WorldWideScience

Sample records for climate models

  1. 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...

  2. Climate models and scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Fortelius, C.; Holopainen, E.; Kaurola, J.; Ruosteenoja, K.; Raeisaenen, J. [Helsinki Univ. (Finland). Dept. of Meteorology

    1996-12-31

    In recent years the modelling of interannual climate variability has been studied, the atmospheric energy and water cycles, and climate simulations with the ECHAM3 model. In addition, the climate simulations of several models have been compared with special emphasis in the area of northern Europe

  3. 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

  4. Modelling Interglacial Climate

    DEFF Research Database (Denmark)

    Pedersen, Rasmus Anker

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

  5. Climate modeling at Manitoba Hydro

    International Nuclear Information System (INIS)

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

  6. 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.

  7. 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...

  8. 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.

  9. 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...

  10. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

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

  11. 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

  12. 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…

  13. 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...

  14. 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".

  15. 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:

  16. 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

  17. 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.

  18. 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.

  19. Likelihood-Based Climate Model Evaluation

    Science.gov (United States)

    Braverman, Amy; Cressie, Noel; Teixeira, Joao

    2012-01-01

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

  20. Uncertainty Quantification in Climate Modeling

    Science.gov (United States)

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

    2011-12-01

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

  1. A National Strategy for Advancing Climate Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Dunlea, Edward; Elfring, Chris

    2012-12-04

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

  2. Essays on Economic Modeling of Climate Change

    OpenAIRE

    Engström, Gustav

    2012-01-01

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

  3. 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

  4. 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...

  5. 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...

  6. Mediterranean climate modelling: variability and climate change scenarios

    International Nuclear Information System (INIS)

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

  7. 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

  8. 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.''

  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. Evaluating models of climate and forest vegetation

    Science.gov (United States)

    Clark, James S.

    1992-01-01

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

  11. Validating predictions from climate envelope models.

    Science.gov (United States)

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

    2013-01-01

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

  12. 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

  13. 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.

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    T. O. Sonnenborg

    2015-04-01

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

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

    Science.gov (United States)

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

    2015-09-01

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

  17. 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.

  18. Ionospheric climate and weather modeling

    International Nuclear Information System (INIS)

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

  19. 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 (...

  20. 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...

  1. Modelling rainfall erosion resulting from climate change

    Science.gov (United States)

    Kinnell, Peter

    2016-04-01

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

  2. 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.

  3. On coupling global biome models with climate models

    International Nuclear Information System (INIS)

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

  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. 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.

  6. 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.

  7. Mapping model agreement on future climate projections

    Science.gov (United States)

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

    2011-12-01

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

  8. The Community Climate System Model, Version 2.

    Science.gov (United States)

    Kiehl, Jeffrey T.; Gent, Peter R.

    2004-10-01

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

  9. Utilizing Cloud Computing to Improve Climate Modeling and Studies

    Science.gov (United States)

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

    2013-12-01

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

  10. 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...

  11. 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.)

  12. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

    1990-12-01

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

  14. The Software Architecture of Global Climate Models

    Science.gov (United States)

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

    2011-12-01

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

  15. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

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

    2013-12-01

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

  16. Global comparison of three greenhouse climate models

    OpenAIRE

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

    1985-01-01

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

  17. 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.

  18. A Practical Philosophy of Complex Climate Modelling

    Science.gov (United States)

    Schmidt, Gavin A.; Sherwood, Steven

    2014-01-01

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

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

    OpenAIRE

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2011-12-01

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

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

    OpenAIRE

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

    2008-01-01

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

  2. 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.

  3. 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

  4. Uncertain climate change in an intergenerational planning model

    International Nuclear Information System (INIS)

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

  5. Climate Modeling with a Linux Cluster

    Science.gov (United States)

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

    2004-08-01

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

  6. 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.)

  7. Climate change policymaking: Three explanatory models

    OpenAIRE

    Bang, Guri

    2000-01-01

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

  8. Modelling Complexity: the case of Climate Science

    OpenAIRE

    Lucarini, Valerio

    2011-01-01

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

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

    Science.gov (United States)

    Anisimov, O.

    2003-04-01

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

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

    OpenAIRE

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

    2001-01-01

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

  11. 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...

  12. 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

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

    International Nuclear Information System (INIS)

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

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

    OpenAIRE

    Döll, Sebastian

    2009-01-01

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

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

    DEFF Research Database (Denmark)

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

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

  16. 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.

  17. 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

  18. Modelling the hydrological cycle in assessments of climate change

    Science.gov (United States)

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

    1992-01-01

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

  19. 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

  20. 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)

  1. 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.

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

    OpenAIRE

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

    2012-01-01

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

  3. Challenges in combining projections from multiple climate models

    OpenAIRE

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

    2010-01-01

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

  4. Modelling precipitation extremes in climate change scenarios

    Czech Academy of Sciences Publication Activity Database

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

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

  5. Mixing parameterizations in ocean climate modeling

    Science.gov (United States)

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

    2016-03-01

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

  6. 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

  7. 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.

  8. 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

  9. Selection of climate change scenario data for impact modelling

    DEFF Research Database (Denmark)

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

    2012-01-01

    illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make...... the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented...... in this paper, applied to relative humidity, but it could be adopted to other variables if needed....

  10. 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/).

  11. 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.

  12. 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).

  13. 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.

  14. 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

  15. Organizational Diversity Climate: Review of Models and Measurement

    OpenAIRE

    Goyal, Saumya; Shrivastava, Dr.Sangya

    2013-01-01

    As organizational climate represents the culture of an organization, similarly diversity climate represents the culture of diversity and inclusion of an organization. Every best practice in diversity management and diversity initiatives and programs are essentially implemented in order to improve the overall organizational diversity climate. Various models exist in literature which illustrates how diversity climate of a company impacts various employee and organizational measures. Over the ye...

  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. 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.

  18. 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

  19. 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.

  20. Linking Output from regional Climat Models with Cryosphere Models

    Science.gov (United States)

    Winter, S.

    2003-04-01

    This study has the objective of linking the results of a low-resolution regional climate model (RCM) with high-resolution cryosphere models in order to determine the manner in which Alpine snow, ice and permafrost is likely to respond to enhanced atmospheric warming resulting from an increase in anthropogenic greenhouse gases. There are several constraints that need to be overcome prior to applying solutions to this problem. Firstly, as a result of the long response time of glaciers and alpine permafrost to climate change, long-term simulations of at least 30 years are required. Secondly, the smallest possible spatial resolution of current RCM still remains quite coarse (~ 50 km) because of the complex mathematical equations to be resolved in the RCM, the limited computer performance and the above mentioned long simulation period. On the other hand, cryosphere models used in the present study require gridded input climate variables with a typical mesh width of 50 m. The proposed solution consists in combining climate change data based on RCM scenarios with meteorological data of high elevation Alpine stations measured during a reference period. A RCM control run matching this reference period is required in order to quantify the expected change for each climate parameter. This approach allows breaking down the initial downscaling problem into two separate steps. First, the quantified change derived from RCM-control and scenario simulations is used to predict change for meteorological stations. Second, data sets of predicted change and meteorological measures of these stations are summed and then regionalized for the study area based on advanced algorithms and GIS techniques. Selecting a case study area close to one or more meteorological stations should minimize the associated regionalization error. A pilot study for a small area at Piz Corvatsch in the Eastern Swiss Alps has been designed. The A2 scenario of the IPCC (Intergovernmental Panel on Climate Change

  1. 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

  2. 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.

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

    Science.gov (United States)

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

    2010-12-01

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

  4. Climate Modeling with a Million CPUs

    Science.gov (United States)

    Tobis, M.; Jackson, C. S.

    2010-12-01

    Michael Tobis, Ph.D. Research Scientist Associate University of Texas Institute for Geophysics Charles S. Jackson Research Scientist University of Texas Institute for Geophysics Meteorological, oceanographic, and climatological applications have been at the forefront of scientific computing since its inception. The trend toward ever larger and more capable computing installations is unabated. However, much of the increase in capacity is accompanied by an increase in parallelism and a concomitant increase in complexity. An increase of at least four additional orders of magnitude in the computational power of scientific platforms is anticipated. It is unclear how individual climate simulations can continue to make effective use of the largest platforms. Conversion of existing community codes to higher resolution, or to more complex phenomenology, or both, presents daunting design and validation challenges. Our alternative approach is to use the expected resources to run very large ensembles of simulations of modest size, rather than to await the emergence of very large simulations. We are already doing this in exploring the parameter space of existing models using the Multiple Very Fast Simulated Annealing algorithm, which was developed for seismic imaging. Our experiments have the dual intentions of tuning the model and identifying ranges of parameter uncertainty. Our approach is less strongly constrained by the dimensionality of the parameter space than are competing methods. Nevertheless, scaling up remains costly. Much could be achieved by increasing the dimensionality of the search and adding complexity to the search algorithms. Such ensemble approaches scale naturally to very large platforms. Extensions of the approach are anticipated. For example, structurally different models can be tuned to comparable effectiveness. This can provide an objective test for which there is no realistic precedent with smaller computations. We find ourselves inventing new code to

  5. 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

  6. 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.

  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. 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.

  9. 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...

  10. THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE

    Science.gov (United States)

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

    2015-01-01

    Background: The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran’s universities. Methods: This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran’s public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. Results: of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran’s libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Conclusions: Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries. PMID:26622203

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

    Science.gov (United States)

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

    2013-10-28

    Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4. PMID:24043872

  12. Storm Water Management Model Climate Adjustment Tool (SWMM-CAT)

    Science.gov (United States)

    The US EPA’s newest tool, the Stormwater Management Model (SWMM) – Climate Adjustment Tool (CAT) is meant to help municipal stormwater utilities better address potential climate change impacts affecting their operations. SWMM, first released in 1971, models hydrology and hydrauli...

  13. Arctic Climate Change Analysed By Two 30-year Scenario Regional Climate Model Runs

    Science.gov (United States)

    Kiilsholm, S.; Christensen, J. H.

    High-resolution climate change simulations for an area covering the entire Arctic have been conducted with the regional climate model (RCM) HIRHAM. The emission sce- narios used were the IPCC SRES1 marker scenarios A2 and B2. Three 30-year time slice experiments were conducted with HIRHAM for periods representing present-day (1961-1990) and the future (2071-2100) in the two scenarios. Changes of the climate between these two periods will be presented with special emphasize on the climate of Greenland.

  14. Extreme precipitation and climate gradients in Patagonia revealed by high-resolution regional atmospheric climate modeling

    NARCIS (Netherlands)

    Lenaerts, J.T.M.; van den Broeke, M.R.; van Wessem, J.M.; van de Berg, W.J.; van Meijgaard, E.; van Ulft, L.H.; Schaefer, M.

    2014-01-01

    This study uses output of a high-resolution (5.5 km) regional atmospheric climate model to describe the present-day (1979–2012) climate of Patagonia, with a particular focus on the surface mass balance (SMB) of the Patagonian ice fields. Through a comparison with available in situ observations, it i

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

    Czech Academy of Sciences Publication Activity Database

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

    2014-01-01

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

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

    KAUST Repository

    Merlis, Timothy M.

    2014-10-01

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

  17. Evaluation of global climate models for Indian monsoon climatology

    International Nuclear Information System (INIS)

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

  18. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Luxmoore, R.J. [Oak Ridge National Lab., TN (United States); Baldocchi, D.D. [National Oceanic and Atmospheric Administration, Oak Ridge, TN (United States)

    1994-09-01

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

  20. Enhancements to modeling regional climate response and global variability; FINAL

    International Nuclear Information System (INIS)

    Efforts during this grant period focused on three main considerations: (a) developing and testing various climate scenarios with SEAM, a newly created model (b) model reconstruction efforts to speed up computations and (c) optimum realization statistics

  1. Modeling key processes causing climate change and variability

    Energy Technology Data Exchange (ETDEWEB)

    Henriksson, S.

    2013-09-01

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

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

    International Nuclear Information System (INIS)

    Article 4.1(F) of the Framework Convention on Climate Change commits all parties to take climate change considerations into account, to the extent feasible, in relevant social, economic and environmental policies and actions and to employ methods such as impact assessments to minimize adverse effects of climate change. This could be achieved by, inter alia, incorporating climate change risk assessment into development planning processes, i.e. relating climatic change to issues of habitability and sustainability. Adaptation is an ubiquitous and beneficial natural and human strategy. Future adaptation (adjustment) to climate is inevitable at the least to decrease the vulnerability to current climatic impacts. An urgent issue is the mismatch between the predictions of global climatic change and the need for information on local to regional change in order to develop adaptation strategies. Mitigation efforts are essential since the more successful mitigation activities are, the less need there will be for adaptation responses. And, mitigation responses can be global (e.g. a uniform percentage reduction in greenhouse gas emissions) while adaptation responses will be local to regional in character and therefore depend upon confident predictions of regional climatic change. The dilemma facing policymakers is that scientists have considerable confidence in likely global climatic changes but virtually zero confidence in regional changes. Mitigation and adaptation strategies relevant to climatic change can most usefully be developed in the context of sound understanding of climate, especially the near-surface continental climate, permitting discussion of societally relevant issues. But, climate models can't yet deliver this type of regionally and locationally specific prediction and some aspects of current research even seem to indicate increased uncertainty. These topics are explored in this paper using the specific example of the prediction of land-surface climate changes

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

    International Nuclear Information System (INIS)

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

  4. Regionalization of climate model results for the North Sea

    Energy Technology Data Exchange (ETDEWEB)

    Kauker, F.

    1999-07-01

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

  5. DIY the Integrated Climate Model and its computational performance

    OpenAIRE

    Wang, Pengfei

    2014-01-01

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

  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. The Urgent Need for Improved Climate Models and Predictions

    Science.gov (United States)

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

    2009-09-01

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

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

    Science.gov (United States)

    Semenov, M. A.

    2009-04-01

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

  9. Statistical Properties of Downscaled CMIP3 Global Climate Model Simulations

    Science.gov (United States)

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

    2009-12-01

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

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

    International Nuclear Information System (INIS)

    Described here is the formulation of the CASA' biogeochemistry model of Fung, et al., which has recently been coupled to the Community Land Model Version 3 (CLM3) and the Community Climate System Model Version 3 (CCSM3). This model is presently being used for Coupled Climate/Carbon Cycle Model Intercomparison Project (C4MIP) Phase 1 experiments. In addition, CASA' is one of three models - in addition to CN (Thornton, et al.) and IBIS (Thompson, et al.) - that are being run within CCSM to investigate their suitability for use in climate change predictions in a future version of CCSM. All of these biogeochemistry experiments are being performed on the Computational Climate Science End Station (Dr. Warren Washington, Principle Investigator) at the National Center for Computational Sciences at Oak Ridge National Laboratory

  11. Agricultural climate impacts assessment for economic modeling and decision support

    Science.gov (United States)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  12. Analysing climate impact on energy demand using the MOLAND model

    OpenAIRE

    Liu, Xiaochen; Twumasi, Bright Osei

    2008-01-01

    The importance and contribution of climate to energy demand are discussed. A linear regression model is developed to analyse future energy demand corresponding to climate change. The methodology for spatial analysis and integration to MOLAND are also provided in order to investigate possible consequences of different urban development paths on energy consumption patterns.

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

    NARCIS (Netherlands)

    Dellink, R.B.

    2011-01-01

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

  14. Detecting Warming Hiatus Periods in CMIP5 Climate Model Projections

    OpenAIRE

    Li, Tony W.; Baker, Noel C.

    2016-01-01

    The observed slow-down in the global-mean surface temperature (GST) warming from 1998 to 2012 has been called a “warming hiatus.” Certain climate models, operating under experiments which simulate warming by increasing radiative forcing, have been shown to reproduce periods which resemble the observed hiatus. The present study provides a comprehensive analysis of 38 CMIP5 climate models to provide further evidence that models produce warming hiatus periods during warming experiments. GST rate...

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    Joseph Leedale

    2016-03-01

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

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

    Science.gov (United States)

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

    2011-12-01

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

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

    International Nuclear Information System (INIS)

    A climate model is developed on the basis of the two-level Mintz-Arakawa general circulation model of the atmosphere and a bulk model of the upper layer of the ocean. A detailed model of the spectral transport of shortwave and longwave radiation is used to investigate the radiative effects of greenhouse gases. The radiative fluxes are calculated at the boundaries of five layers, each with a pressure thickness of about 200 mb. The results of the climate sensitivity calculations for mean-annual and perpetual seasonal regimes are discussed. The CCAS (Computer Center of the Academy of Sciences) climate model is used to investigate the climatic effects of anthropogenic changes of the optical properties of the atmosphere due to increasing CO2 content and aerosol pollution, and to calculate the sensitivity to changes of land surface albedo and humidity

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

    Science.gov (United States)

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

    2008-10-01

    We present revised probability density functions for climate model parameters (effective climate sensitivity, the rate of deep-ocean heat uptake, and the strength of the net aerosol forcing) that are based on climate change observations from the 20th century. First, we compare observed changes in surface, upper-air, and deep-ocean temperature changes against simulations of 20th century climate in which the climate model parameters were systematically varied. The estimated 90% range of effective climate sensitivity is 2-5 K but no corresponding upper bound can be placed on the equilibrium climate sensitivity. The net aerosol forcing strength for the 1980s has 90% bounds of -0.70 to -0.27 Wm-2. The rate of deep-ocean heat uptake corresponds to an effective diffusivity, Kv, with a 90% range of 0.04-4.1 cm2s-1. Second, we estimate the effective climate sensitivity and rate of deep-ocean heat uptake for 11 of the IPCC AR4 AOGCMs. By comparing against the acceptable combinations inferred from the observations, we conclude that the rates of deep-ocean heat uptake for the majority of AOGCMs lie above the observationally based median value. This implies a bias in the predictions inferred from the IPCC models alone.

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

    Energy Technology Data Exchange (ETDEWEB)

    Forest, Chris E.; Stone, Peter H.; Sokolov, Andrei P. (Massachusetts Inst. of Technology, Cambridge, MA 02139 (United States)). e-mail: ceforest@mit.edu

    2008-07-01

    We present revised probability density functions for climate model parameters (effective climate sensitivity, the rate of deep-ocean heat uptake, and the strength of the net aerosol forcing) that are based on climate change observations from the 20th century. First, we compare observed changes in surface, upper-air, and deep-ocean temperature changes against simulations of 20th century climate in which the climate model parameters were systematically varied. The estimated 90% range of effective climate sensitivity is 2-5 K but no corresponding upper bound can be placed on the equilibrium climate sensitivity. The net aerosol forcing strength for the 1980s has 90% bounds of -0.70 to -0.27 W/m2. The rate of deep-ocean heat uptake corresponds to an effective diffusivity, Kv , with a 90% range of 0.04-4.1 cm2/s. Second, we estimate the effective climate sensitivity and rate of deep-ocean heat uptake for 11 of the IPCC AR4 AOGCMs. By comparing against the acceptable combinations inferred from the observations, we conclude that the rates of deep-ocean heat uptake for the majority of AOGCMs lie above the observationally based median value. This implies a bias in the predictions inferred from the IPCC models alone

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

    Energy Technology Data Exchange (ETDEWEB)

    Forest, Chris E.; Stone, Peter H.; Sokolov, Andrei P. (Massachusetts Inst. of Technology, Cambridge, MA 02139 (US)). e-mail: ceforest@mit.edu

    2008-07-01

    We present revised probability density functions for climate model parameters (effective climate sensitivity, the rate of deep-ocean heat uptake, and the strength of the net aerosol forcing) that are based on climate change observations from the 20th century. First, we compare observed changes in surface, upper-air, and deep-ocean temperature changes against simulations of 20th century climate in which the climate model parameters were systematically varied. The estimated 90% range of effective climate sensitivity is 2-5 K but no corresponding upper bound can be placed on the equilibrium climate sensitivity. The net aerosol forcing strength for the 1980s has 90% bounds of -0.70 to -0.27 W/m2. The rate of deep-ocean heat uptake corresponds to an effective diffusivity, K_v , with a 90% range of 0.04-4.1 cm2/s. Second, we estimate the effective climate sensitivity and rate of deep-ocean heat uptake for 11 of the IPCC AR4 AOGCMs. By comparing against the acceptable combinations inferred from the observations, we conclude that the rates of deep-ocean heat uptake for the majority of AOGCMs lie above the observationally based median value. This implies a bias in the predictions inferred from the IPCC models alone

  2. Combining Global Climate Model Outputs and Insights from Downscaling for Australian Climate Projections

    Science.gov (United States)

    Grose, M. R.; Timbal, B.; Katzfey, J. J.; Moise, A. F.; Eksrtrom, M.; Whetton, P.

    2013-12-01

    Dynamical and statistical downscaling of global climate model (GCM) outputs has the potential to provide valuable insights when making regional climate projections. It may reveal regional detail in the projected climate change signal through higher resolution and accounting for local influences such as topography and coastlines. However, climate change adaptation research and planning desires a coherent view of possible future climate that accounts for the various sources of uncertainty and at a relevant spatial scale. This means there is value in combining the most useful insights from all available downscaling with a more comprehensive set of designed global climate model (GCM) projections (e.g. the CMIP5 archive), and this is done for the next set of national climate projections products in Australia. There are several practical considerations in this process that affect the process, primarily because downscaling is done using various disparate methods for a limited set of models and scenarios. There is no objective framework to combine different sets of ad hoc downscaling simulations with a set of GCMs, so some degree of expert judgment is used. We emphasize cases where there is the most apparent ';added value' and report these insights in complement, and in some cases in preference to, GCM projections. Confidence in such insights first requires understanding of what input data is used from the host model, what biases are reduced and what new biases are potentially introduced. We then seek an understanding of how the climate change signal differs from that of the host model, and an attribution of the cause of this difference. Several case studies within Australia are discussed.

  3. Emulation of MIROC5 with a simple climate model

    Science.gov (United States)

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

    2014-05-01

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

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

    Science.gov (United States)

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

    2016-04-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1994-05-01

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

  6. 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.

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    M. Eby

    2012-08-01

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

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

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

    Science.gov (United States)

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

    2009-12-01

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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  11. A probabilistic model of ecosystem response to climate change

    International Nuclear Information System (INIS)

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

  12. Simulation of convective and stratiform precipitation in regional climate models

    Czech Academy of Sciences Publication Activity Database

    Rulfová, Zuzana; Kyselý, Jan

    Washington: Association of American Geographers, 2014. [AAG Annual Meeting /59./. 08.04.2014-12.04.2014, Tampa] Institutional support: RVO:68378289 Keywords : climate model * convective precipitation * stratiform precipitation * Central Europe Subject RIV: DG - Athmosphere Sciences, Meteorology

  13. California Basin Characterization Model Downscaled Climate and Hydrology

    Data.gov (United States)

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

  14. Future extreme events in European climate: an exploration of regional climate model projections

    OpenAIRE

    Beniston, Martin; Stephenson, David B.; Christensen, Ole B.; Ferro, Christopher A. T.; Frei, Christoph; Goyette, Stéphane; Halsnaes, Kirsten; Holt, Tom; Jylhä, Kirsti; Koffi, Brigitte; Palutikof, Jean; Schöll, Regina; Semmler, Tido; Woth, Katja

    2007-01-01

    This paper presents an overview of changes in the extreme events that are most likely to affect Europe in forthcoming decades. A variety of diagnostic methods are used to determine how heat waves, heavy precipitation, drought, wind storms, and storm surges change between present (1961–90) and future (2071–2100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves – Regional surface warming causes the fre...

  15. 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...

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

    Science.gov (United States)

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

    2016-01-01

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

  17. Climate simulations for 1880-2003 with GISS modelE

    CERN Document Server

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

    2006-01-01

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

  18. 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

  19. 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.

  20. Verification of regional climate models over the territory of Ukraine

    Science.gov (United States)

    Krakovska, S.; Palamarchuk, L.; Shedemenko, I.; Djukel, G.; Gnatjuk, N.

    2009-04-01

    Verification of regional climate models (RCMs) over the territory of Ukraine was the first stage of the National project for assessment of possible climate change and its impact on the economic and social life in Ukraine in XXI century. Since Ukraine has pretty different climates in different parts, the territory of Ukraine was divided on 11 regions with more or less uniform climate conditions: 7 almost equal in space regions in plain terrain, 2 - in coastal zones near the Black and Azov seas and 2 - in the Carpathian and the Crimean mountains. Verification of RCMs for climate characteristics was carried out for each defined region separately. Data of meteorological network in Ukraine (187 stations) and the Climate Research Unit (CRU 10-min global data-set) for multy-year monthly, season and annual means of temperature and precipitation for the period 1961-90 were used for verification of models' results. Two RCMs were used in the analysis of the past climate of Ukraine: REMO (MPI-M, Hamburg) and RegCM3 (ICTP, Trieste). Both models were constructed with initial and boundary conditions from ERA-40 data-set with horizontal spacing of ~25 km and vertically 27 (REMO) and 18 (RegCM3) Z-σ levels. In a whole, both models demonstrated better ability for temperature than precipitation characteristics. Very high correlation of 0.9 was found between models, network and CRU for temperatures and 0.7-0.8 for precipitation. Generally, models were warmer especially for summer months up to 2 oC. More precipitation in the models was found for winter season and less - for summer and in the mountainous subregions comparably with observations. In perspective we intend to run RCMs initialized with GCMs for the same period and for XXI century and account for the obtained systematic models' errors in the analysis of possible climate change over the territory of Ukraine.

  1. 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.

  2. Links between atmospheric circulation and surface air temperature in climate models in control climate and future scenarios

    Czech Academy of Sciences Publication Activity Database

    Plavcová, Eva; Kyselý, Jan

    Bern: Swiss Climate Research, 2011, s. 84-85. [International NCCR Climate Summer School "Climate Change, Extremes and Ecosystem Services" /10./. Grindelwald (CH), 04.09.2001-09.09.2011] R&D Projects: GA ČR GAP209/10/2265 Institutional research plan: CEZ:AV0Z30420517 Keywords : regional climate models * air temperature * atmospheric circulation * future climate change scenarios Subject RIV: DG - Athmosphere Sciences, Meteorology

  3. 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.

  4. Multi-model assessment of water scarcity under climate change

    Science.gov (United States)

    Schewe, J.; Heinke, J.; Gerten, D.; Haddeland, I.; Arnell, N. W.; Clark, D. B.; Dankers, R.; Eisner, S.; Fekete, B. M.; Colon-Gonzalez, F. J.; Gosling, S. N.; KIM, H.; Liu, X.; Masaki, Y.; Portmann, F. T.; Satoh, Y.; Stacke, T.; Tang, Q.; Wada, Y.; Wisser, D.; albrecht, T.; Frieler, K.; Piontek, F.; Warszawski, L.; Kabat, P.

    2013-12-01

    Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. In the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) we use a large ensemble of global hydrological models (GHMs) forced by five global climate models (GCMs) and the latest greenhouse--gas concentration scenarios (RCPs) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that up to a global warming of 2°C above present (approx. 2.7°C above pre--industrial), each additional degree of warming will confront an additional approx. 7% of the global population with a severe decrease in water resources; and that climate change will increase the number of people living under absolute water scarcity (five global climate models (GCMs). Color hues show the multi-model mean change, and saturation shows the agreement on the sign of change across all GHM-GCM combinations (percentage of model runs agreeing on the sign).

