WorldWideScience

Sample records for regional climate model

  1. Regionalizing global climate models

    NARCIS (Netherlands)

    Pitman, A.J.; Arneth, A.; Ganzeveld, L.N.

    2012-01-01

    Global climate models simulate the Earth's climate impressively at scales of continents and greater. At these scales, large-scale dynamics and physics largely define the climate. At spatial scales relevant to policy makers, and to impacts and adaptation, many other processes may affect regional and

  2. Spatial scale separation in regional climate modelling

    Energy Technology Data Exchange (ETDEWEB)

    Feser, F.

    2005-07-01

    In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter

  3. Daily precipitation statistics in regional climate models

    DEFF Research Database (Denmark)

    Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel

    2003-01-01

    An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...

  4. Regional model simulations of New Zealand climate

    Science.gov (United States)

    Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

    1998-03-01

    Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

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

    Science.gov (United States)

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

    2004-06-01

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

  6. Regional climate model sensitivity to domain size

    Energy Technology Data Exchange (ETDEWEB)

    Leduc, Martin [Universite du Quebec a Montreal, Canadian Regional Climate Modelling and Diagnostics (CRCMD) Network, ESCER Centre, Montreal (Canada); UQAM/Ouranos, Montreal, QC (Canada); Laprise, Rene [Universite du Quebec a Montreal, Canadian Regional Climate Modelling and Diagnostics (CRCMD) Network, ESCER Centre, Montreal (Canada)

    2009-05-15

    Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the ''perfect model'' approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 x 100 grid points). The permanent ''spatial spin-up'' corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere. (orig.)

  7. Assessing NARCCAP climate model effects using spatial confidence regions

    Directory of Open Access Journals (Sweden)

    J. P. French

    2017-07-01

    Full Text Available We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

  8. Regional climate model sensitivity to domain size

    Science.gov (United States)

    Leduc, Martin; Laprise, René

    2009-05-01

    Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere.

  9. A Regional Climate Model Evaluation System

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop a packaged data management infrastructure for the comparison of generated climate model output to existing observational datasets that includes capabilities...

  10. Abilities and limitations in the use of regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Koeltzov, Morten Andreas Oedegaard

    2012-11-01

    In order to say something about the effect of climate change at the regional level, one takes in use regional climate models. In these models the thesis introduce regional features, which are not included in the global climate models (which are basically in climate research). Regional models can provide good and useful climate projections that add more value than the global climate models, but also introduces an uncertainty in the calculations. How should this uncertainty affect the use of regional climate models?The most common methodology for calculating potential future climate developments are based on different scenarios of possible emissions of greenhouse gases. These scenarios operates as global climate models using physical laws and calculate possible future developments. This is considered mathematical complexed and processes with limited supercomputing capacity calculates the global models for the larger scale of the climate system. To study the effects of climate change are regional details required and the regional models used therefore in a limited area of the climate system. These regional models are driven by data from the global models and refines and improves these data. Impact studies can then use the data from the regional models or data which are further processed to provide more local details using geo-statistical methods. In the preparation of the climate projections is there a minimum of 4 sources of uncertainty. This uncertainty is related to the provision of emission scenarios of greenhouse gases, uncertainties related to the use of global climate models, uncertainty related to the use of regional climate models and the uncertainty of internal variability in the climate system. This thesis discusses the use of regional climate models, and illustrates how the regional climate model adds value to climate projections, and at the same time introduce uncertainty in the calculations. It discusses in particular the importance of the choice of

  11. Wind climate from the regional climate model REMO

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Mann, Jakob; Berg, Jacob

    2010-01-01

    Selected outputs from simulations with the regional climate model REMO from the Max Planck Institute, Hamburg, Germany were studied in connection with wind energy resource assessment. It was found that the mean wind characteristics based on observations from six mid-latitude stations are well...... described by the standard winds derived from the REMO pressure data. The mean wind parameters include the directional wind distribution, directional and omni-directional mean values and Weibull fitting parameters, spectral analysis and interannual variability of the standard winds. It was also found that......, on average, the wind characteristics from REMO are in better agreement with observations than those derived from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis pressure data. The spatial correlation of REMO surface winds in Europe...

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

    Science.gov (United States)

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

    2014-12-01

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

  13. Evaluating the performance and utility of regional climate models

    DEFF Research Database (Denmark)

    Christensen, Jens H.; Carter, Timothy R.; Rummukainen, Markku

    2007-01-01

    This special issue of Climatic Change contains a series of research articles documenting co-ordinated work carried out within a 3-year European Union project 'Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects' (PRUDENCE). The main objective...... of the PRUDENCE project was to provide high resolution climate change scenarios for Europe at the end of the twenty-first century by means of dynamical downscaling (regional climate modelling) of global climate simulations. The first part of the issue comprises seven overarching PRUDENCE papers on: (1) the design...... of the model simulations and analyses of climate model performance, (2 and 3) evaluation and intercomparison of simulated climate changes, (4 and 5) specialised analyses of impacts on water resources and on other sectors including agriculture, ecosystems, energy, and transport, (6) investigation of extreme...

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

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, Raymond S; Diaz, Henry F

    2010-12-14

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

  15. Modelling the regional effects of climate change on air quality

    International Nuclear Information System (INIS)

    Giorgi, F.; Meleux, F.

    2007-01-01

    The life cycle of pollutants is affected by chemical as well as meteorological factors, such as wind, temperature, precipitation, solar radiation. Therefore, climatic changes induced by anthropogenic emissions of greenhouse gases may be expected to have significant effects on air quality. Because of the spatial variability of the pollutant emissions and climate-change signals, these effects are particularly relevant at the regional to local scales. This paper first briefly reviews modelling tools and methodologies used to study regional climate-change impacts on air quality. Patterns of regional precipitation, temperature, and sea-level changes emerging from the latest set of general circulation model projections are then discussed. Finally, the specific case of climate-change effects on summer ozone concentrations over Europe is presented to illustrate the potential impacts of climate change on pollutant amounts. It is concluded that climate change is an important factor that needs to be taken into account when designing future pollution-reduction policies. (authors)

  16. The regional climate model RegCM3 performances over several regions and climate regimes

    Science.gov (United States)

    Coppola, E.; Rauscher, S.; Gao, X.; Giorgi, F.; Im, E. S.; Mariotti, L.; Seth, A.; Sylla, M. B.

    2009-04-01

    Regional Climate models are more and more needed to provide high resolution regional climate information in climate impact studies. Water availability in a future scenario is the main request of policy makers for adaptation and mitigation purposes. However precipitation changes are unlikely to be as spatially coherent as temperature changes and they are closely related to the regional model itself. In addition model skill varies regionally. An example of several ICTP regional climate model (RegCM3) simulations is reported over China, Korea, Africa, Central and Southern America, Europe and Australia. Over China, Australia, and Korea the regional model improves the simulation compared to the driving GCM when compared with CRU observations. In China, for example, the higher resolution of the regional model inhibits the penetration of the monsoon precipitation front from the southern slope of the Himalaya onto the Tibetan Plateau. In Korea the nested domain simulation (20 km) shows an encouraging performance with regard to capturing extreme precipitation episodes and the finer spatial distribution reflects the detailed geography of the Korean Peninsula. Over South America, RegCM captures the annual cycle of precipitation over Northeast Brazil and the South American Monsoon region, although the monsoon onset occurs too early in the model. Precipitation over the Amazon is not well captured, with too little precipitation associated with weak easterlies and reduced moisture transport into the interior of the continent. RegCM simulates the annual cycle of precipitation over Central America and the Caribbean fairly well; in particular, the complex spatial distribution of the Mid-Summer Drought, a decrease in precipitation that occurs during the middle of the rainy season in July and August, is better captured by RegCM than by the GCM. In addition, RegCM simulates the strength and position of the Caribbean low level jet, a mesoscale feature related to precipitation anomalies

  17. Effective single scattering albedo estimation using regional climate model

    CSIR Research Space (South Africa)

    Tesfaye, M

    2011-09-01

    Full Text Available In this study, by modifying the optical parameterization of Regional Climate model (RegCM), the authors have computed and compared the Effective Single-Scattering Albedo (ESSA) which is a representative of VIS spectral region. The arid, semi...

  18. Multisite bias correction of precipitation data from regional climate models

    Czech Academy of Sciences Publication Activity Database

    Hnilica, Jan; Hanel, M.; Puš, V.

    2017-01-01

    Roč. 37, č. 6 (2017), s. 2934-2946 ISSN 0899-8418 R&D Projects: GA ČR GA16-05665S Grant - others:Grantová agentura ČR - GA ČR(CZ) 16-16549S Institutional support: RVO:67985874 Keywords : bias correction * regional climate model * correlation * covariance * multivariate data * multisite correction * principal components * precipitation Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Climatic research Impact factor: 3.760, year: 2016

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

    DEFF Research Database (Denmark)

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

    2007-01-01

    -90) and future (2071-2 100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves - Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first...

  20. Impact of surface waves in a Regional Climate Model

    DEFF Research Database (Denmark)

    Rutgersson, Anna; Sætra, Oyvind; Semedo, Alvaro

    2010-01-01

    A coupled regional atmosphere-wave model system is developed with the purpose of investigating the impact of climate changes on the wave field, as well as feed-back effects of the wave field on the atmospheric parameters. This study focuses on the effects of introducing a two-way atmosphere...

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

    KAUST Repository

    Stenchikov, Georgiy L.

    2011-04-09

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

  2. A review on regional convection permitting climate modeling

    Science.gov (United States)

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

    2016-04-01

    are addressed in future research. Coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs. Brisson, E., K. Van Weverberg, M. Demuzere, A. Devis, S. Saeed, M. Stengel, N.P.M. van Lipzig, 2016. How well can a convection-permitting climate model reproduce 1 decadal statistics of precipitation, temperature and cloud characteristics? Clim. Dyn. (minor revisions). Prein, Andreas F., Wolfgang Langhans, Giorgia Fosser, Andrew Ferrone, Nikolina Ban, Klaus Goergen, Michael Keller, Merja Tölle, Oliver Gutjahr, Frauke Feser, Erwan Brisson, Stefan Kollet, Juerg Schmidli, Nicole P. M. van Lipzig, Ruby Leung. (2015) A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Reviews of Geophysics 53:10.1002/rog.v53.2, 323-361

  3. Climate change projections for Greek viticulture as simulated by a regional climate model

    Science.gov (United States)

    Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos

    2017-07-01

    Viticulture represents an important economic activity for Greek agriculture. Winegrapes are cultivated in many areas covering the whole Greek territory, due to the favorable soil and climatic conditions. Given the dependence of viticulture on climate, the vitivinicultural sector is expected to be affected by possible climatic changes. The present study is set out to investigate the impacts of climatic change in Greek viticulture, using nine bioclimatic indices for the period 1981-2100. For this purpose, reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the regional climatic model Regional Climate Model Version 3 (RegCM3) are used. It was found that the examined regional climate model estimates satisfactorily these bioclimatic indices. The results of the study show that the increasing trend of temperature and drought will affect all wine-producing regions in Greece. In vineyards in mountainous regions, the impact is positive, while in islands and coastal regions, it is negative. Overall, it should be highlighted that for the first time that Greece is classified into common climatic characteristic categories, according to the international Geoviticulture Multicriteria Climatic Classification System (MCC system). According to the proposed classification, Greek viticulture regions are estimated to have similar climatic characteristics with the warmer wine-producing regions of the world up to the end of twenty-first century. Wine growers and winemakers should take the findings of the study under consideration in order to take measures for Greek wine sector adaptation and the continuation of high-quality wine production.

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

    Science.gov (United States)

    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

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

    Czech Academy of Sciences Publication Activity Database

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

    2014-01-01

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

  6. Implementation of a parallel version of a regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Gerstengarbe, F.W. [ed.; Kuecken, M. [Potsdam-Institut fuer Klimafolgenforschung (PIK), Potsdam (Germany); Schaettler, U. [Deutscher Wetterdienst, Offenbach am Main (Germany). Geschaeftsbereich Forschung und Entwicklung

    1997-10-01

    A regional climate model developed by the Max Planck Institute for Meterology and the German Climate Computing Centre in Hamburg based on the `Europa` and `Deutschland` models of the German Weather Service has been parallelized and implemented on the IBM RS/6000 SP computer system of the Potsdam Institute for Climate Impact Research including parallel input/output processing, the explicit Eulerian time-step, the semi-implicit corrections, the normal-mode initialization and the physical parameterizations of the German Weather Service. The implementation utilizes Fortran 90 and the Message Passing Interface. The parallelization strategy used is a 2D domain decomposition. This report describes the parallelization strategy, the parallel I/O organization, the influence of different domain decomposition approaches for static and dynamic load imbalances and first numerical results. (orig.)

  7. A Reusable Framework for Regional Climate Model Evaluation

    Science.gov (United States)

    Hart, A. F.; Goodale, C. E.; Mattmann, C. A.; Lean, P.; Kim, J.; Zimdars, P.; Waliser, D. E.; Crichton, D. J.

    2011-12-01

    Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and

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

    Czech Academy of Sciences Publication Activity Database

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

    2014-01-01

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

  9. Ensemble of regional climate model projections for Ireland

    Science.gov (United States)

    Nolan, Paul; McGrath, Ray

    2016-04-01

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

  10. The regional aerosol-climate model REMO-HAM

    Directory of Open Access Journals (Sweden)

    J.-P. Pietikäinen

    2012-11-01

    Full Text Available REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes most of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM is coupled with a two-moment stratiform cloud scheme. On the other hand, REMO-HAM does not include an online coupled aerosol-radiation nor a secondary organic aerosol module. In this work, we evaluate the model and compare the results against ECHAM5-HAM and measurements. Four different measurement sites were chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50 × 50 km2 and 10 × 10 km2. Based on our simulations, REMO-HAM is in reasonable agreement with the measured values. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. Since we did not use activation nor kinetic nucleation for the boundary layer, the total number concentrations are somewhat underestimated. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we show that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.

  11. Internal variability in a regional climate model over West Africa

    Energy Technology Data Exchange (ETDEWEB)

    Vanvyve, Emilie; Ypersele, Jean-Pascal van [Universite catholique de Louvain, Institut d' astronomie et de geophysique Georges Lemaitre, Louvain-la-Neuve (Belgium); Hall, Nicholas [Laboratoire d' Etudes en Geophysique et Oceanographie Spatiales/Centre National d' Etudes Spatiales, Toulouse Cedex 9 (France); Messager, Christophe [University of Leeds, Institute for Atmospheric Science, Environment, School of Earth and Environment, Leeds (United Kingdom); Leroux, Stephanie [Universite Joseph Fourier, Laboratoire d' etude des Transferts en Hydrologie et Environnement, BP53, Grenoble Cedex 9 (France)

    2008-02-15

    Sensitivity studies with regional climate models are often performed on the basis of a few simulations for which the difference is analysed and the statistical significance is often taken for granted. In this study we present some simple measures of the confidence limits for these types of experiments by analysing the internal variability of a regional climate model run over West Africa. Two 1-year long simulations, differing only in their initial conditions, are compared. The difference between the two runs gives a measure of the internal variability of the model and an indication of which timescales are reliable for analysis. The results are analysed for a range of timescales and spatial scales, and quantitative measures of the confidence limits for regional model simulations are diagnosed for a selection of study areas for rainfall, low level temperature and wind. As the averaging period or spatial scale is increased, the signal due to internal variability gets smaller and confidence in the simulations increases. This occurs more rapidly for variations in precipitation, which appear essentially random, than for dynamical variables, which show some organisation on larger scales. (orig.)

  12. Does Nudging Squelch the Extremes in Regional Climate Modeling?

    Science.gov (United States)

    An important question in regional climate downscaling is whether to constrain (nudge) the interior of the limited-area domain toward the larger-scale driving fields. Prior research has demonstrated that interior nudging can increase the skill of regional climate predictions origin...

  13. REGIONAL CLIMATE MODELING STUDY FOR THE CARPATHIAN REGION USING REGCM4 EXPERIMENTS

    Directory of Open Access Journals (Sweden)

    PIECZKA I.

    2015-03-01

    Full Text Available The newest model version of RegCM is adapted with the ultimate aim of providing climate projection for the Carpathian region with 10 km horizontal resolution. For this purpose, first, coarse resolution reanalysis data and global climate model outputs are used to drive 50 km resolution model experiments, from which the outputs are used to provide necessary boundary conditions for the fine scale model runs. Besides the historical runs (for the period 1981-2010, RCP4.5 scenario is also analyzed in this paper for the 21st century. These experiments are essential since they form the basis of national climate and adaptation strategies by providing detailed regional scale climatic projections and enabling specific impact studies for various sectors.

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

    Science.gov (United States)

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

    2016-01-01

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

  15. Evaluation of an ensemble of Arctic regional climate models

    DEFF Research Database (Denmark)

    Rinke, A.; Dethloff, K.; Cassano, J. J.

    2006-01-01

    Simulations of eight different regional climate models (RCMs) have been performed for the period September 1997-September 1998, which coincides with the Surface Heat Budget of the Arctic Ocean (SHEBA) project period. Each of the models employed approximately the same domain covering the western......, temperature, cloud cover, and long-/shortwave downward radiation between the individual model simulations are investigated. With this work, we quantify the scatter among the models and therefore the magnitude of disagreement and unreliability of current Arctic RCM simulations. Even with the relatively...... constrained experimental design we notice a considerable scatter among the different RCMs. We found the largest across-model scatter in the 2 m temperature over land, in the surface radiation fluxes, and in the cloud cover which implies a reduced confidence level for these variables....

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

    Directory of Open Access Journals (Sweden)

    S. D. Outten

    2013-05-01

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

  17. Regional Spectral Model simulations of the summertime regional climate over Taiwan and adjacent areas

    Science.gov (United States)

    Ching-Teng Lee; Ming-Chin Wu; Shyh-Chin Chen

    2005-01-01

    The National Centers for Environmental Prediction (NCEP) regional spectral model (RSM) version 97 was used to investigate the regional summertime climate over Taiwan and adjacent areas for June-July-August of 1990 through 2000. The simulated sea-level-pressure and wind fields of RSM1 with 50-km grid space are similar to the reanalysis, but the strength of the...

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

    Science.gov (United States)

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

    2013-04-01

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

  19. Use of regional climate model simulations as an input for hydrological models for the Hindukush-Karakorum-Himalaya region

    NARCIS (Netherlands)

    Akhtar, M.; Ahmad, N.; Booij, Martijn J.

    2009-01-01

    The most important climatological inputs required for the calibration and validation of hydrological models are temperature and precipitation that can be derived from observational records or alternatively from regional climate models (RCMs). In this paper, meteorological station observations and

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

    Science.gov (United States)

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

    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. A characteristics of East Asian climate using high-resolution regional climate model

    Science.gov (United States)

    Yhang, Y.

    2013-12-01

    Climate research, particularly application studies for water, agriculture, forestry, fishery and energy management require fine scale multi-decadal information of meteorological, oceanographic and land states. Unfortunately, spatially and temporally homogeneous multi-decadal observations of these variables in high horizontal resolution are non-existent. Some long term surface records of temperature and precipitation exist, but the number of observation is very limited and the measurements are often contaminated by changes in instrumentation over time. Some climatologically important variables, such as soil moisture, surface evaporation, and radiation are not even measured over most of East Asia. Reanalysis is one approach to obtaining long term homogeneous analysis of needed variables. However, the horizontal resolution of global reanalysis is of the order of 100 to 200 km, too coarse for many application studies. Regional climate models (RCMs) are able to provide valuable regional finescale information, especially in regions where the climate variables are strongly regulated by the underlying topography and the surface heterogeneity. In this study, we will provide accurately downscaled regional climate over East Asia using the Global/Regional Integrated Model system [GRIMs; Hong et al. 2013]. A mixed layer model is embedded within the GRIMs in order to improve air-sea interaction. A detailed description of the characteristics of the East Asian summer and winter climate will be presented through the high-resolution numerical simulations. The increase in horizontal resolution is expected to provide the high-quality data that can be used in various application areas such as hydrology or environmental model forcing.

  2. California Wintertime Precipitation in Regional and Global Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Caldwell, P M

    2009-04-27

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

  3. The spread amongst ENSEMBLES regional scenarios: regional climate models, driving general circulation models and interannual variability

    Energy Technology Data Exchange (ETDEWEB)

    Deque, M.; Somot, S. [Meteo-France, Centre National de Recherches Meteorologiques, CNRS/GAME, Toulouse Cedex 01 (France); Sanchez-Gomez, E. [Cerfacs/CNRS, SUC URA1875, Toulouse Cedex 01 (France); Goodess, C.M. [University of East Anglia, Climatic Research Unit, Norwich (United Kingdom); Jacob, D. [Max Planck Institute for Meteorology, Hamburg (Germany); Lenderink, G. [KNMI, Postbus 201, De Bilt (Netherlands); Christensen, O.B. [Danish Meteorological Institute, Copenhagen Oe (Denmark)

    2012-03-15

    Various combinations of thirteen regional climate models (RCM) and six general circulation models (GCM) were used in FP6-ENSEMBLES. The response to the SRES-A1B greenhouse gas concentration scenario over Europe, calculated as the difference between the 2021-2050 and the 1961-1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance explained for temperature and precipitation changes over eight European sub-areas. Three sources of uncertainty can be evaluated from the ENSEMBLES database. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30) despite a non-negligible interannual variability. Regional model uncertainty is due to the fact that the RCMs use different techniques to discretize the equations and to represent sub-grid effects. Global model uncertainty is due to the fact that the RCMs have been driven by different GCMs. Two methods are presented to fill the many empty cells of the ENSEMBLES RCM x GCM matrix. The first one is based on the same approach as in FP5-PRUDENCE. The second one uses the concept of weather regimes to attempt to separate the contribution of the GCM and the RCM. The variance of the climate response is analyzed with respect to the contribution of the GCM and the RCM. The two filling methods agree that the main contributor to the spread is the choice of the GCM, except for summer precipitation where the choice of the RCM dominates the uncertainty. Of course the implication of the GCM to the spread varies with the region, being maximum in the South-western part of Europe, whereas the continental parts are more sensitive to the choice of the RCM. The third cause of spread is systematically the interannual variability. The total uncertainty about temperature is not large enough to mask the 2021-2050 response which shows a similar pattern to the one obtained for 2071-2100 in PRUDENCE. The uncertainty

  4. Regionalization of climate model results for the North Sea

    Energy Technology Data Exchange (ETDEWEB)

    Kauker, F.

    1999-07-01

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

  5. Evaluating the impacts of climate change on diurnal wind power cycles using multiple regional climate models

    KAUST Repository

    Goddard, Scott D.

    2015-05-01

    Electrical utility system operators must plan resources so that electricity supply matches demand throughout the day. As the proportion of wind-generated electricity in the US grows, changes in daily wind patterns have the potential either to disrupt the utility or increase the value of wind to the system over time. Wind power projects are designed to last many years, so at this timescale, climate change may become an influential factor on wind patterns. We examine the potential effects of climate change on the average diurnal power production cycles at 12 locations in North America by analyzing averaged and individual output from nine high-resolution regional climate models comprising historical (1971–1999) and future (2041–2069) periods. A semi-parametric mixed model is fit using cubic B-splines, and model diagnostics are checked. Then, a likelihood ratio test is applied to test for differences between the time periods in the seasonal daily averaged cycles, and agreement among the individual regional climate models is assessed. We investigate the significant changes by combining boxplots with a differencing approach and identify broad categories of changes in the amplitude, shape, and position of the average daily cycles. We then discuss the potential impact of these changes on wind power production.

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

    Science.gov (United States)

    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

  7. Climate change due to greenhouse effects in China as simulated by a regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Gao, X.J.; Zhao, Z.C.; Ding, Y.H.; Huang, R.H.; Giorgi, F. [National Climate Centre, Beijing (China)

    2001-07-01

    Impacts of greenhouse effects (2 x CO{sub 2}) upon climate change over China as simulated by a regional climate model over China (RegCM / China) have been investigated. The model was based on RegCM2 and was nested to a global coupled ocean-atmosphere model (CSIRO R21L9 AOGCM model). Results of the control run (1 x CO{sub 2}) indicated that simulations of surface air temperature and precipitation in China by RegCM are much better than that by the global coupled model because of a higher resolution. Results of sensitive experiment by RegCM with 2 x CO{sub 2} showed that the surface air temperature over China might increase remarkably due to greenhouse effect, especially in winter season and in North China. Precipitation might also increase in most parts of China due to the CO{sub 2} doubling.

  8. Zooming in on cirrus with the Canadian Regional Climate Model

    Science.gov (United States)

    Stefanof, C.; Stefanof, A.; Beaulne, A.; Munoz Alpizar, R.; Szyrmer, W.; Blanchet, J.

    2004-05-01

    The Canadian Regional Climate Model plus a microphysical scheme: two-moments microphysics with three hydrometeor categories (cloud liquid water, pristine ice crystals and larger precipitation crystals) is used to test the simulation in forecast mode using ECMWF data at 0.4 X 0.4 degree. We are zooming in on cirrus at higher resolutions (9, 1.8, 0.36 km). We are currently using the data set measured in APEX-E3, measurements of radar, lidar, passive instruments and interpreted microphysics for some flights (G-II, C404, B200). The radar and lidar data are available for high level cirrus. The south west of Japon is the flight region. The dates are March 20, March 27 and April 2, 2003. We first focus on the March 27 frontal system. We did a rigorous synoptical analysis for the cases. The cirrus at 360 m resolution are simulated. The cloud structure and some similarities between model simulation and observations will be presented.

  9. Heat waves over Central Europe in regional climate model simulations

    Science.gov (United States)

    Lhotka, Ondřej; Kyselý, Jan

    2014-05-01

    Regional climate models (RCMs) have become a powerful tool for exploring impacts of global climate change on a regional scale. The aim of the study is to evaluate the capability of RCMs to reproduce characteristics of major heat waves over Central Europe in their simulations of the recent climate (1961-2000), with a focus on the most severe and longest Central European heat wave that occurred in 1994. We analyzed 7 RCM simulations with a high resolution (0.22°) from the ENSEMBLES project, driven by the ERA-40 reanalysis. In observed data (the E-OBS 9.0 dataset), heat waves were defined on the basis of deviations of daily maximum temperature (Tmax) from the 95% quantile of summer Tmax distribution in grid points over Central Europe. The same methodology was applied in the RCM simulations; we used corresponding 95% quantiles (calculated for each RCM and grid point) in order to remove the bias of modelled Tmax. While climatological characteristics of heat waves are reproduced reasonably well in the RCM ensemble, we found major deficiencies in simulating heat waves in individual years. For example, METNOHIRHAM simulated very severe heat waves in 1996, when no heat wave was observed. Focusing on the major 1994 heat wave, considerable differences in simulated temperature patterns were found among the RCMs. The differences in the temperature patterns were clearly linked to the simulated amount of precipitation during this event. The 1994 heat wave was almost absent in all RCMs that did not capture the observed precipitation deficit, while it was by far most pronounced in KNMI-RACMO that simulated virtually no precipitation over Central Europe during the 15-day period of the heat wave. By contrast to precipitation, values of evaporative fraction in the RCMs were not linked to severity of the simulated 1994 heat wave. This suggests a possible major contribution of other factors such as cloud cover and associated downward shortwave radiation. Therefore, a more detailed

  10. Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain

    Science.gov (United States)

    Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.

    2015-12-01

    In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.

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

    Science.gov (United States)

    Leckebusch, G. C.; Ulbrich, U.

    2003-04-01

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

  12. Scale dependency of regional climate modeling of current and future climate extremes in Germany

    Science.gov (United States)

    Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

    2017-11-01

    A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

  13. Regional Scale/Regional Climate Model Development and Its Applications at Goddard

    Science.gov (United States)

    Tao, W.-K.; Lau, W.; Qian, J.; Jia, Y.; Wetzel, P.; Chou, M.-D.; Wang, Y.; Lynn, B.

    2000-01-01

    A Regional Land-Atmosphere Climate Simulation System (RELACS) is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model (Penn State/NCAR MM5) with improved physical processes and in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water/energy cycles in the Indo-China/South China Sea (SCS)/China, N. America and S. America region.

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

    Science.gov (United States)

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

    2014-01-01

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

  15. Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific

    Science.gov (United States)

    Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B.

    2015-12-01

    Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study.

  16. Multi-model Ensemble Regional Climate Projection of the Maritime Continent using the MIT Regional Climate Model

    Science.gov (United States)

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

    2016-12-01

    In this study, the future change in precipitation due to global warming is investigated over the Maritime Continent using the MIT Regional Climate Model (MRCM). A total of nine 30-year projections under multi-GCMs (CCSM, MPI, ACCESS) and multi-scenarios of emissions (Control, RCP4.5, RCP8.5) are dynamically downscaled using the MRCM with 12km horizontal resolution. Since downscaled results tend to systematically overestimate the precipitation regardless of GCM used as lateral boundary conditions, the Parametric Quantile Mapping (PQM) is applied to reduce this wet bias. The cross validation for the control simulation shows that the PQM method seems to retain the spatial pattern and temporal variability of raw simulation, however it effectively reduce the wet bias. Based on ensemble projections produced by dynamical downscaling and statistical bias correction, a reduction of future precipitation is discernible, in particular during dry season (June-July-August). For example, intense precipitation in Singapore is expected to be reduced in RCP8.5 projection compared to control simulation. However, the geographical patterns and magnitude of changes still remain uncertain, suffering from statistical insignificance and a lack of model agreement. Acknowledgements This research is supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise programme. The Center for Environmental Sensing and Modeling is an interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology

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

    Directory of Open Access Journals (Sweden)

    Claas Teichmann

    2013-06-01

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

  18. Improvement of snowpack simulations in a regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Jin, J.; Miller, N.L.

    2011-01-10

    To improve simulations of regional-scale snow processes and related cold-season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth-generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5–CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5–CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land-surface model. One important cause for the underestimated SWE in Noah is its unrealistic land-surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow-season surface albedo overestimated by MM5–Noah is now more accurately predicted by MM5–CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near-surface cold bias in MM5–Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5–CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5–Noah. In addition, the over-predicted precipitation in the Pacific Northwest as shown in MM5–Noah is significantly decreased in MM5 CLM3 due to the lower evaporation resulting from the

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

    DEFF Research Database (Denmark)

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

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

  20. Adjustment of regional climate model output for modeling the climatic mass balance of all glaciers on Svalbard.

    NARCIS (Netherlands)

    Möller, M.; Obleitner, F.; Reijmer, C.H.; Pohjola, V.A.; Glowacki, P.; Kohler, J.

    2016-01-01

    Large-scale modeling of glacier mass balance relies often on the output from regional climate models (RCMs). However, the limited accuracy and spatial resolution of RCM output pose limitations on mass balance simulations at subregional or local scales. Moreover, RCM output is still rarely available

  1. Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

    Science.gov (United States)

    Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

    2013-12-01

    Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

  2. Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

    Science.gov (United States)

    Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

    2002-12-01

    There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human

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

    Science.gov (United States)

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

    2016-05-01

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

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

    KAUST Repository

    Evans, J. P.; McCabe, Matthew

    2013-01-01

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

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

    KAUST Repository

    Evans, J. P.

    2013-03-26

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

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

    Directory of Open Access Journals (Sweden)

    Asma Foughali

    2015-07-01

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

  7. Does temperature nudging overwhelm aerosol radiative effects in regional integrated climate models?

    Science.gov (United States)

    For over two decades, data assimilation (popularly known as nudging) methods have been used for improving regional weather and climate simulations by reducing model biases in meteorological parameters and processes. Similar practice is also popular in many regional integrated met...

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

    Czech Academy of Sciences Publication Activity Database

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

    2014-01-01

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

  9. Integrated climate and hydrology modelling - Coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model

    Energy Technology Data Exchange (ETDEWEB)

    Dahl Larsen, M.A. [Technical Univ. of Denmark. DTU Management Engineering, DTU Risoe Campus, Roskilde (Denmark)

    2013-10-15

    To ensure optimal management and sustainable strategies for water resources, infrastructures, food production and ecosystems there is a need for an improved understanding of feedback and interaction mechanisms between the atmosphere and the land surface. This is especially true in light of expected global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate and hydrology have used each model component in an offline mode where the models are run in sequential steps and one model serves as a boundary condition or data input source to the other. Within recent years a new field of research has emerged where efforts have been made to dynamically couple existing climate and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface. The modelling tool consists of a fully dynamic two-way coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model. The expected gain is twofold. Firstly, HIRHAM utilizes the land surface component of the combined MIKE SHE/SWET hydrology and land surface model (LSM), which is superior to the LSM in HIRHAM. A wider range of processes are included at the land surface, subsurface flow is distributed in three dimensions and the temporal and spatial resolution is higher. Secondly, the feedback mechanisms of e.g. soil moisture and precipitation between the two models are included. The preparation of the HIRHAM and MIKE SHE models for the coupled study revealed several findings. The performance of HIRHAM was highly affected by the domain size, domain

  10. Regionalizing Africa: Patterns of Precipitation Variability in Observations and Global Climate Models

    Science.gov (United States)

    Badr, Hamada S.; Dezfuli, Amin K.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.

    2016-01-01

    Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios.

  11. Artificial snowmaking possibilities and climate change based on regional climate modeling in the Southern Black Forest

    Energy Technology Data Exchange (ETDEWEB)

    Schmidt, Philipp; Matzarakis, Andreas [Freiburg Univ. (Germany). Meteorological Inst.; Steiger, Robert [alpS - Centre for Climate Change Adaptation Technologies, Innsbruck (Austria)

    2012-04-15

    Winter sport, especially ski tourism - is one of those sectors of tourism that will be affected by climate change. Ski resorts across the Alps and in the adjacent low mountain ranges react to warm winter seasons by investing in artificial snowmaking. But snowmaking in warm winter seasons is fraught with risk, because sufficiently low air temperature will become less frequent in the future. The present study deals with the ski resort Feldberg, which has 14 ski lifts and 16 ski slopes which is the biggest ski resort in the German Federal state Baden-Wuerttemberg. The impact of climate change in this region is extraordinary important because winter tourism is the main source of revenue for the whole area around the ski resort. The study area is in altitudinal range of 850 to 1450 meters above sea level. At the moment, it is possible to supply one third of the whole area with artificial snow, but there is plan for artificial snowmaking of the whole Feldberg area by the year 2020. Based on this, more detailed investigations of season length and the needed volume of produced snow are necessary. A ski season simulation model (SkiSim 2.0) was applied in order to assess potential impacts of climate change on the Feldberg ski area for the A1B and B1 emission scenarios based on the ECHAM5 GCM downscaled by the REMO RCM. SkiSim 2.0 calculates daily snow depth (natural and technically produced snow) and the required amount of artificial snow for 100 m altitudinal bands. Analysing the development of the number of potential skiing days, it can be assessed whether ski operation is cost covering or not. Model results of the study show a more pronounced and rapid shortening of the ski season in the lower ranges until the year 2100 in each climate scenario. In both the A1B and B1 scenario runs of REMO, a cost-covering ski season of 100 days cannot be guaranteed in every altitudinal range even if snowmaking is considered. In this context, the obtained high-resolution snow data can

  12. Regionalization of climate model results for the North Sea

    Energy Technology Data Exchange (ETDEWEB)

    Kauker, F. [Alfred-Wegener-Institut fuer Polar- und Meeresforschung, Bremerhaven (Germany); Storch, H. von [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

    2000-07-01

    A dynamical downscaling for the North Sea is presented. The numerical model used for the study is the coupled ice-ocean model OPYC. In a hindcast of the years 1979 to 1993 it was forced with atmospheric forcing of the ECMWF reanalysis. The models capability in simulating the observed mean state and variability in the North Sea is demonstrated by the hindcast. Two time scale ranges, from weekly to seasonal and the longer-than-seasonal time scales are investigated. Shorter time scales, for storm surges, are not captured by the model formulation. The main modes of variability of sea level, sea-surface circulation, sea-surface temperature, and sea-surface salinity are described and connections to atmospheric phenomena, like the NAO, are discussed. T106 ''time-slice'' simulations with a ''2 x CO{sub 2}'' horizon are used to estimate the effects of a changing climate on the shelf sea ''North Sea''. The ''2 x CO{sub 2}'' changes in the surface forcing are accompanied by changes in the lateral oceanic boundary conditions taken from a global coupled climate model. For ''2 x CO{sub 2}'' the time mean sea level increases up to 25 cm in the German Bight in the winter, where 15 cm are due to the surface forcing and 10 cm due to thermal expansion. This change is compared to the ''natural'' variability as simulated in the ECMWF integration and found to be not outside the range spanned by it. The variability of sea level on the weekly-to-seasonal time-scales is significantly reduced in the scenario integration. The variability on the longer-than-seasonal time-scales in the control and scenario runs is much smaller then in the ECMWF integration. This is traced back to the use of ''time-slice'' experiments. Discriminating between locally forced changes and changes induced at the lateral oceanic boundaries of the model in the circulation and

  13. Regional climate change scenarios

    International Nuclear Information System (INIS)

    Somot, S.

    2005-01-01

    Because studies of the regional impact of climate change need higher spatial resolution than that obtained in standard global climate change scenarios, developing regional scenarios from models is a crucial goal for the climate modelling community. The zoom capacity of ARPEGE-Climat, the Meteo-France climate model, allows use of scenarios with a horizontal resolution of about 50 km over France and the Mediterranean basin. An IPCC-A2 scenario for the end of the 21. century in France shows higher temperatures in each season and more winter and less summer precipitation than now. Tuning the modelled statistical distributions to observed temperature and precipitation allows us to study changes in the frequency of extreme events between today's climate and that at the end of century. The frequency of very hot days in summer will increase. In particular, the frequency of days with a maximum temperature above 35 deg C will be multiplied by a factor of 10, on average. In our scenario, the Toulouse area and Provence might see one quarter of their summer days with a maximum temperature above 35 deg C. (author)

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

    Science.gov (United States)

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

    2016-01-01

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

  15. A Statistical Model for Regional Tornado Climate Studies.

    Directory of Open Access Journals (Sweden)

    Thomas H Jagger

    Full Text Available Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA. A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.

  16. A Statistical Model for Regional Tornado Climate Studies.

    Science.gov (United States)

    Jagger, Thomas H; Elsner, James B; Widen, Holly M

    2015-01-01

    Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA). A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.

  17. Determination of clouds in MSG data for the validation of clouds in a regional climate model

    OpenAIRE

    Huckle, Roger

    2009-01-01

    Regional climate models (e.g. CLM) can help to asses the influence of the antropogenic climate change on the different regions of the earth. Validation of these models is very important. Satellite data are of great benefit, as data on a global scale and high temporal resolution is available. In this thesis a cloud detection and object based cloud classification for Meteosat Second Generation (MSG) was developed and used to validate CLM clouds. Results show sometimes too many clouds in the CLM.

  18. Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models

    Science.gov (United States)

    Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby

    2018-06-01

    The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices.

  19. Intercomparison of four regional climate models for the German State of Saxonia

    Science.gov (United States)

    Kreienkamp, F.; Spekat, A.; Enke, W.

    2009-09-01

    Results from four regional climate models which focus on Central Europe are presented: CCLM, the climate version of the German Weather Service's Local Model - REMO, the regional dynamic model from the Max Planck Institute for Meteorology in Hamburg - STAR, the statistical model developed at the PIK Potsdam Institute and WETTREG, the statistic-dynamic model developed by the company CEC Potsdam. For the area of the German State of Saxonia a host of properties and indicators were analyzed aiming to show the models' abilities to reconstruct the current climate and compare climate model scenarios. These include a group of thermal indicators, such as the number of ice, frost, summer and hot days, the number of tropical nights; then there are hydrometeorological indicators such as the exceedance of low and high precipitation thresholds; humidity, cloudiness and wind indicators complement the array. A selection of them showing similarities and differences of the models investigated will be presented.

  20. Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions

    Science.gov (United States)

    Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier

    2015-04-01

    At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community.

  1. Alpine snow cover in a changing climate: a regional climate model perspective

    Science.gov (United States)

    Steger, Christian; Kotlarski, Sven; Jonas, Tobias; Schär, Christoph

    2013-08-01

    An analysis is presented of an ensemble of regional climate model (RCM) experiments from the ENSEMBLES project in terms of mean winter snow water equivalent (SWE), the seasonal evolution of snow cover, and the duration of the continuous snow cover season in the European Alps. Two sets of simulations are considered, one driven by GCMs assuming the SRES A1B greenhouse gas scenario for the period 1951-2099, and the other by the ERA-40 reanalysis for the recent past. The simulated SWE for Switzerland for the winters 1971-2000 is validated against an observational data set derived from daily snow depth measurements. Model validation shows that the RCMs are capable of simulating the general spatial and seasonal variability of Alpine snow cover, but generally underestimate snow at elevations below 1,000 m and overestimate snow above 1,500 m. Model biases in snow cover can partly be related to biases in the atmospheric forcing. The analysis of climate projections for the twenty first century reveals high inter-model agreement on the following points: The strongest relative reduction in winter mean SWE is found below 1,500 m, amounting to 40-80 % by mid century relative to 1971-2000 and depending upon the model considered. At these elevations, mean winter temperatures are close to the melting point. At higher elevations the decrease of mean winter SWE is less pronounced but still a robust feature. For instance, at elevations of 2,000-2,500 m, SWE reductions amount to 10-60 % by mid century and to 30-80 % by the end of the century. The duration of the continuous snow cover season shows an asymmetric reduction with strongest shortening in springtime when ablation is the dominant factor for changes in SWE. We also find a substantial ensemble-mean reduction of snow reliability relevant to winter tourism at elevations below about 1,800 m by mid century, and at elevations below about 2,000 m by the end of the century.

  2. Representation of aerosol particles and associated transport pathways in regional climate modelling in Africa

    CSIR Research Space (South Africa)

    Garland, Rebecca M

    2016-11-01

    Full Text Available Aerosol particles can have large impacts on air quality and on the climate system. Regional climate models for Africa have not been well-tested and validated for their representation and simulation of aerosol particles. This study aimed to validate...

  3. Examining Interior Grid Nudging Techniques Using Two-Way Nesting in the WRF Model for Regional Climate Modeling

    Science.gov (United States)

    This study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP–Department of Energy Atmospheric Model Intercomparison Pro...

  4. Climate change impact on shallow groundwater conditions in Hungary: Conclusions from a regional modelling study

    Science.gov (United States)

    Kovács, Attila; Marton, Annamária; Tóth, György; Szöcs, Teodóra

    2016-04-01

    A quantitative methodology has been developed for the calculation of groundwater table based on measured and simulated climate parameters. The aim of the study was to develop a toolset which can be used for the calculation of shallow groundwater conditions for various climate scenarios. This was done with the goal of facilitating the assessment of climate impact and vulnerability of shallow groundwater resources. The simulated groundwater table distributions are representative of groundwater conditions at the regional scale. The introduced methodology is valid for modelling purposes at various scales and thus represents a versatile tool for the assessment of climate vulnerability of shallow groundwater bodies. The calculation modules include the following: 1. A toolset to calculate climate zonation from climate parameter grids, 2. Delineation of recharge zones (Hydrological Response Units, HRUs) based on geology, landuse and slope conditions, 3. Calculation of percolation (recharge) rates using 1D analytical hydrological models, 4. Simulation of the groundwater table using numerical groundwater flow models. The applied methodology provides a quantitative link between climate conditions and shallow groundwater conditions, and thus can be used for assessing climate impacts. The climate data source applied in our calculation comprised interpolated daily climate data of the Central European CARPATCLIM database. Climate zones were determined making use of the Thorntwaite climate zonation scheme. Recharge zones (HRUs) were determined based on surface geology, landuse and slope conditions. The HELP hydrological model was used for the calculation of 1D water balance for hydrological response units. The MODFLOW numerical groundwater modelling code was used for the calculation of the water table. The developed methodology was demonstrated through the simulation of regional groundwater table using spatially averaged climate data and hydrogeological properties for various time

  5. Variability of effects of spatial climate data aggregation on regional yield simulation by crop models

    NARCIS (Netherlands)

    Hoffmann, H.; Zhao, G.; Bussel, van L.G.J.

    2015-01-01

    Field-scale crop models are often applied at spatial resolutions coarser than that of the arable field. However, little is known about the response of the models to spatially aggregated climate input data and why these responses can differ across models. Depending on the model, regional yield

  6. Towards a regional climate model coupled to a comprehensive hydrological model

    Science.gov (United States)

    Rasmussen, S. H.; Drews, M.; Christensen, J. H.; Butts, M. B.; Jensen, K. H.; Refsgaard, J.; Hydrological ModellingAssessing Climate Change Impacts At Different Scales (Hyacints)

    2010-12-01

    When planing new ground water abstractions wells, building areas, roads or other land use activities information about expected future groundwater table location for the lifetime of the construction may be critical. The life time of an abstraction well can be expected to be more than 50 years, while if for buildings may be up to 100 years or more. The construction of an abstraction well is expensive and it is important to know if clean groundwater is available for its expected life time. The future groundwater table is depending on the future climate. With climate change the hydrology is expected to change as well. Traditionally, this assessment has been done by driving hydrological models with output from a climate model. In this way feedback between the groundwater hydrology and the climate is neglected. Neglecting this feedback can lead to imprecise or wrong results. The goal of this work is to couple the regional climate model HIRHAM (Christensen et al. 2006) to the hydrological model MIKE SHE (Graham and Butts, 2006). The coupling exploits the new OpenMI technology that provides a standardized interface to define, describe and transfer data on a time step basis between software components that run simultaneously (Gregersen et al., 2007). HIRHAM runs on a UNIX platform whereas MIKE SHE and OpenMI are under WINDOWS. Therefore the first critical task has been to develop an effective communication link between the platforms. The first step towards assessing the coupled models performance are addressed by looking at simulated land-surface atmosphere feedback through variables such as evapotranspiration, sensible heat flux and soil moisture content. Christensen, O.B., Drews, M., Christensen, J.H., Dethloff, K., Ketelsen, K., Hebestadt, I. and Rinke, A. (2006) The HIRHAM Regional Climate Model. Version 5; DMI Scientific Report 0617. Danish Meteorological Institute. Graham, D.N. and Butts, M.B. (2005) Flexible, integrated watershed modelling with MIKE SHE, In

  7. Regional climate models' performance in representing precipitation and temperature over selected Mediterranean areas

    Directory of Open Access Journals (Sweden)

    R. Deidda

    2013-12-01

    Full Text Available This paper discusses the relative performance of several climate models in providing reliable forcing for hydrological modeling in six representative catchments in the Mediterranean region. We consider 14 Regional Climate Models (RCMs, from the EU-FP6 ENSEMBLES project, run for the A1B emission scenario on a common 0.22° (about 24 km rotated grid over Europe and the Mediterranean region. In the validation period (1951 to 2010 we consider daily precipitation and surface temperatures from the observed data fields (E-OBS data set, available from the ENSEMBLES project and the data providers in the ECA&D project. Our primary objective is to rank the 14 RCMs for each catchment and select the four best-performing ones to use as common forcing for hydrological models in the six Mediterranean basins considered in the EU-FP7 CLIMB project. Using a common suite of four RCMs for all studied catchments reduces the (epistemic uncertainty when evaluating trends and climate change impacts in the 21st century. We present and discuss the validation setting, as well as the obtained results and, in some detail, the difficulties we experienced when processing the data. In doing so we also provide useful information and advice for researchers not directly involved in climate modeling, but interested in the use of climate model outputs for hydrological modeling and, more generally, climate change impact studies in the Mediterranean region.

  8. Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

    Directory of Open Access Journals (Sweden)

    Dmitry V. Sein

    2014-07-01

    Full Text Available The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis. Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the

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

    Science.gov (United States)

    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

  10. Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

    Science.gov (United States)

    Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

    2018-04-01

    The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

  11. An intercomparison of regional climate model data for hydrological impact studies in Denmark

    DEFF Research Database (Denmark)

    Van Roosmalen, Lieke Petronella G; Christensen, Jens Hesselbjerg; Butts, Michael

    2010-01-01

    The use of high-resolution regional climate models (RCM) to examine the hydrological impacts of climate change has grown significantly in recent years due to the improved representation of the local climate. However, the application is not straightforward because most RCMs are subject to consider......The use of high-resolution regional climate models (RCM) to examine the hydrological impacts of climate change has grown significantly in recent years due to the improved representation of the local climate. However, the application is not straightforward because most RCMs are subject...... to considerable systematic errors. In this study, projected climate change data from the RCM HIRHAM4 are used to generate climate scenario time series of precipitation, temperature, and reference evapotranspiration for the period 2071-2100 for hydrological impact assessments in Denmark. RCM output for the present......-day period (1961-1990) are compared to an observational data set, with precipitation corrected for undercatch and wetting losses, to quantify systematic model errors. A delta change method is applied to cope with these biases. A question arises as to how variable the climate change signals are...

  12. Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

    Science.gov (United States)

    Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

    2017-12-01

    Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land

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

    Science.gov (United States)

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

    2012-12-01

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

  14. Regional greenhouse climate effects

    International Nuclear Information System (INIS)

    Hansen, J.; Rind, D.; Delgenio, A.; Lacis, A.; Lebedeff, S.; Prather, M.; Ruedy, R.; Karl, T.

    1990-01-01

    The authors discuss the impact of an increasing greenhouse effect on three aspects of regional climate: droughts, storms and temperature. A continuous of current growth rates of greenhouse gases causes an increase in the frequency and severity of droughts in their climate model simulations, with the greatest impacts in broad regions of the subtropics and middle latitudes. But the greenhouse effect enhances both ends of the hydrologic cycle in the model, that is, there is an increased frequency of extreme wet situations, as well as increased drought. Model results are shown to imply that increased greenhouse warming will lead to more intense thunderstorms, that is, deeper thunderstorms with greater rainfall. Emanual has shown that the model results also imply that the greenhouse warming leads to more destructive tropical cyclones. The authors present updated records of observed temperatures and show that the observations and model results, averaged over the globe and over the US, are generally consistent. The impacts of simulated climate changes on droughts, storms and temperature provide no evidence that there will be regional winners if greenhouse gases continue to increase rapidly

  15. High-resolution regional climate model evaluation using variable-resolution CESM over California

    Science.gov (United States)

    Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

    2015-12-01

    Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine

  16. Wildfire potential evaluation during a drought event with a regional climate model and NDVI

    Science.gov (United States)

    Y. Liu; J. Stanturf; S. Goodrick

    2010-01-01

    Regional climate modeling is a technique for simulating high-resolution physical processes in the atmosphere, soil and vegetation. It can be used to evaluate wildfire potential by either providing meteorological conditions for computation of fire indices or predicting soil moisture as a direct measure of fire potential. This study examines these roles using a regional...

  17. Mixed precipitation occurrences over southern Québec, Canada, under warmer climate conditions using a regional climate model

    Science.gov (United States)

    Matte, Dominic; Thériault, Julie M.; Laprise, René

    2018-05-01

    Winter weather events with temperatures near 0°C are often associated with freezing rain. They can have major impacts on the society by causing power outages and disruptions to the transportation networks. Despite the catastrophic consequences of freezing rain, very few studies have investigated how their occurrences could evolve under climate change. This study aims to investigate the change of freezing rain and ice pellets over southern Québec using regional climate modeling at high resolution. The fifth-generation Canadian Regional Climate Model with climate scenario RCP 8.5 at 0.11° grid mesh was used. The precipitation types such as freezing rain, ice pellets or their combination are diagnosed using five methods (Cantin and Bachand, Bourgouin, Ramer, Czys and, Baldwin). The occurrences of the diagnosed precipitation types for the recent past (1980-2009) are found to be comparable to observations. The projections for the future scenario (2070-2099) suggested a general decrease in the occurrences of mixed precipitation over southern Québec from October to April. This is mainly due to a decrease in long-duration events (≥6 h ). Overall, this study contributes to better understand how the distribution of freezing rain and ice pellets might change in the future using high-resolution regional climate model.

  18. A multi-model assessment of regional climate disparities caused by solar geoengineering

    International Nuclear Information System (INIS)

    Kravitz, Ben; Rasch, Philip J; Singh, Balwinder; Yoon, Jin-Ho; MacMartin, Douglas G; Robock, Alan; Ricke, Katharine L; Cole, Jason N S; Curry, Charles L; Irvine, Peter J; Ji, Duoying; Moore, John C; Keith, David W; Egill Kristjánsson, Jón; Muri, Helene; Tilmes, Simone; Watanabe, Shingo; Yang, Shuting

    2014-01-01

    Global-scale solar geoengineering is the deliberate modification of the climate system to offset some amount of anthropogenic climate change by reducing the amount of incident solar radiation at the surface. These changes to the planetary energy budget result in differential regional climate effects. For the first time, we quantitatively evaluate the potential for regional disparities in a multi-model context using results from a model experiment that offsets the forcing from a quadrupling of CO 2 via reduction in solar irradiance. We evaluate temperature and precipitation changes in 22 geographic regions spanning most of Earth's continental area. Moderate amounts of solar reduction (up to 85% of the amount that returns global mean temperatures to preindustrial levels) result in regional temperature values that are closer to preindustrial levels than an un-geoengineered, high CO 2 world for all regions and all models. However, in all but one model, there is at least one region for which no amount of solar reduction can restore precipitation toward its preindustrial value. For most metrics considering simultaneous changes in both variables, temperature and precipitation values in all regions are closer to the preindustrial climate for a moderate amount of solar reduction than for no solar reduction. (letter)

  19. A review on vegetation models and applicability to climate simulations at regional scale

    Science.gov (United States)

    Myoung, Boksoon; Choi, Yong-Sang; Park, Seon Ki

    2011-11-01

    The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson's rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.

  20. A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

    Science.gov (United States)

    Rummukainen, M.; Räisänen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willén, U.; Hansson, U.; Jones, C.

    This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results.

  1. A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

    Energy Technology Data Exchange (ETDEWEB)

    Rummukainen, M.; Raeisaenen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willen, U.; Hansson, U.; Jones, C. [Rossby Centre, Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden)

    2001-03-01

    This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results. (orig.)

  2. Medicanes in an ocean-atmosphere coupled regional climate model

    Science.gov (United States)

    Akhtar, N.; Brauch, J.; Dobler, A.; Béranger, K.; Ahrens, B.

    2014-08-01

    So-called medicanes (Mediterranean hurricanes) are meso-scale, marine, and warm-core Mediterranean cyclones that exhibit some similarities to tropical cyclones. The strong cyclonic winds associated with medicanes threaten the highly populated coastal areas around the Mediterranean basin. To reduce the risk of casualties and overall negative impacts, it is important to improve the understanding of medicanes with the use of numerical models. In this study, we employ an atmospheric limited-area model (COSMO-CLM) coupled with a one-dimensional ocean model (1-D NEMO-MED12) to simulate medicanes. The aim of this study is to assess the robustness of the coupled model in simulating these extreme events. For this purpose, 11 historical medicane events are simulated using the atmosphere-only model, COSMO-CLM, and coupled model, with different setups (horizontal atmospheric grid spacings of 0.44, 0.22, and 0.08°; with/without spectral nudging, and an ocean grid spacing of 1/12°). The results show that at high resolution, the coupled model is able to not only simulate most of medicane events but also improve the track length, core temperature, and wind speed of simulated medicanes compared to the atmosphere-only simulations. The results suggest that the coupled model is more proficient for systemic and detailed studies of historical medicane events, and that this model can be an effective tool for future projections.

  3. Application of regional climate models to the Indian winter monsoon over the western Himalayas.

    Science.gov (United States)

    Dimri, A P; Yasunari, T; Wiltshire, A; Kumar, P; Mathison, C; Ridley, J; Jacob, D

    2013-12-01

    The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid-solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. Implications of regional improvement in global climate models for agricultural impact research

    International Nuclear Information System (INIS)

    Ramirez-Villegas, Julian; Thornton, Philip K; Jarvis, Andy; Challinor, Andrew J

    2013-01-01

    Global climate models (GCMs) have become increasingly important for climate change science and provide the basis for most impact studies. Since impact models are highly sensitive to input climate data, GCM skill is crucial for getting better short-, medium- and long-term outlooks for agricultural production and food security. The Coupled Model Intercomparison Project (CMIP) phase 5 ensemble is likely to underpin the majority of climate impact assessments over the next few years. We assess 24 CMIP3 and 26 CMIP5 simulations of present climate against climate observations for five tropical regions, as well as regional improvements in model skill and, through literature review, the sensitivities of impact estimates to model error. Climatological means of seasonal mean temperatures depict mean errors between 1 and 18 ° C (2–130% with respect to mean), whereas seasonal precipitation and wet-day frequency depict larger errors, often offsetting observed means and variability beyond 100%. Simulated interannual climate variability in GCMs warrants particular attention, given that no single GCM matches observations in more than 30% of the areas for monthly precipitation and wet-day frequency, 50% for diurnal range and 70% for mean temperatures. We report improvements in mean climate skill of 5–15% for climatological mean temperatures, 3–5% for diurnal range and 1–2% in precipitation. At these improvement rates, we estimate that at least 5–30 years of CMIP work is required to improve regional temperature simulations and at least 30–50 years for precipitation simulations, for these to be directly input into impact models. We conclude with some recommendations for the use of CMIP5 in agricultural impact studies. (letter)

  5. A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges.

    Science.gov (United States)

    Prein, Andreas F; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P M; Leung, Ruby

    2015-06-01

    Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing 10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

  6. Quantifying uncertainty due to internal variability using high-resolution regional climate model simulations

    Science.gov (United States)

    Gutmann, E. D.; Ikeda, K.; Deser, C.; Rasmussen, R.; Clark, M. P.; Arnold, J. R.

    2015-12-01

    The uncertainty in future climate predictions is as large or larger than the mean climate change signal. As such, any predictions of future climate need to incorporate and quantify the sources of this uncertainty. One of the largest sources comes from the internal, chaotic, variability within the climate system itself. This variability has been approximated using the 30 ensemble members of the Community Earth System Model (CESM) large ensemble. Here we examine the wet and dry end members of this ensemble for cool-season precipitation in the Colorado Rocky Mountains with a set of high-resolution regional climate model simulations. We have used the Weather Research and Forecasting model (WRF) to simulate the periods 1990-2000, 2025-2035, and 2070-2080 on a 4km grid. These simulations show that the broad patterns of change depicted in CESM are inherited by the high-resolution simulations; however, the differences in the height and location of the mountains in the WRF simulation, relative to the CESM simulation, means that the location and magnitude of the precipitation changes are very different. We further show that high-resolution simulations with the Intermediate Complexity Atmospheric Research model (ICAR) predict a similar spatial pattern in the change signal as WRF for these ensemble members. We then use ICAR to examine the rest of the CESM Large Ensemble as well as the uncertainty in the regional climate model due to the choice of physics parameterizations.

  7. ARCAS (ACACIA Regional Climate-data Access System) -- a Web Access System for Climate Model Data Access, Visualization and Comparison

    Science.gov (United States)

    Hakkarinen, C.; Brown, D.; Callahan, J.; hankin, S.; de Koningh, M.; Middleton-Link, D.; Wigley, T.

    2001-05-01

    A Web-based access system to climate model output data sets for intercomparison and analysis has been produced, using the NOAA-PMEL developed Live Access Server software as host server and Ferret as the data serving and visualization engine. Called ARCAS ("ACACIA Regional Climate-data Access System"), and publicly accessible at http://dataserver.ucar.edu/arcas, the site currently serves climate model outputs from runs of the NCAR Climate System Model for the 21st century, for Business as Usual and Stabilization of Greenhouse Gas Emission scenarios. Users can select, download, and graphically display single variables or comparisons of two variables from either or both of the CSM model runs, averaged for monthly, seasonal, or annual time resolutions. The time length of the averaging period, and the geographical domain for download and display, are fully selectable by the user. A variety of arithmetic operations on the data variables can be computed "on-the-fly", as defined by the user. Expansions of the user-selectable options for defining analysis options, and for accessing other DOD-compatible ("Distributed Ocean Data System-compatible") data sets, residing at locations other than the NCAR hardware server on which ARCAS operates, are planned for this year. These expansions are designed to allow users quick and easy-to-operate web-based access to the largest possible selection of climate model output data sets available throughout the world.

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

    Science.gov (United States)

    Kara, Fatih; Yucel, Ismail

    2015-09-01

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

  9. The regional climate model as a tool for long-term planning of Quebec water resources

    International Nuclear Information System (INIS)

    Frigon, A.

    2008-01-01

    'Full text': In recent years, important progress has been made in downscaling GCM (Global Climate Model) projections to a resolution where hydrological studies become feasible. Climate change simulations performed with RCMs (Regional Climate Models) have reached a level of confidence that allows us to take advantage of this information in long-term planning of water resources. The RCMs' main advantage consist in their construction based on balanced land as well as atmosphere water and energy budgets, and on their inclusion of feedbacks between the surface and the atmosphere. Such models therefore generate sequences of weather events, providing long time series of hydro-climatic variables that are internally consistent, allowing the analysis of hydrologic regimes. At OURANOS, special attention is placed on the hydrological cycle, given its key role on socioeconomic activities. The Canadian Regional Climate Model (CRCM) was developed as a potential tool to provide climate projections at the watershed scale. Various analyses performed over small basins in Quebec provide information on the level of confidence we have in the CRCM for use in hydrological studies. Even though this approach is not free of uncertainty, it was found useful by some water resource managers and hence this information should be considered. One of the keys to retain usefulness, despite the associated uncertainties, is to make use of more than a single regional climate projection. This approach will allow for the evaluation of the climate change signal and its associated level of confidence. Such a methodology is already applied by Hydro-Quebec in the long-term planning of its water resources for hydroelectric generation over the Quebec territory. (author)

  10. Global and regional health effects of future food production under climate change: a modelling study.

    Science.gov (United States)

    Springmann, Marco; Mason-D'Croz, Daniel; Robinson, Sherman; Garnett, Tara; Godfray, H Charles J; Gollin, Douglas; Rayner, Mike; Ballon, Paola; Scarborough, Peter

    2016-05-07

    One of the most important consequences of climate change could be its effects on agriculture. Although much research has focused on questions of food security, less has been devoted to assessing the wider health impacts of future changes in agricultural production. In this modelling study, we estimate excess mortality attributable to agriculturally mediated changes in dietary and weight-related risk factors by cause of death for 155 world regions in the year 2050. For this modelling study, we linked a detailed agricultural modelling framework, the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT), to a comparative risk assessment of changes in fruit and vegetable consumption, red meat consumption, and bodyweight for deaths from coronary heart disease, stroke, cancer, and an aggregate of other causes. We calculated the change in the number of deaths attributable to climate-related changes in weight and diets for the combination of four emissions pathways (a high emissions pathway, two medium emissions pathways, and a low emissions pathway) and three socioeconomic pathways (sustainable development, middle of the road, and more fragmented development), which each included six scenarios with variable climatic inputs. The model projects that by 2050, climate change will lead to per-person reductions of 3·2% (SD 0·4%) in global food availability, 4·0% (0·7%) in fruit and vegetable consumption, and 0·7% (0·1%) in red meat consumption. These changes will be associated with 529,000 climate-related deaths worldwide (95% CI 314,000-736,000), representing a 28% (95% CI 26-33) reduction in the number of deaths that would be avoided because of changes in dietary and weight-related risk factors between 2010 and 2050. Twice as many climate-related deaths were associated with reductions in fruit and vegetable consumption than with climate-related increases in the prevalence of underweight, and most climate-related deaths were projected to

  11. Very high resolution regional climate model simulations over Greenland: Identifying added value

    DEFF Research Database (Denmark)

    Lucas-Picher, P.; Wulff-Nielsen, M.; Christensen, J.H.

    2012-01-01

    models. However, the bias between the simulations and the few available observations does not reduce with higher resolution. This is partly explained by the lack of observations in regions where the higher resolution is expected to improve the simulated climate. The RCM simulations show......This study presents two simulations of the climate over Greenland with the regional climate model (RCM) HIRHAM5 at 0.05° and 0.25° resolution driven at the lateral boundaries by the ERA-Interim reanalysis for the period 1989–2009. These simulations are validated against observations from...... that the temperature has increased the most in the northern part of Greenland and at lower elevations over the period 1989–2009. Higher resolution increases the relief variability in the model topography and causes the simulated precipitation to be larger on the coast and smaller over the main ice sheet compared...

  12. A comparative review of multi-risk modelling methodologies for climate change adaptation in mountain regions

    Science.gov (United States)

    Terzi, Stefano; Torresan, Silvia; Schneiderbauer, Stefan

    2017-04-01

    Keywords: Climate change, mountain regions, multi-risk assessment, climate change adaptation. Climate change has already led to a wide range of impacts on the environment, the economy and society. Adaptation actions are needed to cope with the impacts that have already occurred (e.g. storms, glaciers melting, floods, droughts) and to prepare for future scenarios of climate change. Mountain environment is particularly vulnerable to the climate changes due to its exposure to recent climate warming (e.g. water regime changes, thawing of permafrost) and due to the high degree of specialization of both natural and human systems (e.g. alpine species, valley population density, tourism-based economy). As a consequence, the mountain local governments are encouraged to undertake territorial governance policies to climate change, considering multi-risks and opportunities for the mountain economy and identifying the best portfolio of adaptation strategies. This study aims to provide a literature review of available qualitative and quantitative tools, methodological guidelines and best practices to conduct multi-risk assessments in the mountain environment within the context of climate change. We analyzed multi-risk modelling and assessment methods applied in alpine regions (e.g. event trees, Bayesian Networks, Agent Based Models) in order to identify key concepts (exposure, resilience, vulnerability, risk, adaptive capacity), climatic drivers, cause-effect relationships and socio-ecological systems to be integrated in a comprehensive framework. The main outcomes of the review, including a comparison of existing techniques based on different criteria (e.g. scale of analysis, targeted questions, level of complexity) and a snapshot of the developed multi-risk framework for climate change adaptation will be here presented and discussed.

  13. Regional climate model downscaling may improve the prediction of alien plant species distributions

    Science.gov (United States)

    Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

    2014-12-01

    Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

  14. Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

    Science.gov (United States)

    Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

    2013-01-01

    Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

  15. Bayesian hierarchical models for regional climate reconstructions of the last glacial maximum

    Science.gov (United States)

    Weitzel, Nils; Hense, Andreas; Ohlwein, Christian

    2017-04-01

    Spatio-temporal reconstructions of past climate are important for the understanding of the long term behavior of the climate system and the sensitivity to forcing changes. Unfortunately, they are subject to large uncertainties, have to deal with a complex proxy-climate structure, and a physically reasonable interpolation between the sparse proxy observations is difficult. Bayesian Hierarchical Models (BHMs) are a class of statistical models that is well suited for spatio-temporal reconstructions of past climate because they permit the inclusion of multiple sources of information (e.g. records from different proxy types, uncertain age information, output from climate simulations) and quantify uncertainties in a statistically rigorous way. BHMs in paleoclimatology typically consist of three stages which are modeled individually and are combined using Bayesian inference techniques. The data stage models the proxy-climate relation (often named transfer function), the process stage models the spatio-temporal distribution of the climate variables of interest, and the prior stage consists of prior distributions of the model parameters. For our BHMs, we translate well-known proxy-climate transfer functions for pollen to a Bayesian framework. In addition, we can include Gaussian distributed local climate information from preprocessed proxy records. The process stage combines physically reasonable spatial structures from prior distributions with proxy records which leads to a multivariate posterior probability distribution for the reconstructed climate variables. The prior distributions that constrain the possible spatial structure of the climate variables are calculated from climate simulation output. We present results from pseudoproxy tests as well as new regional reconstructions of temperatures for the last glacial maximum (LGM, ˜ 21,000 years BP). These reconstructions combine proxy data syntheses with information from climate simulations for the LGM that were

  16. Nudging and predictability in regional climate modelling: investigation in a nested quasi-geostrophic model

    Science.gov (United States)

    Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

    2010-05-01

    In this work, we consider the effect of indiscriminate and spectral nudging on the large and small scales of an idealized model simulation. The model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by the « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. The effect of large-scale nudging is studied by using the "perfect model" approach. Two sets of experiments are performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic Limited Area Model (LAM) where the size of the LAM domain comes into play in addition to the first set of simulations. The study shows that the indiscriminate nudging time that minimizes the error at both the large and small scales is reached for a nudging time close to the predictability time, for spectral nudging, the optimum nudging time should tend to zero since the best large scale dynamics is supposed to be given by the driving large-scale fields are generally given at much lower frequency than the model time step(e,g, 6-hourly analysis) with a basic interpolation between the fields, the optimum nudging time differs from zero, however remaining smaller than the predictability time.

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

    Science.gov (United States)

    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. Copyright © 2016. Published by Elsevier B.V.

  18. Description and evaluation of the Earth System Regional Climate Model (RegCM-ES)

    Science.gov (United States)

    Farneti, Riccardo; Sitz, Lina; Di Sante, Fabio; Fuentes-Franco, Ramon; Coppola, Erika; Mariotti, Laura; Reale, Marco; Sannino, Gianmaria; Barreiro, Marcelo; Nogherotto, Rita; Giuliani, Graziano; Graffino, Giorgio; Solidoro, Cosimo; Giorgi, Filippo

    2017-04-01

    The increasing availability of satellite remote sensing data, of high temporal frequency and spatial resolution, has provided a new and enhanced view of the global ocean and atmosphere, revealing strong air-sea coupling processes throughout the ocean basins. In order to obtain an accurate representation and better understanding of the climate system, its variability and change, the inclusion of all mechanisms of interaction among the different sub-components, at high temporal and spatial resolution, becomes ever more desirable. Recently, global coupled models have been able to progressively refine their horizontal resolution to attempt to resolve smaller-scale processes. However, regional coupled ocean-atmosphere models can achieve even finer resolutions and provide additional information on the mechanisms of air-sea interactions and feedbacks. Here we describe a new, state-of-the-art, Earth System Regional Climate Model (RegCM-ES). RegCM-ES presently includes the coupling between atmosphere, ocean, land surface and sea-ice components, as well as an hydrological and ocean biogeochemistry model. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains. RegCM-ES has shown improvements in the representation of precipitation and SST fields over the tested domains, as well as realistic representations of coupled air-sea processes and interactions. The RegCM-ES model, which can be easily implemented over any regional domain of interest, is open source making it suitable for usage by the large scientific community.

  19. Preliminary evaluation of techniques for transforming regional climate model output to the potential repository site in support of Yucca Mountain future climate synthesis

    International Nuclear Information System (INIS)

    Church, H.W.; Zak, B.D.; Behl, Y.K.

    1995-06-01

    The report describes a preliminary evaluation of models for transforming regional climate model output from a regional to a local scale for the Yucca Mountain area. Evaluation and analysis of both empirical and numerical modeling are discussed which is aimed at providing site-specific, climate-based information for use by interfacing activities. Two semiempirical approaches are recommended for further analysis

  20. Simulated trends of extreme climate indices for the Carpathian basin using outputs of different regional climate models

    Science.gov (United States)

    Pongracz, R.; Bartholy, J.; Szabo, P.; Pieczka, I.; Torma, C. S.

    2009-04-01

    Regional climatological effects of global warming may be recognized not only in shifts of mean temperature and precipitation, but in the frequency or intensity changes of different climate extremes. Several climate extreme indices are analyzed and compared for the Carpathian basin (located in Central/Eastern Europe) following the guidelines suggested by the joint WMO-CCl/CLIVAR Working Group on climate change detection. Our statistical trend analysis includes the evaluation of several extreme temperature and precipitation indices, e.g., the numbers of severe cold days, winter days, frost days, cold days, warm days, summer days, hot days, extremely hot days, cold nights, warm nights, the intra-annual extreme temperature range, the heat wave duration, the growing season length, the number of wet days (using several threshold values defining extremes), the maximum number of consecutive dry days, the highest 1-day precipitation amount, the greatest 5-day rainfall total, the annual fraction due to extreme precipitation events, etc. In order to evaluate the future trends (2071-2100) in the Carpathian basin, daily values of meteorological variables are obtained from the outputs of various regional climate model (RCM) experiments accomplished in the frame of the completed EU-project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). Horizontal resolution of the applied RCMs is 50 km. Both scenarios A2 and B2 are used to compare past and future trends of the extreme climate indices for the Carpathian basin. Furthermore, fine-resolution climate experiments of two additional RCMs adapted and run at the Department of Meteorology, Eotvos Lorand University are used to extend the trend analysis of climate extremes for the Carpathian basin. (1) Model PRECIS (run at 25 km horizontal resolution) was developed at the UK Met Office, Hadley Centre, and it uses the boundary conditions from the HadCM3 GCM. (2) Model Reg

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

    Science.gov (United States)

    Horton, Radley M.

    Climate variability has large impacts on humans and their agricultural systems. Farmers are at the center of this agricultural network, but it is often agricultural planners---regional planners, extension agents, commodity groups and cooperatives---that translate climate information for users. Global climate models (GCMs) are a leading tool for understanding and predicting climate and climate change. Armed with climate projections and forecasts, agricultural planners adapt their decision-making to optimize outcomes. This thesis explores what GCMs can, and cannot, tell us about climate variability and change at regional scales. The question is important, since high-quality regional climate projections could assist farmers and regional planners in key management decisions, contributing to better agricultural outcomes. To answer these questions, climate variability and its regional impacts are explored in observations and models for the current and future climate. The goals are to identify impacts of observed variability, assess model simulation of variability, and explore how climate variability and its impacts may change under enhanced greenhouse warming. Chapter One explores how well Goddard Institute for Space Studies (GISS) atmospheric models, forced by historical sea surface temperatures (SST), simulate climatology and large-scale features during the exceptionally strong 1997--1999 El Nino Southern Oscillation (ENSO) cycle. Reasonable performance in this 'proof of concept' test is considered a minimum requirement for further study of variability in models. All model versions produce appropriate local changes with ENSO, indicating that with correct ocean temperatures these versions are capable of simulating the large-scale effects of ENSO around the globe. A high vertical resolution model (VHR) provides the best simulation. Evidence is also presented that SST anomalies outside the tropical Pacific may play a key role in generating remote teleconnections even

  2. Greenland ice sheet surface mass balance: evaluating simulations and making projections with regional climate models

    NARCIS (Netherlands)

    Rae, J.G.L.; Aðalgeirsdóttir, G.; Edwards, T.L.; Fettweis, X.; Gregory, J.M.; Hewitt, H.T.; Lowe, J.A.; Lucas-Picher, P.; Mottram, R.H.; Payne, A.J.; Ridley, J.K.; Shannon, S.R.; van de Berg, W.J.; van de Wal, R.S.W.; van den Broeke, M.R.

    2012-01-01

    Four high-resolution regional climate models (RCMs) have been set up for the area of Greenland, with the aim of providing future projections of Greenland ice sheet surface mass balance (SMB), and its contribution to sea level rise, with greater accuracy than is possible from coarser-resolution

  3. Impact of Desiccation of Aral Sea on the Regional Climate of Central Asia Using WRF Model

    Science.gov (United States)

    Sharma, Ashish; Huang, Huei-Ping; Zavialov, Peter; Khan, Valentina

    2018-01-01

    This study explores the impacts of the desiccation of the Aral Sea and large-scale climate change on the regional climate of Central Asia in the post-1960 era. A series of climate downscaling experiments for the 1960's and 2000's decades were performed using the Weather Research and Forecast model at 12-km horizontal resolution. To quantify the impacts of the changing surface boundary condition, a set of simulations with an identical lateral boundary condition but different extents of the Aral Sea were performed. It was found that the desiccation of the Aral Sea leads to more snow (and less rain) as desiccated winter surface is relatively much colder than water surface. In summer, desiccation led to substantial warming over the Aral Sea. These impacts were largely confined to within the area covered by the former Aral Sea and its immediate vicinity, although desiccation of the Sea also led to minor cooling over the greater Central Asia in winter. A contrasting set of simulations with an identical surface boundary condition but different lateral boundary conditions produced more identifiable changes in regional climate over the greater Central Asia which was characterized by a warming trend in both winter and summer. Simulations also showed that while the desiccation of the Aral Sea has significant impacts on the local climate over the Sea, the climate over the greater Central Asia on inter-decadal time scale was more strongly influenced by the continental or global-scale climate change on that time scale.

  4. Climatic features of the Red Sea from a regional assimilative model

    KAUST Repository

    Viswanadhapalli, Yesubabu

    2016-08-16

    The Advanced Research version of Weather Research and Forecasting (WRF-ARW) model was used to generate a downscaled, 10-km resolution regional climate dataset over the Red Sea and adjacent region. The model simulations are performed based on two, two-way nested domains of 30- and 10-km resolutions assimilating all conventional observations using a cyclic three-dimensional variational approach over an initial 12-h period. The improved initial conditions are then used to generate regional climate products for the following 24 h. We combined the resulting daily 24-h datasets to construct a 15-year Red Sea atmospheric downscaled product from 2000 to 2014. This 15-year downscaled dataset is evaluated via comparisons with various in situ and gridded datasets. Our analysis indicates that the assimilated model successfully reproduced the spatial and temporal variability of temperature, wind, rainfall, relative humidity and sea level pressure over the Red Sea region. The model also efficiently simulated the seasonal and monthly variability of wind patterns, the Red Sea Convergence Zone and associated rainfall. Our results suggest that dynamical downscaling and assimilation of available observations improve the representation of regional atmospheric features over the Red Sea compared to global analysis data from the National Centers for Environmental Prediction. We use the dataset to describe the atmospheric climatic conditions over the Red Sea region. © 2016 Royal Meteorological Society.

  5. Modeling climate change impacts on overwintering of Spodoptera exigua Hübner in regions of China

    Directory of Open Access Journals (Sweden)

    Xia-Lin Zheng

    2015-09-01

    Full Text Available Inferential models are usually used to evaluate the effect of winter warming on range expansion of insects. Generally, correlative approaches used to predict changes in the distributions of organisms are based on the assumption that climatic boundaries are fixed. Spodoptera exigua Htibner (Lepidoptera: Noctuidae overwinters as larvae or pupae in China regions. To understand the climate change impacts on overwintering of this species in regions of China, CLIMEX and Arc-GIS models were used to predict possible changes of distribution based on temperature. The climate change projection clearly indicated that the northern boundary of overwintering for S. exigua will shift northward from current distribution. Thus, the ongoing winter warming is likely to increase the frequency of S. exigua outbreaks.

  6. Strategies for Teaching Regional Climate Modeling: Online Professional Development for Scientists and Decision Makers

    Science.gov (United States)

    Walton, P.; Yarker, M. B.; Mesquita, M. D. S.; Otto, F. E. L.

    2014-12-01

    There is a clear role for climate science in supporting decision making at a range of scales and in a range of contexts: from Global to local, from Policy to Industry. However, clear a role climate science can play, there is also a clear discrepancy in the understanding of how to use the science and associated tools (such as climate models). Despite there being a large body of literature on the science there is clearly a need to provide greater support in how to apply appropriately. However, access to high quality professional development courses can be problematic, due to geographic, financial and time constraints. In attempt to address this gap we independently developed two online professional courses that focused on helping participants use and apply two regional climate models, WRF and PRECIS. Both courses were designed to support participants' learning through tutor led programs that covered the basic climate scientific principles of regional climate modeling and how to apply model outputs. The fundamental differences between the two courses are: 1) the WRF modeling course expected participants to design their own research question that was then run on a version of the model, whereas 2) the PRECIS course concentrated on the principles of regional modeling and how the climate science informed the modeling process. The two courses were developed to utilise the cost and time management benefits associated with eLearning, with the recognition that this mode of teaching can also be accessed internationally, providing professional development courses in countries that may not be able to provide their own. The development teams saw it as critical that the courses reflected sound educational theory, to ensure that participants had the maximum opportunity to learn successfully. In particular, the role of reflection is central to both course structures to help participants make sense of the science in relation to their own situation. This paper details the different

  7. Regional climate models downscaling in the Alpine area with multimodel superensemble

    Directory of Open Access Journals (Sweden)

    D. Cane

    2013-05-01

    Full Text Available The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs, are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project, which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to

  8. Regional climate models downscaling in the Alpine area with multimodel superensemble

    Science.gov (United States)

    Cane, D.; Barbarino, S.; Renier, L. A.; Ronchi, C.

    2013-05-01

    The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs), are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs) runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project), which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present) were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the

  9. Forcing of a photochemical air quality model with atmospheric fields simulated by a regional climate model

    CSIR Research Space (South Africa)

    Naidoo, M

    2010-10-01

    Full Text Available to the enhanced greenhouse effect (e.g. Engelbrecht et al, 2009). Such changes are likely to influence the future transport and chemistry of air pollutants over the region. The complexity in which climate change may affect regional air quality is evident...

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

    Science.gov (United States)

    Tao, F.; Rötter, R.

    2013-12-01

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

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

    Science.gov (United States)

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

    2014-07-01

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

  12. Modelling the regional climate and isotopic composition of Svalbard precipitation using REMOiso

    DEFF Research Database (Denmark)

    Divine..[], D.V.; Sjolte, Jesper; Isaksson, E.

    2011-01-01

    Simulations of a regional (approx. 50 km resolution) circulation model REMOiso with embedded stable water isotope module covering the period 1958-2001 are compared with the two instrumental climate and four isotope series (d18O) from western Svalbard. We examine the data from ice cores drilled...... than summer. The simulated and measured Holtedahlfonna d18O series agree reasonably well, whereas no significant correlation has been observed between the modelled and measured Lomonosovfonna ice core isotopic series. It is shown that sporadic nature as well as variability in the amount inherent...... in reproducing the local climate. The model successfully captures the climate variations on the daily to multidecadal times scales although it tends to systematically underestimate the winter SAT. Analysis suggests that REMOiso performs better at simulating isotope compositions of precipitation in the winter...

  13. Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions

    Science.gov (United States)

    Santos, João A.; Malheiro, Aureliano C.; Karremann, Melanie K.; Pinto, Joaquim G.

    2011-03-01

    The impact of projected climate change on wine production was analysed for the Demarcated Region of Douro, Portugal. A statistical grapevine yield model (GYM) was developed using climate parameters as predictors. Statistically significant correlations were identified between annual yield and monthly mean temperatures and monthly precipitation totals during the growing cycle. These atmospheric factors control grapevine yield in the region, with the GYM explaining 50.4% of the total variance in the yield time series in recent decades. Anomalously high March rainfall (during budburst, shoot and inflorescence development) favours yield, as well as anomalously high temperatures and low precipitation amounts in May and June (May: flowering and June: berry development). The GYM was applied to a regional climate model output, which was shown to realistically reproduce the GYM predictors. Finally, using ensemble simulations under the A1B emission scenario, projections for GYM-derived yield in the Douro Region, and for the whole of the twenty-first century, were analysed. A slight upward trend in yield is projected to occur until about 2050, followed by a steep and continuous increase until the end of the twenty-first century, when yield is projected to be about 800 kg/ha above current values. While this estimate is based on meteorological parameters alone, changes due to elevated CO2 may further enhance this effect. In spite of the associated uncertainties, it can be stated that projected climate change may significantly benefit wine yield in the Douro Valley.

  14. Spectral nudging in regional climate modelling: How strongly should we nudge?

    OpenAIRE

    Omrani , Hiba; Drobinski , Philippe; Dubos , Thomas

    2012-01-01

    International audience; Spectral nudging is a technique consisting in driving regional climate models (RCMs) on selected spatial scales corresponding to those produced by the driving global circulation model (GCM). This technique prevents large and unrealistic departures between the GCM driving fields and the RCM fields at the GCM spatial scales. Theoretically, the relaxation of the RCM towards the GCM should be infinitely strong provided thre are perfect large-scale fields. In practice, the ...

  15. Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

    Science.gov (United States)

    Erfanian, A.; Fomenko, L.; Wang, G.

    2016-12-01

    Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

  16. Model Consistent Pseudo-Observations of Precipitation and Their Use for Bias Correcting Regional Climate Models

    Directory of Open Access Journals (Sweden)

    Peter Berg

    2015-01-01

    Full Text Available Lack of suitable observational data makes bias correction of high space and time resolution regional climate models (RCM problematic. We present a method to construct pseudo-observational precipitation data bymerging a large scale constrained RCMreanalysis downscaling simulation with coarse time and space resolution observations. The large scale constraint synchronizes the inner domain solution to the driving reanalysis model, such that the simulated weather is similar to observations on a monthly time scale. Monthly biases for each single month are corrected to the corresponding month of the observational data, and applied to the finer temporal resolution of the RCM. A low-pass filter is applied to the correction factors to retain the small spatial scale information of the RCM. The method is applied to a 12.5 km RCM simulation and proven successful in producing a reliable pseudo-observational data set. Furthermore, the constructed data set is applied as reference in a quantile mapping bias correction, and is proven skillful in retaining small scale information of the RCM, while still correcting the large scale spatial bias. The proposed method allows bias correction of high resolution model simulations without changing the fine scale spatial features, i.e., retaining the very information required by many impact models.

  17. Modelling regional cropping patterns under scenarios of climate and socio-economic change in Hungary.

    Science.gov (United States)

    Li, Sen; Juhász-Horváth, Linda; Pintér, László; Rounsevell, Mark D A; Harrison, Paula A

    2018-05-01

    Impacts of socio-economic, political and climatic change on agricultural land systems are inherently uncertain. The role of regional and local-level actors is critical in developing effective policy responses that accommodate such uncertainty in a flexible and informed way across governance levels. This study identified potential regional challenges in arable land use systems, which may arise from climate and socio-economic change for two counties in western Hungary: Veszprém and Tolna. An empirically-grounded, agent-based model was developed from an extensive farmer household survey about local land use practices. The model was used to project future patterns of arable land use under four localised, stakeholder-driven scenarios of plausible future socio-economic and climate change. The results show strong differences in farmers' behaviour and current agricultural land use patterns between the two regions, highlighting the need to implement focused policy at the regional level. For instance, policy that encourages local food security may need to support improvements in the capacity of farmers to adapt to physical constraints in Veszprém and farmer access to social capital and environmental awareness in Tolna. It is further suggested that the two regions will experience different challenges to adaptation under possible future conditions (up to 2100). For example, Veszprém was projected to have increased fallow land under a scenario with high inequality, ineffective institutions and higher-end climate change, implying risks of land abandonment. By contrast, Tolna was projected to have a considerable decline in major cereals under a scenario assuming a de-globalising future with moderate climate change, inferring challenges to local food self-sufficiency. The study provides insight into how socio-economic and physical factors influence the selection of crop rotation plans by farmers in western Hungary and how farmer behaviour may affect future risks to agricultural

  18. Dynamical downscaling of ERA-40 in complex terrain using the WRF regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Heikkilae, U. [Bjerknes Centre for Climate Research, Uni Bjerknes Centre, Bergen (Norway); Sandvik, A. [Bjerknes Centre for Climate Research, Institute for Marine Research (IMR), Bergen (Norway); Sorteberg, A. [University of Bergen, Geophysical Institute, Bergen (Norway)

    2011-10-15

    Results from a first-time employment of the WRF regional climate model to climatological simulations in Europe are presented. The ERA-40 reanalysis (resolution 1 ) has been downscaled to a horizontal resolution of 30 and 10 km for the period of 1961-1990. This model setup includes the whole North Atlantic in the 30 km domain and spectral nudging is used to keep the large scales consistent with the driving ERA-40 reanalysis. The model results are compared against an extensive observational network of surface variables in complex terrain in Norway. The comparison shows that the WRF model is able to add significant detail to the representation of precipitation and 2-m temperature of the ERA-40 reanalysis. Especially the geographical distribution, wet day frequency and extreme values of precipitation are highly improved due to the better representation of the orography. Refining the resolution from 30 to 10 km further increases the skill of the model, especially in case of precipitation. Our results indicate that the use of 10-km resolution is advantageous for producing regional future climate projections. Use of a large domain and spectral nudging seems to be useful in reproducing the extreme precipitation events due to the better resolved synoptic scale features over the North Atlantic, and also helps to reduce the large regional temperature biases over Norway. This study presents a high-resolution, high-quality climatological data set useful for reference climate impact studies. (orig.)

  19. Climate-model induced differences in the 21st century global and regional glacier contributions to sea-level rise

    NARCIS (Netherlands)

    Giesen, R.H.|info:eu-repo/dai/nl/304831603; Oerlemans, J.|info:eu-repo/dai/nl/06833656X

    2013-01-01

    The large uncertainty in future global glacier volume projections partly results from a substantial range in future climate conditions projected by global climate models. This study addresses the effect of global and regional differences in climate input data on the projected twenty-first century

  20. Consistency of climate change projections from multiple global and regional model intercomparison projects

    Science.gov (United States)

    Fernández, J.; Frías, M. D.; Cabos, W. D.; Cofiño, A. S.; Domínguez, M.; Fita, L.; Gaertner, M. A.; García-Díez, M.; Gutiérrez, J. M.; Jiménez-Guerrero, P.; Liguori, G.; Montávez, J. P.; Romera, R.; Sánchez, E.

    2018-03-01

    We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021-2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM-RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes.

  1. Which complexity of regional climate system models is essential for downscaling anthropogenic climate change in the Northwest European Shelf?

    Science.gov (United States)

    Mathis, Moritz; Elizalde, Alberto; Mikolajewicz, Uwe

    2018-04-01

    Climate change impact studies for the Northwest European Shelf (NWES) make use of various dynamical downscaling strategies in the experimental setup of regional ocean circulation models. Projected change signals from coupled and uncoupled downscalings with different domain sizes and forcing global and regional models show substantial uncertainty. In this paper, we investigate influences of the downscaling strategy on projected changes in the physical and biogeochemical conditions of the NWES. Our results indicate that uncertainties due to different downscaling strategies are similar to uncertainties due to the choice of the parent global model and the downscaling regional model. Downscaled change signals reveal to depend stronger on the downscaling strategy than on the model skills in simulating present-day conditions. Uncoupled downscalings of sea surface temperature (SST) changes are found to be tightly constrained by the atmospheric forcing. The incorporation of coupled air-sea interaction, by contrast, allows the regional model system to develop independently. Changes in salinity show a higher sensitivity to open lateral boundary conditions and river runoff than to coupled or uncoupled atmospheric forcings. Dependencies on the downscaling strategy for changes in SST, salinity, stratification and circulation collectively affect changes in nutrient import and biological primary production.

  2. Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

    Czech Academy of Sciences Publication Activity Database

    Beranová, Romana; Kyselý, Jan; Hanel, M.

    2018-01-01

    Roč. 132, 1-2 (2018), s. 515-527 ISSN 0177-798X R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : sub-daily precipitation * regional climate models * extremes * Czech Republic Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 2.640, year: 2016 https://link.springer.com/article/10.1007/s00704-017-2102-0

  3. An evaluation of temperature and precipitation from global and regional climate models over Scandinavia

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-07-01

    Precipitation and temperature from global (GCMs) and regional (RCMs) climate models are compared with reanalysis and observations over Scandinavia. Also projections for the next 50-100 years are considered. The climate development is visualised as moving averages (1920-2100). Box plots are used to illuminate how well GCM runs capture the observed seasonal cycle. Maps show the seasonal difference between results from control runs (RCM) and observations (E-OBS dataset) for the reference period 1981-2000. Plots illustrate the RCM-representation of seasonal temperature and precipitations cycle for five locations in Norway and Sweden: Oslo, Bergen, Trondheim, Tromsoe and Oestersund. The results show rather large differences between control runs and observations, demonstrating the need for bias correction of results from climate models. To get an indicator of which GC M-RCM-combination give the best representation of present climate over Scandinavia, a model ranking is provided. The performance measure used is the root-mean-square deviation of mean monthly and seasonal values. The data is compared both in an area-weighted spatial average of the whole domain as well as for the selected locations. The results indicate that the regional models RACMO2 and RCA show the smallest deviations from observed climate. Among the top ranking GCM-RCM combinations, most were driven by the global model ECHAM5 and some by a version of HadCM3. These two GCMs are also present among the worst performing GCM-RCM combinations indicating that selection of RCMs is crucial. (Author)

  4. Extreme temperature events on Greenland in observations and the MAR regional climate model

    Science.gov (United States)

    Leeson, Amber A.; Eastoe, Emma; Fettweis, Xavier

    2018-03-01

    Meltwater from the Greenland Ice Sheet contributed 1.7-6.12 mm to global sea level between 1993 and 2010 and is expected to contribute 20-110 mm to future sea level rise by 2100. These estimates were produced by regional climate models (RCMs) which are known to be robust at the ice sheet scale but occasionally miss regional- and local-scale climate variability (e.g. Leeson et al., 2017; Medley et al., 2013). To date, the fidelity of these models in the context of short-period variability in time (i.e. intra-seasonal) has not been fully assessed, for example their ability to simulate extreme temperature events. We use an event identification algorithm commonly used in extreme value analysis, together with observations from the Greenland Climate Network (GC-Net), to assess the ability of the MAR (Modèle Atmosphérique Régional) RCM to reproduce observed extreme positive-temperature events at 14 sites around Greenland. We find that MAR is able to accurately simulate the frequency and duration of these events but underestimates their magnitude by more than half a degree Celsius/kelvin, although this bias is much smaller than that exhibited by coarse-scale Era-Interim reanalysis data. As a result, melt energy in MAR output is underestimated by between 16 and 41 % depending on global forcing applied. Further work is needed to precisely determine the drivers of extreme temperature events, and why the model underperforms in this area, but our findings suggest that biases are passed into MAR from boundary forcing data. This is important because these forcings are common between RCMs and their range of predictions of past and future ice sheet melting. We propose that examining extreme events should become a routine part of global and regional climate model evaluation and that addressing shortcomings in this area should be a priority for model development.

  5. Streamflow in the upper Mississippi river basin as simulated by SWAT driven by 20{sup th} century contemporary results of global climate models and NARCCAP regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Takle, Eugene S.; Jha, Manoj; Lu, Er; Arritt, Raymond W.; Gutowski, William J. [Iowa State Univ. Ames, IA (United States)

    2010-06-15

    We use Soil and Water Assessment Tool (SWAT) when driven by observations and results of climate models to evaluate hydrological quantities, including streamflow, in the Upper Mississippi River Basin (UMRB) for 1981-2003 in comparison to observed streamflow. Daily meteorological conditions used as input to SWAT are taken from (1) observations at weather stations in the basin, (2) daily meteorological conditions simulated by a collection of regional climate models (RCMs) driven by reanalysis boundary conditions, and (3) daily meteorological conditions simulated by a collection of global climate models (GCMs). Regional models used are those whose data are archived by the North American Regional Climate Change Assessment Program (NARCCAP). Results show that regional models correctly simulate the seasonal cycle of precipitation, temperature, and streamflow within the basin. Regional models also capture interannual extremes represented by the flood of 1993 and the dry conditions of 2000. The ensemble means of both the GCM-driven and RCM-driven simulations by SWAT capture both the timing and amplitude of the seasonal cycle of streamflow with neither demonstrating significant superiority at the basin level. (orig.)

  6. Use of variability modes to evaluate AR4 climate models over the Euro-Atlantic region

    Energy Technology Data Exchange (ETDEWEB)

    Casado, M.J.; Pastor, M.A. [Agencia Estatal de Meteorologia (AEMET), Madrid (Spain)

    2012-01-15

    This paper analyzes the ability of the multi-model simulations from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) to simulate the main leading modes of variability over the Euro-Atlantic region in winter: the North-Atlantic Oscillation (NAO), the Scandinavian mode (SCAND), the East/Atlantic Oscillation (EA) and the East Atlantic/Western Russia mode (EA/WR). These modes of variability have been evaluated both spatially, by analyzing the intensity and location of their anomaly centres, as well as temporally, by focusing on the probability density functions and e-folding time scales. The choice of variability modes as a tool for climate model assessment can be justified by the fact that modes of variability determine local climatic conditions and their likely change may have important implications for future climate changes. It is found that all the models considered are able to simulate reasonably well these four variability modes, the SCAND being the mode which is best spatially simulated. From a temporal point of view the NAO and SCAND modes are the best simulated. UKMO-HadGEM1 and CGCM3.1(T63) are the models best at reproducing spatial characteristics, whereas CCSM3 and CGCM3.1(T63) are the best ones with regard to the temporal features. GISS-AOM is the model showing the worst performance, in terms of both spatial and temporal features. These results may bring new insight into the selection and use of specific models to simulate Euro-Atlantic climate, with some models being clearly more successful in simulating patterns of temporal and spatial variability than others. (orig.)

  7. Superensemble of a Regional Climate Model for the Western US using Climateprediction.net

    Science.gov (United States)

    Mote, P.; Salahuddin, A.; Allen, M.; Jones, R.

    2010-12-01

    For over a decade, a citizen science experiment called climateprediction.net organized by Oxford University has used computer time contributed by over 80,000 volunteers around the world to create superensembles of global climate simulations. A new climateprediction.net experiment built by the UK Meteorological Office and Oxford, and released in late summer 2010, brings these computing resources to bear on regional climate modeling for the Western US, western Europe, and southern Africa. For the western US, the spatial resolution of 25km permits important topological features -- mountain ranges and valleys -- to be resolved and to influence simulated climate, which consequently includes many important observed features of climate like the fact that California’s Central Valley is hottest at the north and south ends in summer, and cooler in the middle owing to the maritime influence that leaks through the gap in the coast range in the San Francisco area. We designed the output variables to satisfy both research needs and societal and environmental impacts needs. These include atmospheric circulation on regional and global scales, surface fluxes of energy, and hydrologic variables; extremes of temperature, precipitation, and wind; and derived quantities like frost days and number of consecutive dry days. Early results from pre-release beta testing suggest that the simulated fields compare favorably with available observations, and that the model performs as well in the distributed computing environment as on a dedicated high-performance machine. The advantages of a superensemble in interpreting regional climate change will permit an unprecedented combination of statistical completeness and spatial resolution.

  8. Effects of lateral boundary condition resolution and update frequency on regional climate model predictions

    Science.gov (United States)

    Pankatz, Klaus; Kerkweg, Astrid

    2015-04-01

    The work presented is part of the joint project "DecReg" ("Regional decadal predictability") which is in turn part of the project "MiKlip" ("Decadal predictions"), an effort funded by the German Federal Ministry of Education and Research to improve decadal predictions on a global and regional scale. In MiKlip, one big question is if regional climate modeling shows "added value", i.e. to evaluate, if regional climate models (RCM) produce better results than the driving models. However, the scope of this study is to look more closely at the setup specific details of regional climate modeling. As regional models only simulate a small domain, they have to inherit information about the state of the atmosphere at their lateral boundaries from external data sets. There are many unresolved questions concerning the setup of lateral boundary conditions (LBC). External data sets come from global models or from global reanalysis data-sets. A temporal resolution of six hours is common for this kind of data. This is mainly due to the fact, that storage space is a limiting factor, especially for climate simulations. However, theoretically, the coupling frequency could be as high as the time step of the driving model. Meanwhile, it is unclear if a more frequent update of the LBCs has a significant effect on the climate in the domain of the RCM. The first study examines how the RCM reacts to a higher update frequency. The study is based on a 30 year time slice experiment for three update frequencies of the LBC, namely six hours, one hour and six minutes. The evaluation of means, standard deviations and statistics of the climate in the regional domain shows only small deviations, some statistically significant though, of 2m temperature, sea level pressure and precipitation. The second part of the first study assesses parameters linked to cyclone activity, which is affected by the LBC update frequency. Differences in track density and strength are found when comparing the simulations

  9. The effect of a giant wind farm on precipitation in a regional climate model

    International Nuclear Information System (INIS)

    Fiedler, B H; Bukovsky, M S

    2011-01-01

    The Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to study the effect of a giant wind farm on warm-season precipitation in the eastern two-thirds of the USA. The boundary conditions for WRF are supplied by 62 years of NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research) global reanalysis. In the model, the presence of a mid-west wind farm, either giant or small, can have an enormous impact on the weather and the amount of precipitation for one season, which is consistent with the known sensitivity of long-term weather forecasts to initial conditions. The effect on climate is less strong. In the average precipitation of 62 warm seasons, there is a statistically significant 1.0% enhancement of precipitation in a multi-state area surrounding and to the south-east of the wind farm.

  10. Future projections of the climate and surface mass balance of Svalbard with the regional climate model MAR

    Science.gov (United States)

    Lang, C.; Fettweis, X.; Erpicum, M.

    2015-01-01

    We have performed future projections of the climate and surface mass balance (SMB) of Svalbard with the MAR regional climate model forced by the MIROC5 global model, following the RCP8.5 scenario at a spatial resolution of 10 km. MAR predicts a similar evolution of increasing surface melt everywhere in Svalbard followed by a sudden acceleration of the melt around 2050, with a larger melt increase in the south compared to the north of the archipelago and the ice caps. This melt acceleration around 2050 is mainly driven by the albedo-melt feedback associated with the expansion of the ablation/bare ice zone. This effect is dampened in part as the solar radiation itself is projected to decrease due to cloudiness increase. The near-surface temperature is projected to increase more in winter than in summer as the temperature is already close to 0 °C in summer. The model also projects a strong winter west-to-east temperature gradient, related to the large decrease of sea ice cover around Svalbard. At the end of the century (2070-2099 mean), SMB is projected to be negative over the entire Svalbard and, by 2085, all glaciated regions of Svalbard are predicted to undergo net ablation, meaning that, under the RCP8.5 scenario, all the glaciers and ice caps are predicted to start their irreversible retreat before the end of the 21st century.

  11. Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

    Science.gov (United States)

    Akperov, Mirseid; Rinke, Annette; Mokhov, Igor I.; Matthes, Heidrun; Semenov, Vladimir A.; Adakudlu, Muralidhar; Cassano, John; Christensen, Jens H.; Dembitskaya, Mariya A.; Dethloff, Klaus; Fettweis, Xavier; Glisan, Justin; Gutjahr, Oliver; Heinemann, Günther; Koenigk, Torben; Koldunov, Nikolay V.; Laprise, René; Mottram, Ruth; Nikiéma, Oumarou; Scinocca, John F.; Sein, Dmitry; Sobolowski, Stefan; Winger, Katja; Zhang, Wenxin

    2018-03-01

    The ability of state-of-the-art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic-CORDEX initiative. Some models employ large-scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA-Interim, National Centers for Environmental Prediction-Climate Forecast System Reanalysis, National Aeronautics and Space Administration-Modern-Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency-Japanese 55-year reanalysis) in winter and summer for 1981-2010 period. In addition, we compare cyclone statistics between ERA-Interim and the Arctic System Reanalysis reanalyses for 2000-2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large-scale spectral nudging show a better agreement with ERA-Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.

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

    Science.gov (United States)

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

    2018-04-01

    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

  13. Observational uncertainty and regional climate model evaluation: A pan-European perspective

    Science.gov (United States)

    Kotlarski, Sven; Szabó, Péter; Herrera, Sixto; Räty, Olle; Keuler, Klaus; Soares, Pedro M.; Cardoso, Rita M.; Bosshard, Thomas; Pagé, Christian; Boberg, Fredrik; Gutiérrez, José M.; Jaczewski, Adam; Kreienkamp, Frank; Liniger, Mark. A.; Lussana, Cristian; Szepszo, Gabriella

    2017-04-01

    Local and regional climate change assessments based on downscaling methods crucially depend on the existence of accurate and reliable observational reference data. In dynamical downscaling via regional climate models (RCMs) observational data can influence model development itself and, later on, model evaluation, parameter calibration and added value assessment. In empirical-statistical downscaling, observations serve as predictand data and directly influence model calibration with corresponding effects on downscaled climate change projections. Focusing on the evaluation of RCMs, we here analyze the influence of uncertainties in observational reference data on evaluation results in a well-defined performance assessment framework and on a European scale. For this purpose we employ three different gridded observational reference grids, namely (1) the well-established EOBS dataset (2) the recently developed EURO4M-MESAN regional re-analysis, and (3) several national high-resolution and quality-controlled gridded datasets that recently became available. In terms of climate models five reanalysis-driven experiments carried out by five different RCMs within the EURO-CORDEX framework are used. Two variables (temperature and precipitation) and a range of evaluation metrics that reflect different aspects of RCM performance are considered. We furthermore include an illustrative model ranking exercise and relate observational spread to RCM spread. The results obtained indicate a varying influence of observational uncertainty on model evaluation depending on the variable, the season, the region and the specific performance metric considered. Over most parts of the continent, the influence of the choice of the reference dataset for temperature is rather small for seasonal mean values and inter-annual variability. Here, model uncertainty (as measured by the spread between the five RCM simulations considered) is typically much larger than reference data uncertainty. For

  14. COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J.

    2013-02-07

    The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

  15. Comparing regional precipitation and temperature extremes in climate model and reanalysis products

    Directory of Open Access Journals (Sweden)

    Oliver Angélil

    2016-09-01

    Full Text Available A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averages over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.

  16. The influence of spectral nudging on typhoon formation in regional climate models

    Science.gov (United States)

    Feser, Frauke; Barcikowska, Monika

    2012-03-01

    Regional climate models can successfully simulate tropical cyclones and typhoons. This has been shown and was evaluated for hindcast studies of the past few decades. But often global and regional weather phenomena are not simulated at the observed location, or occur too often or seldom even though the regional model is driven by global reanalysis data which constitute a near-realistic state of the global atmosphere. Therefore, several techniques have been developed in order to make the regional model follow the global state more closely. One is spectral nudging, which is applied for horizontal wind components with increasing strength for higher model levels in this study. The aim of this study is to show the influence that this method has on the formation of tropical cyclones (TC) in regional climate models. Two ensemble simulations (each with five simulations) were computed for Southeast Asia and the Northwestern Pacific for the typhoon season 2004, one with spectral nudging and one without. First of all, spectral nudging reduced the overall TC number by about a factor of 2. But the number of tracks which are similar to observed best track data (BTD) was greatly increased. Also, spatial track density patterns were found to be more similar when using spectral nudging. The tracks merge after a short time for the spectral nudging simulations and then follow the BTD closely; for the no nudge cases the similarity is greatly reduced. A comparison of seasonal precipitation, geopotential height, and temperature fields at several height levels with observations and reanalysis data showed overall a smaller ensemble spread, higher pattern correlations and reduced root mean square errors and biases for the spectral nudged simulations. Vertical temperature profiles for selected TCs indicate that spectral nudging is not inhibiting TC development at higher levels. Both the Madden-Julian Oscillation and monsoonal precipitation are reproduced realistically by the regional model

  17. The influence of spectral nudging on typhoon formation in regional climate models

    International Nuclear Information System (INIS)

    Feser, Frauke; Barcikowska, Monika

    2012-01-01

    Regional climate models can successfully simulate tropical cyclones and typhoons. This has been shown and was evaluated for hindcast studies of the past few decades. But often global and regional weather phenomena are not simulated at the observed location, or occur too often or seldom even though the regional model is driven by global reanalysis data which constitute a near-realistic state of the global atmosphere. Therefore, several techniques have been developed in order to make the regional model follow the global state more closely. One is spectral nudging, which is applied for horizontal wind components with increasing strength for higher model levels in this study. The aim of this study is to show the influence that this method has on the formation of tropical cyclones (TC) in regional climate models. Two ensemble simulations (each with five simulations) were computed for Southeast Asia and the Northwestern Pacific for the typhoon season 2004, one with spectral nudging and one without. First of all, spectral nudging reduced the overall TC number by about a factor of 2. But the number of tracks which are similar to observed best track data (BTD) was greatly increased. Also, spatial track density patterns were found to be more similar when using spectral nudging. The tracks merge after a short time for the spectral nudging simulations and then follow the BTD closely; for the no nudge cases the similarity is greatly reduced. A comparison of seasonal precipitation, geopotential height, and temperature fields at several height levels with observations and reanalysis data showed overall a smaller ensemble spread, higher pattern correlations and reduced root mean square errors and biases for the spectral nudged simulations. Vertical temperature profiles for selected TCs indicate that spectral nudging is not inhibiting TC development at higher levels. Both the Madden–Julian Oscillation and monsoonal precipitation are reproduced realistically by the regional model

  18. Regional Climate Modeling and Remote Sensing to Characterize Impacts of Civil War Driven Land Use Change on Regional Hydrology and Climate

    Science.gov (United States)

    Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

    2016-12-01

    Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are extensive enough. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from an extended civil conflict in Mozambique. Civil war from 1977-1992 in Mozambique led to land use change at a regional scale as a result of the collapse of large herbivore populations due to poaching. Since the war ended, farming has increased, poaching was curtailed, and animal populations were reintroduced. In this study LULC in a region encompassing Gorongosa is classified at three instances between 1977 to 2015 using Landsat imagery. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from conflict-driven land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the civil war. Analysis of the Landsat data shows measurable land cover change from 1977-present as tree cover encroached into grasslands. Initial tests show corresponding sensitivities to different LULC schemes within the WRF model. Preliminary results suggest that the war did indeed impact regional hydroclimate in a significant way via its direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional conflicts are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

  19. Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

    Science.gov (United States)

    Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.

    2018-03-01

    In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

  20. Applicability of ranked Regional Climate Models (RCM) to assess the impact of climate change on Ganges: A case study.

    Science.gov (United States)

    Anand, Jatin; Devak, Manjula; Gosain, Ashvani Kumar; Khosa, Rakesh; Dhanya, Ct

    2017-04-01

    The negative impact of climate change is felt over wide range of spatial scales, ranging from small basins to large watershed area, which can possibly outweighs the benefits of natural water system. General Circulation Models (GCMs) has been widely used as an input to a hydrological models (HMs), to simulate different hydrological components of a river basin. However, the coarser scale of GCMs and spatio-temporal biases, restricted its use at finer resolution. If downscaled, adds one more level of uncertainty i.e., downscaling uncertainty together with model and scenario uncertainty. The outputs computed from Regional Climate Models (RCM) may aid the uncertainties arising from GCMs, as the RCMs are the miniatures of GCMs. However, the RCMs do have some inherent systematic biases, hence bias correction is a prerequisite process before it is fed to HMs. RCMs, together with the input from GCMs at later boundaries also takes topography of the area into account. Hence, RCMs need to be ranked a priori. In this study, impact of climate change on the Ganga basin, India, is assessed using the ranked RCMs. Firstly, bias correction of 14 RCM models are done using Quantile-Quantile mapping and Equidistant cumulative distribution method, for historic (1990-2004) and future scenario (2021-2100), respectively. The runoff simulations from Soil Water Assessment Tool (SWAT), for historic scenario is used for ranking of RCMs. Entropy and PROMETHEE-2 method is employed to rank the RCMs based on five performance indicators namely, Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), normalised root mean square error (NRMSE), absolute normalised mean bias error (ANMBE) and average absolute relative error (AARE). The results illustrated that each of the performance indicators behaves differently for different RCMs. RCA 4 (CNRM-CERFACS) is found as the best model with the highest value of  (0.85), followed by RCA4 (MIROC) and RCA4 (ICHEC) with  values of 0.80 and 0

  1. Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations

    NARCIS (Netherlands)

    Pelt, van S.C.; Beersma, J.J.; Buishand, T.A.; Hurk, van den B.J.J.M.; Kabat, P.

    2012-01-01

    Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks.

  2. Investigating added value of regional climate modeling in North American winter storm track simulations

    Science.gov (United States)

    Poan, E. D.; Gachon, P.; Laprise, R.; Aider, R.; Dueymes, G.

    2018-03-01

    Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981-2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal `seriality', as a measure of their temporal variability at a given

  3. Regional Community Climate Simulations with variable resolution meshes in the Community Earth System Model

    Science.gov (United States)

    Zarzycki, C. M.; Gettelman, A.; Callaghan, P.

    2017-12-01

    Accurately predicting weather extremes such as precipitation (floods and droughts) and temperature (heat waves) requires high resolution to resolve mesoscale dynamics and topography at horizontal scales of 10-30km. Simulating such resolutions globally for climate scales (years to decades) remains computationally impractical. Simulating only a small region of the planet is more tractable at these scales for climate applications. This work describes global simulations using variable-resolution static meshes with multiple dynamical cores that target the continental United States using developmental versions of the Community Earth System Model version 2 (CESM2). CESM2 is tested in idealized, aquaplanet and full physics configurations to evaluate variable mesh simulations against uniform high and uniform low resolution simulations at resolutions down to 15km. Different physical parameterization suites are also evaluated to gauge their sensitivity to resolution. Idealized variable-resolution mesh cases compare well to high resolution tests. More recent versions of the atmospheric physics, including cloud schemes for CESM2, are more stable with respect to changes in horizontal resolution. Most of the sensitivity is due to sensitivity to timestep and interactions between deep convection and large scale condensation, expected from the closure methods. The resulting full physics model produces a comparable climate to the global low resolution mesh and similar high frequency statistics in the high resolution region. Some biases are reduced (orographic precipitation in the western United States), but biases do not necessarily go away at high resolution (e.g. summertime JJA surface Temp). The simulations are able to reproduce uniform high resolution results, making them an effective tool for regional climate studies and are available in CESM2.

  4. 2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2013-05-01

    Full Text Available Most land surface hydrological models (LSHMs consider land surface processes (e.g. soil–plant–atmosphere interactions, lateral water flows, snow and ice in a spatially detailed manner. The atmosphere is considered as exogenous driver, neglecting feedbacks between the land surface and the atmosphere. On the other hand, regional climate models (RCMs generally simulate land surface processes through coarse descriptions and spatial scales but include land–atmosphere interactions. What is the impact of the differently applied model physics and spatial resolution of LSHMs on the performance of RCMs? What feedback effects are induced by different land surface models? This study analyses the impact of replacing the land surface module (LSM within an RCM with a high resolution LSHM. A 2-way coupling approach was applied using the LSHM PROMET (1 × 1 km2 and the atmospheric part of the RCM MM5 (45 × 45 km2. The scaling interface SCALMET is used for down- and upscaling the linear and non-linear fluxes between the model scales. The change in the atmospheric response by MM5 using the LSHM is analysed, and its quality is compared to observations of temperature and precipitation for a 4 yr period from 1996 to 1999 for the Upper Danube catchment. By substituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses when compared to measurements from 277 meteorological weather stations within the Upper Danube catchment. The mean annual bias was improved from −0.85 to −0.13 K. In particular, the improved afternoon heating from May to September is caused by increased sensible heat flux and decreased latent heat flux as well as more incoming solar radiation in the fully coupled PROMET/MM5 in comparison to the NOAH/MM5 simulation. Triggered by the LSM replacement, precipitation overall is reduced; however simulated precipitation amounts are still of high uncertainty, both

  5. Impacts of using spectral nudging on regional climate model RCA4 simulations of the Arctic

    Directory of Open Access Journals (Sweden)

    P. Berg

    2013-06-01

    Full Text Available The performance of the Rossby Centre regional climate model RCA4 is investigated for the Arctic CORDEX (COordinated Regional climate Downscaling EXperiment region, with an emphasis on its suitability to be coupled to a regional ocean and sea ice model. Large biases in mean sea level pressure (MSLP are identified, with pronounced too-high pressure centred over the North Pole in summer of over 5 hPa, and too-low pressure in winter of a similar magnitude. These lead to biases in the surface winds, which will potentially lead to strong sea ice biases in a future coupled system. The large-scale circulation is believed to be the major reason for the biases, and an implementation of spectral nudging is applied to remedy the problems by constraining the large-scale components of the driving fields within the interior domain. It is found that the spectral nudging generally corrects for the MSLP and wind biases, while not significantly affecting other variables, such as surface radiative components, two-metre temperature and precipitation.

  6. Climate change projections over three metropolitan regions in Southeast Brazil using the non-hydrostatic Eta regional climate model at 5-km resolution

    Science.gov (United States)

    Lyra, Andre; Tavares, Priscila; Chou, Sin Chan; Sueiro, Gustavo; Dereczynski, Claudine; Sondermann, Marcely; Silva, Adan; Marengo, José; Giarolla, Angélica

    2018-04-01

    The objective of this work is to assess changes in three metropolitan regions of Southeast Brazil (Rio de Janeiro, São Paulo, and Santos) based on the projections produced by the Eta Regional Climate Model (RCM) at very high spatial resolution, 5 km. The region, which is densely populated and extremely active economically, is frequently affected by intense rainfall events that trigger floods and landslides during the austral summer. The analyses are carried out for the period between 1961 and 2100. The 5-km simulations are results from a second downscaling nesting in the HadGEM2-ES RCP4.5 and RCP8.5 simulations. Prior to the assessment of the projections, the higher resolution simulations were evaluated for the historical period (1961-1990). The comparison between the 5-km and the coarser driver model simulations shows that the spatial patterns of precipitation and temperature of the 5-km Eta simulations are in good agreement with the observations. The simulated frequency distribution of the precipitation and temperature extremes from the 5-km Eta RCM is consistent with the observed structure and extreme values. Projections of future climate change using the 5-km Eta runs show stronger warming in the region, primarily during the summer season, while precipitation is strongly reduced. Projected temperature extremes show widespread heating with maximum temperatures increasing by approximately 9 °C in the three metropolitan regions by the end of the century in the RCP8.5 scenario. A trend of drier climate is also projected using indices based on daily precipitation, which reaches annual rainfall reductions of more than 50 % in the state of Rio de Janeiro and between 40 and 45 % in São Paulo and Santos. The magnitude of these changes has negative implications to the population health conditions, energy security, and economy.

  7. An investigation of tropical Atlantic bias in a high-resolution coupled regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Patricola, Christina M.; Saravanan, R.; Hsieh, Jen-Shan [Texas A and M University, Department of Atmospheric Sciences, College Station, TX (United States); Li, Mingkui; Xu, Zhao [Texas A and M University, Department of Oceanography, College Station, TX (United States); Ocean University of China, Key Laboratory of Physical Oceanography of Ministry of Education, Qingdao (China); Chang, Ping [Texas A and M University, Department of Oceanography, College Station, TX (United States); Ocean University of China, Key Laboratory of Physical Oceanography of Ministry of Education, Qingdao (China); Second Institute of Oceanography, State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou, Zhejiang (China)

    2012-11-15

    Coupled atmosphere-ocean general circulation models (AOGCMs) commonly fail to simulate the eastern equatorial Atlantic boreal summer cold tongue and produce a westerly equatorial trade wind bias. This tropical Atlantic bias problem is investigated with a high-resolution (27-km atmosphere represented by the Weather Research and Forecasting Model, 9-km ocean represented by the Regional Ocean Modeling System) coupled regional climate model. Uncoupled atmospheric simulations test climate sensitivity to cumulus, land-surface, planetary boundary layer, microphysics, and radiation parameterizations and reveal that the radiation scheme has a pronounced impact in the tropical Atlantic. The CAM radiation simulates a dry precipitation (up to -90%) and cold land-surface temperature (up to -8 K) bias over the Amazon related to an over-representation of low-level clouds and almost basin-wide westerly trade wind bias. The Rapid Radiative Transfer Model and Goddard radiation simulates doubled Amazon and Congo Basin precipitation rates and a weak eastern Atlantic trade wind bias. Season-long high-resolution coupled regional model experiments indicate that the initiation of the warm eastern equatorial Atlantic sea surface temperature (SST) bias is more sensitive to the local rather than basin-wide trade wind bias and to a wet Congo Basin instead of dry Amazon - which differs from AOGCM simulations. Comparisons between coupled and uncoupled simulations suggest a regional Bjerknes feedback confined to the eastern equatorial Atlantic amplifies the initial SST, wind, and deepened thermocline bias, while barrier layer feedbacks are relatively unimportant. The SST bias in some CRCM simulations resembles the typical AOGCM bias indicating that increasing resolution is unlikely a simple solution to this problem. (orig.)

  8. Modelling Regional Climate Change Effects On Potential Natural Ecosystems in Sweden

    Energy Technology Data Exchange (ETDEWEB)

    Koca, D.; Smith, B.; Sykes, M.T. [Centre for GeoBiosphere Science, Department of Physical Geography and Ecosystems Analysis, Lund University, Soelvegatan 12, S-223 62 Lund (Sweden)

    2006-10-15

    This study aims to demonstrate the potential of a process-based regional ecosystem model, LPJ-GUESS, driven by climate scenarios generated by a regional climate model system (RCM) to generate predictions useful for assessing effects of climatic and CO2 change on the key ecosystem services of carbon uptake and storage. Scenarios compatible with the A2 and B2 greenhouse gas emission scenarios of the Special Report on Emission Scenarios (SRES) and with boundary conditions from two general circulation models (GCMs) - HadAM3H and ECHAM4/OPYC3 - were used in simulations to explore changes in tree species distributions, vegetation structure, productivity and ecosystem carbon stocks for the late 21st Century, thus accommodating a proportion of the GCM-based and emissions-based uncertainty in future climate development. The simulations represented in this study were of the potential natural vegetation ignoring direct anthropogenic effects. Results suggest that shifts in climatic zones may lead to changes in species distribution and community composition among seven major tree species of natural Swedish forests. All four climate scenarios were associated with an extension of the boreal forest treeline with respect to altitude and latitude. In the boreal and boreo-nemoral zones, the dominance of Norway spruce and to a lesser extent Scots pine was reduced in favour of deciduous broadleaved tree species. The model also predicted substantial increases in vegetation net primary productivity (NPP), especially in central Sweden. Expansion of forest cover and increased local biomass enhanced the net carbon sink over central and northern Sweden, despite increased carbon release through decomposition processes in the soil. In southern Sweden, reduced growing season soil moisture levels counterbalanced the positive effects of a longer growing season and increased carbon supply on NPP, with the result that many areas were converted from a sink to a source of carbon by the late 21st

  9. Modelling Regional Climate Change Effects On Potential Natural Ecosystems in Sweden

    International Nuclear Information System (INIS)

    Koca, D.; Smith, B.; Sykes, M.T.

    2006-01-01

    This study aims to demonstrate the potential of a process-based regional ecosystem model, LPJ-GUESS, driven by climate scenarios generated by a regional climate model system (RCM) to generate predictions useful for assessing effects of climatic and CO2 change on the key ecosystem services of carbon uptake and storage. Scenarios compatible with the A2 and B2 greenhouse gas emission scenarios of the Special Report on Emission Scenarios (SRES) and with boundary conditions from two general circulation models (GCMs) - HadAM3H and ECHAM4/OPYC3 - were used in simulations to explore changes in tree species distributions, vegetation structure, productivity and ecosystem carbon stocks for the late 21st Century, thus accommodating a proportion of the GCM-based and emissions-based uncertainty in future climate development. The simulations represented in this study were of the potential natural vegetation ignoring direct anthropogenic effects. Results suggest that shifts in climatic zones may lead to changes in species distribution and community composition among seven major tree species of natural Swedish forests. All four climate scenarios were associated with an extension of the boreal forest treeline with respect to altitude and latitude. In the boreal and boreo-nemoral zones, the dominance of Norway spruce and to a lesser extent Scots pine was reduced in favour of deciduous broadleaved tree species. The model also predicted substantial increases in vegetation net primary productivity (NPP), especially in central Sweden. Expansion of forest cover and increased local biomass enhanced the net carbon sink over central and northern Sweden, despite increased carbon release through decomposition processes in the soil. In southern Sweden, reduced growing season soil moisture levels counterbalanced the positive effects of a longer growing season and increased carbon supply on NPP, with the result that many areas were converted from a sink to a source of carbon by the late 21st

  10. Evaluation of regional climate model simulations versus gridded observed and regional reanalysis products using a combined weighting scheme

    Energy Technology Data Exchange (ETDEWEB)

    Eum, Hyung-Il; Laprise, Rene [University of Quebec at Montreal, ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada); Gachon, Philippe [University of Quebec at Montreal, ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada); Environment Canada, Adaptation and Impacts Research Section, Climate Research Division, Montreal, QC (Canada); Ouarda, Taha [University of Quebec, INRS-ETE (Institut National de la Recherche Scientifique, Centre Eau-Terre-Environnement), Quebec, QC (Canada)

    2012-04-15

    This study presents a combined weighting scheme which contains five attributes that reflect accuracy of climate data, i.e. short-term (daily), mid-term (annual), and long-term (decadal) timescales, as well as spatial pattern, and extreme values, as simulated from Regional Climate Models (RCMs) with respect to observed and regional reanalysis products. Southern areas of Quebec and Ontario provinces in Canada are used for the study area. Three series of simulation from two different versions of the Canadian RCM (CRCM4.1.1, and CRCM4.2.3) are employed over 23 years from 1979 to 2001, driven by both NCEP and ERA40 global reanalysis products. One series of regional reanalysis dataset (i.e. NARR) over North America is also used as reference for comparison and validation purpose, as well as gridded historical observed daily data of precipitation and temperatures, both series have been beforehand interpolated on the CRCM 45-km grid resolution. Monthly weighting factors are calculated and then combined into four seasons to reflect seasonal variability of climate data accuracy. In addition, this study generates weight averaged references (WARs) with different weighting factors and ensemble size as new reference climate data set. The simulation results indicate that the NARR is in general superior to the CRCM simulated precipitation values, but the CRCM4.1.1 provides the highest weighting factors during the winter season. For minimum and maximum temperature, both the CRCM4.1.1 and the NARR products provide the highest weighting factors, respectively. The NARR provides more accurate short- and mid-term climate data, but the two versions of the CRCM provide more precise long-term data, spatial pattern and extreme events. Or study confirms also that the global reanalysis data (i.e. NCEP vs. ERA40) used as boundary conditions in the CRCM runs has non-negligible effects on the accuracy of CRCM simulated precipitation and temperature values. In addition, this study demonstrates

  11. Near-surface wind variability over the broader Adriatic region: insights from an ensemble of regional climate models

    Science.gov (United States)

    Belušić, Andreina; Prtenjak, Maja Telišman; Güttler, Ivan; Ban, Nikolina; Leutwyler, David; Schär, Christoph

    2018-06-01

    Over the past few decades the horizontal resolution of regional climate models (RCMs) has steadily increased, leading to a better representation of small-scale topographic features and more details in simulating dynamical aspects, especially in coastal regions and over complex terrain. Due to its complex terrain, the broader Adriatic region represents a major challenge to state-of-the-art RCMs in simulating local wind systems realistically. The objective of this study is to identify the added value in near-surface wind due to the refined grid spacing of RCMs. For this purpose, we use a multi-model ensemble composed of CORDEX regional climate simulations at 0.11° and 0.44° grid spacing, forced by the ERA-Interim reanalysis, a COSMO convection-parameterizing simulation at 0.11° and a COSMO convection-resolving simulation at 0.02° grid spacing. Surface station observations from this region and satellite QuikSCAT data over the Adriatic Sea have been compared against daily output obtained from the available simulations. Both day-to-day wind and its frequency distribution are examined. The results indicate that the 0.44° RCMs rarely outperform ERA-Interim reanalysis, while the performance of the high-resolution simulations surpasses that of ERA-Interim. We also disclose that refining the grid spacing to a few km is needed to properly capture the small-scale wind systems. Finally, we show that the simulations frequently yield the accurate angle of local wind regimes, such as for the Bora flow, but overestimate the associated wind magnitude. Finally, spectral analysis shows good agreement between measurements and simulations, indicating the correct temporal variability of the wind speed.

  12. Sensitivity experiments of a regional climate model to the different convective schemes over Central Africa

    Science.gov (United States)

    Armand J, K. M.

    2017-12-01

    In this study, version 4 of the regional climate model (RegCM4) is used to perform 6 years simulation including one year for spin-up (from January 2001 to December 2006) over Central Africa using four convective schemes: The Emmanuel scheme (MIT), the Grell scheme with Arakawa-Schulbert closure assumption (GAS), the Grell scheme with Fritsch-Chappell closure assumption (GFC) and the Anthes-Kuo scheme (Kuo). We have investigated the ability of the model to simulate precipitation, surface temperature, wind and aerosols optical depth. Emphasis in the model results were made in December-January-February (DJF) and July-August-September (JAS) periods. Two subregions have been identified for more specific analysis namely: zone 1 which corresponds to the sahel region mainly classified as desert and steppe and zone 2 which is a region spanning the tropical rain forest and is characterised by a bimodal rain regime. We found that regardless of periods or simulated parameters, MIT scheme generally has a tendency to overestimate. The GAS scheme is more suitable in simulating the aforementioned parameters, as well as the diurnal cycle of precipitations everywhere over the study domain irrespective of the season. In JAS, model results are similar in the representation of regional wind circulation. Apart from the MIT scheme, all the convective schemes give the same trends in aerosols optical depth simulations. Additional experiment reveals that the use of BATS instead of Zeng scheme to calculate ocean flux appears to improve the quality of the model simulations.

  13. Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

    Energy Technology Data Exchange (ETDEWEB)

    Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Flörke, M.; Huang, S.; Motovilov, Y.; Buda, S.; Yang, T.; Müller, C.; Leng, G.; Tang, Q.; Portmann, F. T.; Hagemann, S.; Gerten, D.; Wada, Y.; Masaki, Y.; Alemayehu, T.; Satoh, Y.; Samaniego, L.

    2017-01-04

    Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.

  14. Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF

    Science.gov (United States)

    Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

    2012-12-01

    This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

  15. Regional emission metrics for short-lived climate forcers from multiple models

    Directory of Open Access Journals (Sweden)

    B. Aamaas

    2016-06-01

    Full Text Available For short-lived climate forcers (SLCFs, the impact of emissions depends on where and when the emissions take place. Comprehensive new calculations of various emission metrics for SLCFs are presented based on radiative forcing (RF values calculated in four different (chemical-transport or coupled chemistry–climate models. We distinguish between emissions during summer (May–October and winter (November–April for emissions in Europe and East Asia, as well as from the global shipping sector and global emissions. The species included in this study are aerosols and aerosol precursors (BC, OC, SO2, NH3, as well as ozone precursors (NOx, CO, VOCs, which also influence aerosols to a lesser degree. Emission metrics for global climate responses of these emissions, as well as for CH4, have been calculated using global warming potential (GWP and global temperature change potential (GTP, based on dedicated RF simulations by four global models. The emission metrics include indirect cloud effects of aerosols and the semi-direct forcing for BC. In addition to the standard emission metrics for pulse and sustained emissions, we have also calculated a new emission metric designed for an emission profile consisting of a ramping period of 15 years followed by sustained emissions, which is more appropriate for a gradual implementation of mitigation policies.For the aerosols, the emission metric values are larger in magnitude for emissions in Europe than East Asia and for summer than winter. A variation is also observed for the ozone precursors, with largest values for emissions in East Asia and winter for CO and in Europe and summer for VOCs. In general, the variations between the emission metrics derived from different models are larger than the variations between regions and seasons, but the regional and seasonal variations for the best estimate also hold for most of the models individually. Further, the estimated climate impact of an illustrative mitigation

  16. Influences of subtropical jet and Tibetan Plateau on precipitation pattern in Asia : Insights from regional climate modeling

    NARCIS (Netherlands)

    Sato, Tomonori

    2009-01-01

    Large topographic features, like the Tibetan Plateau (TP) and the Rocky Mountains, have significant impacts on Earth's climate. Numerical experiments were carried out using a regional climate model in order to study the sensitivity of rainfall distribution to the TP's thermal/dynamic effects and

  17. Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

    Science.gov (United States)

    Beranová, Romana; Kyselý, Jan; Hanel, Martin

    2018-04-01

    The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May-September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.

  18. Adapting crop rotations to climate change in regional impact modelling assessments.

    Science.gov (United States)

    Teixeira, Edmar I; de Ruiter, John; Ausseil, Anne-Gaelle; Daigneault, Adam; Johnstone, Paul; Holmes, Allister; Tait, Andrew; Ewert, Frank

    2018-03-01

    The environmental and economic sustainability of future cropping systems depends on adaptation to climate change. Adaptation studies commonly rely on agricultural systems models to integrate multiple components of production systems such as crops, weather, soil and farmers' management decisions. Previous adaptation studies have mostly focused on isolated monocultures. However, in many agricultural regions worldwide, multi-crop rotations better represent local production systems. It is unclear how adaptation interventions influence crops grown in sequences. We develop a catchment-scale assessment to investigate the effects of tactical adaptations (choice of genotype and sowing date) on yield and underlying crop-soil factors of rotations. Based on locally surveyed data, a silage-maize followed by catch-crop-wheat rotation was simulated with the APSIM model for the RCP 8.5 emission scenario, two time periods (1985-2004 and 2080-2100) and six climate models across the Kaituna catchment in New Zealand. Results showed that direction and magnitude of climate change impacts, and the response to adaptation, varied spatially and were affected by rotation carryover effects due to agronomical (e.g. timing of sowing and harvesting) and soil (e.g. residual nitrogen, N) aspects. For example, by adapting maize to early-sowing dates under a warmer climate, there was an advance in catch crop establishment which enhanced residual soil N uptake. This dynamics, however, differed with local environment and choice of short- or long-cycle maize genotypes. Adaptation was insufficient to neutralize rotation yield losses in lowlands but consistently enhanced yield gains in highlands, where other constraints limited arable cropping. The positive responses to adaptation were mainly due to increases in solar radiation interception across the entire growth season. These results provide deeper insights on the dynamics of climate change impacts for crop rotation systems. Such knowledge can be used

  19. Future Changes in Surface Runoff over Korea Projected by a Regional Climate Model under A1B Scenario

    Directory of Open Access Journals (Sweden)

    Ji-Woo Lee

    2014-01-01

    Full Text Available This study assesses future change of surface runoff due to climate change over Korea using a regional climate model (RCM, namely, the Global/Regional Integrated Model System (GRIMs, Regional Model Program (RMP. The RMP is forced by future climate scenario, namely, A1B of Intergovernmental Panel on Climate Change (IPCC Fourth Assessment Report (AR4. The RMP satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation. The distribution of monsoonal precipitation-related runoff is adequately captured by the RMP. In the future (2040–2070 simulation, it is shown that the increasing trend of temperature has significant impacts on the intra-annual runoff variation. The variability of runoff is increased in summer; moreover, the strengthened possibility of extreme occurrence is detected in the future climate. This study indicates that future climate projection, including surface runoff and its variability over Korea, can be adequately addressed on the RMP testbed. Furthermore, this study reflects that global warming affects local hydrological cycle by changing major water budget components. This study adduces that the importance of runoff should not be overlooked in regional climate studies, and more elaborate presentation of fresh-water cycle is needed to close hydrological circulation in RCMs.

  20. A New Estimate of North American Mountain Snow Accumulation From Regional Climate Model Simulations

    Science.gov (United States)

    Wrzesien, Melissa L.; Durand, Michael T.; Pavelsky, Tamlin M.; Kapnick, Sarah B.; Zhang, Yu; Guo, Junyi; Shum, C. K.

    2018-02-01

    Despite the importance of mountain snowpack to understanding the water and energy cycles in North America's montane regions, no reliable mountain snow climatology exists for the entire continent. We present a new estimate of mountain snow water equivalent (SWE) for North America from regional climate model simulations. Climatological peak SWE in North America mountains is 1,006 km3, 2.94 times larger than previous estimates from reanalyses. By combining this mountain SWE value with the best available global product in nonmountain areas, we estimate peak North America SWE of 1,684 km3, 55% greater than previous estimates. In our simulations, the date of maximum SWE varies widely by mountain range, from early March to mid-April. Though mountains comprise 24% of the continent's land area, we estimate that they contain 60% of North American SWE. This new estimate is a suitable benchmark for continental- and global-scale water and energy budget studies.

  1. Does Dynamical Downscaling Introduce Novel Information in Climate Model Simulations of Recipitation Change over a Complex Topography Region?

    Science.gov (United States)

    Tselioudis, George; Douvis, Costas; Zerefos, Christos

    2012-01-01

    Current climate and future climate-warming runs with the RegCM Regional Climate Model (RCM) at 50 and 11 km-resolutions forced by the ECHAM GCM are used to examine whether the increased resolution of the RCM introduces novel information in the precipitation field when the models are run for the mountainous region of the Hellenic peninsula. The model results are inter-compared with the resolution of the RCM output degraded to match that of the GCM, and it is found that in both the present and future climate runs the regional models produce more precipitation than the forcing GCM. At the same time, the RCM runs produce increases in precipitation with climate warming even though they are forced with a GCM that shows no precipitation change in the region. The additional precipitation is mostly concentrated over the mountain ranges, where orographic precipitation formation is expected to be a dominant mechanism. It is found that, when examined at the same resolution, the elevation heights of the GCM are lower than those of the averaged RCM in the areas of the main mountain ranges. It is also found that the majority of the difference in precipitation between the RCM and the GCM can be explained by their difference in topographic height. The study results indicate that, in complex topography regions, GCM predictions of precipitation change with climate warming may be dry biased due to the GCM smoothing of the regional topography.

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

    Science.gov (United States)

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

    2015-02-01

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

  3. Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

    Science.gov (United States)

    Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

    2018-01-01

    Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are

  4. Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method

    Science.gov (United States)

    Li, Y.; Kurkute, S.; Chen, L.

    2017-12-01

    Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution.

  5. Climatic features of the Red Sea from a regional assimilative model

    KAUST Repository

    Viswanadhapalli, Yesubabu; Dasari, Hari Prasad; Langodan, Sabique; Challa, Venkata Srinivas; Hoteit, Ibrahim

    2016-01-01

    over the Red Sea compared to global analysis data from the National Centers for Environmental Prediction. We use the dataset to describe the atmospheric climatic conditions over the Red Sea region. © 2016 Royal Meteorological Society.

  6. Methodological challenges to bridge the gap between regional climate and hydrology models

    Science.gov (United States)

    Bozhinova, Denica; José Gómez-Navarro, Juan; Raible, Christoph; Felder, Guido

    2017-04-01

    The frequency and severity of floods worldwide, together with their impacts, are expected to increase under climate change scenarios. It is therefore very important to gain insight into the physical mechanisms responsible for such events in order to constrain the associated uncertainties. Model simulations of the climate and hydrological processes are important tools that can provide insight in the underlying physical processes and thus enable an accurate assessment of the risks. Coupled together, they can provide a physically consistent picture that allows to assess the phenomenon in a comprehensive way. However, climate and hydrological models work at different temporal and spatial scales, so there are a number of methodological challenges that need to be carefully addressed. An important issue pertains the presence of biases in the simulation of precipitation. Climate models in general, and Regional Climate models (RCMs) in particular, are affected by a number of systematic biases that limit their reliability. In many studies, prominently the assessment of changes due to climate change, such biases are minimised by applying the so-called delta approach, which focuses on changes disregarding absolute values that are more affected by biases. However, this approach is not suitable in this scenario, as the absolute value of precipitation, rather than the change, is fed into the hydrological model. Therefore, bias has to be previously removed, being this a complex matter where various methodologies have been proposed. In this study, we apply and discuss the advantages and caveats of two different methodologies that correct the simulated precipitation to minimise differences with respect an observational dataset: a linear fit (FIT) of the accumulated distributions and Quantile Mapping (QM). The target region is Switzerland, and therefore the observational dataset is provided by MeteoSwiss. The RCM is the Weather Research and Forecasting model (WRF), driven at the

  7. A Bayesian posterior predictive framework for weighting ensemble regional climate models

    Directory of Open Access Journals (Sweden)

    Y. Fan

    2017-06-01

    Full Text Available We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.

  8. Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

    Science.gov (United States)

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

    2018-04-01

    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. 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. Monthly temperature 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. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. 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

  9. Capturing flood-to-drought transitions in regional climate model simulations

    Science.gov (United States)

    Anders, Ivonne; Haslinger, Klaus; Hofstätter, Michael; Salzmann, Manuela; Resch, Gernot

    2017-04-01

    In previous studies atmospheric cyclones have been investigated in terms of related precipitation extremes in Central Europe. Mediterranean (Vb-like) cyclones are of special relevance as they are frequently related to high atmospheric moisture fluxes leading to floods and landslides in the Alpine region. Another focus in this area is on droughts, affecting soil moisture and surface and sub-surface runoff as well. Such events develop differently depending on available pre-saturation of water in the soil. In a first step we investigated two time periods which encompass a flood event and a subsequent drought on very different time scales, one long lasting transition (2002/2003) and a rather short one between May and August 2013. In a second step we extended the investigation to the long time period 1950-2016. We focused on high spatial and temporal scales and assessed the currently achievable accuracy in the simulation of the Vb-events on one hand and following drought events on the other hand. The state-of-the-art regional climate model CCLM is applied in hindcast-mode simulating the single events described above, but also the time from 1948 to 2016 to evaluate the results from the short runs to be valid for the long time period. Besides the conventional forcing of the regional climate model at its lateral boundaries, a spectral nudging technique is applied. The simulations covering the European domain have been varied systematically different model parameters. The resulting precipitation amounts have been compared to E-OBS gridded European precipitation data set and a recent high spatially resolved precipitation data set for Austria (GPARD-6). For the drought events the Standardized Precipitation Evapotranspiration Index (SPEI), soil moisture and runoff has been investigated. Varying the spectral nudging setup helps us to understand the 3D-processes during these events, but also to identify model deficiencies. To improve the simulation of such events in the past

  10. Quantification of climate tourism potential of Croatia based on measured data and regional modeling.

    Science.gov (United States)

    Brosy, Caroline; Zaninovic, Ksenija; Matzarakis, Andreas

    2014-08-01

    Tourism is one of the most important economic sectors in Croatia. The Adriatic coast is a popular travel destination for tourists, especially during the summer months. During their activities, tourists are affected by atmospheric conditions and therefore by weather and climate. Therefore, it is important to have reliable information about thermal conditions as well as their impacts on human beings. Here, the climate tourism potential of Croatia is presented and quantified on the basis of three selected stations in different climatic regions. The physiologically equivalent temperature is used for analysis as well as other climatic parameters relevant for tourism and recreation. The results already point to hot conditions for outdoor activities in summer during afternoons, especially along the coast but also for continental regions, resulting in a reduction of the climate tourism potential. In the future, this trend looks set to increase, possibly leading to a changing tourism sector in Croatia requiring adaptation and new strategies.

  11. Modelling and mapping climate change adaptability in the historic tourism region of the Salzkammergut in Austria

    Science.gov (United States)

    Berger, Stefan; Lang, Stefan; Pernkopf, Lena

    2017-04-01

    actual salt production site, some 800 km2 in size [Geuter 1913], it is now self-defined [Kurz 2006] as a magnet for tourism still steadily growing by attendance of municipalities on its northern fringe (2008: 54 municipalities, 2013: 59). The region is exemplarily for comparable regions in Austria or the Alps in terms of national/regional and transnational (UNFCCC) climate change adaptation strategies towards local/regional transfer and adjustment. Adaption remains an ambitious, cross-cutting issue with a range of societal areas and policy domains involved and to be integrated. The set of indicators to be chosen depends on the focus of the adaptation strategy. Here we focus on tourism, because it is of paramount importance for the well-being of the region from an economic point of view, but also from the perspective of sustainability and conservation of the historic heritage. In order to model the adaptive behaviour towards tourism, we work with the following twelve indicators: (1) bathing lakes / (2) skiing resorts, (4) connection to public transport, (10) bicycle ways, (5) average number of summer days / (6) heat days / (7) freezing days / (11) rain days, (8) temperature raise, (3) elevation a.s.l. / (9) slope, (12) cultural heritage. Using standardisation, we regionalise the set of indicators achieving a set of units that represent areas of uniform adaption behaviour, scaled to the policy scale and revealing in a spatial explicit manner the aggregated adaptability in terms of their potential to sustain tourism. The approach can be applied also to other transformative, yet strongly CC-affected mountain areas with a similar setting regarding their climate change adaptation potential. REFERENCES Folke, C. (2006) Resilience: The emergence of a perspective for social-ecological systems analyses. Global Environmental Change, 16, pp. 253-267. Geuter, K. P. (1913) Illustrierter Führer durch das Salzkammergut und Salzburg mit Umgebung, Linz. IPCC (2007) Fourth Assessment

  12. Effects of increasing aerosol on regional climate change in China: Observation and modeling

    Science.gov (United States)

    Qian, Y.; Leung, L.; Ghan, S. J.

    2002-12-01

    We present regional simulations of climate, aerosol properties, and direct radiative forcing and climatic effects of aerosol and analyze the pollutant emissions and observed climatic data during the latter decades of last century in China. The regional model generally captures the spatial distributions and seasonal pattern of temperature and precipitation. Aerosol extinction coefficient and aerosol optical depth are generally well simulated in both magnitude and spatial distribution, which provides a reliable foundation for estimating the radiative forcing and climatic effects of aerosol. The radiative forcing of aerosol is in the range of -1 to -14 W m-2 in autumn and summer and -1 to -9 W m-2 in spring and winter, with substantial spatial variability at the sub-regional scale. A strong maximum in negative radiative forcing corresponding to the maximum optical depth is found over the Sichuan Basin, where emission as well as relative humidity are high, and stagnant atmospheric conditions inhibit pollutants dispersion. Negative radiative forcing of aerosol induces a surface cooling, which is stronger in the range of -0.6 to -1.2oC in autumn and winter than in spring (-0.3 to -0.6oC) and summer (0.0 to -0.9oC) over the Sichuan Basin and East China due to more significant effects of cloud and precipitation in the summer and spring. Aerosol-induced cooling is mainly contributed by cooling in the daytime temperature. The cooling reaches a maximum and is statistically significant in the Sichuan Basin. The effect of aerosol on precipitation is not evident in our simulations. The temporal and spatial patterns of temperature trends observed in the second half of the twentieth century, including the asymmetric daily maximum and minimum temperature trends, are at least qualitatively consistent with the simulated aerosol-induced cooling over the Sichuan Basin and East China. It supports the hypothesis that the observed temperature trends during the latter decades of the

  13. Application of remote sensing for analyzing climatic variation in the boreal and subarctic regions of Canada and for validating the Canadian Regional Climate Model; Application de la teledetection a l'analyse de la variabilite climatique des regions boreales et subarctiques du Canada et a la validation du modele regional canadien du climat

    Energy Technology Data Exchange (ETDEWEB)

    Fillol, E.J.

    2003-07-01

    This study examined climate variations over the past few decades as well as the tools used to model future climate. The study included an interpretation of the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) time series data at the continental spatial scale. Data collected over a period of two decades was used to study and monitor Canada's boreal ecosystem activity and to observe recent climatic change. The study involved the use of classical parameters associated with remote sensing in the visible and thermal infrared spectra for vegetation activity and land-surface temperatures. Problems associated with instrumental drift and inter-satellite adjustment were minimized by choosing indicators for the length of the growing season, annual growing degree-days and ecotone displacement. Climate variations over the past twenty years were compared with daily meteorological data of temperature, precipitation and snow cover. Rapid cycle climatic phenomena such as the El Nino and La Nina appear to have influenced the central region of Canada. The North Atlantic Oscillation and Arctic Oscillation also influenced the climate regime of Canada and annual growing degree-days. Indicators for vegetation activity and land-surface temperature suggest that a North-South disparity exists over Canada. A warming trend with an increased growing season was observed for the region north of the 55 parallel, while southern regions appear to be cooling. This study also used remote sensing to validate the Canadian Regional Climate Model (CRCM) through a comparison of ground temperature values modelled by the CRCM with composite satellite temperatures. The results indicate a small under-estimation of the CRCM ground temperature during the summer due to an overestimation of the precipitation rate. It was concluded that climate models such as the CRCM are useful in making reliable predictions of future climate trends.

  14. Regional Climate Models as a Tool for Assessing Changes in the Laurentian Great Lakes Net Basin Supply

    Science.gov (United States)

    Music, B.; Mailhot, E.; Nadeau, D.; Irambona, C.; Frigon, A.

    2017-12-01

    Over the last decades, there has been growing concern about the effects of climate change on the Great Lakes water supply. Most of the modelling studies focusing on the Laurentian Great Lakes do not allow two-way exchanges of water and energy between the atmosphere and the underlying surface, and therefore do not account for important feedback mechanisms. Moreover, energy budget constraint at the land surface is not usually taken into account. To address this issue, several recent climate change studies used high resolution Regional Climate Models (RCMs) for evaluating changes in the hydrological regime of the Great Lakes. As RCMs operate on the concept of water and energy conservation, an internal consistency of the simulated energy and water budget components is assured. In this study we explore several recently generated Regional Climate Model (RCM) simulations to investigate the Great Lakes' Net Basin Supply (NBS) in a changing climate. These include simulations of the Canadian Regional Climate Model (CRCM5) supplemented by simulations from several others RCMs participating to the North American CORDEX project (CORDEX-NA). The analysis focuses on the NBS extreme values under nonstationary conditions. The results are expected to provide useful information to the industries in the Great Lakes that all need to include accurate climate change information in their long-term strategy plans to better anticipate impacts of low and/or high water levels.

  15. Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

    Energy Technology Data Exchange (ETDEWEB)

    Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Cassano, John J. [Univ. of Colorado, Boulder, CO (United States); Gutowski, Jr., William J. [Iowa State Univ., Ames, IA (United States); Lipscomb, William H. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nijssen, Bart [Univ. of Washington, Seattle, WA (United States); Roberts, Andrew [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Robertson, William [Univ. of Texas, El Paso, TX (United States); Tulaczyk, Slawek [Univ. of California, Santa Cruz, CA (United States); Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States)

    2011-05-15

    The primary outcome of the project was the development of the Regional Arctic System Model (RASM) and evaluation of its individual model components, coupling among them and fully coupled model results. Overall, we have demonstrated that RASM produces realistic mean and seasonal surface climate as well as its interannual and decadal variability and trends.

  16. Downscaling a global climate model to simulate climate change over the US and the implication on regional and urban air quality

    Directory of Open Access Journals (Sweden)

    M. Trail

    2013-09-01

    Full Text Available Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US, one region during summer (Texas, and one region where changes potentially would lead to better air quality during spring (Northeast. Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air

  17. Hydrological processes in regional climate model simulations of the central United States flood of June-July 1993

    DEFF Research Database (Denmark)

    Anderson, Christopher J.; Arritt, Raymond W.; Takle, Eugene S.

    2003-01-01

    Thirteen regional climate model (RCM) simulations of June-July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° X 10° subregion of the upper Mississippi River basin, containing the region of maximum...

  18. On the use of nudging techniques for regional climate modeling: application for tropical convection

    Science.gov (United States)

    Pohl, Benjamin; Crétat, Julien

    2014-09-01

    Using a large set of WRF ensemble simulations at 70-km horizontal resolution over a domain encompassing the Warm Pool region and its surroundings [45°N-45°S, 10°E-240°E], this study aims at quantifying how nudging techniques can modify the simulation of deep atmospheric convection. Both seasonal mean climate, transient variability at intraseasonal timescales, and the respective weight of internal (stochastic) and forced (reproducible) variability are considered. Sensitivity to a large variety of nudging settings (nudged variables and layers and nudging strength) and to the model physics (using 3 convective parameterizations) is addressed. Integrations are carried out during a 7-month season characterized by neutral background conditions and strong intraseasonal variability. Results show that (1) the model responds differently to the nudging from one parameterization to another. Biases are decreased by ~50 % for Betts-Miller-Janjic convection against 17 % only for Grell-Dévényi, the scheme producing yet the largest biases; (2) relaxing air temperature is the most efficient way to reduce biases, while nudging the wind increases most co-variability with daily observations; (3) the model's internal variability is drastically reduced and mostly depends on the nudging strength and nudged variables; (4) interrupting the relaxation before the end of the simulations leads to an abrupt convergence towards the model's natural solution, with no clear effects on the simulated climate after a few days. The usefulness and limitations of the approach are finally discussed through the example of the Madden-Julian Oscillation, that the model fails at simulating and that can be artificially and still imperfectly reproduced in relaxation experiments.

  19. Spectral nudging to eliminate the effects of domain position and geometry in regional climate model simulations

    Science.gov (United States)

    Miguez-Macho, Gonzalo; Stenchikov, Georgiy L.; Robock, Alan

    2004-07-01

    It is well known that regional climate simulations are sensitive to the size and position of the domain chosen for calculations. Here we study the physical mechanisms of this sensitivity. We conducted simulations with the Regional Atmospheric Modeling System (RAMS) for June 2000 over North America at 50 km horizontal resolution using a 7500 km × 5400 km grid and NCEP/NCAR reanalysis as boundary conditions. The position of the domain was displaced in several directions, always maintaining the U.S. in the interior, out of the buffer zone along the lateral boundaries. Circulation biases developed a large scale structure, organized by the Rocky Mountains, resulting from a systematic shifting of the synoptic wave trains that crossed the domain. The distortion of the large-scale circulation was produced by interaction of the modeled flow with the lateral boundaries of the nested domain and varied when the position of the grid was altered. This changed the large-scale environment among the different simulations and translated into diverse conditions for the development of the mesoscale processes that produce most of precipitation for the Great Plains in the summer season. As a consequence, precipitation results varied, sometimes greatly, among the experiments with the different grid positions. To eliminate the dependence of results on the position of the domain, we used spectral nudging of waves longer than 2500 km above the boundary layer. Moisture was not nudged at any level. This constrained the synoptic scales to follow reanalysis while allowing the model to develop the small-scale dynamics responsible for the rainfall. Nudging of the large scales successfully eliminated the variation of precipitation results when the grid was moved. We suggest that this technique is necessary for all downscaling studies with regional models with domain sizes of a few thousand kilometers and larger embedded in global models.

  20. Modeling water scarcity and droughts for policy adaptation to climate change in arid and semiarid regions

    Science.gov (United States)

    Kahil, Mohamed Taher; Dinar, Ariel; Albiac, Jose

    2015-03-01

    Growing water extractions combined with emerging demands for environment protection increase competition for scarce water resources worldwide, especially in arid and semiarid regions. In those regions, climate change is projected to exacerbate water scarcity and increase the recurrence and intensity of droughts. These circumstances call for methodologies that can support the design of sustainable water management. This paper presents a hydro-economic model that links a reduced form hydrological component, with economic and environmental components. The model is applied to an arid and semiarid basin in Southeastern Spain to analyze the effects of droughts and to assess alternative adaptation policies. Results indicate that drought events have large impacts on social welfare, with the main adjustments sustained by irrigation and the environment. The water market policy seems to be a suitable option to overcome the negative economic effects of droughts, although the environmental effects may weaken its advantages for society. The environmental water market policy, where water is acquired for the environment, is an appealing policy to reap the private benefits of markets while protecting ecosystems. The current water management approach in Spain, based on stakeholders' cooperation, achieves almost the same economic outcomes and better environmental outcomes compared to a pure water market. These findings call for a reconsideration of the current management in arid and semiarid basins around the world. The paper illustrates the potential of hydro-economic modeling for integrating the multiple dimensions of water resources, becoming a valuable tool in the advancement of sustainable water management policies.

  1. Evaluation of trends in high temperature extremes in north-western Europe in regional climate models

    International Nuclear Information System (INIS)

    Min, E; Hazeleger, W; Van Oldenborgh, G J; Sterl, A

    2013-01-01

    Projections of future changes in weather extremes on the regional and local scale depend on a realistic representation of trends in extremes in regional climate models (RCMs). We have tested this assumption for moderate high temperature extremes (the annual maximum of the daily maximum 2 m temperature, T ann.max ). Linear trends in T ann.max from historical runs of 14 RCMs driven by atmospheric reanalysis data are compared with trends in gridded station data. The ensemble of RCMs significantly underestimates the observed trends over most of the north-western European land surface. Individual models do not fare much better, with even the best performing models underestimating observed trends over large areas. We argue that the inability of RCMs to reproduce observed trends is probably not due to errors in large-scale circulation. There is also no significant correlation between the RCM T ann.max trends and trends in radiation or Bowen ratio. We conclude that care should be taken when using RCM data for adaptation decisions. (letter)

  2. THE EVOLUTION OF ANNUAL MEAN TEMPERATURE AND PRECIPITATION QUANTITY VARIABILITY BASED ON ESTIMATED CHANGES BY THE REGIONAL CLIMATIC MODELS

    Directory of Open Access Journals (Sweden)

    Paula Furtună

    2013-03-01

    Full Text Available Climatic changes are representing one of the major challenges of our century, these being forcasted according to climate scenarios and models, which represent plausible and concrete images of future climatic conditions. The results of climate models comparison regarding future water resources and temperature regime trend can become a useful instrument for decision makers in choosing the most effective decisions regarding economic, social and ecologic levels. The aim of this article is the analysis of temperature and pluviometric variability at the closest grid point to Cluj-Napoca, based on data provided by six different regional climate models (RCMs. Analysed on 30 year periods (2001-2030,2031-2060 and 2061-2090, the mean temperature has an ascending general trend, with great varability between periods. The precipitation expressed trough percentage deviation shows a descending general trend, which is more emphazied during 2031-2060 and 2061-2090.

  3. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model

    Energy Technology Data Exchange (ETDEWEB)

    Cassano, John [Principal Investigator

    2013-06-30

    The primary research task completed for this project was the development of the Regional Arctic Climate Model (RACM). This involved coupling existing atmosphere, ocean, sea ice, and land models using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) coupler (CPL7). RACM is based on the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP) ocean model, the CICE sea ice model, and the Variable Infiltration Capacity (VIC) land model. A secondary research task for this project was testing and evaluation of WRF for climate-scale simulations on the large pan-Arctic model domain used in RACM. This involved identification of a preferred set of model physical parameterizations for use in our coupled RACM simulations and documenting any atmospheric biases present in RACM.

  4. Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

    Energy Technology Data Exchange (ETDEWEB)

    Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States)

    2016-10-17

    This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate through polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.

  5. Tropospheric aerosols radiation feedback on the climate of Pearl River Delta Region using an air quality model

    Science.gov (United States)

    Nduka, I. C.

    2016-12-01

    The Pearl River Delta (PRD) region, one of the most vibrant economic regions in China has been witnessing rapid population, economic and structural growth and development. It is also one of the regions mostly polluted with trace gases and particulates. Recent reviews show large uncertainties in climate modification studies, indicating the need for further investigations, such as the role of tropospheric aerosols on direct and indirect climate modification. The aim of this research is to appraise the impacts of tropospheric aerosols on the climate of PRD region. An integrated air quality downscale meteorology and air quality from regional scale (27km) to local scale (3km). The model will be evaluated for both meteorology and air quality by comparing model results with measurements. The radiative forcing of tropospheric aerosols will also be determined so as to estimate the feedbacks and impacts on the climate. This research, when completed, is expected to improve our understanding of tropospheric aerosol-cloud thermodynamic interactions at regional and local scales, thus enhancing our knowledge of the regional and local climate system, which is anticipated to provide critical references for formulating sustainable environment and air quality policies.

  6. Assessment of the Ability of Contemporary Climate Models to Assess Adequately the Risk of Possible Regional Anomalies and Trends

    Science.gov (United States)

    Mokhov, I. I.

    2018-04-01

    The results describing the ability of contemporary global and regional climate models not only to assess the risk of general trends of changes but also to predict qualitatively new regional effects are presented. In particular, model simulations predicted spatially inhomogeneous changes in the wind and wave conditions in the Arctic basins, which have been confirmed in recent years. According to satellite and reanalysis data, a qualitative transition to the regime predicted by model simulations occurred about a decade ago.

  7. Performance of the CORDEX regional climate models in simulating offshore wind and wind potential

    Science.gov (United States)

    Kulkarni, Sumeet; Deo, M. C.; Ghosh, Subimal

    2018-03-01

    This study is oriented towards quantification of the skill addition by regional climate models (RCMs) in the parent general circulation models (GCMs) while simulating wind speed and wind potential with particular reference to the Indian offshore region. To arrive at a suitable reference dataset, the performance of wind outputs from three different reanalysis datasets is evaluated. The comparison across the RCMs and their corresponding parent GCMs is done on the basis of annual/seasonal wind statistics, intermodel bias, wind climatology, and classes of wind potential. It was observed that while the RCMs could simulate spatial variability of winds, well for certain subregions, they generally failed to replicate the overall spatial pattern, especially in monsoon and winter. Various causes of biases in RCMs were determined by assessing corresponding maps of wind vectors, surface temperature, and sea-level pressure. The results highlight the necessity to carefully assess the RCM-yielded winds before using them for sensitive applications such as coastal vulnerability and hazard assessment. A supplementary outcome of this study is in form of wind potential atlas, based on spatial distribution of wind classes. This could be beneficial in suitably identifying viable subregions for developing offshore wind farms by intercomparing both the RCM and GCM outcomes. It is encouraging that most of the RCMs and GCMs indicate that around 70% of the Indian offshore locations in monsoon would experience mean wind potential greater than 200 W/m2.

  8. Sensitivity analysis with the regional climate model COSMO-CLM over the CORDEX-MENA domain

    Science.gov (United States)

    Bucchignani, E.; Cattaneo, L.; Panitz, H.-J.; Mercogliano, P.

    2016-02-01

    The results of a sensitivity work based on ERA-Interim driven COSMO-CLM simulations over the Middle East-North Africa (CORDEX-MENA) domain are presented. All simulations were performed at 0.44° spatial resolution. The purpose of this study was to ascertain model performances with respect to changes in physical and tuning parameters which are mainly related to surface, convection, radiation and cloud parameterizations. Evaluation was performed for the whole CORDEX-MENA region and six sub-regions, comparing a set of 26 COSMO-CLM runs against a combination of available ground observations, satellite products and reanalysis data to assess temperature, precipitation, cloud cover and mean sea level pressure. The model proved to be very sensitive to changes in physical parameters. The optimized configuration allows COSMO-CLM to improve the simulated main climate features of this area. Its main characteristics consist in the new parameterization of albedo, based on Moderate Resolution Imaging Spectroradiometer data, and the new parameterization of aerosol, based on NASA-GISS AOD distributions. When applying this configuration, Mean Absolute Error values for the considered variables are as follows: about 1.2 °C for temperature, about 15 mm/month for precipitation, about 9 % for total cloud cover, and about 0.6 hPa for mean sea level pressure.

  9. Estimating Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR

    NARCIS (Netherlands)

    Fettweis, X.; Franco, B.; Tedesco, M.; van Angelen, J.H.; Lenaerts, J.T.M.; van den Broeke, M.R.; Gallee, H

    2012-01-01

    We report future projections of Surface Mass Balance (SMB) over the Greenland ice sheet (GrIS) obtained with the regional climate model MAR, forced by the outputs of three CMIP5 General Circulation Models (GCMs) when considering two different warming scenarios (RCP 4.5 and RCP 8.5). The GCMs

  10. Representation of monsoon intraseasonal oscillations in regional climate model: sensitivity to convective physics

    KAUST Repository

    Umakanth, U.

    2015-11-07

    The aim of the study is to evaluate the performance of regional climate model (RegCM) version 4.4 over south Asian CORDEX domain to simulate seasonal mean and monsoon intraseasonal oscillations (MISOs) during Indian summer monsoon. Three combinations of Grell (G) and Emanuel (E) cumulus schemes namely, RegCM-EG, RegCM-EE and RegCM-GE have been used. The model is initialized at 1st January, 2000 for a 13-year continuous simulation at a spatial resolution of 50 km. The models reasonably simulate the seasonal mean low level wind pattern though they differ in simulating mean precipitation pattern. All models produce dry bias in precipitation over Indian land region except in RegCM-EG where relatively low value of dry bias is observed. On seasonal scale, the performance of RegCM-EG is more close to observation though it fails at intraseasonal time scales. In wave number-frequency spectrum, the observed peak in zonal wind (850 hPa) at 40–50 day scale is captured by all models with a slight change in amplitude, however, the 40–50 day peak in precipitation is completely absent in RegCM-EG. The space–time characteristics of MISOs are well captured by RegCM-EE over RegCM-GE, however it fails to show the eastward propagation of the convection across the Maritime Continent. Except RegCM-EE all other models completely underestimates the moisture advection from Equatorial Indian Ocean onto Indian land region during life-cycle of MISOs. The characteristics of MISOs are studied for strong (SM) and weak (WM) monsoon years and the differences in model performances are analyzed. The wavelet spectrum of rainfall over central India denotes that, the SM years are dominated by high frequency oscillations (period <20 days) whereas little higher periods (>30 days) along with dominated low periods (<20 days) observed during WM years. During SM, RegCM-EE is dominated with high frequency oscillations (period <20 days) whereas in WM, RegCM-EE is dominated with periods >20

  11. Performance of Regional Climate Model in Simulating Monsoon Onset Over Indian Subcontinent

    Science.gov (United States)

    Bhatla, R.; Mandal, B.; Verma, Shruti; Ghosh, Soumik; Mall, R. K.

    2018-06-01

    The performance of various Convective Parameterization Schemes (CPSs) of Regional Climate Model version 4.3 (RegCM-4.3) for simulation of onset phase of Indian summer monsoon (ISM) over Kerala was studied for the period of 2001-2010. The onset date and its associated spatial variation were simulated using RegCM-4.3 four core CPS, namely Kuo, Tiedtke, Emanuel and Grell; and with two mixed convection schemes Mix98 (Emanuel over land and Grell over ocean) and Mix99 (Grell over land and Emanuel over ocean) on the basis of criteria given by the India Meteorological Department (IMD) (Pai and Rajeevan in Indian summer monsoon onset: variability and prediction. National Climate Centre, India Meteorological Department, 2007). It has been found that out of six CPS, two schemes, namely Tiedtke and Mix99 simulated the onset date properly. The onset phase is characterized with several transition phases of atmosphere. Therefore, to study the thermal response or the effect of different sea surface temperature (SST), namely ERA interim (ERSST) and weekly optimal interpolation (OI_WK SST) on Indian summer monsoon, the role of two different types of SST has been used to investigate the simulated onset date. In addition, spatial atmospheric circulation pattern during onset phase were analyzed using reanalyze dataset of ERA Interim (EIN15) and National Oceanic and Atmospheric Administration (NOAA), respectively, for wind and outgoing long-wave radiation (OLR) pattern. Among the six convective schemes of RegCM-4.3 model, Tiedtke is in good agreement with actual onset dates and OI_WK SST forcing is better for simulating onset of ISM over Kerala.

  12. Greenland ice sheet surface mass balance: evaluating simulations and making projections with regional climate models

    Directory of Open Access Journals (Sweden)

    J. G. L. Rae

    2012-11-01

    Full Text Available Four high-resolution regional climate models (RCMs have been set up for the area of Greenland, with the aim of providing future projections of Greenland ice sheet surface mass balance (SMB, and its contribution to sea level rise, with greater accuracy than is possible from coarser-resolution general circulation models (GCMs. This is the first time an intercomparison has been carried out of RCM results for Greenland climate and SMB. Output from RCM simulations for the recent past with the four RCMs is evaluated against available observations. The evaluation highlights the importance of using a detailed snow physics scheme, especially regarding the representations of albedo and meltwater refreezing. Simulations with three of the RCMs for the 21st century using SRES scenario A1B from two GCMs produce trends of between −5.5 and −1.1 Gt yr−2 in SMB (equivalent to +0.015 and +0.003 mm sea level equivalent yr−2, with trends of smaller magnitude for scenario E1, in which emissions are mitigated. Results from one of the RCMs whose present-day simulation is most realistic indicate that an annual mean near-surface air temperature increase over Greenland of ~ 2°C would be required for the mass loss to increase such that it exceeds accumulation, thereby causing the SMB to become negative, which has been suggested as a threshold beyond which the ice sheet would eventually be eliminated.

  13. Regional impacts of climate change and atmospheric CO2 on future ocean carbon uptake: a multi model linear feedback analysis

    International Nuclear Information System (INIS)

    Roy, Tilla; Bopp, Laurent; Gehlen, Marion; Cadule, Patricia; Schneider, Birgit; Frolicher, Thomas L.; Segschneider, Joachim; Tjiputra, Jerry; Heinze, Christoph; Joos, Fortunat

    2011-01-01

    The increase in atmospheric CO 2 over this century depends on the evolution of the oceanic air-sea CO 2 uptake, which will be driven by the combined response to rising atmospheric CO 2 itself and climate change. Here, the future oceanic CO 2 uptake is simulated using an ensemble of coupled climate-carbon cycle models. The models are driven by CO 2 emissions from historical data and the Special Report on Emissions Scenarios (SRES) A2 high-emission scenario. A linear feedback analysis successfully separates the regional future (2010-2100) oceanic CO 2 uptake into a CO 2 -induced component, due to rising atmospheric CO 2 concentrations, and a climate-induced component, due to global warming. The models capture the observation based magnitude and distribution of anthropogenic CO 2 uptake. The distributions of the climate-induced component are broadly consistent between the models, with reduced CO 2 uptake in the sub polar Southern Ocean and the equatorial regions, owing to decreased CO 2 solubility; and reduced CO 2 uptake in the mid-latitudes, owing to decreased CO 2 solubility and increased vertical stratification. The magnitude of the climate-induced component is sensitive to local warming in the southern extra-tropics, to large freshwater fluxes in the extra-tropical North Atlantic Ocean, and to small changes in the CO 2 solubility in the equatorial regions. In key anthropogenic CO 2 uptake regions, the climate-induced component offsets the CO 2 - induced component at a constant proportion up until the end of this century. This amounts to approximately 50% in the northern extra-tropics and 25% in the southern extra-tropics and equatorial regions. Consequently, the detection of climate change impacts on anthropogenic CO 2 uptake may be difficult without monitoring additional tracers, such as oxygen. (authors)

  14. Regional impacts of climate change and atmospheric CO2 on future ocean carbon uptake: a multi model linear feedback analysis

    International Nuclear Information System (INIS)

    Roy, Tilla; Bopp, Laurent; Gehlen, Marion; Cadule, Patricia

    2011-01-01

    The increase in atmospheric CO 2 over this century depends on the evolution of the oceanic air-sea CO 2 uptake, which will be driven by the combined response to rising atmospheric CO 2 itself and climate change. Here, the future oceanic CO 2 uptake is simulated using an ensemble of coupled climate-carbon cycle models. The models are driven by CO 2 emissions from historical data and the Special Report on Emissions Scenarios (SRES) A2 high-emission scenario. A linear feedback analysis successfully separates the regional future (2010-2100) oceanic CO 2 uptake into a CO 2 -induced component, due to rising atmospheric CO 2 concentrations, and a climate-induced component, due to global warming. The models capture the observation based magnitude and distribution of anthropogenic CO 2 uptake. The distributions of the climate-induced component are broadly consistent between the models, with reduced CO 2 uptake in the sub-polar Southern Ocean and the equatorial regions, owing to decreased CO 2 solubility; and reduced CO 2 uptake in the mid latitudes, owing to decreased CO 2 solubility and increased vertical stratification. The magnitude of the climate-induced component is sensitive to local warming in the southern extra tropics, to large freshwater fluxes in the extra tropical North Atlantic Ocean, and to small changes in the CO 2 solubility in the equatorial regions. In key anthropogenic CO 2 uptake regions, the climate-induced component offsets the CO 2 - induced component at a constant proportion up until the end of this century. This amounts to approximately 50% in the northern extra tropics and 25% in the southern extra tropics and equatorial regions. Consequently, the detection of climate change impacts on anthropogenic CO 2 uptake may be difficult without monitoring additional tracers, such as oxygen. (authors)

  15. Impact of evolving greenhouse gas forcing on the warming signal in regional climate model experiments.

    Science.gov (United States)

    Jerez, S; López-Romero, J M; Turco, M; Jiménez-Guerrero, P; Vautard, R; Montávez, J P

    2018-04-03

    Variations in the atmospheric concentrations of greenhouse gases (GHG) may not be included as external forcing when running regional climate models (RCMs); at least, this is a non-regulated, non-documented practice. Here we investigate the so far unexplored impact of considering the rising evolution of the CO 2 , CH 4 , and N 2 O atmospheric concentrations on near-surface air temperature (TAS) trends, for both the recent past and the near future, as simulated by a state-of-the-art RCM over Europe. The results show that the TAS trends are significantly affected by 1-2 K century -1 , which under 1.5 °C global warming translates into a non-negligible impact of up to 1 K in the regional projections of TAS, similarly affecting projections for maximum and minimum temperatures. In some cases, these differences involve a doubling signal, laying further claim to careful reconsideration of the RCM setups with regard to the inclusion of GHG concentrations as an evolving external forcing which, for the sake of research reproducibility and reliability, should be clearly documented in the literature.

  16. The use of the k - {epsilon} turbulence model within the Rossby Centre regional ocean climate model: parameterization development and results

    Energy Technology Data Exchange (ETDEWEB)

    Markus Meier, H.E. [Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden). Rossby Centre

    2000-09-01

    As mixing plays a dominant role for the physics of an estuary like the Baltic Sea (seasonal heat storage, mixing in channels, deep water mixing), different mixing parameterizations for use in 3D Baltic Sea models are discussed and compared. For this purpose two different OGCMs of the Baltic Sea are utilized. Within the Swedish regional climate modeling program, SWECLIM, a 3D coupled ice-ocean model for the Baltic Sea has been coupled with an improved version of the two-equation k - {epsilon} turbulence model with corrected dissipation term, flux boundary conditions to include the effect of a turbulence enhanced layer due to breaking surface gravity waves and a parameterization for breaking internal waves. Results of multi-year simulations are compared with observations. The seasonal thermocline is simulated satisfactory and erosion of the halocline is avoided. Unsolved problems are discussed. To replace the controversial equation for dissipation the performance of a hierarchy of k-models has been tested and compared with the k - {epsilon} model. In addition, it is shown that the results of the mixing parameterization depend very much on the choice of the ocean model. Finally, the impact of two mixing parameterizations on Baltic Sea climate is investigated. In this case the sensitivity of mean SST, vertical temperature and salinity profiles, ice season and seasonal cycle of heat fluxes is quite large.

  17. Large Scale Skill in Regional Climate Modeling and the Lateral Boundary Condition Scheme

    Science.gov (United States)

    Veljović, K.; Rajković, B.; Mesinger, F.

    2009-04-01

    Several points are made concerning the somewhat controversial issue of regional climate modeling: should a regional climate model (RCM) be expected to maintain the large scale skill of the driver global model that is supplying its lateral boundary condition (LBC)? Given that this is normally desired, is it able to do so without help via the fairly popular large scale nudging? Specifically, without such nudging, will the RCM kinetic energy necessarily decrease with time compared to that of the driver model or analysis data as suggested by a study using the Regional Atmospheric Modeling System (RAMS)? Finally, can the lateral boundary condition scheme make a difference: is the almost universally used but somewhat costly relaxation scheme necessary for a desirable RCM performance? Experiments are made to explore these questions running the Eta model in two versions differing in the lateral boundary scheme used. One of these schemes is the traditional relaxation scheme, and the other the Eta model scheme in which information is used at the outermost boundary only, and not all variables are prescribed at the outflow boundary. Forecast lateral boundary conditions are used, and results are verified against the analyses. Thus, skill of the two RCM forecasts can be and is compared not only against each other but also against that of the driver global forecast. A novel verification method is used in the manner of customary precipitation verification in that forecast spatial wind speed distribution is verified against analyses by calculating bias adjusted equitable threat scores and bias scores for wind speeds greater than chosen wind speed thresholds. In this way, focusing on a high wind speed value in the upper troposphere, verification of large scale features we suggest can be done in a manner that may be more physically meaningful than verifications via spectral decomposition that are a standard RCM verification method. The results we have at this point are somewhat

  18. Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region

    DEFF Research Database (Denmark)

    Xia, Jianyang; McGuire, A. David; Lawrence, David

    2017-01-01

    productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m−2 yr−1), most models produced higher NPP (309 ± 12 g C m−2 yr−1) over...... and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost...... regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change....

  19. Future hydroclimatological changes in South America based on an ensemble of regional climate models

    Science.gov (United States)

    Zaninelli, Pablo G.; Menéndez, Claudio G.; Falco, Magdalena; López-Franca, Noelia; Carril, Andrea F.

    2018-05-01

    Changes between two time slices (1961-1990 and 2071-2100) in hydroclimatological conditions for South America have been examined using an ensemble of regional climate models. Annual mean precipitation (P), evapotranspiration (E) and potential evapotranspiration (EP) are jointly considered through the balances of land water and energy. Drying or wetting conditions, associated with changes in land water availability and atmospheric demand, are analysed in the Budyko space. The water supply limit (E limited by P) is exceeded at about 2% of the grid points, while the energy limit to evapotranspiration (E = EP) is overall valid. Most of the continent, except for the southeast and some coastal areas, presents a shift toward drier conditions related to a decrease in water availability (the evaporation rate E/P increases) and, mostly over much of Brazil, to an increase in the aridity index (V = EP/P). These changes suggest less humid conditions with decreasing surface runoff over Amazonia and the Brazilian Highlands. In contrast, Argentina and the coasts of Ecuador and Peru are characterized by a tendency toward wetter conditions associated with an increase of water availability and a decrease of aridity index, primarily due to P increasing faster than both E and EP. This trend towards wetter soil conditions suggest that the chances of having larger periods of flooding and enhanced river discharges would increase over parts of southeastern South America. Interannual variability increases with V (for a given time slice) and with climate change (for a given aridity regimen). There are opposite interannual variability responses to the cliamte change in Argentina and Brazil by which the variability increases over the Brazilian Highlands and decreases in central-eastern Argentina.

  20. Analysis of future drought characteristics in China using the regional climate model CCLM

    Science.gov (United States)

    Huang, Jinlong; Zhai, Jianqing; Jiang, Tong; Wang, Yanjun; Li, Xiucang; Wang, Run; Xiong, Ming; Su, Buda; Fischer, Thomas

    2018-01-01

    In this paper, the intensity, area and duration of future droughts in China are analyzed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SPI and SPEI are used to evaluate the simulation ability of drought characteristics with the regional climate model COSMO-CLM (CCLM). The projected intensity and duration of future drought events are analyzed for the period 2016-2050 under three different respective concentration pathways (RCPs). The simulated and projected drought events are analyzed by applying the intensity-area-duration method. The results show that CCLM has a robust capability to simulate the average drought characteristics, while some regional disparities are not well captured, mainly the simulation of more drought events of shorter duration in Northwest China. For the future period 2016-2050, more intense dryness conditions are projected for China. An increase in evapotranspiration is found all over China, while a reduction in precipitation is apparent in the southern river basins. The increase in evapotranspiration plays an important role in the changes of future droughts over the northern river basins and southern river basins. Under RCP2.6, drought events of longer duration and with higher frequency are projected for the southwest and southeast of China. Under RCP4.5 and RCP8.5, a continuing tendency to more dry conditions is projected along a dryness band stretching from the southwest to the northeast of China. More frequent drought events of longer duration are projected in the southwestern river basins. For all future droughts, larger extents are projected, especially for events with long-term duration. The projected long-term drought events will occur more often and more severe than during the baseline period, and their central locations will likely shift towards Southeast China. The results of this study can be used to initiate and strengthen drought adaptation measures at

  1. Assessing the outstanding 2003 fire events in Portugal with a Regional Climate Model

    Science.gov (United States)

    Trigo, Ricardo; Jerez, Sonia; Camara, Carlos; Montávez, Juan Pedro

    2013-04-01

    The heatwave that struck western Iberia in the early days of August 2003 was characterized by record high values of both maximum (47.3°C) and minimum (30.6°c) temperatures in Portugal, associated with extremely low humidity levels and relatively intense wind speed (Trigo et al., 2006). These conditions triggered the most devastating sequence of large fires ever registered in Portugal. The estimated total burnt area was about 450.000 ha, including 280.000 ha of forest (Pereira et al., 2011). The outstanding total burnt area value corresponds to roughly 5% of the Portuguese territory, and represents approximately twice the previous maximum observed in 1998 (~220.000 ha), and about four times the long-term average observed between 1980 and 2004. Here we characterise this unusual episode using meteorological fields obtained from both observations and a regional climate model. In this work we use the longest (49-years) high-resolution regional climate simulation available driven by reanalysis data spanning from 1959 to 2007 and covering the entire Iberian Peninsula. This long run was obtained using the MM5 model with a spatial resolution of 10 km. Using this high spatial and temporal resolution we have computed the Canadian Fire Weather Index (FWI) System to produce hourly values of fire risk. The FWI System consists of six components that account for the effects of fuel moisture and wind on fire behaviour (van Wagner, 1987). We show the temporal evolution of high resolution patterns for several fire related variables during the most important days for triggering new fires (the first week of August 2003). Besides the absolute value of Tmax, Tmin, wind (speed and direction), relative humidity and FWI we also evaluate the corresponding anomalies of these fields, obtained after removing the long-term smoothed daily climatology. Pereira M.G., Malamude B.D., Trigo R.M., Alves P.I. (2011) "The History and Characteristics of the 1980-2005 Portuguese Rural Fire Database

  2. Singular vector decomposition of the internal variability of the Canadian Regional Climate Model

    Energy Technology Data Exchange (ETDEWEB)

    Diaconescu, Emilia Paula; Laprise, Rene [University of Quebec at Montreal (UQAM), Department of Earth and Atmospheric Sciences, Canadian Network for Regional Climate Modelling and Diagnostics, P.O. Box 8888, Montreal, QC (Canada); Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada); Zadra, Ayrton [University of Quebec at Montreal (UQAM), Department of Earth and Atmospheric Sciences, Canadian Network for Regional Climate Modelling and Diagnostics, P.O. Box 8888, Montreal, QC (Canada); Environment Canada, Meteorological Research Division, Montreal, QC (Canada); Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada)

    2012-03-15

    Previous studies have shown that Regional Climate Models (RCM) internal variability (IV) fluctuates in time depending on synoptic events. This study focuses on the physical understanding of episodes with rapid growth of IV. An ensemble of 21 simulations, differing only in their initial conditions, was run over North America using version 5 of the Canadian RCM (CRCM). The IV is quantified in terms of energy of CRCM perturbations with respect to a reference simulation. The working hypothesis is that IV is arising through rapidly growing perturbations developed in dynamically unstable regions. If indeed IV is triggered by the growth of unstable perturbations, a large proportion of the CRCM perturbations must project onto the most unstable singular vectors (SVs). A set of ten SVs was computed to identify the orthogonal set of perturbations that provide the maximum growth with respect to the dry total-energy norm during the course of the CRCM ensemble of simulations. CRCM perturbations were then projected onto the subspace of SVs. The analysis of one episode of rapid growth of IV is presented in detail. It is shown that a large part of the IV growth is explained by initially small-amplitude unstable perturbations represented by the ten leading SVs, the SV subspace accounting for over 70% of the CRCM IV growth in 36 h. The projection on the leading SV at final time is greater than the projection on the remaining SVs and there is a high similarity between the CRCM perturbations and the leading SV after 24-36 h tangent-linear model integration. The vertical structure of perturbations revealed that the baroclinic conversion is the dominant process in IV growth for this particular episode. (orig.)

  3. Regional Climate Modelling of the Western Iberian Low-Level Wind Jet

    Science.gov (United States)

    Soares, Pedro M. M.; Lima, Daniela C. A.; Cardoso, Rita M.; Semedo, Álvaro

    2016-04-01

    The Iberian coastal low-level jet (CLLJ) is one the less studied boundary layer wind jet features in the Eastern Boundary Currents Systems (EBCS). These regions are amongst the most productive ocean ecosystems, where the atmosphere-land-ocean feedbacks, which include marine boundary layer clouds, coastal jets, upwelling and inland soil temperature and moisture, play an important role in defining the regional climate along the sub-tropical mid-latitude western coastal areas. Recently, the present climate western Iberian CLLJ properties were extensively described using a high resolution regional climate hindcast simulation. A summer maximum frequency of occurrence above 30% was found, with mean maximum wind speeds around 15 ms-1, between 300 and 400m heights (at the jet core). Since the 1990s the climate change impact on the EBCS is being studied, nevertheless some lack of consensus still persists regarding the evolution of upwelling and other components of the climate system in these areas. However, recently some authors have shown that changes are to be expected concerning the timing, intensity and spatial homogeneity of coastal upwelling and of CLLJs, in response to future warming, especially at higher latitudes, namely in Iberia and Canaries. In this study, the first climate change assessment study regarding the Western Iberian CLLJ, using a high resolution (9km) regional climate simulation, is presented. The properties of this CLLJ are studied and compared using two 30 years simulations: one historical simulation for the 1971-2000 period, and another simulation for future climate, in agreement with the RCP8.5 scenario, for the 2071-2100 period. Robust and consistent changes are found: 1) the hourly frequency of occurrence of the CLLJ is expected to increase in summer along the western Iberian coast, from mean maximum values of around 35% to approximately 50%; 2) the relative increase of the CLLJ frequency of occurrence is higher in the north off western Iberia

  4. Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

    Energy Technology Data Exchange (ETDEWEB)

    Di Luca, Alejandro; Laprise, Rene [Universite du Quebec a Montreal (UQAM), Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Departement des Sciences de la Terre et de l' Atmosphere, PK-6530, Succ. Centre-ville, B.P. 8888, Montreal, QC (Canada); De Elia, Ramon [Universite du Quebec a Montreal, Ouranos Consortium, Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal (Canada)

    2012-03-15

    Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions. (orig.)

  5. Evaluating adaptation options for urban flooding based on new high-end emission scenario regional climate model simulations

    DEFF Research Database (Denmark)

    Arnbjerg-Nielsen, Karsten; Leonardsen, L.; Madsen, Henrik

    2015-01-01

    Climate change adaptation studies on urban flooding are often based on a model chain approach from climate forcing scenarios to analysis of adaptation measures. Previous analyses of climate change impacts in Copenhagen, Denmark, were supplemented by 2 high-end scenario simulations. These include...... a regional climate model projection forced to a global temperature increase of 6 degrees C in 2100 as well as a projection based on a high radiative forcing scenario (RCP8.5). With these scenarios, projected impacts of extreme precipitation increase significantly. For extreme sea surges, the impacts do...... by almost 4 and 8 times the current EAD for the RCP8.5 and 6 degrees C scenario, respectively. For both hazards, business-as-usual is not a possible scenario, since even in the absence of policy-driven changes, significant autonomous adaptation is likely to occur. Copenhagen has developed an adaptation plan...

  6. Aerosol indirect effects on summer precipitation in a regional climate model for the Euro-Mediterranean region

    Science.gov (United States)

    Da Silva, Nicolas; Mailler, Sylvain; Drobinski, Philippe

    2018-03-01

    Aerosols affect atmospheric dynamics through their direct and semi-direct effects as well as through their effects on cloud microphysics (indirect effects). The present study investigates the indirect effects of aerosols on summer precipitation in the Euro-Mediterranean region, which is located at the crossroads of air masses carrying both natural and anthropogenic aerosols. While it is difficult to disentangle the indirect effects of aerosols from the direct and semi-direct effects in reality, a numerical sensitivity experiment is carried out using the Weather Research and Forecasting (WRF) model, which allows us to isolate indirect effects, all other effects being equal. The Mediterranean hydrological cycle has often been studied using regional climate model (RCM) simulations with parameterized convection, which is the approach we adopt in the present study. For this purpose, the Thompson aerosol-aware microphysics scheme is used in a pair of simulations run at 50 km resolution with extremely high and low aerosol concentrations. An additional pair of simulations has been performed at a convection-permitting resolution (3.3 km) to examine these effects without the use of parameterized convection. While the reduced radiative flux due to the direct effects of the aerosols is already known to reduce precipitation amounts, there is still no general agreement on the sign and magnitude of the aerosol indirect forcing effect on precipitation, with various processes competing with each other. Although some processes tend to enhance precipitation amounts, some others tend to reduce them. In these simulations, increased aerosol loads lead to weaker precipitation in the parameterized (low-resolution) configuration. The fact that a similar result is obtained for a selected area in the convection-permitting (high-resolution) configuration allows for physical interpretations. By examining the key variables in the model outputs, we propose a causal chain that links the aerosol

  7. Embedding complex hydrology in the regional climate system – Dynamic coupling across different modelling domains

    DEFF Research Database (Denmark)

    Butts, Michael; Drews, Martin; Larsen, Morten Andreas Dahl

    2014-01-01

    the atmosphere and the groundwater via the land surface and can represent the lateral movement of water in both the surface and subsurface and their interactions, not normally accounted for in climate models. Meso-scale processes are important for climate in general and rainfall in particular. Hydrological......To improve our understanding of the impacts of feedback between the atmosphere and the terrestrial water cycle including groundwater and to improve the integration of water resource management modelling for climate adaption we have developed a dynamically coupled climate–hydrological modelling...... impacts are assessed at the catchment scale, the most important scale for water management. Feedback between groundwater, the land surface and the atmosphere occurs across a range of scales. Recognising this, the coupling was developed to allow dynamic exchange of water and energy at the catchment scale...

  8. Aspect of ECMWF downscaled Regional Climate Modeling in simulating Indian summer monsoon rainfall and dependencies on lateral boundary conditions

    Science.gov (United States)

    Ghosh, Soumik; Bhatla, R.; Mall, R. K.; Srivastava, Prashant K.; Sahai, A. K.

    2018-03-01

    Climate model faces considerable difficulties in simulating the rainfall characteristics of southwest summer monsoon. In this study, the dynamical downscaling of European Centre for Medium-Range Weather Forecast's (ECMWF's) ERA-Interim (EIN15) has been utilized for the simulation of Indian summer monsoon (ISM) through the Regional Climate Model version 4.3 (RegCM-4.3) over the South Asia Co-Ordinated Regional Climate Downscaling EXperiment (CORDEX) domain. The complexities of model simulation over a particular terrain are generally influenced by factors such as complex topography, coastal boundary, and lack of unbiased initial and lateral boundary conditions. In order to overcome some of these limitations, the RegCM-4.3 is employed for simulating the rainfall characteristics over the complex topographical conditions. For reliable rainfall simulation, implementations of numerous lower boundary conditions are forced in the RegCM-4.3 with specific horizontal grid resolution of 50 km over South Asia CORDEX domain. The analysis is considered for 30 years of climatological simulation of rainfall, outgoing longwave radiation (OLR), mean sea level pressure (MSLP), and wind with different vertical levels over the specified region. The dependency of model simulation with the forcing of EIN15 initial and lateral boundary conditions is used to understand the impact of simulated rainfall characteristics during different phases of summer monsoon. The results obtained from this study are used to evaluate the activity of initial conditions of zonal wind circulation speed, which causes an increase in the uncertainty of regional model output over the region under investigation. Further, the results showed that the EIN15 zonal wind circulation lacks sufficient speed over the specified region in a particular time, which was carried forward by the RegCM output and leads to a disrupted regional simulation in the climate model.

  9. The simulation of medicanes in a high-resolution regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Cavicchia, Leone [Centro Euro-Mediterraneo per i Cambiamenti Climatici, Bologna (Italy); Helmholtz-Zentrum Geesthacht, Institute of Coastal Research, Geesthacht (Germany); Ca' Foscari University, Venice (Italy); Storch, Hans von [Helmholtz-Zentrum Geesthacht, Institute of Coastal Research, Geesthacht (Germany); University of Hamburg, Meteorological Institute, Hamburg (Germany)

    2012-11-15

    Medicanes, strong mesoscale cyclones with tropical-like features, develop occasionally over the Mediterranean Sea. Due to the scarcity of observations over sea and the coarse resolution of the long-term reanalysis datasets, it is difficult to study systematically the multidecadal statistics of sub-synoptic medicanes. Our goal is to assess the long-term variability and trends of medicanes, obtaining a long-term climatology through dynamical downscaling of the NCEP/NCAR reanalysis data. In this paper, we examine the robustness of this method and investigate the value added for the study of medicanes. To do so, we performed several climate mode simulations with a high resolution regional atmospheric model (CCLM) for a number of test cases described in the literature. We find that the medicanes are formed in the simulations, with deeper pressures and stronger winds than in the driving global NCEP reanalysis. The tracks are adequately reproduced. We conclude that our methodology is suitable for constructing multi-decadal statistics and scenarios of current and possible future medicane activities. (orig.)

  10. The application of a dynamic OpenMI coupling between a regional climate model and a distributed surface water-groundwater model

    DEFF Research Database (Denmark)

    Butts, Michael; Drews, Martin; Larsen, Morten Andreas Dahl

    2014-01-01

    To support climate adaptation measures for water resources, we have developed and evaluated a dynamic coupling between a comprehensive distributed hydrological modelling system, MIKE SHE, and a regional climate modelling system, HIRHAM. The coupled model enables two-way interaction between the at......, including local measurements of energy fluxes. The results presented here suggest that there may be important differences in the simulated water balances for this catchment created by introducing an alternative hydrological model into the RCM....

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

    International Nuclear Information System (INIS)

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

    1992-01-01

    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

  12. Atmospheric circulation in regional climate models over Central Europe: links to surface air temperature and the influence of driving data

    Czech Academy of Sciences Publication Activity Database

    Plavcová, Eva; Kyselý, Jan

    2012-01-01

    Roč. 39, 7-8 (2012), s. 1681-1695 ISSN 0930-7575 R&D Project s: GA ČR GAP209/10/2265 Grant - others:ENSEMBLES: EU-FP6(XE) 505539 Program:FP6 Institutional support: RVO:68378289 Keywords : Regional climate models * Global climate models * Atmospheric circulation * Surface air temperature * ENSEMBLES * Central Europe Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 4.231, year: 2012 http://link.springer.com/article/10.1007%2Fs00382-011-1278-8#

  13. Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

    Science.gov (United States)

    Wanders, N.; Van Lanen, H. A. J.

    2015-03-01

    Hydrological drought characteristics (drought in groundwater and streamflow) likely will change in the 21st century as a result of climate change. The magnitude and directionality of these changes and their dependency on climatology and catchment characteristics, however, is uncertain. In this study a conceptual hydrological model was forced by downscaled and bias-corrected outcome from three general circulation models for the SRES A2 emission scenario (GCM forced models), and the WATCH Forcing Data set (reference model). The threshold level method was applied to investigate drought occurrence, duration and severity. Results for the control period (1971-2000) show that the drought characteristics of each GCM forced model reasonably agree with the reference model for most of the climate types, suggesting that the climate models' results after post-processing produce realistic outcomes for global drought analyses. For the near future (2021-2050) and far future (2071-2100) the GCM forced models show a decrease in drought occurrence for all major climates around the world and increase of both average drought duration and deficit volume of the remaining drought events. The largest decrease in hydrological drought occurrence is expected in cold (D) climates where global warming results in a decreased length of the snow season and an increased precipitation. In the dry (B) climates the smallest decrease in drought occurrence is expected to occur, which probably will lead to even more severe water scarcity. However, in the extreme climate regions (desert and polar), the drought analysis for the control period showed that projections of hydrological drought characteristics are most uncertain. On a global scale the increase in hydrological drought duration and severity in multiple regions will lead to a higher impact of drought events, which should motivate water resource managers to timely anticipate the increased risk of more severe drought in groundwater and streamflow

  14. Spatial-Scale Characteristics of Precipitation Simulated by Regional Climate Models and the Implications for Hydrological Modeling

    DEFF Research Database (Denmark)

    Rasmussen, S.H.; Christensen, J. H.; Drews, Martin

    2012-01-01

    Precipitation simulated by regional climate models (RCMs) is generally biased with respect to observations, especially at the local scale of a few tens of kilometers. This study investigates how well two different RCMs are able to reproduce the spatial correlation patterns of observed summer...... length scales on the order of 130 km are found in both observed data and RCM simulations. When simulations and observations are aggregated to different grid sizes, the pattern correlation significantly decreases when the aggregation length is less than roughly 100 km. Furthermore, the intermodel standard......, reflecting larger predictive certainty of the RCMs at larger scales. The findings on aggregated grid scales are shown to be largely independent of the underlying RCMs grid resolutions but not of the overall size of RCM domain. With regard to hydrological modeling applications, these findings indicate...

  15. An efficient regional energy-moisture balance model for simulation of the Greenland Ice Sheet response to climate change

    Directory of Open Access Journals (Sweden)

    A. Robinson

    2010-04-01

    Full Text Available In order to explore the response of the Greenland ice sheet (GIS to climate change on long (centennial to multi-millennial time scales, a regional energy-moisture balance model has been developed. This model simulates seasonal variations of temperature and precipitation over Greenland and explicitly accounts for elevation and albedo feedbacks. From these fields, the annual mean surface temperature and surface mass balance can be determined and used to force an ice sheet model. The melt component of the surface mass balance is computed here using both a positive degree day approach and a more physically-based alternative that includes insolation and albedo explicitly. As a validation of the climate model, we first simulated temperature and precipitation over Greenland for the prescribed, present-day topography. Our simulated climatology compares well to observations and does not differ significantly from that of a simple parameterization used in many previous simulations. Furthermore, the calculated surface mass balance using both melt schemes falls within the range of recent regional climate model results. For a prescribed, ice-free state, the differences in simulated climatology between the regional energy-moisture balance model and the simple parameterization become significant, with our model showing much stronger summer warming. When coupled to a three-dimensional ice sheet model and initialized with present-day conditions, the two melt schemes both allow realistic simulations of the present-day GIS.

  16. Modulation of extremes in the Atlantic region by modes of climate variability/change: A mechanistic coupled regional model study

    Energy Technology Data Exchange (ETDEWEB)

    Saravanan, Ramalingam [Texas A & M Univ., College Station, TX (United States)

    2015-01-09

    During the course of this project, we have accomplished the following: 1) Explored the parameter space of component models to minimize regional model bias 2) Assessed the impact of air-sea interaction on hurricanes, focusing in particular on the role of the oceanic barrier layer 3) Contributed to the activities of the U.S. CLIVAR Hurricane Working Group 4) Assessed the impact of lateral and lower boundary conditions on extreme flooding events in the U.S. Midwest in regional model simulations 5) Analyzed the concurrent impact of El Niño-Southern Oscillation and Atlantic Meridional Mode on Atlantic Hurricane activity using observations and regional model simulations

  17. Projecting regional climate and cropland changes using a linked biogeophysical-socioeconomic modeling framework: 1. Model description and an equilibrium application over West Africa

    Science.gov (United States)

    Wang, Guiling; Ahmed, Kazi Farzan; You, Liangzhi; Yu, Miao; Pal, Jeremy; Ji, Zhenming

    2017-03-01

    Agricultural land use alters regional climate through modifying the surface mass, energy, and momentum fluxes; climate influences agricultural land use through their impact on crop yields. These interactions are not well understood and have not been adequately considered in climate projections. This study tackles the critical linkages within the coupled natural-human system of West Africa in a changing climate based on an equilibrium application of a modeling framework that asynchronously couples models of regional climate, crop yield, multimarket agricultural economics, and cropland expansion. Using this regional modeling framework driven with two global climate models, we assess the contributions of land use change (LUC) and greenhouse gas (GHGs) concentration changes to regional climate changes and assess the contribution of climate change and socioeconomic factors to agricultural land use changes. For future cropland expansion in West Africa, our results suggest that socioeconomic development would be the dominant driver in the east (where current cropland coverage is already high) and climate changes would be the primary driver in the west (where future yield drop is severe). For future climate, it is found that agricultural expansion would cause a dry signal in the west and a wet signal in the east downwind, with an east-west contrast similar to the GHG-induced changes. Over a substantial portion of West Africa, the strength of the LUC-induced climate signals is comparable to the GHG-induced changes. Uncertainties originating from the driving global models are small; human decision making related to land use and international trade is a major source of uncertainty.

  18. Evaluation of skill at simulating heatwave and heat-humidity indices in Global and Regional Climate Models

    Science.gov (United States)

    Goldie, J. K.; Alexander, L. V.; Lewis, S. C.; Sherwood, S. C.

    2017-12-01

    A wide body of literature now establishes the harm of extreme heat on human health, and work is now emerging on the projection of future health impacts. However, heat-health relationships vary across different populations (Gasparrini et al. 2015), so accurate simulation of regional climate is an important component of joint health impact projection. Here, we evaluate the ability of nine Global Climate Models (GCMs) from CMIP5 and the NARCliM Regional Climate Model to reproduce a selection of 15 health-relevant heatwave and heat-humidity indices over the historical period (1990-2005) using the Perkins skill score (Perkins et al. 2007) in five Australian cities. We explore the reasons for poor model skill, comparing these modelled distributions to both weather station observations and gridded reanalysis data. Finally, we show changes in the modelled distributions from the highest-performing models under RCP4.5 and RCP8.5 greenhouse gas scenarios and discuss the implications of simulated heat stress for future climate change adaptation. ReferencesGasparrini, Antonio, Yuming Guo, Masahiro Hashizume, Eric Lavigne, Antonella Zanobetti, Joel Schwartz, Aurelio Tobias, et al. "Mortality Risk Attributable to High and Low Ambient Temperature: A Multicountry Observational Study." The Lancet 386, no. 9991 (July 31, 2015): 369-75. doi:10.1016/S0140-6736(14)62114-0. Perkins, S. E., A. J. Pitman, N. J. Holbrook, and J. McAneney. "Evaluation of the AR4 Climate Models' Simulated Daily Maximum Temperature, Minimum Temperature, and Precipitation over Australia Using Probability Density Functions." Journal of Climate 20, no. 17 (September 1, 2007): 4356-76. doi:10.1175/JCLI4253.1.

  19. Producing an integrated climate-land-energy-water (CLEW) model for glaciated regions in the developing world

    Science.gov (United States)

    Delman, E. M.; Thomas, B. F.; Famiglietti, J. S.

    2013-12-01

    Growing concern over the impact of climate change on global freshwater resources has spurred a demand for practical, basin-specific adaptation tools. The potential for water stress is particularly inflated in the glaciated watersheds of the developing world; widespread and rapid glacial retreat has forced regional resource managers to reconcile the reality of a diminishing supply with an overall increase in demand, while accounting for the underlying geopolitical and cultural context. An integrated approach, such as the development of a Climate-Land-Energy-Water (CLEW) model that examines relationships among climate, land-use, and the energy and water sectors, can be used to assess the impact of different climate change scenarios on basin sustainability and vulnerability. This study will first constrain the hydrologic budget in the Río Santa Watershed of Peru using satellite imagery, historical and contemporary stream discharge data, hydrologic modeling, climatic data analysis, and isotopic and chemical tracers. Ultimately, glacier retreat will be examined at the watershed scale and be used as an input in the CLEW model framework to assess hydrologic budget scenarios and the subsequent impact on regional economic and environmental sustainability.

  20. Vegetation-climate feedback causes reduced precipitation in CMIP5 regional Earth system model simulation over Africa

    Science.gov (United States)

    Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick

    2013-04-01

    Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and

  1. Future Precipitation Extremes in China Under Climate Change and Their Possible Mechanisms by Regional Climate Model and Earth System Model Simulations

    Science.gov (United States)

    Qin, P.; Xie, Z.

    2017-12-01

    Future precipitation extremes in China for the mid and end of 21st century were detected with six simulations using the regional climate model RegCM4 (RCM) and 17 global climate models (GCM) participated in the coupled Model Intercomparison Project Phase 5 (CMIP5). Prior to understanding the future changes in precipitation extremes, we overviewed the performance of precipitation extremes simulated by the CMIP5s and RCMs, and found both CMIP5s and RCMs could capture the temporal and spatial pattern of the historical precipitation extremes in China. In the mid-future period 2039-2058 (MF) and far-future 2079-2098 (FF), more wet precipitation extremes will occur in most area of China relative to the present period 1982-2001 (RF). We quantified the rates of the changes in precipitation extremes in China with the changes in air surface temperature (T2M) for the MF and FF period. Changes in precipitation extremes R95p were found around 5% K-1 for the MF period and 10% K-1 for the FF period, and changes in maximum 5 day precipitation (Rx5day) were detected around 4% K-1 for the MF period and 7% K-1 for the FF period, respectively. Finally, the possible physical mechanisms behind the changes in precipitation extremes in China were also discussed through the changes in specific humidity and vertical wind.

  2. Sensitivity of Greenland Ice Sheet surface mass balance to surface albedo parameterization: a study with a regional climate model

    OpenAIRE

    Angelen, J. H.; Lenaerts, J. T. M.; Lhermitte, S.; Fettweis, X.; Kuipers Munneke, P.; Broeke, M. R.; Meijgaard, E.; Smeets, C. J. P. P.

    2012-01-01

    We present a sensitivity study of the surface mass balance (SMB) of the Greenland Ice Sheet, as modeled using a regional atmospheric climate model, to various parameter settings in the albedo scheme. The snow albedo scheme uses grain size as a prognostic variable and further depends on cloud cover, solar zenith angle and black carbon concentration. For the control experiment the overestimation of absorbed shortwave radiation (+6%) at the K-transect (west Greenland) for the period 2004–2009 is...

  3. Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

    Science.gov (United States)

    Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

    2014-12-01

    The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

  4. Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models

    Science.gov (United States)

    Marengo, Jose A.; Ambrizzi, Tercio; Da Rocha, Rosmeri P.; Alves, Lincoln M.; Cuadra, Santiago V.; Valverde, Maria C.; Torres, Roger R.; Santos, Daniel C.; Ferraz, Simone E. T.

    2010-11-01

    Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961-1990) and projections for the IPCC A2 high emission scenario for 2071-2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5°N-15°S band, both in summer and especially in winter, reaching up to 6-8°C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4°C and in winter between 3 and 5°C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of

  5. Modeling framework for estimating impacts of climate change on electricity demand at regional level: Case of Greece

    International Nuclear Information System (INIS)

    Mirasgedis, S.; Sarafidis, Y.; Georgopoulou, E.; Kotroni, V.; Lagouvardos, K.; Lalas, D.P.

    2007-01-01

    This paper focuses on the potential upcoming impacts of climate change in the 21st century on electricity demand at regional/national levels for regions where topography and location result in large differences in local climate. To address this issue, a regional climate model, PRECIS, has been used to predict future climatic conditions under different emissions scenarios (namely A2 and B2 of the IPCC special report on emissions scenarios (SRES)) as an input to a multiple regression model of the sensitivity of electricity demand in the Greek interconnected power system to climate and socio-economic factors. The economic development input to the multiple regression model follows the same storylines of the SRES scenarios upto 2100 and includes sub-scenarios to cover larger and smaller economic development rates. The results of the analysis indicate an increase of the annual electricity demand attributable solely to climate change of 3.6-5.5% under all scenarios examined, most of which results from increased annual variability with substantial increases during the summer period that outweighs moderate declines estimated for the winter period. This becomes more pronounced if inter-annual variability, especially of summer months, is taken into consideration. It was also found that in the long run, economic development will have a strong effect on future electricity demand, thus increasing substantially the total amount of energy consumed for cooling and heating purposes. This substantial increase in energy demand with strong annual variability will lead to the need for inordinate increases of installed capacity, a large percentage of which will be under utilized. Thus, appropriate adaptation strategies (e.g. new investments, interconnections with other power systems, energy saving programmes, etc.) need to be developed at the state level in order to ensure the security of energy supply. (author)

  6. Projected Crop Production under Regional Climate Change Using Scenario Data and Modeling: Sensitivity to Chosen Sowing Date and Cultivar

    Directory of Open Access Journals (Sweden)

    Sulin Tao

    2016-02-01

    Full Text Available A sensitivity analysis of the responses of crops to the chosen production adaptation options under regional climate change was conducted in this study. Projections of winter wheat production for different sowing dates and cultivars were estimated for a major economic and agricultural province of China from 2021 to 2080 using the World Food Study model (WOFOST under representative concentration pathways (RCPs scenarios. A modeling chain was established and a correction method was proposed to reduce the bias of the resulting model-simulated climate data. The results indicated that adjusting the sowing dates and cultivars could mitigate the influences of climate change on winter wheat production in Jinagsu. The yield gains were projected from the chosen sowing date and cultivar. The following actions are recommended to ensure high and stable yields under future climate changes: (i advance the latest sowing date in some areas of northern Jiangsu; and (ii use heat-tolerant or heat-tolerant and drought-resistant varieties in most areas of Jiangsu rather than the currently used cultivar. Fewer of the common negative effects of using a single climate model occurred when using the sensitivity analysis because our bias correction method was effective for scenario data and because the WOFOST performed well for Jiangsu after calibration.

  7. Representation of fine scale atmospheric variability in a nudged limited area quasi-geostrophic model: application to regional climate modelling

    Science.gov (United States)

    Omrani, H.; Drobinski, P.; Dubos, T.

    2009-09-01

    In this work, we consider the effect of indiscriminate nudging time on the large and small scales of an idealized limited area model simulation. The limited area model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by its « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. Compared to a previous study by Salameh et al. (2009) who investigated the existence of an optimal nudging time minimizing the error on both large and small scale in a linear model, we here use a fully non-linear model which allows us to represent the chaotic nature of the atmosphere: given the perfect quasi-geostrophic model, errors in the initial conditions, concentrated mainly in the smaller scales of motion, amplify and cascade into the larger scales, eventually resulting in a prediction with low skill. To quantify the predictability of our quasi-geostrophic model, we measure the rate of divergence of the system trajectories in phase space (Lyapunov exponent) from a set of simulations initiated with a perturbation of a reference initial state. Predictability of the "global", periodic model is mostly controlled by the beta effect. In the LAM, predictability decreases as the domain size increases. Then, the effect of large-scale nudging is studied by using the "perfect model” approach. Two sets of experiments were performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic LAM where the size of the LAM domain comes into play in addition to the first set of simulations. In the two sets of experiments, the best spatial correlation between the nudge simulation and the reference is observed with a nudging time close to the predictability time.

  8. Can Regional Climate Models be used in the assessment of vulnerability and risk caused by extreme events?

    Science.gov (United States)

    Nunes, Ana

    2015-04-01

    Extreme meteorological events played an important role in catastrophic occurrences observed in the past over densely populated areas in Brazil. This motived the proposal of an integrated system for analysis and assessment of vulnerability and risk caused by extreme events in urban areas that are particularly affected by complex topography. That requires a multi-scale approach, which is centered on a regional modeling system, consisting of a regional (spectral) climate model coupled to a land-surface scheme. This regional modeling system employs a boundary forcing method based on scale-selective bias correction and assimilation of satellite-based precipitation estimates. Scale-selective bias correction is a method similar to the spectral nudging technique for dynamical downscaling that allows internal modes to develop in agreement with the large-scale features, while the precipitation assimilation procedure improves the modeled deep-convection and drives the land-surface scheme variables. Here, the scale-selective bias correction acts only on the rotational part of the wind field, letting the precipitation assimilation procedure to correct moisture convergence, in order to reconstruct South American current climate within the South American Hydroclimate Reconstruction Project. The hydroclimate reconstruction outputs might eventually produce improved initial conditions for high-resolution numerical integrations in metropolitan regions, generating more reliable short-term precipitation predictions, and providing accurate hidrometeorological variables to higher resolution geomorphological models. Better representation of deep-convection from intermediate scales is relevant when the resolution of the regional modeling system is refined by any method to meet the scale of geomorphological dynamic models of stability and mass movement, assisting in the assessment of risk areas and estimation of terrain stability over complex topography. The reconstruction of past extreme

  9. Regional climate change for the Pacific Northwest

    International Nuclear Information System (INIS)

    McBean, G.A.; Thomas, G.

    1991-01-01

    The Pacific Northwest climate is dominated by topography and the Pacific Ocean; the forests have become adapted to the present climate. Within short distances there are large changes in precipitation and temperature, with resultant changes in ecosystems. As the atmospheric concentrations of greenhouse gases increase, global climate is expected to warm and precipitation to increase. Global climate model simulations show enhanced warming at high northern latitudes. For the Pacific Northwest, models show 2-6 degree C warming and increased precipitation in the winter for doubled atmospheric CO 2 concentration. However, the regional details of these models are presently not very reliable. The results and limitations of present global climate models are reviewed. The roles of the oceans, clouds, and other feedback mechanisms are described along with some of the possible impacts of climate change on forest resources. 24 refs., 2 figs., 1 tab

  10. Greenhouse Gas Induced Changes in the Seasonal Cycle of the Amazon Basin in Coupled Climate-Vegetation Regional Model

    Directory of Open Access Journals (Sweden)

    Flavio Justino

    2016-01-01

    Full Text Available Previous work suggests that changes in seasonality could lead to a 70% reduction in the extent of the Amazon rainforest. The primary cause of the dieback of the rainforest is a lengthening of the dry season due to a weakening of the large-scale tropical circulation. Here we examine these changes in the seasonal cycle. Under present day conditions the Amazon climate is characterized by a zonal separation of the dominance of the annual and semi-annual seasonal cycles. This behavior is strongly modified under greenhouse warming conditions, with the annual cycle becoming dominant throughout the Amazon basin, increasing differences between the dry and wet seasons. In particular, there are substantial changes in the annual cycle of temperature due to the increase in the temperature of the warmest month, but the lengthening of the dry season is believed to be particularly important for vegetation-climate feedbacks. Harmonic analysis performed to regional climate model simulations yields results that differ from the global climate model that it is forced from, with the regional model being more sensitive to changes in the seasonal cycle.

  11. Analyzing Multidecadal Trends in Cloudiness Over the Subtropical Andes Mountains of South America Using a Regional Climate Model.

    Science.gov (United States)

    Zaitchik, B. F.; Russell, A.; Gnanadesikan, A.

    2016-12-01

    Satellite-based products indicate that many parts of South America have been experiencing increases in outgoing longwave radiation (OLR) and corresponding decreases in cloudiness over the last few decades, with the strongest trends occurring in the subtropical Andes Mountains - an area that is highly vulnerable to climate change due to its reliance on glacial melt for dry-season runoff. Changes in cloudiness may be contributing to increases in atmospheric temperature, thereby raising the freezing level height (FLH) - a critical geophysical parameter. Yet these trends are only partially captured in reanalysis products, while AMIP climate models generally show no significant trend in OLR over this timeframe, making it difficult to determine the underlying drivers. Therefore, controlled numerical experiments with a regional climate model are performed in order to investigate drivers of the observed OLR and cloudiness trends. The Weather Research and Forecasting model (WRF) is used here because it offers several advantages over global models, including higher resolution - a critical asset in areas of complex topography - as well as flexible physics, parameterization, and data assimilation capabilities. It is likely that changes in the mean states and meridional gradients of SSTs in the Pacific and Atlantic oceans are driving regional trends in clouds. A series of lower boundary manipulations are performed with WRF to determine to what extent changes in SSTs influence regional OLR.

  12. Modeling aquifer behaviour under climate change and high consumption: Case study of the Sfax region, southeast Tunisia

    Science.gov (United States)

    Boughariou, Emna; Allouche, Nabila; Jmal, Ikram; Mokadem, Naziha; Ayed, Bachaer; Hajji, Soumaya; Khanfir, Hafedh; Bouri, Salem

    2018-05-01

    The water resources are exhausted by the increasing demand related to the population growth. They are also affected by climate circumstances, especially in arid and semi-arid regions. These areas are already undergoing noticeable shortages and low annual precipitation rate. This paper presents a numerical model of the Sfax shallow aquifer system that was developed by coupling the geographical information system tool ArcGIS 9.3 and ground water modeling system GMS6.5's interface, ground water flow modeling MODFLOW 2000. Being in coastal city and having an arid climate with high consumption rates, this aquifer is undergoing a hydraulic stress situation. Therefore, the groundwater piezometric variations were calibrated for the period 2003-2013 and simulated based on two scenarios; first the constant and growing consumption and second the rainfall forecast as a result of climate change scenario released by the Tunisian Ministry of Agriculture and Water Resources and the German International Cooperation Agency "GIZ" using HadCM3 as a general circulation model. The piezometric simulations globally forecast a decrease that is about 0.5 m in 2020 and 1 m in 2050 locally the decrease is more pronounced in "Chaffar" and "Djbeniana" regions and that is more evident for the increasing consumption scenario. The two scenarios announce a quantitative degradation of the groundwater by the year 2050 with an alarming marine intrusion in "Djbeniana" region.

  13. Dynamical Downscaling of Seasonal Climate Prediction over Nordeste Brazil with ECHAM3 and NCEP's Regional Spectral Models at IRI.

    Science.gov (United States)

    Nobre, Paulo; Moura, Antonio D.; Sun, Liqiang

    2001-12-01

    This study presents an evaluation of a seasonal climate forecast done with the International Research Institute for Climate Prediction (IRI) dynamical forecast system (regional model nested into a general circulation model) over northern South America for January-April 1999, encompassing the rainy season over Brazil's Nordeste. The one-way nesting is one in two tiers: first the NCEP's Regional Spectral Model (RSM) runs with an 80-km grid mesh forced by the ECHAM3 atmospheric general circulation model (AGCM) outputs; then the RSM runs with a finer grid mesh (20 km) forced by the forecasts generated by the RSM-80. An ensemble of three realizations is done. Lower boundary conditions over the oceans for both ECHAM and RSM model runs are sea surface temperature forecasts over the tropical oceans. Soil moisture is initialized by ECHAM's inputs. The rainfall forecasts generated by the regional model are compared with those of the AGCM and observations. It is shown that the regional model at 80-km resolution improves upon the AGCM rainfall forecast, reducing both seasonal bias and root-mean-square error. On the other hand, the RSM-20 forecasts presented larger errors, with spatial patterns that resemble those of local topography. The better forecast of the position and width of the intertropical convergence zone (ITCZ) over the tropical Atlantic by the RSM-80 model is one of the principal reasons for better-forecast scores of the RSM-80 relative to the AGCM. The regional model improved the spatial as well as the temporal details of rainfall distribution, and also presenting the minimum spread among the ensemble members. The statistics of synoptic-scale weather variability on seasonal timescales were best forecast with the regional 80-km model over the Nordeste. The possibility of forecasting the frequency distribution of dry and wet spells within the rainy season is encouraging.

  14. A Hybrid Framework to Bias Correct and Empirically Downscale Daily Temperature and Precipitation from Regional Climate Models

    Science.gov (United States)

    Tan, P.; Abraham, Z.; Winkler, J. A.; Perdinan, P.; Zhong, S. S.; Liszewska, M.

    2013-12-01

    Bias correction and statistical downscaling are widely used approaches for postprocessing climate simulations generated by global and/or regional climate models. The skills of these approaches are typically assessed in terms of their ability to reproduce historical climate conditions as well as the plausibility and consistency of the derived statistical indicators needed by end users. Current bias correction and downscaling approaches often do not adequately satisfy the two criteria of accurate prediction and unbiased estimation. To overcome this limitation, a hybrid regression framework was developed to both minimize prediction errors and preserve the distributional characteristics of climate observations. Specifically, the framework couples the loss functions of standard (linear or nonlinear) regression methods with a regularization term that penalizes for discrepancies between the predicted and observed distributions. The proposed framework can also be extended to generate physically-consistent outputs across multiple response variables, and to incorporate both reanalysis-driven and GCM-driven RCM outputs into a unified learning framework. The effectiveness of the framework is demonstrated using daily temperature and precipitation simulations from the North American Regional Climate Change Program (NARCCAP) . The accuracy of the framework is comparable to standard regression methods, but, unlike the standard regression methods, the proposed framework is able to preserve many of the distribution properties of the response variables, akin to bias correction approaches such as quantile mapping and bivariate geometric quantile mapping.

  15. Errors and uncertainties introduced by a regional climate model in climate impact assessments: example of crop yield simulations in West Africa

    International Nuclear Information System (INIS)

    Ramarohetra, Johanna; Pohl, Benjamin; Sultan, Benjamin

    2015-01-01

    The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting (WRF) regional climate model to downscale ERA-Interim (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model (LSM) is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments. (letter)

  16. Validation of EURO-CORDEX regional climate models in reproducing the variability of precipitation extremes in Romania

    Science.gov (United States)

    Dumitrescu, Alexandru; Busuioc, Aristita

    2016-04-01

    EURO-CORDEX is the European branch of the international CORDEX initiative that aims to provide improved regional climate change projections for Europe. The main objective of this paper is to document the performance of the individual models in reproducing the variability of precipitation extremes in Romania. Here three EURO-CORDEX regional climate models (RCMs) ensemble (scenario RCP4.5) are analysed and inter-compared: DMI-HIRHAM5, KNMI-RACMO2.2 and MPI-REMO. Compared to previous studies, when the RCM validation regarding the Romanian climate has mainly been made on mean state and at station scale, a more quantitative approach of precipitation extremes is proposed. In this respect, to have a more reliable comparison with observation, a high resolution daily precipitation gridded data set was used as observational reference (CLIMHYDEX project). The comparison between the RCM outputs and observed grid point values has been made by calculating three extremes precipitation indices, recommended by the Expert Team on Climate Change Detection Indices (ETCCDI), for the 1976-2005 period: R10MM, annual count of days when precipitation ≥10mm; RX5DAY, annual maximum 5-day precipitation and R95P%, precipitation fraction of annual total precipitation due to daily precipitation > 95th percentile. The RCMs capability to reproduce the mean state for these variables, as well as the main modes of their spatial variability (given by the first three EOF patterns), are analysed. The investigation confirms the ability of RCMs to simulate the main features of the precipitation extreme variability over Romania, but some deficiencies in reproducing of their regional characteristics were found (for example, overestimation of the mea state, especially over the extra Carpathian regions). This work has been realised within the research project "Changes in climate extremes and associated impact in hydrological events in Romania" (CLIMHYDEX), code PN II-ID-2011-2-0073, financed by the Romanian

  17. A statistical adjustment approach for climate projections of snow conditions in mountain regions using energy balance land surface models

    Science.gov (United States)

    Verfaillie, Deborah; Déqué, Michel; Morin, Samuel; Lafaysse, Matthieu

    2017-04-01

    Projections of future climate change have been increasingly called for lately, as the reality of climate change has been gradually accepted and societies and governments have started to plan upcoming mitigation and adaptation policies. In mountain regions such as the Alps or the Pyrenees, where winter tourism and hydropower production are large contributors to the regional revenue, particular attention is brought to current and future snow availability. The question of the vulnerability of mountain ecosystems as well as the occurrence of climate-related hazards such as avalanches and debris-flows is also under consideration. In order to generate projections of snow conditions, however, downscaling global climate models (GCMs) by using regional climate models (RCMs) is not sufficient to capture the fine-scale processes and thresholds at play. In particular, the altitudinal resolution matters, since the phase of precipitation is mainly controlled by the temperature which is altitude-dependent. Simulations from GCMs and RCMs moreover suffer from biases compared to local observations, due to their rather coarse spatial and altitudinal resolution, and often provide outputs at too coarse time resolution to drive impact models. RCM simulations must therefore be adjusted using empirical-statistical downscaling and error correction methods, before they can be used to drive specific models such as energy balance land surface models. In this study, time series of hourly temperature, precipitation, wind speed, humidity, and short- and longwave radiation were generated over the Pyrenees and the French Alps for the period 1950-2100, by using a new approach (named ADAMONT for ADjustment of RCM outputs to MOuNTain regions) based on quantile mapping applied to daily data, followed by time disaggregation accounting for weather patterns selection. We first introduce a thorough evaluation of the method using using model runs from the ALADIN RCM driven by a global reanalysis over the

  18. Integration of prognostic aerosol-cloud interactions in a chemistry transport model coupled offline to a regional climate model

    Science.gov (United States)

    Thomas, M. A.; Kahnert, M.; Andersson, C.; Kokkola, H.; Hansson, U.; Jones, C.; Langner, J.; Devasthale, A.

    2015-06-01

    To reduce uncertainties and hence to obtain a better estimate of aerosol (direct and indirect) radiative forcing, next generation climate models aim for a tighter coupling between chemistry transport models and regional climate models and a better representation of aerosol-cloud interactions. In this study, this coupling is done by first forcing the Rossby Center regional climate model (RCA4) with ERA-Interim lateral boundaries and sea surface temperature (SST) using the standard cloud droplet number concentration (CDNC) formulation (hereafter, referred to as the "stand-alone RCA4 version" or "CTRL" simulation). In the stand-alone RCA4 version, CDNCs are constants distinguishing only between land and ocean surface. The meteorology from this simulation is then used to drive the chemistry transport model, Multiple-scale Atmospheric Transport and Chemistry (MATCH), which is coupled online with the aerosol dynamics model, Sectional Aerosol module for Large Scale Applications (SALSA). CDNC fields obtained from MATCH-SALSA are then fed back into a new RCA4 simulation. In this new simulation (referred to as "MOD" simulation), all parameters remain the same as in the first run except for the CDNCs provided by MATCH-SALSA. Simulations are carried out with this model setup for the period 2005-2012 over Europe, and the differences in cloud microphysical properties and radiative fluxes as a result of local CDNC changes and possible model responses are analysed. Our study shows substantial improvements in cloud microphysical properties with the input of the MATCH-SALSA derived 3-D CDNCs compared to the stand-alone RCA4 version. This model setup improves the spatial, seasonal and vertical distribution of CDNCs with a higher concentration observed over central Europe during boreal summer (JJA) and over eastern Europe and Russia during winter (DJF). Realistic cloud droplet radii (CD radii) values have been simulated with the maxima reaching 13 μm, whereas in the stand

  19. Links between circulation types and precipitation in Central Europe in the observed data and regional climate model simulations

    Czech Academy of Sciences Publication Activity Database

    Plavcová, Eva; Kyselý, Jan; Štěpánek, P.

