Science.gov

Sample records for climate models final

  1. Exploitation of parallelism in climate models. Final report

    SciTech Connect

    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.

  2. Final Technical Report: "Representing Endogenous Technological Change in Climate Policy Models: General Equilibrium Approaches"

    SciTech Connect

    Ian Sue Wing

    2006-04-18

    The research supported by this award pursued three lines of inquiry: (1) The construction of dynamic general equilibrium models to simulate the accumulation and substitution of knowledge, which has resulted in the preparation and submission of several papers: (a) A submitted pedagogic paper which clarifies the structure and operation of computable general equilibrium (CGE) models (C.2), and a review article in press which develops a taxonomy for understanding the representation of technical change in economic and engineering models for climate policy analysis (B.3). (b) A paper which models knowledge directly as a homogeneous factor, and demonstrates that inter-sectoral reallocation of knowledge is the key margin of adjustment which enables induced technical change to lower the costs of climate policy (C.1). (c) An empirical paper which estimates the contribution of embodied knowledge to aggregate energy intensity in the U.S. (C.3), followed by a companion article which embeds these results within a CGE model to understand the degree to which autonomous energy efficiency improvement (AEEI) is attributable to technical change as opposed to sub-sectoral shifts in industrial composition (C.4) (d) Finally, ongoing theoretical work to characterize the precursors and implications of the response of innovation to emission limits (E.2). (2) Data development and simulation modeling to understand how the characteristics of discrete energy supply technologies determine their succession in response to emission limits when they are embedded within a general equilibrium framework. This work has produced two peer-reviewed articles which are currently in press (B.1 and B.2). (3) Empirical investigation of trade as an avenue for the transmission of technological change to developing countries, and its implications for leakage, which has resulted in an econometric study which is being revised for submission to a journal (E.1). As work commenced on this topic, the U.S. withdrawal

  3. Predicting Coupled Ocean-Atmosphere Modes with a Climate Modeling Hierarchy -- Final Report

    SciTech Connect

    Michael Ghil, UCLA; Andrew W. Robertson, IRI, Columbia Univ.; Sergey Kravtsov, U. of Wisconsin, Milwaukee; Padhraic Smyth, UC Irvine

    2006-08-04

    The goal of the project was to determine midlatitude climate predictability associated with tropical-extratropical interactions on interannual-to-interdecadal time scales. Our strategy was to develop and test a hierarchy of climate models, bringing together large GCM-based climate models with simple fluid-dynamical coupled ocean-ice-atmosphere models, through the use of advanced probabilistic network (PN) models. PN models were used to develop a new diagnostic methodology for analyzing coupled ocean-atmosphere interactions in large climate simulations made with the NCAR Parallel Climate Model (PCM), and to make these tools user-friendly and available to other researchers. We focused on interactions between the tropics and extratropics through atmospheric teleconnections (the Hadley cell, Rossby waves and nonlinear circulation regimes) over both the North Atlantic and North Pacific, and the ocean’s thermohaline circulation (THC) in the Atlantic. We tested the hypothesis that variations in the strength of the THC alter sea surface temperatures in the tropical Atlantic, and that the latter influence the atmosphere in high latitudes through an atmospheric teleconnection, feeding back onto the THC. The PN model framework was used to mediate between the understanding gained with simplified primitive equations models and multi-century simulations made with the PCM. The project team is interdisciplinary and built on an existing synergy between atmospheric and ocean scientists at UCLA, computer scientists at UCI, and climate researchers at the IRI.

  4. Final Progress Report [Testing Climate Model Simulations of Tropical Cirrus Lifecycles: A Lagrangian

    SciTech Connect

    Soden, Brian J

    2009-06-30

    This project integrates ARM data sets with satellite observations and model simulations to improve the representation of tropical cloud systems in climate models. We focus on describing and understanding relevant features of the lifecycle of tropical cirrus cloud systems using an innovative method which combines the Eulerian-based ARM measurements with Lagrangian information from geostationary satellites.

  5. Final Report on Hierarchical Coupled Modeling and Prediction of Regional Climate Change in the Atlantic Sector

    SciTech Connect

    Saravanan, Ramalingam

    2011-10-30

    During the course of this project, we have accomplished the following: a) Carried out studies of climate changes in the past using a hierarchy of intermediate coupled models (Chang et al., 2008; Wan et al 2009; Wen et al., 2010a,b) b) Completed the development of a Coupled Regional Climate Model (CRCM; Patricola et al., 2011a,b) c) Carried out studies testing hypotheses testing the origin of systematic errors in the CRCM (Patricola et al., 2011a,b) d) Carried out studies of the impact of air-sea interaction on hurricanes, in the context of barrier layer interactions (Balaguru et al)

  6. Final Report for High Latitude Climate Modeling: ARM Takes Us Beyond Case Studies

    SciTech Connect

    Russell, Lynn M

    2013-06-18

    The main thrust of this project was to devise a method by which the majority of North Slope of Alaska (NSA) meteorological and radiometric data, collected on a daily basis, could be used to evaluate and improve global climate model (GCM) simulations and their parameterizations, particularly for cloud microphysics. Although the standard ARM Program sensors for a less complete suite of instruments for cloud and aerosol studies than the instruments on an intensive field program such as the 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC), the advantage they offer lies in the long time base and large volume of data that covers a wide range of meteorological and climatological conditions. The challenge has been devising a method to interpret the NSA data in a practical way, so that a wide variety of meteorological conditions in all seasons can be examined with climate models. If successful, climate modelers would have a robust alternative to the usual “case study” approach (i.e., from intensive field programs only) for testing and evaluating their parameterizations’ performance. Understanding climate change on regional scales requires a broad scientific consideration of anthropogenic influences that goes beyond greenhouse gas emissions to also include aerosol-induced changes in cloud properties. For instance, it is now clear that on small scales, human-induced aerosol plumes can exert microclimatic radiative and hydrologic forcing that rivals that of greenhouse gas–forced warming. This project has made significant scientific progress by investigating what causes successive versions of climate models continue to exhibit errors in cloud amount, cloud microphysical and radiative properties, precipitation, and radiation balance, as compared with observations and, in particular, in Arctic regions. To find out what is going wrong, we have tested the models' cloud representation over the full range of meteorological conditions found in the Arctic using the ARM

  7. Climate Models

    NASA Technical Reports Server (NTRS)

    Druyan, Leonard M.

    2012-01-01

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

  8. An experimental climate modeling laboratory. DOE CHAMMP Program, year 2 final report

    SciTech Connect

    1996-02-01

    The major focus of this two year duration CHAMMP science team project is the development and in-model testing of new numerical methods and dynamical algorithms which are particularly well suited to massively parallel computers. The project includes efforts relevant to both global ocean circulation models and atmospheric GCMs. During the course of the authors investigations they focused on two basic areas. The first of these was the implementation and testing of a global non-linear dynamics code using the Local Spectral (LS) formalism. The LS method is of considerable interest for atmospheric GCMs since it has a computational complexity of N{sup 2} as opposed to the N{sup 3} log N complexity of Spectral Transform (ST) implementations while maintaining many of the same properties of the ST models which have become the dominant method employed for global climate model studies. A second element of the investigation has been the evaluation of alternate dynamical systems for use in global ocean circulation models. Some of the investigations have focused on the use of split-explicit hydrostatic models while others have made use of non-hydrostatic dynamics with vertically implicit integrations of equation systems using artificial compressibility.

  9. Final Report: Climate Variability, Stochasticity and Learning in Integrated Assessment Models, September 15, 1996 - September 14, 1999

    SciTech Connect

    Kolstad, Charles D.

    1999-09-14

    The focus of the work has been on climate variability and learning within computational climate-economy models (integrated assessment models--IAM's). The primary objective of the research is to improve the representation of learning in IAM's. This include's both endogenous and exogenous learning. A particular focus is on Bayesian learning about climate damage. A secondary objective is to improve the representation of climate variability within IAM's.

  10. Modeling the effects of vegetation on methane oxidation and emissions through soil landfill final covers across different climates.

    PubMed

    Abichou, Tarek; Kormi, Tarek; Yuan, Lei; Johnson, Terry; Francisco, Escobar

    2015-02-01

    Plant roots are reported to enhance the aeration of soil by creating secondary macropores which improve the diffusion of oxygen into soil as well as the supply of methane to bacteria. Therefore, methane oxidation can be improved considerably by the soil structuring processes of vegetation, along with the increase of organic biomass in the soil associated with plant roots. This study consisted of using a numerical model that combines flow of water and heat with gas transport and oxidation in soils, to simulate methane emission and oxidation through simulated vegetated and non-vegetated landfill covers under different climatic conditions. Different simulations were performed using different methane loading flux (5-200 g m(-2) d(-1)) as the bottom boundary. The lowest modeled surface emissions were always obtained with vegetated soil covers for all simulated climates. The largest differences in simulated surface emissions between the vegetated and non-vegetated scenarios occur during the growing season. Higher average yearly percent oxidation was obtained in simulations with vegetated soil covers as compared to non-vegetated scenario. The modeled effects of vegetation on methane surface emissions and percent oxidation were attributed to two separate mechanisms: (1) increase in methane oxidation associated with the change of the physical properties of the upper vegetative layer and (2) increase in organic matter associated with vegetated soil layers. Finally, correlations between percent oxidation and methane loading into simulated vegetated and non-vegetated covers were proposed to allow decision makers to compare vegetated versus non-vegetated soil landfill covers. These results were obtained using a modeling study with several simplifying assumptions that do not capture the complexities of vegetated soils under field conditions.

  11. Land Processes in a High Resolution Community Climate Model with Sub-Grid Scale Parameterizations Final Report

    SciTech Connect

    R. E. Dickinson; Andrea N. Hahmann

    2002-07-17

    The characteristics of land important for climate are very heterogeneous, as are the key atmospheric inputs to land, i.e. precipitation and radiation. To adequately represent this heterogeneity, state-of-the-art climate models should represent atmospheric inputs to land, land properties, and the dynamical changes of land at the highest resolution accessible by climate models. The research funded under this project focused on the development of an alternative approach to this problem in which a sub-mesh is imposed on each atmospheric model grid square. This allows representation of the land climate dynamics at a higher resolution than that achievable in the global atmospheric models. The high spatial detail of the fine-mesh treatment provides not only a more accurate representation of land processes to the atmospheric model, but also the opportunity for direct downscaling of the surface climate. The proposed project continued the development and refinement of a high-resolution land surface model that is compatible for inclusion into the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM), a state-of-the-art atmospheric general circulation model (GCM) that is used for climate simulation and prediction.

  12. Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Final Report, Version 2)

    EPA Science Inventory

    EPA's announced the availability of the final report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Version 2). This update furthered land change modeling by providing nationwide housing developmen...

  13. Watershed Modeling to Assess the Sensitivity of Streamflow, Nutrient, and Sediment Loads to Potential Climate Change and Urban Development in 20 U.S. Watersheds (Final Report)

    EPA Science Inventory

    In September 2013, EPA announced the release of the final report, Watershed Modeling to Assess the Sensitivity of Streamflow, Nutrient, and Sediment Loads to Potential Climate Change and Urban Development in 20 U.S. Watersheds.

    Watershed modeling was conducted in ...

  14. Transforming the representation of the boundary layer and low clouds for high-resolution regional climate modeling: Final report

    SciTech Connect

    Huang, Hsin-Yuan; Hall, Alex

    2013-07-24

    Stratocumulus and shallow cumulus clouds in subtropical oceanic regions (e.g., Southeast Pacific) cover thousands of square kilometers and play a key role in regulating global climate (e.g., Klein and Hartmann, 1993). Numerical modeling is an essential tool to study these clouds in regional and global systems, but the current generation of climate and weather models has difficulties in representing them in a realistic way (e.g., Siebesma et al., 2004; Stevens et al., 2007; Teixeira et al., 2011). While numerical models resolve the large-scale flow, subgrid-scale parameterizations are needed to estimate small-scale properties (e.g. boundary layer turbulence and convection, clouds, radiation), which have significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. To represent the contribution of these fine-scale processes to the resolved scale, climate models use various parameterizations, which are the main pieces in the model that contribute to the low clouds dynamics and therefore are the major sources of errors or approximations in their representation. In this project, we aim to 1) improve our understanding of the physical processes in thermal circulation and cloud formation, 2) examine the performance and sensitivity of various parameterizations in the regional weather model (Weather Research and Forecasting model; WRF), and 3) develop, implement, and evaluate the advanced boundary layer parameterization in the regional model to better represent stratocumulus, shallow cumulus, and their transition. Thus, this project includes three major corresponding studies. We find that the mean diurnal cycle is sensitive to model domain in ways that reveal the existence of different contributions originating from the Southeast Pacific land-masses. The experiments suggest that diurnal variations in circulations and thermal structures over this region are influenced by convection over the Peruvian sector of the Andes cordillera, while

  15. Final Technical Report for Collaborative Research: Regional climate-change projections through next-generation empirical and dynamical models, DE-FG02-07ER64429

    SciTech Connect

    Smyth, Padhraic

    2013-07-22

    This is the final report for a DOE-funded research project describing the outcome of research on non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. The main results consist of extensive development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes.

  16. Carbon dioxide, climate and the deep ocean circulation: Carbon chemistry model. Final report

    SciTech Connect

    Menawat, A.S.

    1992-09-21

    The objective of this study was to investigate the role of oceanic carbon chemistry in modulating the atmospheric levels of CO{sub 2}. It is well known that the oceans are the primary sink of the excess carbon pumped into the atmosphere since the beginning of the industrial period. The suspended particulate and the dissolved organic matters in the deep ocean play important roles as carriers of carbon and other elements critical to the fate of CO{sub 2}. In addition, the suspended particulate matter provides sites for oxidation-reduction reactions and microbial activities. The problem is of an intricate system with complex chemical, physical and biological processes. This report describes a methodology to describe the interconversions of different forms of the organic and inorganic nutrients, that may be incorporated in the ocean circulation models. Our approach includes the driving force behind the transfers in addition to balancing the elements. Such thermodynamic considerations of describing the imbalance in the chemical potentials is a new and unique feature of our approach.

  17. Final Technical Report for "Collaborative Research: Regional climate-change projections through next-generation empirical and dynamical models"

    SciTech Connect

    Robertson, A.W.; Ghil, M.; Kravtsov, K.; Smyth, P.J.

    2011-04-08

    This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs, we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to

  18. Final Technical Report for "Collaborative Research. Regional climate-change projections through next-generation empirical and dynamical models"

    SciTech Connect

    Kravtsov, S.; Robertson, Andrew W.; Ghil, Michael; Smyth, Padhraic J.

    2011-04-08

    This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs, we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to

  19. Assessing the climatic effect of carbon dioxide and other trace gases using an interactive two-dimensional climate-chemistry model. Final report, December 1992--August 1996

    SciTech Connect

    Ko, M.K.W.

    1996-12-31

    In the recent IPCC report, the role of tropospheric aerosols, stratospheric aerosols, and natural solar variability have also been identified as having sizable effects on climate, both by direct perturbation of the radiative balance and indirectly by changing ozone. Although the effect of changing CO{sub 2} is by far the dominant factor on a century time scale, the effects from the other identified factors are important on a decade time scale. It is important to understand the mechanisms that relate these changes to climatic responses. Developing appropriate numerical models with the capability to simulate these mechanisms will enable one to correctly interpret the observed climate changes that have occurred to data, as well as predict future changes in climate. It is presently impractical to run comprehensive 3-D general circulation model simulations of the interactions between atmospheric chemistry and the rest of the climate system on time scales of decades to centuries. Thus, 2-D models and other lower resolution models play an essential role in understanding the complex interactions of the integrated climate system.

  20. A reduced-form approach to characterizing sulfate aerosol effects on climate in integrated assessment models. Final report

    SciTech Connect

    Wigley, T.M.L.

    1996-04-01

    The objective of this study was to devise a methodology for estimating the spatial patterns of future climate change accounting for the effects of both greenhouse gases and sulfate aerosols under a wide range of emissions scenarios, using the results of General Circulation Models.

  1. Evaluation of the appropriate land-surface resolution for climate models. Final report, August 1, 1992--July 31, 1995

    SciTech Connect

    Avissar, R.

    1998-07-17

    The land surface interacts strongly with the atmosphere at all spatial and temporal scales. Therefore, land-surface processes must be represented as accurately as possible in climate models. The investigation conducted under this project was aimed at answering two major questions related to land-surface processes: (1) What are the land-surface characteristics and processes that need to be represented in a climate model? (2) How does one average, in a nonlinear form, land-surface energy fluxes over heterogeneous domain at the scale that is not represented explicitly in the model? Correspondingly, two major tasks were conducted: (1) an evaluation of the relative importance of the various land-surface characteristics based on their impact on the redistribution of energy into turbulent sensible heat flux and turbulent latent heat flux at the ground surface; and (2) an evaluation of the impact of the heterogeneity of these characteristics on land-surface energy and mass fluxes into the atmosphere.

  2. Theoretical models of the impact of climate change on natural populations, communities and ecosystems. Final report, 1989--1992

    SciTech Connect

    Wiegert, R.

    1992-12-31

    Land use change is a relatively understudied aspect of global change. In many cases, the impact of land use on plant and animal species may be far greater than the impact of climate change per se. As an integral part of our long-term studies of the response of animal populations to global change, we have focused on land use change as a dominant driving force. Climate change, no doubt, will also play a role in determining the future abundance and distribution of many species, but, for many species, the signal from climate change per se may be difficult to detect if we do not first understand the impact of land use change. This formed the dominant theme of the research by the PI (Pulliam). Both land use change and year to year climate change can directly affect other populations and two examples of this formed the focus of the remaining research, models of invertebrates in Carolina Bays and a model of a commercial estuarine population of blue crabs.

  3. Natural and anthropogenic climate change. Final report

    SciTech Connect

    Wang, W.C.; Ronberg, B.; Gutowski, W.; Molnar, G.; Li, K.R.

    1986-08-01

    The report describes a one-year research project which was the initial phase of a research program intended: (1) to refine and validate a 2-D climate model for studying the CO/sub 2/ and trace gases climatic effects; and (2) to participate in the United States of America (USA) Department of Energy/The People's Republic of China (PRC) Academia Sinica research project on CO/sub 2/-induced climate changes. The overall objective is to find ways to model regional climate change in a global warming environment potentially induced by CO/sub 2/ increase. The first task has two subtasks: (a) to incorporate a boundary layer parameterization into the 2-D radiative-dynamical model of Wang et al. (1984) and study its impact on climate sensitivity; and (b) to validate the 2-D radiative-dynamical models through comparisons with data and with other more comprehensive climate models so that our confidence in the model simulation of trace gases climatic effects can be increased. The second task is intended to: (a) analyze the climate data to improve our understanding of local/regional climate changes (in particular the desertification problem); and (b) coordinate the various research programs within the USA/PRC CO/sub 2/ project, which is critical in successfully achieving the research project scientific goals.

  4. FY08 LDRD Final Report Regional Climate

    SciTech Connect

    Bader, D C; Chin, H; Caldwell, P M

    2009-05-19

    An integrated, multi-model capability for regional climate change simulation is needed to perform original analyses to understand and prepare for the impacts of climate change on the time and space scales that are critical to California's future environmental quality and economic prosperity. Our intent was to develop a very high resolution regional simulation capability to address consequences of climate change in California to complement the global modeling capability that is supported by DOE at LLNL and other institutions to inform national and international energy policies. The California state government, through the California Energy Commission (CEC), institutionalized the State's climate change assessment process through its biennial climate change reports. The bases for these reports, however, are global climate change simulations for future scenarios designed to inform international policy negotiations, and are primarily focused on the global to continental scale impacts of increasing emissions of greenhouse gases. These simulations do not meet the needs of California public and private officials who will make major decisions in the next decade that require an understanding of climate change in California for the next thirty to fifty years and its effects on energy use, water utilization, air quality, agriculture and natural ecosystems. With the additional development of regional dynamical climate modeling capability, LLNL will be able to design and execute global simulations specifically for scenarios important to the state, then use those results to drive regional simulations of the impacts of the simulated climate change for regions as small as individual cities or watersheds. Through this project, we systematically studied the strengths and weaknesses of downscaling global model results with a regional mesoscale model to guide others, particularly university researchers, who are using the technique based on models with less complete parameterizations or

  5. Final scientific report for DOE award title: Improving the Representation of Ice Sedimentation Rates in Global Climate Models

    SciTech Connect

    Mitchell, David L.

    2013-09-05

    It is well known that cirrus clouds play a major role in regulating the earth’s climate, but the details of how this works are just beginning to be understood. This project targeted the main property of cirrus clouds that influence climate processes; the ice fall speed. That is, this project improves the representation of the mass-weighted ice particle fall velocity, Vm, in climate models, used to predict future climate on global and regional scales. Prior to 2007, the dominant sizes of ice particles in cirrus clouds were poorly understood, making it virtually impossible to predict how cirrus clouds interact with sunlight and thermal radiation. Due to several studies investigating the performance of optical probes used to measure the ice particle size distribution (PSD), as well as the remote sensing results from our last ARM project, it is now well established that the anomalously high concentrations of small ice crystals often reported prior to 2007 were measurement artifacts. Advances in the design and data processing of optical probes have greatly reduced these ice artifacts that resulted from the shattering of ice particles on the probe tips and/or inlet tube, and PSD measurements from one of these improved probes (the 2-dimensional Stereo or 2D-S probe) are utilized in this project to parameterize Vm for climate models. Our original plan in the proposal was to parameterize the ice PSD (in terms of temperature and ice water content) and ice particle mass and projected area (in terms of mass- and area-dimensional power laws or m-D/A-D expressions) since these are the microphysical properties that determine Vm, and then proceed to calculate Vm from these parameterized properties. But the 2D-S probe directly measures ice particle projected area and indirectly estimates ice particle mass for each size bin. It soon became apparent that the original plan would introduce more uncertainty in the Vm calculations

  6. Climate system modeling program

    SciTech Connect

    1995-12-31

    The Climate System Modeling Project is a component activity of NSF's Climate Modeling, Analysis and Prediction Program, supported by the Atmospheric Sciences Program, Geosciences Directorate. Its objective is to accelerate progress toward reliable prediction of global and regional climate changes in the decades ahead. CSMP operates through workshops, support for post-docs and graduate students and other collaborative activities designed to promote interdisciplinary and strategic work in support of the overall objective (above) and specifically in three areas, (1) Causes of interdecadal variability in the climate system, (2) Interactions of regional climate forcing with global processes, and (3) Scientific needs of climate assessment.

  7. Research on the climatic effects of nuclear winter: Final report

    SciTech Connect

    Dickinson, R.E.

    1986-12-03

    The National Center for Atmospheric Research (NCAR) has undertaken a series of research efforts to develop and implement improvements to the Community Climate Model (CCM) needed to make the model more applicable to studies of the climatic effects of nuclear war. The development of the model improvements has reached a stage where implementation may proceed, and several of the developed routines are being incorporated into the next approved version of the CCM (CCM1). Formal documentation is being completed describing the specific model improvements that have been successfully implemented. This final report includes the series of annual proposals and progress reports that have guided the project.

  8. Climate models and model evaluation

    SciTech Connect

    Gates, W.L.

    1994-12-31

    This brief overview addresses aspects of the nature, uses, evaluation and limitations of climate models. A comprehensive global modeling capability has been achieved only for the physical climate system, which is characterized by processes that serve to transport and exchange momentum, heat and moisture within and between the atmosphere, ocean and land surface. The fundamental aim of climate modeling, and the justification for the use of climate models, is the need to achieve a quantitative understanding of the operation of the climate system and to exploit any potential predictability that may exist.

  9. A dynamically-coupled groundwater, land surface and regional climate model to predict seasonal watershed flow and groundwater response, FINAL LDRD REPORT.

    SciTech Connect

    Maxwell, R; Kollet, S; Chow, F; Granvold, P; Duan, Q

    2007-02-23

    This final report is organized in four sections. Section 1 is the project summary (below), Section 2 is a submitted manuscript that describes the offline, or spinup simulations in detail, Section 3 is also a submitted manuscript that describes the online, or fully-coupled simulations in detail and Section 3, which is report that describes work done via a subcontract with UC Berkeley. The goal of this project was to develop and apply a coupled regional climate, land-surface, groundwater flow model as a means to further understand important mass and energy couplings between regional climate, the land surface, and groundwater. The project involved coupling three distinct submodels that are traditionally used independently with abstracted and potentially oversimplified (inter-model) boundary conditions. This coupled model lead to (1) an improved understanding of the sensitivity and importance of coupled physical processes from the subsurface to the atmosphere; (2) a new tool for predicting hydrologic conditions (rainfall, temperature, snowfall, snowmelt, runoff, infiltration and groundwater flow) at the watershed scale over a range of timeframes; (3) a simulation of hydrologic response of a characteristic watershed that will provide insight into the certainty of hydrologic forecasting, dominance and sensitivity of groundwater dynamics on land-surface fluxes; and (4) a more realistic model representation of weather predictions, precipitation and temperature, at the regional scale. Regional climate models are typically used for the simulation of weather, precipitation and temperature behavior over 10-1000 km domains for weather or climate prediction purposes, and are typically driven by boundary conditions derived from global climate models (GCMs), observations or both. The land or ocean surface typically represents a bottom boundary condition of these models, where important mass (water) and energy fluxes are approximated. The viability and influence of these

  10. Regional climates in GCMs. Final report

    SciTech Connect

    Crane, R.G.

    1995-12-31

    This research describes empirical methods developed to obtain short-term, regional results from global climate models. Observational data sets were compared to the GENESIS climate model; spatial and temporal variability were examined to validate the circulation model on the synoptic scale. A feed-forward neural network was used to determine transfer functions for circulation-precipitation relationships. The empirical methodologies derived were then applied to the analysis of mountain snowpack in the upper Colorado Basin. The comparison of observational data and the model showed that the synoptic scale circulation of the GENESIS model is realistic over the eastern United States; however, the model features are displaced south by about five degrees and actual pressures in the model are much lower than observed pressures. Preliminary results from the neural network produced correlations between observed and predicted rainfall of about 0.7 to 0.8, depending on the net configuration. Similar results were obtained for the upper Colorado Basin study in the prediction of winter snowfall. 6 refs., 3 figs.

  11. Regional Climate Modeling: Progress, Challenges, and Prospects

    SciTech Connect

    Wang, Yuqing; Leung, Lai R.; McGregor, John L.; Lee, Dong-Kyou; Wang, Wei-Chyung; Ding, Yihui; Kimura, Fujio

    2004-12-01

    Regional climate modeling with regional climate models (RCMs) has matured over the past decade and allows for meaningful utilization in a broad spectrum of applications. In this paper, latest progresses in regional climate modeling studies are reviewed, including RCM development, applications of RCMs to dynamical downscaling for climate change assessment, seasonal climate predictions and climate process studies, and the study of regional climate predictability. Challenges and potential directions of future research in this important area are discussed, with the focus on those to which less attention has been given previously, such as the importance of ensemble simulations, further development and improvement of regional climate modeling approach, modeling extreme climate events and sub-daily variation of clouds and precipitation, model evaluation and diagnostics, applications of RCMs to climate process studies and seasonal predictions, and development of regional earth system models. It is believed that with both the demonstrated credibility of RCMs’ capability in reproducing not only monthly to seasonal mean climate and interannual variability but also the extreme climate events when driven by good quality reanalysis and the continuous improvements in the skill of global general circulation models (GCMs) in simulating large-scale atmospheric circulation, regional climate modeling will remain an important dynamical downscaling tool for providing the needed information for assessing climate change impacts and seasonal climate predictions, and a powerful tool for improving our understanding of regional climate processes. An internationally coordinated effort can be developed with different focuses by different groups to advance regional climate modeling studies. It is also recognized that since the final quality of the results from nested RCMs depends in part on the realism of the large-scale forcing provided by GCMs, the reduction of errors and improvement in

  12. Refining climate models

    SciTech Connect

    Warren, Jeff; Iversen, Colleen; Brooks, Jonathan; Ricciuto, Daniel

    2012-10-31

    Using dogwood trees, Oak Ridge National Laboratory researchers are gaining a better understanding of the role photosynthesis and respiration play in the atmospheric carbon dioxide cycle. Their findings will aid computer modelers in improving the accuracy of climate simulations.

  13. Refining climate models

    ScienceCinema

    Warren, Jeff; Iversen, Colleen; Brooks, Jonathan; Ricciuto, Daniel

    2016-07-12

    Using dogwood trees, Oak Ridge National Laboratory researchers are gaining a better understanding of the role photosynthesis and respiration play in the atmospheric carbon dioxide cycle. Their findings will aid computer modelers in improving the accuracy of climate simulations.

  14. Modeling the response of plants and ecosystems to CO{sub 2} and climate change. Final technical report, September 1, 1992--August 31, 1996

    SciTech Connect

    Reynolds, J.F.

    1998-04-10

    Objectives can be divided into those for plant modeling and those for ecosystem modeling and experimental work in support of both. The author worked in a variety of ecosystem types, including pine, arctic, desert, and grasslands. Plant modeling objectives are: (1) to construct generic models of leaf, canopy, and whole-plant response to elevated CO{sub 2} and climate change; (2) to validate predictions of whole-plant response against various field studies of elevated CO{sub 2} and climate change; (3) to use these models to test specific hypotheses and to make predictions about primary, secondary and tertiary effects of elevated CO{sub 2} and climate change on individual plants for conditions and time frames beyond those used to calibrate the model; and (4) to provide information to higher-level models, such as community models and ecosystem models. Ecosystem level modeling objectives are: (1) to incorporate models of plant responses to elevated CO{sub 2} into a generic ecosystem model in order to predict the direct and indirect effects of elevated CO{sub 2} and climate change on ecosystems; (2) to validate model predictions of total system-level response (including decomposition) against various ecosystem field studies of elevated CO{sub 2} and climate change; (3) to use the ecosystem model to test specific hypotheses and to make predictions about primary, secondary and tertiary effects of elevated CO{sub 2} and climate change on ecosystems for conditions and time frames beyond those used to calibrate the model; and (4) to use the ecosystem model to study effects of change in CO{sub 2} and climate at regional and global scales. Occasionally the author conducted some experimental work that was deemed important to the development of the models. This work was mainly physiological work that could be performed in the Duke University Phytotron, using existing facilities.

  15. Modeling Climate Dynamically

    ERIC Educational Resources Information Center

    Walsh, Jim; McGehee, Richard

    2013-01-01

    A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…

  16. Modeling glacial climates

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

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

    SciTech Connect

    Chassignet, Eric P

    2013-03-18

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

  18. Collaborative Project: The problem of bias in defining uncertainty in computationally enabled strategies for data-driven climate model development. Final Technical Report.

    SciTech Connect

    Huerta, Gabriel

    2016-05-10

    The objective of the project is to develop strategies for better representing scientific sensibilities within statistical measures of model skill that then can be used within a Bayesian statistical framework for data-driven climate model development and improved measures of model scientific uncertainty. One of the thorny issues in model evaluation is quantifying the effect of biases on climate projections. While any bias is not desirable, only those biases that affect feedbacks affect scatter in climate projections. The effort at the University of Texas is to analyze previously calculated ensembles of CAM3.1 with perturbed parameters to discover how biases affect projections of global warming. The hypothesis is that compensating errors in the control model can be identified by their effect on a combination of processes and that developing metrics that are sensitive to dependencies among state variables would provide a way to select version of climate models that may reduce scatter in climate projections. Gabriel Huerta at the University of New Mexico is responsible for developing statistical methods for evaluating these field dependencies. The UT effort will incorporate these developments into MECS, which is a set of python scripts being developed at the University of Texas for managing the workflow associated with data-driven climate model development over HPC resources. This report reflects the main activities at the University of New Mexico where the PI (Huerta) and the Postdocs (Nosedal, Hattab and Karki) worked on the project.

  19. Final Report: Fine-Mesh Treatment of the Land Component of a Global Climate Model, September 1, 1994 - August 31, 1998

    SciTech Connect

    Dickinson, Robert E.

    1998-08-31

    The characteristics of land important for climate are very heterogeneous, as are the key atmospheric inputs to land, i.e. precipitation and radiation. To adequately represent this heterogeneity, state-of-the-art climate models should represent atmospheric inputs to land, land properties, and the dynamical changes of land at the highest resolution accessible by climate models. The research funded under this project focused on the development of an alternative approach to this problem in which a sub-mesh is imposed on each atmospheric model grid square. This allows representation of the land climate dynamics at a higher resolution than that achievable in the global atmospheric models. The high spatial detail of the fine-mesh treatment provides not only a more accurate representation of land processes to the atmospheric model, but also the opportunity for direct downscaling of the surface climate. The principal objectives were: (1) To complete the development of fine-mesh data structures in the VBATS model and its link to CCM2; (2) To improve BATS model parameterizations; (3) To complete and refine fine-mesh atmospheric parameterizations; and (4) To conduct sensitivity studies. The primary shift in goals has been to include and emphasize linkages to CCM3 which has been publicly released as of May 1996.

  20. Energy balance climate models

    NASA Technical Reports Server (NTRS)

    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.

  1. Climate Model Predictions and Climate Observations: Where are we going?

    NASA Astrophysics Data System (ADS)

    Wielicki, B. A.

    2011-12-01

    such a system beyond our reach? Have we failed to communicate clearly enough to the public and policymakers? Do climate modeling groups understand the needed observations? Have we failed to perform climate Observing System Simulation Experiments (OSSEs) similar to those we do more routinely for weather observations? Is the complexity of the job (atmosphere, ocean, cyrosphere, biosphere, chemistry) too large for specialist scientists or policymakers to embrace or understand? This paper provides a view of these questions with a perspective ranging from the beginning of the NASA Earth Observing System to the current observing system situation. The observation requirements will be put in the context of testing climate model predictions on decade time scale to narrow key uncertainties like radiative forcing, climate response, and climate sensitivity. Testing the accuracy of climate model predictions is in essence an uncertainty traceability tree from climate model predicted decadal change, through the uncertainty of natural variability, and through a range of intermediate observational uncertainties that finally reach comparisons to international physical standards like the watt or the kelvin. This traceability tree will be used to consider the current and future state of observations used to rigorously test the accuracy of climate model predictions.

  2. Watershed Modeling to Assess the Sensitivity of Streamflow, Nutrient, and Sediment Loads to Potential Climate Change and Urban Development in 20 U.S. Watersheds (Final Report)

    EPA Science Inventory

    Watershed modeling was conducted in 20 large, U.S. watersheds to assess the sensitivity of streamflow, nutrient (nitrogen and phosphorus), and sediment loading to a range of plausible mid-21st Century climate change and urban development scenarios in different regions of the nati...

  3. Integrating Remote Sensing, Field Observations, and Models to Understand Disturbance and Climate Effects on the Carbon Balance of the West Coast U.S., Final Report

    SciTech Connect

    Beverly E. Law

    2011-10-05

    As an element of NACP research, the proposed investigation is a two pronged approach that derives and evaluates a regional carbon (C) budget for Oregon, Washington, and California. Objectives are (1) Use multiple data sources, including AmeriFlux data, inventories, and multispectral remote sensing data to investigate trends in carbon storage and exchanges of CO2 and water with variation in climate and disturbance history; (2) Develop and apply regional modeling that relies on these multiple data sources to reduce uncertainty in spatial estimates of carbon storage and NEP, and relative contributions of terrestrial ecosystems and anthropogenic emissions to atmospheric CO2 in the region; (3) Model terrestrial carbon processes across the region, using the Biome-BGC terrestrial ecosystem model, and an atmospheric inverse modeling approach to estimate variation in rate and timing of terrestrial uptake and feedbacks to the atmosphere in response to climate and disturbance.

  4. Climate Change and Aquatic Invasive Species (Final Report)

    EPA Science Inventory

    EPA announced the availability of the final report, Climate Change and Aquatic Invasive Species. This report reviews available literature on climate-change effects on aquatic invasive species (AIS) and examines state-level AIS management activities. Data on management ...

  5. Climate Model Output Rewriter

    SciTech Connect

    Taylor, K. E.; Doutriaux, C.

    2004-06-21

    CMOR comprises a set of FORTRAN 90 dunctions that can be used to produce CF-compliant netCDF files. The structure of the files created by CMOR and the metadata they contain fulfill the requirements of many of the climate community’s standard model experiments (which are referred to here as "MIPS", which stands for "model intercomparison project", including, for example, AMIP, CMIP, CFMIP, PMIP, APE, and IPCC scenario runs), CMOR was not designed to serve as an all-purpose wfiter of CF-compliant netCDF files, but simply to reduce the effort required to prepare and manage MIP data. Although MIPs encourage systematic analysis of results across models, this is only easy to do if the model output is written in a common format with files structured similarly and with sufficient metadata uniformly stored according to a common standard. Individual modeling groups store their data in different ways. but if a group can read its own data with FORTRAN, then it should easily be able to transform the data, using CMOR, into the common format required by the MIPs, The adoption of CMOR as a standard code for exchanging climate data will facilitate participation in MIPs because after learning how to satisfy the output requirements of one MIP, it will be easy to prepare output for the other MIPs.

  6. A coupled regional climate-biosphere model for climate studies

    SciTech Connect

    Bossert, J.; Winterkamp, J.; Barnes, F.; Roads, J.

    1996-04-01

    This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The objective of this project has been to develop and test a regional climate modeling system that couples a limited-area atmospheric code to a biosphere scheme that properly represents surface processes. The development phase has included investigations of the impact of variations in surface forcing parameters, meteorological input data resolution, and model grid resolution. The testing phase has included a multi-year simulation of the summer climate over the Southwest United States at higher resolution than previous studies. Averaged results from a nine summer month simulation demonstrate the capability of the regional climate model to produce a representative climatology of the Southwest. The results also show the importance of strong summertime thermal forcing of the surface in defining this climatology. These simulations allow us to observe the climate at much higher temporal and spatial resolutions than existing observational networks. The model also allows us to see the full three-dimensional state of the climate and thereby deduce the dominant physical processes at any particular time.

  7. Thermohaline circulations and global climate change. Final report

    SciTech Connect

    Hanson, H.P.