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

    Science.gov (United States)

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

    2013-04-01

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

  6. 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

  7. 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

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

    Institute of Scientific and Technical Information of China (English)

    郑益群; 于革; 王苏民; 薛滨; 刘华强; 曾新民

    2003-01-01

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

  9. Planetary boundary layer energetics simulated from a regional climate model over Europe for present climate and climate change conditions

    Science.gov (United States)

    Sánchez, E.; Yagüe, C.; Gaertner, M. A.

    2007-01-01

    This paper presents a description of the planetary boundary layer (PBL) for current (1960-1990) and future (2070-2100) climate periods as obtained from a regional climate model (RCM) centered on the Mediterranean basin. Vertically integrated turbulent kinetic energy (TKEZ) and boundary layer height (z i ) are used to describe PBL energetics. Present climate shows a TKEZ annual cycle with a clear summer maximum for southern regions, while northern regions of Europe exhibit a smoother or even a lack of cycle. Future climate conditions exhibit a similar behaviour, with an increase in the summer maximum peaks. A detailed analysis of summer surface climate change energetics over land shows an increased Bowen ratio and decreases in the evaporative fraction. The enhanced sensible heat flux responsible for these results causes an energy surplus inside the PBL, resulting in increased convective activity and corresponding TKEZ. These results are consistent with temperature increases obtained by several other model simulations, and also indicate that changes in the turbulent transport from the PBL to the free troposphere can affect atmospheric circulations.

  10. Climate-methane cycle feedback in global climate model model simulations forced by RCP scenarios

    Science.gov (United States)

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

    2013-04-01

    Methane cycle module of the global climate model of intermediate complexity developed at the A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS CM) is extended by coupling with a detailed module for thermal and hydrological processes in soil (Deep Soil Simulator, (Arzhanov et al., 2008)). This is an important improvement with respect with the earlier IAP RAS CM version (Eliseev et al., 2008) which has employed prescribed soil hydrology to simulate CH4 emissions from soil. Geographical distribution of water inundated soil in the model was also improved by replacing the older Olson's ecosystem data base by the data based on the SCIAMACHY retrievals (Bergamaschi et al., 2007). New version of the IAP RAS CM module for methane emissions from soil is validated by using the simulation protocol adopted in the WETCHIMP (Wetland and Wetland CH4 Inter-comparison of Models Project). In addition, atmospheric part of the IAP RAS CM methane cycle is extended by temperature dependence of the methane life-time in the atmosphere in order to mimic the respective dependence of the atmospheric methane chemistry (Denisov et al., 2012). The IAP RAS CM simulations are performed for the 18th-21st centuries according with the CMIP5 protocol taking into account natural and anthropogenic forcings. The new IAP RAS CM version realistically reproduces pre-industrial and present-day characteristics of the global methane cycle including CH4 concentration qCH4 in the atmosphere and CH4 emissions from soil. The latter amounts 150 - 160 TgCH4-yr for the late 20th century and increases to 170 - 230 TgCH4-yr in the late 21st century. Atmospheric methane concentration equals 3900 ppbv under the most aggressive anthropogenic scenario RCP 8.5 and 1850 - 1980 ppbv under more moderate scenarios RCP 6.0 and RCP 4.5. Under the least aggressive scenario RCP 2.6 qCH4 reaches maximum 1730 ppbv in 2020s and declines afterwards. Climate change impact on the methane emissions from

  11. 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

  12. Coastal Ecosystems and Climate Change: Is Modeling and Monitoring Enough?

    Science.gov (United States)

    Cronin, T. M.; Walker, H. A.

    2005-05-01

    Many coastal ecosystems are severely degraded due to a variety of human factors, requiring large and expensive monitoring and modeling efforts for restoration and management. Climate variability, including abrupt climate change, is seldom factored into coastal ecosystem management despite growing evidence for climate forcing of precipitation, river discharge, water quality, salinity, turbidity, faunal and phytoplankton dynamics, dissolved oxygen, and other ecosystem processes. We will review evidence from long-term monitoring records, multi-proxy paleoclimatic and paleoecological records, and climatic modeling that suggests that the effects of climate can override local and regional human activities and may potentially diminish the success of restoration efforts. Because ecosystem restoration often involves long-term objectives requiring decades to achieve, our focus will be on examples from sub-tropical and temperate estuaries in North America that show ecosystem response over decadal timescales to variability related to El Niño-Southern Oscillation, the Pacific Decadal Oscillation and the North Atlantic Oscillation. Climatic variability evident from paleo-records of the past few centuries exceeds that recorded in most 20th century monitoring records. This raises issues about the efficacy of local and regional ecosystem and hydrodynamic models designed to simulate ecosystem response to anthropogenic changes in sediment and nutrient input, fresh-water discharge, and land-use because such models, though tested with rigorous validation procedures, use calibration data sets limited to a few years. Thus, they might not be appropriate for simulating response to climatic extremes on the scale and duration of past events outside their calibration range. Understanding the complexities of ecosystem response to climatic forcing, especially in the context of local and regional ecosystem disturbance, raises formidable challenges, but attempts to integrate climate

  13. 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

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

    International Nuclear Information System (INIS)

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

  15. Exploitation of parallelism in climate models. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Baer, Ferdinand; Tribbia, Joseph J.; Williamson, David L.

    2001-02-05

    This final report includes details on the research accomplished by the grant entitled 'Exploitation of Parallelism in Climate Models' to the University of Maryland. The purpose of the grant was to shed light on (a) how to reconfigure the atmospheric prediction equations such that the time iteration process could be compressed by use of MPP architecture; (b) how to develop local subgrid scale models which can provide time and space dependent parameterization for a state-of-the-art climate model to minimize the scale resolution necessary for a climate model, and to utilize MPP capability to simultaneously integrate those subgrid models and their statistics; and (c) how to capitalize on the MPP architecture to study the inherent ensemble nature of the climate problem. In the process of addressing these issues, we created parallel algorithms with spectral accuracy; we developed a process for concurrent climate simulations; we established suitable model reconstructions to speed up computation; we identified and tested optimum realization statistics; we undertook a number of parameterization studies to better understand model physics; and we studied the impact of subgrid scale motions and their parameterization in atmospheric models.

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

    Institute of Scientific and Technical Information of China (English)

    Hyuntaik Oh; Ho-Jeong Shin

    2016-01-01

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

  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. Performance of climate envelope models in retrodicting recent changes in bird population size from observed climatic change

    OpenAIRE

    Green, Rhys E.; Collingham, Yvonne C.; Willis, Stephen G; Gregory, Richard D; Smith, Ken W.; Huntley, Brian

    2008-01-01

    Twenty-five-year population trends of 42 bird species rare as breeders in the UK were examined in relation to changes in climatic suitability simulated using climatic envelope models. The effects of a series of potential ‘nuisance’ variables were also assessed. A statistically significant positive correlation was found across species between population trend and climate suitability trend. The demonstration that climate envelope models are able to retrodict species' population trends provides ...

  19. 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.

  20. The origins of computer weather prediction and climate modeling

    International Nuclear Information System (INIS)

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

  1. The transferability of hydrological models under nonstationary climatic conditions

    Directory of Open Access Journals (Sweden)

    C. Z. Li

    2012-04-01

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

  2. Do bioclimate variables improve performance of climate envelope models?

    Science.gov (United States)

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

    2012-01-01

    Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

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

    Science.gov (United States)

    Hunt, B. G.

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

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and...... continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures...

  5. Dynamically combining climate models to "supermodel" the tropical Pacific

    Science.gov (United States)

    Shen, Mao-Lin; Keenlyside, Noel; Selten, Frank; Wiegerinck, Wim; Duane, Gregory S.

    2016-01-01

    We construct an interactive ensemble of two different climate models to improve simulation of key aspects of tropical Pacific climate. Our so-called supermodel is based on two atmospheric general circulation models (AGCMs) coupled to a single ocean GCM, which is driven by a weighted average of the air-sea fluxes. Optimal weights are determined using a machine learning algorithm to minimize sea surface temperature errors over the tropical Pacific. This coupling strategy synchronizes atmospheric variability in the two AGCMs over the equatorial Pacific, where it improves the representation of ocean-atmosphere interaction and the climate state. In particular, the common double Intertropical Convergence Zone error is suppressed, and the positive Bjerknes feedback improves substantially to match observations well, and the negative heat flux feedback is also much improved. This study supports the concept of supermodeling as a promising multimodel ensemble strategy to improve weather and climate predictions.

  6. Isotopes as validation tools for global climate models

    International Nuclear Information System (INIS)

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

  7. Multi-model drought estimation using regional climate model output

    Science.gov (United States)

    McCabe, M. F.; Sung, B.; Evans, J. P.; Sheffield, J.

    2012-12-01

    Drought is a recurring climatic phenomenon in Australia and many other regions of the world. Apart from the considerable social and health repercussions that widespread drought has at a community level, there are major implications to the landscape, economy and water resources sectors. One of the key outputs in drought characterisation is determining the degree, extent and severity of the actual drought. However, there exist a range of techniques to quantify drought (each with its own definition) that adds to the level of uncertainty in accurate estimation. To examine the range and variability in multi-model drought prediction, a study of drought characteristics is undertaken, focusing on one of Australia's most significant agricultural regions: the Murray Darling Basin (MDB). Common drought indices including the Reconnaissance Drought Index (RDI), Standard Runoff Index (SRI), Soil Moisture Percentiles (SMP) and Palmer Drought Severity Index (PDSI) were derived using output from a high resolution regional climate simulation of the MDB for the period from 1985 to 2008. Spatial and temporal analyses were conducted by comparing these indices across regional scales. A severity-area-duration analysis and drought clustering approach were also used to characterize the extent and severity of these events across south-eastern Australia. Overall it was found that the four drought indices responded similarly to precipitation anomalies and successfully captured the major droughts over the nearly 25 years of simulation. The recent Australian drought from 2002-2008 was the most severe as shown by various analyses. Indeed, the Murray Darling Basin experienced contiguous moderate to extreme drought conditions for long periods, covering almost 100% of both the Darling and Murray Basins. Analysis of results also showed that the duration of droughts varied greatly between indices, as drought assessments using soil moisture parameters tended to recover in response to precipitation at

  8. Model biases in rice phenology under warmer climates

    Science.gov (United States)

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

    2016-06-01

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

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

    OpenAIRE

    Lan, Zhanggui; Li, Guanghai; Liand, Yulian; Yand, Yuhong; Li, Xiaoping

    2014-01-01

    According to spatial distribution of climate disasters in Nanning City and physiological and ecological indicator demands of sugarcane, with the aid of HJ-1 CCD satellite remote sensing images, basic meteorological data and geographic information data, this paper established the model for predicting climatic yield of sugarcane in Nanning City, to predict total yield of sugarcane in Nanning City. Results indicated that the distribution of sugarcane in Nanning City is greatly influenced by drou...

  10. Induced innovation in a decentralized model of climate change

    OpenAIRE

    Jérémy Laurent-Lucchetti; Andrew Leach

    2006-01-01

    We propose a model of climate change consistent with four principal stylized facts. First, the benefits and costs of climate change mitigation policies are not evenly distributed across generations. Second, capital accumulation is not determined jointly with emissions policy, but rather as a choice made by self-interested economic agents. Third, most research and development activity in the energy sector is undertaken by private firms. Fourth, significant imperfections exist in the market for...

  11. Partnership Models for Climate Compatible Development: Experiences from Zambia

    OpenAIRE

    Dyer, Jen; Leventon, Julia; Stringer, Lindsay; Dougill, Andrew; Syampungani, Stephen; Nshimbi, Muleba; Chama, Francis; Kafwifwi, Ackson

    2013-01-01

    Partnership working is necessary to allow nations to harness the evolving opportunities presented by climate finance and to progress towards climate compatible development (CCD). However, the new multi-stakeholder partnerships being formed and the factors affecting their outcomes remain poorly understood. This paper aims to identify the characteristics of partnership models that can lead to successful delivery of CCD projects by analyzing case study data from two projects in Zambia. The proje...

  12. THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE

    OpenAIRE

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

    2015-01-01

    Background: The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran’s universities. Methods: This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran’s public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For pr...

  13. 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.

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

    OpenAIRE

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

    2011-01-01

    More accurate simulation of the energy and water balance near the Earth surface is important to improve the performance of regional climate models. We used a detailed ecohydrological model to rank the importance of vegetation and soil factors with respect to evapotranspiration modeling. The results show that type of lower boundary condition, root zone depth, and temporal course of leaf area index have the strongest effect on yearly and monthly evapotranspiration. Soil texture data from the WI...

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

    Energy Technology Data Exchange (ETDEWEB)

    Lohmann,U.; Schwartz, S. E.

    2008-03-02

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

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

    Science.gov (United States)

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

    2016-06-01

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

  17. 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.

  18. A review on regional convection permitting climate modeling

    Science.gov (United States)

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

    2016-04-01

    With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using CPMs to study climate change it is necessary that these deficiencies are addressed in future research. Coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and

  19. 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.

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

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

    OpenAIRE

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

    2015-01-01

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

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

    International Nuclear Information System (INIS)

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

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

    International Nuclear Information System (INIS)

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

  4. Reliability of regional climate model simulations of extremes and of long-term climate

    Directory of Open Access Journals (Sweden)

    U. Böhm

    2004-01-01

    Full Text Available We present two case studies that demonstrate how a common evaluation methodology can be used to assess the reliability of regional climate model simulations from different fields of research. In Case I, we focused on the agricultural yield loss risk for maize in Northeastern Brazil during a drought linked to an El-Niño event. In Case II, the present-day regional climatic conditions in Europe for a 10-year period are simulated. To comprehensively evaluate the model results for both kinds of investigations, we developed a general methodology. On its basis, we elaborated and implemented modules to assess the quality of model results using both advanced visualization techniques and statistical algorithms. Besides univariate approaches for individual near-surface parameters, we used multivariate statistics to investigate multiple near-surface parameters of interest together. For the latter case, we defined generalized quality measures to quantify the model's accuracy. Furthermore, we elaborated a diagnosis tool applicable for atmospheric variables to assess the model's accuracy in representing the physical processes above the surface under various aspects. By means of this evaluation approach, it could be demonstrated in Case Study I that the accuracy of the applied regional climate model resides at the same level as that we found for another regional model and a global model. Excessive precipitation during the rainy season in coastal regions could be identified as a major contribution leading to this result. In Case Study II, we also identified the accuracy of the investigated mean characteristics for near-surface temperature and precipitation to be comparable to another regional model. In this case, an artificial modulation of the used initial and boundary data during preprocessing could be identified as the major source of error in the simulation. Altogether, the achieved results for the presented investigations indicate the potential of our

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

    International Nuclear Information System (INIS)

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

  6. Climate Modeling in the Calculus and Differential Equations Classroom

    Science.gov (United States)

    Kose, Emek; Kunze, Jennifer

    2013-01-01

    Students in college-level mathematics classes can build the differential equations of an energy balance model of the Earth's climate themselves, from a basic understanding of the background science. Here we use variable albedo and qualitative analysis to find stable and unstable equilibria of such a model, providing a problem or perhaps a…

  7. 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.

  8. Assessment of the future climate change in the Czech Republic based on ALADIN-CLIMATE/CZ and AR4 models

    Science.gov (United States)

    Kalvova, J.; Holtanova, E.; Crhova, L.; Miksovsky, J.; Pisoft, P.; Motl, M.

    2010-09-01

    The regional climate model ALADIN-CLIMATE/CZ (25 km resolution) is going to be used for the new climate change scenarios for the Czech Republic. However, for effective use of such scenario for impact studies, it is necessary to provide an estimate of related uncertainty. The driving global model is an important source of uncertainty in RCM simulations. We present a comparison of changes in basic climate characteristics simulated by ALADIN-CLIMATE/CZ and a set of eight AR4 models for the periods of 2010-39, 2040-69, 2070-99. The global climate models were chosen based on its ability to simulate observed climate characteristics in the reference period (1961-1990).

  9. 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.

  10. Climate Change Policy: What Do the Models Tell Us?

    OpenAIRE

    Robert S. Pindyck

    2013-01-01

    Very little. A plethora of integrated assessment models (IAMs) have been constructed and used to estimate the social cost of carbon (SCC) and evaluate alternative abatement policies. These models have crucial flaws that make them close to useless as tools for policy analysis: certain inputs (e.g., the discount rate) are arbitrary, but have huge effects on the SCC estimates the models produce; the models' descriptions of the impact of climate change are completely ad hoc, with no theoretical o...

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

    Science.gov (United States)

    Soliman, E.; Jeuland, M.

    2009-04-01

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

  12. Modelling of diurnal cycle under climate change

    Energy Technology Data Exchange (ETDEWEB)

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

    1995-12-31

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

  13. High Resolution Modelling of Crop Response to Climate Change

    Science.gov (United States)

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

    2014-12-01

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

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

    OpenAIRE

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

    2016-01-01

    As the most recent warm period in Earth’s history with a sea-level stand higher than present, the Last Interglacial period (~130 to 115 kyr BP) is often considered a prime example to study the impact of a warmer climate on the two polar ice sheets remaining today. Here we simulate the Last Interglacial climate, ice sheet and sea-level evolution with the Earth system model of intermediate complexity LOVECLIM v.1.3, which includes dynamic and fully-coupled components representing...

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

    Czech Academy of Sciences Publication Activity Database

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

    2011-01-01

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

  16. 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.

  17. Use and interpretation of climate envelope models: a practical guide

    Science.gov (United States)

    Watling, James I.; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.

    2013-01-01

    This guidebook is intended to provide a practical overview of climate envelope modeling for conservation professionals and natural resource managers. The material is intended for people with little background or experience in climate envelope modeling who want to better understand and interpret models developed by others and the results generated by such models, or want to do some modeling themselves. This is not an exhaustive review of climate envelope modeling, but rather a brief introduction to some key concepts in the discipline. Readers interested in a more in-depth treatment of much of the material presented here are referred to an excellent book, Mapping Species Distributions: Spatial Inference and Prediction by Janet Franklin. Also, a recent review (Araújo & Peterson 2012) provides an excellent, though more technical, discussion of many of the issues dealt with here. Here we treat selected topics from a practical perspective, using minimal jargon to explain and illustrate some of the many issues that one has to be aware of when using climate envelope models. When we do introduce specialized terminology in the guidebook, we bold the term when it is first used; a glossary of these terms is included at the back of the guidebook.

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

    Science.gov (United States)

    Teranes, J. L.

    2008-12-01

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

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

    DEFF Research Database (Denmark)

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

    2007-01-01

    regions of Holland, Germany and Denmark, in particular. These results are found to depend to different degrees on model formulation. While the responses of heat waves are robust to model formulation, the magnitudes of changes in precipitation and wind speed are sensitive to the choice of regional model......This paper presents an overview of changes in the extreme events that are most likely to affect Europe in forthcoming decades. A variety of diagnostic methods are used to determine how heat waves, heavy precipitation, drought, wind storms, and storm surges change between present (1961......-90) and future (2071-2 100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves - Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first...

  20. A Simple Climate Model Program for High School Education

    Science.gov (United States)

    Dommenget, D.

    2012-04-01

    The future climate change projections of the IPCC AR4 are based on GCM simulations, which give a distinct global warming pattern, with an arctic winter amplification, an equilibrium land sea contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the IPCC predictions, the conceptual understanding of these predicted structures of climate change are very difficult to reach if only based on these highly complex GCM simulations and they are not accessible for ordinary people. In this study presented here we will introduce a very simple gridded globally resolved energy balance model based on strongly simplified physical processes, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the 1-dimensional energy balance models and the fully coupled 4-dimensional complex GCMs. It runs on standard PC computers computing globally resolved climate simulation with 2yrs per second or 100,000yrs per day. The program can compute typical global warming scenarios in a few minutes on a standard PC. The computer code is only 730 line long with very simple formulations that high school students should be able to understand. The simple model's climate sensitivity and the spatial structure of the warming pattern is within the uncertainties of the IPCC AR4 models simulations. It is capable of simulating the arctic winter amplification, the equilibrium land sea contrast and the inter-hemispheric warming gradient with good agreement to the IPCC AR4 models in amplitude and structure. The program can be used to do sensitivity studies in which students can change something (e.g. reduce the solar radiation, take away the clouds or make snow black) and see how it effects the climate or the climate response to changes in greenhouse gases. This program is available for every one and could be the basis for high school education. Partners for a high school project are wanted!

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

    Institute of Scientific and Technical Information of China (English)

    高学杰; 罗勇; 林万涛; 赵宗慈; FilippoGIORGI

    2003-01-01

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

  2. Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models

    Science.gov (United States)

    Drijfhout, Sybren; Bathiany, Sebastian; Beaulieu, Claudie; Brovkin, Victor; Claussen, Martin; Huntingford, Chris; Scheffer, Marten; Sgubin, Giovanni; Swingedouw, Didier

    2015-10-01

    Abrupt transitions of regional climate in response to the gradual rise in atmospheric greenhouse gas concentrations are notoriously difficult to foresee. However, such events could be particularly challenging in view of the capacity required for society and ecosystems to adapt to them. We present, to our knowledge, the first systematic screening of the massive climate model ensemble informing the recent Intergovernmental Panel on Climate Change report, and reveal evidence of 37 forced regional abrupt changes in the ocean, sea ice, snow cover, permafrost, and terrestrial biosphere that arise after a certain global temperature increase. Eighteen out of 37 events occur for global warming levels of less than 2°, a threshold sometimes presented as a safe limit. Although most models predict one or more such events, any specific occurrence typically appears in only a few models. We find no compelling evidence for a general relation between the overall number of abrupt shifts and the level of global warming. However, we do note that abrupt changes in ocean circulation occur more often for moderate warming (less than 2°), whereas over land they occur more often for warming larger than 2°. Using a basic proportion test, however, we find that the number of abrupt shifts identified in Representative Concentration Pathway (RCP) 8.5 scenarios is significantly larger than in other scenarios of lower radiative forcing. This suggests the potential for a gradual trend of destabilization of the climate with respect to such shifts, due to increasing global mean temperature change.

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

    Science.gov (United States)

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

    2013-08-01

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

  4. An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models

    Science.gov (United States)

    David E. Rupp

    2016-01-01

    The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.

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

    Science.gov (United States)

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

    1988-01-01

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

  6. 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.

  7. Recursive inter-generational utility in global climate risk modeling

    Energy Technology Data Exchange (ETDEWEB)

    Minh, Ha-Duong [Centre International de Recherche sur l' Environnement et le Developpement (CIRED-CNRS), 75 - Paris (France); Treich, N. [Institut National de Recherches Agronomiques (INRA-LEERNA), 31 - Toulouse (France)

    2003-07-01

    This paper distinguishes relative risk aversion and resistance to inter-temporal substitution in climate risk modeling. Stochastic recursive preferences are introduced in a stylized numeric climate-economy model using preliminary IPCC 1998 scenarios. It shows that higher risk aversion increases the optimal carbon tax. Higher resistance to inter-temporal substitution alone has the same effect as increasing the discount rate, provided that the risk is not too large. We discuss implications of these findings for the debate upon discounting and sustainability under uncertainty. (author)

  8. The impact of ocean tides on a climate model simulation.

    OpenAIRE

    Müller, M; Haak, H.; J. Jungclaus; Maik Thomas;  ,

    2008-01-01

    We explicitly include the forcing of ocean tides in a global ocean general circulation model (OGCM). The tidal forcing is deduced from lunisolar ephemerides according to the instantaneous positions of moon and sun. In this real-time approach we consider the complete lunisolar tides of second degree. The OGCM is part of a state-of-the-art climate model which was used for the fourth assessment report simulations of the Intergovernmental Panel on Climate Change (IPCC). An ensemble of five IPCC A...

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

    Science.gov (United States)

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

    2015-09-01

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

  10. Climate Change and Groundwater: A Coupling of Models

    Science.gov (United States)

    Chesebrough, E.; Gorokhovich, Y.

    2012-12-01

    Groundwater is the largest source of readily available freshwater on our planet. Aquifers are vulnerable to climate change and require new groundwater management plans to account for changing precipitation patterns and sea level rise, among other factors. Atmospheric General Circulation Models (GCMs) use algorithms applied to historic and modern data to simulate current climatic conditions and predict future changes on a global scale. However, these GCMs are limited in their application at a regional level, thus making hydrogeological predictions difficult. Models designed specifically for hydrogeology are most commonly designed for regional assessment, and they can incorporate GCM outputs. Some of the challenges in coupling GCM outputs and hydrogeological models are the differences in spatial and temporal scales. In addition, the different scenarios of climate response to Greenhouse Gas forcings create a range of outputs from GCMs, affecting the predicting capacity of hydrogeological models. The use of dynamic and statistical downscaling of GCMs make it possible to overcome these challenges by taking the climate simulation output from GCMs and incorporating it as the input for hydrogeological models. This coupling of GCMs to groundwater models makes new groundwater management plans possible, which will ensure the sustainability of these resources in the future. The studies referenced within this paper highlight the advantages and disadvantages of various combinations of coupling and downscaling methodologies.

  11. Preparing local climate change scenarios for the Netherlands using resampling of climate model output

    International Nuclear Information System (INIS)

    A method to prepare a set of four climate scenarios for the Netherlands is presented. These scenarios for climate change in 2050 and 2085 (compared to present-day) are intended for general use in climate change adaptation in the Netherlands. An ensemble of eight simulations with the global model EC-Earth and the regional climate model RACMO2 (run at 12 km resolution) is used. For each scenario time horizon, two target values of the global mean temperature rise are chosen based on the spread in the CMIP5 simulations. Next, the corresponding time periods in the EC-Earth/RACMO2 simulations are selected in which these target values of the global temperature rise are reached. The model output for these periods is then resampled using blocks of 5 yr periods. The rationale of resampling is that natural variations in the EC-Earth/RACMO2 ensemble are used to represent (part of the) uncertainty in the CMIP5 projections. Samples are then chosen with the aim of reconstructing the spread in seasonal temperature and precipitation changes in CMIP5 for the Netherlands. These selected samples form the basis of the scenarios. The resulting four scenarios represent 50–80% of the CMIP5 spread for summer and winter changes in seasonal means as well as a limited number of monthly statistics (warm, cold, wet and dry months). The strong point of the method—also in relation to the previous set of the climate scenarios for the Netherlands issued in 2006—is that it preserves nearly all physical inter-variable consistencies as they exist in the original model output in both space and time. (paper)

  12. Natural climate variability in a coupled model

    International Nuclear Information System (INIS)

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

  13. Atmospheric Climate Model Experiments Performed at Multiple Horizontal Resolutions

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T; Bala, G; Gleckler, P; Lobell, D; Mirin, A; Maxwell, R; Rotman, D

    2007-12-21

    This report documents salient features of version 3.3 of the Community Atmosphere Model (CAM3.3) and of three climate simulations in which the resolution of its latitude-longitude grid was systematically increased. For all these simulations of global atmospheric climate during the period 1980-1999, observed monthly ocean surface temperatures and sea ice extents were prescribed according to standard Atmospheric Model Intercomparison Project (AMIP) values. These CAM3.3 resolution experiments served as control runs for subsequent simulations of the climatic effects of agricultural irrigation, the focus of a Laboratory Directed Research and Development (LDRD) project. The CAM3.3 model was able to replicate basic features of the historical climate, although biases in a number of atmospheric variables were evident. Increasing horizontal resolution also generally failed to ameliorate the large-scale errors in most of the climate variables that could be compared with observations. A notable exception was the simulation of precipitation, which incrementally improved with increasing resolution, especially in regions where orography plays a central role in determining the local hydroclimate.

