WorldWideScience

Sample records for climate system models

  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. Parameter sensitivity of climate models and climate driven ecological systems

    NARCIS (Netherlands)

    Moolenaar, H.E.

    2006-01-01

    Uncertainty in the outcome of numerical models of physical and biological processes, such as the climate and ecological systems, is widely recognized. One contributing factor is uncertainty in model parameters. Because of this uncertainty, a range of model outcomes is usually given. This might obstr

  5. 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.

  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. Model based design of optimal multivariable climate control systems.

    NARCIS (Netherlands)

    Henten, van E.J.

    1989-01-01

    The simulation results are presented of the application of the linear quadratic performance (LQP) control design methodology to a non-linear physical greenhouse climate system. A multivariable greenhouse climate model designed by Bot (1983) is used for controller design and evaluation. First, the no

  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. An overview of BCC climate system model development and application for climate change studies

    Science.gov (United States)

    Wu, Tongwen; Song, Lianchun; Li, Weiping; Wang, Zaizhi; Zhang, Hua; Xin, Xiaoge; Zhang, Yanwu; Zhang, Li; Li, Jianglong; Wu, Fanghua; Liu, Yiming; Zhang, Fang; Shi, Xueli; Chu, Min; Zhang, Jie; Fang, Yongjie; Wang, Fang; Lu, Yixiong; Liu, Xiangwen; Wei, Min; Liu, Qianxia; Zhou, Wenyan; Dong, Min; Zhao, Qigeng; Ji, Jinjun; Li, Laurent; Zhou, Mingyu

    2014-02-01

    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 coupled 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 five (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 projections. 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 projections 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 indicate that the higher resolution in BCC_CSM1.1(m) improves the simulation of mean climate relative to BCC_CSM1.1, particularly on regional scales.

  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. Modeling lakes and reservoirs in the climate system

    NARCIS (Netherlands)

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

    2009-01-01

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

  15. Climate Ocean Modeling on a Beowulf Class System

    Science.gov (United States)

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

    2000-01-01

    With the growing power and shrinking cost of personal computers. the availability of fast ethernet interconnections, and public domain software packages, it is now possible to combine them to build desktop parallel computers (named Beowulf or PC clusters) at a fraction of what it would cost to buy systems of comparable power front supercomputer companies. This led as to build and assemble our own sys tem. specifically for climate ocean modeling. In this article, we present our experience with such a system, discuss its network performance, and provide some performance comparison data with both HP SPP2000 and Cray T3E for an ocean Model used in present-day oceanographic research.

  16. 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

  17. Investigations of the Climate System Response to Climate Engineering in a Hierarchy of Models

    Science.gov (United States)

    McCusker, Kelly E.

    Global warming due to anthropogenic emissions of greenhouse gases is causing negative impacts on diverse ecological and human systems around the globe, and these impacts are projected to worsen as climate continues to warm. In the absence of meaningful greenhouse gas emissions reductions, new strategies have been proposed to engineer the climate, with the aim of preventing further warming and avoiding associated climate impacts. We investigate one such strategy here, falling under the umbrella of `solar radiation management', in which sulfate aerosols are injected into the stratosphere. We use a global climate model with a coupled mixed-layer depth ocean and with a fully-coupled ocean general circulation model to simulate the stabilization of climate by balancing increasing carbon dioxide with increasing stratospheric sulfate concentrations. We evaluate whether or not severe climate impacts, such as melting Arctic sea ice, tropical crop failure, or destabilization of the West Antarctic ice sheet, could be avoided. We find that while tropical climate emergencies might be avoided by use of stratospheric aerosol injections, avoiding polar emergencies cannot be guaranteed due to large residual climate changes in those regions, which are in part due to residual atmospheric circulation anomalies. We also find that the inclusion of a fully-coupled ocean is important for determining the regional climate response because of its dynamical feedbacks. The efficacy of stratospheric sulfate aerosol injections, and solar radiation management more generally, depends on its ability to be maintained indefinitely, without interruption from a variety of possible sources, such as technological failure, a breakdown in global cooperation, lack of funding, or negative unintended consequences. We next consider the scenario in which stratospheric sulfate injections are abruptly terminated after a multi- decadal period of implementation while greenhouse gas emissions have continued unabated

  18. 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.

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    C. E. Brennan

    2011-09-01

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

  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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-04-01

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

  4. 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.

  5. 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.

  6. 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

  7. A new marine ecosystem model for the University of Victoria Earth System Climate Model

    Directory of Open Access Journals (Sweden)

    D. P. Keller

    2012-09-01

    Full Text Available Earth System Climate Models (ESCMs are valuable tools that can be used to gain a better understanding of the climate system, global biogeochemical cycles and how anthropogenically-driven changes may affect them. Here we describe improvements made to the marine biogeochemical ecosystem component of the University of Victoria's ESCM (version 2.9. Major changes include corrections to the code and equations describing phytoplankton light limitation and zooplankton grazing, the implementation of a more realistic zooplankton growth and grazing model, and the implementation of an iron limitation scheme to constrain phytoplankton growth. The new model is evaluated after a 10 000-yr spin-up and compared to both the previous version and observations. For the majority of biogeochemical tracers and ecosystem processes the new model shows significant improvements when compared to the previous version and evaluated against observations. Many of the improvements are due to better simulation of seasonal changes in higher latitude ecosystems and the effect that this has on ocean biogeochemistry. This improved model is intended to provide a basic new ESCM model component, which can be used as is or expanded upon (i.e., the addition of new tracers, for climate change and biogeochemical cycling research.

  8. 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.

    2016-10-01

    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.

  9. 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

  10. 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.

  11. 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.

  12. Global Modeling and Projection of Short-Lived Climate Pollutants in an Earth System Model

    Science.gov (United States)

    Sudo, K.; Takemura, T.; Klimont, Z.; Kurokawa, J.; Akimoto, H.

    2013-12-01

    In predicting and mitigating future global warming, short-lived climate pollutants (SLCPs) such as tropospheric ozone (O3), black carbon (BC), and other related components including CH4/VOCs and aerosols play crucial roles as well as long-lived species like CO2 or N2O. Several recent studies suggests that reduction of heating SLCPs (i.e., O3 and black carbon) together with CH4 can decrease and delay the expected future warming, and can be an alternative to CO2 mitigation (Shindell et al., 2012). However it should be noted that there are still large uncertainties in simulating SLCPs and their climate impacts. For instance, present global models generally have a severe tendency to underestimate BC especially in remote areas like the polar regions as shown by the recent model intercomparison project under the IPCC (ACCMIP/AeroCOM). This problem in global BC modeling, basically coming from aging and removal processes of BC, causes still a large uncertainty in the estimate of BC's atmospheric heating and climate impacts (Bond et al., 2013; Kerr et al., 2013). This study attempted to improve global simulation of BC by developing a new scheme for simulating aging process of BC and re-evaluate radiative forcing of BC in the framework of a chemistry-aerosol coupled climate model (Earth system model) MIROC-ESM-CHEM. Our improved model with the new aging scheme appears to relatively well reproduce the observed BC concentrations and seasonality in the Arctic/Antarctic region. The new model estimates radiative forcing of BC to be 0.83 W m-2 which is about two times larger than the estimate by our original model with no aging scheme (0.41 W m-2), or the model ensemble mean in the IPCC report. Using this model, future projection of SLCPs and their climate impacts is conducted following the recent IIASA emission scenarios for the year 2030 (Klimont et al., 2006; Cofala et al., 2007). Our simulation suggests that heating SLCPs components (O3, BC, and CH4) are significantly reduced

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

    Science.gov (United States)

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

    2009-03-13

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

  14. 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...

  15. 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...

  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. A Power Efficient Exaflop Computer Design for Global Cloud System Resolving Climate Models.

    Science.gov (United States)

    Wehner, M. F.; Oliker, L.; Shalf, J.

    2008-12-01

    Exascale computers would allow routine ensemble modeling of the global climate system at the cloud system resolving scale. Power and cost requirements of traditional architecture systems are likely to delay such capability for many years. We present an alternative route to the exascale using embedded processor technology to design a system optimized for ultra high resolution climate modeling. These power efficient processors, used in consumer electronic devices such as mobile phones, portable music players, cameras, etc., can be tailored to the specific needs of scientific computing. We project that a system capable of integrating a kilometer scale climate model a thousand times faster than real time could be designed and built in a five year time scale for US$75M with a power consumption of 3MW. This is cheaper, more power efficient and sooner than any other existing technology.

  19. 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.

  20. Anticipating Vulnerability to Climate Change in Dryland Pastoral Systems: Using Dynamic Systems Models for the Kalahari

    Directory of Open Access Journals (Sweden)

    Evan D.G. Fraser

    2010-06-01

    Full Text Available It is vitally important to identify agroecosystems that may cease functioning because of changing climate or land degradation. However, identifying such systems is confounded on both conceptual and methodological grounds, especially in systems that are moving toward thresholds, a common trait of dryland environments. This study explores these challenges by analyzing how a range of external pressures affect the vulnerability of dryland pastoral systems in the Kalahari. This is achieved by employing dynamic systems modeling approaches to understand the pathways by which communities became vulnerable to drought. Specifically, we evaluate how external pressures have changed: (1 different agroecosystems' abilities to tolerate drought, i.e., ecosystem resilience; (2 rural communities' abilities to adapt to drought, mediated via their access to assets; and (3 the ability of institutions and policy interventions to play a role in mediating drought-related crises, i.e., socio-political governance. This is done by reanalyzing ecological and participatory research findings along with farm-scale livestock offtake data from across the Kalahari in Botswana. An iterative process was followed to establish narratives exploring how external drivers led to changes in agroecosystem resilience, access to assets, and the institutional capacity to buffer the system. We use "causal loop diagrams" and statistical dynamic system models to express key quantitative relationships and establish future scenarios to help define where uncertainties lie by showing where the system is most sensitive to change. We highlight how that greater sharing of land management knowledge and practices between private and communal land managers can provide 'win-win-win' benefits of reducing system vulnerability, increasing economic income, and building social capital. We use future scenario analyses to identify key areas for future studies of climate change adaptation across the Kalahari.

  1. Abrupt change in climate and climate models

    Directory of Open Access Journals (Sweden)

    A. J. Pitman

    2006-01-01

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

  2. Abrupt change in climate and climate models

    Directory of Open Access Journals (Sweden)

    A. J. Pitman

    2006-07-01

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

  3. 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

  4. 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.;

    and marginal costs of the power producers. Two effects of climate change on the power system were studied: changes in the hydropower production caused by changes in precipitation and temperature, and changes in the electricity demand over the year caused by temperature changes. A rainfall-runoff model......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...