    1996-10-01

    This report discusses results from the project entitled Thermohaline Circulations and Global Climate Change. Results are discussed in three sections related to the development of the Miami Isopycnic Coordinate Ocean Model (MICOM), surface forcing of the ocean by the atmosphere, and experiments with the MICOM related to the problem of the ocean`s response to global climate change. It will require the use of a global, coupled ocean-atmospheric climate model to quantify the feedbacks between ocean and atmosphere associated with climate changes. The results presented here do provide guidance for such studies in the future.

  8. Climate and atmospheric modeling studies

    NASA Technical Reports Server (NTRS)

    1992-01-01

    The climate and atmosphere modeling research programs have 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 model, and an upper ocean model. Principal applications were the study of the impact of CO2, aerosols, and the solar 'constant' on climate.

  9. Several Computational Opportunities and Challenges Associated with Climate Change Modeling

    SciTech Connect

    Wang, Dali; Post, Wilfred M; Wilson, Bruce E

    2010-01-01

    One of the key factors in the improved understanding of climate science is the development and improvement of high fidelity climate models. These models are critical for projections of future climate scenarios, as well as for highlighting the areas where further measurement and experimentation are needed for knowledge improvement. In this paper, we focus on several computing issues associated with climate change modeling. First, we review a fully coupled global simulation and a nested regional climate model to demonstrate key design components, and then we explain the underlying restrictions associated with the temporal and spatial scale for climate change modeling. We then discuss the role of high-end computers in climate change sciences. Finally, we explain the importance of fostering regional, integrated climate impact analysis. Although we discuss the computational challenges associated with climate change modeling, and we hope those considerations can also be beneficial to many other modeling research programs involving multiscale system dynamics.

  10. Climate Change and Aquatic Invasive Species (Final Report) ...

    EPA Pesticide Factsheets

    EPA announced the availability of the final report, Climate Change and Aquatic Invasive Species. This report reviews available literature on climate-change effects on aquatic invasive species (AIS) and examines state-level AIS management activities. Data on management activities came from publicly available information, was analyzed with respect to climate-change effects, and was reviewed by managers. This report also analyzes state and regional AIS management plans to determine their capacity to incorporate information on changing conditions generally, and climate change specifically. The report is intended for managers and scientists working with AIS to provide them with information on the potential effects of climate change on AIS, strategies for adapting their management to accomodate these environmental changes, and highlight further research needs and gaps.

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

    SciTech Connect

    Not Available

    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.

  12. Do regional climate models represent regional climate?

    NASA Astrophysics Data System (ADS)

    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

  13. Climate Models: A New Babel?

    NASA Astrophysics Data System (ADS)

    Steinhaeuser, Karsten; Tsonis, Anastasios

    2013-04-01

    Today there are over 20 different climate models which are used to make climate simulations and future climate projections. These models are used as tools to understand climate variability (control runs) and to simulate how climate change will affect the planet (forced runs) not only at the annual/global average level but over specific areas of the globe. In these models the evaluation of large scale variability such as the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), the El Nino/Southern Oscillation (ENSO), and the Pacific/North American (PNA) pattern is done at the component level. To evaluate how well the models reproduce ENSO, for example, the average temperature of the NINO3 area (5deg N to 5deg S, 140deg W to 90deg W) is computed for all models and the corresponding power spectra are compared to that of the actual observations (reality). This component-level evaluation gives an idea of how well a certain mode or pattern is simulated by the models. It does not, however, give an indication of how well the models generate the interplay of a set of modes. The above mentioned oscillations as well as other modes are major atmospheric and oceanic signals in the temperature and pressure (sea and upper levels) fields. They are coupled, they often synchronize, and their collective behavior defines the large scale variability of climate at interannual and decadal time scales. Thus, if a model simulates adequately ENSO but not PDO to which is coupled, then the model does not adequately simulates their interplay and thus the dynamics. We will address the issue of comparing climate models at the "dynamics" level with a new approach involving climate networks.

  14. Modeling of hydrologic conditions and solute movement in processed oil shale waste embankments under simulated climatic conditions. Final report, November 1995

    SciTech Connect

    1995-12-31

    A study is described on the hydrological and geotechnical behavior of an oil shale solid waste. The objective was to obtain information which can be used to assess the environmental impacts of oil shale solid waste disposal in the Green River Basin. The spent shale used in this study was combusted by the Lurgi-Ruhrgas process by Rio Blanco Oil Shale Company, Inc. Laboratory bench-scale testing included index properties, such as grain size distribution and Atterberg limits, and tests for engineering properties including hydraulic conductivity and shear strength. Large-scale tests were conducted on model spent shale waste embankments to evaluate hydrological response, including infiltration, runoff, and seepage. Large-scale tests were conducted at a field site in western Colorado and in the Environmental Simulation Laboratory (ESL)at the University of Wyoming. The ESL tests allowed the investigators to control rainfall and temperature, providing information on the hydrological response of spent shale under simulated severe climatic conditions. All experimental methods, materials, facilities, and instrumentation are described in detail, and results are given and discussed. 34 refs.

  15. Modeling Earth's Climate

    ERIC Educational Resources Information Center

    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…

  16. Contribution to the development of DOE ARM Climate Modeling Best Estimate Data (CMBE) products: Satellite data over the ARM permanent and AMF sites: Final Report

    SciTech Connect

    Xie, B; Dong, X; Xie, S

    2012-05-18

    To support the LLNL ARM infrastructure team Climate Modeling Best Estimate (CMBE) data development, the University of North Dakota (UND)'s group will provide the LLNL team the NASA CERES and ISCCP satellite retrieved cloud and radiative properties for the periods when they are available over the ARM permanent research sites. The current available datasets, to date, are as follows: the CERES/TERRA during 200003-200812; the CERES/AQUA during 200207-200712; and the ISCCP during 199601-200806. The detailed parameters list below: (1) CERES Shortwave radiative fluxes (net and downwelling); (2) CERES Longwave radiative fluxes (upwelling) - (items 1 & 2 include both all-sky and clear-sky fluxes); (3) CERES Layered clouds (total, high, middle, and low); (4) CERES Cloud thickness; (5) CERES Effective cloud height; (6) CERES cloud microphysical/optical properties; (7) ISCCP optical depth cloud top pressure matrix; (8) ISCCP derived cloud types (r.g., cirrus, stratus, etc.); and (9) ISCCP infrared derived cloud top pressures. (10) The UND group shall apply necessary quality checks to the original CERES and ISCCP data to remove suspicious data points. The temporal resolution for CERES data should be all available satellite overpasses over the ARM sites; for ISCCP data, it should be 3-hourly. The spatial resolution is the closest satellite field of view observations to the ARM surface sites. All the provided satellite data should be in a format that is consistent with the current ARM CMBE dataset so that the satellite data can be easily merged into the CMBE dataset.

  17. BASINs and WEPP Climate Assessment Tools (CAT): Case Study Guide to Potential Applications (Final Report)

    EPA Science Inventory

    EPA announced the release of the final report, BASINs and WEPP Climate Assessment Tools (CAT): Case Study Guide to Potential Applications. This report supports application of two recently developed water modeling tools, the Better Assessment Science Integrating point & ...

  18. Use of ARM data to test an improved parameterization of upper tropospheric clouds for use in climate models. Final report, December 1, 1991--May 30, 1995

    SciTech Connect

    Randall, D.A.; Xu, KuanMan

    1995-03-01

    We have developed new cloud parameterizations, and tested them in an SCM, a CEM, and a full three-dimensional GCM. We have demonstrated the ability to drive the SCM and the CEM with observations similar to those that we are about to receive from ARM. We have used the three-dimensional GCM to investigate some aspects of the role of clouds in climate. The climate simulation, and especially the Earth`s radiation budget, has been substantially improved through use of the new parameterizations.

  19. The Finer Details: Climate Modeling

    NASA Technical Reports Server (NTRS)

    2000-01-01

    If you want to know whether you will need sunscreen or an umbrella for tomorrow's picnic, you can simply read the local weather report. However, if you are calculating the impact of gas combustion on global temperatures, or anticipating next year's rainfall levels to set water conservation policy, you must conduct a more comprehensive investigation. Such complex matters require long-range modeling techniques that predict broad trends in climate development rather than day-to-day details. Climate models are built from equations that calculate the progression of weather-related conditions over time. Based on the laws of physics, climate model equations have been developed to predict a number of environmental factors, for example: 1. Amount of solar radiation that hits the Earth. 2. Varying proportions of gases that make up the air. 3. Temperature at the Earth's surface. 4. Circulation of ocean and wind currents. 5. Development of cloud cover. Numerical modeling of the climate can improve our understanding of both the past and, the future. A model can confirm the accuracy of environmental measurements taken. in, the past and can even fill in gaps in those records. In addition, by quantifying the relationship between different aspects of climate, scientists can estimate how a future change in one aspect may alter the rest of the world. For example, could an increase in the temperature of the Pacific Ocean somehow set off a drought on the other side of the world? A computer simulation could lead to an answer for this and other questions. Quantifying the chaotic, nonlinear activities that shape our climate is no easy matter. You cannot run these simulations on your desktop computer and expect results by the time you have finished checking your morning e-mail. Efficient and accurate climate modeling requires powerful computers that can process billions of mathematical calculations in a single second. The NCCS exists to provide this degree of vast computing capability.

  20. Environmental, genetic, and ecophysiological variation of western and Utah juniper and their hybrids: A model system for vegetation response to climate change. Final report

    SciTech Connect

    Nowak, R.S.; Tausch, R.J.

    1998-11-01

    This report focuses on the following two research projects relating to the biological effects of climate change: Hybridization and genetic diversity populations of Utah (Juniperus osteosperma) and western (Juniperus occidentalis) juniper: Evidence from nuclear ribosomal and chloroplast DNA; and Ecophysiological patterns of pinyon and juniper.

  1. Aggregate Models of Climate Change

    NASA Astrophysics Data System (ADS)

    Hooss, G.; Voss, R.; Hasselmann, K.; Maier-Reimer, E.; Joos, F.

    Integrated assessment of climate change generally requires the evaluation of many transient scenario simulations of century-timescale changes in atmospheric compo- sition and climate, desirably with the accuracy of state-of-the-art three-dimensional (3D) coupled atmosphere-ocean general circulation models (GCMs). Such multi- scenario GCM computations are possible through appropriate representation of the models in aggregate forms. For this purpose, we developed Nonlinear Impulse- response projections of 3D models of the global (oceanic and terrestrial) Carbon cycle and the atmosphere-ocean Climate System (NICCS). For higher CO2 forcing, appli- cability is extended beyond the linear response domain through explicit treatment of dominant nonlinear effects. The climate change module was furthermore augmented with spatial patterns of change in some of the most impact-relevant fields. Applied to three long-term CO2 emission scenarios, the model demonstrates (a) the minor rela- tive role of the terrestrial carbon sink through CO2 fertilization, and (b) the necessity to reduce fossil carbon emissions to a very small fraction of today's rates within the next few decades if a major climate change is to be avoided.

  2. Model confirmation in climate economics.

    PubMed

    Millner, Antony; McDermott, Thomas K J

    2016-08-02

    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.

  3. Model confirmation in climate economics

    PubMed Central

    Millner, Antony; McDermott, Thomas K. J.

    2016-01-01

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

  4. Energy-balance climate models

    NASA Technical Reports Server (NTRS)

    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.

  5. An Analog Earth Climate Model

    NASA Astrophysics Data System (ADS)

    Varekamp, J. C.

    2010-12-01

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

  6. The Monash University Interactive Simple Climate Model

    NASA Astrophysics Data System (ADS)

    Dommenget, D.

    2013-12-01

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

  7. The Monash University Interactive Simple Climate Model

    NASA Astrophysics Data System (ADS)

    Dommenget, Dietmar

    2013-04-01

    The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 1000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

  8. Thermohaline circulations and global climate change. Final report

    SciTech Connect

    Hanson, H.P.

    1994-09-01

    This research is ultimately concerned with investigating the hypothesis that changes in surface thermal and hydrological forcing of the North Atlantic, changes that might be expected to accompany CO2-induced global warming, could result in ocean-atmosphere interactions` exerting a positive feedback on the climate system. This report concerns research conducted with funding from the Carbon Dioxide Research Program (now the Global Climate Change Program) of the US Department of Energy via grant no. DE-FG02-90ER61019 during the period 15 July 1990 - 14 July 1994. This was a three-year award, extended to a fourth year (15 July 1993 - 14 July 1994) via a no-cost extension. It is important to emphasize that this award has been renewed for an additional two years (15 July 1993 - 14 July 1995) via grant no. DE-FG03-93ER61646 (with the same title). Because the project was originally envisioned to be a five-year effort, many of the important results and conclusions will be available for the Final Report of that second award. This report therefore concerns mainly preliminary conclusions and a discussion of progress toward understanding the central hypothesis of the research.

  9. The impact of recent model improvements on GISS GCM predictions of climate change. Final technical report, September 15, 1992--September 14, 1994

    SciTech Connect

    Druyan, L.M.

    1994-12-31

    The response of the 8 x 10{degree} horizontal resolution version of Model 2 to the forcing of globally observed SST (1980--1986) was evaluated. The simulations showed a realistic interannual variability of interhemispheric gradients of layer mean temperatures in response to observed SST gradients, but modeled near-surface winds over the Atlantic Ocean were much weaker than observed, a symptom of the Model 2 planetary boundary layer (PBL). In addition, the interannual variability of peak-season rainfall rates over Northeast Brazil (Nordeste) from the experiment was considerably smaller than the observed, although the observed negative association between seasonal Nordeste rainfall and interhemispheric Atlantic SST differences was weakly present. Preliminary experiments at 4 x 5{degree} resolution incorporating two of the new model parameterizations show more variability of the simulated Nordeste rainfall in response to the SST forcing, but only slight improvement in the correlation with observations.

  10. Likelihood-Based Climate Model Evaluation

    NASA Technical Reports Server (NTRS)

    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.

  11. Climate Change Vulnerability Assessments: Four Case Studies of Water Utility Practices (2011 Final)

    EPA Science Inventory

    EPA is releasing the final report titled, Climate Change Vulnerability Assessments: Four Case Studies of Water Utility Practices. This report was prepared by the National Center for Environmental Assessment's Global Climate Research Staff in the Office of Research and Developmen...

  12. Final Report. Evaluating the Climate Sensitivity of Dissipative Subgrid-Scale Mixing Processes and Variable Resolution in NCAR's Community Earth System Model

    SciTech Connect

    Jablonowski, Christiane

    2015-12-14

    The goals of this project were to (1) assess and quantify the sensitivity and scale-dependency of unresolved subgrid-scale mixing processes in NCAR’s Community Earth System Model (CESM), and (2) to improve the accuracy and skill of forthcoming CESM configurations on modern cubed-sphere and variable-resolution computational grids. The research thereby contributed to the description and quantification of uncertainties in CESM’s dynamical cores and their physics-dynamics interactions.

  13. Evaluating climate models: Should we use weather or climate observations?

    SciTech Connect

    Oglesby, Robert J; Erickson III, David J

    2009-12-01

    Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their ability to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.

  14. Evaluating Climate Models: Should We Use Weather or Climate Observations?

    NASA Astrophysics Data System (ADS)

    Oglesby, R. J.; Rowe, C. M.; Maasch, K. A.; Erickson, D. J.; Hays, C.

    2009-12-01

    Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their ability to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.

  15. Uncertainty Quantification in Climate Modeling

    NASA Astrophysics Data System (ADS)

    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

  16. A National Strategy for Advancing Climate Modeling

    SciTech Connect

    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.

  17. Questions of bias in climate models

    SciTech Connect

    Smith, Steven J.; Wigley, Tom M.; Meinshausen, Malte; Rogelj, Joeri

    2014-08-27

    The recent work by Shindell usefully contributes to the debate over estimating climate sensitivity by highlighting an important aspect of the climate system: that climate forcings that occur over land result in a more rapid temperature response than forcings that are distributed more uniformly over the globe. While, as noted in this work, simple climate models may be biased by assuming the same temperature response for all forcing agents, the implication that the MAGICC model is biased in this way is not correct.

  18. Modeling climate related feedback processes

    SciTech Connect

    Elzen, M.G.J. den; Rotmans, J. )

    1993-11-01

    In order to assess their impact, the feedbacks which at present can be quantified reasonably are built into the Integrated Model to Assess the Greenhouse Effect (IMAGE). Unlike previous studies, this study describes the scenario- and time-dependent role of biogeochemical feedbacks. A number of simulation experiments are performed with IMAGE to project climate changes. Besides estimates of their absolute importance, the relative importance of individual biogeochemical feedbacks is considered by calculating the gain for each feedback process. This study focuses on feedback processes in the carbon cycle and the methane (semi-) cycle. Modeled feedbacks are then used to balance the past and present carbon budget. This results in substantially lower projections for atmospheric carbon dioxide than the Intergovernmental Panel on Climate Change (IPCC) estimates. The difference is approximately 18% from the 1990 level for the IPCC [open quotes]Business-as-Usual[close quotes] scenario. Furthermore, the IPCC's [open quotes]best guess[close quotes] value of the CO[sub 2] concentration in the year 2100 falls outside the uncertainty range estimated with our balanced modeling approach. For the IPCC [open quotes]Business-as-Usual[close quotes] scenario, the calculated total gain of the feedbacks within the carbon cycle appears to be negative, a result of the dominant role of the fertilization feedback. This study also shows that if temperature feedbacks on methane emissions from wetlands, rice paddies, and hydrates do materialize, methane concentrations might be increased by 30% by 2100. 70 refs., 17 figs., 7 tabs.

  19. Climate Sensitivity and Solar Cycle Response in Climate Models

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  20. Climate system studies: final report to the U.S. Department of Energy

    SciTech Connect

    Bradley, Raymond S.; Diaz, Henry F.

    2000-03-01

    In this final report, we summarize research on climate variability and forcing mechanisms responsible for these changes. We report on research related to high elevation climate change, changes in the hydrological cycle and the seasonality of precipitation and on changes in climatic extremes. A comprehensive bibliography of research articles and books arising from this grant is included as an appendix.

  1. Observations and simulations of climate forcings and feedbacks. Final report

    SciTech Connect

    Del Genio, A.D.

    1996-02-01

    The research conducted under this agreement sought to use available satellite data sets to document a variety of climate feedback processes by understanding the mechanisms of current climate variability (seasonal, interannual, temperature dependence). Comparisons with feedback processes operating in the GCM were performed to determine which aspects of the variability serve as the most reliable proxies for decadal climate change. This report focuses on three general areas of progress: upper troposphere water vapor, low cloud optical thickness, and tropical cumulus anvil clouds.

  2. Interactive Puzzles for the mean climate dyanmics and climate change with the Monash Simple Climate Model

    NASA Astrophysics Data System (ADS)

    Dommenget, D.

    2014-12-01

    The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model that simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations. Despite its simplicity the model simulates the mean climate and its response to external forcings, such as doubling of the CO2 concentrations very realistically.The Monash simple climate model web-interface allows you to do some entertaining and educational puzzles about the interaction of climate dynamics. By turning switches OFF and ON you control physical processes in the climate system, but you do not know what these processes. By testing a number of experiments you learn about the interactions in the climate system and thereby figure out which switch controls what process in the climate system. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

  3. Selecting global climate models for regional climate change studies.

    PubMed

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

    2009-05-26

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

  4. Selecting global climate models for regional climate change studies

    PubMed Central

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

    2009-01-01

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

  5. CLIMATE CHANGE AND AQUATIC INVASIVE SPECIES (Final Report)

    EPA Science Inventory

    This report reviews available literature on climate-change effects on aquatic invasive species (AIS) and examines state-level AIS management activities. Data on management activities came from publicly available information, was analyzed with respect to climate-change effects, a...

  6. Climate Sensitivity of the Community Climate System Model, Version 4

    SciTech Connect

    Bitz, Cecilia M.; Shell, K. M.; Gent, P. R.; Bailey, D. A.; Danabasoglu, G.; Armour, K. C.; Holland, M. M.; Kiehl, J. T.

    2012-05-01

    Equilibrium climate sensitivity of the Community Climate System Model Version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. We use the radiative kernel technique to show that from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude, and the shortwave cloud feedback increases. These two warming effects are partially canceled by cooling due to slight decreases in the global mean water-vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed-layer, slab ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab ocean model version for both CCSM3 and CCSM4. We argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.

  7. Climate Sensitivity of the Community Climate System Model, Version 4

    DOE PAGES

    Bitz, Cecilia M.; Shell, K. M.; Gent, P. R.; ...

    2012-05-01

    Equilibrium climate sensitivity of the Community Climate System Model Version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. We use the radiative kernel technique to show that from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude, and the shortwave cloud feedback increases. These twomore » warming effects are partially canceled by cooling due to slight decreases in the global mean water-vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed-layer, slab ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab ocean model version for both CCSM3 and CCSM4. We argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.« less

  8. A personal perspective on modelling the climate system

    PubMed Central

    Palmer, T. N.

    2016-01-01

    Given their increasing relevance for society, I suggest that the climate science community itself does not treat the development of error-free ab initio models of the climate system with sufficient urgency. With increasing levels of difficulty, I discuss a number of proposals for speeding up such development. Firstly, I believe that climate science should make better use of the pool of post-PhD talent in mathematics and physics, for developing next-generation climate models. Secondly, I believe there is more scope for the development of modelling systems which link weather and climate prediction more seamlessly. Finally, here in Europe, I call for a new European Programme on Extreme Computing and Climate to advance our ability to simulate climate extremes, and understand the drivers of such extremes. A key goal for such a programme is the development of a 1 km global climate system model to run on the first exascale supercomputers in the early 2020s. PMID:27274686

  9. Fully nonlinear data-assimilation in climate models

    NASA Astrophysics Data System (ADS)

    van Leeuwen, P. J.; Browne, P.

    2014-12-01

    While climate modelling requires huge computational resources, initialising climate models using data assimilation is even more demanding. As the climate system is highly nonlinear both through nonlinear dynamics and strong feed backs the data-assimilation methodology has to be nonlinear too. Furthermore, it has been realised that one best forecast is not that useful and proper uncertainty quantification is essential for advances in the field. Both requirements point to fully nonlinear ensemble techniques, such as particle filters. Recently particle filters have been generated that allow for efficient ensemble members for climate model initialisation, by generating proper samples from the posterior probability density function in huge dimensional spaces. Another issue is to connect the complex climate model to the data-assimilation code. We have developed a very efficient framework to do this using only MPI communication between separate model and data-assimilation executables, called EMPIRE. This framework allows for very fast connection of any complex model to state-of-the-art ensemble data-assimilation methods. We will show an example of use of this new methodology to the HadCM3 climate model, which has over 2 million model variables, using the EMPIRE framework. We will discuss timings and efficiency, as well as some of the physical results. Finally, we will discuss the coupling with the very high resolution UM vn8.2 with close to 300 million model variables.

  10. DOE SBIR Phase II Final Technical Report - Assessing Climate Change Effects on Wind Energy

    SciTech Connect

    Whiteman, Cameron; Capps, Scott

    2014-11-05

    Specialized Vertum Partners software tools were prototyped, tested and commercialized to allow wind energy stakeholders to assess the uncertainties of climate change on wind power production and distribution. This project resulted in three commercially proven products and a marketing tool. The first was a Weather Research and Forecasting Model (WRF) based resource evaluation system. The second was a web-based service providing global 10m wind data from multiple sources to wind industry subscription customers. The third product addressed the needs of our utility clients looking at climate change effects on electricity distribution. For this we collaborated on the Santa Ana Wildfire Threat Index (SAWTi), which was released publicly last quarter. Finally to promote these products and educate potential users we released “Gust or Bust”, a graphic-novel styled marketing publication.

  11. Land-Use Scenarios: National-Scale Housing-Density Scenarios Consistent with Climate Change Storylines (Final Report)

    EPA Science Inventory

    EPA announced the availability of the final report, Land-Use Scenarios: National-Scale Housing-Density Scenarios Consistent with Climate Change Storylines. This report describes the scenarios and models used to generate national-scale housing density scenarios for the con...

  12. Crop response to climate: ecophysical models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ecophysiological models were the dominant tools used to estimate the potential impact of climate change in agroecosystems in the Third and Fourth Assessment Reports of the IPCC and are widely used elsewhere in climate change research. These models, also known as “crop models” or “simulation models”,...

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

    SciTech Connect

    Kukla, G.; Gavin, J.

    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.

  14. Climate Model Diagnostic Analyzer Web Service System

    NASA Astrophysics Data System (ADS)

    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

  15. Final Report for "Analyzing and visualizing next generation climate data"

    SciTech Connect

    Pletzer, Alexander

    2012-11-13

    The project "Analyzing and visualizing next generation climate data" adds block-structured (mosaic) grid support, parallel processing, and 2D/3D curvilinear interpolation to the open-source UV-CDAT climate data analysis tool. Block structured grid support complies to the Gridspec extension submitted to the Climate and Forecast metadata conventions. It contains two parts: aggregation of data spread over multiple mosaic tiles (M-SPEC) and aggregation of temporal data stored in different files (F-SPEC). Together, M-SPEC and F-SPEC allow users to interact with data stored in multiple files as if the data were in a single file. For computational expensive tasks, a flexible, multi-dimensional, multi-type distributed array class allows users to process data in parallel using remote memory access. Both nodal and cell based interpolation is supported; users can choose between different interpolation libraries including ESMF and LibCF depending on the their particular needs.

  16. Model Learning Center. Final Report.

    ERIC Educational Resources Information Center

    Daviess County School District, Owensboro, KY.

    This handbook describes the model learning resources center in operation at Daviess County (Kentucky) State Vocational-Technical School and details its objectives, materials, and methods of operation. The manual is organized in six sections. The first section describes the learning resources center, and details its philosophy, purpose, objectives,…

  17. Weather Forecaster Understanding of Climate Models

    NASA Astrophysics Data System (ADS)

    Bol, A.; Kiehl, J. T.; Abshire, W. E.

    2013-12-01

    Weather forecasters, particularly those in broadcasting, are the primary conduit to the public for information on climate and climate change. However, many weather forecasters remain skeptical of model-based climate projections. To address this issue, The COMET Program developed an hour-long online lesson of how climate models work, targeting an audience of weather forecasters. The module draws on forecasters' pre-existing knowledge of weather, climate, and numerical weather prediction (NWP) models. In order to measure learning outcomes, quizzes were given before and after the lesson. Preliminary results show large learning gains. For all people that took both pre and post-tests (n=238), scores improved from 48% to 80%. Similar pre/post improvement occurred for National Weather Service employees (51% to 87%, n=22 ) and college faculty (50% to 90%, n=7). We believe these results indicate a fundamental misunderstanding among many weather forecasters of (1) the difference between weather and climate models, (2) how researchers use climate models, and (3) how they interpret model results. The quiz results indicate that efforts to educate the public about climate change need to include weather forecasters, a vital link between the research community and the general public.

  18. Physics modeling support contract: Final report

    SciTech Connect

    Not Available

    1987-09-30

    This document is the final report for the Physics Modeling Support contract between TRW, Inc. and the Lawrence Livermore National Laboratory for fiscal year 1987. It consists of following projects: TIBER physics modeling and systems code development; advanced blanket modeling task; time dependent modeling; and free electron maser for TIBER II.

  19. Climate modeling with decision makers in mind

    SciTech Connect

    Jones, Andrew; Calvin, Katherine; Lamarque, Jean -Francois

    2016-04-27

    The need for regional- and local-scale climate information is increasing rapidly as decision makers seek to anticipate and manage a variety of context-specific climate risks over the next several decades. Furthermore, global climate models are not developed with these user needs in mind, and they typically operate at resolutions that are too coarse to provide information that could be used to support regional and local decisions.

  20. An Appraisal of Coupled Climate Model Simulations

    SciTech Connect

    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.''

  1. Uncertainty Quantification in Climate Modeling and Projection

    SciTech Connect

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

    2016-05-01

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

  2. Climate Change and Interacting Stressors: Implications for Coral Reef Management in American Samoa (Final Report)

    EPA Science Inventory

    EPA announced the release of the final document, Climate Change and Interacting Stressors: Implications for Coral Reef Management in American Samoa. This report provides a synthesis of information on the interactive effects of climate change and other stressors on the reef...

  3. Climate Change Vulnerability Assessments: Four Case Studies of Water Utility Practices (2011 Final)

    EPA Science Inventory

    EPA has released the final report titled, Climate Change Vulnerability Assessments: Four Case Studies of Water Utility Practices. This report was prepared by the National Center for Environmental Assessment's Global Climate Research Staff in the Office of Research and D...

  4. Modeling and assessing international climate financing

    NASA Astrophysics Data System (ADS)

    Wu, Jing; Tang, Lichun; Mohamed, Rayman; Zhu, Qianting; Wang, Zheng

    2016-06-01

    Climate financing is a key issue in current negotiations on climate protection. This study establishes a climate financing model based on a mechanism in which donor countries set up funds for climate financing and recipient countries use the funds exclusively for carbon emission reduction. The burden-sharing principles are based on GDP, historical emissions, and consumptionbased emissions. Using this model, we develop and analyze a series of scenario simulations, including a financing program negotiated at the Cancun Climate Change Conference (2010) and several subsequent programs. Results show that sustained climate financing can help to combat global climate change. However, the Cancun Agreements are projected to result in a reduction of only 0.01°C in global warming by 2100 compared to the scenario without climate financing. Longer-term climate financing programs should be established to achieve more significant benefits. Our model and simulations also show that climate financing has economic benefits for developing countries. Developed countries will suffer a slight GDP loss in the early stages of climate financing, but the longterm economic growth and the eventual benefits of climate mitigation will compensate for this slight loss. Different burden-sharing principles have very similar effects on global temperature change and economic growth of recipient countries, but they do result in differences in GDP changes for Japan and the FSU. The GDP-based principle results in a larger share of financial burden for Japan, while the historical emissions-based principle results in a larger share of financial burden for the FSU. A larger burden share leads to a greater GDP loss.

  5. Evaluating models of climate and forest vegetation

    NASA Technical Reports Server (NTRS)

    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.

  6. COP21 climate negotiators' responses to climate model forecasts

    NASA Astrophysics Data System (ADS)

    Bosetti, Valentina; Weber, Elke; Berger, Loïc; Budescu, David V.; Liu, Ning; Tavoni, Massimo

    2017-02-01

    Policymakers involved in climate change negotiations are key users of climate science. It is therefore vital to understand how to communicate scientific information most effectively to this group. We tested how a unique sample of policymakers and negotiators at the Paris COP21 conference update their beliefs on year 2100 global mean temperature increases in response to a statistical summary of climate models' forecasts. We randomized the way information was provided across participants using three different formats similar to those used in Intergovernmental Panel on Climate Change reports. In spite of having received all available relevant scientific information, policymakers adopted such information very conservatively, assigning it less weight than their own prior beliefs. However, providing individual model estimates in addition to the statistical range was more effective in mitigating such inertia. The experiment was repeated with a population of European MBA students who, despite starting from similar priors, reported conditional probabilities closer to the provided models' forecasts than policymakers. There was also no effect of presentation format in the MBA sample. These results highlight the importance of testing visualization tools directly on the population of interest.

  7. The Status of Mars Climate Change Modeling

    NASA Technical Reports Server (NTRS)

    Haberle, Robert M.

    1997-01-01

    Researchers have reviewed the evidence that the climate of Mars has changed throughout its history. In this paper, the discussion focuses on where we stand in terms of modeling these climate changes. For convenience, three distinct types of climate regimes are considered: very early in the planet's history (more than 3.5 Ga), when warm wet conditions are thought to have prevailed; the bulk of the planet's history (3.5-1 Ga), during which episodic ocean formation has been suggested; and relatively recently in the planet's history (less than 1 Ga), when orbitally induced climate change is thought to have occurred.

  8. The Monash Simple Climate Model: An interactive climate model for teaching

    NASA Astrophysics Data System (ADS)

    Dommenget, Dietmar

    2015-04-01

    The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model that simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations. Despite its simplicity the model simulates the mean climate and its response to external forcings, such as doubling of the CO2 concentrations very realistically. The Monash simple climate model web-interface allows you to explore thousands of experiments, scenarios and tutorials in an interactive way. You can do some entertaining and educational puzzles about the interaction of climate dynamics. By turning switches OFF and ON you control physical processes in the climate system ansd see how the interaction of the processes builds up the climate. By testing a number of experiments you learn about the interactions in the climate system and thereby figure out which switch controls what process in the climate system. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

  9. Exploitation of Parallelism in Climate Models

    SciTech Connect

    Baer, F.; Tribbia, J.J.; Williamson, D.L.

    1999-03-01

    The US Department of Energy (DOE), through its CHAMMP initiative, hopes to develop the capability to make meaningful regional climate forecasts on time scales exceeding a decade, such capability to be based on numerical prediction type models. We propose research to contribute to each of the specific items enumerated in the CHAMMP announcement (Notice 91-3); i.e., to consider theoretical limits to prediction of climate and climate change on appropriate time scales, to develop new mathematical techniques to utilize massively parallel processors (MPP), to actually utilize MPPs as a research tool, and to develop improved representations of some processes essential to climate prediction. In particular, our goals are to: (1) Reconfigure the prediction equations such that the time iteration process can be compressed by use of MMP architecture, and to develop appropriate algorithms. (2) Develop local subgrid scale models which can provide time and space dependent parameterization for a state- of-the-art climate model to minimize the scale resolution necessary for a climate model, and to utilize MPP capability to simultaneously integrate those subgrid models and their statistics. (3) Capitalize on the MPP architecture to study the inherent ensemble nature of the climate problem. By careful choice of initial states, many realizations of the climate system can be determined concurrently and more realistic assessments of the climate prediction can be made in a realistic time frame. To explore these initiatives, we will exploit all available computing technology, and in particular MPP machines. We anticipate that significant improvements in modeling of climate on the decadal and longer time scales for regional space scales will result from our efforts.

  10. Validating predictions from climate envelope models

    USGS Publications Warehouse

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

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

  11. Final Laurentide ice-sheet deglaciation and Holocene climate-sea level change

    NASA Astrophysics Data System (ADS)

    Ullman, David J.; Carlson, Anders E.; Hostetler, Steven W.; Clark, Peter U.; Cuzzone, Joshua; Milne, Glenn A.; Winsor, Kelsey; Caffee, Marc

    2016-11-01

    Despite elevated summer insolation forcing during the early Holocene, global ice sheets retained nearly half of their volume from the Last Glacial Maximum, as indicated by deglacial records of global mean sea level (GMSL). Partitioning the GMSL rise among potential sources requires accurate dating of ice-sheet extent to estimate ice-sheet volume. Here, we date the final retreat of the Laurentide Ice Sheet with 10Be surface exposure ages for the Labrador Dome, the largest of the remnant Laurentide ice domes during the Holocene. We show that the Labrador Dome deposited moraines during North Atlantic cold events at ∼10.3 ka, 9.3 ka and 8.2 ka, suggesting that these regional climate events helped stabilize the retreating Labrador Dome in the early Holocene. After Hudson Bay became seasonally ice free at ∼8.2 ka, the majority of Laurentide ice-sheet melted abruptly within a few centuries. We demonstrate through high-resolution regional climate model simulations that the thermal properties of a seasonally ice-free Hudson Bay would have increased Laurentide ice-sheet ablation and thus contributed to the subsequent rapid Labrador Dome retreat. Finally, our new 10Be chronology indicates full Laurentide ice-sheet had completely deglaciated by 6.7 ± 0.4 ka, which re quires that Antarctic ice sheets contributed 3.6-6.5 m to GMSL rise since 6.3-7.1 ka.

  12. Modeling the Climatic Consequences of Geoengineering

    NASA Astrophysics Data System (ADS)

    Somerville, R. C.

    2005-12-01

    The last half-century has seen the development of physically comprehensive computer models of the climate system. These models are the primary tool for making predictions of climate change due to human activities, such as emitting greenhouse gases into the atmosphere. Because scientific understanding of the climate system is incomplete, however, any climate model will necessarily have imperfections. The inevitable uncertainties associated with these models have sometimes been cited as reasons for not taking action to reduce such emissions. Climate models could certainly be employed to predict the results of various attempts at geoengineering, but many questions would arise. For example, in considering proposals to increase the planetary reflectivity by brightening parts of the land surface or by orbiting mirrors, can models be used to bound the results and to warm of unintended consequences? How could confidence limits be placed on such model results? How can climate changes due to proposed geoengineering be distinguished from natural variability? There are historical parallels on smaller scales, in which models have been employed to predict the results of attempts to alter the weather, such as the use of cloud seeding for precipitation enhancement, hail suppression and hurricane modification. However, there are also many lessons to be learned from the recent record of using models to simulate the effects of the great unintended geoengineering experiment involving greenhouse gases, now in progress. In this major research effort, the same types of questions have been studied at length. The best modern models have demonstrated an impressive ability to predict some aspects of climate change. A large body of evidence has already accumulated through comparing model predictions to many observed aspects of recent climate change, ranging from increases in ocean heat content to changes in atmospheric water vapor to reductions in glacier extent. The preponderance of expert

  13. World Climate Research Programme (WCRP) Open Science Conference Final Report

    SciTech Connect

    Amy Honchar

    2012-11-07

    Travel support was provided for a range of invited speakers, students, early-career, and developing-country, and key scientists who required financial assistance to participate, and would otherwise be unable to attend, to contribute to, and benefit from, this important event. This support also allowed participants to present their research findings, provide input to WCRP planning and plans, and encourage collaboration with other research scientists. In particular, the participation and engagement of regional scientists in the OSC helped to ensure communication and advocacy in identifying the climate research needs of the region and their inclusion in the WCRP long-range research priorities.

  14. A Global Climate Model for Instruction.

    ERIC Educational Resources Information Center

    Burt, James E.

    This paper describes a simple global climate model useful in a freshman or sophomore level course in climatology. There are three parts to the paper. The first part describes the model, which is a global model of surface air temperature averaged over latitude and longitude. Samples of the types of calculations performed in the model are provided.…

  15. Climate Modeling and Prediction at NSIPP

    NASA Technical Reports Server (NTRS)

    Suarez, Max; Einaudi, Franco (Technical Monitor)

    2001-01-01

    The talk will review modeling and prediction efforts undertaken as part of NASA's Seasonal to Interannual Prediction Project (NSIPP). The focus will be on atmospheric model results, including its use for experimental seasonal prediction and the diagnostic analysis of climate anomalies. The model's performance in coupled experiments with land and atmosphere models will also be discussed.