  14. 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...

  15. 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

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

    Science.gov (United States)

    Somerville, R. C.

    2010-12-01

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

  17. 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

  18. Climate model response from the Geoengineering Model Intercomparison Project (GeoMIP)

    OpenAIRE

    Kravitz, B; Caldeira, K.; Boucher, O.; Robock, A.; P. Rasch; Alterskjær, K.; D. Karam; Cole, J.; Curry, C.; J. Haywood; Irvine, P; Ji, D.; Jones, A; Kristjánsson, J.; Lunt, D.

    2013-01-01

    Solar geoengineering - deliberate reduction in the amount of solar radiation retained by the Earth - has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform redu...

  19. 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...

  20. 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

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

    Directory of Open Access Journals (Sweden)

    Asma Foughali

    2015-07-01

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

  2. Appropriate Hydrological Modelling of Climate Change Impacts on River Flooding

    OpenAIRE

    Booij, M. J.; Rizzoli, A.E.; Jakeman, A. J.

    2002-01-01

    How good should a river basin model be to assess the impact of climate change on river flooding for a specific geographical area? The determination of such an appropriate model should reveal which physical processes should be incorporated and which data and mathematical process descriptions should be used at which spatial and temporal scales. A procedure for determining an appropriate model has been developed and applied to the above mentioned specific problem for the Meuse river in France, B...

  3. 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.)

  4. A validated physical model of greenhouse climate

    International Nuclear Information System (INIS)

    In the greenhouse model the momentaneous environmental crop growth factors are calculated as output, together with the physical behaviour of the crop. The boundary conditions for this model are the outside weather conditions; other inputs are the physical characteristics of the crop, of the greenhouse and of the control system. The greenhouse model is based on the energy, water vapour and CO2 balances of the crop-greenhouse system. While the emphasis is on the dynamic behaviour of the greenhouse for implementation in continuous optimization, the state variables temperature, water vapour pressure and carbondioxide concentration in the relevant greenhouse parts crop, air, soil and cover are calculated from the balances over these parts. To do this in a proper way, the physical exchange processes between the system parts have to be quantified first. Therefore the greenhouse model is constructed from submodels describing these processes: a. Radiation transmission model for the modification of the outside to the inside global radiation. b. Ventilation model to describe the ventilation exchange between greenhouse and outside air. c. The description of the exchange of energy and mass between the crop and the greenhouse air. d. Calculation of the thermal radiation exchange between the various greenhouse parts. e. Quantification of the convective exchange processes between the greenhouse air and respectively the cover, the heating pipes and the soil surface and between the cover and the outside air. f. Determination of the heat conduction in the soil. The various submodels are validated first and then the complete greenhouse model is verified

  5. Uncertainties and ensembles in global climate models: open issues with model dependence, performance, and robustness (Invited)

    Science.gov (United States)

    Knutti, R.; Tebaldi, C.

    2013-12-01

    Climate projections have often been summarized as multi model means, assuming that the average of models is better than a single model. Yet averaging models is problematic, because the models are not independent and share biases, and the models may not span the full uncertainty range. A model average can significantly underestimate the climate change signal if the changes are spatially heterogeneous. A seemingly obvious step is to select individual models based on how well they simulate the past and present climate. But metrics of model performance and model weighting is a thorny issue. The lack of verification of the actual climate projections means that we do not know, or cannot agree on which metrics are most relevant to identify a good model. An overview of recent coupled model intercomparisons is given along with a set of major challenges in interpreting them. It is shown that uncertainty in climate projections is difficult to quantify, and has not decreased significantly in the past few years, partly as a result of irreducible climate variability. Progress in model evaluation as well as statistical methods to interpret and combine model projections is urgently needed, in particular as more models of different quality and complexity, including perturbed physics ensembles and ensembles with structurally different models become available.

  6. Modeling impacts of climate change on freshwater availability in Africa

    Science.gov (United States)

    Faramarzi, Monireh; Abbaspour, Karim C.; Ashraf Vaghefi, Saeid; Farzaneh, Mohammad Reza; Zehnder, Alexander J. B.; Srinivasan, Raghavan; Yang, Hong

    2013-02-01

    SummaryThis study analyzes the impact of climate change on freshwater availability in Africa at the subbasin level for the period of 2020-2040. Future climate projections from five global circulation models (GCMs) under the four IPCC emission scenarios were fed into an existing SWAT hydrological model to project the impact on different components of water resources across the African continent. The GCMs have been downscaled based on observed data of Climate Research Unit to represent local climate conditions at 0.5° grid spatial resolution. The results show that for Africa as a whole, the mean total quantity of water resources is likely to increase. For individual subbasins and countries, variations are substantial. Although uncertainties are high in the simulated results, we found that in many regions/countries, most of the climate scenarios projected the same direction of changes in water resources, suggesting a relatively high confidence in the projections. The assessment of the number of dry days and the frequency of their occurrences suggests an increase in the drought events and their duration in the future. Overall, the dry regions have higher uncertainties than the wet regions in the projected impacts on water resources. This poses additional challenge to the agriculture in dry regions where water shortage is already severe while irrigation is expected to become more important to stabilize and increase food production.

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    J.-F. Lamarque

    2012-08-01

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

  9. Integration of climatic indices in an objective probabilistic model for establishing and mapping viticultural climatic zones in a region

    Science.gov (United States)

    Moral, Francisco J.; Rebollo, Francisco J.; Paniagua, Luis L.; García, Abelardo; Honorio, Fulgencio

    2016-05-01

    Different climatic indices have been proposed to determine the wine suitability in a region. Some of them are related to the air temperature, but the hydric component of climate should also be considered which, in turn, is influenced by the precipitation during the different stages of the grapevine growing and ripening periods. In this study, we propose using the information obtained from ten climatic indices [heliothermal index (HI), cool night index (CI), dryness index (DI), growing season temperature (GST), the Winkler index (WI), September mean thermal amplitude (MTA), annual precipitation (AP), precipitation during flowering (PDF), precipitation before flowering (PBF), and summer precipitation (SP)] as inputs in an objective and probabilistic model, the Rasch model, with the aim of integrating the individual effects of them, obtaining the climate data that summarize all main climatic indices, which could influence on wine suitability from a climate viewpoint, and utilizing the Rasch measures to generate homogeneous climatic zones. The use of the Rasch model to estimate viticultural climatic suitability constitutes a new application of great practical importance, enabling to rationally determine locations in a region where high viticultural potential exists and establishing a ranking of the climatic indices which exerts an important influence on wine suitability in a region. Furthermore, from the measures of viticultural climatic suitability at some locations, estimates can be computed using a geostatistical algorithm, and these estimates can be utilized to map viticultural climatic zones in a region. To illustrate the process, an application to Extremadura, southwestern Spain, is shown.

  10. US Climate Sensitivity Simulated with the NCEP Regional Spectral Model

    International Nuclear Information System (INIS)

    10-year continuous U.S. climate simulations were conducted with the Regional Spectral Model (RSM) using boundary conditions from the National Centers for Environmental Prediction/Dept. of Energy reanalyses and the global PCM (Parallel Climate Model) simulations for present day (1986-1996) and future (2040-2050) CO2 concentrations (about a 36% increased CO2). In order to examine the influence of physical parameterization differences as well as grid-resolution, fine resolution RSM simulations (50 km) were compared to coarse resolution (180 and 250 km) RSM simulations, which had resolutions comparable to the T62 reanalysis and PCM simulations. During the winter, the fine resolution RSM simulations provided more realistic detail over the western mountains. During the summer, large differences between the RSM and driving PCM simulations were found. Our results with present CO2 suggest that most of the differences between the regional climate model simulations and the climate simulations driven by the global model used to drive the regional climate model were not due to the finer resolution of the regional climate model but to the different treatment of the physical processes in the two models, especially when the subgrid scale physics was important, like during summer. Compared to the coarse resolution RSM simulation results, on the other hand, the fine resolution RSM simulations did show improved simulation skills especially when a good boundary condition such as the reanalysis was used to drive the RSM. Under increased CO2, the driving PCM and downscaled RSM simulations exhibited warming over all vertical layers and all regions. Both the RSM and PCM had increased precipitation during the winter, but during the summer, the PCM simulation had an overall precipitation increase mainly due to increased subgrid scale convective activity, whereas the RSM simulations exhibited precipitation decreases and the resulting RSM soil moisture became dryer, especially in the U

  11. 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

  12. Modelling mid-Pliocene climate with COSMOS

    Directory of Open Access Journals (Sweden)

    C. Stepanek

    2012-10-01

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

  13. 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.

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

    Science.gov (United States)

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

  15. Integrating Climate Model Data into Power System Planning

    OpenAIRE

    Chattopadhyay, Debabrata; Rhonda L. Jordan

    2015-01-01

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

  16. Modeling of Regional Climate over Red Sea and Arabian Peninsula

    KAUST Repository

    Stenchikov, Georgiy L.

    2011-04-09

    Observations, re-analyses, and climate model simulations show strong surface temperature trends in Middle East and Arabian Peninsula in the last 30 years. Trends are especially pronounced in summer exceeding +1K/decade. However, some regions, e.g., the So

  17. 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

  18. The Arctic Climate Modeling Program: Professional Development for Rural Teachers

    Science.gov (United States)

    Bertram, Kathryn Berry

    2010-01-01

    The Arctic Climate Modeling Program (ACMP) offered yearlong science, technology, engineering, and math (STEM) professional development to teachers in rural Alaska. Teacher training focused on introducing youth to workforce technologies used in Arctic research. Due to challenges in making professional development accessible to rural teachers, ACMP…

  19. Modelling climate change impacts on stream habitat conditions

    DEFF Research Database (Denmark)

    Boegh, Eva; Conallin, John; Karthikeyan, Matheswaran;

    , climate impacts on stream ecological conditions were quantified by combining a heat and mass stream flow with a habitat suitability modelling approach. Habitat suitability indices were developed for stream velocity, water depth, water temperature and substrate. Generally, water depth was found...

  20. Real-time multi-model decadal climate predictions

    NARCIS (Netherlands)

    Smith, D.M.; Scaife, A.A.; Boer, G.J.; Caian, M.; Doblas-Reyes, F.J.; Guemas, V.; Hawkins, E.; Hazeleger, W.; Hermanson, L.; Ho, C.K.; Ishii, M.; Kharin, V.; Kimoto, M.; Kirtman, B.; Lean, J.; Matei, D.; Merryfield, W.J.; Muller, W.A.; Pohlmann, H.; Rosati, A.; Wouters, B.; Wyser, K.

    2013-01-01

    We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus

  1. 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.

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

    OpenAIRE

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

    2011-01-01

    Coupled climate and carbon cycle modelling studies have shown that the feedback between global warming and the carbon cycle, in particular the terrestrial carbon cycle, could accelerate climate change and result in greater warming. In this paper we investigate the sensitivity of this feedback for year 2100 global warming in the range of 0 to 8 K. Differing climate sensitivities to increased CO2content are imposed on the carbon cycle models for the same emissions. Emissions from the SRES A2 sc...

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

    International Nuclear Information System (INIS)

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

  4. Radiative heating in global climate models

    Energy Technology Data Exchange (ETDEWEB)

    Baer, F.; Arsky, N.; Rocque, K. [Univ. of Maryland, College Park, MD (United States)

    1996-04-01

    LWR algorithms from various GCMs vary significantly from one another for the same clear sky input data. This variability becomes pronounced when clouds are included. We demonstrate this effect by intercomparing the various models` output using observed data including clouds from ARM/CART data taken in Oklahoma.

  5. 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

  6. Greenhouse climate model : an aid to estimate the influence of supplemental lighting on greenhouse climate

    OpenAIRE

    Binotto, Marco 1987

    2012-01-01

    GeoGreenhouse project involves the construction of a greenhouse for growing tomatoes in Iceland. The first stage consists of a gross area of five hectares. Due to the peculiarities of such project and because of the unique weather, a greenhouse climate model is advisable to analyze various design solutions. Iceland's weather has a seasonal change in the length of day and night, creating unique weather phenomena. In midwinter, there is a period where darkness prevails. In midsummer, dayligh...

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

    Science.gov (United States)

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

    2016-04-01

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

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

    Science.gov (United States)

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

    2014-01-01

    The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions. PMID:24518587

  9. Ensemble of regional climate model projections for Ireland

    Science.gov (United States)

    Nolan, Paul; McGrath, Ray

    2016-04-01

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

  10. Modelling recent and future climatic suitability for fasciolosis in Europe.

    Science.gov (United States)

    Caminade, Cyril; van Dijk, Jan; Baylis, Matthew; Williams, Diana

    2015-01-01

    Fasciola hepatica is a parasitic worm responsible for fasciolosis in grazed ruminants in Europe. The free-living stages of this parasite are sensitive to temperature and soil moisture, as are the intermediate snail hosts the parasite depends on for its life-cycle. We used a climate-driven disease model in order to assess the impact of recent and potential future climate changes on the incidence of fasciolosis and to estimate the related uncertainties at the scale of the European landmass. The current climate appears to be highly suitable for fasciolosis throughout the European Union with the exception of some parts of the Mediterranean region. Simulated climatic suitability for fasciolosis significantly increased during the 2000s in central and northwestern Europe, which is consistent with an observed increased in ruminant infections. The simulation showed that recent trends are likely to continue in the future with the estimated pattern of climate change for northern Europe, possibly extending the season suitable for development of the parasite in the environment by up to four months. For southern Europe, the simulated burden of disease may be lower, but the projected climate change will increase the risk during the winter months, since the simulated changes in temperature and moisture support the development of the free-living and intra-molluscan stages between November and March. In the event of predicted climate change, F. hepatica will present a serious risk to the health, welfare and productivity of all ruminant livestock. Improved, bespoke control programmes, both at farm and region levels, will then become imperative if problems, such as resistance of the parasite associated with increased drug use, are to be mitigated. PMID:25826311

  11. 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...

  12. A first appraisal of prognostic ocean DMS models and prospects for their use in climate models

    OpenAIRE

    Le Clainche, Y.; Vezina, A.; Levasseur, M; Cropp, R.; Gunson, J.; Vallina, S; M. Vogt; Lancelot, C.; Allen, J; Archer, S; Bopp, L.; Deal, C; Elliott, S.; Jin, M.; Malin, G

    2010-01-01

    Ocean dimethylsulfide (DMS) produced by marine biota is the largest natural source of atmospheric sulfur, playing a major role in the formation and evolution of aerosols, and consequently affecting climate. Several dynamic process-based DMS models have been developed over the last decade, and work is progressing integrating them into climate models. Here we report on the first international comparison exercise of both 1D and 3D prognostic ocean DMS models. Four global 3D models were compared ...

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

    Science.gov (United States)

    Knutti, R.

    2009-12-01

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

  14. Modelling impact of climate variability on rainfed groundnut

    OpenAIRE

    Gadgil, Sulochana; Rao, Seshagiri PR; Sridhar, S.

    1999-01-01

    We present here a heuristic model for the indirect impact of climate variability via the triggering of pests/diseases/weeds for rainfed groundnut over the Anantapur region. A simple hydrological model is used to determine the soil moisture for the rainfall pattern, in any given year. The criteria for determining when specific farming operations, such as ploughing and sowing, are performed are defined in terms of the soil moisture, on the basis of the farming practices in the region. With the ...

  15. Performance of ALADIN-Climate/CZ over the area of the Czech Republic in comparison with ENSEMBLES regional climate models

    Czech Academy of Sciences Publication Activity Database

    Crhová, L.; Holtanova, E.; Kalvová, J.; Farda, Aleš

    2014-01-01

    Roč. 58, č. 1 (2014), s. 148-169. ISSN 0039-3169 R&D Projects: GA MŽP(CZ) SP/1A6/108/07 Institutional support: RVO:67179843 Keywords : regional climate model * climate model performance * Taylor diagram * skill score Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.806, year: 2014

  16. Increase of Carbon Cycle Feedback with Climate Sensitivity: Results from a coupled Climate and Carbon Cycle Model

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-04-01

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

  17. Climate modelling of mass-extinction events: a review

    Science.gov (United States)

    Feulner, Georg

    2009-07-01

    Despite tremendous interest in the topic and decades of research, the origins of the major losses of biodiversity in the history of life on Earth remain elusive. A variety of possible causes for these mass-extinction events have been investigated, including impacts of asteroids or comets, large-scale volcanic eruptions, effects from changes in the distribution of continents caused by plate tectonics, and biological factors, to name but a few. Many of these suggested drivers involve or indeed require changes of Earth's climate, which then affect the biosphere of our planet, causing a global reduction in the diversity of biological species. It can be argued, therefore, that a detailed understanding of these climatic variations and their effects on ecosystems are prerequisites for a solution to the enigma of biological extinctions. Apart from investigations of the paleoclimate data of the time periods of mass extinctions, climate-modelling experiments should be able to shed some light on these dramatic events. Somewhat surprisingly, however, only a few comprehensive modelling studies of the climate changes associated with extinction events have been undertaken. These studies will be reviewed in this paper. Furthermore, the role of modelling in extinction research in general and suggestions for future research are discussed.

  18. 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

  19. 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.

  20. A Gaussian graphical model approach to climate networks

    International Nuclear Information System (INIS)

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

  1. 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.

  2. Climate and atmospheric modeling studies. Climate applications of Earth and planetary observations. Chemistry of Earth and environment

    Science.gov (United States)

    1990-01-01

    The research conducted during the past year in the climate and atmospheric modeling programs concentrated on the development of appropriate atmospheric and upper ocean models, and preliminary applications of these models. Principal models are a one-dimensional radiative-convective model, a three-dimensional global climate model, and an upper ocean model. Principal applications have been the study of the impact of CO2, aerosols and the solar 'constant' on climate. Progress was made in the 3-D model development towards physically realistic treatment of these processes. In particular, a map of soil classifications on 1 degree x 1 degree resolution has been digitized, and soil properties have been assigned to each soil type. Using this information about soil properties, a method was developed to simulate the hydraulic behavior of soils of the world. This improved treatment of soil hydrology, together with the seasonally varying vegetation cover, will provide a more realistic study of the role of the terrestrial biota in climate change. A new version of the climate model was created which follows the isotopes of water and sources of water (or colored water) throughout the planet. Each isotope or colored water source is a fraction of the climate model's water. It participates in condensation and surface evaporation at different fractionation rates and is transported by the dynamics. A major benefit of this project has been to improve the programming techniques and physical simulation of the water vapor budget of the climate model.

  3. 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

  4. Regional Climate Model Aladin-Climate - a Tool for Regionalization of Climate Change Estimates in Central Europe: First Results

    Czech Academy of Sciences Publication Activity Database

    Huth, Radan; Metelka, L.; Kliegerová, S.; Sedlák, Pavel; Kyselý, Jan; Mládek, R.; Halenka, T.; Kalvová, J.

    Bratislava: Geophysical Institute of SAS, Slovak Hydrometeorological Institute, Slovak Mining Society, Slovak Meteorological Society, 2001 - (Matejka, F.; Ostrožlík, M.), s. - ISBN 80-85754-10-X. [150 years of the meteorological service in central Europe. Stará Lesná (SK), 09.10.2001-11.10.2001] R&D Projects: GA ČR GA205/01/0804 Institutional research plan: CEZ:AV0Z3042911 Keywords : Regional Climate Model * validation * Central Europe Subject RIV: DG - Athmosphere Sciences, Meteorology

  5. 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

  6. Hydroclimatology of the Nile: results from a regional climate model

    Science.gov (United States)

    Mohamed, Y. A.; van den Hurk, B. J. J. M.; Savenije, H. H. G.; Bastiaanssen, W. G. M.

    2005-09-01

    This paper presents the result of the regional coupled climatic and hydrologic model of the Nile Basin. For the first time the interaction between the climatic processes and the hydrological processes on the land surface have been fully coupled. The hydrological model is driven by the rainfall and the energy available for evaporation generated in the climate model, and the runoff generated in the catchment is again routed over the wetlands of the Nile to supply moisture for atmospheric feedback. The results obtained are quite satisfactory given the extremely low runoff coefficients in the catchment. The paper presents the validation results over the sub-basins: Blue Nile, White Nile, Atbara river, the Sudd swamps, and the Main Nile for the period 1995 to 2000. Observational datasets were used to evaluate the model results including radiation, precipitation, runoff and evaporation data. The evaporation data were derived from satellite images over a major part of the Upper Nile. Limitations in both the observational data and the model are discussed. It is concluded that the model provides a sound representation of the regional water cycle over the Nile. The sources of atmospheric moisture to the basin, and location of convergence/divergence fields could be accurately illustrated. The model is used to describe the regional water cycle in the Nile basin in terms of atmospheric fluxes, land surface fluxes and land surface-climate feedbacks. The monthly moisture recycling ratio (i.e. locally generated/total precipitation) over the Nile varies between 8 and 14%, with an annual mean of 11%, which implies that 89% of the Nile water resources originates from outside the basin physical boundaries. The monthly precipitation efficiency varies between 12 and 53%, and the annual mean is 28%. The mean annual result of the Nile regional water cycle is compared to that of the Amazon and the Mississippi basins.

  7. Hydroclimatology of the Nile: results from a regional climate model

    Directory of Open Access Journals (Sweden)

    Y. A. Mohamed

    2005-01-01

    Full Text Available This paper presents the result of the regional coupled climatic and hydrologic model of the Nile Basin. For the first time the interaction between the climatic processes and the hydrological processes on the land surface have been fully coupled. The hydrological model is driven by the rainfall and the energy available for evaporation generated in the climate model, and the runoff generated in the catchment is again routed over the wetlands of the Nile to supply moisture for atmospheric feedback. The results obtained are quite satisfactory given the extremely low runoff coefficients in the catchment. The paper presents the validation results over the sub-basins: Blue Nile, White Nile, Atbara river, the Sudd swamps, and the Main Nile for the period 1995 to 2000. Observational datasets were used to evaluate the model results including radiation, precipitation, runoff and evaporation data. The evaporation data were derived from satellite images over a major part of the Upper Nile. Limitations in both the observational data and the model are discussed. It is concluded that the model provides a sound representation of the regional water cycle over the Nile. The sources of atmospheric moisture to the basin, and location of convergence/divergence fields could be accurately illustrated. The model is used to describe the regional water cycle in the Nile basin in terms of atmospheric fluxes, land surface fluxes and land surface-climate feedbacks. The monthly moisture recycling ratio (i.e. locally generated/total precipitation over the Nile varies between 8 and 14%, with an annual mean of 11%, which implies that 89% of the Nile water resources originates from outside the basin physical boundaries. The monthly precipitation efficiency varies between 12 and 53%, and the annual mean is 28%. The mean annual result of the Nile regional water cycle is compared to that of the Amazon and the Mississippi basins.

  8. Hydroclimatology of the Nile: results from a regional climate model

    Directory of Open Access Journals (Sweden)

    Y. A. Mohamed

    2005-02-01

    Full Text Available This paper is the result of the first regional coupled climatic and hydrologic model of the Nile. For the first time the interaction between the climatic processes and the hydrological processes on the land surface have been fully coupled. The hydrological model is driven by the rainfall and the energy available for evaporation generated in the climate model, and the runoff generated in the catchment is again routed over the wetlands of the Nile to supply moisture for atmospheric feedback. The results obtained are surprisingly accurate given the extremely low runoff coefficients in the catchment.

    The paper presents model results over the sub-basins: Blue Nile, White Nile, Atbara river and the Main Nile for the period 1995 to 2000, but focuses on the Sudd swamp. Limitations in both the observational data and the model are discussed. It is concluded that the model provides a sound representation of the regional water cycle over the Nile. The model is used to describe the regional water cycle in the Nile basin in terms of atmospheric fluxes, land surface fluxes and land surface-climate feedbacks. The monthly moisture recycling ratio (i.e. locally generated/total precipitation over the Nile varies between 8 and 14%, with an annual mean of 11%, which implies that 89% of the Nile water resources originates from outside the basin physical boundaries. The monthly precipitation efficiency varies between 12 and 53%, and the annual mean is 28%. The mean annual result of the Nile regional water cycle is compared to that of the Amazon and the Mississippi basins.

  9. Modelling impacts of climate change on arable crop diseases: progress, challenges and applications.

    Science.gov (United States)

    Newbery, Fay; Qi, Aiming; Fitt, Bruce Dl

    2016-08-01

    Combining climate change, crop growth and crop disease models to predict impacts of climate change on crop diseases can guide planning of climate change adaptation strategies to ensure future food security. This review summarises recent developments in modelling climate change impacts on crop diseases, emphasises some major challenges and highlights recent trends. The use of multi-model ensembles in climate change modelling and crop modelling is contributing towards measures of uncertainty in climate change impact projections but other aspects of uncertainty remain largely unexplored. Impact assessments are still concentrated on few crops and few diseases but are beginning to investigate arable crop disease dynamics at the landscape level. PMID:27471781

  10. 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.

  11. Climate stability and sensitivity in some simple conceptual models

    Science.gov (United States)

    Bates, J. Ray

    2012-02-01

    A theoretical investigation of climate stability and sensitivity is carried out using three simple linearized models based on the top-of-the-atmosphere energy budget. The simplest is the zero-dimensional model (ZDM) commonly used as a conceptual basis for climate sensitivity and feedback studies. The others are two-zone models with tropics and extratropics of equal area; in the first of these (Model A), the dynamical heat transport (DHT) between the zones is implicit, in the second (Model B) it is explicitly parameterized. It is found that the stability and sensitivity properties of the ZDM and Model A are very similar, both depending only on the global-mean radiative response coefficient and the global-mean forcing. The corresponding properties of Model B are more complex, depending asymmetrically on the separate tropical and extratropical values of these quantities, as well as on the DHT coefficient. Adopting Model B as a benchmark, conditions are found under which the validity of the ZDM and Model A as climate sensitivity models holds. It is shown that parameter ranges of physical interest exist for which such validity may not hold. The 2 × CO2 sensitivities of the simple models are studied and compared. Possible implications of the results for sensitivities derived from GCMs and palaeoclimate data are suggested. Sensitivities for more general scenarios that include negative forcing in the tropics (due to aerosols, inadvertent or geoengineered) are also studied. Some unexpected outcomes are found in this case. These include the possibility of a negative global-mean temperature response to a positive global-mean forcing, and vice versa.

