technical Information of China (English)

    XU Tengfei; YUAN Dongliang; YU Yongqiang; ZHAO Xia

    2013-01-01

    Lag correlations of sea surface temperature anomalies (SSTAs),sea surface height anomalies (SSHAs),subsurface temperature anomalies,and surface zonal wind anomalies (SZWAs) produced by the Flexible Global Ocean-Atmosphere-Land System model:Grid-point Version 2 (FGOALS-g2) are analyzed and compared with observations.The insignificant,albeit positive,lag correlations between the SSTAs in the southeastern tropical Indian Ocean (STIO) in fall and the SSTAs in the central-eastern Pacific cold tongue in the following summer through fall are found to be not in agreement with the observational analysis.The model,however,does reproduce the significant lag correlations between the SSHAs in the STIO in fall and those in the cold tongue at the one-year time lag in the observations.These,along with the significant lag correlations between the SSTAs in the STIO in fall and the subsurface temperature anomalies in the equatorial Pacific vertical section in the following year,suggest that the Indonesian Throughflow plays an important role in propagating the Indian Ocean anomalies into the equatorial Pacific Ocean.Analyses of the interannual anomalies of the Indonesian Throughflow transport suggest that the FGOALS-g2 climate system simulates,but underestimates,the oceanic channel dynamics between the Indian and Pacific Oceans.FGOALS-g2 is shown to produce lag correlations between the SZWAs over the western equatorial Pacific in fall and the cold tongue SSTAs at the one-year time lag that are too strong to be realistic in comparison with observations.The analyses suggest that the atmospheric bridge over the Indo-Pacific Ocean is overestimated in the FGOALS-g2 coupled climate model.

  1. Toward an early warning system for dengue prevention : modeling climate impact on dengue transmission

    OpenAIRE

    Dégallier, Nicolas; Favier, C.; Menkès, Christophe; Lengaigne, Matthieu; Ramalho, W. M.; . R. Souza; Servain, Jacques; Boulanger, Jean-Philippe

    2010-01-01

    Dengue fever is the most prevalent mosquito-borne viral disease of humans in tropical lands. As an efficient vaccine is not yet available, the only means to prevent epidemics is to control mosquito populations. These are influenced by human behavior and climatic conditions and thus, need constant effort and are very expansive. Examples of succeeded prevention are rare because of the continuous reintroduction of virus or vector from outside, or growing resistance of mosquito populations to ins...

  2. Modelling the Effect of Climate Change on Environmental Pollution Losses from Dairy Systems in the UK

    OpenAIRE

    Prado, Agustin del; Shepherd, Anita; Wu, Lianhai; Topp, Cairistiona; Moran, Dominic; Tolkamp, Bert; Chadwick, David

    2010-01-01

    21 p. So far, there has been strong emphasis on studying the impacts of climate change on agriculture in terms of changes in food production; however, there is increasing evidence that agricultural ecosystems (e.g. livestock) will also be severely affected in terms of other goods and services. For example, patterns and loads of environmental pollution derived from nutrient losses are expected to change dramatically (e.g. increased run-off: Betts et al., 2007). There have been few studies t...

  3. The Norwegian Earth System Model, NorESM1-M – Part 2: Climate response and scenario projections

    Directory of Open Access Journals (Sweden)

    T. Iversen

    2013-03-01

    Full Text Available NorESM is a generic name of the Norwegian earth system model. The first version is named NorESM1, and has been applied with medium spatial resolution to provide results for CMIP5 (http://cmip-pcmdi.llnl.gov/cmip5/index.html without (NorESM1-M and with (NorESM1-ME interactive carbon-cycling. Together with the accompanying paper by Bentsen et al. (2012, this paper documents that the core version NorESM1-M is a valuable global climate model for research and for providing complementary results to the evaluation of possible anthropogenic climate change. NorESM1-M is based on the model CCSM4 operated at NCAR, but the ocean model is replaced by a modified version of MICOM and the atmospheric model is extended with online calculations of aerosols, their direct effect and their indirect effect on warm clouds. Model validation is presented in the companion paper (Bentsen et al., 2012. NorESM1-M is estimated to have equilibrium climate sensitivity of ca. 2.9 K and a transient climate response of ca. 1.4 K. This sensitivity is in the lower range amongst the models contributing to CMIP5. Cloud feedbacks dampen the response, and a strong AMOC reduces the heat fraction available for increasing near-surface temperatures, for evaporation and for melting ice. The future projections based on RCP scenarios yield a global surface air temperature increase of almost one standard deviation lower than a 15-model average. Summer sea-ice is projected to decrease considerably by 2100 and disappear completely for RCP8.5. The AMOC is projected to decrease by 12%, 15–17%, and 32% for the RCP2.6, 4.5, 6.0, and 8.5, respectively. Precipitation is projected to increase in the tropics, decrease in the subtropics and in southern parts of the northern extra-tropics during summer, and otherwise increase in most of the extra-tropics. Changes in the atmospheric water cycle indicate that precipitation events over continents will become more intense and dry spells more frequent. Extra

  4. Climate change impacts on food system

    Science.gov (United States)

    Zhang, X.; Cai, X.; Zhu, T.

    2014-12-01

    Food system includes biophysical factors (climate, land and water), human environments (production technologies and food consumption, distribution and marketing), as well as the dynamic interactions within them. Climate change affects agriculture and food systems in various ways. Agricultural production can be influenced directly by climatic factors such as mean temperature rising, change in rainfall patterns, and more frequent extreme events. Eventually, climate change could cause shift of arable land, alteration of water availability, abnormal fluctuation of food prices, and increase of people at risk of malnutrition. This work aims to evaluate how climate change would affect agricultural production biophysically and how these effects would propagate to social factors at the global level. In order to model the complex interactions between the natural and social components, a Global Optimization model of Agricultural Land and Water resources (GOALW) is applied to the analysis. GOALW includes various demands of human society (food, feed, other), explicit production module, and irrigation water availability constraint. The objective of GOALW is to maximize global social welfare (consumers' surplus and producers' surplus).Crop-wise irrigation water use in different regions around the world are determined by the model; marginal value of water (MVW) can be obtained from the model, which implies how much additional welfare benefit could be gained with one unit increase in local water availability. Using GOALW, we will analyze two questions in this presentation: 1) how climate change will alter irrigation requirements and how the social system would buffer that by price/demand adjustment; 2) how will the MVW be affected by climate change and what are the controlling factors. These results facilitate meaningful insights for investment and adaptation strategies in sustaining world's food security under climate change.

  5. 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)

  6. Modeling Water, Climate, Agriculture, and the Economy

    OpenAIRE

    Yu, Winston; Yang, Yi-chen; Savitsky, Andre; Alford, Donald; Brown, Casey; Wescoat, James; Debowicz, Dario; Robinson, Sherman

    2013-01-01

    Describes two models used in the integrated modeling framework designed to study water, climate, agriculture and the economy in Pakistan's Indus Basin: (1) the Indus Basin Model Revised (IBMR-1012), a hydro-economic optimization model that takes a variety of inputs (such as agronomic information, irrigation system data, and water inflows) to generate the optimal crop production across the provinces (subject to a variety of physical and political constraints) for every month of the year; and (...

  7. Orbital modulation of millennial-scale climate variability in an earth system model of intermediate complexity

    Directory of Open Access Journals (Sweden)

    T. Friedrich

    2009-07-01

    Full Text Available The effect of orbital variations on simulated millennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC is studied using the earth system model of intermediate complexity LOVECLIM. It is found that for present-day topographic boundary conditions low obliquity values (~22.1° favor the triggering of internally generated millennial-scale variability in the North Atlantic region. Reducing the obliquity leads to changes of the pause-pulse ratio of the corresponding AMOC oscillations. Stochastic excitations of the density-driven overturning circulation in the Nordic Seas can create regional sea-ice anomalies and a subsequent reorganization of the atmospheric circulation. The resulting remote atmospheric anomalies over the Hudson Bay can release freshwater pulses into the Labrador Sea leading to a subsequent reduction of convective activity. The millennial-scale AMOC oscillations disappear if LGM bathymetry (with closed Hudson Bay is prescribed. Furthermore, our study documents the marine and terrestrial carbon cycle response to millennial-scale AMOC variability. Our model results support the notion that stadial regimes in the North Atlantic are accompanied by relatively high levels of oxygen in thermocline and intermediate waters off California – in agreement with paleo-proxy data.

  8. Diagnosing the average spatio-temporal impact of convective systems - Part 1: A methodology for evaluating climate models

    Science.gov (United States)

    Johnston, M. S.; Eliasson, S.; Eriksson, P.; Forbes, R. M.; Wyser, K.; Zelinka, M. D.

    2013-12-01

    An earlier method to determine the mean response of upper-tropospheric water to localised deep convective systems (DC systems) is improved and applied to the EC-Earth climate model. Following Zelinka and Hartmann (2009), several fields related to moist processes and radiation from various satellites are composited with respect to the local maxima in rain rate to determine their spatio-temporal evolution with deep convection in the central Pacific Ocean. Major improvements to the earlier study are the isolation of DC systems in time so as to prevent multiple sampling of the same event, and a revised definition of the mean background state that allows for better characterisation of the DC-system-induced anomalies. The observed DC systems in this study propagate westward at ~4 m s-1. Both the upper-tropospheric relative humidity and the outgoing longwave radiation are substantially perturbed over a broad horizontal extent and for periods >30 h. The cloud fraction anomaly is fairly constant with height but small maximum can be seen around 200 hPa. The cloud ice water content anomaly is mostly confined to pressures greater than 150 hPa and reaches its maximum around 450 hPa, a few hours after the peak convection. Consistent with the large increase in upper-tropospheric cloud ice water content, albedo increases dramatically and persists about 30 h after peak convection. Applying the compositing technique to EC-Earth allows an assessment of the model representation of DC systems. The model captures the large-scale responses, most notably for outgoing longwave radiation, but there are a number of important differences. DC systems appear to propagate eastward in the model, suggesting a strong link to Kelvin waves instead of equatorial Rossby waves. The diurnal cycle in the model is more pronounced and appears to trigger new convection further to the west each time. Finally, the modelled ice water content anomaly peaks at pressures greater than 500 hPa and in the upper

  9. Diagnosing the average spatio-temporal impact of convective systems – Part 1: A methodology for evaluating climate models

    Directory of Open Access Journals (Sweden)

    M. S. Johnston

    2013-12-01

    Full Text Available An earlier method to determine the mean response of upper-tropospheric water to localised deep convective systems (DC systems is improved and applied to the EC-Earth climate model. Following Zelinka and Hartmann (2009, several fields related to moist processes and radiation from various satellites are composited with respect to the local maxima in rain rate to determine their spatio-temporal evolution with deep convection in the central Pacific Ocean. Major improvements to the earlier study are the isolation of DC systems in time so as to prevent multiple sampling of the same event, and a revised definition of the mean background state that allows for better characterisation of the DC-system-induced anomalies. The observed DC systems in this study propagate westward at ~4 m s−1. Both the upper-tropospheric relative humidity and the outgoing longwave radiation are substantially perturbed over a broad horizontal extent and for periods >30 h. The cloud fraction anomaly is fairly constant with height but small maximum can be seen around 200 hPa. The cloud ice water content anomaly is mostly confined to pressures greater than 150 hPa and reaches its maximum around 450 hPa, a few hours after the peak convection. Consistent with the large increase in upper-tropospheric cloud ice water content, albedo increases dramatically and persists about 30 h after peak convection. Applying the compositing technique to EC-Earth allows an assessment of the model representation of DC systems. The model captures the large-scale responses, most notably for outgoing longwave radiation, but there are a number of important differences. DC systems appear to propagate eastward in the model, suggesting a strong link to Kelvin waves instead of equatorial Rossby waves. The diurnal cycle in the model is more pronounced and appears to trigger new convection further to the west each time. Finally, the modelled ice water content anomaly peaks at pressures greater than 500 h

  10. Modelling the coupled surface water and groundwater system of the Middle Upper Rhine Valley and its response to climate change.

    Science.gov (United States)

    Queguiner, Solen; Martin, Eric; Thierion, Charlotte; Habets, Florence; Ackerer, Philippe; Lecluse, Simon; Majdalani, Samer

    2010-05-01

    The Upper Rhine Graben hydrosystem holds one of the most important groundwater resources in Europe. This alluvial aquifer provides three-quarters of the regional needs for water. Its functioning is tightly linked to the hydrographic network in the alluvial plain. Indeed an important part of the available groundwater comes from the infiltration of rivers in the very permeable alluvial material of the plain. In other places in the plain a heavy drainage of the aquifer occurs, contributing to the very dense river network. Consequently, this hydrosystem has to be studied in a coupled way, taking into account the complex interaction between surface and subsurface processes. In the framework of the VULNAR project several surface, hydrological and aquifer models are used to study the vulnerability of the Rhine aquifer. This presentation will focuses on the meteorological and surface aspects and their coupling with hydrological models. The Safran-Isba-Modcou (SIM) chain is used to estimate the climate change impact on the hydrology of the region. SIM is composed of a meteorological analysis system (SAFRAN), a land surface model describing the exchange with the atmosphere (ISBA) and a hydrogeological model (MODCOU). A specific version of MODCOU is currently being developed for the region of study. The mass and energy exchanges between the continental surface (including vegetation and snow) and the atmosphere are simulated by ISBA. The LAI (Leaf Area Index) is provided by the ECOCLIMAP2 database and the vegetation is divided into 12 types. The SAFRAN meteorological analysis is used at a resolution of 8 km in the plain and down to a 1km resolution on the mountains bordering the alluvial plain. In a first step a simulation of the water balance on the studied area is presented. The simulation covers a period of 17 years: 1986-2002. The drainage and the runoff are provided to MODCOU and a comparison of the discharges with the observations is presented. Several developments are

  11. Energy-balance climate models

    Science.gov (United States)

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

    1980-01-01

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

  12. A numerical modelling tool for assessing the impact of climate change and management options on water supply systems

    Science.gov (United States)

    Romano, Emanuele; Guyennon, Nicolas; Mariani, Davide; Bruna Petrangeli, Anna; Portoghese, Ivan

    2014-05-01

    Conditions of scarcity for a water supply system occur when the available resource are not able to satisfy the connected demands. They can arise both from a decreasing of the inflow to the exploited resources and/or from a increasing of the demand. Such conditions can be assessed by a water balance model able to simulate both the hydrological processes describing the relationships between the meteorological forcing (precipitation) and the inflows to the exploited reservoir, and the intra- and inter-annual time distribution of the connected demand and the reservoir management policies. We present a numerical modelling tool, developed for the management of the Maggiore Lake, that computes at daily scale the water budget of such reservoir taking into account 1) the monthly precipitation over the watershed basin and the related inflow; 2) the seasonal demand for irrigation and 3) the operative hydrometric levels constraints to the lake water withdrawal. The model represents precipitation over the basin through the space mean of the standardized precipitation indices computed at different aggregation scales using observed time series. The relationship between the precipitation regime and the inflow to the reservoir is obtained through a simple multilinear regression model, considering the SPI computed at 1, 3 and 6 months as independent variables: this allows to take hydrological processes into account featuring different characteristic times and to simulate both the historic inflow regime and the possible conditions forecast by climate scenarios. The regression model is validated on the precipitation and lake inflow observations in the period 1996-2013 using a leave-one-out cross validation. The seasonal irrigation demand is assigned based on the extensions of crops fed by the lake water and regardless of the climate conditions; the actual supply is limited by the operative hydrometric range of allowable water levels, which stop water distribution when the lake level

  13. Climate Variability over India and Bangladesh from the Perturbed UK Met Office Hadley Model: Impacts on Flow and Nutrient Fluxes in the Ganges Delta System

    Science.gov (United States)

    Whitehead, P. G.; Caesar, J.; Crossman, J.; Barbour, E.; Ledesma, J.; Futter, M. N.

    2015-12-01

    A semi-distributed flow and water quality model (INCA- Integrated Catchments Model) has been set up for the whole of the Ganges- Brahmaputra- Meghna (GBM) River system in India and Bangladesh. These massive rivers transport large fluxes of water and nutrients into the Bay of Bengal via the GBM Delta system in Bangladesh. Future climate change will impact these fluxes with changing rainfall, temperature, evapotranspiration and soil moisture deficits being altered in the catchment systems. In this study the INCA model has been used to assess potential impacts of climate change using the UK Met Office Hadley Centre GCM model linked to a regionally coupled model of South East Asia, covering India and Bangladesh. The Hadley Centre model has been pururbed by varying the parameters in the model to generate 17 realisations of future climates. Some of these reflect expected change but others capture the more extreme potential behaviour of future climate conditions. The 17 realisations have been used to drive the INCA Flow and Nitrogen model inorder to generate downstream times series of hydrology and nitrate- nitrogen. The variability of the climates on these fluxes are investigated and and their likley impact on the Bay of Begal Delta considered. Results indicate a slight shift in the monsoon season with increased wet season flows and increased temperatures which alter nutrient fluxes. Societal Importance to Stakeholders The GBM Delta supports one of the most densely populated regions of people living in poverty, who rely on ecosystem services provided by the Delta for survival. These ecosystem services are dependent upon fluxes of water and nutrients. Freshwater for urban, agriculture, and aquaculture requirements are essential to livelihoods. Nutrient loads stimulate estuarine ecosystems, supporting fishing stocks, which contribute significantly the economy of Bangladesh. Thus the societal importance of upstream climate driven change change in Bangladesh are very

  14. Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C earth system model

    Directory of Open Access Journals (Sweden)

    P. D. Falloon

    2012-06-01

    Full Text Available The aim of our study was to use the coupled climate-carbon cycle model HadCM3C to quantify climate impact of ecosystem changes over recent decades and under future scenarios, due to changes in both atmospheric CO2 and surface albedo. We use two future scenarios – the IPCC SRES A1B scenario, and a climate stabilisation scenario (2C20, allowing us to assess the impact of climate mitigation on results. We performed a pair of simulations under each scenario – one in which vegetation was fixed at the initial state and one in which vegetation changes dynamically in response to climate change, as determined by the interactive vegetation model within HadCM3C.

    In our simulations with interactive vegetation, relatively small changes in global vegetation coverage were found, mainly dominated by increases in scrub and needleleaf trees at high latitudes and losses of broadleaf trees and grasses across the Amazon. Globally this led to a loss of terrestrial carbon, mainly from the soil. Global changes in carbon storage were related to the regional losses from the Amazon and gains at high latitude. Regional differences in carbon storage between the two scenarios were largely driven by the balance between warming-enhanced decomposition and altered vegetation growth. Globally, interactive vegetation reduced albedo acting to enhance albedo changes due to climate change. This was mainly related to the darker land surface over high latitudes (due to vegetation expansion, particularly during winter and spring; small increases in albedo occurred over the Amazon. As a result, there was a relatively small impact of vegetation change on most global annual mean climate variables, which was generally greater under A1B than 2C20, with markedly stronger local-to-regional and seasonal impacts. Globally, vegetation change amplified future annual temperature increases by 0.24 and 0.15 K (under A1B and 2C20, respectively and increased global precipitation

  15. Challenges in Modeling Regional Climate Change (Invited)

    Science.gov (United States)

    Leung, L.

    2013-12-01

    Precipitation, soil moisture, and runoff are vital to ecosystems and human activities. Predicting changes in the space-time characteristics of these water cycle processes has been a longstanding challenge in climate modeling. Different modeling approaches have been developed to allow high resolution to be achieved using available computing resources. Although high resolution is necessary to better resolve regional forcing and processes, improvements in simulating water cycle response are difficult to demonstrate and climate models have so far shown irreducible sensitivity to model resolution, dynamical framework, and physics parameterizations that confounds reliable predictions of regional climate change. Additionally, regional climate responds to both regional and global forcing but predicting changes in regional and global forcing such as related to land use/land cover and aerosol requires improved understanding and modeling of the dynamics of human-earth system interactions. Furthermore, regional response and regional forcing may be related through complex interactions that are dependent on the regional climate regimes, making decisions on regional mitigation and adaptation more challenging. Examples of the aforementioned challenges from on-going research and possible future directions will be discussed.

  16. Adaptation strategies of Mediterranean cropping systems to climate change

    OpenAIRE

    Mula, Laura

    2014-01-01

    The EPIC simulation model was used to assess the impact of climate change (CC) on intensive and extensive Mediterranean forage systems to study the effects of CC and adaptation strategies. The intensive cropping system (corn silage – Italian ryegrass) is linked to dairy cattle farms. As first step the EPIC model was calibrated based on experimental data. After calibration the EPIC model was used to perform simulations with different climate scenarios (present and future climate) with diffe...

  17. The El Niño-Southern Oscillation cycle simulated by the climate system model of Chinese Academy of Sciences

    Institute of Scientific and Technical Information of China (English)

    SU Tonghua; XUE Feng; SUN Hongchuan; ZHOU Guangqing

    2015-01-01

    On the basis of more than 200-year control run, the performance of the climate system model of Chinese Academy of Sciences (CAS-ESM-C) in simulating the El Niño-Southern Oscillation (ENSO) cycle is evalu-ated, including the onset, development and decay of the ENSO. It is shown that, the model can reasonably simulate the annual cycle and interannual variability of sea surface temperature (SST) in the tropical Pacif-ic, as well as the seasonal phase-locking of the ENSO. The model also captures two prerequisites for the El Niño onset, i.e., a westerly anomaly and a warm SST anomaly in the equatorial western Pacific. Owing to too strong forcing from an extratropical meridional wind, however, the westerly anomaly in this region is largely overestimated. Moreover, the simulated thermocline is much shallower with a weaker slope. As a result, the warm SST anomaly from the western Pacific propagates eastward more quickly, leading to a faster develop-ment of an El Niño. During the decay stage, owing to a stronger El Niño in the model, the secondary Gill-type response of the tropical atmosphere to the eastern Pacific warming is much stronger, thereby resulting in a persistent easterly anomaly in the western Pacific. Meanwhile, a cold anomaly in the warm pool appears as a result of a lifted thermocline via Ekman pumping. Finally, an El Niño decays into a La Niña through their interactions. In addition, the shorter period and larger amplitude of the ENSO in the model can be attribut-ed to a shallower thermocline in the equatorial Pacific, which speeds up the zonal redistribution of a heat content in the upper ocean.

  18. Conceptualizing Climate Change in the Context of a Climate System: Implications for Climate and Environmental Education

    Science.gov (United States)

    Shepardson, Daniel P.; Niyogi, Dev; Roychoudhury, Anita; Hirsch, Andrew

    2012-01-01

    Today there is much interest in teaching secondary students about climate change. Much of this effort has focused directly on students' understanding of climate change. We hypothesize, however, that in order for students to understand climate change they must first understand climate as a system and how changes to this system due to both natural…

  19. Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

    Science.gov (United States)

    Lu, M.; Lall, U.

    2013-12-01

    In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The

  20. Modeling the impact of climate change on sediment transport and morphology in coupled watershed-coast systems:A case study using an integrated approach

    Institute of Scientific and Technical Information of China (English)

    Achilleas GSAMARAS; Christopher GKOUTITAS

    2014-01-01

    Climate change is an issue of major concern nowadays. Its impact on the natural and human environment is studied intensively, as the expected shift in climate will be significant in the next few decades. Recent experience shows that the effects will be critical in coastal areas, resulting in erosion and inundation phenomena worldwide. In addition to that, coastal areas are subject to"pressures"from upstream watersheds in terms of water quality and sediment transport. The present paper studies the impact of climate change on sediment transport and morphology in the aforementioned coupled system. The study regards a sandy coast and its upstream watershed in Chalkidiki, North Greece; it is based on: (a) an integrated approach for the quantitative correlation of the two through numerical modeling, developed by the authors, and (b) a calibrated application of the relevant models Soil and Water Assessment Tool (SWAT) and PELNCON-M, applied to the watershed and the coastal zone, respectively. The examined climate change scenarios focus on a shift of the rainfall distribution towards fewer and more extreme rainfall events, and an increased frequency of occurrence of extreme wave events. Results indicate the significance of climatic pressures in wide-scale sediment dynamics, and are deemed to provide a useful perspective for researchers and policy planners involved in the study of coastal morphology evolution in a changing climate.

  1. A fully coupled Mediterranean regional climate system model: design and evaluation of the ocean component for the 1980–2012 period

    Directory of Open Access Journals (Sweden)

    Florence Sevault

    2014-11-01

    Full Text Available A fully coupled regional climate system model (CNRM-RCSM4 dedicated to the Mediterranean region is described and evaluated using a multidecadal hindcast simulation (1980–2012 driven by global atmosphere and ocean reanalysis. CNRM-RCSM4 includes the regional representation of the atmosphere (ALADIN-Climate model, land surface (ISBA model, rivers (TRIP model and the ocean (NEMOMED8 model, with a daily coupling by the OASIS coupler. This model aims to reproduce the regional climate system with as few constraints as possible: there is no surface salinity, temperature relaxation, or flux correction; the Black Sea budget is parameterised and river runoffs (except for the Nile are fully coupled. The atmospheric component of CNRM-RCSM4 is evaluated in a companion paper; here, we focus on the air–sea fluxes, river discharges, surface ocean characteristics, deep water formation phenomena and the Mediterranean thermohaline circulation. Long-term stability, mean seasonal cycle, interannual variability and decadal trends are evaluated using basin-scale climatologies and in-situ measurements when available. We demonstrate that the simulation shows overall good behaviour in agreement with state-of-the-art Mediterranean RCSMs. An overestimation of the shortwave radiation and latent heat loss as well as a cold Sea Surface Temperature (SST bias and a slight trend in the bottom layers are the primary current deficiencies. Further, CNRM-RCSM4 shows high skill in reproducing the interannual to decadal variability for air–sea fluxes, river runoffs, sea surface temperature and salinity as well as open-sea deep convection, including a realistic simulation of the Eastern Mediterranean Transient. We conclude that CNRM-RCSM4 is a mature modelling tool allowing the climate variability of the Mediterranean regional climate system to be studied and understood. It is used in hindcast and scenario modes in the HyMeX and Med-CORDEX programs.

  2. High dimensional decision dilemmas in climate models

    Directory of Open Access Journals (Sweden)

    A. Bracco

    2013-10-01

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

  3. High dimensional decision dilemmas in climate models

    Directory of Open Access Journals (Sweden)

    A. Bracco

    2013-05-01

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

  4. 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.

  5. Arctic melt ponds and bifurcations in the climate system

    CERN Document Server

    Sudakov, Ivan; Golden, Kenneth M

    2014-01-01

    Understanding how sea ice melts is critical to climate projections. In the Arctic, melt ponds that develop on the surface of sea ice floes during the late spring and summer largely determine their albedo $-$ a key parameter in climate modeling. Here we explore the possibility of a simple sea ice climate model passing through a bifurcation point $-$ an irreversible critical threshold as the system warms, by incorporating geometric information about melt pond evolution. This study is based on a nonlinear phase transition model for melt ponds, and bifurcation analysis of a simple climate model with ice - albedo feedback as the key mechanism driving the system to a potential bifurcation point.

  6. Visualization of uncertainty and ensemble data: Exploration of climate modeling and weather forecast data with integrated ViSUS-CDAT systems

    International Nuclear Information System (INIS)

    Climate scientists and meteorologists are working towards a better understanding of atmospheric conditions and global climate change. To explore the relationships present in numerical predictions of the atmosphere, ensemble datasets are produced that combine time- and spatially-varying simulations generated using multiple numeric models, sampled input conditions, and perturbed parameters. These data sets mitigate as well as describe the uncertainty present in the data by providing insight into the effects of parameter perturbation, sensitivity to initial conditions, and inconsistencies in model outcomes. As such, massive amounts of data are produced, creating challenges both in data analysis and in visualization. This work presents an approach to understanding ensembles by using a collection of statistical descriptors to summarize the data, and displaying these descriptors using variety of visualization techniques which are familiar to domain experts. The resulting techniques are integrated into the ViSUS/Climate Data and Analysis Tools (CDAT) system designed to provide a directly accessible, complex visualization framework to atmospheric researchers.

  7. Tropical Indian Ocean surface salinity bias in Climate Forecasting System coupled models and the role of upper ocean processes

    Science.gov (United States)

    Parekh, Anant; Chowdary, Jasti S.; Sayantani, Ojha; Fousiya, T. S.; Gnanaseelan, C.

    2016-04-01

    In the present study sea surface salinity (SSS) biases and seasonal tendency over the Tropical Indian Ocean (TIO) in the coupled models [Climate Forecasting System version 1 (CFSv1) and version 2 (CFSv2)] are examined with respect to observations. Both CFSv1 and CFSv2 overestimate SSS over the TIO throughout the year. CFSv1 displays improper SSS seasonal cycle over the Bay of Bengal (BoB), which is due to weaker model precipitation and improper river runoff especially during summer and fall. Over the southeastern Arabian Sea (AS) weak horizontal advection associated with East Indian coastal current during winter limits the formation of spring fresh water pool. On the other hand, weaker Somali jet during summer results for reduced positive salt tendency in the central and eastern AS. Strong positive precipitation bias in CFSv1 over the region off Somalia during winter, weaker vertical mixing and absence of horizontal salt advection lead to unrealistic barrier layer during winter and spring. The weaker stratification and improper spatial distribution of barrier layer thickness (BLT) in CFSv1 indicate that not only horizontal flux distribution but also vertical salt distribution displays large discrepancies. Absence of fall Wyrtki jet and winter equatorial currents in this model limit the advection of horizontal salt flux to the eastern equatorial Indian Ocean. The associated weaker stratification in eastern equatorial Indian Ocean can lead to deeper mixed layer and negative Sea Surface Temperature (SST) bias, which in turn favor positive Indian Ocean Dipole bias in CFSv1. It is important to note that improper spatial distribution of barrier layer and stratification can alter the air-sea interaction and precipitation in the models. On the other hand CFSv2 could produce the seasonal evolution and spatial distribution of SSS, BLT and stratification better than CFSv1. However CFSv2 displays positive bias in evaporation over the whole domain and negative bias in

  8. An expressed sequence tag (EST library for Drosophila serrata, a model system for sexual selection and climatic adaptation studies

    Directory of Open Access Journals (Sweden)

    McGraw Elizabeth A

    2009-01-01

    Full Text Available Abstract Background The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup. Results A normalized cDNA library was constructed from whole fly bodies at several developmental stages, including larvae and adults. Assembly of 11,616 clones sequenced from the 3' end allowed us to identify 6,607 unique contigs, of which at least 90% encoded peptides. Partial transcripts were discovered from a variety of genes of evolutionary interest by BLASTing contigs against the 12 Drosophila genomes currently sequenced. By incorporating into the cDNA library multiple individuals from populations spanning a large portion of the geographical range of D. serrata, we were able to identify 11,057 putative single nucleotide polymorphisms (SNPs, with 278 different contigs having at least one "double hit" SNP that is highly likely to be a real polymorphism. At least 394 EST-associated microsatellite markers, representing 355 different contigs, were also found, providing an additional set of genetic markers. The assembled EST library is available online at http://www.chenowethlab.org/serrata/index.cgi. Conclusion We have provided the first gene collection and largest set of polymorphic genetic markers, to date, for the fly D. serrata. The EST

  9. Diagnosing the average spatio-temporal impact of convective systems – Part 1: A methodology for evaluating climate models

    OpenAIRE

    Johnston, M. S.; Eriksson, P.; S. Eliasson; Zelinka, M. D.; Forbes, R.M.; Wyser, K.

    2013-01-01

    A~method to determine the mean response of upper tropospheric water to localised deep convective (DC) events is improved and applied to the EC-Earth climate model. Following Zelinka and Hartmann (2009), several fields related to moist processes and radiation are composited with respect to local maxima in rain rate to determine their spatio-temporal evolution with deep convection in the central Pacific Ocean. Major improvements to the above study are the isolation of DC events in time...