  16. Developing Models for Predictive Climate Science

    SciTech Connect

    Drake, John B; Jones, Philip W

    2007-01-01

    The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strong tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of the

  17. Basins and Wepp Climate Assessment Tools (Cat): Case Study Guide to Potential Applications (Final Report)

    EPA Science Inventory

    Cover of the BASINS and WEPP <span class=Climate Assessment Tool: Case Study Final report"> This final report supports application of two recently developed...

  18. Some Do's and Dont's in Integrated Modelling for Climate Policy

    NASA Astrophysics Data System (ADS)

    Warren, R. F.

    2010-12-01

    Integrated models were originally developed to encompass an inter-disciplinary approach to the study of climate change and climate change policy. However, simple integrated models that have been applied to cost-benefit analysis (e.g., DICE/RICE, FUND, PAGE, etc.) suffer from a number of problems. Firstly, the ‘optimal’ climate policy is highly dependent on a number of key assumptions, such as discount rate and equity considerations. Secondly, impacts are generally represented simplistically, typically based on global estimates of market and non-market damages; the damage function shape used is theoretical and often based on an arbitrary choice of function; it is often calibrated using studies of climate change impacts in the USA, scaled to represent impacts in other regions. Thirdly, the representation of climate change itself may be inconsistent with IPCC projections. Fourthly, the ‘optimal’ policy derived is highly dependent on the methodology and parameters chosen in valuation of the damages. Thus it is recommended that future decision support in climate policy is supported by a risk assessment approach rather than an attempt to derive an ‘optimal’ level of climate change mitigation. Such a risk assessment approach is better suited to use of biophysically-based, IAMs such as CIAS, IMAGE, AIM, ICLIPS, GCAM, and CLIMPACTS that variously examine sectors and/or regions of the world, spanning multiple disciplines. The representation of impacts in these models is detailed but varies significantly between them. In the case of IMAGE, they are detailed and include interactions such as carbon cycle induced terrestrial vegetation die-back due to climate change (leading to an accelerated rate of climate change), links between climate change, land use change and changes to agricultural systems, and demographics. In others, such as ICLIPS and AIM, lookup tables relating impacts to climate variables are used. Even these models still generally omit the interactions

  19. Model Democracy: Are All Climate Models Equally Good?

    NASA Astrophysics Data System (ADS)

    Shukla, J.

    2008-05-01

    We compare the ability of IPCC climate models to simulate present climate and their sensitivity to increased greenhouse gases. We find that models with higher fidelity in simulating the present climate produce higher values of global warming due to increased greenhouse gases. We also compare the forecast skill of dynamical seasonal prediction by coupled ocean-atmosphere models and their ability to simulate observed climate. Although all the current generation of coupled models have large error in simulating observed climate, yet the models with higher fidelity have higher skill. We conclude that there is a significant relationship between model fidelity and model sensitivity, and therefore, the IPCC assessments should not accept the concept of model democracy. We further conjecture that inaccuracy of climate models is the most dominant obstacle in both realizing the potential predictability of climate variations, and in providing reliable information on regional climate change. We make some proposals for the future pathways to improve the fidelity of climate models, and to harvest the realizable predictability.

  20. Whither low-order climate models?

    NASA Astrophysics Data System (ADS)

    Viebahn, Jan; Dijkstra, Henk A.

    2015-04-01

    A zoo of low-order (small degrees of freedom) deterministic and stochastic climate models has appeared in the literature with each focussing on specific aspects of (paleo)climate variability. The advantage of these models is that their behavior can be analyzed in detail and hence cause and effect (mechanisms) can be disentangled efficiently. Indeed, much insight has been obtained by `thinking deep about simple models'. However, the disadvantage is that each model usually contains idealizations and severe approximations such that the mechanisms underlying a certain phenomenon in these models may not represent the mechanisms which are at work in more detailed models and in observations. The danger is thus that low-order model results will be ignored by many of the climate science community. In this presentation, focus will be on several issues related to the use of low-order model results. Did the results of these models contribute to a better understanding of observed climate variability or did they only aggravate the confusion about cause and effect? In the spirit of `essentially all models are wrong but some are useful' (George Box), which type of models (e.g. stochastic versus deterministic, ad hoc versus truncated, etc.) has been more useful than others (has been the best fit for purpose)? Does this provide future guidelines on the development and usage of these models? Example models and their results will serve to address these issues.

  1. Modeling of Past Climates: Some Perspectives

    NASA Astrophysics Data System (ADS)

    Kutzbach, J. E.

    2008-12-01

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

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

    SciTech Connect

    Forster, P M A F; Taylor, K E

    2006-07-25

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

  3. The Community Climate System Model: CCSM3

    SciTech Connect

    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.

  4. ARM Climate Modeling Best Estimate Data

    SciTech Connect

    Xie, S.; Jensen, M.; McCoy, R. B.; Klein, S. A.; Cederwall, R. T.; Wiscombe, W. J.; Clothiaux, E. E.; Gaustad, K. L.; Golaz, J.-C.; Hall, S.; Johnson, K. L.; Lin, Y.; Long, C. N.; Mather, J. H.; McCord, R. A.; McFarlane, S. A.; Palanisamy, G.; Shi, Y.; Turner, D. D.

    2010-01-01

    The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) was created in 1989 to address scientific uncertainties related to global climate change, with a focus on the crucial role of clouds and their influence on the transfer of radiation in the atmosphere. A central activity is the acquisition of detailed observations of clouds and radiation, as well as related atmospheric variables for climate model evaluation and improvement. Since 1992, ARM has established six permanent ARM Climate Research Facility (ACRF) sites and deployed an ARM Mobile Facility (AMF) in diverse climate regimes around the world (Fig. 1) to perform long-term continuous field measurements. The time record of ACRF data now exceeds a decade at most ACRF fixed sites and ranges from several months to one year for AMF deployments. Billions of measurements are currently stored in millions of data files in the ACRF Data Archive. The long-term continuous ACRF data provide invaluable information to improve our understanding of the interaction between clouds and radiation, and an observational basis for model validation and improvement and climate studies. Given the huge number of data files and current diversity of archived ACRF data structures, however, it can be difficult for an outside user such as a climate modeler to quickly find the ACRF data product(s) that best meets their research needs. The required geophysical quantities may exist in multiple data streams, and over the history of ACRF operations, the measurements could be obtained by a variety of instruments, reviewed with different levels of data quality assurance, or derived using different algorithms. In addition, most ACRF data are stored in daily-based files with a temporal resolution that ranges from a few seconds to a few minutes, which is much finer than that sought by some users. Therefore, it is not as convenient for data users to perform quick comparisons over large spans of data, and this

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

    SciTech Connect

    Liu, Zhengyu; Kutzbach, J.; Jacob, R.; Prentice, C.

    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.

  6. Modelling climate change and malaria transmission.

    PubMed

    Parham, Paul E; Michael, Edwin

    2010-01-01

    The impact of climate change on human health has received increasing attention in recent years, with potential impacts due to vector-borne diseases only now beginning to be understood. As the most severe vector-borne disease, with one million deaths globally in 2006, malaria is thought most likely to be affected by changes in climate variables due to the sensitivity of its transmission dynamics to environmental conditions. While considerable research has been carried out using statistical models to better assess the relationship between changes in environmental variables and malaria incidence, less progress has been made on developing process-based climate-driven mathematical models with greater explanatory power. Here, we develop a simple model of malaria transmission linked to climate which permits useful insights into the sensitivity of disease transmission to changes in rainfall and temperature variables. Both the impact of changes in the mean values of these key external variables and importantly temporal variation in these values are explored. We show that the development and analysis of such dynamic climate-driven transmission models will be crucial to understanding the rate at which P. falciparum and P. vivax may either infect, expand into or go extinct in populations as local environmental conditions change. Malaria becomes endemic in a population when the basic reproduction number R0 is greater than unity and we identify an optimum climate-driven transmission window for the disease, thus providing a useful indicator for determing how transmission risk may change as climate changes. Overall, our results indicate that considerable work is required to better understand ways in which global malaria incidence and distribution may alter with climate change. In particular, we show that the roles of seasonality, stochasticity and variability in environmental variables, as well as ultimately anthropogenic effects, require further study. The work presented here

  7. Climate Change Modeling:Computational Opportunities and Challenges

    SciTech Connect

    Wang, Dali; Post, Wilfred M; Wilson, Bruce E

    2011-01-01

    High- delity climate models are the workhorses of modern climate change sciences. In this article, the authors focus on several computational issues associated with climate change modeling, covering simulation methodologies, temporal and spatial modeling restrictions, the role of high-end computing, as well as the importance of data-driven regional climate impact modeling.

  8. Objective calibration of regional climate models

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  9. Towards convection-resolving climate modeling

    NASA Astrophysics Data System (ADS)

    Schar, C.; Ban, N.; Fuhrer, O.; Keller, M.; Lapillonne, X.; Leutwyler, D.; Lüthi, D.; Schlemmer, L.; Schmidli, J.; Schulthess, T. C.

    2015-12-01

    Moist convection is a fundamental process in our climate system, but is usually parameterized in climate models. The underlying approximations introduce significant uncertainties and biases, and there is thus a general thrust towards the explicit representation of convection. For climate applications, convection-resolving simulations are still very expensive, but are increasingly becoming feasible. Here we present recent results pertaining to the development and exploitation of convection-resolving regional climate models. We discuss the potential and challenges of the approach, highlight validation using decade-long simulations, explore convection-resolving climate change scenarios, and provide an outlook on the use of next-generation supercomputing architectures. Detailed results will be presented using the COSMO model over two computational domains at a horizontal resolution of 2.2 km. The first covers an extended Alpine region from Northern Italy to Northern Germany. For this domain decade-long simulations have been conducted, driven by both reanalysis as well as CMIP5 model data. Results show that explicit convection leads to significant improvements in the representation of summer precipitation, and to substantial differences in climate projections in terms of precipitation statistics. The second domain covers European (with 1536x1536x60 grid points) and the respective simulations exploit heterogeneous many-core hardware architectures. Results demonstrate realistic mesoscale processes embedded in synoptic-scale features, such as line convection along cold frontal systems, or the triggering of moist convection by propagating cold-air pools. Currently a 10-year simulation using this set up is near completion. To efficiently use GPU-based high-performance computers, the model code underwent significant development, including a rewrite of the dynamical core in C++. It is argued that today's largest supercomputers would in principle be able to support - already

  10. Final Laurentide ice-sheet deglaciation and Holocene climate-sea level change

    USGS Publications Warehouse

    Ullman, David J.; Carlson, Anders E.; Hostetler, Steven W.; Clark, Peter U.; Cuzzone, Joshua; Milne, Glenn A.; Winsor, Kelsey; Caffee, Marc A.

    2016-01-01

    Despite elevated summer insolation forcing during the early Holocene, global ice sheets retained nearly half of their volume from the Last Glacial Maximum, as indicated by deglacial records of global mean sea level (GMSL). Partitioning the GMSL rise among potential sources requires accurate dating of ice-sheet extent to estimate ice-sheet volume. Here, we date the final retreat of the Laurentide Ice Sheet with 10Be surface exposure ages for the Labrador Dome, the largest of the remnant Laurentide ice domes during the Holocene. We show that the Labrador Dome deposited moraines during North Atlantic cold events at ∼10.3 ka, 9.3 ka and 8.2 ka, suggesting that these regional climate events helped stabilize the retreating Labrador Dome in the early Holocene. After Hudson Bay became seasonally ice free at ∼8.2 ka, the majority of Laurentide ice-sheet melted abruptly within a few centuries. We demonstrate through high-resolution regional climate model simulations that the thermal properties of a seasonally ice-free Hudson Bay would have increased Laurentide ice-sheet ablation and thus contributed to the subsequent rapid Labrador Dome retreat. Finally, our new 10Be chronology indicates full Laurentide ice-sheet had completely deglaciated by 6.7 ± 0.4 ka, which re quires that Antarctic ice sheets contributed 3.6–6.5 m to GMSL rise since 6.3–7.1 ka.

  11. A Regional Climate Modeling Study of the Effects of Irrigation and Urbanization on California Climate

    NASA Astrophysics Data System (ADS)

    Kueppers, L. M.; Snyder, M. A.; Sloan, L. C.; Bryant, S.

    2005-12-01

    California and neighboring states have seen significant changes in land cover and land use over the past century, with expanding urbanization along the Pacific coast and extensive agricultural development inland. Expanded irrigation and urbanization both have implications for local and regional climate due to changes in land surface albedo, vegetation roughness, maximum vegetation cover, and seasonal variation in soil moisture. We modified a regional climate model, RegCM3, which already included irrigated and dryland crop types, to include urban and suburban land cover types. We used the model to quantify the difference in climate between cases using pre-settlement land cover and modern (~1990) land cover. We used 1979-1989 NCEP reanalysis data as input at the model perimeter, encompassing a very wet year and several very dry years. We analyzed the final 8 years of output to give soil moisture adequate time to equilibrate. Irrigated agricultural land in California's Central and Imperial Valleys had the strongest effect on both temperature and relative humidity. During the April-November dry season, monthly average surface temperature was cooler after conversion from pre-settlement vegetation to modern irrigated cropland. During the same period, relative humidity was higher. We found no change in precipitation rates. The effects were likely due to the increased soil water availability with irrigation, as the changes largely vanish during the rainy months of December-March. At the resolution of our model (30km), we found no significant effects of urbanization on local or regional climate. This could be due to the proximity of most urban areas to the coast, or due to the urban parameterization that we employed. Overall, the modeled effect of irrigation on temperature is comparable in magnitude, but opposite in sign, to the temperature effect of business-as-usual CO2 increases predicted for California by RegCM. This result emphasizes the need for models of future

  12. Inter-variable relations in regional climate model outputs

    NASA Astrophysics Data System (ADS)

    Wilcke, R.; Chandler, R. E.; Prein, A. F.

    2015-12-01

    Regional climate models (RCMs) intent to provide physically consistent climate data to the climate change impact research community. However, the effects of parametrisations of unresolved sub-grid processes and systematic biases in the model output requires not only a post-processing in form of bias adjustment but also an analysis of inter-variable relations. Many impact models require several climate variables as input data, which makes it necessary to check if the inter-variable dependence structure is simulated realistically by RCMs. A common practice is to bias adjust RCM output variables to improve their individual distribution and mean climate characteristics. This can be done by empirical bias adjustment procedures such as quantile mapping. However, applying statistical bias adjustment procedures on individual variables may alter the inter-variable relationships given by the climate model and hence distort the physical consistency.In our study we examined the inter-variable relations of RCM output variables by using estimates of conditional probability density functions for pairs of variables. Conditional densities obtained from multiple European RCMs were compared with those obtained from observations. We quantified the extent to which these conditional density estimates are distorted by an empirical bias adjustment procedure. Additionally, the influence of the model physics on the representation of inter-variable relations is analysed for a 24 member perturbed physics ensemble of WRF simulations in the U.S.. Here, multiple observational data sets were used to address the influence of observational uncertainties on the analysis. Finally, the results obtained from the European and U.S. modelling initiatives are compared to provide a common basis on the representation of inter-variable relations in RCM outputs.

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

    USGS Publications Warehouse

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-08-01

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

  15. Bjerknes compensation in the Bergen Climate Model

    NASA Astrophysics Data System (ADS)

    Outten, Stephen; Esau, Igor

    2016-11-01

    The meridional transport of heat is a critical component of the Earth's climate system. If the total heat transported by the climate system is approximately constant, then the anomalies of heat transported by the atmosphere and ocean should be approximately equal and opposite, a scenario now called Bjerknes compensation. This has previously been found in two coupled climate models, with both showing multi-decadal variability in the heat transports. This work identifies Bjerknes compensation in the Bergen Climate Model, adding to the understanding of the robust features of Bjerknes compensation in coupled climate models. The atmospheric and oceanic heat transports are investigated in the 600-year control run of a fully-coupled global climate model. The presence of Bjerknes compensation is confirmed by the strong anti-correlation and equal magnitude of the anomalies of these heat transports. The heat transport anomalies contain a signal of multi-decadal variability. Since natural variability in global heat transport could mask anthropogenic climate change signals, understanding Bjerknes compensation is of socio-economic importance. Using regression analysis the atmospheric and oceanic responses to the multi-decadal variability of the Bjerknes compensation signal are investigated. This highlights the importance of the marginal ice zones of the Greenland and Barents Seas as the critical location for coupling the atmosphere and ocean. During periods of increased heat transport in the ocean, these regions show decreased sea-ice, leading to increased fluxes and local temperatures, and giving rise to a thermal low-pressure center and a non-local high-pressure centre, thus changing the atmospheric flow on multi-decadal timescales.

  16. 21 Layer troposphere-stratosphere climate model

    NASA Technical Reports Server (NTRS)

    Rind, D.; Suozzo, R.; Lacis, A.; Russell, G.; Hansen, J.

    1984-01-01

    The global climate model is extended through the stratosphere by increasing the vertical resolution and raising the rigid model top to the 0.01 mb (75 km) level. The inclusion of a realistic stratosphere is necessary for the investigation of the climate effects of stratospheric perturbations, such as changes of ozone, aerosols or solar ultraviolet irradiance, as well as for studying the effect on the stratosphere of tropospheric climate changes. The observed temperature and wind patterns throughout the troposphere and stratosphere are simulated. In addition to the excess planetary wave amplitude in the upper stratosphere, other model deficiences include the Northern Hemisphere lower stratospheric temperatures being 5 to 10 C too cold in winter at high latitudes and the temperature at 50 to 60 km altitude near the equator are too cold. Methods of correcting these deficiencies are discussed.

  17. High dimensional decision dilemmas in climate models

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    PubMed

    Hoffmann, Holger; Rath, Thomas

    2013-01-01

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

  19. INCCA: Integrated Climate and Carbon Final Report of the LLNL LDRD Strategic Initiative

    SciTech Connect

    Thompson, S L

    2004-02-13

    The INCCA (Integrated Climate and Carbon) strategic initiative developed and applied the ability to simulate the fate and climate impact of fossil fuel-derived carbon dioxide (CO{sub 2}) on a global scale. Coupled climate and carbon cycle modeling like that of INCCA is required to understand and predict the future environmental impacts of fossil fuel burning. At present, atmospheric CO{sub 2} concentrations are prescribed, not simulated, in large climate models. Credible simulations of the entire climate system, however, need to predict time-evolving climate forcing using anthropogenic emissions as the fundamental input. Predicting atmospheric CO{sub 2} concentrations represents a substantial scientific advance because there are large natural sources and sinks of carbon that are likely to change as a result of climate change. Both terrestrial (e.g., vegetation on land) and oceanic components of the carbon cycle are known to be sensitive to climate change. Estimates of the amount of man-made CO{sub 2} that will accumulate in the atmosphere depend on understanding the carbon cycle. For this reason, models that use CO{sub 2} emissions, not prescribed atmospheric concentrations, as fundamental inputs are required to directly address greenhouse-related questions of interest to policymakers.

  20. Testing Connections between Campanian Ignimbrite Volcanism, Climate, and the Final Decline of the Neanderthals

    NASA Astrophysics Data System (ADS)

    Black, B. A.; Manga, M.; Neely, R. R., III

    2014-12-01

    The eruption of the Campanian Ignimbrite 40,000 years ago coincided approximately with the final decline of the Neanderthals and a technological and cultural transition from the Middle to Upper Paleolithic. Two end-member hypotheses have been advanced to explain Neanderthal decline: competition with anatomically modern humans and failure to adapt in the face of environmental stresses. The eruption of the Campanian Ignimbrite has been cited as a potentially major cause of such environmental stress. In this work, we draw on published datasets including ice core records, maps and simulations of ash dispersal, and petrologic measurements to constrain the characteristics of the Campanian Ignimbrite eruption. To investigate the climatic effects of the eruption, we use a three-dimensional sectional aerosol model to simulate the global aerosol cloud after 25 Tg and 100 Tg sulfur release scenarios. We couple these aerosol properties to a comprehensive earth system model under last glacial conditions. We find that summer temperatures were colder for several years after the eruption, with some simulations predicting temperature decreases of up to 10 degrees in Eastern Europe and Asia. While this cold interval may have impacted hominid communities in Siberia, the overall distribution of the cooling we observe in our model is inconsistent with catastrophic collapse of Neanderthal populations in Europe. Nonetheless, the volcanic cooling could have influenced daily life for a generation of Neanderthals and anatomically modern humans.

  1. Evaluating Urban Resilience to Climate Change: A Multi-Sector Approach (Final Report)

    EPA Science Inventory

    EPA is announcing the availability of this final report prepared by the Air, Climate, and Energy (ACE) Research Program, located within the Office of Research and Development, with support from Cadmus. One of the goals of the ACE research program is to provide scientific informat...

  2. Implications of Climate Change for State Bioassessment Programs and Approaches to Account for Effects (Final Report)

    EPA Science Inventory

    EPA announced the availability of the final report, Implications of Climate Change for State Bioassessment Programs and Approaches to Account for Effects. This report uses biological data collected by four states in wadeable rivers and streams to examine the components ...

  3. Implications of Climate Change for State Bioassessment Programs and Approaches to Account for Effects (Final Report)

    EPA Science Inventory

    This final report uses biological data collected by four states in wadeable rivers and streams to examine the components of state and tribal bioassessment and biomonitoring programs that may be vulnerable to climate change. The study investigates the potential to identify biologi...

  4. Global Climate Models of the Terrestrial Planets

    NASA Astrophysics Data System (ADS)

    Forget, F.; Lebonnois, S.

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

  5. A framework for regional modeling of past climates

    NASA Astrophysics Data System (ADS)

    Sloan, L. C.

    2006-09-01

    The methods of reconstructing ancient climate information from the rock record are summarized, and the climate forcing factors that have been active at global and regional scales through Earth history are reviewed. In this context, the challenges and approaches to modeling past climates by using a regional climate model are discussed. A significant challenge to such modeling efforts arises if the time period of interest occurred prior to the past ˜3 5 million years, at which point land sea distributions and topography markedly different from present must be specified at the spatial resolution required by regional climate models. Creating these boundary conditions requires a high degree of geologic knowledge, and also depends greatly upon the global climate model driving conditions. Despite this and other challenges, regional climate models represent an important and unique tool for paleoclimate investigations. Application of regional climate models to paleoclimate studies may provide another way to assess the overall performance of regional climate models.

  6. FOAM: Expanding the horizons of climate modeling

    SciTech Connect

    Tobis, M.; Foster, I.T.; Schafer, C.M.

    1997-10-01

    We report here on a project that expands the applicability of dynamic climate modeling to very long time scales. The Fast Ocean Atmosphere Model (FOAM) is a coupled ocean atmosphere model that incorporates physics of interest in understanding decade to century time scale variability. It addresses the high computational cost of this endeavor with a combination of improved ocean model formulation, low atmosphere resolution, and efficient coupling. It also uses message passing parallel processing techniques, allowing for the use of cost effective distributed memory platforms. The resulting model runs over 6000 times faster than real time with good fidelity, and has yielded significant results.

  7. Modeling the climatic response to orbital variations.

    PubMed

    Imbrie, J; Imbrie, J Z

    1980-02-29

    According to the astronomical theory of climate, variations in the earth's orbit are the fundamental cause of the succession of Pleistocene ice ages. This article summarizes how the theory has evolved since the pioneer studies of James Croll and Milutin Milankovitch, reviews recent evidence that supports the theory, and argues that a major opportunity is at hand to investigate the physical mechanisms by which the climate system responds to orbital forcing. After a survey of the kinds of models that have been applied to this problem, a strategy is suggested for building simple, physically motivated models, and a time-dependent model is developed that simulates the history of planetary glaciation for the past 500,000 years. Ignoring anthropogenic and other possible sources of variation acting at frequencies higher than one cycle per 19,000 years, this model predicts that the long-term cooling trend which began some 6000 years ago will continue for the next 23,000 years.

  8. The impact of ARM on climate modeling

    SciTech Connect

    Randall, David A.; Del Genio, Anthony D.; Donner, Lee J.; Collins, William D.; Klein, Stephen A.

    2016-07-15

    Climate models are among humanity’s most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of Earth down to 100 km or smaller and implicitly include the effects of processes on even smaller scales down to a micron or so. In addition, the atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM).

  9. The impact of ARM on climate modeling

    DOE PAGES

    Randall, David A.; Del Genio, Anthony D.; Donner, Lee J.; ...

    2016-07-15

    Climate models are among humanity’s most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of Earth down to 100 km or smaller and implicitly include the effects of processes on even smaller scales down to a micron or so. In addition, themore » atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM).« less

  10. Climate Model Diagnostic Analyzer Web Service System

    NASA Astrophysics Data System (ADS)

    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

  11. A Practical Philosophy of Complex Climate Modelling

    NASA Technical Reports Server (NTRS)

    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.

  12. ARM Climate Modeling Best Estimate Data - A new data product for climate modelers

    SciTech Connect

    Xie, Shaocheng; McCoy, Renata; Klein, Stephen A.; Cederwall, Richard T.; Wiscombe, Warren J.; Clothiaux, Eugene E.; Gaustad, Krista L.; Golaz, Jean-Christophe; Hall, Stefanie; Jensen, Michael; Johnson, Karen L.; Lin, Yanluan; Long, Charles N.; Mather, James H.; McCord, Raymond A.; McFarlane, Sally A.; Palanisamy, Giriprakash; Shi, Yan; Turner, David D.

    2010-01-01

    This paper provides an overview of a new data product, named the Climate Modeling Best Estimate (CMBE) dataset, developed by the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Program in order to better serve the need of climate model developers and encourage greater use of ARM data by modelers. The CMBE dataset contains those quantities that are often used in model evaluation and reflect unique ARM measurements of clouds and radiation (e.g., cloud occurrence, liquid water path, and surface radiative fluxes) from the highest quality data that ARM has for many years. The data are averaged over one hour period, which is comparable to a typical temporal resolution used in climate model output. They are currently available at five ARM Climate Research Facility (ACRF) sites located at the Southern Great Plains, North Slope of Alaska, and Tropic Western Pacific, and can be obtained from the ACRF data archive. The long-term continuous ARM data provide invaluable information to improve our understanding of the interaction between clouds and radiation and a solid observational basis for model validation and improvement. This paper shows some examples to demonstrate its unique values in studies of cloud processes, climate variability and change, and climate modeling. Plans for future enhancements of the CMBE product are also discussed.

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

    NASA Astrophysics Data System (ADS)

    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.

  14. A Model for Climate Change Adaptation

    NASA Astrophysics Data System (ADS)

    Pasqualini, D.; Keating, G. N.

    2009-12-01

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

  15. LINKING MICROBES TO CLIMATE: INCORPORATING MICROBIAL ACTIVITY INTO CLIMATE MODELS COLLOQUIUM

    SciTech Connect

    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.

  16. A scalable climate health justice assessment model

    PubMed Central

    McDonald, Yolanda J.; Grineski, Sara E.; Collins, Timothy W.; Kim, Young-An

    2014-01-01

    This paper introduces a scalable “climate health justice” model for assessing and projecting incidence, treatment costs, and sociospatial disparities for diseases with well-documented climate change linkages. The model is designed to employ low-cost secondary data, and it is rooted in a perspective that merges normative environmental justice concerns with theoretical grounding in health inequalities. Since the model employs International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) disease codes, it is transferable to other contexts, appropriate for use across spatial scales, and suitable for comparative analyses. We demonstrate the utility of the model through analysis of 2008–2010 hospitalization discharge data at state and county levels in Texas (USA). We identified several disease categories (i.e., cardiovascular, gastrointestinal, heat-related, and respiratory) associated with climate change, and then selected corresponding ICD-9 codes with the highest hospitalization counts for further analyses. Selected diseases include ischemic heart disease, diarrhea, heat exhaustion/cramps/stroke/syncope, and asthma. Cardiovascular disease ranked first among the general categories of diseases for age-adjusted hospital admission rate (5286.37 per 100,000). In terms of specific selected diseases (per 100,000 population), asthma ranked first (517.51), followed by ischemic heart disease (195.20), diarrhea (75.35), and heat exhaustion/cramps/stroke/syncope (7.81). Charges associated with the selected diseases over the 3-year period amounted to US$5.6 billion. Blacks were disproportionately burdened by the selected diseases in comparison to non-Hispanic whites, while Hispanics were not. Spatial distributions of the selected disease rates revealed geographic zones of disproportionate risk. Based upon a downscaled regional climate-change projection model, we estimate a >5% increase in the incidence and treatment costs of asthma attributable to

  17. A scalable climate health justice assessment model.

    PubMed

    McDonald, Yolanda J; Grineski, Sara E; Collins, Timothy W; Kim, Young-An

    2015-05-01

    This paper introduces a scalable "climate health justice" model for assessing and projecting incidence, treatment costs, and sociospatial disparities for diseases with well-documented climate change linkages. The model is designed to employ low-cost secondary data, and it is rooted in a perspective that merges normative environmental justice concerns with theoretical grounding in health inequalities. Since the model employs International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) disease codes, it is transferable to other contexts, appropriate for use across spatial scales, and suitable for comparative analyses. We demonstrate the utility of the model through analysis of 2008-2010 hospitalization discharge data at state and county levels in Texas (USA). We identified several disease categories (i.e., cardiovascular, gastrointestinal, heat-related, and respiratory) associated with climate change, and then selected corresponding ICD-9 codes with the highest hospitalization counts for further analyses. Selected diseases include ischemic heart disease, diarrhea, heat exhaustion/cramps/stroke/syncope, and asthma. Cardiovascular disease ranked first among the general categories of diseases for age-adjusted hospital admission rate (5286.37 per 100,000). In terms of specific selected diseases (per 100,000 population), asthma ranked first (517.51), followed by ischemic heart disease (195.20), diarrhea (75.35), and heat exhaustion/cramps/stroke/syncope (7.81). Charges associated with the selected diseases over the 3-year period amounted to US$5.6 billion. Blacks were disproportionately burdened by the selected diseases in comparison to non-Hispanic whites, while Hispanics were not. Spatial distributions of the selected disease rates revealed geographic zones of disproportionate risk. Based upon a downscaled regional climate-change projection model, we estimate a >5% increase in the incidence and treatment costs of asthma attributable to

  18. CLIMATE IMPACTS ON REGIONAL AIR QUALITY (CIRAQ): MODELING OZONE SENSITIVITIES TO FUTURE CLIMATE

    EPA Science Inventory

    Using global and regional modeling tools, predictions of future climate and ozone concentrations are developed for the continental United States. Results suggest that future changes in climate will contribute to an increase in ozone concentrations; however, the future changes in...

  19. Load-balancing algorithms for climate models

    NASA Astrophysics Data System (ADS)

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

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

  20. Infrared radiation parameterizations in numerical climate models

    NASA Technical Reports Server (NTRS)

    Chou, Ming-Dah; Kratz, David P.; Ridgway, William

    1991-01-01

    This study presents various approaches to parameterizing the broadband transmission functions for utilization in numerical climate models. One-parameter scaling is applied to approximate a nonhomogeneous path with an equivalent homogeneous path, and the diffuse transmittances are either interpolated from precomputed tables or fit by analytical functions. Two-parameter scaling is applied to parameterizing the carbon dioxide and ozone transmission functions in both the lower and middle atmosphere. Parameterizations are given for the nitrous oxide and methane diffuse transmission functions.

  1. Modeling climate change impacts on water trading.

    PubMed

    Luo, Bin; Maqsood, Imran; Gong, Yazhen

    2010-04-01

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

  2. An Earth radiation budget climate model

    NASA Technical Reports Server (NTRS)

    Bartman, Fred L.

    1988-01-01

    A 2-D Earth Radiation Budget Climate Model has been constructed from an OLWR (Outgoing Longwave Radiation) model and an Earth albedo model. Each of these models uses the same cloud cover climatology modified by a factor GLCLC which adjusts the global annual average cloud cover. The two models are linked by a set of equations which relate the cloud albedos to the cloud top temperatures of the OLWR model. These equations are derived from simultaneous narrow band satellite measurements of cloud top temperature and albedo. Initial results include global annual average values of albedo and latitude/longitude radiation for 45 percent and 57 percent global annual average cloud cover and two different forms of the cloud albedo-cloud top temperature equations.

  3. New Gravity Wave Treatments for GISS Climate Models

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    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, we introduce a relatively simple and computationally efficient specification of unresolved orographic and non-orographic gravity waves and their interaction with the resolved flow. We show comparisons of the GISS model winds and temperatures with no gravity wave parametrization; with only orographic gravity wave parameterization; and with both orographic and non-orographic gravity wave parameterizations to illustrate how the zonal mean winds and temperatures converge toward observations. We also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. We then show results where the non-orographic gravity wave sources are specified to represent sources from convection in the Intertropical Convergence Zone and spontaneous emission from jet imbalances. Finally, we suggest a strategy to include these effects in a climate dependent manner.

  4. New Gravity Wave Treatments for GISS Climate Models

    NASA Technical Reports Server (NTRS)

    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.

  5. Climate Science for a Sustainable Energy Future Test Bed and Data Infrastructure Final Report

    SciTech Connect

    Williams, Dean N.; Foster, I.; Van Dam, Kerstin Kleese; Shipman, G.

    2014-05-04

    The collaborative Climate Science for a Sustainable Energy Future (CSSEF) project started in July 2011 with the goal of accelerating the development of climate model components (i.e., atmosphere, ocean and sea ice, and land surface) and enhancing their predictive capabilities while incorporating uncertainty quantification (UQ). This effort required accessing and converting observational data sets into specialized model testing and verification data sets and building a model development test bed, where model components and sub-models can be rapidly evaluated. CSSEF’s prototype test bed demonstrated, how an integrated testbed could eliminate tedious activities associated with model development and evaluation, by providing the capability to constantly compare model output—where scientists store, acquire, reformat, regrid, and analyze data sets one-by-one—to observational measurements in a controlled test bed.

  6. The seasonal-cycle climate model

    NASA Technical Reports Server (NTRS)

    Marx, L.; Randall, D. A.

    1981-01-01

    The seasonal cycle run which will become the control run for the comparison with runs utilizing codes and parameterizations developed by outside investigators is discussed. The climate model currently exists in two parallel versions: one running on the Amdahl and the other running on the CYBER 203. These two versions are as nearly identical as machine capability and the requirement for high speed performance will allow. Developmental changes are made on the Amdahl/CMS version for ease of testing and rapidity of turnaround. The changes are subsequently incorporated into the CYBER 203 version using vectorization techniques where speed improvement can be realized. The 400 day seasonal cycle run serves as a control run for both medium and long range climate forecasts alsensitivity studies.

  7. A new model for quantifying climate episodes

    NASA Astrophysics Data System (ADS)

    Biondi, Franco; Kozubowski, Tomasz J.; Panorska, Anna K.

    2005-07-01

    When long records of climate (precipitation, temperature, stream runoff, etc.) are available, either from instrumental observations or from proxy records, the objective evaluation and comparison of climatic episodes becomes necessary. Such episodes can be quantified in terms of duration (the number of time intervals, e.g. years, the process remains continuously above or below a reference level) and magnitude (the sum of all series values for a given duration). The joint distribution of duration and magnitude is represented here by a stochastic model called BEG, for bivariate distribution with exponential and geometric marginals. The model is based on the theory of random sums, and its mathematical derivation confirms and extends previous empirical findings. Probability statements that can be obtained from the model are illustrated by applying it to a 2300-year dendroclimatic reconstruction of water-year precipitation for the eastern Sierra Nevada-western Great Basin. Using the Dust Bowl drought period as an example, the chance of a longer or greater drought is 8%. Conditional probabilities are much higher, i.e. a drought of that magnitude has a 62% chance of lasting for 11 years or longer, and a drought that lasts 11 years has a 46% chance of having an equal or greater magnitude. In addition, because of the bivariate model, we can estimate a 6% chance of witnessing a drought that is both longer and greater. Additional examples of model application are also provided. This type of information provides a way to place any climatic episode in a temporal perspective, and such numerical statements help with reaching science-based management and policy decisions.

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

    NASA Astrophysics Data System (ADS)

    Alexandru, Adelina; Sushama, Laxmi

    2014-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Alexandru, Adelina; Sushama, Laxmi

    2015-08-01

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

  10. On quantifying the climate of the nonautonomous Lorenz-63 model.

    PubMed

    Daron, J D; Stainforth, D A

    2015-04-01

    The Lorenz-63 model has been frequently used to inform our understanding of the Earth's climate and provide insight for numerical weather and climate prediction. Most studies have focused on the autonomous (time invariant) model behaviour in which the model's parameters are constants. Here, we investigate the properties of the model under time-varying parameters, providing a closer parallel to the challenges of climate prediction, in which climate forcing varies with time. Initial condition (IC) ensembles are used to construct frequency distributions of model variables, and we interpret these distributions as the time-dependent climate of the model. Results are presented that demonstrate the impact of ICs on the transient behaviour of the model climate. The location in state space from which an IC ensemble is initiated is shown to significantly impact the time it takes for ensembles to converge. The implication for climate prediction is that the climate may-in parallel with weather forecasting-have states from which its future behaviour is more, or less, predictable in distribution. Evidence of resonant behaviour and path dependence is found in model distributions under time varying parameters, demonstrating that prediction in nonautonomous nonlinear systems can be sensitive to the details of time-dependent forcing/parameter variations. Single model realisations are shown to be unable to reliably represent the model's climate; a result which has implications for how real-world climatic timeseries from observation are interpreted. The results have significant implications for the design and interpretation of Global Climate Model experiments.

  11. Coupling Climate Models and Forward-Looking Economic Models

    NASA Astrophysics Data System (ADS)

    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

  12. Confidence in climate models including those with suspended particles

    NASA Astrophysics Data System (ADS)

    Reck, Ruth A.