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

    Science.gov (United States)

    Stagge, James; Tallaksen, Lena; Rizzi, Jonathan

    2015-04-01

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

  13. On the evaluation of climate model simulated precipitation extremes

    International Nuclear Information System (INIS)

    The evaluation of precipitation extremes is a paramount challenging issue in climate sciences and there is a need of both assessing changes in climate projections and comparing climate model simulations with observations. To address these needs, a non-parametric approach specifically designed for extremes is here proposed. The method is tested and applied to observations and CMIP5 historical simulations and future projections (under the high emission scenario RCP8.5) over the Euro-Mediterranean region. Results support the existence of a scaling relationship among models and between models and observations in terms of conditional mean of the extremes. However, the rescaled tails of models’ precipitation show significant differences when compared with observations. Concerning future projections, models show an intensification of heavy precipitation (especially at the end of the 21st century) linked to a change in the conditional mean of extremes. More complex changes in the upper tails are not identified at the mid-century, while a lack of model agreement prevents drawing definitive conclusions for the end of the century. (letter)

  14. Modelling middle pliocene warm climates of the USA

    Science.gov (United States)

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

    2001-01-01

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

  15. ESCAPE: an integrated climate model for the EC

    International Nuclear Information System (INIS)

    A framework has been developed for the evaluation of policy options for climate change, called ESCAPE (Evaluation of Strategies to address Climate change by Adapting to and Preventing Emissions). ESCAPE consists of a suite of linked models which enables scenarios of greenhouse gas emissions to be constructed and their impact on global and regional climate and sea level and sectors of the European economy to be assessed. Conclusions resulting from simulations with the ESCAPE 1.1 model include: the major problem of a climate change for the EC is a sea level rise; Greece, Italy, Portugal and Spain will be faced with higher costs in the agricultural sector; worldwide implementation of an EC carbon tax leads to about 12% lower worldwide CO2 emissions; to stabilize CO2 emissions an Ecotax of 18 dollars per barrel would be required; and in all cases the rate of global temperature increase will be above the rate of 0.1 degree C per decade for the coming 40 years. 2 figs

  16. 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.

  17. Modeling maize response to climate modification in Hungary

    Directory of Open Access Journals (Sweden)

    Angela Anda

    2006-09-01

    Full Text Available Modeling provides a tool for a better understanding of the modified plant behaviour that results from various climatic differences. The present study provides new information about the physiological processes in maize (Zea mays L. in response to climatic changes. The aim was to help local farmers adapt to climate modifications in Hungary and mitigate the future consequences of these changes. A simulation model was applied to estimate the possible feedback on crop properties and elevated CO2. Increased CO2 and warming increased the ratio of energy converted into sensible heat. At canopy level, warming and elevated CO2 strengthened the influence of an external rise in air temperature. It was cooler inside the stand, as the canopy was able to compensate for external warming. Doubled CO2 concentration had a positive influence on photosynthesis when rainfall remained unchanged. Precipitation shortage decreased the positive effects of warming and elevated CO2. Considering the sensitivity of the photosynthetic process to meteorological factors, a gain in maize production with climate modification is not probable in Hungary.

  18. The regional aerosol-climate model REMO-HAM

    Directory of Open Access Journals (Sweden)

    J.-P. Pietikäinen

    2012-03-01

    Full Text Available REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes all of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM-M7 has been coupled with a two-moment stratiform cloud scheme. In this work, we have evaluated the model and compared the results against ECHAM5-HAM and measurements. Four different measurement sites was chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50×50 km2 and 10×10 km2. Based on our simulations, REMO-HAM can represent the measured values reasonably well. The total number concentrations are slightly underestimated, which is probably due to the missing boundary layer nucleation and online secondary organic aerosol model. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we have shown that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.

  19. 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

  20. Projecting Wind Energy Potential Under Climate Change with Ensemble of Climate Model Simulations

    Science.gov (United States)

    Jain, A.; Shashikanth, K.; Ghosh, S.; Mukherjee, P. P.

    2013-12-01

    Recent years have witnessed an increasing global concern over energy sustainability and security, triggered by a number of issues, such as (though not limited to): fossil fuel depletion, energy resource geopolitics, economic efficiency versus population growth debate, environmental concerns and climate change. Wind energy is a renewable and sustainable form of energy in which wind turbines convert the kinetic energy of wind into electrical energy. Global warming and differential surface heating may significantly impact the wind velocity and hence the wind energy potential. Sustainable design of wind mills requires understanding the impacts of climate change on wind energy potential, which we evaluate here with multiple General Circulation Models (GCMs). GCMs simulate the climate variables globally considering the greenhouse emission scenarios provided as Representation Concentration path ways (RCPs). Here we use new generation climate model outputs obtained from Coupled model Intercomparison Project 5(CMIP5). We first compute the wind energy potential with reanalysis data (NCEP/ NCAR), at a spatial resolution of 2.50, where the gridded data is fitted to Weibull distribution and with the Weibull parameters, the wind energy densities are computed at different grids. The same methodology is then used, to CMIP5 outputs (resultant of U-wind and V-wind) of MRI, CMCC, BCC, CanESM, and INMCM4 for historical runs. This is performed separately for four seasons globally, MAM, JJA, SON and DJF. We observe the muti-model average of wind energy density for historic period has significant bias with respect to that of reanalysis product. Here we develop a quantile based superensemble approach where GCM quantiles corresponding to selected CDF values are regressed to reanalysis data. It is observed that this regression approach takes care of both, bias in GCMs and combination of GCMs. With superensemble, we observe that the historical wind energy density resembles quite well with

  1. 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

  2. Investigations into a plankton population model: Mortality and its importance in climate change scenarios

    OpenAIRE

    Cropp, Roger; Norbury, John

    2006-01-01

    The potential for marine plankton ecosystems to influence climate by the production of dimethylsulphide (DMS) has been an important topic of recent research into climate change. Several General Circulation Models, used to predict climate change, have or are being modified to include interactions of ecosystems with climate. Climate change necessitates that parameters within ecosystem models must change during long-term simulations, especially mortality parameters that increase as organisms are...

  3. Ground surface temperature scenarios in complex high-mountain topography based on regional climate model results

    OpenAIRE

    Salzmann, N.; Noetzli, J.; C. Hauck; Gruber, S.; M. Hoelzle; Haeberli, W.

    2007-01-01

    Climate change can have severe impacts on the high-mountain cryosphere, such as instabilities in rock walls induced by thawing permafrost. Relating climate change scenarios produced from global climate models (GCMs) and regional climate models (RCMs) to complex high-mountain environments is a challenging task. The qualitative and quantitative impact of changes in climatic conditions on local to microscale ground surface temperature (GST) and the ground thermal regime is not readily apparent. ...

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

    Science.gov (United States)

    Smith, James A.

    2009-01-01

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

  5. Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada

    Science.gov (United States)

    Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

    2014-07-01

    Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

  6. Climate change projections for CORDEX-Africa with COSMO-CLM regional climate model and differences with the driving global climate models

    Science.gov (United States)

    Dosio, Alessandro; Panitz, Hans-Jürgen

    2016-03-01

    In the framework of the coordinated regional climate downscaling experiment (CORDEX), an ensemble of climate change projections for Africa has been created by downscaling the simulations of four global climate models (GCMs) by means of the consortium for small-scale modeling (COSMO) regional climate model (RCM) (COSMO-CLM, hereafter, CCLM). Differences between the projected temperature and precipitation simulated by CCLM and the driving GCMs are analyzed and discussed. The projected increase of seasonal temperature is found to be relatively similar between GCMs and RCM, although large differences (more than 1 °C) exist locally. Differences are also found for extreme-event related quantities, such as the spread of the upper end of the maximum temperature probability distribution function and, in turn, the duration of heat waves. Larger uncertainties are found in the future precipitation changes; this is partly a consequence of the inter-model (GCMs) variability over some areas (e.g. Sahel). However, over other regions (e.g. Central Africa) the rainfall trends simulated by CCLM and the GCMs show opposite signs, with CCLM showing a significant reduction in precipitation at the end of the century. This uncertain and sometimes contrasting behaviour is further investigated by analyzing the different models' response to the land-atmosphere interaction and feedback. Given the large uncertainty associated with inter-model variability across GCMs and the reduced spread in the results when a single RCM is used for downscaling, we strongly emphasize the importance of exploiting fully the CORDEX-Africa multi-GCM/multi-RCM ensemble in order to assess the robustness of the climate change signal and, possibly, to identify and quantify the many sources of uncertainty that still remain.

  7. Software Testing and Verification in Climate Model Development

    Science.gov (United States)

    Clune, Thomas L.; Rood, RIchard B.

    2011-01-01

    Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

  8. MODELING THE EFFECTS OF ANTHROPOGENIC SULFATE IN CLIMATE CHANGE BY USING A REGIONAL CLIMATE MODEL

    Institute of Scientific and Technical Information of China (English)

    高学杰; 林一骅; 赵宗慈

    2003-01-01

    Effects of aerosol with focus on the direct climate effect of anthropogenic sulfate aerosol under 2×CO2 condition were investigated by introducing aerosol distribution into the latest version of RegCM2. Two experiments, first run(2×CO2 + 0 aerosol concentration) and second run (2×CO2 + aerosol distribution), were made for 5 years respectively. Preliminary analysis shows that the direct climate effect of aerosol might cause a decrease of surface air temperature.The decrease might be larger in winter and in South China. The regional-averaged monthly precipitation might also decrease in most of the months due to the effect. The annual mean change of precipitation might be a decrease in East and an increase in West China. But the changes of both temperature and precipitation simulated were much smaller as compared to the greenhouse effect.

  9. 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

  10. The Use and Misuse of Models for Climate Policy

    OpenAIRE

    Robert S. Pindyck

    2015-01-01

    In recent articles, I have argued that integrated assessment models (IAMs) have flaws that make them close to useless as tools for policy analysis. IAM-based analyses of climate policy create a perception of knowledge and precision that is illusory, and can fool policy-makers into thinking that the forecasts the models generate have some kind of scientific legitimacy. But some have claimed that we need some kind of model, and that IAMs can be structured and used in ways that correct for their...

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

    DEFF Research Database (Denmark)

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

    - and river flow as well as land surface-atmosphere fluxes of water (evapotranspiration) and energy - significantly reduces precipitation bias compared to the regional climate model alone. For a six year simulation period (2004 – 2010) covering a 2500 km2 catchment substantial improvements in the......The complexity of precipitation processes makes it difficult for climate models to reliably simulate precipitation, particularly at sub-grid scales, where the important processes are associated with detailed land-atmosphere feedbacks like the vertical circulations driven by latent heat that affect...... convective precipitation systems. As a result climate model simulations let alone future projections of precipitation often exhibit substantial biases. Here we show that the dynamical coupling of a regional climate model to a detailed fully distributed hydrological model - including groundwater-, overland...

  12. High resolution global climate modelling from the UPSCALE simulation campaign

    Science.gov (United States)

    Vidale, Pier-Luigi; Roberts, Malcolm; Mizielinski, Matthew; Demory, Marie-Estelle; Schiemann, Reinhard; Strachan, Jane

    2014-05-01

    A traceable hierarchy of global climate models (based on the Met Office Unified Model, GA3 formulation), with mesh sizes ranging from 130km to 25km, has been developed in order to study the impact of improved representation of small-scale processes on the mean climate, its variability and extremes. Five-member ensembles of atmosphere-only integrations were completed at these resolutions, each 27 years in length, using both present day forcing and a future climate scenario. These integrations, collectively known as the "UPSCALE campaign", were completed using time provided by the European PrACE project on supercomputer HERMIT (HLRS Stuttgart). A wide variety of processes are being studied to assess these integrations, in particular with regards to the role of resolution. Tropical cyclone characteristics are shown to improve as resolution is increased (in terms of spatial extent, frequency, structure and variability), particularly in the Atlantic basin, where ensemble correlations with observed interannual variability approach 0.8. Mid-latitude Atlantic jet positioning improves in some seasons, although the spread between ensemble members has a similar magnitude to the spread between ensembles means at resolution. The simulation of decadal trends in Sahel rainfall also improve as resolution is increased, which is very likely linked to processes such as African Easterly Waves. The simulation of polar lows and other processes also become more realistic in the higher resolution simulations. Some aspects of the relationship between the improved simulation of the current climate, and how this impacts on changes in the future climate, will also be discussed. In particular tropical cyclone frequency decreases robustly in the Southern Hemisphere, but changes in the Northern Hemisphere are more basin-dependent, with a decrease in the Atlantic but a shift in tracks in the Pacific.

  13. Design for and efficient dynamic climate model with realistic geography

    Science.gov (United States)

    Suarez, M. J.; Abeles, J.

    1984-01-01

    The long term climate sensitivity which include realistic atmospheric dynamics are severely restricted by the expense of integrating atmospheric general circulation models are discussed. Taking as an example models used at GSFC for this dynamic model is an alternative which is of much lower horizontal or vertical resolution. The model of Heid and Suarez uses only two levels in the vertical and, although it has conventional grid resolution in the meridional direction, horizontal resolution is reduced by keeping only a few degrees of freedom in the zonal wavenumber spectrum. Without zonally asymmetric forcing this model simulates a day in roughly 1/2 second on a CRAY. The model under discussion is a fully finite differenced, zonally asymmetric version of the Heid-Suarez model. It is anticipated that speeds can be obtained a few seconds a day roughly 50 times faster than moderate resolution, multilayer GCM's.

  14. Nordic climate change: data for modeling vector borne diseases

    DEFF Research Database (Denmark)

    Kristensen, Birgit; Bødker, Rene

    derivatives were calculated in order to assess the geographical and seasonal variation in the area. In order to evaluate the response of vector borne diseases to possible future climate changes and the subsequent potential spread into new areas, daily temperature predictions (mean, min and max) for three 20......The distribution of vector species is generally restricted by a range of different climatic and geographical factors, while the development and spread of the vector-borne diseases (veterinary and zoonotic) is often primarily temperature driven. Thus temperature and its derivatives are key factors...... in the modelling of vector-borne diseases. This puts a high demand on the quality and accuracy of the temperature data to be used as input in such models. In order to best capture the local temporal and spatial variation in the temperature surfaces, accurate daily temperature data were used in the present project...

  15. Groundwater flow across spatial scales: importance for climate modeling

    International Nuclear Information System (INIS)

    Current regional and global climate models generally do not represent groundwater flow between grid cells as a component of the water budget. We estimate the magnitude of between-cell groundwater flow as a function of grid cell size by aggregating results from a numerical model of equilibrium groundwater flow run and validated globally. We find that over a broad range of cell sizes spanning that of state-of-the-art regional and global climate models, mean between-cell groundwater flow magnitudes scale with the reciprocal of grid cell length. We also derive this scaling a priori from a simple statistical model of a flow network. We offer operational definitions of ‘significant’ groundwater flow contributions to the grid cell water budget in both relative and absolute terms (between-cell flow magnitude exceeding 10% of local recharge or 10 mm y−1, respectively). Groundwater flow is a significant part of the water budget, as measured by a combined test requiring both relative and absolute significance, over 42% of the land area at 0.1° grid cell size (typical of regional and mesoscale models), decreasing to 1.5% at 1° (typical of global models). Based on these findings, we suggest that between-cell groundwater flow should be represented in regional and mesoscale climate models to ensure realistic water budgets, but will have small effects on water exchanges in current global models. As well, parameterization of subgrid moisture heterogeneity should include the effects of within-cell groundwater flow. (paper)

  16. Mesozoic climates: General circulation models and the rock record

    Science.gov (United States)

    Sellwood, Bruce W.; Valdes, Paul J.

    2006-08-01

    General circulation models (GCMs) use the laws of physics and an understanding of past geography to simulate climatic responses. They are objective in character. However, they tend to require powerful computers to handle vast numbers of calculations. Nevertheless, it is now possible to compare results from different GCMs for a range of times and over a wide range of parameterisations for the past, present and future (e.g. in terms of predictions of surface air temperature, surface moisture, precipitation, etc.). GCMs are currently producing simulated climate predictions for the Mesozoic, which compare favourably with the distributions of climatically sensitive facies (e.g. coals, evaporites and palaeosols). They can be used effectively in the prediction of oceanic upwelling sites and the distribution of petroleum source rocks and phosphorites. Models also produce evaluations of other parameters that do not leave a geological record (e.g. cloud cover, snow cover) and equivocal phenomena such as storminess. Parameterisation of sub-grid scale processes is the main weakness in GCMs (e.g. land surfaces, convection, cloud behaviour) and model output for continental interiors is still too cold in winter by comparison with palaeontological data. The sedimentary and palaeontological record provides an important way that GCMs may themselves be evaluated and this is important because the same GCMs are being used currently to predict possible changes in future climate. The Mesozoic Earth was, by comparison with the present, an alien world, as we illustrate here by reference to late Triassic, late Jurassic and late Cretaceous simulations. Dense forests grew close to both poles but experienced months-long daylight in warm summers and months-long darkness in cold snowy winters. Ocean depths were warm (8 °C or more to the ocean floor) and reefs, with corals, grew 10° of latitude further north and south than at the present time. The whole Earth was warmer than now by 6 °C or

  17. Climate change and the Portuguese precipitation: ENSEMBLES regional climate models results

    Science.gov (United States)

    Soares, Pedro M. M.; Cardoso, Rita M.; Ferreira, João Jacinto; Miranda, Pedro M. A.

    2015-10-01

    In Portugal, the precipitation regimes present one of the highest volumes of extreme precipitation occurrence in Europe, and one of the largest mean precipitation spatial gradient (annual observed values above 2,500 mm in the NW and under 400 mm in the SE). Moreover, southern Europe is one of the most vulnerable regions in the world to climate change. In the ENSEMBLES framework many climate change assessment studies were performed, but none focused on Portuguese precipitation. An extensive evaluation and ranking of the RCMs results addressing the representation of mean precipitation and frequency distributions was performed through the computation of statistical errors and frequency distribution scores. With these results, an ensemble was constructed; giving the same weight to mean precipitation and distribution model skills. This ensemble reveals a good ability to describe the precipitation regime in Portugal, and enables the evaluation of the eventual impact of climate change on Portuguese precipitation according to the A1B scenario. The mean seasonal precipitation is expected to decrease substantially in all seasons, excluding winter. This reduction is statistically significant; it spans from less than 20 % in the north to 40 % in the south in the intermediate seasons, and is above 50 % in the largest portion of mainland in summer. At a basin level the precipitation diminishes in all months for all the basins with exception of December. Total precipitation PDFs reveal an important decrease of the contribution from low to moderate/high precipitation bins, and a striking rise for days with extreme rainfall, up to 30 %.

  18. Tropical cyclone genesis potential index in climate models

    OpenAIRE

    Camargo, Suzana J.; Sobel, Adam H.; Barnston, Anthony G.; Kerry A. Emanuel

    2007-01-01

    The potential for tropical cyclogenesis in a given ocean basin during its active season has been represented by genesis potential indices, empirically determined functions of large-scale environmental variables which influence tropical cyclone (TC) genesis. Here we examine the ability of some of today’s atmospheric climate models, forced with historical observedSSTover a multidecadal hindcast period, to reproduce observed values and patterns of one such genesis potential index (GP), as well a...

  19. Future bloom and blossom frost risk for Malus domestica considering climate model and impact model uncertainties.

    Directory of Open Access Journals (Sweden)

    Holger Hoffmann

    Full Text Available The future bloom and risk of blossom frosts for Malus domestica were projected using regional climate realizations and phenological ( = impact models. As climate impact projections are susceptible to uncertainties of climate and impact models and model concatenation, the significant horizon of the climate impact signal was analyzed by applying 7 impact models, including two new developments, on 13 climate realizations of the IPCC emission scenario A1B. Advancement of phenophases and a decrease in blossom frost risk for Lower Saxony (Germany for early and late ripeners was determined by six out of seven phenological models. Single model/single grid point time series of bloom showed significant trends by 2021-2050 compared to 1971-2000, whereas the joint signal of all climate and impact models did not stabilize until 2043. Regarding blossom frost risk, joint projection variability exceeded the projected signal. Thus, blossom frost risk cannot be stated to be lower by the end of the 21st century despite a negative trend. As a consequence it is however unlikely to increase. Uncertainty of temperature, blooming date and blossom frost risk projection reached a minimum at 2078-2087. The projected phenophases advanced by 5.5 d K(-1, showing partial compensation of delayed fulfillment of the winter chill requirement and faster completion of the following forcing phase in spring. Finally, phenological model performance was improved by considering the length of day.

  20. 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.

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

    Institute of Scientific and Technical Information of China (English)

    SHI Xueli

    2009-01-01

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

  2. New Gravity Wave Treatments for GISS Climate Models

    Science.gov (United States)

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

    2011-01-01

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

  3. Modelling the effect of UK energy policy and climate change

    Science.gov (United States)

    Chan, Ronald Wai Ho

    The central aim of this thesis is to investigate various UK energy policy documents and identify how they are implanted to the main energy consuming sectors in order to achieve a reduction of 60 percent of carbon emissions by 2050. This has lead to two key questions: What are the pros and cons of the various UK energy policy documents What are the impacts of currently proposed environmental policies in UK on economic growth in the 21st century To answer these questions, the following four energy policy documents are reviewed. UK Energy White Paper Energy Efficiency Commitment Climate Change Levy and UK Emissions Trading Scheme Renewable Obligations Also, the following macro energy modelling work is also investigated: Markal Model E3ME The UK Energy White Paper has shown the government is being very eager to solve the climate change and its associated problems by reducing carbon dioxide emissions by 60 percent by 2050. The four documents have illustrated the UK government main strategies to tackle climate change they are based on developing new technology, improving energy efficiency and to increase the use of renewables considerably. The analysis of these policies and macro-scale model has forecasted that the UK is going to have a slow down economic growth due to the environmental pressure.

  4. Extreme winds over Europe in the ENSEMBLES regional climate models

    Directory of Open Access Journals (Sweden)

    S. D. Outten

    2013-05-01

    Full Text Available Extreme winds cause vast amounts of damage every year and represent a major concern for numerous industries including construction, afforestation, wind energy and many others. Under a changing climate, the intensity and frequency of extreme events are expected to change, and accurate projections of these changes will be invaluable to decision makers and society as a whole. This work examines four regional climate model downscalings over Europe following the SRES A1B scenario from the "ENSEMBLE-based Predictions of Climate Changes and their Impacts" project (ENSEMBLES. It investigates the projected changes in the 50 yr return wind speeds and the associated uncertainties. This is accomplished by employing the peaks-over-threshold method with the use of the generalised Pareto distribution. The models show that, for much of Europe, the 50 yr return wind is projected to change by less than 2 m s−1, while the uncertainties associated with the statistical estimates are larger than this. In keeping with previous works in this field, the largest source of uncertainty is found to be the inter-model spread, with some locations showing differences in the 50 yr return wind of over 20 m s−1 between two different downscalings.

  5. From nanoclusters to climate forcers. Global modeling of aerosol climate effects

    Energy Technology Data Exchange (ETDEWEB)

    Makkonen, R.

    2012-11-01

    Atmospheric aerosol particles influence everyday life through their adverse health effects. Aerosols also affect the Earth's climate, directly by scattering and absorbing radiation and indirectly by acting as cloud condensation nuclei (CCN) and modifying cloud properties. The net effect of aerosols on climate is cooling. Although only a small fraction of atmospheric aerosol mass is of direct human origin, the anthropogenic aerosol climate forcing can be of same magnitude, but opposite in sign, as the anthropogenic forcing via CO{sub 2}. As aerosols are short-lived and respond rapidly to changes in emissions, they are an important factor in determining the future climate change. Aerosols are either emitted as primary particles or they are formed from gas-phase precursors. Atmospheric new particle formation is observed around the world. In this thesis, new particle formation is studied with a global aerosol-climate model. Several thermodynamic and semi- empirical parameterizations of nucleation are investigated. It is shown that in addition to the thermodynamic models, semi-empirical parameterizations are needed to explain the observed aerosol number concentrations. Volatile organic compounds (VOCs) can contribute to particle number, particle growth, and total aerosol mass. It was shown that biogenic VOCs have an important role in growing the freshly-nucleated particles to sizes capable of acting as CCN. It was also shown that the current atmospheric concentrations of nitric acid can greatly affect cloud droplet activation and increase the number of cloud droplets, making a large contribution to the indirect aerosols effect. With current scenarios for anthropogenic SO{sub 2} emissions, the formation of new particles will diminish significantly by the year 2100. Together with the predicted reductions in primary particles, the future cloud droplet number concentrations were shown to decrease close to pre-industrial levels. As a result, the anthropogenic aerosol

  6. Regional climate model projections of the South Pacific Convergence Zone

    Science.gov (United States)

    Evans, J. P.; Bormann, K.; Katzfey, J.; Dean, S.; Arritt, R.

    2015-10-01

    This study presents results from regional climate model (RCM) projections for the south-west Pacific Ocean. The regional models used bias corrected sea surface temperatures. Six global climate models (GCMs) were used to drive a global variable resolution model on a quasi-uniform 60 km grid. One of these simulations was used to drive three limited area regional models. Thus a four member ensemble was produced by different RCMs downscaling the same GCM (GFDL2.1), and a six member ensemble was produced by the same RCM (Conformal Cubic Atmospheric Model—CCAM) downscaling six different GCMs. Comparison of the model results with precipitation observations shows the differences to be dominated by the choice of RCM, with all the CCAM simulations performing similarly and generally having lower error than the other RCMs. However, evaluating aspects of the model representation of the South Pacific Convergence Zone (SPCZ) does not show CCAM to perform better in this regard. In terms of the future projections of the SPCZ for the December-January-February season, the ensemble showed no consensus change in most characteristics though a majority of the ensemble members project a decrease in the SPCZ strength. Thus, similar to GCM based studies, there is large uncertainty concerning future changes in the SPCZ and there is no evidence to suggest that future changes will be outside the natural variability. These RCM simulations do not support an increase in the frequency of zonal SPCZ events.

  7. Regional climate model projections of the South Pacific Convergence Zone

    Science.gov (United States)

    Evans, J. P.; Bormann, K.; Katzfey, J.; Dean, S.; Arritt, R.

    2016-08-01

    This study presents results from regional climate model (RCM) projections for the south-west Pacific Ocean. The regional models used bias corrected sea surface temperatures. Six global climate models (GCMs) were used to drive a global variable resolution model on a quasi-uniform 60 km grid. One of these simulations was used to drive three limited area regional models. Thus a four member ensemble was produced by different RCMs downscaling the same GCM (GFDL2.1), and a six member ensemble was produced by the same RCM (Conformal Cubic Atmospheric Model—CCAM) downscaling six different GCMs. Comparison of the model results with precipitation observations shows the differences to be dominated by the choice of RCM, with all the CCAM simulations performing similarly and generally having lower error than the other RCMs. However, evaluating aspects of the model representation of the South Pacific Convergence Zone (SPCZ) does not show CCAM to perform better in this regard. In terms of the future projections of the SPCZ for the December-January-February season, the ensemble showed no consensus change in most characteristics though a majority of the ensemble members project a decrease in the SPCZ strength. Thus, similar to GCM based studies, there is large uncertainty concerning future changes in the SPCZ and there is no evidence to suggest that future changes will be outside the natural variability. These RCM simulations do not support an increase in the frequency of zonal SPCZ events.

  8. Climate change scenarios of precipitation extremes in the Carpathian region based on an ENSEMBLE of regional climate models

    Czech Academy of Sciences Publication Activity Database

    Gaál, Ladislav; Beranová, Romana; Hlavčová, K.; Kyselý, Jan

    2014-01-01

    Roč. 2014, č. 943487 (2014), s. 1-14. ISSN 1687-9309 R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.946, year: 2014 http://www.hindawi.com/journals/amete/2014/943487/

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

    Science.gov (United States)

    Stephenson, Scott R.; Smith, Laurence C.

    2015-11-01

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

  10. 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

  11. 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.

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  13. A 2D climate energy balance model coupled with a 3D deep ocean model

    Directory of Open Access Journals (Sweden)

    J. Ildefonso Diaz

    2007-05-01

    Full Text Available We study a three dimensional climate model which represents the coupling of the mean surface temperature with the ocean temperature. We prove the existence of a bounded weak solution by a fixed point argument.