  10. Modeling Impact of Climate Change on Water Resources and Agriculture Demand in the Volta Basin and other Basin Systems in Ghana

    Directory of Open Access Journals (Sweden)

    Barnabas A. Amisigo

    2015-05-01

    Full Text Available An assessment of the impacts of projected climate change on water availability and crop production in the Volta Basin and the southwestern and coastal basin systems of Ghana has been undertaken as a component of the impacts and adaptation study for Ghana by UNU-WIDER and the University of Ghana. Four climate change scenarios were considered in addition to a reference (no change scenario—two dry and two wet scenarios. To conduct the analysis, a portion of a special framework using three water models was used; the framework is called the Strategic Analysis of Climate resilient Development (SACReD. First, the CliRun water balance model was used to simulate catchment runoffs using projected rainfall and temperature under the scenarios. Second, climate impacts on yields of the economically important Ghana crops were modeled using the AquaCrop software. Third, the Water Evaluation and Planning (WEAP software was used for the water allocation modeling. The results show that all water demands (municipal, hydropower, and agriculture cannot be simultaneously met currently, or under any of the scenarios used, including the wet scenarios. This calls for an evaluation of groundwater as an additional source of water supply and an integrated water resources management plan in the catchments to balance demand with supply and ensure sustainable socio-economic development. In addition, the AquaCrop model forecasts negative impacts for the crop yields studied, with some crops and regions seeing larger impacts than others.

  11. Uncertainty Quantification in Climate Modeling

    Science.gov (United States)

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

    2011-12-01

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

  12. Enabling Philippine Farmers to Adapt to Climate Variability Using Seasonal Climate and Weather Forecast with a Crop Simulation Model in an SMS-based Farmer Decision Support System

    Science.gov (United States)

    Ebardaloza, J. B. R.; Trogo, R.; Sabido, D. J.; Tongson, E.; Bagtasa, G.; Balderama, O. F.

    2015-12-01

    Corn farms in the Philippines are rainfed farms, hence, it is of utmost importance to choose the start of planting date so that the critical growth stages that are in need of water will fall on dates when there is rain. Most farmers in the Philippines use superstitions and traditions as basis for farming decisions such as when to start planting [1]. Before climate change, superstitions like planting after a feast day of a saint has worked for them but with the recent progression of climate change, farmers now recognize that there is a need for technological intervention [1]. The application discussed in this paper presents a solution that makes use of meteorological station sensors, localized seasonal climate forecast, localized weather forecast and a crop simulation model to provide recommendations to farmers based on the crop cultivar, soil type and fertilizer type used by farmers. It is critical that the recommendations given to farmers are not generic as each farmer would have different needs based on their cultivar, soil, fertilizer, planting schedule and even location [2]. This application allows the farmer to inquire about whether it will rain in the next seven days, the best date to start planting based on the potential yield upon harvest, when to apply fertilizer and by how much, when to water and by how much. Short messaging service (SMS) is the medium chosen for this application because while mobile penetration in the Philippines is as high as 101%, the smart phone penetration is only at 15% [3]. SMS has been selected as it has been identified as the most effective way of reaching farmers with timely agricultural information and knowledge [4,5]. The recommendations while derived from making use of Automated Weather Station (AWS) sensor data, Weather Research Forecasting (WRF) models and DSSAT 4.5 [9], are translated into the local language of the farmers and in a format that is easily understood as recommended in [6,7,8]. A pilot study has been started

  13. Assessing the role of deep rooted vegetation in the climate system with model simulations: mechanism, comparison to observations and implications for Amazonian deforestation

    Energy Technology Data Exchange (ETDEWEB)

    Kleidon, A.; Heimann, M. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany)

    2000-02-01

    Deep rooted vegetation (of up to 68 m) has been found in many parts of the tropics. However, models of the general atmospheric circulation (GCMs) typically use rooting depths of less than 2 m in their land surface parametrizations. How does the incorporation of deep roots into such a model affect the simulated climate? We assess this question by using a GCM and find that deeper roots lead to a pronounced seasonal response. During the dry season, evapotranspiration and the associated latent heat flux are considerably increased over large regions leading to a cooling of up to 8 K. The enhanced atmospheric moisture is transported towards the main convection areas in the inner tropical convergence zone where it supplies more energy to convection thus intensifying the tropical circulation patterns. Comparison to different kinds of data reveals that the simulation with deeper roots is much closer to observations. The inclusion of deep roots also leads to a general increased climatic sensitivity to rooting depth change. We investigate this aspect in the context of the climatic effects of large-scale deforestation in Amazonia. Most of the regional and remote changes can be attributed to the removal of deep roots. We conclude that deep rooted vegetation is an important part of the tropical climate system. Without the consideration of deep roots, the present-day surface climate cannot adequately be simulated. (orig.)

  14. 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.

  15. Climate, Hydrochemistry and Economics of Surface-water Systems (CHESS): adding a European dimension to the catchment modelling experience developed under LOIS.

    Science.gov (United States)

    Boorman, David B

    2003-10-01

    One achievement of the UK Land-Ocean Interaction Study (LOIS) was to link dynamic biogeochemical models of different domains, e.g. rivers, estuaries and coastal waters, and to use the linked model to investigate possible changes from the current status that might occur in the future, for example as the result of climate change. The Climate, Hydrochemistry and Economics of Surface-water Systems (CHESS) project has taken the LOIS methodology forward by exploring possible impacts of climate change on the water quality of European rivers, with the purpose of informing future catchment management. This was achieved by the application of a standard modelling framework to a set of five European catchments located in Finland (River Vantaa), United Kingdom (Yorkshire Ouse), Belgium (Dender), Italy (Enza) and Greece (Pinios). Baseline conditions were simulated using existing meteorological data from the period 1961-1990, and in all cases the modelling framework was able to reproduce key features of the flow and water quality regimes of the study catchments. The modelling framework comprised two models. The Soil Water Assessment Tool (SWAT) was used to simulate water and chemical fluxes, primarily nutrients and sediment, generated from diffuse areas and thereby provide sub-catchment inputs to an in-stream water quality model, the Quality Evaluation and Simulation Tool for River Systems (QUESTOR). QUESTOR integrated the diffuse runoff along the channel network, together with point source discharges from industry and sewage treatment works, and water abstractions for public supply, industry and agriculture. The modelling framework has been used for the baseline conditions, along with a set of six climate scenarios. These comprised four scenarios derived from different general circulation models (GCMs) representing the 2050s, and three scenarios from the same GCM representing the 2020s, 2050s and 2080s, with one scenario in both groups. Results have been explored using a range

  16. Glacial-interglacial variability in Tropical Pangaean Precipitation during the Late Paleozoic Ice Age: simulations with the Community Climate System Model

    Directory of Open Access Journals (Sweden)

    N. G. Heavens

    2012-05-01

    Full Text Available The Late Paleozoic Ice Age (LPIA, the Earth's penultimate "icehouse climate", was a critical time in the history of biological and ecological evolution. Many questions remain about the connections between high-latitude glaciation in Gondwanaland and low-latitude precipitation variability in Pangaea. We have simulated the Earth's climate during Asselian-Sakmarian time (299–284 Ma with the Community Climate System Model version 3 (CCSM3, a coupled dynamic atmosphere-ocean-land-sea-ice model. Our simulations test the sensitivity of the model climate to direct and indirect effects of glaciation as well as variability in the Earth's orbit. Our focus is on precipitation variability in tropical (30° S–30° N Pangaea, where there has been the most interpretation of glacial-interglacial climate change during the LPIA. The results of these simulations suggest that glacials generally were drier than interglacials in tropical Pangaea, though exceptional areas may have been wetter, depending on location and the mode of glaciation. Lower sea level, an indirect effect of changes in glacial extent, appears to reduce tropical Pangaean precipitation more than the direct radiative/topographic effects of high-latitude glaciation. Glaciation of the Central Pangaean Mountains would have greatly reduced equatorial Pangaean precipitation, while perhaps enhancing precipitation at higher tropical latitudes and in equatorial rain shadows. Variability evident in strata with 5th order stratigraphic cycles may have resulted from precipitation changes owing to precession forcing of monsoon circulations and would have differed in character between greenhouse and icehouse climates.

  17. Impact of Stochastic Parameterization Schemes on Coupled and Uncoupled Climate Simulations with the Community Earth System Model

    Science.gov (United States)

    Christensen, H. M.; Berner, J.; Coleman, D.; Palmer, T.

    2015-12-01

    Stochastic parameterizations have been used for more than a decade in atmospheric models to represent the variability of unresolved sub-grid processes. They have a beneficial effect on the spread and mean state of medium- and extended-range forecasts (Buizza et al. 1999, Palmer et al. 2009). There is also increasing evidence that stochastic parameterization of unresolved processes could be beneficial for the climate of an atmospheric model through noise enhanced variability, noise-induced drift (Berner et al. 2008), and by enabling the climate simulator to explore other flow regimes (Christensen et al. 2015; Dawson and Palmer 2015). We present results showing the impact of including the Stochastically Perturbed Parameterization Tendencies scheme (SPPT) in coupled runs of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4) with historical forcing. The SPPT scheme accounts for uncertainty in the CAM physical parameterization schemes, including the convection scheme, by perturbing the parametrised temperature, moisture and wind tendencies with a multiplicative noise term. SPPT results in a large improvement in the variability of the CAM4 modeled climate. In particular, SPPT results in a significant improvement to the representation of the El Nino-Southern Oscillation in CAM4, improving the power spectrum, as well as both the inter- and intra-annual variability of tropical pacific sea surface temperatures. References: Berner, J., Doblas-Reyes, F. J., Palmer, T. N., Shutts, G. J., & Weisheimer, A., 2008. Phil. Trans. R. Soc A, 366, 2559-2577 Buizza, R., Miller, M. and Palmer, T. N., 1999. Q.J.R. Meteorol. Soc., 125, 2887-2908. Christensen, H. M., I. M. Moroz & T. N. Palmer, 2015. Clim. Dynam., doi: 10.1007/s00382-014-2239-9 Dawson, A. and T. N. Palmer, 2015. Clim. Dynam., doi: 10.1007/s00382-014-2238-x Palmer, T.N., R. Buizza, F. Doblas-Reyes, et al., 2009, ECMWF technical memorandum 598.

  18. A framework for modeling uncertainty in regional climate change (Invited)

    Science.gov (United States)

    Monier, E.; Gao, X.; Scott, J. R.; Sokolov, A. P.; Schlosser, C. A.

    2013-12-01

    In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the United States associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework are the emissions projections (using different climate policies), the climate system response (represented by different values of climate sensitivity and net aerosol forcing), natural variability (by perturbing initial conditions) and structural uncertainty (using different climate models). The modeling framework revolves around the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model with an intermediate complexity earth system model (with a two-dimensional zonal-mean atmosphere). Regional climate change over the United States is obtained through a two-pronged approach. First, we use the IGSM-CAM framework which links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Secondly, we use a pattern-scaling method that extends the IGSM zonal mean based on climate change patterns from various climate models. Results show that uncertainty in temperature changes are mainly driven by policy choices and the range of climate sensitivity considered. Meanwhile, the four sources of uncertainty contribute more equally to precipitation changes, with natural variability having a large impact in the first part of the 21st century. Overall, the choice of policy is the largest driver of uncertainty in future projections of climate change over the United States. In light of these results, we recommend that when investigating climate change impacts over specific regions, studies consider all four sources of uncertainty analyzed in this paper.

  19. Linked models to assess the impacts of climate change on nitrogen in a Norwegian river basin and fjord system

    International Nuclear Information System (INIS)

    Dynamically downscaled data from two Atmosphere-Ocean General Circulation Models (AOGCMs), ECHAM4 from the Max-Planck Institute (MPI), Germany and HadAm3H from the Hadley Centre (HAD), UK, driven with two scenarios of greenhouse gas emissions (IS92a and A2, respectively) were used to make climate change projections. These projections were then used to drive four effect models linked to assess the effects on hydrology, and nitrogen (N) concentrations and fluxes, in the Bjerkreim river basin (685-km2) and its coastal fjord, southwestern Norway. The four effect models were the hydrological model HBV, the water quality models MAGIC, INCA-N and the NIVA FJORD model. The downscaled climate scenarios project a general temperature increase in the study region of approximately 1 deg. C by 2030-2049 (MPI IS92a) and approximately 3 deg. C by 2071-2100 (HAD A2). Both scenarios imply increased winter precipitation, whereas the projections of summer and autumn precipitation are quite different, with the MPI scenario projecting a slight increase and the HAD scenario a significant decrease. As a response to increased winter temperature, the HBV model simulates a dramatic reduction of snow accumulation in the upper parts of the catchment, which in turn lead to higher runoff during winter and lower runoff during snowmelt in the spring. With the HAD scenario, runoff in summer and early autumn is substantially reduced as a result of reduced precipitation, increased temperatures and thereby increased evapotranspiration. The water quality models, MAGIC and INCA-N project no major changes in nitrate (NO3-) concentrations and fluxes within the MPI scenario, but a significant increase in concentrations and a 40-50% increase in fluxes in the HAD scenario. As a consequence, the acidification of the river could increase, thus offsetting ongoing recovery from acidification due to reductions in acid deposition. Additionally, the increased N loading may stimulate growth of N-limited benthic

  20. Comparison of SVAT models for simulating and optimizing deficit irrigation systems in arid and semi-arid countries under climate variability

    Science.gov (United States)

    Kloss, Sebastian; Schuetze, Niels; Schmitz, Gerd H.

    2010-05-01

    The strong competition for fresh water in order to fulfill the increased demand for food worldwide has led to a renewed interest in techniques to improve water use efficiency (WUE) such as controlled deficit irrigation. Furthermore, as the implementation of crop models into complex decision support systems becomes more and more common, it is imperative to reliably predict the WUE as ratio of water consumption and yield. The objective of this paper is the assessment of the problems the crop models - such as FAO-33, DAISY, and APSIM in this study - face when maximizing the WUE. We applied these crop models for calculating the risk in yield reduction in view of different sources of uncertainty (e.g. climate) employing a stochastic framework for decision support for the planning of water supply in irrigation. The stochastic framework consists of: (i) a weather generator for simulating regional impacts of climate change; (ii) a new tailor-made evolutionary optimization algorithm for optimal irrigation scheduling with limited water supply; and (iii) the above mentioned models for simulating water transport and crop growth in a sound manner. The results present stochastic crop water production functions (SCWPF) for different crops which can be used as basic tools for assessing the impact of climate variability on the risk for the potential yield. Case studies from India, Oman, Malawi, and France are presented to assess the differences in modeling water stress and yield response for the different crop models.

  1. Climate Modeling with a Linux Cluster

    Science.gov (United States)

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

    2004-08-01

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

  2. Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change

    Science.gov (United States)

    Elliott, Caroline M.; Jacobson, Robert B.; Freeman, Mary C.

    2014-01-01

    A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia. The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling. The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the

  3. Essays on Economic Modeling of Climate Change

    OpenAIRE

    Engström, Gustav

    2012-01-01

    Structural change in a two-sector model of the climate and the economy introduces issues concerning substitutability among goods in a two-sector economic growth model where emissions from fossil fuels give rise to a climate externality. Substitution is modeled using a CES-production function where the intermediate inputs differ only in their technologies and the way they are affected by the climate externality. I derive a simple formula for optimal taxes and resource allocation over time and ...

  4. Global analysis theory of climate system and its applications

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The idea and main theoretical results of the global analysis theory of climate system are briefly summarized in this paper. A theorem on the global behavior of climate system is given, i.e. there exists a global attractor in the dynamical equations of climate, any state of climate system will be evolved into the global attractor as time increases, indicating the nonlinear adjustment process of climate system to external forcing. The different effects of external forcing, dissipation and nonlinearity on the long-term behavior of solutions are pointed out, and some main applications of the global analysis theory are also introduced. Especially, three applications, the adjustment and evolution processes of climate, the principle of numerical model design and the optimally numerical integration, are discussed.

  5. A System Dynamics Approach to Modeling Future Climate Scenarios: Quantifying and Projecting Patterns of Evapotranspiration and Precipitation in the Salton Sea Watershed

    Directory of Open Access Journals (Sweden)

    Michael E. Kjelland

    2014-01-01

    Full Text Available The need for improved quantitative precipitation forecasts and realistic assessments of the regional impacts of natural climate variability and climate change has generated increased interest in regional (i.e., systems-scale climate simulation. The Salton Sea Stochastic Simulation Model (S4M was developed to assist planners and residents of the Salton Sea (SS transboundary watershed (USA and Mexico in making sound policy decisions regarding complex water-related issues. In order to develop the S4M with a higher degree of climate forecasting resolution, an in-depth analysis was conducted regarding precipitation and evapotranspiration for the semiarid region of the watershed. Weather station data were compiled for both precipitation and evapotranspiration from 1980 to 2004. Several logistic regression models were developed for determining the relationships among precipitation events, that is, duration and volume, and evapotranspiration levels. These data were then used to develop a stochastic weather generator for S4M. Analyses revealed that the cumulative effects and changes of ±10 percent in SS inflows can have significant effects on sea elevation and salinity. The aforementioned technique maintains the relationships between the historic frequency distributions of both precipitation and evapotranspiration, and not as separate unconnected and constrained variables.

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

    NARCIS (Netherlands)

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

    2016-01-01

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

  7. 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

  8. A Hybrid Evaluation System Framework (Shell & Web) with Standardized Access to Climate Model Data and Verification Tools for a Clear Climate Science Infrastructure on Big Data High Performance Computers

    Science.gov (United States)

    Kadow, Christopher; Illing, Sebastian; Kunst, Oliver; Ulbrich, Uwe; Cubasch, Ulrich

    2015-04-01

    The project 'Integrated Data and Evaluation System for Decadal Scale Prediction' (INTEGRATION) as part of the German decadal prediction project MiKlip develops a central evaluation system. The fully operational hybrid features a HPC shell access and an user friendly web-interface. It employs one common system with a variety of verification tools and validation data from different projects in- and outside of MiKlip. The evaluation system is located at the German Climate Computing Centre (DKRZ) and has direct access to the bulk of its ESGF node including millions of climate model data sets, e.g. from CMIP5 and CORDEX. The database is organized by the international CMOR standard using the meta information of the self-describing model, reanalysis and observational data sets. Apache Solr is used for indexing the different data projects into one common search environment. This implemented meta data system with its advanced but easy to handle search tool supports users, developers and their tools to retrieve the required information. A generic application programming interface (API) allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language used. Users of the evaluation techniques benefit from the common interface of the evaluation system without any need to understand the different scripting languages. Facilitating the provision and usage of tools and climate data increases automatically the number of scientists working with the data sets and identify discrepancies. Additionally, the history and configuration sub-system stores every analysis performed with the evaluation system in a MySQL database. Configurations and results of the tools can be shared among scientists via shell or web-system. Therefore, plugged-in tools gain automatically from transparency and reproducibility. Furthermore, when configurations match while starting a evaluation tool, the system suggests to use results already produced

  9. The Atmosphere-Ocean System of IMAGE 2.2. A global model approach for atmospheric concentrations, and climate and sea level projections

    Energy Technology Data Exchange (ETDEWEB)

    Eickhout, B.; Den Elzen, M.G.J.; Kreileman, G.J.J.

    2004-07-01

    The technical background of the Atmosphere Ocean System (AOS) of the Integrated Model to Assess the Global Environment (IMAGE, version 2.2) is described. The AOS submodel elaborates the global concentrations of the most important greenhouse gases and ozone precursors, along with their direct and indirect effects on global-mean radiative forcing. These submodels are based on state-of-the-art approximations, as published by the Intergovernmental Panel on Climate Change (IPCC) in its Third Assessment Report (TAR). That these simple submodels can adequately reproduce the global concentrations and forcings of more complex models in a very short runtime is also true for the simple climate submodel for calculating the consequences for the climate system and sea-level rise described in this report. We also elaborate on the scientific background and the most important features of the different submodels, comparing the results with other models and observations. Furthermore, we demonstrate that AOS adequately represents the 1970-1995 period for the main global indicators (concentrations, temperature increase and sea-level rise)

  10. The Norwegian Earth System Model, NorESM1-M – Part 2: Climate response and scenario projections

    Directory of Open Access Journals (Sweden)

    T. Iversen

    2012-09-01

    Full Text Available The NorESM1-M simulation results for CMIP5 (http://cmip-pcmdi.llnl.gov/cmip5/index.html are described and discussed. Together with the accompanying paper by Bentsen et al. (2012, this paper documents that NorESM1-M is a valuable global climate model for research and for providing complementary results to the evaluation of possible man made climate change. NorESM is based on the model CCSM4 operated at NCAR on behalf of many contributors in USA. The ocean model is replaced by a developed version of MICOM and the atmospheric model is extended with on-line calculations of aerosols, their direct effect, and their indirect effect on warm clouds. Model validation is presented in a companion paper (Bentsen et al., 2012. NorESM1-M is estimated to have equilibrium climate sensitivity slightly smaller than 2.9 K, a transient climate response just below 1.4 K, and is less sensitive than most other models. Cloud feedbacks damp the response, and a strong AMOC reduces the heat fraction available for increasing near surface temperatures, for evaporation, and for melting ice. The future projections based on RCP scenarios yield global surface air temperature increase almost one standard deviation lower than a 15-model average. Summer sea-ice is projected to decrease considerably by 2100, and completely for RCP8.5. The AMOC is projected to reduce by 12%, 15–17%, and 32% for the RCP2.6, 4.5, 6.0 and 8.5 respectively. Precipitation is projected to increase in the tropics, decrease in the subtropics and in southern parts of the northern extra-tropics during summer, and otherwise increase in most of the extra-tropics. Changes in the atmospheric water cycle indicate that precipitation events over continents will become more intense and dry spells more frequent. Extra-tropical storminess in the Northern Hemisphere is projected to shift northwards. There are indications of more frequent spring and

  11. 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.

  12. The Ancient Martian Climate System

    Science.gov (United States)

    Haberle, Robert M.

    2014-01-01

    Today Mars is a cold, dry, desert planet. The atmosphere is thin and liquid water is not stable. But there is evidence that very early in its history it was warmer and wetter. Since Mariner 9 first detected fluvial features on its ancient terrains researchers have been trying to understand what climatic conditions could have permitted liquid water to flow on the surface. Though the evidence is compelling, the problem is not yet solved. The main issue is coping with the faint young sun. During the period when warmer conditions prevailed 3.5-3.8 Gy the sun's luminosity was approximately 25% less than it is today. How can we explain the presence of liquid water on the surface of Mars under such conditions? A similar problem exists for Earth, which would have frozen over under a faint sun even though the evidence suggests otherwise. Attempts to solve the "Faint Young Sun Paradox" rely on greenhouse warming from an atmosphere with a different mass and composition than we see today. This is true for both Mars and Earth. However, it is not a straightforward solution. Any greenhouse theory must (a) produce the warming and rainfall needed, (b) have a plausible source for the gases required, (c) be sustainable, and (d) explain how the atmosphere evolved to its present state. These are challenging requirements and judging from the literature they have yet to be met. In this talk I will review the large and growing body of work on the early Mars climate system. I will take a holistic approach that involves many disciplines since our goal is to present an integrated view that touches on each of the requirements listed in the preceding paragraph. I will begin with the observational evidence, which comes from the geology, mineralogy, and isotopic data. Each of the data sets presents a consistent picture of a warmer and wetter past with a thicker atmosphere. How much warmer and wetter and how much thicker is a matter of debate, but conditions then were certainly different than

  13. Explosive cyclones in CMIP5 climate models

    Science.gov (United States)

    Seiler, C.; Zwiers, F. W.

    2014-12-01

    Explosive cyclones are rapidly intensifying low pressure systems with severe wind speeds and precipitation, affecting livelihoods and infrastructure primarily in coastal and marine environments. A better understanding of the potential impacts of climate change on these so called meteorological bombs is therefore of great societal relevance. This study evaluates how well CMIP5 climate models reproduce explosive cyclones in the extratropics of the northern hemisphere, and how these bombs respond to global warming. For this purpose an objective-feature tracking algorithm was used to identify and track extratropical cyclones from 25 CMIP5 models and 3 reanalysis products for the periods 1980 to 2005 and 2070 to 2099. Cyclones were identified as the maxima of T42 vorticity of 6h wind speed at 850 hPa. Explosive and non-explosive cyclones were separated based on the corresponding deepening rates of mean sea level pressure. Most models accurately reproduced the spatial distribution of bombs when compared to results from reanalysis data (R2 = 0.84, p-value = 0.00), with high frequencies along the Kuroshio Current and the Gulf Stream, as well as the exit regions of the polar jet streaks. Most models however significantly underestimated bomb frequencies by a third on average, and by 74% in the most extreme case. This negative frequency bias coincided with significant underestimations of either meridional sea surface temperature (SST) gradients, or wind speeds of the polar jet streaks. Bomb frequency biases were significantly correlated with the number vertical model levels (R2= 0.36, p-value = 0.001), suggesting that the vertical atmospheric model resolution is crucial for simulating bomb frequencies accurately. The impacts of climate change on the location, frequency, and intensity of explosive cyclones were then explored for the Representative Concentration Pathway 8.5. Projections were related to model bias, resolution, projected changes of SST gradients, and wind speeds

  14. Enabling the use of climate model data in the Dutch climate effect community

    Science.gov (United States)

    Som de Cerff, Wim; Plieger, Maarten

    2010-05-01

    Within the climate effect community the usage of climate model data is emerging. Where mostly climate time series and weather generators were used, there is a shift to incorporate climate model data into climate effect models. The use of climate model data within the climate effect models is difficult, due to missing metadata, resolution and projection issues, data formats and availability of the parameters of interest. Often the climate effect modelers are not aware of available climate model data or are not aware of how they can use it. Together with seven other partners (CERFACS, CNR-IPSL, SMHI, INHGA, CMCC, WUR, MF-CNRM), KNMI is involved in the FP7 IS ENES (http://www.enes.org) project work package 10/JRA5 ‘Bridging Climate Research Data and the Needs of the Impact Community. The aims of this work package are to enhance the use of Climate Research Data and to enhance the interaction with climate effect/impact communities. Phase one is to define use cases together with the Dutch climate effect community, which describe the intended use of climate model data in climate effect models. We defined four use cases: 1) FEWS hydrological Framework (Deltares) 2) METAPHOR, a plants and species dispersion model (Wageningen University) 3) Natuurplanner, an Ecological model suite (Wageningen University) 4) Land use models (Free University/JRC). Also the other partners in JRA5 have defined use cases, which are representative for the climate effect and impact communities in their country. Goal is to find commonalities between all defined use cases. The common functionality will be implemented as e-tools and incorporated in the IS-ENES data portal. Common issues relate to e.g., need for high resolution: downscaling from GCM to local scale (also involves interpolation); parameter selection; finding extremes; averaging methods. At the conference we will describe the FEWS case in more detail: Delft FEWS is an open shell system (in development since 1995) for performing

  15. Climate Forecast System Version 2 (CFSv2) Operational Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

  16. Climate Forecast System Version 2 (CFSv2) Operational Forecasts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

  17. DIY the Integrated Climate Model and its computational performance

    OpenAIRE

    Wang, Pengfei

    2014-01-01

    This article describes the software engineering framework and computation performance of a global climate system model which helps the user to understand the step-by-step technical to DIY(do it yourself) a climate model by your own. The model integrates ECHAM5 and NEMO2.3 using OASIS3 as the coupler. The program skill of the Integrated global Climate Model (ICM) is demonstrated here, including the porting of NEMO into the COSMOS framework, the organization of variable exchange, and component ...

  18. Mediterranean climate modelling: variability and climate change scenarios

    International Nuclear Information System (INIS)

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

  19. Application of CarboSOIL model to predict the effects of climate change on soil organic carbon stocks in agro-silvo-pastoral Mediterranean management systems

    Science.gov (United States)

    Muñoz-Rojas, Miriam; Doro, Luca; Ledda, Luigi; Francaviglia, Rosa

    2014-05-01

    CarboSOIL is an empirical model based on regression techniques and developed to predict soil organic carbon contents (SOC) at standard soil depths of 0-25, 25-50 and 50-75 cm (Muñoz-Rojas et al., 2013). The model was applied to a study area of north-eastern Sardinia (Italy) (40° 46'N, 9° 10'E, mean altitude 285 m a.s.l.), characterized by extensive agro-silvo-pastoral systems which are typical of similar areas of the Mediterranean basin (e.g. the Iberian peninsula). The area has the same soil type (Haplic Endoleptic Cambisols, Dystric according to WRB), while cork oak forest (Quercus suber L.) is the potential native vegetation which has been converted to managed land with pastures and vineyards in recent years (Lagomarsino et al., 2011; Francaviglia et al., 2012; Bagella et al, 2013; Francaviglia et al., 2014). Six land uses with different levels of cropping intensification were compared: Tilled vineyards (TV); No-tilled grassed vineyards (GV); Hay crop (HC); Pasture (PA); Cork oak forest (CO) and Semi-natural systems (SN). The HC land use includes oats, Italian ryegrass and annual clovers or vetch for 5 years and intercropped by spontaneous herbaceous vegetation in the sixth year. The PA land use is 5 years of spontaneous herbaceous vegetation, and one year of intercropping with oats, Italian ryegrass and annual clovers or vetch cultivated as a hay crop. The SN land use (scrublands, Mediterranean maquis and Helichrysum meadows) arise from the natural re-vegetation of former vineyards which have been set-aside probably due to the low grape yields and the high cost of modern tillage equipment. Both PA and HC are grazed for some months during the year, and include scattered cork-oak trees, which are key components of the 'Dehesa'-type landscape (grazing system with Quercus L.) typical of this area of Sardinia and other areas of southern Mediterranean Europe. Dehesas are often converted to more profitable land uses such as vineyards (Francaviglia et al., 2012; Mu

  20. Climate Change Education in Earth System Science

    Science.gov (United States)

    Hänsel, Stephanie; Matschullat, Jörg

    2013-04-01

    The course "Atmospheric Research - Climate Change" is offered to master Earth System Science students within the specialisation "Climate and Environment" at the Technical University Bergakademie Freiberg. This module takes a comprehensive approach to climate sciences, reaching from the natural sciences background of climate change via the social components of the issue to the statistical analysis of changes in climate parameters. The course aims at qualifying the students to structure the physical and chemical basics of the climate system including relevant feedbacks. The students can evaluate relevant drivers of climate variability and change on various temporal and spatial scales and can transform knowledge from climate history to the present and the future. Special focus is given to the assessment of uncertainties related to climate observations and projections as well as the specific challenges of extreme weather and climate events. At the end of the course the students are able to critically reflect and evaluate climate change related results of scientific studies and related issues in media. The course is divided into two parts - "Climate Change" and "Climate Data Analysis" and encompasses two lectures, one seminar and one exercise. The weekly "Climate change" lecture transmits the physical and chemical background for climate variation and change. (Pre)historical, observed and projected climate changes and their effects on various sectors are being introduced and discussed regarding their implications for society, economics, ecology and politics. The related seminar presents and discusses the multiple reasons for controversy in climate change issues, based on various texts. Students train the presentation of scientific content and the discussion of climate change aspects. The biweekly lecture on "Climate data analysis" introduces the most relevant statistical tools and methods in climate science. Starting with checking data quality via tools of exploratory

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

    Science.gov (United States)

    Gordova, Yulia; Martynova, Yulia; Shulgina, Tamara

    2014-05-01

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

  2. Projections of long-term changes in solar radiation based on CMIP5 climate models and their influence on energy yields of photovoltaic systems

    Science.gov (United States)

    Wild, Martin; Folini, Doris; Henschel, Florian; Müller, Björn

    2015-04-01

    Traditionally, for the planning and assessment of solar energy systems, the amount of solar radiation (sunlight) incident on the Earth's surface is assumed to be constant over the years. However, with changing climate and air pollution levels, solar resources may no longer be stable over time and undergo substantial decadal changes. Observational records covering the past decades confirm long-term changes in this quantity. Here we examine, how the latest generation of climate models used for the 5th IPCC report projects potential changes in surface solar radiation over the coming decades, and how this may affect, in combination with the expected greenhouse warming, solar power output from photovoltaic (PV) systems. For this purpose, projections up to the mid 21th century from 39 state of the art climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are analysed globally and for selected key regions with major solar power production capacity. The large model ensemble allows to assess the degree of consistency of their projections. Models are largely consistent in the sign of the projected changes in solar radiation under cloud-free conditions as well as in surface temperatures over most of the globe, while still reasonably consistent over a considerable part of the globe in the sign of changes in cloudiness and associated changes in solar radiation. A first order estimate of the impact of solar radiation and temperature changes on energy yields of PV systems under the RPC8.5 scenario indicates statistically significant decreases in PV outputs in large parts of the world, but notable exceptions with positive trends in parts of Europe and the South-East of China. Projected changes between 2006 and 2049 under the RCP8.5 scenario overall are on the order of 1 % per decade for horizontal planes, but may be larger for tilted or tracked planes as well as on shorter (decadal) timescales. Related References: Wild, M., Folini, D., Henschel, F., and M

  3. Weak response of the Atlantic thermohaline circulation to an increase of atmospheric carbon dioxide in IAP/LASG Climate System Model

    Institute of Scientific and Technical Information of China (English)

    ZHOU Tianjun; YU Rucong; LIU Xiying; GUO Yufu; YU Yongqiang; ZHANG Xuehong

    2005-01-01

    Response of the Atlantic thermohaline circula- tion (THC) to global warming is examined by using the climate system model developed at IAP/LASG. The evidence indicates that the gradually warming climate associated with the increased atmospheric carbon dioxide leads to a warmer and fresher sea surface water at the high latitudes of the North Atlantic Ocean, which prevents the down-welling of the surface water. The succedent reduction of the pole-to- equator meridional potential density gradient finally results in the decrease of the THC in intensity. When the atmospheric carbon dioxide is doubled, the maximum value of the Atlantic THC decreases approximately by 8%. The associated poleward oceanic heat transport also becomes weaker. This kind of THC weakening centralizes mainly in the northern part of the North Atlantic basin, indicating briefly a local scale adjustment rather than a loop oscillation with the whole Atlantic "conveyor belt" decelerating.