    1982-05-01

    Confidence in the predictions of atmospheric models is limited, (1) by the uncertainty in our knowledge of the existing atmospheric system as it is defined by input data, and (2) by the ability of the model to describe all pertinent atmospheric processes. This paper describes a thermal sensitivity study of the global parameters in one version of the Manabe-Wetherald radiative-convective model which inclkudes Mie scattering particles. The relative importance of the usual global model parameters is identified in addition to other atmospheric constituents not commonly included in climate models. In particular this work emphasizes the role of Mie scattering suspended aerosol particles, a component which is seldom included in climate models. Here we discuss the major sources of particles, how the optical properties of individual particles determine the radiative effects of a particle layer, and also illustrate the separate role of absorption and backscatter in determining the sign of the surface temperature change. In addition, the coupling of the particle effects to surface albedo is indicated. Finally, the sign of the surface temperature change from anthropogenic particles is estimated using (1) global maps of particle abundance developed by Kellogg, (2) previous calculations for the Northern Hemisphere published by the author and (3) the surface albedo maps of Hummel and Reck.

  13. Downscaling GISS ModelE boreal summer climate over Africa

    NASA Astrophysics Data System (ADS)

    Druyan, Leonard M.; Fulakeza, Matthew

    2016-12-01

    The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June-September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2° latitude by 2.5° longitude and the RM3 grid spacing is 0.44°. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

  14. Downscaling GISS ModelE Boreal Summer Climate over Africa

    NASA Technical Reports Server (NTRS)

    Druyan, Leonard M.; Fulakeza, Matthew

    2015-01-01

    The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June- September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2deg latitude by 2.5deg longitude and the RM3 grid spacing is 0.44deg. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

  15. CROW{trademark} process modeling. Final report

    SciTech Connect

    1996-01-01

    The Western Research Institute (WRI) has patented a technology (CROW{trademark}) for the recovery of oily contaminants from water-saturated formations. The CROW process uses either hot water or low-pressure steam to flush contaminants to the surface by means of production wells. CROW is typically applied to highly permeable aquifers that have been invaded by organics such as coal tars or chemical solvents. In conceptualizing a model of the CROW process, we draw an analogy between flushing organics from an organic-contaminated aquifer and producing oil from a petroleum reservoir. The organic-contaminated aquifer can be represented as a petroleum reservoir. The injection of water or steam and production of water/organic admixtures can be described by standard reservoir well equations. Finally, the movement of organic and water within the aquifer can be represented by Darcy flow of the individual phases. Thus, in modeling the CROW process, it is reasonable to assume that a petroleum reservoir simulator would accurately portray the recovery of organics from a contaminated aquifer. Of course, the reservoir simulator would need to incorporate thermal aspects of Darcy flow to accurately represent recovery during CROW processing.

  16. A Solar-luminosity Model and Climate

    NASA Technical Reports Server (NTRS)

    Perry, Charles A.

    1990-01-01

    Although the mechanisms of climatic change are not completely understood, the potential causes include changes in the Sun's luminosity. Solar activity in the form of sunspots, flares, proton events, and radiation fluctuations has displayed periodic tendencies. Two types of proxy climatic data that can be related to periodic solar activity are varved geologic formations and freshwater diatom deposits. A model for solar luminosity was developed by using the geometric progression of harmonic cycles that is evident in solar and geophysical data. The model assumes that variation in global energy input is a result of many periods of individual solar-luminosity variations. The 0.1-percent variation of the solar constant measured during the last sunspot cycle provided the basis for determining the amplitude of each luminosity cycle. Model output is a summation of the amplitudes of each cycle of a geometric progression of harmonic sine waves that are referenced to the 11-year average solar cycle. When the last eight cycles in Emiliani's oxygen-18 variations from deep-sea cores were standardized to the average length of glaciations during the Pleistocene (88,000 years), correlation coefficients with the model output ranged from 0.48 to 0.76. In order to calibrate the model to real time, model output was graphically compared to indirect records of glacial advances and retreats during the last 24,000 years and with sea-level rises during the Holocene. Carbon-14 production during the last millenium and elevations of the Great Salt Lake for the last 140 years demonstrate significant correlations with modeled luminosity. Major solar flares during the last 90 years match well with the time-calibrated model.

  17. Towards Systematic Benchmarking of Climate Model Performance

    NASA Astrophysics Data System (ADS)

    Gleckler, P. J.

    2014-12-01

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

  18. Borehole climatology: a discussion based on contributions from climate modeling

    NASA Astrophysics Data System (ADS)

    González-Rouco, J. F.; Beltrami, H.; Zorita, E.; Stevens, M. B.

    2008-01-01

    Progress in understanding climate variability through the last millennium leans on simulation and reconstruction efforts. Exercises blending both approaches present a great potential for answering questions relevant both for the simulation and reconstruction of past climate, and depend on the specific peculiarities of proxies and methods involved in climate reconstructions, as well as on the realism and limitations of model simulations. This paper explores research specifically related to paleoclimate modeling and borehole climatology as a branch of climate reconstruction that has contributed significantly to our knowledge of the low frequency climate evolution during the last five centuries. The text flows around three main issues that group most of the interaction between model and geothermal efforts: the use of models as a validation tool for borehole climate reconstructions; comparison of geothermal information and model simulations as a means of either model validation or inference about past climate; and implications of the degree of realism on simulating subsurface climate on estimations of future climate change. The use of multi-centennial simulations as a surrogate reality for past climate suggests that within the simplified reality of climate models, methods and assumptions in borehole reconstructions deliver a consistent picture of past climate evolution at long time scales. Comparison of model simulations and borehole profiles indicate that borehole temperatures are responding to past external forcing and that more realism in the development of the soil model components in climate models is desirable. Such an improved degree of realism is important for the simulation of subsurface climate and air-ground interaction; results indicate it could also be crucial for simulating the adequate energy balance within climate change scenario experiments.

  19. Borehole climatology: a discussion based on contributions from climate modeling

    NASA Astrophysics Data System (ADS)

    González-Rouco, J. F.; Beltrami, H.; Zorita, E.; Stevens, M. B.

    2009-03-01

    Progress in understanding climate variability through the last millennium leans on simulation and reconstruction efforts. Exercises blending both approaches present a great potential for answering questions relevant both for the simulation and reconstruction of past climate, and depend on the specific peculiarities of proxies and methods involved in climate reconstructions, as well as on the realism and limitations of model simulations. This paper explores research specifically related to paleoclimate modeling and borehole climatology as a branch of climate reconstruction that has contributed significantly to our knowledge of the low frequency climate evolution during the last five centuries. The text flows around three main issues that group most of the interaction between model and geothermal efforts: the use of models as a validation tool for borehole climate reconstructions; comparison of geothermal information and model simulations as a means of either model validation or inference about past climate; and implications of the degree of realism on simulating subsurface climate on estimations of future climate change. The use of multi-centennial simulations as a surrogate reality for past climate suggests that within the simplified reality of climate models, methods and assumptions in borehole reconstructions deliver a consistent picture of past climate evolution at long time scales. Comparison of model simulations and borehole profiles indicate that borehole temperatures are responding to past external forcing and that more realism in the development of the soil model components in climate models is desirable. Such an improved degree of realism is important for the simulation of subsurface climate and air-ground interaction; results indicate it could also be crucial for simulating the adequate energy balance within climate change scenario experiments.

  20. Emulating AOGCM results using simple climate models

    NASA Astrophysics Data System (ADS)

    Olivié, Dirk; Stuber, Nicola

    2010-12-01

    Three simple climate models (SCMs) are calibrated using simulations from atmosphere ocean general circulation models (AOGCMs). In addition to using two conventional SCMs, results from a third simpler model developed specifically for this study are obtained. An easy to implement and comprehensive iterative procedure is applied that optimises the SCM emulation of global-mean surface temperature and total ocean heat content, and, if available in the SCM, of surface temperature over land, over the ocean and in both hemispheres, and of the global-mean ocean temperature profile. The method gives best-fit estimates as well as uncertainty intervals for the different SCM parameters. For the calibration, AOGCM simulations with two different types of forcing scenarios are used: pulse forcing simulations performed with 2 AOGCMs and gradually changing forcing simulations from 15 AOGCMs obtained within the framework of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. The method is found to work well. For all possible combinations of SCMs and AOGCMs the emulation of AOGCM results could be improved. The obtained SCM parameters depend both on the AOGCM data and the type of forcing scenario. SCMs with a poor representation of the atmosphere thermal inertia are better able to emulate AOGCM results from gradually changing forcing than from pulse forcing simulations. Correct simultaneous emulation of both atmospheric temperatures and the ocean temperature profile by the SCMs strongly depends on the representation of the temperature gradient between the atmosphere and the mixed layer. Introducing climate sensitivities that are dependent on the forcing mechanism in the SCMs allows the emulation of AOGCM responses to carbon dioxide and solar insolation forcings equally well. Also, some SCM parameters are found to be very insensitive to the fitting, and the reduction of their uncertainty through the fitting procedure is only marginal, while other parameters

  1. Using climate model output to assess the impacts of climate change on water resources

    SciTech Connect

    Cushman, R.M.

    1990-01-01

    The use of general circulation models (GCMs) to provide climate data for regional assessments of the impacts of changing climate on water resources stretches the limits of what the models were designed for. Problems that must be addressed include disagreement on a regional scale among GCMs and between the modeled and observed climate; coarse spatial resolution of the models; and simplistic representation of surface hydrology. It is important that continued progress be made in developing the methodology for using GCM output in climate-impact assessments. 18 refs.

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

    SciTech Connect

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

    1992-08-01

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

  3. A Tool for Sharing Empirical Models of Climate Impacts

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  4. Regional climate simulations over Vietnam using the WRF model

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  5. Soil Moisture Memory in Climate Models

    NASA Technical Reports Server (NTRS)

    Koster, Randal D.; Suarez, Max J.; Zukor, Dorothy J. (Technical Monitor)

    2000-01-01

    Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to (1) seasonality in the statistics of the atmospheric forcing, (2) the variation of evaporation with soil moisture, (3) the variation of runoff with soil moisture, and (4) persistence in the atmospheric forcing, as perhaps induced by land atmosphere feedback. Geographical variations in the relative strengths of these factors, which can be established through analysis of model diagnostics and which can be validated to a certain extent against observations, lead to geographical variations in simulated soil moisture memory and thus, in effect, to geographical variations in seasonal precipitation predictability associated with soil moisture. The use of the equation to characterize controls on soil moisture memory is demonstrated with data from the modeling system of the NASA Seasonal-to-Interannual Prediction Project.

  6. Mixing parametrizations for ocean climate modelling

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  7. Final Report for the portion performed in the University of Illinois on the project entitled "Optimizing the Cloud-Aerosol-Radiation Ensemble Modeling System to Improve Future Climate Change Projections at Regional to Local Scales"

    SciTech Connect

    Liang, Xin-Zhong

    2011-01-31

    This is the final report for the closure of the research tasks on the project that have performed during the entire reporting period in the University of Illinois. It contains a summary of the achievements and details of key results as well as the future plan for this project to be continued in the University of Maryland.

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

    NASA Astrophysics Data System (ADS)

    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

  9. Climate and Land Use Change Effects on Ecological Resources in Three Watersheds: A Synthesis Report (Final Report)

    EPA Science Inventory

    The purpose of this final report is to provide a summary of climate change impacts to selected watersheds and recommendations for how to improve the process of conducting watershed assessments in the future.

  10. A HYPOTHESIS-DRIVEN FRAMEWORK FOR ASSESSING CLIMATE INDUCED CHANGES IN COASTAL FINAL ECOSYSTEM GOODS AND SERVICES

    EPA Science Inventory

    Understanding how climate change will alter the availability of coastal final ecosystem goods and services (FEGS; such as food provisioning from fisheries, property protection, and recreation) has significant implications for coastal planning and the development of adaptive manag...

  11. Climate Impact of Transportation A Model Comparison

    SciTech Connect

    Girod, Bastien; Van Vuuren, Detlef; Grahn, Maria; Kitous, Alban; Kim, Son H.; Kyle, G. Page

    2013-06-01

    Transportation contributes to a significant and rising share of global energy use and GHG emissions. Therefore modeling future travel demand, its fuel use, and resulting CO2 emission is highly relevant for climate change mitigation. In this study we compare the baseline projections for global service demand (passenger-kilometers, ton-kilometers), fuel use, and CO2 emissions of five different global transport models using harmonized input assumptions on income and population. For four models we also evaluate the impact of a carbon tax. All models project a steep increase in service demand over the century. Technology is important for limiting energy consumption and CO2 emissions, but quite radical changes in the technology mix are required to stabilize or reverse the trend. While all models project liquid fossil fuels dominating up to 2050, they differ regarding the use of alternative fuels (natural gas, hydrogen, biofuels, and electricity), because of different fuel price projections. The carbon tax of US$200/tCO2 in 2050 stabilizes or reverses global emission growth in all models. Besides common findings many differences in the model assumptions and projections indicate room for improvement in modeling and empirical description of the transport system.

  12. Climate and Land Use Change Effects on Ecological Resources in Three Watersheds: A Synthesis Report (Final Report)

    EPA Science Inventory

    EPA announced the availability of the final report, Climate and Land-Use Change Effects on Ecological Resources in Three Watersheds: A Synthesis Report. This report provides a summary of climate change impacts to selected watersheds and recommendations for how to improv...

  13. The Mechanisms of Natural Variability and its Interaction with Anthropogenic Climate Change Final Report

    SciTech Connect

    Vallis, Geoffrey K.

    2015-01-30

    The project had two main components. The first concerns estimating the climate sensitivity in the presence of forcing uncertainty and natural variability. Climate sensitivity is the increase in the average surface temperature for a given increase in greenhouse gases, for example a doubling of carbon dioxide. We have provided new, probabilistic estimates of climate sensitivity using a simple climate model an the observed warming in the 20th century, in conjunction with ideas in data assimilation and parameter estimation developed in the engineering community. The estimates combine the uncertainty in the anthropogenic aerosols with the uncertainty arising because of natural variability. The second component concerns how the atmospheric circulation itself might change with anthropogenic global warming. We have shown that GCMs robustly predict an increase in the length scale of eddies, and we have also explored the dynamical mechanisms whereby there might be a shift in the latitude of the jet stream associated with anthropogenic warming. Such shifts in the jet might cause large changes in regional climate, potentially larger than the globally-averaged signal itself. We have also shown that the tropopause robustly increases in height with global warming, and that the Hadley Cell expands, and that the expansion of the Hadley Cell is correlated with the polewards movement of the mid-latitude jet.

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

    SciTech Connect

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

    2013-06-28

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

  15. The climate of the Iberian Peninsula during the last five centuries from a regional climate model perspective.

    NASA Astrophysics Data System (ADS)

    Gomez-Navarro, J. J.; Montavez, J. P.; Jerez, S.; Garcia-Valero, J. A.; Jimenez-Guerrero, P.; Zorita, E.; Gonzalez-Rouco, J. F.

    2009-09-01

    During the last years the use of paleoclimate simulations with models of different complexity has become an usual tool in paleoclimate studies. Progress in understanding climate variability leans on simulation and reconstruction efforts. Exercises blending both approaches present a great potential for answering questions relevant for both the simulation and reconstruction of past climate, and depend on the specific peculiarities of proxies and methods involved in climate reconstructions, as well as on the realism and limitations of model simulations. Most of paleoclimate integrations available in the literature covering the last millennium have been performed with relative rough resolution which does not allow to analyze regional climate features that can be of interest in the context of proxies evidence. In this work we present a new high resolution (30 km) regional climate simulation over the Iberian Peninsula of the last five. The regional simulations were performed with a climate version of the MM5 model coupled to the Noah LSM. The driving conditions used follow the Erik1 experiment, performed with the ECHO-G global circulation model. The results indicate that the seasonal modes of variation for near surface air temperature and precipitation obtained within the regional paleoclimate experiment are consistent with the obtained using the observational databases and equivalent to regional climate integrations driven by reanalysis data. On the other hand, the main modes of variation show strong signals in historical periods such as the Maunder and Dalton Minimum. Finally, some preliminary comparisons between the global and the regional model against reconstructions are also reported in this contribution.

  16. Regional forecasting with global atmospheric models; Final report

    SciTech Connect

    Crowley, T.J.; Smith, N.R.

    1994-05-01

    The purpose of the project was to conduct model simulations for past and future climate change with respect to the proposed Yucca Mtn. repository. The authors report on three main topics, one of which is boundary conditions for paleo-hindcast studies. These conditions are necessary for the conduction of three to four model simulations. The boundary conditions have been prepared for future runs. The second topic is (a) comparing the atmospheric general circulation model (GCM) with observations and other GCMs; and (b) development of a better precipitation data base for the Yucca Mtn. region for comparisons with models. These tasks have been completed. The third topic is preliminary assessments of future climate change. Energy balance model (EBM) simulations suggest that the greenhouse effect will likely dominate climate change at Yucca Mtn. for the next 10,000 years. The EBM study should improve rational choice of GCM CO{sub 2} scenarios for future climate change.

  17. Conceptual Model of Climate Change Impacts at LANL

    SciTech Connect

    Dewart, Jean Marie

    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/).

  18. Nitrogen Controls on Climate Model Evapotranspiration.

    NASA Astrophysics Data System (ADS)

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

    2002-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  20. Aerosol Properties and Processes: A Path from Field and Laboratory Measurements to Global Climate Models

    SciTech Connect

    Ghan, Steven J.; Schwartz, Stephen E.

    2007-07-01

    Aerosols exert a substantial influence on climate and climate change through a variety of complex mechanisms. Consequently there is a need to represent aerosol effects in global climate models, and models have begun to include representations of these effects. However, the treatment of aerosols in current global climate models is presently highly simplified, omitting many important processes and feedbacks. Consequently there is need for substantial improvement. Here we describe the U. S. Department of Energy strategy for improving the treatment of aerosol properties and processes in global climate models. The strategy begins with a foundation of field and laboratory measurements that provide the basis for modules of selected aerosol properties and processes. These modules are then integrated in regional aerosol models, which are evaluated by comparing with field measurements. Issues of scale are then addressed so that the modules can be applied to global aerosol models, which are evaluated by comparing with global satellite measurements. Finally, the validated set of modules are applied to global climate models for multi-century simulations. This strategy can be applied to successive generations of global climate models.

  1. Climate Modeling: Ocean Cavities below Ice Shelves

    SciTech Connect

    Petersen, Mark Roger

    2016-09-12

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

  2. Grassland/atmosphere response to changing climate: Coupling regional and local scales. Final report

    SciTech Connect

    Coughenour, M.B.; Kittel, T.G.F.; Pielke, R.A.; Eastman, J.

    1993-10-01

    The objectives of the study were: to evaluate the response of grassland ecosystems to atmospheric change at regional and site scales, and to develop multiscaled modeling systems to relate ecological and atmospheric models with different spatial and temporal resolutions. A menu-driven shell was developed to facilitate use of models at different temporal scales and to facilitate exchange information between models at different temporal scales. A detailed ecosystem model predicted that C{sub 3} temperate grasslands wig respond more strongly to elevated CO{sub 2} than temperate C{sub 4} grasslands in the short-term while a large positive N-PP response was predicted for a C{sub 4} Kenyan grassland. Long-term climate change scenarios produced either decreases or increases in Colorado plant productivity (NPP) depending on rainfall, but uniform increases in N-PP were predicted in Kenya. Elevated CO{sub 2} is likely to have little effect on ecosystem carbon storage in Colorado while it will increase carbon storage in Kenya. A synoptic climate classification processor (SCP) was developed to evaluate results of GCM climate sensitivity experiments. Roughly 80% agreement was achieved with manual classifications. Comparison of lx and 2xCO{sub 2} GCM Simulations revealed relatively small differences.

  3. Coupled Climate Model Appraisal a Benchmark for Future Studies

    SciTech Connect

    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 discussed here.

  4. Weakening of atmospheric information flow in a warming climate in the Community Climate System Model

    NASA Astrophysics Data System (ADS)

    Deng, Yi; Ebert-Uphoff, Imme

    2014-01-01

    We introduce a new perspective of climate change by revealing the changing characteristics of atmospheric information flow in a warming climate. The key idea is to interpret large-scale atmospheric dynamical processes as information flow around the globe and to identify the pathways of this information flow using a climate network based on causal discovery and graphical models. We construct such networks using the daily geopotential height data from the Community Climate System Model Version 4.0 (CCSM4.0)'s 20th century climate simulation and 21st century climate projection. We show that in the CCSM4.0 model under enhanced greenhouse gases (GHGs) forcing, prominent midlatitude information pathways in the midtroposphere weaken and shift poleward, while major tropical information pathways start diminishing. Averaged over the entire Northern Hemisphere, the atmospheric information flow weakens. The implications of this weakening for the interconnectivity among different geographical locations and for the intrinsic predictability of the atmosphere are discussed.

  5. A transient stochastic weather generator incorporating climate model uncertainty

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Technical Reports Server (NTRS)

    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.

  7. Hybrid Surface Mesh Adaptation for Climate Modeling

    SciTech Connect

    Ahmed Khamayseh; Valmor de Almeida; Glen Hansen

    2008-10-01

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

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

    SciTech Connect

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

    1991-10-01

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

  9. Evaluation of Northern Hemisphere natural climate variability in multiple temperature reconstructions and global climate model simulations

    NASA Astrophysics Data System (ADS)

    Bell, J. L.; Sloan, L. C.; Revenaugh, J.; Duffy, P. B.

    2003-06-01

    The detection of anthropogenic climate change in observations and the validation of climate models both rely on understanding natural climate variability. To evaluate internal climate variability, we apply spectral analysis to time series of surface air temperature (SAT) from nine coupled general circulation model (GCM) simulations, three recent global paleotemperature reconstructions, and Northern Hemisphere (NH) instrumental records. Our comparison is focused on the NH due to the greater spatial and temporal coverage and validation of the available NH temperature reconstructions. The paleotemperature reconstructions capture the general magnitude of NH climate variability, but not the precise variance and specific spatial, temporal, or periodic signals demonstrated in the instrumental record. The models achieved varying degrees of success for each measure of variability analyzed, with none of the models consistently capturing the appropriate variability. In general, the models performed best in the analysis of combined mean annual land and marine variability.

  10. Climates as commodities: Jean Pierre Purry and the modelling of the best climate on Earth

    NASA Astrophysics Data System (ADS)

    Jankovic, Vladimir

    The paper looks at how an early eighteenth-century climatological model of the 'best climate' on Earth became a platform for political, economic, and demographic action of extraordinary significance for the colonization of new commodity environments. It analyzes the science used by an early modern business adventurer to model 'climate' as an economic tool informing imperial governance and exploitation of local resources. Jean Pierre Purry's construction of 'model climate' portrayed North Carolina's township at Yamassee River as an ideal environment geared toward mercantilist principles of trade but also as a model community based on skilled labor and optimal climatic capital. His climatological analysis was a purposeful act of policy making based on a science of colonial expansion similar to more recent calls at economic modelling of future climate impact.

  11. Assessing Statistical Model Assumptions under Climate Change

    NASA Astrophysics Data System (ADS)

    Varotsos, Konstantinos V.; Giannakopoulos, Christos; Tombrou, Maria

    2016-04-01

    The majority of the studies assesses climate change impacts on air-quality using chemical transport models coupled to climate ones in an off-line mode, for various horizontal resolutions and different present and future time slices. A complementary approach is based on present-day empirical relations between air-pollutants and various meteorological variables which are then extrapolated to the future. However, the extrapolation relies on various assumptions such as that these relationships will retain their main characteristics in the future. In this study we focus on the ozone-temperature relationship. It is well known that among a number of meteorological variables, temperature is found to exhibit the highest correlation with ozone concentrations. This has led, in the past years, to the development and application of statistical models with which the potential impact of increasing future temperatures on various ozone statistical targets was examined. To examine whether the ozone-temperature relationship retains its main characteristics under warmer temperatures we analyze the relationship during the heatwaves events of 2003 and 2006 in Europe. More specifically, we use available gridded daily maximum temperatures (E-OBS) and hourly ozone observations from different non-urban stations (EMEP) within the areas that were impacted from the two heatwave events. In addition, we compare the temperature distributions of the two events with temperatures from two different future time periods 2021-2050 and 2071-2100 from a number of regional climate models developed under the framework of the Cordex initiative (http://www.cordex.org) with a horizontal resolution of 12 x 12km, based on different IPCC RCPs emissions scenarios. A statistical analysis is performed on the ozone-temperature relationship for each station and for the two aforementioned years which are then compared against the ozone-temperature relationships obtained from the rest of the available dataseries. The

  12. Climate Model Diagnostic Analyzer Web Service System

    NASA Astrophysics Data System (ADS)

    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

  13. Potato model uncertainty across common datasets and varying climate

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. An Earth longwave radiation climate model

    NASA Technical Reports Server (NTRS)

    Yang, S. K.

    1984-01-01

    An Earth outgoing longwave radiation (OLWR) climate model was constructed for radiation budget study. Required information is provided by on empirical 100mb water vapor mixing ratio equation of the mixing ratio interpolation scheme. Cloud top temperature is adjusted so that the calculation would agree with NOAA scanning radiometer measurements. Both clear sky and cloudy sky cases are calculated and discussed for global average, zonal average and world-wide distributed cases. The results agree well with the satellite observations. The clear sky case shows that the OLWR field is highly modulated by water vapor, especially in the tropics. The strongest longitudinal variation occurs in the tropics. This variation can be mostly explained by the strong water vapor gradient. Although in the zonal average case the tropics have a minimum in OLWR, the minimum is essentially contributed by a few very low flux regions, such as the Amazon, Indonesian and the Congo.

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

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Astrophysics Data System (ADS)

    Steffens, K.; Larsbo, M.; Moeys, J.; Kjellström, E.; Jarvis, N.; Lewan, E.

    2014-02-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Steffens, K.; Larsbo, M.; Moeys, J.; Kjellström, E.; Jarvis, N.; Lewan, E.

    2013-08-01

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

  18. Integrating chemistry into 3D climate models: Detailed kinetics in the troposphere and stratosphere of a global climate model

    SciTech Connect

    Kao, C.Y.J.; Elliott, S.; Turco, R.P.; Zhao, X.

    1997-11-01

    This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). The motivation for the project is to create the first complete, three-dimensional climate model that enfolds atmospheric photochemistry. The LANL chemical global climate model (GCM) not only distributes the trace greenhouse gases and modifies their concentrations within the detailed photochemical web, but also permits them to influence the radiation field and so force their own transport. Both atmospheric chemistry and fluid dynamics are nonlinear and zonally asymmetric phenomena. They can only be adequately modeled in three dimensions on the global grid. The kinetics-augmented GCM is the only program within the atmospheric community capable of investigating interaction involving chemistry and transport. The authors have conducted case studies of timely three-dimensional chemistry issues. Examples include ozone production from biomass burning plumes, kinetic feedbacks in zonally asymmetric transport phenomena with month- to year-long time scales, and volcano sulfate aerosols with respect to their potential effects on tropospheric ozone depletion.

  19. Modeling of GE Appliances: Final Presentation

    SciTech Connect

    Fuller, Jason C.; Vyakaranam, Bharat; Leistritz, Sean M.; Parker, Graham B.

    2013-01-31

    This report is the final in a series of three reports funded by U.S. Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE) in collaboration with GE Appliances’ through a Cooperative Research and Development Agreement (CRADA) to describe the potential of GE Appliances’ DR-enabled appliances to provide benefits to the utility grid.

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

    PubMed

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

    2012-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Gordova, Yulia; Martynova, Yulia; Shulgina, Tamara

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  3. Climate Modeling with a Million CPUs

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

    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

  6. The Community Climate System Model Version 4

    SciTech Connect

    Gent, Peter R.; Danabasoglu, Gokhan; Donner, Leo J.; Holland, Marika M.; Hunke, Elizabeth C.; Jayne, Steve R.; Lawrence, David M.; Neale, Richard; Rasch, Philip J.; Vertenstein, Mariana; Worley, Patrick; Yang, Zong-Liang; Zhang, Minghua

    2011-10-01

    The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all the CCSM components, and documents fully coupled pre-industrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1{sup o} results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4{sup o} resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in the CCSM4 producing El Nino/Southern Oscillation variability with a much more realistic frequency distribution than the CCSM3, although the amplitude is too large compared to observations. They also improve the representation of the Madden-Julian Oscillation, and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the deep ocean density structure, especially in the North Atlantic. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than the CCSM3, and the Arctic sea ice concentration is improved in the CCSM4. An ensemble of 20th century simulations runs produce an excellent match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally-averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4 C. This is consistent with the fact that the CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of short-wave and long-wave cloud forcings.

  7. Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

    NASA Technical Reports Server (NTRS)

    Thiele, O. (Editor); Schiffer, R. A. (Editor)

    1985-01-01

    The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

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

    PubMed

    Lawing, A Michelle; Polly, P David

    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 synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models), phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species), and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr) than it has been on average for the past 320 ky (2.3 m/yr).

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

    PubMed Central

    Lawing, A. Michelle; Polly, P. David

    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 synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models), phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species), and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr) than it has been on average for the past 320 ky (2.3 m/yr). PMID:22164305

  10. THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE

    PubMed Central

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

    EPA Science Inventory

    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...

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  13. Final Project Report Load Modeling Transmission Research

    SciTech Connect

    Lesieutre, Bernard; Bravo, Richard; Yinger, Robert; Chassin, Dave; Huang, Henry; Lu, Ning; Hiskens, Ian; Venkataramanan, Giri

    2012-03-31

    The research presented in this report primarily focuses on improving power system load models to better represent their impact on system behavior. The previous standard load model fails to capture the delayed voltage recovery events that are observed in the Southwest and elsewhere. These events are attributed to stalled air conditioner units after a fault. To gain a better understanding of their role in these events and to guide modeling efforts, typical air conditioner units were testing in laboratories. Using data obtained from these extensive tests, new load models were developed to match air conditioner behavior. An air conditioner model is incorporated in the new WECC composite load model. These models are used in dynamic studies of the West and can impact power transfer limits for California. Unit-level and systemlevel solutions are proposed as potential solutions to the delayed voltage recovery problem.

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

    SciTech Connect

    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.

  15. Response of plants and ecosystems to CO{sub 2} and climate change. Final technical report

    SciTech Connect

    Reynolds, J.F.

    1993-12-31

    In recognition of the important role of vegetation in the bio-geosphere carbon cycle, the Carbon Dioxide Research Program of the US Department of Energy established the research program: Direct Effects of increasing Carbon Dioxide on Vegetation. The ultimate goal is to develop a general ecosystem model to investigate, via hypothesis testing, the potential responses of different terrestrial ecosystems to changes in the global environment over the next century. The approach involves the parallel development of models at several hierarchical levels, from the leaf to the ecosystem. At the plant level, mechanism and the direct effects of CO{sub 2} in the development of a general plant growth model, GEPSI - GEneral Plant SImulator has been stressed. At the ecosystem level, we have stressed the translation Of CO{sub 2} effects and other aspects of climate change throughout the ecosystem, including feedbacks and constraints to system response, in the development of a mechanistic, general ecosystem model SERECO - Simulation of Ecosystem Response to Elevated CO{sub 2} and Climate Change has been stressed.

  16. A Model Based Mars Climate Database for the Mission Design

    NASA Technical Reports Server (NTRS)

    2005-01-01

    A viewgraph presentation on a model based climate database is shown. The topics include: 1) Why a model based climate database?; 2) Mars Climate Database v3.1 Who uses it ? (approx. 60 users!); 3) The new Mars Climate database MCD v4.0; 4) MCD v4.0: what's new ? 5) Simulation of Water ice clouds; 6) Simulation of Water ice cycle; 7) A new tool for surface pressure prediction; 8) Acces to the database MCD 4.0; 9) How to access the database; and 10) New web access

  17. Adapting the GISS Climate GCM to Model Extra-Solar Climate Regimes

    NASA Astrophysics Data System (ADS)

    Lacis, A. A.

    2013-12-01

    Hundreds of extra-solar planets have been discovered by NASA's Kepler mission, some potentially habitable, most exhibiting extremes in climate beyond current modeling experience. Zero-order assessment of the stellar type and the planet's distance from the star serves to identify the ballpark of whether silicon dioxide is likely to be in gaseous or liquid phase in the planet's atmosphere, or a part of the solid planetary ground surface. A lot of first-order modeling would involve assessing the chemical limitations to establish the likely chemical composition of the planetary atmosphere. For a more detailed analysis of the prevailing climate on an extra-solar planet a 3-D global climate model would be required. We begin the Extra-Solar Climate Model development by starting the with GISS Climate GCM by having key model parameters be expressed in physics based terms rather than Earth specific parameters. Examples of such key parameters are: the Planet's mass and radius, mass and composition of the atmosphere, Star-Planet distance, rotation rate and orbital parameters, stellar spectral distribution, land topography, and land-ocean distribution. These are parameters that are more or less straight forward to redefine for extra-solar conditions that are not greatly different for what may be considered as the ';habitable' zone. We present extreme climate simulations ranging from snowball Earth conditions to near-runaway greenhouse conditions. The objective of this modeling study is the development of a more physically based climate model that will be adaptable for assessing habitable climate regimes on newly discovered extra-solar planets, and will also facilitate the study terrestrial climate system analysis in paleoclimate applications.

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

    SciTech Connect

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

    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.

  19. Statistical modeling of electrical components: Final report

    SciTech Connect

    Jolly, R.L.

    1988-07-01

    A method of forecasting production yields based on SPICE (University of California at Berkeley) circuit simulation and Monte Carlo techniques was evaluated. This method involved calculating functionally accurate component models using statistical techniques and using these component models in a SPICE electrical circuit simulation program. The results of the simulation program allow production yields to be calculated using standard statistical techniques.

  20. An overview of decadal climate predictability in a multi-model ensemble by climate model MIROC

    NASA Astrophysics Data System (ADS)

    Chikamoto, Yoshimitsu; Kimoto, Masahide; Ishii, Masayoshi; Mochizuki, Takashi; Sakamoto, Takashi T.; Tatebe, Hiroaki; Komuro, Yoshiki; Watanabe, Masahiro; Nozawa, Toru; Shiogama, Hideo; Mori, Masato; Yasunaka, Sayaka; Imada, Yukiko

    2013-03-01

    Decadal climate predictability is examined in hindcast experiments by a multi-model ensemble using three versions of the coupled atmosphere-ocean model MIROC. In these hindcast experiments, initial conditions are obtained from an anomaly assimilation procedure using the observed oceanic temperature and salinity with prescribed natural and anthropogenic forcings on the basis of the historical data and future emission scenarios in the Intergovernmental Panel of Climate Change. Results of the multi-model ensemble in our hindcast experiments show that predictability of surface air temperature (SAT) anomalies on decadal timescales mostly originates from externally forced variability. Although the predictable component of internally generated variability has considerably smaller SAT variance than that of externally forced variability, ocean subsurface temperature variability has predictive skills over almost a decade, particularly in the North Pacific and the North Atlantic where dominant signals associated with Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO) are observed. Initialization enhances the predictive skills of AMO and PDO indices and slightly improves those of global mean temperature anomalies. Improvement of these predictive skills in the multi-model ensemble is higher than that in a single-model ensemble.

  1. Chesapeake Bay sediment flux model. Final report

    SciTech Connect

    Di Toro, D.M.; Fitzpatrick, J.J.

    1993-06-01

    Formulation and application of a predictive diagenetic sediment model are described in this report. The model considers two benthic sediment layers: a thin aerobic layer in contact with the water column and a thicker anaerobic layer. Processes represented include diagenesis, diffusion, particle mixing, and burial. Deposition of organic matter, water column concentrations, and temperature are treated as independent variables that influence sediment-water fluxes. Sediment oxygen demand and sediment-water fluxes of sulfide, ammonium, nitrate, phosphate, and silica are predicted. The model was calibrated using sediment-water flux observations collected in Chesapeake Bay 1985-1988. When independent variables were specified based on observations, the model correctly represented the time series of sediment-water fluxes observed at eight stations in the Bay and tributaries.... Chesapeake Bay, Models, Sediments, Dissolved oxygen, Nitrogen Eutrophication, Phosphorus.

  2. SEISMIC MODELING ENGINES PHASE 1 FINAL REPORT

    SciTech Connect

    BRUCE P. MARION

    2006-02-09

    Seismic modeling is a core component of petroleum exploration and production today. Potential applications include modeling the influence of dip on anisotropic migration; source/receiver placement in deviated-well three-dimensional surveys for vertical seismic profiling (VSP); and the generation of realistic data sets for testing contractor-supplied migration algorithms or for interpreting AVO (amplitude variation with offset) responses. This project was designed to extend the use of a finite-difference modeling package, developed at Lawrence Berkeley Laboratories, to the advanced applications needed by industry. The approach included a realistic, easy-to-use 2-D modeling package for the desktop of the practicing geophysicist. The feasibility of providing a wide-ranging set of seismic modeling engines was fully demonstrated in Phase I. The technical focus was on adding variable gridding in both the horizontal and vertical directions, incorporating attenuation, improving absorbing boundary conditions and adding the optional coefficient finite difference methods.

  3. Evaluation of climate models in terms of relationship between cloud fraction and cloud albedo

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Song, H.; Lin, W.; Wu, W.; Jensen, M. P.; Toto, T.

    2011-12-01

    Cloud fraction and cloud albedo have been investigated extensively but often separately in studying cloud-climate interaction; their quantitative relationship has been much less studied and understood, in both observations and climate models. In this study, we first examine this crucial relationship by empirical analysis of observational data, both surface-based and satellite measurements. We then decipher the key variables/processes that determine the relationship using designed simulations of the single-column model of the NCAR CAM (SCAM). Finally we explore how well or poor this relationship is simulated in the AR4 climate simulations. The preliminary results indicate that all the AR4 models as a group produce a cloud fraction-albedo relationship that is literally opposite to that observed. This stark contrast between model and observational results calls for new strategies and approaches in future development of cloud parameterizations and application of observations as model constraints.

  4. Modeling deoxynivalenol contamination of wheat in northwestern Europe for climate change assessments.

    PubMed

    van der Fels-Klerx, H J; Goedhart, P W; Elen, O; Börjesson, T; Hietaniemi, V; Booij, C J H

    2012-06-01

    Climate change will affect mycotoxin contamination of feed and food. Mathematical models for predicting mycotoxin concentrations in cereal grains are useful for estimating the impact of climate change on these toxins. The objective of the current study was to construct a descriptive model to estimate climate change impacts on deoxynivalenol (DON) contamination of mature wheat grown in northwestern Europe. Observational data from 717 wheat fields in Norway, Sweden, Finland, and The Netherlands were analyzed, including the DON concentrations in mature wheat, agronomical practices, and local weather. Multiple regression analyses were conducted, and the best set of explanatory variables, mainly including weather factors, was selected. The final model included the following variables: flowering date, length of time between flowering and harvest, wheat resistance to Fusarium infection, and several climatic variables related to relative humidity, temperature, and rainfall during critical stages of wheat cultivation. The model accounted for 50 % of the variance, which was sufficient to make this model useful for estimating the trends of climate change on DON contamination of wheat in northwestern Europe. Application of the model in possible climate change scenarios is illustrated.