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. Regional modelling of nitrate leaching from Swiss organic and conventional cropping systems under climate change

    Science.gov (United States)

    Calitri, Francesca; Necpalova, Magdalena; Lee, Juhwan; Zaccone, Claudio; Spiess, Ernst; Herrera, Juan; Six, Johan

    2016-04-01

    Organic cropping systems have been promoted as a sustainable alternative to minimize the environmental impacts of conventional practices. Relatively little is known about the potential to reduce NO3-N leaching through the large-scale adoption of organic practices. Moreover, the potential to mitigate NO3-N leaching and thus the N pollution under future climate change through organic farming remain unknown and highly uncertain. Here, we compared regional NO3-N leaching from organic and conventional cropping systems in Switzerland using a terrestrial biogeochemical process-based model DayCent. The objectives of this study are 1) to calibrate and evaluate the model for NO3-N leaching measured under various management practices from three experiments at two sites in Switzerland; 2) to estimate regional NO3-N leaching patterns and their spatial uncertainty in conventional and organic cropping systems (with and without cover crops) for future climate change scenario A1B; 3) to explore the sensitivity of NO3-N leaching to changes in soil and climate variables; and 4) to assess the nitrogen use efficiency for conventional and organic cropping systems with and without cover crops under climate change. The data for model calibration/evaluation were derived from field experiments conducted in Liebefeld (canton Bern) and Eschikon (canton Zürich). These experiments evaluated effects of various cover crops and N fertilizer inputs on NO3-N leaching. The preliminary results suggest that the model was able to explain 50 to 83% of the inter-annual variability in the measured soil drainage (RMSE from 12.32 to 16.89 cm y-1). The annual NO3-N leaching was also simulated satisfactory (RMSE = 3.94 to 6.38 g N m-2 y-1), although the model had difficulty to reproduce the inter-annual variability in the NO3-N leaching losses correctly (R2 = 0.11 to 0.35). Future climate datasets (2010-2099) from the 10 regional climate models (RCM) were used in the simulations. Regional NO3-N leaching

  11. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-11-13

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

  13. 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.

  14. 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.)

  15. 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...

  16. 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

    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 relationships between climate change, management and policy choices, food production, and the maintenance...... and disease is a priority. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management...

  17. 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.

  18. 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

    , 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......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...... 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 changes...

  19. 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)

  20. 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

  1. 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...

  2. 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

  3. 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

  4. Modeling and Analysis Compute Environments, Utilizing Virtualization Technology in the Climate and Earth Systems Science domain

    Science.gov (United States)

    Michaelis, A.; Nemani, R. R.; Wang, W.; Votava, P.; Hashimoto, H.

    2010-12-01

    Given the increasing complexity of climate modeling and analysis tools, it is often difficult and expensive to build or recreate an exact replica of the software compute environment used in past experiments. With the recent development of new technologies for hardware virtualization, an opportunity exists to create full modeling, analysis and compute environments that are “archiveable”, transferable and may be easily shared amongst a scientific community or presented to a bureaucratic body if the need arises. By encapsulating and entire modeling and analysis environment in a virtual machine image, others may quickly gain access to the fully built system used in past experiments, potentially easing the task and reducing the costs of reproducing and verify past results produced by other researchers. Moreover, these virtual machine images may be used as a pedagogical tool for others that are interested in performing an academic exercise but don't yet possess the broad expertise required. We built two virtual machine images, one with the Community Earth System Model (CESM) and one with Weather Research Forecast Model (WRF), then ran several small experiments to assess the feasibility, performance overheads costs, reusability, and transferability. We present a list of the pros and cons as well as lessoned learned from utilizing virtualization technology in the climate and earth systems modeling domain.

  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. 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

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

  7. Evaluation of the Regional Arctic System Model (RASM) - Process-resolving Arctic Climate Simulation

    Science.gov (United States)

    Maslowski, Wieslaw

    2016-04-01

    The Regional Arctic System Model (RASM) has been developed to better understand the past and present operation of Arctic System at process scale and to predict its change at time scales from days to decades, in support of the US environmental assessment and prediction needs. RASM is a limited-area, fully coupled ice-ocean-atmosphere-land model that uses the Community Earth System Model (CESM) framework. It includes the Weather Research and Forecasting (WRF) model, the LANL Parallel Ocean Program (POP) and Community Ice Model (CICE) and the Variable Infiltration Capacity (VIC) land hydrology model. The ocean and sea ice models used in RASM are regionally configured versions of those used in CESM, while WRF replaces the Community Atmospheric Model (CAM). In addition, a streamflow routing (RVIC) model was recently implemented in RASM to transport the freshwater flux from the land surface to the Arctic Ocean. The model domain is configured at an eddy-permitting resolution of 1/12° (or ~9km) for the ice-ocean and 50 km for the atmosphere-land model components. It covers the entire Northern Hemisphere marine cryosphere, terrestrial drainage to the Arctic Ocean and its major inflow and outflow pathways, with optimal extension into the North Pacific / Atlantic to model the passage of cyclones into the Arctic. In addition, a 1/48° (or ~2.4km) grid for the ice-ocean model components has been recently configured. All RASM components are coupled at high frequency (currently at 20-minute intervals) to allow realistic representation of inertial interactions among the model components. In addition to an overview of RASM technical details, model results are presented from both fully coupled and subsets of RASM, where the atmospheric and land components are replaced with prescribed realistic atmospheric reanalysis data to evaluate model skill in representing seasonal climatology as well as interannual and multidecadal climate variability. Selected physical processes and resulting

  8. 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 ...

  9. Land Management for Climate Change Mitigation and Geoengineering - Are Earth System Models up to the Challenge?

    Science.gov (United States)

    Bonan, G. B.

    2015-12-01

    Many of the terrestrial models included in Earth system models simulate changes to the land surface from human activities. In the Community Land Model (CLM), for example, irrigation, nitrogen fertilization, soil tillage, wood harvesting, and numerous crop types are represented in addition to anthropogenic land-cover change (e.g., deforestation, reforestation, and afforestation). These land uses are included in the models because they have a strong influence on the hydrological cycle (irrigation), crop yield and greenhouse gas emissions (nitrogen fertilization, crop type), and carbon storage (wood harvesting, tillage). However, the representation of these processes in Earth system models is uncertain, as is the specification of transient changes from 1850 through the historical era and into the future. A more fundamental aspect of land surface models is the coupling of land and atmosphere through exchanges of energy, mass, and momentum. Here, too, anthropogenic activities can affect climate through land-cover change and land management. Eddy covariance flux tower analyses suggest that the land management effects are as significant as the land-cover change effects. These analyses pose a challenge to land surface models - How well do the models simulate the effects of land management (e.g., changes in leaf area index or community composition) on surface flux exchange with the atmosphere? Here I use the CLM and a new, advanced multilayer canopy flux model to illustrate challenges in model surface fluxes and the influence of land management on surface fluxes.

  10. 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

  11. 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

  12. 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 Univ., New Haven, CT (United States)

    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.

  13. PyMCT: A Very High Level Language Coupling Tool For Climate System Models

    Science.gov (United States)

    Tobis, M.; Pierrehumbert, R. T.; Steder, M.; Jacob, R. L.

    2006-12-01

    At the Climate Systems Center of the University of Chicago, we have been examining strategies for applying agile programming techniques to complex high-performance modeling experiments. While the "agile" development methodology differs from a conventional requirements process and its associated milestones, the process remain a formal one. It is distinguished by continuous improvement in functionality, large numbers of small releases, extensive and ongoing testing strategies, and a strong reliance on very high level languages (VHLL). Here we report on PyMCT, which we intend as a core element in a model ensemble control superstructure. PyMCT is a set of Python bindings for MCT, the Fortran-90 based Model Coupling Toolkit, which forms the infrastructure for the inter-component communication in the Community Climate System Model (CCSM). MCT provides a scalable model communication infrastructure. In order to take maximum advantage of agile software development methodologies, we exposed MCT functionality to Python, a prominent VHLL. We describe how the scalable architecture of MCT allows us to overcome the relatively weak runtime performance of Python, so that the performance of the combined system is not severely impacted. To demonstrate these advantages, we reimplemented the CCSM coupler in Python. While this alone offers no new functionality, it does provide a rigorous test of PyMCT functionality and performance. We reimplemented the CPL6 library, presenting an interesting case study of the comparison between conventional Fortran-90 programming and the higher abstraction level provided by a VHLL. The powerful abstractions provided by Python will allow much more complex experimental paradigms. In particular, we hope to build on the scriptability of our coupling strategy to enable systematic sensitivity tests. Our most ambitious objective is to combine our efforts with Bayesian inverse modeling techniques toward objective tuning at the highest level, across model

  14. 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.

  15. 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)

  16. Design and implementation of the infrastructure of HadGEM3: the next-generation Met Office climate modelling system

    Directory of Open Access Journals (Sweden)

    H. T. Hewitt

    2010-10-01

    Full Text Available This paper describes the development of a technically robust climate modelling system, HadGEM3, which couples the Met Office Unified Model atmosphere component, the NEMO ocean model and the Los Alamos sea ice model (CICE using the OASIS coupler. Details of the coupling and technical solutions are documented in the paper in addition to a description of the configurations of the individual submodels. The paper demonstrates that the implementation of the model has resulted in accurate conservation of heat and freshwater across the model components. The model performance in early versions of this climate model is briefly described to demonstrate that the results are scientifically credible. HadGEM3 is the basis for a number of modelling efforts outside of the Met Office, both within the UK and internationally. This documentation of the HadGEM3 system provides a detailed reference for developers of HadGEM3-based climate configurations.

  17. A stochastic rainfall model for the assessment of regional water resource systems under changed climatic condition

    Directory of Open Access Journals (Sweden)

    H. J. Fowler

    2000-01-01

    Full Text Available A stochastic model is developed for the synthesis of daily precipitation using conditioning by weather types. Daily precipitation statistics at multiple sites within the region of Yorkshire, UK, are linked to objective Lamb weather types (LWTs and used to split the region into three distinct precipitation sub-regions. Using a variance minimisation criterion, the 27 LWTs are clustered into three physically realistic groups or ‘states'. A semi-Markov chain model is used to synthesise long sequences of weather states, maintaining the observed persistence and transition probabilities. The Neyman-Scott Rectangular Pulses (NSRP model is then fitted for each weather state, using a defined summer and winter period. The combined model reproduces key aspects of the historic precipitation regime at temporal resolutions down to the hourly level. Long synthetic precipitation series are useful in the sensitivity analysis of water resource systems under current and changed climatic conditions. This methodology enables investigation of the impact of variations in weather type persistence or frequency. In addition, rainfall model statistics can be altered to simulate instances of increased intensity or proportion of dry days for example, for individual weather groups. The input of such data into a water resource model, simulating potential atmospheric circulation changes, will provide a valuable tool for future planning of water resource systems. The ability of the model to operate at an hourly level also allows its use in a wider range of hydrological impact studies, e.g. variations in river flows, flood risk estimation etc. Keywords: water resources; climate change; impacts; stochastic rainfall model; Lamb weather types

  18. GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics

    Science.gov (United States)

    Dunne, John P.; John, Jasmin G.; Adcroft, Alistair J.; Griffies, Stephen M.; Hallberg, Robert W.; Shevalikova, Elena; Stouffer, Ronald J.; Cooke, William; Dunne, Krista A.; Harrison, Matthew J.; Krasting, John P.; Malyshev, Sergey L.; Milly, P.C.D.; Phillipps, Peter J.; Sentman, Lori A.; Samuels, Bonita L.; Spelman, Michael J.; Winton, Michael; Wittenberg, Andrew T.; Zadeh, Niki

    2012-01-01

    We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

  19. Direct and semi-direct aerosol radiative effect on the Mediterranean climate variability using a coupled regional climate system model

    Science.gov (United States)