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

    Science.gov (United States)

    Semenov, M. A.

    2009-04-01

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

  5. Arctic Climate Forcing Observations to Improve Earth System Models: Measurements at High Frequency, Fine Spatial Resolution, and Climatically Relevant Spatial Scales with the use of the Recently Deployed NGEE-Arctic Tram

    Science.gov (United States)

    Curtis, J. B.; Serbin, S.; Dafflon, B.; Raz Yaseef, N.; Torn, M. S.; Cook, P. J.; Lewin, K. F.; Wullschleger, S. D.

    2014-12-01

    In order to improve the representation of the land surface and subsurface properties and their associated feedbacks with climate forcings, climate change, and drivers in Earth System Models (ESMs), detailed observations need to be made at climatically relevant spatial and temporal scales. Pan-Arctic spatial heterogeneity and temporal variation present major challenges to the current generation of ESMs. To enable highly spatially resolved and high temporal frequency measurements for the independent validation of modeled energy and greenhouse gas surface fluxes at core to intermediate scales, we have developed, tested, and deployed an automated observational platform, the Next Generation Ecosystem Experiment (NGEE)-Arctic Tram. The NGEE-Arctic Tram, installed on the Barrow Environmental Observatory (BEO) near Barrow, AK in mid May 2014, consists of 65 meters of elevated track and a fully automated cart carrying a suite of radiation and remote sensing instrumentation. The tram transect is located within the NGEE eddy covariance tower footprint to help better understand the relative contribution of different landforms (e.g. low center vs high center polygonal tundra and associated vegetation) to the overall energy budget of the footprint. Electrical resistivity tomography (ERT), soil moisture, and soil temperature sensors are acquired autonomously and co-located with the tram to link subsurface properties with surface observations. To complement the high frequency and fine spatial resolution of the tram, during the summer field seasons of 2013 and 2014 a portable version of the NGEE-Arctic Tram (also know as the portable energy pole or PEP); was used to characterize surface albedo, NDVI, surface temperature, and photosynthetically active radiation (PAR) across two ~500 m BEO transects co-located with subsurface ERT and ground penetrating radar (GPR) measurements. In addition, a ~ 3 Km transect across three drained thaw-lake basins (DTLB) of different climate

  6. Global off-line evaluation of the ISBA-TRIP continental hydrological system used in the CNRM-CM6 climate model for the next CMIP6 exercise

    Science.gov (United States)

    Decharme, Bertrand; Vergnes, Jean-Pierre; Minvielle, Marie; Colin, Jeanne; Delire, Christine

    2016-04-01

    The land surface hydrology represents an active component of the climate system. It is likely to influence the water and energy exchanges at the land surface, the ocean salinity and temperature at the mouth of the largest rivers, and the climate at least at the regional scale. In climate models, the continental hydrology is simulated via Land Surface Models (LSM), which compute water and energy budgets at the surface, coupled to River Routing Model (RRM), which convert the runoff simulated by the LSMs into river discharge in order to transfer the continental fresh water into the oceans and then to close the global hydrological cycle. Validating these Continental Hydrological Systems (CHS) at the global scale is therefore a crucial task, which requires off-line simulations driven by realistic atmospheric fluxes to avoid the systematic biases commonly found in the atmospheric models. In the CNRM-CM6 climate model of Météo-France, that will be used for the next Coupled Climate Intercomparison Project phase 6 (CMIP6) exercise, the land surface hydrology is simulated using the ISBA-TRIP CHS coupled via the OASIS-MCT coupler. The ISBA LSM solves explicitly the one dimensional Fourier law for soil temperature and the mixed form of the Richards equation for soil moisture using a 14-layers discretization over 12m depths. For the snowpack, a discretization using 12 layers allows the explicit representation of some snow key processes as its viscosity, its compaction due to wind, its age and its albedo on the visible and near infrared spectra. The TRIP RRM uses a global river channel network at 0.5° resolution. It is based on a three prognostic equations for the surface stream water, the seasonal floodplains, and the groundwater. The streamflow velocity is computed using the Maning's formula. The floodplain reservoir fills when the river height exceeds the river bankfull height and vice-versa. The flood interacts with the ISBA soil hydrology through infiltration and with

  7. An Appraisal of Coupled Climate Model Simulations

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-02-24

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

  8. Global climate models: Past, present, and future

    OpenAIRE

    Stute, Martin; Clement, Amy; Lohmann, Gerrit

    2001-01-01

    One of the main features of climate spectra is their redness which originates from stochastic mechanisms (see e.g. the time scale arguments of Hasselmann, 1976). The variance increases toward the longer time scales and is limited by the negative feedback mechanisms in the climate system. Apart from this there is climate variability at distinct time scales due to external forcing (e.g. Milankowitch cycles), or internal oscillations (e.g. ENSO, decadal oscillations). The understanding of long-t...

  9. Impact of biodiversity-climate futures on primary production and metabolism in a model benthic estuarine system

    Directory of Open Access Journals (Sweden)

    Raffaelli Dave

    2011-02-01

    Full Text Available Abstract Background Understanding the effects of anthropogenically-driven changes in global temperature, atmospheric carbon dioxide and biodiversity on the functionality of marine ecosystems is crucial for predicting and managing the associated impacts. Coastal ecosystems are important sources of carbon (primary production to shelf waters and play a vital role in global nutrient cycling. These systems are especially vulnerable to the effects of human activities and will be the first areas impacted by rising sea levels. Within these coastal ecosystems, microalgal assemblages (microphytobenthos: MPB are vital for autochthonous carbon fixation. The level of in situ production by MPB mediates the net carbon cycling of transitional ecosystems between net heterotrophic or autotrophic metabolism. In this study, we examine the interactive effects of elevated atmospheric CO2 concentrations (370, 600, and 1000 ppmv, temperature (6°C, 12°C, and 18°C and invertebrate biodiversity on MPB biomass in experimental systems. We assembled communities of three common grazing invertebrates (Hydrobia ulvae, Corophium volutator and Hediste diversicolor in monoculture and in all possible multispecies combinations. This experimental design specifically addresses interactions between the selected climate change variables and any ecological consequences caused by changes in species composition or richness. Results The effects of elevated CO2 concentration, temperature and invertebrate diversity were not additive, rather they interacted to determine MPB biomass, and overall this effect was negative. Diversity effects were underpinned by strong species composition effects, illustrating the importance of individual species identity. Conclusions Overall, our findings suggest that in natural systems, the complex interactions between changing environmental conditions and any associated changes in invertebrate assemblage structure are likely to reduce MPB biomass. Furthermore

  10. MOSAICC: An inter-disciplinary system of models to evaluate the impact of climate change on agriculture.

    NARCIS (Netherlands)

    Poortinga, A.; Delobel, F.; Rojas, O.

    2012-01-01

    ABSTRACT Climate change potentially threatens the livelihood of many people who depend on local food production. Information from different disciplines has become an essential to estimate and predict the impact of climate change on local food production. However, data is often scattered and specific

  11. 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.

  12. Training a Data Scientist: A Multi-year, Multi-Project View from the Trenches of the Regional Climate Model Evaluation System at the Jet Propulsion Laboratory

    Science.gov (United States)

    Whittell, J.

    2013-12-01

    Society and technology growth has lead to an age of voluminous, heterogeneous data that requires timely analysis. There are many instruments, models and experiments that generate large amounts of data in various formats, resolutions and location. The answers to the questions posed are embedded in these big data that require the formidable task of data handling, manipulation, visualization and storage. To navigate this space persons with experience handling these data and also with some (high-level or deeper) knowledge of the science that these data represent are necessary. Persons with this unique set of skills are data scientists. Most data scientists possess a cross-disciplinary approach to their research/work, but few actually possess a true inter-disciplinary background and expertise that is demanded of the profession. This poster outlines a method in which a young person was introduced to data science from an inter-disciplinary perspective within the STEM disciplines. The Regional Climate Model Evaluation System (RCMES, http://rcmes.jpl.nasa.gov) at NASA's Jet Propulsion Laboratory seeks to improve regional climate model evaluation by comparing past model predictions with observation datasets including those originating from Earth-orbiting satellite data. The successful development of the RCMES software package relies on collaboration between climate scientists and computer scientists, as evidenced by the RCMES team's longstanding work with the International Coordinated Regional Downscaling Experiment (CORDEX), a large, multidisciplinary modeling group focused on regional downscaling. Over a total of 17 weeks during the summers of 2011, 2012, and 2013, a high school student, with no formal background in either the earth sciences or computer technology, was immersed (interned) with the RCMES team. This student successfully provided support on both disciplines of the project and developed their 'data scientist toolkit' through learning about the science involved

  13. Developing a Common Information Model for climate models and data

    Science.gov (United States)

    Valcke, S.; Balaji, V.; Bentley, P.; Guilyardi, E.; Lawrence, B.; Pascoe, C.; Steenman-Clark, L.; Toussaint, F.; Treshansky, A.

    2009-04-01

    The Metafor project, funded under the EU Framework Programme 7, proposes a Common Information Model (CIM) to describe in a standard way climate data and the models and modelling environments that produced this data. To establish the CIM, Metafor first considered the metadata models developed by other groups engaged in similar efforts in Europe and worlwide, such as the US Earth System Curator, explored fragmentation and gaps as well as duplication of information present in these metadata models, and reviewed current problems in identifying, accessing or using climate data present in existing repositories. Based on this analysis and on different use cases, the first version of the CIM is composed of 5 packages. The "data" package is used to describe the data objects that can be collected and stored in any number of ways; the "activity" package details the simulations and experiments and related requirements that were performed with numerical (possibly coupled) models described with the "software" packages. Both data and models can be associated with numerical grids represented by the "grid" package and finally the "shared" package gathers concepts shared among the other packages. The CIM is defined and implemented in the Unified Modelling Language (UML) and application schema have been generated in XML schema. Aiming at a wide adoption of the CIM, Metafor will optimize the way climate data infrastructures are used to store knowledge, thereby adding value to primary research data and information, and providing an essential asset for the numerous stakeholders actively engaged in climate change issues (policy, research, impacts, mitigation, private sector).

  14. Evaluating models of climate and forest vegetation

    Science.gov (United States)

    Clark, James S.

    1992-01-01

    Understanding how the biosphere may respond to increasing trace gas concentrations in the atmosphere requires models that contain vegetation responses to regional climate. Most of the processes ecologists study in forests, including trophic interactions, nutrient cycling, and disturbance regimes, and vital components of the world economy, such as forest products and agriculture, will be influenced in potentially unexpected ways by changing climate. These vegetation changes affect climate in the following ways: changing C, N, and S pools; trace gases; albedo; and water balance. The complexity of the indirect interactions among variables that depend on climate, together with the range of different space/time scales that best describe these processes, make the problems of modeling and prediction enormously difficult. These problems of predicting vegetation response to climate warming and potential ways of testing model predictions are the subjects of this chapter.

  15. Use of the computational-informational web-GIS system for the development of climatology students' skills in modeling and understanding climate change

    Science.gov (United States)

    Gordova, Yulia; Martynova, Yulia; Shulgina, Tamara

    2015-04-01

    The current situation with the training of specialists in environmental sciences is complicated by the fact that the very scientific field is experiencing a period of rapid development. Global change has caused the development of measurement techniques and modeling of environmental characteristics, accompanied by the expansion of the conceptual and mathematical apparatus. Understanding and forecasting processes in the Earth system requires extensive use of mathematical modeling and advanced computing technologies. As a rule, available training programs in the environmental sciences disciplines do not have time to adapt to such rapid changes in the domain content. As a result, graduates of faculties do not understand processes and mechanisms of the global change, have only superficial knowledge of mathematical modeling of processes in the environment. They do not have the required skills in numerical modeling, data processing and analysis of observations and computation outputs and are not prepared to work with the meteorological data. For adequate training of future specialists in environmental sciences we propose the following approach, which reflects the new "research" paradigm in education. We believe that the training of such specialists should be done not in an artificial learning environment, but based on actual operating information-computational systems used in environment studies, in the so-called virtual research environment via development of virtual research and learning laboratories. In the report the results of the use of computational-informational web-GIS system "Climate" (http://climate.scert.ru/) as a prototype of such laboratory are discussed. The approach is realized at Tomsk State University to prepare bachelors in meteorology. Student survey shows that their knowledge has become deeper and more systemic after undergoing training in virtual learning laboratory. The scientific team plans to assist any educators to utilize the system in earth

  16. Modelling the long-term morphological evolution of a coupled open coast, inlet and estuary system to explore climate change impacts

    Science.gov (United States)

    van Maanen, Barend; Walkden, Mike; Barnes, John; Nicholls, Robert

    2016-04-01

    Coastal and shoreline management increasingly needs to account for morphological change occurring at decadal to centennial timescales. Critical aspects of geomorphic behaviour at these temporal scales emerge at a system level, such that accounting for the feedbacks between different landform components is of key importance. In this study we develop new methods to simulate the large-scale evolution of a coupled open coast - inlet - estuary system, allowing us to explore the system's response to climate change impacts and management interventions. The system explored here encompasses the Deben estuary (eastern England) and its adjacent shorelines. The estuary itself mainly consists of finer sediments. Sediments throughout the inlet, on the other hand, including the ebb-tidal delta itself, comprise a mixture of gravel and sand. The ebb-tidal shoals and sediment bypassing show broadly cyclic behaviour on a 10 to 30 year timescale. Neighbouring beaches consist of mixed sediment and are partially backed up by sedimentary cliffs, the behaviour of which is potentially influenced by the sediment bypassing at the inlet. In addition, the open coast has undergone major transformations as a result of numerous sea defences which have altered sediment availability and supply. The interlinked behaviour of this system is approached by coupling a new inlet model (MESO_i) with an existing, and recently extended, model for the open coast (SCAPE+). MESOi simulates the evolution at the mouth of the Deben at an aggregated scale, conceptualizing the inlet by different geomorphic features that are characterized mainly by their volume. The behaviour of the inlet shoals is influenced by the estuarine tidal prism, linking estuarine processes with inlet dynamics. SCAPE+ computes the shaping of the shore profile and has proven capable of providing valuable information in terms of decadal evolution and related cliff recession rates. Simulations conducted with this composition of models highlight

  17. 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.

  18. An analysis of long-term climate change mitigation in power generation sector by using a world energy systems model

    International Nuclear Information System (INIS)

    Development and diffusion of various technologies are important for reducing CO2 emission. In power generation sector, nuclear power generation, CO2 capture and storage, and renewable energies such as wind power and PV are hoped as effective technologies for reducing CO2 emission. However, social acceptance, cost, supply potential and etc. are problems to be solved for their diffusion. In this paper, climate change mitigations in power generation sector for four scenarios with considering uncertainty of the above three technologies were quantitatively analyzed by using DNE21+. Model analysis reveals that 1) If the three technologies are developed and diffused, CO2 shadow price for achieving 450 ppm CO2 is $100/tCO2 in the year 2050. 2) If technology development and diffusion are stagnant, the CO2 shadow price for achieving 450 ppm CO2 are risen up and the price are $149/tCO2 - $334/tCO2 in the year 2050, 3) Power generation sector play an important role for CO2 emission reduction. Large CO2 emission reduction is really difficult without technology development and diffusion of power generation sector. (author)

  19. Statistical Properties of Downscaled CMIP3 Global Climate Model Simulations

    Science.gov (United States)

    Duffy, P.; Tyan, S.; Thrasher, B.; Maurer, E. P.; Tebaldi, C.

    2009-12-01

    Spatial downscaling of global climate model projections adds physically meaningful spatial detail, and brings the results down to a scale that is more relevant to human and ecological systems. Statistical/empirical downscaling methods are computationally inexpensive, and thus can be applied to large ensembles of global climate model projections. Here we examine some of the statistical properties of a large ensemble of empirically downscale global climate projections. The projections are the CMIP3 global climate model projections that were performed by modeling groups around the world and archived by the Program for Climate Model Diagnosis and Intercomparison at Lawrence Livermore National Laboratory. Downscaled versions of 112 of these simulations were created on 2007 and are archived at http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/dcpInterface.html. The downscaling methodology employed, “Bias Correction/Spatial Downscaling” (BCSD), includes a correction of GCM biases relative to observations during a historical reference period, as well as empirical downscaling to grid scale of ~12 km. We analyzed these downscaled projections and some of the original global model results to assess effects of the bias correction and downscaling on the statistical properties of the ensemble. We also assessed uncertainty in the climate response to increased greenhouse gases from initial conditions relative to the uncertainty introduced by choice of global climate model.

  20. Impacts of trait variation through observed trait-climate relationships on performance of a representative Earth System model: a conceptual analysis

    Directory of Open Access Journals (Sweden)

    L. M. Verheijen

    2012-12-01

    Full Text Available In current dynamic global vegetation models (DGVMs, including those incorporated into Earth System Models (ESMs, terrestrial vegetation is represented by a small number of plant functional types (PFTs, each with fixed properties irrespective of their predicted occurrence. This contrasts with natural vegetation, in which many plant traits vary systematically along geographic and environmental gradients. In the JSBACH DGVM, which is part of the MPI-ESM, we allowed three traits (specific leaf area (SLA, maximum carboxylation rate at 25 °C (Vcmax25 and maximum electron transport rate (Jmax25 to vary within PFTs via trait-climate relationships based on a large trait database. For all three traits, the means of observed natural trait values strongly deviated from values used in the default model, with mean differences of 32.3% for Vcmax25, 26.8% for Jmax25 and 17.3% for SLA. Compared to the default simulation, allowing trait variation within PFTs resulted in GPP differences up to 50% in the tropics, in > 35% different dominant vegetation cover, and a closer match with a natural vegetation map. The discrepancy between default trait values and natural trait variation, combined with the substantial changes in simulated vegetation properties, together emphasize that incorporating observational data based on the ecological concepts of environmental filtering will improve the modeling of vegetation behavior in DGVMs and as such will enable more reliable projections in unknown climates.

  1. Paleoclimatology: a survey on ancient climates. Volume 1 - To find, date and interpret indices; Volume 2 - To fit the puzzle pieces one to the other: to understand and model a complex system

    International Nuclear Information System (INIS)

    The first volume of this collective publication gathers contributions on techniques used to reconstruct past climates. The chapters address the climate system operation and history (evolution, mechanisms, the atmosphere, oceans, ground and marine biosphere, cryo-sphere, lithosphere), propose an introduction to geochronology, present and discuss various dating methods (carbon 14, K-Ar and Ar-Ar methods, dating of corals and other geological samples based the disequilibrium between uranium and thorium isotopes, use of magnetic stratigraphy, dendro-chronology, dating of ice archives), discuss how to reconstruct atmosphere physics and circulation, address the use and properties of different interfaces (air-ice with polar ices, air-plants with pollen, air-soil with loessic sequences as markers of atmospheric circulation or reconstruction of paleo-climates with speleothems, air-lake, plant-atmosphere, air-plant, air-water, air-ice in tropical glaciers), and discuss the use of paleo-oceanography data. The second volume gathers contributions in which the authors present the most recent approaches used to reconstruct the operation of the climate system in the past by using present observations and models. The chapters address the biochemistry of the climate system during the last million of years, the relationship between cryo-sphere and sea level, the climate at the scale of geological times, modelling approaches in paleoclimatology, the Precambrian climate, the Phanerozoic climates, the relationship between climate and astronomic cycles, the description and mechanisms of quick climate variability, the Holocene and the anthropogenic perturbation, and the evolution from past climates to future climates

  2. Validating predictions from climate envelope models.

    Science.gov (United States)

    Watling, James I; Bucklin, David N; Speroterra, Carolina; Brandt, Laura A; Mazzotti, Frank J; Romañach, Stephanie S

    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. PMID

  3. Diagnosing the average spatio-temporal impact of convective systems – Part 1: A methodology for evaluating climate models

    Directory of Open Access Journals (Sweden)

    M. S. Johnston

    2013-05-01

    Full Text Available A~method to determine the mean response of upper tropospheric water to localised deep convective (DC events is improved and applied to the EC-Earth climate model. Following Zelinka and Hartmann (2009, several fields related to moist processes and radiation are composited with respect to local maxima in rain rate to determine their spatio-temporal evolution with deep convection in the central Pacific Ocean. Major improvements to the above study are the isolation of DC events in time so as to prevent multiple sampling of the same event, and a revised definition of the mean background state that allows for better characterization of the DC-induced anomalies. The DC events observed in this study propagate westward at ~ 4 m s−1. Both the upper tropospheric relative humidity and outgoing longwave radiation are substantially perturbed over a broad horizontal extent during peak convection and for long periods of time. Cloud fraction anomaly increases throughout the upper troposphere, especially in the 200–250 hPa layer, reaching peak coverage following deep convection. Cloud ice water content anomaly confined to pressures greater than about 250 hPa and peaks near 450 hPa within a few hours of the DC event but remain enhanced following the DC event. Consistent with the large increase in upper tropospheric cloud ice, albedo increases dramatically and persists for sometime following the DC event. Applying the method to the model demonstrates that it is able to capture the large-scale responses to DC events, most notably for outgoing longwave radiation, but there are a number of important differences. For example, the DC signature of upper tropospheric humidity consistently covers a broader horizontal area than what is observed. In addition, the DC events move eastward in the model, but westward in the observations, and exhibit an unrealistic 24 h repeat cycle. Moreover, the modeled upper tropospheric cloud fraction anomalies – despite being of

  4. 7th International Seminar on Climate System and Climate Change(ISCS) through the Eyes of a Trainee

    Institute of Scientific and Technical Information of China (English)

    Karen K.Y.Shum

    2010-01-01

    @@ At the invitation of Dr.Dahe Qin,the president of ISCS and the Co-Chair of IPCC WGI,the Hong Kong Observatory has been obliged to participate and benefit from the International Seminar in Beijing,China on 19-30 July 2010.Seminar topics included atmospheric chemistry and climate effects of aerosol biogeochemical cycles,cryosphere and its role in the climate system and climate change,climate models and its application in climate change research,climate change adaptation and mitigation.Data is a common ground for these multi-disciplinary studies around the globe.

  5. Dynamic modeling of the Ganga river system: impacts of future climate and socio-economic change on flows and nitrogen fluxes in India and Bangladesh.

    Science.gov (United States)

    Whitehead, P G; Sarkar, S; Jin, L; Futter, M N; Caesar, J; Barbour, E; Butterfield, D; Sinha, R; Nicholls, R; Hutton, C; Leckie, H D

    2015-06-01

    This study investigates the potential impacts of future climate and socio-economic change on the flow and nitrogen fluxes of the Ganga river system. This is the first basin scale water quality study for the Ganga considering climate change at 25 km resolution together with socio-economic scenarios. The revised dynamic, process-based INCA model was used to simulate hydrology and water quality within the complex multi-branched river basins. All climate realizations utilized in the study predict increases in temperature and rainfall by the 2050s with significant increase by the 2090s. These changes generate associated increases in monsoon flows and increased availability of water for groundwater recharge and irrigation, but also more frequent flooding. Decreased concentrations of nitrate and ammonia are expected due to increased dilution. Different future socio-economic scenarios were found to have a significant impact on water quality at the downstream end of the Ganga. A less sustainable future resulted in a deterioration of water quality due to the pressures from higher population growth, land use change, increased sewage treatment discharges, enhanced atmospheric nitrogen deposition, and water abstraction. However, water quality was found to improve under a more sustainable strategy as envisaged in the Ganga clean-up plan. PMID:25692851

  6. From snowball to moist greenhouse: the climatological evolution of Earth-analog planets simulated with a 3D climate system model

    Science.gov (United States)

    Wolf, Eric T.; Kopparapu, Ravi; Haqq-Misra, Jacob; Toon, Owen Brian

    2015-12-01

    The host star imposes a primary control on terrestrial planet climate. Both the spectral energy distribution and the main sequence lifetime vary as a function of stellar type. Here we present recent results from three-dimensional climate system models describing the evolutionary sequence of Earth-analog planets throughout their habitable lifetimes. Climatological evolution is traced from snowball to moist greenhouse, representing the conventional end-member states of the habitable zone. For Earth the habitable period would have been tantalizingly short, if not for geological and biological regulation of greenhouse gases. Without active carbon cycling, an early snowball could not have been broken until late in Earth’s history. Abrupt solar driven deglaciation would soon be followed by the onset of the water vapor greenhouse feedback and a moist greenhouse climate, leaving little over 1 billion years of habitable surface conditions. Around bluer stars, the habitable period for terrestrial planets is constricted further due to their reduced main sequence lifetimes and thus more rapid brightening. Planets with long-lived habitable periods are most likely found around stars redder than the Sun due to their more gradual brightening.

  7. Long-term Archiving of Climate Model Data at WDC Climate and DKRZ

    OpenAIRE

    M. Lautenschlager; Stahl, W

    2007-01-01

    The computing capabilities for production of Earth system model data are growing faster than the prices for mass storage media sink. If the archive philosophy left unchanged during the migration to the next compute server generation consequently the amount of money for long-term archiving rises and the total amount of money for archiving tends to exceed the money which is left for compute services. At WDCC (World Data Center Climate) and DKRZ (German Climate Computing Centre) a new conc...

  8. A Water Balance Model for assessing Hydro Climatic Variability in Tropical Lake Systems: Application to Lake Babati and Lake Emakat, Nothern Tanzania

    Science.gov (United States)

    Pericles Mbanguka, Rene; Girons Lopez, Marc; Jarsjö, Jerker

    2013-04-01

    A comprehensive understanding of lake hydrology is important to enhance the interpretation of information on past climatic variations retained in tropical lakes as well as to investigate the effect of future climate conditions on lake ecosystems. In this study, a lumped water balance model is developed to describe historical lake water levels and to investigate the impacts of hydro-climatological changes on Lake Emakat and Lake Babati, two closed tropical lakes in Northern Tanzania (East Africa). The model concept is based on maintaining the water mass balance of the lake system, which is simplified into three main modules: the lake, its catchment area and the connected groundwater reservoir. Water mass exchanges with the atmosphere occur through precipitation, the main input, and evaporation, calculated from meteorological variables using two different energy balance equations. The model also integrates lake and groundwater interaction, by letting the lake water surface balance with the water table in the surrounding groundwater reservoir after every time step. A FORTRAN code is used to solve the water balance equation on a year time step and give the lake volume change resulting from meteorological inputs. The associated lake surface area and lake level are then determined from a depth-volume-area relationship developed from a high resolution bathymetric and topographical maps of the lake and its catchment. The model parameters were calibrated using available meteorological data and corresponding lake level records. A sensitivity study to assess the relative importance of different hydro-meteorological parameters on the model response indicates that changes in cloud fraction have the largest impact on evaporation, the most important component of the water mass balance. This parameter, therefore, proved to be one of the ultimate control factors of the lakes water balance. The model application to Lake Emakat suggests that precipitation and cloud fraction changes

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

    Institute of Scientific and Technical Information of China (English)

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

    2005-01-01

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

  10. Towards Fully Coupled Atmosphere-Hydrology Model Systems: Recent Developments and Performance Evaluation For Different Climate Regions

    Science.gov (United States)

    Kunstmann, Harald; Fersch, Benjamin; Rummler, Thomas; Wagner, Sven; Arnault, Joel; Senatore, Alfonso; Gochis, David

    2015-04-01

    Limitations in the adequate representation of terrestrial hydrologic processes controlling the land-atmosphere coupling are assumed to be a significant factor currently limiting prediction skills of regional atmospheric models. The necessity for more comprehensive process descriptions accounting for the interdependencies between water- and energy fluxes at the compartmental interfaces are driving recent developments in hydrometeorological modeling towards more sophisticated treatment of terrestrial hydrologic processes. It is particularly the lateral surface and subsurface water fluxes that are neglected in standard regional atmospheric models. Current developments in enhanced lateral hydrological process descriptions in the WRF model system will be presented. Based on WRF and WRF-Hydro, new modules and concepts for integrating the saturated zone by a 2-dim groundwater scheme and coupling approaches to the unsaturated zone will be presented. The fully coupled model system allows to model the complete regional water cycle, from the top of the atmosphere, via the boundary layer, the land surface, the unsaturated zone and the saturated zone till the flow in the river beds. With this increasing complexity, that also allows to describe the complex interaction of the regional water cycle on different spatial and temporal scales, the reliability and predictability of model simulations can only be shown, if performance is tested for a variety of hydrological variables for different climatological environments. We will show results of fully coupled simulations for the regions of sempiternal humid Southern Bavaria/Germany (rivers Isar and Ammer) and semiarid to subhumid Westafrica (river Sissilli). In both regions, in addition to streamflow measurements, also the validation of heat fluxes is possible via Eddy-Covariance stations within hydrometeorological testbeds. In the German Isar/Ammer region, e.g., we apply the extended WRF-Hydro modeling system in 3km atmospheric- grid

  11. 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.

  12. Management system, organizational climate and performance relationships

    Science.gov (United States)

    Davis, B. D.