  5. Modeling High-Impact Weather and Climate: Lessons From a Tropical Cyclone Perspective

    SciTech Connect

    Done, James; Holland, Greg; Bruyere, Cindy; Leung, Lai-Yung R.; Suzuki-Parker, Asuka

    2012-06-01

    Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding of the underlying physical processes. This challenge is driving fresh approaches to assess high-impact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias in the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be guided by the need to: include relevant regional climate physical processes; resolve key impact parameters; and to accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters. Finally, through the example of a tropical cyclone damage index, direct impact assessments are presented as powerful tools that distill complex datasets into concise statements on likely impact, and as highly effective communication devices. Capsule: "Combining dynamical modeling of high-impact weather using traditional regional climate models with statistical techniques allows for comprehensive sampling of the full distribution, uncertainty estimation, direct assessment of impacts, and increased confidence in future changes."

  6. Production and use of regional climate model projections - A Swedish perspective on building climate services.

    PubMed

    Kjellström, Erik; Bärring, Lars; Nikulin, Grigory; Nilsson, Carin; Persson, Gunn; Strandberg, Gustav

    2016-09-01

    We describe the process of building a climate service centred on regional climate model results from the Rossby Centre regional climate model RCA4. The climate service has as its central facility a web service provided by the Swedish Meteorological and Hydrological Institute where users can get an idea of various aspects of climate change from a suite of maps, diagrams, explaining texts and user guides. Here we present the contents of the web service and how this has been designed and developed in collaboration with users of the service in a dialogue reaching over more than a decade. We also present the ensemble of climate projections with RCA4 that provides the fundamental climate information presented at the web service. In this context, RCA4 has been used to downscale nine different coupled atmosphere-ocean general circulation models (AOGCMs) from the 5th Coupled Model Intercomparison Project (CMIP5) to 0.44° (c. 50 km) horizontal resolution over Europe. Further, we investigate how this ensemble relates to the CMIP5 ensemble. We find that the iterative approach involving the users of the climate service has been successful as the service is widely used and is an important source of information for work on climate adaptation in Sweden. The RCA4 ensemble samples a large degree of the spread in the CMIP5 ensemble implying that it can be used to illustrate uncertainties and robustness in future climate change in Sweden. The results also show that RCA4 changes results compared to the underlying AOGCMs, sometimes in a systematic way.

  7. Crop phenology feedback on climate over central US in a regional climate model

    NASA Astrophysics Data System (ADS)

    Pan, Z.; Takle, E.; Xue, L.; Segal, M.

    2004-12-01

    The moisture and CO2 fluxes over cropland represent local climate forcing and an important component of atmospheric energy and CO2 budgets. Since observed fluxes, especially for CO2, are rarely available over extensive areas the fluxes are mainly estimated by climate models. The carbon sequestration and water consumption by crops are only crudely represented in the models. For example, most climate models use climatological or static crop growth and development that do not change from year to year, indistinguishable between flood and drought years. To improve the moisture and CO2 fluxes (i.e., photosynthesis) from crops we coupled crop models (CERES for corn and CropGro for soybean) with the regional model (MM5) along with the land surface model (LSM). This crop-climate coupled model with interactive crop phenology can simulate interannual variations in CO2 and water fluxes from the surface. The coupled model was used to simulate CO2 and moisture fluxes in the past couple of growing seasons in the central U.S. Results were compared with available CO2 flux observations at some AmeriFlux sites. It is found that the coupled model gives more realistic seasonal accumulation of CO2 fluxes and that the dynamic crop development in the coupled model has a strong feedback on regional precipitation. The typical climate models using static crop phenology significantly overestimate CO2 fluxes during early growing season because of positive biases in specifying leaf area index.

  8. Landscape-scale modelling of soil carbon dynamics under land use and climate change

    NASA Astrophysics Data System (ADS)

    Lacoste, Marine; Viaud, Valérie; Michot, Didier; Christian, Walter

    2013-04-01

    Soil organic carbon (SOC) sequestration is highly linked to soil use and farming practices, but also to soil redistributions, soil properties, and climate. In a global change context, landscape, farming practice and climate changes are expected; and they will most probably impact SOC dynamics. To assess their respective impacts, we modelled the SOC contents and stocks evolution at the scale of an agricultural landscape, by taking into account the soil redistribution by tillage and water processes. The simulations were conducted from 2010 to 2100 under different scenarios of landscape and climate. These scenarios combined different land uses associated to specific farming practices (mixed dairy with rotations of crops and grasslands, intensive cropping with only crops rotations or permanent grasslands), landscape managements (hedges planting or removal), and climates (business-as-usual climate and climate change, with temperature and precipitations increase). We used a spatially SOC dynamic model (adapted from RothC), coupled to a soil redistribution model (LandSoil). SOC dynamics were spatially modelled with a lateral resolution of 2-m and for soil organic layers up to 105 cm. Initial SOC stocks were described with a 2-m resolution map based on field data and produced with digital soil mapping methods. The major factor of change in SOC stocks was land use change, the second factor of importance was climate change, and finally landscape management: for the total SOC stocks (0-to-105 cm soil layer) the change of land use, climate and landscape management induced a respective mean absolute variation of 10 to 20 tC ha-1, 9 tC ha-1 and 0.4 tC ha-1. When considering the 0-to-105 cm soil layer, the different modelled landscapes showed the same sensitivity to climate change, with induced a mean decrease of 10 tC ha-1. However, the impact of climate change was found different according to the different modelled landscape when considering the 0-to-7.5 and 0-to-30 cm soil

  9. Climate model studies of synchronously rotating planets.

    PubMed

    Joshi, Manoj

    2003-01-01

    M stars constitute 75% of main sequence stars though, until recently, their star systems have not been considered suitable places for habitable planets to exist. In this study the climate of a synchronously rotating planet around an M dwarf star is evaluated using a three-dimensional global atmospheric circulation model. The presence of clouds and evaporative cooling at the surface of the planet result in a cooler surface temperature at the subsolar point. Water ice forms at the polar regions and on the dark side, where the minimum temperature lies between -30 degrees C and 0 degrees C. As expected, rainfall is extremely high on the starlit side and extremely low on the dark side. The presence of a dry continent causes higher temperatures on the dayside, and allows accumulation of snow on the nightside. The absence of any oceans leads to higher day-night temperature differences, consistent with previous work. The present study reinforces recent conclusions that synchronously rotating planets within the circumstellar habitable zones of M dwarf stars should be habitable, and therefore M dwarf systems should not be excluded in future searches for exoplanets.

  10. Extracting climate memory using Fractional Integrated Statistical Model: A new perspective on climate prediction

    PubMed Central

    Yuan, Naiming; Fu, Zuntao; Liu, Shida

    2014-01-01

    Long term memory (LTM) in climate variability is studied by means of fractional integral techniques. By using a recently developed model, Fractional Integral Statistical Model (FISM), we in this report proposed a new method, with which one can estimate the long-lasting influences of historical climate states on the present time quantitatively, and further extract the influence as climate memory signals. To show the usability of this method, two examples, the Northern Hemisphere monthly Temperature Anomalies (NHTA) and the Pacific Decadal Oscillation index (PDO), are analyzed in this study. We find the climate memory signals indeed can be extracted and the whole variations can be further decomposed into two parts: the cumulative climate memory (CCM) and the weather-scale excitation (WSE). The stronger LTM is, the larger proportion the climate memory signals will account for in the whole variations. With the climate memory signals extracted, one can at least determine on what basis the considered time series will continue to change. Therefore, this report provides a new perspective on climate prediction. PMID:25300777

  11. Modeling Climate Impacts on Agriculture in South East South America

    NASA Astrophysics Data System (ADS)

    Ines, A. M.; Baethgen, W.; Greene, A. M.; Goddard, L. M.

    2013-12-01

    In the past two decades, a rapid expansion of croplands in South East South America is observed. This drastic change in landuse is seen to be due to two major factors - climate and economics. Converting marginal lands into agricultural lands is possible due to the increase in annual precipitation in the region and the increasing prices of soybeans and higher demands for grain crops have played a key role to this expansion. But the question is, how sustainable is the current trend in the future? A modeling study is conducted to evaluate the impacts of climate on agriculture in the Southern Cone of South America. We examine the impacts of climate variability and current climate change to crop yields using crop simulation models. Using the results of our current climate analysis as a baseline, we evaluate the impacts of future climate change in the next 10-30 years. Climate projections include scenarios considering only global warming, ozone and both impacting the near-term climate of the future in the region and considering decadal variability. We aim to evaluate the vulnerability of the current system to climate change. This paper will present the results of our modeling study.

  12. Comparison of climate model simulated and observed borehole temperature profiles

    NASA Astrophysics Data System (ADS)

    Gonzalez-Rouco, J. F.; Stevens, M. B.; Beltrami, H.; Goosse, H.; Rath, V.; Zorita, E.; Smerdon, J.

    2009-04-01

    Advances in understanding climate variability through the last millennium lean on simulation and reconstruction efforts. Progress in the integration of both approaches can potentially provide new means of assessing confidence on model projections of future climate change, of constraining the range of climate sensitivity and/or attributing past changes found in proxy evidence to external forcing. This work addresses specifically possible strategies for comparison of paleoclimate model simulations and the information recorded in borehole temperature profiles (BTPs). First efforts have allowed to design means of comparison of model simulated and observed BTPs in the context of the climate of the last millennium. This can be done by diffusing the simulated temperatures into the ground in order to produce synthetic BTPs that can be in turn assigned to collocated, real BTPs. Results suggest that there is sensitivity of borehole temperatures at large and regional scales to changes in external forcing over the last centuries. The comparison between borehole climate reconstructions and model simulations may also be subjected to non negligible uncertainties produced by the influence of past glacial and Holocene changes. While the thermal climate influence of the last deglaciation can be found well below 1000 m depth, such type of changes can potentially exert an influence on our understanding of subsurface climate in the top ca. 500 m. This issue is illustrated in control and externally forced climate simulations of the last millennium with the ECHO-G and LOVECLIM models, respectively.

  13. The Urgent Need for Improved Climate Models and Predictions

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

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

  15. New Study For Climate Modeling, Analyses, and Scenarios

    NASA Astrophysics Data System (ADS)

    Lowe, Jason A.; Hewitt, Chris D.; van Vuuren, Detlef P.; Johns, Tim C.; Stehfest, Elke; Royer, Jean-François; van der Linden, Paul J.

    2009-05-01

    The European Commission is funding the ENSEMBLES project, which aims to provide policy makers with information from the latest climate modeling, analyses, and scenarios. Currently, the most comprehensive estimates of climate change are made using general circulation models (GCMs) and Earth system models, but these have been used mostly to simulate futures that do not factor in climate mitigation policy. The results of these simulations typically show global average warming greatly exceeding the European Union (EU) climate policy target of 2°C above preindustrial levels, with associated large impacts on human and natural systems. To date, simple climate models typically have been used to assess the emissions trajectories that are required for meeting this target. The ENSEMBLES project is the first international multiclimate model intercomparison using a politically relevant aggressive mitigation scenario, referred to as E1 (Figures 1a and 1b). This scenario leads to a peak in the carbon dioxide (CO2) equivalent concentration in the atmosphere at around 535 parts per million (ppm) in 2045 before eventually stabilizing at around 450 ppm during the 22nd century. The climate models used are generally improved or extended versions of models contributing to the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report.

  16. Modeling of CWM droplet combustion. Final report

    SciTech Connect

    Pandalai, K.; Aggarwal, S.; Sirignano, W.

    1983-10-01

    The objective of the present study was to develop a one-dimensional, unsteady state model for coal-water mixture droplet combustion, and to compare the characteristic times for the various processes, such as water vaporization, devolatilization and char oxidation with available experimental data. A water film surrounding a spherical coal particle is considered to undergo vaporization by heat transfer from the hot air. After the water vaporization is complete, devolatilization begins. This process is assumed to be kinetically controlled. Water vaporization and devolatilization processes are modeled by using a hybrid Eulerian-Lagrangian method to obtain the properties of the gas-phase and the condensed-phase. An explicit finite difference scheme is used to solve the Eulerian gas-phase equation where as a Runga-Kutta scheme is employed to solve the Lagrangian condensed-phase equations. The predicted characteristic times for water vaporization is in good agreement with values proposed in the literature. At the present time there is insufficient data to draw any conclusions on the model. Methods are proposed to refine the simple kinetic model which takes into account pore diffusion and mass transfer for devolatilization and char oxidation. 9 references, 12 figures.

  17. Evaluation Model for Career Programs. Final Report.

    ERIC Educational Resources Information Center

    Byerly, Richard L.; And Others

    A study was conducted to provide and test an evaluative model that could be utilized in providing curricular evaluation of the various career programs. Two career fields, dental assistant and auto mechanic, were chosen for study. A questionnaire based upon the actual job performance was completed by six groups connected with the auto mechanics and…

  18. An introduction to three-dimensional climate modeling

    NASA Technical Reports Server (NTRS)

    Washington, W. M.; Parkinson, C. L.

    1986-01-01

    The development and use of three-dimensional computer models of the earth's climate are discussed. The processes and interactions of the atmosphere, oceans, and sea ice are examined. The basic theory of climate simulation which includes the fundamental equations, models, and numerical techniques for simulating the atmosphere, oceans, and sea ice is described. Simulated wind, temperature, precipitation, ocean current, and sea ice distribution data are presented and compared to observational data. The responses of the climate to various environmental changes, such as variations in solar output or increases in atmospheric carbon dioxide, are modeled. Future developments in climate modeling are considered. Information is also provided on the derivation of the energy equation, the finite difference barotropic forecast model, the spectral transform technique, and the finite difference shallow water waved equation model.

  19. Cloud optical thickness feedbacks on climate: evidence from satellite remote sensing. Final report

    SciTech Connect

    Somerville, R.C.J.; Chertock, B.

    1986-05-01

    Satellite data from the Earth Radiation Budget (ERB) experiment aboard Nimbus-7 have been used to seek evidence for cloud-radiation climate feedback mechanisms. One such feedback is microphysical, involving changes in cloud optical thickness. Theoretical results indicate that an increase in temperature, such as might occur in response to an increase in atmospheric CO/sub 2/ concentration, may be accompanied by an increase in the albedo of low and middle clouds. This temperature dependence of albedo arises from changes in cloud liquid water content and is potentially strong enough to reduce the CO/sub 2/-induced climate warming substantially. Preliminary analyses of the Nimbus-7 satellite data show some systematic dependence of cloud radiative properties on sea surface temperature, in a test region north of Hawaii. This evidence is consistent with the proposed cloud optical thickness feedback, but it is far from conclusive. To further explore such feedbacks, research should be carried out to improve and generalize the original theoretical model by adding non-black cirrus, upgrading the radiative transfer and moist convection algorithms, improving cloud microphysics, and incorporating seasonal variability and additional feedback physics. It is also feasible to seek evidence for validating hypothesized cloud feedback processes in atmospheric general circulation model integration and diagnostic studies and also in more extensive analyses of regional and seasonal variability of satellite observations of cloud properties.

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

    NASA Astrophysics Data System (ADS)

    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

  1. The potential effects of climate change on the native vascular flora of North America. A preliminary climate envelopes analysis: Final report

    SciTech Connect

    Morse, L.E.; Kutner, L.S.; Maddox, G.D.; Honey, L.L.; Thurman, C.M.; Kartesz, J.T.; Chaplin, S.J.

    1993-11-01

    To assess the potential effects of global warming on the North American flora, the reported geographical distributions of the 15,148 native North American vascular plant species were matched with climate data for 194 geographical areas to estimate the current ``climate envelope`` for each species. Three methods of analysis were used to construct these envelopes, all based on the limits of mean annual temperatures currently experienced by each species within its present range. Published models of future climates predict a possible increase in mean annual temperatures of 3{degree}C (5.4{degree}F) within the next century. Assuming that species might be eliminated from areas outside their present climate envelope, then about 7% to 11% of North America`s native plant species would be entirely out of their envelopes in a +3{degree}C climate. Rare species would be disproportionately affected -- between 10% and 18% of these species would be entirely out of their climate envelopes. However, some rare species may be able to persist at their present sites due to the availability of suitable microhabitats or genetic variation in climate tolerances. Of the more common species, only about 1% to 2% would be vulnerable in a +3{degree}C climate. The local effects of climate change on plant species would vary considerably if species withdraw from the southern or low-elevation portions of their ranges. Species may expand their ranges northwards as new areas become climatically suitable for them, producing significant changes in local floras. Species vary in their ability to make such migrations, depending upon limitations imposed by dispersal ability and/or specialized habitat requirements. An estimate of dispersibility suggests that species with narrow climate envelopes tend to lack characteristics promoting mobility.

  2. Climate and Agriculture: Model Inter-Comparison for Evaluating the Uncertainties in Climate Change Impact Assessment

    NASA Astrophysics Data System (ADS)

    Geethalakshmi, V.; Lakshmanan, A.; Bhuvaneswari, K.; Rajalakshmi, D.; Sekhar, N. U.; Anbhazhagan, R.; Gurusamy, L.

    2011-12-01

    Presence of large uncertainties in climate models (CM) and in future emission scenarios makes it difficult to predict the long-term climate changes at regional scales. Climate models do a reasonable job of capturing the large-scale aspects of current climate but still contain systematic model errors adding uncertainty to the future projections. Using CM outputs in impact models also cascade the uncertainty in climate change research. A study was undertaken with the objective of evaluating the uncertainty of climate change predictions by comparing the outputs from Regional Climate Models (RCM) and their resultant impact on rice productivity in Bhavani basin of Tamil Nadu, India. Current and future climate data were developed using RCMs viz., RegCM3 and PRECIS considering SRES A1B scenario for 130 years (1971-2100). The RCM outputs were used in DSSAT and EPIC models for assessing the impact of climate change. Results were compared to assess the magnitude of uncertainty in predicting the future climate and the resultant impacts. Comparison of predicted current climate with observed data indicated that RegCM3 under estimates maximum temperature by 1.8 °C while, PRECIS over estimates by 1.1°C over 40 years (1971 - 2010). The minimum temperature was under estimated by both the models, but with varying magnitude (3.8 °C for RegCM3 and 1 °C for PRECIS). RegCM3 over predicted rainfall (14 %), in contrast, PRECIS underpredicted (30.9 %) the same. Future climate projections indicated gradual increase in maximum and minimum temperatures with progress of time. Increase of maximum and minimum temperatures in PRECIS was 3.7oC and 4.2oC respectively and in RegCM3, it was 3.1oC and 3.7oC by 2100. No clear trend could be observed for rainfall other than increase in the quantum compared to current rainfall. Rice yield simulated over Bhavani basin for current and future climate by DSSAT, without CO2 fertilization effect, indicated reduction of 356 and 217 Kg ha-1decade-1 for

  3. A framework for modeling uncertainty in regional climate change

    EPA Science Inventory

    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 ...

  4. Analysis of cloud radiative forcing and feedback in a climate GCM. Final report

    SciTech Connect

    Lacis, A.

    1996-12-31

    The principal objectives of the research supported at the Goddard Institute for Space Studies (GISS) by the Atmospheric Radiation Measurement (ARM) Program for a three year period commencing September 1990, were: (1) to improve and validate the radiation parameterizations in the GISS GCM through model intercomparisons with line-by-line calculations and through comparisons with ARM observations; (2) to improve the GISS GCM diagnostic output to enable more effective comparisons to global cloud/radiation data sets; and (3) to use ARM data to develop improved parameterization of clouds in the GCM and to study the interaction of dynamics and radiation. The ARM Program support has made it possible to establish and support an active and productive research group at GISS specializing in radiative transfer and cloud process modeling in support of improving the performance of a climate GCM.

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

    PubMed

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

    2016-03-31

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

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

    NASA Astrophysics Data System (ADS)

    Tsunematsu, N.; Dairaku, K.

    2011-12-01

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

  7. Spread in model climate sensitivity traced to atmospheric convective mixing.

    PubMed

    Sherwood, Steven C; Bony, Sandrine; Dufresne, Jean-Louis

    2014-01-02

    Equilibrium climate sensitivity refers to the ultimate change in global mean temperature in response to a change in external forcing. Despite decades of research attempting to narrow uncertainties, equilibrium climate sensitivity estimates from climate models still span roughly 1.5 to 5 degrees Celsius for a doubling of atmospheric carbon dioxide concentration, precluding accurate projections of future climate. The spread arises largely from differences in the feedback from low clouds, for reasons not yet understood. Here we show that differences in the simulated strength of convective mixing between the lower and middle tropical troposphere explain about half of the variance in climate sensitivity estimated by 43 climate models. The apparent mechanism is that such mixing dehydrates the low-cloud layer at a rate that increases as the climate warms, and this rate of increase depends on the initial mixing strength, linking the mixing to cloud feedback. The mixing inferred from observations appears to be sufficiently strong to imply a climate sensitivity of more than 3 degrees for a doubling of carbon dioxide. This is significantly higher than the currently accepted lower bound of 1.5 degrees, thereby constraining model projections towards relatively severe future warming.

  8. ARM Climate Modeling Best Estimate Data, A New Data Product for Climate Studies

    SciTech Connect

    Xie, Shaocheng; McCoy, Renata B.; Klein, Stephen A.; Cederwall, Richard T.; Wiscombe, Warren J.; Clothiaux, Eugene E.; Gaustad, Krista L.; Golaz, Jean-Christophe; Shamblin, Stefanie H; Jensen, Michael P.; Johnson, Karen L.; Lin, Yanluan; Long, Charles N.; Mather, James H.; McCord, Raymond A; McFarlane, Sally A.; Palanisamy, Giri; Shi, Yan; Turner, David D.

    2010-01-01

    The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) was created in 1989 to address scientific uncertainties related to global climate change, with a focus on the crucial role of clouds and their influence on the transfer of radiation in the atmosphere. A central activity is the acquisition of detailed observations of clouds and radiation, as well as related atmospheric variables for climate model evaluation and improvement. Since 1992, ARM has established six permanent ARM Climate Research Facility (ACRF) sites and deployed an ARM Mobile Facility (AMF) in diverse climate regimes around the world (Fig. 1) to perform long-term continuous field measurements. The time record of ACRF data now exceeds a decade at most ACRF fixed sites and ranges from several months to one year for AMF deployments. Billions of measurements are currently stored in millions of data files in the ACRF Data Archive. The long-term continuous ACRF data provide invaluable information to improve our understanding of the interaction between clouds and radiation, and an observational basis for model validation and improvement and climate studies. Given the huge number of data files and current diversity of archived ACRF data structures, however, it can be difficult for an outside user such as a climate modeler to quickly find the ACRF data product(s) that best meets their research needs. The required geophysical quantities may exist in multiple data streams, and over the history of ACRF operations, the measurements could be obtained by a variety of instruments, reviewed with different levels of data quality assurance, or derived using different algorithms. In addition, most ACRF data are stored in daily-based files with a temporal resolution that ranges from a few seconds to a few minutes, which is much finer than that sought by some users. Therefore, it is not as convenient for data users to perform quick comparisons over large spans of data, and this

  9. Systematic Characterization of Cyclogenesis in High Resolution Climate Model Simulations

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Rao, P.; Kashinath, K.; Prabhat, M.; O'Brien, T. A.

    2015-12-01

    In this study we develop a systematic methodology to analyze cyclogenesis in high resolution climate model simulations. The motivation for this study is to understand how cyclones develop in simulations with the objective of improving the theoretical foundations of cyclogenesis. We use the toolkit for extreme climate analysis (TECA) [Prabhat et al., ICCS 2012] to detect and track cyclones (TCs) in recent high resolution simulations (25km) of current day and climate change scenarios [Wehner et al, J Climate 2015], as well as reanalyses. We systematically adjust the tracking criteria to identify developing and non-developing TCs. The detection and tracking criteria are based on (i) the local relative vorticity maximum being above a certain value, (ii) the colocation of vorticity maximum, surface pressure minimum and warm core temperature maximum, (iii) surface pressure gradient around the storm center to be above a certain value, and (iv) temperature gradient around the warm core center to be above a certain value. To identify non-developing TCs, we systematically characterize the sensitivity of cyclone detection to these criteria using a principal component analysis on the criteria. First, we composite vorticity, pressure and temperature fields around the start of each cyclone's trajectory. Second, we find the covariance of pairs of thresholded variables, for example, vorticity and pressure gradient. Finally, we construct a cross-correlation matrix with these covariances and find the eigenvectors. The eigenvector corresponding to the largest eigenvalue describes the direction of maximum sensitivity.We simultaneously lower thresholds along the direction of maximum sensitivity, which results in an increase in the number of TC-like systems and trajectory lengths compared to the baseline case. We contrast the behavior of developing and non-developing TCs by constructing multivariate joint PDFs of various environmental conditions along their trajectories. We also compute

  10. Lessons from Climate Modeling on the Design and Use of Ensembles for Crop Modeling

    NASA Technical Reports Server (NTRS)

    Wallach, Daniel; Mearns, Linda O.; Ruane, Alexander C.; Roetter, Reimund P.; Asseng, Senthold

    2016-01-01

    Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.

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

    NASA Astrophysics Data System (ADS)

    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.

  12. An Assessment of Decision-Making Processes: Evaluation of Where Land Protection Planning Can Incorporate Climate Change Information (Final Report)

    EPA Science Inventory

    EPA announced the availability of the final report, An Assessment of Decision-Making Processes: Evaluation of Where Land Protection Planning Can Incorporate Climate Change Information. This report is a review of decision-making processes of selected land protection prog...

  13. Very High Resolution Climate Modelling in Northern Russia

    NASA Astrophysics Data System (ADS)

    Stendel, M.; Christensen, J. H.

    2009-04-01

    Simulations with global climate models (GCMs) clearly indicate that major climate changes for the Arctic can be expected during the 21st century. Already now, there are substantial changes in sea-ice extent and thickness and a considerable increase in air temperature in several regions. Contemporary GCMs are unable to give a realistic representation of the climate and climate change in regions with steep orography, due to their coarse resolution. But even relatively high resolution regional climate models (RCMs) fail in this respect. We have therefore conducted a transient simulation with the newest version of the HIRHAM RCM, covering the period 1958-2001 over a region in northeast European Russia, including the Ural Mountains, with the unprecedented horizontal resolution of 4 km. For this simulation, a double downscaling procedure was applied. Average and extreme values will be discussed, and a comparison of subsurface temperatures to a set of observations from the region will be presented.

  14. Predictive modelling of boiler fouling. Final report.

    SciTech Connect

    Chatwani, A

    1990-12-31

    A spectral element method embodying Large Eddy Simulation based on Re- Normalization Group theory for simulating Sub Grid Scale viscosity was chosen for this work. This method is embodied in a computer code called NEKTON. NEKTON solves the unsteady, 2D or 3D,incompressible Navier Stokes equations by a spectral element method. The code was later extended to include the variable density and multiple reactive species effects at low Mach numbers, and to compute transport of large particles governed by inertia. Transport of small particles is computed by treating them as trace species. Code computations were performed for a number of test conditions typical of flow past a deep tube bank in a boiler. Results indicate qualitatively correct behavior. Predictions of deposition rates and deposit shape evolution also show correct qualitative behavior. These simulations are the first attempts to compute flow field results at realistic flow Reynolds numbers of the order of 10{sup 4}. Code validation was not done; comparison with experiment also could not be made as many phenomenological model parameters, e.g., sticking or erosion probabilities and their dependence on experimental conditions were not known. The predictions however demonstrate the capability to predict fouling from first principles. Further work is needed: use of large or massively parallel machine; code validation; parametric studies, etc.

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

    PubMed

    Diffenbaugh, Noah S; Giorgi, Filippo

    2012-01-10

    We use a statistical metric of multi-dimensional climate change to quantify the emergence of global climate change hotspots in the CMIP5 climate model ensemble. Our hotspot metric extends previous work through the inclusion of extreme seasonal temperature and precipitation, which exert critical influence on climate change impacts. The results identify areas of the Amazon, the Sahel and tropical West Africa, Indonesia, and the Tibetan Plateau as persistent regional climate change hotspots throughout the 21(st) century of the RCP8.5 and RCP4.5 forcing pathways. In addition, areas of southern Africa, the Mediterranean, the Arctic, and Central America/western North America also emerge as prominent regional climate change hotspots in response to intermediate and high levels of forcing. Comparisons of different periods of the two forcing pathways suggest that the pattern of aggregate change is fairly robust to the level of global warming below approximately 2°C of global warming (relative to the late-20(th)-century baseline), but not at the higher levels of global warming that occur in the late-21(st)-century period of the RCP8.5 pathway, with areas of southern Africa, the Mediterranean, and the Arctic exhibiting particular intensification of relative aggregate climate change in response to high levels of forcing. Although specific impacts will clearly be shaped by the interaction of climate change with human and biological vulnerabilities, our identification of climate change hotspots can help to inform mitigation and adaptation decisions by quantifying the rate, magnitude and causes of the aggregate climate response in different parts of the world.

  16. Clouds and more: ARM climate modeling best estimate data: A new data product for climate studies

    DOE PAGES

    Xie, Shaocheng; McCoy, Renata B.; Klein, Stephen A.; ...

    2010-01-01

    The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) was created in 1989 to address scientific uncertainties related to global climate change, with a focus on the crucial role of clouds and their influence on the transfer of radiation atmosphere. Here, a central activity is the acquisition of detailed observations of clouds and radiation, as well as related atmospheric variables for climate model evaluation and improvement.

  17. A probabilistic model of ecosystem response to climate change

    SciTech Connect

    Shevliakova, E.; Dowlatabadi, H.

    1994-12-31

    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.

  18. Climate change and health modeling: horses for courses

    PubMed Central

    Ebi, Kristie L.; Rocklöv, Joacim

    2014-01-01

    Mathematical and statistical models are needed to understand the extent to which weather, climate variability, and climate change are affecting current and may affect future health burdens in the context of other risk factors and a range of possible development pathways, and the temporal and spatial patterns of any changes. Such understanding is needed to guide the design and the implementation of adaptation and mitigation measures. Because each model projection captures only a narrow range of possible futures, and because models serve different purposes, multiple models are needed for each health outcome (‘horses for courses’). Multiple modeling results can be used to bracket the ranges of when, where, and with what intensity negative health consequences could arise. This commentary explores some climate change and health modeling issues, particularly modeling exposure-response relationships, developing early warning systems, projecting health risks over coming decades, and modeling to inform decision-making. Research needs are also suggested. PMID:24861341

  19. Towards Better Integration of Climate Models and Models for the Terrestrial Cryosphere (Permafrost and Glaciers)

    NASA Astrophysics Data System (ADS)

    Etzelmuller, B.; Westermann, S.; Gisnas, K.; Aas, K. S.; Schuler, T.; Dunse, T.; Ostby, T.; Berntsen, T.; Kristjansson, J. E.; Stordal, F.

    2014-12-01

    , which is not possible without subgrid representation of snow depths. Finally, we evaluate the possibility to improve simulations of surface energy fluxes also in atmosphere and climate models, through better representation of sub-grid scale variability of variables relevant for atmosphere-cryosphere interactions.

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

    NASA Technical Reports Server (NTRS)

    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

  1. Modeling lakes and reservoirs in the climate system

    USGS Publications Warehouse

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

    2009-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main features of the RCM ALARO-Climate and results of the first model simulations on longer time-scales (1961-1990). The model was driven by the ERA-40/Interim re-analyses and run on the large pan-European integration domain ("ENSEMBLES / Euro-Cordex domain") with spatial resolution of 25 km. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version 7 dataset. The validation of the first ERA-40 simulation has revealed significant cold biases in all seasons (between -4 and -2 °C) and overestimation of precipitation on 20% to 60% in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The consequent adaptations in the model and their effect on the simulated properties of climate variables are illustrated. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1.05/1.1.00/02.0073). The partial support was also provided under the projects P209-11-0956 of the Czech Science Foundation and CZ.1.07/2.4.00/31.0056 (Operational Programme of Education for Competitiveness of Ministry of Education, Youth and Sports of the Czech Republic).

  4. A Model of the Responses of Ecotones to Climate Change.

    PubMed

    Noble, Ian R

    1993-08-01

    It has been suggested that global climatic change may be detected by monitoring the positions of ecotones. I built a model of the dynamics of ecotones similar to those found in altitudinal or latitudinal treelines, where a slow tendency for the ecotone to advance is counterbalanced by disturbances such as fire or landslides. The model showed that the response of such ecotones to a wide range of simulated climate changes was slow and that the ecotone front was dissected. It would appear that such ecotones would not make suitable sites for monitoring climate change.

  5. Air quality research: perspective from climate change modelling research.

    PubMed

    Semazzi, Fredrick

    2003-06-01

    A major component of climate change is a manifestation of changes in air quality. This paper explores the question of air quality from the climate change modelling perspective. It reviews recent research advances on the cause-effect relationships between atmospheric air composition and climate change, primarily based on the Intergovernmental Panel on Climate Change (IPCC) assessment of climate change over the past decade. There is a growing degree of confidence that the warming world over the past century was caused by human-related changes in the composition of air. Reliability of projections of future climate change is highly dependent on future emission scenarios that have been identified that in turn depend on a multitude of complicated interacting social-economic factors. Anticipated improvements in the performance of climate models is a major source of optimism for better climate projections in the future, but the real benefits of its contribution will be closely coupled with other sources of uncertainty, and in particular emission projections.

  6. Parameterization of clouds and radiation in climate models

    SciTech Connect

    Roeckner, E.

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  10. Final Progress Report: Collaborative Research: Decadal-to-Centennial Climate & Climate Change Studies with Enhanced Variable and Uniform Resolution GCMs Using Advanced Numerical Techniques

    SciTech Connect

    Fox-Rabinovitz, M; Cote, J

    2009-06-05

    The joint U.S-Canadian project has been devoted to: (a) decadal climate studies using developed state-of-the-art GCMs (General Circulation Models) with enhanced variable and uniform resolution; (b) development and implementation of advanced numerical techniques; (c) research in parallel computing and associated numerical methods; (d) atmospheric chemistry experiments related to climate issues; (e) validation of regional climate modeling strategies for nested- and stretched-grid models. The variable-resolution stretched-grid (SG) GCMs produce accurate and cost-efficient regional climate simulations with mesoscale resolution. The advantage of the stretched grid approach is that it allows us to preserve the high quality of both global and regional circulations while providing consistent interactions between global and regional scales and phenomena. The major accomplishment for the project has been the successful international SGMIP-1 and SGMIP-2 (Stretched-Grid Model Intercomparison Project, phase-1 and phase-2) based on this research developments and activities. The SGMIP provides unique high-resolution regional and global multi-model ensembles beneficial for regional climate modeling and broader modeling community. The U.S SGMIP simulations have been produced using SciDAC ORNL supercomputers. Collaborations with other international participants M. Deque (Meteo-France) and J. McGregor (CSIRO, Australia) and their centers and groups have been beneficial for the strong joint effort, especially for the SGMIP activities. The WMO/WCRP/WGNE endorsed the SGMIP activities in 2004-2008. This project reflects a trend in the modeling and broader communities to move towards regional and sub-regional assessments and applications important for the U.S. and Canadian public, business and policy decision makers, as well as for international collaborations on regional, and especially climate related issues.

  11. Assessing climate change impact by integrated hydrological modelling

    NASA Astrophysics Data System (ADS)

    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

  12. Evaluation of regional climate simulations for air quality modelling purposes

    NASA Astrophysics Data System (ADS)

    Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

    2013-05-01

    In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

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

    NASA Astrophysics Data System (ADS)

    Stone, K. A.; Morgenstern, O.; Karoly, D. J.; Klekociuk, A. R.; French, W. J. R.; Abraham, N. L.; Schofield, R.

    2015-07-01

    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 these

  14. Berry composition and climate: responses and empirical models

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  15. Tropical deforestation: Modeling local- to regional-scale climate change

    SciTech Connect

    Henderson-Sellers, A.; Durbidge, T.B.; Pitman, A.J. ); Dickinson, R.E. ); Kennedy, P.J. ); McGuffie, K. )

    1993-04-20

    The authors report results from a model study using the National Center for Atmospheric Research Community Climate Model (Version 1) general circulation model to assess the impact of regional scale deforestation on climate change. In the model a large parcel in the Amazon basin is changed from tropical rain forest to scrub grassland. Impacts can include adding CO[sub 2] to the atmosphere by biomass burning, increasing surface albedo, changing precipitation and evaporation rates, impacting soil moisture, and general weather patterns. They compare their model results with earlier work which has looked at this same problem.

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

    NASA Astrophysics Data System (ADS)

    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

  17. Wavelet-based time series bootstrap model for multidecadal streamflow simulation using climate indicators

    NASA Astrophysics Data System (ADS)

    Erkyihun, Solomon Tassew; Rajagopalan, Balaji; Zagona, Edith; Lall, Upmanu; Nowak, Kenneth

    2016-05-01

    A model to generate stochastic streamflow projections conditioned on quasi-oscillatory climate indices such as Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO) is presented. Recognizing that each climate index has underlying band-limited components that contribute most of the energy of the signals, we first pursue a wavelet decomposition of the signals to identify and reconstruct these features from annually resolved historical data and proxy based paleoreconstructions of each climate index covering the period from 1650 to 2012. A K-Nearest Neighbor block bootstrap approach is then developed to simulate the total signal of each of these climate index series while preserving its time-frequency structure and marginal distributions. Finally, given the simulated climate signal time series, a K-Nearest Neighbor bootstrap is used to simulate annual streamflow series conditional on the joint state space defined by the simulated climate index for each year. We demonstrate this method by applying it to simulation of streamflow at Lees Ferry gauge on the Colorado River using indices of two large scale climate forcings: Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO), which are known to modulate the Colorado River Basin (CRB) hydrology at multidecadal time scales. Skill in stochastic simulation of multidecadal projections of flow using this approach is demonstrated.