    Nabat, Pierre; Somot, Samuel; Mallet, Marc; Sevault, Florence; Chiacchio, Marc; Wild, Martin

    2015-02-01

    A fully coupled regional climate system model (CNRM-RCSM4) has been used over the Mediterranean region to investigate the direct and semi-direct effects of aerosols, but also their role in the radiation-atmosphere-ocean interactions through multi-annual ensemble simulations (2003-2009) with and without aerosols and ocean-atmosphere coupling. Aerosols have been taken into account in CNRM-RCSM4 through realistic interannual monthly AOD climatologies. An evaluation of the model has been achieved, against various observations for meteorological parameters, and has shown the ability of CNRM-RCSM4 to reproduce the main patterns of the Mediterranean climate despite some biases in sea surface temperature (SST), radiation and cloud cover. The results concerning the aerosol radiative effects show a negative surface forcing on average because of the absorption and scattering of the incident radiation. The SW surface direct effect is on average -20.9 Wm-2 over the Mediterranean Sea, -14.7 Wm-2 over Europe and -19.7 Wm-2 over northern Africa. The LW surface direct effect is weaker as only dust aerosols contribute (+4.8 Wm-2 over northern Africa). This direct effect is partly counterbalanced by a positive semi-direct radiative effect over the Mediterranean Sea (+5.7 Wm-2 on average) and Europe (+5.0 Wm-2) due to changes in cloud cover and atmospheric circulation. The total aerosol effect is consequently negative at the surface and responsible for a decrease in land (on average -0.4 °C over Europe, and -0.5 °C over northern Africa) and sea surface temperature (on average -0.5 °C for the Mediterranean SST). In addition, the latent heat loss is shown to be weaker (-11.0 Wm-2) in the presence of aerosols, resulting in a decrease in specific humidity in the lower troposphere, and a reduction in cloud cover and precipitation. Simulations also indicate that dust aerosols warm the troposphere by absorbing solar radiation, and prevent radiation from reaching the surface, thus

  20. Revisiting the climate impacts of cool roofs around the globe using an Earth system model

    Science.gov (United States)

    Zhang, Jiachen; Zhang, Kai; Liu, Junfeng; Ban-Weiss, George

    2016-08-01

    Solar reflective ‘cool roofs’ absorb less sunlight than traditional dark roofs, reducing solar heat gain, and decreasing the amount of heat transferred to the atmosphere. Widespread adoption of cool roofs could therefore reduce temperatures in urban areas, partially mitigating the urban heat island effect, and contributing to reversing the local impacts of global climate change. The impacts of cool roofs on global climate remain debated by past research and are uncertain. Using a sophisticated Earth system model, the impacts of cool roofs on climate are investigated at urban, continental, and global scales. We find that global adoption of cool roofs in urban areas reduces urban heat islands everywhere, with an annual- and global-mean decrease from 1.6 to 1.2 K. Decreases are statistically significant, except for some areas in Africa and Mexico where urban fraction is low, and some high-latitude areas during wintertime. Analysis of the surface and TOA energy budget in urban regions at continental-scale shows cool roofs causing increases in solar radiation leaving the Earth-atmosphere system in most regions around the globe, though the presence of aerosols and clouds are found to partially offset increases in upward radiation. Aerosols dampen cool roof-induced increases in upward solar radiation, ranging from 4% in the United States to 18% in more polluted China. Adoption of cool roofs also causes statistically significant reductions in surface air temperatures in urbanized regions of China (-0.11 ± 0.10 K) and the United States (-0.14 ± 0.12 K); India and Europe show statistically insignificant changes. Though past research has disagreed on whether widespread adoption of cool roofs would cool or warm global climate, these studies have lacked analysis on the statistical significance of global temperature changes. The research presented here indicates that adoption of cool roofs around the globe would lead to statistically insignificant reductions in global mean

  1. 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.

  2. The Monash University Interactive Simple Climate Model

    Science.gov (United States)

    Dommenget, D.

    2013-12-01

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

  3. 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...

  4. 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.

  5. 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.

  6. 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".

  7. 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...

  8. 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…

  9. 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

  10. 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)

  11. 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.

  12. 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

  13. Simulating the Pineapple Express in the half degree Community Climate System Model, CCSM4

    Science.gov (United States)

    Shields, Christine A.; Kiehl, Jeffrey T.

    2016-07-01

    Atmospheric rivers are recognized as major contributors to the poleward transport of water vapor. Upon reaching land, these phenomena also play a critical role in extreme precipitation and flooding events. The Pineapple Express (PE) is defined as an atmospheric river extending out of the deep tropics and reaching the west coast of North America. Community Climate System Model (CCSM4) high-resolution ensemble simulations for the twentieth and 21st centuries are diagnosed to identify the PE. Analysis of the twentieth century simulations indicated that the CCSM4 accurately captures the spatial and temporal climatology of the PE. Analysis of the end 21st century simulations indicates a significant increase in storm duration and intensity of precipitation associated with landfall of the PE. Only a modest increase in the number of atmospheric rivers of a few percent is projected for the end of 21st century.

  14. Energy balance climate models

    Science.gov (United States)

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

    1981-01-01

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

  15. 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.

  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. Climate data management system

    Energy Technology Data Exchange (ETDEWEB)

    Drach, R

    1999-07-13

    The Climate Data Management System is an object-oriented data management system, specialized for organizing multidimensional, gridded data used in climate analysis and simulation. The building blocks of CDMS are variables, container classes, structural classes, and links. All gridded data stored in CDMS is associated with variables. The container objects group variables and structural objects. Variables are defined in terms of structural objects. Most CDMS objects can have attributes, which are scalar or one-dimensional metadata items. Attributes which are stored in the database, that is are persistent, are called external attributes. Some attributes are internal; they are associated with an object but do not appear explicitly in the database.

  18. 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

    the 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...... the coupled model including groundwater and the RCM where groundwater is neglected. However, the resulting differences in the net precipitation and the catchment runoff in this groundwater dominated catchment were small. The need for further decadal scale simulations to understand the differences...

  19. 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.

  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. 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...

  2. 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

  3. 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

  4. 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

  5. Flexible climate modeling systems: Lessons from Snowball Earth, Titan and Mars

    Science.gov (United States)

    Pierrehumbert, R. T.

    2007-12-01

    Climate models are only useful to the extent that real understanding can be extracted from them. Most leading- edge problems in climate change, paleoclimate and planetary climate require a high degree of flexibility in terms of incorporating model physics -- for example in allowing methane or CO2 to be a condensible substance instead of water vapor. This puts a premium on model design that allows easy modification, and on physical parameterizations that are close to fundamentals with as little empirical ad-hoc formulation as possible. I will provide examples from two approaches to this problem we have been using at the University of Chicago. The first is the FOAM general circulation model, which is a clean single-executable Fortran-77/c code supported by auxiliary applications in Python and Java. The second is a new approach based on using Python as a shell for assembling building blocks in compiled-code into full models. Applications to Snowball Earth, Titan and Mars, as well as pedagogical uses, will be discussed. One painful lesson we have learned is that Fortran-95 is a major impediment to portability and cross-language interoperability; in this light the trend toward Fortran-95 in major modelling groups is seen as a significant step backwards. In this talk, I will focus on modeling projects employing a full representation of atmospheric fluid dynamics, rather than "intermediate complexity" models in which the associated transports are parameterized.

  6. 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.

  7. 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

  8. Assessing the Impact of Climate Change on Columbia River Basin Agriculture through Integrated Crop Systems, Hydrologic, and Water Management Modeling

    Science.gov (United States)

    Rajagopalan, K.; Chinnayakanahalli, K.; Adam, J. C.; Barber, M. E.; Yorgey, G.; Stockle, C.; Nelson, R.; Brady, M.; Dinesh, S.; Malek, K.; Kruger, C.; Yoder, J.; Marsh, T.

    2011-12-01

    The Columbia River Basin (CRB) in the Pacific Northwest covers parts of US and Canada with a total drainage area of about 670,000 square kilometers. The water resources of the CRB are managed to satisfy multiple objectives including agricultural withdrawal, which is the largest consumptive user of Columbia River water with 14,000 square kilometers of irrigated area in the CRB. Agriculture is an important component of the economy in the region, with an annual value over $5 billion in Washington State alone. The availability of surface water for irrigation in the basin is expected to be negatively impacted by climate change. Previous climate change studies in the CRB region suggest a likelihood of increasing temperatures and a shift in precipitation patterns, with precipitation higher in the winter and lower in the summer. Warming further exacerbates summer water availability in many CRB tributaries as they shift from snowmelt-dominant towards rain-dominant hydrologic regimes. The goal of this research is to study the impacts of climate change on CRB water availability and agricultural production in the expectation that curtailment will occur more frequently in an altered climate. Towards this goal it is essential that we understand the interactions between crop-growth dynamics, climate dynamics, the hydrologic cycle, water management, and agricultural economy. To study these interactions at the regional scale, we use the newly developed crop-hydrology model VIC-CropSyst, which integrates a crop growth model CropSyst with the hydrologic model, Variable Infiltration Capacity (VIC). Simulation of future climate by VIC-CropSyst captures the socio-economic aspects of this system through economic analysis of the impacts of climate change on crop patterns. This integrated framework (submitted as a separate paper) is linked to a reservoir operations simulations model, Colsim. ColSim is modified to explicitly account for agricultural withdrawals. Washington State water

  9. Design and implementation of the infrastructure of HadGEM3: the next-generation Met Office climate modelling system

    Directory of Open Access Journals (Sweden)

    H. T. Hewitt

    2011-04-01

    Full Text Available This paper describes the development of a technically robust climate modelling system, HadGEM3, which couples the Met Office Unified Model atmosphere component, the NEMO ocean model and the Los Alamos sea ice model (CICE using the OASIS coupler. Details of the coupling and technical solutions of the physical model (HadGEM3-AO are documented, in addition to a description of the configurations of the individual submodels. The paper demonstrates that the implementation of the model has resulted in accurate conservation of heat and freshwater across the model components. The model performance in early versions of this climate model is briefly described to demonstrate that the results are scientifically credible. HadGEM3-AO is the basis for a number of modelling efforts outside of the Met Office, both within the UK and internationally. This documentation of the HadGEM3-AO system provides a detailed reference for developers of HadGEM3-based climate configurations.

  10. 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.

  11. 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

  12. 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.

  13. Modeling the Roles of Precipitation Increasing in Glacier Systems Responding to Climate Warming - Taking Xinjiang Glaciated Region as Example

    Institute of Scientific and Technical Information of China (English)

    WANG Xin; XIE Zichu; LIU Shiyin; TAO Jianjun; HAN Yongshun; YANG Yuelong

    2005-01-01

    The studies on prediction of climate in Xinjiang almost show that the precipitation would increase in the coming 50 years, although there were surely some uncertainties in precipitation predictions.On the basis of the structure of glacier system and nature of equilibrium line altitude at steady state (ELAo), a functional model of the glacier system responding to climate changes was established, and it simultaneously involved the rising of summer mean temperature and increasing of mean precipitation.The results from the functional model under the climatic scenarios with temperature increasing rates of 0.01, 0.03 and 0.05 K/year indicated that the precipitation increasing would play an evident role in glacier system responding to climate change: if temperature become 1℃ higher, the precipitation would be increased by 10%, which can slow down the glaciers retreating rate in the area by 4%, accelerate runoff increasing rate by 8% and depress the ELAo rising gradient by 24 m in northern Xinjiang glacier system where semi-continental glaciers dominate,while it has corresponding values of only 1%, 5 % and 18m respectively in southern Xinjiang glacier system,where extremely continental glaciers dominate.