    1979-01-01

    Seven aerospace firms were investigated to determine if a relationship existed among management systems, organizational climate, and organization performance. Positive relationships were found between each of these variables, but a statistically significant relationship existed only between the management system and organizational climate. The direction and amount of communication and the degree of decentralized decision-making, elements of the management system, also had a statistically significant realtionship with organization performance.

  13. The impact of climate change on the European energy system

    International Nuclear Information System (INIS)

    Climate change can affect the economy via many different channels in many different sectors. The POLES global energy model has been modified to widen the coverage of climate change impacts on the European energy system. The impacts considered are changes in heating and cooling demand in the residential and services sector, changes in the efficiency of thermal power plants, and changes in hydro, wind (both on- and off-shore) and solar PV electricity output. Results of the impacts of six scenarios on the European energy system are presented, and the implications for European energy security and energy imports are presented. Main findings include: demand side impacts (heating and cooling in the residential and services sector) are larger than supply side impacts; power generation from fossil-fuel and nuclear sources decreases and renewable energy increases; and impacts are larger in Southern Europe than in Northern Europe. There remain many more climate change impacts on the energy sector that cannot currently be captured due to a variety of issues including: lack of climate data, difficulties translating climate data into energy-system-relevant data, lack of detail in energy system models where climate impacts act. This paper does not attempt to provide an exhaustive analysis of climate change impacts in the energy sector, it is rather another step towards an increasing coverage of possible impacts. - Highlights: • Expanded coverage of climate change impacts on European energy system. • Demand side impacts are larger than supply side impacts. • Power from fossil and nuclear sources decreases, renewable energy increases. • Impacts are larger in Southern Europe than in Northern Europe. • Synergies exist between climate change mitigation and climate change adaptation

  14. The origins of computer weather prediction and climate modeling

    Science.gov (United States)

    Lynch, Peter

    2008-03-01

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

  15. The origins of computer weather prediction and climate modeling

    International Nuclear Information System (INIS)

    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

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

    Directory of Open Access Journals (Sweden)

    J. Brandefelt

    2011-01-01

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

  17. Assessing Climate Impacts on Air Pollution from Models and Measurements

    Science.gov (United States)

    Holloway, T.; Plachinski, S. D.; Morton, J. L.; Spak, S.

    2011-12-01

    It is well known that large-scale patterns in temperature, humidity, solar radiation and atmospheric circulation affect formation and transport of atmospheric constituents. These relationships have supported a growing body of work projecting changes in ozone (O3), and to a lesser extent aerosols, as a function of changing climate. Typically, global and regional chemical transport models are used to quantify climate impacts on air pollution, but the ability of these models to assess weather-dependent chemical processes has not been thoroughly evaluated. Quantifying model sensitivity to climate poses the additional challenge of isolating the local to synoptic scale effects of meteorological conditions on chemistry and transport from concurrent trends in emissions, hemispheric background concentrations, and land cover change. Understanding how well models capture historic climate-chemistry relationships is essential in projecting future climate impacts, in that it allows for better evaluation of model skill and improved understanding of climate-chemistry relationships. We compare the sensitivity of chemistry-climate relationships, as simulated by the EPA Community Multiscale Air Quality (CMAQ) model, with observed historical response characteristics from EPA Air Quality System (AQS) monitoring data. We present results for O3, sulfate and nitrate aerosols, and ambient mercury concentrations. Despite the fact that CMAQ over-predicts daily maximum 8-hour ground-level O3 concentrations relative to AQS data, the model does an excellent job at simulating the response of O3 to daily maximum temperature. In both model and observations, we find that higher temperatures produce higher O3 across most of the U.S., as expected in summertime conditions. However, distinct regions appear in both datasets where temperature and O3 are anti-correlated - for example, over the Upper Midwestern U.S. states of Iowa, Missouri, Illinois, and Indiana in July 2002. Characterizing uncertainties

  18. Climate Change Impact Assessments for International Market Systems (CLIMARK)

    Science.gov (United States)

    Winkler, J. A.; Andresen, J.; Black, J.; Bujdoso, G.; Chmielewski, F.; Kirschke, D.; Kurlus, R.; Liszewska, M.; Loveridge, S.; Niedzwiedz, T.; Nizalov, D.; Rothwell, N.; Tan, P.; Ustrnul, Z.; von Witzke, H.; Zavalloni, C.; Zhao, J.; Zhong, S.

    2012-12-01

    The vast majority of climate change impact assessments evaluate how local or regional systems and processes may be affected by a future climate. Alternative strategies that extend beyond the local or regional scale are needed when assessing the potential impacts of climate change on international market systems, including agricultural commodities. These industries have multiple production regions that are distributed worldwide and are likely to be differentially impacted by climate change. Furthermore, for many industries and market systems, especially those with long-term climate-dependent investments, temporal dynamics need to be incorporated into the assessment process, including changing patterns of international trade, consumption and production, and evolving adaptation strategies by industry stakeholder groups. A framework for conducting climate change assessments for international market systems, developed as part of the CLIMARK (Climate Change and International Markets) project is outlined, and progress toward applying the framework for an impact assessment for the international tart cherry industry is described. The tart cherry industry was selected for analysis in part because tart cherries are a perennial crop requiring long-term investments by the producer. Components of the project include the preparation of fine resolution climate scenarios, evaluation of phenological models for diverse production regions, the development of a yield model for tart cherry production, new methods for incorporating individual decision making and adaptation options into impact assessments, and modification of international trade models for use in impact studies. Innovative aspects of the project include linkages between model components and evaluation of the mega-uncertainty surrounding the assessment outcomes. Incorporation of spatial and temporal dynamics provides a more comprehensive evaluation of climate change impacts and an assessment product of potentially greater

  19. The evolution of sub-monsoon systems in the Afro-Asian monsoon region during the Holocene- comparison of different transient climate model simulations

    Science.gov (United States)

    Dallmeyer, A.; Claussen, M.; Fischer, N.; Haberkorn, K.; Wagner, S.; Pfeiffer, M.; Jin, L.; Khon, V.; Wang, Y.; Herzschuh, U.

    2015-02-01

    The recently proposed global monsoon hypothesis interprets monsoon systems as part of one global-scale atmospheric overturning circulation, implying a connection between the regional monsoon systems and an in-phase behaviour of all northern hemispheric monsoons on annual timescales (Trenberth et al., 2000). Whether this concept can be applied to past climates and variability on longer timescales is still under debate, because the monsoon systems exhibit different regional characteristics such as different seasonality (i.e. onset, peak and withdrawal). To investigate the interconnection of different monsoon systems during the pre-industrial Holocene, five transient global climate model simulations have been analysed with respect to the rainfall trend and variability in different sub-domains of the Afro-Asian monsoon region. Our analysis suggests that on millennial timescales with varying orbital forcing, the monsoons do not behave as a tightly connected global system. According to the models, the Indian and North African monsoons are coupled, showing similar rainfall trend and moderate correlation in centennial rainfall variability in all models. The East Asian monsoon changes independently during the Holocene. The dissimilarities in the seasonality of the monsoon sub-systems lead to a stronger response of the North African and Indian monsoon systems to the Holocene insolation forcing than of the East Asian monsoon and affect the seasonal distribution of Holocene rainfall variations. Within the Indian and North African monsoon domain, precipitation solely changes during the summer months, showing a decreasing Holocene precipitation trend. In the East Asian monsoon region, the precipitation signal is determined by an increasing precipitation trend during spring and a decreasing precipitation change during summer, partly balancing each other. A synthesis of reconstructions and the model results do not reveal an impact of the different seasonality on the timing of the

  20. 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

    Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations

  1. An energy balance model of carbon's effect on climate change

    CERN Document Server

    Benney, Lucas

    2015-01-01

    Due to climate change, the interest of studying our climatic system using mathematical modeling has become tremendous in recent years. One well-known model is Budyko's system, which represents the coupled evolution of two variables, the ice-line and the average earth surface temperature. The system depends on natural parameters, such as the earth albedo, and the amount A of carbon in the atmosphere. We introduce a 3-dimensional extension of this model in which we regard A as the third coupled variable of the system. We analyze the phase space and dependence on parameters, looking for Hopf bifurcations and the birth of cycling behavior. We interpret the cycles as climatic oscillations triggered by the sensitivity in our regulation of carbon emissions at extreme temperatures.

  2. DESYCO: a Decision Support System to provide climate services for coastal stakeholders dealing with climate change impacts.

    Science.gov (United States)

    Torresan, S.; Gallina, V.; Giannini, V.; Rizzi, J.; Zabeo, A.; Critto, A.; Marcomini, A.

    2012-04-01

    At the international level climate services are recognized as innovative tools aimed at providing and distributing climate data and information according to the needs of end-users. Furthermore, needs-based climate services are extremely effective to manage climate risks and take advantage of the opportunities associated with climate change impacts. To date, climate services are mainly related to climate models that supply climate data (e.g. temperature, precipitations) at different spatial and time scales. However, there is a significant gap of tools aimed at providing information about risks and impacts induced by climate change and allowing non-expert stakeholders to use both climate-model and climate-impact data. DESYCO is a GIS-Decision Support System aimed at the integrated assessment of multiple climate change impacts on vulnerable coastal systems (e.g. beaches, river deltas, estuaries and lagoons, wetlands, agricultural and urban areas). It is an open source software that manages different input data (e.g. raster or shapefiles) coming from climate models (e.g. global and regional climate projections) and high resolution impact models (e.g. hydrodynamic, hydrological and biogeochemical simulations) in order to provide hazard, exposure, susceptibility, risk and damage maps for the identification and prioritization of hot-spot areas and to provide a basis for the definition of coastal adaptation and management strategies. Within the CLIM-RUN project (FP7) DESYCO is proposed as an helpful tool to bridge the gap between climate data and stakeholder needs and will be applied to the coastal area of the North Adriatic Sea (Italy) in order to provide climate services for local authorities involved in coastal zone management. Accordingly, a first workshop was held in Venice (Italy) with coastal authorities, climate experts and climate change risk experts, in order to start an iterative exchange of information about the knowledge related to climate change, climate

  3. Modeling Renewable Water Resources under Climate Change

    Science.gov (United States)

    Liu, X.; Tang, Q.

    2014-12-01

    The impacts of climate change on renewable water resources are usually assessed using hydrological models driven by downscaled climate outputs from global climate models. Most hydrological models do not have explicit parameterization of vegetation and thus are unable to assess the effects of elevated atmospheric CO2 on stomatal conductance and water loss of leaf. The response of vegetation to elevated atmospheric CO2 would reduce evaporation and affect runoff and renewable water resources. To date, the impacts of elevated CO2 on vegetation transpiration were not well addressed in assessment of water resources under climate change. In this study, the distributed biosphere-hydrological (DBH) model, which incorporates a simple biosphere model into a distributed hydrological scheme, was used to assess the impacts of elevated CO2 on vegetation transpiration and consequent runoff. The DBH model was driven by five General Circulation Models (GCMs) under four Representative Concentration Pathways (RCPs). For each climate scenario, two model experiments were conducted. The atmospheric CO2 concentration in one experiment was assumed to remain at the level of 2000 and increased as described by the RCPs in the other experiment. The results showed that the elevated CO2 would result in decrease in evapotranspiration, increase in runoff, and have considerable impacts on water resources. However, CO2 induced runoff change is generally small in dry areas likely because vegetation is usually sparse in the arid area.

  4. Probabilistic hindcasts and projections of the coupled climate, carbon cycle and Atlantic meridional overturning circulation system: a Bayesian fusion of century-scale observations with a simple model

    Science.gov (United States)

    Urban, Nathan M.; Keller, Klaus

    2010-10-01

    How has the Atlantic Meridional Overturning Circulation (AMOC) varied over the past centuries and what is the risk of an anthropogenic AMOC collapse? We report probabilistic projections of the future climate which improve on previous AMOC projection studies by (i) greatly expanding the considered observational constraints and (ii) carefully sampling the tail areas of the parameter probability distribution function (pdf). We use a Bayesian inversion to constrain a simple model of the coupled climate, carbon cycle and AMOC systems using observations to derive multicentury hindcasts and projections. Our hindcasts show considerable skill in representing the observational constraints. We show that robust AMOC risk estimates can require carefully sampling the parameter pdfs. We find a low probability of experiencing an AMOC collapse within the 21st century for a business-as-usual emissions scenario. The probability of experiencing an AMOC collapse within two centuries is 1/10. The probability of crossing a forcing threshold and triggering a future AMOC collapse (by 2300) is approximately 1/30 in the 21st century and over 1/3 in the 22nd. Given the simplicity of the model structure and uncertainty in the forcing assumptions, our analysis should be considered a proof of concept and the quantitative conclusions subject to severe caveats.

  5. Intercomparison of the capabilities of simplified climate models to project the effects of aviation CO2 on climate

    Science.gov (United States)

    Khodayari, Arezoo; Wuebbles, Donald J.; Olsen, Seth C.; Fuglestvedt, Jan S.; Berntsen, Terje; Lund, Marianne T.; Waitz, Ian; Wolfe, Philip; Forster, Piers M.; Meinshausen, Malte; Lee, David S.; Lim, Ling L.

    2013-08-01

    This study evaluates the capabilities of the carbon cycle and energy balance treatments relative to the effect of aviation CO2 emissions on climate in several existing simplified climate models (SCMs) that are either being used or could be used for evaluating the effects of aviation on climate. Since these models are used in policy-related analyses, it is important that the capabilities of such models represent the state of understanding of the science. We compare the Aviation Environmental Portfolio Management Tool (APMT) Impacts climate model, two models used at the Center for International Climate and Environmental Research-Oslo (CICERO-1 and CICERO-2), the Integrated Science Assessment Model (ISAM) model as described in Jain et al. (1994), the simple Linear Climate response model (LinClim) and the Model for the Assessment of Greenhouse-gas Induced Climate Change version 6 (MAGICC6). In this paper we select scenarios to illustrate the behavior of the carbon cycle and energy balance models in these SCMs. This study is not intended to determine the absolute and likely range of the expected climate response in these models but to highlight specific features in model representations of the carbon cycle and energy balance models that need to be carefully considered in studies of aviation effects on climate. These results suggest that carbon cycle models that use linear impulse-response-functions (IRF) in combination with separate equations describing air-sea and air-biosphere exchange of CO2 can account for the dominant nonlinearities in the climate system that would otherwise not have been captured with an IRF alone, and hence, produce a close representation of more complex carbon cycle models. Moreover, results suggest that an energy balance model with a 2-box ocean sub-model and IRF tuned to reproduce the response of coupled Earth system models produces a close representation of the globally-averaged temperature response of more complex energy balance models.

  6. A Web-Based Geovisual Analytical System for Climate Studies

    Directory of Open Access Journals (Sweden)

    Zhenlong Li

    2012-12-01

    Full Text Available Climate studies involve petabytes of spatiotemporal datasets that are produced and archived at distributed computing resources. Scientists need an intuitive and convenient tool to explore the distributed spatiotemporal data. Geovisual analytical tools have the potential to provide such an intuitive and convenient method for scientists to access climate data, discover the relationships between various climate parameters, and communicate the results across different research communities. However, implementing a geovisual analytical tool for complex climate data in a distributed environment poses several challenges. This paper reports our research and development of a web-based geovisual analytical system to support the analysis of climate data generated by climate model. Using the ModelE developed by the NASA Goddard Institute for Space Studies (GISS as an example, we demonstrate that the system is able to (1 manage large volume datasets over the Internet; (2 visualize 2D/3D/4D spatiotemporal data; (3 broker various spatiotemporal statistical analyses for climate research; and (4 support interactive data analysis and knowledge discovery. This research also provides an example for managing, disseminating, and analyzing Big Data in the 21st century.

  7. Incorporating climate-system and carbon-cycle uncertainties in integrated assessments of climate change. (Invited)

    Science.gov (United States)

    Rogelj, J.; McCollum, D. L.; Reisinger, A.; Knutti, R.; Riahi, K.; Meinshausen, M.

    2013-12-01

    The field of integrated assessment draws from a large body of knowledge across a range of disciplines to gain robust insights about possible interactions, trade-offs, and synergies. Integrated assessment of climate change, for example, uses knowledge from the fields of energy system science, economics, geophysics, demography, climate change impacts, and many others. Each of these fields comes with its associated caveats and uncertainties, which should be taken into account when assessing any results. The geophysical system and its associated uncertainties are often represented by models of reduced complexity in integrated assessment modelling frameworks. Such models include simple representations of the carbon-cycle and climate system, and are often based on the global energy balance equation. A prominent example of such model is the 'Model for the Assessment of Greenhouse Gas Induced Climate Change', MAGICC. Here we show how a model like MAGICC can be used for the representation of geophysical uncertainties. Its strengths, weaknesses, and limitations are discussed and illustrated by means of an analysis which attempts to integrate socio-economic and geophysical uncertainties. These uncertainties in the geophysical response of the Earth system to greenhouse gases remains key for estimating the cost of greenhouse gas emission mitigation scenarios. We look at uncertainties in four dimensions: geophysical, technological, social and political. Our results indicate that while geophysical uncertainties are an important factor influencing projections of mitigation costs, political choices that delay mitigation by one or two decades a much more pronounced effect.

  8. Coupled Climate Model Simulations of a Late Cretaceous (Maastrichtian) Greenhouse Climate: Comparison with Proxy Data

    Science.gov (United States)

    Upchurch, G. R.; Kiehl, J. T.; Shields, C. A.; Scotese, C.

    2009-12-01

    Earth’s future climate is expected to warm considerably due to increased atmospheric carbon dioxide. Paleoclimate records indicate that pre-Quaternary time periods provide the best possible view of Earth under warm greenhouse conditions. Thus, past warm greenhouse climates provide an important tool to evaluate fully coupled climate models that are currently used to study future climate change. In this study, we use the Community Climate System Model (CCSM3) to investigate the climate of the latest Cretaceous (Maastrichtian). CCSM3 is a fully coupled three-dimensional global model that includes atmospheric, oceanic, sea-ice and terrestrial processes. The CCSM3 simulations employ slight modifications of the paleogeographic and global vegetation reconstructions used in earlier simulations of the late Maastrichtian with the GENESIS Earth System Model (Upchurch, Otto-Bliesner, and Scotese, 1999). CCSM3 simulations include two levels of atmospheric carbon dioxide (2XPAL and 6XPAL), best estimates of atmospheric methane, changes to low level liquid cloud properties based on the hypothesis of Kump and Pollard (2008), and different paleoelevations for the interior of Siberia. A coupled simulation of multi-century length is carried out to study steady state conditions for the surface ocean. For terrestrial regions, model mean annual temperatures and seasonality are compared with data from angiosperm leaf physiognomy, plant life form distribution, and other climatic indicators to determine how well the model represents high latitude warmth on a zonal and regional basis. Model precipitation is compared with a database of climatically restricted sediments and angiosperm leaf physiognomy for specific sites. For oceanic regions, the CCSM3 simulations are compared to marine proxies of surface and benthic temperatures, especially the δ18O of exceptionally preserved carbonate. Our simulations reproduce many features of Maastrichtian climate, such as the latitudinal gradient of

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

    Directory of Open Access Journals (Sweden)

    M. Eby

    2012-08-01

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

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

  10. Energy policies avoiding a tipping point in the climate system

    International Nuclear Information System (INIS)

    Paleoclimate evidence and climate models indicate that certain elements of the climate system may exhibit thresholds, with small changes in greenhouse gas emissions resulting in non-linear and potentially irreversible regime shifts with serious consequences for socio-economic systems. Such thresholds or tipping points in the climate system are likely to depend on both the magnitude and rate of change of surface warming. The collapse of the Atlantic thermohaline circulation (THC) is one example of such a threshold. To evaluate mitigation policies that curb greenhouse gas emissions to levels that prevent such a climate threshold being reached, we use the MERGE model of Manne, Mendelsohn and Richels. Depending on assumptions on climate sensitivity and technological progress, our analysis shows that preserving the THC may require a fast and strong greenhouse gas emission reduction from today's level, with transition to nuclear and/or renewable energy, possibly combined with the use of carbon capture and sequestration systems. - Research Highlights: → Preserving the THC may require a fast and strong greenhouse gas emission reduction. → This could be achieved through strong changes in the energy mix. → Similar results would apply to any climate system tipping points.

  11. Applying "Climate" system to teaching basic climatology and raising public awareness of climate change issues

    Science.gov (United States)

    Gordova, Yulia; Okladnikov, Igor; Titov, Alexander; Gordov, Evgeny

    2016-04-01

    While there is a strong demand for innovation in digital learning, available training programs in the environmental sciences have no time to adapt to rapid changes in the domain content. A joint group of scientists and university teachers develops and implements an educational environment for new learning experiences in basics of climatic science and its applications. This so-called virtual learning laboratory "Climate" contains educational materials and interactive training courses developed to provide undergraduate and graduate students with profound understanding of changes in regional climate and environment. The main feature of this Laboratory is that students perform their computational tasks on climate modeling and evaluation and assessment of climate change using the typical tools of the "Climate" information-computational system, which are usually used by real-life practitioners performing such kind of research. Students have an opportunity to perform computational laboratory works using information-computational tools of the system and improve skills of their usage simultaneously with mastering the subject. We did not create an artificial learning environment to pass the trainings. On the contrary, the main purpose of association of the educational block and computational information system was to familiarize students with the real existing technologies for monitoring and analysis of data on the state of the climate. Trainings are based on technologies and procedures which are typical for Earth system sciences. Educational courses are designed to permit students to conduct their own investigations of ongoing and future climate changes in a manner that is essentially identical to the techniques used by national and international climate research organizations. All trainings are supported by lectures, devoted to the basic aspects of modern climatology, including analysis of current climate change and its possible impacts ensuring effective links between

  12. A Review on Evaluation Methods of Climate Modeling

    Institute of Scientific and Technical Information of China (English)

    ZHAO; Zong-Ci; LUO; Yong; HUANG; Jian-Bin

    2013-01-01

    There is scientific progress in the evaluation methods of recent Earth system models(ESMs).Methods range from single variable to multi-variables,multi-processes,multi-phenomena quantitative evaluations in five layers(spheres)of the Earth system,from climatic mean assessment to climate change(such as trends,periodicity,interdecadal variability),extreme values,abnormal characters and quantitative evaluations of phenomena,from qualitative assessment to quantitative calculation of reliability and uncertainty for model simulations.Researchers started considering independence and similarity between models in multi-model use,as well as the quantitative evaluation of climate prediction and projection efect and the quantitative uncertainty contribution analysis.In this manuscript,the simulations and projections by both CMIP5 and CMIP3 that have been published after 2007 are reviewed and summarized.

  13. On the reduced lifetime of nitrous oxide due to climate change induced acceleration of the Brewer-Dobson circulation as simulated by the MPI Earth System Model

    Science.gov (United States)

    Kracher, D.; Manzini, E.; Reick, C. H.; Schultz, M. G.; Stein, O.

    2014-12-01

    Greenhouse gas induced climate change will modify the physical conditions of the atmosphere. One of the projected changes is an acceleration of the Brewer-Dobson circulation in the stratosphere, as it has been shown in many model studies. This change in the stratospheric circulation consequently bears an effect on the transport and distribution of atmospheric components such as N2O. Since N2O is involved in ozone destruction, a modified distribution of N2O can be of importance for ozone chemistry. N2O is inert in the troposphere and decays only in the stratosphere. Thus, changes in the exchange between troposphere and stratosphere can also affect the stratospheric sink of N2O, and consequently its atmospheric lifetime. N2O is a potent greenhouse gas with a global warming potential of currently approximately 300 CO2-equivalents in a 100-year perspective. A faster decay in atmospheric N2O mixing ratios, i.e. a decreased atmospheric lifetime of N2O, will also reduce its global warming potential. In order to assess the impact of climate change on atmospheric circulation and implied effects on the distribution and lifetime of atmospheric N2O, we apply the Max Planck Institute Earth System Model, MPI-ESM. MPI-ESM consists of the atmospheric general circulation model ECHAM, the land surface model JSBACH, and MPIOM/HAMOCC representing ocean circulation and ocean biogeochemistry. Prognostic atmospheric N2O concentrations in MPI-ESM are determined by land N2O emissions, ocean-atmosphere N2O exchange and atmospheric tracer transport. As stratospheric chemistry is not explicitly represented in MPI-ESM, stratospheric decay rates of N2O are prescribed from a MACC MOZART simulation. Increasing surface temperatures and CO2 concentrations in the stratosphere impact atmospheric circulation differently. Thus, we conduct a series of transient runs with the atmospheric model of MPI-ESM to isolate different factors governing a shift in atmospheric circulation. From those transient

  14. Thermodynamic efficiency and entropy production in the climate system.

    Science.gov (United States)

    Lucarini, Valerio

    2009-08-01

    We present an outlook on the climate system thermodynamics. First, we construct an equivalent Carnot engine with efficiency eta and frame the Lorenz energy cycle in a macroscale thermodynamic context. Then, by exploiting the second law, we prove that the lower bound to the entropy production is eta times the integrated absolute value of the internal entropy fluctuations. An exergetic interpretation is also proposed. Finally, the controversial maximum entropy production principle is reinterpreted as requiring the joint optimization of heat transport and mechanical work production. These results provide tools for climate change analysis and for climate models' validation. PMID:19792088

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

    Directory of Open Access Journals (Sweden)

    T. O. Sonnenborg

    2015-04-01

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

  16. Climate model uncertainty versus conceptual geological uncertainty in hydrological modeling

    Science.gov (United States)

    Sonnenborg, T. O.; Seifert, D.; Refsgaard, J. C.

    2015-09-01

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

  17. AGU Position Statement: Geoengineering the Climate System

    Science.gov (United States)

    2010-04-01

    Human responsibility for most of the well-documented increase in global average temperatures over the last half century is well established. Further greenhouse gas emissions, particularly of carbon dioxide from the burning of fossil fuels, will almost certainly contribute to additional widespread climate changes that can be expected to cause major negative consequences for most nations.1 Three proactive strategies could reduce the risks of climate change: 1) mitigation: reducing emissions; 2) adaptation: moderating climate impacts by increasing our capacity to cope with them; and 3) geoengineering: deliberately manipulating physical, chemical, or biological aspects of the Earth system.2 This policy statement focuses on large-scale efforts to geoengineer the climate system to counteract the consequences of increasing greenhouse gas emissions.

  18. Ionospheric climate and weather modeling

    International Nuclear Information System (INIS)

    Simulations of the ionospheric model of Schunk et al. (1986) have been used for climatology and weather modeling. Steady state empirical models were used in the climatology model to provide plasma convection and particle precipitation patterns in the northern high-latitude region. The climatology model also depicts the ionospheric electron density and ion and electron temperatures for solar maximum, winter solstice, and strong geomagnetic activity conditions. The weather model describes the variations of ionospheric features during the solar cycle, seasonal changes, and geomagnetic activity. Prospects for future modeling are considered. 23 references

  19. The heartbeat of the Oligocene climate system

    OpenAIRE

    H. Pälike; Norris, R. D.; Herrle, J. O.; Wilson, P. A.; Coxall, H.K.; Lear, C.H.; Shackleton, N. J.; A. K. Tripati; Wade, B. S.

    2006-01-01

    A 13-million-year continuous record of Oligocene climate from the equatorial Pacific reveals a pronounced “heartbeat” in the global carbon cycle and periodicity of glaciations. This heartbeat consists of 405,000-, 127,000-, and 96,000-year eccentricity cycles and 1.2-million-year obliquity cycles in periodically recurring glacial and carbon cycle events. That climate system response to intricate orbital variations suggests a fundamental interaction of the carbon cycle, solar forcing, and glac...

  20. A Variable-Resolution Stretched-Grid General Circulation Model and Data Assimilation System with Multiple Areas of Interest: Studying the Anomalous Regional Climate Events of 1998

    Science.gov (United States)

    Fox-Rabinovitz, Michael S.; Takacs, Lawrence; Govindaraju, Ravi C.; Atlas, Robert (Technical Monitor)

    2002-01-01

    The new stretched-grid design with multiple (four) areas of interest, one at each global quadrant, is implemented into both a stretched-grid GCM (general circulation model) and a stretched-grid data assimilation system (DAS). The four areas of interest include: the U.S./Northern Mexico, the El Nino area/Central South America, India/China, and the Eastern Indian Ocean/Australia. Both the stretched-grid GCM and DAS annual (November 1997 through December 1998) integrations are performed with 50 km regional resolution. The efficient regional down-scaling to mesoscales is obtained for each of the four areas of interest while the consistent interactions between regional and global scales and the high quality of global circulation, are preserved. This is the advantage of the stretched-grid approach. The global variable resolution DAS incorporating the stretched-grid GCM has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The anomalous regional climate events of 1998 that occurred over the U.S., Mexico, South America, China, India, African Sahel, and Australia are investigated in both simulation and data assimilation modes. Tree assimilated products are also used, along with gauge precipitation data, for validating the simulation results. The obtained results show that the stretched-grid GCM and DAS are capable of producing realistic high quality simulated and assimilated products at mesoscale resolution for regional climate studies and applications.

  1. Long-Term Changes in Stratospheric Age Spectra in the 21st Century in the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM)

    Science.gov (United States)

    Li, Feng; Waugh, Darryn W.; Douglass, Anne R.; Newman, Paul A.; Strahan, Susan E.; Ma, Jun; Nielsen, J. Eric; Liang, Qing

    2012-01-01

    In this study we investigate the long-term variations in the stratospheric age spectra using simulations of the 21st century with the Goddard Earth Observing System Chemistry- Climate Model (GEOSCCM). Our purposes are to characterize the long-term changes in the age spectra and identify processes that cause the decrease of the mean age in a warming climate. Changes in the age spectra in the 21st century simulations are characterized by decreases in the modal age, the mean age, the spectral width, and the tail decay timescale. Our analyses show that the decrease in the mean age is caused by two processes: the acceleration of the residual circulation that increases the young air masses in the stratosphere, and the weakening of the recirculation that leads to the decrease of tail of the age spectra and the decrease of the old air masses. The weakening of the stratospheric recirculation is also strongly correlated with the increase of the residual circulation. One important result of this study is that the decrease of the tail of the age spectra makes an important contribution to the decrease of the main age. Long-term changes in the stratospheric isentropic mixing are investigated. Mixing increases in the subtropical lower stratosphere, but its impact on the age spectra is outweighed by the increase of the residual circulation. The impacts of the long-term changes in the age spectra on long-lived chemical traces are also investigated. 37 2

  2. Climate Model Intercomparison at the Dynamics Level (Invited)

    Science.gov (United States)

    Tsonis, A.; Steinhaeuser, K.

    2013-12-01

    Until now, climate model intercomparison has focused primarily on annual and global averages of various quantities or on specific components, not on how well the general dynamics in the models compare to each other. In order to address how well models agree when it comes to dynamics they generate, we have adopted a new approach based on climate networks. We have considered 28 pre-industrial control runs as well as 70 20th-century forced runs from 23 climate models and have constructed networks for the 500 hPa, surface air temperature (SAT), sea level pressure (SLP), and precipitation fields for each run. Then we employed a widely used algorithm to derive the community structure in these networks. Communities separate 'nodes' in the network sharing similar dynamics. It has been shown that these communities, or sub-systems, in the climate system are associated with major climate modes and physics of the atmosphere. Once the community structure for all runs is derived, we use a pattern matching statistic to obtain a measure of how well any two models agree with each other. We find that, with possibly the exception of the 500 hPa field, the consistency for the SAT, SLP, and precipitation fields is questionable. More importantly, none of the models comes close to the community structure of the actual observations (reality). This is a significant finding especially for the temperature and precipitation fields, as these are the fields widely used to produce future projections in time and in space.

  3. 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.

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2climate 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...