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

    NASA Astrophysics Data System (ADS)

    McCusker, Kelly E.

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

  19. Regional Climate Model Sensitivity to Domain Size

    NASA Astrophysics Data System (ADS)

    Leduc, M.; Laprise, R.

    2006-05-01

    Regional Climate Models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBCs). It is well known that the limited area over which a model integrates must be large enough to allow the full development of small scales features (Jones et al., 1995). On the other hand, integrations on very large domains have shown important departures from the driving data, unless large-scale nudging is applied (e.g., Castro and Pielke, 2005). Here the effects of domain size on the development of small-scales are examined using the "Big-Brother" approach developed by Denis et al. (2002). This method consists of generating a high-resolution simulation over a large domain (the Big-Brother). The next step is to degrade this dataset with a low-pass filter based on discrete cosine transform (DCT; Denis et al., 2002) to emulate coarse-resolution LBCs that are usually taken from GCMs or reanalyses. A second simulation (the Little-Brother) is driven by the coarse-resolution LBCs and generates its own small-scale features inside the new smaller domain. Nested and added scales of the Little- Brother can then be compared with the Big-Brother (unfiltered) ones by using the DCT-filter again. Three February months (1990,1991 and 1992) were integrated over a continental grid (Big-Brother: 196x196 gridpoints) with a spatial resolution of 45 km covering almost the entire North-America. After filtering, this dataset is used to drive five simulations with varying domain size (48x48, 72x72, 96x96, 120x120 and 144x144) centred on the same geographic location; all other parameters are kept constant. Monthly statistics of the five Little-Brothers are compared with the virtual reference (Big-Brother) over the common domain (28x28) corresponding to the smallest Little-Brother but without its sponge zone. Results show that temporal correlation of large-scale events increases when the domain size is reduced from 144x144 to 48x48. For the same domain

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

    NASA Astrophysics Data System (ADS)

    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.

  1. Cloud fractional coverage: A key uncertainty in current climate models

    SciTech Connect

    Walcek, C.J.

    1996-12-31

    Climate models being used to study global warming use highly uncertain and widely divergent methods for calculating fractional cloudiness, which plays a significant role in regulating global albedo and climate. In this study the author compares cloud cover formulations used by various climate models with observations of fractional cloudiness and related meteorology derived from surface reports, upper atmospheric soundings, and satellites. He found that relative humidity is the best single predictor of cloud coverage, in agreement with most climate model formulations. However, the precise functional relationships used by climate models to estimate cloud coverage disagree significantly with observed cloud relationships. In the middle troposphere, most climate models probably underestimate cloud coverage since they specify zero cloud amounts when relative humidities are below 60--80%, while observed cloud amounts range from 20--60% at these height and humidity ranges. At humidities close to saturation, current algorithms probably overestimate cloud coverage. Cloud fractional cover observations compiled in this study suggest that at any level in the atmosphere, cloud amount decreases exponentially as humidity falls below 100%, and there is no evidence for critical humidities below which no clouds exist.

  2. Representation of Clear and Cloudy Boundary Layers in Climate Models. Chapter 14

    NASA Technical Reports Server (NTRS)

    Randall, D. A.; Shao, Q.; Branson, M.

    1997-01-01

    The atmospheric general circulation models which are being used as components of climate models rely on their boundary layer parameterizations to produce realistic simulations of the surface turbulent fluxes of sensible heat. moisture. and momentum: of the boundary-layer depth over which these fluxes converge: of boundary layer cloudiness: and of the interactions of the boundary layer with the deep convective clouds that grow upwards from it. Two current atmospheric general circulation models are used as examples to show how these requirements are being addressed: these are version 3 of the Community Climate Model. which has been developed at the U.S. National Center for Atmospheric Research. and the Colorado State University atmospheric general circulation model. The formulations and results of both models are discussed. Finally, areas for future research are suggested.

  3. Modeling Climate Change Effects on Stream Temperatures in Regulated Rivers

    NASA Astrophysics Data System (ADS)

    Null, S. E.; Akhbari, M.; Ligare, S. T.; Rheinheimer, D. E.; Peek, R.; Yarnell, S. M.; Viers, J. H.

    2013-12-01

    We provide a method for examining mesoscale stream temperature objectives downstream of dams with anticipated climate change using an integrated multi-model approach. Changing hydroclimatic conditions will likely impact stream temperatures within reservoirs and below dams, and affect downstream ecology. We model hydrology and water temperature using a series of linked models that includes a hydrology model to predict natural unimpaired flows in upstream reaches, a reservoir temperature simulation model , an operations model to simulate reservoir releases, and a stream temperature simulation model to simulate downstream conditions . All models are 1-dimensional and operate on either a weekly or daily timestep. First, we model reservoir thermal dynamics and release operations of hypothetical reservoirs of different sizes, elevations, and latitudes with climate-forced inflow hydrologies to examine the potential to manage stream temperatures for coldwater habitat. Results are presented as stream temperature change from the historical time period and indicate that reservoir releases are cooler than upstream conditions, although the absolute temperatures of reaches below dams warm with climate change. We also apply our method to a case study in California's Yuba River watershed to evaluate water regulation and hydropower operation effects on stream temperatures with climate change. Catchments of the upper Yuba River are highly-engineered, with multiple, interconnected infrastructure to provide hydropower, water supply, flood control, environmental flows, and recreation. Results illustrate climate-driven versus operations-driven changes to stream temperatures. This work highlights the need for methods to consider reservoir regulation effects on stream temperatures with climate change, particularly for hydropower relicensing (which currently ignores climate change) such that impacts to other beneficial uses like coldwater habitat and instream ecosystems can be

  4. Anthropocene changes in desert area: Sensitivity to climate model predictions

    NASA Astrophysics Data System (ADS)

    Mahowald, Natalie M.

    2007-09-01

    Changes in desert area due to humans have important implications from a local, regional to global level. Here I focus on the latter in order to better understand estimated changes in desert dust aerosols and the associated iron deposition into oceans. Using 17 model simulations from the World Climate Research Programme's Coupled Model Intercomparison Project phase 3 multi-model dataset and the BIOME4 equilibrium vegetation model, I estimate changes in desert dust source areas due to climate change and carbon dioxide fertilization. If I assume no carbon dioxide fertilization, the mean of the model predictions is that desert areas expand from the 1880s to the 2080s, due to increased aridity. If I allow for carbon dioxide fertilization, the desert areas become smaller. Thus better understanding carbon dioxide fertilization is important for predicting desert response to climate. There is substantial spread in the model simulation predictions for regional and global averages.

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

    SciTech Connect

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

    1995-12-31

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

  6. Climate change and heat-related mortality in six cities Part 2: climate model evaluation and projected impacts from changes in the mean and variability of temperature with climate change.

    PubMed

    Gosling, Simon N; McGregor, Glenn R; Lowe, Jason A

    2009-01-01

    the daily and extreme temperatures from HadCM3, which demonstrates that the estimates of future heat-related mortality for Dallas and Lisbon may be overestimated due to positive climate model bias. Likewise, estimates for Boston and London may be underestimated due to negative climate model bias. Finally, we briefly consider uncertainties in the impacts associated with greenhouse gas emissions and acclimatisation. The uncertainties in the mortality impacts due to different emissions scenarios of greenhouse gases in the future varied considerably by location. Allowing for acclimatisation to an extra 2 degrees C in mean temperatures reduced future heat-related mortality by approximately half that of no acclimatisation in each city.

  7. Evaluation of climate modeling factors impacting the variance of streamflow

    NASA Astrophysics Data System (ADS)

    Al Aamery, N.; Fox, J. F.; Snyder, M.

    2016-11-01

    The present contribution quantifies the relative importance of climate modeling factors and chosen response variables upon controlling the variance of streamflow forecasted with global climate model (GCM) projections, which has not been attempted in previous literature to our knowledge. We designed an experiment that varied climate modeling factors, including GCM type, project phase, emission scenario, downscaling method, and bias correction. The streamflow response variable was also varied and included forecasted streamflow and difference in forecast and hindcast streamflow predictions. GCM results and the Soil Water Assessment Tool (SWAT) were used to predict streamflow for a wet, temperate watershed in central Kentucky USA. After calibrating the streamflow model, 112 climate realizations were simulated within the streamflow model and then analyzed on a monthly basis using analysis of variance. Analysis of variance results indicate that the difference in forecast and hindcast streamflow predictions is a function of GCM type, climate model project phase, and downscaling approach. The prediction of forecasted streamflow is a function of GCM type, project phase, downscaling method, emission scenario, and bias correction method. The results indicate the relative importance of the five climate modeling factors when designing streamflow prediction ensembles and quantify the reduction in uncertainty associated with coupling the climate results with the hydrologic model when subtracting the hindcast simulations. Thereafter, analysis of streamflow prediction ensembles with different numbers of realizations show that use of all available realizations is unneeded for the study system, so long as the ensemble design is well balanced. After accounting for the factors controlling streamflow variance, results show that predicted average monthly change in streamflow tends to follow precipitation changes and result in a net increase in the average annual precipitation and

  8. Regional Climate Model Projections for the State of Washington

    SciTech Connect

    Salathe, E.; Leung, Lai-Yung R.; Qian, Yun; Zhang, Yongxin

    2010-05-05

    Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional heterogeneity of the climate of the State of Washington. If future large-scale weather patterns interact differently with the local terrain and coastlines than current weather patterns, local changes in temperature and precipitation could be quite different from the coarse-scale changes projected by global models. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year climate simulations using the Weather and Research Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970-1999) to the mid 21st century (2030-2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in

  9. Modeling High-Impact Weather and Climate: Lessons From a Tropical Cyclone Perspective

    SciTech Connect

    Done, James; Holland, Greg; Bruyere, Cindy; Leung, Lai-Yung R.; Suzuki-Parker, Asuka

    2013-10-19

    Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding of the underlying physical processes. This challenge is driving fresh approaches to assess high-impact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias in the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be guided by the need to: include relevant regional climate physical processes; resolve key impact parameters; and to accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters. Finally, through the example of a tropical cyclone damage index, direct impact assessments are resented as powerful tools that distill complex datasets into concise statements on likely impact, and as highly effective communication devices.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    USGS Publications Warehouse

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  13. Testing the Effects of Increased Horizontal Resolution in a Regional Climate Model for a Climatically Vulnerable Region

    NASA Astrophysics Data System (ADS)

    Snyder, M. A.; Sloan, L. C.; Bell, J. L.

    2002-12-01

    The need for high-resolution simulations of modern and future climates has driven the use of regional climate models in recent years. Regional climate models use a much higher horizontal resolution than global climate models, allowing more detailed investigations of climate at scales of importance to a wider range of parties. Here we explore the effects of increased horizontal resolution on the simulation of climate over the Western U. S. We performed three experiments of modern day climate, using the same boundary conditions, at three different horizontal resolutions, 20 km, 30 km, and 40 km. We compared the experiments with observations of climate and with each other in order to evaluate any improvement or lack of improvement in using the higher resolution. Initial comparisons suggest that a 20 km resolution produces more accurate snow and precipitation results, with temperature results being more similar and accurate between the 20 and 30 km cases.

  14. Regional climate model performance in the Lake Victoria basin

    NASA Astrophysics Data System (ADS)

    Williams, Karina; Chamberlain, Jill; Buontempo, Carlo; Bain, Caroline

    2015-03-01

    Lake Victoria, the second largest freshwater lake in the world, plays a crucial role in the hydrology of equatorial eastern Africa. Understanding how climate change may alter rainfall and evaporation patterns is thus of vital importance for the economic development and the livelihood of the region. Regional rainfall distribution appears, up to a large extent, to be controlled by local drivers which may be not well resolved in general circulation model simulations. We investigate the performance over the Lake Victoria basin of an ensemble of UK Met Office Hadley Centre regional climate model (HadRM3P) simulations at 50 km, driven by five members of the Hadley Centre global perturbed-physics ensemble (QUMP). This is part of the validation of an ensemble of simulations that has been used to assess the impacts of climate change over the continent over the period 1950-2099. We find that the regional climate model is able to simulate a lake/land breeze over Lake Victoria, which is a significant improvement over the driving global climate model and a vital step towards reproducing precipitation characteristics in the region. The local precipitation correlates well with large-scale processes in the Pacific Ocean and Indian Ocean, which is in agreement with observations. We find that the spatial pattern of precipitation in the region and the diurnal cycle of convection is well represented although the amount of rainfall over the lake appears to be overestimated in most seasons. Reducing the observational uncertainty in precipitation over the lake through future field campaigns would enable this model bias to be better quantified. We conclude that increasing the spatial resolution of the model significantly improves its ability to simulate the current climate of the Lake Victoria basin. We suggest that, despite the higher computational costs, the inclusion of a model which allows two-way interactions between the lake and its surroundings should be seriously considered for

  15. The UC-LLNL Regional Climate System Model

    SciTech Connect

    Miller, N.L.; Kim, Jinwon

    1996-09-01

    The UC-LLNL Regional Climate System Model has been under development since 1991. The unique system simulates climate from the global scale down to the watershed catchment scale, and consists of data pre- and post- processors, and four model components. The four model components are (1) a mesoscale atmospheric simulation model, (2) a soil-plant-snow model, (3) a watershed hydrology-riverflow model, and (4) a suite of crop response models. The first three model components have been coupled, and the system includes two-way feedbacks between the soil-plant-snow model and the mesoscale atmospheric simulation model. This three-component version of RCSM has been tested, validated, and successfully used for operational quantitative precipitation forecasts and seasonal water resource studies over the southwestern US. We are currently implementation and validating the fourth component, the Decision Support system for Agrotechnology Transfer (DSSAT). A description of the UC-LLNL RCSM and some recent results are presented.

  16. Spatial-temporal assessment of climate model drifts

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  17. Towards Ultra-High Resolution Models of Climate and Weather

    SciTech Connect

    Wehner, Michael; Oliker, Leonid; Shalf, John

    2007-01-01

    We present a speculative extrapolation of the performance aspects of an atmospheric general circulation model to ultra-high resolution and describe alternative technological paths to realize integration of such a model in the relatively near future. Due to a superlinear scaling of the computational burden dictated by stability criterion, the solution of the equations of motion dominate the calculation at ultra-high resolutions. From this extrapolation, it is estimated that a credible kilometer scale atmospheric model would require at least a sustained ten petaflop computer to provide scientifically useful climate simulations. Our design study portends an alternate strategy for practical power-efficient implementations of petaflop scale systems. Embedded processor technology could be exploited to tailor a custom machine designed to ultra-high climate model specifications at relatively affordable cost and power considerations. The major conceptual changes required by a kilometer scale climate model are certain to be difficult to implement. Although the hardware, software, and algorithms are all equally critical in conducting ultra-high climate resolution studies, it is likely that the necessary petaflop computing technology will be available in advance of a credible kilometer scale climate model.

  18. Greenhouse Models of Early Mars Climate

    NASA Astrophysics Data System (ADS)

    Kasting, J. F.

    2002-12-01

    Nearly all authors agree that Mars early (pre-3.8 Ga) surface was wet, as evidenced by many signs of flowing water on its heavily cratered southern highlands. Exactly what this implies about the early martian climate is a topic of ongoing debate. Some authors (1) have argued for a warm, nearly Earth-like climate; others (2) have suggested that the mean surface temperature could have been significantly below freezing. Here, I argue that the wetter early Mars was, the higher its mean surface temperature must have been in order to create the observed fluvial features. A planet with a large ocean, like Earth, would need to have a mean surface temperature at or above 0oC in order to avoid freezing over entirely. For a low-obliquity planet like Earth, ice albedo feedback causes the climate to become unstable when the polar caps extend equatorward of 30o (3). Mars has a highly variable obliquity, but the same reasoning is still likely to apply. If, indeed, Mars had an Earth-like early climate, then it must have had a substantial atmospheric greenhouse effect. Solar luminosity increased from about 70 percent of its present value at 4.6 Ga to 0.75 times present at 3.8 Ga (4). Gaseous CO2-H2O atmospheres can produce surface temperatures no higher than 225 K during this time (5). Radiative heating by CO2 ice clouds might raise this temperature somewhat (6). Obtaining surface temperatures above freezing with this mechanism, though, requires nearly 100 percent cloud cover, which is highly unlikely for condensation clouds. A methane greenhouse is a more attractive mechanism. The combination of a few bars of CO2, along with a few tenths of a percent CH4, could have kept early martian surface temperatures above freezing. This would probably have required a biogenic source for methane, however, as abiogenic sources are unlikely to have been strong enough to maintain such concentrations in the face of photolysis by solar UV radiation. Although admittedly speculative, such a

  19. Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models.

    PubMed

    Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Barbraud, Christophe; Weimerskirch, Henri; Serreze, Mark; Caswell, Hal

    2012-09-01

    Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa , because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SICa , which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor

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

    NASA Astrophysics Data System (ADS)

    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

  1. Modeling climate change impacts on overwintering bald eagles

    PubMed Central

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

    2012-01-01

    Bald eagles (Haliaeetus leucocephalus) are recovering from severe population declines, and are exerting pressure on food resources in some areas. Thousands of bald eagles overwinter near Puget Sound, primarily to feed on chum salmon (Oncorhynchus keta) carcasses. We used modeling techniques to examine how anticipated climate changes will affect energetic demands of overwintering bald eagles. We applied a regional downscaling method to two global climate change models to obtain hourly temperature, precipitation, wind, and longwave radiation estimates at the mouths of three Puget Sound tributaries (the Skagit, Hamma Hamma, and Nisqually rivers) in two decades, the 1970s and the 2050s. Climate data were used to drive bald eagle bioenergetics models from December to February for each river, year, and decade. Bald eagle bioenergetics were insensitive to climate change: despite warmer winters in the 2050s, particularly near the Nisqually River, bald eagle food requirements declined only slightly (<1%). However, the warming climate caused salmon carcasses to decompose more rapidly, resulting in 11% to 14% less annual carcass biomass available to eagles in the 2050s. That estimate is likely conservative, as it does not account for decreased availability of carcasses due to anticipated increases in winter stream flow. Future climate-driven declines in winter food availability, coupled with a growing bald eagle population, may force eagles to seek alternate prey in the Puget Sound area or in more remote ecosystems. PMID:22822430

  2. Modeling climate change impacts on overwintering bald eagles.

    PubMed

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

    2012-03-01

    Bald eagles (Haliaeetus leucocephalus) are recovering from severe population declines, and are exerting pressure on food resources in some areas. Thousands of bald eagles overwinter near Puget Sound, primarily to feed on chum salmon (Oncorhynchus keta) carcasses. We used modeling techniques to examine how anticipated climate changes will affect energetic demands of overwintering bald eagles. We applied a regional downscaling method to two global climate change models to obtain hourly temperature, precipitation, wind, and longwave radiation estimates at the mouths of three Puget Sound tributaries (the Skagit, Hamma Hamma, and Nisqually rivers) in two decades, the 1970s and the 2050s. Climate data were used to drive bald eagle bioenergetics models from December to February for each river, year, and decade. Bald eagle bioenergetics were insensitive to climate change: despite warmer winters in the 2050s, particularly near the Nisqually River, bald eagle food requirements declined only slightly (<1%). However, the warming climate caused salmon carcasses to decompose more rapidly, resulting in 11% to 14% less annual carcass biomass available to eagles in the 2050s. That estimate is likely conservative, as it does not account for decreased availability of carcasses due to anticipated increases in winter stream flow. Future climate-driven declines in winter food availability, coupled with a growing bald eagle population, may force eagles to seek alternate prey in the Puget Sound area or in more remote ecosystems.

  3. Considerations for building climate-based species distribution models

    USGS Publications Warehouse

    Bucklin, David N.; Basille, Mathieu; Romanach, Stephanie; Brandt, Laura A.; Mazzotti, Frank J.; Watling, James I.

    2016-01-01

    Climate plays an important role in the distribution of species. A given species may adjust to new conditions in-place, move to new areas with suitable climates, or go extinct. Scientists and conservation practitioners use mathematical models to predict the effects of future climate change on wildlife and plan for a biodiverse future. This 8-page fact sheet written by David N. Bucklin, Mathieu Basille, Stephanie S. Romañach, Laura A. Brandt, Frank J. Mazzotti, and James I. Watling and published by the Department of Wildlife Ecology and Conservation explains how, with a better understanding of species distribution models, we can predict how species may respond to climate change. The models alone cannot tell us how a certain species will actually respond to changes in climate, but they can inform conservation planning that aims to allow species to both adapt in place and (for those that are able to) move to newly suitable areas. Such planning will likely minimize loss of biodiversity due to climate change.

  4. Modeled regional climate change and California endemic oak ranges

    PubMed Central

    Kueppers, Lara M.; Snyder, Mark A.; Sloan, Lisa C.; Zavaleta, Erika S.; Fulfrost, Brian

    2005-01-01

    In the coming century, anthropogenic climate change will threaten the persistence of restricted endemic species, complicating conservation planning. Although most efforts to quantify potential shifts in species' ranges use global climate model (GCM) output, regional climate model (RCM) output may be better suited to predicting shifts by restricted species, particularly in regions with complex topography or other regionally important climate-forcing factors. Using a RCM-based future climate scenario, we found that potential ranges of two California endemic oaks, Quercus douglasii and Quercus lobata, shrink considerably (to 59% and 54% of modern potential range sizes, respectively) and shift northward. This result is markedly different from that obtained by using a comparable GCM-based scenario, under which these species retain 81% and 73% of their modern potential range sizes, respectively. The difference between RCM- and GCM-based scenarios is due to greater warming and larger precipitation decreases during the growing season predicted by the RCM in these species' potential ranges. Based on the modeled regional climate change, <50% of protected land area currently containing these species is expected to contain them under a future midrange “business-as-usual” path of greenhouse gas emissions. PMID:16260750

  5. Knowledge discovery and nonlinear modeling can complement climate model simulations for predictive insights about climate extremes and their impacts

    NASA Astrophysics Data System (ADS)

    Ganguly, A. R.; Steinbach, M.; Kumar, V.

    2009-12-01

    The IPCC AR4 not only provided conclusive evidence about anticipated global warming at century scales, but also indicated with a high level of certainty that the warming is caused by anthropogenic emissions. However, an outstanding knowledge-gap is to develop credible projections of climate extremes and their impacts. Climate extremes are defined in this context as extreme weather and hydrological events, as well as changes in regional hydro-meteorological patterns, especially at decadal scales. While temperature extremes from climate models have relatively better skills, hydrological variables and their extremes have significant shortcomings. Credible projections about tropical storms, sea level rise, coastal storm surge, land glacier melts, and landslides remain elusive. The next generation of climate models is expected to have higher precision. However, their ability to provide more accurate projections of climate extremes remains to be tested. Projections of observed trends into the future may not be reliable in non-stationary environments like climate change, even though functional relationships derived from physics may hold. On the other hand, assessments of climate change impacts which are useful for stakeholders and policy makers depend critically on regional and decadal scale projections of climate extremes. Thus, climate impacts scientists often need to develop qualitative inferences about the not so-well predicted climate extremes based on insights from observations (e.g., increased hurricane intensity) or conceptual understanding (e.g., relation of wildfires to regional warming or drying and hurricanes to SST). However, neither conceptual understanding nor observed trends may be reliable when extrapolating in a non-stationary environment. These urgent societal priorities offer fertile grounds for nonlinear modeling and knowledge discovery approaches. Thus, qualitative inferences on climate extremes and impacts may be transformed into quantitative

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  7. Community Climate System Model (CCSM) Experiments and Output Data

    DOE Data Explorer

    The National Center for Atmospheric Research (NCAR) created the first version of the Community Climate Model (CCM) in 1983 as a global atmosphere model. It was improved in 1994 when NCAR, with support from the National Science Foundation (NSF), developed and incorporated a Climate System Model (CSM) that included atmosphere, land surface, ocean, and sea ice. As the capabilities of the model grew, so did interest in its applications and changes in how it would be managed. A workshop in 1996 set the future management structure, marked the beginning of the second phase of the model, a phase that included full participation of the scientific community, and also saw additional financial support, including support from the Department of Energy. In recognition of these changes, the model was renamed to the Community Climate System Model (CCSM). It began to function as a model with the interactions of land, sea, and air fully coupled, providing computer simulations of Earth's past climate, its present climate, and its possible future climate. The CCSM website at http://www2.cesm.ucar.edu/ describes some of the research that has been done since then: A 300-year run has been performed using the CSM, and results from this experiment have appeared in a special issue of theJournal of Climate, 11, June, 1998. A 125-year experiment has been carried out in which carbon dioxide was described to increase at 1% per year from its present concentration to approximately three times its present concentration. More recently, the Climate of the 20th Century experiment was run, with carbon dioxide and other greenhouse gases and sulfate aerosols prescribed to evolve according to our best knowledge from 1870 to the present. Three scenarios for the 21st century were developed: a "business as usual" experiment, in which greenhouse gases are assumed to increase with no economic constraints; an experiment using the Intergovernmental Panel on Climate Change (IPCC) Scenario A1; and a "policy

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

    NASA Astrophysics Data System (ADS)

    Rood, R. B.

    2011-12-01

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

  9. On the suitability of regional climate models for reconstructing climatologies

    NASA Astrophysics Data System (ADS)

    Tapiador, Francisco J.; Angelis, Carlos F.; Viltard, Nicolas; Cuartero, Fernando; de Castro, Manuel

    2011-08-01

    This paper discusses the potential of Regional Climate Models (RCMs) as reanalysis tools by presenting a reconstruction of the European climate using several RCMs with diverse physical parameterizations. The use of RCMs is intended to increase the spatial resolution of the analysis provided by Global Models through dynamic downscaling. At the same time, the use of several models allows us to characterize the uncertainties, as these can be estimated from the spread of the ensemble. When the RCMs are nested in reanalyses instead of in a Global Model it is possible to create climatologies of unprecedented robustness for variables such as temperature, precipitation, wind speed, and humidity, among others. While these climatologies are subject to further improvement as methods and computing power evolve, they point the way forward to the development of atmospheric information products suitable for a variety of studies including education, agriculture, renewable energies and climate change research, biogeography, insurance, risk assessment, hydrology, and regional planning.

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

    SciTech Connect

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

    1993-09-01

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

  11. Watershed Model Parameterization for Assessing Impacts due to Climate Change

    NASA Astrophysics Data System (ADS)

    Yactayo, G. A.; Bhatt, G.

    2014-12-01

    The Chesapeake Bay (CB) Total Maximum Daily Load (TMDL) program drives water quality policy and management in parts of six states — Delaware, Maryland, New York, Pennsylvania, Virginia, and West Virginia — along with the District of Columbia to achieve water quality standards in the Bay through reductions in nutrient and sediment pollution. The HSPF Watershed Model (WSM) is used as an accounting tool in the development of the TMDL to track progress and guide implementations of best management practices. Published research has shown that precipitation has increased in the US during 20th century by about ten percent, and half of the increase is due to changes in frequency and intensity in the upper tenth percentile of the distribution. Projections from global climate models suggest that these trends are anticipated to continue over the next century. Our analysis of climate data over the last three decades show similar trends in observed precipitation in the CB Watershed. The impact of climate change on the CB TMDL will be examined in a 2017 assessment of progress in the State and Federal partnership of the Chesapeake Bay Program. This is consistent with the CB Executive Order of May 12, 2009 mandates assessment of the impacts of climate change on the CB TMDL. The WSM has a simulation period of more than 3 decades from 1985 to 2011. Over the simulation period precipitation intensity, temperatures, and CO2 levels are increasing. A study conducted by Najjar et al. (2010) that included regional climate projections suggests that pollutant loads in the CB region will increase over the next century. Butcher et al. (2014) demonstrated that a watershed model parameter needs to be adjusted to compensate for the effect of elevated CO2 concentrations on plant transpiration in climate projection applications. This raises the question of whether parameters within a watershed model calibrated using historical climate data are sufficient for assessing hydrologic and water

  12. On the Representation of Ice Nucleation in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

    NASA Astrophysics Data System (ADS)

    Storelvmo, T.

    2015-12-01

    Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

  13. World agriculture and climate change: Current modeling issues

    SciTech Connect

    Darwin, R.

    1996-12-31

    Recent studies suggest that although global increases in temperature and changes in precipitation patterns during the next century will affect world agriculture, farmer adaptations are likely to prevent climate change from jeopardizing world food production. The costs and benefits of global climate change, however, are not equally distributed around the world. Agricultural production may increase in high latitude and alpine areas, but decrease in tropical and some other areas. Also, land use changes that accompany climate-induced shifts in cropland and permanent pasture are likely to raise additional social and environmental issues. Despite these advances, some important aspects of climate change have not been adequately simulated in global models. These include the effects that climate-induced changes in water resources are likely to have on agricultural production, the well-documented beneficial effects of higher concentrations of atmospheric carbon dioxide on plant growth and water use, and the cooling effects of tropospheric emissions of sulfur dioxide. In addition, past research generally relied on equilibrium climates based on a doubling of atmospheric carbon dioxide. Now, however, results from transient climate change experiments are available.

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

    SciTech Connect

    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.

  15. Modeling Climate Change Impacts on Landscape Evolution, Fire, and Hydrology

    NASA Astrophysics Data System (ADS)

    Sheppard, B. S.; O Connor, C.; Falk, D. A.; Garfin, G. M.

    2015-12-01

    Landscape disturbances such as wildfire interact with climate variability to influence hydrologic regimes. We coupled landscape, fire, and hydrologic models and forced them using projected climate to demonstrate climate change impacts anticipated at Fort Huachuca in southeastern Arizona, USA. The US Department of Defense (DoD) recognizes climate change as a trend that has implications for military installations, national security and global instability. The goal of this DoD Strategic Environmental Research and Development Program (SERDP) project (RC-2232) is to provide decision making tools for military installations in the southwestern US to help them adapt to the operational realities associated with climate change. For this study we coupled the spatially explicit fire and vegetation dynamics model FireBGCv2 with the Automated Geospatial Watershed Assessment tool (AGWA) to evaluate landscape vegetation change, fire disturbance, and surface runoff in response to projected climate forcing. A projected climate stream for the years 2005-2055 was developed from the Multivariate Adaptive Constructed Analogs (MACA) 4 km statistical downscaling of the CanESM2 GCM using Representative Concentration Pathway (RCP) 8.5. AGWA, an ArcGIS add-in tool, was used to automate the parameterization and execution of the Soil Water Assessment Tool (SWAT) and the KINematic runoff and EROSion2 (KINEROS2) models based on GIS layers. Landscape raster data generated by FireBGCv2 project an increase in fire and drought associated tree mortality and a decrease in vegetative basal area over the years of simulation. Preliminary results from SWAT modeling efforts show an increase to surface runoff during years following a fire, and for future winter rainy seasons. Initial results from KINEROS2 model runs show that peak runoff rates are expected to increase 10-100 fold as a result of intense rainfall falling on burned areas.

  16. Modeling Climate Change and Sturgeon Populations in the Missouri River

    USGS Publications Warehouse

    Wildhaber, Mark L.

    2010-01-01

    The U.S. Geological Survey (USGS) Columbia Environmental Research Center (CERC), in collaboration with researchers from the University of Missouri and Iowa State University, is conducting research to address effects of climate change on sturgeon populations (Scaphirhynchus spp.) in the Missouri River. The CERC is conducting laboratory, field, and modeling research to identify causative factors for the responses of fish populations to natural and human-induced environmental changes and using this information to understand sensitivity of sturgeon populations to potential climate change in the Missouri River drainage basin. Sturgeon response information is being used to parameterize models predicting future population trends. These models will provide a set of tools for natural resource managers to assess management strategies in the context of global climate change. This research complements and builds on the ongoing Comprehensive Sturgeon Research Program (CSRP) at the CERC. The CSRP is designed to provide information critical to restoration of the Missouri River ecosystem and the endangered pallid sturgeon (S. albus). Current research is being funded by USGS through the National Climate Change Wildlife Science Center (NCCWSC) and the Science Support Partnership (SSP) Program that is held by the USGS and the U.S. Fish and Wildlife Service. The national mission of the NCCWSC is to improve the capacity of fish and wildlife agencies to respond to climate change and to address high-priority climate change effects on fish and wildlife. Within the national context, the NCCWSC research on the Missouri River focuses on temporal and spatial downscaling and associated uncertainty in modeling climate change effects on sturgeon species in the Missouri River. The SSP research focuses on improving survival and population estimates for pallid sturgeon population models.

  17. On the Representation of Cloud Phase in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

    NASA Astrophysics Data System (ADS)

    Storelvmo, Trude; Sagoo, Navjit; Tan, Ivy

    2016-04-01

    Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

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

    NASA Astrophysics Data System (ADS)

    Böhm, U.; Kücken, M.; Hauffe, D.; Gerstengarbe, F.-W.; Werner, P. C.; Flechsig, M.; Keuler, K.; Block, A.; Ahrens, W.; Nocke, Th.

    2004-06-01

    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 methodology to be

  19. Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment

    NASA Technical Reports Server (NTRS)

    Skiles, J. W.

    1995-01-01

    Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of particles, thermodynamics and radiation, and continuity of water vapor. Hydrology and heat balance are usually included for continents, and sea ice and heat balance are included for oceans. The current issue of this journal contains a paper by Van Blarcum et al. (1995) that predicts runoff from nine high-latitude rivers under a doubled CO2 atmosphere. The paper is important since river flow is an indicator variable for climate change. The authors show that precipitation will increase under the imposed perturbations and that owing to higher temperatures earlier in the year that cause the snow pack to melt sooner, runoff will also increase. They base their simulations on output from a GCM coupled with an interesting water routing scheme they have devised. Climate change models have been linked to other models to predict deforestation.

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

    NASA Astrophysics Data System (ADS)

    Rasch, P. J.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    The Late Pleistocene was a period which lasted from the Eemian interglacial period to the start of the warm Holocene and was characterized mostly by widespread glacial ice. It was also a period which saw modern humans spread throughout the world and other species of the same genus, like the Neanderthals, become extinct. Various hypotheses have been put forward to explain the extinction of Neanderthals, about 30,000 years ago. Among these is one which involves changes in past climate and the inability of Neanderthals to adapt to such changes. The last traces of Neanderthals coincide with the end of Marine Isotope Stage 3 (MIS3) which was marked by large fluctuations in temperature and so-called Heinrich events, as suggested by geochemical records from ice cores. It is thought that melting sea ice or icebergs originating from the Laurentide ice sheet led to a large discharge of freshwater into the North Atlantic Ocean during the Heinrich events and severely weakened the Atlantic meridional overturning circulation, with important environmental ramifications across parts of Europe such as sharp decreases in temperature and reduction in forest cover. In order to assess the effects of past climate change on past hominin migration and on the extinction of certain species, it is first important to have a good understanding of the past climate itself. In this study, we have used three variants of MIROC (The Model for Interdisciplinary Research on Climate), a global climate model, for a time slice experiment within the Late Pleistocene: two mid-resolution models (an atmosphere model and a coupled atmosphere-ocean model) and a high-resolution atmosphere model. To obtain a fuller picture, we also look at a cool stadial state as obtained from a 'freshwater hosing' coupled-model experiment, designed to mimic the effects of freshwater discharge in the North Atlantic. We next use the sea surface temperature response from this experiment to drive the atmosphere models. We discuss

  2. Modeling Two Types of Adaptation to Climate Change

    EPA Science Inventory

    Mitigation and adaptation are the two key responses available to policymakers to reduce the risks of climate change. We model these two policies together in a new DICE-based integrated assessment model that characterizes adaptation as either short-lived flow spending or long-live...

  3. Climate Modeling in the Calculus and Differential Equations Classroom

    ERIC Educational Resources Information Center

    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…

  4. Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models

    ERIC Educational Resources Information Center

    Pallant, Amy; Lee, Hee-Sun

    2015-01-01

    Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students (N = 512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation…

  5. A community diagnostic tool for chemistry climate model validation

    NASA Astrophysics Data System (ADS)

    Gettelman, A.; Eyring, V.; Fischer, C.; Shiona, H.; Cionni, I.; Neish, M.; Morgenstern, O.; Wood, S. W.; Li, Z.

    2012-09-01

    This technical note presents an overview of the Chemistry-Climate Model Validation Diagnostic (CCMVal-Diag) tool for model evaluation. The CCMVal-Diag tool is a flexible and extensible open source package that facilitates the complex evaluation of global models. Models can be compared to other models, ensemble members (simulations with the same model), and/or many types of observations. The initial construction and application is to coupled chemistry-climate models (CCMs) participating in CCMVal, but the evaluation of climate models that submitted output to the Coupled Model Intercomparison Project (CMIP) is also possible. The package has been used to assist with analysis of simulations for the 2010 WMO/UNEP Scientific Ozone Assessment and the SPARC Report on the Evaluation of CCMs. The CCMVal-Diag tool is described and examples of how it functions are presented, along with links to detailed descriptions, instructions and source code. The CCMVal-Diag tool supports model development as well as quantifies model changes, both for different versions of individual models and for different generations of community-wide collections of models used in international assessments. The code allows further extensions by different users for different applications and types, e.g. to other components of the Earth system. User modifications are encouraged and easy to perform with minimum coding.

  6. A community diagnostic tool for Chemistry Climate Model Validation

    NASA Astrophysics Data System (ADS)

    Gettelman, A.; Eyring, V.; Fischer, C.; Shiona, H.; Cionni, I.; Neish, M.; Morgenstern, O.; Wood, S. W.; Li, Z.

    2012-05-01

    This technical note presents an overview of the Chemistry-Climate Model Validation Diagnostic (CCMVal-Diag) tool for model evaluation. The CCMVal-Diag tool is a flexible and extensible open source package that facilitates the complex evaluation of global models. Models can be compared to other models, ensemble members (simulations with the same model), and/or many types of observations. The tool can also compute quantitative performance metrics. The initial construction and application is to coupled Chemistry-Climate Models (CCMs) participating in CCMVal, but the evaluation of climate models that submitted output to the Coupled Model Intercomparison Project (CMIP) is also possible. The package has been used to assist with analysis of simulations for the 2010 WMO/UNEP Scientific Ozone Assessment and the SPARC Report on the Evaluation of CCMs. The CCMVal-Diag tool is described and examples of how it functions are presented, along with links to detailed descriptions, instructions and source code. The CCMVal-Diag tool is supporting model development as well as quantifying model improvements, both for different versions of individual models and for different generations of community-wide collections of models used in international assessments. The code allows further extensions by different users for different applications and types, e.g. to other components of the Earth System. User modifications are encouraged and easy to perform with a minimum of coding.