  14. Simulating Late Ordovician deep ocean O2 with an earth system climate model. Preliminary results.

    Science.gov (United States)

    D'Amico, Daniel F.; Montenegro, Alvaro

    2016-04-01

    The geological record provides several lines of evidence that point to the occurrence of widespread and long lasting deep ocean anoxia during the Late Ordovician, between about 460-440 million years ago (ma). While a series of potential causes have been proposed, there is still large uncertainty regarding how the low oxygen levels came about. Here we use the University of Victoria Earth System Climate Model (UVic ESCM) with Late Ordovician paleogeography to verify the impacts of paleogeography, bottom topography, nutrient loading and cycling and atmospheric concentrations of O2 and CO2 on deep ocean oxygen concentration during the period of interest. Preliminary results so far are based on 10 simulations (some still ongoing) covering the following parameter space: CO2 concentrations of 2240 to 3780 ppmv (~8x to 13x pre-industrial), atmospheric O2 ranging from 8% to 12% per volume, oceanic PO4 and NO3 loading from present day to double present day, reductions in wind speed of 50% and 30% (winds are provided as a boundary condition in the UVic ESCM). For most simulations the deep ocean remains well ventilated. While simulations with higher CO2, lower atmospheric O2 and greater nutrient loading generate lower oxygen concentration in the deep ocean, bottom anoxia - here defined as concentrations concentrations.

  15. 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

  16. 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

  17. The climate system

    Directory of Open Access Journals (Sweden)

    Brunetti M.

    2015-01-01

    Full Text Available An overview of what we know about the climate of the planet Earth up to 5.5 millions of years from now is presented first, with the air temperature in proximity to the surface as the main, and more feasible, parameter to be followed. The behavior of this parameter exhibits a distinct periodicity with more internal fluctuations. This overview prompts us to a description of the physical basis of the climate system, capable of explaining such fluctuations. The system is the star-planet, initially described as a lamp-billiard ball simple system. Astronomical causes affect the distance lamp-billiard ball (star-planet and the ball (Earth rotation axis orientation, while astronomical causes affect the intensity of radiation emitted from the lamp (Sun. The complication introduced by the atmosphere is then explained, essentially through the triatomic gas molecules, aerosol and clouds. Atmospheric composition affects incoming solar radiation and outgoing infrared one. The compartments relevant for climate definition are examined: lithosphere, hydrosphere, cryosphere, biosphere including vegetation and humans. However due to space limitations the interactions between the different compartments are not treated here and we restrict ourselves to the treatment of the atmosphere.

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

    Science.gov (United States)

    Amna, S.; Samreen, N.; Khalid, B.; Shamim, A.

    2013-06-01

    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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    M. Lawrence

    2012-01-01

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

  5. The importance of terrestrial weathering for climate system modelling on extended timescales: a study with the UVic ESCM

    Science.gov (United States)

    Brault, Marc-Olivier; Matthews, Damon; Mysak, Lawrence

    2016-04-01

    The chemical erosion of carbonate and silicate rocks is a key process in the global carbon cycle and, through its coupling with calcium carbonate deposition in the ocean, is the primary sink of carbon on geologic timescales. The dynamic interdependence of terrestrial weathering rates with atmospheric temperature and carbon dioxide concentrations is crucial to the regulation of Earth's climate over multi-millennial timescales. However any attempts to develop a modeling context for terrestrial weathering as part of a dynamic climate system are limited, mostly because of the difficulty in adapting the multi-millennial timescales of the implied negative feedback mechanism with those of the atmosphere and ocean. Much of the earlier work on this topic is therefore based on box-model approaches, abandoning spatial variability for the sake of computational efficiency and the possibility to investigate the impact of weathering on climate change over time frames much longer than those allowed by traditional climate system models. As a result we still have but a rudimentary understanding of the chemical weathering feedback mechanism and its effects on ocean biogeochemistry and atmospheric CO2. Here, we introduce a spatially-explicit, rock weathering model into the University of Victoria Earth System Climate Model (UVic ESCM). We use a land map which takes into account a number of different rock lithologies, changes in sea level, as well as an empirical model of the temperature and NPP dependency of weathering rates for the different rock types. We apply this new model to the last deglacial period (c. 21000BP to 13000BP) as well as a future climate change scenario (c. 1800AD to 6000AD+), comparing the results of our 2-D version of the weathering feedback mechanism to simulations using only the box-model parameterizations of Meissner et al. [2012]. These simulations reveal the importance of two-dimensional factors (i.e., changes in sea level and rock type distribution) in the

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. Final Report for DOE Grant DE-FG02-07ER64470 [“Incorporation of the HYbrid Coordinate Ocean Model (HYCOM) into the Community Climate System Model (CCSM): Evaluation and Climate Applications”

    Energy Technology Data Exchange (ETDEWEB)

    Chassignet, Eric P

    2013-03-18

    The primary goal of the project entitled “Incorporation of the HYbrid Coordinate Ocean Model (HYCOM) into the Community Climate System Model (CCSM): Evaluation and Climate Applications” was to systematically investigate the performance of the HYbrid Coordinate Ocean Model (HYCOM) as an alternative oceanic component of the NCAR’s Community Climate System Model (CCSM). We have configured two versions of the fully coupled CCSM3/HYCOM: one with a medium resolution (T42) Community Atmospheric Model (CAM) and the other with higher resolution (T85). We have performed a comprehensive analysis of the 400-year fully coupled CCSM3/HYCOM simulations and compared the results with those from CCSM3/POP and with climatological observations, and also we have performed tuning of critical model parameters, including Smagorinsky viscosity, isopycnal diffusivity, and background vertical diffusivity. The analysis shows that most oceanic features are well represented in the CCSM3/HYCOM. The coupled CCSM3/HYCOM (T42) has been integrated for 400 years, and the results have been archived and transferred to the High Performance Computer in the Florida State Univesity. In the last year, we have made comprehensive diagnostics of the long-term simulations by the comparison with the original CCSM3/POP simulation and with the observations. To gain some understanding of the model biases, the mean climate and modes of climate variability of the two models are compared with observations. The examination includes the Northern and Southern Annular Modes (NAM and SAM), the Pacific-North-American (PNA) pattern, the Atlantic Multidecadal Oscillation (AMO), and the main Southern Ocean SST mode. We also compared the performance of ENSO simulation in the coupled models. This report summarizes the main findings from the comparison of long-term CCSM3/HYCOM and CCSM3/POP simulations.

  19. Uncertainty Quantification in Climate Modeling and Projection

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Ivan Morales

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

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

    Science.gov (United States)

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

    2016-01-01

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

  5. 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.

  6. Performance of Versions 1,2 and 3 of the Goddard Earth Observing System (GEOS) Chemistry-Climate Model (CCM)

    Science.gov (United States)

    Pawson, Steven; Stolarski, Richard S.; Nielsen, J. Eric; Duncan, Bryan N.

    2008-01-01

    Version 1 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) was used in the first CCMVa1 model evaluation and forms the basis for several studies of links between ozone and the circulation. That version of the CCM was based on the GEOS-4 GCM. Versions 2 and 3 of the GEOS CCM are based on the GEOS-5 GCM, which retains the "Lin-Rood" dynamical core but has a totally different set of physical parameterizatiOns to GEOS-4. In Version 2 of the GEOS CCM the Goddard stratospheric chemistry module is retained. Difference between Versions 1 and 2 thus reflect the physics changes of the underlying GCMs. Several comparisons between these two models are made, several of which reveal improvements in Version 2 (including a more realistic representation of the interannual variability of the Antarctic vortex). In Version 3 of the GEOS CCM, the stratospheric chemistry mechanism is replaced by the "GMI COMBO" code that includes tropospheric chemistry and different computational approaches. An advantage of this model version. is the reduction of high ozone biases that prevail at low chlorine loadings in Versions 1 and 2. This poster will compare and contrast various aspects of the three model versions that are relevant for understanding interactions between ozone and climate.

  7. 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

  8. 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

  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.

    2016-09-01

    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. 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

  13. Final Progress Report for DOE Award # DE-SC0001898 at University of Alaska Fairbanks, Characterization of the dynamics of climate systems and identification of missing mechanisms impacting the long term predictive capabilities of Global Climate Models utilizing dynamical systems approaches to the analysis of observed and modeled climate

    Energy Technology Data Exchange (ETDEWEB)

    Bhatt, Uma S. [University of Alaska Fairbanks; Wackerbauer, Renate [University of Alaska Fairbanks; Polyakov, Igor V. [University of Alaska Fairbanks; Newman, David E. [University of Alaska Fairbanks; Sanchez, Raul [ORNL (past), Carlos III University (present)

    2015-11-13

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

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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...

  19. 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

  20. 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.

  1. 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)

  2. 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 (...

  3. 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

  4. Measure the Climate, Model the City

    Science.gov (United States)

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

    2011-08-01

    Modern large cities are characterized by a high building concentration, little aeration and lack of green spaces. Such characteristics create an urban climate which is different from the climate outside of cities. An example of an urban climate effect is the so-called Urban Heat Island: cities tend to be warmer than the surrounding rural areas. The higher temperature results in an increase in energy consumption since people, especially in summer, use artificial means to cool themselves. Although means of mitigating the UHI effect exist, they are difficult to justify, as knowledge about urban climate is limited, and analysis tools are lacking. This paper presents the work carried during the 2010 MSc Geomatics Synthesis Project. A 3D spatial relational database has been implemented which is meant to act as starting point in the development of a 3D climate-enabled geographical information system. To this end, the database stores 3D geometries representing the built environment and its thematic properties. The database is also able to store measurements of climate parameters, in this case temperature, obtained through mobile sensors. Spatial analyses and queries are supported, allowing users to calculate areas, distances, buffers, add and remove geometries and thematic attributes. The database design is based on the CityGML information model which has been extended to allow the storage of climate parameters relevant to urban climate research.

  5. Seasonal Evolution of Subtropical Anticyclones in the Climate System Model FGOALS-s2

    Institute of Scientific and Technical Information of China (English)

    LIU Yimin; HU Jun; HE Bian; BAO Qing; DUAN Anmin; WU Guoxiong

    2013-01-01

    The simulation characteristics of the seasonal evolution of subtropical anticyclones in the Northern Hemisphere are documented for the Flexible Global Ocean-Atmosphere-Land System model,Spectral Version 2 (FGOALS-s2),developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,the Institute of Atmospheric Physics.An understanding of the seasonal evolution of the subtropical anticyclones is also addressed.Compared with the global analysis established by the European Centre for Medium-Range Forecasts,the ERA-40 global reanalysis data,the general features of subtropical anticyclones and their evolution are simulated well in both winter and summer,while in spring a pronounced bias in the generation of the South Asia Anticyclone(SAA) exists.Its main deviation in geopotential height from the reanalysis is consistent with the bias of temperature in the troposphere.It is found that condensation heating (CO) plays a dominant role in the seasonal development of the SAA and the subtropical anticyclone over the western Pacific (SAWP) in the middle troposphere.The CO biases in the model account for the biases in the establishment of the SAA in spring and the weaker strength of the SAA and the SAWP from spring to summer.CO is persistently overestimated in the central-east tropical Pacific from winter to summer,while it is underestimated over the area from the South China Sea to the western Pacific from spring to summer.Such biases generate an illusive anticyclonic gyre in the upper troposphere above the middle Pacific and delay the generation of the SAA over South Asia in April.In midsummer,the simulated SAA is located farther north than in the ERA-40 data owing to excessively strong surface sensible heating (SE) to the north of the Tibetan Plateau.Whereas,the two surface subtropical anticyclones in the eastern oceans during spring to summer are controlled mainly by the surface SE over the two continents in the Northern

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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.