  14. Polar Climate Change from Recent Observations and in Global Climate Models

    Science.gov (United States)

    Weatherly, J. W.

    2002-12-01

    Recent papers on the thinning and shrinking sea ice cover of the Arctic Ocean have suggested that these changes can be explained by both natural climate oscillations and large-scale trends. The changes in patterns of ice motion are consistent with the dynamic response of sea ice to changing pressure patterns indicated by the Arctic Oscillation, which seem to transport thicker sea ice out of the Arctic Ocean. Anomalously warm air temperatures and ocean temperatures also appear to have contributed to less sea ice growth, resulting in thinner ice. Both warmer air and ocean temperatures are consistent with the warmer phase of the Arctic Oscillation. Global climate model simulations that include complex dynamic and thermodynamic ice models also show that anthropogenic global warming trends since the 1980's have also contributed to the present-day thinning and shrinking sea ice cover. However, the models also show the large natural variability in the ice cover that must be overcome before the anthropogenic trends can be reliably measured. Estimates of the number of additional ice observing stations that will be required to measure the secular trend will be presented.

  15. A strategy for using climate data for hydrological modelling

    Science.gov (United States)

    Rust, Henning W.; Ulbrich, Uwe; Vagenas, Christos; Meredith, Edmund; Agbeko Kpogo-Nuwoklo, Komlan

    2016-04-01

    Hydrological modeling is the basis for water related impact assessment and the development of management strategies. These models are driven with meteorological data such as precipitation, temperature, wind and humidity. Depending on the nature of the problem, hydrological modelers require meteorological data with a very high spatial and temporal resolution, e.g. to a few kilometers and hours. As dynamical downscaling to such a high resolution is computationally very costly, a continuous downscaling of global climate projections is not feasible for a longer time period. For BINGO, a double-tracked strategy will be implemented to cope with this problem: 1) high resolution dynamical downscaling is limited to episodes favoring hydrological extremes and 2) conditional weather generators are used to simulated large ensembles of spatio-temporal driving fields consistent with the current or projected climate. The first track requires identification of the relevant episodes from global simulations. This is realized by clustering atmospheric variables to obtain a set of circulation patterns. Episodes containing sequences of circulation patterns associated with hydrological extremes are then further downscaled and bias corrected. The second track relies on setting up a weather generator allowing to simulate all relevant variables consistent with the recent climate. We seek to establish a link between this generator and large scale atmospheric drivers to allow simulations consistent with climate projections. While dynamical downscaling is strong in simulating meteorological driving data associated with particular events, conditional weather generators simulate a broader range of events consistent with the large scale situation. The two tracks thus complement each other.

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

    Science.gov (United States)

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

    2012-04-01

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

  17. Simulation of the Arid Climate of the Southern Great Basin Using a Regional Climate Model.

    Science.gov (United States)

    Giorgi, Filippo; Bates, Gary T.; Nieman, Steven J.

    1992-11-01

    As part of the development effort of a regional climate model (RCM)for the southern Great Basin, this paper present savalidation analysis of the climatology generated by a high-resolution RCM driven by observations. The RCM is aversion of the National Center for atmospheric Research-Pennsylvania State University mesoscale model, version 4 (MM4), modified for application to regional climate simulation. Two multiyear simulations, for the periods 1 January 1982 to 31 December 1983 and 1 January 1988 to 25 April 1989, were performed over the western United States with the RCM driven by European Centre for Medium-Range Weather Forecasts analyses of observations. The model resolution is 60 km. This validation analysis is the first phase of a project to produce simulations of future climate scenarios over a region surrounding Yucca Mountain, Nevada, the only location currently being considered as a potential high-level nuclear-waste repository site.Model-produced surface air temperatures and precipitation were compared with observations from five southern Nevada stations located in the vicinity of Yucca Mountain. The seasonal cycles of temperature and precipitation were simulated well. Monthly and seasonal temperature biases were generally negative and largely explained by differences in elevation between the observing stations and the model topography. The model-simulated precipitation captured the extreme dryness of the Great Basin. Average yearly precipitation was generally within 30% of observed and the range of monthly precipitation amounts was the same as in the observations. Precipitation biases were mostly negative in the summer and positive in the winter. The number of simulated daily precipitation events for various precipitation intervals was within factors of 1.5-3.5 of observed. Overall, the model tended to overestimate the number of light precipitation events and underestimate the number of heavy precipitation events. At Yucca Mountain, simulated

  18. Modeling forest dynamics along climate gradients in Bolivia

    Science.gov (United States)

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

    2014-05-01

    Dynamic vegetation models have been used to assess the resilience of tropical forests to climate change, but the global application of these modeling experiments often misrepresents carbon dynamics at a regional level, limiting the validity of future projections. Here a dynamic vegetation model (Lund Potsdam Jena General Ecosystem Simulator) was adapted to simulate present-day potential vegetation as a baseline for climate change impact assessments in the evergreen and deciduous forests of Bolivia. Results were compared to biomass measurements (819 plots) and remote sensing data. Using regional parameter values for allometric relations, specific leaf area, wood density, and disturbance interval, a realistic transition from the evergreen Amazon to the deciduous dry forest was simulated. This transition coincided with threshold values for precipitation (1400 mm yr-1) and water deficit (i.e., potential evapotranspiration minus precipitation) (-830 mm yr-1), beyond which leaf abscission became a competitive advantage. Significant correlations were found between modeled and observed values of seasonal leaf abscission (R2 = 0.6, p <0.001) and vegetation carbon (R2 = 0.31, p <0.01). Modeled Gross Primary Productivity (GPP) and remotely sensed normalized difference vegetation index showed that dry forests were more sensitive to rainfall anomalies than wet forests. GPP was positively correlated to the El Niño-Southern Oscillation index in the Amazon and negatively correlated to consecutive dry days. Decreasing rainfall trends were simulated to reduce GPP in the Amazon. The current model setup provides a baseline for assessing the potential impacts of climate change in the transition zone from wet to dry tropical forests in Bolivia.

  19. 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

  20. Evaluation of radiation scheme performance within chemistry climate models

    OpenAIRE

    Forster, P. M.; Mayer, B.; et, al.

    2011-01-01

    This paper evaluates global mean radiatively important properties of chemistry climate models (CCMs). We evaluate stratospheric temperatures and their 1980�2000 trends, January clear sky irradiances, heating rates, and greenhouse gas radiative forcings from an offline comparison of CCM radiation codes with line�by�line models, and CCMs� representation of the solar cycle. CCM global mean temperatures and their change can give an indication of errors in radiative trans...

  1. Hydrological responses to dynamically and statistically downscaled climate model output

    Science.gov (United States)

    Wilby, R.L.; Hay, L.E.; Gutowski, W.J., Jr.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.

    2000-01-01

    Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.

  2. Hydrological Response to Climate Change over the Blue Nile Basin Distributed hydrological modeling based on surrogate climate change scenarios

    Science.gov (United States)

    Berhane, F. G.; Anyah, R. O.

    2010-12-01

    The program Soil and Water Assessment Tool (SWAT2009) model has been applied to the Blue Nile Basin to study the hydrological response to surrogate climate changes over the Blue Nile Basin (Ethiopia) by downscaling gridded weather data. The specific objectives of the study include (i) examining the performance of the SWAT model in simulating hydrology-climate interactions and feedbacks within the entire Blue Nile Basin, and (ii) investigating the response of hydrological variables to surrogate climate changes. Monthly weather data from the Climate Research Unit (CRU) are converted to daily values as input into the SWAT using Monthly to Daily Weather Converter (MODAWEC). Using the program SUFI-2 (Sequential Uncertainty Fitting Algorithm), data from 1979 to 1983 are applied for sensitivity analysis and calibration (P-factor = 90%, R-factor =0.7, R2 =0.93 and NS=0.93) and subsequently to validate hindcasts over the period 1984-1989 (R2 =0.92 and NS=0.92). The period from 1960-2000 was used as baseline and has been used to determine the changes and the effect of the surrogate climate changes over the Blue Nile Basin. Overall, our surrogate climate change based simulations indicate the hydrology of the Blue Nile catchment is very sensitive to potential climate change with 100%, 34% and 51% increase to the surface runoff, lateral flow and water yield respectively for the A2 scenario surrogate. Key Words: SWAT, MODAWEC, Blue Nile Basin, SUFI-2, climate change, hydrological modeling, CRU

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

    International Nuclear Information System (INIS)

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

  4. Estimating climate projection uncertainties from multi model ensembles of global general circulation models (Invited)

    Science.gov (United States)

    Knutti, R.

    2009-12-01

    Recent coordinated efforts, in which numerous general circulation climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Those multi-model ensembles sample initial condition, parameter as well as structural uncertainties in the model design, and they have prompted a variety of approaches to quantifying uncertainty in future regional climate change. International climate change assessments also rely heavily on these models and often provide model ranges as uncertainties and equal-weighted averages as best-guess results, the latter assuming that individual model biases will at least partly cancel and that a model average prediction is more likely to be correct than a prediction from a single model. This is based on the result that a multi-model average of present-day climate generally out-performs any individual model. This presentation outlines the motivation for using multi-model ensembles and discusses various challenges in interpreting them. Among these challenges are that the number of models in these ensembles is usually small, their distribution in the model or parameter space is unclear and the fact that extreme behavior is often not sampled when each institution is only developing one or two model versions. Model skill in simulating present day climate conditions is shown to relate only weakly to the magnitude of predicted change. It is thus unclear how the skill of these models should be evaluated and by how much our confidence in future projections should increase based on improvements in simulating present day conditions, a reduction of intermodel spread or a larger number of models. The result is that despite of a massive increase computational capacity and despite of (or maybe because of) an increase in model complexity, the model spread in future projections is often not decreasing. Even on the largest scale, e.g. for climate sensitivity, the range covered by

  5. Climate implications of carbonaceous aerosols: An aerosol microphysical study using the GISS/MATRIX climate model

    Energy Technology Data Exchange (ETDEWEB)

    Bauer, Susanne E.; Menon, Surabi; Koch, Dorothy; Bond, Tami; Tsigaridis, Kostas

    2010-04-09

    Recently, attention has been drawn towards black carbon aerosols as a likely short-term climate warming mitigation candidate. However the global and regional impacts of the direct, cloud-indirect and semi-direct forcing effects are highly uncertain, due to the complex nature of aerosol evolution and its climate interactions. Black carbon is directly released as particle into the atmosphere, but then interacts with other gases and particles through condensation and coagulation processes leading to further aerosol growth, aging and internal mixing. A detailed aerosol microphysical scheme, MATRIX, embedded within the global GISS modelE includes the above processes that determine the lifecycle and climate impact of aerosols. This study presents a quantitative assessment of the impact of microphysical processes involving black carbon, such as emission size distributions and optical properties on aerosol cloud activation and radiative forcing. Our best estimate for net direct and indirect aerosol radiative forcing change is -0.56 W/m{sup 2} between 1750 and 2000. However, the direct and indirect aerosol effects are very sensitive to the black and organic carbon size distribution and consequential mixing state. The net radiative forcing change can vary between -0.32 to -0.75 W/m{sup 2} depending on these carbonaceous particle properties. Assuming that sulfates, nitrates and secondary organics form a coating shell around a black carbon core, rather than forming a uniformly mixed particles, changes the overall net radiative forcing from a negative to a positive number. Black carbon mitigation scenarios showed generally a benefit when mainly black carbon sources such as diesel emissions are reduced, reducing organic and black carbon sources such as bio-fuels, does not lead to reduced warming.

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

    Institute of Scientific and Technical Information of China (English)

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

    2014-01-01

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

  7. A Data Driven Framework for Integrating Regional Climate Models

    Science.gov (United States)

    Lansing, C.; Kleese van Dam, K.; Liu, Y.; Elsethagen, T.; Guillen, Z.; Stephan, E.; Critchlow, T.; Gorton, I.

    2012-12-01

    There are increasing needs for research addressing complex climate sensitive issues of concern to decision-makers and policy planners at a regional level. Decisions about allocating scarce water across competing municipal, agricultural, and ecosystem demands is just one of the challenges ahead, along with decisions regarding competing land use priorities such as biofuels, food, and species habitat. Being able to predict the extent of future climate change in the context of introducing alternative energy production strategies requires a new generation of modeling capabilities. We will also need more complete representations of human systems at regional scales, incorporating the influences of population centers, land use, agriculture and existing and planned electrical demand and generation infrastructure. At PNNL we are working towards creating a first-of-a-kind capability known as the Integrated Regional Earth System Model (iRESM). The fundamental goal of the iRESM initiative is the critical analyses of the tradeoffs and consequences of decision and policy making for integrated human and environmental systems. This necessarily combines different scientific processes, bridging different temporal and geographic scales and resolving the semantic differences between them. To achieve this goal, iRESM is developing a modeling framework and supporting infrastructure that enable the scientific team to evaluate different scenarios in light of specific stakeholder questions such as "How do regional changes in mean climate states and climate extremes affect water storage and energy consumption and how do such decisions influence possible mitigation and carbon management schemes?" The resulting capability will give analysts a toolset to gain insights into how regional economies can respond to climate change mitigation policies and accelerated deployment of alternative energy technologies. The iRESM framework consists of a collection of coupled models working with high

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

    KAUST Repository

    Evans, J. P.

    2013-03-26

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

  9. Agents, Bayes, and Climatic Risks - a modular modelling approach

    Directory of Open Access Journals (Sweden)

    A. Haas

    2005-01-01

    Full Text Available When insurance firms, energy companies, governments, NGOs, and other agents strive to manage climatic risks, it is by no way clear what the aggregate outcome should and will be. As a framework for investigating this subject, we present the LAGOM model family. It is based on modules depicting learning social agents. For managing climate risks, our agents use second order probabilities and update them by means of a Bayesian mechanism while differing in priors and risk aversion. The interactions between these modules and the aggregate outcomes of their actions are implemented using further modules. The software system is implemented as a series of parallel processes using the CIAMn approach. It is possible to couple modules irrespective of the language they are written in, the operating system under which they are run, and the physical location of the machine.

  10. Simulation of the arid climate of the southern great basin using a regional climate model

    International Nuclear Information System (INIS)

    As part of the development effort of a regional climate model (RCM) for the southern Great Basin, this paper presents a validation analysis of the climatology generated by a high-resolution RCM driven by observations. Two multiyear simulations were performed over the western United States with the RCM driven by European Centre for Medium-Range Weather Forecasts analyses of observations. This validation analysis is the first phase of a project to produce simulations of future climate scenarios over a region surrounding Yucca Mountain, Nevada, the only location currently being considered as a potential high-level nuclear-waste repository site. Model-produced surface air temperatures and precipitation were compared with observations from five southern Nevada stations located in the vicinity of Yucca Mountain. The seasonal cycles of temperature and precipitation were simulated well. Monthly and seasonal temperature biases were generally negative and largely explained by differences in elevation between the observing stations and the model topography. The model-simulated precipitation captured the extreme dryness of the Great Basin. Average yearly precipitation biases were mostly negative in the summer and positive in the winter. The number of simulated daily precipitation events for various precipitation intervals was within factors of 1.5-3.5 of observed. Overall, the model tended to overestimate the number of light precipitation events and underestimate the number of heavy precipitation events. At Yucca Mountain, simulated precipitation, soil moisture content, and water infiltration below the root zone (top 1 m) were maximized in the winter. Evaporation peaked in the spring after temperatures began to increase. The conclusion drawn from this validation analysis is that this high-resolution RCM simulates the regional surface climatology of the southern Great Basin reasonably well when driven by meteorological fields derived from observations. 26 refs., 9 figs., 4 tabs

  11. Climate Modeling at the Austrian Weather Service (ZAMG)

    Science.gov (United States)

    Matulla, C.; Anders, I.; Auer, I.

    2009-05-01

    In later 2007 the Austrian Weather Service (ZAMG) established a group that shall deal with climate change modeling. Two of the group's main goals are to provide climate change scenarios for the assessment of the impact on ecosystems and to reconstruct past climate states along with their change. The former aim is to derive estimates of might happen to our ecosystems under different emission-pathways, whilst the latter goal is to better understand what has caused characteristical changes, which are to be found in proxies. Both aims can be achieved by empirical or dynamical downscaling models, which are ultimately based on the reliability of the driving GCMs results. It is well known that empirical and dynamical downscaling models do have advantages and disadvantages, which are different. As such it appears reasonable to use the approach which is better adapted to the considered question. It may be meaningful to apply empirical downscaling if long periods of time (such as substantial parts of the Holocene) are in the center of attention, whereas dynamical downscaling may be better suited to address questions that are related to decades. Up to now we were more involved with empirical downscaling that helped us to work together with scientists assessing the impact on ecosystems, as for instance, fish in a river (Matulla et al. 2007), forests (Lexer et al. 2002) or phenological phases (Scheifinger et al. 2007). After catching a glimpse of those results, we will turn to dynamical modeling. Here we would like to present findings from case studies, which are related to the more recent past. Our next target is the modelling of possible future climate conditions within the Greater Alpine Region (GAR, see e.g. Auer et al. 2007) as well as some characteristical periods throughout the Holocene as for instance the 8.2k event. This event is to be found in a variety of proxies within and also outside GAR. Auer I., Boehm R., Jurkovic A., Lipa W., Orlik A., Potzmann R., Schoener W

  12. 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...

  13. 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.

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

    CERN Document Server

    Pisnichenko, I A

    2007-01-01

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

  15. Evolution of Climate Science Modelling Language within international standards frameworks

    Science.gov (United States)

    Lowe, Dominic; Woolf, Andrew

    2010-05-01

    The Climate Science Modelling Language (CSML) was originally developed as part of the NERC Data Grid (NDG) project in the UK. It was one of the first Geography Markup Language (GML) application schemas describing complex feature types for the metocean domain. CSML feature types can be used to describe typical climate products such as model runs or atmospheric profiles. CSML has been successfully used within NDG to provide harmonised access to a number of different data sources. For example, meteorological observations held in heterogeneous databases by the British Atmospheric Data Centre (BADC) and Centre for Ecology and Hydrology (CEH) were served uniformly as CSML features via Web Feature Service. CSML has now been substantially revised to harmonise it with the latest developments in OGC and ISO conceptual modelling for geographic information. In particular, CSML is now aligned with the near-final ISO 19156 Observations & Measurements (O&M) standard. CSML combines the O&M concept of 'sampling features' together with an observation result based on the coverage model (ISO 19123). This general pattern is specialised for particular data types of interest, classified on the basis of sampling geometry and topology. In parallel work, the OGC Met Ocean Domain Working Group has established a conceptual modelling activity. This is a cross-organisational effort aimed at reaching consensus on a common core data model that could be re-used in a number of met-related application areas: operational meteorology, aviation meteorology, climate studies, and the research community. It is significant to note that this group has also identified sampling geometry and topology as a key classification axis for data types. Using the Model Driven Architecture (MDA) approach as adopted by INSPIRE we demonstrate how the CSML application schema is derived from a formal UML conceptual model based on the ISO TC211 framework. By employing MDA tools which map consistently between UML and GML we

  16. Decadal climate predictions with an high resolution coupled model

    Science.gov (United States)

    Monerie, P. A.; Valcke, S.; Moine, M. P.; Maisonnave, E.; Coquart, L.; Cassou, C.; Terray, L.

    2014-12-01

    We analyze the decadal prediction skill of sea surface temperature variability with a high resolution coupled Ocean-Atmosphere General Circulation Model (OAGCM). The HR CERFACS was developed at the CERFACS (Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique) laboratory in the framework of the EU-FP7 SPECS (Seasonal-to-decadal climate Predictions for the improvement of European Climate Services) project in order to address the question of decadal predictability with the use of a high spatial resolution. The atmospheric model is ARPEGE/IFS with a T359 spectral truncature and the oceanic model is NEMO at 0.25° resolution including the LIM2 sea ice model. Each hindcasts consist of a 10-members ensemble integrated over a 10-years period. These hindcasts are full-field initialized every year from 1993 to 2009 and initial oceanic state is given by the GLORYS2V1 (0.25° resolution) sea-surface temperatures. Members of a given ensemble (one initialization date) are generated by perturbations of the atmospheric initial conditions. We study the predictability of the global sea-surface temperature focusing on the Atlantic Multidecadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO), the North Atlantic Subpolar Gyre (SPG) and the El-Nino Southern Oscillation (ENSO). We also investigate the prediction skill of the Atlantic Meridional Overturning Circulation (AMOC).

  17. Do projections from bioclimatic envelope models and climate change metrics match?

    DEFF Research Database (Denmark)

    Garcia, Raquel A.; Cabeza, Mar; Altwegg, Res;

    2016-01-01

    Aim: Bioclimatic envelope models are widely used to describe changes in climatically suitable areas for species under future climate scenarios. Climate change metrics are applied independently of species data to characterize the spatio-temporal dynamics of climate, and have also been used...... for sub-Saharan Africa with ensembles of bioclimatic envelope models for 2723 species of amphibians, snakes, mammals and birds. For each taxonomic group, we performed three comparisons between the two approaches: (1) is projected change in local climatic suitability (models) greater in grid cells...... with larger temporal differences in local climate (metrics); (2) are projected losses or gains of climatically suitable areas (models) greater for species in grid cells with climates that are projected to be less or more available in the future, respectively (metrics); and (3) are projected shifts...

  18. 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

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

    OpenAIRE

    Foley, Aideen

    2010-01-01

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

  20. Socioeconomic Drought in a Changing Climate: Modeling and Management

    Science.gov (United States)

    AghaKouchak, Amir; Mehran, Ali; Mazdiyasni, Omid

    2016-04-01

    Drought is typically defined based on meteorological, hydrological and land surface conditions. However, in many parts of the world, anthropogenic changes and water management practices have significantly altered local water availability. Socioeconomic drought refers to conditions whereby the available water supply cannot satisfy the human and environmental water needs. Surface water reservoirs provide resilience against local climate variability (e.g., droughts), and play a major role in regional water management. This presentation focuses on a framework for describing socioeconomic drought based on both water supply and demand information. We present a multivariate approach as a measure of socioeconomic drought, termed Multivariate Standardized Reliability and Resilience Index (MSRRI; Mehran et al., 2015). This model links the information on inflow and surface reservoir storage to water demand. MSRRI integrates a "top-down" and a "bottom-up" approach for describing socioeconomic drought. The "top-down" component describes processes that cannot be simply controlled or altered by local decision-makers and managers (e.g., precipitation, climate variability, climate change), whereas the "bottom-up" component focuses on the local resilience, and societal capacity to respond to droughts. The two components (termed, Inflow-Demand Reliability (IDR) indicator and Water Storage Resilience (WSR) indicator) are integrated using a nonparametric multivariate approach. We use this framework to assess the socioeconomic drought during the Australian Millennium Drought (1998-2010) and the 2011-2014 California Droughts. MSRRI provides additional information on socioeconomic drought onset, development and termination based on local resilience and human demand that cannot be obtained from the commonly used drought indicators. We show that MSRRI can be used for water management scenario analysis (e.g., local water availability based on different human water demands scenarios). Finally

  1. Pleistocene Climate, Phylogeny, and Climate Envelope Models: An Integrative Approach to Better Understand Species' Response to Climate Change

    OpenAIRE

    A Michelle Lawing; David Polly, P

    2011-01-01

    Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM) and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we sy...

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

    Science.gov (United States)

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

    2008-01-01

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

  3. A multi-model study of impacts of climate change on surface ozone in Europe

    OpenAIRE

    Langner, J.; M. Engardt; A. Baklanov; J. H. Christensen; Gauss, M.; C. Geels; G. B. Hedegaard; Nuterman, R.; Simpson, D.; Soares, J; Sofiev, M.; Wind, P.; Zakey, A.

    2012-01-01

    The impact of climate change on surface ozone over Europe was studied using four offline regional chemistry transport models (CTMs) and one online regional integrated climate-chemistry model (CCM), driven by the same global projection of future climate under the SRES A1B scenario. Anthropogenic emissions of ozone precursors from RCP4.5 for year 2000 were used for simulations of both present and future periods in order to isolate the impact of climate change and to assess the...

  4. Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century

    OpenAIRE

    Kerry A. Emanuel

    2013-01-01

    A recently developed technique for simulating large [O(104)] numbers of tropical cyclones in climate states described by global gridded data is applied to simulations of historical and future climate states simulated by six Coupled Model Intercomparison Project 5 (CMIP5) global climate models. Tropical cyclones downscaled from the climate of the period 1950–2005 are compared with those of the 21st century in simulations that stipulate that the radiative forcing from greenhouse gases increases...

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

    Science.gov (United States)

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

    2016-04-01

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

  6. An efficient climate model with water isotope physics: NEEMY

    Science.gov (United States)

    Hu, J.; Emile-Geay, J.

