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Sample records for climate models part

  1. 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

  2. The Rossby Centre Regional Atmospheric Climate Model part II: application to the Arctic climate.

    PubMed

    Jones, Colin G; Wyser, Klaus; Ullerstig, Anders; Willén, Ulrika

    2004-06-01

    The Rossby Centre regional climate model (RCA2) has been integrated over the Arctic Ocean as part of the international ARCMIP project. Results have been compared to observations derived from the SHEBA data set. The standard RCA2 model overpredicts cloud cover and downwelling longwave radiation, during the Arctic winter. This error was improved by introducing a new cloud parameterization, which significantly improves the annual cycle of cloud cover. Compensating biases between clear sky downwelling longwave radiation and longwave radiation emitted from cloud base were identified. Modifications have been introduced to the model radiation scheme that more accurately treat solar radiation interaction with ice crystals. This leads to a more realistic representation of cloud-solar radiation interaction. The clear sky portion of the model radiation code transmits too much solar radiation through the atmosphere, producing a positive bias at the top of the frequent boundary layer clouds. A realistic treatment of the temporally evolving albedo, of both sea-ice and snow, appears crucial for an accurate simulation of the net surface energy budget. Likewise, inclusion of a prognostic snow-surface temperature seems necessary, to accurately simulate near-surface thermodynamic processes in the Arctic.

  3. Uncertainty in runoff based on Global Climate Model precipitation and temperature data - Part 1: Assessment of Global Climate Models

    NASA Astrophysics Data System (ADS)

    McMahon, T. A.; Peel, M. C.; Karoly, D. J.

    2014-05-01

    Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between Global Climate Models (GCMs) and within a GCM. Uncertainty between GCM projections of future climate can be assessed through analysis of runs of a given scenario from a wide range of GCMs. Within GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The objective of this, the first of two complementary papers, is to reduce between-GCM uncertainty by identifying and removing poorly performing GCMs prior to the analysis presented in the second paper. Here we assess how well 46 runs from 22 Coupled Model Intercomparison Project phase 3 (CMIP3) GCMs are able to reproduce observed precipitation and temperature climatological statistics. The performance of each GCM in reproducing these statistics was ranked and better performing GCMs identified for later analyses. Observed global land surface precipitation and temperature data were drawn from the CRU 3.10 gridded dataset and re-sampled to the resolution of each GCM for comparison. Observed and GCM based estimates of mean and standard deviation of annual precipitation, mean annual temperature, mean monthly precipitation and temperature and Köppen climate type were compared. The main metrics for assessing GCM performance were the Nash-Sutcliffe efficiency index and RMSE between modelled and observed long-term statistics. This information combined with a literature review of the performance of the CMIP3 models identified the following five models as the better performing models for the next phase of our analysis in assessing the uncertainty in runoff estimated from GCM projections of precipitation and temperature: HadCM3 (Hadley Centre for Climate Prediction and Research), MIROCM (Center for Climate System Research (The University of Tokyo), National Institute for

  4. Multivariate probabilistic projections using imperfect climate models part I: outline of methodology

    NASA Astrophysics Data System (ADS)

    Sexton, David M. H.; Murphy, James M.; Collins, Mat; Webb, Mark J.

    2012-06-01

    We demonstrate a method for making probabilistic projections of climate change at global and regional scales, using examples consisting of the equilibrium response to doubled CO2 concentrations of global annual mean temperature and regional climate changes in summer and winter temperature and precipitation over Northern Europe and England-Wales. This method combines information from a perturbed physics ensemble, a set of international climate models, and observations. Our approach is based on a multivariate Bayesian framework which enables the prediction of a joint probability distribution for several variables constrained by more than one observational metric. This is important if different sets of impacts scientists are to use these probabilistic projections to make coherent forecasts for the impacts of climate change, by inputting several uncertain climate variables into their impacts models. Unlike a single metric, multiple metrics reduce the risk of rewarding a model variant which scores well due to a fortuitous compensation of errors rather than because it is providing a realistic simulation of the observed quantity. We provide some physical interpretation of how the key metrics constrain our probabilistic projections. The method also has a quantity, called discrepancy, which represents the degree of imperfection in the climate model i.e. it measures the extent to which missing processes, choices of parameterisation schemes and approximations in the climate model affect our ability to use outputs from climate models to make inferences about the real system. Other studies have, sometimes without realising it, treated the climate model as if it had no model error. We show that omission of discrepancy increases the risk of making over-confident predictions. Discrepancy also provides a transparent way of incorporating improvements in subsequent generations of climate models into probabilistic assessments. The set of international climate models is used to derive

  5. Global climate modeling of Saturn’s atmosphere. Part I: Evaluation of the radiative transfer model

    NASA Astrophysics Data System (ADS)

    Guerlet, S.; Spiga, A.; Sylvestre, M.; Indurain, M.; Fouchet, T.; Leconte, J.; Millour, E.; Wordsworth, R.; Capderou, M.; Bézard, B.; Forget, F.

    2014-08-01

    We have developed and optimized a seasonal, radiative-convective model of Saturn’s upper troposphere and stratosphere. It is used to investigate Saturn’s radiatively-forced thermal structure between 3 and 10-6 bar, and is intended to be included in a Saturn global climate model (GCM), currently under development. The main elements of the radiative transfer model are detailed as well as the sensitivity to spectroscopic parameters, hydrocarbon abundances, aerosol properties, oblateness, and ring shadowing effects. The vertical temperature structure and meridional seasonal contrasts obtained by the model are then compared to Cassini/CIRS observations. Several significant model-observation mismatches reveal that Saturn’s atmosphere departs from radiative equilibrium. For instance, we find that the modeled temperature profile is close to isothermal above the 2-mbar level, while the temperature retrieved from ground-based or Cassini/CIRS data continues to increase with altitude. Also, no local temperature minimum associated to the ring shadowing is observed in the data, while the model predicts stratospheric temperatures 10 K to 20 K cooler than in the absence of rings at winter tropical latitudes. These anomalies are strong evidence that processes other that radiative heating and cooling control Saturn’s stratospheric thermal structure. Finally, the model is used to study the warm stratospheric anomaly triggered after the 2010 Great White Spot. Comparison with recent Cassini/CIRS observations suggests that the rapid cooling phase of this warm “beacon” in May-June 2011 can be explained by radiative processes alone. Observations on a longer timeline are needed to better characterize and understand its long-term evolution.

  6. 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.

  7. Chemistry-Climate Interactions in the GISS GCM. Part 1; Tropospheric Chemistry Model Description and Evaluation

    NASA Technical Reports Server (NTRS)

    Shindell, Drew T.; Grenfell, J. Lee; Rind, David; Price, Colin; Grewe, Volker; Hansen, James E. (Technical Monitor)

    2001-01-01

    than 0.8 W/sq m are seen over large areas of the United States, Southern Europe, North Africa, the Middle East, Central Asia, and the Arctic. Radiative forcing is greater than 1.5 W/sq m over parts of these areas during Northern summer Though there are local differences, the radiative forcing is overall in good agreement with the results of other modeling studies in both its magnitude and spatial distribution, demonstrating that the simplified chemistry is adequate for climate studies.

  8. GFDL's CM2 global coupled climate models. Part I: Formulation and simulation characteristics

    USGS Publications Warehouse

    Delworth, T.L.; Broccoli, A.J.; Rosati, A.; Stouffer, R.J.; Balaji, V.; Beesley, J.A.; Cooke, W.F.; Dixon, K.W.; Dunne, J.; Dunne, K.A.; Durachta, J.W.; Findell, K.L.; Ginoux, P.; Gnanadesikan, A.; Gordon, C.T.; Griffies, S.M.; Gudgel, R.; Harrison, M.J.; Held, I.M.; Hemler, R.S.; Horowitz, L.W.; Klein, S.A.; Knutson, T.R.; Kushner, P.J.; Langenhorst, A.R.; Lee, H.-C.; Lin, S.-J.; Lu, J.; Malyshev, S.L.; Milly, P.C.D.; Ramaswamy, V.; Russell, J.; Schwarzkopf, M.D.; Shevliakova, E.; Sirutis, J.J.; Spelman, M.J.; Stern, W.F.; Winton, M.; Wittenberg, A.T.; Wyman, B.; Zeng, F.; Zhang, R.

    2006-01-01

    The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved. Tw o versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2?? latitude ?? 2.5?? longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1?? in latitude and longitude, with meridional resolution equatorward of 30?? becoming progressively finer, such that the meridional resolution is 1/3?? at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments. The co ntrol simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and

  9. The tropical water and energy cycles in a cumulus ensemble model. Part 1: Equilibrium climate

    NASA Technical Reports Server (NTRS)

    Sui, C. H.; Lau, K. M.; Tao, W. K.; Simpson, J.

    1994-01-01

    A cumulus ensemble model is used to study the tropical water and energy cycles and their role in the climate system. The model includes cloud dynamics, radiative processes, and microphysics that incorporate all important production and conversion processes among water vapor and five species of hydrometeors. Radiative transfer in clouds is parameterized based on cloud contents and size distributions of each bulk hydrometeor. Several model integrations have been carried out under a variety of imposed boundary and large-scale conditions. In Part 1 of this paper, the primary focus is on the water and heat budgets of the control experiment, which is designed to simulate the convective - radiative equilibrium response of the model to an imposed vertical velocity and a fixed sea surface temperature at 28 C. The simulated atmosphere is conditionally unstable below the freezing level and close to neutral above the freezing level. The equilibrium water budget shows that the total moisture source, M(sub s), which is contributed by surface evaporation (0.24 M(sub s)) and the large-scale advection (0.76 M(sub s)), all converts to mean surface precipitation bar-P(sub s). Most of M(sub s) is transported verticaly in convective regions where much of the condensate is generated and falls to surface (0.68 bar-P(sub s)). The remaining condensate detrains at a rate of 0.48 bar-P(sub s) and constitutes 65% of the source for stratiform clouds above the melting level. The upper-level stratiform cloud dissipates into clear environment at a rate of 0.14 bar-P(sub s), which is a significant moisture source comparable to the detrained water vapor (0.15 bar-P(sub s)) to the upper troposphere from convective clouds. In the lower troposphere, stratiform clouds evaporate at a rate of 0.41 bar-P(sub s), which is a more dominant moisture source than surface evaporation (0.22 bar-P(sub s)). The precipitation falling to the surface in the stratiform region is about 0.32 bar-P(sub s). The associated

  10. Evaluation of the new UKCA climate-composition model - Part 2: The Troposphere

    NASA Astrophysics Data System (ADS)

    O'Connor, F. M.; Johnson, C. E.; Morgenstern, O.; Abraham, N. L.; Braesicke, P.; Dalvi, M.; Folberth, G. A.; Sanderson, M. G.; Telford, P. J.; Voulgarakis, A.; Young, P. J.; Zeng, G.; Collins, W. J.; Pyle, J. A.

    2014-01-01

    In this paper, we present a description of the tropospheric chemistry component of the UK Chemistry and Aerosols (UKCA) model which has been coupled to the Met Office Hadley Centre's HadGEM family of climate models. We assess the model's transport and scavenging processes, in particular focussing on convective transport, boundary layer mixing, wet scavenging and inter-hemispheric exchange. Simulations with UKCA of the short-lived radon tracer suggest that modelled distributions are comparable to those of other models and the comparison with observations indicate that apart from a few locations, boundary layer mixing and convective transport are effective in the model as a means of vertically redistributing surface emissions of radon. Comparisons of modelled lead tracer concentrations with observations suggest that UKCA captures surface concentrations in both hemispheres very well, although there is a tendency to underestimate the observed geographical and interannual variability in the Northern Hemisphere. In particular, UKCA replicates the shape and absolute concentrations of observed lead profiles, a key test in the evaluation of a model's wet scavenging scheme. The timescale for inter-hemispheric transport, calculated in the model using a simple krypton tracer experiment, does appear to be long relative to other models and could indicate deficiencies in tropical deep convection and/or insufficient boundary layer mixing. We also describe the main components of the tropospheric chemistry and evaluate it against observations and other tropospheric chemistry models. In particular, from a climate forcing perspective, present-day observed surface methane concentrations and tropospheric ozone concentrations are reproduced very well by the model, thereby making it suitable for long centennial integrations as well as studies of biogeochemical feedbacks. Results from both historical and future simulations with UKCA tropospheric chemistry are presented. Future projections

  11. Evaluation of the new UKCA climate-composition model - Part 2: The Troposphere

    NASA Astrophysics Data System (ADS)

    O'Connor, F. M.; Johnson, C. E.; Morgenstern, O.; Abraham, N. L.; Braesicke, P.; Dalvi, M.; Folberth, G. A.; Sanderson, M. G.; Telford, P. J.; Young, P. J.; Zeng, G.; Collins, W. J.; Pyle, J. A.

    2013-03-01

    In this paper, we present a description of the tropospheric chemistry component of the UK Chemistry and Aerosols (UKCA) model which has been coupled to the Met Office Hadley Centre's HadGEM family of climate models. We assess the model's transport and scavenging processes, in particular focussing on convective transport, boundary layer mixing, wet scavenging and inter-hemispheric exchange. Simulations with UKCA of the short-lived radon tracer suggest that modelled distributions are comparable to those of other models and the comparison with observations indicate that apart from a few locations, boundary layer mixing and convective transport are effective in the model as a means of vertically re-distributing surface emissions of radon. Comparisons of modelled lead tracer concentrations with observations suggest that UKCA captures surface concentrations in both hemispheres very well although there is a tendency to underestimate the observed geographical and interannual variability in the Northern Hemisphere. In particular, UKCA replicates the shape and absolute concentrations of observed lead profiles, a key test in the evaluation of a model's wet scavenging scheme. The timescale for inter-hemispheric transport, calculated in the model using a simple krypton tracer experiment, does appear to be long relative to other models and could indicate deficiencies in tropical deep convection and/or insufficient boundary layer mixing. We also describe the main components of the tropospheric chemistry and evaluate it against observations and other tropospheric chemistry models. In particular, from a climate forcing perspective, present-day observed surface methane concentrations and tropospheric ozone concentrations are reproduced very well by the model, thereby making it suitable for long centennial integrations as well as studies of biogeochemical feedbacks. Results from both historical and future simulations with UKCA tropospheric chemistry are presented. Future projections

  12. Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models Part I: Convective Signals

    SciTech Connect

    Lin, J; Kiladis, G N; Mapes, B E; Weickmann, K M; Sperber, K R; Lin, W; Wheeler, M; Schubert, S D; Genio, A D; Donner, L J; Emori, S; Gueremy, J; Hourdin, F; Rasch, P J; Roeckner, E; Scinocca, J F

    2005-05-06

    This study evaluates the tropical intraseasonal variability, especially the fidelity of Madden-Julian Oscillation (MJO) simulations, in 14 coupled general circulation models (GCMs) participating in the Inter-governmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Eight years of daily precipitation from each model's 20th century climate simulation are analyzed and compared with daily satellite retrieved precipitation. Space-time spectral analysis is used to obtain the variance and phase speed of dominant convectively coupled equatorial waves, including the MJO, Kelvin, equatorial Rossby (ER), mixed Rossby-gravity (MRG), and eastward inertio-gravity (EIG) and westward inertio-gravity (WIG) waves. The variance and propagation of the MJO, defined as the eastward wavenumbers 1-6, 30-70 day mode, are examined in detail. The results show that current state-of-the-art GCMs still have significant problems and display a wide range of skill in simulating the tropical intraseasonal variability. The total intraseasonal (2-128 day) variance of precipitation is too weak in most of the models. About half of the models have signals of convectively coupled equatorial waves, with Kelvin and MRG-EIG waves especially prominent. However, the variances are generally too weak for all wave modes except the EIG wave, and the phase speeds are generally too fast, being scaled to excessively deep equivalent depths. An interesting result is that this scaling is consistent within a given model across modes, in that both the symmetric and antisymmetric modes scale similarly to a certain equivalent depth. Excessively deep equivalent depths suggest that these models may not have a large enough reduction in their ''effective static stability'' due to diabatic heating. The MJO variance approaches the observed value in only two of the 14 models, but is less than half of the observed value in the other 12 models. The ratio between the eastward MJO variance and the variance of its

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

    NASA Astrophysics Data System (ADS)

    Yuan, Xing

    2016-06-01

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

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

    USGS Publications Warehouse

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

    2012-01-01

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

  15. Climate change impact assessment on Veneto and Friuli Plain groundwater. Part I: an integrated modeling approach for hazard scenario construction.

    PubMed

    Baruffi, F; Cisotto, A; Cimolino, A; Ferri, M; Monego, M; Norbiato, D; Cappelletto, M; Bisaglia, M; Pretner, A; Galli, A; Scarinci, A; Marsala, V; Panelli, C; Gualdi, S; Bucchignani, E; Torresan, S; Pasini, S; Critto, A; Marcomini, A

    2012-12-01

    Climate change impacts on water resources, particularly groundwater, is a highly debated topic worldwide, triggering international attention and interest from both researchers and policy makers due to its relevant link with European water policy directives (e.g. 2000/60/EC and 2007/118/EC) and related environmental objectives. The understanding of long-term impacts of climate variability and change is therefore a key challenge in order to address effective protection measures and to implement sustainable management of water resources. This paper presents the modeling approach adopted within the Life+ project TRUST (Tool for Regional-scale assessment of groUndwater Storage improvement in adaptation to climaTe change) in order to provide climate change hazard scenarios for the shallow groundwater of high Veneto and Friuli Plain, Northern Italy. Given the aim to evaluate potential impacts on water quantity and quality (e.g. groundwater level variation, decrease of water availability for irrigation, variations of nitrate infiltration processes), the modeling approach integrated an ensemble of climate, hydrologic and hydrogeologic models running from the global to the regional scale. Global and regional climate models and downscaling techniques were used to make climate simulations for the reference period 1961-1990 and the projection period 2010-2100. The simulation of the recent climate was performed using observed radiative forcings, whereas the projections have been done prescribing the radiative forcings according to the IPCC A1B emission scenario. The climate simulations and the downscaling, then, provided the precipitation, temperatures and evapo-transpiration fields used for the impact analysis. Based on downscaled climate projections, 3 reference scenarios for the period 2071-2100 (i.e. the driest, the wettest and the mild year) were selected and used to run a regional geomorphoclimatic and hydrogeological model. The final output of the model ensemble produced

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

    NASA Astrophysics Data System (ADS)

    Iversen, T.; Bentsen, M.; Bethke, I.; Debernard, J. B.; Kirkevåg, A.; Seland, Ø.; Drange, H.; Kristjansson, J. E.; Medhaug, I.; Sand, M.; Seierstad, I. A.

    2013-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

  18. Pacific Northwest Sensitivity Simulated by a Regional Climate Model Driven by a GCM. Part I: Control Simulations

    SciTech Connect

    Leung, Lai R.; Ghan, Steven J.

    1999-07-01

    A model nesting approach has been used to simulate the regional climate over the Pacific Northwest. The present-day global climatology is first simulated using the NCAR Community Climate Model (CCM3) driven by observed sea surface temperature and sea ice distribution at T42 (2.8{sup o}) resolution. This large-scale simulation is used to provide lateral boundary conditions for driving the Pacific Northwest National Laboratory Regional Climate Model (RCM). One notable feature of the RCM is the use of subgrid parameterizations of orographic precipitation and vegetation cover, in which subgrid variations of surface elevation and vegetation are aggregated to a limited number of elevation-vegetation classes. An airflow model and a thermodynamic model are used to parameterize the orographic uplift/descent as air parcels cross over mountain barriers or valleys. The 7-yr climatologies as simulated by CCM3 and RCM are evaluated and compared in terms of large-scale spatial patterns and regional means. Biases are found in the simulation of large-scale circulations, which also affect the regional model simulation. Therefore, the regional simulation is not very different from the CCM3 simulation in terms of large-scale features. However, the regional model greatly improves the simulation of precipitation, surface temperature, and snow cover at the local scales. This is shown by improvements in the spatial correlation between the observations and simulations. The RCM simulation is further evaluated using station observations of surface temperature and precipitation to compare the simulated and observed relationships between surface temperature-precipitation and altitude. The model is found to correctly capture the surface temperature-precipitation variations as functions of surface topography over different mountain ranges, and under different climate regimes.

  19. 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.

  20. A Formal Analysis of the Feedback Concept in Climate Models. Part I: Exclusive and Inclusive Feedback Analyses

    NASA Astrophysics Data System (ADS)

    Lahellec, Alain; Dufresne, Jean-Louis

    2013-12-01

    Climate sensitivity and feedback are key concepts if the complex behavior of climate response to perturbation is to be interpreted in a simple way. They have also become an essential tool for comparing global circulation models and assessing the reason for the spread in their results. The authors introduce a formal basic model to analyze the practical methods used to infer climate feedbacks and sensitivity from GCMs. The tangent linear model is used first to critically review the standard methods of feedback analyses that have been used in the GCM community for 40 years now. This leads the authors to distinguish between exclusive feedback analyses as in the partial radiative perturbation approach and inclusive analyses as in the "feedback suppression" methods. This review explains the hypotheses needed to apply these methods with confidence. Attention is paid to the more recent regression technique applied to the abrupt 2-CO2 experiment. A numerical evaluation of it is given, related to the Lyapunov analysis of the dynamical feature of the regression. It is applied to the Planck response, determined in its most strict definition within the GCM. In this approach, the Planck feedback becomes a dynamical feedback among others and, as such, also has a fast response differing from its steady-state profile.

  1. Coupled Climate-Economy-Biosphere (CoCEB) model - Part 1: Abatement share and investment in low-carbon technologies

    NASA Astrophysics Data System (ADS)

    Ogutu, K. B. Z.; D'Andrea, F.; Ghil, M.; Nyandwi, C.; Manene, M. M.; Muthama, J. N.

    2015-04-01

    The Coupled Climate-Economy-Biosphere (CoCEB) model described herein takes an integrated assessment approach to simulating global change. By using an endogenous economic growth module with physical and human capital accumulation, this paper considers the sustainability of economic growth, as economic activity intensifies greenhouse gas emissions that in turn cause economic damage due to climate change. Different types of fossil fuels and different technologies produce different volumes of carbon dioxide in combustion. The shares of different fuels and their future evolution are not known. We assume that the dynamics of hydrocarbon-based energy share and their replacement with renewable energy sources in the global energy balance can be modeled into the 21st century by use of logistic functions. Various climate change mitigation policy measures are considered. While many integrated assessment models treat abatement costs merely as an unproductive loss of income, we consider abatement activities also as an investment in overall energy efficiency of the economy and decrease of overall carbon intensity of the energy system. The paper shows that these efforts help to reduce the volume of industrial carbon dioxide emissions, lower temperature deviations, and lead to positive effects in economic growth.

  2. Multi-decadal scenario simulation over Korea using a one-way double-nested regional climate model system. Part 1: recent climate simulation (1971 2000)

    NASA Astrophysics Data System (ADS)

    Im, Eun-Soon; Kwon, Won-Tae; Ahn, Joong-Bae; Giorgi, Filippo

    2007-06-01

    We present an analysis of a high resolution multi-decadal simulation of recent climate (1971 2000) over the Korean Peninsula with a regional climate model (RegCM3) using a one-way double-nested system. Mean climate state as well as frequency and intensity of extreme climate events are investigated at various temporal and spatial scales, with focus on surface air temperature and precipitation. The mother intermediate resolution model domain encompasses the eastern regions of Asia at 60 km grid spacing while the high resolution nested domain covers the Korean Peninsula at 20 km grid spacing. The simulation spans the 30-year period of January 1971 through December 2000, and initial and lateral boundary conditions for the mother domain are provided from ECHO-G fields based on the IPCC SRES B2 scenario. The model shows a good performance in reproducing the climatological and regional characteristics of surface variables, although some persistent biases are present. Main results are as follows: (1) The RegCM3 successfully simulates the fine-scale structure of the temperature field due to topographic forcing but it shows a systematic cold bias mostly due to an underestimate of maximum temperature. (2) The frequency distribution of simulated daily mean temperature agrees well with the observed seasonal and spatial patterns. In the summer season, however, daily variability is underestimated. (3) The RegCM3 simulation adequately captures the seasonal evolution of precipitation associated to the East Asia monsoon. In particular, the simulated winter precipitation is remarkably good, clearly showing typical precipitation patterns that occur on the northwestern areas of Japan during the winter monsoon. Although summer precipitation is underestimated, area-averaged time series of precipitation over Korea show that the RegCM3 agrees better with observations than ECHO-G both in terms of seasonal evolution and precipitation amounts. (4) Heavy rainfall phenomena exceeding 300 mm

  3. Regional Climate Zone Modeling of a Commercial Absorption Heat Pump Hot Water Heater Part 1: Southern and South Central Climate Zones

    SciTech Connect

    Geoghegan, Patrick J; Shen, Bo; Keinath, Christopher M.; Garrabrant, Michael A.

    2016-01-01

    Commercial hot water heating accounts for approximately 0.78 Quads of primary energy use with 0.44 Quads of this amount from natural gas fired heaters. An ammonia-water based commercial absorption system, if fully deployed, could achieve a high level of savings, much higher than would be possible by conversion to the high efficiency nonheat-pump gas fired alternatives. In comparison with air source electric heat pumps, the absorption system is able to maintain higher coefficients of performance in colder climates. The ammonia-water system also has the advantage of zero Ozone Depletion Potential and low Global Warming Potential. A thermodynamic model of a single effect ammonia-water absorption system for commercial space and water heating was developed, and its performance was investigated for a range of ambient and return water temperatures. This allowed for the development of a performance map which was then used in a building energy modeling software. Modeling of two commercial water heating systems was performed; one using an absorption heat pump and another using a condensing gas storage system. The energy and financial savings were investigated for a range of locations and climate zones in the southern and south central United States. A follow up paper will analyze northern and north/central regions. Results showed that the system using an absorption heat pump offers significant savings.

  4. A global climate model (GENESIS) with a land-surface transfer scheme (LSX). Part II: CO{sub 2} sensitivity

    SciTech Connect

    Thompson, S.L.; Pollard, D.

    1995-05-01

    The sensitivity of the equilibrium climate to doubled atmospheric CO{sub 2} is investigated using the GENESIS global climate model version 1.02. The atmospheric general circulation model is a heavily modified version of the NCAR CCM1 and is coupled to a multicanopy lane-surface model (LSX); multilayer models of soil, snow, and sea ice; and a slab ocean mixed layer. Features that are relatively new in CO{sub 2} sensitivity studies include explicit subgrid convective plumes, PBL mixing, a diurnal cycle, a complex land-surface model, sea ice dynamics, and semi-Lagrangian transport of water vapor. The global annual surface-air warming in the model is 2.1{degrees}C, with global precipitation increasing by 3.3%. Over most land areas, most of the changes in precipitation are insignificant at the 5% level compared to interannual variability. Decreases in soil moisture in summer are not as large as in most previous models and only occur poleward of {approximately}55{degrees} in Siberia, northern CAnada, and Alaska. Sea ice area in September recedes by 62% in the Artic and by 43% in the Antarctic. The area of Northern Hemispheric permafrost decreases by 48%, while the the total area of Northern hemispheric snowcover in January decreases by 48%, while the total area of Northern Hemispheric snowcover in January decreases by on 13%. The effects of several modifications to the model physics are described. Replacing LSX and the multilayer soil with a single-layer bucket model causes little change to CO{sub 2} sensitivities on global scales, and the regions of summer drying in northern high latitudes are reproduced, although with somewhat greater amplitude. Compared to convective adjustment, penetrative plume convection increases the tropical Hadley Cell response but decreases the global warming slightly by 0.1{degrees} to 0.3{degrees}, contrary to several previous GCM studies in which penetrative convection was associated with greater CO{sub 2} warming. 60 refs., 20 figs., 3 tabs.

  5. Wonderland climate model

    NASA Astrophysics Data System (ADS)

    Hansen, J.; Ruedy, R.; Lacis, A.; Russell, G.; Sato, M.; Lerner, J.; Rind, D.; Stone, P.

    1997-03-01

    We obtain a highly efficient global climate model by defining a sector version (120° of longitude) of the coarse resolution Goddard Institute for Space Studies model II. The geography of Wonderland is chosen such that the amount of land as a function of latitude is the same as on Earth. We show that the zonal mean climate of the Wonderland model is very similar to that of the parent model II.

  6. Multi-model ensemble simulation and projection in the climate change in the Mekong River Basin. Part I: temperature.

    PubMed

    Huang, Yong; Wang, Fengyou; Li, Yi; Cai, Tijiu

    2014-11-01

    This paper evaluates the performance of the Coupled Model Intercomparison Project phase 5 (CMIP5) in simulating annual and decadal temperature in the Mekong River Basin from 1950 to 2005. By use of Bayesian multi-model averaging method, the future projection of temperature variation under different scenarios are also analyzed. The results show, the performances of climate model are more accurate in space than time, the model can catch the warming characteristics in the Mekong river Basin, but the accuracy of simulation is not good enough. Bayesian multi-model averaging method can improve the annual and decadal temperature simulation when compared to a single result. The projected temperature in Mekong River will increase by 0.88 °C/100 year, 2.15 °C/100 year and 4.96 °C/100 year for the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, over the twenty-first century. The findings will be beneficial for local people and policy-maker to formulate regional strategies against the potential menaces of warming scenarios.