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

    Science.gov (United States)

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

    2013-12-01

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

  12. Hierarchical Climate Modeling for Cosmoclimatology

    Science.gov (United States)

    Ohfuchi, Wataru

    2010-05-01

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

  13. 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

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  15. Energy, environmental and climate assessment with the EPA MARKAL energy system modeling framework

    Science.gov (United States)

    The energy system is comprised of the technologies and fuels that extend from the import or extraction of energy resources (e.g., mines and wells), through the conversion of these resources into useful forms (e.g., electricity and gasoline), to the technologies (e.g., cars, light...

  16. 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…

  17. 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.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    R. M. Law

    2015-09-01

    Full Text Available 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 phosphorous limitation on the land carbon uptake. The ocean carbon model simulates the evolution of nitrate, oxygen, dissolved inorganic carbon, alkalinity and iron with one class of phytoplankton and zooplankton. From two multi-centennial simulations of the pre-industrial period with different land carbon model configurations, we evaluate the equilibration of the carbon cycle and present the spatial and temporal variability in key carbon exchanges. For the land carbon cycle, leaf area index is simulated reasonably, and seasonal carbon exchange is well represented. Interannual variations of land carbon exchange are relatively large, driven by variability in precipitation and temperature. We find that the response of the ocean carbon cycle shows reasonable agreement with observations and very good agreement with existing Coupled Model Intercomparison Project (CMIP5 models. While our model over estimates surface nitrate values, the primary productivity agrees well with observations. Our analysis highlights some deficiencies inherent in the carbon models and where the carbon simulation is negatively impacted by known biases in the underlying physical model. We conclude the study with a brief discussion of key developments required to further improve the realism of our model simulation.

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

    Science.gov (United States)

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

    2015-09-01

    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 phosphorous limitation on the land carbon uptake. The ocean carbon model simulates the evolution of nitrate, oxygen, dissolved inorganic carbon, alkalinity and iron with one class of phytoplankton and zooplankton. From two multi-centennial simulations of the pre-industrial period with different land carbon model configurations, we evaluate the equilibration of the carbon cycle and present the spatial and temporal variability in key carbon exchanges. For the land carbon cycle, leaf area index is simulated reasonably, and seasonal carbon exchange is well represented. Interannual variations of land carbon exchange are relatively large, driven by variability in precipitation and temperature. We find that the response of the ocean carbon cycle shows reasonable agreement with observations and very good agreement with existing Coupled Model Intercomparison Project (CMIP5) models. While our model over estimates surface nitrate values, the primary productivity agrees well with observations. Our analysis highlights some deficiencies inherent in the carbon models and where the carbon simulation is negatively impacted by known biases in the underlying physical model. We conclude the study with a brief discussion of key developments required to further improve the realism of our model simulation.

  1. 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.

  2. 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.

  3. High dimensional decision dilemmas in climate models

    Science.gov (United States)

    Bracco, A.; Neelin, J. D.; Luo, H.; McWilliams, J. C.; Meyerson, J. E.

    2013-10-01

    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.

  4. An Analog Earth Climate Model

    Science.gov (United States)

    Varekamp, J. C.

    2010-12-01

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

  5. Data and Knowledge Base on the Basis of the Expanded Matrix Model of Their Representation for the Intelligent System of Road-Climatic Zoning of Territories

    Science.gov (United States)

    Yankovskaya, A.; Cherepanov, D.; Selivanikova, O.

    2016-08-01

    An extended matrix model of data and knowledge representation on the investigated area, as well as a matrix model of data representation on the territory under investigation, are proposed for the intelligent system of road-climatic zoning of territories (RCZT) - the main information technology of RCZT. A part of the West Siberian region has been selected as the investigated territory. The extended matrix model of knowledge representation is filled out by knowledge engineers with participation of highly qualified experts in the field of RCZT. The matrix model of data representation on the territory under investigation is filled out by persons concerned in RCZT of the motor-roads management system.

  6. 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.

  7. Sea-spray geoengineering in the HadGEM2-ES Earth-system model: radiative impact and climate response

    Directory of Open Access Journals (Sweden)

    A. Jones

    2012-08-01

    Full Text Available The radiative impact and climate effects of geoengineering using sea-spray aerosols have been investigated in the HadGEM2-ES Earth system model using a fully prognostic treatment of the sea-spray aerosols and also including their direct raditive effect. Two different emission patterns were considered, one to maximise the direct effect in clear skies, the other to maximise the indirect effects of the sea-spray on low clouds; in both cases the emissions were limited to 10% of the ocean area. While the direct effect was found to be significant, the indirect effects on clouds were much more effective in reducing global mean temperature. Moreover, the impact on global mean precipitation per unit temperature reduction was found to be greatest when the emission pattern for maximising the direct effect was used, suggesting that targeting the direct effect of sea-spray is not a good strategy. The impact on the distribution of precipitation was found to be similar in character, but less in degree, than that simulated by a previous study using a much simpler treatment of this geoengineering process.

  8. Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg. in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling

    Directory of Open Access Journals (Sweden)

    Kyung Ah Koo

    2015-04-01

    Full Text Available Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species’ distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate change effects on the distribution of red spruce (Picea rubens Sarg. in the Great Smoky Mountains National Park (GSMNP, eastern USA. Climate change is, however, conflated with other environmental factors, making its assessment a complex systems problem in which indirect effects are significant in causality. Predictions were made by linking a tree growth simulation model, red spruce growth model (ARIM.SIM, to a GIS spatial model, red spruce habitat model (ARIM.HAB. ARIM.SIM quantifies direct and indirect interactions between red spruce and its growth factors, revealing the latter to be dominant. ARIM.HAB spatially distributes the ARIM.SIM simulations under the assumption that greater growth reflects higher probabilities of presence. ARIM.HAB predicts the future habitat suitability of red spruce based on growth predictions of ARIM.SIM under climate change and three air pollution scenarios: 10% increase, no change and 10% decrease. Results show that suitable habitats shrink most when air pollution increases. Higher temperatures cause losses of most low-elevation habitats. Increased precipitation and air pollution produce acid rain, which causes loss of both low- and high-elevation habitats. The general prediction is that climate change will cause contraction of red spruce habitats at both lower and higher elevations in GSMNP, and the effects will be exacerbated by increased air pollution. These predictions provide valuable information for understanding potential impacts of global climate change on the spatiotemporal distribution of red spruce habitats in GSMNP.

  9. 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

  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. Integrated approaches to climate-crop modelling: needs and challenges.

    Science.gov (United States)

    Betts, Richard A

    2005-11-29

    This paper discusses the need for a more integrated approach to modelling changes in climate and crops, and some of the challenges posed by this. While changes in atmospheric composition are expected to exert an increasing radiative forcing of climate change leading to further warming of global mean temperatures and shifts in precipitation patterns, these are not the only climatic processes which may influence crop production. Changes in the physical characteristics of the land cover may also affect climate; these may arise directly from land use activities and may also result from the large-scale responses of crops to seasonal, interannual and decadal changes in the atmospheric state. Climate models used to drive crop models may, therefore, need to consider changes in the land surface, either as imposed boundary conditions or as feedbacks from an interactive climate-vegetation model. Crops may also respond directly to changes in atmospheric composition, such as the concentrations of carbon dioxide (CO2), ozone (03) and compounds of sulphur and nitrogen, so crop models should consider these processes as well as climate change. Changes in these, and the responses of the crops, may be intimately linked with meteorological processes so crop and climate models should consider synergies between climate and atmospheric chemistry. Some crop responses may occur at scales too small to significantly influence meteorology, so may not need to be included as feedbacks within climate models. However, the volume of data required to drive the appropriate crop models may be very large, especially if short-time-scale variability is important. Implementation of crop models within climate models would minimize the need to transfer large quantities of data between separate modelling systems. It should also be noted that crop responses to climate change may interact with other impacts of climate change, such as hydrological changes. For example, the availability of water for irrigation

  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, 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

  15. 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.

  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. 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.

  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. 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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-12-15

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

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Bahn, Olivier [GERAD and Department of Management Sciences, HEC Montreal, Montreal (Qc) (Canada); Edwards, Neil R. [Earth and Environmental Sciences, CEPSAR, Open University, Milton Keynes MK7 6AA (United Kingdom); Knutti, Reto [Institute for Atmospheric and Climate Science, ETH Zurich, CH-8092 Zurich (Switzerland); Stocker, Thomas F. [Climate and Environmental Physics, Physics Institute, and Oeschger Centre for Climate Change Research, University of Bern, CH-3012 Bern (Switzerland)

    2011-01-15

    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. (author)

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

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, Raymond S; Diaz, Henry F

    2010-12-14

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

  8. 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

  9. 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

  10. 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

  11. 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...

  12. 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...

  13. 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

  14. Interpolation of climate variables and temperature modeling

    Science.gov (United States)

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

    2012-01-01

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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. Improving Climate Literacy Using The Ice Sheet System Model (ISSM): A Prototype Virtual Ice Sheet Laboratory For Use In K-12 Classrooms

    Science.gov (United States)

    Halkides, D. J.; Larour, E. Y.; Perez, G.; Petrie, K.; Nguyen, L.

    2013-12-01

    Statistics indicate that most Americans learn what they will know about science within the confines of our public K-12 education system and the media. Next Generation Science Standards (NGSS) aim to remedy science illiteracy and provide guidelines to exceed the Common Core State Standards that most U.S. state governments have adopted, by integrating disciplinary cores with crosscutting ideas and real life practices. In this vein, we present a prototype ';Virtual Ice Sheet Laboratory' (I-Lab), geared to K-12 students, educators and interested members of the general public. I-Lab will allow users to perform experiments using a state-of-the-art dynamical ice sheet model and provide detailed downloadable lesson plans, which incorporate this model and are consistent with NGSS Physical Science criteria for different grade bands (K-2, 3-5, 6-8, and 9-12). The ultimate goal of this website is to improve public climate science literacy, especially in regards to the crucial role of the polar ice sheets in Earth's climate and sea level. The model used will be the Ice Sheet System Model (ISSM), an ice flow model developed at NASA's Jet Propulsion Laboratory and UC Irvine, that simulates the near-term evolution of polar ice sheets (Greenland and Antarctica) and includes high spatial resolution capabilities and data assimilation to produce realistic simulations of ice sheet dynamics at the continental scale. Open sourced since 2011, ISSM is used in cutting edge cryosphere research around the globe. Thru I-Lab, students will be able to access ISSM using a simple, online graphical interface that can be launched from a web browser on a computer, tablet or smart phone. The interface will allow users to select different climate conditions and watch how the polar ice sheets evolve in time under those conditions. Lesson contents will include links to background material and activities that teach observation recording, concept articulation, hypothesis formulation and testing, and

  20. 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

  1. 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.''

  2. 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

  3. Modeling the Earth: Climate on an Icosphere

    Science.gov (United States)

    Fouts, Stephanie; Cook, L. Jonathan

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

  4. 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...

  5. 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

  6. 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

  7. 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).

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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...

  20. 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.

  1. Modeling Impacts of Climate Change on Giant Panda Habitat

    Directory of Open Access Journals (Sweden)

    Melissa Songer

    2012-01-01

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

  2. 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.

  3. Climate change and health modeling: horses for courses

    Directory of Open Access Journals (Sweden)

    Kristie L. Ebi

    2014-05-01

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

  4. 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.

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. Climate Model Intercomparisons: Preparing for the Next Phase

    Science.gov (United States)

    Meehl, Gerald A.; Moss, Richard; Taylor, Karl E.; Eyring, Veronika; Stouffer, Ronald J.; Bony, Sandrine; Stevens, Bjorn

    2014-03-01

    Since 1995, the Coupled Model Intercomparison Project (CMIP) has coordinated climate model experiments involving multiple international modeling teams. Through CMIP, climate modelers and scientists from around the world have analyzed and compared state-of-the-art climate model simulations to gain insights into the processes, mechanisms, and consequences of climate variability and climate change. This has led to a better understanding of past, present, and future climate, and CMIP model experiments have routinely been the basis for future climate change assessments made by the Intergovernmental Panel on Climate Change (IPCC) [e.g., IPCC, 2013, and references therein].

  14. 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.

  15. Model experiments on climate change in the Tokyo metropolitan area using regional climate scenarios

    Science.gov (United States)

    Tsunematsu, N.; Dairaku, K.

    2011-12-01

    There is a possibility that the future atmospheric warming leads to more frequent heavy rainfall in the metropolitan area, thereby increasing the risk of floods. As part of REsearch Program on Climate Change Adaptation (RECCA) funded by Ministry of Education, Culture, Sports, Science and Technology, Japan, we started numerical model experiments for investigating the vulnerability and adaptation to climate change in water hazard assessments in the metropolitan area by the use of regional climate scenarios. The model experiments adopt dynamical downscaling techniques. Future climate projections obtained from regional climate model simulations at 20 km horizontal grid spacing are downscaled into finer grids (less than 5 km resolutions) of Regional Atmospheric Modeling System Version 6.0 modified by National Research Institute for Earth Science and Disaster Prevention (NIED-RAMS). Prior to performing the dynamical downscaling experiments, the NIED-RAMS model biases are evaluated by comparing long-term surface meteorological observations with results of the model simulations that are carried out by using the Japanese Re-Analysis (JRA) data and Japan Meteorological Agency Meso-Scale Model outputs as the initial and boundary conditions.

  16. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Forster, P M A F; Taylor, K E

    2006-07-25

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

  18. 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

  19. Diagnostic indicators for integrated assessment models of climate policy

    NARCIS (Netherlands)

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

    2015-01-01

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

  20. The impact of climate and land use changes on water resources. The application of the integrated hydrological modelling system, IHMS (Invited)

    Science.gov (United States)

    Ragab, R.; Bromley, J.; Dörflinger, G.; Katsikides, S.; D'Agostino, D. R.; Lamaddalena, N.; Trisorio, G. L.; Montenegro, S. G.; Montenegro, A.

    2010-12-01

    An Integrated Hydrological Modelling System, IHMS has been developed to study the impact of climate and land use changes on water resources. The system comprises three packages: the DiCaSM, MODFLOW and SWI models. The Distributed Catchment Scale Model DiCaSM, produces the recharge data for MODFLOW which in turn produces the head distribution for the Sea Water Intrusion model, SWI. These models can run separately. The DiCaSM model simulates the water balance and produces values of evapotranspiration, rainfall interception, infiltration, transpiration, soil water content, groundwater recharge, streamflow and surface runoff. In the 1st example of application, the IHMS was applied on Kouris and Akrotiri catchments in Cyprus. The system was successfully tested against the streamflow and groundwater levels data. Further, the model showed that by 2050, groundwater and surface water would decrease by 35% and 24% for Kouris and 20% and 17% for Akrotiri, respectively. In the 2nd example, the reliability of DiCaSM application on Candelaro catchment in the Apulia region, southern Italy was assessed and the uncertainty of the results were investigated using GLUE (Generalised Likelihood Uncertainty Estimation) methodology. In the 3rd example, DiCaSM model was applied on Tapacurá catchment in the NE of Brazil. The model successfully simulated streamflow and the soil moisture. The climate change scenarios indicated a possible reduction in surface water availability by -13.9%, -22.63% and -32.91% in groundwater recharge and by -4.98%, -14.28% and -20.58% in surface flows for the time spans 2010-2039, 2040-2069, 2070-2099, respectively. Changing the land use by reforestation of part of the catchment area, i.e. replacing current use of arable land would decrease groundwater recharge by -4.2% and streamflow by -2.7%. Changing land use from vegetables to sugar cane would result in decreasing groundwater recharge by around -10%, and increasing stream flow by 5%. In the 4th example, the

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. Climate Modeling Computing Needs Assessment

    Science.gov (United States)

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

    2011-12-01

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

  6. Objective calibration of regional climate models

    Science.gov (United States)

    Bellprat, O.; Kotlarski, S.; Lüthi, D.; SchäR, C.

    2012-12-01

    Climate models are subject to high parametric uncertainty induced by poorly confined model parameters of parameterized physical processes. Uncertain model parameters are typically calibrated in order to increase the agreement of the model with available observations. The common practice is to adjust uncertain model parameters manually, often referred to as expert tuning, which lacks objectivity and transparency in the use of observations. These shortcomings often haze model inter-comparisons and hinder the implementation of new model parameterizations. Methods which would allow to systematically calibrate model parameters are unfortunately often not applicable to state-of-the-art climate models, due to computational constraints facing the high dimensionality and non-linearity of the problem. Here we present an approach to objectively calibrate a regional climate model, using reanalysis driven simulations and building upon a quadratic metamodel presented by Neelin et al. (2010) that serves as a computationally cheap surrogate of the model. Five model parameters originating from different parameterizations are selected for the optimization according to their influence on the model performance. The metamodel accurately estimates spatial averages of 2 m temperature, precipitation and total cloud cover, with an uncertainty of similar magnitude as the internal variability of the regional climate model. The non-linearities of the parameter perturbations are well captured, such that only a limited number of 20-50 simulations are needed to estimate optimal parameter settings. Parameter interactions are small, which allows to further reduce the number of simulations. In comparison to an ensemble of the same model which has undergone expert tuning, the calibration yields similar optimal model configurations, but leading to an additional reduction of the model error. The performance range captured is much wider than sampled with the expert-tuned ensemble and the presented

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Impact of surface waves in a Regional Climate Model

    DEFF Research Database (Denmark)

    Rutgersson, Anna; Sætra, Oyvind; Semedo, Alvaro;

    2010-01-01

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

  14. 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

  15. 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

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

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

    Science.gov (United States)

    Chen, Lin; Yu, Yongqiang; Zheng, Weipeng

    2016-10-01

    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.

  4. 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.)

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

    Science.gov (United States)

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

    2011-08-01

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

  6. 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.

  7. Selection of climate change scenario data for impact modelling

    DEFF Research Database (Denmark)

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

    2012-01-01

    Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study...

  8. 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...

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

    Science.gov (United States)

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

    2011-06-01

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

  10. 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

  11. 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...

  12. 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

  13. 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.)

  14. 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

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

    DEFF Research Database (Denmark)

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

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

  16. Modelling the wind climate of Ireland

    DEFF Research Database (Denmark)

    Frank, H.P.; Landberg, L.

    1997-01-01

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

  17. Global comparison of three greenhouse climate models

    NARCIS (Netherlands)

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

    1985-01-01

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

  18. 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.

  19. 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

  20. 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...

  1. 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.

  2. 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

    -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...

  3. 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.

  4. A Standardized Evaluation System for Decadal Climate Prediction

    Science.gov (United States)

    Kadow, C.; Cubasch, U.

    2012-12-01

    The evaluation of decadal prediction systems is a scientific challenge as well as a technical challenge in the climate research. The major project MiKlip (www.fona-miklip.de) for medium-term climate prediction funded by the Federal Ministry of Education and Research in Germany (BMBF) has the aim to create a model system that can provide reliable decadal forecasts on climate and weather. The model system to be developed will be novel in several aspects, with great challenges for the methodology development. This concerns especially the determination of the initial conditions, the inclusion into the model of processes relevant to decadal predictions, the increase of the spatial resolution through regionalisation, the improvement or adjustment of statistical post-processing, and finally the synthesis and validation of the entire model system. Therefore, a standardized evaluation system will be part of the MiKlip system to validate it - developed by the project 'Integrated data and evaluation system for decadal scale prediction' (INTEGRATION). The presentation gives an overview of the different linkages of such a project, shows the different development stages and gives an outlook for users and possible end users in climate service. The technical interface combines all projects inside of MiKlip and invites them to participate in a common evaluation system. The system design and the validation strategy from a standalone tool in the beginning to a user friendly web based system using GRID technologies to an integrated part of the operational MiKlip system for industry and society will give the opportunity to enhance the MiKlip strategy. First results of different possibilities of such a system will be shown to present the scientific background through Taylor diagrams, ensemble skill scores and e.g. climatological means to show the usability and possibilities of MiKlip and the INTEGRATION project.

  5. 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...

  6. 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.

  7. Impacts of Climate Change on Stream Flow in the Upper Mississippi River Basin: A Regional Climate Model Perspective, The

    OpenAIRE

    Manoj Jha; Zaitao Pan; Takle, Eugene S.; Roy Gu

    2003-01-01

    We evaluate the impact of climate change on stream flow in the Upper Mississippi River Basin (UMRB) by using a regional climate model (RCM) coupled with a hydrologic model, the Soil and Water Assessment Tool (SWAT). The SWAT model was calibrated and validated against measured stream flow data using observed weather data and inputs from the Environmental Protection Agency's BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) geographical information/database system. The c...

  8. 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.

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

    Science.gov (United States)

    Rood, R. B.

    2011-12-01

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

  10. 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

  11. 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

  12. The control of climate and base-level change on the stratigraphic architecture of fluvio-deltaic systems, investigated by quantitative analogue modelling

    NARCIS (Netherlands)

    Berg van Saparoea, Aart-Peter van den

    2005-01-01

    River systems play an important role in the filling of sedimentary basins and record the history of external forcing processes, such as climate, tectonics and sea-level change, acting on them. They are potential reservoirs for oil, gas and water, and can host coal and placer mineral deposits. Becaus

  13. 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

  14. 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...

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. 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...