    2015-12-01

    This work describes the development of an isotope-enabled atmosphere-ocean global climate model, NEEMY. This is a model of intermediate complexity, which can run 100 model years in 30 hours using 33 CPUs. The atmospheric component is the SPEEDY-IER (Molteni et al. 2003; Dee et al. 2015a), which is a water isotope-enabled (with equilibrium and kinetic fractionation schemes in precipitation, evaporation and soil moisture) simplified atmospheric general circulation model, with T30 horizontal resolution and 8 vertical layers. The oceanic component is NEMO 3.4 (Madec 2008), a state-of-the-art oceanic model (~2° horizontal resolution and 31 vertical layers) with an oceanic isotope module (a passive tracer scheme). A 1000-year control run shows that NEEMY is stable and its energy is conserved. The mean state is comparable to that of CMIP3-era CGCMs, though much cheaper to run. Atmospheric teleconnections such as the NAO and PNA are simulated very well. NEEMY also simulates the oceanic meridional overturning circulation well. The tropical climate variability is weaker than observations, and the climatology exhibits a double ITCZ problem despite bias corrections. The standard deviation of the monthly mean Nino3.4 index is 0.61K, compared to 0.91K in observations (Reynolds et al. 2002). We document similarities and differences with a close cousin, SPEEDY-NEMO (Kucharski et al. 2015). With its fast speed and relatively complete physical processes, NEEMY is suitable for paleoclimate studies ; we will present some forced simulations of the past millennium and their use in forward-modeling climate proxies, via proxy system models (PSMs, Dee et al 2015b). References Dee, S., D. Noone, N. Buenning, J. Emile-Geay, and Y. Zhou, 2015a: SPEEDY-IER: A fast atmospheric GCM with water isotope physics. J. Geophys. Res. Atmos., 120: 73-91. doi:10.1002/2014JD022194. Dee, S. G., J. Emile-Geay, M. N. Evans, Allam, A., D. M. Thompson, and E. J. Steig, 2015b: PRYSM: an open-source framework

  7. The Precession Index and a Nonlinear Energy Balance Climate Model

    Science.gov (United States)

    Rubincam, David

    2004-01-01

    A simple nonlinear energy balance climate model yields a precession index-like term in the temperature. Despite its importance in the geologic record, the precession index e sin (Omega)S, where e is the Earth's orbital eccentricity and (Omega)S is the Sun's perigee in the geocentric frame, is not present in the insolation at the top of the atmosphere. Hence there is no one-for-one mapping of 23,000 and 19,000 year periodicities from the insolation to the paleoclimate record; a nonlinear climate model is needed to produce these long periods. A nonlinear energy balance climate model with radiative terms of form T n, where T is surface temperature and n less than 1, does produce e sin (omega)S terms in temperature; the e sin (omega)S terms are called Seversmith psychroterms. Without feedback mechanisms, the model achieves extreme values of 0.64 K at the maximum orbital eccentricity of 0.06, cooling one hemisphere while simultaneously warming the other; the hemisphere over which perihelion occurs is the cooler. In other words, the nonlinear energy balance model produces long-term cooling in the northern hemisphere when the Sun's perihelion is near northern summer solstice and long-term warming in the northern hemisphere when the aphelion is near northern summer solstice. (This behavior is similar to the inertialess gray body which radiates like T 4, but the amplitude is much lower for the energy balance model because of its thermal inertia.) This seemingly paradoxical behavior works against the standard Milankovitch model, which requires cool northern summers (Sun far from Earth in northern summer) to build up northern ice sheets, so that if the standard model is correct it must be more efficient than previously thought. Alternatively, the new mechanism could possibly be dominant and indicate southern hemisphere control of the northern ice sheets, wherein the southern oceans undergo a long-term cooling when the Sun is far from the Earth during northern summer. The cold

  8. Linking seasonal climate forecasts with crop models in Iberian Peninsula

    Science.gov (United States)

    Capa, Mirian; Ines, Amor; Baethgen, Walter; Rodriguez-Fonseca, Belen; Han, Eunjin; Ruiz-Ramos, Margarita

    2015-04-01

    Translating seasonal climate forecasts into agricultural production forecasts could help to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. In this study, we use seasonal rainfall forecasts and crop models to improve predictability of wheat yield in the Iberian Peninsula (IP). Additionally, we estimate economic margins and production risks associated with extreme scenarios of seasonal rainfall forecast. This study evaluates two methods for disaggregating seasonal climate forecasts into daily weather data: 1) a stochastic weather generator (CondWG), and 2) a forecast tercile resampler (FResampler). Both methods were used to generate 100 (with FResampler) and 110 (with CondWG) weather series/sequences for three scenarios of seasonal rainfall forecasts. Simulated wheat yield is computed with the crop model CERES-wheat (Ritchie and Otter, 1985), which is included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5, Hoogenboom et al., 2010). Simulations were run at two locations in northeastern Spain where the crop model was calibrated and validated with independent field data. Once simulated yields were obtained, an assessment of farmer's gross margin for different seasonal climate forecasts was accomplished to estimate production risks under different climate scenarios. This methodology allows farmers to assess the benefits and risks of a seasonal weather forecast in IP prior to the crop growing season. The results of this study may have important implications on both, public (agricultural planning) and private (decision support to farmers, insurance companies) sectors. Acknowledgements Research by M. Capa-Morocho has been partly supported by a PICATA predoctoral fellowship of the Moncloa Campus of International Excellence (UCM-UPM) and MULCLIVAR project (CGL2012-38923-C02-02) References Hoogenboom, G. et al., 2010. The Decision

  9. Modeling, Estimation and Control of Indoor Climate in Livestock Buildings

    DEFF Research Database (Denmark)

    Wu, Zhuang

    The main objective of this research is to design an efficient control system for the indoor climate of a large-scale partition-less livestock building, in order to maintain a healthy, comfortable and economically energy consuming indoor environment for the agricultural animals and farmers. In this...... resilience of the control system to disturbances beyond its bandwidth, increases the manipulators utilization efficiency, and reduces energy consumption by solving a constrained convex optimization. Through comparative simulation results analysis, the proposed modeling and control technique is proved to be...... scale livestock buildings, and could be considered as an alternative solution to the current used decentralized PID controller....

  10. Parametrization of contrails in a comprehensive climate model

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-12-31

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

  11. The influence of model structure on groundwater recharge rates in climate-change impact studies

    Science.gov (United States)

    Moeck, Christian; Brunner, Philip; Hunkeler, Daniel

    2016-02-01

    Numerous modeling approaches are available to provide insight into the relationship between climate change and groundwater recharge. However, several aspects of how hydrological model choice and structure affect recharge predictions have not been fully explored, unlike the well-established variability of climate model chains—combination of global climate models (GCM) and regional climate models (RCM). Furthermore, the influence on predictions related to subsoil parameterization and the variability of observation data employed during calibration remain unclear. This paper compares and quantifies these different sources of uncertainty in a systematic way. The described numerical experiment is based on a heterogeneous two-dimensional reference model. Four simpler models were calibrated against the output of the reference model, and recharge predictions of both reference and simpler models were compared to evaluate the effect of model structure on climate-change impact studies. The results highlight that model simplification leads to different recharge rates under climate change, especially under extreme conditions, although the different models performed similarly under historical climate conditions. Extreme weather conditions lead to model bias in the predictions and therefore must be considered. Consequently, the chosen calibration strategy is important and, if possible, the calibration data set should include climatic extremes in order to minimise model bias introduced by the calibration. The results strongly suggest that ensembles of climate projections should be coupled with ensembles of hydrogeological models to produce credible predictions of future recharge and with the associated uncertainties.

  12. Climate change and voltinism in Californian insect pest species: sensitivity to location, scenario and climate model choice.

    Science.gov (United States)

    Ziter, Carly; Robinson, Emily A; Newman, Jonathan A

    2012-09-01

    Experimental studies of the impact of climatic change are hampered by their inability to consider multiple climate change scenarios and indeed often consider no more than simple climate sensitivity such as a uniform increase in temperature. Modelling efforts offer the ability to consider a much wider range of realistic climate projections and are therefore useful, in particular, for estimating the sensitivity of impact predictions to differences in geographical location, and choice of climate change scenario and climate model projections. In this study, we used well-established degree-day models to predict the voltinism of 13 agronomically important pests in California, USA. We ran these models using the projections from three Atmosphere-Ocean Coupled Global Circulation Models (AOCGCMs or GCMs), in conjunction with the SRES scenarios. We ran these for two locations representing northern and southern California. We did this for both the 2050s and 2090s. We used anova to partition the variation in the resulting voltinism among time period, climate change scenario, GCM and geographical location. For these 13 pest species, the choice of climate model explained an average of 42% of the total variation in voltinism, far more than did geographical location (33%), time period (17%) or scenario (1%). The remaining 7% of the variation was explained by various interactions, of which the location by GCM interaction was the strongest (5%). Regardless of these sources of uncertainty, a robust conclusion from our work is that all 13 pest species are likely to experience increases in the number of generations that they complete each year. Such increased voltinism is likely to have significant consequences for crop protection and production. PMID:24501055

  13. Multi-scale modelling to improve climate data for building energy models

    OpenAIRE

    Mauree, Dasaraden; Kämpf, Jérôme Henri; Scartezzini, Jean-Louis

    2015-01-01

    The recent AR5 report from the Intergovernmental Panel on Climate Change has again stressed on the need for mitigation and adaptation measures to tackle issues related to climate change. Tackling future urban planning and energy efficiency in the building sector is crucial as they account for almost 40% of energy use in developed countries. A one-dimensional canopy interface module (CIM) was recently developed to improve the surface representation in meteorological models and to enhance boun...

  14. Climate Change and Market Collapse: A Model Applied to Darfur

    Directory of Open Access Journals (Sweden)

    Ola Olsson

    2016-03-01

    Full Text Available A recurring argument in the global debate is that climate deterioration is likely to make social conflicts over diminishing natural resources more common in the future. The exact mechanism behind such a development has so far not been successfully characterized in the literature. In this paper, we present a general model of a community populated by farmers and herders who can either divide up land in a market economy or in autarky. The key insight from our model is that decreasing resources can make trade between the two groups collapse, which in turn makes each group’s welfare independent of that of the other. Predictions from the model are then applied to the conflict in Darfur. Our analysis suggests that three decades of drought in the area can at least partially explain the observed disintegration of markets and the subsequent rise of social tensions.

  15. Cloud-radiation interactions and their parameterization in climate models

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-11-01

    This report contains papers from the International Workshop on Cloud-Radiation Interactions and Their Parameterization in Climate Models met on 18--20 October 1993 in Camp Springs, Maryland, USA. It was organized by the Joint Working Group on Clouds and Radiation of the International Association of Meteorology and Atmospheric Sciences. Recommendations were grouped into three broad areas: (1) general circulation models (GCMs), (2) satellite studies, and (3) process studies. Each of the panels developed recommendations on the. themes of the workshop. Explicitly or implicitly, each panel independently recommended observations of basic cloud microphysical properties (water content, phase, size) on the scales resolved by GCMs. Such observations are necessary to validate cloud parameterizations in GCMs, to use satellite data to infer radiative forcing in the atmosphere and at the earth`s surface, and to refine the process models which are used to develop advanced cloud parameterizations.

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

    International Nuclear Information System (INIS)

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

  17. Integrated climate modelling at the Kiel Institute for World Economics: The DART Model and its applications.

    OpenAIRE

    Deke, Oliver; Peterson, Sonja

    2003-01-01

    The aim of this paper is to give an overview over the DART model and its applications. The main focus is on the implementation of climate impacts into DART in the course of coupling DART to the ocean-atmosphere model and on the associated empirical problems. The basic DART model and some applications are presented in the next section. Section 3 describes in detail how the economic impacts of climate change on the agricultural sector and the impact of sea level rise are implemented in DART. Se...

  18. Emulating Future Climate Projections from Global Climate Models: Methodologies and Challenges

    Science.gov (United States)

    Murphy, J.; Tebaldi, C.

    2014-12-01

    Pattern scaling methods have been used since the 1990s to estimate the results of global climate models (GCMs), in particular for emissions scenarios for which GCM simulations are not available. The basic method uses global mean surface temperature as the scaling variable, and relies on the assumption of a constant spatial pattern of change per unit global warming. This presentation will briefly review the status of pattern scaling science, using results from the published literature, and from a recent workshop held at NCAR. Successes and challenges will be illustrated of the use of pattern scaling to provide information on future changes for use by the impacts and integrated assessment modelling communities. This activity reflects anticipation of an enhanced role for emulation methods in a new process underway to produce integrated scenarios of future climate and societal change, which extends the number of scenarios of interest beyond the small set of RCPs used in GCM simulations for CMIP5. Relevant challenges include effects of non-linearities caused by: different responses to different levels of greenhouse gas forcing; different timescales of regional response for alternative forcing pathways leading to the same global temperature response; combining the effects of multiple individual forcing agents. Understanding and projecting the responses to forcing agents such as aerosols and land use is likely to be particularly important in emulating changes during the next few decades. Further challenges include how to represent uncertainties and multivariate changes robustly in order to provide a basis for realistic assessments of impacts and risks, and extensions to the basic pattern scaling paradigm. Such extensions include consideration of scaling variables other than global mean temperature, and the recent development of new approaches to emulation using alternative statistical techniques and different physical assumptions.

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

    Directory of Open Access Journals (Sweden)

    Orien M W Richmond

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

  20. Using Weather to Model Impacts of Climate Change on Terrestrial Birds

    Science.gov (United States)

    Schuetz, J.; Distler, T.; Soykan, C.; Velásquez-Tibatá, J.; Langham, G.

    2013-12-01

    Climate change is expected to disrupt terrestrial ecosystems in the coming century in part by redistributing the species they contain. To date, research on species' responses to climate change has focused primarily on how shifts in climatic means will affect their future distributions. The influence of climatic variability, on the other hand, has received relatively little attention, even though it has the potential to significantly affect species distributions. Using historical observations of 20 species of wintering birds, we assessed the consequences of building species distribution models with two sets of climate data: 1) mean climate from 1971-2000 and 2) 1971-2000 climates parsed on an annual basis to reflect climatic variability experienced by species. We evaluated the predictive performance of the resulting species distribution models built with different climate data sets by projecting them to 2001-2009 climates, a period for which independent species occurrence data were also available. Species distribution models constructed with climate data parsed on an annual basis (i.e., those explicitly accounting for annual variability) showed higher predictive performance than models constructed with mean climate data. By making projections of the two sets of models onto current and future climate surfaces, we were also able to quantify, in geographic space, the degree to which descriptions of species distributions differed. For some species, the two approaches resulted in markedly different geographic distributions, particularly when projected on future climate surfaces. These results demonstrate the value of incorporating climatic variability into species distribution models and help to build a foundation for understanding responses of terrestrial ecosystems to coming climate change.

  1. Drivers of organizational creativity: A path model of creative climate in pharmaceutical R&D

    OpenAIRE

    Sundgren, Mats; Dimenäs, Elof; Gustafsson, Jan-Eric; Selart, Marcus

    2005-01-01

    A path model of organizational creativity was presented; it conceptualized the influences of information sharing, learning culture, motivation, and networking on creative climate. A structural equation model was fitted to data from the pharmaceutical industry to test the proposed model. The model accounted for 86% of the variance in the creative climate-dependent variable. Information sharing had a positive effect on learning culture, which in turn had a positive effect on creative climate, w...

  2. Modelling robust crop production portfolios to assess agricultural vulnerability to climate change

    OpenAIRE

    Mitter, Hermine; Heumesser, Christine; Schmid, Erwin

    2014-01-01

    Agricultural vulnerability is assessed by (i) modelling climate change impacts on crop yields and gross margins, (ii) identifying crop production portfolios for adaptation, and (iii) analyzing the effect of agricultural policies and risk aversion on adaptive capacity. We combine, spatially explicit, a statistical climate change model, the bio-physical process model EPIC and a portfolio optimization model. Under climate change, optimal portfolios include higher shares of intensive crop managem...

  3. Slarti: A boundary condition editor for a coupled climate model

    Science.gov (United States)

    Mickelson, S. A.; Jacob, R. L.; Pierrehumbert, R.

    2006-12-01

    One of the largest barriers to making climate models more flexible is the difficulty in creating new boundary conditions, especially for "deep time" paleoclimate cases where continents are in different positions. Climate models consist of several mutually-interacting component models and the boundary conditions must be consistent between them. We have developed a program called Slarti which uses a Graphical User Interface and a set of consistency rules to aid researchers in creating new, consistent, boundary condition files for the Fast Ocean Atmosphere Model (FOAM). Users can start from existing mask, topography, or bathymetry data or can build a "world" entirely from scratch (e.g. a single island continent). Once a case has been started, users can modify mask, vegetation, bathymetry, topography, and river flow fields by drawing new data through a "paint" interface. Users activate a synchronization button which goes through the fields to eliminate inconsistencies. When the changes are complete and save is selected, Slarti creates all the necessary files for an initial run of FOAM. The data is edited at the highest resolution (the ocean-land surface in FOAM) and then interpolated to the atmosphere resolution. Slarti was implemented in Java to maintain portability across platforms. We also relied heavily on Java Swing components to create the interface. This allowed us to create an object-oriented interface that could be used on many different systems. Since Slarti allows users to visualize their changes, they are able to see areas that may cause problems when the model is ran. Some examples would be lakes from the river flow field and narrow trenches within the bathymetry. Through different checks and options available through its interface, Slarti makes the process of creating new boundary conditions for FOAM easier and faster while reducing the chance for user errors.

  4. The MARKAL-MACRO model and the climate change

    Energy Technology Data Exchange (ETDEWEB)

    Kypreos, S. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

    1996-07-01

    MARKAL-MACRO and its extensions is a model appropriate to study partial and general equilibrium in the energy markets and the implications of the carbon dioxide mitigation policy. The main advantage of MM is the explicit treatment of energy demand, supply and conversion technologies, including emission control and conservation options, within a general equilibrium framework. The famous gap between top-down and bottom-up models is resolved and the economic implications of environmental and supply policy constraints can be captured either in an aggregated (Macro) or in a sectorial (Micro) level. The multi-regional trade version of the model allows to study questions related to efficient and equitable allocation of cost and benefits associated with the climate change issue. Finally, the stochastic version of the model allows to assess policies related to uncertain and even catastrophic effects and define appropriate hedging strategies. The report is divided in three parts: - the first part gives an overview of the new model structure. It describes its macro economic part and explains its calibration, - the second part refers to the model applications for Switzerland when analyzing the economic implications of curbing CO{sub 2} emissions or policies related to the introduction of a carbon tax, including a hedging strategy, - the last part is organized in form of Appendices and gives a mathematical description and some potential extensions of the model. It describes also a sensitivity analysis done with MARKAL-MACRO in 1992. (author) figs., tabs., refs.

  5. The MARKAL-MACRO model and the climate change

    International Nuclear Information System (INIS)

    MARKAL-MACRO and its extensions is a model appropriate to study partial and general equilibrium in the energy markets and the implications of the carbon dioxide mitigation policy. The main advantage of MM is the explicit treatment of energy demand, supply and conversion technologies, including emission control and conservation options, within a general equilibrium framework. The famous gap between top-down and bottom-up models is resolved and the economic implications of environmental and supply policy constraints can be captured either in an aggregated (Macro) or in a sectorial (Micro) level. The multi-regional trade version of the model allows to study questions related to efficient and equitable allocation of cost and benefits associated with the climate change issue. Finally, the stochastic version of the model allows to assess policies related to uncertain and even catastrophic effects and define appropriate hedging strategies. The report is divided in three parts: - the first part gives an overview of the new model structure. It describes its macro economic part and explains its calibration, - the second part refers to the model applications for Switzerland when analyzing the economic implications of curbing CO2 emissions or policies related to the introduction of a carbon tax, including a hedging strategy, - the last part is organized in form of Appendices and gives a mathematical description and some potential extensions of the model. It describes also a sensitivity analysis done with MARKAL-MACRO in 1992. (author) figs., tabs., refs

  6. Evaluating cloud tuning in a climate model with satellite observations

    Science.gov (United States)

    Suzuki, K.; Golaz, J.; Stephens, G. L.

    2013-12-01

    Climate model representation of the aerosol indirect effect is largely dependent on how to tune uncertain parameters in the models. The threshold particle radius triggering the warm rain formation, among others, is one particular 'tunable knob' that severely affects the indirect radiative forcing. Alternate values of the model's particular parameter within uncertainty have been shown to produce severely different historical temperature tends due to differing magnitude of aerosol indirect forcing. This study examines the validity of three different threshold radii assumed in GFDL CM3 with satellite observations in an attempt to constrain which value is more plausible than others. For this purpose, the methodologies developed to analyze multi-sensor satellite observations are employed to construct the statistics that fingerprint process-level signatures of the warm rain formation. The statistics are then used as observation-based metrics and compared between the model and satellite observations to examine how the alternate model configurations lead to different microphysical characteristics and to evaluate how they compare to satellite observations. The results show that the threshold radius that best reproduces satellite-observed microphysical statistics leads to the historical temperature trend that worst matches to observed trend and vice-versa. This inconsistency between the 'bottom-up' process-based constraint and the 'top-down' temperature trend constraint implies the presence of compensating errors in the model. This study underscores the importance of observation-based, process-level constraints on model microphysics uncertainties for more reliable predictions of aerosol indirect forcing.

  7. Modelling the economic impacts of addressing climate change

    International Nuclear Information System (INIS)

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

  8. Progress in the Development and Application of Climate Ocean Models and Ocean-Atmosphere Coupled Models in China

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A review is presented about the development and application of climate ocean models and oceanatmosphere coupled models developed in China as well as 8 review of climate variability and climate change studies performed with these models.While the history of model development is briefly reviewed,emphasis has been put on the achievements made in the last five years.Advances in model development are described along with a summary on scientific issues addressed by using these models.The focus of the review is the climate ocean models and the associated coupled models,including both global and regional models,developed at the Institute of Atmospheric Physics,Chinese Academy of Sciences.The progress of either coupled model development made by other institutions or climate modeling using internationally developed models also is reviewed.

  9. Holocene glacier variability: three case studies using an intermediate-complexity climate model

    NARCIS (Netherlands)

    Weber, S.L.; Oerlemans, J.

    2003-01-01

    Synthetic glacier length records are generated for the Holocene epoch using a process-based glacier model coupled to the intermediate-complexity climate model ECBilt. The glacier model consists of a massbalance component and an ice-flow component. The climate model is forced by the insolation change

  10. Estimates of Climate Change Impact on River Discharge in Japan Based on a Super-High-Resolution Climate Model

    OpenAIRE

    Yoshinobu Sato; Toshiharu Kojiri; Yuri Michihiro; Yasushi Suzuki; and Eiichi Nakakita

    2012-01-01

    The impact of climate change on river discharge was assessed by hydrological simulations for several major river basins in Japan using the latest version of a super-high-resolution atmospheric general circulation model (AGCM) with a horizontal resolution of about 20 km. Projections were made using two different datasets, one representing the present climate (1980 - 1999) and the other representing the end of the 21st century (2080 - 2099) assuming the SRES A1B scenario. River discharge was es...

  11. Assessing Low Frequency Climate Signals in Global Circulation Models using an Integrated Hydrologic Model

    Science.gov (United States)

    Niswonger, R. G.; Huntington, J. L.

    2010-12-01

    Climate signals with periodicities of approximately one decade are pervasive in long-term streamflow records for streams in the western United States that receive significant baseflow. The driver of these signals is unknown but hypotheses have been presented, such as variations in solar input to the Earth, or harmonics of internal (i.e., processes in the ocean and troposphere) forcings like the Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO). Climate signals of about 1 decade are important for several reasons, including their relation to climate extremes (i.e., droughts and floods), and because the drivers of these climate signals are clearly important for projecting future climate conditions. Furthermore, identifying the drivers of these climate signals is important for separating the relative impacts of human production of greenhouse gases on global warming verses external drivers of climate change, such as sunspot cycles. Studies using Global Circulation Models (GCMs) that do not incorporate solar forcings associated with sun spots have identified oscillations of about a decade long in certain model output. However, these oscillations can be difficult to identify in simulated precipitation data due to high frequency variations (less than 1 year) that obscure low frequency (decade) signals. We have found that simulations using an integrated hydrologic model (IHM) called GSFLOW reproduce decade-long oscillations in streamflow when driven by measured precipitation records, and that these oscillations are also present in simulated streamflow when driven by temperature and precipitation data projected by GCMs. Because the IHM acts as a low-pass filter that reveals low frequency signals (i.e. decadal oscillations), they can be used to assess GCMs in terms of their ability to reproduce important low-frequency climate oscillations. We will present results from GSFLOW applied to three basins in the eastern Sierra Nevada driven by 100 years of

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

    International Nuclear Information System (INIS)

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

  13. Coupled heat and moisture transport model for underground climate prediction

    International Nuclear Information System (INIS)

    This paper discusses a numerical code which is being developed to analyze the climate parameters of the ventilating air in a representative drift of the proposed high-level waste repository. In the present stage of the model, coupled heat and moisture transfer with a pre-determined wetness factor is assumed for the drift surfaces. The model is used to predict permanent water and heat removal from the repository by the ventilating air. It is concluded that moderate ventilation of 25-35 m3/s sufficient for cooling during drift emplacement, and a small quantity of 1 m3/s can remove a significant amount of water and heat during the pre-closure time period. However, intensive ventilation during preclosure is inefficient in reducing drift surface temperatures and peak temperatures that will develop after closure of the repository, and this fact underlines the importance of thermal enhancement techniques to supplement ventilation

  14. Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method.

    Science.gov (United States)

    Kara, Fatih; Yucel, Ismail

    2015-09-01

    This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained. PMID:26293893

  15. 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.

  16. Possible impact of climate change on meningitis in northwest Nigeria: an assessment using CMIP5 climate model simulations

    Science.gov (United States)

    Abdussalam, Auwal; Monaghan, Andrew; Steinhoff, Daniel; Dukic, Vanja; Hayden, Mary; Hopson, Thomas; Thornes, John; Leckebusch, Gregor

    2014-05-01

    Meningitis remains a major health burden throughout Sahelian Africa, especially in heavily-populated northwest Nigeria. Cases exhibit strong sensitivity to intra- and inter-annual climate variability, peaking during the hot and dry boreal spring months, raising concern that future climate change may increase the incidence of meningitis in the region. The impact of future climate change on meningitis risk in northwest Nigeria is assessed by forcing an empirical model of meningitis with monthly simulations from an ensemble of thirteen statistically downscaled global climate model projections from the Coupled Model Intercomparison Experiment Phase 5 (CMIP5) for RCPs 2.6, 6.0 and 8.5 scenarios. The results suggest future temperature increases due to climate change has the potential to significantly increase meningitis cases in both the early and late 21st century, and to increase the length of the meningitis season in the late century. March cases may increase from 23 per 100,000 people for present day (1990-2005), to 29-30 per 100,000 (p<0.01) in the early century (2020-2035) and 31-42 per 100,000 (p<0.01) in the late century (2060-2075), the range being dependent on the emissions scenario. It is noteworthy that these results represent the climatological potential for increased cases due to climate change, as we assume current prevention and treatment strategies remain similar in the future.

  17. Regional Modeling of Climate Change Impacts on Groundwater Resources Sustainability in Peninsular Malaysia

    OpenAIRE

    K.A. Mogaji; H. S. Lim; Abdullah, K.

    2013-01-01

    Projection of climate for the 2020s and 2080s from an ensemble of global climate models (GCMs) run under A2, A1B and B1 emission scenarios are used for regional modeling of climate change impacts on groundwater resources sustainability in Peninsular Malaysia. Few studies that have modeled climate change impacts on groundwater resources used the physically-based surface-subsurface flow model. In this paper, the suite of GCM outputs were modeled for the impact studies via integrative approach i...

  18. A new time-stepping method for regional climate models

    Science.gov (United States)

    Williams, P. D.

    2010-12-01

    The dynamical cores of many regional climate models use the Robert-Asselin filter to suppress the spurious computational mode of the leapfrog scheme. Unfortunately, whilst successfully eliminating the unwanted mode, the Robert-Asselin filter also weakly suppresses the physical solution and degrades the numerical accuracy. These two concomitant problems occur because the filter does not conserve the mean state, averaged over the three time slices on which it operates. This presentation proposes a simple modification to the Robert-Asselin filter, which does conserve the three-time-level mean state. When used in conjunction with the leapfrog scheme, the modification vastly reduces the artificial damping of the physical solution. Correspondingly, the modification increases the numerical accuracy for amplitude errors by two orders, yielding third-order accuracy. The modified filter may easily be incorporated into existing regional climate models, via the addition of only a few lines of code that are computationally very inexpensive. Results will be shown from recent implementations of the modified filter in various models. The modification will be shown to reduce model biases and to significantly improve the predictive skill. Magnitude of the complex amplification factor as a function of the non-dimensional time step, for leapfrog integrations. This quantity would be identical to 1 for a perfect numerical scheme. Clearly, the filter proposed here (case α=0.53) has much smaller numerical errors than the original Robert-Asselin filter (case α=1). Moreover, the proposed filter is trivial to implement and is no more computationally expensive. Taken from Williams (2009; Monthly Weather Review).