  7. The Role of Sea Ice in 2 x CO2 Climate Model Sensitivity. Part 2; Hemispheric Dependencies

    NASA Technical Reports Server (NTRS)

    Rind, D.; Healy, R.; Parkinson, C.; Martinson, D.

    1997-01-01

    How sensitive are doubled CO2 simulations to GCM control-run sea ice thickness and extent? This issue is examined in a series of 10 control-run simulations with different sea ice and corresponding doubled CO2 simulations. Results show that with increased control-run sea ice coverage in the Southern Hemisphere, temperature sensitivity with climate change is enhanced, while there is little effect on temperature sensitivity of (reasonable) variations in control-run sea ice thickness. In the Northern Hemisphere the situation is reversed: sea ice thickness is the key parameter, while (reasonable) variations in control-run sea ice coverage are of less importance. In both cases, the quantity of sea ice that can be removed in the warmer climate is the determining factor. Overall, the Southern Hemisphere sea ice coverage change had a larger impact on global temperature, because Northern Hemisphere sea ice was sufficiently thick to limit its response to doubled CO2, and sea ice changes generally occurred at higher latitudes, reducing the sea ice-albedo feedback. In both these experiments and earlier ones in which sea ice was not allowed to change, the model displayed a sensitivity of -0.02 C global warming per percent change in Southern Hemisphere sea ice coverage.

  8. Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 1: surface air temperature

    NASA Astrophysics Data System (ADS)

    Suh, Myoung-Seok; Oh, Seok-Geun; Lee, Young-Suk; Ahn, Joong-Bae; Cha, Dong-Hyun; Lee, Dong-Kyou; Hong, Song-You; Min, Seung-Ki; Park, Seong-Chan; Kang, Hyun-Suk

    2016-05-01

    We projected surface air temperature changes over South Korea during the mid (2026-2050) and late (2076-2100) 21st century against the current climate (1981-2005) using the simulation results from five regional climate models (RCMs) driven by Hadley Centre Global Environmental Model, version 2, coupled with the Atmosphere- Ocean (HadGEM2-AO), and two ensemble methods (equal weighted averaging, weighted averaging based on Taylor's skill score) under four Representative Concentration Pathways (RCP) scenarios. In general, the five RCM ensembles captured the spatial and seasonal variations, and probability distribution of temperature over South Korea reasonably compared to observation. They particularly showed a good performance in simulating annual temperature range compared to HadGEM2-AO. In future simulation, the temperature over South Korea will increase significantly for all scenarios and seasons. Stronger warming trends are projected in the late 21st century than in the mid-21st century, in particular under RCP8.5. The five RCM ensembles projected that temperature changes for the mid/late 21st century relative to the current climate are +1.54°C/+1.92°C for RCP2.6, +1.68°C/+2.91°C for RCP4.5, +1.17°C/+3.11°C for RCP6.0, and +1.75°C/+4.73°C for RCP8.5. Compared to the temperature projection of HadGEM2-AO, the five RCM ensembles projected smaller increases in temperature for all RCP scenarios and seasons. The inter-RCM spread is proportional to the simulation period (i.e., larger in the late-21st than mid-21st century) and significantly greater (about four times) in winter than summer for all RCP scenarios. Therefore, the modeled predictions of temperature increases during the late 21st century, particularly for winter temperatures, should be used with caution.

  9. 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…

  10. 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.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  13. Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 2: precipitation

    NASA Astrophysics Data System (ADS)

    Oh, Seok-Geun; Suh, Myoung-Seok; Lee, Young-Suk; Ahn, Joong-Bae; Cha, Dong-Hyun; Lee, Dong-Kyou; Hong, Song-You; Min, Seung-Ki; Park, Seong-Chan; Kang, Hyun-Suk

    2016-05-01

    Precipitation changes over South Korea were projected using five regional climate models (RCMs) with a horizontal resolution of 12.5 km for the mid and late 21st century (2026-2050, 2076- 2100) under four Representative Concentration Pathways (RCP) scenarios against present precipitation (1981-2005). The simulation data of the Hadley Centre Global Environmental Model version 2 coupled with the Atmosphere-Ocean (HadGEM2-AO) was used as boundary data of RCMs. In general, the RCMs well simulated the spatial and seasonal variations of present precipitation compared with observation and HadGEM2-AO. Equal Weighted Averaging without Bias Correction (EWA_NBC) significantly reduced the model biases to some extent, but systematic biases in results still remained. However, the Weighted Averaging based on Taylor's skill score (WEA_Tay) showed a good statistical correction in terms of the spatial and seasonal variations, the magnitude of precipitation amount, and the probability density. In the mid-21st century, the spatial and interannual variabilities of precipitation over South Korea are projected to increase regardless of the RCP scenarios and seasons. However, the changes in area-averaged seasonal precipitation are not significant due to mixed changing patterns depending on locations. Whereas, in the late 21st century, the precipitation is projected to increase proportionally to the changes of net radiative forcing. Under RCP8.5, WEA_Tay projects the precipitation to be increased by about +19.1, +20.5, +33.3% for annual, summer and winter precipitation at 1-5% significance levels, respectively. In addition, the probability of strong precipitation (≥ 15 mm d-1) is also projected to increase significantly, particularly in WEA_Tay under RCP8.5.

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  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. 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

  17. Coupled Climate-Economy-Biosphere (CoCEB) model - Part 2: Deforestation control and investment in carbon capture and storage technologies

    NASA Astrophysics Data System (ADS)

    Ogutu, K. B. Z.; D'Andrea, F.; Ghil, M.; Nyandwi, C.; Manene, M. M.; Muthama, J. N.

    2015-04-01

    This study uses the global climate-economy-biosphere (CoCEB) model developed in Part 1 to investigate economic aspects of deforestation control and carbon sequestration in forests, as well as the efficiency of carbon capture and storage (CCS) technologies as policy measures for climate change mitigation. We assume - as in Part 1 - that replacement of one technology with another occurs in terms of a logistic law, so that the same law also governs the dynamics of reduction in carbon dioxide emission using CCS technologies. In order to take into account the effect of deforestation control, a slightly more complex description of the carbon cycle than in Part 1 is needed. Consequently, we add a biomass equation into the CoCEB model and analyze the ensuing feedbacks and their effects on per capita gross domestic product (GDP) growth. Integrating biomass into the CoCEB and applying deforestation control as well as CCS technologies has the following results: (i) low investment in CCS contributes to reducing industrial carbon emissions and to increasing GDP, but further investment leads to a smaller reduction in emissions, as well as in the incremental GDP growth; and (ii) enhanced deforestation control contributes to a reduction in both deforestation emissions and in atmospheric carbon dioxide concentration, thus reducing the impacts of climate change and contributing to a slight appreciation of GDP growth. This effect is however very small compared to that of low-carbon technologies or CCS. We also find that the result in (i) is very sensitive to the formulation of CCS costs, while to the contrary, the results for deforestation control are less sensitive.

  18. 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.

  19. 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.

  20. 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.…

  1. Drivers of soil organic matter vulnerability to climate change, Part II: RothC modelling of carbon dynamics including radiocarbon data

    NASA Astrophysics Data System (ADS)

    Studer, Mirjam S.; Abiven, Samuel; González Domínguez, Beatriz R.; Hagedorn, Frank; Reisser, Moritz; Walthert, Lorenz; Zimmermann, Stephan; Niklaus, Pascal A.

    2016-04-01

    It is still largely unknown what drives the vulnerability of soil organic carbon (SOC) stocks to climate change, i.e. the likelihood of a soil to loose its SOC along with the change in environmental conditions. Our objective is to assess the SOC vulnerability of Swiss forest soils and identify its potential drivers: climate (temperature, soil moisture), soil (clay content, pH) and landscape (slope, aspect) properties. Fifty-four sites were selected for balanced spatial and driver magnitudes distribution. We measured the SOC characteristics (content and radiocarbon) and studied the C decomposition by laboratory soil incubations (details in Part I, abstract by B. González Domínguez). In order to assess the current SOC pool distribution and its radiocarbon signatures, we extended the Rothamsted Carbon (RothC) model with radiocarbon (14C) isotope modelling (RothCiso). The RothC model distinguishes four active SOC pools, decomposable and resistant plant material, microbial biomass and humified organic matter, and an inert SOC pool (Jenkinson 1990). The active pools are decomposed and mineralized to CO2 by first order kinetics. The RothCiso assigns all pools a 14C signature, based on the atmospheric 14C concentrations of the past century (plant C inputs) and their turnover. Currently we constrain the model with 14C signatures measured on the 54 fresh and their corresponding archived bulk soil samples, taken 12-24 years before. We were able to reproduce the measured radiocarbon concentrations of the SOC with the RothCiso and first results indicate, that the assumption of an inert SOC pool, that is radiocarbon dead, is not appropriate. In a second step we will compare the SOC mean residence time assessed by the two methodological approaches - incubation (C efflux based) and modelling (C stock based) - and relate it to the environmental drivers mentioned above. With the combination of the two methodological approaches and 14C analysis we hope to gain more insights into

  2. 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.

  3. Climate Model Output Rewriter

    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 anmore » 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.« less

  4. Nation-wide assessment of climate change impacts on crops in the Philippines and Peru as part of multi-disciplinary modelling framework

    NASA Astrophysics Data System (ADS)

    Fujisawa, Mariko; Kanamaru, Hideki

    2016-04-01

    Agriculture is vulnerable to environmental changes, and climate change has been recognized as one of the most devastating factors. In many developing countries, however, few studies have focused on nation-wide assessment of crop yield and crop suitability in the future, and hence there is a large pressure on science to provide policy makers with solid predictions for major crops in the countries in support of climate risk management policies and programmes. FAO has developed the tool MOSAICC (Modelling System for Agricultural Impacts of Climate Change) where statistical climate downscaling is combined with crop yield projections under climate change scenarios. Three steps are required to get the results: 1. The historical meteorological data such as temperature and precipitation for about 30 years were collected, and future climates were statistically downscaled to the local scale, 2. The historical crop yield data were collected and regression functions were made to estimate the yield by using observed climatic data and water balance during the growing period for each crop, and 3. The yield changes in the future were estimated by using the future climate data, produced by the first step, as an input to the yield regression functions. The yield was first simulated at sub-national scale and aggregated to national scale, which is intended to provide national policies with adaptation options. The methodology considers future changes in characteristics of extreme weather events as the climate projections are on daily scale while crop simulations are on 10-daily scale. Yields were simulated with two greenhouse gas concentration pathways (RCPs) for three GCMs per crop to account for uncertainties in projections. The crop assessment constitutes a larger multi-disciplinary assessment of climate change impacts on agriculture and vulnerability of livelihoods in terms of food security (e.g. water resources, agriculture market, household-level food security from socio

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

    Earth System Models (ESMs) that incorporate carbon-climate feedbacks represent the present state of the art in climate modelling. Here, we describe the Australian Community Climate and Earth System Simulator (ACCESS)-ESM1 that combines existing ocean and land carbon models into the physical climate model to simulate exchanges of carbon between the land, atmosphere and ocean. The land carbon model can optionally include both nitrogen and phosphorous limitation on the land carbon uptake. The ocean carbon model simulates the evolution of nitrate, oxygen, dissolved inorganic carbon, alkalinity and iron with one class of phytoplankton and zooplankton. From two multi-centennial simulations of the pre-industrial period with different land carbon model configurations, we evaluate the equilibration of the carbon cycle and present the spatial and temporal variability in key carbon exchanges. For the land carbon cycle, leaf area index is simulated reasonably, and seasonal carbon exchange is well represented. Interannual variations of land carbon exchange are relatively large, driven by variability in precipitation and temperature. We find that the response of the ocean carbon cycle shows reasonable agreement with observations and very good agreement with existing Coupled Model Intercomparison Project (CMIP5) models. While our model over estimates surface nitrate values, the primary productivity agrees well with observations. Our analysis highlights some deficiencies inherent in the carbon models and where the carbon simulation is negatively impacted by known biases in the underlying physical model. We conclude the study with a brief discussion of key developments required to further improve the realism of our model simulation.

  6. 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.

  7. 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

  8. The role of sea ice in 2 x CO2 climate model sensitivity. Part 1: The total influence of sea ice thickness and extent

    NASA Technical Reports Server (NTRS)

    Rind, D.; Healy, R.; Parkinson, C.; Martinson, D.

    1995-01-01

    As a first step in investigating the effects of sea ice changes on the climate sensitivity to doubled atmospheric CO2, the authors use a standard simple sea ice model while varying the sea ice distributions and thicknesses in the control run. Thinner ice amplifies the atmospheric temperature senstivity in these experiments by about 15% (to a warming of 4.8 C), because it is easier for the thinner ice to be removed as the climate warms. Thus, its impact on sensitivity is similar to that of greater sea ice extent in the control run, which provides more opportunity for sea ice reduction. An experiment with sea ice not allowed to change between the control and doubled CO2 simulations illustrates that the total effect of sea ice on surface air temperature changes, including cloud cover and water vapor feedbacks that arise in response to sea ice variations, amounts to 37% of the temperature sensitivity to the CO2 doubling, accounting for 1.56 C of the 4.17 C global warming. This is about four times larger than the sea ice impact when no feedbacks are allowed. The different experiments produce a range of results for southern high latitudes with the hydrologic budget over Antarctica implying sea level increases of varying magnitude or no change. These results highlight the importance of properly constraining the sea ice response to climate perturbations, necessitating the use of more realistic sea ice and ocean models.

  9. Uncertainty in runoff based on Global Climate Model precipitation and temperature data - Part 2: Estimation and uncertainty of annual runoff and reservoir yield

    NASA Astrophysics Data System (ADS)

    Peel, M. C.; Srikanthan, R.; McMahon, T. A.; Karoly, D. J.

    2014-05-01

    Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between Global Climate Models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) datasets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to approximate within-GCM uncertainty of monthly precipitation and temperature projections and assess its impact on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. To-date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2014) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from CMIP3 for use in this paper. Here we present within- and between-GCM uncertainty results in mean annual precipitation (MAP), temperature (MAT) and runoff (MAR), the standard deviation of annual precipitation (SDP) and runoff (SDR) and reservoir yield for five CMIP3 GCMs at 17 world-wide catchments. Based on 100

  10. 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

  11. A regional climate palaeosimulation for Europe in the period 1500-1990 - Part 2: Shortcomings and strengths of models and reconstructions

    NASA Astrophysics Data System (ADS)

    Gómez-Navarro, J. J.; Bothe, O.; Wagner, S.; Zorita, E.; Werner, J. P.; Luterbacher, J.; Raible, C. C.; Montávez, J. P.

    2015-08-01

    This study compares gridded European seasonal series of surface air temperature (SAT) and precipitation (PRE) reconstructions with a regional climate simulation over the period 1500-1990. The area is analysed separately for nine subareas that represent the majority of the climate diversity in the European sector. In their spatial structure, an overall good agreement is found between the reconstructed and simulated climate features across Europe, supporting consistency in both products. Systematic biases between both data sets can be explained by a priori known deficiencies in the simulation. Simulations and reconstructions, however, largely differ in the temporal evolution of past climate for European subregions. In particular, the simulated anomalies during the Maunder and Dalton minima show stronger response to changes in the external forcings than recorded in the reconstructions. Although this disagreement is to some extent expected given the prominent role of internal variability in the evolution of regional temperature and precipitation, a certain degree of agreement is a priori expected in variables directly affected by external forcings. In this sense, the inability of the model to reproduce a warm period similar to that recorded for the winters during the first decades of the 18th century in the reconstructions is indicative of fundamental limitations in the simulation that preclude reproducing exceptionally anomalous conditions. Despite these limitations, the simulated climate is a physically consistent data set, which can be used as a benchmark to analyse the consistency and limitations of gridded reconstructions of different variables. A comparison of the leading modes of SAT and PRE variability indicates that reconstructions are too simplistic, especially for precipitation, which is associated with the linear statistical techniques used to generate the reconstructions. The analysis of the co-variability between sea level pressure (SLP) and SAT and PRE

  12. Potential impact of climate change on the Intra-Americas Sea: Part-1. A dynamic downscaling of the CMIP5 model projections

    NASA Astrophysics Data System (ADS)

    Liu, Yanyun; Lee, Sang-Ki; Enfield, David B.; Muhling, Barbara A.; Lamkin, John T.; Muller-Karger, Frank E.; Roffer, Mitchell A.

    2015-08-01

    This study examines the potential impact of anthropogenic greenhouse warming on the Intra-Americas Sea (IAS, Caribbean Sea and Gulf of Mexico) by downscaling the Coupled Model Intercomparison Project phase-5 (CMIP5) model simulations under historical and two future emission scenarios using an eddy-resolving resolution regional ocean model. The simulated volume transport by the western boundary current system in the IAS, including the Caribbean Current, Yucatan Current and Loop Current (LC), is reduced by 20-25% during the 21st century, consistent with a similar rate of reduction in the Atlantic Meridional Overturning Circulation (AMOC). The effect of the LC in the present climate is to warm the Gulf of Mexico (GoM). Therefore, the reduced LC and the associated weakening of the warm transient LC eddies have a cooling impact in the GoM, particularly during boreal spring in the northern deep basin, in agreement with an earlier dynamic downscaling study. In contrast to the reduced warming in the northern deep GoM, the downscaled model predicts an intense warming in the shallow (≤ 200 m) northeastern shelf of the GoM especially during boreal summer since there is no effective mechanism to dissipate the increased surface heating. Potential implications of the regionally distinctive warming trend pattern in the GoM on the marine ecosystems and hurricane intensifications during landfall are discussed. This study also explores the effects of 20th century warming and climate variability in the IAS using the regional ocean model forced with observed surface flux fields. The main modes of sea surface temperature variability in the IAS are linked to the Atlantic Multidecadal Oscillation and a meridional dipole pattern between the GoM and Caribbean Sea. It is also shown that variability of the IAS western boundary current system in the 20th century is largely driven by wind stress curl in the Sverdrup interior and the AMOC.

  13. Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes: Part I. Comprehensive model evaluation and trend analysis for 2006 and 2011

    DOE PAGES

    Chen, Ying; Zhang, Yang; Fan, Jiwen; Leung, Lai -Yung; Zhang, Qiang; He, Kebin

    2015-08-18

    Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO2 but relatively poor for surface concentrations of several species such as CO, NO2, SO2, PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that

  14. Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes: Part I. Comprehensive model evaluation and trend analysis for 2006 and 2011

    SciTech Connect

    Chen, Ying; Zhang, Yang; Fan, Jiwen; Leung, Lai -Yung; Zhang, Qiang; He, Kebin

    2015-08-18

    Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at the surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO2 but relatively poor for surface concentrations of several species such as CO, NO2, SO2, PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is

  15. Climate Modeling and Projections of Global Warming

    NASA Astrophysics Data System (ADS)

    Fung, Inez

    2008-04-01

    Physics of the climate system is captured, with varying degrees of success, in climate models used to hindcast paleoclimates and project future climate change. This talk reviews the formulation of climate models, validation/falsification of processes included, and presents research challenges for advancing projections of future climate change.

  16. 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.

  17. Climate model benchmarking with glacial and mid-Holocene climates

    NASA Astrophysics Data System (ADS)

    Harrison, S. P.; Bartlein, P. J.; Brewer, S.; Prentice, I. C.; Boyd, M.; Hessler, I.; Holmgren, K.; Izumi, K.; Willis, K.

    2014-08-01

    Past climates provide a test of models' ability to predict climate change. We present a comprehensive evaluation of state-of-the-art models against Last Glacial Maximum and mid-Holocene climates, using reconstructions of land and ocean climates and simulations from the Palaeoclimate Modelling and Coupled Modelling Intercomparison Projects. Newer models do not perform better than earlier versions despite higher resolution and complexity. Differences in climate sensitivity only weakly account for differences in model performance. In the glacial, models consistently underestimate land cooling (especially in winter) and overestimate ocean surface cooling (especially in the tropics). In the mid-Holocene, models generally underestimate the precipitation increase in the northern monsoon regions, and overestimate summer warming in central Eurasia. Models generally capture large-scale gradients of climate change but have more limited ability to reproduce spatial patterns. Despite these common biases, some models perform better than others.

  18. "Ask Argonne" - Robert Jacob, Climate Scientist, Part 2

    ScienceCinema

    Jacob, Robert

    2016-07-12

    Previously, climate scientist Robert Jacob talked a bit about the work he does and invited questions from the public during Part 1 of his "Ask Argonne" video set (http://bit.ly/1aK6WDv). In Part 2, he answers some of the questions that were submitted.

  19. "Ask Argonne" - Robert Jacob, Climate Scientist, Part 2

    SciTech Connect

    Jacob, Robert

    2014-01-08

    Previously, climate scientist Robert Jacob talked a bit about the work he does and invited questions from the public during Part 1 of his "Ask Argonne" video set (http://bit.ly/1aK6WDv). In Part 2, he answers some of the questions that were submitted.

  20. Models (Part 1).

    ERIC Educational Resources Information Center

    Callison, Daniel

    2002-01-01

    Defines models and describes information search models that can be helpful to instructional media specialists in meeting users' abilities and information needs. Explains pathfinders and Kuhlthau's information search process, including the pre-writing information search process. (LRW)

  1. Models, Part IV: Inquiry Models.

    ERIC Educational Resources Information Center

    Callison, Daniel

    2002-01-01

    Discusses models for information skills that include inquiry-oriented activities. Highlights include WebQuest, which uses Internet resources supplemented with videoconferencing; Minnesota's Inquiry Process based on the Big Six model for information problem-solving; Indiana's Student Inquiry Model; constructivist learning models for inquiry; and…

  2. Model confirmation in climate economics.

    PubMed

    Millner, Antony; McDermott, Thomas K J

    2016-08-01

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

  3. Model confirmation in climate economics.

    PubMed

    Millner, Antony; McDermott, Thomas K J

    2016-08-01

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

  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. 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.

  6. Making Industry Part of the Climate Solution

    SciTech Connect

    Lapsa, Melissa Voss; Brown, Dr. Marilyn Ann; Jackson, Roderick K; Cox, Matthew; Cortes, Rodrigo; Deitchman, Benjamin H

    2011-06-01

    Improving the energy efficiency of industry is essential for maintaining the viability of domestic manufacturing, especially in a world economy where production is shifting to low-cost, less regulated developing countries. Numerous studies have shown the potential for significant cost-effective energy-savings in U.S. industries, but the realization of this potential is hindered by regulatory, information, workforce, and financial obstacles. This report evaluates seven federal policy options aimed at improving the energy efficiency of industry, grounded in an understanding of industrial decision-making and the barriers to efficiency improvements. Detailed analysis employs the Georgia Institute of Technology's version of the National Energy Modeling System and spreadsheet calculations, generating a series of benefit/cost metrics spanning private and public costs and energy bill savings, as well as air pollution benefits and the social cost of carbon. Two of the policies would address regulatory hurdles (Output-Based Emissions Standards and a federal Energy Portfolio Standard with Combined Heat and Power); three would help to fill information gaps and workforce training needs (the Superior Energy Performance program, Implementation Support Services, and a Small Firm Energy Management program); and two would tackle financial barriers (Tax Lien Financing and Energy-Efficient Industrial Motor Rebates). The social benefit-cost ratios of these policies appear to be highly favorable based on a range of plausible assumptions. Each of the seven policy options has an appropriate federal role, broad applicability across industries, utilizes readily available technologies, and all are administratively feasible.

  7. Climate modelling: Northern Hemisphere circulation.

    PubMed

    Gillett, Nathan P

    2005-09-22

    Air pressure at sea level during winter has decreased over the Arctic and increased in the Northern Hemisphere subtropics in recent decades, a change that has been associated with 50% of the Eurasian winter warming observed over the past 30 years, with 60% of the rainfall increase in Scotland and with 60% of the rainfall decrease in Spain. This trend is inconsistent with the simulated response to greenhouse-gas and sulphate-aerosol changes, but it has been proposed that other climate influences--such as ozone depletion--could account for the discrepancy. Here I compare observed Northern Hemisphere sea-level pressure trends with those simulated in response to all the major human and natural climate influences in nine state-of-the-art coupled climate models over the past 50 years. I find that these models all underestimate the circulation trend. This inconsistency suggests that we cannot yet simulate changes in this important property of the climate system or accurately predict regional climate changes.

  8. Integrated Climate and Carbon-cycle Model

    2006-03-06

    The INCCA model is a numerical climate and carbon cycle modeling tool for use in studying climate change and carbon cycle science. The model includes atmosphere, ocean, land surface, and sea ice components.

  9. Radiance Covariance and Climate Models

    NASA Technical Reports Server (NTRS)

    Haskins, R.; Goody, R.; Chen, L.

    1998-01-01

    Spectral Empirical Orhtogonal Functions (EOFs) derived from the covariance of satellite radiance spectra may be interpreted in terms of the vertical distribution of the covariance of temperature, water vapor, and clouds. The purpose of the investigation is to demonstrate the important constraints that resolved spectral radiances can place upon climate models.

  10. Models, Part V: Composition Models.

    ERIC Educational Resources Information Center

    Callison, Daniel

    2003-01-01

    Describes four models: The Authoring Cycle, a whole language approach that reflects the inquiry process; I-Search, an approach to research that uses the power of student interests; Cultural Celebration, using local heritage topics; and Science Lab Report, for the composition of a lab report. (LRW)

  11. Hierarchical Climate Modeling for Cosmoclimatology

    NASA Astrophysics Data System (ADS)

    Ohfuchi, Wataru

    2010-05-01

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

  12. Developing Grid based infrastructure or climate modeling

    SciTech Connect

    Taylor, J.; Dvorak, M.; Mickelson, S.

    2002-08-15

    In this paper we discuss the development of a high performance climate modeling system as an example of the application of Grid based technology to climate modeling. The climate simulation system at Argonne currently includes a scientific modeling interface (Espresso) written in Java which incorporates Globus middleware to facilitate climate simulations on the Grid. The climate modeling system also includes a high performance version of MM5v3.4 modified for long climate simulations on our 512 processor Linux cluster (Chiba City), an interactive web based tool to facilitate analysis and collaboration via the web, and an enhanced version of the Cave5D software capable of visualizing large climate data sets. We plan to incorporate other climate modeling systems such as the Fast Ocean Atmosphere Model (FOAM) and the National Center for Atmospheric Research's (NCAR) Community Climate Systems Model (CCSM) within Espresso to facilitate their application on computational grids.

  13. Climate Modeling using High-Performance Computing

    SciTech Connect

    Mirin, A A; Wickett, M E; Duffy, P B; Rotman, D A

    2005-03-03

    The Center for Applied Scientific Computing (CASC) and the LLNL Atmospheric Science Division (ASD) are working together to improve predictions of future climate by applying the best available computational methods and computer resources to this problem. Over the last decade, researchers at the Lawrence Livermore National Laboratory (LLNL) have developed a number of climate models that provide state-of-the-art simulations on a wide variety of massively parallel computers. We are now developing and applying a second generation of high-performance climate models. As part of LLNL's participation in DOE's Scientific Discovery through Advanced Computing (SciDAC) program, members of CASC and ASD are collaborating with other DOE labs and NCAR in the development of a comprehensive, next-generation global climate model. This model incorporates the most current physics and numerics and capably exploits the latest massively parallel computers. One of LLNL's roles in this collaboration is the scalable parallelization of NASA's finite-volume atmospheric dynamical core. We have implemented multiple two-dimensional domain decompositions, where the different decompositions are connected by high-speed transposes. Additional performance is obtained through shared memory parallelization constructs and one-sided interprocess communication. The finite-volume dynamical core is particularly important to atmospheric chemistry simulations, where LLNL has a leading role.

  14. 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.

  15. 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.

  16. 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.

  17. Hydroclimate of the Western United States Based on Observations and Regional Climate Simulations of 1981-2000. Part II: Mesoscale ENSO Anomalies

    SciTech Connect

    Leung, Lai R.; Qian, Yun; Bian, Xindi; Hunt, Allen G.

    2003-06-15

    Regional climate of the western U.S. shows clear footprints of interactions between atmospheric circulation and orography. The unique features of the diverse climate regimes challenge climate modeling. These papers provide detailed analyses of observations and regional climate simulations to improve our understanding and modeling of regional climate of the region. Part II focuses on evaluation of simulated interannual climate variability associated with the El Nino-Southern Oscillation.

  18. 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.

  19. 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.

  20. 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.

  1. On the software quality of climate models

    NASA Astrophysics Data System (ADS)

    Pipitone, J.; Easterbrook, S.

    2009-12-01

    A climate model is an executable theory of the climate; the model encapsulates climatological theories in software so that they can be simulated and their implications investigated directly. Thus, in order to trust a climate model one must trust that the software it is built from is robust. Our study explores the nature of software quality in the context of climate modelling: How do we characterise and assess the quality of climate modelling software? We use two major research strategies: (1) analysis of defect densities of leading global climate models and (2) semi-structured interviews with researchers from several climate modelling centres. Defect density analysis is an established software engineering technique for studying software quality. We collected our defect data from bug tracking systems, version control repository comments, and from static analysis of the source code. As a result of our analysis, we characterise common defect types found in climate model software and we identify the software quality factors that are relevant for climate scientists. We also provide a roadmap to achieve proper benchmarks for climate model software quality, and we discuss the implications of our findings for the assessment of climate model software trustworthiness.

  2. A spectral solar/climatic model

    NASA Technical Reports Server (NTRS)

    Sleeper, H. P., Jr.

    1975-01-01

    A summary is presented of pertinent research on solar activity variations and climate variations, together with the presentation of an empirical solar/climatic model that attempts to clarify the nature of the relationships.

  3. 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.

  4. Verification of regional climates of GISS GCM. Part 2: Summer

    NASA Technical Reports Server (NTRS)

    Druyan, Leonard M.; Rind, David

    1989-01-01

    Verification is made of the synoptic fields, sea-level pressure, precipitation rate, 200mb zonal wind and the surface resultant wind generated by two versions of the Goddard Institute for Space Studies (GISS) climate model. The models differ regarding the horizontal resolution of the computation grids and the specification of the sea-surface temperatures. Maps of the regional distributions of seasonal means of the model fields are shown alongside maps that show the observed distributions. Comparisons of the model results with observations are discussed and also summarized in tables according to geographic region.

  5. Verification of regional climates of GISS GCM. Part 1: Winter

    NASA Technical Reports Server (NTRS)

    Druyan, Leonard M.; Rind, David

    1988-01-01

    Verification is made of the synoptic fields, sea level pressure, precipitation rate, 200 mb zonal wind and the surface resultant wind, generated by two versions of the GISS climate model. The models differ regarding the horizontal resolution of the computational grids and the specification of the sea surface temperatures. Maps of the regional distributions of seasonal variations of the model fields are shown alongside maps showing the observed distributions. Comparisons of the model results with observations are discussed, and also summarized in tables according to geographic regions.

  6. 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

  7. Observationally-Based Data/Model Metrics from the Southern Ocean Climate Model Atlas

    NASA Astrophysics Data System (ADS)

    Abell, J.; Russell, J. L.; Goodman, P. J.

    2015-12-01

    The Southern Ocean Climate Model Atlas makes available observationally-based standardized data/model metrics of the latest simulations of climate and projections of climate change from available climate models. Global climate model simulations differ greatly in the Southern Ocean, so the development of consistent, observationally-based metrics, by which to assess the fidelity of model simulations is essential. We will present metrics showing and quantifying the results of the modern day climate simulations over the Southern Ocean from models submitted as part of the CMIP5/IPCC-AR5 process. Our analysis will focus on the simulations of the temperature, salinity and carbon at various depths and along significant hydrographic sections. The models exhibit different skill levels with various metrics between models and also within individual models.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  9. 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

  10. 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.

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

    DOE PAGES

    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 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

  12. 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.

  13. Interpolation of climate variables and temperature modeling

    NASA Astrophysics Data System (ADS)

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

    2012-01-01

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

  14. Climate Modeling using High-Performance Computing

    SciTech Connect

    Mirin, A A

    2007-02-05

    The Center for Applied Scientific Computing (CASC) and the LLNL Climate and Carbon Science Group of Energy and Environment (E and E) are working together to improve predictions of future climate by applying the best available computational methods and computer resources to this problem. Over the last decade, researchers at the Lawrence Livermore National Laboratory (LLNL) have developed a number of climate models that provide state-of-the-art simulations on a wide variety of massively parallel computers. We are now developing and applying a second generation of high-performance climate models. Through the addition of relevant physical processes, we are developing an earth systems modeling capability as well.

  15. Teaching Climate and Culture as Part of Advanced Climate Change Education at the University of North Carolina

    NASA Astrophysics Data System (ADS)

    Heim, R. R.; Voos, G.; Shein, K. A.

    2008-12-01

    A new class, 'Climate and Culture' was introduced at the University of North Carolina Asheville (UNCA) during the 2007-2008 fall semester. This multi-disciplinary course addresses climate, climate change, and climatological impacts on various aspects of society and culture. UNCA's proximity to the NOAA National Climatic Data Center and several climate consultancies allows the university to tap climate specialists for their expertise. Four contemporary climate textbooks provide broad background reading material and are accompanied by a series of guest lecturers who explore a diverse set of issues including climate fundamentals, uncertainty in science and decision-making, natural resources and climate, climate in the media, urban and regional planning for climate change, and the impact of climate change on various socio-economic sectors, developing countries, international negotiations, policy making, and strategies. This paper provides an overview of the 'Climate and Culture' course and discusses its role as part of the UNCA Master of Liberal Arts Degree. Stemming from the success of this course, UNCA is also initiating a graduate program titled: Climate Change and Society, which is an innovative, interdisciplinary graduate program aimed at bridging the gap between climate change science and climate's effects on society. That program will begin offering classes August 2009.

  16. The Los Alamos coupled climate model

    SciTech Connect

    Jones, P.W.; Malone, R.C.; Lai, C.A.

    1998-12-31

    To gain a full understanding of the Earth`s climate system, it is necessary to understand physical processes in the ocean, atmosphere, land and sea ice. In addition, interactions between components are very important and models which couple all of the components into a single coupled climate model are required. A climate model which couples ocean, sea ice, atmosphere and land components is described. The component models are run as autonomous processes coupled to a flux coupler through a flexible communications library. Performance considerations of the model are examined, particularly for running the model on distributed-shared-memory machine architectures.

  17. 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.

  18. 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.

  19. 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”,...

  20. 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

  1. 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

  2. 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

  3. 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.''

  4. Climate modeling with decision makers in mind

    DOE PAGES

    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.

  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. 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.

  7. 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.

  8. 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.

  9. Weighting climate model projections using observational constraints.

    PubMed

    Gillett, Nathan P

    2015-11-13

    Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081-2100 relative to 1986-2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5-95% warming range of 0.8-2.5 K is somewhat lower than the unweighted range of 1.1-2.6 K reported in the IPCC AR5.

  10. 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.

  11. 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.

  12. 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.

  13. Validating Predictions from Climate Envelope Models

    PubMed Central

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

    2013-01-01

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

  14. Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes. Part II. Sensitivity to heterogeneous ice nucleation parameterizations and dust emissions

    DOE PAGES

    Zhang, Yang; Chen, Ying; Fan, Jiwen; Leung, Lai -Yung

    2015-09-14

    Aerosol particles can affect cloud microphysical properties by serving as ice nuclei (IN). Large uncertainties exist in the ice nucleation parameterizations (INPs) used in current climate models. In this Part II paper, to examine the sensitivity of the model predictions to different heterogeneous INPs, WRF-CAM5 simulation using the INP of Niemand et al. (N12) [1] is conducted over East Asia for two full years, 2006 and 2011, and compared with simulation using the INP of Meyers et al. (M92) [2], which is the original INP used in CAM5. M92 calculates the nucleated ice particle concentration as a function of icemore » supersaturation, while N12 represents the nucleated ice particle concentration as a function of temperature and the number concentrations and surface areas of dust particles. Compared to M92, the WRF-CAM5 simulation with N12 produces significantly higher nucleated ice crystal number concentrations (ICNCs) in the northern domain where dust sources are located, leading to significantly higher cloud ice number and mass concentrations and ice water path, but the opposite is true in the southern domain where temperatures and moistures play a more important role in ice formation. Overall, the simulation with N12 gives lower downward shortwave radiation but higher downward longwave radiation, cloud liquid water path, cloud droplet number concentrations, and cloud optical depth. The increase in cloud optical depth and the decrease in downward solar flux result in a stronger shortwave and longwave cloud forcing, and decreases temperature at 2-m and precipitation. Changes in temperature and radiation lower surface concentrations of OH, O₃, SO₄²⁻, and PM2.5, but increase surface concentrations of CO, NO₂, and SO₂ over most of the domain. By acting as cloud condensation nuclei (CCN) and IN, dust particles have different impacts on cloud water and ice number concentrations, radiation, and temperature at 2-m and precipitation depending on whether the

  15. Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes. Part II. Sensitivity to heterogeneous ice nucleation parameterizations and dust emissions

    SciTech Connect

    Zhang, Yang; Chen, Ying; Fan, Jiwen; Leung, Lai -Yung

    2015-09-14

    Aerosol particles can affect cloud microphysical properties by serving as ice nuclei (IN). Large uncertainties exist in the ice nucleation parameterizations (INPs) used in current climate models. In this Part II paper, to examine the sensitivity of the model predictions to different heterogeneous INPs, WRF-CAM5 simulation using the INP of Niemand et al. (N12) [1] is conducted over East Asia for two full years, 2006 and 2011, and compared with simulation using the INP of Meyers et al. (M92) [2], which is the original INP used in CAM5. M92 calculates the nucleated ice particle concentration as a function of ice supersaturation, while N12 represents the nucleated ice particle concentration as a function of temperature and the number concentrations and surface areas of dust particles. Compared to M92, the WRF-CAM5 simulation with N12 produces significantly higher nucleated ice crystal number concentrations (ICNCs) in the northern domain where dust sources are located, leading to significantly higher cloud ice number and mass concentrations and ice water path, but the opposite is true in the southern domain where temperatures and moistures play a more important role in ice formation. Overall, the simulation with N12 gives lower downward shortwave radiation but higher downward longwave radiation, cloud liquid water path, cloud droplet number concentrations, and cloud optical depth. The increase in cloud optical depth and the decrease in downward solar flux result in a stronger shortwave and longwave cloud forcing, and decreases temperature at 2-m and precipitation. Changes in temperature and radiation lower surface concentrations of OH, O₃, SO₄²⁻, and PM2.5, but increase surface concentrations of CO, NO₂, and SO₂ over most of the domain. By acting as cloud condensation nuclei (CCN) and IN, dust particles have different impacts on cloud water and ice number concentrations, radiation, and temperature at 2-m and precipitation depending on

  16. Continental river routing for fully coupled climate system models

    NASA Astrophysics Data System (ADS)

    Graham, Stephen Thomas

    climate. These simulations used the continental runoff as input to the oceans and close the global water cycle in a realistic way that involves the interactions between the land, ocean, ice, and atmospheric components of the model. The results indicate that hydrology is important in global climate models, not only with respect to the land surface, but to all the components that interact to produce climate.* *The dissertation includes a CD that is compound (contains both a paper copy and a CD as part of the dissertation). The CD requires the following applications: Internet access, WinZip.

  17. Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections

    NASA Astrophysics Data System (ADS)

    Sillmann, J.; Kharin, V. V.; Zwiers, F. W.; Zhang, X.; Bronaugh, D.

    2013-03-01

    This study provides an overview of projected changes in climate extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The temperature- and precipitation-based indices are computed with a consistent methodology for climate change simulations using different emission scenarios in the Coupled Model Intercomparison Project Phase 3 (CMIP3) and Phase 5 (CMIP5) multimodel ensembles. We analyze changes in the indices on global and regional scales over the 21st century relative to the reference period 1981-2000. In general, changes in indices based on daily minimum temperatures are found to be more pronounced than in indices based on daily maximum temperatures. Extreme precipitation generally increases faster than total wet-day precipitation. In regions, such as Australia, Central America, South Africa, and the Mediterranean, increases in consecutive dry days coincide with decreases in heavy precipitation days and maximum consecutive 5 day precipitation, which indicates future intensification of dry conditions. Particularly for the precipitation-based indices, there can be a wide disagreement about the sign of change between the models in some regions. Changes in temperature and precipitation indices are most pronounced under RCP8.5, with projected changes exceeding those discussed in previous studies based on SRES scenarios. The complete set of indices is made available via the ETCCDI indices archive to encourage further studies on the various aspects of changes in extremes.

  18. Subsea climate modeling - challenges and first results

    NASA Astrophysics Data System (ADS)

    Rodehacke, Christian; Stendel, Martin; Christensen, Jens; Romanovsky, Vladimir; Marchenko, Sergey

    2015-04-01

    Recent observations indicate that the East Siberian Arctic Shelf (ESAS) releases methane, which stems from shallow hydrate seabed reservoirs. The total amount of carbon within the ESAS is so large that release of only a small fraction, for example via taliks, which are columns of unfrozen sediment within the permafrost, could impact distinctly the global climate. Therefore it is crucial to simulate the future fate of ESAS' subsea permafrost with regard to changing atmospheric and oceanic conditions. However only very few attempts to address the vulnerability of subsea permafrost have been made, instead most studies have focused on the evolution of permafrost since the Late Pleistocene ocean transgression, approximately 14000 years ago. In contrast to land permafrost modeling, any attempt to model the future fate of subsea permafrost needs to consider several additional factors, in particular the dependence of freezing temperature on water depth and salt content and the differences in ground heat flux depending on the seabed properties. Also the amount of unfrozen water in the sediment needs to be taken into account. Using a system of coupled ocean, atmosphere and permafrost models allows us to capture the complexity of the different parts of the system and evaluate the relative importance of different processes. Here we present the first results of a novel approach by means of a dedicated permafrost model which has been driven by oceanic conditions of the Laptev Sea region in East Siberia.

  19. 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

  20. Developing a likely climate scenario from multiple regional climate model simulations with an optimal weighting factor

    NASA Astrophysics Data System (ADS)

    Eum, Hyung-Il; Gachon, Philippe; Laprise, René

    2014-07-01

    This study presents a performance-based comprehensive weighting factor that accounts for the skill of different regional climate models (RCMs), including the effect of the driving lateral boundary condition coming from either atmosphere-ocean global climate models (AOGCMs) or reanalyses. A differential evolution algorithm is employed to identify the optimal relative importance of five performance metrics, and corresponding weighting factors, that include the relative absolute mean error (RAME), annual cycle, spatial pattern, extremes and multi-decadal trend. Based on cumulative density functions built by weighting factors of various RCMs/AOGCMs ensemble simulations, current and future climate projections were then generated to identify the level of uncertainty in the climate scenarios. This study selected the areas of southern Ontario and Québec in Canada as a case study. The main conclusions are as follows: (1) Three performance metrics were found essential, having the greater relative importance: the RAME, annual variability and multi-decadal trend. (2) The choice of driving conditions from the AOGCM had impacts on the comprehensive weighting factor, particularly for the winter season. (3) Combining climate projections based on the weighting factors significantly increased the consistency and reduced the spread among models in the future climate changes. These results imply that the weighting factors play a more important role in reducing the effects of outliers on plausible future climate conditions in regions where there is a higher level of variability in RCM/AOGCM simulations. As a result of weighting, substantial increases in the projected warming were found in the southern part of the study area during summer, and the whole region during winter, compared to the simple equal weighting scheme from RCM runs. This study is an initial step toward developing a likelihood procedure for climate scenarios on a regional scale using equal or different probabilities

  1. Asmparts: assembly of biological model parts.

    PubMed

    Rodrigo, Guillermo; Carrera, Javier; Jaramillo, Alfonso

    2007-12-01

    We propose a new computational tool to produce models of biological systems by assembling models from biological parts. Our software not only takes advantage of modularity, but it also enforces standardisation in part characterisation by considering a model of each part. We have used model parts in SBML to design transcriptional networks. Our software is open source, it works in linux and windows platforms, and it could be used to automatically produce models in a server. Our tool not only facilitates model design, but it will also help to promote the establishment of a registry of model parts.

  2. Asmparts: assembly of biological model parts

    PubMed Central

    Rodrigo, Guillermo; Carrera, Javier

    2008-01-01

    We propose a new computational tool to produce models of biological systems by assembling models from biological parts. Our software not only takes advantage of modularity, but it also enforces standardisation in part characterisation by considering a model of each part. We have used model parts in SBML to design transcriptional networks. Our software is open source, it works in linux and windows platforms, and it could be used to automatically produce models in a server. Our tool not only facilitates model design, but it will also help to promote the establishment of a registry of model parts. PMID:19003441

  3. 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. PMID:24014154

  4. 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.

  5. Advances in ocean modeling for climate change research

    NASA Astrophysics Data System (ADS)

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

    1995-07-01

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

  6. 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.

  7. Modeling Renewable Water Resources under Climate Change

    NASA Astrophysics Data System (ADS)

    Liu, X.; Tang, Q.

    2014-12-01

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

  8. Climate Model Intercomparisons: Preparing for the Next Phase

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  9. Measure the Climate, Model the City

    NASA Astrophysics Data System (ADS)

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

    2011-08-01

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

  10. Climate change and malaria risk in the European part of Russia in 21st century

    NASA Astrophysics Data System (ADS)

    Shartova, N.; Malkhazova, S.

    2009-04-01

    The purpose of this research is development of prognostic model of malaria risk for European part of Russia (EPR) in the 21st century according to climate scenario IPCC "A2". The following issues have been formulated to reach the goal of the research: define the basic epidemiological parameters describing malaria situation and methods of data processing; creating of maps of malaria risk; analysis of changes in malaria distribution for predictable future climate conditions in comparison with conditions of a modern climate. A lot of reasons (biological, social and economic) impact on malaria distribution. Nevertheless, incubation period of the parasite first of all depends on temperature. This is a primary factor that defines a potential area of infection, ability and specificity to transmit malaria. According to this, the model is based on the relationship between climate (average daily temperature) and the intensity of malaria transmission. The object of research is malaria parasite Plasmodium vivax, which has for Russia (particularly for EPR) the greatest importance because it has the lowest minimal temperature threshold for development. Climate data is presented by daily average temperatures of air for three analyzed periods. 1961 -1989 describes a modern climate and corresponds to the minimum 30-year period that is necessary for an assessment of climate and changes connected with biotic components. Prognostic malaria model is based on predicted daily average temperatures for 2046-2065 (the middle of century) and 2089-2100 (the end of century). All data sets for EPR are presented in the grid 2x2. The conclusion on possible changes in malaria distribution and transmission in the middle and the end of the 21st century: There is going to be the increase of duration of effective temperatures period (period when parasite development is possible), period of effective susceptibility to infection of mosquitoes (period when malaria transmission cycle is possible); shift

  11. 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.

  12. Influence of Regional Climate Model spatial resolution on wind climates

    NASA Astrophysics Data System (ADS)

    Pryor, S. C.; Barthelmie, R. J.; Nikulin, G.; Jones, C.

    2010-12-01

    Global and regional climate models are being run at increasingly fine horizontal and vertical resolution with the goal of increased skill. However, relatively few studies have quantified the change in modeled wind climates that derives from applying a Regional Climate Model (RCM) at varying resolutions, and the response to varying resolution may be highly non-linear since most models run in climate mode are hydrostatic. Thus, herein we examine the influence of grid-resolution on modelled wind speeds and gusts and derived extremes thereof over southern Scandinavia using output from the Rossby Centre (RCA3) RCM run at four different resolutions from 50 x 50 km to 6 x 6 km, and with two different vertical grid-spacings. Domain averaged fifty-year return period wind speeds and wind gusts derived using the method of moments approach to compute the Gumbel parameters, increase with resolution (Table 1), though the change is strongly mediated by the model grid-cell surface characteristics. Power spectra of the 3-hourly model time-step ‘instantaneous’ wind speeds and daily wind gusts at all four resolutions show clear peaks in the variance associated with bi-annual, annual, seasonal and synoptic frequencies. The variance associated with these peaks is enhanced with increased resolution, though not in a monotonic fashion, and is more marked in wind gusts than wind speeds. Relative to in situ observations, the model generally underestimates the variance, particularly associated with the synoptic time scale, even for the highest resolution simulations. There is some evidence to suggest that the change in the power spectra with horizontal resolution is less marked in the transition from 12.5 km to 6.25 km, than from 50 to 25 km, or 25 km to 12.5 km.Table 1. Domain averaged mean annual wind speed (U), 50-year return period extreme wind speed (U50yr) and wind gust (Gust50yr) (m/s) from the four RCA3 simulations at different resolution based on output from 1987-2008. The

  13. A Climate Driven Speleothem Stable Isotope Model

    NASA Astrophysics Data System (ADS)

    Shorey, C. V.; Gonzalez, L. A.

    2004-12-01

    We have constructed a climate driven stalagmite growth model that faithfully reproduces the major annual growth trends of temperate climate stalagmites. Model results indicate that speleothem growth rate in temperate regions, although depending primarily on precipitation amount, is a complex function of the timing of precipitation relative to seasonal temperature changes as well as other non-climatic parameters. We have incorporated into this climate driven growth model the capability to simulate climate driven carbon and oxygen stable isotope changes and their incorporation in speleothem calcite. The model allows us to investigate the relationship between isotopic changes in soil CO2 and seepage fluids, and the isotopic composition of the growing stalagmite. We also explore the impact of sampling resolution on the extracted speleothem isotope record. We calibrated the model to replicate the growth and isotopic record of a stalagmite collected in 1982 from Mystery Cave State Park, in Southeastern Minnesota and using temperature and precipitation records spanning 1935-1982 from a nearby weather station. The model generally replicates the \\delta13C and \\delta18O record for this case. Model ouput indicates that that large deviations of temperature or precipitation from average conditions in a single year can be recorded in speleothems. Increases in temperature have a clear postive correlation with \\delta13C values, and a less direct negative correlation with \\delta18O values. Increases in precipitation have an inconsistent positive correlation with \\delta13C values and a clear positive correlation with \\delta18O values.

  14. 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

  15. Introduction. Stochastic physics and climate modelling.

    PubMed

    Palmer, T N; Williams, P D

    2008-07-28

    Finite computing resources limit the spatial resolution of state-of-the-art global climate simulations to hundreds of kilometres. In neither the atmosphere nor the ocean are small-scale processes such as convection, clouds and ocean eddies properly represented. Climate simulations are known to depend, sometimes quite strongly, on the resulting bulk-formula representation of unresolved processes. Stochastic physics schemes within weather and climate models have the potential to represent the dynamical effects of unresolved scales in ways which conventional bulk-formula representations are incapable of so doing. The application of stochastic physics to climate modelling is a rapidly advancing, important and innovative topic. The latest research findings are gathered together in the Theme Issue for which this paper serves as the introduction.

  16. 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

  17. Using simple chaotic models to interpret climate under climate change: Implications for probabilistic climate prediction

    NASA Astrophysics Data System (ADS)

    Daron, Joseph

    2010-05-01

    Exploring the reliability of model based projections is an important pre-cursor to evaluating their societal relevance. In order to better inform decisions concerning adaptation (and mitigation) to climate change, we must investigate whether or not our models are capable of replicating the dynamic nature of the climate system. Whilst uncertainty is inherent within climate prediction, establishing and communicating what is plausible as opposed to what is likely is the first step to ensuring that climate sensitive systems are robust to climate change. Climate prediction centers are moving towards probabilistic projections of climate change at regional and local scales (Murphy et al., 2009). It is therefore important to understand what a probabilistic forecast means for a chaotic nonlinear dynamic system that is subject to changing forcings. It is in this context that we present the results of experiments using simple models that can be considered analogous to the more complex climate system, namely the Lorenz 1963 and Lorenz 1984 models (Lorenz, 1963; Lorenz, 1984). Whilst the search for a low-dimensional climate attractor remains illusive (Fraedrich, 1986; Sahay and Sreenivasan, 1996) the characterization of the climate system in such terms can be useful for conceptual and computational simplicity. Recognising that a change in climate is manifest in a change in the distribution of a particular climate variable (Stainforth et al., 2007), we first establish the equilibrium distributions of the Lorenz systems for certain parameter settings. Allowing the parameters to vary in time, we investigate the dependency of such distributions to initial conditions and discuss the implications for climate prediction. We argue that the role of chaos and nonlinear dynamic behaviour ought to have more prominence in the discussion of the forecasting capabilities in climate prediction. References: Fraedrich, K. Estimating the dimensions of weather and climate attractors. J. Atmos. Sci

  18. A Climate Process Team focused on better representation of aerosol indirect effects in climate models through improved cloud macrophysical parameterization

    NASA Astrophysics Data System (ADS)

    Wood, R.; Larson, V. E.; Donner, L.; Golaz, J.; Guo, H.; Gettelman, A.; Morrison, H.; Bogenschutz, P.; Feingold, G.; Yamaguchi, T.; Lee, S.; Stephens, G. L.; Lebsock, M. D.; Kubar, T. L.; Grosvenor, D. P.

    2011-12-01

    The representation of aerosol indirect effects (AIEs) in climate models is hampered in part by a poor representation of cloud macrophysical processes. Accurate representation of AIEs involves a complex interplay between cloud microphysics, turbulent dynamics, and radiation. This presentation describes the goals, progress, and future activities of a NSF/NOAA Climate Process Team focused on the improved representation of cloud macrophysical processes through the incorporation of a unified cloud and turbulence scheme into two of the leading US climate models (NCAR CAM, GFDL AM3). We describe how a combination of process modeling, field observations, and single column modeling can be used to improve model physics. We then describe progress in the implementation of the scheme in the full climate model. We describe observational metrics from satellites that the team is using to establish the fidelity of the model results and guide future model development.

  19. 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

  20. 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

  1. The role of large-scale eddies in the climate equilibrium. Part 2: Variable static stability

    NASA Technical Reports Server (NTRS)

    Zhou, Shuntai; Stone, Peter H.

    1993-01-01

    Lorenz's two-level model on a sphere is used to investigate how the results of Part 1 are modified when the interaction of the vertical eddy heat flux and static stability is included. In general, the climate state does not depend very much on whether or not this interaction is included, because the poleward eddy heat transport dominates the eddy forcing of mean temperature and wind fields. However, the climatic sensitivity is significantly affected. Compared to two-level model results with fixed static stability, the poleward eddy heat flux is less sensitive to the meridional temperature gradient and the gradient is more sensitive to the forcing. For example, the logarithmic derivative of the eddy flux with respect to the gradient has a slope that is reduced from approximately 15 on a beta-plane with fixed static stability and approximately 6 on a sphere with fixed static stability, to approximately 3 to 4 in the present model. This last result is more in line with analyses from observations. The present model also has a stronger baroclinic adjustment than that in Part 1, more like that in two-level beta-plane models with fixed static stability, that is, the midlatitude isentropic slope is very insensitive to the forcing, the diabatic heating, and the friction, unless the forcing is very weak.

  2. 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

  3. COMPARING MODEL RESULTS TO NATIONAL CLIMATE POLICY GOALS: RESULTS FROM THE ASIA MODELING EXERCISE

    SciTech Connect

    Calvin, Katherine V.; Fawcett, Allen A.; Jiang, Kejun

    2012-12-01

    While the world has yet to adopt a single unified policy to limit climate change, many countries and regions have adopted energy and climate policies that have implications for global emissions. In this paper, we discuss a few key policies and how they are included in a set of 24 energy and integrated assessment models that participated in the Asia Modeling Exercise. We also compare results from these models for a small set of stylized scenarios to the pledges made as part of the Copenhagen Accord and the goals stated by the Major Economies Forum. We find that the targets outlined by the United States, the European Union, Japan, and Korea require significant policy action in most of the models analyzed. For most of the models in the study, however, the goals outlined by India are met without any climate policy. The stringency of climate policy required to meet China’s Copenhagen pledges varies across models and accounting methodologies.

  4. 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.

  5. Modelling rainfall erosion resulting from climate change

    NASA Astrophysics Data System (ADS)

    Kinnell, Peter

    2016-04-01

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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

    2013-05-01

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

  11. 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

  12. Hydrologic Response to Climate Variability, Climate Change, and Climate Extreme in the U.S.: Climate Model Evaluation and Projections

    SciTech Connect

    Leung, Lai R.; Qian, Yun

    2005-08-01

    Water resources are sensitive to climate variability and change; predictions of seasonal to interannual climate variations and projections of long-term climate trends can provide significant values in managing water resources. This study examines the control (1975–1995) and future (1995–2100) climate simulated by a global climate model (GCM) and a regional climate simulation driven by the GCM control simulation for the U.S. Comparison of the regional climate simulation with observations across 13 subregions showed that the simulation captured the seasonality and the distributions of precipitation rate quite well. The GCM control and climate change simulations showed that, as a result of a 1% increase in greenhouse gas concentrations per year, there will be a warming of 2–3°C across the U.S. from 2000 to 2100. Although precipitation is not projected to change during this century, the warming trend will increase evapotranspiration to reduce annual basin mean runoff over five subregions along the coastal and south-central U.S.

  13. Utilizing Cloud Computing to Improve Climate Modeling and Studies

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  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. 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.

  16. Modeling Evapotranspiration in Subtropical Climate

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Evapotranspiration loss is estimated at about 80% of annual precipitation in south Florida. Accurate prediction of evapotranspiration is important during and beyond the implementation of the Comprehensive Everglades Restoration Project(CERP). In the USDA’s Everglades Agro-Hydrology Model (EAHM) the...

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  18. Making the climate part of the human world: Why addressing beliefs and biases is necessary part of effective climate change education

    NASA Astrophysics Data System (ADS)

    Donner, S. D.

    2009-12-01

    Efforts to raise public awareness and understanding of the social, cultural and economic consequences of climate change often encounter skepticism. The primary causes of this skepticism, whether in the form of a mild rejection of proposed policy responses or an outright rejection of the basic scientific findings, is often cited to be the poor framing of issues by the scientific community, the quality of science education or public science literacy, disinformation campaigns by representatives of the coal and gas industry, individual resistance to behavioral change, and the hyperactive nature of the modern information culture. However, the root cause may be that the weather and climate, and by association climate change, is viewed as independent of the sphere of human influence in ancient and modern societies. In this presentation, I will outline how long-standing human beliefs in the separation between the earth and the sky and the modern framing of climate change as an “environmental” issue are limiting efforts to education the public about the causes, effects and possible response to climate change. First, sociological research in the Pacific Islands (Fiji, Kiribati, Tuvalu) finds strong evidence that beliefs in divine control of the weather and climate limit public acceptance of human-induced climate change. Second, media analysis and polling data from North America supports the role of belief and provides further evidence that climate change is viewed as a threat to an “other” labeled “the environment”, rather than a threat to people or society. The consequences of these mental models of the climate can be an outright reject of scientific theory related to climate change, a milder distrust of climate change predictions, a lack of urgency about mitigation, and an underestimate of the effort required to adapt to climate change. In order to be effective, public education about climate change needs to directly address the two, critical beliefs held by

  19. The impact of ARM on climate modeling

    DOE PAGES

    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, themore » atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM).« less

  20. Climate Change Education as an Integral Part of the United Nations Framework Convention on Climate Change

    ERIC Educational Resources Information Center

    Journal of Education for Sustainable Development, 2012

    2012-01-01

    The United Nations Framework Convention on Climate Change (UNFCCC), through its Article 6, and the Convention's Kyoto Protocol, through its Article 10 (e), call on governments to develop and implement educational programmes on climate change and its effects. In particular, Article 6 of the Convention, which addresses the issue of 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. 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

  3. 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.

  4. Instructional Climates in Preschool Children Who Are At-Risk. Part II: Perceived Physical Competence

    ERIC Educational Resources Information Center

    Robinson, Leah E.; Rudisill, Mary E.; Goodway, Jacqueline D.

    2009-01-01

    In Part II of this study, we examined the effect of two 9-week instructional climates (low-autonomy [LA] and mastery motivational climate [MMC]) on perceived physical competence (PPC) in preschoolers (N = 117). Participants were randomly assigned to an LA, MMC, or comparison group. PPC was assessed by a pretest, posttest, and retention test with…

  5. 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.

  6. Big Data and Data Models for Climate System Energetics

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed

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

    2004-06-01

    The Swedish Regional Climate Modelling Programme, SWECLIM, was a 6.5-year national research network for regional climate modeling, regional climate change projections and hydrological impact assessment and information to a wide range of stakeholders. Most of the program activities focussed on the regional climate system of Northern Europe. This led to the establishment of an advanced, coupled atmosphere-ocean-hydrology regional climate model system, a suite of regional climate change projections and progress on relevant data and process studies. These were, in turn, used for information and educational purposes, as a starting point for impact analyses on different societal sectors and provided contributions also to international climate research. PMID:15264594

  8. Climate Modeling Computing Needs Assessment

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  9. Toward a high performance distributed memory climate model

    SciTech Connect

    Wehner, M.F.; Ambrosiano, J.J.; Brown, J.C.; Dannevik, W.P.; Eltgroth, P.G.; Mirin, A.A.; Farrara, J.D.; Ma, C.C.; Mechoso, C.R.; Spahr, J.A.

    1993-02-15

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

  10. Selection of climate change scenario data for impact modelling.

    PubMed

    Sloth Madsen, M; Maule, C Fox; MacKellar, N; Olesen, J E; Christensen, J Hesselbjerg

    2012-01-01

    Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.

  11. World Climate Research Programme (WCRP) Coupled Model Intercomparison Project phase 3 (CMIP3): Multi-Model Dataset Archive at PCMDI (Program for Climate Model Diagnosis and Intercomparison)

    DOE Data Explorer

    In response to a proposed activity of the WCRP's Working Group on Coupled Modelling (WGCM),PCMDI volunteered to collect model output contributed by leading modeling centers around the world. Climate model output from simulations of the past, present and future climate was collected by PCMDI mostly during the years 2005 and 2006, and this archived data constitutes phase 3 of the Coupled Model Intercomparison Project (CMIP3). In part, the WGCM organized this activity to enable those outside the major modeling centers to perform research of relevance to climate scientists preparing the Fourth Asssessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The IPCC was established by the World Meteorological Organization and the United Nations Environmental Program to assess scientific information on climate change. The IPCC publishes reports that summarize the state of the science. This unprecedented collection of recent model output is officially known as the WCRP CMIP3 multi-model dataset. It is meant to serve IPCC's Working Group 1, which focuses on the physical climate system - atmosphere, land surface, ocean and sea ice - and the choice of variables archived at the PCMDI reflects this focus. A more comprehensive set of output for a given model may be available from the modeling center that produced it. As of November 2007, over 35 terabytes of data were in the archive and over 303 terabytes of data had been downloaded among the more than 1200 registered users. Over 250 journal articles, based at least in part on the dataset, have been published or have been accepted for peer-reviewed publication. Countries from which models have been gathered include Australia, Canada, China, France, Germany and Korea, Italy, Japan, Norway, Russia, Great Britain and the United States. Models, variables, and documentation are collected and stored. Check http://www-pcmdi.llnl.gov/ipcc/data_status_tables.htm to see at a glance the output that is available

  12. 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

  13. 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

  14. Challenging some tenets of Regional Climate Modelling

    NASA Astrophysics Data System (ADS)

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

    2008-08-01

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

  15. 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

  16. Continental-scale river flow in climate models

    NASA Technical Reports Server (NTRS)

    Miller, James R.; Russell, Gary L.; Caliri, Guilherme

    1994-01-01

    The hydrologic cycle is a major part of the global climate system. There is an atmospheric flux of water from the ocean surface to the continents. The cycle is closed by return flow in rivers. In this paper a river routing model is developed to use with grid box climate models for the whole earth. The routing model needs an algorithm for the river mass flow and a river direction file, which has been compiled for 4 deg x 5 deg and 2 deg x 2.5 deg resolutions. River basins are defined by the direction files. The river flow leaving each grid box depends on river and lake mass, downstream distance, and an effective flow speed that depends on topography. As input the routing model uses monthly land source runoff from a 5-yr simulation of the NASA/GISS atmospheric climate model (Hansen et al.). The land source runoff from the 4 deg x 5 deg resolution model is quartered onto a 2 deg x 2.5 deg grid, and the effect of grid resolution is examined. Monthly flow at the mouth of the world's major rivers is compared with observations, and a global error function for river flow is used to evaluate the routing model and its sensitivity to physical parameters. Three basinwide parameters are introduced: the river length weighted by source runoff, the turnover rate, and the basinwide speed. Although the values of these parameters depend on the resolution at which the rivers are defined, the values should converge as the grid resolution becomes finer. When the routing scheme described here is coupled with a climate model's source runoff, it provides the basis for closing the hydrologic cycle in coupled atmosphere-ocean models by realistically allowing water to return to the ocean at the correct location and with the proper magnitude and timing.

  17. Continental-scale river flow in climate models

    SciTech Connect

    Miller, J.R. ); Russell, G.L. ); Caliri, G. )

    1994-06-01

    The hydrologic cycle is a major part of the global climate system. There is an atmospheric flux of water from the ocean surface to the continents. The cycle is closed by return flow in rivers. In this paper a river routing model is developed, to use with grid box climate models for the whole earth. The routing model needs an algorithm for the river mass flow and a river direction file, which has been compiled for 4[degrees] x 5[degrees] and 2[degrees] x 2.5[degrees] resolutions. River basins are defined by the direction files. The river flow leaving each grid box depends on river and lake mass, downstream distance, and an effective flow speed that depends on topography. As input the routing model uses monthly land source runoff from a 5-yr simulation of the NASA/GISS atmospheric climate model. The land source runoff from the 4[degrees] x 5[degrees] resolution model is quartered onto a 2[degrees] x 2.5[degrees] grid, and the effect of grid resolution is examined. Monthly flow at the mouth of the world's major rivers is compared with observations, and a global error function for river flow is used to evaluate the routing model and its sensitivity to physical parameters. Three basinwide parameters are introduced: the river length weighted by source runoff, the turnover rate, and the basinwide speed. Although the values of these parameters depend on the resolution at which the rivers are defined, the values should converge as the grid resolution becomes finer. When the routing scheme described here is coupled with a climate model's source runoff, it provides the basis for closing the hydrologic cycle in coupled atmosphere-ocean models by realistically allowing water to return to the ocean at the correct location and with the proper magnitude and timing. 26 refs., 10 figs., 4 tabs.

  18. Modeling Arctic Climate with a Regional Arctic System Model (RASM)

    NASA Astrophysics Data System (ADS)

    Cassano, J. J.; Duvivier, A.; Hughes, M.; Roberts, A.; Brunke, M.; Fisel, B. J.; Gutowski, W. J.; Maslowski, W.; Nijssen, B.; Osinski, R.; Zeng, X.

    2013-12-01

    A new regional Earth system model of the Arctic, the Regional Arctic System Model (RASM), has recently been developed. The initial version of this model includes atmosphere (WRF), ocean (POP), sea ice (CICE), and land (VIC) component models coupled with the NCAR CESM CPL7 coupler. The model is configured to run on a large pan-Arctic domain that includes all sea ice covered waters in the Northern Hemisphere and all Arctic Ocean draining land areas. Results from multi-decadal (1989 to present) simulations with RASM will be presented and will focus on the model's representation of atmosphere, ocean, sea ice, and land surface climate, emphasizing both strengths and weaknesses of the current model climate and comparisons with atmosphere-only WRF simulations. Results from the model show both areas of improvement and degraded results relative to stand-alone WRF. Improvement in the coupled model climate are related to more physically realistic representation of coupled processes such as energy transfer from the ocean to the atmosphere through leads in the sea ice during winter. Degraded results come from feedbacks in model component biases, such as atmospheric circulation biases resulting in incorrect local sea ice cover that then result in large local atmospheric temperature biases. The issue of spectral nudging in a coupled regional climate model system as well as other lessons learned during the development of RASM will be discussed. The presentation will conclude with future plans for RASM.

  19. 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.

  20. Load-balancing algorithms for climate models

    SciTech Connect

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

    1994-06-01

    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 de scribe 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.

  1. High-Resolution Dynamical Downscaling of ERA-Interim Using the WRF Regional Climate Model for the Area of Poland. Part 2: Model Performance with Respect to Automatically Derived Circulation Types

    NASA Astrophysics Data System (ADS)

    Ojrzyńska, Hanna; Kryza, Maciej; Wałaszek, Kinga; Szymanowski, Mariusz; Werner, Małgorzata; Dore, Anthony J.

    2016-03-01

    This paper presents the application of the high-resolution WRF model data for the automatic classification of the atmospheric circulation types and the evaluation of the model results for daily rainfall and air temperatures. The WRF model evaluation is performed by comparison with measurements and gridded data (E-OBS). The study is focused on the area of Poland and covers the 1981-2010 period, for which the WRF model has been run using three nested domains with spatial resolution of 45 km × 45 km, 15 km × 15 km and 5 km × 5 km. For the model evaluation, we have used the data from the innermost domain, and data from the second domain were used for circulation typology. According to the circulation type analysis, the anticyclonic types (AAD and AAW) are the most frequent. The WRF model is able to reproduce the daily air temperatures and the error statistics are better, compared with the interpolation-based gridded dataset. The high-resolution WRF model shows a higher spatial variability of both air temperature and rainfall, compared with the E-OBS dataset. For the rainfall, the WRF model, in general, overestimates the measured values. The model performance shows a seasonal pattern and is also dependent on the atmospheric circulation type, especially for daily rainfall.

  2. 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.

  3. Application and impacts of the GlobeLand30 land cover dataset on the Beijing Climate Center Climate Model

    NASA Astrophysics Data System (ADS)

    Shi, X.; Nie, S.; Ju, W.; Yu, L.

    2016-04-01

    Land cover (LC) is a necessary and important input variable of the land surface and climate model, and has significant impacts on climate and climate changes. In this paper, the new higher-resolution global LC dataset, GlobeLand30, was employed in the Beijing Climate Center Climate System Model (BCC_CSM) to investigate LC impacts on the land surface and climate via simulation experiments. The strategy for connecting the new LC dataset and model was to merge the GlobeLand30 data with other satellite remote sensing datasets to enlarge the plant function types (PFT) fitted for the BCC_CSM. The area-weighted up-scaling approach was used to aggregate the 30m-resolution GlobeLand30 data onto the coarser model grids and derive PFT as well as percentage information. The LC datasets of GlobeLand30 and the original BCC_CSM had generally consistent spatial features but with significant differences. Numerical simulations with these two LC datasets were conducted and compared to present the effects of the new GlobeLand30 data on the climate. Results show that with the new LC data products, several model biases between simulations and observations in the BCC climate model with original LC datasets were effectively reduced, including the positive bias of precipitation in the mid-high latitude of the northern hemisphere and the negative bias in the Amazon, as well as the negative bias of air temperature in part of the southern hemisphere. Therefore, the GlobeLand30 data are suitable for use in the BCC_CSM component models and can improve the performance of climate simulations.

  4. Climate Change Impacts for the Conterminous USA: An Integrated Assessment Part 5. Irrigated Agriculture and National Grain Crop Production

    SciTech Connect

    Thomson, Allison M.; Rosenberg, Norman J.; Izaurralde, Roberto C.; Brown, Robert A.

    2005-04-01

    Over the next century global warming will lead to changes in weather patterns, affecting many aspects of our environment. In the United States, the one sector of the economy most likely to be directly impacted by the changes in climate is agriculture. We have examined potential changes in dryland agriculture (Part 2) and in water resources necessary for crop production (Part 3). Here we assess to what extent, under a set of climate change scenarios, water supplies will be sufficient to meet the irrigation requirement of major grain crops in the U.S. In addition, we assess the overall impacts of changes in water supply on national grain production. We applied 12 climate change scenarios based on the predictions of General Circulation Models to a water resources model and a crop growth simulator for the conterminous United States. We calculate national production in current crop growing regions by applying irrigation where it is necessary and water is available. Irrigation declines under all climate change scenarios employed in this study. In certain regions and scenarios, precipitation declines so much that water supplies are too limited; in other regions it plentiful enough that little value is derived from irrigation. Total crop production is greater when irrigation is applied, but corn and soybean production declines under most scenarios. Winter wheat production responds significantly to elevated atmospheric CO2 and appears likely to increase under climate change.

  5. 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.

  6. Explosive cyclones in CMIP5 climate models

    NASA Astrophysics Data System (ADS)

    Seiler, C.; Zwiers, F. W.

    2014-12-01

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

  7. 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.

  8. Toxicological Models Part B: Environmental Models

    NASA Astrophysics Data System (ADS)

    Garric, Jeanne; Thybaud, Eric

    Assessment of ecotoxicological risks due to chemical substances is based in part on establishing concentration-response relationships for different organisms, including plants, invertebrates, and vertebrates living on land, fresh water, or sea water. European regulations for assessing the risks due to chemical products thus recommend the measurement of toxic effects on at least three taxons (algae, crustacea, fish) [1]. The assessment becomes more relevant when based upon a variety of different organisms, with a range of different biological and ecological features (autotrophic or heterotrophic, benthic or pelagic habitat, and different modes of reproduction, growth, respiration, or feeding, etc.), but also when it describes the effects of contaminants on sensitive physiological functions such as growth and reproduction, which determine the balance of populations of terrestrial and aquatic species in their environment.

  9. Climate Change Impacts for the Conterminous USA: An Integrated Assessment Part 1. Scenarios and Context

    SciTech Connect

    Smith, Steven J.; Thomson, Allison M.; Rosenberg, Norman J.; Izaurralde, R Cesar C.; Brown, Robert A.; Wigley, T. M.

    2005-04-01

    As CO2 and other greenhouse gasses accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how a changing climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using a suite of climate change projections from General Circulation Models (GCMs) and three biophysical models. In this paper we present the climate change scenarios used to drive the impact analyses. The assumed levels of global-mean climate changes are discussed and placed in the context of recent work on climate-change scenarios for the next 100 years. The spatial variation of these changes given by the GCM results used for the impact analyses are also discussed.

  10. 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

  11. Cyclones and extreme windstorm events over Europe under climate change: Global and regional climate model diagnostics

    NASA Astrophysics Data System (ADS)

    Leckebusch, G. C.; Ulbrich, U.

    2003-04-01

    More than any changes of the climate system mean state conditions, the development of extreme events may influence social, economic and legal aspects of our society. This linkage results from the impact of extreme climate events (natural hazards) on environmental systems which again are directly linked to human activities. Prominent examples from the recent past are the record breaking rainfall amounts of August 2002 in central Europe which produced widespread floodings or the wind storm Lothar of December 1999. Within the MICE (Modelling the Impact of Climate Extremes) project framework an assessment of the impact of changes in extremes will be done. The investigation is carried out for several different impact categories as agriculture, energy use and property damage. Focus is laid on the diagnostics of GCM and RCM simulations under different climate change scenarios. In this study we concentrate on extreme windstorms and their relationship to cyclone activity in the global HADCM3 as well as in the regional HADRM3 model under two climate change scenarios (SRESA2a, B2a). In order to identify cyclones we used an objective algorithm from Murry and Simmonds which was widely tested under several different conditions. A slight increase in the occurrence of systems is identified above northern parts of central Europe for both scenarios. For more severe systems (core pressure < 990 hPa) we find an increase for western Europe. Strong wind events can be defined via different percentile values of the windspeed (e.g. above the 95 percentile). By this means the relationship between strong wind events and cyclones is also investigated. For several regions (e.g. Germany, France, Spain) a shift to more deep cyclones connected with an increasing number of strong wind events is found.

  12. 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.

  13. Induced technological change with applications to modeling of climate-change policies

    SciTech Connect

    Nordhaus, Wiliam D.

    2002-04-01

    This grant supported research on induced innovation in the energy sector and the implications of induced innovation for climate change and climate-change policy. The first part of the research investigated the impact of energy prices on inventive activity focusing on the energy sector. The purpose was to improve our understanding of the determinants of inventive activity and to examine a number of hypotheses and specifications of the relationship. The second part incorporated the theoretical specifications and empirical results of the first part into the DICE integrated assessment models of climate change. This resulted in a revised model, known as the ''R&DICE model,'' and the major results are forthcoming in Grubler, Nakicenovic, and Nordhaus (GNN), ''Induced Technological Change and the Environment, Resources for the Future'', Washington, D.C., 2002, in a chapter entitled, ''Modeling Induced Innovation in Climate-Change Policy.''

  14. Creating a New Model for Mainstreaming Climate Change Adaptation for Critical Infrastructure: The New York City Climate Change Adaptation Task Force and the NYC Panel on Climate Change

    NASA Astrophysics Data System (ADS)

    Rosenzweig, C.; Solecki, W. D.; Freed, A. M.

    2008-12-01

    The New York City Climate Change Adaptation Task Force, launched in August 2008, aims to secure the city's critical infrastructure against rising seas, higher temperatures and fluctuating water supplies projected to result from climate change. The Climate Change Adaptation Task Force is part of PlaNYC, the city's long- term sustainability plan, and is composed of over 30 city and state agencies, public authorities and companies that operate the region's roads, bridges, tunnels, mass transit, and water, sewer, energy and telecommunications systems - all with critical infrastructure identified as vulnerable. It is one of the most comprehensive adaptation efforts yet launched by an urban region. To guide the effort, Mayor Michael Bloomberg has formed the New York City Panel on Climate Change (NPCC), modeled on the Intergovernmental Panel on Climate Change (IPCC). Experts on the panel include climatologists, sea-level rise specialists, adaptation experts, and engineers, as well as representatives from the insurance and legal sectors. The NPCC is developing planning tools for use by the Task Force members that provide information about climate risks, adaptation and risk assessment, prioritization frameworks, and climate protection levels. The advisory panel is supplying climate change projections, helping to identify at- risk infrastructure, and assisting the Task Force in developing adaptation strategies and guidelines for design of new structures. The NPCC will also publish an assessment report in 2009 that will serve as the foundation for climate change adaptation in the New York City region, similar to the IPCC reports. Issues that the Climate Change Adaptation Task Force and the NPCC are addressing include decision- making under climate change uncertainty, effective ways for expert knowledge to be incorporated into public actions, and strategies for maintaining consistent and effective attention to long-term climate change even as municipal governments cycle

  15. 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.

  16. 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

  17. 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.

  18. Downscaling GISS ModelE boreal summer climate over Africa

    NASA Astrophysics Data System (ADS)

    Druyan, Leonard M.; Fulakeza, Matthew

    2015-11-01

    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.

  19. 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.

  20. Modelling the hydrological cycle in assessments of climate change

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  1. Recent Advances in Regional Climate System Modeling and ClimateChange Analyses of Extreme Heat

    SciTech Connect

    Miller, Norman L.

    2004-09-24

    During the period May 2003 to May 2004, there were two CEC/PIER funded primary research activities by the Atmosphere and Ocean Sciences Group/Earth Science Division at LBNL. These activities are the implementation and testing of the National Center for Atmospheric Research Community Land Model (CLM) into MM5, and the analysis of extreme heat days under a new set of climate simulations. The new version of MM5,MM5-CLM, has been tested for a 90 day snowmelt period in the northwestern U.S. Results show that this new code upgrade, as compared to the MM5-NOAH, has improved snowmelt, temperature, and precipitation when compared to observations. These are due in part to a subgrid scheme,advanced snow processes, and advanced vegetation. The climate change analysis is the upper and lower IPCC Special Report on Emission Scenarios, representing fossil fuel intensive and energy conserving future emission scenarios, and medium and low sensitivity Global Climate Models. Results indicate that California cities will see increases in the number of heat wave and temperature threshold days from two to six times.These results may be viewed as potential outcomes based on today's decisions on emissions.

  2. A Saturnian stratospheric seasonal climate model

    NASA Technical Reports Server (NTRS)

    Cess, R. D.; Caldwell, J.

    1979-01-01

    Motivated by recent observational evidence that seasonal processes occur within Saturn's stratosphere, a seasonal stratospheric climate model has been constructed. This model predicts stratospheric temperatures above the P = 0.1-atm level as a function of time throughout the Saturnian year. Specific results are presented for south-polar and equatorial temperatures. The model predicts that substantial seasonal phase lags exist; maximum stratospheric temperatures at the south pole occur at the southern hemisphere's autumnal equinox. Brightness temperature observations at 17.8 microns, taken during 1977/1978, indicate that stratospheric temperatures are greater at the south pole than at the equator. The model is consistent with these observations, predicting enhanced south polar temperatures, relative to the equator, from 1975 to 1983.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  5. A cloud-radiation climate model

    SciTech Connect

    Yi, C.; Wu, R.

    1996-12-31

    Choosing the global average surface temperature T and cloudiness n as state variables, the relations of planetary albedo {alpha} and the atmospheric effective emissivity {epsilon} with the state variables are developed to study the important feedback processes in the climate system. They lead to a highly simplified nonlinear climate model which shows a self organization mechanism for cloud-radiation interaction. Solar radiation directly affects the surface temperature by which cloudiness changes are driven. The cloudiness changes in turn react on the surface temperature by the planetary albedo {alpha} and the atmospheric effective emittance {epsilon}. In the processes of cooperation and competition between the two subsystems, the surface temperature dominates and cloudiness responds rapidly to the surface temperature. Near the Hopf bifurcation, the analytical solutions of the limit cycle are obtained which are in agreement with numerical solutions. With these analytical solutions, the effects of solar radiation and carbon dioxide on the amplitude, period and phase lag are examined. The authors find that in addition to increasing temperature, an increase in concentration of atmospheric carbon dioxide could enhance sharply the amplitudes of climate oscillation. This implies that increasing carbon dioxide could periodically bring about hazardous impacts.

  6. 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

  7. From climate model ensembles to statistics: Introducing the "wux" package

    NASA Astrophysics Data System (ADS)

    Mendlik, Thomas; Heinrich, Georg; Gobiet, Andreas; Leuprecht, Armin

    2015-04-01

    We present the R package "wux", a toolbox to analyze climate change uncertainties projected by numerical climate model simulations. The focus of this package is to automatically process big amounts of climate simulations from multi-model ensembles in a user-friendly way. For that, climate model output in binary NetCDF format is read in and stored in a data frame, after first being aggregated to a desired temporal resolution and then being averaged over spatial domains of interest. The data processing can be performed for any number of meteorological parameters at one go, which allows multivariate statistical analysis of the climate model ensemble. The data to be processed is not restricted to any specific type of climate simulation: Global circulation models (GCMs), as the CMIP5 or CMIP3 simulations, can be read in the same way as Regional Climate Models (RCMs), as e.g. the CORDEX or ENSEMBLES simulations.

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

    NASA Astrophysics Data System (ADS)

    Rugenstein, M.; Knutti, R.

    2015-12-01

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

  9. 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 consequences will not be felt uniformly around the globe or even across a given region. Policy models must comprehend all of these considerations. Combining physics-based models of the Earth's climate and biosphere with societal models of population dynamics, economics, and politics is a grand challenge with high stakes. We propose to leverage our recent advances in modeling and simulation of military stability and reconstruction operations to models that address all these areas of concern. Following over twenty years' experience of successful combat simulation, JPL has started developing Minerva, which will add demographic, economic, political, and media/information models to capabilities that already exist. With these new models, for which we have design concepts, it will be possible to address a very wide range of potential national and international problems that were previously inaccessible. Our climate change model builds on Minerva and expands the geographical horizon from playboxes containing regions and neighborhoods to the entire globe. This system consists of a collection of interacting simulation models that specialize in different aspects of the global situation. They will each contribute to and draw from a pool of shared data. The basic models are: the physical model; the demographic model; the political model; the economic model; and the media

  10. 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.

  11. 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.

  12. The Whole Atmosphere Community Climate Model

    NASA Astrophysics Data System (ADS)

    Boville, B. A.; Garcia, R. R.; Sassi, F.; Kinnison, D.; Roble, R. G.

    The Whole Atmosphere Community Climate Model (WACCM) is an upward exten- sion of the National Center for Atmospheric Research Community Climate System Model. WACCM simulates the atmosphere from the surface to the lower thermosphere (140 km) and includes both dynamical and chemical components. The salient points of the model formulation will be summarized and several aspects of its performance will be discussed. Comparison with observations indicates that WACCM produces re- alistic temperature and zonal wind distributions. Both the mean state and interannual variability will be summarized. Temperature inversions in the midlatitude mesosphere have been reported by several authors and are also found in WACCM. These inver- sions are formed primarily by planetary wave forcing, but the background state on which they form also requires gravity wave forcing. The response to sea surface temperature (SST) anomalies will be examined by com- paring simulations with observed SSTs for 1950-1998 to a simulation with clima- tological annual cycle of SSTs. The response to ENSO events is found to extend though the winter stratosphere and mesosphere and a signal is also found at the sum- mer mesopause. The experimental framework allows the ENSO signal to be isolated, because no other forcings are included (e.g. solar variability and volcanic eruptions) which complicate the observational record. The temperature and wind variations asso- ciated with ENSO are large enough to generate significant perturbations in the chem- ical composition of the middle atmosphere, which will also be discussed.

  13. Mixing parameterizations in ocean climate modeling

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  14. 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.

  15. 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

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

    PubMed

    Betts, Richard A

    2005-11-29

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

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

    PubMed

    Betts, Richard A

    2005-11-29

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

  18. 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.

  19. 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.

  20. Regional climate simulations over Vietnam using the WRF model

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    Treshansky, Allyn; Devine, Gerard

    2010-05-01

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

  3. North African climate variability. Part 1: Tropical thermocline coupling

    NASA Astrophysics Data System (ADS)

    Yeshanew, A.; Jury, M. R.

    2007-05-01

    Tropical ocean thermocline variability is studied using gridded data assimilated by an ocean model in the period 1950-2000. The dominant patterns and variability are identified using EOF analysis applied to E-W depth slices of sea temperatures averaged over the tropics. After removing the annual cycle, an east-west ‘see-saw’ with an interannual to decadal rhythm is the leading mode in each of the tropical basins. In the case of the leading mode in the Pacific, the thermocline oscillation forms a dipole structure, but in the (east) Atlantic and (southwest) Indian Ocean there is a single center of action. The interaction of the ocean thermocline and atmospheric Walker circulations is studied through cross-modulus analysis of wavelet-filtered EOF time scores. Our study demonstrates how tropical ocean thermocline variability contributes to zonal circulation anomalies in the atmosphere. The equatorial Pacific thermocline oscillation explains 62 and 53% of the variability of the Pacific and Atlantic zonal overturning circulations, the latter driving convective polarity between North Africa and South America. The Pacific sea-saw leads the Atlantic zonal circulation by a few months.

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

    USGS Publications Warehouse

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

    2016-01-01

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

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

    SciTech Connect

    Auffhammer, Maximilian; Hsiang, Solomon M.; Schlenker, Wolfram; Sobel, Adam H.

    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.

  6. From quantifying historical LULCC impacts to optimizing land management for climate mitigation: Insights from climate modelling

    NASA Astrophysics Data System (ADS)

    Davin, E.; Lejeune, Q.; Seneviratne, S. I.

    2015-12-01

    Human activities have profoundly transformed the land surface through land use/land cover change (LULCC). The consequence of this transformation is twofold: First, the conversion from natural to anthropogenic systems exert a direct forcing on climate (through both biogeochemical and biogeophysical processes); Second the transformed ecosystems may modify land-atmosphere feedback mechanisms thus modulating the response to climate change or to specific weather events. The first point will be illustrated by reviewing recent modelling results, including LUCID and CMIP5 model intercomparisons, to shed some light on the relative importance of LULCC versus other climate forcings. Given the importance of LULCC impacts at the regional scale, some recent efforts to improve the representation of land processes in regional climate models [1] as well as a regional assessment of the impact of amazonian deforestation [2] will be presented. The second point will be discussed through two examples. First, the fact that LULCC may modulate certain modes of variability will be illustrated based on model experiments highlighting the regional interplay between ENSO variability and amazonian deforestation. Second, we will show that peak temperatures during heat waves can be strongly influenced locally by the type of land cover or land management practices. In particular no-till farming, by increasing surface albedo, can lead to a substantial attenuation of hot temperatures during heat waves, in part due to a more efficient radiative cooling effect during cloud-free conditions [3]. References:[1] Davin, E.L. and S.I. Seneviratne (2012), Role of land surface processes and diffuse/direct radiation partitioning in simulating the European climate, Biogeosciences, 9, 1695-1707, doi:10.5194/bg-9-1695-2012.[2] Lejeune, Q., E.L. Davin, B. Guillod and S.I. Seneviratne (2015), Influence of Amazonian deforestation on the future evolution of regional surface fluxes, circulation, surface temperature and

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2002-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank

    2016-03-01

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

  10. Climate Model Response from the Geoengineering Model Intercomparison Project (GeoMIP)

    SciTech Connect

    Kravitz, Benjamin S.; Caldeira, Ken; Boucher, Olivier; Robock, Alan; Rasch, Philip J.; Alterskjaer, Kari; Bou Karam, Diana; Cole, Jason N.; Curry, Charles L.; Haywood, J.; Irvine, Peter; Ji, Duoying; Jones, A.; Kristjansson, J. E.; Lunt, Daniel; Moore, John; Niemeier, Ulrike; Schmidt, Hauke; Schulz, M.; Singh, Balwinder; Tilmes, S.; Watanabe, Shingo; Yang, Shuting; Yoon, Jin-Ho

    2013-08-09

    Solar geoengineering—deliberate reduction in the amount of solar radiation retained by the Earth—has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwise occur under high CO2 levels but, compared to the preindustrial climate, leaves the tropics cooler (-0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2mmday-1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO2 fertilization, but also in part due to reduced plant heat stress compared to a high CO2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels.

  11. Climate modelling: IPCC gazes into the future

    NASA Astrophysics Data System (ADS)

    Raper, Sarah

    2012-04-01

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

  12. Modeling the Earth: Climate on an Icosphere

    NASA Astrophysics Data System (ADS)

    Fouts, Stephanie; Cook, L. Jonathan

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

  13. 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.

  14. Hybrid Surface Mesh Adaptation for Climate Modeling

    SciTech Connect

    Khamayseh, Ahmed K; de Almeida, Valmor F; Hansen, Glen

    2008-01-01

    Solution-driven mesh adaptation is becoming quite popular for spatial error control in the numerical simulation of complex computational physics applications, such as climate modeling. Typically, spatial adaptation is achieved by element subdivision (h adaptation) with a primary goal of resolving the local length scales of interest. A second, 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.

  15. 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.

  16. 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

  17. 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

  18. A modeling approach to estimate the effect of climate change on reservoir water quality

    NASA Astrophysics Data System (ADS)

    Huang, Y.; Pierson, D. C.; Frei, A.; Samal, N. R.; Schneiderman, E.; Zion, M.; Owens, E.; Anandhi, A.

    2011-12-01

    Climate change may affect the inflow and loadings of reservoirs and thus change their water quality. It may also affect the kinetic and transport characteristics of nutrients in the reservoirs. This study aims at investigating the effect of climate change on the nutrients and eutrophic status of Cannonsville Reservoir which is part of the New York City Water Supply. The effect is explored using a watershed model (the Generalized Watershed Loading Function-Variable Source Area model, or GWLF-VSA) and a reservoir model which are driven by meteorological data generated from measured meteorological data and the outputs of global climate models (GCMs). Outputs of three GCMs were used in this study: Goddard Institute of Space Studies (GISS), European Center Hamburg Model (ECHAM) and the third generation atmospheric general circulation model (CGCM3) by Canadian Center for Climate modeling and analysis (CCCma). Three climate change scenarios were developed for each GCM model based on three emission scenarios (i.e. A2, A1B and B1 emission scenarios which represent future high, medium and low greenhouse gases concentrations, respectively). Based on down-scaled data from the outputs of GCMs and measured data during the 1981-2000 period, meteorological data for future scenarios were generated. They were used to drive the watershed model and the reservoir model. Measured meteorological data during 1966-2004 were used to represent Baseline climate condition (current climate condition). The main results are as follows: (1) climate change may result in an increase of annual average temperature in both epilimnion and hypolimnion layers, and a decrease of the concentrations of dissolved oxygen in both layers; (2) the concentrations of total phosphorus and chlorophyll a in the epilimnion and hypolimnion layers are projected to rise under future climate change conditions. Keywords: Climate change; Eutrophication; Reservoir model; Water quality

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

    NASA Astrophysics Data System (ADS)

    Sellwood, Bruce W.; Valdes, Paul J.

    2006-08-01

    more, giving more atmospheric humidity and a greatly enhanced hydrological cycle. Much of the rainfall was predominantly convective in character, often focused over the oceans and leaving major desert expanses on the continental areas. Polar ice sheets are unlikely to have been present because of the high summer temperatures achieved. The model indicates extensive sea ice in the nearly enclosed Arctic seaway through a large portion of the year during the late Cretaceous, and the possibility of sea ice in adjacent parts of the Midwest Seaway over North America. The Triassic world was a predominantly warm world, the model output for evaporation and precipitation conforming well with the known distributions of evaporites, calcretes and other climatically sensitive facies for that time. The message from the geological record is clear. Through the Phanerozoic, Earth's climate has changed significantly, both on a variety of time scales and over a range of climatic states, usually baldly referred to as "greenhouse" and "icehouse", although these terms disguise more subtle states between these extremes. Any notion that the climate can remain constant for the convenience of one species of anthropoid is a delusion (although the recent rate of climatic change is exceptional).

  20. 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.

  1. Cpl6: The New Extensible, High-Performance Parallel Coupler forthe Community Climate System Model

    SciTech Connect

    Craig, Anthony P.; Jacob, Robert L.; Kauffman, Brain; Bettge,Tom; Larson, Jay; Ong, Everest; Ding, Chris; He, Yun

    2005-03-24

    Coupled climate models are large, multiphysics applications designed to simulate the Earth's climate and predict the response of the climate to any changes in the forcing or boundary conditions. The Community Climate System Model (CCSM) is a widely used state-of-art climate model that has released several versions to the climate community over the past ten years. Like many climate models, CCSM employs a coupler, a functional unit that coordinates the exchange of data between parts of climate system such as the atmosphere and ocean. This paper describes the new coupler, cpl6, contained in the latest version of CCSM,CCSM3. Cpl6 introduces distributed-memory parallelism to the coupler, a class library for important coupler functions, and a standardized interface for component models. Cpl6 is implemented entirely in Fortran90 and uses Model Coupling Toolkit as the base for most of its classes. Cpl6 gives improved performance over previous versions and scales well on multiple platforms.

  2. 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) ...

  3. Climate Model Evaluation in Distributed Environments.

    NASA Astrophysics Data System (ADS)

    Braverman, A. J.

    2014-12-01

    As the volume of climate-model-generated and observational data increases, it has become infeasible to perform large-scale comparisons of model output against observations by moving the data to a central location. Data reduction techniques, such as gridding or subsetting, can reduce data volume, but also sacrifice information about spatial and temporal variability that may be important for the comparison. Alternatively, it is generally recognized that "moving the computaton to the data" is more efficient for leveraging large data sets. In the spirit of the latter approach, we describe a new methodology for comparing time series structure in model-generated and observational time series when those data are stored on different computers. The method involves simulating the sampling distribution of the difference between a statistic computed from the model output and the same statistic computed from the observed data. This is accomplished with separate wavelet decompositions of the two time series on their respective local machines, and the transmission of only a very small set of information computed from the wavelet coefficients. The smaller that set is, the cheaper it is to transmit, but also the less accurate will be the result. From the standpoint of the analysis of distributed data, the main question concerns the nature of that trade-off. In this talk, we describe the comparison methodology and the results of some preliminary studies on the cost-accuracy trade-off.

  4. 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.

  5. New parameterizations and sensitivities for simple climate models

    NASA Technical Reports Server (NTRS)

    Graves, Charles E.; Lee, Wan-Ho; North, Gerald R.

    1993-01-01

    This paper presents a reexamination of the earth radiation budget parameterization of energy balance climate models in light of data collected over the last 12 years. The study consists of three parts: (1) an examination of the infrared terrestrial radiation to space and its relationship to the surface temperature field on time scales from 1 month to 10 years; (2) an examination of the albedo of the earth with special attention to the seasonal cycle of snow and clouds; (3) solutions for the seasonal cycle using the new parameterizations with special attention to changes in sensitivity. While the infrared parameterization is not dramatically different from that used in the past, the albedo in the new data suggest that a stronger latitude dependence be employed. After retuning the diffusion coefficient the simulation results for the present climate generally show only a slight dependence on the new parameters. Also, the sensitivity parameter for the model is still about the same (1.25 C for a 1 percent increase of solar constant) for the linear models and for the nonlinear models that include a seasonal snow line albedo feedback (1.34 C). One interesting feature is that a clear-sky planet with a snow line albedo feedback has a significantly higher sensitivity (2.57 C) due to the absence of smoothing normally occurring in the presence of average cloud cover.

  6. GCM simulations of volcanic aerosol forcing. Part I: Climate changes induced by stead-state perturbations

    SciTech Connect

    Pollack, J.B. ); Rind, D.; Lacis, A.; Hansen, J.E.; Sato, M.; Ruedy, R. )

    1993-09-01

    The Goddard Institute for Space Studies Climate Model II was used to simulate the response of the climate system to a spatially and temporally constant forcing by volcanic aerosols. The climatic changes produced by differencing this simulation and one made for the present climate with no volcanic aerosol forcing. These climatic changes are also compared with those obtained when CO[sub 2] in the atmosphere was doubled and when the boundary conditions associated with the peak of the last ice age. In all three cases, the absolute magnitude of the change in the globally averaged air temperature at the surface is approximately 5K. The simulations imply a significant cooling of the troposphere and surface can occur at times of closely spaced, multiple, sulfur-rich volcanic explosions that span time scales of decades to centuries, such as occurred at the end of the nineteenth and beginning of the twentieth centuries. The steady-state climate response to volcanic forcing includes a expansion of sea ice, especially Southern Hemisphere; a large increase in surface and planetary albedo at high latitudes; and sizable changes in the annually and zonally averaged air temperature. The climate response to three different forcings is similar in 3 ways: direct radiative forcing accounts for 30% and 25% of the total [delta]T[sub s]; Changes in atmospheric water vapor are the most important positive feedback; Albedo feedback is significant, positive at high latitudes. The climate response to the three forcings also differs. The latitudinal profiles of [delta]T[sub s] differ, reflecting significant variations in the latitudinal profiles of the primary radiative forcing. Changes in eddy kinetic energy, heat transport by atmospheric eddies, and total atmospheric heat transport are quite different. These results raise questions about the ease with which atmospheric heat transport can be parameterized in a simple way in energy climate models. 44 refs., 32 figs.

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

    PubMed

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

    2014-01-01

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

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

    PubMed

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

    2014-02-13

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

  9. Simulations of the future precipitation climate of the Central Andes using a coupled regional climate model

    NASA Astrophysics Data System (ADS)

    Nicholls, S.; Mohr, K. I.

    2014-12-01

    The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. Global climate models, although capable of resolving synoptic-scale South American climate features, are inadequate for fully-resolving the strong gradients between climate regimes and the complex orography which define the Tropical Andes given their low spatial and temporal resolution. Recent computational advances now make practical regional climate modeling with prognostic mesoscale atmosphere-ocean coupled models, such as the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system, to climate research. Previous work has shown COAWST to reasonably simulate the both the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data. More recently, COAWST simulations have also been shown to sensibly reproduce the entire annual cycle of rainfall (Oct 2003 - Oct 2004) with historical climate model input. Using future global climate model input for COAWST, the present work involves year-long cycle spanning October to October for the years 2031, 2059, and 2087 assuming the most likely regional climate pathway (RCP): RCP 6.0. COAWST output is used to investigate how global climate change impacts the spatial distribution, precipitation rates, and diurnal cycle of precipitation patterns in the Central Andes vary in these yearly "snapshots". Initial results show little change to precipitation coverage or its diurnal cycle, however precipitation amounts did tend drier over the Brazilian Plateau and wetter over the Western Amazon and Central Andes. These results suggest potential adjustments to large-scale climate features (such as the Bolivian High).

  10. Climate change as a three-part ethical problem: a response to Jamieson and Gardiner.

    PubMed

    Kingston, Ewan

    2014-12-01

    Dale Jamieson has claimed that conventional human-directed ethical concepts are an inadequate means for accurately understanding our duty to respond to climate change. Furthermore, he suggests that a responsibility to respect nature can instead provide the appropriate framework with which to understand such a duty. Stephen Gardiner has responded by claiming that climate change is a clear case of ethical responsibility, but the failure of institutions to respond to it creates a (not unprecedented) political problem. In assessing the debate between Gardiner and Jamieson, I develop an analysis which shows a three-part structure to the problem of climate change, in which the problem Gardiner identifies is only one of three sub-problems of climate change. This analysis highlights difficulties with Jamieson's argument that the duty of respect for nature is necessary for a full understanding of climate ethics, and suggests how a human-directed approach based on the three-part analysis can avoid Jamieson's charge of inadequacy. PMID:24146296

  11. Unpacking the mechanisms captured by a correlative species distribution model to improve predictions of climate refugia.

    PubMed

    Briscoe, Natalie J; Kearney, Michael R; Taylor, Chris A; Wintle, Brendan A

    2016-07-01

    Climate refugia are regions that animals can retreat to, persist in and potentially then expand from under changing environmental conditions. Most forecasts of climate change refugia for species are based on correlative species distribution models (SDMs) using long-term climate averages, projected to future climate scenarios. Limitations of such methods include the need to extrapolate into novel environments and uncertainty regarding the extent to which proximate variables included in the model capture processes driving distribution limits (and thus can be assumed to provide reliable predictions under new conditions). These limitations are well documented; however, their impact on the quality of climate refugia predictions is difficult to quantify. Here, we develop a detailed bioenergetics model for the koala. It indicates that range limits are driven by heat-induced water stress, with the timing of rainfall and heat waves limiting the koala in the warmer parts of its range. We compare refugia predictions from the bioenergetics model with predictions from a suite of competing correlative SDMs under a range of future climate scenarios. SDMs were fitted using combinations of long-term climate and weather extremes variables, to test how well each set of predictions captures the knowledge embedded in the bioenergetics model. Correlative models produced broadly similar predictions to the bioenergetics model across much of the species' current range - with SDMs that included weather extremes showing highest congruence. However, predictions in some regions diverged significantly when projecting to future climates due to the breakdown in correlation between climate variables. We provide unique insight into the mechanisms driving koala distribution and illustrate the importance of subtle relationships between the timing of weather events, particularly rain relative to hot-spells, in driving species-climate relationships and distributions. By unpacking the mechanisms

  12. Unpacking the mechanisms captured by a correlative species distribution model to improve predictions of climate refugia.

    PubMed

    Briscoe, Natalie J; Kearney, Michael R; Taylor, Chris A; Wintle, Brendan A

    2016-07-01

    Climate refugia are regions that animals can retreat to, persist in and potentially then expand from under changing environmental conditions. Most forecasts of climate change refugia for species are based on correlative species distribution models (SDMs) using long-term climate averages, projected to future climate scenarios. Limitations of such methods include the need to extrapolate into novel environments and uncertainty regarding the extent to which proximate variables included in the model capture processes driving distribution limits (and thus can be assumed to provide reliable predictions under new conditions). These limitations are well documented; however, their impact on the quality of climate refugia predictions is difficult to quantify. Here, we develop a detailed bioenergetics model for the koala. It indicates that range limits are driven by heat-induced water stress, with the timing of rainfall and heat waves limiting the koala in the warmer parts of its range. We compare refugia predictions from the bioenergetics model with predictions from a suite of competing correlative SDMs under a range of future climate scenarios. SDMs were fitted using combinations of long-term climate and weather extremes variables, to test how well each set of predictions captures the knowledge embedded in the bioenergetics model. Correlative models produced broadly similar predictions to the bioenergetics model across much of the species' current range - with SDMs that included weather extremes showing highest congruence. However, predictions in some regions diverged significantly when projecting to future climates due to the breakdown in correlation between climate variables. We provide unique insight into the mechanisms driving koala distribution and illustrate the importance of subtle relationships between the timing of weather events, particularly rain relative to hot-spells, in driving species-climate relationships and distributions. By unpacking the mechanisms

  13. 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

  14. Evaluation of the new EMAC-SWIFT chemistry climate model

    NASA Astrophysics Data System (ADS)

    Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Rex, Markus

    2016-04-01

    It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Including atmospheric ozone chemistry into climate simulations is usually done by prescribing a climatological ozone field, by including a fast linear ozone scheme into the model or by using a climate model with complex interactive chemistry. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. Although interactive chemistry provides a realistic representation of atmospheric chemistry such model simulations are computationally very expensive and hence not suitable for ensemble simulations or simulations with multiple climate change scenarios. A new approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has recently been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. Here, we show first results of EMAC-SWIFT simulations and validate these against EMAC simulations using the complex interactive chemistry scheme MECCA, and against observations.

  15. [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. PMID:23431809

  16. [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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  18. 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

  19. The impact of iceberg calving on climate: a model study with a fully coupled ice-sheet - climate model

    NASA Astrophysics Data System (ADS)

    Bugelmayer, Marianne; Roche, Didier; Renssen, Hans

    2013-04-01

    In the current period of climate change the understanding of the interactions between different parts of the climate system gets more and more important. The ice-sheets and ice-shelves, an important part of this system, experienced strong changes in the geological past, ranging from fully ice free to ice covered - thereby altering the whole climate. In the present climate, thousands of icebergs are released every year from Greenland and Antarctica, acting as a moving source of freshwater and a sink of latent heat. As a consequence, these icebergs alter the oceans' stratification and facilitate the formation of sea ice, thus influencing the state of the ocean and of the atmosphere. Up to now, the impact of icebergs on climate has been addressed in different studies which utilize climate models using freshwater and latent heat fluxes to parameterize icebergs. Mostly these fluxes were equally distributed around the coast. However, more recently iceberg modules were integrated into climate models to take into account the temporal and spatial distribution of the iceberg melting. In the presented study, an earth system model of intermediate complexity - iLOVECLIM - that includes a 3D dynamic - thermodynamic iceberg module (Jongma et al., 2008) is coupled to the Grenoble ice shelves and land ice model - GRISLI (Ritz et al., 1997, 2001). In GRISLI, ice sheets evolve according to the precipitation and temperature received from iLOVECLIM. In turn, GRISLI provides its topography and the ice mask to the atmospheric component of iLOVECLIM and all freshwater fluxes (ablation and calving) to its oceanic component. The ablation is directly put into the uppermost layer of the ocean, whereas the calving is used to generate icebergs at the calving sites following the size distribution of Bigg et al. (1997). Using this model set-up we analyse the evolution and the equilibrium state of the Greenland ice-sheet under pre-industrial conditions within three different coupling methods. All

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

    NASA Astrophysics Data System (ADS)

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

    1992-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Zhang, Xianliang; Yan, Xiaodong

    2016-05-01

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

  3. 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.

  4. Report calls for measures to advance climate modeling

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2012-09-01

    While climate modeling has made enormous strides over the past several decades, a critical step toward making more rapid, efficient, and coordinated progress in modeling would require “an evolutionary change in U.S. climate modeling institutions away from developing multiple completely independent models toward a collaborative approach,” according to a 7 September report by a committee of the U.S. National Research Council's Board on Atmospheric Sciences and Climate (BASC). “The Committee believes that the best path forward is a strategy centered around the integration of the decentralized U.S. climate modeling enterprise—across modeling efforts, across a hierarchy of model types, across modeling communities focused on different space and timescales, and between model developers and model output users,” the report notes. “A diversity of approaches is necessary for progress in many areas of climate modeling and is vital for addressing the breadth of users needs.” Entitled A National Strategy for Advancing Climate Modeling, the report states that, “If adopted, this strategy of increased unification amidst diversity will allow the United States to more effectively meet the climate information needs of the Nation in the coming decades and beyond.”

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

    This paper reviews recent progress in the development of the Beijing Climate Center Climate System Model (BCC_CSM) and its four component models (atmosphere, land surface, ocean, and sea ice). Two recent versions are described: BCC_CSM1.1 with coarse resolution (approximately 2.8125°×2.8125°) and BCC_CSM1.1(m) with moderate resolution (approximately 1.125°×1.125°). Both versions are fully coupled climate-carbon cycle models that simulate the global terrestrial and oceanic carbon cycles and include dynamic vegetation. Both models well simulate the concentration and temporal evolution of atmospheric CO2 during the 20th century with anthropogenic CO2 emissions prescribed. Simulations using these two versions of the BCC_CSM model have been contributed to the Coupled Model Intercomparison Project phase five (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). These simulations are available for use by both national and international communities for investigating global climate change and for future climate projections. Simulations of the 20th century climate using BCC_CSM1.1 and BCC_CSM1.1(m) are presented and validated, with particular focus on the spatial pattern and seasonal evolution of precipitation and surface air temperature on global and continental scales. Simulations of climate during the last millennium and projections of climate change during the next century are also presented and discussed. Both BCC_CSM1.1 and BCC_CSM1.1(m) perform well when compared with other CMIP5 models. Preliminary analyses indicate that the higher resolution in BCC_CSM1.1(m) improves the simulation of mean climate relative to BCC_CSM1.1, particularly on regional scales.

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  8. The present-day climate of Greenland : a study with a regional climate model

    NASA Astrophysics Data System (ADS)

    Ettema, J.

    2010-04-01

    Present-day climate of Greenland Over the past 20 years, the Greenland ice sheet (GrIS) has warmed. This temperature increase can be explained by an increase in downwelling longwave radiation due to a warmer overlying atmosphere. These temperature changes are strongly correlated to changes in the large scale circulation over the ice sheet. Since 1990, the melt has also strongly increased along the ice margins, inducing significant increase in runoff. With no significant change found in the total precipitation, the GrIS surface mass balance (SMB) decreased by 12 Gt yr-1 or 7 kg m-2 yr-1 since 1990. Locally, the SMB trend reaches -90 kg m-2 yr-1 at the western and eastern ice margins. These conclusions are drawn from a modelling study by Janneke Ettema, which discusses the present-day climate and surface mass balance of the GrIS. The emphasis of this research is on understanding the underlying physical processes. Using the regional atmospheric climate model RACMO2/GR at high horizontal resolution (11km) has resulted in unprecedented detail in the ice sheet climatology and SMB. By incorporating processes such as percolation, retention and refreezing of meltwater in the surface parameterisation, the model explicitly calculates how these processes affect snow pack temperature, density and surface albedo. RACMO2/GR shows that the GrIS climate is spatially very variable. Characteristic for the ice sheet climate are the persistent katabatic winds and a quasi-permanent surface temperature deficit. Due to strong radiative cooling and turbulent heat transport towards the surface, the atmospheric boundary layer cools, providing optimal conditions for strong katabatic winds to occur. The strongest temperature deficit and wind speeds are found in the northeastern part of the ice sheet, whereas in the lower ablation zone the temperatures are more moderate due to surface melt and warm air advection. The high-resolution climate model revealed that the surface mass balance of the Gr

  9. Climates of the Twentieth and Twenty-First Centuries Simulated by the NCAR Climate System Model.

    NASA Astrophysics Data System (ADS)

    Dai, Aiguo; Wigley, T. M. L.; Boville, B. A.; Kiehl, J. T.; Buja, L. E.

    2001-02-01

    The Climate System Model, a coupled global climate model without `flux adjustments' recently developed at the National Center for Atmospheric Research, was used to simulate the twentieth-century climate using historical greenhouse gas and sulfate aerosol forcing. This simulation was extended through the twenty-first century under two newly developed scenarios, a business-as-usual case (ACACIA-BAU, CO2 710 ppmv in 2100) and a CO2 stabilization case (STA550, CO2 540 ppmv in 2100). Here we compare the simulated and observed twentieth-century climate, and then describe the simulated climates for the twenty-first century. The model simulates the spatial and temporal variations of the twentieth-century climate reasonably well. These include the rapid rise in global and zonal mean surface temperatures since the late 1970s, the precipitation increases over northern mid- and high-latitude land areas, ENSO-induced precipitation anomalies, and Pole-midlatitude oscillations (such as the North Atlantic oscillation) in sea level pressure fields. The model has a cold bias (2°-6°C) in surface air temperature over land, overestimates of cloudiness (by 10%-30%) over land, and underestimates of marine stratus clouds to the west of North and South America and Africa.The projected global surface warming from the 1990s to the 2090s is 1.9°C under the BAU scenario and 1.5°C under the STA550 scenario. In both cases, the midstratosphere cools due to the increase in CO2, whereas the lower stratosphere warms in response to recovery of the ozone layer. As in other coupled models, the surface warming is largest at winter high latitudes (5.0°C from the 1990s to the 2090s) and smallest (1.0°C) over the southern oceans, and is larger over land areas than ocean areas. Globally averaged precipitation increases by 3.5% (3.0%) from the 1990s to the 2090s in the BAU (STA550) case. In the BAU case, large precipitation increases (up to 50%) occur over northern mid- and high latitudes and over

  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. 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.

  12. CONSTABLE: A Global Climate Model for Classroom Use.

    ERIC Educational Resources Information Center

    Cerveny, Randall S.; And Others

    1985-01-01

    Described is the global climate model CONSTABLE (Climatic One-Dimensional Numerical Simulation of the Annual Balance of Latitudinal Energy), which can be used in undergraduate and graduate level climatology courses. Classroom exercises that can be used with the model are also included. (RM)

  13. 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...

  14. 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

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

    PubMed

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

    2013-10-28

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  17. 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).

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  19. Carbon uptake sensitivity of the North Atlantic to climate change: A model study with the Bergen Climate Model

    NASA Astrophysics Data System (ADS)

    Goris, Nadine; Heinze, Christoph; Tjiputra, Jerry; Schwinger, Jörg

    2015-04-01

    The efficiency of the world's oceans to take up carbon is expected to decrease with ongoing climate change, thereby increasing the atmospheric burden of carbon. Here, the North Atlantic is a region of special interest as it is one of the most important oceanic carbon sinks, featuring an exceptionally high column inventory of anthropogenic CO2. Several model studies have identified the carbon uptake of the North Atlantic as highly sensitive to climate change, but these studies are mostly global studies and are not concerned with a detailed attribution of the underlying mechanisms and their regional differences within the North Atlantic. Yet, quantifying the climate change induced CO2-uptake variability in the North Atlantic and identifying its main drivers is of high relevance for improving climate projections. In order to assess and understand the climate sensitivity of the CO2 uptake of the North Atlantic, we investigate the differences between two simulations (denoted as simulation COU and simulation BGC) carried out with the Bergen Earth System Model (BCM-C). While simulation COU features rising atmospheric CO2 concentrations (based on observed records for 1850-1999 and the IPCC SRES-A2 scenario for 2000-2099) for radiation code and carbon fluxes, simulation BGC uses rising atmospheric concentrations only for the calculation of the carbon fluxes. The differences between those simulations identify climate induced changes. Our analysis confirms the important role of the North Atlantic for carbon uptake and demonstrates that this region is most sensitive to climate change (in comparison to other oceanic regions as defined in Tjiputra et al., 2010). We furthermore identify substantially different responses to climate change in different parts of the North Atlantic. Based on these differing responses, we divide the North Atlantic into 3 regions, namely the subpolar gyre region (SPG), the high latitude region (HL) and the rest of the North Atlantic (rNAT*, covering

  20. 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.

  1. Pacific Northwest Laboratory annual report for 1991 to the DOE Office of Energy Research. Part 3, Atmospheric and climate research

    SciTech Connect

    Not Available

    1992-05-01

    Within the US Department of Energy`s (DOE`s) Office of Health and Environmental Research (OHER), the atmospheric sciences and carbon dioxide research programs are part of the Environmental Sciences Division (ESD). One of the central missions of the division Is to provide the DOE with scientifically defensible information on the local, regional, and global distributions of energy-related pollutants and their effects on climate. This information is vital to the definition and Implementation of a sound national energy strategy. This volume reports on the progress and status of all OHER atmospheric science and climate research projects at the Pacific Northwest Laboratory (PNL). Research at PNL provides basic scientific underpinnings to DOE`s program of global climate research. Research projects within the core carbon dioxide and ocean research programs are now integrated with those in the Atmospheric Radiation Measurements (ARM), the Computer Hardware, Advanced Mathematics and Model Physics (CHAMMP), and quantitative links programs to form DOEs contribution to the US Global Change Research Program. Climate research in the ESD has the common goal of improving our understanding of the physical, chemical, biological, and social processes that influence the Earth system so that national and international policymaking relating to natural and human-induced changes in the Earth system can be given a firm scientific basis. This report describes the progress In FY 1991 in each of these areas.

  2. 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.

  3. 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

  4. Changes in the Global Wave Climate from Single-Model Projections

    NASA Astrophysics Data System (ADS)

    Lemos, Gil; Behrens, Arno; Dobrynin, Mikhail; Miranda, Pedro; Semedo, Alvaro; Staneva, Joanna

    2016-04-01

    Ocean surface wind waves are of outmost relevance for practical and scientific reasons. On the one hand waves have a direct impact in coastal erosion, but also in sediment transport and beach nourishment, in ship routing and ship design, as well as in coastal and offshore infrastructures, just to mention the most relevant. On the other hand waves are part of the climate system, and modulate most of the exchanges that take place at the atmosphere-ocean interface. In fact waves are the "ultimate" air-sea interaction process, clearly visible and noticeable. Up until recently the impact of climate change in future global wave climate had received very little attention. Some single model single scenario global wave climate projections, based on CMIP3 scenarios, were pursuit and received relative attention in the IPCC (Intergovernmental Panel for Climate Change) AR5 (Fifth Assessment Report). In the present study the impact of a warmer climate in the future global wave climate is investigated through a 3-member "coherent" ensemble of wave climate projections: single-model, single-forcing, and single-scenario. In this methodology model variability is eliminated, leaving only room for the climate change signal. The three ensemble members were produced with the wave model WAM, forced with wind speed and ice coverage from EC-Earth projections, following the representative concentration pathway with a high emissions scenario 8.5 (RCP8.5). The ensemble present climate reference period (the control run) has been set for 1971 to 2005. The projected changes in the global wave climate are analyzed for the 2071-2100 period. The ensemble reference period is evaluated trough the comparison with the European Centre for medium-range weather forecasts (ECMWF) ERA-Interim reanalysis.

  5. 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.

  6. Initiative to improve process representation in chemistry-climate models

    SciTech Connect

    Doherty, Sarah J.; Rasch, Philip J.; Ravishankara, A.R.

    2009-06-16

    The Atmospheric Chemistry and Climate Initiative (AC&C) will address the current large uncertainties in our understanding of chemistry-climate interactions for short-lived atmospheric chemical constituents (e.g. aerosols, ozone, and methane). Understanding what controls the distribution of these species, how they affect climate, and how their distributions might change with a changing climate are important for air quality and climate forecasts. AC&C will address this issue in its first phase through a series of modeling exercises designed to test models’ ability to reproduce observed changes in these species distributions, to produce a set of coordinated forecasts for their future distribution, and to understand how processes are represented in different models. Observational databases will be used to test the models and to better understand processes represented in the models. This article describes the plans for this first phase of activities and seeks participation from the research community.

  7. Modeling the Martian climate with a new general circulation model

    NASA Astrophysics Data System (ADS)

    Urata, R.; Toon, O. B.

    2009-12-01

    We have adapted the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM3.0) to Martian conditions. Several modifications to the original model have been made. These include adjusting the physical parameters to Mars-like values, changing atmospheric composition, changing the calendar to cover a Martian year, and the addition of a carbon dioxide condensation scheme. The Martian atmosphere is composed of 95% carbon dioxide, and as much as 25% of the atmosphere can condense out at the winter pole so it is important to include the carbon dioxide condensation in the model. We plan to use the model to simulate impacts on Mars during the late Noachian. As a reference point we have performed some climate simulations with a 500 mbar carbon dioxide atmosphere. The results will be presented at the meeting. Currently a few general circulation models are available for Mars. However instead of using one of these previously developed models, we have chosen to develop our own based off of CAM3 for a number of reasons. These include the model’s support for multi-processor runs, the model’s compatibility with other models including land, aerosol, and chemistry, and the fact many in our group already use the Earth version of this model, so we are familiar with it. During the development of our model, we have been in contact with NCAR, and have plans to make the model readily available to the public through NCAR.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  9. Climate Models, Spatial Scale, and Impacts of Climate Change on Agriculture (Invited)

    NASA Astrophysics Data System (ADS)

    Mearns, L. O.

    2010-12-01

    Agriculture is among the resource sectors that received very early attention regarding possible climate change effects, and it has continued to receive considerable attention since that early research in the mid-1980s. Agriculture was also the sector wherein studies of possible adaptation to climate change first appeared. Application of results from climate models that simulate the effects of increased greenhouse gases on the atmosphere and earth system were an important component of this impacts research from the beginning, when the typical spatial resolution of climate models was on the order of 5 ° latitude by 5° longitude, or about 500 km × 500 km. This was recognized as being a very coarse resolution for applications to agriculture, and this ‘mismatch’ of scale between the climate models and the resolution at which one would want to determine impacts has remained a concern. Climate models have improved tremendously over the past 25 years since the early days of climate impacts research, in terms of the processes represented in the models as well as in their spatial resolution. Typically global models have resolutions of about 2 ° latitude and longitude, and some atmosphere-ocean general circulation models (AOGCMs) are now being run at a 1° spatial resolution. Nevertheless, even this resolution is viewed as being relatively coarse from the perspective of resolving important physical processes that govern climate as well as for the apparent needs of impacts researchers and policy makers. Over the past couple of decades techniques have been developed to allow for producing information about climate change at higher resolutions. Generating information at grid scales below that of AOGCMs is referred to as downscaling, and there are at least four different techniques for developing such information. In this talk I will present an overview of these techniques and how higher resolution information has been used in agricultural impacts assessments. Most

  10. Projecting future climate change: Implications of carbon cycle model intercomparisons

    NASA Astrophysics Data System (ADS)

    Kheshgi, Haroon S.; Jain, Atul K.

    2003-06-01

    The range of responses of alternate detailed models for the ocean and biosphere components of the global carbon cycle, cataloged in model intercomparison studies, are simulated by a reduced form Earth system model employing a range of model parameters. The reduced form model, parameterized in this way, allows the integration of these components of the carbon cycle with an energy balance climate model with a prescribed range of climate sensitivity. We use this model to construct ranges of: (1) past carbon budgets given past CO2 concentrations, fossil carbon emissions, and temperature records, (2) future CO2 concentrations and temperature for given emission scenarios, and (3) CO2 emissions and temperature for given trajectories of future CO2 concentrations leading to constant levels within the next several centuries. Carbon cycle is an additional contributor to uncertainty in climate projections that is calculated to expand the range of projected global temperature beyond that reported in the 2001 Intergovernmental Panel on Climate Change assessment.

  11. The cascade of uncertainty in modeling the impacts of climate change on Europe's forests

    NASA Astrophysics Data System (ADS)

    Reyer, Christopher; Lasch-Born, Petra; Suckow, Felicitas; Gutsch, Martin

    2015-04-01

    Projecting the impacts of global change on forest ecosystems is a cornerstone for designing sustainable forest management strategies and paramount for assessing the potential of Europe's forest to contribute to the EU bioeconomy. Research on climate change impacts on forests relies to a large extent on model applications along a model chain from Integrated Assessment Models to General and Regional Circulation Models that provide important driving variables for forest models. Or to decision support systems that synthesize findings of more detailed forest models to inform forest managers. At each step in the model chain, model-specific uncertainties about, amongst others, parameter values, input data or model structure accumulate, leading to a cascade of uncertainty. For example, climate change impacts on forests strongly depend on the in- or exclusion of CO2-effects or on the use of an ensemble of climate models rather than relying on one particular climate model. In the past, these uncertainties have not or only partly been considered in studies of climate change impacts on forests. This has left managers and decision-makers in doubt of how robust the projected impacts on forest ecosystems are. We deal with this cascade of uncertainty in a structured way and the objective of this presentation is to assess how different types of uncertainties affect projections of the effects of climate change on forest ecosystems. To address this objective we synthesized a large body of scientific literature on modeled productivity changes and the effects of extreme events on plant processes. Furthermore, we apply the process-based forest growth model 4C to forest stands all over Europe and assess how different climate models, emission scenarios and assumptions about the parameters and structure of 4C affect the uncertainty of the model projections. We show that there are consistent regional changes in forest productivity such as an increase in NPP in cold and wet regions while

  12. Estimating the Health Impact of Climate Change with Calibrated Climate Model Output.

    PubMed

    Zhou, Jingwen; Chang, Howard H; Fuentes, Montserrat

    2012-09-01

    Studies on the health impacts of climate change routinely use climate model output as future exposure projection. Uncertainty quantification, usually in the form of sensitivity analysis, has focused predominantly on the variability arise from different emission scenarios or multi-model ensembles. This paper describes a Bayesian spatial quantile regression approach to calibrate climate model output for examining to the risks of future temperature on adverse health outcomes. Specifically, we first estimate the spatial quantile process for climate model output using nonlinear monotonic regression during a historical period. The quantile process is then calibrated using the quantile functions estimated from the observed monitoring data. Our model also down-scales the gridded climate model output to the point-level for projecting future exposure over a specific geographical region. The quantile regression approach is motivated by the need to better characterize the tails of future temperature distribution where the greatest health impacts are likely to occur. We applied the methodology to calibrate temperature projections from a regional climate model for the period 2041 to 2050. Accounting for calibration uncertainty, we calculated the number of of excess deaths attributed to future temperature for three cities in the US state of Alabama.

  13. Eliciting climate experts' knowledge to address model uncertainties in regional climate projections: a case study of Guanacaste, Northwest Costa Rica

    NASA Astrophysics Data System (ADS)

    Grossmann, I.; Steyn, D. G.

    2014-12-01

    Global general circulation models typically cannot provide the detailed and accurate regional climate information required by stakeholders for climate adaptation efforts, given their limited capacity to resolve the regional topography and changes in local sea surface temperature, wind and circulation patterns. The study region in Northwest Costa Rica has a tropical wet-dry climate with a double-peak wet season. During the dry season the central Costa Rican mountains prevent tropical Atlantic moisture from reaching the region. Most of the annual precipitation is received following the northward migration of the ITCZ in May that allows the region to benefit from moist southwesterly flow from the tropical Pacific. The wet season begins with a short period of "early rains" and is interrupted by the mid-summer drought associated with the intensification and westward expansion of the North Atlantic subtropical high in late June. Model projections for the 21st century indicate a lengthening and intensification of the mid-summer drought and a weakening of the early rains on which current crop cultivation practices rely. We developed an expert elicitation to systematically address uncertainties in the available model projections of changes in the seasonal precipitation pattern. Our approach extends an elicitation approach developed previously at Carnegie Mellon University. Experts in the climate of the study region or Central American climate were asked to assess the mechanisms driving precipitation during each part of the season, uncertainties regarding these mechanisms, expected changes in each mechanism in a warming climate, and the capacity of current models to reproduce these processes. To avoid overconfidence bias, a step-by-step procedure was followed to estimate changes in the timing and intensity of precipitation during each part of the season. The questions drew upon interviews conducted with the regions stakeholders to assess their climate information needs. This

  14. A toy climate model for Mars

    NASA Astrophysics Data System (ADS)

    Savijärvi, Hannu

    2014-11-01

    A "toy climate model" TCM was constructed for Mars. It returns the midday surface and near-surface air temperatures, given the orbital parameters, season (Ls), latitude, thermal inertia, albedo, surface pressure and dust visible optical depth (τ). The TCM is based on the surface energy balance with radiation terms calibrated against line-by-line calculations and surface heat flux terms against 1D model simulations. The TCM air temperatures match various lander observations reasonably well, e.g. the 3.4 martian years of recovered T1.6m from Viking Lander 1. The results demonstrate strong sensitivity of Ts and T1.6m to the dust load. All the VL1 years suggest major dust storms around Ls 270-300°, while τ appears only moderate in the simultaneous VL2 observations. The TCM was further extended to increased surface pressures, using moist 1D simulations. The greenhouse warming remained modest and the diurnal range was small in a thick CO2 atmosphere. As the CO2 condensation temperature Tc increases rapidly with pressure, the range of afternoon temperatures at various latitudes remains quite narrow in a thick atmosphere. The TCM can also deal with orbital parameter variations. A high-eccentricity, high-obliquity case was demonstrated for the present 7 mb (Tc 150 K) and a 1 bar CO2 atmosphere (Tc 195 K). High obliquity of 45° led to quite wide winter polar ice caps, which extended down to the subtropics. In the 1 bar case even the equatorial Ts was close to Tc at aphelion; a major dust storm at that time led to a tropical CO2 ice cover.

  15. The Community Climate System Model Project from an Interagency Perspective

    SciTech Connect

    Bader, D C; Bamzai, A; Fein, J; Patrinos, A; Leinen, M

    2005-06-16

    In 2007, the Intergovernmental Panel on Climate Change (IPCC) will publish its Fourth Assessment Report of the Scientific Basis of Climate Change (AR4). A significant portion of the AR4 will be the analysis of coupled general circulation model (GCM) simulations of the climate of the past century as well as scenarios of future climates under prescribed emission scenarios. Modeling groups worldwide have contributed to AR4, including three from the U.S., the Community Climate System Model (CCSM) project, the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Sciences, and the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory (GFDL). This collection of model results is providing a wealth of new information that will be used to examine the state of climate science, the potential impacts from climate changes, and the policy consequences that they imply. Our focus here is on the CCSM project. Although it is centered at the National Center for Atmospheric Research (NCAR), the CCSM version 3 (CCSM3) was designed, developed, and applied in a uniquely distributed fashion with participation by many institutions. This model has produced some of the most scientifically complete and highest resolution simulations of climate change to date, thanks to the teamwork of many scientists and software engineers. Their contributions will become obvious as a steady stream of peer-reviewed publications appears in the scientific literature. Less obvious, however, is the largely hidden, unprecedented level of interagency cooperation and multi-institutional coordination that provided the direction and resources necessary to make the CCSM project successful. Contrary to the widely-held opinion that the US climate research effort in general, and the climate modeling effort in particular, is fragmented and disorganized (NRC 1998, 2001), the success of the CCSM project demonstrates that a uniquely US approach to model

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

    NASA Astrophysics Data System (ADS)

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

    2011-01-01

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

  17. 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.

  18. Climatic Signal and Climatic Noise in Lorenz's Low Order Model of the Atmospheric Circulation

    NASA Astrophysics Data System (ADS)

    Freire, J.; Dacamara, C.; Corte-Real, J.; Gallas, J. A. C.

    2003-04-01

    The climate state may be defined by a set of statistics computed over a very large number of replicas of the Atmosphere (ensemble), each replica evolving independently of each other, but all replicas subject to the same boundary conditions (external forcing). Such dynamic approach of the climate state is particulary adequate to define the concepts of climatic signal (linked to external forcing) and climatic noise (associated to distinct events of the same climatic state). Lorenz's low-order model of the general circulation is a useful tool to study the atmospheric signal and noise when the system is subject to prescribed forcing (e.g. seasonal forcing). This is due to the richness of the model as a dynamical system together with its low computacional cost that allows building ensembles with a large number of replicas. In our study we analyse the dynamical behavior of the atmospheric circulation based on a large set of numerical integrations (≈10000). The climate state is analysed and particular attention is devoted to the problem of separating the climatic signal from the climatic noise for different types of seasonal forcing.

  19. 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.

  20. Climate change and the potential global distribution of Aedes aegypti: spatial modelling using GIS and CLIMEX.

    PubMed

    Khormi, Hassan M; Kumar, Lalit

    2014-05-01

    We examined the potential added risk posed by global climate change on the dengue vector Aedes aegypti abundance using CLIMEX, a powerful tool for exploring the relationship between the fundamental and realised niche of any species. After calibrating the model using data from several knowledge domains, including geographical distribution records, we estimated potential distributions of the mosquito under current and future potential scenarios. The impact of climate change on its potential distribution was assessed with two global climate models, the CSIRO-Mk3.0 and the MIROC-H, run with two potential, future emission scenarios (A1B and A2) published by the Intergovernmental Panel on Climate Change. We compared today's climate situation with two arbitrarily chosen future time points (2030 and 2070) to see the impact on the worldwide distribution of A. aegypti . The model for the current global climate indicated favourable areas for the mosquito within its known distribution in tropical and subtropical areas. However, even if much of the tropics and subtropics will continue to be suitable, the climatically favourable areas for A. aegypti globally are projected to contract under the future scenarios produced by these models, while currently unfavourable areas, such as inland Australia, the Arabian Peninsula, southern Iran and some parts of North America may become climatically favourable for this mosquito species. The climate models for the Aedes dengue vector presented here should be useful for management purposes as they can be adapted for decision/making regarding allocation of resources for dengue risk toward areas where risk infection remains and away from areas where climatic suitability is likely to decrease in the future. PMID:24893017

  1. Climate change and the potential global distribution of Aedes aegypti: spatial modelling using GIS and CLIMEX.

    PubMed

    Khormi, Hassan M; Kumar, Lalit

    2014-05-01

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

  2. Modelling urban climate under global climate change in Central European cities

    NASA Astrophysics Data System (ADS)

    Zuvela-Aloise, Maja; Bokwa, Anita; Dobrovolny, Petr; Gal, Tamas; Geletic, Jan; Gulyas, Agnes; Hajto, Monika; Hollosi, Brigitta; Kielar, Rafal; Lehnert, Michal; Skarbit, Nora; Stastny, Pavel; Svec, Marek; Unger, Janos; Vysoudil, Miroslav; Walawender, Jakub P.

    2015-04-01

    The global and regional climate warming is expected to increase the heat load in urban areas. In order to develop adaptation and mitigation strategies in particular cities, it is necessary to evaluate possible range of heat load increase, in terms of both its magnitude and spatial extent. The present study shows preliminary results of an international project aimed to evaluate the expected heat load increase in four Central European cities (Krakow, Poland; Bratislava, Slovakia; Brno, Czech Republic and Szeged, Hungary) using the non-hydrostatic MUKLIMO 3 model developed by DWD (Deutscher Wetterdienst) for micro-scale urban climate and planning applications. The investigation is focused on the spatial gradients of temperature during potential summer day conditions and possible change in heat load signal under future climate conditions. In order to identify thermally sensitive areas within the city, idealized simulations of temperature, wind and relative humidity in the urban area are performed based on the orography and land use data with 100 m resolution. The model setup uses standardize classification of land use properties based on local climate zones (LCZ) classification system (Stewart and Oke, 2012) which allows inter-comparison of the modelling results. The Landsat satellite images are used to identify typical land use classes in all the cities. The climatological changes in urban heat load are evaluated in terms of expected increase in the mean annual number of summer days (Tmax ≥ 25°C). The 30-year climatological indices are calculated based on the cuboid method. Timeseries of mean daily temperature, wind and relative humidity from a local meteorological station are used to evaluate the climatic indices for the recent climatic period, while the future climate signal is based on the data from regional climate projections of the EURO-CORDEX project. The project "Urban climate in Central European cities and global climate change" is funded within the

  3. Biotic Interactions in the Face of Climate Change: A Comparison of Three Modelling Approaches

    PubMed Central

    Jaeschke, Anja; Bittner, Torsten; Jentsch, Anke; Reineking, Björn; Schlumprecht, Helmut; Beierkuhnlein, Carl

    2012-01-01

    Climate change is expected to alter biotic interactions, and may lead to temporal and spatial mismatches of interacting species. Although the importance of interactions for climate change risk assessments is increasingly acknowledged in observational and experimental studies, biotic interactions are still rarely incorporated in species distribution models. We assessed the potential impacts of climate change on the obligate interaction between Aeshna viridis and its egg-laying plant Stratiotes aloides in Europe, based on an ensemble modelling technique. We compared three different approaches for incorporating biotic interactions in distribution models: (1) We separately modelled each species based on climatic information, and intersected the future range overlap (‘overlap approach’). (2) We modelled the potential future distribution of A. viridis with the projected occurrence probability of S. aloides as further predictor in addition to climate (‘explanatory variable approach’). (3) We calibrated the model of A. viridis in the current range of S. aloides and multiplied the future occurrence probabilities of both species (‘reference area approach’). Subsequently, all approaches were compared to a single species model of A. viridis without interactions. All approaches projected a range expansion for A. viridis. Model performance on test data and amount of range gain differed depending on the biotic interaction approach. All interaction approaches yielded lower range gains (up to 667% lower) than the model without interaction. Regarding the contribution of algorithm and approach to the overall uncertainty, the main part of explained variation stems from the modelling algorithm, and only a small part is attributed to the modelling approach. The comparison of the no-interaction model with the three interaction approaches emphasizes the importance of including obligate biotic interactions in projective species distribution modelling. We recommend the use of

  4. Modelling Phanerozoic Climate Change (Milutin Milankovic Medal Lecture)

    NASA Astrophysics Data System (ADS)

    Valdes, Paul J.

    2015-04-01

    Palaeoclimate Modelling is a powerful tool for helping to understand the processes and mechanisms involved in climate change, as well as testing the climate models used to predict future change. Traditionally, such work has had to focus on a few specific time periods (such as the Holocene, LGM, or early Eocene). However, with the advent of increased computer power and faster models, it is now possible to use models to examine the transient behaviour of the climate system in the past. The talk will review modelling work of the last glacial-interglacial cycle, examining the relative role of orbital forcing, greenhouse gases, and feedbacks from ice sheets. The talk will then present new work examining the variability of climate over the last 400 million years. The results show that the changes of palaeogeographies can have major impact on climate at continental scales but that on global scales the changes in palaeogeography are much less important. Global temperatures are primarily controlled by the long term change in solar constant, greenhouse gases, and feedbacks from the ice sheets. The work also shows that the modelled climate is consistent with the longer-term transitions from icehouse to greenhouse worlds. The large regional variability of modelled climate suggests that the palaeodata estimates of past global mean temperatures should be treated with some caution.

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

    NASA Astrophysics Data System (ADS)

    Semenov, M. A.

    2009-04-01

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

  6. 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

  7. Combining data sources to characterise climatic variability for hydrological modelling in high mountain catchments

    NASA Astrophysics Data System (ADS)

    Pritchard, David; Fowler, Hayley; Bardossy, Andras; O'Donnell, Greg; Forsythe, Nathan

    2016-04-01

    Robust hydrological modelling of high mountain catchments to support water resources management depends critically on the accuracy of climatic input data. However, the hydroclimatological complexity and sparse measurement networks typically characteristic of these environments present significant challenges for determining the structure of spatial and temporal variability in key climatic variables. Focusing on the Upper Indus Basin (UIB), this research explores how different data sources can be combined in order to characterise climatic patterns and related uncertainties at the scales required in hydrological modelling. Analysis of local observations with respect to underlying climatic processes and variability is extended relative to previous studies in this region, which forms a basis for evaluating the domains of applicability and potential insights associated with selected remote sensing and reanalysis products. As part of this, the information content of recent high resolution simulations for understanding climatic patterns is assessed, with particular reference to the High Asia Refined Analysis (HAR). A strategy for integrating these different data sources to obtain plausible realisations of the distributed climatic fields needed for hydrological modelling is developed on the basis of this analysis, which provides a platform for exploring uncertainties arising from potential biases and other sources of error. The interaction between uncertainties in climatic input data and alternative approaches to process parameterisation in hydrological and cryospheric modelling is explored.

  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. 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 ...

  10. Quantification of Modeled Streamflow under Climate Change over the Flint River Watershed in Northern Alabama

    NASA Astrophysics Data System (ADS)

    Acharya, A.; Tadesse, W.; Lemke, D.; Subedi, S.

    2015-12-01

    This study is carried out to quantify the impacts of climate change and land use change on water availability over the Flint River watershed (FRW) located in the wheeler lake watershed in Northern Alabama. The FRW directly drains into the Tennessee River, which is a major source of water supply for the Southern States. The observed precipitation and temperature data are obtained from the Alabama Mesonet Stations which are also a part of National Resources Conservation Service (USDA NRCS) Soil Climate Analysis Network (SCAN). The GCM simulated climate data are obtained from the WCRP CMIP5 ensemble that consists of 234 downscaled climate projections from four emission scenarios and 37 GCMs. The hydrologic model SWAT is calibrated and validated for a period of 2004 to 2014, based on daily meteorological forcing and monthly streamflow data for the FRW. A total of 15 parameters that directly influences the surface/base flow and basin response are selected and calibrated. The anticipated change in future climate (2030s, 2050s, 2070s, 2090s) with respect to baseline period (2004-2014/2010s) for each emission scenario are introduced into baseline climate to perturb it to future climate pattern. Various climate scenarios based on future climate are forced into the calibrated SWAT model to quantify future water availability over the basin and compared with the baseline period. This is a part of the Geospatial Education and Research Center (GERC) project and the major research findings from this project will help decision makers in evaluating the combined impacts of climate change and land use change on water availability, and developing strategies to sustain available natural resources.

  11. 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

  12. 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.

  13. A 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.

    2000-01-01

    This paper describes a radiative transfer model developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. We use a newly developed k-distribution model for both the thermal and solar parts of the spectrum. We employ a generalized two-stream approximation for the scattering by aerosol and clouds. 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. We perform several calculations focussing primarily on the question of absorption of solar radiation by gases and aerosols. We estimate the accuracy of the k-distribution to be approx. 1 W/sq m for the gaseous absorption in the solar spectrum. We estimate the accuracy of the two-stream method to be 3-12 W/sq m for the downward solar flux and 1-5 W/sq m for the upward solar flux at the top of atmosphere depending on the optical depth of the aerosol layer. We also show that the effect of ignoring aerosol absorption on the downward solar flux at the surface is 50 W/sq m for the TARFOX aerosol for an optical depth of 0.5 and 150 W/sq m for a highly absorbing mineral aerosol. Thus, we conclude that the uncertainty introduced by the aerosol solar radiative properties (and merely assuming some "representative" model) can be considerably larger than the error introduced by the use of a two-stream method.

  14. Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

    NASA Astrophysics Data System (ADS)

    MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

    2015-04-01

    The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

  15. JPEG-2000 Part 10 Verification Model

    2003-03-04

    VM10 is a research software implementation of the ISO/IEC JPEG-2000 Still Image Coding standard (ISO international Standard 15444). JPEG-2000 image coding involves subband codiing and compression of digital raster images to facilitate storage and transmission of such imagery. Images are decomposed into space/scale subbands using cascades of two-dimensional (tensor product) discrete wavelet transforms. The wavelet transforms can be either reversible (integer-to-integer) transforms or irreversible (integer-to-float). The subbands in each resolution level are quantized by uniformmore » scalar quantization in the irreversible case. The resulting integer subbands in each resolution level are partitioned into spatially localized code blocks to facilitate localized entropy decoding. Code blocks are encoded and packaged into an embedded bitstream using binary arithmetic bitplane coding (the MQ Coder algorithm applied to hierarchical bitplane coding (the MQ coder algorithm applied to hierachical bitplane context modeling). The resultant compressed bitstream is configured for use with the JPIP interactive client-server protocol (JPEG-2000 part 9). VM10 is written in ANSI C++ using the Biltz++ array class library. To enable development of multidimensional image coding algorithms, VM10 is templated on the dimension of the array containers. It was developed with the GNU g++ compiler on both Linux (Red Hat) and Windows/cygwin platforms, although it should compile and run under other ANSI C++ compilers as well. Software design is highly modular and object-oriented in order to facilitate rapid development and frequent revision and experimentation. No attempt has been made to optimize the run-time performance of the code. The software performs both the encoding and decoding operations involved in JPEG-2000 image coding, as implemented in apps/compress/main.cpp and apps/expand/main.cpp. VM10 implements all of the JPEG-2000 baseline (Part 1, ISO 15444-1) and portions of the

  16. The Program for climate Model diagnosis and Intercomparison: 20-th anniversary Symposium

    SciTech Connect

    Potter, Gerald L; Bader, David C; Riches, Michael; Bamzai, Anjuli; Joseph, Renu

    2011-01-05

    Twenty years ago, W. Lawrence (Larry) Gates approached the U.S. Department of Energy (DOE) Office of Energy Research (now the Office of Science) with a plan to coordinate the comparison and documentation of climate model differences. This effort would help improve our understanding of climate change through a systematic approach to model intercomparison. Early attempts at comparing results showed a surprisingly large range in control climate from such parameters as cloud cover, precipitation, and even atmospheric temperature. The DOE agreed to fund the effort at the Lawrence Livermore National Laboratory (LLNL), in part because of the existing computing environment and because of a preexisting atmospheric science group that contained a wide variety of expertise. The project was named the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and it has changed the international landscape of climate modeling over the past 20 years. In spring 2009 the DOE hosted a 1-day symposium to celebrate the twentieth anniversary of PCMDI and to honor its founder, Larry Gates. Through their personal experiences, the morning presenters painted an image of climate science in the 1970s and 1980s, that generated early support from the international community for model intercomparison, thereby bringing PCMDI into existence. Four talks covered Gates's early contributions to climate research at the University of California, Los Angeles (UCLA), the RAND Corporation, and Oregon State University through the founding of PCMDI to coordinate the Atmospheric Model Intercomparison Project (AMIP). The speakers were, in order of presentation, Warren Washington [National Center for Atmospheric Research (NCAR)], Kelly Redmond (Western Regional Climate Center), George Boer (Canadian Centre for Climate Modelling and Analysis), and Lennart Bengtsson [University of Reading, former director of the European Centre for Medium-Range Weather Forecasts (ECMWF)]. The afternoon session emphasized

  17. The Martian Atmosphere, Climate, and General Circulation Models

    NASA Astrophysics Data System (ADS)

    Richardson, M. I.

    2004-05-01

    Our understanding of the Martian atmosphere, and the embodiment of this understanding in GCM models, sits part way between that of the Earth's atmosphere and that of the other planets in the solar system. Compared to the Earth, it is incomplete even as it applies to certain basic, elementary components and it is studied by a very limited community. Compared to the other planets in the solar system, most elements of the circulation are understood in outline, the data sets are vast and rich, and a number of well-staffed, competing modeling groups exist. Given this ``middle sibling'' status of Martian atmospheric science, an obvious issue arises as to whom it should be compared: Is the paucity of our understanding compared to the Earth motivation for redoubled efforts, or advanced state of knowledge cause to refocus on other planetary bodies? In this presentation, I will review the components of the Martian circulation and the progress that has been made in their understanding through the synthesis of data with GCMs. I will also review the aspects of Martian climate that uniquely influence the atmosphere. These include the lofting of dust by large-scale winds and thermal convection, resulting in a permanent (if varying) dust haze that significantly increases atmospheric temperatures, and occasionally leading to the generation of global dust storms. The spontaneous generation of such storms in a GCM has only very recently been accomplished. The condensation of the major atmospheric constituent (CO2) onto the surface to form massive seasonal ice caps in the frigid polar winter also generates a significant climate signal and a pole-to-pole condensation flow. Finally, Mars possesses an active water cycle with the development of clouds, formation of seasonal water ice deposits, and storage of water in the near-sub surface as adsorbate. The water cycle is fundamentally driven by exchange with a residual water ice cap at the northern (and not the southern) pole. Such

  18. Emulation of MIROC5 with a simple climate model

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    PubMed

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

    2014-01-01

    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.

  20. 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.

  1. Climate and natural production of rubber ( Hevea brasiliensis) in Xishuangbanna, southern part of Yunnan province, China

    NASA Astrophysics Data System (ADS)

    Jiang, Ailiang

    1988-12-01

    According to the author's and his collaborators' investigations, the climate influences the growth of rubber trees ( Hevea brasiliensis) in Xishuangbanna, the southern part of Yunnan Province, China, in at least four aspects: (1) The yield of latex per tapping and the final yield of dry rubber per tree per year or per unit area per year; (2) the growth rate, as expressed by increment of girth in cm; (3) the survival during the over-wintering period; (4) the initiation or suppression of certain diseases; In this paper the author would like to describe the influence of climatic elements on yield of latex and on survival during the over-wintering period. As for the other two aspects, only general comments are given.

  2. 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.

  3. 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

  4. The influence of HBV model calibration on flood predictions for future climate

    NASA Astrophysics Data System (ADS)

    Osuch, Marzena; Romanowicz, Renata

    2014-05-01

    The temporal variability of HBV rainfall-runoff model parameters was tested to address the influence of climate characteristics on the values of model optimal parameters. HBV is a conceptual model with a physically-based structure that takes into account soil moisture, snow-melt and dynamic runoff components. The model parameters were optimized by the DEGL method (Differential Evolution with Global and Local neighbours) for a set of catchments located in Poland. The methodology consisted of the calibration and cross-validation of the HBV models on a series of five-year periods within a moving window. The optimal parameter values show large temporal variability and dependence on climatic conditions described by the mean and standard deviation of precipitation, air temperature and PET. Derived regressions models between parameters and climatic indices were statistically significant at the 0.05 level. The set of model optimal values was applied to simulate future flows in a changed climate. We used the precipitation and temperature series from 6 RCM/GCM models for 2071-2100 following the A1B climate change scenario. The climatic variables were obtained from the KLIMADA project. The resulting flow series for the future climate scenario were used to derive flow indices, including the flood quantiles. Results indicate a large influence of climatic variability on flow indices. This work was partly supported by the project "Stochastic flood forecasting system (The River Vistula reach from Zawichost to Warsaw)" carried out by the Institute of Geophysics, Polish Academy of Sciences by order of the National Science Centre (contract No. 2011/01/B/ST10/06866). The rainfall and flow data were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

  5. Assessing climate model software quality: a defect density analysis of three models

    NASA Astrophysics Data System (ADS)

    Pipitone, J.; Easterbrook, S.

    2012-02-01

    A climate model is an executable theory of the climate; the model encapsulates climatological theories in software so that they can be simulated and their implications investigated. Thus, in order to trust a climate model one must trust that the software it is built from is built correctly. Our study explores the nature of software quality in the context of climate modelling. We performed an analysis of defect reports and defect fixes in several versions of leading global climate models by collecting defect data from bug tracking systems and version control repository comments. We found that the climate models all have very low defect densities compared to well-known, similarly sized open-source projects. We discuss the implications of our findings for the assessment of climate model software trustworthiness.

  6. Assessing climate model software quality: a defect density analysis of three models

    NASA Astrophysics Data System (ADS)

    Pipitone, J.; Easterbrook, S.

    2012-08-01

    A climate model is an executable theory of the climate; the model encapsulates climatological theories in software so that they can be simulated and their implications investigated. Thus, in order to trust a climate model, one must trust that the software it is built from is built correctly. Our study explores the nature of software quality in the context of climate modelling. We performed an analysis of defect reports and defect fixes in several versions of leading global climate models by collecting defect data from bug tracking systems and version control repository comments. We found that the climate models all have very low defect densities compared to well-known, similarly sized open-source projects. We discuss the implications of our findings for the assessment of climate model software trustworthiness.

  7. Climate change of the last millennium inferred from borehole temperatures: regional patterns of climatic changes in the Czech Republic — Part III

    NASA Astrophysics Data System (ADS)

    Bodri, L.; Čermák, V.

    1999-09-01

    Accurate temperature-depth profiles may help to assess the temperature variations associated with the climate changes in the past. Ninety-eight ground surface temperature histories inverted from the temperature-depth borehole logs drilled on the territory of the Czech Republic [Bodri, L., Čermák, V., 1995. Climate changes of the last millennium inferred from borehole temperatures: results from the Czech Republic — Part I. Global Planet. Change 11, pp. 111-125; Bodri, L., Čermák, V., 1997. Climate changes of the last two millennia inferred from borehole temperatures: results from the Czech Republic — Part II. Global Planet. Change 14, pp. 163-173.] are used to reconstruct the regional patterns of the respective climate change. The climate was mapped for the following periods: 1100-1300 A.D. (Little Climatic Optimum), 1400-1500 A.D., 1600-1700 A.D. (main phase of the Little Ice Age), and for the most recent climate trend after year 1960. Comparison of the obtained maps with the meteorological observations and proxy climatic reconstructions confirmed good applicability of the "geothermal" paleoclimatic reconstructions for the regional studies.

  8. 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.

  9. 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

  10. 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.; Cederwall, Richard T.; Wiscombe, Warren J.; Clothiaux, Eugene E.; Gaustad, Krista L.; Golaz, Jean -Christophe; Hall, Stephanie D.; Jensen, Michael P.; et al

    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.

  11. Climate condition in the Central Europe during the Weichselian Ice Sheet according to the Educational Global Climate Modeling Project

    NASA Astrophysics Data System (ADS)

    Szuman, Izabela; Czernecki, Bartosz

    2010-05-01

    The expansion and retreat of the ice sheet is controlled by climate changes, and from the other hand, a huge ice mass influences on the climate in the regional scale. This mechanism is commonly known as the fact but often without making reconstruction by using climatological modeling. The purpose of our study is to reconstruct the climate condition during the Weichselian Ice Sheet in the Central Europe, especially for Poland and surrounded countries. The Global Climate Model (GCM) is made for predicting climate, but simplified version can be useful for reconstructing paleoclimate. Hence, the simple initial conditions and surface data proposed by the Educational version of the GCM was applied. In our study we used a simplified version of the GCM to calculate main climate characteristics within the time limits c. 21 000 BP - 18 000 BP, which has been previously invented on Columbia University. The model is constructed on grid with a horizontal resolution 8° latitude by 10° longitude and was establish for modeling most of weather conditions based on available paleoclimate data. It is possible to estimate the probable climate condition along the southern ice sheets margin on the basis of output from the GCM and GIS modeling techniques. Above the ice mass occurs local high pressure area, which seriously interfered on atmospheric circulation. Whereas the low pressure systems in the southern part of continent may caused permanent barometric situation, which stimulates wind directions as well as the precipitable water available in the mass of air. The climate on the east-south border of ice margin was colder and drier than on the west-south region, where it was more ocean-reliable and gentle with higher temperatures. The differences in temperature between the western and eastern part of the Central Europe reached few centigrade. Against a background of the mean paleoclimatic situation in the Central Europe there is coming out a question about the particular paleoclimate

  12. 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.

  13. 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

  14. Instructional Climates in Preschool Children Who Are At-Risk. Part I: Object-Control Skill Development

    ERIC Educational Resources Information Center

    Robinson, Leah E.; Goodway, Jacqueline D.

    2009-01-01

    Part I of this study examined the effect of two 9-week instructional climates (low autonomy [LA] and mastery motivational climate [MMC]) on object-control (OC) skill development in preschoolers (N = 117). Participants were randomly assigned to an LA, MMC, or comparison group. OC skills were assessed at pretest, posttest, and retention test with…

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

    SciTech Connect

    Mahowald, Natalie; Rothenberg, D.; Lindsay, Keith; Doney, Scott C.; Moore, Jefferson Keith; Randerson, James T.; Thornton, Peter E; Jones, C. D.

    2011-02-01

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

  16. Changes in methane fluxes from the North Eurasian wetlands associated with climate changes simulated by the regional climate model

    NASA Astrophysics Data System (ADS)

    Denisov, S. N.; Eliseev, A. V.; Mokhov, I. I.

    2009-04-01

    Climate changes in pan-Arctic regions and their impact on methane emissions from wetlands are estimated based on simulations for the European and Asian parts of Russia with a regional climate model developed at the A.I. Voeikov Main Geophysical Observatory. These simulations are forced by the large-scale climate fields obtained in the SRES B1 and SRES A2 runs. Methane fluxes from wetlands are diagnosed making use the modified Christensen-Cox model. For the late 20th century, total wetland CH4 emissions amount 8 MtCH4/yr and 10 MtCH4/yr for the European and Asian parts of Russia respectively. To the end of the 21st century, these emissions increase up to 14 MtCH4/yr and 17 MtCH4/yr correspondingly. The dominant mechanism of growth for the CH4 emission from wetlands is a methane production enhancement in water filled soils due to increase of soil temperature.

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  18. GCM Simulations of Volcanic Aerosol Forcing. Part I: Climate Changes Induced by Steady-State Perturbations.

    NASA Astrophysics Data System (ADS)

    Pollack, James B.; Rind, David; Lacis, Andrew; Hansen, James E.; Sato, Makiko; Ruedy, Reto

    1993-09-01

    The authors have used the Goddard Institute for Space Studies Climate Model II to simulate the response of the climate system to a spatially and temporally constant forcing by volcanic aerosols having an optical depth of 0.15. The climatic changes produced by long-term volcanic aerosol forcing are obtained by differencing this simulation and one made for the present climate with no volcanic aerosol forcing. These climatic changes are compared with those obtained with the same climate model when the C02 content of the atmosphere was doubled (2×C02) and when the boundary conditions associated with the peak of the last ice age were used (18 K). In all three cases, the absolute magnitude of the change in the globally averaged air temperature at the surface is approximately the same, 5 K.The simulations imply that a significant cooling of the troposphere and surface can occur at times of closely spaced, multiple, sulfur-rich volcanic explosions that span time scales of decades to centuries, such as occurred at the end of the nineteenth and beginning of the twentieth centuries. The steady-state climate response to volcanic forcing includes a large expansion of sea ice, especially in the Southern Hemisphere; a resultant large increase in surface and planetary albedo at high latitudes; and sizable changes in the annually and zonally averaged air temperature, T; T at the surface (Ts) does not sharply increase with increasing latitude, while T in the lower stratosphere is positive at low latitudes and negative at high latitudes.In certain ways, the climate response to the three different forcings is similar. Direct radiative forcing accounts for 30% and 25% of the total Ts in the volcano and 2×C02 runs, respectively. Changes in atmospheric water vapor act as the most important feedback, and are positive in all three cases. Albedo feedback is a significant, positive feedback at high latitudes in all three simulations, although the land ice feedback is prominent only in the

  19. 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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  2. 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.

  3. Animal Models of Ischemic Stroke. Part One: Modeling Risk Factors

    PubMed Central

    Bacigaluppi, Marco; Comi, Giancarlo; Hermann, Dirk M.

    2010-01-01

    Ischemic stroke is one of the leading causes of long-term disability and death in developed and developing countries. As emerging disease, stroke related mortality and morbidity is going to step up in the next decades. This is both due to the poor identification of risk factors and persistence of unhealthy habits, as well as to the aging of the population. To counteract the estimated increase in stroke incidence, it is of primary importance to identify risk factors, study their effects, to promote primary and secondary prevention, and to extend the therapeutic repertoire that is currently limited to the very first hours after stroke. While epidemiologic studies in the human population are essential to identify emerging risk factors, adequate animal models represent a fundamental tool to dissect stroke risk factors to their molecular mechanism and to find efficacious therapeutic strategies for this complex multi- factorial disorder. The present review is organized into two parts: the first part deals with the animal models that have been developed to study stroke and its related risk factors and the second part analyzes the specific stroke models. These models represent an indispensable tool to investigate the mechanisms of cerebral injury and to develop novel therapies. PMID:20802809

  4. Use of regional climate models data for groundwater recharge modelling in Baltic artesian basin

    NASA Astrophysics Data System (ADS)

    Timuhins, A.; Klints, I.; Sennikovs, J.; Virbulis, J.

    2012-04-01

    Baltic artesian basin (BAB) covers about 480000 square kilometres. BAB includes territory of Latvia, Lithuania, Estonia, parts of Poland, Russia, Belarus and Baltic Sea. The closed hydrogeological mathematical model for the BAB is developed in University of Latvia and reference calculations made in steady state mode. No-flow boundary condition is applied on the bottom and side boundaries of BAB. Hydraulic head is fixed on the seabed and largest lakes, and along the main river lines. Main water supply wells also are presented in the model as a pointwise water extraction. Precipitation is the main source of the groundwater recharge in the BAB region. Infiltration parameterization is responsible for this water source in BAB model. During the early stage of calibration of BAB hydrogeological model an automatic calibration for the hydraulic conductivities of permeable layers and single infiltration rate was attempted. Performing BAB model calibration it was noted that the differences of calculated and observed hydraulic heads (used for calculating the calibration penalty function) can be reduced by introducing a spatially distributed infiltration model. The aim of the present study is improving of the infiltration model, as well as preserving a short computation time (several minutes) for the piezometric head. Direct solution of improvement of the infiltration would be a usage of the advanced hydrological models. However, an accurate hydrological model requires a lot of computational power. It should couple meteorological and hydrological parameters and requires additional calibration. The regional climate model (KNMI-RACMO2 25 km resolution) results from ENSEMBLES project are used for the spatially distributed infiltration field calculation. The infiltration field is constructed as weighted difference of 30 year averaged precipitation and evaporation fields. The weight value is calibrated and a considerable decrease of the value of penalty function of the groundwater

  5. Teacher Challenges, Perceptions, and Use of Science Models in Middle School Classrooms about Climate, Weather, and Energy Concepts

    ERIC Educational Resources Information Center

    Yarker, Morgan Brown

    2013-01-01

    Research suggests that scientific models and modeling should be topics covered in K-12 classrooms as part of a comprehensive science curriculum. It is especially important when talking about topics in weather and climate, where computer and forecast models are the center of attention. There are several approaches to model based inquiry, but it can…

  6. Berry composition and climate: responses and empirical models.

    PubMed

    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

  7. 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

  8. Climate-Driven Phenological Change: Developing Robust Spatiotemporal Modeling and Projection Capability.

    PubMed

    Prieto, Carmen; Destouni, Georgia

    2015-01-01

    Our possibility to appropriately detect, interpret and respond to climate-driven phenological changes depends on our ability to model and predict the changes. This ability may be hampered by non-linearity in climate-phenological relations, and by spatiotemporal variability and scale mismatches of climate and phenological data. A modeling methodology capable of handling such complexities can be a powerful tool for phenological change projection. Here we develop such a methodology using citizen scientists' observations of first flight dates for orange tip butterflies (Anthocharis cardamines) in three areas extending along a steep climate gradient. The developed methodology links point data of first flight observations to calculated cumulative degree-days until first flight based on gridded temperature data. Using this methodology we identify and quantify a first flight model that is consistent across different regions, data support scales and assumptions of subgrid variability and observation bias. Model application to observed warming over the past 60 years demonstrates the model usefulness for assessment of climate-driven first flight change. The cross-regional consistency of the model implies predictive capability for future changes, and calls for further application and testing of analogous modeling approaches to other species, phenological variables and parts of the world. PMID:26545112

  9. 12 CFR Appendix A to Part 233 - Model Notice

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... Federal Regulations (12 CFR part 233) and part 132 of title 31 of the U.S. Code of Federal Regulations (31 CFR part 132). ... FUNDING OF UNLAWFUL INTERNET GAMBLING (REGULATION GG) Part 233, App. A Appendix A to Part 233—Model...

  10. 31 CFR Appendix A to Part 132 - Model Notice

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... one another can be found at part 233 of title 12 of the U.S. Code of Federal Regulations (12 CFR part 233) and part 132 of title 31 of the U.S. Code of Federal Regulations (31 CFR part 132). ... INTERNET GAMBLING Pt. 132, App. A Appendix A to Part 132—Model Notice Re: U.S. Unlawful Internet...

  11. 12 CFR Appendix A to Part 233 - Model Notice

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... Federal Regulations (12 CFR part 233) and part 132 of title 31 of the U.S. Code of Federal Regulations (31 CFR part 132). ... FUNDING OF UNLAWFUL INTERNET GAMBLING (REGULATION GG) Part 233, App. A Appendix A to Part 233—Model...

  12. 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

  13. Perspective: The Climate-Population-Infrastructure Modeling and Simulation Fertile Area for New Research

    SciTech Connect

    Allen, Melissa R; Fernandez, Steven J; Walker, Kimberly A; Fu, Joshua S

    2014-01-01

    Managing the risks posed by climate change and extreme weather to energy production and delivery is a challenge to communities worldwide. As climate conditions change, populations will shift, and demand will re-locate; and networked infrastructures will evolve to accommodate new load centers, and, hopefully, minimize vulnerability to natural disaster. Climate effects such as sea level rise, increased frequency and intensity of natural disasters, force populations to move locations. Displaced population creates new demand for built infrastructure that in turn generates new economic activity that attracts new workers and associated households to the new locations. Infrastructures and their interdependencies will change in reaction to climate drivers as the networks expand into new population areas and as portions of the networks are abandoned as people leave. Thus, infrastructures will evolve to accommodate new load centers while some parts of the network are underused, and these changes will create emerging vulnerabilities. Forecasting the location of these vulnerabilities by combining climate predictions and agent based population movement models shows promise for defining these future population distributions and changes in coastal infrastructure configurations. By combining climate and weather data, engineering algorithms and social theory it has been only recently possible to examine electricity demand response to increased climactic temperatures, population relocation in response to extreme cyclonic events, consequent net population changes and new regional patterns in electricity demand. These emerging results suggest a research agenda of coupling these disparate modelling approaches to understand the implications of climate change for protecting the nation s critical infrastructure.

  14. 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

  15. Modelling climate change: the role of unresolved processes.

    PubMed

    Williams, Paul D

    2005-12-15

    Our understanding of the climate system has been revolutionized recently, by the development of sophisticated computer models. The predictions of such models are used to formulate international protocols, intended to mitigate the severity of global warming and its impacts. Yet, these models are not perfect representations of reality, because they remove from explicit consideration many physical processes which are known to be key aspects of the climate system, but which are too small or fast to be modelled. The purpose of this paper is to give a personal perspective of the current state of knowledge regarding the problem of unresolved scales in climate models. A recent novel solution to the problem is discussed, in which it is proposed, somewhat counter-intuitively, that the performance of models may be improved by adding random noise to represent the unresolved processes.

  16. Climate Sensitivity

    NASA Astrophysics Data System (ADS)

    Hansen, J.

    2007-12-01

    Discussion of climate sensitivity requires careful definition of forcings, feedbacks and response times, indeed, foggy definitions have produced flawed assessments of climate sensitivity. The best information available on climate sensitivity comes from insightful interpretation of the Earth's history aided by quantitative information from climate models and understanding of climate processes. Climate sensitivity is a strong function of time scale, in part because of the nature of climate feedbacks. Unfortunately for humanity, the preponderance of feedbacks on the century time scale appears to be positive. The chief implication is the need for a sharp reversal in the trend of human-made climate forcing, if we are to avoid creating a planet that is dramatically different than the one on which civilization developed.

  17. 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.

  18. 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.

  19. Progress in climate model simulations of geoengineering

    NASA Astrophysics Data System (ADS)

    Kravitz, Ben; Robock, Alan; Haywood, James M.

    2012-08-01

    Second GeoMIP Stratospheric Aerosol Geoengineering Workshop; Exeter, United Kingdom, 30-31 March 2012 Geoengineering through solar radiation management consists of hypothetical approaches to directly intervene in the climate system to counteract some consequences of anthropogenic greenhouse gas emissions. One commonly studied method involves creating a layer of sulfate aerosols in the stratosphere covering most of the globe. This method takes inspiration from large volcanic eruptions, which cool the planet for a few years after the eruption.

  20. Variable-Resolution GCMs for Regional Climate Modeling: Stretched-Grid Model Intercomparison Project (SGMIP)

    NASA Astrophysics Data System (ADS)

    Fox-Rabinovitz, M.; Cote, J.; Dugas, B.; Deque, M.; McGregor, J.

    2006-05-01

    Variable-resolution GCMs using a global stretched grid (SG) with enhanced resolution over the region(s) of interest have proven to be an established approach to regional climate modeling providing an efficient regional down-scaling to mesoscales. This approach has been used since the early-mid 90s by the French, U.S., Canadian, Australian and other climate modeling groups along with the widely-used nested-grid approach. The important advantages of SG-GCMs are that they do not require any lateral boundary conditions/forcing and are free of the associated undesirable computational problems. SG-GCMs provide self-consistent interactions between global and regional scales, while a high quality of global circulation is preserved. The international SGMIP-1 (Stretched-Grid Model Intercomparison Project, phase-1), using SG-GCMs developed at the major centers/groups in Australia, Canada, France, and the U.S., has been successfully conducted in 2002-2005. The results of the 12-year (1987-1998) climate simulations for a major part of North America are available at the SGMIP web site: http://essic.umd.edu/~foxrab/sgmip.html, and are described in [1]. The multi-model SGMIP-1 regional climate simulations were conducted with enhanced 0.45 - 0.5 degree regional resolution for SG-GCMs, with the same or a similar number of global grid points as in a 1 x 1 degree global grid. The SGMIP-1 SG-GCM simulations were analyzed in terms of studying the impact of high regional resolution on efficient downscaling to realistic mesoscales and regional climate variability. We focused mostly on studying the quality of the multi-model ensemble results. The SGMIP-1 multi-model ensemble results for the region compare well with reanalysis and observations, in terms of spatial and temporal diagnostics. The next SGMIP phase, SGMIP-2 (phase-2), includes comparisons of high resolution stretched and uniform grid GCMs. These SGMIP-2 experiments provide the possibility for a comprehensive analysis of enhanced

  1. Diagnosing Present and Future Permafrost from Climate Models

    NASA Astrophysics Data System (ADS)

    Lawrence, D. M.; Slater, A. G.

    2012-12-01

    Permafrost is a characteristic aspect of the terrestrial Arctic and the fate of near-surface permafrost over the next century is likely to exert strong controls on Arctic hydrology and biogeochemistry. Using output from CMIP5 climate models, we assess their ability to simulate present-day and future permafrost. Permafrost extent diagnosed directly from each climate model's soil temperature is a function of the modeled surface climate as well as the ability of the land surface model to represent permafrost physics. For each CMIP5 model we separate these two effects by using indirect estimators of permafrost driven by climatic indices and compare them to permafrost extent directly diagnosed via soil temperatures. Several robust conclusions can be drawn from our analysis. Significant air temperature and snow depth biases exist in some model's climates, which degrade both directly and indirectly diagnosed permafrost conditions. The range of directly calculated present-day (1986-2005) permafrost area is extremely large (~4 to 25×106 km2). Several land models contain structural weaknesses that limit their skill in simulating cold regions subsurface processes. The sensitivity of future permafrost extent to temperature change over the present-day observed permafrost region averages 1.67(±0.7)×106 km2/°C but is a function of the spatial and temporal distribution of climate change. Due to sizable differences in future climates for the RCP emission scenarios, a wide variety of future permafrost states is predicted by 2100. Conservatively, the models suggest that for RCP4.5, permafrost will retreat completely from the present-day discontinuous zone. Under RCP8.5, permafrost will be most probable only in the Canadian Archipelago, Russian Arctic coast and East Siberian uplands.

  2. 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

  3. Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

    PubMed Central

    Hansen, James W

    2005-01-01

    Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

  4. 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.

  5. Evaluation of the impact of climate change on hydrology and water resources in Swaziland: Part I

    NASA Astrophysics Data System (ADS)

    Matondo, Jonathan I.; Peter, Graciana; Msibi, Kenneth M.

    It has been identified that, long-term climatic changes (Pleistocene ice ages) have been caused by periodic changes in the distribution of incoming solar radiation due to the variations in the earth’s orbital geometry, that is the tilt, precision of equinoxes and eccentricity which take place with periodicity ranging from 41 to 9508 thousand years. However, it has been considered that the major potential mechanism of climate change over the next few hundred years will be anthropogenic green house gas warming up. A number of gases that occur naturally in the atmosphere in small quantities are known as ”greenhouse gases. Water vapour, carbon dioxide, ozone, methane, and nitrous oxide trap solar energy in much the same way as do the glass panes of a greenhouse or a closed automobile. This natural greenhouse gases effect has kept the earth’s atmosphere some 30 °C hotter, than it would otherwise be, making it possible for humans to exist on earth. Human activities, however, are now raising the concentrations of these gases in the atmosphere and thus increasing their ability to trap energy. The enhanced greenhouse gas effect is expected to cause high temperature increase globally (1-3.5 °C) and this will lead to an increase in precipitation in some regions while other regions will experience reduced precipitation (±20%). The impact of expected climate change will affect almost all the sectors of the human endeavor. However, the major purpose of this project is to evaluate the impact of climate change on hydrology and water resources and establish the appropriate adaptation strategies for Swaziland. The impact of climate change on hydrology and water resources will be evaluated using General Circulation Model results (rainfall, potential evapotranspiration, air temperature, etc.) as inputs to a rainfall runoff model. Water use in all the sectors of the human endeavor will be determined in order to establish the water availability given different climate change

  6. The origins of computer weather prediction and climate modeling

    SciTech Connect

    Lynch, Peter

    2008-03-20

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

  7. Using Clustered Climate Regimes to Analyze and Compare Predictions from Fully Coupled General Circulation Models

    SciTech Connect

    Hoffman, Forrest M; Hargrove, William Walter; Erickson III, David J; Oglesby, Robert J

    2005-01-01

    Changes in Earth's climate in response to atmospheric greenhouse gas buildup impact the health of terrestrial ecosystems and the hydrologic cycle. The environmental conditions influential to plant and animal life are often mapped as ecoregions, which are land areas having similar combinations of environmental characteristics. This idea is extended to establish regions of similarity with respect to climatic characteristics that evolve through time using a quantitative statistical clustering technique called Multivariate Spatio-Temporal Clustering (MSTC). MSTC was applied to the monthly time series output from a fully coupled general circulation model (GCM) called the Parallel Climate Model (PCM). Results from an ensemble of five 99-yr Business-As-Usual (BAU) transient simulations from 2000 to 2098 were analyzed. MSTC establishes an exhaustive set of recurring climate regimes that form a 'skeleton' through the 'observations' (model output) throughout the occupied portion of the climate phase space formed by the characteristics being considered. MSTC facilitates direct comparison of ensemble members and ensemble and temporal averages since the derived climate regimes provide a basis for comparison. Moreover, by mapping all land cells to discrete climate states, the dynamic behavior of any part of the system can be studied by its time-varying sequence of climate state occupancy. MSTC is a powerful tool for model developers and environmental decision makers who wish to understand long, complex time series predictions of models. Strong predicted interannual trends were revealed in this analysis, including an increase in global desertification; a decrease in the cold, dry high-latitude conditions typical of North American and Asian winters; and significant warming in Antarctica and western Greenland.

  8. Modelling of labour productivity loss due to climate change: HEAT-SHIELD

    NASA Astrophysics Data System (ADS)

    Kjellstrom, Tord; Daanen, Hein

    2016-04-01

    Climate change will bring higher heat levels (temperature and humidity combined) to large parts of the world. When these levels reach above thresholds well defined by human physiology, the ability to maintain physical activity levels decrease and labour productivity is reduced. This impact is of particular importance in work situations in areas with long high intensity hot seasons, but also affects cooler areas during heat waves. Our modelling of labour productivity loss includes climate model data of the Inter-Sectoral Impact Model Inter-comparison Project (ISI-MIP), calculations of heat stress indexes during different months, estimations of work capacity loss and its annual impacts in different parts of the world. Different climate models will be compared for the Representative Concentration Pathways (RCPs) and the outcomes of the 2015 Paris Climate Conference (COP21) agreements. The validation includes comparisons of modelling outputs with actual field studies using historical heat data. These modelling approaches are a first stage contribution to the European Commission funded HEAT-SHIELD project.

  9. Estimation of the fractional coverage of rainfall in climate models

    NASA Technical Reports Server (NTRS)

    Eltahir, E. A. B.; Bras, R. L.

    1993-01-01

    The fraction of the grid cell area covered by rainfall, mu, is an essential parameter in descriptions of land surface hydrology in climate models. A simple procedure is presented for estimating this fraction, based on extensive observations of storm areas and rainfall volumes. Storm area and rainfall volume are often linearly related; this relation can be used to compute the storm area from the volume of rainfall simulated by a climate model. A formula is developed for computing mu, which describes the dependence of the fractional coverage of rainfall on the season of the year, the geographical region, rainfall volume, and the spatial and temporal resolution of the model. The new formula is applied in computing mu over the Amazon region. Significant temporal variability in the fractional coverage of rainfall is demonstrated. The implications of this variability for the modeling of land surface hydrology in climate models are discussed.

  10. 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.

  11. 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.

  12. 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

  13. Long-Term Climate Commitments Projected with Climate-Carbon Cycle Models

    NASA Astrophysics Data System (ADS)

    Plattner, G.

    2008-12-01

    Earth system models of intermediate complexity (EMICs) are increasingly used to project long-term carbon cycle and climate change commitments. Here I present results from several EMICs used in the IPCC AR4 to project the climate response to stabilization scenarios and to estimate emissions requirements for climate stabilization. Substantial climate change commitments for sea level rise and global mean surface temperature increase after a stabilization of atmospheric greenhouse gases and radiative forcing in the year 2100 are identified. The additional warming by the year 3000 is 0.6-1.6 K for the low-CO2 IPCC SRES B1 scenario and 1.3-2.2 K for the high-CO2 SRES A2 scenario. The post-2100 thermal expansion commitment is 0.3-1.1 m for SRES B1 and 0.5-2.2 m for SRES A2. Sea level continues to rise due to thermal expansion for several centuries after CO2 stabilization. In contrast, surface temperature changes slow down after a century. Emissions during the twenty-first century continue to impact atmospheric CO2 and climate even at year 3000, highlighting the longevity of the atmospheric CO2 perturbation. All models find that while most of the anthropogenic carbon emissions are eventually taken up by the ocean (49%- 62%) in year 3000, a substantial fraction (15%-28%) is still airborne even 900 yr after carbon emissions have ceased. Future stabilization of atmospheric CO2 and climate change require a substantial reduction of CO2 emissions below present levels in all EMICs. This reduction needs to be substantially larger if carbon cycle-climate feedbacks are accounted for or if terrestrial CO2 fertilization is not operating. Large differences among EMICs are identified in both the response to increasing atmospheric CO2 and the response to climate change. This highlights the need for improved representations of carbon cycle processes in these models apart from the sensitivity to climate change. Both carbon cycle and climate sensitivity related uncertainties on projected

  14. Model biases in rice phenology under warmer climates

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  15. Model biases in rice phenology under warmer climates.

    PubMed

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

    2016-01-01

    Climate-induced crop yields model projections are constrained by the accuracy of the phenology simulation in crop models. Here, we use phenology observations from 775 trials with 19 rice cultivars in 5 Asian countries to compare the performance of four rice phenology models (growing-degree-day (GDD), exponential, beta and bilinear models) when applied to warmer climates. For a given cultivar, the difference in growing season temperature (GST) varied between 2.2 and 8.2 °C in different trials, which allowed us to calibrate the models for lower GST and validate under higher GST, with three calibration experiments. The results show that in warmer climates the bilinear and beta phenology models resulted in gradually increasing bias for phenology predication and double yield bias per percent increase in phenology simulation bias, while the GDD and exponential models maintained a comparatively constant bias. The phenology biases were primarily attributed to varying phenological patterns to temperature in models, rather than on the size of the calibration dataset. Additionally, results suggest that model simulations based on multiple cultivars provide better predictability than using one cultivar. Therefore, to accurately capture climate change impacts on rice phenology, we recommend simulations based on multiple cultivars using the GDD and exponential phenology models. PMID:27273847

  16. Model biases in rice phenology under warmer climates.

    PubMed

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

    2016-06-07

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

  17. Model biases in rice phenology under warmer climates

    PubMed Central

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

    2016-01-01

    Climate-induced crop yields model projections are constrained by the accuracy of the phenology simulation in crop models. Here, we use phenology observations from 775 trials with 19 rice cultivars in 5 Asian countries to compare the performance of four rice phenology models (growing-degree-day (GDD), exponential, beta and bilinear models) when applied to warmer climates. For a given cultivar, the difference in growing season temperature (GST) varied between 2.2 and 8.2 °C in different trials, which allowed us to calibrate the models for lower GST and validate under higher GST, with three calibration experiments. The results show that in warmer climates the bilinear and beta phenology models resulted in gradually increasing bias for phenology predication and double yield bias per percent increase in phenology simulation bias, while the GDD and exponential models maintained a comparatively constant bias. The phenology biases were primarily attributed to varying phenological patterns to temperature in models, rather than on the size of the calibration dataset. Additionally, results suggest that model simulations based on multiple cultivars provide better predictability than using one cultivar. Therefore, to accurately capture climate change impacts on rice phenology, we recommend simulations based on multiple cultivars using the GDD and exponential phenology models. PMID:27273847

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

    NASA Astrophysics Data System (ADS)

    Tsonis, A.; Steinhaeuser, K.

    2013-12-01

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

  19. A climate model intercomparison at the dynamics level

    NASA Astrophysics Data System (ADS)

    Tsonis, A.; Steinhaeuser, K.

    2012-12-01

    Up to now climate model intercomparison has focused on annual and global averages of various quantities or on specific components, not on how well the general dynamics in the models compare to each other. In order to address how well the models agree when it comes to dynamics they generate, we have adopted a new approach based on climate networks. We have considered 57 20th-century control runs from 17 climate models and have constructed networks for the 500 hPa, surface air temperature (SAT), and sea level pressure (SLP) fields for each run. Then we used two different algorithms to derive the community structure in these networks. Communities separate "nodes' in the network sharing similar dynamics. It has been shown that these communities, or sub-systems, in the climate system are associated with major climate modes and physics of the atmosphere 1-3. Once the community structure for all runs is derived we use a pattern matching statistic to obtain a measure of how well any two models agree with each other. We find that with possibly the exception of the 500 hPa filed, the consistency for the SLP and especially SAT fields is questionable. More importantly none of the models comes close to the community structure of the actual observations (reality). This is a significant finding especially for the temperature field, as this is the field predicted to produce temperature projections in time and in space.

  20. A climate model intercomparison at the dynamics level

    NASA Astrophysics Data System (ADS)

    Tsonis, Anastasios; Steinhaeuser, Karsten

    2013-04-01

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

  1. Development of the Southern Ocean Climate Model Atlas

    NASA Astrophysics Data System (ADS)

    Rudd, J.; Russell, J. L.; Goodman, P. J.

    2014-12-01

    The development of consistent, observationally-based metrics, by which to assess the fidelity of a model simulation is being undertaken by many modelers and modeling groups. A "Southern Ocean Climate Model Atlas" is under construction that will house the results of these various analyses and will provide access for fellow scientists, stakeholders, resource managers and the public to the latest projections of climate and climate change from all of the available climate models. This Atlas will allow a visual comparison of simulated fields, differences and errors and will include quantification of the errors where the observations permit. It will also include the scripts required for anyone to create a comparable map with their own data/output. We will discuss the creation of observationally-based metrics and some of the challenges associated with the consistent quantification of simulations errors and inter-model differences. We will also present some of the commonly assessed variables (e.g. temperature, winds, ice, pH) useful to climate scientists, ecosystem scientists and the general public.

  2. 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.

  3. Spatial Modeling of Indian Agriculture, Economic Activity and Population under Climate Change

    NASA Astrophysics Data System (ADS)

    McCord, G. C.

    2010-12-01

    We present a spatial model of economic activity and human population built on physical geography that takes particular account of its effects through agricultural productivity and transport costs for trade. A major component of this work is an agricultural model, driven in part by high-resolution climate data and model output. We put forward India as the initial region for this modeling work; India is a relatively data-rich country, it exhibits significant within-country spatial and temporal variation in agricultural productivity, urbanization rates, and population growth rates, and the climate dynamics of the monsoon are well-studied and expected to change on decadal time scales. Agricultural productivity is modeled as a function of soil, climate, and technology variables. Farmers locate optimally given varying geography and transport costs; in turn, food availability defines urbanization rates and economic activity in non-agricultural sectors. This “social system” integrated assessment model is a step towards a valuable policy tool, but requires a significant mobilization of data and a grid-cell-level system of equations to describe the underlying dynamics of the model. We test against past trends of social-natural system progression in demography, human location, income, food production, etc., and argue that the model could be used to assess future trends under varying climate change scenarios, and eventually serve to model feedbacks through effects on migration, population growth rates, or economic activity.

  4. An overview of the Yucca Mountain Global/Regional Climate Modeling Program

    SciTech Connect

    Sandoval, R.P.; Behl, Y.K.; Thompson, S.L.

    1992-01-10

    The US Department of Energy (DOE) has developed a site characterization plan (SCP) to collect detailed information on geology, geohydrology, geochemistry, geoengineering, hydrology, climate, and meteorology (collectively referred to as ``geologic information``) of the Yucca Mountain site. This information will be used to determine if a mined geologic disposal system (MGDS) capable of isolating high-level radioactive waste without adverse effects to public health and safety over 10,000 years, as required by regulations 40 CFR Part 191 and 10 CFR Part 60, could be constructed at the Yucca Mountain site. Forecasts of future climates conditions for the Yucca Mountain area will be based on both empirical and numerical techniques. The empirical modeling is based on the assumption that future climate change will follow past patterns. In this approach, paleclimate records will be analyzed to estimate the nature, timing, and probability of occurrence of certain climate states such as glacials and interglacials over the next 10,000 years. For a given state, key climate parameters such as precipitation and temperature will be assumed to be the same as determined from the paleoclimate data. The numerical approach, which is the primary focus of this paper, involves the numerical solution of basic equations associated with atmospheric motions. This paper describes these equations and the strategy for solving them to predict future climate conditions around Yucca Mountain.

  5. Modeling Transient Response of Forests to Climate Change

    SciTech Connect

    Dale, Virginia H; Tharp, M Lynn; Lannom, Karen O.; Hodges, Donald G

    2010-01-01

    Our hypothesis is that a high diversity of dominant life forms in Tennessee forests conveys resilience to disturbance such as climate change. Because of uncertainty in climate change and their effects, three climate change scenarios for 2030 and 2080 from three General Circulation Models (GCMs) were used to simulate a range of potential climate conditions for the state. These climate changes derive from the Intergovernmental Panel on Climate Change (IPCC) A1B storyline that assumes rapid global economic growth. The precipitation and temperature projections from the three GCMs for 2030 and 2080 were related to changes in five ecological provinces using the monthly record of temperature and precipitation from 1980 to 1997 for each 1 km cell across the state as aggregated into the provinces. Temperatures are projected to increase in all ecological provinces in all months for all three GCMs for both 2030 and 2080. Precipitation differences from the long-term average are more complex but less striking. The forest ecosystem model LINKAGES was used to simulate conditions for five ecological provinces from 1989 to 2300. Average output projects changes in tree diversity and species composition in all ecological provinces in Tennessee with the greatest changes in the Southern Mixed Forest province. Projected declines in total tree biomass are followed by biomass recovery as species replacement occurs in stands. The Southern Mixed Forest province results in less diversity in dominant trees as well as lower overall biomass than projections for the other four provinces. The biomass and composition changes projected in this study differ from forest dynamics expected without climate change. These results suggest that biomass recovery following climate change is linked to dominant tree diversity in the southeastern forest of the US. The generality of this observation warrants further investigation, for it relates to ways that forest management may influence climate change effects.

  6. 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.

  7. 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.

  8. 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. PMID:22822430

  9. Modeled regional climate change and California endemic oak ranges.

    PubMed

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

    2005-11-01

    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.

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  12. 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

  13. Use of multi-model ensembles for regional climate downscaling

    NASA Astrophysics Data System (ADS)

    Reichler, Thomas; Andrade, Marcos; Ohara, Noriaki

    2014-05-01

    Dynamic regional downscaling requires use of a regional model driven at its boundaries by the output from coarse-scale global climate models. But individual members from global multi-model ensembles often lead to contradicting answers, and the important question arises of which of the many global models to select for the downscaling work. The perhaps most obvious solution to downscale various models is usually too expensive. Numerous studies have shown that the performance of the multi-model mean of an ensemble is usually superior to that of any individual model. However, it is unclear how to employ the multi-model mean framework for regional downscaling. We propose a simple method that allows use of a multi-model mean for downscaling work. We demonstrate the performance of our method using the WRF regional model system coupled to CMIP5 output. The system is used to perform high-resolution climate change simulations over our prototypical study region of tropical South America. We use objective criteria to select three CMIP5 models that perform best in terms of simulating present day climate. The outcomes from using these three individual global models are contrasted against that from using the CMIP5 multi-model mean. We discuss the advantages and limitations of the new method, and conclude that it represents a promising and computationally inexpensive alternative to the traditional downscaling of individual models.

  14. Pacific Northwest Laboratory annual report for 1992 to the DOE Office of Energy Research. Part 3, Atmospheric and climate research

    SciTech Connect

    Schrempf, R.E.

    1993-04-01

    Within the US Department of Energy`s (DOE`s) Office of Health and Environmental Research (OHER), the atmospheric sciences and carbon dioxide research programs are part of the Environmental Sciences Division (ESD). One of the central missions of the division is to provide the DOE with scientifically defensible information on the local, regional, and global distributions of energy-related pollutants and their effects on climate. This information is vital to the definition and implementation of a sound national energy strategy. This volume reports on the progress and status of all OHER atmospheric science and climate research projects at the Pacific Northwest Laboratory (PNL). PNL has had a long history of technical leadership in the atmospheric sciences research programs within OHER. Within the ESD, the Atmospheric Chemistry Program (ACP) continues DOE`s long-term commitment to study the continental and oceanic fates of energy-related air pollutants. Research through direct measurement, numerical modeling, and laboratory studies in the ACP emphasizes the long-range transport, chemical transformation, and removal of emitted pollutants, oxidant species, nitrogen-reservoir species, and aerosols. The Atmospheric Studies in Complex Terrain (ASCOT) program continues to apply basic research on density-driven circulations and on turbulent mixing and dispersion in the atmospheric boundary layer to the micro- to mesoscale meteorological processes that affect air-surface exchange and to emergency preparedness at DOE and other facilities. Research at PNL provides basic scientific underpinnings to DOE`s program of global climate research. Research projects within the core carbon dioxide and ocean research programs are now integrated with those in the Atmospheric Radiation Measurements (ARM), the Computer Hardware, Advanced Mathematics and Model Physics (CHAMMP), and Quantitative Links programs to form DOE`s contribution to the US Global Change Research Program.

  15. Intercomparison of hydrologic processes in global climate models

    NASA Technical Reports Server (NTRS)

    Lau, W. K.-M.; Sud, Y. C.; Kim, J.-H.

    1995-01-01

    In this report, we address the intercomparison of precipitation (P), evaporation (E), and surface hydrologic forcing (P-E) for 23 Atmospheric Model Intercomparison Project (AMIP) general circulation models (GCM's) including relevant observations, over a variety of spatial and temporal scales. The intercomparison includes global and hemispheric means, latitudinal profiles, selected area means for the tropics and extratropics, ocean and land, respectively. In addition, we have computed anomaly pattern correlations among models and observations for different seasons, harmonic analysis for annual and semiannual cycles, and rain-rate frequency distribution. We also compare the joint influence of temperature and precipitation on local climate using the Koeppen climate classification scheme.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Quantitative Study of the Present-Day Climate of the Middle Tennessee Elk Watershed Area From Global and Regional Climate Model Simulations

    NASA Astrophysics Data System (ADS)

    Kebede, G.

    2015-12-01

    As part of a wider hydro climatic modeling research, we studied the spatial and temporal variability of precipitation and temperature over the Middle Tennessee Elk watershed and its environs using regional climate model simulations over the past 30 years. Three sets of simulations with the Hadley Center's regional climate model (PRECIS) were carried out for the present day climate (1980-2010) at a resolution of 25km covering the southeastern U.S. These three sets simulations are driven by lateral boundary conditions taken from ERA-Interim reanalysis, and two global climate models (HadCM3 and ECHAM5) respectively. For validation, high resolution observed daily data sets from North American Land-Data Assimilation System (NLDAS) and Climate Research Unit, CRU data are used. Preliminary results show that the spatial distribution of the present-day seasonal mean rainfall and temperature, simulated by PRECIS, are not only consistent with NLDAS and CRU but also captured fine scale spatial structures that are missing in the global model simulations due to their coarse resolution. In addition, the annual cycle and intera-anual variability, particularly that of temperature, are reasonably well reproduced by the PRECIS. When comparing the PRECIS simulations with the driving GCMs, PRECIS is sensitive to the choice of the driving GCM, suggesting a careful selection of driving GCM based on the current climate performance for the use of future climate impact assessment. Quantitative understanding of the climate system and better estimation of the fresh water balance over the Middle Tennessee Elk watershed is a vital corner stone for a sustainable economic growth of the region over the coming decades.

  2. 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…

  3. 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…

  4. 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...

  5. Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

    NASA Astrophysics Data System (ADS)

    Smith, B.

    2015-12-01

    In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs

  6. 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.

  7. 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.

  8. Subsea Permafrost Climate Modeling - Challenges and First Results

    NASA Astrophysics Data System (ADS)

    Rodehacke, C. B.; Stendel, M.; Marchenko, S. S.; Christensen, J. H.; Romanovsky, V. E.; Nicolsky, D.

    2015-12-01

    Recent observations indicate that the East Siberian Arctic Shelf (ESAS) releases methane, which stems from shallow hydrate seabed reservoirs. The total amount of carbon within the ESAS is so large that release of only a small fraction, for example via taliks, which are columns of unfrozen sediment within the permafrost, could impact distinctly the global climate. Therefore it is crucial to simulate the future fate of ESAS' subsea permafrost with regard to changing atmospheric and oceanic conditions. However only very few attempts to address the vulnerability of subsea permafrost have been made, instead most studies have focused on the evolution of permafrost since the Late Pleistocene ocean transgression, approximately 14000 years ago.In contrast to land permafrost modeling, any attempt to model the future fate of subsea permafrost needs to consider several additional factors, in particular the dependence of freezing temperature on water depth and salt content and the differences in ground heat flux depending on the seabed properties. Also the amount of unfrozen water in the sediment needs to be taken into account. Using a system of coupled ocean, atmosphere and permafrost models will allow us to capture the complexity of the different parts of the system and evaluate the relative importance of different processes. Here we present the first results of a novel approach by means of dedicated permafrost model simulations. These have been driven by conditions of the Laptev Sea region in East Siberia. By exploiting the ensemble approach, we will show how uncertainties in boundary conditions and applied forcing scenarios control the future fate of the sub sea permafrost.

  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. 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.

  11. Climate science: Unexpected fix for ocean models

    NASA Astrophysics Data System (ADS)

    Kelly, Kathryn A.; Thompson, Luanne

    2016-07-01

    Computational models persistently underestimate strong currents that redistribute ocean heat. This problem is solved in models in which ocean eddies are damped by coupling of the atmosphere with the sea. See Letter p.533

  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. A new generation of the regional climate model REMO: REMO non-hydrostatic

    NASA Astrophysics Data System (ADS)

    Sieck, Kevin; Raub, Thomas; Marien, Lennart; Buntemeyer, Lars; Jacob, Daniela

    2016-04-01

    The regional climate model REMO is well established and has proofed it's value in regional climate simulations for more than a decade. However, due to the hydrostatic formulation REMO is not able to produce useful regional climate information on scales smaller than ~10 km. The demand for higher resolution data especially in the climate service sector is evident. Often climate change information on urban district or even point level is needed. A previous development of a non-hydrostatic dynamical core for REMO utilizing ideas of Miller and Pearce (1974) and Janjic (2001) has been picked up and implemented into the latest hydrostatic REMO version. One of the advantages of the Janjic formulation is that hydrostatic and non-hydrostatic computations are well separated. This offers a straightforward implementation of the non-hydrostatic calculations into an existing hydrostatic model. Other advantages are the easy quantification of the error done by the hydrostatic approximation and the lower computational costs at lower resolutions by switching of the non-hydrostatic part. We will show results from climate simulations on the EURO-CORDEX domain with and without non-hydrostatic option.

  14. Dependence of warm and cold climate depiction on climate model resolution

    NASA Technical Reports Server (NTRS)

    Rind, David

    1988-01-01

    Climate change simulations run with two different resolutions (8 deg by 10 deg and 4 deg by 5 deg) of the NASA Goddard Institute for Space Studies model are used to investigate radiative, dynamical, and regional sensitivities to model grid size. The results show that model resolution affected two key processes in the control runs, moist convection and the nonlinear transfer of kinetic energy into the zonal mean flow. It was found that the finer resolution model has more penetrative convection but less convection overall, with the results that its temperature and wind structure were altered with respect to the coarser grid model.

  15. 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.

  16. 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. PMID:23808659

  17. Improvement and Application of Atmospheric Radiative Transfer Models for Prediction of the Climatic Effects of Aerosol

    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.

  18. Improvement and Application of Atmospheric Radiative Transfer Models for Prediction of the Climatic Effects of Aerosol

    NASA Technical Reports Server (NTRS)

    Bergstrom, Robert W.

    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.

  19. Complex networks for climate model evaluation with application to statistical versus dynamical modeling of South American climate

    NASA Astrophysics Data System (ADS)

    Feldhoff, Jan H.; Lange, Stefan; Volkholz, Jan; Donges, Jonathan F.; Kurths, Jürgen; Gerstengarbe, Friedrich-Wilhelm

    2015-03-01

    In this study we introduce two new node-weighted difference measures on complex networks as a tool for climate model evaluation. The approach facilitates the quantification of a model's ability to reproduce the spatial covariability structure of climatological time series. We apply our methodology to compare the performance of a statistical and a dynamical regional climate model simulating the South American climate, as represented by the variables 2 m temperature, precipitation, sea level pressure, and geopotential height field at 500 hPa. For each variable, networks are constructed from the model outputs and evaluated against a reference network, derived from the ERA-Interim reanalysis, which also drives the models. We compare two network characteristics, the (linear) adjacency structure and the (nonlinear) clustering structure, and relate our findings to conventional methods of model evaluation. To set a benchmark, we construct different types of random networks and compare them alongside the climate model networks. Our main findings are: (1) The linear network structure is better reproduced by the statistical model statistical analogue resampling scheme (STARS) in summer and winter for all variables except the geopotential height field, where the dynamical model CCLM prevails. (2) For the nonlinear comparison, the seasonal differences are more pronounced and CCLM performs almost as well as STARS in summer (except for sea level pressure), while STARS performs better in winter for all variables.

  20. 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.

  1. 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.

  2. The development of climate models: tuning vs. flux corrections

    NASA Astrophysics Data System (ADS)

    Dommenget, Dietmar

    2016-04-01

    Current state-of-the-art coupled general circulation models (CGCMs) have substantial errors in their main climate representations. In particular they have large uncertainties in the simulated climate sensitivity on regional and global scale to a doubling of CO2 that result from model errors. The current approach in developing CGCMs and dealing with the error in it involves substantial amount of tuning of uncertain parameters of sub-scale process that need to be parameterized. This tuning process is neither documented, nor reproducible nor is it clear if it indeed improves the model performance. Alternative methods such as flux correcting are not used nor is it clear if such methods would perform better. In the study presented here we will perform perturbed physics experiments with the simplified globally resolved energy balance (GREB) model to test the different ideas of dealing with model errors in the development of models. It will be illustrated that tuning of CGCM is very likely to fail given the complexity of the system, the limited resources and the limited observations to optimize parameters. While tuning will improve the models performance on the cost function (such as the observed past climate), it will not get closer to the 'true' physics nor will it improve future climate change projection. In turn, not tuning or flux correcting is not only much cheaper and simpler, but it will actually perform better in nearly all aspects. This, however, varies whether one is focussed on regional or global scales.

  3. Continental-scale convection-permitting modeling of the current and future climate of North America

    NASA Astrophysics Data System (ADS)

    Liu, Changhai; Ikeda, Kyoko; Rasmussen, Roy; Barlage, Mike; Newman, Andrew J.; Prein, Andreas F.; Chen, Fei; Chen, Liang; Clark, Martyn; Dai, Aiguo; Dudhia, Jimy; Eidhammer, Trude; Gochis, David; Gutmann, Ethan; Kurkute, Sopan; Li, Yanping; Thompson, Gregory; Yates, David

    2016-08-01

    Orographic precipitation and snowpack provide a vital water resource for the western U.S., while convective precipitation accounts for a significant part of annual precipitation in the eastern U.S. As a result, water managers are keenly interested in their fate under climate change. However, previous studies of water cycle changes in the U.S. have been conducted with climate models of relatively coarse resolution, leading to potential misrepresentation of key physical processes. This paper presents results from a high-resolution climate change simulation that permits convection and resolves mesoscale orography at 4-km grid spacing over much of North America using the Weather Research and Forecasting (WRF) model. Two 13-year simulations were performed, consisting of a retrospective simulation (October 2000-September 2013) with initial and boundary conditions from ERA-interim and a future climate sensitivity simulation with modified reanalysis-derived initial and boundary conditions through adding the CMIP5 ensemble-mean high-end emission scenario climate change. The retrospective simulation is evaluated by validating against Snowpack Telemetry (SNOTEL) and an ensemble of gridded observational datasets. It shows overall good performance capturing the annual/seasonal/sub-seasonal precipitation and surface temperature climatology except for a summer dry and warm bias in the central U.S. In particular, the WRF seasonal precipitation agrees with SNOTEL observations within a few percent over the mountain ranges, providing confidence in the model's estimation of western U.S. seasonal snowfall and snowpack. The future climate simulation forced with warmer and moister perturbed boundary conditions enhances annual and winter-spring-fall seasonal precipitation over most of the contiguous United States (CONUS), but suppresses summertime precipitation in the central U.S. The WRF-downscaled climate change simulations provide a high-resolution dataset (i.e., High-Resolution CONUS

  4. 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

  5. The effects of climate model similarity on probabilistic climate projections and the implications for local, risk-based adaptation planning

    NASA Astrophysics Data System (ADS)

    Steinschneider, Scott; McCrary, Rachel; Mearns, Linda O.; Brown, Casey

    2015-06-01

    Approaches for probability density function (pdf) development of future climate often assume that different climate models provide independent information, despite model similarities that stem from a common genealogy (models with shared code or developed at the same institution). Here we use an ensemble of projections from the Coupled Model Intercomparison Project Phase 5 to develop probabilistic climate information, with and without an accounting of intermodel correlations, for seven regions across the United States. We then use the pdfs to estimate midcentury climate-related risks to a water utility in one of the regions. We show that the variance of climate changes is underestimated across all regions if model correlations are ignored, and in some cases, the mean change shifts as well. When coupled with impact models of the hydrology and infrastructure of a water utility, the underestimated likelihood of large climate changes significantly alters the quantification of risk for water shortages by midcentury.

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

    PubMed

    Vučetić, V

    2011-04-01

    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 CO(2) 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 CO(2) 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 suggested that

  7. 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

  8. Future climate o