  20. A technique for generating consistent ice sheet initial conditions for coupled ice-sheet/climate models

    Directory of Open Access Journals (Sweden)

    J. G. Fyke

    2013-04-01

    Full Text Available A new technique for generating ice sheet preindustrial 1850 initial conditions for coupled ice-sheet/climate models is developed and demonstrated over the Greenland Ice Sheet using the Community Earth System Model (CESM. Paleoclimate end-member simulations and ice core data are used to derive continuous surface mass balance fields which are used to force a long transient ice sheet model simulation. The procedure accounts for the evolution of climate through the last glacial period and converges to a simulated preindustrial 1850 ice sheet that is geometrically and thermodynamically consistent with the 1850 preindustrial simulated CESM state, yet contains a transient memory of past climate that compares well to observations and independent model studies. This allows future coupled ice-sheet/climate projections of climate change that include ice sheets to integrate the effect of past climate conditions on the state of the Greenland Ice Sheet, while maintaining system-wide continuity between past and future climate simulations.

  1. 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

  2. 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

  3. 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

  4. 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

  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. 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.)

  7. 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

  8. 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...

  9. Challenging some tenets of Regional Climate Modelling

    Science.gov (United States)

    Laprise, R.; de Elía, R.; Caya, D.; Biner, S.; Lucas-Picher, P.; Diaconescu, E.; Leduc, M.; Alexandru, A.; Separovic, L.

    2008-08-01

    Nested Regional Climate Models (RCMs) are increasingly used for climate-change projections in order to achieve spatial resolutions that would be computationally prohibitive with coupled global climate models. RCMs are commonly thought to behave as a sort of sophisticated magnifying glass to perform dynamical downscaling, which is to add fine-scale details upon the large-scale flow provided as time-dependent lateral boundary condition. Regional climate modelling is a relatively new approach, initiated less than twenty years ago. The interest for the approach has grown rapidly as it offers a computationally affordable means of entering into appealing applications of timely societal relevance, such as high-resolution climate-change projections and seasonal prediction. There exists however a need for basic research aiming at establishing firmly the strengths and limitations of the technique. This paper synthesises the results of a stream of investigations on the merits and weaknesses of the nested approach, initiated almost a decade ago by some members of our team. This short paper revisits some commonly accepted notions amongst practitioners of Regional Climate Modelling, in the form of four tenets that will be challenged: (1) RCMs are capable of generating small-scale features absent in the driving fields supplied as lateral boundary conditions; (2) The generated small scales have the appropriate amplitudes and statistics; (3) The generated small scales accurately represent those that would be present in the driving data if it were not limited by resolution; (4) In performing dynamical downscaling, RCMs operate as a kind of sophisticated magnifying glass, in the sense that the small scales that are generated are uniquely defined for a given set of lateral boundary conditions (LBC). From the partial failure of the last two tenets emerges the notion of internal variability, which has often been thought to be negligible in one-way nested models due to the control

  10. 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

  11. 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.

  12. 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

  13. 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.)

  14. 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.

  15. 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...

  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. 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.

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

    DEFF Research Database (Denmark)

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

    2007-01-01

    of emission coefficients is described. Emission dependent parameters are identified in order to perform model projections. The model system is demonstrated by projections of agricultural-related emissions in Denmark under two alternative sets of assumptions: a baseline projection and a policy scenario...... economic model, environmental satellite models of energy and waste related emissions contributing to climate change and acidification. The model extension allows the main Danish contribution to climate change and acidification to be modelled. The existing model system is extended by environmental satellite...... models, in which emission coefficients are linked to economic activity variables as modelled by the agricultural sector model ESMERALDA. Agricultural emission sources related to the activity variables in ESMERALDA are mapped in order to develop the environmental satellite models and the development...

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. 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.

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

    NARCIS (Netherlands)

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

    1998-01-01

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

  6. Variable temperature seat climate control system

    Science.gov (United States)

    Karunasiri, Tissa R.; Gallup, David F.; Noles, David R.; Gregory, Christian T.

    1997-05-06

    A temperature climate control system comprises a variable temperature seat, at least one heat pump, at least one heat pump temperature sensor, and a controller. Each heat pump comprises a number of Peltier thermoelectric modules for temperature conditioning the air in a main heat exchanger and a main exchanger fan for passing the conditioned air from the main exchanger to the variable temperature seat. The Peltier modules and each main fan may be manually adjusted via a control switch or a control signal. Additionally, the temperature climate control system may comprise a number of additional temperature sensors to monitor the temperature of the ambient air surrounding the occupant as well as the temperature of the conditioned air directed to the occupant. The controller is configured to automatically regulate the operation of the Peltier modules and/or each main fan according to a temperature climate control logic designed both to maximize occupant comfort during normal operation, and minimize possible equipment damage, occupant discomfort, or occupant injury in the event of a heat pump malfunction.

  7. Diagnostic indicators for integrated assessment models of climate policy

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-01-01

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

  8. 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

  9. 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

  10. 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 thesis, a conceptual multi-zone climate model is proposed according to the knowledge about the hybrid ventilation theory. The method is to compartmentalize the building into some well-mixed macroscopic homogeneous zones, with the major emphasizes on the occupied spaces where the animals confined in...... the 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...

  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. Towards Systematic Benchmarking of Climate Model Performance

    Science.gov (United States)

    Gleckler, P. J.

    2014-12-01

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

  13. 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

  14. Modelling and observing urban climate in the Netherlands

    Energy Technology Data Exchange (ETDEWEB)

    Van Hove, B. [Wageningen University, Earth System Science, Wageningen (Netherlands); Steeneveld, G.J.; Heusinkveld, B.; Holtslag, B. [Wageningen University, Meteorology and Air Quality, Wageningen (Netherlands); Jacobs, C.; Ter Maat, H.; Elbers, J.; Moors, E. [Wageningen UR, Alterra, Climate Change, Wageningen (Netherlands)

    2011-06-15

    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

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

    Science.gov (United States)

    Scafetta, Nicola

    2012-05-01

    We compare the performance of a recently proposed empirical climate model based on astronomical harmonics against all CMIP3 available general circulation climate models (GCM) used by the IPCC (2007) to interpret the 20th century global surface temperature. The proposed astronomical empirical climate model assumes that the climate is resonating with, or synchronized to a set of natural harmonics that, in previous works (Scafetta, 2010b, 2011b), have been associated to the solar system planetary motion, which is 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 (which herein uses cycles with 9.1, 10-10.5, 20-21, 60-62 year periods) is found to well reconstruct the observed climate oscillations from 1850 to 2011, and it is shown to be 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 synchronous to solar and heliospheric planetary oscillations. We show that the IPCC GCM's claim that all warming observed from 1970 to 2000 has been anthropogenically induced is erroneous because of the GCM failure in reconstructing the quasi 20-year and 60-year climatic cycles. Finally, we show how the presence of these large natural cycles can be used to correct the IPCC projected anthropogenic warming trend for the 21st century. By combining this corrected trend with the natural cycles, we show that the temperature may not significantly increase during the next 30 years mostly because of the negative phase of the 60-year cycle. If multisecular natural cycles (which according to some authors have significantly contributed to the observed 1700-2010 warming and may contribute to an

  16. 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.

  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. Climate model boundary conditions for four Cretaceous time slices

    Directory of Open Access Journals (Sweden)

    J. O. Sewall

    2007-06-01

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

  19. Climate model boundary conditions for four Cretaceous time slices

    Directory of Open Access Journals (Sweden)

    J. O. Sewall

    2007-11-01

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

  20. 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: ...

  1. 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.

  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. Assessing the links between Greenland Ice Sheet Surface Mass Balance and Arctic climate using Climate Models and Observations

    Science.gov (United States)

    Mottram, Ruth; Rodehacke, Christian; Boberg, Fredrik; Langen, Peter; Sloth Madsen, Marianne; Høyer Svendsen, Synne; Yang, Shuting; Hesselbjerg Christensen, Jens; Olesen, Martin

    2016-04-01

    Changes in different parts of the Arctic cryosphere may have knock-on effects on other parts of the system. The fully coupled climate model EC-Earth, which includes the ice sheet model PISM, is a useful tool to examine interactions between sea ice, ice sheet, ocean and atmosphere. Here we present results from EC-Earth experimental simulations that show including an interactive ice sheet model changes ocean circulation, sea ice extent and regional climate with, for example, a dampening of the expected increase in Arctic temperatures under the RCP scenarios when compared with uncoupled experiments. However, the relatively coarse resolution of the climate model likely influences the calculated surface mass balance forcing applied to the ice sheet model and it is important therefore to evaluate the model performance over the ice sheet. Here, we assess the quality of the climate forcing from the GCM to the ice sheet model by comparing the energy balance and surface mass balance (SMB) output from EC-Earth with that from a regional climate model (RCM) run at very high resolution (0.05 degrees) over Greenland. The RCM, HIRHAM5, has been evaluated over a wide range of climate parameters for Greenland which allows us to be confident it gives a representative climate forcing for the Greenland ice sheet. To evaluate the internal variability in the climate forcing, we compare simulations from HIRHAM5 forced with both the EC-Earth historical emissions and the ERA-Interim reanalysis on the boundaries. The EC-Earth-PISM RCP8.5 scenario is also compared with an EC-Earth run without an ice sheet to assess the impact of an interactive ice sheet on likely future changes. To account for the resolution difference between the models we downscale both EC-Earth and HIRHAM5 simulations with a simple offline energy balance model (EBM).

  4. 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...

  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. 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.

  7. Precambrian evolution of the climate system.

    Science.gov (United States)

    Walker, J C

    1990-01-01

    Climate is an important environmental parameter of the early Earth, likely to have affected the origin and evolution of life, the composition and mineralogy of sedimentary rocks, and stable isotope ratios in sedimentary minerals. There is little observational evidence constraining Precambrian climates. Most of our knowledge is at present theoretical. Factors that must have affected the climate include reduced solar luminosity, enhanced rotation rate of the Earth, an area of land that probably increased with time, and biological evolution, particularly as it affected the composition of the atmosphere and the greenhouse effect. Cloud cover is a major uncertainty about the early Earth. Carbon dioxide and its greenhouse effect are the factors that have been most extensively studied. This paper presents a new examination of the biogeochemical cycles of carbon as they may have changed between an Archean Earth deficient in land, sedimentary rocks, and biological activity, and a Proterozoic Earth much like the modern Earth, but lacking terrestrial life and carbonate-secreting plankton. Results of a numerical simulation of this transition show how increasing biological activity could have drawn down atmospheric carbon dioxide by extracting sedimentary organic carbon from the system. Increasing area of continents could further have drawn down carbon dioxide by encouraging the accumulation of carbonate sediments. An attempt to develop a numerical simulation of the carbon cycles of the Precambrian raises questions about sources and sinks of marine carbon and alkalinity on a world without continents. More information is needed about sea-floor weathering processes.

  8. 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

  9. 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

  10. 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.

  11. Regional climate simulations over Vietnam using the WRF model

    Science.gov (United States)

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

    2016-10-01

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

  12. 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.

  13. 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

  14. 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

  15. 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

  16. 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

  17. On the importance of observational data properties when assessing regional climate model performance of extreme precipitation

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Sørup, Hjalte Jomo Danielsen; Christensen, Ole Bøssing;

    2013-01-01

    . In the majority of such studies the characteristics and uncertainties of the observational data are neglected. This study addresses the influence of using different observational datasets to assess the climate model performance. Four different datasets covering Denmark using different gauge systems and comprising......In recent years, there has been an increase in the number of climate studies addressing changes in extreme precipitation. A common step in these studies involves the assessment of the climate model performance. This is often measured by comparing climate model output with observational data...

  18. The ATOMMS Radio Occultation Climate Remote Sensing System

    Science.gov (United States)

    Kursinski, E. R.; Otarola, A. C.; Ward, D.; McGhee, J.; Reed, H.; Walden, L.

    2012-12-01

    Increasingly complex computer models approximate the climate system and make predictions about how climate will change. In order to make informed decisions about what to do about climate change, one must know how trustworthy these predictions are. Assessing the accuracy of the models and their predictions can only come from comparing models with observations of the real climate. Therefore, we must have observations that precisely and unambiguously determine the state of the climate system, and they must do so independently from the atmospheric models they are being compared against. While this is a very basic point of logic, it is quite difficult to achieve in practice because of the difficulties and limitations of the observations. For this purpose we have been developing a new orbiting remote sensing system called the Active Temperature, Ozone and Moisture Microwave Spectrometer (ATOMMS) that is a cross between GPS radio occultation and the Microwave Limb Sounder (MLS). Unlike GPS which uses wavelengths that minimize interaction with the atmosphere, ATOMMS actively probes water vapor and other absorption lines at cm and mm wavelengths in an occultation geometry to simultaneously profile temperature and water vapor. During each occultation, ATOMMS measures the changes in signal amplitude and frequency caused by passage through the atmosphere relative to the amplitude and frequency measured less than 100 seconds earlier when the signal path was above the atmosphere. As such, the ATOMMS observations are inherently self-calibrating. Furthermore, unlike the inherently ambiguous and non-unique atmospheric profiles retrieved from thermal radiance measurements, the atmospheric profiles retrieved from occultations are unique. The expected accuracy of individual ATOMMS profiles of water vapor, temperature and pressure heights is approximately 1%, 0.4K and 10 m respectively with 200 m or better vertical resolution. Performance in cloudy areas will be within a factor of 2 of

  19. 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.

  20. 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/).

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

    Science.gov (United States)

    Rugenstein, M.; Knutti, R.

    2015-12-01

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

  2. 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.

  3. Climate Modeling: Ocean Cavities below Ice Shelves

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-09-12

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

  4. 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.

  5. A bio-economic farm household model to assess cropping systems in the Rift valley of Ethiopia : towards climate smart agriculture: do food security and mitigration goals match?

    NARCIS (Netherlands)

    Hengsdijk, H.; Verhagen, A.

    2012-01-01

    Modelling approach for rain fed farm household systems in the Central Rif Valley of Ethiopia to assess the possible effects of intensification of cereal-based cropping systems to farm income, mitigation of GHG emissions and other household indicators

  6. 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

  7. Empirical correction of a toy climate model

    CERN Document Server

    Allgaier, Nicholas A; Danforth, Christopher M

    2011-01-01

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

  8. Impact of climate Change on Groundwater Recharge in the Tiber River Basin (Central Italy) Using Regional Climate model Outputs

    Science.gov (United States)

    Muluneh, F. B.; Setegn, S. G.; Melesse, A. M.; Fiori, A.

    2011-12-01

    Quantification of the various components of hydrological processes in a watershed remains a challenging topic as the hydrological system is altered by many internal and external drivers. Changes in climate variables can affect the quantity and quality of various components of hydrological cycle. Among others, the local effects of climate change on groundwater resources were not fully studied in different part of the world as compared to the surface water. Moreover, understanding the potential impact of climate change on groundwater is more complex than surface water. The main objective of this study is to analyze the potential impact of climate change on Groundwater recharge in the Tiber River Basin using outputs from Regional Climate model. In this study, a physically-based watershed model called Soil Water Assessment Tool (SWAT) was used to estimate recharge characteristics and its response to climate change in Tiber River Basin (central Italy). The SWAT model was successfully calibrated and validated using observed weather and flow data for the period of 1963-1970 and 1971-1978 respectively. During calibration, the model was highly sensitivity to groundwater flow parameters. Dynamically downscaled rainfall and temperature datasets from ten Regional Climate Models (RCM) archived in 'Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects (PRUDENCE)' were used to force the model to assess the climate change impact on the study area. A quantile-mapping statistical correction procedure was applied to the RCM dataset to correct the inherent systematic biases. The climate change analysis indicated that by the end of 2080s the rainfall was found to decrease nearly up to 40% in dry period and there was an increase in temperature that could reach as high as 3 to 5 oC. By the end of 2080s the ground water recharge shows a decreasing trend as a response to changes in rainfall. However as the timing of both precipitation and

  9. 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.

  10. 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

  11. 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.

  12. Time scale interaction in low-order climate models

    NARCIS (Netherlands)

    Veen, Lennaert van

    2002-01-01

    Over the last decades, the study of climate variability has attracted ample attention. The observation of structural climatic change has led to questions about the causes and the mechanisms involved. The task to understand interactions in the complex climate system is particularly di±cult because of

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

    Directory of Open Access Journals (Sweden)

    Claas Teichmann

    2013-06-01

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

  14. 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.

  15. Climate modelling: IPCC gazes into the future

    Science.gov (United States)

    Raper, Sarah

    2012-04-01

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

  16. Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

    Science.gov (United States)

    Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

    2016-01-01

    We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

  17. Hybrid Surface Mesh Adaptation for Climate Modeling

    Institute of Scientific and Technical Information of China (English)

    Ahmed Khamayseh; Valmor de Almeida; Glen Hansen

    2008-01-01

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

  18. On a minimal model for estimating climate sensitivity

    OpenAIRE

    Cawley, G.C.; Cowtan, K.; Way, R.G.; Jacobs, P.; Jokimäki, A.

    2015-01-01

    In a recent issue of this journal, Loehle (2014) presents a "minimal model" for estimating climate sensitivity, identical to that previously published by Loehle and Scafetta (2011). The novelty in the more recent paper lies in the straightforward calculation of an estimate of transient climate response based on the model and an estimate of equilibrium climate sensitivity derived therefrom, via a flawed methodology. We demonstrate that the Loehle and Scafetta model systematically underestimate...

  19. 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.

  20. Measure the climate, model the city

    NARCIS (Netherlands)

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

    2011-01-01

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

  1. 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.

  2. 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.

  3. 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.

  4. 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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  6. 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

  7. 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

  8. Climate and land use change impacts on global terrestrial ecosystems, fire, and river flows in the HadGEM2-ES Earth System Model using the Representative Concentration Pathways

    Directory of Open Access Journals (Sweden)

    R. A. Betts

    2013-04-01

    Full Text Available A new generation of an Earth System Model now includes a number of land surface processes directly relevant to analyzing potential impacts of climate change. This model, HadGEM2-ES, allows us to assess the impacts of climate change, multiple interactions, and feedbacks as the model is run. This paper discusses the results of century-scale HadGEM2-ES simulations from an impacts perspective–specifically, terrestrial ecosystems and water resources–for four different scenarios following the Representative Concentration Pathways (RCPs, being used for next assessment report of the Intergovernmental Panel on Climate Change (IPCC. Over the 21st Century, simulated changes in global and continential-scale terrestrial ecosystems due to climate change appear to be very similar in all 4 RCPs, even though the level of global warming by the end of the 21st Century ranges from 2 °C in the lowest scenario to 5.5° in the highest. A warming climate generally favours broadleaf trees over needleleaf, needleleaf trees over shrubs, and shrubs over herbaceous vegetation, resulting in a poleward shift of temperate and boreal forests and woody tundra in all scenarios. Although climate related changes are slightly larger in scenarios of greater warming, the largest differences between scenarios arise at regional scales as a consequence of different patterns of anthropogenic land cover change. In the model, the scenario with the lowest global warming results in the most extensive decline in tropical forest cover due to a large expansion of agriculture. Under all four RCPs, fire potential could increase across extensive land areas, particularly tropical and sub-tropical latitudes. River outflows are simulated to increase with higher levels of CO2 and global warming in all projections, with outflow increasing with mean temperature at the end of the 21st Century at the global scale and in North America, Asia, and Africa. In South America, Europe, and Australia, the

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

    Science.gov (United States)

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

    2015-04-01

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

  10. 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.

  11. 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.

  12. 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.

  13. 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...

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

    Science.gov (United States)

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

    2015-04-01

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

  15. 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.

  16. 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%.

  17. 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 forc...

  18. 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

  19. 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,...

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

    Directory of Open Access Journals (Sweden)

    K. Steffens

    2013-08-01

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

  1. 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.

  2. Modelling and (adaptive) control of greenhouse climates

    NARCIS (Netherlands)

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.System conceptsIn Chapters 1 and 2 an overview of the problem formulation is presented. It is suggested that there

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Predictive modelling of climate suitability for Pinus halepensis in Spain

    OpenAIRE

    Gastón González, Aitor; Garcia Viñas, Juan Ignacio

    2010-01-01

    The response of Mediterranean pine species distribution to global change is a key feature of forest management in a changing environment. Climate suitability models are valuable tools for understanding and anticipating the effects of climate change on species distributions. Logistic regression was used to model climate suitability for Pinus halepensis in Spain, using National Forest Inventory as training sample. Predictive performance was evaluated using ICP Forests Level I grid as independen...

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

    Science.gov (United States)

    Zhang, Xianliang; Yan, Xiaodong

    2016-05-01

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

  9. A new framework for climate sensitivity and prediction: a modelling perspective

    Science.gov (United States)

    Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank

    2016-03-01

    The sensitivity of climate models to increasing CO2 concentration and the climate response at decadal time-scales are still major factors of uncertainty for the assessment of the long and short term effects of anthropogenic climate change. While the relative slow progress on these issues is partly due to the inherent inaccuracies of numerical climate models, this also hints at the need for stronger theoretical foundations to the problem of studying climate sensitivity and performing climate change predictions with numerical models. Here we demonstrate that it is possible to use Ruelle's response theory to predict the impact of an arbitrary CO2 forcing scenario on the global surface temperature of a general circulation model. Response theory puts the concept of climate sensitivity on firm theoretical grounds, and addresses rigorously the problem of predictability at different time-scales. Conceptually, these results show that performing climate change experiments with general circulation models is a well defined problem from a physical and mathematical point of view. Practically, these results show that considering one single CO2 forcing scenario is enough to construct operators able to predict the response of climatic observables to any other CO2 forcing scenario, without the need to perform additional numerical simulations. We also introduce a general relationship between climate sensitivity and climate response at different time scales, thus providing an explicit definition of the inertia of the system at different time scales. This technique allows also for studying systematically, for a large variety of forcing scenarios, the time horizon at which the climate change signal (in an ensemble sense) becomes statistically significant. While what we report here refers to the linear response, the general theory allows for treating nonlinear effects as well. These results pave the way for redesigning and interpreting climate change experiments from a radically new

  10. Biosphere modeling with climate changes for safety assessment of high-level radioactive waste geological isolation

    International Nuclear Information System (INIS)

    In the safety assessment of a high-level radioactive waste (HLW) disposal system, it is required to estimate radiological impacts on future human beings arising from potential radionuclide releases from a deep repository into the surface environment. In order to estimate the impacts, a biosphere model is developed by reasonably assuming radionuclide migration processes in the surface environment and relevant human lifestyles. Releases from the repository might not occur for many thousands of years after disposal. Over such timescales, it is anticipated that the considerable climatic change, for example, induced by the next glaciation period expected to occur in