  19. Climate-based risk models for Fasciola hepatica in Colombia

    Directory of Open Access Journals (Sweden)

    Natalia Valencia-López

    2012-09-01

    Full Text Available A predictive Fasciola hepatica model, based on the growing degree day-water budget (GDD-WB concept and the known biological requirements of the parasite, was developed within a geographical information system (GIS in Colombia. Climate-based forecast index (CFI values were calculated and represented in a national-scale, climate grid (18 x 18 km using ArcGIS 9.3. A mask overlay was used to exclude unsuitable areas where mean annual temperature exceeded 25 °C, the upper threshold for development and propagation of the F. hepatica life cycle. The model was then validated and further developed by studies limited to one department in northwest Colombia. F. hepatica prevalence data was obtained from a 2008-2010 survey in 10 municipalities of 6,016 dairy cattle at 673 herd study sites, for which global positioning system coordinates were recorded. The CFI map results were compared to F. hepatica environmental risk models for the survey data points that had over 5% prevalence (231 of the 673 sites at the 1 km2 scale using two independent approaches: (i a GIS map query based on satellite data parameters including elevation, enhanced vegetation index and land surface temperature day-night difference; and (ii an ecological niche model (MaxEnt, for which geographic point coordinates of F. hepatica survey farms were used with BioClim data as environmental variables to develop a probability map. The predicted risk pattern of both approaches was similar to that seen in the forecast index grid. The temporal risk, evaluated by the monthly CFIs and a daily GDD-WB forecast software for 2007 and 2008, revealed a major July-August to January transmission period with considerable inter-annual differences.

  20. Interannual climate variability seen in the Pliocene Model Intercomparison Project

    Directory of Open Access Journals (Sweden)

    C. M. Brierley

    2014-09-01

    Full Text Available Following proxy observations of weakened temperature gradients along the Equator in the early Pliocene, there has been much speculation about Pliocene climate variability. A major advance for our knowledge about the later Pliocene has been the coordination of modelling efforts through the Pliocene Model Intercomparison Project (PlioMIP. Here the changes in interannual modes of sea surface temperature variability will be presented across PlioMIP. Previously model ensembles have shown little consensus in the response of the El Niño–Southern Oscillation (ENSO to imposed forcings – either for the past or future. The PlioMIP ensemble, however, shows surprising agreement with eight models simulating reduced variability and only one model indicating no change. The Pliocene's robustly weaker ENSO also saw a shift to lower frequencies. Model ensembles focussed at a wide variety of forcing scenarios have not yet shown this level of coherency. Nonetheless the PlioMIP ensemble does not show a robust response of either ENSO flavour or sea surface temperature variability in the Tropical Indian and North Pacific Oceans. Existing suggestions of ENSO properties linked to changes in zonal temperature gradient, seasonal cycle and the elevation of the Andes Mountains are investigated, yet prove insufficient to explain the coherent response. The reason for this surprisingly coherent signal warrants further investigation.

  1. Photosynthesis sensitivity to climate change in land surface models

    Science.gov (United States)

    Manrique-Sunen, Andrea; Black, Emily; Verhoef, Anne; Balsamo, Gianpaolo

    2016-04-01

    Accurate representation of vegetation processes within land surface models is key to reproducing surface carbon, water and energy fluxes. Photosynthesis determines the amount of CO2 fixated by plants as well as the water lost in transpiration through the stomata. Photosynthesis is calculated in land surface models using empirical equations based on plant physiological research. It is assumed that CO2 assimilation is either CO2 -limited, radiation -limited ; and in some models export-limited (the speed at which the products of photosynthesis are used by the plant) . Increased levels of atmospheric CO2 concentration tend to enhance photosynthetic activity, but the effectiveness of this fertilization effect is regulated by environmental conditions and the limiting factor in the photosynthesis reaction. The photosynthesis schemes at the 'leaf level' used by land surface models JULES and CTESSEL have been evaluated against field photosynthesis observations. Also, the response of photosynthesis to radiation, atmospheric CO2 and temperature has been analysed for each model, as this is key to understanding the vegetation response that climate models using these schemes are able to reproduce. Particular emphasis is put on the limiting factor as conditions vary. It is found that while at present day CO2 concentrations export-limitation is only relevant at low temperatures, as CO2 levels rise it becomes an increasingly important restriction on photosynthesis.

  2. Modeling irrigation-based climate change adaptation in agriculture: Model development and evaluation in Northeast China

    Science.gov (United States)

    Okada, Masashi; Iizumi, Toshichika; Sakurai, Gen; Hanasaki, Naota; Sakai, Toru; Okamoto, Katsuo; Yokozawa, Masayuki

    2015-09-01

    Replacing a rainfed cropping system with an irrigated one is widely assumed to be an effective measure for climate change adaptation. However, many agricultural impact studies have not necessarily accounted for the space-time variations in the water availability under changing climate and land use. Moreover, many hydrologic and agricultural assessments of climate change impacts are not fully integrated. To overcome this shortcoming, a tool that can simultaneously simulate the dynamic interactions between crop production and water resources in a watershed is essential. Here we propose the regional production and circulation coupled model (CROVER) by embedding the PRYSBI-2 (Process-based Regional Yield Simulator with Bayesian Inference version 2) large-area crop model into the global water resources model (called H08), and apply this model to the Songhua River watershed in Northeast China. The evaluation reveals that the model's performance in capturing the major characteristics of historical change in surface soil moisture, river discharge, actual crop evapotranspiration, and soybean yield relative to the reference data during the interval 1979-2010 is satisfactory accurate. The simulation experiments using the model demonstrated that subregional irrigation management, such as designating the area to which irrigation is primarily applied, has measurable influences on the regional crop production in a drought year. This finding suggests that reassessing climate change risk in agriculture using this type of modeling is crucial not to overestimate potential of irrigation-based adaptation.

  3. ClimatePipes: User-Friendly Data Access, Manipulation, Analysis & Visualization of Community Climate Models

    Science.gov (United States)

    Chaudhary, A.; DeMarle, D.; Burnett, B.; Harris, C.; Silva, W.; Osmari, D.; Geveci, B.; Silva, C.; Doutriaux, C.; Williams, D. N.

    2013-12-01

    The impact of climate change will resonate through a broad range of fields including public health, infrastructure, water resources, and many others. Long-term coordinated planning, funding, and action are required for climate change adaptation and mitigation. Unfortunately, widespread use of climate data (simulated and observed) in non-climate science communities is impeded by factors such as large data size, lack of adequate metadata, poor documentation, and lack of sufficient computational and visualization resources. We present ClimatePipes to address many of these challenges by creating an open source platform that provides state-of-the-art, user-friendly data access, analysis, and visualization for climate and other relevant geospatial datasets, making the climate data available to non-researchers, decision-makers, and other stakeholders. The overarching goals of ClimatePipes are: - Enable users to explore real-world questions related to climate change. - Provide tools for data access, analysis, and visualization. - Facilitate collaboration by enabling users to share datasets, workflows, and visualization. ClimatePipes uses a web-based application platform for its widespread support on mainstream operating systems, ease-of-use, and inherent collaboration support. The front-end of ClimatePipes uses HTML5 (WebGL, Canvas2D, CSS3) to deliver state-of-the-art visualization and to provide a best-in-class user experience. The back-end of the ClimatePipes is built around Python using the Visualization Toolkit (VTK, http://vtk.org), Climate Data Analysis Tools (CDAT, http://uv-cdat.llnl.gov), and other climate and geospatial data processing tools such as GDAL and PROJ4. ClimatePipes web-interface to query and access data from remote sources (such as ESGF). Shown in the figure is climate data layer from ESGF on top of map data layer from OpenStreetMap. The ClimatePipes workflow editor provides flexibility and fine grained control, and uses the VisTrails (http

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

    International Nuclear Information System (INIS)

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

  5. Analysis of extreme climatic features over South America from CLARIS-LPB ensemble of regional climate models for future conditions

    Science.gov (United States)

    Sanchez, E.; Zaninelli, P.; Carril, A.; Menendez, C.; Dominguez, M.

    2012-04-01

    An ensemble of seven regional climate models (RCM) included in the European CLARIS-LPB project (A Europe-South America Network for Climate Change Assessment and Impact Studies in La Plata Basin) are used to study how some features related to climatic extremes are projected to be changed by the end of XXIst century. These RCMs are forced by different IPCC-AR4 global climate models (IPSL, ECHAM5 and HadCM3), covering three different 30-year periods: present (1960-1990), near future (2010-2040) and distant future (2070-2100), with 50km of horizontal resolution. These regional climate models have previously been forced with ERA-Interim reanalysis, in a consistent procedure with CORDEX (A COordinated Regional climate Downscaling EXperiment) initiative for the South-America domain. The analysis shows a good agreement among them and the available observational databases to describe the main features of the mean climate of the continent. Here we focus our analysis on some topics of interest related to extreme events, such as the development of diagnostics related to dry-spells length, the structure of the frequency distribution functions over several subregions defined by more or less homogeneous climatic conditions (four sub-basins over the La Plata Basin, the southern part of the Amazon basin, Northeast Brazil, and the South Atlantic Convergence Zone (SACZ)), the structure of the annual cycle and their main features and relation with the length of the seasons, or the frequency of anomalous hot or cold events. One shortcoming that must be considered is the lack of observational databases with both time and spatial frequency to validate model outputs. At the same time, one challenging issue of this study is the regional modelling description of a continent where a huge variety of climates are present, from desert to mountain conditions, and from tropical to subtropical regimes. Another basic objective of this preliminary work is also to obtain a measure of the spread among

  6. Modelling flood damages under climate change conditions – a case study for Germany

    OpenAIRE

    Hattermann, F. F.; Huang, S.; O. Burghoff; Willems, W.; Österle, H.; Büchner, M.; Kundzewicz, Z.

    2014-01-01

    The aim of the study is to analyze and discuss possible climate change impacts on flood damages in Germany. The study was initiated and supported by the German insurance sector whereby the main goal was to identify general climate-related trends in flood hazard and damages and to explore sensitivity of results to climate scenario uncertainty. The study makes use of climate scenarios regionalized for the main river basins in Germany. A hydrological model (SWIM) ...

  7. Climatic information improves statistical individual-tree mortality models for three key species of Sichuan Province, China

    OpenAIRE

    Qiu, Shuai; Xu, Ming; Li, Renqiang; Zheng, Yunpu; Clark, Daniel; Cui, Xiaowei; Liu, Lixiang; Lai, Changhong; Zhang, Wen; Liu, Bo

    2015-01-01

    Key message Climate variables improve individual-tree mortality models for fir, oak and birch.• Context Climate is considered as an important driver of tree mortality, but few studies have included climate factors in models to explore their importance for modelling individual-tree mortality.• Aims To measure the performance of climate-based models, we built individual-tree mortality models using individual, stand, and climate variables for fir (Abies faxoniana Rehd. et Wils.), oak (Quercus aq...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-12-05

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

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

    Directory of Open Access Journals (Sweden)

    B. Schneider

    2008-04-01

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

  10. Modeling Mediterranean ocean climate of the Last Glacial Maximum

    Directory of Open Access Journals (Sweden)

    U. Mikolajewicz

    2010-10-01

    Full Text Available A regional ocean general circulation model of the Mediterranean is used to study the climate of the last glacial maximum. The atmospheric forcing for these simulations has been derived from simulations with an atmospheric general circulation model, which in turn was forced with surface conditions from a coarse resolution earth system model. The model is successful in reproducing the general patterns of reconstructed sea surface temperature anomalies with the strongest cooling in summer in the northwestern Mediterranean and weak cooling in the Levantine, although the model underestimates the extent of the summer cooling in the western Mediterranean. However, there is a strong vertical gradient associated with this pattern of summer cooling, which makes the comparison with reconstructions nontrivial. The exchange with the Atlantic is decreased to roughly one half of its present value, which can be explained by the shallower Strait of Gibraltar as a consequence of lower global sea level. This reduced exchange causes a strong increase of the salinity in the Mediterranean in spite of reduced net evaporation.

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

    International Nuclear Information System (INIS)

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

  12. 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...

  13. North Atlantic climate variability in coupled models and data

    Directory of Open Access Journals (Sweden)

    S. K. Kravtsov

    2008-01-01

    Full Text Available We show that the observed zonally averaged jet in the Northern Hemisphere atmosphere exhibits two spatial patterns with broadband variability in the decadal and inter-decadal range; these patterns are consistent with an important role of local, mid-latitude ocean–atmosphere coupling. A key aspect of this behaviour is the fundamentally nonlinear bi-stability of the atmospheric jet's latitudinal position, which enables relatively small sea-surface temperature anomalies associated with ocean processes to affect the large-scale atmospheric winds. The wind anomalies induce, in turn, complex three-dimensional anomalies in the ocean's main thermocline; in particular, they may be responsible for recently reported cooling of the upper ocean. Both observed modes of variability, decadal and inter-decadal, have been found in our intermediate climate models. One mode resembles North Atlantic tri-polar sea-surface temperature (SST patterns described elsewhere. The other mode, with mono-polar SST pattern, is novel; its key aspects include interaction of oceanic turbulence with the large-scale oceanic flow. To the extent these anomalies exist, the interpretation of observed climate variability in terms of natural and human-induced changes will be affected. Coupled mid-latitude ocean-atmosphere modes do, however, suggest some degree of predictability is possible.

  14. Review of models on energy and climate change

    International Nuclear Information System (INIS)

    The Energy Modeling Forum recently has initiated a global climate change project. The purpose of the project is to summarize the work which has already been done on this topic and to evaluate the quality of the work. Several critical issues arise in any effort to make credible estimates of the cost of greenhouse control strategies. First, a worldwide modeling framework must be developed because carbon emissions from particular regions affect the global atmosphere. Because the data available on developing countries is quite poor at present, future efforts should focus on new data collection and modeling efforts in these regions. Second, all the major greenhouse gases - CO2, CFCs, methane and N2O - and not just carbon dioxide must be considered in future analyses. It is the overall concentration of all these different greenhouse gases in the atmosphere that ultimately will lead to global climate change. Third, an effective means for analyzing the various greenhouse gas control strategies must be developed. In order to successfully carry out the final task, a method must be developed which integrates a top-down macro-economic approach with a bottom-up process engineering approach. When implementing the macro-economic approach, one must choose plausible ranges for future economic and population growth rates. The reason for this is that even small changes in these driving factors can have huge impacts on emissions projections over the 100 or more year time frames required to address the greenhouse gas problem. The implementation of the process engineering approach requires: an accurate characterization of the costs, performance and availability of current and likely future technologies; an assessment of the likely barriers to technology transfer of both existing and new technologies, particularly from the developed to the developing countries; and an evaluation of the impact of energy prices and greenhouse gas policies on new technological development

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

    Science.gov (United States)

    Waliser, Duane

    2011-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  17. 20th and 21st Century Climate Simulations and Projections in Central Africa by CMIP5 Climate Models

    Science.gov (United States)

    Aloysius, N. R.; Saiers, J. E.; Sheffield, J.

    2013-12-01

    Global and regional climate change assessments rely heavily on the Global Climate Model (GCM) outputs provided by the IPCC's Coupled Model Inter-comparison Project (CMIP5). In this study, we evaluate the ability of 25 GCMs to simulate historical precipitation and near surface temperature fields in Central Africa, apply a quantile-mapping based bias correction to monthly climate fields, and develop three-hourly, daily, and monthly bias-corrected fields for the period 1948-2099. The dataset, at 1.0o latitude/longitude horizontal resolution, is constructed by combining a suite of global observation and reanalysis based monthly and three-hourly data, monthly GCM simulations for the twentieth century, and twenty-first century projections for the IPCC medium mitigation (RCP45) and high emission (RCP85) scenarios. The GCMs simulate historical temperature better than precipitation, but substantial spatial heterogeneity exists among models. Many models show limited skill in simulating the seasonal evolution of present day precipitation, but none of them reveal changes in the seasonality in the future at monthly scale. We present the comparison of historical model performance by individual GCMs as well as several combinations of multimodel ensemble averages. Our results do not reveal any improvement in model performance between high- and low-resolution GCMs during the historical period. But, the multimodel averages of better performing models show greater skills in reproducing the historical climate over randomly selected GCM averages in Central Africa. Our analyses also show that the choice of GCM and emission scenario will dominate the uncertainty in climate change projections. Although our analyses are done for the Central African region, the final dataset is available for global land areas, which will be useful for a variety of climate impact, assessment, and adaptation studies.

  18. Groundwater flow modelling of periods with temperate climate conditions - Laxemar

    International Nuclear Information System (INIS)

    As a part of the license application for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different hydraulic conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. This report concerns the modelling of a repository at the Laxemar-Simpevarp site during temperate climate conditions as a comparison to corresponding modelling carried out for Forsmark /Joyce et al. 2010/. The collation and implementation of onsite hydrogeological and hydrogeochemical data from previous reports are used in the construction of a Hydrogeological base case (reference case conceptualisation) and then an examination of various areas of uncertainty within the current understanding by a series of model variants. The Hydrogeological base case models at three different scales, 'repository', 'site' and 'regional' make use of a discrete fracture network (DFN) and equivalent continuous porous medium (ECPM) models. The use of hydrogeological models allow for the investigation of the groundwater flow from a deep disposal facility to the biosphere and for the calculation of performance measures that will provide an input to the site performance assessment. The focus of the study described in this report has been to perform numerical simulations of the hydrogeological system from post-closure and throughout the temperate period up until the receding shoreline leaves the modelling domain at around 15,000 AD. Besides providing quantitative results for the immediate temperate period following post-closure, these results are also intended to give a qualitative indication of the evolution of the groundwater system during future temperate periods within an ongoing cycle of glacial/inter-glacial events

  19. Groundwater flow modelling of periods with temperate climate conditions - Laxemar

    Energy Technology Data Exchange (ETDEWEB)

    Joyce, Steven; Simpson, Trevor; Hartley, Lee; Applegate, David; Hoek, Jaap; Jackson, Peter; Roberts, David; Swan, David (Serco Technical Consulting Services (United Kingdom)); Gylling, Bjoern; Marsic, Niko (Kemakta Konsult AB, Stockholm (Sweden)); Rhen, Ingvar (SWECO Environment AB, Falun (Sweden))

    2010-12-15

    As a part of the license application for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different hydraulic conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. This report concerns the modelling of a repository at the Laxemar-Simpevarp site during temperate climate conditions as a comparison to corresponding modelling carried out for Forsmark /Joyce et al. 2010/. The collation and implementation of onsite hydrogeological and hydrogeochemical data from previous reports are used in the construction of a Hydrogeological base case (reference case conceptualisation) and then an examination of various areas of uncertainty within the current understanding by a series of model variants. The Hydrogeological base case models at three different scales, 'repository', 'site' and 'regional' make use of a discrete fracture network (DFN) and equivalent continuous porous medium (ECPM) models. The use of hydrogeological models allow for the investigation of the groundwater flow from a deep disposal facility to the biosphere and for the calculation of performance measures that will provide an input to the site performance assessment. The focus of the study described in this report has been to perform numerical simulations of the hydrogeological system from post-closure and throughout the temperate period up until the receding shoreline leaves the modelling domain at around 15,000 AD. Besides providing quantitative results for the immediate temperate period following post-closure, these results are also intended to give a qualitative indication of the evolution of the groundwater system during future temperate periods within an ongoing cycle of glacial/inter-glacial events

  20. Communication of climate projections in US media amid politicization of model science

    Science.gov (United States)

    Akerlof, Karen; Rowan, Katherine E.; Fitzgerald, Dennis; Cedeno, Andrew Y.

    2012-09-01

    Computer models generate projections of future climatic conditions that lie at the crux of climate change science and policy, and are increasingly used by decision-makers. Yet their complexity and politicization can hinder the communication of their science, uses and limitations. Little information on climate models has appeared in US newspapers over more than a decade. Indeed, we show it is declining relative to climate change. When models do appear, it is often within sceptic discourses. Using a media index from 2007, we find that model projections were frequently portrayed as likely to be inaccurate. Political opinion outlets provided more explanation than many news sources.

  1. Mediterranean climate modelling: variability and climate change scenarios; Modelisation climatique du Bassin mediterraneen: variabilite et scenarios de changement climatique

    Energy Technology Data Exchange (ETDEWEB)

    Somot, S

    2005-12-15

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

  2. Regional climate change scenarios over South Asia in the CMIP5 coupled climate model simulations

    Science.gov (United States)

    Prasanna, Venkatraman

    2015-10-01

    This paper evaluates the performance of a suite of state-of-art coupled atmosphere-ocean general circulation models (AOGCMs) in their representation of regional characteristics of hydrological cycle and temperature over South Asia. Based on AOGCM experiments conducted for two types of future greenhouse gas emission scenarios (RCP4.5 and RCP8.5) extending up to the end of 21st century, scenarios of temperature and hydrological cycle are presented. The AOGCMs, despite their relatively coarse resolution, have shown a reasonable skill in depicting the hydrological cycle over the South Asian region. However, considerable biases do exist with reference to the observed hydrological cycle and also inter-model differences. The regional climate change scenarios of temperature ( T), atmospheric water balance components, precipitation, moisture convergence and evaporation ( P, C and E) up to the end of the 21st century based on CMIP5 modeling experiments conducted for (RCP4.5 and RCP8.5) indicate marked increase in both rainfall and temperature into the 21st century, particularly becoming conspicuous after the 2050s. The monsoon rainfall and atmospheric water balance changes under RCP4.5 and RCP8.5 scenarios are discussed in detail in this paper. Spatial patterns of rainfall change projections indicate maximum increase over South Asia in most of the models. Model simulations under scenarios of increased greenhouse gas concentrations suggests that the intensification of the hydrological cycle is driven mainly by the increased moisture convergence due to increase in the water holding capacity of the atmosphere in a warmer environment, the intensification of the hydrological cycle is greater for RCP8.5 compared to RCP4.5, also fewer models indicate increased variance of temperature and rainfall in a warmer environment. While the scenarios presented in this study are indicative of the expected range of rainfall and water balance changes, it must be noted that the quantitative

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

    Science.gov (United States)

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

    2014-01-01

    The Asian tiger mosquito, Aedes albopictus, is capable of transmitting a broad range of viruses to humans. Since its introduction at the end of the 20th century, it has become well established in large parts of southern Europe. As future expansion as a result of climate change can be expected, determining the current and projected future climatic suitability of this invasive mosquito in Europe is of interest. Several studies have tried to detect the potential habitats for this species, but differing data sources and modelling approaches must be considered when interpreting the findings. Here, various modelling methodologies are compared with special emphasis on model set-up and study design. Basic approaches and model algorithms for the projection of spatio-temporal trends within the 21st century differ substantially. Applied methods range from mechanistic models (e.g. overlay of climatic constraints based on geographic information systems or rather process-based approaches) to correlative niche models. We conclude that spatial characteristics such as introduction gateways and dispersal pathways need to be considered. Laboratory experiments addressing the climatic constraints of the mosquito are required for improved modelling results. However, the main source of uncertainty remains the insufficient knowledge about the species' ability to adapt to novel environments. PMID:24556349

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-03-31

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

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

    Science.gov (United States)

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

    2008-12-01

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

  6. A model validation framework for climate change projection and impact assessment

    DEFF Research Database (Denmark)

    Madsen, Henrik; Refsgaard, Jens C.; Andréassian, Vazken;

    2014-01-01

    using proxies of future conditions. In general, a model that has been setup for solving a specific problem at a particular site should be tested in order to document its predictive capability and credibility. In a climate change context such tests, often referred to as model validations tests, are......Models used for projection of climate change and its impacts are usually not validated for simulation of future climate conditions. This is a serious deficiency that introduces an unknown level of uncertainty in the projections. A framework and guiding principles are presented for testing models...... particularly challenging since the model is used for an unknown future with a climate that is significantly different from current conditions. Most model studies reported on projections of climate change and its impacts have not included formal model validation tests that address this issue. A model validation...

  7. The multi-scale aerosol-climate model PNNL-MMF: model description and evaluation

    Directory of Open Access Journals (Sweden)

    M. Wang

    2011-03-01

    Full Text Available Anthropogenic aerosol effects on climate produce one of the largest uncertainties in estimates of radiative forcing of past and future climate change. Much of this uncertainty arises from the multi-scale nature of the interactions between aerosols, clouds and large-scale dynamics, which are difficult to represent in conventional general circulation models (GCMs. In this study, we develop a multi-scale aerosol-climate model that treats aerosols and clouds across different scales, and evaluate the model performance, with a focus on aerosol treatment. This new model is an extension of a multi-scale modeling framework (MMF model that embeds a cloud-resolving model (CRM within each grid column of a GCM. In this extension, the effects of clouds on aerosols are treated by using an explicit-cloud parameterized-pollutant (ECPP approach that links aerosol and chemical processes on the large-scale grid with statistics of cloud properties and processes resolved by the CRM. A two-moment cloud microphysics scheme replaces the simple bulk microphysics scheme in the CRM, and a modal aerosol treatment is included in the GCM. With these extensions, this multi-scale aerosol-climate model allows the explicit simulation of aerosol and chemical processes in both stratiform and convective clouds on a global scale.

    Simulated aerosol budgets in this new model are in the ranges of other model studies. Simulated gas and aerosol concentrations are in reasonable agreement with observations (within a factor of 2 in most cases, although the model underestimates black carbon concentrations at the surface by a factor of 2–4. Simulated aerosol size distributions are in reasonable agreement with observations in the marine boundary layer and in the free troposphere, while the model underestimates the accumulation mode number concentrations near the surface, and overestimates the accumulation mode number concentrations in the middle and upper free troposphere by a factor

  8. California Wintertime Precipitation in Regional and Global Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Caldwell, P M

    2009-04-27

    In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California (CA) and compared. Several averaging methodologies are considered and all are found to give similar values when model grid spacing is less than 3{sup o}. This suggests that CA is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict CA precipitation. This appears to be due mainly to overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge/satellite observations which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait which doesn't seem tied to model resolution. GCM daily and interannual variability is generally underpredicted.

  9. Improving NASA's Multiscale Modeling Framework for Tropical Cyclone Climate Study

    Science.gov (United States)

    Shen, Bo-Wen; Nelson, Bron; Cheung, Samson; Tao, Wei-Kuo

    2013-01-01

    One of the current challenges in tropical cyclone (TC) research is how to improve our understanding of TC interannual variability and the impact of climate change on TCs. Recent advances in global modeling, visualization, and supercomputing technologies at NASA show potential for such studies. In this article, the authors discuss recent scalability improvement to the multiscale modeling framework (MMF) that makes it feasible to perform long-term TC-resolving simulations. The MMF consists of the finite-volume general circulation model (fvGCM), supplemented by a copy of the Goddard cumulus ensemble model (GCE) at each of the fvGCM grid points, giving 13,104 GCE copies. The original fvGCM implementation has a 1D data decomposition; the revised MMF implementation retains the 1D decomposition for most of the code, but uses a 2D decomposition for the massive copies of GCEs. Because the vast majority of computation time in the MMF is spent computing the GCEs, this approach can achieve excellent speedup without incurring the cost of modifying the entire code. Intelligent process mapping allows differing numbers of processes to be assigned to each domain for load balancing. The revised parallel implementation shows highly promising scalability, obtaining a nearly 80-fold speedup by increasing the number of cores from 30 to 3,335.

  10. Multi-Scale Coupling in Ocean and Climate Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Zhengyu Liu, Leslie Smith

    2009-08-14

    We have made significant progress on several projects aimed at understanding multi-scale dynamics in geophysical flows. Large-scale flows in the atmosphere and ocean are influenced by stable density stratification and rotation. The presence of stratification and rotation has important consequences through (i) the conservation of potential vorticity q = {omega} {center_dot} {del} {rho}, where {omega} is the total vorticity and {rho} is the density, and (ii) the existence of waves that affect the redistribution of energy from a given disturbance to the flow. Our research is centered on quantifying the effects of potential vorticity conservation and of wave interactions for the coupling of disparate time and space scales in the oceans and the atmosphere. Ultimately we expect the work to help improve predictive capabilities of atmosphere, ocean and climate modelers. The main findings of our research projects are described.