  5. Changes in Winter Stratospheric Circulation in CMIP5 Scenarios Simulated by the Climate System Model FGOALS-s2

    Institute of Scientific and Technical Information of China (English)

    REN Rongcai; YANG Yang

    2012-01-01

    Diagnosis of changes in the winter stratospheric circulation in the Fifth Coupled Model Intercomparison Project (CMIP5) scenarios simulated by the Flexible Global Ocean-Atmosphere-Land System model,second version spectrum (FGOALS-s2),indicates that the model can generally reproduce the present climatology of the stratosphere and can capture the general features of its long-term changes during 1950 2000,including the global stratospheric cooling and the strengthening of the westerly polar jet,though the simulated polar vortex is much cooler,the jet is much stronger,and the projected changes are generally weaker than those revealed by observation data.With the increase in greenhouse gases (GHGs) effect in the historical simulation from 1850 to 2005 (called the HISTORICAL run) and the two future projections for Representative Concentration Pathways (called the RCP4.5 and RCP8.5 scenarios) from 2006 to 2100,the stratospheric response was generally steady,with an increasing stratospheric cooling and a strengthening polar jet extending equatorward.Correspondingly,the leading oscillation mode,defined as the Polar Vortex Oscillation (PVO),exhibited a clear positive trend in each scenario,confirming the steady strengthening of the polar vortex.However,the positive trend of the PVO and the strengthening of the polar jet were not accompanied by decreased planetary-wave dynamical heating,suggesting that the cause of the positive PVO trend and the polar stratospheric cooling trend is probably the radiation cooling effect due to increase in GHGs.Nevertheless,without the long-term linear trend,the temporal variations of the wave dynamic heating,the PVO,and the polar stratospheric temperature are still closely coupled in the interannual and decadal time scales.

  6. Wind climate from the regional climate model REMO

    DEFF Research Database (Denmark)

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

    2010-01-01

    Selected outputs from simulations with the regional climate model REMO from the Max Planck Institute, Hamburg, Germany were studied in connection with wind energy resource assessment. It was found that the mean wind characteristics based on observations from six mid-latitude stations are well...... described by the standard winds derived from the REMO pressure data. The mean wind parameters include the directional wind distribution, directional and omni-directional mean values and Weibull fitting parameters, spectral analysis and interannual variability of the standard winds. It was also found that...

  7. Impact of an extremely large magnitude volcanic eruption on the global climate and carbon cycle estimated from ensemble Earth System Model simulations

    Directory of Open Access Journals (Sweden)

    J. Segschneider

    2013-02-01

    Full Text Available The response of the global climate-carbon cycle system to an extremely large Northern Hemisphere mid-latitude volcanic eruption is investigated using ensemble integrations with the comprehensive Earth System Model MPI-ESM. The model includes dynamical compartments of the atmosphere and ocean and interactive modules of the terrestrial biosphere as well as ocean biogeochemistry. The MPI-ESM was forced with anomalies of aerosol optical depth and effective radius of aerosol particles corresponding to a super eruption of the Yellowstone volcanic system. The model experiment consists of an ensemble of fifteen model integrations that are started at different pre-ENSO states of a control experiment and run for 200 years after the volcanic eruption. The climate response to the volcanic eruption is a maximum global monthly mean surface air temperature cooling of 3.8 K for the ensemble mean and from 3.3 K to 4.3 K for individual ensemble members. Atmospheric pCO2 decreases by a maximum of 5 ppm for the ensemble mean and by 3 ppm to 7 ppm for individual ensemble members approximately 6 years after the eruption. The atmospheric carbon content only very slowly returns to near pre-eruption level at year 200 after the eruption. The ocean takes up carbon shortly after the eruption in response to the cooling, changed wind fields and ice cover. This physics-driven uptake is weakly counteracted by a reduction of the biological export production mainly in the tropical Pacific. The land vegetation pool shows a decrease by 4 GtC due to reduced short-wave radiation that has not been present in a smaller scale eruption. The gain of the soil carbon pool determines the amplitude of the CO2 perturbation and the long-term behaviour of the overall system: an initial gain caused by reduced soil respiration is followed by a rather slow return towards pre-eruption levels. During this phase, the ocean compensates partly for the reduced atmospheric

  8. Impact of an extremely large magnitude volcanic eruption on the global climate and carbon cycle estimated from ensemble Earth System Model simulations

    Directory of Open Access Journals (Sweden)

    J. Segschneider

    2012-07-01

    Full Text Available The response of the global climate-carbon cycle system to an extremely large Northern Hemisphere mid latitude volcanic eruption is investigated using ensemble integrations with the comprehensive Earth System Model MPI-ESM. The model includes dynamical compartments of the atmosphere and ocean and interactive modules of the terrestrial biosphere as well as ocean biogeochemistry. The MPI-ESM was forced with anomalies of aerosol optical depth and effective radius of aerosol particles corresponding to a super eruption of the Yellowstone volcanic system. The model experiment consists of an ensemble of fifteen model integrations that are started at different pre-ENSO states of a contol experiment and run for 200 yr after the volcanic eruption. The climate response to the volcanic eruption is a maximum global monthly mean surface air temperature cooling of 3.8 K for the ensemble mean and from 3.3 K to 4.3 K for individual ensemble members. Atmospheric pCO2 decreases by a maximum of 5 ppm for the ensemble mean and by 3 ppm to 7 ppm for individual ensemble members approximately 6 yr after the eruption. The atmospheric carbon content only very slowly returns to near pre-eruption level at year 200 after the eruption. The ocean takes up carbon shortly after the eruption in response to the cooling, changed wind fields, and ice cover. This physics driven uptake is weakly counteracted by a reduction of the biological export production mainly in the tropical Pacific. The land vegetation pool shows a distinct loss of carbon in the initial years after the eruption which has not been present in simulations of smaller scale eruptions. The gain of the soil carbon pool determines the amplitude of the CO2 perturbation and the long term behaviour of the overall system: an initial gain caused by reduced soil respiration is followed by a rather slow return towards pre-eruption levels. During this phase, the ocean compensates partly for the

  9. Advances in ocean modeling for climate change research

    Science.gov (United States)

    Holland, William R.; Capotondi, Antonietta; Holland, Marika M.

    1995-07-01

    An adequate understanding of climate variability and the eventual prediction of climate change are among the most urgent and far-reaching efforts of the scientific community. The climate system is in an ever-changing state with vast impact on mankind in all his activities. Both short and long-term aspects of climate variability are of concern, and the unravelling of "natural" variability from "man-induced" climate change is required to prepare for and ameliorate, if possible, the potentially devastating aspects of such change. In terms of scientific effort, the climate community can be thought of as the union of the disciplinary sciences of meteorology, oceanography, sea ice and glaciology, and land surface processes. Since models are based upon mathematical and numerical constructs, mathematics and computer sciences are also directly involved. In addition, some of the problems of man-induced climate change (release of greenhouse gases, the ozone-hole problem, etc.) are basically chemical in nature, and the expertise of the atmospheric and oceanic chemist is also required. In addition, some part of the response to climate perturbations will arise in the biological world, due to upsetting the balance in the great food web that binds communities together on both the land and the sea. Thus, the problems to be solved are extraordinarily complex and require the efforts of many kinds of scientist.

  10. 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.

  11. Urban Climate Resilience - Connecting climate models with decision support cyberinfrastructure using open standards

    Science.gov (United States)

    Bermudez, L. E.; Percivall, G.; Idol, T. A.

    2015-12-01

    Experts in climate modeling, remote sensing of the Earth, and cyber infrastructure must work together in order to make climate predictions available to decision makers. Such experts and decision makers worked together in the Open Geospatial Consortium's (OGC) Testbed 11 to address a scenario of population displacement by coastal inundation due to the predicted sea level rise. In a Policy Fact Sheet "Harnessing Climate Data to Boost Ecosystem & Water Resilience", issued by White House Office of Science and Technology (OSTP) in December 2014, OGC committed to increase access to climate change information using open standards. In July 2015, the OGC Testbed 11 Urban Climate Resilience activity delivered on that commitment with open standards based support for climate-change preparedness. Using open standards such as the OGC Web Coverage Service and Web Processing Service and the NetCDF and GMLJP2 encoding standards, Testbed 11 deployed an interoperable high-resolution flood model to bring climate model outputs together with global change assessment models and other remote sensing data for decision support. Methods to confirm model predictions and to allow "what-if-scenarios" included in-situ sensor webs and crowdsourcing. A scenario was in two locations: San Francisco Bay Area and Mozambique. The scenarios demonstrated interoperation and capabilities of open geospatial specifications in supporting data services and processing services. The resultant High Resolution Flood Information System addressed access and control of simulation models and high-resolution data in an open, worldwide, collaborative Web environment. The scenarios examined the feasibility and capability of existing OGC geospatial Web service specifications in supporting the on-demand, dynamic serving of flood information from models with forecasting capacity. Results of this testbed included identification of standards and best practices that help researchers and cities deal with climate-related issues

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

    Science.gov (United States)

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

    2014-01-01

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

  13. On coupling global biome models with climate models

    International Nuclear Information System (INIS)

    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. Comments on Current Space Systems Observing the Climate

    Science.gov (United States)

    Fisk, L. A.

    2016-07-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-08-15

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

  16. The Influence of Climate, Soil and Pasture Type on Productivity and Greenhouse Gas Emissions Intensity of Modeled Beef Cow-Calf Grazing Systems in Southern Australia

    Directory of Open Access Journals (Sweden)

    Richard J. Eckard

    2012-10-01

    Full Text Available A biophysical whole farm system model was used to simulate the interaction between the historical climate, soil and pasture type at sites in southern Australia and assess the balance between productivity and greenhouse gas emissions (expressed in carbon dioxide equivalents, CO2-eq. intensity of beef cow-calf grazing systems. Four sites were chosen to represent a range of climatic zones, soil and pasture types. Poorer feed quality and supply limited the annual carrying capacity of the kikuyu pasture compared to phalaris pastures, with an average long-term carrying capacity across sites estimated to be 0.6 to 0.9 cows/ha. A relative reduction in level of feed intake to productivity of calf live weight/ha at weaning by feeding supplementary feed reduced the average CO2-eq. emissions/kg calf live weight at weaning of cows on the kikuyu pasture (18.4 and 18.9 kg/kg with and without supplementation, respectively, whereas at the other sites studied an increase in intake level to productivity and emission intensity was seen (between 10.4 to 12.5 kg/kg without and with supplementary feed, respectively. Enteric fermentation and nitrous oxide emissions from denitrification were the main sources of annual variability in emissions intensity, particularly at the lower rainfall sites. Emissions per unit product of low input systems can be minimized by efficient utilization of pasture to maximize the annual turnoff of weaned calves and diluting resource input per unit product.

  17. Climate Modeling with a Million CPUs

    Science.gov (United States)

    Tobis, M.; Jackson, C. S.

    2010-12-01

    manage our ensembles. Component computations involve tens to hundreds of CPUs and tens to hundreds of hours. The results of these moderately large parallel jobs influence the scheduling of subsequent jobs, and complex algorithms may be easily contemplated for this. The operating system concept of a "thread" re-emerges at a very coarse level, where each thread manages atomic computations of thousands of CPU-hours. That is, rather than multiple threads operating on a processor, at this level, multiple processors operate within a single thread. In collaboration with the Texas Advanced Computing Center, we are developing a software library at the system level, which should facilitate the development of computations involving complex strategies which invoke large numbers of moderately large multi-processor jobs. While this may have applications in other sciences, our key intent is to better characterize the coupled behavior of a very large set of climate model configurations.

  18. Improved ENSO simulation from climate system model FGOALS-g1.0 to FGOALS-g2

    Science.gov (United States)

    Chen, Lin; Yu, Yongqiang; Zheng, Weipeng

    2016-02-01

    This study presents an overview of the improvement in the simulation of El Niño-Southern Oscillation (ENSO) in the latest generation of the Institute of Atmospheric Physics' coupled general circulation model (CGCM), the Flexible Global Ocean-Atmosphere-Land System model Grid-point Version 2 (FGOALS-g2; hereafter referred to as "g2") from its predecessor FGOALS-g1.0 (referred to as "g1"), including the more realistic amplitude, irregularity, and ENSO cycle. The changes have been analyzed quantitatively based on the Bjerknes stability index, which serves as a measure of ENSO growth rate. The improved simulation of ENSO amplitude is mainly due to the reasonable representation of the thermocline and thermodynamic feedbacks: On the one hand, the deeper mean thermocline results in a weakened thermocline response to the zonal wind stress anomaly, and the looser vertical stratification of mean temperature leads to a weakened response of anomalous subsurface temperature to anomalous thermocline depth, both of which cause the reduced thermocline feedback in g2; on the other hand, the alleviated cold bias of mean sea surface temperature leads to more reasonable thermodynamic feedback in g2. The regular oscillation of ENSO in g1 is associated with its unsuccessful representation of the role of atmospheric noise over the western-central equatorial Pacific (WCEP) in triggering ENSO events, which arises from the weak synoptic-intraseasonal variability of zonal winds over the WCEP in g1. The asymmetric transition of ENSO in g1 is attributed to the asymmetric effect of thermocline feedback, which is due to the annual cycle of mean upwelling in the eastern Pacific. This study highlights the great impact of improving the representation of mean states on the improved simulation of air-sea feedback processes and ultimately more reasonable depiction of ENSO behaviors in CGCMs.

  19. Observing the carbon-climate system

    CERN Document Server

    Schimel, David; Moore, Berrien; Chatterjee, Abhishek; Baker, David; Berry, Joe; Bowman, Kevin; Crisp, Phillipe Ciais David; Crowell, Sean; Denning, Scott; Duren, Riley; Friedlingstein, Pierre; Gierach, Michelle; Gurney, Kevin; Hibbard, Kathy; Houghton, Richard A; Huntzinger, Deborah; Hurtt, George; Jucks, Ken; Kawa, Randy; Koster, Randy; Koven, Charles; Luo, Yiqi; Masek, Jeff; McKinley, Galen; Miller, Charles; Miller, John; Moorcroft, Paul; Nassar, Ray; ODell, Chris; Ott, Leslie; Pawson, Steven; Puma, Michael; Quaife, Tristan; Riris, Haris; Romanou, Anastasia; Rousseaux, Cecile; Schuh, Andrew; Shevliakova, Elena; Tucker, Compton; Wang, Ying Ping; Williams, Christopher; Xiao, Xiangming; Yokota, Tatsuya

    2016-01-01

    Increases in atmospheric CO2 and CH4 result from a combination of forcing from anthropogenic emissions and Earth System feedbacks that reduce or amplify the effects of those emissions on atmospheric concentrations. Despite decades of research carbon-climate feedbacks remain poorly quantified. The impact of these uncertainties on future climate are of increasing concern, especially in the wake of recent climate negotiations. Emissions, long concentrated in the developed world, are now shifting to developing countries, where the emissions inventories have larger uncertainties. The fraction of anthropogenic CO2 remaining in the atmosphere has remained remarkably constant over the last 50 years. Will this change in the future as the climate evolves? Concentrations of CH4, the 2nd most important greenhouse gas, which had apparently stabilized, have recently resumed their increase, but the exact cause for this is unknown. While greenhouse gases affect the global atmosphere, their sources and sinks are remarkably he...

  20. Mapping model agreement on future climate projections

    Science.gov (United States)

    Tebaldi, Claudia; Arblaster, Julie M.; Knutti, Reto

    2011-12-01

    Climate change projections are often based on simulations from multiple global climate models and are presented as maps with some form of stippling or measure of robustness to indicate where different models agree on the projected anthropogenically forced changes. The criteria used to determine model agreement, however, often ignore the presence of natural internal variability. We demonstrate that this leads to misleading presentations of the degree of model consensus on the sign and magnitude of the change if the ratio of the signal from the externally forced change to internal variability is low. We present a simple alternative method of depicting multimodel projections which clearly separates lack of climate change signal from lack of model agreement by assessing the degree of consensus on the significance of the change as well as the sign of the change. Our results demonstrate that the common interpretation of lack of model agreement in precipitation projections is largely an artifact of the large noise from climate variability masking the signal, an issue exacerbated by performing analyses at the grid point scale. We argue that separating more clearly the case of lack of agreement from the case of lack of signal will add valuable information for stake-holders' decision making, since adaptation measures required in the two cases are potentially very different.

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

    Directory of Open Access Journals (Sweden)

    J. Brandefelt

    2011-06-01

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

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

    DEFF Research Database (Denmark)

    Eby, M.; Weaver, A. J.; Alexander, K.; Zickfeld, K.; Abe-Ouchi, A.; Cimatoribus, A. A.; Crespin, E.; Drijfhout, S. S.; Edwards, N. R.; Eliseev, A. V.; Feulner, G.; Fichefet, T.; Forest, C. E.; Goosse, H.; Holden, P. B.; Joos, F.; Kawamiya, M.; Kicklighter, D.; Kienert, H.; Matsumoto, K.; Mokhov, I. I.; Monier, E.; Olsen, S. M.; Pedersen, Jens Olaf Pepke; Perrette, M.; Philippon-Berthier, G.; Ridgwell, A.; Schlosser, A.; Deimling, T. Schneider von; Shaffer, G.; Smith, R. S.; Spahni, R.; Sokolov, A. P.; Steinacher, M.; Tachiiri, K.; Tokos, K.; Yoshimori, M.; Zeng, N.; Zhao, F.

    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......> between 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...

  3. Intercomparison of 20th century tropical climate model hindcasts and coral δ18O data using a forward proxy system model

    Science.gov (United States)

    Thompson, D. M.; Ault, T. R.; Evans, M. N.; Cole, J. E.; Emile-Geay, J.

    2010-12-01

    When coupled to climate model (CGCM) output, forward models provide a means to assess CGCM output through direct comparison with the available proxy observations. Here we model reef coral oxygen isotopic composition (δ18O) as a function of sea-surface temperature (SST) and sea-surface salinity (SSS), with SSS acting as a linear proxy for the isotopic composition of seawater. When driven with historical SST and SSS data over the 1958-1990 period, the forward model is able to capture the spatial pattern and temporal evolution of the El Niño-Southern Oscillation (ENSO) and trend observed in a sparse observational network of 23 Indo-Pacific coral δ18O records. The SST and SSS components of the model are both necessary to capture the full magnitude of the coral trend. The δ18O trend simulated from historical SST and SSS data is equivalent to or smaller than the observed δ18O trend. For the 1890-1990 period, δ18O records simulated from AR4 CGCMs generally display greater overall interannual variance and a weaker 20th century warming/freshening trend than is observed in corals. The discrepancies between observed and CGCM-simulated δ18O trends may arise in part from unmodeled physiological controls on δ18O or from sampling-network induced biases. On the other hand, the tropical Pacific may be more sensitive to radiative changes during the 20th century than is simulated by the AR4 generation of CGCMs.

  4. Developing a National Climate Indicators System to Track Climate Changes, Impacts, Vulnerabilities, and Preparedness

    Science.gov (United States)

    Kenney, M. A.; Janetos, A. C.; Arndt, D.; Chen, R. S.; Pouyat, R.; Anderson, S. M.

    2013-12-01

    The National Climate Assessment (NCA) is being conducted under the auspices of the U.S. Global Change Research Program (USGCRP), pursuant to the Global Change Research Act of 1990, Section 106, which requires a report to Congress every 4 years. Part of the vision, which is now under development, for the sustained National Climate Assessment (NCA) process is a system of physical, ecological, and societal indicators that communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness for the purpose of informing both decision makers and the public with scientifically valid information that is useful to inform decision-making processes such as the development and implementation of climate adaptation strategies in a particular sector or region. These indicators will be tracked as a part of ongoing assessment activities, with adjustments as necessary to adapt to changing conditions and understanding. The indicators will be reviewed and updated so that the system adapts to new information. The NCA indicator system is not intended to serve as a vehicle for documenting rigorous cause and effect relationships. It is reasonable, however, for it to serve as a guide to those factors that affect the evolution of variability and change in the climate system, the resources and sectors of concern that are affected by it, and how society chooses to respond. Different components of the end-to-end climate issue serve as categories within which to organize an end-to-end system of indicators: Greenhouse Gas Emissions and Sinks, Atmospheric Composition, Physical Climate Variability and Change, Sectors and Resources of Concern, and Adaptation and Mitigation Responses. This framing has several advantages. It can be used to identify the different components of the end-to-end climate issue that both decision-makers and researchers are interested in. It is independent of scale, and therefore allows the indicators themselves to be described at spatial

  5. Examine Climate Models by Using Infrared Spectrum

    OpenAIRE

    Yi Huang; Ramaswamy, V.

    2008-01-01

    We examine global climate models by comparing the satellite-observed high resolution global infrared spectra with the model-simulated counterpart. Because the topof-the-atmosphere outgoing Earth thermal emission at different frequencies is sensitive to different geophysical variables (temperature, water vapor and other greenhouse gas concentrations, clouds, etc.) at various levels, a comparison of observed and simulated spectra is as challenging as examining a variety of model-simulated geoph...

  6. High Resolution Modelling of Crop Response to Climate Change

    Science.gov (United States)

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

    2014-12-01

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

  7. Quantifying sources of uncertainty in regional climate model scenarios for Ireland

    OpenAIRE

    Foley, Aideen

    2010-01-01

    This thesis develops a novel framework for model skill assessment and the generation of probabilistic future climate scenarios. Traditional approaches to model validation assume that skill in simulating the mean climate is a valid indicator of skill in modelling the climate system. However, without information about how errors arise, conclusions cannot be drawn about whether models are genuinely skilful. Initially, verification statistics are used to assess model skill in simul...

  8. A model approach to climate change

    International Nuclear Information System (INIS)

    The Earth is warming up, with potentially disastrous consequences. Computer climate models based on physics are our best hope of predicting and managing climate change, as Adam Scaife, Chris Folland and John Mitchell explain. This month scientists from over 60 nations on the Intergovernmental Panel on Climate Change (IPCC) released the first part of their latest report on global warming. In the report the panel concludes that it is very likely that most of the 0.5 deg. C increase in global temperature over the last 50 years is due to man-made emissions of greenhouse gases. And the science suggests that much greater changes are in store: by 2100 anthropogenic global warming could be comparable to the warming of about 6 deg. C since the last ice age. The consequences of global warming could be catastrophic. As the Earth continues to heat up, the frequency of floods and droughts is likely to increase, water supplies and ecosystems will be placed under threat, agricultural practices will have to be changed and millions of people may be displaced as the sea level rises. The global economy could also be severely affected. The scientific consensus is that the observed warming of the Earth during the past half-century is mostly due to human emissions of greenhouse gases. Predicting climate change depends on sophisticated computer models developed over the past 50 years. Climate models are based on the Navier-Stokes equations for fluid flow, which are solved numerically on a grid covering the globe. These models have been very successful in simulating the past climate, giving researchers confidence in their predictions. The most likely value for the global temperature increase by 2100 is in the range 1.4-5.8 deg. C, which could have catastrophic consequences. (U.K.)

  9. 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

  10. Terrestrial biogeochemical feedbacks in the climate system

    Science.gov (United States)

    Arneth, A.; Harrison, S. P.; Zaehle, S.; Tsigaridis, K.; Menon, S.; Bartlein, P. J.; Feichter, J.; Korhola, A.; Kulmala, M.; O'Donnell, D.; Schurgers, G.; Sorvari, S.; Vesala, T.

    2010-08-01

    The terrestrial biosphere is a key regulator of atmospheric chemistry and climate. During past periods of climate change, vegetation cover and interactions between the terrestrial biosphere and atmosphere changed within decades. Modern observations show a similar responsiveness of terrestrial biogeochemistry to anthropogenically forced climate change and air pollution. Although interactions between the carbon cycle and climate have been a central focus, other biogeochemical feedbacks could be as important in modulating future climate change. Total positive radiative forcings resulting from feedbacks between the terrestrial biosphere and the atmosphere are estimated to reach up to 0.9 or 1.5 W m-2 K-1 towards the end of the twenty-first century, depending on the extent to which interactions with the nitrogen cycle stimulate or limit carbon sequestration. This substantially reduces and potentially even eliminates the cooling effect owing to carbon dioxide fertilization of the terrestrial biota. The overall magnitude of the biogeochemical feedbacks could potentially be similar to that of feedbacks in the physical climate system, but there are large uncertainties in the magnitude of individual estimates and in accounting for synergies between these effects.

  11. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

    1990-12-01

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

  13. 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.

  14. GIS and crop simulation modelling applications in climate change research

    Science.gov (United States)

    The challenges that climate change presents humanity require an unprecedented ability to predict the responses of crops to environment and management. Geographic information systems (GIS) and crop simulation models are two powerful and highly complementary tools that are increasingly used for such p...

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

    NARCIS (Netherlands)

    den Toom, M.

    2013-01-01

    The Atlantic Meridional Overturning Circulation (AMOC) is considered an important component of the climate system, because of its significant contribution to the heat budget of the Northern Hemisphere. Theoretical models indicate that the AMOC has non-linear dynamics, which result in a strong sensit

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

    OpenAIRE

    Goelzer, H.; Huybrechts, P; Loutre, M.-F.; T. Fichefet

    2016-01-01

    As the most recent warm period in Earth’s history with a sea-level stand higher than present, the Last Interglacial period (~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...

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

    Directory of Open Access Journals (Sweden)

    J. H. T. Williams

    2012-10-01

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

  18. A description of persistent climatic anomalies in a 1000-year climatic model simulation

    Science.gov (United States)

    Hunt, B. G.

    The Mark 2 version of the CSIRO coupled global climatic model has been used to generate a 1000-year simulation of natural (i.e. unforced) climatic variability representative of ``present conditions''. The annual mean output from the simulation has been used to investigate the occurrence of decadal and longer trends over the globe for a number of climatic variables. Here trends are defined to be periods of years with a climatic anomaly of a given sign. The analysis reveals substantial differences between the trend characteristics of the various climatic variables. Trends longer than 12years duration were unusual for rainfall. Such trends were fairly uniformly distributed over the globe and had an asymmetry in the rate of occurrence for wet or dry conditions. On the other hand, trends in surface wind stress, and especially the atmospheric screen temperature, were of longer duration but primarily confined to oceanic regions. The trends in the atmospheric screen temperature could be traced deep into the oceanic mixed layer, implying large changes in oceanic thermal inertia. This thermal inertia then constituted an important component of the `memory' of the climatic system. While the geographic region associated with a given trend could be identified over several adjacent grid boxes of the model, regional plots for individual years of the trend revealed a range of variations, suggesting that a consistent forcing mechanism may not be responsible for a trend at a given location. Typical return periods for 12-year rainfall trends were once in 1000years, highlighting the rarity of such events. Using a looser definition of a trend revealed that drying trends up to 50 years duration were also possible, attributable solely to natural climatic variability. Significant ( 20% to 40%) rainfall reductions per year can be associated with a long-term drying trend, hence such events are of considerable climatic significance. It can take more than 100years for the hydrologic losses

  19. System Identification for Indoor Climate Control

    CERN Document Server

    M., A W; H., P W M; Steskens,

    2012-01-01

    The study focuses on the applicability of system identification to identify building and system dynamics for climate control design. The main problem regarding the simulation of the dynamic response of a building using building simulation software is that (1) the simulation of a large complex building is time consuming, and (2) simulation results often lack information regarding fast dynamic behaviour (in the order of seconds), since most software uses a discrete time step, usually fixed to one hour. The first objective is to study the applicability of system identification to reduce computing time for the simulation of large complex buildings. The second objective is to research the applicability of system identification to identify building dynamics based on discrete time data (one hour) for climate control design. The study illustrates that system identification is applicable for the identification of building dynamics with a frequency that is smaller as the maximum sample frequency as used for identificat...

  20. Global comparison of three greenhouse climate models

    OpenAIRE

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

    1985-01-01

    Three dynamic simulation models for calculating the greenhouse climate and its energy requirements for both heating and cooling were compared by making detailed computations for each of seven sets of data. The data sets ranged from a cold winter day, requiring heating, to a hot summer day, requiring cooling. On the whole, the models agreed in regard to calculated air temperature, humidity, and heating requirements. Significant differences were found between the estimates of fan-and-pad (evapo...

  1. Advance in Application of Regional Climate Models in China

    Institute of Scientific and Technical Information of China (English)

    ZHANG Wei; YAN Minhua; CHEN Panqin; XU Helan

    2008-01-01

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

  2. Energy saving systems in hot humid climates

    NARCIS (Netherlands)

    Hadjilambi, A.; D'Aquilo, A.; Rodenberg, O.

    2014-01-01

    This "designers' manual" is made during the TIDO-course AR0533 Innovation & Sustainability. The aim of this manual is the description and comparison of several systems and strategies for cooling buildings in hot humid climates. To cool down a building you need to move the energy from a space or fro

  3. 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.

  4. Uncertainty propagation within an integrated model of climate change

    International Nuclear Information System (INIS)

    This paper demonstrates a methodology whereby stochastic dynamical systems are used to investigate a climate model's inherent capacity to propagate uncertainty over time. The usefulness of the methodology stems from its ability to identify the variables that account for most of the model's uncertainty. We accomplish this by reformulating a deterministic dynamical system capturing the structure of an integrated climate model into a stochastic dynamical system. Then, via the use of computational techniques of stochastic differential equations accurate uncertainty estimates of the model's variables are determined. The uncertainty is measured in terms of properties of probability distributions of the state variables. The starting characteristics of the uncertainty of the initial state and the random fluctuations are derived from estimates given in the literature. Two aspects of uncertainty are investigated: (1) the dependence on environmental scenario - which is determined by technological development and actions towards environmental protection; and (2) the dependence on the magnitude of the initial state measurement error determined by the progress of climate change and the total magnitude of the system's random fluctuations as well as by our understanding of the climate system. Uncertainty of most of the system's variables is found to be nearly independent of the environmental scenario for the time period under consideration (1990-2100). Even conservative uncertainty estimates result in scenario overlap of several decades during which the consequences of any actions affecting the environment could be very difficult to identify with a sufficient degree of confidence. This fact may have fundamental consequences on the level of social acceptance of any restrictive measures against accelerating global warming. In general, the stochastic fluctuations contribute more to the uncertainty than the initial state measurements. The variables coupling all major climate elements

  5. Climatic change and impacts: a general introduction

    International Nuclear Information System (INIS)

    These proceedings are divided into six parts containing 29 technical papers. 1. An Overview of the Climatic System, 2. Past climate Changes, 3. Climate Processes and Climate Modelling, 4. Greenhouse Gas Induced Climate Change, 5. Climatic Impacts, 6. STUDENTS' PAPERS

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

    OpenAIRE

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

    2012-01-01

    Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological 5 models (eight) were used to systematically assess the hydrological response to climate change and project the future state of global water resources. The results show a large spread in projected changes in water resources within the climat...

  7. Cross-scale modelling of the climate-change mitigation potential of biochar systems: Global implications of nano-scale processes

    Science.gov (United States)

    Woolf, Dominic; Lehmann, Johannes

    2014-05-01

    With CO2 emissions still tracking the upper bounds of projected emissions scenarios, it is becoming increasingly urgent to reduce net greenhouse gas (GHG) emissions, and increasingly likely that restricting future atmospheric GHG concentrations to within safe limits will require an eventual transition towards net negative GHG emissions. Few measures capable of providing negative emissions at a globally-significant scale are currently known. Two that are most often considered include carbon sequestration in biomass and soil, and biomass energy with carbon capture and storage (BECCS). In common with these two approaches, biochar also relies on the use of photosynthetically-bound carbon in biomass. But, because biomass and land are limited, it is critical that these resources are efficiently allocated between biomass/soil sequestration, bioenergy, BECCS, biochar, and other competing uses such as food, fiber and biodiversity. In many situations, biochar can offer advantages that may make it the preferred use of a limited biomass supply. These advantages include that: 1) Biochar can provide valuable benefits to agriculture by improving soil fertility and crop production, and reducing fertlizer and irrigation requirements. 2) Biochar is significantly more stable than biomass or other forms of soil carbon, thus lowering the risk of future losses compared to sequestration in biomass or soil organic carbon. 3) Gases and volatiles produced by pyrolysis can be combusted for energy (which may offset fossil fuel emissions). 4) Biochar can further lower GHG emissions by reducing nitrous oxide emissions from soil and by enhancing net primary production. Determining the optimal use of biomass requires that we are able to model not only the climate-change mitigation impact of each option, but also their economic and wider environmental impacts. Thus, what is required is a systems modelling approach that integrates components representing soil biogeochemistry, hydrology, crop

  8. Operating Water Resources Systems Under Climate Change Scenarios

    Science.gov (United States)

    Ahmad, S.

    2002-12-01

    Population and industrial growth has resulted in intense demands on the quantity and quality of water resources worldwide. Moreover, climate change/variability is making a growing percentage of the earth's population vulnerable to extreme weather events (drought and flood). The 1996 Saguenay flood, 1997 Red River flood, the 1998 ice storm, and recent droughts in prairies are few examples of extreme weather events in Canada. Rising economic prosperity, growth in urban population, aging infrastructure, and a changing climate are increasing the vulnerability of Canadians to even more serious impacts. This growing threat can seriously undermine the social and economic viability of the country. Our ability to understand the impacts of climate change/variability on water quantity, quality, and its distribution in time and space can prepare us for sustainable management of this precious resource. The sustainability of water resources, over the medium to long-term, is critically dependent on the ability to manage (plan and operate) water resource systems under a more variable and perhaps warmer future climate. Studying the impacts of climate change/variability on water resources is complex and challenging. It is further complicated by the fact that impacts vary with time and are different at different locations. This study deals with the impacts of climate change/variability on water resources in a portion of the Red River Basin in Canada, both in terms of change in quantity and spatial-temporal distribution. A System Dynamics model is developed to describe the operation of the Shellmouth Reservoir located on the Red River in Canada. The climate data from Canadian Global Coupled Model, CGCM1 is used. The spatial system dynamics approach, based on distributed parameter control theory, is used to model the impacts of climate change/variability on water resources in time and space. A decision support system is developed to help reservoir operators and decision makers in

  9. Climate change mitigation through livestock system transitions

    OpenAIRE

    Havlík, Petr; Valin, Hugo; Herrero, Mario; Obersteiner, Michael; Schmid, Erwin; Rufino, Mariana C.; Mosnier, Aline; Thornton, Philip K.; Böttcher, Hannes; Conant, Richard T.; Frank, Stefan; FRITZ, Steffen; Fuss, Sabine; Kraxner, Florian; Notenbaert, An

    2014-01-01

    The livestock sector contributes significantly to global warming through greenhouse gas (GHG) emissions. At the same time, livestock is an invaluable source of nutrition and livelihood for millions of poor people. Therefore, climate mitigation policies involving livestock must be designed with extreme care. Here we demonstrate the large mitigation potential inherent in the heterogeneity of livestock production systems. We find that even within existing systems, autonomous transitions from ext...

  10. Performance investigation of solid desiccant evaporative cooling system configurations in different climatic zones

    International Nuclear Information System (INIS)

    Highlights: • Five configurations of a DEC system are analyzed in five climate zones. • DEC system model configurations are developed in Dymola/Modelica. • Performance analysis predicted a suitable DEC system configuration for each climate zone. • Results show that climate of Vienna, Sao Paulo, and Adelaide favors the ventilated-dunkle cycle. • While ventilation cycle configuration suits the climate of Karachi and Shanghai. - Abstract: Performance of desiccant evaporative cooling (DEC) system configurations is strongly influenced by the climate conditions and varies widely in different climate zones. Finding the optimal configuration of DEC systems for a specific climatic zone is tedious and time consuming. This investigation conducts performance analysis of five DEC system configurations under climatic conditions of five cities from different zones: Vienna, Karachi, Sao Paulo, Shanghai, and Adelaide. On the basis of operating cycle, three standard and two modified system configurations (ventilation, recirculation, dunkle cycles; ventilated-recirculation and ventilated-dunkle cycles) are analyzed in these five climate zones. Using an advance equation-based object-oriented (EOO) modeling and simulation approach, optimal configurations of a DEC system are determined for each climate zone. Based on the hourly climate data of each zone for its respective design cooling day, performance of each system configuration is estimated using three performance parameters: cooling capacity, COP, and cooling energy delivered. The results revealed that the continental/micro-thermal climate of Vienna, temperate/mesothermal climate of Sao Paulo, and dry-summer subtropical climate of Adelaide favor the use of ventilated-dunkle cycle configuration with average COP of 0.405, 0.89 and 1.01 respectively. While ventilation cycle based DEC configuration suits arid and semiarid climate of Karachi and another category of temperate/mesothermal climate of Shanghai with average COP of

  11. Guiding climate change adaptation within vulnerable natural resource management systems.

    Science.gov (United States)

    Bardsley, Douglas K; Sweeney, Susan M

    2010-05-01

    Climate change has the potential to compromise the sustainability of natural resources in Mediterranean climatic systems, such that short-term reactive responses will increasingly be insufficient to ensure effective management. There is a simultaneous need for both the clear articulation of the vulnerabilities of specific management systems to climate risk, and the development of appropriate short- and long-term strategic planning responses that anticipate environmental change or allow for sustainable adaptive management in response to trends in resource condition. Governments are developing climate change adaptation policy frameworks, but without the recognition of the importance of responding strategically, regional stakeholders will struggle to manage future climate risk. In a partnership between the South Australian Government, the Adelaide and Mt Lofty Ranges Natural Resource Management Board and the regional community, a range of available research approaches to support regional climate change adaptation decision-making, were applied and critically examined, including: scenario modelling; applied and participatory Geographical Information Systems modelling; environmental risk analysis; and participatory action learning. As managers apply ideas for adaptation within their own biophysical and socio-cultural contexts, there would be both successes and failures, but a learning orientation to societal change will enable improvements over time. A base-line target for regional responses to climate change is the ownership of the issue by stakeholders, which leads to an acceptance that effective actions to adapt are now both possible and vitally important. Beyond such baseline knowledge, the research suggests that there is a range of tools from the social and physical sciences available to guide adaptation decision-making. PMID:20383706

  12. Guiding Climate Change Adaptation Within Vulnerable Natural Resource Management Systems

    Science.gov (United States)

    Bardsley, Douglas K.; Sweeney, Susan M.

    2010-05-01

    Climate change has the potential to compromise the sustainability of natural resources in Mediterranean climatic systems, such that short-term reactive responses will increasingly be insufficient to ensure effective management. There is a simultaneous need for both the clear articulation of the vulnerabilities of specific management systems to climate risk, and the development of appropriate short- and long-term strategic planning responses that anticipate environmental change or allow for sustainable adaptive management in response to trends in resource condition. Governments are developing climate change adaptation policy frameworks, but without the recognition of the importance of responding strategically, regional stakeholders will struggle to manage future climate risk. In a partnership between the South Australian Government, the Adelaide and Mt Lofty Ranges Natural Resource Management Board and the regional community, a range of available research approaches to support regional climate change adaptation decision-making, were applied and critically examined, including: scenario modelling; applied and participatory Geographical Information Systems modelling; environmental risk analysis; and participatory action learning. As managers apply ideas for adaptation within their own biophysical and socio-cultural contexts, there would be both successes and failures, but a learning orientation to societal change will enable improvements over time. A base-line target for regional responses to climate change is the ownership of the issue by stakeholders, which leads to an acceptance that effective actions to adapt are now both possible and vitally important. Beyond such baseline knowledge, the research suggests that there is a range of tools from the social and physical sciences available to guide adaptation decision-making.

  13. Modeling Impact of Climate Change on Water Resources and Agriculture Demand in the Volta Basin and other Basin Systems in Ghana

    OpenAIRE

    Barnabas A. Amisigo; Alyssa McCluskey; Richard Swanson

    2015-01-01

    An assessment of the impacts of projected climate change on water availability and crop production in the Volta Basin and the southwestern and coastal basin systems of Ghana has been undertaken as a component of the impacts and adaptation study for Ghana by UNU-WIDER and the University of Ghana. Four climate change scenarios were considered in addition to a reference (no change) scenario—two dry and two wet scenarios. To conduct the analysis, a portion of a special framework using three wat...

  14. Constraining climate model parameters from observed 20th century changes

    OpenAIRE

    Forest, Chris E.; Stone, Peter H; Sokolov, Andrei P.

    2008-01-01

    We present revised probability density functions for climate model parameters (effective climate sensitivity, the rate of deep-ocean heat uptake, and the strength of the net aerosol forcing) that are based on climate change observations from the 20th century. First, we compare observed changes in surface, upper-air, and deep-ocean temperature changes against simulations of 20th century climate in which the climate model parameters were systematically varied. The estimated 90% range of effecti...

  15. 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.)

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

    Science.gov (United States)

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

    2010-05-01

    Future climate change will affect aquatic systems on various pathways. Regarding the hydrological cycle, which is a very important pathway, changes in hydrometeorological variables (air temperature, precipitation, evapotranspiration) in first order impact discharges. The fourth report assessment of the Intergovernmental Panel for Climate Change indicates there is evidence that the recent warming of the climate system would result in more frequent extreme precipitation events, increased winter flood likelihoods, increased and widespread melting of snow and ice, longer and more widespread droughts, and rising sea level. Available research and climate model outputs indicate a range of hydrological impacts with likely to very likely probabilities (67 to 99%). For example, it is likely that up to 20% of the world population will live in areas where river flood potential could increase by the 2080s. In Spain, within the Atlantic basin, the hydrological variability will increase in the future due to the intensification of the positive phase of the North Atlantic Oscillation (NAO) index. This might cause flood frequency decreases, but its magnitude does not decrease. The generation of flood, its duration and magnitude are closely linked to changes in winter precipitation. The climatic conditions and relief of the Iberian Peninsula favour the generation of floods. In Spain, floods had historically strong socio-economic impacts, with more than 1525 victims in the past five decades. This upward trend of hydrological variability is expected to remain in the coming decades (medium uncertainty) when the intensification of the positive phase of the NAO index (MMA, 2006) is considered. In order to adapt or minimize climate change impacts in water resources, it is necessary to use climate projections as well as hydrological modelling tools. The main objective of this paper is to evaluate and assess the hydrological response to climate changes in flow conditions in Nerbioi river

  17. Systemic Modeling for the diagnosis of the interaction climate-malaria in Colombia, application during El Nino 1997-1998 and La Nina 1998-2000

    International Nuclear Information System (INIS)

    A vector-borne disease model has been developed to represent the entomological, epidemiological and climatic interactions of malaria transmission conductive to disease outbreaks in Nuqui prone-region, Choco province, along the pacific Colombian coast. Considering breeding place availability model and several predator-prey-food models allow us to represent the vectorial densities fluctuations observed during the field's campaigns. The comprehensive model has been applied to represent malaria incidence during the period Nov/1997-Feb/2001 (1200 days simulation period), when both El Nino and la Nina events strongly affected the hydro-climatology of Colombia. The model has been run for observed climatic patterns such as mean daily temperatures, total daily precipitation records, and mean daily relative humidities gathered by a nearby climatological station. Diverse temperature scenarios have been considered to deepen the understanding of the entomological-climatic linkages conductive to malaria outbreaks. Sensitivity analysis and instabilities cases have been also studied during the experimentation-validation processes. Obtained results allow us to conclude that the model constitutes a promising tool to deepen the understanding of the ecological, entomological, and epidemiological linkages conductive to malaria outbreaks

  18. Testing an astronomically-based decadal-scale empirical harmonic climate model versus the IPCC (2007) general circulation climate models

    CERN Document Server

    Scafetta, Nicola

    2012-01-01

    We compare the performance of a recently proposed empirical climate model based on astronomical harmonics against all available general circulation climate models (GCM) used by the IPCC (2007) to interpret the 20th century global surface temperature. The proposed model assumes that the climate is resonating with, or synchronized to a set of natural harmonics that have been associated to the solar system planetary motion, mostly determined by Jupiter and Saturn. We show that the GCMs fail to reproduce the major decadal and multidecadal oscillations found in the global surface temperature record from 1850 to 2011. On the contrary, the proposed harmonic model is found to well reconstruct the observed climate oscillations from 1850 to 2011, and it is able to forecast the climate oscillations from 1950 to 2011 using the data covering the period 1850-1950, and vice versa. The 9.1-year cycle is shown to be likely related to a decadal Soli/Lunar tidal oscillation, while the 10-10.5, 20-21 and 60-62 year cycles are sy...

  19. Spatial Self-Organization of Vegetation Subject to Climatic Stress—Insights from a System Dynamics—Individual-Based Hybrid Model

    Science.gov (United States)

    Vincenot, Christian E.; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

    2016-01-01

    In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)—Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non

  20. Spatial Self-Organization of Vegetation Subject to Climatic Stress-Insights from a System Dynamics-Individual-Based Hybrid Model.

    Science.gov (United States)

    Vincenot, Christian E; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

    2016-01-01

    In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)-Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total

  1. Modeling Infrastructure Vulnerabilities and Adaptation to Climate Change in Urban Systems: Methodology and Application to Metropolitan Boston

    OpenAIRE

    Ruth, Matthias

    2003-01-01

    Much of the infrastructure in use today was designed and constructed decades if not centuries ago. Many of these infrastructure systems are vulnerable to a variety of anthropogenic or natural disruptions even though their functioning is vital to the creation and maintenance of quality of life in a region. Moreover, concepts and designs have persisted even as technologies have changed. Yet the demands and technologies of the future may require infrastructures - both material facilities and hum...

  2. Impact of biodiversity-climate futures on primary production and metabolism in a model benthic estuarine system

    OpenAIRE

    Raffaelli Dave; Solan Martin; Bulling Mark T; Hicks Natalie; White Piran CL; Paterson David M

    2011-01-01

    Abstract Background Understanding the effects of anthropogenically-driven changes in global temperature, atmospheric carbon dioxide and biodiversity on the functionality of marine ecosystems is crucial for predicting and managing the associated impacts. Coastal ecosystems are important sources of carbon (primary production) to shelf waters and play a vital role in global nutrient cycling. These systems are especially vulnerable to the effects of human activities and will be the first areas im...

  3. Quantifying the response of climate to changes in land cover : can we separate direct effects from feedbacks in earth system models' outputs?

    Science.gov (United States)

    Devaraju, Narayanappa; de Noblet-Ducoudré, Nathalie

    2016-04-01

    Regional and global climate responses to biophysical effects of land use and land cover changes (LULCC) still largely differ among the models used in the LUCID intercomparison project, despite some constrained protocol (Boisier et al. 2012). de Noblet-Ducoudré et al. (2012) have shown that ~1/3rd of the differences can be attributed to the lack of consistent implementation of land uses in earth system models (ESM), while the remaining 2/3rd result from differences between land-surface models as well as from the climate feedbacks simulated in each ESM. However, to our knowledge, no study has yet tried to i) disentangle direct effects from feedbacks, and ii) see whether regional sensitivity can be assessed rather than the more traditional global one. In this study we focus on the spatially distributed biophysical effects of LULCC. The important contributors to spatially distributed effects are inhomogeneous changes in direct effects (albedo, evapotranspiration efficiency, surface roughness), and their atmospheric feedbacks. Among those feedbacks one can cite changes in air humidity, air temperature, cloud cover, water vapor and planetary boundary layer height. Direct effects from feedbacks are separated by solving the surface energy budget equation. We have first applied this method to quantify regional and global land surface temperature changes in IPSL-CM5 and NCAR CAM5.0 ESMs that have simulated the effects of idealized global deforestation. In IPSL-CM5, direct effects over land south of latitude 20°N are stronger (warming of 2.26 K in JJA and 1.28 K in DJF) when compared to CAM5.0 (cooling of 0.05 K in JJA and 0.06 K in DJF). In contrast, feedbacks over land north of latitude 20°N are stronger in CAM5.0 (cooling of 4.4 K in JJA and 3.9 K in DJF) when compared to IPSL-CM5 (cooling of 1.9 K in JJA and 3.0 K in DJF). However, on average over global land in both the models we find that direct effects (eg. JJA: 0.55 K in IPSL-CM5 and -0.8 K in CAM5.0) are weaker

  4. A View of Earth System Model Development

    Institute of Scientific and Technical Information of China (English)

    ZHOU Tianjun; YU Yongqiang; WANG Bin

    2009-01-01

    This paper gives a definition of earth system model and shows three development phases of it, including physical climate system model, earth climate system model, and earth system model, based on an inves-tigation of climate system models in the world. It provides an expatiation on the strategic significance of future development of earth system model, an introduction of some representative scientific research plans on development of earth system model home and abroad, and a review of its status and trends based on the models of the fourth assessment report (AR4) of the Intergovernmental Panel on Climate Change (IPCC).Some suggestions on future development of earth system model in China are given, which are expected to be helpful to advance the development.

  5. Rainwater catchment system design using simulated future climate data

    Science.gov (United States)

    Wallace, Corey D.; Bailey, Ryan T.; Arabi, Mazdak

    2015-10-01

    Rainwater harvesting techniques are used worldwide to augment potable water supply, provide water for small-scale irrigation practices, increase rainwater-use efficiency for sustained crop growth in arid and semi-arid regions, decrease urban stormwater flow volumes, and in general to relieve dependency on urban water resources cycles. A number of methods have been established in recent years to estimate reliability of rainwater catchment systems (RWCS) and thereby properly size the components (roof catchment area, storage tank size) of the system for a given climatic region. These methods typically use historical or stochastically-generated rainfall patterns to quantify system performance and optimally size the system, with the latter accounting for possible rainfall scenarios based on statistical relationships of historical rainfall patterns. To design RWCS systems that can sustainably meet water demand under future climate conditions, this paper introduces a method that employs climatic data from general circulation models (GCMs) to develop a suite of catchment area vs. storage size design curves that capture uncertainty in future climate scenarios. Monthly rainfall data for the 2010-2050 time period is statistically downscaled to daily values using a Markov chain algorithm, with results used only from GCMs that yield rainfall patterns that are statistically consistent with historical rainfall patterns. The process is demonstrated through application to two climatic regions of the Federated States of Micronesia (FSM) in the western Pacific, wherein the majority of the population relies on rainwater harvesting for potable water supply. Through the use of design curves, communities can provide household RWCS that achieve a certain degree of storage reliability. The method described herein can be applied generally to any geographic region. It can be used to first, assess the future performance of existing household systems; and second, to design or modify systems

  6. 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.

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

    NARCIS (Netherlands)

    Wolf, J.

    2002-01-01

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

  8. 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;

    - and river flow as well as land surface-atmosphere fluxes of water (evapotranspiration) and energy - significantly reduces precipitation bias compared to the regional climate model alone. For a six year simulation period (2004 – 2010) covering a 2500 km2 catchment substantial improvements in the......The complexity of precipitation processes makes it difficult for climate models to reliably simulate precipitation, particularly at sub-grid scales, where the important processes are associated with detailed land-atmosphere feedbacks like the vertical circulations driven by latent heat that affect...... 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...

  9. Uncertain climate change in an intergenerational planning model

    International Nuclear Information System (INIS)

    A three-generation planning model incorporating uncertain climate change is developed. Each generation features a production activity based on capital and an exhaustible resource. An irreversible climate change may occur in period two or three, reducing the productivity for this and the remaining generation. The model is solved by stochastic dynamic programming. If the climate impact and climate change probability is constant, the optimal period one (and two) resource extraction is larger than for the reference case of climate stability. If, however, climate impact and climate change probability increases with increased aggregate resource use, this result is reversed. 5 tabs., 1 appendix, 22 refs

  10. 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

  11. Precalibrating an intermediate complexity climate model

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-10-15

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

  12. Online Mapping Systems for Climate Data Delivery

    Science.gov (United States)

    Gray, S. T.; Nicholson, C. M.; Bergantino, A. R.

    2009-12-01

    Online, map-based applications have experienced an explosion in popularity over the past decade. The success of these systems is largely due to their ability to provide a spatial framework data exploration, and for the visual context (e.g., satellite images) they offer. Here we detail the development of a new online mapping system for Wyoming that will serve as a portal for the delivery of weather, climate, and water-related data for users across the state. While capitalizing on the success of previous online mapping efforts, this new system also highlights the potential for additional applications and functionality. Known as the Wyoming Internet Map Server (WyoIMS), the system brings together real-time observations and summary products from multiple federal agencies (NOAA-NWS, NRCS, USGS) to provide “one-stop-shopping” for key climatic datasets. Likewise this system is providing a platform for data delivery, archiving, and QC/QA as part of a new statewide hydroclimatic monitoring network. Moving beyond the simple transfer of data, this system also allows users to access information from resources that include state libraries and various databases that contain information related to climate and water resources. Users can, for example, select individual counties, watersheds, irrigation districts, or municipalities and download a wide range of documents and reports specific to those locations. On the whole, WyoIMS has become a catalyst for the development of new climate-related products, and a foundation for decision support with applications in water resources, wildlife management, and agriculture.

  13. Climate change policymaking: Three explanatory models

    OpenAIRE

    Bang, Guri

    2000-01-01

    This paper gives an outline of three explanatory approaches to policymaking processes that allow the development of a rich set of non-trivial, probable assumptions. These assumptions provide a foundation for understanding climate policymaking behavior. First, the Unitary Rational Actor model provides a set of assumptions about the state’s interest in calculating costs and benefits as a basis for decision-making. By avoiding the inclusion of sub-actors in the analysis, it is possible to analyz...

  14. Modelling Complexity: the case of Climate Science

    OpenAIRE

    Lucarini, Valerio

    2011-01-01

    We briefly review some of the scientific challenges and epistemological issues related to climate science. We discuss the formulation and testing of theories and numerical models, which, given the presence of unavoidable uncertainties in observational data, the non-repeatability of world-experiments, and the fact that relevant processes occur in a large variety of spatial and temporal scales, require a rather different approach than in other scientific contexts. A brief discussion of the intr...

  15. Permafrost, climate, and change: predictive modelling approach.

    Science.gov (United States)

    Anisimov, O.

    2003-04-01

    Predicted by GCMs enhanced warming of the Arctic will lead to discernible impacts on permafrost and northern environment. Mathematical models of different complexity forced by scenarios of climate change may be used to predict such changes. Permafrost models that are currently in use may be divided into four groups: index-based models (e.g. frost index model, N-factor model); models of intermediate complexity based on equilibrium simplified solution of the Stephan problem ("Koudriavtcev's" model and its modifications), and full-scale comprehensive dynamical models. New approach of stochastic modelling came into existence recently and has good prospects for the future. Important task is to compare the ability of the models that are different in complexity, concept, and input data requirements to capture the major impacts of changing climate on permafrost. A progressive increase in the depth of seasonal thawing (often referred to as the active-layer thickness, ALT) could be a relatively short-term reaction to climatic warming. At regional and local scales, it may produce substantial effects on vegetation, soil hydrology and runoff, as the water storage capacity of near-surface permafrost will be changed. Growing public concerns are associated with the impacts that warming of permafrost may have on engineered infrastructure built upon it. At the global scale, increase of ALT could facilitate further climatic change if more greenhouse gases are released when the upper layer of the permafrost thaws. Since dynamic permafrost models require complete set of forcing data that is not readily available on the circumpolar scale, they could be used most effectively in regional studies, while models of intermediate complexity are currently best tools for the circumpolar assessments. Set of five transient scenarios of climate change for the period 1980 - 2100 has been constructed using outputs from GFDL, NCAR, CCC, HadCM, and ECHAM-4 models. These GCMs were selected in the course

  16. Possible (water sensitive) mitigation strategies for the urban climate in a regional climate modelling context

    OpenAIRE

    Demuzere, Matthias; Coutts, Andrew; Van Lipzig, Nicole

    2012-01-01

    Urban climate models provide a useful tool for assessing the impacts of urban land surface modification on urban climates. It provides a mechanism for trialling different scenarios for urban heat island mitigation. Only recently, urban land surfaces have been included in global and regional climate models. Often they represent a trade-off between the complexity of the biophysical processes of the urban canopy layer and the computational demands in order to be workable on regional climate time...

  17. Prediction of future climate change for the Blue Nile, using a nested Regional Climate Model

    Science.gov (United States)

    Soliman, E.; Jeuland, M.

    2009-04-01

    Although the Nile River Basin is rich in natural resources, it faces many challenges. Rainfall is highly variable across the region, on both seasonal and inter-annual scales. This variability makes the region vulnerable to droughts and floods. Many development projects involving Nile waters are currently underway, or being studied. These projects will lead to land-use patterns changes and water distribution and availability. It is thus important to assess the effects of a) these projects and b) evolving water resource management and policies, on regional hydrological processes. This paper seeks to establish a basis for evaluation of such impacts within the Blue Nile River sub-basin, using the RegCM3 Regional Climate Model to simulate interactions between the land surface and climatic processes. We first present results from application of this RCM model nested with downscaled outputs obtained from the ECHAM5/MPI-OM1 transient simulations for the 20th Century. We then investigate changes associated with mid-21st century emissions forcing of the SRES A1B scenario. The results obtained from the climate model are then fed as inputs to the Nile Forecast System (NFS), a hydrologic distributed rainfall runoff model of the Nile Basin, The interaction between climatic and hydrological processes on the land surface has been fully coupled. Rainfall patterns and evaporation rates have been generated using RegCM3, and the resulting runoff and Blue Nile streamflow patterns have been simulated using the NFS. This paper compares the results obtained from the RegCM3 climate model with observational datasets for precipitation and temperature from the Climate Research Unit (UK) and the NASA Goddard Space Flight Center GPCP (USA) for 1985-2000. The validity of the streamflow predictions from the NFS is assessed using historical gauge records. Finally, we present results from modeling of the A1B emissions scenario of the IPCC for the years 2034-2055. Our results indicate that future

  18. A climate model intercomparison at the dynamics level

    Science.gov (United States)

    Steinhaeuser, Karsten; Tsonis, Anastasios A.

    2014-03-01

    Until now, climate model intercomparison has focused primarily on annual and global averages of various quantities or on specific components, not on how well the general dynamics in the models compare to each other. In order to address how well models agree when it comes to the dynamics they generate, we have adopted a new approach based on climate networks. We have considered 28 pre-industrial control runs as well as 70 20th-century forced runs from 23 climate models and have constructed networks for the 500 hPa, surface air temperature (SAT), sea level pressure (SLP), and precipitation fields for each run. We then employed a widely used algorithm to derive the community structure in these networks. Communities separate "nodes" in the network sharing similar dynamics. It has been shown that these communities, or sub-systems, in the climate system are associated with major climate modes and physics of the atmosphere (Tsonis AA, Swanson KL, Wang G, J Clim 21: 2990-3001 in 2008; Tsonis AA, Wang G, Swanson KL, Rodrigues F, da Fontura Costa L, Clim Dyn, 37: 933-940 in 2011; Steinhaeuser K, Ganguly AR, Chawla NV, Clim Dyn 39: 889-895 in 2012). Once the community structure for all runs is derived, we use a pattern matching statistic to obtain a measure of how well any two models agree with each other. We find that, with the possible exception of the 500 hPa field, consistency for the SAT, SLP, and precipitation fields is questionable. More importantly, none of the models comes close to the community structure of the actual observations (reality). This is a significant finding especially for the temperature and precipitation fields, as these are the fields widely used to produce future projections in time and in space.

  19. Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures

    OpenAIRE

    Cowtan, Kevin; Hausfather, Zeke; Hawkins, Ed; Jacobs, Peter; Mann, Michael E.; Miller, Sonya K.; Byron A. Steinman; Stolpe, Martin B.; Way, Robert G.

    2015-01-01

    The level of agreement between climate model simulations and observed surface temperature change is a topic of scientific and policy concern. While the Earth system continues to accumulate energy due to anthropogenic and other radiative forcings, estimates of recent surface temperature evolution fall at the lower end of climate model projections. Global mean temperatures from climate model simulations are typically calculated using surface air temperatures, while the corresponding observation...

  20. Toward a high performance distributed memory climate model

    Energy Technology Data Exchange (ETDEWEB)

    Wehner, M.F.; Ambrosiano, J.J.; Brown, J.C.; Dannevik, W.P.; Eltgroth, P.G.; Mirin, A.A. [Lawrence Livermore National Lab., CA (United States); Farrara, J.D.; Ma, C.C.; Mechoso, C.R.; Spahr, J.A. [Univ. of California, Los Angeles, CA (US). Dept. of Atmospheric Sciences

    1993-02-15

    As part of a long range plan to develop a comprehensive climate systems modeling capability, the authors have taken the Atmospheric General Circulation Model originally developed by Arakawa and collaborators at UCLA and have recast it in a portable, parallel form. The code uses an explicit time-advance procedure on a staggered three-dimensional Eulerian mesh. The authors have implemented a two-dimensional latitude/longitude domain decomposition message passing strategy. Both dynamic memory management and interprocessor communication are handled with macro constructs that are preprocessed prior to compilation. The code can be moved about a variety of platforms, including massively parallel processors, workstation clusters, and vector processors, with a mere change of three parameters. Performance on the various platforms as well as issues associated with coupling different models for major components of the climate system are discussed.

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

    International Nuclear Information System (INIS)

    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

  2. Anticipating the uncertain: economic modeling and climate change policy

    Energy Technology Data Exchange (ETDEWEB)

    Jensen, Svenn

    2012-11-01

    With this thesis I wish to contribute to the understanding of how uncertainty and the anticipation of future events by economic actors affect climate policies. The thesis consists of four papers. Two papers are analytical models which explicitly consider that emissions are caused by extracting scarce fossil fuels which in the future must be replaced by clean technologies. The other two are so called numerical integrated assessment models. Such models represent the world economy, the climate system and the interactions between those two quantitatively, complementing more abstract theoretical work. Should policy makers discriminate between subsidizing renewable energy sources such as wind or solar power, and technologies such as carbon capture and storage (CCS)? Focusing only on the dynamic supply of fossil fuels and hence Co{sub 2}, we find here that cheaper future renewables cause extraction to speed up, lower costs of CCS may delay it. CCS hence may dampen the dynamic inefficiency caused by the absence of comprehensive climate policies today. Does it matter whether uncertainty about future damage assessment is due to scientific complexities or stems from the political process? In paper two, I find that political and scientific uncertainties have opposing effects on the incentives to investment in renewables and the extraction of fossil fuels: The prospect of scientific learning about the climate system increases investment incentives and, ceteris paribus, slows extraction down; uncertainty about future political constellations does the opposite. The optimal carbon tax under scientific uncertainty equals expected marginal damages, whereas political uncertainty demands a tax below marginal damages that decreases over time. Does uncertainty about economic growth impact optimal climate policy today? Here we are the first to consistently analyze how uncertainty about future economic growth affects optimal emission reductions and the optimal social cost of carbon. We

  3. Assembling Tools and Data for Climate Model Decision Support

    Science.gov (United States)

    Batcheller, A. L.; VanWijngaarden, F.

    2011-12-01

    The Global Earth Observation System of Systems (GEOSS) effort has identified nine areas in which society benefits from appropriate environmental information. We have targeted specific issues within these societal benefit areas by determining appropriate data sets needed and transforming these data into information useable by decision makers. Here we describe the service-oriented architecture that allows us to ingest real-time or static data into a database with a spatial data engine, make appropriate manipulations to the data using domain knowledge relevant to the problem, and expose the data as services. We then build custom portals using a library of common widgets to display and overlay the data for users to analyze. By using portals and a service-oriented architecture we can reuse services and widgets to rapidly assemble a view of geographic data, and assist decision-makers in applying and interpreting the latest scientific results. As a case study with our system, we have integrated data from Intergovernmental Panel on Climate Change (IPCC) climate models, crop yields, and environmental thresholds for crops to present a first level analysis of the impact of climate change on key crops grown in Mexico. Knowledge about changes in the regions that are favorable for crop growth is important for many stakeholders, ranging from individual farmers, to governments, to scientists working to create new seed varieties. Our work also highlights research opportunities in climate science by identifying the types and resolution of parameters modeled.

  4. Climate change impacts in computable general equilibrium models: An overview

    OpenAIRE

    Döll, Sebastian

    2009-01-01

    This paper gives an overview about existing Computable General Equilibrium (CGE) models dealing with climate impacts focusing on damage calculations and adaptation modelling. Empirical CGE models are used in a broad field of policy analysis. With respect to climate change applications have been focused on the calculation of climate damages and the mitigation of these damages. Facing the non-preventable damages from climate change that occur already in the next decades adaptation is becoming a...

  5. The Informed Guide to Climate Data Sets, a web-based community resource to facilitate the discussion and selection of appropriate datasets for Earth System Model Evaluation

    Science.gov (United States)

    Schneider, D. P.; Deser, C.; Shea, D.

    2011-12-01

    When comparing CMIP5 model output to observations, researchers will be faced with a bewildering array of choices. Considering just a few of the different products available for commonly analyzed climate variables, for reanalysis there are at least half a dozen different products, for sea ice concentrations there are NASA Team or Bootstrap versions, for sea surface temperatures there are HadISST or NOAA ERSST data, and for precipitation there are CMAP and GPCP data sets. While many data centers exist to host data, there is little centralized guidance on discovering and choosing appropriate climate data sets for the task at hand. Common strategies like googling "sea ice data" yield results that at best are substantially incomplete. Anecdotal evidence suggests that individual researchers often base their selections on non-scientific criteria-either the data are in a convenient format that the user is comfortable with, a co-worker has the data handy on her local server, or a mentor discourages or recommends the use of particular products for legacy or other non-objective reasons. Sometimes these casual recommendations are sound, but they are not accessible to the broader community or adequately captured in the peer-reviewed literature. These issues are addressed by the establishment of a web-based Informed Guide with the specific goals to (1) Evaluate and assess selected climate datasets and (2) Provide expert user guidance on the strengths and limitations of selected climate datasets. The Informed Guide is based at NCAR's Climate and Global Dynamics Division, Climate Analysis Section and is funded by NSF. The Informed Guide is an interactive website that welcomes participation from the broad scientific community and is scalable to grow as participation increases. In this presentation, we will present the website, discuss how you can participate, and address the broader issues about its role in the evaluation of CMIP5 and other climate model simulations. A link to the

  6. Sensitivity of Future U.S. Water Shortages to Socioeconomic and Climate Drivers: A Case Study in Georgia Using an Integrated Human-Earth System Modeling Framework

    Energy Technology Data Exchange (ETDEWEB)

    Scott, Michael J.; Daly, Don S.; Hejazi, Mohamad I.; Kyle, G. Page; Liu, Lu; McJeon, Haewon C.; Mundra, Anupriya; Patel, Pralit L.; Rice, Jennie S.; Voisin, Nathalie

    2016-01-06

    One of the most important interactions between humans and climate is in the demand and supply of water. Humans withdraw, use, and consume water and return waste water to the environment for a variety of socioeconomic purposes, including domestic, commercial ,and industrial use, production of energy resources and cooling thermal-electric power plants, and growing food, fiber, and chemical feedstocks for human consumption. Uncertainties in the future human demand for water and in the future impacts of climatic change on water supplies are expected to impinge on policy decisions at the international, national, regional, and local level, but until recently tools were not available to assess the uncertainties surrounding these decisions. This paper demonstrates the use of a multi-model framework in a structured sensitivity analysis to project and quantify uncertainty in deficits in future surface water in the context of climate and socioeconomic change for all U.S. states and sub-basins. The framework treats all sources of water demand and supply consistently from the world to local level. The paper features an illustrative case study of a river basin in Georgia within the South Atlantic-Gulf Basin. Despite a substantial climate-related uncertainty in water supplies, the uncertainty with the largest impact on deficits was identified as growth of irrigation demand. Potential adaptive responses are discussed.

  7. Modelling Complexity: the case of Climate Science

    CERN Document Server

    Lucarini, Valerio

    2011-01-01

    We briefly review some of the scientific challenges and epistemological issues related to climate science. We discuss the formulation and testing of theories and numerical models, which, given the presence of unavoidable uncertainties in observational data, the non-repeatability of world-experiments, and the fact that relevant processes occur in a large variety of spatial and temporal scales, require a rather different approach than in other scientific contexts. A brief discussion of the intrinsic limitations of geo-engineering solutions to global warming is presented, and a framework of investigation based upon non-equilibrium thermodynamics is proposed. We also critically discuss recently proposed perspectives of development of climate science based purely upon massive use of supercomputer and centralized planning of scientific priorities.

  8. Impacts of Future Climate Change on California Perennial Crop Yields: Model Projections with Climate and Crop Uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Lobell, D; Field, C; Cahill, K; Bonfils, C

    2006-01-10

    Most research on the agricultural impacts of climate change has focused on the major annual crops, yet perennial cropping systems are less adaptable and thus potentially more susceptible to damage. Improved assessments of yield responses to future climate are needed to prioritize adaptation strategies in the many regions where perennial crops are economically and culturally important. These impact assessments, in turn, must rely on climate and crop models that contain often poorly defined uncertainties. We evaluated the impact of climate change on six major perennial crops in California: wine grapes, almonds, table grapes, oranges, walnuts, and avocados. Outputs from multiple climate models were used to evaluate climate uncertainty, while multiple statistical crop models, derived by resampling historical databases, were used to address crop response uncertainties. We find that, despite these uncertainties, climate change in California is very likely to put downward pressure on yields of almonds, walnuts, avocados, and table grapes by 2050. Without CO{sub 2} fertilization or adaptation measures, projected losses range from 0 to >40% depending on the crop and the trajectory of climate change. Climate change uncertainty generally had a larger impact on projections than crop model uncertainty, although the latter was substantial for several crops. Opportunities for expansion into cooler regions are identified, but this adaptation would require substantial investments and may be limited by non-climatic constraints. Given the long time scales for growth and production of orchards and vineyards ({approx}30 years), climate change should be an important factor in selecting perennial varieties and deciding whether and where perennials should be planted.

  9. Modelling the hydrological cycle in assessments of climate change

    Science.gov (United States)

    Rind, D.; Rosenzweig, C.; Goldberg, R.

    1992-01-01

    The predictions of climate change studies depend crucially on the hydrological cycles embedded in the different models used. It is shown here that uncertainties in hydrological processes and inconsistencies in both climate and impact models limit confidence in current assessments of climate change. A future course of action to remedy this problem is suggested.

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  11. 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

  12. Modeling interactions between land cover and climate in integrated assessment models (Invited)

    Science.gov (United States)

    Calvin, K. V.

    2013-12-01

    Integrated Assessment Models (IAMs) link representations of the regionally disaggregated global economy, energy system, agriculture and land-use, terrestrial carbon cycle, oceans and climate in an internally consistent framework. These models are often used as science-based decision-support tools for evaluating the consequences of climate, energy, and other policies, and their use in this framework is likely to increase in the future. Additionally, these models are used to develop future scenarios of emissions and land cover for use in climate models (e.g., RCPs and CMIP5). Land use is strongly influenced by assumptions about population, income, diet, ecosystem productivity change, and climate policy. Population, income, and diet determine the amount of food production needed in the future. Assumptions about future changes in crop yields due to agronomic developments influence the amount of land needed to produce food crops. Climate policy has implications for land when land-based mitigation options (e.g., afforestation and bioenergy) are considered. IAM models consider each of these factors in their computation of land use in the future. As each of these factors is uncertain in the future, IAM models use scenario analysis to explore the implications of each. For example, IAMs have been used to explore the effect of different mitigation policies on land cover. These models can quantify the trade-offs in terms of land cover, energy prices, food prices, and mitigation costs of each of these policies. Furthermore, IAMs are beginning to explore the effect of climate change on land productivity, and the implications that changes in productivity have on mitigation efforts. In this talk, we describe the implications for future land use and land cover of a variety of socioeconomic, technological, and policy drivers in several IAM models. Additionally, we will discuss the effects of future land cover on climate and the effects of climate on future land cover, as simulated

  13. Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems

    DEFF Research Database (Denmark)

    del Prado, A; Crosson, P; Olesen, Jørgen E;

    2013-01-01

    The farm level is the most appropriate scale for evaluating options for mitigating greenhouse gas (GHG) emissions, because the farm represents the unit at which management decisions in livestock production are made. To date, a number of whole farm modelling approaches have been developed to...... components and the sensitivity of GHG outputs and mitigation measures to different approaches. Potential challenges for linking existing models with the simulation of impacts and adaptation measures under climate change are explored along with a brief discussion of the effects on other ecosystem services....

  14. 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.

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

    OpenAIRE

    Hagemann, S.; Chen, C.; Clark, D.B.; S. Folwell; Gosling, S.N.; Haddeland, I.; Hanasaki, N.; J. Heinke; F. Ludwig; Voß, F.; A. J. Wiltshire

    2012-01-01

    Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological models (eight) were used to systematically assess the hydrological response to climate change and project the future state of global water resources. The results show a large spread in projected changes in water resources within the climate–...

  16. Modelling and observing urban climate in the Netherlands

    International Nuclear Information System (INIS)

    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

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

    Science.gov (United States)

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

    2010-12-01

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

  18. Computing and Systems Applied in Support of Coordinated Energy, Environmental, and Climate Planning

    Science.gov (United States)

    This talk focuses on how Dr. Loughlin is applying Computing and Systems models, tools and methods to more fully understand the linkages among energy systems, environmental quality, and climate change. Dr. Loughlin will highlight recent and ongoing research activities, including: ...

  19. Challenges in combining projections from multiple climate models

    OpenAIRE

    J. Cermak; Furrer, R.; Knutti, R.; Meehl, G. A.; Tebaldi, C.

    2010-01-01

    Recent coordinated efforts, in which numerous general circulation climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Those multimodel ensembles sample initial conditions, parameters, and structural uncertainties in the model design, and they have prompted a variety of approaches to quantifying uncertainty in future climate change. International climate change assessments also rely heavily on these ...

  20. A Gaussian graphical model approach to climate networks

    Science.gov (United States)

    Zerenner, Tanja; Friederichs, Petra; Lehnertz, Klaus; Hense, Andreas

    2014-06-01

    Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately.

  1. A Gaussian graphical model approach to climate networks

    International Nuclear Information System (INIS)

    Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately

  2. A Gaussian graphical model approach to climate networks

    Energy Technology Data Exchange (ETDEWEB)

    Zerenner, Tanja, E-mail: tanjaz@uni-bonn.de [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Friederichs, Petra; Hense, Andreas [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany); Lehnertz, Klaus [Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn (Germany); Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany)

    2014-06-15

    Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately.

  3. Bio-physical interactions and feedbacks in a global climate model

    OpenAIRE

    Patara, Lavinia

    2010-01-01

    This PhD thesis addresses the topic of large-scale interactions between climate and marine biogeochemistry. To this end, centennial simulations are performed under present and projected future climate conditions with a coupled ocean-atmosphere model containing a complex marine biogeochemistry model. The role of marine biogeochemistry in the climate system is first investigated. Phytoplankton solar radiation absorption in the upper ocean enhances sea surface temperatures and upper ocean strati...

  4. Modelling precipitation extremes in climate change scenarios

    Czech Academy of Sciences Publication Activity Database

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

    Patras: University of Patras, 2010 - (Argiriou, A.; Kazantzidis, A.), s. 833-838 ISBN 978-960-99254-0-2. [International Conference of Meteorology, Climatology and Atmospheric Physics (COMECAP2010) /10./. Patras (GR), 25.05.2010-28.05.2010] R&D Projects: GA AV ČR KJB300420801 Grant ostatní: ENSEMBLES(XE) 505539 Institutional research plan: CEZ:AV0Z30420517 Keywords : precipitation extremes * region-of-influence method * regional climate models Subject RIV: DG - Athmosphere Sciences, Meteorology

  5. Mixing parameterizations in ocean climate modeling

    Science.gov (United States)

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

    2016-03-01

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

  6. Effects of adjusting cropping systems on utilization efficiency of climatic resources in Northeast China under future climate scenarios

    Science.gov (United States)

    Guo, Jianping; Zhao, Junfang; Xu, Yanhong; Chu, Zheng; Mu, Jia; Zhao, Qian

    Quantitatively evaluating the effects of adjusting cropping systems on the utilization efficiency of climatic resources under climate change is an important task for assessing food security in China. To understand these effects, we used daily climate variables obtained from the regional climate model RegCM3 from 1981 to 2100 under the A1B scenario and crop observations from 53 agro-meteorological experimental stations from 1981 to 2010 in Northeast China. Three one-grade zones of cropping systems were divided by heat, water, topography and crop-type, including the semi-arid areas of the northeast and northwest (III), the one crop area of warm-cool plants in semi-humid plain or hilly regions of the northeast (IV), and the two crop area in irrigated farmland in the Huanghuaihai Plain (VI). An agro-ecological zone model was used to calculate climatic potential productivities. The effects of adjusting cropping systems on climate resource utilization in Northeast China under the A1B scenario were assessed. The results indicated that from 1981 to 2100 in the III, IV and VI areas, the planting boundaries of different cropping systems in Northeast China obviously shifted toward the north and the east based on comprehensively considering the heat and precipitation resources. However, due to high temperature stress, the climatic potential productivity of spring maize was reduced in the future. Therefore, adjusting the cropping system is an effective way to improve the climatic potential productivity and climate resource utilization. Replacing the one crop in one year model (spring maize) by the two crops in one year model (winter wheat and summer maize) significantly increased the total climatic potential productivity and average utilization efficiencies. During the periods of 2011-2040, 2041-2070 and 2071-2100, the average total climatic potential productivities of winter wheat and summer maize increased by 9.36%, 11.88% and 12.13% compared to that of spring maize

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

    International Nuclear Information System (INIS)

    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

  8. Earth System Grid II, Turning Climate Datasets into Community Resources

    Energy Technology Data Exchange (ETDEWEB)

    Middleton, Don

    2006-08-01

    The Earth System Grid (ESG) II project, funded by the Department of Energy’s Scientific Discovery through Advanced Computing program, has transformed climate data into community resources. ESG II has accomplished this goal by creating a virtual collaborative environment that links climate centers and users around the world to models and data via a computing Grid, which is based on the Department of Energy’s supercomputing resources and the Internet. Our project’s success stems from partnerships between climate researchers and computer scientists to advance basic and applied research in the terrestrial, atmospheric, and oceanic sciences. By interfacing with other climate science projects, we have learned that commonly used methods to manage and remotely distribute data among related groups lack infrastructure and under-utilize existing technologies. Knowledge and expertise gained from ESG II have helped the climate community plan strategies to manage a rapidly growing data environment more effectively. Moreover, approaches and technologies developed under the ESG project have impacted datasimulation integration in other disciplines, such as astrophysics, molecular biology and materials science.

  9. 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.

  10. Avoiding Dangerous Anthropogenic Interference with the Climate System

    Energy Technology Data Exchange (ETDEWEB)

    Keller, K. [Department of Geosciences, Penn State, PA (United States); Hall, M. [Brookings Institution, Washington, DC (United States); Kim, Seung-Rae [Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ (United States); Bradford, D.F. [Department of Economics, Princeton University, Princeton, NJ (United States); Oppenheimer, M. [Woodrow Wilson School and Department of Geosciences, Princeton University, Robertson Hall 448, Princeton, NJ, 08544 (United States)

    2005-12-01

    The UN Framework Convention on Climate Change calls for the avoidance of 'dangerous anthropogenic interference with the climate system'. Among the many plausible choices, dangerous interference with the climate system may be interpreted as anthropogenic radiative forcing causing distinct and widespread climate change impacts such as a widespread demise of coral reefs or a disintegration of the West Antarctic ice sheet. The geological record and numerical models suggest that limiting global warming below critical temperature thresholds significantly reduces the likelihood of these eventualities. Here we analyze economically optimal policies that may ensure this risk-reduction. Reducing the risk of a widespread coral reef demise implies drastic reductions in greenhouse gas emissions within decades. Virtually unchecked greenhouse gas emissions to date (combined with the inertia of the coupled natural and human systems) may have already committed future societies to a widespread demise of coral reefs. Policies to reduce the risk of a West Antarctic ice sheet disintegration allow for a smoother decarbonization of the economy within a century and may well increase consumption in the long run.

  11. Regional climate simulations over Vietnam using the WRF model

    Science.gov (United States)

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

    2015-07-01

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

  12. Comparison of a global-climate model simulation to a cloud-system resolving model simulation for long-term thin stratocumulus clouds

    Directory of Open Access Journals (Sweden)

    S. S. Lee

    2009-05-01

    Full Text Available A case of thin, warm marine-boundary-layer (MBL clouds is simulated by a cloud-system resolving model (CSRM and is compared to the same case of clouds simulated by a general circulation model (GCM. In this study, the simulation by the CSRM adopts higher resolutions and more advanced microphysics as compared to those by the GCM, enabling the CSRM-simulation to act as a benchmark to assess the simulation by the GCM. Explicitly simulated interactions among the surface latent heat (LH fluxes, buoyancy fluxes, and cloud-top entrainment lead to the deepening-warming decoupling and thereby the transition from stratiform clouds to cumulus clouds in the CSRM. However, in the simulation by the GCM, these interactions are not resolved and thus the transition to cumulus clouds is not simulated. This leads to substantial differences in cloud mass and radiation between simulations by the CSRM and the GCM. When stratocumulus clouds are dominant prior to the transition to cumulus clouds, interactions between supersaturation and cloud droplet number concentration (CDNC (controlling condensation and those between rain evaporation and cloud-base instability (controlling cloud dynamics and thereby condensation determine cloud mass and thus the radiation budget in the simulation by the CSRM. These interactions result in smaller condensation and thus smaller cloud mass and reflected solar radiation by clouds in the simulation by the CSRM than in the simulation by the GCM where these interactions are not resolved. The resolved interactions (associated with condensation and the transition to cumulus clouds lead to better agreement between the CSRM-simulation and observation than that between the GCM-simulation and observation.

  13. Strengthening Carrying Capacity of a Water Supply System under Climate Change with the Drought Early Warning System

    Science.gov (United States)

    Huang, Syujie; Liu, Tzuming; Li, Minghsu; Tung, Chingpin

    2016-04-01

    The carrying capacity of a water supply system is the maximal probable water supply amount under an acceptable risk which is related to the systematic combination of hydrology conditions, climatic conditions, and water infrastructures, for instance, reservoirs, weirs, and water treatment plants. Due to long-term imbalance of water supply and demand during the drought seasons, the carrying capacity of a water supply system may be affected gradually with more extreme climate events resulting from the climate change. To evaluate the carrying capacity of the water supply system under climate change, three major steps to build adaptation capacity under climate change are adopted, including problem identification and goal setting, current risk assessment, and future risk assessment. The carrying capacities for current climate condition and future climate condition were estimated respectively. The early warning system was taken as the effective measure to strengthen the carrying capacity for the uncertain changing climate. The water supply system of Chuoshui River basin in Taiwan is used as the case study. The system dynamics modeling software, Vensim, was used to build the water resources allocation model for Chuoshui River basin. To apply the seasonal climate forecasts released from Taiwan Central Weather Bureau (CWB) on modeling, a weather generator is adopted to generate daily weather data for the input of the hydrological component of GWLF model, to project inflows with the lead time of three months. Consequently, the water shortages with and without a drought early warning system were estimated to evaluate the effectiveness of a drought early warning system under climate change. Keywords: Climate change, Carrying capacity, Risk Assessment, Seasonal Climate Forecasts, Drought Early Warning System

  14. A 'Common Information Model' for the climate modelling process

    Science.gov (United States)

    Treshansky, Allyn; Devine, Gerard

    2010-05-01

    The Common Information Model (CIM), developed by the EU-funded METAFOR project (http://metaforclimate.eu), is a formal model of the climate modeling process. It provides a rich structured description of not only climate data but also the "provenance" of that data: the software models and tools used to generate that data, the simulations those models implement, the experiments those simulations conform to, etc.. This formal metadata model is expected to add value to those datasets by firstly codifying what is currently found only in the heads of climate experts (the aforementioned provenance of climate datasets), and secondly by allowing tools to be developed that make searching for and analysing climate datasets a much more intuitive process than it has been in the past. This paper will describe the structure of the CIM, concentrating on how it works with and what it adds to other metadata standards. As alluded to above, current metadata standards concentrate on the contents of a climate dataset. Scientific detail and relevance of the model components that generated that data as well as the context for why it was run are missing. The CIM addresses this gap. However, it does not aim to replace existing standards. Rather, wherever possible it re-uses them. It also attempts to standardise our understanding of climate modeling at a very high level, at a conceptual level. This results in a UML description of climate modeling, the CONCIM. METAFOR extracts from this high-level UML the bits of the CIM that we want to use in our applications; These bits get converted into a set of XSD application schemas, the APPCIM. Other user groups may derive a different APPCIM (in a different format) that suits them from the same CONCIM. Thus there is a common understanding of the concepts used in climate modeling even if the implementation differs. In certain key places the CIM describes a general structure over which a specific Controlled Vocabulary (CV) can be applied. For example

  15. Selection of climate change scenario data for impact modelling

    DEFF Research Database (Denmark)

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

    2012-01-01

    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...... in this paper, applied to relative humidity, but it could be adopted to other variables if needed....

  16. 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

  17. Economic impacts of climate change. Flooding and salinity in scenarios, models and cases

    International Nuclear Information System (INIS)

    In this report, climatic and economic scenarios are combined and future risks are calculated for the consequences of climate change, such as a rising sea level, flooding, extreme draughts and salinity. The calculation of these economic effects of climate change are based on climate scenarios of the KNMI (Royal Dutch Meteorological Institute), TNO's RAEM model (Spatial General Economic Model), the high tide information system of the Dutch Ministry of Waterways and Public Works and the Space scanner of the Environmental Assessment Agency. Next to information on scenarios and models, this report also addresses damage calculations of flooding near Lopik and Ter Heide. The report ends with policy recommendations for adaptation policy. [mk

  18. 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/).

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

    Energy Technology Data Exchange (ETDEWEB)

    Auffhammer, Maximilian [University of California at Berkeley; Hsiang, Solomon M. [Princeton University; Schlenker, Wolfram [Columbia University; Sobel, Adam H. [Columbia University

    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.

  20. A New Paradigm for Assessing the Role of Agriculture in the Climate System and in Climate Change

    Science.gov (United States)

    Pielke, Roger A., Sr.; Adegoke, Jimmy O.; Chase, Thomas N.; Marshall, Curtis H.; Matsui, Toshihisa; Niyogi, Dev

    2007-01-01

    This paper discusses the diverse climate forcings that impact agricultural systems, and contrasts the current paradigm of using global models downscaled to agricultural areas (a top-down approach) with a new paradigm that first assesses the vulnerability of agricultural activities to the spectrum of environmental risk including climate (a bottom-up approach). To illustrate the wide spectrum of climate forcings, regional climate forcings are presented including land-use/land-cover change and the influence of aerosols on radiative and biogeochemical fluxes and cloud/precipitation processes, as well as how these effects can be teleconnected globally. Examples are presented of the vulnerability perspective, along with a small survey of the perceived drought impacts in a local area, in which a wide range of impacts for the same precipitation deficits are found. This example illustrates why agricultural assessments of risk to climate change and variability and of other environmental risks should start with a bottom-up perspective.

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

    Science.gov (United States)

    Knutti, R.

    2009-12-01

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

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

    Science.gov (United States)

    Rugenstein, M.; Knutti, R.

    2015-12-01

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

  3. The Impact of IBM Cell Technology on the Programming Paradigm in the Context of Computer Systems for Climate and Weather Models

    International Nuclear Information System (INIS)

    The call for ever-increasing model resolutions and physical processes in climate and weather models demands a continual increase in computing power. The IBM Cell processor's order-of-magnitude peak performance increase over conventional processors makes it very attractive to fulfill this requirement. However, the Cell's characteristics, 256KB local memory per SPE and the new low-level communication mechanism, make it very challenging to port an application. As a trial, we selected the solar radiation component of the NASA GEOS-5 climate model, which: (1) is representative of column physics components (half the total computational time), (2) has an extremely high computational intensity: the ratio of computational load to main memory transfers, and (3) exhibits embarrassingly parallel column computations. In this paper, we converted the baseline code (single-precision Fortran) to C and ported it to an IBM BladeCenter QS20. For performance, we manually SIMDize four independent columns and include several unrolling optimizations. Our results show that when compared with the baseline implementation running on one core of Intel's Xeon Woodcrest, Dempsey, and Itanium2, the Cell is approximately 8.8x, 11.6x, and 12.8x faster, respectively. Our preliminary analysis shows that the Cell can also accelerate the dynamics component (∼ 25% total computational time). We believe these dramatic performance improvements make the Cell processor very competitive as an accelerator

  4. The Impact of IBM Cell Technology on the Programming Paradigm in the Context of Computer Systems for Climate and Weather Models

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Shujia; Duffy, Daniel; Clune, Thomas; Suarez, Max; Williams, Samuel; Halem, Milton

    2009-01-10

    The call for ever-increasing model resolutions and physical processes in climate and weather models demands a continual increase in computing power. The IBM Cell processor's order-of-magnitude peak performance increase over conventional processors makes it very attractive to fulfill this requirement. However, the Cell's characteristics, 256KB local memory per SPE and the new low-level communication mechanism, make it very challenging to port an application. As a trial, we selected the solar radiation component of the NASA GEOS-5 climate model, which: (1) is representative of column physics components (half the total computational time), (2) has an extremely high computational intensity: the ratio of computational load to main memory transfers, and (3) exhibits embarrassingly parallel column computations. In this paper, we converted the baseline code (single-precision Fortran) to C and ported it to an IBM BladeCenter QS20. For performance, we manually SIMDize four independent columns and include several unrolling optimizations. Our results show that when compared with the baseline implementation running on one core of Intel's Xeon Woodcrest, Dempsey, and Itanium2, the Cell is approximately 8.8x, 11.6x, and 12.8x faster, respectively. Our preliminary analysis shows that the Cell can also accelerate the dynamics component (~;;25percent total computational time). We believe these dramatic performance improvements make the Cell processor very competitive as an accelerator.

  5. Climate-based models for understanding and forecasting dengue epidemics.

    Directory of Open Access Journals (Sweden)

    Elodie Descloux

    Full Text Available BACKGROUND: Dengue dynamics are driven by complex interactions between human-hosts, mosquito-vectors and viruses that are influenced by environmental and climatic factors. The objectives of this study were to analyze and model the relationships between climate, Aedes aegypti vectors and dengue outbreaks in Noumea (New Caledonia, and to provide an early warning system. METHODOLOGY/PRINCIPAL FINDINGS: Epidemiological and meteorological data were analyzed from 1971 to 2010 in Noumea. Entomological surveillance indices were available from March 2000 to December 2009. During epidemic years, the distribution of dengue cases was highly seasonal. The epidemic peak (March-April lagged the warmest temperature by 1-2 months and was in phase with maximum precipitations, relative humidity and entomological indices. Significant inter-annual correlations were observed between the risk of outbreak and summertime temperature, precipitations or relative humidity but not ENSO. Climate-based multivariate non-linear models were developed to estimate the yearly risk of dengue outbreak in Noumea. The best explicative meteorological variables were the number of days with maximal temperature exceeding 32°C during January-February-March and the number of days with maximal relative humidity exceeding 95% during January. The best predictive variables were the maximal temperature in December and maximal relative humidity during October-November-December of the previous year. For a probability of dengue outbreak above 65% in leave-one-out cross validation, the explicative model predicted 94% of the epidemic years and 79% of the non epidemic years, and the predictive model 79% and 65%, respectively. CONCLUSIONS/SIGNIFICANCE: The epidemic dynamics of dengue in Noumea were essentially driven by climate during the last forty years. Specific conditions based on maximal temperature and relative humidity thresholds were determinant in outbreaks occurrence. Their persistence was

  6. Progress in rapid climate changes and their modeling study in millennial and centennial scales

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Rapid climate change at millennial and centennial scales is one of the most important aspects in paleoclimate study.It has been found that rapid climate change at millennial and centennial scales is a global phenomenon during both the glacial age and the Holocene with amplitudes typical of geological or astronomical time-scales.Simulations of glacial and Holocene climate changes have demonstrated the response of the climate system to the changes of earth orbital parameter and the importance of variations in feedbacks of ocean,vegetation,icecap and greenhouse gases.Modeling experiments suggest that the Atlantic thermohaline circulation was sensitive to the fresh water input into the North Atlantic and was closely related to the rapid climate changes during the last glacial age and the Holocene.Adopting the Earth-system models of inter mediate complexity (EMICs),CLIMBER-2,the response of East Asian climate change to Dansgaard/Oeschger and Heinrich events during the typical last glacial period (60 ka B.P.-20 ka B.P.) and impacts of ice on the Tibetan plateau on Holocene climate change were stimulated,studied and revealed.Further progress of paleoclimate modeling depends on developing finer-grid models and reconstructing more reliable boundary conditions.More attention should be paid on the study of mechanisms of abrupt climatic changes as well as regional climate changes in the background of global climate change.

  7. Agents, Bayes, and Climatic Risks - a modular modelling approach

    Directory of Open Access Journals (Sweden)

    A. Haas

    2005-01-01

    Full Text Available When insurance firms, energy companies, governments, NGOs, and other agents strive to manage climatic risks, it is by no way clear what the aggregate outcome should and will be. As a framework for investigating this subject, we present the LAGOM model family. It is based on modules depicting learning social agents. For managing climate risks, our agents use second order probabilities and update them by means of a Bayesian mechanism while differing in priors and risk aversion. The interactions between these modules and the aggregate outcomes of their actions are implemented using further modules. The software system is implemented as a series of parallel processes using the CIAMn approach. It is possible to couple modules irrespective of the language they are written in, the operating system under which they are run, and the physical location of the machine.

  8. Coupled Climate Model Appraisal a Benchmark for Future Studies

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J; AchutaRao, K; Bader, D; Covey, C; Doutriaux, C M; Fiorino, M; Gleckler, P J; Sperber, K R; Taylor, K E

    2005-08-22

    The Program for Climate Model Diagnosis and Intercomparison (PCMDI) has produced an extensive appraisal of simulations of present-day climate by eleven representative coupled ocean-atmosphere general circulation models (OAGCMs) which were developed during the period 1995-2002. Because projections of potential future global climate change are derived chiefly from OAGCMs, there is a continuing need to test the credibility of these predictions by evaluating model performance in simulating the historically observed climate. For example, such an evaluation is an integral part of the periodic assessments of climate change that are reported by the Intergovernmental Panel on Climate Change. The PCMDI appraisal thus provides a useful benchmark for future studies of this type. The appraisal mainly analyzed multi-decadal simulations of present-day climate by models that employed diverse representations of climate processes for atmosphere, ocean, sea ice, and land, as well as different techniques for coupling these components (see Table). The selected models were a subset of those entered in phase 2 of the Coupled Model Intercomparison Project (CMIP2, Covey et al. 2003). For these ''CMIP2+ models'', more atmospheric or oceanic variables were provided than the minimum requirements for participation in CMIP2. However, the appraisal only considered those climate variables that were supplied from most of the CMIP2+ models. The appraisal focused on three facets of the simulations of current global climate: (1) secular trends in simulation time series which would be indicative of a problematical ''coupled climate drift''; (2) comparisons of temporally averaged fields of simulated atmospheric and oceanic climate variables with available observational climatologies; and (3) correspondences between simulated and observed modes of climatic variability. Highlights of these climatic aspects manifested by different CMIP2+ simulations are briefly

  9. Assessing the impacts of climate change on natural resource systems

    Energy Technology Data Exchange (ETDEWEB)

    Frederick, K.D.; Rosenberg, N.J. [eds.

    1994-11-30

    This volume is a collection of papers addressing the theme of potential impacts of climatic change. Papers are entitled Integrated Assessments of the Impacts of Climatic Change on Natural Resources: An Introductory Editorial; Framework for Integrated Assessments of Global Warming Impacts; Modeling Land Use and Cover as Part of Global Environmental Change; Assessing Impacts of Climatic Change on Forests: The State of Biological Modeling; Integrating Climatic Change and Forests: Economic and Ecological Assessments; Environmental Change in Grasslands: Assessment using Models; Assessing the Socio-economic Impacts of Climatic Change on Grazinglands; Modeling the Effects of Climatic Change on Water Resources- A Review; Assessing the Socioeconomic Consequences of Climate Change on Water Resources; and Conclusions, Remaining Issues, and Next Steps.

  10. Fast adjustment of the climate system to changes in atmospheric CO2 and solar radiation

    Science.gov (United States)

    Cao, L.; Caldeira, K.; Bala, G.

    2011-12-01

    A key issue in the study of global climate change is the climate response to external forcing. When radiative forcing is applied to the climate system, the climate system starts to respond, resulting in changes in temperature and other fields. A new quasi-equilibrium climate state is achieved when the global mean net energy balance at the top-of-atmosphere returns to zero. The adjustment of the climate system is governed by different processes on different timescales. Within days to months, the climate system adjusts mainly to the imposed forcing and the change of land surface temperature. On longer timescale of years to centuries, when the ocean temperature starts to respond, changes in sea surface temperature exert a strong control on the adjustment of the climate system. By performing ensemble simulations using Hadley Center climate model, HadCM3L, we investigate climate system response to the applied forcing in the forms of additional atmospheric carbon dioxide and an increase in solar insolation. Both carbon dioxide and solar forcing affects the Earth's radiation balance and carbon dioxide also affects the climate system through its impact on plant stomata. We focus on the daily evolution of climate response within a timescale of one month over land and oceans. We will provide a mechanistic understanding of why increasing atmospheric CO2 causes a reduction in global-mean precipitation in the absence of sea surface temperature change. We will also discuss the adjustment of radiative forcing and the usefulness in radiative forcing as a predictor of equilibrium climate change. A discussion of the climate response from daily to millennium timescale will also be presented.

  11. Organizational Diversity Climate: Review of Models and Measurement

    OpenAIRE

    Goyal, Saumya; Shrivastava, Dr.Sangya

    2013-01-01

    As organizational climate represents the culture of an organization, similarly diversity climate represents the culture of diversity and inclusion of an organization. Every best practice in diversity management and diversity initiatives and programs are essentially implemented in order to improve the overall organizational diversity climate. Various models exist in literature which illustrates how diversity climate of a company impacts various employee and organizational measures. Over the ye...

  12. Complex systems approach to fire dynamics and climate change impacts

    Science.gov (United States)

    Pueyo, S.

    2012-04-01

    I present some recent advances in complex systems theory as a contribution to understanding fire regimes and forecasting their response to a changing climate, qualitatively and quantitatively. In many regions of the world, fire sizes have been found to follow, approximately, a power-law frequency distribution. As noted by several authors, this distribution also arises in the "forest fire" model used by physicists to study mechanisms that give rise to scale invariance (the power law is a scale-invariant distribution). However, this model does not give and does not pretend to give a realistic description of fire dynamics. For example, it gives no role to weather and climate. Pueyo (2007) developed a variant of the "forest fire" model that is also simple but attempts to be more realistic. It also results into a power law, but the parameters of this distribution change through time as a function of weather and climate. Pueyo (2007) observed similar patterns of response to weather in data from boreal forest fires, and used the fitted response functions to forecast fire size distributions in a possible climate change scenario, including the upper extreme of the distribution. For some parameter values, the model in Pueyo (2007) displays a qualitatively different behavior, consisting of simple percolation. In this case, fire is virtually absent, but megafires sweep through the ecosystem a soon as environmental forcings exceed a critical threshold. Evidence gathered by Pueyo et al. (2010) suggests that this is realistic for tropical rainforests (specifically, well-conserved upland rainforests). Some climate models suggest that major tropical rainforest regions are going to become hotter and drier if climate change goes ahead unchecked, which could cause such abrupt shifts. Not all fire regimes are well described by this model. Using data from a tropical savanna region, Pueyo et al. (2010) found that the dynamics in this area do not match its assumptions, even though fire

  13. 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.

  14. A transient stochastic weather generator incorporating climate model uncertainty

    Science.gov (United States)

    Glenis, Vassilis; Pinamonti, Valentina; Hall, Jim W.; Kilsby, Chris G.

    2015-11-01

    Stochastic weather generators (WGs), which provide long synthetic time series of weather variables such as rainfall and potential evapotranspiration (PET), have found widespread use in water resources modelling. When conditioned upon the changes in climatic statistics (change factors, CFs) predicted by climate models, WGs provide a useful tool for climate impacts assessment and adaption planning. The latest climate modelling exercises have involved large numbers of global and regional climate models integrations, designed to explore the implications of uncertainties in the climate model formulation and parameter settings: so called 'perturbed physics ensembles' (PPEs). In this paper we show how these climate model uncertainties can be propagated through to impact studies by testing multiple vectors of CFs, each vector derived from a different sample from a PPE. We combine this with a new methodology to parameterise the projected time-evolution of CFs. We demonstrate how, when conditioned upon these time-dependent CFs, an existing, well validated and widely used WG can be used to generate non-stationary simulations of future climate that are consistent with probabilistic outputs from the Met Office Hadley Centre's Perturbed Physics Ensemble. The WG enables extensive sampling of natural variability and climate model uncertainty, providing the basis for development of robust water resources management strategies in the context of a non-stationary climate.

  15. NASA's climate data system primer, version 1.2

    Science.gov (United States)

    Closs, James W.; Reph, Mary G.; Olsen, Lola M.

    1989-01-01

    This is a beginner's manual for NASA's Climate Data System (NCDS), an interactive scientific information management system that allows one to locate, access, manipulate, and display climate-research data. Additional information on the use of the system is available from the system itself.

  16. Integrated Information Systems Across the Weather-Climate Continuum

    Science.gov (United States)

    Pulwarty, R. S.; Higgins, W.; Nierenberg, C.; Trtanj, J.

    2015-12-01

    The increasing demand for well-organized (integrated) end-to-end research-based information has been highlighted in several National Academy studies, in IPCC Reports (such as the SREX and Fifth Assessment) and by public and private constituents. Such information constitutes a significant component of the "environmental intelligence" needed to address myriad societal needs for early warning and resilience across the weather-climate continuum. The next generation of climate research in service to the nation requires an even more visible, authoritative and robust commitment to scientific integration in support of adaptive information systems that address emergent risks and inform longer-term resilience strategies. A proven mechanism for resourcing such requirements is to demonstrate vision, purpose, support, connection to constituencies, and prototypes of desired capabilities. In this presentation we will discuss efforts at NOAA, and elsewhere, that: Improve information on how changes in extremes in key phenomena such as drought, floods, and heat stress impact management decisions for resource planning and disaster risk reduction Develop regional integrated information systems to address these emergent challenges, that integrate observations, monitoring and prediction, impacts assessments and scenarios, preparedness and adaptation, and coordination and capacity-building. Such systems, as illustrated through efforts such as NIDIS, have strengthened the integration across the foundational research enterprise (through for instance, RISAs, Modeling Analysis Predictions and Projections) by increasing agility for responding to emergent risks. The recently- initiated Climate Services Information System, in support of the WMO Global Framework for Climate Services draws on the above models and will be introduced during the presentation.

  17. Does the public deserve free access to climate system science?

    Science.gov (United States)

    Grigorov, Ivo

    2010-05-01

    Some time ago it was the lack of public access to medical research data that really stirred the issue and gave inertia for legislation and a new publishing model that puts tax payer-funded medical research in the hands of those who fund it. In today's age global climate change has become the biggest socio-economic challenge, and the same argument resonates: climate affects us all and the publicly-funded science quantifying it should be freely accessible to all stakeholders beyond academic research. Over the last few years the ‘Open Access' movement to remove as much as possible subscription, and other on-campus barriers to academic research has rapidly gathered pace, but despite significant progress, the climate system sciences are not among the leaders in providing full access to their publications and data. Beyond the ethical argument, there are proven and tangible benefits for the next generation of climate researchers to adapt the way their output is published. Through the means provided by ‘open access', both data and ideas can gain more visibility, use and citations for the authors, but also result in a more rapid exchange of knowledge and ideas, and ultimately progress towards a sought solution. The presentation will aim to stimulate discussion and seek progress on the following questions: Should free access to climate research (& data) be mandatory? What are the career benefits of using ‘open access' for young scientists? What means and methods should, or could, be incorporated into current European graduate training programmes in climate research, and possible ways forward?

  18. Economic Value of an Advanced Climate Observing System

    Science.gov (United States)

    Wielicki, B. A.; Cooke, R.; Young, D. F.; Mlynczak, M. G.

    2013-12-01

    Scientific missions increasingly need to show the monetary value of knowledge advances in budget-constrained environments. For example, suppose a climate science mission promises to yield decisive information on the rate of human caused global warming within a shortened time frame. How much should society be willing to pay for this knowledge today? The US interagency memo on the social cost of carbon (SCC) creates a standard yardstick for valuing damages from carbon emissions. We illustrate how value of information (VOI) calculations can be used to monetize the relative value of different climate observations. We follow the SCC, setting uncertainty in climate sensitivity to a truncated Roe and Baker (2007) distribution, setting discount rates of 2.5%, 3% and 5%, and using one of the Integrated Assessment Models sanctioned in SCC (DICE, Nordhaus 2008). We consider three mitigation scenarios: Business as Usual (BAU), a moderate mitigation response DICE Optimal, and a strong response scenario (Stern). To illustrate results, suppose that we are on the BAU emissions scenario, and that we would switch to the Stern emissions path if we learn with 90% confidence that the decadal rate of temperature change reaches or exceeds 0.2 C/decade. Under the SCC assumptions, the year in which this happens, if it happens, depends on the uncertain climate sensitivity and on the emissions path. The year in which we become 90% certain that it happens depends, in addition, on our Earth observations, their accuracy, and their completeness. The basic concept is that more accurate observations can shorten the time for societal decisions. The economic value of the resulting averted damages depends on the discount rate, and the years in which the damages occur. A new climate observation would be economically justified if the net present value (NPV) of the difference in averted damages, relative to the existing systems, exceeds the NPV of the system costs. Our results (Cooke et al. 2013

  19. Modeling, Estimation and Control of Indoor Climate in Livestock Buildings

    DEFF Research Database (Denmark)

    Wu, Zhuang

    The main objective of this research is to design an efficient control system for the indoor climate of a large-scale partition-less livestock building, in order to maintain a healthy, comfortable and economically energy consuming indoor environment for the agricultural animals and farmers. In this...... resilience of the control system to disturbances beyond its bandwidth, increases the manipulators utilization efficiency, and reduces energy consumption by solving a constrained convex optimization. Through comparative simulation results analysis, the proposed modeling and control technique is proved to be...... scale livestock buildings, and could be considered as an alternative solution to the current used decentralized PID controller....

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

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

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

  1. Uncertainty in runoff based on Global Climate Model precipitation and temperature data – Part 1: Assessment of Global Climate Models

    Directory of Open Access Journals (Sweden)

    T. A. McMahon

    2014-05-01

    Full Text Available Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between Global Climate Models (GCMs and within a GCM. Uncertainty between GCM projections of future climate can be assessed through analysis of runs of a given scenario from a wide range of GCMs. Within GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The objective of this, the first of two complementary papers, is to reduce between-GCM uncertainty by identifying and removing poorly performing GCMs prior to the analysis presented in the second paper. Here we assess how well 46 runs from 22 Coupled Model Intercomparison Project phase 3 (CMIP3 GCMs are able to reproduce observed precipitation and temperature climatological statistics. The performance of each GCM in reproducing these statistics was ranked and better performing GCMs identified for later analyses. Observed global land surface precipitation and temperature data were drawn from the CRU 3.10 gridded dataset and re-sampled to the resolution of each GCM for comparison. Observed and GCM based estimates of mean and standard deviation of annual precipitation, mean annual temperature, mean monthly precipitation and temperature and Köppen climate type were compared. The main metrics for assessing GCM performance were the Nash–Sutcliffe efficiency index and RMSE between modelled and observed long-term statistics. This information combined with a literature review of the performance of the CMIP3 models identified the following five models as the better performing models for the next phase of our analysis in assessing the uncertainty in runoff estimated from GCM projections of precipitation and temperature: HadCM3 (Hadley Centre for Climate Prediction and Research, MIROCM (Center for Climate System Research (The University of Tokyo, National

  2. Impact of climate change on electricity systems and markets

    Science.gov (United States)

    Chandramowli, Shankar N.

    Climate change poses a serious threat to human welfare. There is now unequivocal scientific evidence that human actions are the primary cause of climate change. The principal climate forcing factor is the increasing accumulation of atmospheric carbon dioxide (CO2) due to combustion of fossil fuels for transportation and electricity generation. Generation of electricity account for nearly one-third of the greenhouse (GHG) emissions globally (on a CO2-equivalent basis). Any kind of economy-wide mitigation or adaptation effort to climate change must have a prominent focus on the electric power sector. I have developed a capacity expansion model for the power sector called LP-CEM (Linear Programming based Capacity Expansion Model). LP-CEM incorporates both the long-term climate change effects and the state/regional-level macroeconomic trends. This modeling framework is demonstrated for the electric power system in the Northeast region of United States. Some of the methodological advances introduced in this research are: the use of high-resolution temperature projections in a power sector capacity expansion model; the incorporation of changes in sectoral composition of electricity demand over time; the incorporation of the effects of climate change and variability on both the demand and supply-side of power sector using parameters estimated in the literature; and an inter-model coupling link with a macroeconomic model to account for price elasticity of demand and other effects on the broader macro-economy. LP-CEM-type models can be of use to state/regional level policymakers to plan for future mitigation and adaptation measures for the electric power sector. From the simulation runs, it is shown that scenarios with climate change effects and with high economic growth rates have resulted in higher capacity addition, optimal supply costs, wholesale/retail prices and total ratepayers' costs. LP-CEM is also adapted to model the implications of the proposed Clean Power Plan

  3. Linking Output from regional Climat Models with Cryosphere Models

    Science.gov (United States)

    Winter, S.

    2003-04-01

    This study has the objective of linking the results of a low-resolution regional climate model (RCM) with high-resolution cryosphere models in order to determine the manner in which Alpine snow, ice and permafrost is likely to respond to enhanced atmospheric warming resulting from an increase in anthropogenic greenhouse gases. There are several constraints that need to be overcome prior to applying solutions to this problem. Firstly, as a result of the long response time of glaciers and alpine permafrost to climate change, long-term simulations of at least 30 years are required. Secondly, the smallest possible spatial resolution of current RCM still remains quite coarse (~ 50 km) because of the complex mathematical equations to be resolved in the RCM, the limited computer performance and the above mentioned long simulation period. On the other hand, cryosphere models used in the present study require gridded input climate variables with a typical mesh width of 50 m. The proposed solution consists in combining climate change data based on RCM scenarios with meteorological data of high elevation Alpine stations measured during a reference period. A RCM control run matching this reference period is required in order to quantify the expected change for each climate parameter. This approach allows breaking down the initial downscaling problem into two separate steps. First, the quantified change derived from RCM-control and scenario simulations is used to predict change for meteorological stations. Second, data sets of predicted change and meteorological measures of these stations are summed and then regionalized for the study area based on advanced algorithms and GIS techniques. Selecting a case study area close to one or more meteorological stations should minimize the associated regionalization error. A pilot study for a small area at Piz Corvatsch in the Eastern Swiss Alps has been designed. The A2 scenario of the IPCC (Intergovernmental Panel on Climate Change

  4. Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

    Science.gov (United States)

    Johnson, Donald R.

    2001-01-01

    This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.

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

    Science.gov (United States)

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

    2015-12-01

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

  6. Amplified Feedback Mechanism of the Forests-Aerosols-Climate System

    Directory of Open Access Journals (Sweden)

    Thomas Hede

    2015-01-01

    Full Text Available Climate change very likely has effects on vegetation so that trees grow faster due to carbon dioxide fertilization (a higher partial pressure increases the rate of reactions with Rubisco during photosynthesis and that trees can be established in new territories in a warmer climate. This has far-reaching significance for the climate system mainly due to a number of feedback mechanisms still under debate. By simulating the vegetation using the Lund-Potsdam-Jena guess dynamic vegetation model, a territory in northern Russia is studied during three different climate protocols assuming a doubling of carbon dioxide levels compared to the year 1975. A back of the envelope calculation is made for the subsequent increased levels of emissions of monoterpenes from spruce and pine forests. The results show that the emissions of monoterpenes at the most northern latitudes were estimated to increase with over 500% for a four-degree centigrade increase protocol. The effect on aerosol and cloud formation is discussed and the cloud optical thickness is estimated to increase more than 2%.

  7. Parallelizing Climate Data Management System, version 3 (CDMS3)

    Science.gov (United States)

    Nadeau, D.; Williams, D. N.; Painter, J.; Doutriaux, C.

    2015-12-01

    The Climate Data Management System is an object-oriented data management system, specialized for organizing multidimensional, gridded data used in climate analyses for data observation and simulation. The basic unit of computation in CDMS3 is the variable, which consist of a multidimensional array that represents climate information in four dimensions corresponding to: time, pressure levels, latitudes, and longitudes. As model become more precise in their computation, the volume of data generated becomes bigger and difficult to handle due to the limit of computational resources. Model today can produce data a time frequency of one hourly, three hourly, or six hourly for spatial footprint close to satellite data used run models. The amount of time for scientists to analyze the data and retrieve useful information is more and more unmanageable. Parallelizing libraries such as CMDS3 would ease the burden of working with such big datasets. Multiple approaches of parallelizing are possible. The most obvious one is embarrassingly parallel or pleasingly parallel programming where each computer node processes one file at a time. A more challenging approach is to send a piece of the data to each node for computation and each node will save the results at its right place in a file as a slab of data. This is possible with Hierarchical Data Format 5 (HDF5) using the Message Passing Interface (MPI). A final approach would be the use of Open Multi-Processing API (OpenMP) where a master thread is split in multiple threads for different sections of the main code. Each method has its advantages and disadvantages. This poster bring to light each benefit of these methods and seek to find an optimal solution to compute climate data analyses in a efficient fashion using one or a mixtures of these parallelized methods.

  8. A simple conceptual model of abrupt glacial climate events

    CERN Document Server

    Braun, H; Christl, M; Chialvo, D R

    2008-01-01

    Here we use a very simple conceptual model in an attempt to reduce essential parts of the complex nonlinearity of abrupt glacial climate changes (the so-called Dansgaard-Oeschger events) to a few simple principles, namely (i) a threshold process, (ii) an overshooting in the stability of the system and (iii) a millennial-scale relaxation. By comparison with a so-called Earth system model of intermediate complexity (CLIMBER-2), in which the events represent oscillations between two climate states corresponding to two fundamentally different modes of deep-water formation in the North Atlantic, we demonstrate that the conceptual model captures fundamental aspects of the nonlinearity of the events in that model. We use the conceptual model in order to reproduce and reanalyse nonlinear resonance mechanisms that were already suggested in order to explain the characteristic time scale of Dansgaard-Oeschger events. In doing so we identify a new form of stochastic resonance (i.e. an overshooting stochastic resonance) a...

  9. Effects of orbital forcing on atmosphere and ocean heat transports in Holocene and Eemian climate simulations with a comprehensive Earth system model

    Directory of Open Access Journals (Sweden)

    N. Fischer

    2010-03-01

    Full Text Available Orbital forcing does not only exert direct insolation effects, but also alters climate indirectly through feedback mechanisms that modify atmosphere and ocean dynamics and meridional heat and moisture transfers. We investigate the regional effects of these changes by detailed analysis of atmosphere and ocean circulation and heat transports in a coupled atmosphere-ocean-sea ice-biosphere general circulation model (ECHAM5/JSBACH/MPI-OM. We perform long term quasi equilibrium simulations under pre-industrial, mid-Holocene (6000 years before present – yBP, and Eemian (125 000 yBP orbital boundary conditions. Compared to pre-industrial climate, Eemian and Holocene temperatures show generally warmer conditions at higher and cooler conditions at lower latitudes. Changes in sea-ice cover, ocean heat transports, and atmospheric circulation patterns lead to pronounced regional heterogeneity. Over Europe, the warming is most pronounced over the north-eastern part in accordance with recent reconstructions for the Holocene. We attribute this warming to enhanced ocean circulation in the Nordic Seas and enhanced ocean-atmosphere heat flux over the Barents Shelf in conduction with retreat of sea ice and intensified winter storm tracks over northern Europe.

  10. Leadership, Organizational Climate, and Working Alliance in a Children's Mental Health Service System

    OpenAIRE

    Green, Amy E; Albanese, Brian J.; Cafri, Guy; Aarons, Gregory A

    2013-01-01

    The goal of this study was to examine the relationships of transformational leadership and organizational climate with working alliance, in a children's mental health service system. Using multilevel structural equation modeling, the effect of leadership on working alliance was mediated by organizational climate. These results suggest that supervisors may be able to impact quality of care through improving workplace climate. Organizational factors should be considered in efforts to improve pu...

  11. From quantifying historical LULCC impacts to optimizing land management for climate mitigation: Insights from climate modelling

    Science.gov (United States)

    Davin, E.; Lejeune, Q.; Seneviratne, S. I.

    2015-12-01

    Human activities have profoundly transformed the land surface through land use/land cover change (LULCC). The consequence of this transformation is twofold: First, the conversion from natural to anthropogenic systems exert a direct forcing on climate (through both biogeochemical and biogeophysical processes); Second the transformed ecosystems may modify land-atmosphere feedback mechanisms thus modulating the response to climate change or to specific weather events. The first point will be illustrated by reviewing recent modelling results, including LUCID and CMIP5 model intercomparisons, to shed some light on the relative importance of LULCC versus other climate forcings. Given the importance of LULCC impacts at the regional scale, some recent efforts to improve the representation of land processes in regional climate models [1] as well as a regional assessment of the impact of amazonian deforestation [2] will be presented. The second point will be discussed through two examples. First, the fact that LULCC may modulate certain modes of variability will be illustrated based on model experiments highlighting the regional interplay between ENSO variability and amazonian deforestation. Second, we will show that peak temperatures during heat waves can be strongly influenced locally by the type of land cover or land management practices. In particular no-till farming, by increasing surface albedo, can lead to a substantial attenuation of hot temperatures during heat waves, in part due to a more efficient radiative cooling effect during cloud-free conditions [3]. References:[1] Davin, E.L. and S.I. Seneviratne (2012), Role of land surface processes and diffuse/direct radiation partitioning in simulating the European climate, Biogeosciences, 9, 1695-1707, doi:10.5194/bg-9-1695-2012.[2] Lejeune, Q., E.L. Davin, B. Guillod and S.I. Seneviratne (2015), Influence of Amazonian deforestation on the future evolution of regional surface fluxes, circulation, surface temperature and

  12. 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.

  13. Parameter-elevation Regressions on Independent Slopes Model Monthly Climate Data for the Continental United States.

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This dataset was created using the PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate mapping system, developed by Dr. Christopher Daly,...

  14. A new coupled ice sheet/climate model: description and sensitivity to model physics under Eemian, Last Glacial Maximum, late Holocene and modern climate conditions

    Directory of Open Access Journals (Sweden)

    J. G. Fyke

    2011-03-01

    Full Text Available The need to better understand long-term climate/ice sheet feedback loops is motivating efforts to couple ice sheet models into Earth System models which are capable of long-timescale simulations. In this paper we describe a coupled model that consists of the University of Victoria Earth System Climate Model (UVic ESCM and the Pennsylvania State University Ice model (PSUI. The climate model generates a surface mass balance (SMB field via a sub-gridded surface energy/moisture balance model that resolves narrow ice sheet ablation zones. The ice model returns revised elevation, surface albedo and ice area fields, plus coastal fluxes of heat and moisture. An arbitrary number of ice sheets can be simulated, each on their own high-resolution grid and each capable of synchronous or asynchronous coupling with the overlying climate model. The model is designed to conserve global heat and moisture. In the process of improving model performance we developed a procedure to account for modelled surface air temperature (SAT biases within the energy/moisture balance surface model and improved the UVic ESCM snow surface scheme through addition of variable albedos and refreezing over the ice sheet.

    A number of simulations for late Holocene, Last Glacial Maximum (LGM, and Eemian climate boundary conditions were carried out to explore the sensitivity of the coupled model and identify model configurations that best represented these climate states. The modelled SAT bias was found to play a significant role in long-term ice sheet evolution, as was the effect of refreezing meltwater and surface albedo. The bias-corrected model was able to reasonably capture important aspects of the Antarctic and Greenland ice sheets, including modern SMB and ice distribution. The simulated northern Greenland ice sheet was found to be prone to ice margin retreat at radiative forcings corresponding closely to those of the Eemian or the present-day.

  15. A new coupled ice sheet-climate model: description and sensitivity to model physics under Eemian, Last Glacial Maximum, late Holocene and modern climate conditions

    Directory of Open Access Journals (Sweden)

    J. G. Fyke

    2010-08-01

    Full Text Available The need to better understand long-term climate/ice sheet feedback loops is motivating efforts to couple ice sheet models into Earth System models which are capable of long-timescale simulations. In this paper we describe a coupled model, that consists of the University of Victoria Earth System Climate Model (UVic ESCM and the Pennsylvania State University Ice model (PSUI. The climate model generates a surface mass balance (SMB field via a sub-gridded surface energy/moisture balance model that resolves narrow ice sheet ablation zones. The ice model returns revised elevation, surface albedo and ice area fields, plus coastal fluxes of heat and moisture. An arbitrary number of ice sheets can be simulated, each on their own high-resolution grid and each capable of synchronous or asynchronous coupling with the overlying climate model. The model is designed to conserve global heat and moisture. In the process of improving model performance we developed a procedure to account for modelled surface air temperature (SAT biases within the energy/moisture balance surface model and improved the UVic ESCM snow surface scheme through addition of variable albedos and refreezing over the ice sheet.

    A number of simulations for late Holocene, Last Glacial Maximum (LGM, and Eemian climate boundary conditions were carried out to explore the sensitivity of the coupled model and identify model configurations that best represented these climate states. The modelled SAT bias was found to play a significant role in long-term ice sheet evolution, as was the effect of refreezing meltwater and surface albedo. The bias-corrected model was able to reasonably capture important aspects of the Antarctic and Greenland ice sheets, including modern SMB and ice distribution. The simulated northern Greenland ice sheet was found to be prone to ice margin retreat at radiative forcings corresponding closely to those of the Eemian or the present-day.

  16. A new coupled ice sheet-climate model: description and sensitivity to model physics under Eemian, Last Glacial Maximum, late Holocene and modern climate conditions

    Science.gov (United States)

    Fyke, J. G.; Weaver, A. J.; Pollard, D.; Eby, M.; Carter, L.; Mackintosh, A.

    2010-08-01

    The need to better understand long-term climate/ice sheet feedback loops is motivating efforts to couple ice sheet models into Earth System models which are capable of long-timescale simulations. In this paper we describe a coupled model, that consists of the University of Victoria Earth System Climate Model (UVic ESCM) and the Pennsylvania State University Ice model (PSUI). The climate model generates a surface mass balance (SMB) field via a sub-gridded surface energy/moisture balance model that resolves narrow ice sheet ablation zones. The ice model returns revised elevation, surface albedo and ice area fields, plus coastal fluxes of heat and moisture. An arbitrary number of ice sheets can be simulated, each on their own high-resolution grid and each capable of synchronous or asynchronous coupling with the overlying climate model. The model is designed to conserve global heat and moisture. In the process of improving model performance we developed a procedure to account for modelled surface air temperature (SAT) biases within the energy/moisture balance surface model and improved the UVic ESCM snow surface scheme through addition of variable albedos and refreezing over the ice sheet. A number of simulations for late Holocene, Last Glacial Maximum (LGM), and Eemian climate boundary conditions were carried out to explore the sensitivity of the coupled model and identify model configurations that best represented these climate states. The modelled SAT bias was found to play a significant role in long-term ice sheet evolution, as was the effect of refreezing meltwater and surface albedo. The bias-corrected model was able to reasonably capture important aspects of the Antarctic and Greenland ice sheets, including modern SMB and ice distribution. The simulated northern Greenland ice sheet was found to be prone to ice margin retreat at radiative forcings corresponding closely to those of the Eemian or the present-day.

  17. A new coupled ice sheet/climate model: description and sensitivity to model physics under Eemian, Last Glacial Maximum, late Holocene and modern climate conditions

    Science.gov (United States)

    Fyke, J. G.; Weaver, A. J.; Pollard, D.; Eby, M.; Carter, L.; Mackintosh, A.

    2011-03-01

    The need to better understand long-term climate/ice sheet feedback loops is motivating efforts to couple ice sheet models into Earth System models which are capable of long-timescale simulations. In this paper we describe a coupled model that consists of the University of Victoria Earth System Climate Model (UVic ESCM) and the Pennsylvania State University Ice model (PSUI). The climate model generates a surface mass balance (SMB) field via a sub-gridded surface energy/moisture balance model that resolves narrow ice sheet ablation zones. The ice model returns revised elevation, surface albedo and ice area fields, plus coastal fluxes of heat and moisture. An arbitrary number of ice sheets can be simulated, each on their own high-resolution grid and each capable of synchronous or asynchronous coupling with the overlying climate model. The model is designed to conserve global heat and moisture. In the process of improving model performance we developed a procedure to account for modelled surface air temperature (SAT) biases within the energy/moisture balance surface model and improved the UVic ESCM snow surface scheme through addition of variable albedos and refreezing over the ice sheet. A number of simulations for late Holocene, Last Glacial Maximum (LGM), and Eemian climate boundary conditions were carried out to explore the sensitivity of the coupled model and identify model configurations that best represented these climate states. The modelled SAT bias was found to play a significant role in long-term ice sheet evolution, as was the effect of refreezing meltwater and surface albedo. The bias-corrected model was able to reasonably capture important aspects of the Antarctic and Greenland ice sheets, including modern SMB and ice distribution. The simulated northern Greenland ice sheet was found to be prone to ice margin retreat at radiative forcings corresponding closely to those of the Eemian or the present-day.

  18. Modelling mid-Pliocene climate with COSMOS

    OpenAIRE

    Stepanek, C.; G. Lohmann

    2012-01-01

    In this manuscript we describe the experimental procedure employed at the Alfred Wegener Institute in Germany in the preparation of the simulations for the Pliocene Model Intercomparison Project (PlioMIP). We present a description of the utilized Community Earth System Models (COSMOS, version: COSMOS-landveg r2413, 2009) and document the procedures that we applied to transfer the Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project mid-Pliocene reconstruction into model