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

    NASA Astrophysics Data System (ADS)

    Trzeciak, Tomasz M.; Knippertz, Peter; Pirret, Jennifer S. R.; Williams, Keith D.

    2016-06-01

    Cyclonic windstorms are one of the most important natural hazards for Europe, but robust climate projections of the position and the strength of the North Atlantic storm track are not yet possible, bearing significant risks to European societies and the (re)insurance industry. Previous studies addressing the problem of climate model uncertainty through statistical comparisons of simulations of the current climate with (re-)analysis data show large disagreement between different climate models, different ensemble members of the same model and observed climatologies of intense cyclones. One weakness of such evaluations lies in the difficulty to separate influences of the climate model's basic state from the influence of fast processes on the development of the most intense storms, which could create compensating effects and therefore suggest higher reliability than there really is. This work aims to shed new light into this problem through a cost-effective "seamless" approach of hindcasting 20 historical severe storms with the two global climate models, ECHAM6 and GA4 configuration of the Met Office Unified Model, run in a numerical weather prediction mode using different lead times, and horizontal and vertical resolutions. These runs are then compared to re-analysis data. The main conclusions from this work are: (a) objectively identified cyclone tracks are represented satisfactorily by most hindcasts; (b) sensitivity to vertical resolution is low; (c) cyclone depth is systematically under-predicted for a coarse resolution of T63 by both climate models; (d) no systematic bias is found for the higher resolution of T127 out to about three days, demonstrating that climate models are in fact able to represent the complex dynamics of explosively deepening cyclones well, if given the correct initial conditions; (e) an analysis using a recently developed diagnostic tool based on the surface pressure tendency equation points to too weak diabatic processes, mainly latent

  8. NCSE's 15th National Conference and Global Forum on Science, Policy, and the Environment: Energy and Climate Change, Final Report

    SciTech Connect

    Levine, Ellen

    2016-07-08

    The National Council for Science and the Environment (NCSE) held its 15th National Conference and Global Forum on Science, Policy and the Environment: Energy and Climate Change, on January 27-29, 2015, at the Hyatt Regency Hotel, Crystal City, VA. The National Conference: Energy and Climate Change developed and advanced partnerships that focused on transitioning the world to a new “low carbon” and “climate resilient” energy system. It emphasized advancing research and technology, putting ideas into action, and moving forward on policy and practice. More than 900 participants from the scientific research, policy and governance, business and civil society, and education communities attended. The Conference was organized around four themes: (1) a new energy system (including energy infrastructure, technologies and efficiencies, changes in distribution of energy sources, and low carbon transportation); (2) energy, climate and sustainable development; (3) financing and markets; and (4) achieving progress (including ideas for the 21st Conference of Parties to the United Nations Framework Convention on Climate Change). The program featured six keynote presentations, six plenary sessions, 41 symposia and 20 workshops. Conference participants were involved in the 20 workshops, each on a specific energy and climate-related issue. The workshops were designed as interactive sessions, with each workshop generating 10-12 recommendations on the topic. The recommendations were prepared in the final conference report, were disseminated nationally, and continue to be available for public use. The conference also featured an exhibition and poster sessions. The National Conference on Energy and Climate Change addressed a wide range of issues specific to the U.S. Department of Energy’s programs; involved DOE’s scientists and program managers in sessions and workshops; and reached out to a broad array of DOE stakeholders.

  9. Climate Models from the Joint Global Change Research Institute

    DOE Data Explorer

    Staff at the Joint Institute develop and use models to simulate the economic and physical impacts of global change policy options. The GCAM, for example, gives analysts insight into how regional and national economies might respond to climate change mitigation policies including carbon taxes, carbon trading, and accelerated deployment of energy technology. Three available models are Phoenix, GCAM, and EPIC. Phoenix is a global, dynamic recursive, computable general equilibrium model that is solved in five-year time steps from 2005 through 2100 and divides the world into twenty-four regions. Each region includes twenty-six industrial sectors. Particular attention is paid to energy production in Phoenix. There are nine electricity-generating technologies (coal, natural gas, oil, biomass, nuclear, hydro, wind, solar, and geothermal) and four additional energy commodities: crude oil, refined oil products, coal, and natural gas. Phoenix is designed to answer economic questions related to international climate and energy policy and international trade. Phoenix replaces the Second Generation Model (SGM) that was formerly used for general equilibrium analysis at JGCRI. GCAM is the Global Change Assessment Model, a partial equilibrium model of the world with 14 regions. GCAM operates in 5 year time steps from 1990 to 2095 and is designed to examine long-term changes in the coupled energy, agriculture/land-use, and climate system. GCAM includes a 151-region agriculture land-use module and a reduced form carbon cycle and climate module in addition to its incorporation of demographics, resources, energy production and consumption. The model has been used extensively in a number of assessment and modeling activities such as the Energy Modeling Forum (EMF), the U.S. Climate Change Technology Program, and the U.S. Climate Change Science Program and IPCC assessment reports. GCAM is now freely available as a community model. The Environmental Policy Integrated Climate (EPIC) Model

  10. Winter and summer simulations with the GLAS climate model

    NASA Technical Reports Server (NTRS)

    Shukla, J.; Straus, D.; Randall, D.; Sud, Y.; Marx, L.

    1981-01-01

    The GLAS climate model is a general circulation model based on the primitive equations in sigma coordinates on a global domain in the presence of orography. The model incorporates parameterizations of the effects of radiation, convection, large scale latent heat release, turbulent and boundary layer fluxes, and ground hydrology. Winter and summer simulations were carried out with this model, and the resulting data are compared to observations.

  11. Simulation of landscape disturbances and the effect of climatic change. Final report, July 15, 1989--July 14, 1990

    SciTech Connect

    Baker, W.L.

    1993-01-29

    The purpose of this research is to understand how changes in climate may affect the structure of landscapes that are subject to periodic disturbances. A general model useful for examining the linkage between climatic change and landscape change has been developed. The model makes use of synoptic climatic data, a geographical information system (GRASS), field data on the location of disturbance patches, simulation code written in the SIMSCRIPT language, and a set of landscape structure analysis programs written specifically for this research project. A simplified version of the model, lacking the climatic driver, has been used to analyze how changes in disturbance regimes (in this case settlement and fire suppression) affect landscape change. Landscape change lagged in its response to changes in the disturbance regime, but the lags differed depending upon the character of the change and the particular measure considered. The model will now be modified for use in a specific setting to analyze the effects of changes in climate on the structure of flood-disturbed patches along the Animas River, Colorado.

  12. Modeled impact of anthropogenic land cover change on climate

    USGS Publications Warehouse

    Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J.

    2007-01-01

    Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.

  13. Hospitable archean climates simulated by a general circulation model.

    PubMed

    Wolf, E T; Toon, O B

    2013-07-01

    Evidence from ancient sediments indicates that liquid water and primitive life were present during the Archean despite the faint young Sun. To date, studies of Archean climate typically utilize simplified one-dimensional models that ignore clouds and ice. Here, we use an atmospheric general circulation model coupled to a mixed-layer ocean model to simulate the climate circa 2.8 billion years ago when the Sun was 20% dimmer than it is today. Surface properties are assumed to be equal to those of the present day, while ocean heat transport varies as a function of sea ice extent. Present climate is duplicated with 0.06 bar of CO2 or alternatively with 0.02 bar of CO2 and 0.001 bar of CH4. Hot Archean climates, as implied by some isotopic reconstructions of ancient marine cherts, are unattainable even in our warmest simulation having 0.2 bar of CO2 and 0.001 bar of CH4. However, cooler climates with significant polar ice, but still dominated by open ocean, can be maintained with modest greenhouse gas amounts, posing no contradiction with CO2 constraints deduced from paleosols or with practical limitations on CH4 due to the formation of optically thick organic hazes. Our results indicate that a weak version of the faint young Sun paradox, requiring only that some portion of the planet's surface maintain liquid water, may be resolved with moderate greenhouse gas inventories. Thus, hospitable late Archean climates are easily obtained in our climate model.

  14. High Resolution Modelling of Crop Response to Climate Change

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Astrophysics Data System (ADS)

    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

  16. Peformance Tuning and Evaluation of a Parallel Community Climate Model

    SciTech Connect

    Drake, J.B.; Worley, P.H.; Hammond, S.

    1999-11-13

    The Parallel Community Climate Model (PCCM) is a message-passing parallelization of version 2.1 of the Community Climate Model (CCM) developed by researchers at Argonne and Oak Ridge National Laboratories and at the National Center for Atmospheric Research in the early to mid 1990s. In preparation for use in the Department of Energy's Parallel Climate Model (PCM), PCCM has recently been updated with new physics routines from version 3.2 of the CCM, improvements to the parallel implementation, and ports to the SGIKray Research T3E and Origin 2000. We describe our experience in porting and tuning PCCM on these new platforms, evaluating the performance of different parallel algorithm options and comparing performance between the T3E and Origin 2000.

  17. Congo Basin rainfall climatology: can we believe the climate models?

    PubMed

    Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M; Moufouma-Okia, Wilfran

    2013-01-01

    The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.

  18. Congo Basin rainfall climatology: can we believe the climate models?

    PubMed Central

    Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M.; Moufouma-Okia, Wilfran

    2013-01-01

    The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models. PMID:23878328

  19. The Mars Climate Orbiter arrives at KSC to begin final preparations for launch

    NASA Technical Reports Server (NTRS)

    1998-01-01

    The Mars Climate Orbiter spacecraft arrives at KSC's Shuttle Landing Facility aboard an Air Force C-17 cargo plane early this morning following its flight from the Lockheed Martin Astronautics plant in Denver, Colo. When the spacecraft arrives at the red planet, it will primarily support its companion Mars Polar Lander spacecraft, planned for launch on Jan. 3, 1999. After that, the Mars Climate Orbiter's instruments will monitor the Martian atmosphere and image the planet's surface on a daily basis for one Martian year (1.8 Earth years). It will observe the appearance and movement of atmospheric dust and water vapor, as well as characterize seasonal changes on the surface. The detailed images of the surface features will provide important clues to the planet's early climate history and give scientists more information about possible liquid water reserves beneath the surface. The scheduled launch date for the Mars Climate Orbiter is Dec. 10, 1998, on a Delta II 7425 rocket.

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

    USGS Publications Warehouse

    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.

  1. 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

    NASA Technical Reports Server (NTRS)

    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.

  2. Modelling of maize production in Croatia: present and future climate

    PubMed Central

    VUČETIĆ, V.

    2011-01-01

    SUMMARY Maize is one of the most important agricultural crops in Croatia, and was selected for research of the effect of climate warming on yields. The Decision Support System for the Agrotechnology Transfer model (DSSAT) is one of the most utilized crop–weather models in the world, and was used in this paper for the investigation of maize growth and production in the present and future climate. The impact of present climate on maize yield was studied using DSSAT 4.0 with meteorological data from the Zagreb–Maksimir station covering the period 1949–2004. Pedological, physiological and genetic data from a 1999 field maize experiment at the same location were added. The location is representative of the continental climate in central Croatia. The linear trends of model outputs and the non-parametric Mann–Kendall test indicate that the beginning of silking has advanced significantly by 1·4 days/decade since the mid-1990s, and maturity by 4·5 days/decade. It also shows a decrease in biomass by 122 kg/ha and in maize yield by 216 kg/ha in 10 years. Estimates of the sensitivity of maize growth and yield in future climates were made by changing the initial weather and CO2 conditions of the DSSAT 4.0 model according to the different climatic scenarios for Croatia at the end of the 21st century. Changed climate suggests increases in global solar radiation, minimal temperature and maximal temperature (×1·07, 2 and 4°C, respectively), but a decrease in the amount of precipitation (×0·92), compared with weather data from the period 1949–2004. The reduction of maize yield was caused by the increase in minimal and maximal temperature and the decrease in precipitation amount, related to the present climate, is 6, 12 and 3%, respectively. A doubling of CO2 concentration stimulates leaf assimilation, but maize yield is only 1% higher, while global solar radiation growth by 7% increases evapotranspiration by 3%. Simultaneous application of all these climate changes

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

    PubMed

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

    2015-10-27

    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.

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

    PubMed Central

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

    2015-01-01

    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. PMID:26460042

  5. Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

    NASA Astrophysics Data System (ADS)

    Tao, F.; Rötter, R.

    2013-12-01

    Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for

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

    NASA Astrophysics Data System (ADS)

    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.

  7. Science of Global Climate Modeling: Confirmation from Discoveries on Mars

    NASA Astrophysics Data System (ADS)

    Hartmann, William K.

    2012-10-01

    As early as 1993, analysis of obliquity changes on Mars revealed irregular cycles of high excursion, over 45°1. Further obliquity analyses indicated that insolation and climatic conditions vary with time, with the four most recent episodes of obliquity >45° occurring about 5.5, 8, 9, and 15 My.2 Various researchers applied global climate models, using Martian parameters and obliquity changes. The models (independent of Martian geomorphological observations) indicate exceptional climate conditions during the high-obliquity episodes at >45°3,4, with localized massive ice deposition effects east of Hellas and on the west slopes of Tharsis.5 At last year’s DPS my co-authors and I detailed evidence of unusual active glaciation in Greg crater, near the center of the predicted area of ice accumulation during high obliquity.6 We found that the timescale of glacial surface layer activity matches the general 5-15 My timescale of the last episodes of high obliquity and ice deposition. Radar results confirm ice deposits in debris aprons concentrated in the same area.7 Less direct evidence has also been found for glacial ice deposits in the west Tharsis region.8 Here I emphasize that if the models can be adjusted to Mars and then successfully indicate unusual, specific features that we see there, it is an argument for the robustness of climate modeling in general. In recent years we have see various public figures casting doubt on the validity of terrestrial global modeling. The successful match of Martian climate modeling with direct Martian geological and chronometric observations provides an interesting and teachable refutation of the attacks on climate science. References: 1. Science 259:1294-1297; 2. LPSC XXXV, Abs. 1600; 3. Nature 412:411-413; 4. Science 295:110-113; 5. Science 311:368-371; 6. EPSC-DPS Abs. 1394; 7. Science 322:1235-1238; 8. Nature 434:346-351.

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

    USGS Publications Warehouse

    David E. Rupp,

    2016-05-05

    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.

  9. FOREST-SAGE, a new deforestation model for climate models and an example deforestation climate impact experiment in the Congo.

    NASA Astrophysics Data System (ADS)

    Tompkins, A. M.; Bell, J.-P.; Caporaso, L.

    2012-04-01

    The impact of deforestation on climate is often studied using highly idealized "instant deforestation" experiments due to the lack of generalized deforestation scenario generators coupled to climate model land-surface schemes. A new deforestation scenario generator has been therefore developed to fulfill this role known as the deFORESTation ScenArio GEnerator, or FOREST-SAGE. The model produces distributed maps of deforestation rates that account for local factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. The integrated deforestation risk is scaled to give the deforestation rate as specified by macro-region scenarios such as "business as usual" or "increased protection legislation" which are a function of future time. FOREST-SAGE is based on the framework of the widely used Community Land Model (CLM), which is the land model for the Community Earth System Model (CESM), the Community Atmosphere Model (CAM) and the 4th generation ICTP regional climate model REGCM4. Example potential future deforestation scenarios for central Africa are shown, along with the resulting climate impact as modelled by REGCM coupled to CLM.

  10. Final Report for LDRD Project ''A New Era of Research in Aerosol/Cloud/Climate Interactions at LLNL''

    SciTech Connect

    Chuang, C; Bergman, D J; Dignon, J E; Connell, P S

    2002-01-31

    Observations of global temperature records seem to show less warming than predictions of global warming brought on by increasing concentrations of CO{sub 2} and other greenhouse gases. One of the reasonable explanations for this apparent inconsistency is that the increasing concentrations of anthropogenic aerosols may be partially counteracting the effects of greenhouse gases. Aerosols can scatter or absorb the solar radiation, directly change the planetary albedo. Aerosols, unlike CO{sub 2}, may also have a significant indirect effect by serving as cloud condensation nuclei (CCN). Increases in CCN can result in clouds with more but smaller droplets, enhancing the reflection of solar radiation. Aerosol direct and indirect effects are a strong function of the distributions of all aerosol types and the size distribution of the aerosol in question. However, the large spatial and temporal variabilities in the concentration, chemical characteristics, and size distribution of aerosols have made it difficult to assess the magnitude of aerosol effects on atmospheric radiation. These variabilities in aerosol characteristics as well as their effects on clouds are the leading sources of uncertainty in predicting future climate variation. Inventory studies have shown that the present-day anthropogenic emissions contribute more than half of fine particle mass primarily due to sulfate and carbonaceous aerosols derived from fossil fuel combustion and biomass burning. Parts of our earlier studies have been focused on developing an understanding of global sulfate and carbonaceous aerosol abundances and investigating their climate effects [Chuang et al., 1997; Penner et al., 1998]. We have also modeled aerosol optical properties to account for changes in the refractive indices with relative humidity and dry aerosol composition [Grant et al., 1999]. Moreover, we have developed parameterizations of cloud response to aerosol abundance for use in global models to evaluate the importance

  11. Linking the Weather Generator with Regional Climate Model

    NASA Astrophysics Data System (ADS)

    Dubrovsky, Martin; Farda, Ales; Skalak, Petr; Huth, Radan

    2013-04-01

    One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series in the first step, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with gridded RCM weather series and spatially scarcer observations. The quality of the weather series produced by the resultant gridded WG will be assessed in terms of selected climatic characteristics (focusing on characteristics related to variability and extremes of surface temperature and precipitation). Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102

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

    NASA Astrophysics Data System (ADS)

    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

  13. Systematic uncertainty reduction strategies for developing streamflow forecasts utilizing multiple climate models and hydrologic models

    NASA Astrophysics Data System (ADS)

    Singh, Harminder; Sankarasubramanian, A.

    2014-02-01

    Recent studies show that multimodel combinations improve hydroclimatic predictions by reducing model uncertainty. Given that climate forecasts are available from multiple climate models, which could be ingested with multiple watershed models, what is the best strategy to reduce the uncertainty in streamflow forecasts? To address this question, we consider three possible strategies: (1) reduce the input uncertainty first by combining climate models and then use the multimodel climate forecasts with multiple watershed models (MM-P), (2) ingest the individual climate forecasts (without multimodel combination) with various watershed models and then combine the streamflow predictions that arise from all possible combinations of climate and watershed models (MM-Q), (3) combine the streamflow forecasts obtained from multiple watershed models based on strategy (1) to develop a single streamflow prediction that reduces uncertainty in both climate forecasts and watershed models (MM-PQ). For this purpose, we consider synthetic schemes that generate streamflow and climate forecasts, for comparing the performance of three strategies with the true streamflow generated by a given hydrologic model. Results from the synthetic study show that reducing input uncertainty first (MM-P) by combining climate forecasts results in reduced error in predicting the true streamflow compared to the error of multimodel streamflow forecasts obtained by combining streamflow forecasts from all-possible combination of individual climate model with various hydrologic models (MM-Q). Since the true hydrologic model structure is unknown, it is desirable to consider MM-PQ as an alternate choice that reduces both input uncertainty and hydrologic model uncertainty. Application on two watersheds in NC also indicates that reducing the input uncertainty first is critical before reducing the hydrologic model uncertainty.

  14. Using Web 2.0 Techniques To Bring Global Climate Modeling To More Users

    NASA Astrophysics Data System (ADS)

    Chandler, M. A.; Sohl, L. E.; Tortorici, S.

    2012-12-01

    The Educational Global Climate Model has been used for many years in undergraduate courses and professional development settings to teach the fundamentals of global climate modeling and climate change simulation to students and teachers. While course participants have reported a high level of satisfaction in these courses and overwhelmingly claim that EdGCM projects are worth the effort, there is often a high level of frustration during the initial learning stages. Many of the problems stem from issues related to installation of the software suite and to the length of time it can take to run initial experiments. Two or more days of continuous run time may be required before enough data has been gathered to begin analyses. Asking users to download existing simulation data has not been a solution because the GCM data sets are several gigabytes in size, requiring substantial bandwidth and stable dedicated internet connections. As a means of getting around these problems we have been developing a Web 2.0 utility called EzGCM (Easy G-G-M) which emphasizes that participants learn the steps involved in climate modeling research: constructing a hypothesis, designing an experiment, running a computer model and assessing when an experiment has finished (reached equilibrium), using scientific visualization to support analysis, and finally communicating the results through social networking methods. We use classic climate experiments that can be "rediscovered" through exercises with EzGCM and are attempting to make this Web 2.0 tool an entry point into climate modeling for teachers with little time to cover the subject, users with limited computer skills, and for those who want an introduction to the process before tackling more complex projects with EdGCM.

  15. Visualizing Life Zone Boundary Sensitivities Across Climate Models and Temporal Spans

    SciTech Connect

    Sisneros, Roberto R; Huang, Jian; Ostrouchov, George; Hoffman, Forrest M

    2011-01-01

    Life zones are a convenient and quantifiable method for delineating areas with similar plant and animal communities based on bioclimatic conditions. Such ecoregionalization techniques have proved useful for defining habitats and for studying how these habitats may shift due to environmental change. The ecological impacts of climate change are of particular interest. Here we show that visualizations of the geographic projection of life zones may be applied to the investigation of potential ecological impacts of climate change using the results of global climate model simulations. Using a multi-factor classification scheme, we show how life zones change over time based on quantitative model results into the next century. Using two straightforward metrics, we identify regions of high sensitivity to climate changes from two global climate simulations under two different greenhouse gas emissions scenarios. Finally, we identify how preferred human habitats may shift under these scenarios. We apply visualization methods developed for the purpose of displaying multivariate relationships within data, especially for situations that involve a large number of concurrent relationships. Our method is based on the concept of multivariate classification, and is implemented directly in VisIt, a production quality visualization package.

  16. Connecting climate model projections of global temperature change with the real world

    NASA Astrophysics Data System (ADS)

    Hawkins, Ed; Sutton, Rowan

    2016-04-01

    Current state-of-the-art global climate models produce different values for Earth's mean temperature. When comparing simulations with each other and with observations it is standard practice to compare temperature anomalies with respect to a reference period. It is not always appreciated that the choice of reference period can affect conclusions, both about the skill of simulations of past climate, and about the magnitude of expected future changes in climate. We discuss some of the key issues that arise when using anomalies relative to a reference period to generate climate projections and highlight that there is no perfect choice of reference period. When evaluating models against observations, a long reference period should generally be used, but how long depends on the quality of the observations available. The IPCC AR5 choice to use a 1986-2005 reference period for future global temperature projections was reasonable, but a case-by-case approach is needed for different purposes and when assessing projections of different climate variables. Finally, we recommend that any studies that involve the use of a reference period should explicitly examine the robustness of the conclusions to alternative choices.

  17. A New Method of Comparing Forcing Agents in Climate Models

    SciTech Connect

    Kravitz, Benjamin S.; MacMartin, Douglas; Rasch, Philip J.; Jarvis, Andrew

    2015-10-14

    We describe a new method of comparing different climate forcing agents (e.g., CO2, CH4, and solar irradiance) that avoids many of the ambiguities introduced by temperature-related climate feedbacks. This is achieved by introducing an explicit feedback loop external to the climate model that adjusts one forcing agent to balance another while keeping global mean surface temperature constant. Compared to current approaches, this method has two main advantages: (i) the need to define radiative forcing is bypassed and (ii) by maintaining roughly constant global mean temperature, the effects of state dependence on internal feedback strengths are minimized. We demonstrate this approach for several different forcing agents and derive the relationships between these forcing agents in two climate models; comparisons between forcing agents are highly linear in concordance with predicted functional forms. Transitivity of the relationships between the forcing agents appears to hold within a wide range of forcing. The relationships between the forcing agents obtained from this method are consistent across both models but differ from relationships that would be obtained from calculations of radiative forcing, highlighting the importance of controlling for surface temperature feedback effects when separating radiative forcing and climate response.

  18. Atmospheric Climate Model Experiments Performed at Multiple Horizontal Resolutions

    SciTech Connect

    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.

  19. Washington State Nursing Home Administrator Model Curriculum. Final Report.

    ERIC Educational Resources Information Center

    Cowan, Florence Kelly

    The course outlines presented in this final report comprise a proposed Fort Steilacoom Community College curriculum to be used as a statewide model two-year associate degree curriculum for nursing home administrators. The eight courses described are introduction to nursing, home administration, financial management of nursing homes, nursing home…

  20. Final Report Fermionic Symmetries and Self consistent Shell Model

    SciTech Connect

    Larry Zamick

    2008-11-07

    In this final report in the field of theoretical nuclear physics we note important accomplishments.We were confronted with "anomoulous" magnetic moments by the experimetalists and were able to expain them. We found unexpected partial dynamical symmetries--completely unknown before, and were able to a large extent to expain them.The importance of a self consistent shell model was emphasized.

  1. Regional climate modeling of heat stress, frost, and water stress events in the agricultural region of Southwest Western Australia under the current climate and future climate scenarios.

    NASA Astrophysics Data System (ADS)

    Kala, Jatin; Lyons, Tom J.; Abbs, Deborah J.; Foster, Ian J.

    2010-05-01

    Heat stress, frost, and water stress events have significant impacts on grain quality and production within the agricultural region (wheat-belt) of Southwest Western Australia (SWWA) (Cramb, 2000) and understanding how the frequency and intensity of these events will change in the future is crucial for management purposes. Hence, the Regional Atmospheric Modeling System (Pielke et al, 1992) (RAMS Version 6.0) is used to simulate the past 10 years of the climate of SWWA at a 20 km grid resolution by down-scaling the 6-hourly 1.0 by 1.0 degree National Center for Environmental Prediction Final Analyses from December 1999 to Present. Daily minimum and maximum temperatures, as well as daily rainfall are validated against observations. Simulations of future climate are carried out by down-scaling the Commonwealth Scientific and Industrial Research Organization (CSIRO) Mark 3.5 General Circulation Model (Gordon et al, 2002) for 10 years (2046-2055) under the SRES A2 scenario using the Cubic Conformal Atmospheric Model (CCAM) (McGregor and Dix, 2008). The 6-hourly CCAM output is then downscaled to a 20 km resolution using RAMS. Changes in extreme events are discussed within the context of the continued viability of agriculture in SWWA. Cramb, J. (2000) Climate in relation to agriculture in south-western Australia. In: The Wheat Book (Eds W. K. Anderson and J. R. Garlinge). Bulletin 4443. Department of Agriculture, Western Australia. Gordon, H. B., Rotstayn, L. D., McGregor, J. L., Dix, M. R., Kowalczyk, E. A., O'Farrell, S. P., Waterman, L. J., Hirst, A. C., Wilson, S. G., Collier, M. A., Watterson, I. G., and Elliott, T. I. (2002). The CSIRO Mk3 Climate System Model [Electronic publication]. Aspendale: CSIRO Atmospheric Research. (CSIRO Atmospheric Research technical paper; no. 60). 130 p McGregor, J. L., and Dix, M. R., (2008) An updated description of the conformal-cubic atmospheric model. High Resolution Simulation of the Atmosphere and Ocean, Hamilton, K. and Ohfuchi

  2. Photovoltaic subsystem marketing and distribution model: programming manual. Final report

    SciTech Connect

    Not Available

    1982-07-01

    Complete documentation of the marketing and distribution (M and D) computer model is provided. The purpose is to estimate the costs of selling and transporting photovoltaic solar energy products from the manufacturer to the final customer. The model adjusts for the inflation and regional differences in marketing and distribution costs. The model consists of three major components: the marketing submodel, the distribution submodel, and the financial submodel. The computer program is explained including the input requirements, output reports, subprograms and operating environment. The program specifications discuss maintaining the validity of the data and potential improvements. An example for a photovoltaic concentrator collector demonstrates the application of the model.

  3. Agent Model Development for Assessing Climate-Induced Geopolitical Instability.

    SciTech Connect

    Boslough, Mark B.; Backus, George A.

    2005-12-01

    We present the initial stages of development of new agent-based computational methods to generate and test hypotheses about linkages between environmental change and international instability. This report summarizes the first year's effort of an originally proposed three-year Laboratory Directed Research and Development (LDRD) project. The preliminary work focused on a set of simple agent-based models and benefited from lessons learned in previous related projects and case studies of human response to climate change and environmental scarcity. Our approach was to define a qualitative model using extremely simple cellular agent models akin to Lovelock's Daisyworld and Schelling's segregation model. Such models do not require significant computing resources, and users can modify behavior rules to gain insights. One of the difficulties in agent-based modeling is finding the right balance between model simplicity and real-world representation. Our approach was to keep agent behaviors as simple as possible during the development stage (described herein) and to ground them with a realistic geospatial Earth system model in subsequent years. This work is directed toward incorporating projected climate data--including various C02 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report--and ultimately toward coupling a useful agent-based model to a general circulation model.3

  4. A Final Approach Trajectory Model for Current Operations

    NASA Technical Reports Server (NTRS)

    Gong, Chester; Sadovsky, Alexander

    2010-01-01

    Predicting accurate trajectories with limited intent information is a challenge faced by air traffic management decision support tools in operation today. One such tool is the FAA's Terminal Proximity Alert system which is intended to assist controllers in maintaining safe separation of arrival aircraft during final approach. In an effort to improve the performance of such tools, two final approach trajectory models are proposed; one based on polynomial interpolation, the other on the Fourier transform. These models were tested against actual traffic data and used to study effects of the key final approach trajectory modeling parameters of wind, aircraft type, and weight class, on trajectory prediction accuracy. Using only the limited intent data available to today's ATM system, both the polynomial interpolation and Fourier transform models showed improved trajectory prediction accuracy over a baseline dead reckoning model. Analysis of actual arrival traffic showed that this improved trajectory prediction accuracy leads to improved inter-arrival separation prediction accuracy for longer look ahead times. The difference in mean inter-arrival separation prediction error between the Fourier transform and dead reckoning models was 0.2 nmi for a look ahead time of 120 sec, a 33 percent improvement, with a corresponding 32 percent improvement in standard deviation.

  5. Performance evaluation of a non-hydrostatic regional climate model over the Mediterranean/Black Sea area and climate projections for the XXI century

    NASA Astrophysics Data System (ADS)

    Mercogliano, Paola; Bucchignani, Edoardo; Montesarchio, Myriam; Zollo, Alessandra Lucia

    2013-04-01

    . A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate trend but also extremes of the present and future climate, in terms of temperature, precipitation and wind.

  6. Why is the choice of future climate scenarios for species distribution modelling important?

    PubMed

    Beaumont, Linda J; Hughes, Lesley; Pitman, A J

    2008-11-01

    Species distribution models (SDMs) are common tools for assessing the potential impact of climate change on species ranges. Uncertainty in SDM output occurs due to differences among alternate models, species characteristics and scenarios of future climate. While considerable effort is being devoted to identifying and quantifying the first two sources of variation, a greater understanding of climate scenarios and how they affect SDM output is also needed. Climate models are complex tools: variability occurs among alternate simulations, and no single 'best' model exists. The selection of climate scenarios for impacts assessments should not be undertaken arbitrarily - strengths and weakness of different climate models should be considered. In this paper, we provide bioclimatic modellers with an overview of emissions scenarios and climate models, discuss uncertainty surrounding projections of future climate and suggest steps that can be taken to reduce and communicate climate scenario-related uncertainty in assessments of future species responses to climate change.

  7. Chemistry-Climate Models of the Stratosphere

    NASA Technical Reports Server (NTRS)

    Austin, J.; Shindell, D.; Bruehl, C.; Dameris, M.; Manzini, E.; Nagashima, T.; Newman, P.; Pawson, S.; Pitari, G.; Rozanov, E.; Bhartia, P. K. (Technical Monitor)

    2001-01-01

    Over the last decade, improved computer power has allowed three-dimensional models of the stratosphere to be developed that can be used to simulate polar ozone levels over long periods. This paper compares the meteorology between these models, and discusses the future of polar ozone levels over the next 50 years.

  8. Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) Final Report

    SciTech Connect

    Williams, Dean N.

    2014-05-19

    A partnership across government, academic, and private sectors has created a novel system that enables climate researchers to solve current and emerging data analysis and visualization challenges. The Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) software project utilizes the Python application programming interface (API) combined with C/C++/Fortran implementations for performance-critical software that offers the best compromise between "scalability" and “ease-of-use.” The UV-CDAT system is highly extensible and customizable for high-performance interactive and batch visualization and analysis for climate science and other disciplines of geosciences. For complex, climate data-intensive computing, UV-CDAT’s inclusive framework supports Message Passing Interface (MPI) parallelism as well as taskfarming and other forms of parallelism. More specifically, the UV-CDAT framework supports the execution of Python scripts running in parallel using the MPI executable commands and leverages Department of Energy (DOE)-funded general-purpose, scalable parallel visualization tools such as ParaView and VisIt. This is the first system to be successfully designed in this way and with these features. The climate community leverages these tools and others, in support of a parallel client-server paradigm, allowing extreme-scale, server-side computing for maximum possible speed-up.

  9. The Mars Climate Orbiter arrives at KSC to begin final preparations for launch

    NASA Technical Reports Server (NTRS)

    1998-01-01

    The Mars Climate Orbiter spacecraft is moved onto a flatbed for transport to the Spacecraft Assembly and Encapsulation Facility-2 (SAEF-2). It arrived at KSC's Shuttle Landing Facility aboard an Air Force C-17 cargo plane early this morning following its flight from the Lockheed Martin Astronautics plant in Denver, Colo. When it arrives at the red planet, the Mars Climate Orbiter will primarily support its companion Mars Polar Lander spacecraft, planned for launch on Jan. 3, 1999. After that, the Mars Climate Orbiter's instruments will monitor the Martian atmosphere and image the planet's surface on a daily basis for one Martian year (1.8 Earth years). It will observe the appearance and movement of atmospheric dust and water vapor, as well as characterize seasonal changes on the surface. The detailed images of the surface features will provide important clues to the planet's early climate history and give scientists more information about possible liquid water reserves beneath the surface. The scheduled launch date for the Mars Climate Orbiter is Dec. 10, 1998, on a Delta II 7425 rocket.

  10. The Mars Climate Orbiter arrives at KSC to begin final preparations for launch

    NASA Technical Reports Server (NTRS)

    1998-01-01

    The Mars Climate Orbiter spacecraft is moved into the Spacecraft Assembly and Encapsulation Facility-2 (SAEF-2) in KSC's industrial area. It arrived at the Shuttle Landing Facility aboard an Air Force C-17 cargo plane early this morning following its flight from the Lockheed Martin Astronautics plant in Denver, Colo. When it arrives at the red planet, the Mars Climate Orbiter will primarily support its companion Mars Polar Lander spacecraft, planned for launch on Jan. 3, 1999. After that, the Mars Climate Orbiter's instruments will monitor the Martian atmosphere and image the planet's surface on a daily basis for one Martian year (1.8 Earth years). It will observe the appearance and movement of atmospheric dust and water vapor, as well as characterize seasonal changes on the surface. The detailed images of the surface features will provide important clues to the planet's early climate history and give scientists more information about possible liquid water reserves beneath the surface. The scheduled launch date for the Mars Climate Orbiter is Dec. 10, 1998, on a Delta II 7425 rocket.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Horton, Radley M.

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

  13. Climate Change, Feedback-Modelling, and Water Resources

    NASA Astrophysics Data System (ADS)

    Davies, E. G.; Simonovic, S. P.

    2008-05-01

    Global change research has generally followed a driving scenario-complex model approach, in which a set of projections provide input data that force the behaviour of an associated complex model. This approach neglects the role of interconnections -- or feedbacks -- between subsystems in determining the evolution of the system as a whole. However, another approach, called integrated assessment modelling (IAM), is available. In IAM, socio- economic adaptation and mitigation efforts become part of the actual physical process of climate change: changes in one sector lead to changes in another through causal, feedback relationships. The physical basis of connections between climate change and the hydrological cycle is already well-understood. Our research, using an eight-sector model of the global society-biosphere-climate system, demonstrates that hydrological and other elements of the socio-economic system are likewise tightly connected, and that their relationship has important implications for both water resources and for the rest of the system. The three water sectors in the model simulate water withdrawals and consumption at a global level in terms of domestic, industrial, and agricultural use, and incorporate wastewater production, treatment, and reuse. Other model sectors include the global climate, carbon cycle, economic, population, and land-use systems. Experimental results indicate that surface water availability and water quality play critical roles in long-term socio- economic wellbeing. For the presentation, we will demonstrate, in general terms, the effects of climate change and other socio-economic changes on water resources and the feedback effects of water-related changes on the larger model. In particular, we will focus on changing water use over time, and on the influence of wastewater treatment and reuse policies on water scarcity levels.

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

    NASA Astrophysics Data System (ADS)

    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.

  15. The climate responses of tropical and boreal ecosystems with an improved land surface model (JULES)

    NASA Astrophysics Data System (ADS)

    Harper, Anna; Friedlingstein, Pierre; Cox, Peter; Wiltshire, Andy; Jones, Chris

    2016-04-01

    The Joint UK Land Environment Simulator (JULES) is the land surface of the next generation UK Earth System Model (UKESM1). Recently, JULES was updated with new plant functional types and physiology based on a global plant trait database. These developments improved the simulation of terrestrial gross and net primary productivity on local and global scales, and enabled a more realistic representation of the global distribution of vegetation. In this study, we explore the present-day distribution of ecosystems and their vulnerability to climate change in JULES with these improvements, focusing on tropical and boreal ecosystems. Changes to these ecosystems will have implications for biogeophysical and biogeochemical feedbacks to climate change and need to be understood. First, we examine the simulated and observed rainforest-savannah boundary, which is strongly related to annual precipitation and the maximum climatological water deficit. Second, we assess the length of growing season and biomass stored in boreal ecosystems, where 20th century warming has likely extended the growing season. In each case, we first evaluate the ability of JULES to capture observed climate-vegetation relationships and trends. Finally, we run JULES to 2100 using climate data from 3 models and 2 RCP scenarios, and examine potential 21st century changes to these ecosystems. For example, do the tropical forests shrink in response to changes in tropical rainfall seasonality? And, how does the composition of boreal ecosystems change in response to climate warming? Given the potential for climate feedbacks and the inherent value in these ecosystems, it is essential to assess their responses to a range of climate change scenarios.