  11. An overlapping generations model of climate-economy interactions

    International Nuclear Information System (INIS)

    A numerically calibrated overlapping generations model of climate change and the world economy is examined in this paper. In the absence of inter-generational transfers, efficient rates of greenhouse gas emissions abatement rise from 16% in the present to 25% in the long run, while mean global temperature increases by 7.4 deg C relative to the pre industrial norm. A utilitarian optimum, which attaches equal weight to each generation's life-cycle utility, yields abatement rates that rise from 48% to 89%, with a long-run temperature increase of 3.4 deg C. A second-best utilitarian path, in which inter-generational transfers are by assumption institutionally infeasible, also supports stringent abatement measures

  12. Evaluation of multiple regional climate models for summer climate extremes over East Asia

    Science.gov (United States)

    Park, Changyong; Min, Seung-Ki; Lee, Donghyun; Cha, Dong-Hyun; Suh, Myoung-Seok; Kang, Hyun-Suk; Hong, Song-You; Lee, Dong-Kyou; Baek, Hee-Jeong; Boo, Kyung-On; Kwon, Won-Tae

    2016-04-01

    In this study, five regional climate models (RCMs) participating in the CORDEX-East Asia project (HadGEM3-RA, RegCM4, SNU-MM5, SNU-WRF, and YSU-RSM) are evaluated in terms of their performances in simulating the climatology of summer extremes in East Asia. Seasonal maxima of daily mean temperature and precipitation are analyzed using the generalized extreme value method. RCMs show systematic bias patterns in both seasonal means and extremes. A cold bias is located along the coast, whereas a warm bias occurs in northern China. Overall, wet bias occurs in East Asia, but with a substantial dry bias centered in South Korea. This dry bias appears to be related to the colder ocean surface around South Korea, positioning the monsoonal front further south compared to observations. Taylor diagram analyses reveal that the models simulate temperature means more accurately compared to extremes because of the higher spatial correlation, whereas precipitation extremes are simulated better than their means because of the higher spatial variability. The latter implies that extreme rainfall events can be captured more accurately by RCMs compared to the driving GCM despite poorer simulation of mean rainfall. Inter-RCM analysis indicates a close relationship between the means and extremes in terms of model skills, but it does not show a clear relationship between temperature and precipitation. Sub-regional analysis largely supports the mean-extreme skill relationship. Analyses of frequency and intensity distributions of daily data for three selected sub-regions suggest that overall shifts of temperature distribution and biases in moderate-heavy precipitations contribute importantly to the seasonal mean biases.

  13. Groundwater flow modelling of periods with temperate climate conditions - Forsmark

    Energy Technology Data Exchange (ETDEWEB)

    Joyce, Steven; Simpson, Trevor; Hartley, Lee; Applegate, David; Hoek, Jaap; Jackson, Peter; Swan, David (Serco Technical Consulting Services (United Kingdom)); Marsic, Niko (Kemakta Konsult AB (Sweden)); Follin, Sven (SF GeoLogic AB (Sweden))

    2010-11-15

    As a part of the license application for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different climate conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. This report concerns the modelling of a repository at the Forsmark site during temperate conditions; i.e. from post-closure and throughout the temperate period up until the receding shoreline leaves the modelling domain at around 12,000 AD. The collation and implementation of onsite hydrogeological and hydrogeochemical data from previous reports are used in the construction of a hydrogeological base case (reference case conceptualisation) and then in an examination of various areas of uncertainty within the current understanding by a series of model variants. The hydrogeological base case models at three different scales, 'repository', 'site' and 'regional', make use of continuous porous medium (CPM), equivalent continuous porous medium (ECPM) and discrete fracture network (DFN) models. The use of hydrogeological models allow for the investigation of the groundwater flow from a deep disposal facility to the biosphere and for the calculation of performance measures that will provide an input to the site performance assessment. The focus of the study described in this report has been to perform numerical simulations of the hydrogeological system from post-closure and throughout the temperate period. Besides providing quantitative results for the immediate temperate period following post-closure, these results are also intended to give a qualitative indication of the evolution of the groundwater system during future temperate periods within an ongoing cycle of glacial/inter-glacial events

  14. Groundwater flow modelling of periods with temperate climate conditions - Forsmark

    International Nuclear Information System (INIS)

    As a part of the license application for a final repository for spent nuclear fuel at Forsmark, the Swedish Nuclear Fuel and Waste Management Company (SKB) has undertaken a series of groundwater flow modelling studies. These represent time periods with different climate conditions and the simulations carried out contribute to the overall evaluation of the repository design and long-term radiological safety. This report concerns the modelling of a repository at the Forsmark site during temperate conditions; i.e. from post-closure and throughout the temperate period up until the receding shoreline leaves the modelling domain at around 12,000 AD. The collation and implementation of onsite hydrogeological and hydrogeochemical data from previous reports are used in the construction of a hydrogeological base case (reference case conceptualisation) and then in an examination of various areas of uncertainty within the current understanding by a series of model variants. The hydrogeological base case models at three different scales, 'repository', 'site' and 'regional', make use of continuous porous medium (CPM), equivalent continuous porous medium (ECPM) and discrete fracture network (DFN) models. The use of hydrogeological models allow for the investigation of the groundwater flow from a deep disposal facility to the biosphere and for the calculation of performance measures that will provide an input to the site performance assessment. The focus of the study described in this report has been to perform numerical simulations of the hydrogeological system from post-closure and throughout the temperate period. Besides providing quantitative results for the immediate temperate period following post-closure, these results are also intended to give a qualitative indication of the evolution of the groundwater system during future temperate periods within an ongoing cycle of glacial/inter-glacial events

  15. Development of Ensemble Neural Network Convection Parameterizations for Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Fox-Rabinovitz, M. S.; Krasnopolsky, V. M.

    2012-05-02

    The novel neural network (NN) approach has been formulated and used for development of a NN ensemble stochastic convection parametrization for climate models. This fast parametrization is built based on data from Cloud Resolving Model (CRM) simulations initialized with and forced by TOGA-COARE data. The SAM (System for Atmospheric Modeling), developed by D. Randall, M. Khairoutdinov, and their collaborators, has been used for CRM simulations. The observational data are also used for validation of model simulations. The SAM-simulated data have been averaged and projected onto the GCM space of atmospheric states to implicitly define a stochastic convection parametrization. This parametrization is emulated using an ensemble of NNs. An ensemble of NNs with different NN parameters has been trained and tested. The inherent uncertainty of the stochastic convection parametrization derived in such a way is estimated. Due to these inherent uncertainties, NN ensemble is used to constitute a stochastic NN convection parametrization. The developed NN convection parametrization have been validated in a diagnostic CAM (CAM-NN) run vs. the control CAM run. Actually, CAM inputs have been used, at every time step of the control/original CAM integration, for parallel calculations of the NN convection parametrization (CAM-NN) to produce its outputs as a diagnostic byproduct. Total precipitation (P) and cloudiness (CLD) time series, diurnal cycles, and P and CLD distributions for the large Tropical Pacific Ocean for the parallel CAM-NN and CAM runs show similarity and consistency with the NCEP reanalysis. The P and CLD distributions for the tropical area for the parallel runs have been analyzed first for the TOGA-COARE boreal winter season (November 1992 through February 1993) and then for the winter seasons of the follow-up parallel decadal simulations. The obtained results are encouraging and practically meaningful. They show the validity of the NN approach. This constitutes an

  16. A new coupled ice sheet/climate model: description and sensitivity to model physics under Eemian, Last Glacial Maximum, late Holocene and modern climate conditions

    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.

  17. A new coupled ice sheet-climate model: description and sensitivity to model physics under Eemian, Last Glacial Maximum, late Holocene and modern climate conditions

    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.

  18. 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.

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    T. L. A. Driessen

    2009-11-01

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

  1. Modelling the International Climate Change Negotiations: A Non-Technical Outline of Model Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Underdal, Arild

    1997-12-31

    This report discusses in non-technical terms the overall architecture of a model that will be designed to enable the user to (1) explore systematically the political feasibility of alternative policy options and (2) to determine the set of politically feasible solutions in the global climate change negotiations. 25 refs., 2 figs., 1 tab.

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

    KAUST Repository

    Castruccio, Stefano

    2014-03-01

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

  3. Projecting hydropower production under future climates: a review of modelling challenges and open questions

    Science.gov (United States)

    Schaefli, Bettina

    2015-04-01

    Hydropower is a pillar for renewable electricity production in almost all world regions. The planning horizon of major hydropower infrastructure projects stretches over several decades and consideration of evolving climatic conditions plays an ever increasing role. This review of model-based climate change impact assessments provides a synthesis of the wealth of underlying modelling assumptions, highlights the importance of local factors and attempts to identify the most urgent open questions. Based on existing case studies, it critically discusses whether current hydro-climatic modelling frameworks are likely to provide narrow enough water scenario ranges to be included into economic analyses for end-to-end climate change impact assessments including electricity market models. This will be completed with an overview of not or indirectly climate-related boundary conditions, such as economic growth, legal constraints, national subsidy frameworks or growing competition for water, which might locally largely outweigh any climate change impacts.

  4. 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 ...

  5. Hydrological and climatic uncertainties associated with modeling the impact of climate change on water resources of small Mediterranean coastal rivers

    Science.gov (United States)

    Lespinas, Franck; Ludwig, Wolfgang; Heussner, Serge

    2014-04-01

    This paper investigates the uncertainties associated with using regional climate models and one hydrological model calibrated from non-stationary hydroclimatic time series to simulate future water resources of six Mediterranean French coastal river basins. First, a conceptual hydrological model (the GR2M model) was implemented in order to reproduce the observed river discharge regimes. Climatic scenarios were then constructed from a set of Regional Climate Models (RCMs) outputs and fed into the hydrological model in order to produce water discharge scenarios for the 2071-2100 period. At last, an assessment of uncertainties associated with the hydrological scenarios is given. With respect to the 1961-1990 period, RCMs project a mean annual temperature increase of 4.3-4.5 °C (3.1-3.2 °C) under the IPCC A2 (B2) scenario. Precipitation changes, although more variable, indicate a decrease between -10% and -15.6% for A2 and between -6.1% and -11.6% for B2. As a result, the GR2M model simulates a general water discharge decrease between -26% (-14%) and -54% (-41%) for the A2 (B2) scenario, depending on the basin of interest. Sensitivity tests on the hydrological modelling revealed that the hydrological scenarios are sensitive to the choice of the PE formulation, although this climatic input is negligible in the model calibration. Also, a slight but significant drift between the modelled and observed time series was detected for most basins, indicating that the hydrological model fails to adapt to non-stationary discharge conditions. A simple correction method based on a dynamical parametrization of one model parameter with temperature data considerably reduces the model drift in half of the investigated basins. When extrapolated this new parametrization to the future climate scenarios, decrease of water discharge is found to be twice as great as estimated from the standard parametrization. Our results suggest that the uncertainties stemming from hydrological models with

  6. Stratospheric aerosol forcing for climate modeling: 1850-1978

    Science.gov (United States)

    Arfeuille, Florian; Luo, Beiping; Thomason, Larry; Vernier, Jean-Paul; Peter, Thomas

    2016-04-01

    We present here a stratospheric aerosol dataset produced using the available aerosol optical depth observations from the pre-satellite period. The scarce atmospheric observations are supplemented by additional information from an aerosol microphysical model, initialized by ice-core derived sulfur emissions. The model is used to derive extinctions at all altitudes, latitudes and times when sulfur injections are known for specific volcanic eruptions. The simulated extinction coefficients are then scaled to match the observed optical depths. In order to produce the complete optical properties at all wavelengths (and the aerosol surface area and volume densities) needed by climate models, we assume a lognormal size distribution of the aerosols. Correlations between the extinctions in the visible and the effective radius and distribution width parameters are taken from the better constrained SAGE II period. The aerosol number densities are then fitted to match the derived extinctions in the 1850-1978 period. From these aerosol size distributions, we then calculate extinction coefficients, single scattering albedos and asymmetry factors at all wavelengths using the Mie theory. The aerosol surface area densities and volume densities are also provided.

  7. 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

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

    Science.gov (United States)

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

    2015-10-01

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

  9. On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models

    OpenAIRE

    Zhang, Shipeng; Wang, Minghuai; Ghan, Steven J; Ding, Aijun; Wang, Hailong; Zhang, Kai; Neubauer, David; Lohmann, Ulrike; Ferrachat, Sylvaine; Takeamura, Toshihiko; Gettelman, Andrew; Morrison, Hugh; Lee, Yunha; Shindell, Drew T.; Partridge, Daniel G.

    2016-01-01

    Aerosol–cloud interactions continue to constitute a major source of uncertainty for the estimate of climate radiative forcing. The variation of aerosol indirect effects (AIE) in climate models is investigated across different dynamical regimes, determined by monthly mean 500 hPa vertical pressure velocity (ω500), lower-tropospheric stability (LTS) and large-scale surface precipitation rate derived from several global climate models (GCMs), with a focus on liquid water path (...

  10. 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...

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

    Science.gov (United States)

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

    2015-10-01

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

  12. Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

    Energy Technology Data Exchange (ETDEWEB)

    Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

    2015-07-14

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

  13. Characterizing climate predictability and model response variability from multiple initial condition and multi-model ensembles

    CERN Document Server

    Kumar, Devashish

    2016-01-01

    Climate models are thought to solve boundary value problems unlike numerical weather prediction, which is an initial value problem. However, climate internal variability (CIV) is thought to be relatively important at near-term (0-30 year) prediction horizons, especially at higher resolutions. The recent availability of significant numbers of multi-model (MME) and multi-initial condition (MICE) ensembles allows for the first time a direct sensitivity analysis of CIV versus model response variability (MRV). Understanding the relative agreement and variability of MME and MICE ensembles for multiple regions, resolutions, and projection horizons is critical for focusing model improvements, diagnostics, and prognosis, as well as impacts, adaptation, and vulnerability studies. Here we find that CIV (MICE agreement) is lower (higher) than MRV (MME agreement) across all spatial resolutions and projection time horizons for both temperature and precipitation. However, CIV dominates MRV over higher latitudes generally an...

  14. Assessing 20th century climate-vegetation feedbacks of land-use change and natural vegetation dynamics in a fully coupled vegetation-climate model

    OpenAIRE

    Strengers, B.J.; C. Müller; Schaeffer, M.; Haarsma, R. J.; C. Severijns; Gerten, D.; Schaphoff, S.; Houdt, Van den, R.; Oostenrijk, R.

    2010-01-01

    This study describes the coupling of the dynamic global vegetation model (DGVM), Lund–Potsdam–Jena Model for managed land (LPJmL), with the general circulation model (GCM), Simplified Parameterizations primitivE Equation DYnamics model (SPEEDY), to study the feedbacks between land-use change and natural vegetation dynamics and climate during the 20th century. We show that anthropogenic land-use change had a stronger effect on climate than the natural vegetation's response to climate change (e...

  15. 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

  16. 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.

  17. Reducing Uncertainty in Chemistry Climate Model Predictions of Stratospheric Ozone

    Science.gov (United States)

    Douglass, A. R.; Strahan, S. E.; Oman, L. D.; Stolarski, R. S.

    2014-01-01

    Chemistry climate models (CCMs) are used to predict the future evolution of stratospheric ozone as ozone-depleting substances decrease and greenhouse gases increase, cooling the stratosphere. CCM predictions exhibit many common features, but also a broad range of values for quantities such as year of ozone-return-to-1980 and global ozone level at the end of the 21st century. Multiple linear regression is applied to each of 14 CCMs to separate ozone response to chlorine change from that due to climate change. We show that the sensitivity of lower atmosphere ozone to chlorine change deltaO3/deltaCly is a near linear function of partitioning of total inorganic chlorine (Cly) into its reservoirs; both Cly and its partitioning are controlled by lower atmospheric transport. CCMs with realistic transport agree with observations for chlorine reservoirs and produce similar ozone responses to chlorine change. After 2035 differences in response to chlorine contribute little to the spread in CCM results as the anthropogenic contribution to Cly becomes unimportant. Differences among upper stratospheric ozone increases due to temperature decreases are explained by differences in ozone sensitivity to temperature change deltaO3/deltaT due to different contributions from various ozone loss processes, each with their own temperature dependence. In the lower atmosphere, tropical ozone decreases caused by a predicted speed-up in the Brewer-Dobson circulation may or may not be balanced by middle and high latitude increases, contributing most to the spread in late 21st century predictions.

  18. Psyplot: Visualizing rectangular and triangular Climate Model Data with Python

    Science.gov (United States)

    Sommer, Philipp

    2016-04-01

    The development and use of climate models often requires the visualization of geo-referenced data. Creating visualizations should be fast, attractive, flexible, easily applicable and easily reproducible. There is a wide range of software tools available for visualizing raster data, but they often are inaccessible to many users (e.g. because they are difficult to use in a script or have low flexibility). In order to facilitate easy visualization of geo-referenced data, we developed a new framework called "psyplot," which can aid earth system scientists with their daily work. It is purely written in the programming language Python and primarily built upon the python packages matplotlib, cartopy and xray. The package can visualize data stored on the hard disk (e.g. NetCDF, GeoTIFF, any other file format supported by the xray package), or directly from the memory or Climate Data Operators (CDOs). Furthermore, data can be visualized on a rectangular grid (following or not following the CF Conventions) and on a triangular grid (following the CF or UGRID Conventions). Psyplot visualizes 2D scalar and vector fields, enabling the user to easily manage and format multiple plots at the same time, and to export the plots into all common picture formats and movies covered by the matplotlib package. The package can currently be used in an interactive python session or in python scripts, and will soon be developed for use with a graphical user interface (GUI). Finally, the psyplot framework enables flexible configuration, allows easy integration into other scripts that uses matplotlib, and provides a flexible foundation for further development.

  19. Groundwater and climate change: mitigating the global groundwater crisis and adapting to climate change model

    Science.gov (United States)

    To better understand the effects of climate change on global groundwater resources, the United Nations Educational, Scientific, and Cultural Organization (UNESCO) International Hydrological Programme (IHP) initiated the GRAPHIC (Groundwater Resources Assessment under the Pressures of Humanity and Cl...

  20. Are climate model simulations useful for forecasting precipitation trends? Hindcast and synthetic-data experiments

    International Nuclear Information System (INIS)

    Water scientists and managers currently face the question of whether trends in climate variables that affect water supplies and hazards can be anticipated. We investigate to what extent climate model simulations may provide accurate forecasts of future hydrologic nonstationarity in the form of changes in precipitation amount. We compare gridded station observations (GPCC Full Data Product, 1901–2010) and climate model outputs (CMIP5 Historical and RCP8.5 simulations, 1901–2100) in real and synthetic-data hindcast experiments. The hindcast experiments show that imputing precipitation trends based on the climate model mean reduced the root mean square error of precipitation trend estimates for 1961–2010 by 9% compared to making the assumption (implied by hydrologic stationarity) of no trend in precipitation. Given the accelerating pace of climate change, the benefits of incorporating climate model assessments of precipitation trends in water resource planning are projected to increase for future decades. The distribution of climate models’ simulated precipitation trends shows substantial spatially coherent biases, suggesting that there may be room for further improvement in how climate models are parametrized and used for precipitation estimation. Linear extrapolation of observed trends in long precipitation records may also be useful, particularly for lead times shorter than about 25 years. Overall, our findings suggest that simulations by current global climate models, combined with the continued maintenance of in situ hydrologic observations, can provide useful information on future changes in the hydrologic cycle. (paper)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-02-17

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

  2. 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

  3. A new Geoengineering Model Intercomparison Project (GeoMIP experiment designed for climate and chemistry models

    Directory of Open Access Journals (Sweden)

    S. Tilmes

    2014-08-01

    Full Text Available A new Geoengineering Model Intercomparison Project (GeoMIP experiment "G4 specified stratospheric aerosols" (short name: G4SSA is proposed to investigate the impact of stratospheric aerosol geoengineering on atmospheric composition, climate, and the environment. In contrast to the earlier G4 GeoMIP experiment, which requires an emission of sulphur dioxide (SO2 into the model, a prescribed aerosol forcing file is provided to the community, to be consistently applied to future model experiments between 2020 and 2100. This stratospheric aerosol distribution, with a total burden of about 2 Tg S has been derived using the ECHAM5-HAM microphysical model, based on a continuous annual tropical emission of 8 Tg SO2 year−1. A ramp-up of geoengineering in 2020 and a ramp-down in 2070 over a period of two years are included in the distribution, while a background aerosol burden should be used for the last 3 decades of the experiment. The performance of this experiment using climate and chemistry models in a multi-model comparison framework will allow us to better understand the significance of the impact of geoengineering and the abrupt termination after 50 years on climate and composition of the atmosphere in a changing environment. The zonal and monthly mean stratospheric aerosol input dataset is available at https://www2.acd.ucar.edu/gcm/geomip-g4-specified-stratospheric-aerosol-data-set.

  4. 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

  5. The representation of location by regional climate models in complex terrain

    Directory of Open Access Journals (Sweden)

    D. Maraun

    2015-03-01

    Full Text Available To assess potential impacts of climate change for a specific location, one typically employs climate model simulations at the grid box corresponding to the same geographical location. But based on regional climate model simulations, we show that simulated climate might be systematically displaced compared to observations. In particular in the rain shadow of moutain ranges, a local grid box is therefore often not representative of observed climate: the simulated windward weather does not flow far enough across the mountains; local grid boxes experience the wrong airmasses and atmospheric circulation. In some cases, also the local climate change signal is deteriorated. Classical bias correction methods fail to correct these location errors. Often, however, a distant simulated time series is representative of the considered observed precipitation, such that a non-local bias correction is possible. These findings also clarify limitations of bias correcting global model errors, and of bias correction against station data.

  6. Selecting representative climate stations for use in a building energy model

    Energy Technology Data Exchange (ETDEWEB)

    Hadley, D.L.

    1993-11-01

    An energy impacts model is being refined to support ongoing development of major energy conservation standards for US commercial buildings. When completed, the model will be used to evaluate potential impacts (energy savings and associated costs) of implementing the proposed standards. To work as intended, the model must contain a set of climate stations to represent the wide range of climatic conditions that occur across the United States. Researchers developed a procedure that employs a user-selectable climate database (1) to objectively identify, using a clustering technique, a unique set of climate zones for a specified geographical area, and (2) to specify the single most representative station for each climate zone. The process provides a more objective, technically sound basis for selecting climate zones and stations, thereby minimizing researcher bias. The procedure and its application to US energy conservation standards development activities are described in this paper.

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

    International Nuclear Information System (INIS)

    Knowledge about climatic variations is essential for SKB in its safety assessments of a geological repository for spent nuclear waste. There is therefore a need for information about possible future climatic variations under a range of possible climatic states. However, predictions of future climate in any deterministic sense are still beyond our reach. We can, nevertheless, try to estimate the magnitude of future climate variability and change due to natural forcing factors, by means of inferences drawn from natural climate variability in the past. Indeed, the climate of the future will be shaped by the sum of natural and anthropogenic climate forcing, as well as the internal climate variability. The aim here is to review and analyse the knowledge about Swedish climate variability, essentially during the past millennium. Available climate proxy data and long instrumental records provide empirical information on past climatic changes. We also demonstrate how climate modelling can be used to extend such knowledge. We use output from a global climate model driven with reconstructed radiative forcings (solar, volcanic and greenhouse gas forcing), to provide boundary conditions for a regional climate model. The regional model provides more details of the climate than the global model, and we develop a simulated climate history for Sweden that is complete in time and space and physically consistent. We use output from a regional model simulation for long periods in the last millennium, to study annual mean temperature, precipitation and runoff for the northern and southern parts of Sweden. The simulated data are used to place corresponding instrumental records for the 20th century into a plausible historical perspective. We also use output from the regional model to study how the frequency distribution of the daily temperature, precipitation, runoff and evaporation at Forsmark and Oskarshamn could have varied between unusually warm and cold 30-year periods during the

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-12-15

    Knowledge about climatic variations is essential for SKB in its safety assessments of a geological repository for spent nuclear waste. There is therefore a need for information about possible future climatic variations under a range of possible climatic states. However, predictions of future climate in any deterministic sense are still beyond our reach. We can, nevertheless, try to estimate the magnitude of future climate variability and change due to natural forcing factors, by means of inferences drawn from natural climate variability in the past. Indeed, the climate of the future will be shaped by the sum of natural and anthropogenic climate forcing, as well as the internal climate variability. The aim here is to review and analyse the knowledge about Swedish climate variability, essentially during the past millennium. Available climate proxy data and long instrumental records provide empirical information on past climatic changes. We also demonstrate how climate modelling can be used to extend such knowledge. We use output from a global climate model driven with reconstructed radiative forcings (solar, volcanic and greenhouse gas forcing), to provide boundary conditions for a regional climate model. The regional model provides more details of the climate than the global model, and we develop a simulated climate history for Sweden that is complete in time and space and physically consistent. We use output from a regional model simulation for long periods in the last millennium, to study annual mean temperature, precipitation and runoff for the northern and southern parts of Sweden. The simulated data are used to place corresponding instrumental records for the 20th century into a plausible historical perspective. We also use output from the regional model to study how the frequency distribution of the daily temperature, precipitation, runoff and evaporation at Forsmark and Oskarshamn could have varied between unusually warm and cold 30-year periods during the

  9. Improving Climate Projections Through the Assessment of Model Uncertainty and Bias in the Global Water Cycle

    Science.gov (United States)

    Baker, Noel C.

    The implications of a changing climate have a profound impact on human life, society, and policy making. The need for accurate climate prediction becomes increasingly important as we better understand these implications. Currently, the most widely used climate prediction relies on the synthesis of climate model simulations organized by the Coupled Model Intercomparison Project (CMIP); these simulations are ensemble-averaged to construct projections for the 21st century climate. However, a significant degree of bias and variability in the model simulations for the 20th century climate is well-known at both global and regional scales. Based on that insight, this study provides an alternative approach for constructing climate projections that incorporates knowledge of model bias. This approach is demonstrated to be a viable alternative which can be easily implemented by water resource managers for potentially more accurate projections. Tests of the new approach are provided on a global scale with an emphasis on semiarid regional studies for their particular vulnerability to water resource changes, using both the former CMIP Phase 3 (CMIP3) and current Phase 5 (CMIP5) model archives. This investigation is accompanied by a detailed analysis of the dynamical processes and water budget to understand the behaviors and sources of model biases. Sensitivity studies of selected CMIP5 models are also performed with an atmospheric component model by testing the relationship between climate change forcings and model simulated response. The information derived from each study is used to determine the progressive quality of coupled climate models in simulating the global water cycle by rigorously investigating sources of model bias related to the moisture budget. As such, the conclusions of this project are highly relevant to model development and potentially may be used to further improve climate projections.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2002-08-01

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

  11. The predictive skill of species distribution models for plankton in a changing climate

    DEFF Research Database (Denmark)

    Brun, Philipp Georg; Kiørboe, Thomas; Licandro, Priscilla;

    2016-01-01

    Statistical species distribution models (SDMs) are increasingly used to project spatial relocations of marine taxa under future climate change scenarios. However, tests of their predictive skill in the real-world are rare. Here, we use data from the Continuous Plankton Recorder program, one of the...... null models, is essential to assess the robustness of projections of marine planktonic species under climate change...

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

    Science.gov (United States)

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

    2016-01-01

    Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate