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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. Climate Change Impacts for Conterminous USA: An Integrated Assessment Part 2. Models and Validation

    SciTech Connect

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

    2005-03-01

    As CO{sub 2} and other greenhouse gases 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 predictions from General Circulation Models (GCMs) as described in Part 1. Here we describe the agriculture model EPIC and the HUMUS water model and validate them with historical crop yields and streamflow data. We compare EPIC simulated grain and forage crop yields with historical crop yields from the US Department of Agriculture and find an acceptable level of agreement for this study. The validation of HUMUS simulated streamflow with estimates of natural streamflow from the US Geological Survey shows that the model is able to reproduce significant relationships and capture major trends.

  4. AUTH Regional Climate Model Contributions to EURO-CORDEX. Part II

    NASA Technical Reports Server (NTRS)

    Katragkou, E.; Gkotovou, I.; Kartsios, S.; Pavlidis, V.; Tsigaridis, K.; Trail, M.; Nazarenko, L.; Karacostas, Theodore S.

    2017-01-01

    Regional climate downscaling techniques are being increasingly used to provide higher-resolution climate information than is available directly from contemporary global climate models. The Coordinated Regional Climate Downscaling Experiment (CORDEX) initiative was build to foster communication and knowledge exchange between regional climate modelers. The Department of Meteorology and Climatology of the Aristotle University of Thessaloniki has been contributing to the CORDEX initiative since 2010, with regional climate model simulations over the European domain (EURO-CORDEX). Results of this work are presented here, including two hindcasts and a historical simulation with the Weather Research Forecasting model (WRF), driven by ERA-interim reanalysis and the NASA Earth System Goddard Institute for Space Studies (GISS) ModelE2, respectively. Model simulations are evaluated with the EOBS climatology and the model performance is assessed.

  5. Mid-Holocene and last glacial maximum climate simulations with the IPSL model: part II: model-data comparisons

    NASA Astrophysics Data System (ADS)

    Kageyama, Masa; Braconnot, Pascale; Bopp, Laurent; Mariotti, Véronique; Roy, Tilla; Woillez, Marie-Noëlle; Caubel, Arnaud; Foujols, Marie-Alice; Guilyardi, Eric; Khodri, Myriam; Lloyd, James; Lombard, Fabien; Marti, Olivier

    2013-05-01

    The climates of the mid-Holocene (MH, 6,000 years ago) and the Last Glacial Maximum (LGM, 21,000 years ago) have been extensively documented and as such, have become targets for the evaluation of climate models for climate contexts very different from the present. In Part 1 of the present work, we have studied the MH and LGM simulations performed with the last two versions of the IPSL model: IPSL_CM4, run for the PMIP2/CMIP3 (Coupled Model Intercomparion Project) projects and IPSL_CM5A, run for the most recent PMIP3/CMIP5 projets. We have shown that not only are these models different in their simulations of the PI climate, but also in their simulations of the climatic anomalies for the MH and LGM. In the Part 2 of this paper, we first examine whether palaeo-data can help discriminate between the model performances. This is indeed the case for the African monsoon for the MH or for North America south of the Laurentide ice sheet, the South Atlantic or the southern Indian ocean for the LGM. For the LGM, off-line vegetation modelling appears to offer good opportunities to distinguish climate model results because glacial vegetation proves to be very sensitive to even small differences in LGM climate. For other cases such as the LGM North Atlantic or the LGM equatorial Pacific, the large uncertainty on the SST reconstructions, prevents model discrimination. We have examined the use of other proxy-data for model evaluation, which has become possible with the inclusion of the biogeochemistry morel PISCES in the IPSL_CM5A model. We show a broad agreement of the LGM-PI export production changes with reconstructions. These changes are related to the mixed layer depth in most regions and to sea-ice variations in the high latitudes. We have also modelled foraminifer abundances with the FORAMCLIM model and shown that the changes in foraminifer abundance in the equatorial Pacific are mainly forced by changes in SSTs, hence confirming the SST-foraminifer abundance relationship

  6. IIASA`s climate-vegetation-biogeochemical cycle module as a part of an integrated model for climate change

    SciTech Connect

    Ganopolski, A.V.; Jonas, M.; Krabec, J.; Olendrzynski, K.; Petoukhov, V.K.; Venevsky, S.V.

    1994-12-31

    The main objective of this study is the development of a hierarchy of coupled climate biosphere models with a full description of the global biogeochemical cycles. These models are planned for use as the core of a set of integrated models of climate change and they will incorporate the main elements of the Earth system (atmosphere, hydrosphere, pedosphere and biosphere) linked with each other (and eventually with the antroposphere) through the fluxes of heat, momentum, water and through the global biogeochemical cycles of carbon and nitrogen. This set of integrated models can be considered to fill the gap between highly simplified integrated models of climate change and very sophisticated and computationally expensive coupled models, developed on the basis of general circulation models (GCMs). It is anticipated that this range of integrated models will be an effective tool for investigating the broad spectrum of problems connected with the coexistence of human society and biosphere.

  7. The GISS Global Climate-Middle Atmosphere Model. Part I: Model Structure and Climatology.

    NASA Astrophysics Data System (ADS)

    Rind, D.; Suozzo, R.; Balachandran, N. K.; Lacis, A.; Russell, G.

    1988-02-01

    The GISS global climate model (Hansen et al.) has been extended to include the middle atmosphere up to an altitude of approximately 85 km. The model has the full array of processes used for climate research, i.e., numerical solutions of the primitive equations, calculation of radiative and surface fluxes, a complete hydrologic cycle with convective and cloud cover parameterizations, etc. In addition, a parameterized gravity wave drag formulation has been incorporated, in which gravity-wave momentum fluxes due to flow over topography, wind shear and convection are calculated at each grid box, using theoretical relationships between the grid-scale variables and expected source strengths. The parameterized waves then propagate vertically upward depending on the instantaneous wind and temperature profiles, with waves breaking at levels in which their momentum flux exceed the background saturation value. Radiative damping is also calculated, and the total momentum convergence in each layer is used to alter the local wind, while the kinetic energy dissipation warms the temperature. Thus the generation, propagation, breaking and drag are all a function of the calculated variables at each grid box for the various vertical levels.The model has been run for five years, and the results compared with observations. The model produces generally realistic fields of temperature and wind throughout the atmosphere up to approximately 75 km. Important aspects of the current simulation include a proper break between the tropospheric and stratospheric jets, realistic closing off of the wintertime jet in the mesosphere, the observed warm winter/cold summer mesosphere, and a semiannual wind oscillation near the stratopause. The most obvious deficiencies are that the long-wave energy itself is somewhat too small in the low and midstratosphere, temperatures are too cold near the model top and are too warm in the polar Southern Hemisphere lower stratosphere during winter. Also, the model

  8. A dynamic, embedded Lagrangian model for ocean climate models, Part II: Idealised overflow tests

    NASA Astrophysics Data System (ADS)

    Bates, Michael L.; Griffies, Stephen M.; England, Matthew H.

    2012-12-01

    Dense gravity current overflows occur in several regions throughout the world and are an important process in the meridional overturning circulation. Overflows are poorly represented in coarse resolution level coordinate ocean climate models. Here, the embedded Lagrangian model formulated in the companion paper of Bates et al. (2012) is used in two idealised test cases to examine the effect on the representation of dense gravity driven plumes, as well as the effect on the circulation of the bulk ocean in the Eulerian model. The results are compared with simulations with no parameterisation for overflows, as well as simulations that use traditional hydrostatic overflow schemes. The use of Lagrangian "blobs" is shown to improve three key characteristics that are poorly represented in coarse resolution level coordinate models: (1) the depth of the plume, (2) the along slope velocity of the plume, and (3) the response of the bulk ocean to the bottom boundary layer. These improvements are associated with the more appropriate set of dynamics satisfied by the blobs, leading to a more physically sound representation. Experiments are also conducted to examine sensitivity to blob parameters. The blob parameters are examined over a large parameter space.

  9. 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.

  10. Potential climate effect of mineral aerosols over West Africa. Part I: model validation and contemporary climate evaluation

    NASA Astrophysics Data System (ADS)

    Ji, Zhenming; Wang, Guiling; Pal, Jeremy S.; Yu, Miao

    2016-02-01

    Mineral dusts present in the atmosphere can play an important role in climate over West Africa and surrounding regions. However, current understanding regarding how dust aerosols influence climate of West Africa is very limited. In this study, a regional climate model is used to investigate the potential climatic impacts of dust aerosols. Two sets of simulations driven by reanalysis and Earth System Model boundary conditions are performed with and without the representation of dust processes. The model, regardless of the boundary forcing, captures the spatial and temporal variability of the aerosol optical depth and surface concentration. The shortwave radiative forcing of dust is negative at the surface and positive in the atmosphere, with greater changes in the spring and summer. The presence of mineral dusts causes surface cooling and lower troposphere heating, resulting in a stabilization effect and reduction in precipitation in the northern portion of the monsoon close to the dust emissions region. This results in an enhancement of precipitation to the south. While dusts cause the lower troposphere to stabilize, upper tropospheric cooling makes the region more prone to intense deep convection as is evident by a simulated increase in extreme precipitation. In a companion paper, the impacts of dust emissions on future West African climate are investigated.

  11. 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.

  12. Advances in geophysics. Volume 28 - issues in atmospheric and oceanic modeling. Part A - climate dynamics

    SciTech Connect

    Manabe, S.

    1985-01-01

    Papers are presented on large-scale eddies and the general circulation of the troposphere; the role of barotropic energy conversions in the general circulation; balance conditions in the earth's climate system, climate sensitivity; CO2 and hydrology; modeling of paleoclimates; and the southern oscillation and El Nino. Topics treated include the stratospheric dynamics of the middle atmosphere, wave-mean-flow interaction in the middle atmosphere, radiative-dynamical interactions in the middle atmosphere, and a mechanistic interpretation of stratospheric tracer transport. Consideration is given to the general circulation of Venus, and Jovian and comparative atmospheric modeling. Also discussed are the modeling of ocean circulation, tropical oceanography, the simulation of mesoscale ocean variability in midlatitude gyres, modeling circulation and mixing in estuaries and coastal oceans, and the modeling of sea-ice dynamics.

  13. 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

  14. 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

  15. Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

    NASA Astrophysics Data System (ADS)

    Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

    2017-02-01

    A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is

  16. The land surface scheme ISBA within the Meteo-France climate model arpege. Part I: Implementation and preliminary results

    SciTech Connect

    Mahfouf, J.F.; Noilhan, J.; Manzi, A.O.

    1995-08-01

    This paper describes recent developments in climate modeling at Meteo-France related to land surface processes. The implementation of a simple land surface parameterization, Interactions between Soil Biosphere Atmosphere (ISBA), has gained from previous validations and calibrations at local scale against field datasets and from aggregation procedures devised to define effective land surface properties. Specific improvements from climate purposes are introduced; spatial variability of convective rainfall in canopy drainage estimation and subsurface gravitational percolation. The methodology used to derive climatological maps of land surface parameters at the grid-scale resolution of the model from existing databases for soil and vegetation types at global scale is described. A 3-yr integration for the present day climate with a T42L30 version of the climate model has been performed. Results obtained compare favorably with available observed climatologies related to the various components of the continental surface energy and water budgets. Differences are due mostly to a poor simulation of the precipitation field. However, some difference suggest specific improvements in the surface scheme concerning representation of the bare soil albedo, the surface runoff, and the soil moisture initialization. As a first step prior to tropical deforestation experiments presented to Part II, regional analyses over the Amazon forest indicate that the modeled evaporation and net radiation are in good agreement with data collected during the Amazon Region Micrometeorological Experiment campaign. 77 refs., 11 figs., 8 tabs.

  17. 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

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

    PubMed

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

    2009-01-01

    Previous assessments of the impacts of climate change on heat-related mortality use the "delta method" to create temperature projection time series that are applied to temperature-mortality models to estimate future mortality impacts. The delta method means that climate model bias in the modelled present does not influence the temperature projection time series and impacts. However, the delta method assumes that climate change will result only in a change in the mean temperature but there is evidence that there will also be changes in the variability of temperature with climate change. The aim of this paper is to demonstrate the importance of considering changes in temperature variability with climate change in impacts assessments of future heat-related mortality. We investigate future heat-related mortality impacts in six cities (Boston, Budapest, Dallas, Lisbon, London and Sydney) by applying temperature projections from the UK Meteorological Office HadCM3 climate model to the temperature-mortality models constructed and validated in Part 1. We investigate the impacts for four cases based on various combinations of mean and variability changes in temperature with climate change. The results demonstrate that higher mortality is attributed to increases in the mean and variability of temperature with climate change rather than with the change in mean temperature alone. This has implications for interpreting existing impacts estimates that have used the delta method. We present a novel method for the creation of temperature projection time series that includes changes in the mean and variability of temperature with climate change and is not influenced by climate model bias in the modelled present. The method should be useful for future impacts assessments. Few studies consider the implications that the limitations of the climate model may have on the heat-related mortality impacts. Here, we demonstrate the importance of considering this by conducting an evaluation of

  19. 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

  20. The greening of the McGill Paleoclimate Model. Part II: Simulation of Holocene millennial-scale natural climate changes

    NASA Astrophysics Data System (ADS)

    Wang, Yi; Mysak, Lawrence A.; Wang, Zhaomin; Brovkin, Victor

    2005-04-01

    Various proxy data reveal that in many regions of the Northern Hemisphere (NH), the middle Holocene (6 kyr BP) was warmer than the early Holocene (8 kyr BP) as well as the later Holocene, up to the end of the pre-industrial period (1800 AD). This pattern of warming and then cooling in the NH represents the response of the climate system to changes in orbital forcing, vegetation cover and the Laurentide Ice Sheet (LIS) during the Holocene. In an attempt to better understand these changes in the climate system, the McGill Paleoclimate Model (MPM) has been coupled to the dynamic global vegetation model known as VECODE (see Part I of this two-part paper), and a number of sensitivity experiments have been performed with the "green" MPM. The model results illustrate the following: (1) the orbital forcing together with the vegetation—albedo feedback result in the gradual cooling of global SAT from about 6 kyr BP to the end of the pre-industrial period; (2) the disappearance of the LIS over the period 8-6 kyr BP, associated with vegetation—albedo feedback, allows the global SAT to increase and reach its maximum at around 6 kyr BP; (3) the northern limit of the boreal forest moves northward during the period 8-6.4 kyr BP due to the LIS retreat; (4) during the period 6.4-0 kyr BP, the northern limit of the boreal forest moves southward about 120 km in response to the decreasing summer insolation in the NH; and (5) the desertification of northern Africa during the period 8-2.6 kyr BP is mainly explained by the decreasing summer monsoon precipitation.

  1. 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.

  2. 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

  3. The Greening of the McGill Paleoclimate Model. Part II: Simulation of Holocene Millennial-Scale Natural Climate Variability

    NASA Astrophysics Data System (ADS)

    Mysak, L. A.; Wang, Y.; Wang, Z.; Brovkin, V.

    2003-12-01

    Multiple proxy data reveal that the middle Holocene (6 kyr BP) was warmer than the early Holocene (8 kyr BP) as well as the preindustrial period (1700 AD) in most regions of the Northern Hemisphere. This warmth is somewhat counterintuitive because the summer insolation was decreasing during this time. Cooling in the late Holocene (after 6 kyr BP) is hypothesized to be due mainly to the astronomical forcing. This cooling was also accompanied by significant changes in vegetation cover (i.e., treeline retreat from northern high latitudes; the desertification of the Sahara/Sahel region) and a small but gradual increase of atmospheric CO2 concentration (from 260 ppm to 280 ppm). The early-to-middle Holocene warming, on the other hand, is hypothesized to be due in part to ice-albedo feedback in Northern America, associated with decreases in the Laurentide ice sheet, which completely disappeared by 6 kyr BP. The snow-vegetation-albedo feedback is also hypothesized to have played a role in this early warming event. To test the above hypotheses, the earlier geophysical McGill Paleoclimate Model has been coupled to the vegetation model known as VECODE (VEgetation COntinuous DEscription, one of the simpler dynamic global vegetation models), and a number of sensitivity experiments have been performed. The model results illustrate the role that Northern Hemisphere land cover changes played in explaining the natural millennial-scale climate variability from the early Holocene (8 kyr BP) to the preindustrial period (1700 AD).

  4. Assessment of climate change impact on water resources in the South-East part of Romania, using different spatial resolution atmospheric model output

    NASA Astrophysics Data System (ADS)

    Mic, Rodica Paula; Corbus, Ciprian; Neculau, Gianina

    2010-05-01

    change on hydrological regime was performed using the simulations with a regional climate model with 25 km grid spacing developed by the ICTP (Trieste, Italy) and interpolated at a resolution of approx. 11 km. Potential monthly and annual flow modification was assess for two time horizon 2021-2050 and 2071-2100. The third part of the study used as input data the results of regional climatic model with 10 km resolution and assesses the impact of climate change in water resources also for the two periods 2021-2050 and 2071-2100.

  5. 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.

  6. Multi-decadal scenario simulation over Korea using a one-way double-nested regional climate model system. Part 2: future climate projection (2021 2050)

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

    An analysis of simulated future surface climate change over the southern half of Korean Peninsula using a RegCM3-based high-resolution one-way double-nested system is presented. Changes in mean climate as well as the frequency and intensity of extreme climate events are discussed for the 30-year-period of 2021 2050 with respect to the reference period of 1971 2000 based on the IPCC SRES B2 emission scenario. Warming in the range of 1 4°C is found throughout the analysis region and in all seasons. The warming is maximum in the higher latitudes of the South Korean Peninsula and in the cold season. A large reduction in snow depth is projected in response to the increase of winter minimum temperature induced by the greenhouse warming. The change in precipitation shows a distinct seasonal variation and a substantial regional variability. In particular, we find a large increase of wintertime precipitation over Korea, especially in the upslope side of major mountain systems. Summer precipitation increases over the northern part of South Korea and decreases over the southern regions, indicating regional diversity. The precipitation change also shows marked intraseasonal variations throughout the monsoon season. The temperature change shows a positive trend throughout 2021 2050 while the precipitation change is characterized by pronounced interdecadal variations. The PDF of the daily temperature is shifted towards higher values and is somewhat narrower in the scenario run than the reference one. The number of frost days decreases markedly and the number of hot days increases. The regional distribution of heavy precipitation (over 80 mm/day) changes considerably, indicating changes in flood vulnerable regions. The climate change signal shows pronounced fine scale signal over Korea, indicating the need of high-resolution climate simulations

  7. Climate models and model evaluation

    SciTech Connect

    Gates, W.L.

    1994-12-31

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

  8. 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.

  9. 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.

  10. 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.

  11. Multi-year simulations and experimental seasonal predictions for rainy seasons in China by using a nested regional climate model (RegCM_NCC). Part I: Sensitivity study

    NASA Astrophysics Data System (ADS)

    Ding, Yihui; Shi, Xueli; Liu, Yiming; Liu, Yan; Li, Qingquan; Qian, Yongfu; Miao, Manqian; Zhai, Guoqing; Gao, Kun

    2006-05-01

    A modified version of the NCAR/RegCM2 has been developed at the National Climate Center (NCC), China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP (Institute of Atmospheric Physics) T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year (2001 to 2004) prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process parameterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme (MFS) and Betts-Miller scheme (BM) for convective precipitation, the LPMI (land surface process model I) and LPMII (land surface process model II) for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE (turbulent kinetic energy) scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 (RegCM_NCC) has been set up for climate simulations and seasonal predictions.

  12. 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…

  13. An empirical model of global climate - Part 1: Reduced impact of volcanoes upon consideration of ocean circulation

    NASA Astrophysics Data System (ADS)

    Canty, T.; Mascioli, N. R.; Smarte, M.; Salawitch, R. J.

    2012-09-01

    Observed reductions in Earth's surface temperature following explosive volcanic eruptions have been used as a proxy for geo-engineering of climate by the artificial enhancement of stratospheric sulfate. Earth cools following major eruptions due to an increase in the reflection of sunlight caused by a dramatic enhancement of the stratospheric sulfate aerosol burden. Significant global cooling has been observed following the four major eruptions since 1900: Santa María, Mount Agung, El Chichón, and Mount Pinatubo, leading IPCC (2007) to state "major volcanic eruptions can thus cause a drop in global mean surface temperature of about half a degree Celsius that can last for months and even years". We use a multiple linear regression model applied to the global surface temperature anomaly to suggest that exchange of heat between the atmosphere and ocean, driven by variations in the strength of the Atlantic Meridional Overturning Circulation (AMOC), has been a factor in the decline of global temperature following these eruptions. The veracity of this suggestion depends on whether the Atlantic Multidecadal Oscillation (AMO) truly represents a proxy for the strength of the AMOC and the precise quantification of global cooling due to volcanoes depends on how the AMO is detrended. If the AMO is detrended using anthropogenic radiative forcing of climate, we find that surface cooling attributed to Mount Pinatubo, using the Hadley Centre/University of East Anglia surface temperature record, maximizes at 0.15 °C globally and 0.35 °C over land. These values are about a factor of 2 less than found when the AMO is neglected in the model and quite a bit lower than the canonical 0.5 °C cooling usually attributed to Pinatubo. The AMO had begun to decrease prior to the four major eruptions, suggesting that exchange of heat between the atmosphere and ocean due to variations in the strength of the AMOC drives the climate system, rather than responds to volcanic perturbations. The

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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…

  19. 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.

  20. 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.

  1. 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.

  2. 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.…

  3. 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.

  4. A new building energy model coupled with an urban canopy parameterization for urban climate simulations—part I. formulation, verification, and sensitivity analysis of the model

    NASA Astrophysics Data System (ADS)

    Salamanca, Francisco; Krpo, Andrea; Martilli, Alberto; Clappier, Alain

    2009-05-01

    The generation of heat in buildings, and the way this heat is exchanged with the exterior, plays an important role in urban climate. To analyze the impact on urban climate of a change in the urban structure, it is necessary to build and use a model capable of accounting for all the urban heat fluxes. In this contribution, a new building energy model (BEM) is developed and implemented in an urban canopy parameterization (UCP) for mesoscale models. The new model accounts for: the diffusion of heat through walls, roofs, and floors; natural ventilation; the radiation exchanged between indoor surfaces; the generation of heat due to occupants and equipments; and the consumption of energy due to air conditioning systems. The behavior of BEM is compared to other models used in the thermal analysis of buildings (CBS-MASS, BLAST, and TARP) and with another box-building model. Eventually, a sensitivity analysis of different parameters, as well as a study of the impact of BEM on the UCP is carried out. The validations indicate that BEM provides good estimates of the physical behavior of buildings and it is a step towards a modeling tool that can be an important support to urban planners.

  5. Climate Model Output Rewriter

    SciTech Connect

    Taylor, K. E.; Doutriaux, C.

    2004-06-21

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

  6. 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

  7. Climate Modeling and Prediction at NSIPP

    NASA Technical Reports Server (NTRS)

    Suarez, Max; Einaudi, Franco (Technical Monitor)

    2001-01-01

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

  8. A non-oscillatory balanced scheme for an idealized tropical climate model. Part II: Nonlinear coupling and moisture effects

    NASA Astrophysics Data System (ADS)

    Khouider, Boualem; Majda, Andrew J.

    2005-10-01

    We use the non-oscillatory balanced numerical scheme developed in Part I to track the dynamics of a dry highly nonlinear barotropic/baroclinic coupled solitary wave, as introduced by Biello and Majda (2004), and of the moisture fronts of Frierson et al. (2004) in the presence of dry gravity waves, a barotropic trade wind, and the beta effect. It is demonstrated that, for the barotropic/baroclinic solitary wave, except for a little numerical dissipation, the scheme utilized here preserves total energy despite the strong interactions and exchange of energy between the baroclinic and barotropic components of the flow. After a short transient period where the numerical solution stays close to the asymptotic predictions, the flow develops small scale eddies and ultimately becomes highly turbulent. It is found here that the interaction of a dry gravity wave with a moisture front can either result in a reflection of a fast moistening front or the pure extinction of the precipitation. The barotropic trade wind stretches the precipitation patches and increases the lifetime of the moisture fronts which decay naturally by the effects of dissipation through precipitation while the Coriolis effect makes the moving precipitation patches disappear and appear at other times and places.

  9. 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

  10. 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.

  11. Effects of excessive equatorial cold tongue bias on the projections of tropical Pacific climate change. Part I: the warming pattern in CMIP5 multi-model ensemble

    NASA Astrophysics Data System (ADS)

    Li, Gen; Xie, Shang-Ping; Du, Yan; Luo, Yiyong

    2016-12-01

    The excessive cold tongue error in the equatorial Pacific has persisted in several generations of climate models. Based on the historical simulations and Representative Concentration Pathway (RCP) 8.5 experiments in the Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model ensemble (MME), this study finds that models with an excessive westward extension of cold tongue and insufficient equatorial western Pacific precipitation tend to project a weaker east-minus-west gradient of sea surface temperature (SST) warming along the equatorial Pacific under increased greenhouse gas (GHG) forcing. This La Niña-like error of tropical Pacific SST warming is consistent with our understanding of negative SST-convective feedback over the western Pacific warm pool. Based on this relationship between the present simulations and future projections, the present study applies an "observational constraint" of equatorial western Pacific precipitation to calibrate the projections of tropical Pacific climate change. After the corrections, CMIP5 models robustly project an El Niño-like warming pattern, with a MME mean increase by a factor of 2.3 in east-minus-west gradient of equatorial Pacific SST warming and reduced inter-model uncertainty. Corrections in projected changes in tropical precipitation and atmospheric circulation are physically consistent. This study suggests that a realistic cold tongue simulation would lead to a more reliable tropical Pacific climate projection.

  12. Do regional climate models represent regional climate?

    NASA Astrophysics Data System (ADS)

    Maraun, Douglas; Widmann, Martin

    2014-05-01

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

  13. Climate Models: A New Babel?

    NASA Astrophysics Data System (ADS)

    Steinhaeuser, Karsten; Tsonis, Anastasios

    2013-04-01

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

  14. 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.

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

    SciTech Connect

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

    1995-03-01

    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.

  16. 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

  17. 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.

  18. 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 generally consistent with

  19. 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; ...

    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

  20. 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

  1. 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.

  2. "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.

  3. "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.

  4. Aggregate Models of Climate Change

    NASA Astrophysics Data System (ADS)

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

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

  5. Model confirmation in climate economics.

    PubMed

    Millner, Antony; McDermott, Thomas K J

    2016-08-02

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

  6. Model confirmation in climate economics

    PubMed Central

    Millner, Antony; McDermott, Thomas K. J.

    2016-01-01

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

  7. 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.

  8. 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.

  9. 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.

  10. Decadal application of WRF/chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 2: Current vs. future simulations

    NASA Astrophysics Data System (ADS)

    Yahya, Khairunnisa; Campbell, Patrick; Zhang, Yang

    2017-03-01

    Following a comprehensive model evaluation, this Part II paper presents projected changes in future (2046-2055) climate, air quality, and their interactions under the RCP4.5 and RCP8.5 scenarios using the Weather, Research and Forecasting model with Chemistry (WRF/Chem). In general, both WRF/Chem RCP4.5 and RCP8.5 simulations predict similar increases on average (∼2 °C) for 2-m temperature (T2) but different spatial distributions of the projected changes in T2, 2-m relative humidity, 10-m wind speed, precipitation, and planetary boundary layer height, due to differences in the spatial distributions of projected emissions, and their feedbacks into climate. Future O3 mixing ratios will decrease for most parts of the U.S. under the RCP4.5 scenario but increase for all areas under the RCP8.5 scenario due to higher projected temperature, greenhouse gas concentrations and biogenic volatile organic compounds (VOC) emissions, higher O3 values for boundary conditions, and disbenefit of NOx reduction and decreased NO titration over VOC-limited O3 chemistry regions. Future PM2.5 concentrations will decrease for both RCP4.5 and RCP8.5 scenarios with different trends in projected concentrations of individual PM species. Total cloud amounts decrease under both scenarios in the future due to decreases in PM and cloud droplet number concentration thus increased radiation. Those results illustrate the impacts of carbon policies with different degrees of emission reductions on future climate and air quality. The WRF/Chem and WRF simulations show different spatial patterns for projected changes in T2 for future decade, indicating different impacts of prognostic and prescribed gas/aerosol concentrations, respectively, on climate change.

  11. 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.

  12. Conceptual Model of Climate Change Impacts at LANL

    SciTech Connect

    Dewart, Jean Marie

    2016-05-17

    Goal 9 of the LANL FY15 Site Sustainability Plan (LANL 2014a) addresses Climate Change Adaptation. As part of Goal 9, the plan reviews many of the individual programs the Laboratory has initiated over the past 20 years to address climate change impacts to LANL (e.g. Wildland Fire Management Plan, Forest Management Plan, etc.). However, at that time, LANL did not yet have a comprehensive approach to climate change adaptation. To fill this gap, the FY15 Work Plan for the LANL Long Term Strategy for Environmental Stewardship and Sustainability (LANL 2015) included a goal of (1) establishing a comprehensive conceptual model of climate change impacts at LANL and (2) establishing specific climate change indices to measure climate change and impacts at Los Alamos. Establishing a conceptual model of climate change impacts will demonstrate that the Laboratory is addressing climate change impacts in a comprehensive manner. This paper fulfills the requirement of goal 1. The establishment of specific indices of climate change at Los Alamos (goal 2), will improve our ability to determine climate change vulnerabilities and assess risk. Future work will include prioritizing risks, evaluating options/technologies/costs, and where appropriate, taking actions. To develop a comprehensive conceptual model of climate change impacts, we selected the framework provided in the National Oceanic and Atmospheric Administration (NOAA) Climate Resilience Toolkit (http://toolkit.climate.gov/).

  13. Decadal application of WRF/Chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 1: Model evaluation and impact of downscaling

    NASA Astrophysics Data System (ADS)

    Yahya, Khairunnisa; Wang, Kai; Campbell, Patrick; Chen, Ying; Glotfelty, Timothy; He, Jian; Pirhalla, Michael; Zhang, Yang

    2017-03-01

    An advanced online-coupled meteorology-chemistry model, i.e., the Weather Research and Forecasting Model with Chemistry (WRF/Chem), is applied for current (2001-2010) and future (2046-2055) decades under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios to examine changes in future climate, air quality, and their interactions. In this Part I paper, a comprehensive model evaluation is carried out for current decade to assess the performance of WRF/Chem and WRF under both scenarios and the benefits of downscaling the North Carolina State University's (NCSU) version of the Community Earth System Model (CESM_NCSU) using WRF/Chem. The evaluation of WRF/Chem shows an overall good performance for most meteorological and chemical variables on a decadal scale. Temperature at 2-m is overpredicted by WRF (by ∼0.2-0.3 °C) but underpredicted by WRF/Chem (by ∼0.3-0.4 °C), due to higher radiation from WRF. Both WRF and WRF/Chem show large overpredictions for precipitation, indicating limitations in their microphysics or convective parameterizations. WRF/Chem with prognostic chemical concentrations, however, performs much better than WRF with prescribed chemical concentrations for radiation variables, illustrating the benefit of predicting gases and aerosols and representing their feedbacks into meteorology in WRF/Chem. WRF/Chem performs much better than CESM_NCSU for most surface meteorological variables and O3 hourly mixing ratios. In addition, WRF/Chem better captures observed temporal and spatial variations than CESM_NCSU. CESM_NCSU performance for radiation variables is comparable to or better than WRF/Chem performance because of the model tuning in CESM_NCSU that is routinely made in global models.

  14. 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.

  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. 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.

  17. Likelihood-Based Climate Model Evaluation

    NASA Technical Reports Server (NTRS)

    Braverman, Amy; Cressie, Noel; Teixeira, Joao

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Wielicki, B. A.

    2011-12-01

    Climate Model Predictions and Climate Observations: Where are we going? A climate model is the explicit expression of a scientific hypothesis on how the Earth's climate works. We test these models against a wide variety of climate observations: climatological mean global maps of many climate variables, seasonal cycles, inter-annual variability, decadal change, and even glacial/interglacial cycles. The most direct method of testing the accuracy of climate model decadal change predictions is to use decades of highly accurate data for radiative forcing and climate response. Relevant data for these tests include all of the key climate variables known to play a role in climate change. There are two primary advantages of this approach: a) it uses the most complete set of climate variables, and b) its directly tests decadal prediction against decadal observations. There are two disadvantages, however, of this direct approach: a) it takes decades to collect enough data to overcome natural variability, and b) the accuracy required for small decadal change signals is very high: much higher than typical weather or research observations. As a result, like paleo data, data accuracy becomes a critical issue. Despite the critical need for climate models to be tested against decadal change observations, we currently have no international designed and implemented climate observing system. There are no international commitments to create one (accuracy) or to maintain one (decades of observations). What is called the Global Climate Observing System is instead a set of documents about how weather and research observing systems might be improved to better provide a climate observing system. Given the importance of this challenge, this seems a strange condition. How did we get here? Is a rigorous climate observing system so expensive as to be unaffordable? Has the science community failed to clearly prioritize and define the requirements of such a system? Is the technology to create

  19. 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.

  20. Photoperiod cues and patterns of genetic variation limit phenological responses to climate change in warm parts of species' range: modeling diameter-growth cessation in coast Douglas-fir.

    PubMed

    Ford, Kevin R; Harrington, Constance A; St Clair, J Bradley

    2017-03-16

    The phenology of diameter-growth cessation in trees will likely play a key role in mediating species and ecosystem responses to climate change. A common expectation is that warming will delay cessation, but the environmental and genetic influences on this process are poorly understood. We modeled the effects of temperature, photoperiod and seed-source climate on diameter-growth cessation timing in coast Douglas-fir (an ecologically and economically vital tree) using high-frequency growth measurements across broad environmental gradients for a range of genotypes from different seed sources. Our model suggests that cool temperatures or short photoperiods can induce cessation in autumn. At cool locations (high latitude and elevation), cessation seems to be induced primarily by low temperatures in early autumn (under relatively long photoperiods), so warming will likely delay cessation and extend the growing season. But at warm locations (low latitude or elevation), cessation seems to be induced primarily by short photoperiods later in autumn, so warming will likely lead to only slight extensions of the growing season, reflecting photoperiod limitations on phenological shifts. Trees from seed sources experiencing frequent frosts in autumn or early winter tended to cease growth earlier in the autumn, potentially as an adaptation to avoid frost. Thus, gene flow into populations in warm locations with little frost will likely have limited potential to delay mean cessation dates because these populations already cease growth relatively late. In addition, data from an abnormal heat wave suggested that very high temperatures during long photoperiods in early summer might also induce cessation. Climate change could make these conditions more common in warm locations, leading to much earlier cessation. Thus, photoperiod cues, patterns of genetic variation and summer heat waves could limit the capacity of coast Douglas-fir to extend its growing season in response to climate

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  3. Uncertainty Quantification in Climate Modeling

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  4. 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.

  5. 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.

  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. Modeling climate related feedback processes

    SciTech Connect

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

    1993-11-01

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

  8. Climate Sensitivity and Solar Cycle Response in Climate Models

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  9. 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.

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

    NASA Astrophysics Data System (ADS)

    Dommenget, D.

    2014-12-01

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

  11. 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.

  12. 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

  13. 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.

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

    DOE PAGES

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

    2012-05-01

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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Lacis, A. A.

    2013-12-01

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

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

    PubMed Central

    Yuan, Naiming; Fu, Zuntao; Liu, Shida

    2014-01-01

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

  20. 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”,...

  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. Learning Climate in Schools: Part II. Teacher Views of the Learning and Organizational Climate in Schools. Evaluation Brief.

    ERIC Educational Resources Information Center

    Cobb, Carolyn

    Part I of the Learning Climate in Schools evaluation brief looked at violence and disruptive behavior in the North Carolina public schools from several perspectives, including that of teachers expressed in an annual survey. Part II examines teacher perceptions of learning and organizational climates using another set of teacher responses to the…

  4. 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

  5. Impact of future climate policy scenarios on air quality and aerosol-cloud interactions using an advanced version of CESM/CAM5: Part I. model evaluation for the current decadal simulations

    NASA Astrophysics Data System (ADS)

    Glotfelty, Timothy; He, Jian; Zhang, Yang

    2017-03-01

    A version of the Community Earth System Model modified at the North Carolina State University (CESM-NCSU) is used to simulate the current and future atmosphere following the representative concentration partway scenarios for stabilization of radiative forcing at 4.5 W m-2 (RCP4.5) and radiative forcing of 8.5 W m-2 (RCP8.5). Part I describes the results from a comprehensive evaluation of current decadal simulations. Radiation and most meteorological variables are well simulated in CESM-NCSU. Cloud parameters are not as well simulated due in part to the tuning of model radiation and general biases in cloud variables common to all global chemistry-climate models. The concentrations of most inorganic aerosol species (i.e., SO42-, NH4+, and NO3-) are well simulated with normalized mean biases (NMBs) typically less than 20%. However, some notable exceptions are European NH4+, which is overpredicted by 33.0-42.2% due to high NH3 emissions and irreversible coarse mode condensation, and Cl-, that is negatively impacted by errors in emissions driven by wind speed and overpredicted HNO3. Carbonaceous aerosols are largely underpredicted following the RCP scenarios due to low emissions of black carbon, organic carbon, and anthropogenic volatile compounds in the RCP inventory and efficient wet removal. This results in underpredictions of PM2.5 and PM10 by 6.4-55.7%. The column mass abundances are reasonably well simulated. Larger biases occur in surface mixing ratios of trace gases in CESM-NCSU, likely due to numerical diffusion from the coarse grid spacing of the CESM-NCSU simulations or errors in the magnitudes and vertical structure of emissions. This is especially true for SO2 and NO2. The mixing ratio of O3 is overpredicted by 38.9-76.0% due to the limitations in the O3 deposition scheme used in CESM and insufficient titration resulted from large underpredictions in NO2. Despite these limitations, CESM-NCSU reproduces reasonably well the current atmosphere in terms of

  6. Weather Forecaster Understanding of Climate Models

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  7. Climate modeling with decision makers in mind

    SciTech Connect

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

    2016-04-27

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

  8. 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.''

  9. Uncertainty Quantification in Climate Modeling and Projection

    SciTech Connect

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

    2016-05-01

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

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. COP21 climate negotiators' responses to climate model forecasts

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Dommenget, Dietmar

    2015-04-01

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

  17. 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.

  18. 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.

  19. Making the climate part of the human world

    NASA Astrophysics Data System (ADS)

    Donner, S. D.

    2011-12-01

    Doubts about the scientific evidence for anthropogenic climate change persist among the general public, particularly in North America, despite overwhelming consensus in the scientific community about the human influence on the climate system. The public uncertainty may be rooted in the belief, held by many cultures across the planet, that the climate is not directly influenced by people. The belief in divine control of weather and climate can in some cases be traced back to the development of agriculture and the early city-states. Drawing upon evidence from anthropology, theology and communication studies, I suggest that in many regions this deeply ingrained belief may limit public acceptance of the evidence for anthropogenic climate change and explain the persistent appeal of climate change "skepticism". Successful climate change education and outreach programs should be designed to help overcome perceived conflict between climate science and long-held cultural beliefs, drawing upon lessons from communication and education of other potentially divisive subjects like evolution.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  1. 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.

  2. 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

  3. 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

    2015-09-01

    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

  4. 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

  5. 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; ...

    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

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

    NASA Astrophysics Data System (ADS)

    Shukla, J.

    2008-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2000-03-01

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

  8. 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.

  9. Modeling of Past Climates: Some Perspectives

    NASA Astrophysics Data System (ADS)

    Kutzbach, J. E.

    2008-12-01

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

  10. 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

  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. 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

  13. 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

  14. ARM Climate Modeling Best Estimate Data

    SciTech Connect

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

    2010-01-01

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

  15. 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

  16. 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

  17. Climate Change Modeling:Computational Opportunities and Challenges

    SciTech Connect

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

    2011-01-01

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

  18. 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

  19. 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.

  20. Towards convection-resolving climate modeling

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  1. Effects of climatic changes on carbon dioxide and water vapor fluxes in boreal forest ecosystems of European part of Russia

    NASA Astrophysics Data System (ADS)

    Olchev, A.; Novenko, E.; Desherevskaya, O.; Krasnorutskaya, K.; Kurbatova, J.

    2009-10-01

    Effects of possible climatic and vegetation changes on H2O and CO2 fluxes in boreal forest ecosystems of the central part of European Russia were quantified using modeling and experimental data. The future pattern of climatic conditions for the period up to 2100 was derived using the global climatic model ECHAM5 (Roeckner et al 2003 The Atmospheric General Circulation Model ECHAM 5. PART I: Model Description, Report 349 (Hamburg: Max-Planck Institute for Meteorology) p 127) with the A1B emission scenario. The possible trends of future vegetation changes were obtained by reconstructions of vegetation cover and paleoclimatic conditions in the Late Pleistocene and Holocene, as provided from pollen and plant macrofossil analysis of profiles in the Central Forest State Natural Biosphere Reserve (CFSNBR). Applying the method of paleoanalogues demonstrates that increasing the mean annual temperature, even by 1-2 °C, could result in reducing the proportion of spruce in boreal forest stands by up to 40%. Modeling experiments, carried out using a process-based Mixfor-SVAT model, show that the expected future climatic and vegetation changes lead to a significant increase of net ecosystem exchange (NEE) and gross primary productivity (GPP) of the boreal forests. Despite the expected warming and moistening of the climate, the modeling experiments indicate a relatively weak increase of annual evapotranspiration (ET) and even a reduction of transpiration (TR) rates of forest ecosystems compared to present conditions.

  2. 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

  3. 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.

  4. 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.

  5. Bjerknes compensation in the Bergen Climate Model

    NASA Astrophysics Data System (ADS)

    Outten, Stephen; Esau, Igor

    2016-11-01

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

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

    DOE Data Explorer

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

  8. 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.

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

    NASA Astrophysics Data System (ADS)

    Yactayo, G. A.; Bhatt, G.

    2014-12-01

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

  10. 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

  11. 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).

  12. Global Climate Models of the Terrestrial Planets

    NASA Astrophysics Data System (ADS)

    Forget, F.; Lebonnois, S.

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

  13. 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.

  14. 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

  15. A framework for regional modeling of past climates

    NASA Astrophysics Data System (ADS)

    Sloan, L. C.

    2006-09-01

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

  16. FOAM: Expanding the horizons of climate modeling

    SciTech Connect

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

    1997-10-01

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

  17. Modeling the climatic response to orbital variations.

    PubMed

    Imbrie, J; Imbrie, J Z

    1980-02-29

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

  18. The impact of ARM on climate modeling

    SciTech Connect

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

    2016-07-15

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

  19. The impact of ARM on climate modeling

    DOE PAGES

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

    2016-07-15

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

  20. 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

  1. 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…

  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. Several Computational Opportunities and Challenges Associated with Climate Change Modeling

    SciTech Connect

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

    2010-01-01

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

  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. Climate Change, Feedback-Modelling, and Water Resources

    NASA Astrophysics Data System (ADS)

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

    2008-05-01

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

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  10. A Model for Climate Change Adaptation

    NASA Astrophysics Data System (ADS)

    Pasqualini, D.; Keating, G. N.

    2009-12-01

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

  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. Simulated pre-industrial climate in Bergen Climate Model (version 2): model description and large-scale circulation features

    NASA Astrophysics Data System (ADS)

    Otterâ, O. H.; Bentsen, M.; Bethke, I.; Kvamstø, N. G.

    2009-11-01

    The Bergen Climate Model (BCM) is a fully-coupled atmosphere-ocean-sea-ice model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate. Here, a pre-industrial multi-century simulation with an updated version of BCM is described and compared to observational data. The model is run without any form of flux adjustments and is stable for several centuries. The simulated climate reproduces the general large-scale circulation in the atmosphere reasonably well, except for a positive bias in the high latitude sea level pressure distribution. Also, by introducing an updated turbulence scheme in the atmosphere model a persistent cold bias has been eliminated. For the ocean part, the model drifts in sea surface temperatures and salinities are considerably reduced compared to earlier versions of BCM. Improved conservation properties in the ocean model have contributed to this. Furthermore, by choosing a reference pressure at 2000 m and including thermobaric effects in the ocean model, a more realistic meridional overturning circulation is simulated in the Atlantic Ocean. The simulated sea-ice extent in the Northern Hemisphere is in general agreement with observational data except for summer where the extent is somewhat underestimated. In the Southern Hemisphere, large negative biases are found in the simulated sea-ice extent. This is partly related to problems with the mixed layer parametrization, causing the mixed layer in the Southern Ocean to be too deep, which in turn makes it hard to maintain a realistic sea-ice cover here. However, despite some problematic issues, the pre-industrial control simulation presented here should still be appropriate for climate change studies requiring multi-century simulations.

  13. 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

  14. 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.

  15. Workshop: Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis: Research on Climate Change Impacts and Associated Economic Damages (part 2)

    EPA Pesticide Factsheets

    This is a workshop titled Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis: Research on Climate Change Impacts and Associated Economic Damages (part 2)

  16. A scalable climate health justice assessment model

    PubMed Central

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

    2014-01-01

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

  17. A scalable climate health justice assessment model.

    PubMed

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

    2015-05-01

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

  18. 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.

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

    EPA Science Inventory

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

  20. Solar influence on climate during the past millennium: results from transient simulations with the NCAR Climate System Model.

    PubMed

    Ammann, Caspar M; Joos, Fortunat; Schimel, David S; Otto-Bliesner, Bette L; Tomas, Robert A

    2007-03-06

    The potential role of solar variations in modulating recent climate has been debated for many decades and recent papers suggest that solar forcing may be less than previously believed. Because solar variability before the satellite period must be scaled from proxy data, large uncertainty exists about phase and magnitude of the forcing. We used a coupled climate system model to determine whether proxy-based irradiance series are capable of inducing climatic variations that resemble variations found in climate reconstructions, and if part of the previously estimated large range of past solar irradiance changes could be excluded. Transient simulations, covering the published range of solar irradiance estimates, were integrated from 850 AD to the present. Solar forcing as well as volcanic and anthropogenic forcing are detectable in the model results despite internal variability. The resulting climates are generally consistent with temperature reconstructions. Smaller, rather than larger, long-term trends in solar irradiance appear more plausible and produced modeled climates in better agreement with the range of Northern Hemisphere temperature proxy records both with respect to phase and magnitude. Despite the direct response of the model to solar forcing, even large solar irradiance change combined with realistic volcanic forcing over past centuries could not explain the late 20th century warming without inclusion of greenhouse gas forcing. Although solar and volcanic effects appear to dominate most of the slow climate variations within the past thousand years, the impacts of greenhouse gases have dominated since the second half of the last century.

  1. Load-balancing algorithms for climate models

    NASA Astrophysics Data System (ADS)

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

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

  2. Simulated pre-industrial climate in Bergen Climate Model (version 2): model description and large-scale circulation features

    NASA Astrophysics Data System (ADS)

    Otterå, O. H.; Bentsen, M.; Bethke, I.; Kvamstø, N. G.

    2009-05-01

    The Bergen Climate Model (BCM) is a fully-coupled atmosphere-ocean-sea-ice model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate. Here, a pre-industrial multi-century simulation with an updated version of BCM is described and compared to observational data. The model is run without any form of flux adjustments and is stable for several centuries. The simulated climate reproduces the general large scale circulation in the atmosphere reasonably well, except for a positive bias in the high latitude sea level pressures distribution. Also, by introducing an updated turbulence scheme in the atmosphere model a persistent cold bias has been eliminated. For the ocean part, the model drifts in sea surface temperatures and salinities are considerably reduced compared to earlier versions of BCM. Improved conservation properties in the ocean have contributed to this. Furthermore, by choosing a reference pressure at 2000 m and including thermobaric effects in the ocean model, a more realistic meridional overturning circulation is simulated in the Atlantic Ocean. The simulated sea-ice extent in the Northern Hemisphere is in general agreement with observational data except for summer where the extent is somewhat underestimated. In the Southern Hemisphere, large negative biases are found in the simulated sea-ice extent. This is partly related to problems with the mixed layer parametrization, causing the mixed layer in the Southern Ocean to be too deep, which in turn makes it hard to maintain a realistic sea-ice cover here. However, despite some problematic issues, the pre-industrial control simulation presented here should still be appropriate for climate change studies requiring multi-century simulations.

  3. 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.

  4. 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

  5. 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.

  6. Modeling climate change impacts on water trading.

    PubMed

    Luo, Bin; Maqsood, Imran; Gong, Yazhen

    2010-04-01

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

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    Dosio, Alessandro; Panitz, Hans-Jürgen

    2016-03-01

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

  13. The seasonal-cycle climate model

    NASA Technical Reports Server (NTRS)

    Marx, L.; Randall, D. A.

    1981-01-01

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

  14. 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.

    2017-02-01

    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.

  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. 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.

  17. Modelling terrestrial nitrous oxide emissions and implications for climate feedback.

    PubMed

    Xu-Ri; Prentice, I Colin; Spahni, Renato; Niu, Hai Shan

    2012-10-01

    Ecosystem nitrous oxide (N2O) emissions respond to changes in climate and CO2 concentration as well as anthropogenic nitrogen (N) enhancements. Here, we aimed to quantify the responses of natural ecosystem N2O emissions to multiple environmental drivers using a process-based global vegetation model (DyN-LPJ). We checked that modelled annual N2O emissions from nonagricultural ecosystems could reproduce field measurements worldwide, and experimentally observed responses to step changes in environmental factors. We then simulated global N2O emissions throughout the 20th century and analysed the effects of environmental changes. The model reproduced well the global pattern of N2O emissions and the observed responses of N cycle components to changes in environmental factors. Simulated 20th century global decadal-average soil emissions were c. 8.2-9.5 Tg N yr(-1) (or 8.3-10.3 Tg N yr(-1) with N deposition). Warming and N deposition contributed 0.85±0.41 and 0.80±0.14 Tg N yr(-1), respectively, to an overall upward trend. Rising CO2 also contributed, in part, through a positive interaction with warming. The modelled temperature dependence of N2O emission (c. 1 Tg N yr(-1) K(-1)) implies a positive climate feedback which, over the lifetime of N2O (114 yr), could become as important as the climate-carbon cycle feedback caused by soil CO2 release.

  18. High-Resolution Dynamical Downscaling of ERA-Interim Using the WRF Regional Climate Model for the Area of Poland. Part 1: Model Configuration and Statistical Evaluation for the 1981-2010 Period

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

    In this work, we present the results of high-resolution dynamical downscaling of air temperature, relative humidity, wind speed and direction, for the area of Poland, with the Weather Research and Forecasting (WRF) model. The model is configured using three nested domains, with spatial resolution of 45 km × 45 km, 15 km × 15 km and 5 km × 5 km. The ERA-Interim database is used for boundary conditions. The results are evaluated by comparison with station measurements for the period 1981-2010. The model is capable of reproducing the main climatological features of the study area. The results are in very close agreement with the measurements, especially for the air temperature. For all four meteorological variables, the model performance captures seasonal and daily cycles. For the air temperature and winter season, the model underestimates the measurements. For summer, the model shows higher values, compared with the measurements. The opposite is the case for relative humidity. There is a strong diurnal pattern in mean error, which changes seasonally. The agreement with the measurements is worse for the seashore and mountain areas, which suggests that the 5 km × 5 km grid might still have an insufficient spatial resolution. There is no statistically significant temporal trend in the model performance. The larger year-to-year changes in the model performance, e.g. for the years 1982 and 2010 for the air temperature should therefore be linked with the natural variability of meteorological conditions.

  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. 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

  1. Downscaling GISS ModelE boreal summer climate over Africa

    NASA Astrophysics Data System (ADS)

    Druyan, Leonard M.; Fulakeza, Matthew

    2016-12-01

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

  2. 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.

  3. 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.

  4. 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.

  5. Seasonal forecasts of impact-relevant climate information indices developed as part of the EUPORIAS project

    NASA Astrophysics Data System (ADS)

    Spirig, Christoph; Bhend, Jonas

    2015-04-01

    Climate information indices (CIIs) represent a way to communicate climate conditions to specific sectors and the public. As such, CIIs provide actionable information to stakeholders in an efficient way. Due to their non-linear nature, such CIIs can behave differently than the underlying variables, such as temperature. At the same time, CIIs do not involve impact models with different sources of uncertainties. As part of the EU project EUPORIAS (EUropean Provision Of Regional Impact Assessment on a Seasonal-to-decadal timescale) we have developed examples of seasonal forecasts of CIIs. We present forecasts and analyses of the skill of seasonal forecasts for CIIs that are relevant to a variety of economic sectors and a range of stakeholders: heating and cooling degree days as proxies for energy demand, various precipitation and drought-related measures relevant to agriculture and hydrology, a wild fire index, a climate-driven mortality index and wind-related indices tailored to renewable energy producers. Common to all examples is the finding of limited forecast skill over Europe, highlighting the challenge for providing added-value services to stakeholders operating in Europe. The reasons for the lack of forecast skill vary: often we find little skill in the underlying variable(s) precisely in those areas that are relevant for the CII, in other cases the nature of the CII is particularly demanding for predictions, as seen in the case of counting measures such as frost days or cool nights. On the other hand, several results suggest there may be some predictability in sub-regions for certain indices. Several of the exemplary analyses show potential for skillful forecasts and prospect for improvements by investing in post-processing. Furthermore, those cases for which CII forecasts showed similar skill values as those of the underlying meteorological variables, forecasts of CIIs provide added value from a user perspective.

  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. 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.

  8. 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.

  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. Emulating AOGCM results using simple climate models

    NASA Astrophysics Data System (ADS)

    Olivié, Dirk; Stuber, Nicola

    2010-12-01

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

  11. 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.

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

    SciTech Connect

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

    1992-08-01

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

  13. On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa

    NASA Astrophysics Data System (ADS)

    Fotso-Nguemo, Thierry C.; Vondou, Derbetini A.; Pokam, Wilfried M.; Djomou, Zéphirin Yepdo; Diallo, Ismaïla; Haensler, Andreas; Tchotchou, Lucie A. Djiotang; Kamsu-Tamo, Pierre H.; Gaye, Amadou T.; Tchawoua, Clément

    2017-02-01

    In this paper, the regional climate model REMO is used to investigate the added value of downscaling low resolutions global climate models (GCMs) and the climate change projections over Central Africa. REMO was forced by two GCMs (EC-Earth and MPI-ESM), for the period from 1950 to 2100 under the Representative Concentration Pathway 8.5 scenario. The performance of the REMO simulations for current climate is compared first with REMO simulation driven by ERA-Interim reanalysis, then by the corresponding GCMs in order to determine whether REMO outputs are able to effectively lead to added value at local scale. We found that REMO is generally able to better represent some aspects of the rainfall inter-annual variability, the daily rainfall intensity distribution as well as the intra-seasonal variability of the Central African monsoon, though few biases are still evident. It is also found that the boundary conditions strongly influences the spatial distribution of seasonal 2-m temperature and rainfall. From the analysis of the climate change signal from the present period 1976-2005 to the future 2066-2095, we found that all models project a warming at the end of the twenty-first century although the details of the climate change differ between REMO and the driving GCMs, specifically in REMO where we observe a general decrease in rainfall. This rainfall decrease is associated with delayed onset and anticipated recession of the Central African monsoon and a shortening of the rainy season. Small-scales variability of the climate change signal for 2-m temperature are usually smaller than that of the large-scales climate change part. For rainfall however, small-scales induce change of about 70% compared to the present climate statistics.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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

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

    SciTech Connect

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

    2013-06-28

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

  2. Nitrogen Controls on Climate Model Evapotranspiration.

    NASA Astrophysics Data System (ADS)

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

    2002-02-01

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

  3. Climate Modeling: Ocean Cavities below Ice Shelves

    SciTech Connect

    Petersen, Mark Roger

    2016-09-12

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

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

    NASA Astrophysics Data System (ADS)

    Kravitz, Ben; Caldeira, Ken; Boucher, Olivier; Robock, Alan; Rasch, Philip J.; AlterskjæR, Kari; Karam, Diana Bou; Cole, Jason N. S.; Curry, Charles L.; Haywood, James M.; Irvine, Peter J.; Ji, Duoying; Jones, Andy; KristjáNsson, Jón Egill; Lunt, Daniel J.; Moore, John C.; Niemeier, Ulrike; Schmidt, Hauke; Schulz, Michael; Singh, Balwinder; Tilmes, Simone; Watanabe, Shingo; Yang, Shuting; Yoon, Jin-Ho

    2013-08-01

    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 0.2 mm day-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.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Deng, Yi; Ebert-Uphoff, Imme

    2014-01-01

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

  7. 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.

  8. 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.

  9. Impacts of multi-scale solar activity on climate. Part I: Atmospheric circulation patterns and climate extremes

    NASA Astrophysics Data System (ADS)

    Weng, Hengyi

    2012-07-01

    The impacts of solar activity on climate are explored in this two-part study. Based on the principles of atmospheric dynamics, Part I propose an amplifying mechanism of solar impacts on winter climate extremes through changing the atmospheric circulation patterns. This mechanism is supported by data analysis of the sunspot number up to the predicted Solar Cycle 24, the historical surface temperature data, and atmospheric variables of NCEP/NCAR Reanalysis up to the February 2011 for the Northern Hemisphere winters. For low solar activity, the thermal contrast between the low- and high-latitudes is enhanced, so as the mid-latitude baroclinic ultra-long wave activity. The land-ocean thermal contrast is also enhanced, which amplifies the topographic waves. The enhanced mid-latitude waves in turn enhance the meridional heat transport from the low to high latitudes, making the atmospheric "heat engine" more efficient than normal. The jets shift southward and the polar vortex is weakened. The Northern Annular Mode (NAM) index tends to be negative. The mid-latitude surface exhibits large-scale convergence and updrafts, which favor extreme weather/climate events to occur. The thermally driven Siberian high is enhanced, which enhances the East Asian winter monsoon (EAWM). For high solar activity, the mid-latitude circulation patterns are less wavy with less meridional transport. The NAM tends to be positive, and the Siberian high and the EAWM tend to be weaker than normal. Thus the extreme weather/climate events for high solar activity occur in different regions with different severity from those for low solar activity. The solar influence on the midto high-latitude surface temperature and circulations can stand out after removing the influence from the El Niño-Southern Oscillation. The atmospheric amplifying mechanism indicates that the solar impacts on climate should not be simply estimated by the magnitude of the change in the solar radiation over solar cycles when it is

  10. 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.

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

    SciTech Connect

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

    1991-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2003-06-01

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

  13. 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.

  14. 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

  15. 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

  16. 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) ...

  17. Using an ensemble of regional climate models to assess climate change impacts on water scarcity in European river basins.

    PubMed

    Gampe, David; Nikulin, Grigory; Ludwig, Ralf

    2016-12-15

    Climate change will likely increase pressure on the water balances of Mediterranean basins due to decreasing precipitation and rising temperatures. To overcome the issue of data scarcity the hydrological relevant variables total runoff, surface evaporation, precipitation and air temperature are taken from climate model simulations. The ensemble applied in this study consists of 22 simulations, derived from different combinations of four General Circulation Models (GCMs) forcing different Regional Climate Models (RCMs) and two Representative Concentration Pathways (RCPs) at ~12km horizontal resolution provided through the EURO-CORDEX initiative. Four river basins (Adige, Ebro, Evrotas and Sava) are selected and climate change signals for the future period 2035-2065 as compared to the reference period 1981-2010 are investigated. Decreased runoff and evaporation indicate increased water scarcity over the Ebro and the Evrotas, as well as the southern parts of the Adige and the Sava, resulting from a temperature increase of 1-3° and precipitation decrease of up to 30%. Most severe changes are projected for the summer months indicating further pressure on the river basins already at least partly characterized by flow intermittency. The widely used Falkenmark indicator is presented and confirms this tendency and shows the necessity for spatially distributed analysis and high resolution projections. Related uncertainties are addressed by the means of a variance decomposition and model agreement to determine the robustness of the projections. The study highlights the importance of high resolution climate projections and represents a feasible approach to assess climate impacts on water scarcity also in regions that suffer from data scarcity.

  18. 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.

  19. Impacts of climatic changes on carbon and water balance components of boreal forest ecosystems in central part of European Russia

    NASA Astrophysics Data System (ADS)

    Olchev, A.; Novenko, E.; Desherevskaya, O.; Kurbatova, J.

    2009-04-01

    Within the framework of the study the possible impacts of climatic changes on carbon and water balances of boreal forest ecosystems of the central part of European Russia for period up to 2100 was estimated using results of model simulations and field measurements. The boreal forests of the Central Forest State Natural Biosphere Reserve (CFSNBR) were selected for the study. They are located at the southern boundary of south taiga zone in the European part of Russia (Tver region) and it can be expected that they will be very sensitive to modern climate warming. Expected future pattern of climatic parameters in the study area was derived using the global climatic model ECHAM5 (MPI Hamburg, Germany) and climatic scenarios B1, A1B and A2 (IPCC 2007). The possible scenarios of species composition changes of the boreal forests were developed using reconstructions of Holocene vegetation cover and climatic conditions on the base of pollen and plant macrofossil analysis of peat profiles in CFSNBR. The annual future pattern of CO2 and H2O fluxes of the forests were simulated using a process-based Mixfor-SVAT model (Olchev et al. 2002, 2008). The main advantage of Mixfor-SVAT is that it allows us to describe CO2 and H2O fluxes both in mono-specific and mixed forest stands. It is able to quantify both total ecosystem fluxes and flux partitioning among different tree species and canopy layers. It is obvious that it can be very helpful to describe accurately effects of species composition changes on structure of dynamics of carbon and water balance of forest ecosystems. Results of modeling experiments show that expected climatic and vegetation changes can have significant impact on evapotranspiration, transpiration, Net Ecosystem Exchange (NEE), Gross (GPP) and Net (NPP) Primary Productivities of boreal forest ecosystems. These changes have a clear seasonal trend and they are depended on species composition of a forest stand. This study was supported by the Russian Foundation

  20. 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.

  1. 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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  5. [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.

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  8. European snow cover in a changing climate: An analysis of the EURO-CORDEX regional climate model ensemble

    NASA Astrophysics Data System (ADS)

    Kotlarski, Sven; Teichmann, Claas; Gobiet, Andreas

    2015-04-01

    Surface snow cover plays an important and interactive role in global and regional climate systems. For this reason, state-of-the-art climate models employ snow parameterization schemes of differing complexity that simulate the snow cover response to climate change and climate variability and that allow for an approximate representation of snow-atmosphere feedbacks. A dedicated validation of snow cover characteristics simulated by climate models can provide valuable insight in the accuracy of the feedback representation and in the origin of, for instance, near-surface temperature biases. The analysis of scenario simulations provides estimates of future snow cover changes on continental and sub-continental scales as a response to rising greenhouse gas concentrations, complementing smaller-scale snow cover scenarios obtained from dedicated cryospheric impact models. We here present a first analysis of surface snow cover characteristics in the recently established EURO-CORDEX regional climate model (RCM) ensemble, considering simulations with grid spacings of both 12 and 50 km. The analysis covers snow cover validation in ERA-Interim-driven hindcast simulations as well as the assessment of 21st century snow cover changes over different parts of Europe. A particular focus is on the European Alps, a region with a high economic vulnerability with respect to the anticipated snow cover reduction. Model evaluation against satellite-derived and surface-based observational datasets reveals an approximate reproduction of spatio-temporal snow cover variability over Europe by the RCMs. In the Alps, however, high-elevation snow mass can be considerably overestimated by individual models. This feature is likely connected to cold high-elevation temperature biases. 21st century snow cover scenarios show an almost complete loss of snow cover in low-elevation regions, largely confirming previous works. The rate of snow cover decrease strongly depends on the warming magnitude and

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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).

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

    PubMed Central

    Lawing, A. Michelle; Polly, P. David

    2011-01-01

    Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM) and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models), phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species), and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr) than it has been on average for the past 320 ky (2.3 m/yr). PMID:22164305

  16. 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

  17. 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...

  18. 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

  19. 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

  20. 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

    2017-02-01

    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.

  1. Impacts of climate change on temperature, precipitation and hydrology in Finland - studies using bias corrected Regional Climate Model data

    NASA Astrophysics Data System (ADS)

    Olsson, T.; Jakkila, J.; Veijalainen, N.; Backman, L.; Kaurola, J.; Vehviläinen, B.

    2015-07-01

    Assessment of climate change impacts on climate and hydrology on catchment scale requires reliable information about the average values and climate fluctuations of the past, present and future. Regional climate models (RCMs) used in impact studies often produce biased time series of meteorological variables. In this study bias correction (BC) of RCM temperature and precipitation for Finland is carried out using different versions of the distribution based scaling (DBS) method. The DBS-adjusted RCM data are used as input of a hydrological model to simulate changes in discharges of four study catchments in different parts of Finland. The annual mean discharges and seasonal variation simulated with the DBS-adjusted temperature and precipitation data are sufficiently close to observed discharges in the control period 1961-2000 and produce more realistic projections for mean annual and seasonal changes in discharges than the uncorrected RCM data. Furthermore, with most scenarios the DBS method used preserves the temperature and precipitation trends of the uncorrected RCM data during 1961-2100. However, if the biases in the mean or the standard deviation of the uncorrected temperatures are large, significant biases after DBS adjustment may remain or temperature trends may change, increasing the uncertainty of climate change projections. The DBS method influences especially the projected seasonal changes in discharges and the use of uncorrected data can produce unrealistic seasonal discharges and changes. The projected changes in annual mean discharges are moderate or small, but seasonal distribution of discharges will change significantly.

  2. 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.

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

    NASA Technical Reports Server (NTRS)

    2005-01-01

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

  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. 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.

  6. Climate variability in a coupled GCM. Part II: The Indian Ocean and monsoon

    SciTech Connect

    Latif, M.; Sterl, A.; Assenbaum, M.; Junge, M.M.; Maier-Reimer, E.

    1994-10-01

    We have investigated the seasonal cycle and the interannual variability of the tropical Indian Ocean circulation and the Indian summer monsoon simulated by a coupled ocean-atmosphere general circulation model in a 26-year integration. Although the model exhibits significant climate drift, overall, the coupled GCM simulates realistically the seasonal changes in the tropical Indian Ocean and the onset and evolution of the Indian summer monsoon. The amplitudes of the seasonal changes, however, are underestimated. The coupled GCM also simulates considerable interannual variability in the tropical Indian Ocean circulation, which is partly related to the El Nino/Southern Oscillation phenomenon and the associated changes in the Walker circulation. Changes in the surface wind stress appear to be crucial in forcing interannual variations in the Indian Ocean SST. As in the Pacific Ocean, the net surface heat flux acts as a negative feedback on the SST anomalies. The interannual variability in monsoon rainfall, simulated by the coupled GCM, is only about half as strong as observed. The reason for this is that the simulated interannual variability in the Indian monsoon appears to be related to internal processes within the atmosphere only. In contrast, an investigation based on observations shows a clear lead-lag relationship between interannual variations in the monsoon rainfall and tropical Pacific SST anomalies. Furthermore, the atmospheric GCM also fails to reproduce this lead-lag relationship between monsoon rainfall and tropical Pacific SST when run in a stand-alone integration with observed SSTs prescribed during the period 1970-1988. These results indicate that important physical processes relating tropical Pacific SST to Indian monsoon rainfall are not adequately modeled in our atmospheric GCM. Monsoon rainfall predictions appear therefore premature. 24 refs., 13 figs, 2 tabs.

  7. 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

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  10. 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

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

    PubMed

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

    2016-09-01

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

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

  14. 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.

  15. Women in the Military; Pregnancy, Command Climate, Organizational Behavior, and Outcome. Part 1

    DTIC Science & Technology

    1996-05-01

    status and sexual harassment may contribute to an increased risk of ill health among women in the military. Pregnancy compounds the problem because it is...HR 96-001 Defense Women’s Health Research Program Women in the Military: Pregnancy, Command Climate, Organizational Behavior, and Outcomes. Mary Ann...Healthcare Education & Studies REPORT NUMBER Academy of Health Sciences, AMEDDC&S HR96-001, Part 1 1608 Stanley Road, Bldg 2268 Fort Sam Houston, TX 78234

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  18. 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.

  19. 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

  20. 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.

  1. Modelling Climate/Global Change and Assessing Environmental Risks for Siberia

    NASA Astrophysics Data System (ADS)

    Lykosov, V. N.; Kabanov, M. V.; Heimann, M.; Gordov, E. P.

    2009-04-01

    The state-of-the-art climate models are based on a combined atmosphere-ocean general circulation model. A central direction of their development is associated with an increasingly accurate description of all physical processes participating in climate formation. In modeling global climate, it is necessary to reconstruct seasonal and monthly mean values, seasonal variability (monsoon cycle, parameters of storm-tracks, etc.), climatic variability (its dominating modes, such as El Niño or Arctic Oscillation), etc. At the same time, it is quite urgent now to use modern mathematical models in studying regional climate and ecological peculiarities, in particular, that of Northern Eurasia. It is related with the fact that, according to modern ideas, natural environment in mid- and high latitudes of the Northern hemisphere is most sensitive to the observed global climate changes. One should consider such tasks of modeling regional climate as detailed reconstruction of its characteristics, investigation of the peculiarities of hydrological cycle, estimation of the possibility of extreme phenomena to occur, and investigation of the consequences of the regional climate changes for the environment and socio-economic relations as its basic tasks. Changes in nature and climate in Siberia are of special interest in view of the global change in the Earth system. The vast continental territory of Siberia is undoubtedly a ponderable natural territorial region of Eurasian continent, which is characterized by the various combinations of climate-forming factors. Forests, water, and wetland areas are situated on a significant part of Siberia. They play planetary important regulating role due to the processes of emission and accumulation of the main greenhouse gases (carbon dioxide, methane, etc.). Evidence of the enhanced rates of the warming observed in the region and the consequences of such warming for natural environment are undoubtedly important reason for integrated regional

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

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

  4. An introduction to three-dimensional climate modeling

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  5. 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

  6. 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

  7. 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

  8. 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 ...

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    /ha in many areas. The simulated yield changes in the future were both spatially explicit and dependent on the GCM used. The effectiveness of agronomic practices was highly varied across the region depending on soil type, agro-ecological zone and projected climate change. The results have critical implications for agronomic research and policy. The study challenges using a ';one size fits all' approach in the identification of potential adaptation strategies. The goal is to use models to target local, optimized solutions as part of the broader need for impact assessments at coarser scales.

  10. Modelling coffee leaf rust risk in Colombia with climate reanalysis data.

    PubMed

    Bebber, Daniel P; Castillo, Ángela Delgado; Gurr, Sarah J

    2016-12-05

    Many fungal plant diseases are strongly controlled by weather, and global climate change is thus likely to have affected fungal pathogen distributions and impacts. Modelling the response of plant diseases to climate change is hampered by the difficulty of estimating pathogen-relevant microclimatic variables from standard meteorological data. The availability of increasingly sophisticated high-resolution climate reanalyses may help overcome this challenge. We illustrate the use of climate reanalyses by testing the hypothesis that climate change increased the likelihood of the 2008-2011 outbreak of Coffee Leaf Rust (CLR, Hemileia vastatrix) in Colombia. We develop a model of germination and infection risk, and drive this model using estimates of leaf wetness duration and canopy temperature from the Japanese 55-Year Reanalysis (JRA-55). We model germination and infection as Weibull functions with different temperature optima, based upon existing experimental data. We find no evidence for an overall trend in disease risk in coffee-growing regions of Colombia from 1990 to 2015, therefore, we reject the climate change hypothesis. There was a significant elevation in predicted CLR infection risk from 2008 to 2011 compared with other years. JRA-55 data suggest a decrease in canopy surface water after 2008, which may have helped terminate the outbreak. The spatial resolution and accuracy of climate reanalyses are continually improving, increasing their utility for biological modelling. Confronting disease models with data requires not only accurate climate data, but also disease observations at high spatio-temporal resolution. Investment in monitoring, storage and accessibility of plant disease observation data are needed to match the quality of the climate data now available.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'.

  11. Modelling coffee leaf rust risk in Colombia with climate reanalysis data

    PubMed Central

    Castillo, Ángela Delgado; Gurr, Sarah J.

    2016-01-01

    Many fungal plant diseases are strongly controlled by weather, and global climate change is thus likely to have affected fungal pathogen distributions and impacts. Modelling the response of plant diseases to climate change is hampered by the difficulty of estimating pathogen-relevant microclimatic variables from standard meteorological data. The availability of increasingly sophisticated high-resolution climate reanalyses may help overcome this challenge. We illustrate the use of climate reanalyses by testing the hypothesis that climate change increased the likelihood of the 2008–2011 outbreak of Coffee Leaf Rust (CLR, Hemileia vastatrix) in Colombia. We develop a model of germination and infection risk, and drive this model using estimates of leaf wetness duration and canopy temperature from the Japanese 55-Year Reanalysis (JRA-55). We model germination and infection as Weibull functions with different temperature optima, based upon existing experimental data. We find no evidence for an overall trend in disease risk in coffee-growing regions of Colombia from 1990 to 2015, therefore, we reject the climate change hypothesis. There was a significant elevation in predicted CLR infection risk from 2008 to 2011 compared with other years. JRA-55 data suggest a decrease in canopy surface water after 2008, which may have helped terminate the outbreak. The spatial resolution and accuracy of climate reanalyses are continually improving, increasing their utility for biological modelling. Confronting disease models with data requires not only accurate climate data, but also disease observations at high spatio-temporal resolution. Investment in monitoring, storage and accessibility of plant disease observation data are needed to match the quality of the climate data now available. This article is part of the themed issue ‘Tackling emerging fungal threats to animal health, food security and ecosystem resilience’. PMID:28080984

  12. 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.

  13. 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.

  14. Holocene climate dynamics in the central part of the East European plain (Russia)

    NASA Astrophysics Data System (ADS)

    Novenko, Elena

    2013-04-01

    The Holocene climate and vegetation dynamics in the broad-leaved forest zone of the central part of the East European plain have been reconstructed on the base of pollen, plant macrofossil, testate amoebae and radiocarbon data from the mire Klukva (N 53.834812, E 36.252488), located in the kast depression in the Upper Oka River basin (Tula region, European Russia). The reconstruction of main parameters of past climate (the mean annual temperature precipitation) was carried out by the "Best Modern Analog" approach. Reconstructions of vegetation show that in the early Holocene the territory was occupied mainly by birch and pine-birch forests. Significant changes in the plant cover of the Upper Oka River basin are attributed to the 7.5 cal kyr BP). The climatic conditions were favorable for development of the broad-leaved forests those persisted in this area up to industrial period. In the 17th century, when the population density greatly increased and watersheds were ploughed, natural vegetation communities were gradually destroyed and transformed into agricultural landscapes. According to obtained climatic reconstructions the period 10-8.5 cal kyr BP was relatively cold and wet, when the mean annual temperature was in 3°C lower and precipitation was in 50-100 mm higher then nowadays. The significant climate warming occurred in about 7.0-5.0 cal kyr BP (The Holocene thermal maximum): the mean annual temperature in 2°C exceeded the modern value and precipitation was close to that. The environment conditions were drier due to decrease of effective moisture. In the second part of the Holocene the sequence of second-, and even third-order climatic oscillations expressed against the background of the overall slight trend towards cooling have been determined. The most pronounced cool and wet intervals were reconstructed in 2.5-2.0 cal kyr BP and 1.5-1.3 cal kyr BP. The mean annual temperature decreased in 1.5-2 °C and precipitation rose in 200 mm in compare to modern

  15. Atmospheric impact of the 1783-1784 Laki Eruption: Part II Climatic effect of sulphate aerosol

    NASA Astrophysics Data System (ADS)

    Highwood, E. J.; Stevenson, D. S.

    2003-03-01

    The long 1783-1784 eruption of Laki, in southern Iceland, was one of the first eruptions to have been linked to an observed climate anomaly, having been held responsible for cold temperatures over much of the Northern Hemisphere in the period 1783-1785. Results from the first climate model simulation of the impact of the 1783-1784 fissure eruption are presented. Using sulphate aerosol fields produced in a companion chemical transport model simulation by Stevenson et al. (2003), the radiative forcing and climate response due to the aerosol are calculated here using the Reading Intermediate General Circulation Model (IGCM). The peak Northern Hemisphere mean direct radiative forcing is -5.5 Wm-2 in August 1783. The radiative forcing dies away quickly as the emissions from the volcano decrease; however, a small forcing remains over the Mediterranean until March 1784. There is little forcing in the Southern Hemisphere. There is shown to be an uncertainty of at least 50% in the direct radiative forcing due to assumptions concerning relative humidity and the sophistication of the radiative transfer code used. The indirect effects of the Laki aerosol are potentially large but essentially unquantifiable at the present time. In the IGCM at least, the aerosol from the eruption produces a climate response that is spatially very variable. The magnitude of the Northern Hemisphere annual mean anomaly for 1783 is -0.21 K, statistically significant at the 95% level and in reasonable agreement with the available observations.

  16. Fully nonlinear data-assimilation in climate models

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  17. 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

  18. Collaborative Project: Understanding Climate Model Biases in Tropical Atlantic and Their Impact on Simulations of Extreme Climate Events

    SciTech Connect

    Chang, Ping

    2016-01-04

    Recent studies have revealed that among all the tropical oceans, the tropical Atlantic has experienced the most pronounced warming trend over the 20th century. Many extreme climate events affecting the U.S., such as hurricanes, severe precipitation and drought events, are influenced by conditions in the Gulf of Mexico and the Atlantic Ocean. It is therefore imperative to have accurate simulations of the climatic mean and variability in the Atlantic region to be able to make credible projections of future climate change affecting the U.S. and other countries adjoining the Atlantic Ocean. Unfortunately, almost all global climate models exhibit large biases in their simulations of tropical Atlantic climate. The atmospheric convection simulation errors in the Amazon region and the associated errors in the trade wind simulations are hypothesized to be a leading cause of the tropical Atlantic biases in climate models. As global climate models have resolutions that are too coarse to resolve some of the atmospheric and oceanic processes responsible for the model biases, we propose to use a high-resolution coupled regional climate model (CRCM) framework to address the tropical bias issue. We propose to combine the expertise in tropical coupled atmosphere-ocean modeling at Texas A&M University (TAMU) and the coupled land-atmosphere modeling expertise at Pacific Northwest National Laboratory (PNNL) to develop a comprehensive CRCM for the Atlantic sector within a general and flexible modeling framework. The atmospheric component of the CRCM will be the NCAR WRF model and the oceanic component will be the Rutgers/UCLA ROMS. For the land component, we will use CLM modified at PNNL to include more detailed representations of vegetation and soil hydrology processes. The combined TAMU-PNNL CRCM model will be used to simulate the Atlantic climate, and the associated land-atmosphere-ocean interactions at a horizontal resolution of 9 km or finer. A particular focus of the model

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

    PubMed

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

    2014-01-02

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

  20. Climate change impacts on hydrological processes in Norway based on two methods for transferring regional climate model results to meteorological station sites

    NASA Astrophysics Data System (ADS)

    Beldring, Stein; Engen-Skaugen, Torill; Førland, Eirik J.; Roald, Lars A.

    2008-05-01

    Climate change impacts on hydrological processes in Norway have been estimated through combination of results from the IPCC SRES A2 and B2 emission scenarios, global climate models from the Hadley Centre and the Max-Planck Institute, and dynamical downscaling using the RegClim HIRHAM regional climate model. Temperature and precipitation simulations from the regional climate model were transferred to meteorological station sites using two different approaches, the delta change or perturbation method and an empirical adjustment procedure that reproduces observed monthly means and standard deviations for the control period. These climate scenarios were used for driving a spatially distributed version of the HBV hydrological model, yielding a set of simulations for the baseline period 1961-1990 and projections of climate change impacts on hydrological processes for the period 2071-2100. A comparison between the two methods used for transferring regional climate model results to meteorological station sites is provided by comparing the results from the hydrological model for basins located in different parts of Norway. Projected changes in runoff are linked to changes in the snow regime. Snow cover will be more unstable and the snowmelt flood will occur earlier in the year. Increased rainfall leads to higher runoff in the autumn and winter.

  1. 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

  2. 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.

  3. 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.

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

    DOE PAGES

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

    2010-01-01

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

  5. A probabilistic model of ecosystem response to climate change

    SciTech Connect

    Shevliakova, E.; Dowlatabadi, H.

    1994-12-31

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

  6. Climate change and health modeling: horses for courses

    PubMed Central

    Ebi, Kristie L.; Rocklöv, Joacim

    2014-01-01

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

  7. 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

  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. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    PubMed

    Noble, Ian R

    1993-08-01

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

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

    PubMed

    Semazzi, Fredrick

    2003-06-01

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

  13. 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.

  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. Modeling of tower relief dynamics: Part 2

    SciTech Connect

    Cassata, J.R.; Dasgupta, S.; Gandhi, S.L. )

    1993-11-01

    Dynamic simulations of individual towers or systems of distillations columns overcome limitations of steady-state models by rigorously determining dynamic responses. These will lead to a realistic quantification of relief header and flare system load and identify the design-setting relief scenario. Determination of distillation tower relief loads based on steady-state simulations or recognized methods of approximation can lead to over designing relief systems by large margins. This can result in unnecessary capital expenditure for relief headers and flare systems that can significantly alter the economics of a proposed project. Such overly conservative requirements may even cause potentially attractive projects to be unnecessarily canceled. In addition, approximate methods or analyses based on steady-state simulations sometimes do not identify the design-setting relief mode. Part 1 introduced the PRV and tower dynamic models. Different strategies were shown that can simplify these models. These strategies include tower segmentation, tray lumping and component lumping. Two case studies illustrate the advantages of dynamic models. The two studies are a depentanizer tower relief study and a delthanizer tower relief study.

  16. Partly conditional survival models for longitudinal data.

    PubMed

    Zheng, Yingye; Heagerty, Patrick J

    2005-06-01

    It is common in longitudinal studies to collect information on the time until a key clinical event, such as death, and to measure markers of patient health at multiple follow-up times. One approach to the joint analysis of survival and repeated measures data adopts a time-varying covariate regression model for the event time hazard. Using this standard approach, the instantaneous risk of death at time t is specified as a possibly semi-parametric function of covariate information that has accrued through time t. In this manuscript, we decouple the time scale for modeling the hazard from the time scale for accrual of available longitudinal covariate information. Specifically, we propose a class of models that condition on the covariate information through time s and then specifies the conditional hazard for times t, where t > s. Our approach parallels the "partly conditional" models proposed by Pepe and Couper (1997, Journal of the American Statistical Association 92, 991-998) for pure repeated measures applications. Estimation is based on the use of estimating equations applied to clusters of data formed through the creation of derived survival times that measure the time from measurement of covariates to the end of follow-up. Patient follow-up may be terminated either by the occurrence of the event or by censoring. The proposed methods allow a flexible characterization of the association between a longitudinal covariate process and a survival time, and facilitate the direct prediction of survival probabilities in the time-varying covariate setting.

  17. 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.

  18. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. Regional Climate Model Sensitivity to Domain Size

    NASA Astrophysics Data System (ADS)

    Leduc, M.; Laprise, R.

    2006-05-01

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

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

    SciTech Connect

    Walcek, C.J.

    1996-12-31

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

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Mahowald, Natalie M.

    2007-09-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  17. 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

  18. 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.

  19. JPEG-2000 Part 10 Verification Model

    SciTech Connect

    Mniszewski, Susan; Rivenburgh, Reid; Brislawn, Chris

    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 uniform 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 published

  20. 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

  1. 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.

  2. 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.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2002-12-01

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

  5. 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.

  6. Spatial-temporal assessment of climate model drifts

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  7. 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

  8. 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.

  9. 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.

  10. Greenhouse Models of Early Mars Climate

    NASA Astrophysics Data System (ADS)

    Kasting, J. F.

    2002-12-01

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

  11. The AWI Climate Model: response to increased resolution in dynamically active regions

    NASA Astrophysics Data System (ADS)

    Sidorenko, Dmitry; Semmler, Tido; Rackow, Thomas; Goessling, Helge F.; Danilov, Sergey; Wang, Qiang; Sein, Dmitry; Jung, Thomas

    2016-04-01

    State-of-the-art climate models do still exhibit pronounced deviations from the measured climate. Those deviations are often common between those models. The challenging problems in the Northern hemisphere include warming and salinization of the deep ocean being most pronounced in the northern North Atlantic, reduced deep water formation in the Labrador Sea which is sometimes accomplished by the sporadic ice coverage of the whole Labrador Sea, and an extensive ice presence in the Barents Sea. All these biases are often attributed in literature to the lack of oceanic resolution. The multi-resolution approach used in the ocean component of the AWI climate model (ECHAM6-FESOM) allows to use enhanced horizontal resolution in dynamical active regions while keeping a coarse-resolution setup everywhere else. In this study we develop strategies for improving the climate model biases by means of increasing resolution in the ocean. The current computations have been performed on multi-centennial time scales using refinement in the different parts of the global ocean. Benefits from the local refinement have been analyzed. It is found that already with moderate refinement of the unstructured ocean grid, AWI-CM performs as well as some of the most sophisticated climate models participating in CMIP5.

  12. 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

  13. Modeling climate change impacts on overwintering bald eagles

    PubMed Central

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

    2012-01-01

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

  14. 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.

  15. 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.

  16. Modeled regional climate change and California endemic oak ranges

    PubMed Central

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

    2005-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  18. 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.

  19. 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.

  20. Modeling extreme precipitation events—a climate change simulation for Europe

    NASA Astrophysics Data System (ADS)

    Semmler, Tido; Jacob, Daniela

    2004-12-01

    The regional climate model REMO 5.1 has been applied to the European region to investigate the impact of future climate changes on the frequency and intensity of extreme precipitation events. For today's climate, not only the climatological mean precipitation, but also the 10- and 20-year return levels of daily precipitation are captured fairly well by the use of the following model configuration: REMO 5.1 at 0.5° resolution is driven by an atmospheric global climate model HadAM3H control simulation at the lateral boundaries. Sea surface temperature (SST) and sea ice distribution (SID) are prescribed from the observed data set HadISST1. In mountainous regions, the differences between simulated and observed return levels are larger than in flat regions. Here, a higher horizontal resolution could probably further improve the results. The regional scenario simulation has been carried out with REMO 5.1 driven by a HadAM3H scenario simulation. This simulation is consistent with the SRES-A2 emission scenario and uses changes in sea surface temperature and sea ice distribution simulated by the coupled global climate model HadCM3. Large increases of the precipitation return levels for the 10- and 20-year return periods are simulated in 2070-2100 compared to 1960-1990. Nearly all regions are affected by higher return levels, even if the mean precipitation decreases in some regions. In most regions, the return levels are increasing up to 50%. In the Baltic Sea region, there are increases by more than 100%, which, however, can be partly related to a very strong increase in the sea surface temperature in the coupled global climate model simulation. This increase is stronger compared to other global climate model simulations and very pronounced in the Baltic Sea.

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2011-08-01

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

  3. 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.

  4. Evaluating Skill of Process-Based Models of Tree-Ring Response to Climate

    NASA Astrophysics Data System (ADS)

    Meko, D. M.; Stahle, D. W.

    2008-12-01

    Process-based models of tree-growth driven by climate input can deal with nonlinear processes and ideally are capable of modeling responses to climate fluctuations outside the range of climate variability in the observed instrumental record. Information from such models can be useful in assessing likely vegetation responses to projected climate change, and in posing climate scenarios associated with outstanding tree-ring anomalies of the past. An essential step in the evaluation of process-based models is assessment of skill, typically defined as accuracy of predictions relative to those generated by some reasonable alternative. A statistical framework for such an assessment is presented, with the alternative a dynamic black-box time series model. The black-box model is illustrated with prediction of the standard chronology tree-ring index for a Quercus douglasii (blue oak) tree-ring site in California from a PRISM-based precipitation record. A time series model with weights on current and past years' winter (Nov-Mar) precipitation is calibrated on data for 1896-1950 and used to predict the tree-ring index for 1951-2007. The variance of tree-ring index explained in the prediction period exceeds 75 percent, but prediction errors are slightly positively autocorrelated, and are negative for 12 consecutive years during a period that includes the drought of the late 1980s to early 1990s. Statistically-based predictions such as these are proposed as test data for skill assessment of process- based models. In such assessment it is essential that the calibration and prediction datasets are kept absolutely separate. No part of the calibration process, including identification of the "season" of climate response, should be allowed to access the data from the prediction interval. Likewise any tuning of the process-based model should be restricted to data outside the prediction period.

  5. 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.

  6. 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.

  7. Radar derived storm dynamics for cloud-resolving model evaluation and climate model parameterization development

    NASA Astrophysics Data System (ADS)

    Collis, S. M.; May, P. T.; Protat, A.; Fridlind, A. M.; Ackerman, A. S.; Williams, C. R.; Varble, A.; Zipser, E. J.

    2010-12-01

    The Tropical Warm Pool-International Cloud Experiment (TWP-ICE) was conducted in and around the US Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Darwin site during January and February 2006. The field program gathered observations that have been used for initializing and driving cloud-resolving models (CRMs, with periodic boundary conditions) and limited-area models (LAMs, with open boundary conditions) for submission to the model intercomparison study, which is organized by the ARM and GEWEX Cloud System Study (GCSS) programs. Measurements also included an extensive set of remotely sensed and in-situ quantities to evaluate model performance, assisting climate model parameterization development. For example, using a combination of operational Doppler radar and CPOL polartimetric research radar data vector winds have been retrieved in storms for part of the model intercomparison period. This presentation will outline the retrieval technique, show preliminary verification of the retrieved updraft intensities and showcase model-measurement comparison with output from the DHARMA cloud-resolving model focusing on vertical winds, a crucial aspect of simulated storm dynamics which exhibit a high degree of model to model variability. Initial comparison has most model updraft speeds substantially higher those retrieved from radar measurements. Investigations into the impact of sampling, scale differences and the cause for this discrepancy are ongoing as is the extension of comparisons to all CRM and LAM submissions. Details on the roll out of the American Recovery and Reinvestment Act funded precipitation radar infrastructure for ACRF and plans for geophysical retrievals from this new instrumentation will also be presented.

  8. 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.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2004-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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...

  16. 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…

  17. 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…

  18. A community diagnostic tool for chemistry climate model validation

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

  19. A community diagnostic tool for Chemistry Climate Model Validation

    NASA Astrophysics Data System (ADS)

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

    2012-05-01

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

  20. 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.

  1. 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

  2. Different parts, different stories: climate sensitivity of growth is stronger in root collars versus stems in tundra shrubs.

    PubMed

    Ropars, Pascale; Angers-Blondin, Sandra; Gagnon, Marianne; Myers-Smith, Isla H; Lévesque, Esther; Boudreau, Stéphane

    2017-01-20

    Shrub densification has been widely reported across the circumpolar arctic and subarctic biomes in recent years. Long-term analyses based on dendrochronological techniques applied to shrubs have linked this phenomenon to climate change. However, the multi-stemmed structure of shrubs makes them difficult to sample and therefore leads to non-uniform sampling protocols among shrub ecologists, who will favor either root collars or stems to conduct dendrochronological analyses. Through a comparative study of the use of root collars and stems of Betula glandulosa, a common North American shrub species, we evaluated the relative sensitivity of each plant part to climate variables, and assessed if this sensitivity is consistent across three different types of environments in northwestern Québec, Canada (terrace, hilltop and snowbed). We found that root collars had greater sensitivity to climate than stems, and that these differences were maintained across the three types of environment. Growth at the root collar was best explained by spring precipitation and summer temperature, whereas stem growth showed weak and inconsistent responses to climate variables. Moreover, sensitivity to climate was not consistent among plant parts, as individuals having climate sensitive root collars did not tend to have climate sensitive stems. These differences in sensitivity of shrub parts to climate highlight the complexity of resource allocation in multi-stemmed plants. Whereas stem initiation and growth are driven by micro-environmental variables such as light availability and competition, root collars integrate the growth of all plant parts instead, rendering them less affected by mechanisms such as competition and more responsive to signals of global change. Although further investigations are required to determine the degree to which these findings are generalizable across the tundra biome, our results indicate that consistency and caution in the choice of plant parts are a key

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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.

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2013-01-01

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

  14. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  16. 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

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

    PubMed

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

    2015-10-27

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

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

    PubMed Central

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

    2015-01-01

    Abrupt transitions of regional climate in response to the gradual rise in atmospheric greenhouse gas concentrations are notoriously difficult to foresee. However, such events could be particularly challenging in view of the capacity required for society and ecosystems to adapt to them. We present, to our knowledge, the first systematic screening of the massive climate model ensemble informing the recent Intergovernmental Panel on Climate Change report, and reveal evidence of 37 forced regional abrupt changes in the ocean, sea ice, snow cover, permafrost, and terrestrial biosphere that arise after a certain global temperature increase. Eighteen out of 37 events occur for global warming levels of less than 2°, a threshold sometimes presented as a safe limit. Although most models predict one or more such events, any specific occurrence typically appears in only a few models. We find no compelling evidence for a general relation between the overall number of abrupt shifts and the level of global warming. However, we do note that abrupt changes in ocean circulation occur more often for moderate warming (less than 2°), whereas over land they occur more often for warming larger than 2°. Using a basic proportion test, however, we find that the number of abrupt shifts identified in Representative Concentration Pathway (RCP) 8.5 scenarios is significantly larger than in other scenarios of lower radiative forcing. This suggests the potential for a gradual trend of destabilization of the climate with respect to such shifts, due to increasing global mean temperature change. PMID:26460042

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  20. Inter-variable relations in regional climate model outputs

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Hartmann, William K.

    2012-10-01

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

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

    USGS Publications Warehouse

    David E. Rupp,

    2016-05-05

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

  3. Impacts of tectonic and orbital forcing on East African climate: A comparison based on global climate model simulations.

    NASA Astrophysics Data System (ADS)

    Kaspar, F.; Prömmel, K.; Cubasch, U.

    2009-04-01

    Tectonic uplift and erosional denudation can have drastic effects on global and regional climate patterns, which in turn have a significant impact on ecosystems and the distribution of biogeographic zones. The interdisciplinary Research Unit RiftLink (www.riftlink.de) addresses the causes of rift-flank uplift in the East African Rift, its impact on climate changes in equatorial Africa, and the possible connection to the evolution of hominids. Understanding the mechanisms and origin of atmospheric moisture transport is essential for the interpretation of paleoclimatic proxies. Here, we present results from the climate modelling component of RiftLink. The global atmosphere-ocean model ECHO-G has been forced with topographic and orbital scenarios in order to evaluate the relative role of both factors for the past climate of East Africa. The model consists of the ECHAM4 atmosphere model at approx. 3.75° resolution coupled to the HOPE-G ocean model at approx. 2.8°. Forcing the model with a significantly reduced topography in Eastern and Southern Africa leads to a distinct increase in moisture transport from the Indian ocean into the eastern part of the continent and increased precipitation in Eastern Africa. Simulations with step-wise reduced height show that this climate change occurs continuously with the change in topography, i.e. an abrupt change of local climatic features with a critical height is not found. If these results are used for the interpretation of proxy data, it has do be considered that other forcing factors can lead to comparable changes in moisture availability. As an example, we tested the impact of changes in the Earth's orbit around the Sun. For these simulations, we forced the same climate model with the orbital configuration of the last interglacial (at 125,000 years before present, i.e. the Eemian interglacial) and the last glacial inception (at 115,000 years before present). The induced changes in the seasonal and spatial structure of

  4. Impacts of Climate Change on Surface Ozone and Intercontinental Ozone Pollution: A Multi-Model Study

    NASA Technical Reports Server (NTRS)

    Doherty, R. M.; Wild, O.; Shindell, D. T.; Zeng, G.; MacKenzie, I. A.; Collins, W. J.; Fiore, A. M.; Stevenson, D. S.; Dentener, F. J.; Schultz, M. G.; Hess, P.; Derwent, R. G.; Keating, T. J.

    2013-01-01

    The impact of climate change between 2000 and 2095 SRES A2 climates on surface ozone (O)3 and on O3 source-receptor (S-R) relationships is quantified using three coupled climate-chemistry models (CCMs). The CCMs exhibit considerable variability in the spatial extent and location of surface O3 increases that occur within parts of high NOx emission source regions (up to 6 ppbv in the annual average and up to 14 ppbv in the season of maximum O3). In these source regions, all three CCMs show a positive relationship between surface O3 change and temperature change. Sensitivity simulations show that a combination of three individual chemical processes-(i) enhanced PAN decomposition, (ii) higher water vapor concentrations, and (iii) enhanced isoprene emission-largely reproduces the global spatial pattern of annual-mean surface O3 response due to climate change (R2 = 0.52). Changes in climate are found to exert a stronger control on the annual-mean surface O3 response through changes in climate-sensitive O3 chemistry than through changes in transport as evaluated from idealized CO-like tracer concentrations. All three CCMs exhibit a similar spatial pattern of annual-mean surface O3 change to 20% regional O3 precursor emission reductions under future climate compared to the same emission reductions applied under present-day climate. The surface O3 response to emission reductions is larger over the source region and smaller downwind in the future than under present-day conditions. All three CCMs show areas within Europe where regional emission reductions larger than 20% are required to compensate climate change impacts on annual-mean surface O3.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  6. Linking the Weather Generator with Regional Climate Model

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate wea