  16. An Interactive Multi-Model for Consensus on Climate Change

    SciTech Connect

    Kocarev, Ljupco

    2014-07-02

    This project purports to develop a new scheme for forming consensus among alternative climate models, that give widely divergent projections as to the details of climate change, that is more intelligent than simply averaging the model outputs, or averaging with ex post facto weighting factors. The method under development effectively allows models to assimilate data from one another in run time with weights that are chosen in an adaptive training phase using 20th century data, so that the models synchronize with one another as well as with reality. An alternate approach that is being explored in parallel is the automated combination of equations from different models in an expert-system-like framework.

  17. Effect of flux adjustments on temperature variability in climate models

    NASA Astrophysics Data System (ADS)

    CMIP investigators; Duffy, P. B.; Bell, J.; Covey, C.; Sloan, L.

    2000-03-01

    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.

  18. Climate model biases and statistical downscaling for application in hydrologic model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Climate change impact studies use global climate model (GCM) simulations to define future temperature and precipitation. The best available bias-corrected GCM output was obtained from Coupled Model Intercomparison Project phase 5 (CMIP5). CMIP5 data (temperature and precipitation) are available in d...

  19. Values and uncertainties in the predictions of global climate models.

    PubMed

    Winsberg, Eric

    2012-06-01

    Over the last several years, there has been an explosion of interest and attention devoted to the problem of Uncertainty Quantification (UQ) in climate science-that is, to giving quantitative estimates of the degree of uncertainty associated with the predictions of global and regional climate models. The technical challenges associated with this project are formidable, and so the statistical community has understandably devoted itself primarily to overcoming them. But even as these technical challenges are being met, a number of persistent conceptual difficulties remain. So why is UQ so important in climate science? UQ, I would like to argue, is first and foremost a tool for communicating knowledge from experts to policy makers in a way that is meant to be free from the influence of social and ethical values. But the standard ways of using probabilities to separate ethical and social values from scientific practice cannot be applied in a great deal of climate modeling, because the roles of values in creating the models cannot be discerned after the fact-the models are too complex and the result of too much distributed epistemic labor. I argue, therefore, that typical approaches for handling ethical/social values in science do not work well here.

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

    ERIC Educational Resources Information Center

    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…

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  2. Modeling Shasta Dam operations to regulate temperatures for Chinook salmon under extreme climate and climate change

    NASA Astrophysics Data System (ADS)

    Dai, A.; Saito, L.; Sapin, J. R.; Rajagopalan, B.; Hanna, R. B.; Kauneckis, D. L.

    2014-12-01

    Chinook salmon populations have declined significantly after the construction of Shasta Dam on the Sacramento River in 1945 prevented them from spawning in the cold waters upstream. In 1994, the winter-run Chinook were listed under the Endangered Species Act and 3 years later the US Bureau of Reclamation began operating a temperature control device (TCD) on the dam that allows for selective withdrawal for downstream temperature control to promote salmon spawning while also maximizing power generation. However, dam operators are responsible to other interests that depend on the reservoir for water such as agriculture, municipalities, industry, and recreation. An increase in temperatures due to climate change may place additional strain on the ability of dam operations to maintain spawning habitat for salmon downstream of the dam. We examined the capability of Shasta Dam to regulate downstream temperatures under extreme climates and climate change by using stochastically generated streamflow, stream temperature, and weather inputs with a two-dimensional CE-QUAL-W2 model under several operational options. Operation performance was evaluated using degree days and cold pool volume (volume of water below a temperature threshold). Model results indicated that a generalized operations release schedule, in which release elevations varied over the year to match downstream temperature targets, performed best overall in meeting temperature targets while preserving cold pool volume. Releasing all water out the bottom throughout the year tended to meet temperature targets at the expense of depleting the cold pool, and releasing all water out uppermost gates preserved the cold pool, but released water that was too warm during the critical spawning period. With higher air temperatures due to climate change, both degree day and cold pool volume metrics were worse than baseline conditions, which suggests that Chinook salmon may be more negatively affected under climate change.

  3. Modelling mid-Pliocene climate with COSMOS

    NASA Astrophysics Data System (ADS)

    Stepanek, C.; Lohmann, G.

    2012-04-01

    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) and document the procedures which we applied to transfer the Pliocene Research, Interpretation and Synoptic Mapping Project (PRISM) 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 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.

  4. Modelling mid-Pliocene climate with COSMOS

    NASA Astrophysics Data System (ADS)

    Stepanek, C.; Lohmann, G.

    2012-10-01

    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 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.

  5. Genetically informed ecological niche models improve climate change predictions.

    PubMed

    Ikeda, Dana H; Max, Tamara L; Allan, Gerard J; Lau, Matthew K; Shuster, Stephen M; Whitham, Thomas G

    2017-01-01

    We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change.

  6. Treatment of Solar and Thermal Radiation in Global Climate Models

    NASA Astrophysics Data System (ADS)

    Lacis, A. A.; Oinas, V.

    2015-12-01

    It is the interaction of solar and thermal radiation with the climate system constituents that determines the prevailing climate on Earth. The principal radiative constituents of the climate system are clouds, aerosols, greenhouse gases, and the ground surface. Accurate rendering of their interaction with the incident solar radiation and the outgoing thermal radiation is required if a climate model is to be capable of simulating and predicting the complex changes that take place in the terrestrial climate system. In the GISS climate model, these radiative tasks are accomplished with a GCM radiation model that utilizes the correlated k-distribution treatment that closely matches Line-by-Line accuracy (Lacis and Oinas, 1991) for the gaseous absorbers, and an adaptation of the doubling/adding method (Lacis and Hansen, 1974) to compute multiple scattering by clouds and aerosols. The radiative parameters to model the spectral dependence of solar and longwave radiation (UV to microwave) utilizes Mie scattering and T-matrix calculations covering the broad range of particle sizes and compositions encountered in the climate system. Cloud treatment also incorporates an empirical representation of sub-grid inhomogeneity and space-time variability of cloud optical properties (derived from ISCCP data) that utilizes a Monte Carlo-based re-scaling parameterization of the cloud plane-parallel radiative parameters (Cairns et al, 2001). The longwave calculations compute correlated k-distribution radiances at three quadrature points (without scattering), and include the effects of cloud scattering in parameterized form for the outgoing and downwelling LW fluxes. For hygroscopic aerosols (e.g., sulfates, nitrates, sea salt), the effects of changing relative humidity on particle size and refractive index are explicitly taken into account. In this way, the GISS GCM radiation model calculates the SW and LW radiative fluxes, and the corresponding radiative heating and cooling rates in

  7. Model based climate information on drought risk in Africa

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  8. Final Report for "Interdecadal climate regime transition and its interaction with climate change in CMIP5 simulations" (DOE Grant DE-SC0005344)

    SciTech Connect

    Huang, Huei-Ping

    2013-12-10

    Large-amplitude interdecadal shifts of atmospheric and ocean states from one climate regime to another have been observed several times in the 20th century. They include the 1976 transition from cool tropical Pacific SST to warm tropical SST and the post-1998 reversal back to a cooler state. The transition events affect both atmospheric circulation and global water cycle. Because on decadal-to-interdecadal time scale the amplitude of the climate shift is comparable to the trend induced by anthropogenic greenhouse gas forcing, understanding the structure, statistics, and predictability of those events is critical for near-term climate projection. This study analyzed the statistics and predictability of the transition events in the CMIP5 climate model simulations by using a set of climate indices, including atmospheric angular momentum (AAM) and regionally integrated hydrological variables. A significant improvement in the simulated 20th century climatology of AAM is found in CMIP5, compared to earlier simulations in CMIP3. Nevertheless, the improvement in the simulated decadal-to-interdecadal variability in AAM is relatively minor. Systematic biases in the regional water cycle that exist in CMIP3 are found to also exist in CMIP5, although with slight improvements in the latter. Climate shift events with an amplitude comparable to the observed 1976 or 1998 event are found to rarely occur in the CMIP5 20th century simulations. In the 21st century simulations with increasing GHG concentration, the upward trend superimposed to natural variability slightly increases the frequency of occurrences of the large-amplitude events. Even so, 1976-like events remain rare in those runs. In an additional analysis of the CMIP5 Decadal Runs for the 20th century, it is found that the decadal predictability in terms of AAM is generally weak, with useful predictability mainly restricted to within ENSO time scale. Overall, this study showed promises in the improved performance of CMIP5

  9. Constructing realistic Szekeres models from initial and final data

    SciTech Connect

    Walters, Anthony; Hellaby, Charles E-mail: charles.hellaby@uct.ac.za

    2012-12-01

    The Szekeres family of inhomogeneous solutions, which are defined by six arbitrary metric functions, offers a wide range of possibilities for modelling cosmic structure. Here we present a model construction procedure for the quasispherical case using given data at initial and final times. Of the six arbitrary metric functions, the three which are common to both Szekeres and Lemaître-Tolman models are determined by the model construction procedure of Krasinski and Hellaby. For the remaining three functions, which are unique to Szekeres models, we derive exact analytic expressions in terms of more physically intuitive quantities — density profiles and dipole orientation angles. Using MATLAB, we implement the model construction procedure and simulate the time evolution.

  10. Organic acid modeling and model validation: Workshop summary. Final report

    SciTech Connect

    Sullivan, T.J.; Eilers, J.M.

    1992-08-14

    A workshop was held in Corvallis, Oregon on April 9--10, 1992 at the offices of E&S Environmental Chemistry, Inc. The purpose of this workshop was to initiate research efforts on the entitled ``Incorporation of an organic acid representation into MAGIC (Model of Acidification of Groundwater in Catchments) and testing of the revised model using Independent data sources.`` The workshop was attended by a team of internationally-recognized experts in the fields of surface water acid-bass chemistry, organic acids, and watershed modeling. The rationale for the proposed research is based on the recent comparison between MAGIC model hindcasts and paleolimnological inferences of historical acidification for a set of 33 statistically-selected Adirondack lakes. Agreement between diatom-inferred and MAGIC-hindcast lakewater chemistry in the earlier research had been less than satisfactory. Based on preliminary analyses, it was concluded that incorporation of a reasonable organic acid representation into the version of MAGIC used for hindcasting was the logical next step toward improving model agreement.

  11. A review on regional convection permitting climate modeling

    NASA Astrophysics Data System (ADS)

    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 <4 km, is that they better resolve complex orography and land use. The regional climate model COSMO-CLM is frequently applied for CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light

  12. BASINs 4.0 Climate Assessment Tool (CAT): Supporting Documentation and User's Manual (Final Report)

    EPA Science Inventory

    EPA announced the availability of the report, BASINS 4.0 Climate Assessment Tool (CAT): Supporting Documentation and User's Manual. This report was prepared by the EPA's Global Change Research Program (GCRP), an assessment-oriented program, that sits within the Office of R...

  13. Predictability and Diagnosis of Low Frequency Climate Processes in the Pacific, Final Technical Report

    SciTech Connect

    Niklas Schneider

    2009-06-17

    The report summarized recent findings with respect to Predictability and Diagnosis of Low Frequency Climate Processes in the Pacific, with focus on the dynamics of the Pacific Decadal Oscillation, oceanic adjustments and the coupled feedback in the western boundary current of the North and South Pacific, decadal dynamics of oceanic salinity, and tropical processes with emphasis on the Indonesian Throughflow.

  14. BASINS 4.0 CLIMATE ASSESSMENT TOOL (CAT): SUPPORTING DOCUMENTATION AND USER'S MANUAL (FINAL REPORT)

    EPA Science Inventory

    The U.S. Environmental Protection Agency’s Global Change Research Program (GCRP) is an assessment-oriented program within the Office of Research and Development that focuses on assessing how potential changes in climate and other global environmental stressors may impact water qu...

  15. CLIMATE CHANGE AND INTERACTING STRESSORS: IMPLICATIONS FOR CORAL REEF MANAGEMENT IN AMERICAN SAMOA (Final Report)

    EPA Science Inventory

    The purpose of this report is to provide the coral reef managers of American Samoa, as well as other coral reef managers in the Pacific region, with some management options to help enhance the capacity of local coral reefs to resist the negative effects of climate change.

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

    NASA Technical Reports Server (NTRS)

    Lau, William K. M.

    2002-01-01

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

  17. Regional Climate Modeling at ZAMG and climate impact assessment for European ecosystems

    NASA Astrophysics Data System (ADS)

    Anders, I.; Zuvela-Aloise, M.; Matulla, C.

    2010-09-01

    The Austrian society, policy, economy and environment request information on changes in the climate during the last years and especially for the near and remote future. Floodings, landslides, snow avalanches and storms belong to the natural hazards that highly impact Austria's socio-economic and environmental systems. In addition to already applied empirical regional modeling at ZAMG there was started dynamical regional climate modeling (RCM) with the COSMOS-CLM (CCLM, http://www.clm-community.eu/) at ZAMG in 2009. The main objective of the Austrian national project "reclip:century" (in cooperation with other Austrian Institutes) is to provide high resolved data sets of climate simulations for the GAR. A one-way double nesting approach is used. The domain used in the first step is Europe with a spatial resolution of 0.44° (50km). Within this simulation the GAR domain is nested having a resolution of 0.09° (10km). The output of these simulations will be evaluated within the project EVACLIM. This is to be done by comparing the output with a variety of regional scale observational datasets. The results of the simulations will be made available to the impact community. Within the international based project HABIT-CHANGE 10km-resolution climate scenarios will be generated. The data sets produced for two different regions the GAR and the Danube Delta - shall be used as a basis for the work of hydrology modelers and for the development of strategies for adaptation and mitigation Based on the CCLM simulations at ZAMG of about 0.03° (4km) spatial resolution for the Northeast of Austria, the project DISTURBANCE aims to develop integrated models for temperate Alpine forest ecosystems. Important tasks for the forest modeling are not only the assessment of changes in temperature, drought and windstorms but also the interactions between wind damages and bark beetle development which might impact the forest structure and its composition of species. In the project DATAPHEN

  18. An investigation of climate patterns on Earth-like planets using the NASA GISS global climate model II

    NASA Astrophysics Data System (ADS)

    Elowitz, Robert Mark

    To determine the capability of NASA's GISS GCM-II global climate model, the user-friendly EdGCM interface to the 3-D climate model code was evaluated by simulating global climate patterns that Earth-like planets may experience. The simulation scenarios involved different greenhouse gas emissions trends, planetary orbital parameters, and solar irradiance variations. It is found that the EdGCM interface to the GCM-II 3-D climate model is capable of studying climate patterns on hypothetical Earth-like planets, with some limitations involved. Studying extreme climate patterns on Earth-like planets as a function of planetary obliquity, orbital eccentricity, atmospheric composition, solar irradiance variations, and location with the host star's habitable zone is needed to determine whether such planets are habitable for life as we know it. Studying the behavior of climate on hypothetical Earth-like planet also provides insight into the future climate of our own planet. A database of climate models based on hypothetical Earth-like worlds will provide a valuable resource to the astrobiology community in support of future detections of exoplanets with masses, sizes, and composition similar to Earth. At present, most studies involved the use of 1-D, or 2-D climate models to explore planetary climate on Earth-like planets. This is due to the difficulty of using very complex 3-D climate model codes that typically have poor user interfaces or interfaces that are very difficult to use. EdGCM provides scientists with a user-friendly interface to a full 3-D climate model capable of simulating the climate on Earth-like planets. However, EdGCM is extremely limited in studying global climate on exo-Earth planets outside our solar system. The user is able to change the simulation initial conditions, including different greenhouse gas concentrations and their associated trends, solar irradiance and its trend over time, planetary obliquity and orbit eccentricity, and heliocentric

  19. Controls on the Archean climate system investigated with a global climate model.

    PubMed

    Wolf, E T; Toon, O B

    2014-03-01

    The most obvious means of resolving the faint young Sun paradox is to invoke large quantities of greenhouse gases, namely, CO2 and CH4. However, numerous changes to the Archean climate system have been suggested that may have yielded additional warming, thus easing the required greenhouse gas burden. Here, we use a three-dimensional climate model to examine some of the factors that controlled Archean climate. We examine changes to Earth's rotation rate, surface albedo, cloud properties, and total atmospheric pressure following proposals from the recent literature. While the effects of increased planetary rotation rate on surface temperature are insignificant, plausible changes to the surface albedo, cloud droplet number concentrations, and atmospheric nitrogen inventory may each impart global mean warming of 3-7 K. While none of these changes present a singular solution to the faint young Sun paradox, a combination can have a large impact on climate. Global mean surface temperatures at or above 288 K could easily have been maintained throughout the entirety of the Archean if plausible changes to clouds, surface albedo, and nitrogen content occurred.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Bauer, S. E.

    2009-12-01

    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 and especially the indirect aerosol 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. Those aerosol characteristics determine their role in direct and indirect aerosol forcing, as their chemical composition and size distribution determine their optical properties and cloud activation potential. A new detailed aerosol microphysical scheme, MATRIX, embedded within the global GISS modelE climate model includes the above processes that determine the lifecycle and climate impact of aerosols. This study presents a quantitative assessment and an uncertainty estimate of the impact of microphysical processes involving black carbon and its optical properties on aerosol cloud activation and radiative forcing. We calculate an anthropogenic net radiative forcing of -0.46 W/m2, relative to emission changes between 1750 and 2000. This study finds the direct and indirect aerosol effect to be very sensitivity towards the size distribution of the emitted black and organic particles. The total net radiative forcing can vary between -0.26 to -0.47 W/m2. The models radiation transfer scheme reacts even more sensitive to black carbon core shell structure assumptions. Assuming that sulfates, nitrates and secondary organics can lead to a coating shell around a black carbon core can turn the overall net radiative forcing from a negative to a positive number. In the light of these sensitivities, black carbon mitigation experiments can show no to up to very significant impact to slower global warming.

  3. Climatic impact of Amazon deforestation - a mechanistic model study

    SciTech Connect

    Ning Zeng; Dickinson, R.E.; Xubin Zeng

    1996-04-01

    Recent general circulation model (GCM) experiments suggest a drastic change in the regional climate, especially the hydrological cycle, after hypothesized Amazon basinwide deforestation. To facilitate the theoretical understanding os such a change, we develop an intermediate-level model for tropical climatology, including atmosphere-land-ocean interaction. The model consists of linearized steady-state primitive equations with simplified thermodynamics. A simple hydrological cycle is also included. Special attention has been paid to land-surface processes. It generally better simulates tropical climatology and the ENSO anomaly than do many of the previous simple models. The climatic impact of Amazon deforestation is studied in the context of this model. Model results show a much weakened Atlantic Walker-Hadley circulation as a result of the existence of a strong positive feedback loop in the atmospheric circulation system and the hydrological cycle. The regional climate is highly sensitive to albedo change and sensitive to evapotranspiration change. The pure dynamical effect of surface roughness length on convergence is small, but the surface flow anomaly displays intriguing features. Analysis of the thermodynamic equation reveals that the balance between convective heating, adiabatic cooling, and radiation largely determines the deforestation response. Studies of the consequences of hypothetical continuous deforestation suggest that the replacement of forest by desert may be able to sustain a dry climate. Scaling analysis motivated by our modeling efforts also helps to interpret the common results of many GCM simulations. When a simple mixed-layer ocean model is coupled with the atmospheric model, the results suggest a 1{degrees}C decrease in SST gradient across the equatorial Atlantic Ocean in response to Amazon deforestation. The magnitude depends on the coupling strength. 66 refs., 16 figs., 4 tabs.

  4. Radiative heating in global climate models

    SciTech Connect

    Baer, F.; Arsky, N.; Rocque, K.

    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. An Improved Radiative Transfer Model for Climate Calculations

    NASA Technical Reports Server (NTRS)

    Bergstrom, Robert W.; Mlawer, Eli J.; Sokolik, Irina N.; Clough, Shepard A.; Toon, Owen B.

    1998-01-01

    This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications, we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  7. Development of lake parametrization in the INMCM climate model

    NASA Astrophysics Data System (ADS)

    Bogomolov, V.; Stepanenko, V.; Volodin, E.

    2016-11-01

    Land surface schemes (LSS or terrestrial models) are a crucial component of both Numerical Weather Prediction (NWP) systems and climate models. An important land- surface type is lakes. This paper presents the mechanism of incorporation of a model LAKE into a coupled general circulation model of the atmosphere and ocean INMCM4, with a space resolution 2° to 1.5° and 21 levels in height, with two-way interaction. A new map for 14 land types distribution was created using a digital map of inland waters for the entire globe. The digital map of water bodies includes the fraction of lake area on the land surface, and the average depth of water bodies, both on the grid of the climate model. This digital map is based on a dataset consisting of 14 000 freshwater lakes. In order to increase the time step in the LAKE model, the k-ε parameterization has been replaced by the parameterization of Henderson-Sellers. With the amended INMCM4 model, numerical experiments were carried out to simulate global climate during the second half of the XX century. The effects of the new lake parameterization on the surface temperature and heat fluxes are analyzed.

  8. Climate Change Student Summits: A Model that Works (Invited)

    NASA Astrophysics Data System (ADS)

    Huffman, L. T.

    2013-12-01

    The C2S2: Climate Change Student Summit project has completed four years of activities plus a year-long longitudinal evaluation with demonstrated positive impacts beyond the life of the project on both students and teachers. This presentation will share the lessons learned about implementing this climate change science education program and suggest that it is a successful model that can be used to scale up from its Midwestern roots to achieve measurable national impact. A NOAA Environmental Literacy grant allowed ANDRILL (ANtarctic geological DRILLing) to grow a 2008 pilot program involving 2 Midwestern sites, to a program 4 years later involving 10 sites. The excellent geographical coverage included 9 of the U.S. National Climate Assessment regions defined by the U.S. Global Change Research Program. Through the delivery of two professional development (PD) workshops, a unique opportunity was provided for both formal and informal educators to engage their classrooms/audiences in understanding the complexities of climate change. For maximum contact hours, the PD experience was extended throughout the school year through the use of an online grouphub. Student teams were involved in a creative investigative science research and presentation experience culminating in a Climate Change Student Summit, an on-site capstone event including a videoconference connecting all sites. The success of this program was based on combining multiple aspects, such as encouraging the active involvement of scientists and early career researchers both in the professional development workshops and in the Student Summit. Another key factor was the close working relationships between informal and formal science entities, including involvement of informal science learning facilities and informal science education leaders. The program also created cutting-edge curriculum materials titled the ELF, (Environmental Literacy Framework with a focus on climate change), providing an earth systems

  9. Ensemble of regional climate model projections for Ireland

    NASA Astrophysics Data System (ADS)

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

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

    2016-09-01

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

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

    SciTech Connect

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  14. Construction of embedding for empirical prognostic models of climate

    NASA Astrophysics Data System (ADS)

    Feigin, A. M.; Mukhin, D.; Gavrilov, A.; Loskutov, E. M.

    2015-12-01

    Empirical approach to modeling and forecasting complex dynamical systems becomes more and more popular in climate science because of two reasons: (i) not confidence reproducing and forecasting some of key climate modes by existing global climate models, and (ii) increasing number and duration of climatic time series which can be considered as a source of information about dynamical laws underlying observational variability. Such an approach is aimed to construction of prognostic models by way of direct analysis of data without involving any detailed physical equations. We developed a method for empirical modeling basing on reconstruction of prognostic evolution operator in a form of random dynamical system [1] - stochastic mapping the current state of the system to the next one. The most crucial point in application of the method to the analysis of real climatic data is the construction of proper embedding: the optimal set of variables - "principal modes" - determining the phase space the model works in. This task is non-trivial due to huge dimension of time series of typical space-distributed climatic fields. We outline two main features these modes should have to capture the main dynamical properties of the system: (i) capturing teleconnections in the atmosphere-ocean system by taking into account time-lagged couplings in data and (ii) reflecting the nonlinear interactions between the time series at different grid points. In this report we present the methodology of empirical forecasting which includes the construction of an embedding on the basis of the above principals: multichannel singular spectrum analysis (MSSA) together with nonlinear principal component analysis (NPCA) are used for phase space construction from data. The proposed methodology is applied to the analysis of sea surface temperature and atmospheric pressure fields. Capabilities to predict various indices of climate (such as SOI, PDO, NAO, NTA, etc.) is demonstrated. This research was supported

  15. Modeling the Effects of Climate Change on Whitebark Pine Along the Pacific Crest Trail

    NASA Astrophysics Data System (ADS)

    Anderson, R. S.; Nguyen, A.; Gill, N.; Kannan, S.; Patadia, N.; Meyer, M.; Schmidt, C.

    2012-12-01

    The Pacific Crest Trail (PCT), one of eight National Scenic Trails, stretches 2,650 miles from Mexico to the Canadian border. At high elevations along this trail, within Inyo and Sierra National Forests, populations of whitebark pine (Pinus albicaulis) have been diminishing due to infestation of the mountain pine beetle (Dendroctonus ponderosae) and are threatened due to a changing climate. Understanding the current and future condition of whitebark pine is a primary goal of forest managers due to its high ecological and economic importance, and it is currently a candidate for protection under the Endangered Species Act (ESA). Using satellite imagery, we analyzed the rate and spatial extent of whitebark pine tree mortality from 1984 to 2011 using the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) program. Climate data, soil properties, and biological features of the whitebark pine were incorporated in the Physiological Principles to Predict Growth (3-PG) model to predict future rates of growth and assess its applicability in modeling natural whitebark pine processes. Finally, the Random Forest algorithm was used with topographic data alongside recent and future climate data from the IPCC A2 and B1 climate scenarios for the years 2030, 2060, and 2090 to model the future distribution of whitebark pine. LandTrendr results indicate beetle related mortality covering 14,940 km2 of forest, 2,880 km2 of which are within whitebark pine forest. By 2090, our results show that under the A2 climate scenario, whitebark pine suitable habitat may be reduced by as much as 99.97% by the year 2090 within our study area. Under the B1 climate scenario, which has decreased CO2 emissions, 13.54% more habitat would be preserved in 2090.

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

    NASA Astrophysics Data System (ADS)

    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 (<500m3/capita/year) by another 40% (according to some models, more than 100%) compared to the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between present--day and 2°C, while indicators of very severe impacts increase unabated beyond 2°C. At the same time, the study highlights large uncertainties associated with these estimates, with both GCMs and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development. Relative change in annual discharge at 2°C compared to present-day, under RCP8.5, from an ensemble of 11 global hydrological models (GHMs) driven by five

  17. Forecasting energy security impacts of biofuels using regional climate models

    NASA Astrophysics Data System (ADS)

    Yang, X.; Campbell, E.; Snyder, M. A.; Sloan, L.; Kueppers, L. M.

    2010-12-01

    Production of biofuels in the U.S. is growing rapidly, with corn providing the dominant feedstock for current production and corn stover potentially providing a critical feedstock source for future cellulosic ethanol production. While production of domestic biofuels is thought to improve energy security, future changes in climate may impact crop yield variability and erode the energy security benefits of biofuels. Here we examine future yield variability for corn and soy using RegCM regional climate data from NARCAPP, historical agronomic data, and statistical models of yield variability. Our simulations of historical yield anomalies using monthly temperature and precipitation data from RegCM show robust relationships to observed yield anomalies. Simulations of future yield anomalies show increased yield variability relative to historical yield variability in the region of high corn production. Since variability in energy supply is a critical concern for energy security we suggest that the climate-induced yield variability on critical biofuels feedstocks be explored more widely.

  18. Potential climatic impacts of vegetation change: A regional modeling study

    USGS Publications Warehouse

    Copeland, J.H.; Pielke, R.A.; Kittel, T.G.F.

    1996-01-01

    The human species has been modifying the landscape long before the development of modern agrarian techniques. Much of the land area of the conterminous United States is currently used for agricultural production. In certain regions this change in vegetative cover from its natural state may have led to local climatic change. A regional climate version of the Colorado State University Regional Atmospheric Modeling System was used to assess the impact of a natural versus current vegetation distribution on the weather and climate of July 1989. The results indicate that coherent regions of substantial changes, of both positive and negative sign, in screen height temperature, humidity, wind speed, and precipitation are a possible consequence of land use change throughout the United States. The simulated changes in the screen height quantities were closely related to changes in the vegetation parameters of albedo, roughness length, leaf area index, and fractional coverage. Copyright 1996 by the American Geophysical Union.

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

    NASA Technical Reports Server (NTRS)

    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.

  20. Modeling Feedbacks Between Water and Vegetation in the Climate System

    NASA Technical Reports Server (NTRS)

    Miller, James R.; Russell, Gary L.; Hansen, James E. (Technical Monitor)

    2001-01-01

    Not only is water essential for life on earth, but life itself affects the global hydrologic cycle and consequently the climate of the planet. Whether the global feedbacks between life and the hydrologic cycle tend to stabilize the climate system about some equilibrium level is difficult to assess. We use a global climate model to examine how the presence of vegetation can affect the hydrologic cycle in a particular region. A control for the present climate is compared with a model experiment in which the Sahara Desert is replaced by vegetation in the form of trees and shrubs common to the Sahel region. A second model experiment is designed to identify the separate roles of two different effects of vegetation, namely the modified albedo and the presence of roots that can extract moisture from deeper soil layers. The results show that the presence of vegetation leads to increases in precipitation and soil moisture in western Sahara. In eastern Sahara, the changes are less clear. The increase in soil moisture is greater when the desert albedo is replaced by the vegetation albedo than when both the vegetation albedo and roots are added. The effect of roots is to withdraw water from deeper layers during the dry season. One implication of this study is that the insertion of vegetation into the Sahara modifies the hydrologic cycle so that the vegetation is more likely to persist than initially.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    NASA Astrophysics Data System (ADS)

    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

  3. A Gaussian graphical model approach to climate networks

    SciTech Connect

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

    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.

  4. Failure of climate regulation in a geophysiological model

    NASA Astrophysics Data System (ADS)

    Lovelock, James E.; Kump, Lee R.

    1994-06-01

    THERE has been much debate about how the Earth responds to changes in climate-specifically, how feedbacks involving the biota change with temperature. There is in particular an urgent need to understand the extent of coupling and feedback between plant growth, global temperature and enhanced atmospheric concentrations of greenhouse gases. Here we present a simple, but we hope qualitatively realistic, analysis of the effects of temperature change on the feedbacks induced by changes in surface distribution of marine algae and land plants. We assume that algae affect climate primarily through their emission of dimethyl sulphide1-8 (which may influence cloud albedo), and that land plants do so by fixation of atmospheric CO2 (refs 9-12). When we consider how the planetary area occupied by these two ecosystems varies with temperature, we find that a simple model based on these ideas exhibits three feedback regimes. In glacial conditions, both marine and terrestrial ecosystems provide a negative feedback. As the temperature rises to present-day values, algae lose their strong climate influence, but terrestrial ecosystems continue to regulate the climate. But if global mean temperatures rise above about 20 °C, both terrestrial and marine ecosystems are in positive feedback, amplifying any further increase of temperature. As the latter conditions have existed in the past, we propose that other climate-regulating mechanisms must operate in this warm regime.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  6. The range of regional climate change projections in central Europe: How to deal with the spread of climate model results?

    NASA Astrophysics Data System (ADS)

    Rechid, D.; Jacob, D.; Podzun, R.

    2010-09-01

    The regional climate change projections for central Europe in the 21st century show a large spread of simulated temperature and precipitation trends due to natural variability and modelling uncertainties. The questions are how to extract robust climate change signals and how to transfer the range of possible temperature and precipitation trends to climate change impact studies and adaptation strategies? Within the BMBF funded research priority "KLIMZUG - Managing Climate Change in the Regions of the Future", innovative strategies for adaptation to climate change are developed. The funding activity particularly stresses the regional aspect since the global problem climate change must be tackled by measures at regional and local level. The focus of the joint project "KLIMZUG-NORD - Strategic Approaches to Climate Change Adaptation in the Hamburg Metropolitan Region" is to establish an interdisciplinary network between the research, administrative and economic sectors in this region. The regional climate change information is provided by the Max-Planck-Institute for Meteorology as input for climate change impact assessments. The cross-sectional task "climate change" is to prepare consistent regional climate data and to advise on its reasonable use. The project benefits from the results of the ENSEMBLES EU project, in which an extensive set of regional climate change simulations at 50 km horizontal resolution were performed for 1950 to 2100. For impact studies, higher horizontal resolutions are required. With the regional climate model REMO, three global climate change scenarios from ECHAM5-MPIOM were downscaled to 50 km with three ensemble members each. In a second step, some members were further downscaled to 10 km for central Europe. For the global and regional simulations, the trends were analysed and indicate a strong internal climate variability, which further increases the range of climate change simulation results. This all recommends the application of 1

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

    PubMed

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

    2017-03-01

    A potato crop multimodel assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low-input (Chinoli, Bolivia and Gisozi, Burundi)- and high-input (Jyndevad, Denmark and Washington, United States) management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield decreased from 38% to 20% between P1 and P2. Model uncertainty increased with interannual variability, and predictions for all agronomic variables were significantly different from one model to another (P < 0.001). Uncertainty averaged 15% higher for low- vs. high-input sites, with larger differences observed for evapotranspiration (ET), nitrogen uptake, and water use efficiency as compared to dry matter. A minimum of five partial, or three full, calibrated models was required for an ensemble approach to keep variability below that of common field variation. Model variation was not influenced by change in carbon dioxide (C), but increased as much as 41% and 23% for yield and ET, respectively, as temperature (T) or rainfall (W) moved away from historical levels. Increases in T accounted for the highest amount of uncertainty, suggesting that methods and parameters for T sensitivity represent a considerable unknown among models. Using median model ensemble values, yield increased on average 6% per 100-ppm C, declined 4.6% per °C, and declined 2% for every 10% decrease in rainfall (for nonirrigated sites). Differences in predictions due to model representation of light utilization were significant (P < 0.01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be

  8. Differences between seasonal and mean annual energy balance model calculations of climate and climate sensitivity

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

    The paper extends a simple Budyko-Sellers mean annual energy balance climate model with diffusive transport to include a seasonal cycle. In the model the latitudinal distribution of the zonal average surface temperature is represented by Legendre polynomials and its time-dependence by a Fourier sine-cosine series, and it has three parameters adjusted so that the observed amplitudes of the Northern Hemisphere zonal mean surface temperature are recovered. The seasonal model is used to reveal how the annual mean climate and the sensitivity to changes in incident radiation differ from the predictions obtained with the corresponding mean annual model. The distribution of the incident solar radiation in the models is shown to be insensitive to changes in the eccentricity and the longitude of perihelion and sensitive only to changes in the obliquity of the earth, and for past orbital changes both the seasonal and the mean annual model fail to produce glacial advances of the magnitude that are thought to have occurred.

  9. Can existing climate models be used to study anthropogenic changes in tropical cyclone climate

    SciTech Connect

    Broccoli, A.J.; Manabe, S.

    1990-10-01

    The utility of current generation climate models for studying the influence of greenhouse warming on the tropical storm climatology is examined. A method developed to identify tropical cyclones is applied to a series of model integrations. The global distribution of tropical storms is simulated by these models in a generally realistic manner. While the model resolution is insufficient to reproduce the fine structure of tropical cyclones, the simulated storms become more realistic as resolution is increased. To obtain a preliminary estimate of the response of the tropical cyclone climatology, CO{sub 2} was doubled using models with varying cloud treatments and different horizontal resolutions. In the experiment with prescribed cloudiness, the number of storm-days, a combined measure of the number and duration of tropical storms, undergoes a statistically significant reduction of the number of storm-days is indicated in the experiment with cloud feedback. In both cases the response is independent of horizontal resolution. While the inconclusive nature of these experimental results highlights the uncertainties that remain in examining the details of greenhouse-gas induced climate change, the ability of the models to qualitatively simulate the tropical storm climatology suggests that they are appropriate tools for this problem.

  10. GFDL's unified regional-global weather-climate modeling system with variable resolution capability for severe weather predictions and regional climate simulations

    NASA Astrophysics Data System (ADS)

    Lin, S. J.

    2015-12-01

    The NOAA/Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions (e.g., tornado outbreak events and cat-5 hurricanes) and ultra-high-resolution (1-km) regional climate simulations within a consistent global modeling framework. The fundation of this flexible regional-global modeling system is the non-hydrostatic extension of the vertically Lagrangian dynamical core (Lin 2004, Monthly Weather Review) known in the community as FV3 (finite-volume on the cubed-sphere). Because of its flexability and computational efficiency, the FV3 is one of the final candidates of NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched (single) grid capability, a two-way (regional-global) multiple nested grid capability, and the combination of the stretched and two-way nests, so as to make convection-resolving regional climate simulation within a consistent global modeling system feasible using today's High Performance Computing System. One of our main scientific goals is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornadoes using a global model that was originally designed for century long climate simulations. As a unified weather-climate modeling system, we evaluated the performance of the model with horizontal resolution ranging from 1 km to as low as 200 km. In particular, for downscaling studies, we have developed various tests to ensure that the large-scale circulation within the global varaible resolution system is well simulated while at the same time the small-scale can be accurately captured

  11. Biogenic Aerosols—Effects on Clouds and Climate (BAECC) Final Campaign Summary

    SciTech Connect

    Petäjä, T; Moisseev, D; Sinclair, V; O’Connor, E; Manninen, A; Levula, J; Väänänen, R; Heikkinen, L; Äijälä, M; Aalto, J; Thornton, JA

    2016-03-01

    Atmospheric aerosol particles impact human health in urban environments, while on regional and global scales they can affect climate patterns, the hydrological cycle, and the intensity of radiation that reaches the Earth’s surface. In spite of recent advances in the understanding of aerosol formation processes and the links between aerosol dynamics and biosphere-atmosphere-climate interactions, great challenges remain in the analysis of related processes on a global scale. Boreal forests, situated in a circumpolar belt in the Northern latitudes throughout the United States, Canada, Russia, and Scandinavia, are, of all biomes, among the most active areas of atmospheric aerosol formation. The formation of aerosol particles and their growth to cloud condensation nuclei sizes in these areas are associated with biogenic volatile organic emissions (BVOC) from vegetation and soil.

  12. Physical-Socio-Economic Modeling of Climate Change

    NASA Astrophysics Data System (ADS)

    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 con