    2014-01-01

    Roč. 34, č. 9 (2014), s. 2885-2898 ISSN 0899-8418 R&D Projects: GA ČR GAP209/10/2265 Grant - others:FP6 ENSEMBLES(XE) 505539 Program:FP6 Institutional support: RVO:68378289 Keywords : precipitation * atmospheric circulation * regional climate models * ENSEMBLES * Central Europe Subject RIV: DG - Athmosphere Sciences, Meteorology; DG - Athmosphere Sciences, Meteorology (UEK-B) Impact factor: 3.157, year: 2014

  20. Regional climate assessment of precipitation and temperature in Southern Punjab (Pakistan) using SimCLIM climate model for different temporal scales

    Science.gov (United States)

    Amin, Asad; Nasim, Wajid; Mubeen, Muhammad; Sarwar, Saleem; Urich, Peter; Ahmad, Ashfaq; Wajid, Aftab; Khaliq, Tasneem; Rasul, Fahd; Hammad, Hafiz Mohkum; Rehmani, Muhammad Ishaq Asif; Mubarak, Hussani; Mirza, Nosheen; Wahid, Abdul; Ahamd, Shakeel; Fahad, Shah; Ullah, Abid; Khan, Mohammad Nauman; Ameen, Asif; Amanullah; Shahzad, Babar; Saud, Shah; Alharby, Hesham; Ata-Ul-Karim, Syed Tahir; Adnan, Muhammad; Islam, Faisal; Ali, Qazi Shoaib

    2018-01-01

    Unbalanced climate during the last decades has created spatially alarming and destructive situations in the world. Anomalies in temperature and precipitation enhance the risks for crop production in large agricultural region (especially the Southern Punjab) of Pakistan. Detailed analysis of historic weather data (1980-2011) record helped in creating baseline data to compare with model projection (SimCLIM) for regional level. Ensemble of 40 GCMs used for climatic projections with greenhouse gas (GHG) representative concentration pathways (RCP-4.5, 6.0, 8.5) was selected on the baseline comparison and used for 2025 and 2050 climate projection. Precipitation projected by ensemble and regional weather observatory at baseline showed highly unpredictable nature while both temperature extremes showed 95 % confidence level on a monthly projection. Percentage change in precipitation projected by model with RCP-4.5, RCP-6.0, and RCP-8.5 showed uncertainty 3.3 to 5.6 %, 2.9 to 5.2 %, and 3.6 to 7.9 % for 2025 and 2050, respectively. Percentage change of minimum temperature from base temperature showed that 5.1, 4.7, and 5.8 % for 2025 and 9.0, 8.1, and 12.0 % increase for projection year 2050 with RCP-4.5, 6.0, and 8.5 and maximum temperature 2.7, 2.5, and 3.0 % for 2025 and 4.7, 4.4, and 6.4 % for 2050 will be increased with RCP-4.5, 6.0, and 8.5, respectively. Uneven increase in precipitation and asymmetric increase in temperature extremes in future would also increase the risk associated with management of climatic uncertainties. Future climate projection will enable us for better risk management decisions.

  1. Geospatial Analysis Tool Kit for Regional Climate Datasets (GATOR) : An Open-source Tool to Compute Climate Statistic GIS Layers from Argonne Climate Modeling Results

    Science.gov (United States)

    2017-08-01

    This large repository of climate model results for North America (Wang and Kotamarthi 2013, 2014, 2015) is stored in Network Common Data Form (NetCDF...Network Common Data Form (NetCDF). UCAR/Unidata Program Center, Boulder, CO. Available at: http://www.unidata.ucar.edu/software/netcdf. Accessed on 6/20...parametric approach. This introduces uncertainty, because the parametric models are only as good as the available observations that form the basis for

  2. New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based, and drifting station data

    Science.gov (United States)

    Klaus, D.; Dethloff, K.; Dorn, W.; Rinke, A.; Wu, D. L.

    2016-05-01

    Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) a more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (<700 m) cloud observations, as these clouds exert a strong impact on the near-surface climate.

  3. Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR

    NARCIS (Netherlands)

    Fettweis, X.; Franco, B.; Tedesco, M.; van Angelen, J.H.; Lenaerts, J.T.M.; van den Broeke, M.R.; Gallée, H.

    2013-01-01

    To estimate the sea level rise (SLR) originating from changes in surface mass balance (SMB) of the Greenland ice sheet (GrIS), we present 21st century climate projections obtained with the regional climate model MAR (Mod`ele Atmosph´erique R´egional), forced by output of three CMIP5 (Coupled Model

  4. Spatio-temporal modelling of heat stress and climate change implications for the Murray dairy region, Australia

    Science.gov (United States)

    Nidumolu, Uday; Crimp, Steven; Gobbett, David; Laing, Alison; Howden, Mark; Little, Stephen

    2014-08-01

    The Murray dairy region produces approximately 1.85 billion litres of milk each year, representing about 20 % of Australia's total annual milk production. An ongoing production challenge in this region is the management of the impacts of heat stress during spring and summer. An increase in the frequency and severity of extreme temperature events due to climate change may result in additional heat stress and production losses. This paper assesses the changing nature of heat stress now, and into the future, using historical data and climate change projections for the region using the temperature humidity index (THI). Projected temperature and relative humidity changes from two global climate models (GCMs), CSIRO MK3.5 and CCR-MIROC-H, have been used to calculate THI values for 2025 and 2050, and summarized as mean occurrence of, and mean length of consecutive high heat stress periods. The future climate scenarios explored show that by 2025 an additional 12-15 days (compared to 1971 to 2000 baseline data) of moderate to severe heat stress are likely across much of the study region. By 2050, larger increases in severity and occurrence of heat stress are likely (i.e. an additional 31-42 moderate to severe heat stress days compared with baseline data). This increasing trend will have a negative impact on milk production among dairy cattle in the region. The results from this study provide useful insights on the trends in THI in the region. Dairy farmers and the dairy industry could use these results to devise and prioritise adaptation options to deal with projected increases in heat stress frequency and severity.

  5. Toward Process-resolving Synthesis and Prediction of Arctic Climate Change Using the Regional Arctic System Model

    Science.gov (United States)

    Maslowski, W.

    2017-12-01

    The Regional Arctic System Model (RASM) has been developed to better understand the operation of Arctic System at process scale and to improve prediction of its change at a spectrum of time scales. RASM is a pan-Arctic, fully coupled ice-ocean-atmosphere-land model with marine biogeochemistry extension to the ocean and sea ice models. The main goal of our research is to advance a system-level understanding of critical processes and feedbacks in the Arctic and their links with the Earth System. The secondary, an equally important objective, is to identify model needs for new or additional observations to better understand such processes and to help constrain models. Finally, RASM has been used to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook of the Sea Ice Prediction Network. Future RASM forecasts, are likely to include increased resolution for model components and ecosystem predictions. Such research is in direct support of the US environmental assessment and prediction needs, including those of the U.S. Navy, Department of Defense, and the recent IARPC Arctic Research Plan 2017-2021. In addition to an overview of RASM technical details, selected model results are presented from a hierarchy of climate models together with available observations in the region to better understand potential oceanic contributions to polar amplification. RASM simulations are analyzed to evaluate model skill in representing seasonal climatology as well as interannual and multi-decadal climate variability and predictions. Selected physical processes and resulting feedbacks are discussed to emphasize the need for fully coupled climate model simulations, high model resolution and sensitivity of simulated sea ice states to scale dependent model parameterizations controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean.

  6. Evaluating Regional Scale Deforestation in the University of Victoria Earth System Climate Model

    Science.gov (United States)

    Longobardi, P.; Montenegro, A.; Beltrami, H.; Eby, M.

    2011-12-01

    Forests play a key role in influencing the Earths climate and at the same time are affected by changing climates. At this point it is estimated that 15-30% of Earths natural forests have already been converted to pasture or cropland. With such large amounts of forest being converted to cropland and grassland, it is important to determine the climatic effects of these actions. To date, most modelling efforts towards understanding the climatic effects of deforestation have simulated global deforestation or have been based on experiments where trees were removed from large areas, i.e. the entire Amazon or all forests above 50 N. Here we use the University of Victoria Earth System Climate model which contains a fully coupled carbon cycle, to evaluate the response to deforestation of 10%, 25%, 50% and 100% of the forested areas in three latitude bands: high (above 50°N), mid (above ± 30°) and low (between ± 30°). All simulations were transient simulations, allowing for changes to atmospheric forcings following the A2 emissions scenario. High latitude deforestation lead to cooling (-.05 °C to -0.45 °C) and increase in soil carbon (0.5 to 3 x 1014 kg) for all fractions of deforestation. Due in part to the increase in soil carbon, there was a decrease in atmospheric CO2 in the 50% (-20 ppm) and 100% (-60 ppm) high-latitude deforestation simulations. Low-latitude deforestation initially produced warming in all scenarios (0.1 to 0.25 °C), although all were colder (-0.05 to -0.1 °C) than the control by the end of the simulation. Atmospheric CO2 increased in all simulations (40 to 80 ppm), as well as soil carbon (2 to 16 x 1013 kg). Mid-latitude deforestation also lead to initial warming (0.01 to 0.1 °C) followed by cooling (-0.01 to -0.1 °C). Mid latitude deforestation also produced an increase in soil carbon (2 to 10 x 1013 kg), and atmospheric CO2 (0 to 25ppm). In all three latitude bands forest dieback was observed. Results range from 7% to 37% for high

  7. Modelling the energy and exergy utilisation of the Mexican non-domestic sector: A study by climatic regions

    International Nuclear Information System (INIS)

    García Kerdan, Iván; Morillón Gálvez, David; Raslan, Rokia; Ruyssevelt, Paul

    2015-01-01

    This paper presents the development of a bottom-up stock model to perform a holistic energy study of the Mexican non-domestic sector. The current energy and exergy flows are shown based on a categorisation by climatic regions with the aim of understanding the impact of local characteristics on regional efficiencies. Due to the limited data currently available, the study is supported by the development of a detailed archetype-based stock model using EnergyPlus as a first law analysis tool combined with an existing exergy analysis method. Twenty-one reference models were created to estimate the electric and gas use in the sector. The results indicate that sectoral energy and exergy annual input are 95.37 PJ and 94.28 PJ, respectively. Regional exergy efficiencies were found to be 17.8%, 16.6% and 23.2% for the hot-dry, hot-humid and temperate climates, respectively. The study concludes that significant potential for improvements still exists, especially in the cases of space conditioning, lighting, refrigeration, and cooking where most exergy destructions occur. Additionally, this work highlights that the method described may be further used to study the impact of large-scale refurbishments and promote national regulations and standards for sustainable buildings that takes into consideration energy and exergy indicators. - Highlights: • A bottom-up physics model was developed to analyse the Mexican commercial stock. • A detailed energy analysis by climate, buildings and end-uses is presented. • The Mexican non-domestic sector as a whole has an exergy efficiency of 19.7%. • The lowest regional exergy efficiency is found at the hot-humid region with 16.6%. • By end use, the highest exergy destructions are caused by HVAC and lighting

  8. TRACKING CLIMATE MODELS

    Data.gov (United States)

    National Aeronautics and Space Administration — CLAIRE MONTELEONI*, GAVIN SCHMIDT, AND SHAILESH SAROHA* Climate models are complex mathematical models designed by meteorologists, geophysicists, and climate...

  9. Evaluating the impact of climate policies on regional food availability and accessibility using an Integrated Assessment Model

    Science.gov (United States)

    Gilmore, E.; Cui, Y. R.; Waldhoff, S.

    2015-12-01

    Beyond 2015, eradicating hunger will remain a critical part of the global development agenda through the Sustainable Development Goals (SDG). Efforts to limit climate change through both mitigation of greenhouse gas emissions and land use policies may interact with food availability and accessibility in complex and unanticipated ways. Here, we develop projections of regional food accessibility to 2050 under the alternative futures outlined by the Shared Socioeconomic Pathways (SSPs) and under different climate policy targets and structures. We use the Global Change Assessment Model (GCAM), an integrated assessment model (IAM), for our projections. We calculate food access as the weighted average of consumption of five staples and the portion of income spend on those commodities and extend the GCAM calculated universal global producer price to regional consumer prices drawing on historical relationships of these prices. Along the SSPs, food access depends largely on expectations of increases in population and economic status. Under a more optimistic scenario, the pressures on food access from increasing demand and rising prices can be counterbalanced by faster economic development. Stringent climate policies that increase commodity prices, however, may hinder vulnerable regions, namely Sub-Saharan Africa, from achieving greater food accessibility.

  10. Modeling the impact of climate change on watershed discharge and sediment yield in the black soil region, northeastern China

    Science.gov (United States)

    Li, Zhiying; Fang, Haiyan

    2017-09-01

    Climate change is expected to impact discharge and sediment yield in watersheds. The purpose of this paper is to assess the potential impacts of climate change on water discharge and sediment yield for the Yi'an watershed of the black soil region, northeastern China, based on the newly released Representative Concentration Pathways (RCPs) during 2071-2099. For this purpose, the TETIS model was implemented to simulate the hydrological and sedimentological responses to climate change. The model calibration (1971-1977) and validation (1978-1987) performances were rated as satisfactory. The modeling results for the four RCP scenarios relative to the control scenario under the same land use configuration indicated an increase in discharge of 16.3% (RCP 2.6), 14.3% (RCP 4.5), 36.7% (RCP 6.0) and 71.4% (RCP 8.5) and an increase in the sediment yield of 16.5% (RCP 2.6), 32.4% (RCP 4.5), 81.8% (RCP 6.0) and 170% (RCP 8.5). This implies that the negative impact of climate change on sediment yield is generally greater than that on discharge. At the monthly scale, both discharge and sediment yield increased dramatically in April to June and August to September. A more vigorous hydrological cycle and an increase in high values of sediment yield are also expected. These changes in annual discharge and sediment yield were closely linked with changes in precipitation, whereas monthly changes in late spring and autumn were mainly related to temperature. This study highlights the possible adverse impact of climate change on discharge and sediment yield in the black soil region of northeastern China and could provide scientific basis for adaptive management.

  11. A Regional Earth System Model of the Northeast Corridor: Analyzing 21st Century Climate and Environment

    Science.gov (United States)

    Vorosmarty, C. J.; Duchin, F.; Melillo, J. M.; Wollheim, W. M.; Gonzalez, J.; Kicklighter, D. W.; Rosenzweig, B.; Yang, P.; Lengyel, F.; Fekete, B. M.

    2012-12-01

    The Northeast region (NE) exhibits many of the changes taking place across the Nation's landscapes and watersheds, yet also provides a unique lens through which to assess options for managing large-scale natural resource systems. We report here on a regional NSF-funded Earth System Modeling (EaSM) project, which has assembled an interdisciplinary research team from academia and government with expertise in physics, biogeochemistry, engineering, energy, economics, and policy engagement. The team is simultaneously studying the evolution of regional human-environment systems and seeking to improve the translation of research findings to the planning community. We hypothesize that there are regionally-significant consequences of human decisions on environmental systems of the NE, expressed through the action of both natural and engineered human systems that dictate the region's biogeophysical state, ecosystem services, energy and economic output. Our central goal is: To build a Northeast Regional Earth System Model (NE-RESM) that improves understanding and capacity to forecast the implications of planning decisions on the region's environment, ecosystem services, energy systems and economy through the 21st century. We are using scenario experiments to test our hypothesis and to make forecasts about the future. We see the proposed research as a major step forward in developing a capacity to diagnose and understand the state of large, interacting human-natural systems. Major foci include: the application of meso-scale atmospheric physics models to drive terrestrial-aquatic ecosystem models; a linked ecosystem services accounting tool; geospatial modeling of anthropogenic GHG emissions and biotic source/sinks at improved space/time resolutions; and meso-economic input-output model to evaluate the impacts of ecosystem services constraints on subregional economies. The presentation will report on recent progress across three strategic planning fronts, which are important to

  12. Stochastic characterization of regional circulation patterns for climate model diagnosis and estimation of local precipitation

    International Nuclear Information System (INIS)

    Zorita, E.; Hughes, J.P.

    1993-01-01

    Two statistical approaches for linking large-scale atmospheric circulation patterns and daily local rainfall are described and applied to several GCM (general circulation model) climate simulations. The ultimate objective is to simulate local precipitation associated with alternative climates. The index stations are located near the West and East North American coasts. The first method is based on CART analysis (Classification and Regression trees). It finds the classification of observed daily SLR (sea level pressure) fields in weather types that are most strongly associated with the presence/absence of rainfall in a set of index stations. The best results were obtained for winter rainfall for the West Coast, where a set of physically reasonable weather types could be identified, whereas for the East Coast the rainfall process seemed to be spatially less coherent. The GCM simulations were validated against observations in terms of probability of occurrence and survival time of these weather states. Some discrepancies werefound but there was no systematic bias, indicating that this behavior depends on the particular dynamics of each model. This classification method was then used for the generation of daily rainfall time series from the daily SLP fields from historical observation and from the GCM simulations. Whereas the mean rainfall and probability distributions were rather well replicated, the simulated dry periods were in all cases shorter than in the rainfall observations. The second rainfall generator is based on the analog method and uses information on the evolution of the SLP field in several previous days. It was found to perform reasonably well, although some downward bias in the simulated rainfall persistence was still present. Rainfall changes in a 2xCO 2 climate were investigated by applying both methods to the output of a greenhouse-gas experiment. The simulated precipitation changes were small. (orig.)

  13. Changes in snow cover over China in the 21st century as simulated by a high resolution regional climate model

    International Nuclear Information System (INIS)

    Shi Ying; Gao Xuejie; Wu Jia; Giorgi, Filippo

    2011-01-01

    On the basis of the climate change simulations conducted using a high resolution regional climate model, the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model, RegCM3, at 25 km grid spacing, future changes in snow cover over China are analyzed. The simulations are carried out for the period of 1951–2100 following the IPCC SRES A1B emission scenario. The results suggest good performances of the model in simulating the number of snow cover days and the snow cover depth, as well as the starting and ending dates of snow cover to the present day (1981–2000). Their spatial distributions and amounts show fair consistency between the simulation and observation, although with some discrepancies. In general, decreases in the number of snow cover days and the snow cover depth, together with postponed snow starting dates and advanced snow ending dates, are simulated for the future, except in some places where the opposite appears. The most dramatic changes are found over the Tibetan Plateau among the three major snow cover areas of Northeast, Northwest and the Tibetan Plateau in China.

  14. Using Perturbed Physics Ensembles and Machine Learning to Select Parameters for Reducing Regional Biases in a Global Climate Model

    Science.gov (United States)

    Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.

    2017-12-01

    This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.

  15. Animating climate model data

    Science.gov (United States)

    DaPonte, John S.; Sadowski, Thomas; Thomas, Paul

    2006-05-01

    This paper describes a collaborative project conducted by the Computer Science Department at Southern Connecticut State University and NASA's Goddard Institute for Space Science (GISS). Animations of output from a climate simulation math model used at GISS to predict rainfall and circulation have been produced for West Africa from June to September 2002. These early results have assisted scientists at GISS in evaluating the accuracy of the RM3 climate model when compared to similar results obtained from satellite imagery. The results presented below will be refined to better meet the needs of GISS scientists and will be expanded to cover other geographic regions for a variety of time frames.

  16. An assessment of aerosol optical properties from remote-sensing observations and regional chemistry-climate coupled models over Europe

    Science.gov (United States)

    Palacios-Peña, Laura; Baró, Rocío; Baklanov, Alexander; Balzarini, Alessandra; Brunner, Dominik; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; María López-Romero, José; Montávez, Juan Pedro; Pérez, Juan Luis; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela; Jiménez-Guerrero, Pedro

    2018-04-01

    Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain climate forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, mainly aerosol optical depth (AOD) and Ångström exponent (AE), their representation by different remote-sensing sensors and regional online coupled chemistry-climate models over Europe are evaluated. This work also characterises whether the inclusion of aerosol-radiation (ARI) or/and aerosol-cloud interactions (ACI) help improve the skills of modelling outputs.Two case studies were selected within the EuMetChem COST Action ES1004 framework when important aerosol episodes in 2010 all over Europe took place: a Russian wildfire episode and a Saharan desert dust outbreak that covered most of the Mediterranean Sea. The model data came from different regional air-quality-climate simulations performed by working group 2 of EuMetChem, which differed according to whether ARI or ACI was included or not. The remote-sensing data came from three different sensors: MODIS, OMI and SeaWIFS. The evaluation used classical statistical metrics to first compare satellite data versus the ground-based instrument network (AERONET) and then to evaluate model versus the observational data (both satellite and ground-based data).Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote-sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in

  17. Potential use of a regional climate model in seasonal tropical cyclone activity predictions in the western North Pacific

    Energy Technology Data Exchange (ETDEWEB)

    Au-Yeung, Andie Y.M.; Chan, Johnny C.L. [City University of Hong Kong, Guy Carpenter Asia-Pacific Climate Impact Centre, School of Energy and Environment, Kowloon, Hong Kong (China)

    2012-08-15

    This study investigates the potential use of a regional climate model in forecasting seasonal tropical cyclone (TC) activity. A modified version of Regional Climate Model Version 3 (RegCM3) is used to examine the ability of the model to simulate TC genesis and landfalling TC tracks for the active TC season in the western North Pacific. In the model, a TC is identified as a vortex satisfying several conditions, including local maximum relative vorticity at 850 hPa with a value {>=}450 x 10{sup -6} s{sup -1}, and the temperature at 300 hPa being 1 C higher than the average temperature within 15 latitude radius from the TC center. Tracks are traced by following these found vortices. Six-month ensemble (8 members each) simulations are performed for each year from 1982 to 2001 so that the climatology of the model can be compared to the Joint Typhoon Warning Center (JTWC) observed best-track dataset. The 20-year ensemble experiments show that the RegCM3 can be used to simulate vortices with a wind structure and temperature profile similar to those of real TCs. The model also reproduces tracks very similar to those observed with features like genesis in the tropics, recurvature at higher latitudes and landfall/decay. The similarity of the 500-hPa geopotential height patterns between RegCM3 and the European Centre for Medium-Range Weather Forecasts 40 Year Re-analysis (ERA-40) shows that the model can simulate the subtropical high to a large extent. The simulated climatological monthly spatial distributions as well as the interannual variability of TC occurrence are also similar to the JTWC data. These results imply the possibility of producing seasonal forecasts of tropical cyclones using real-time global climate model predictions as boundary conditions for the RegCM3. (orig.)

  18. Projected Changes to Streamflow Characteristics in Quebec Basins as Simulated by the Canadian Regional Climate Model (CRCM4)

    Science.gov (United States)

    Huziy, O.; Sushama, L.; Khaliq, M.; Lehner, B.; Laprise, R.; Roy, R.

    2011-12-01

    According to the Intergovernmental Panel on Climate Change (IPCC, 2007), an intensification of the global hydrological cycle and increase in precipitation for some regions around the world, including the northern mid- to high-latitudes, is expected in future climate. This will have an impact on mean and extreme flow characteristics, which need to be assessed for better development of adaptation strategies. Analysis of the mean and extreme streamflow characteristics for Quebec (North-eastern Canada) basins in current climate and their projected changes in future climate are assessed using a 10 member ensemble of current (1970 - 1999) and future (2041 - 2070) Canadian RCM (CRCM4) simulations. Validation of streamflow characteristics, performed by comparing modeled values with those observed, available from the Centre d'expertise hydrique du Quebec (CEHQ) shows that the model captures reasonably well the high flows. Results suggest increase in mean and 10 year return levels of 1 day high flows, which appear significant for most of the northern basins.

  19. Validation of precipitation over Japan during 1985-2004 simulated by three regional climate models and two multi-model ensemble means

    Energy Technology Data Exchange (ETDEWEB)

    Ishizaki, Yasuhiro [Meteorological Research Institute, Tsukuba (Japan); National Institute for Environmental Studies, Tsukuba (Japan); Nakaegawa, Toshiyuki; Takayabu, Izuru [Meteorological Research Institute, Tsukuba (Japan)

    2012-07-15

    We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate. (orig.)

  20. Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

    Science.gov (United States)

    Tariku, Tebikachew Betru; Gan, Thian Yew

    2018-06-01

    Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

  1. Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

    Science.gov (United States)

    Tariku, Tebikachew Betru; Gan, Thian Yew

    2017-08-01

    Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

  2. Simulation of Lake Surface Heat Fluxes by the Canadian Small Lake Model: Offline Performance Assessment for Future Coupling with a Regional Climate Model

    Science.gov (United States)

    Pernica, P.; Guerrero, J. L.; MacKay, M.; Wheater, H. S.

    2014-12-01

    Lakes strongly influence local and regional climate especially in regions where they are abundant. Development of a lake model for the purpose of integration within a regional climate model is therefore a subject of scientific interest. Of particular importance are the heat flux predictions provided by the lake model since they function as key forcings in a fully coupled atmosphere-land-lake system. The first step towards a coupled model is to validate and characterize the accuracy of the lake model over a range of conditions and to identify limitations. In this work, validation results from offline tests of the Canadian Small Lake Model; a deterministic, computationally efficient, 1D integral model, are presented. Heat fluxes (sensible and latent) and surface water temperatures simulated by the model are compared with in situ observations from two lakes; Landing Lake (NWT, Canada) and L239 (ELA, Canada) for the 2007-2009 period. Sensitivity analysis is performed to identify key parameters important for heat flux predictions. The results demonstrate the ability of the 1-D lake model to reproduce both diurnal and seasonal variations in heat fluxes and surface temperatures for the open water period. These results, in context of regional climate modelling are also discussed.

  3. BRICK v0.2, a simple, accessible, and transparent model framework for climate and regional sea-level projections

    Science.gov (United States)

    Wong, Tony E.; Bakker, Alexander M. R.; Ruckert, Kelsey; Applegate, Patrick; Slangen, Aimée B. A.; Keller, Klaus

    2017-07-01

    Simple models can play pivotal roles in the quantification and framing of uncertainties surrounding climate change and sea-level rise. They are computationally efficient, transparent, and easy to reproduce. These qualities also make simple models useful for the characterization of risk. Simple model codes are increasingly distributed as open source, as well as actively shared and guided. Alas, computer codes used in the geosciences can often be hard to access, run, modify (e.g., with regards to assumptions and model components), and review. Here, we describe the simple model framework BRICK (Building blocks for Relevant Ice and Climate Knowledge) v0.2 and its underlying design principles. The paper adds detail to an earlier published model setup and discusses the inclusion of a land water storage component. The framework largely builds on existing models and allows for projections of global mean temperature as well as regional sea levels and coastal flood risk. BRICK is written in R and Fortran. BRICK gives special attention to the model values of transparency, accessibility, and flexibility in order to mitigate the above-mentioned issues while maintaining a high degree of computational efficiency. We demonstrate the flexibility of this framework through simple model intercomparison experiments. Furthermore, we demonstrate that BRICK is suitable for risk assessment applications by using a didactic example in local flood risk management.

  4. FY08 LDRD Final Report Regional Climate

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-05-19

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

  5. Using nudging to improve global-regional dynamic consistency in limited-area climate modeling: What should we nudge?

    Science.gov (United States)

    Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

    2015-03-01

    Regional climate modelling sometimes requires that the regional model be nudged towards the large-scale driving data to avoid the development of inconsistencies between them. These inconsistencies are known to produce large surface temperature and rainfall artefacts. Therefore, it is essential to maintain the synoptic circulation within the simulation domain consistent with the synoptic circulation at the domain boundaries. Nudging techniques, initially developed for data assimilation purposes, are increasingly used in regional climate modeling and offer a workaround to this issue. In this context, several questions on the "optimal" use of nudging are still open. In this study we focus on a specific question which is: What variable should we nudge? in order to maintain the consistencies between the regional model and the driving fields as much as possible. For that, a "Big Brother Experiment", where a reference atmospheric state is known, is conducted using the weather research and forecasting (WRF) model over the Euro-Mediterranean region. A set of 22 3-month simulations is performed with different sets of nudged variables and nudging options (no nudging, indiscriminate nudging, spectral nudging) for summer and winter. The results show that nudging clearly improves the model capacity to reproduce the reference fields. However the skill scores depend on the set of variables used to nudge the regional climate simulations. Nudging the tropospheric horizontal wind is by far the key variable to nudge to simulate correctly surface temperature and wind, and rainfall. To a lesser extent, nudging tropospheric temperature also contributes to significantly improve the simulations. Indeed, nudging tropospheric wind or temperature directly impacts the simulation of the tropospheric geopotential height and thus the synoptic scale atmospheric circulation. Nudging moisture improves the precipitation but the impact on the other fields (wind and temperature) is not significant. As

  6. Use of circulation types classifications to evaluate AR4 climate models over the Euro-Atlantic region

    Energy Technology Data Exchange (ETDEWEB)

    Pastor, M.A.; Casado, M.J. [Agencia Estatal de Meteorologia (AEMET), Madrid (Spain)

    2012-10-15

    This paper presents an evaluation of the multi-model simulations for the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) in terms of their ability to simulate the ERA40 circulation types over the Euro-Atlantic region in winter season. Two classification schemes, k-means and SANDRA, have been considered to test the sensitivity of the evaluation results to the classification procedure. The assessment allows establishing different rankings attending spatial and temporal features of the circulation types. Regarding temporal characteristics, in general, all AR4 models tend to underestimate the frequency of occurrence. The best model simulating spatial characteristics is the UKMO-HadGEM1 whereas CCSM3, UKMO-HadGEM1 and CGCM3.1(T63) are the best simulating the temporal features, for both classification schemes. This result agrees with the AR4 models ranking obtained when having analysed the ability of the same AR4 models to simulate Euro-Atlantic variability modes. This study has proved the utility of applying such a synoptic climatology approach as a diagnostic tool for models' assessment. The ability of the models to properly reproduce the position of ridges and troughs and the frequency of synoptic patterns, will therefore improve our confidence in the response of models to future climate changes. (orig.)

  7. A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology.

    Science.gov (United States)

    Tompkins, Adrian M; Ermert, Volker

    2013-02-18

    The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions.

  8. Regional climate service in Southern Germany

    Science.gov (United States)

    Schipper, Janus; Hackenbruch, Julia

    2013-04-01

    Climate change challenges science, politics, business and society at the international, national and regional level. The South German Climate Office at the Karlsruhe Institute of Technology (KIT) is a contact for the structuring and dissemination of information on climate and climate change in the South German region. It provides scientifically based and user-oriented climate information. Thereby it builds a bridge between the climate sciences and society and provides scientific information on climate change in an understandable way. The expertise of KIT, in which several institutions operate on fundamental and applied climate research, and of partner institutions is the basis for the work in the climate office. The regional focus is on the south of Germany. Thematic focuses are e.g. regional climate modeling, trends in extreme weather events such as heavy rain and hail event, and issues for energy and water management. The South German Climate Office is one of four Regional Helmholtz Climate Offices, of which each has a regional and thematic focus. The users of the Climate Office can be summarized into three categories. First, there is the general public. This category consists mainly of non-professionals. Here, special attention is on an understandable translation of climate information. Attention is paid to application-related aspects, because each individual is affected in a different way by climate change. Typical examples of this category are school groups, citizens and the media. The second category consists of experts of other disciplines. Unlike the first category they are mainly interested in the exchange of results and data. It is important to the climate office to provide support for the use of climatological results. Typical representatives of this category are ministries, state offices, and companies. In the third and final category are scientists. In addition to the climatologists, this category also holds representatives from other scientific

  9. Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

    Science.gov (United States)

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

    2018-01-01

    Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

  10. Simulation of the summer circulation over South America by two regional climate models. Part I: Mean climatology

    Science.gov (United States)

    Fernandez, J. P. R.; Franchito, S. H.; Rao, V. B.

    2006-09-01

    This study investigates the capabilities of two regional models (the ICTP RegCM3 and the climate version of the CPTEC Eta model - EtaClim) in simulating the mean climatological features of the summer quasi-stationary circulations over South America. Comparing the results with the NCEP/DOE reanalysis II data it is seen that the RegCM3 simulates a weaker and southward shifted Bolivian high (BH). But, the Nordeste low (NL) is located close to its climatological position. In the EtaClim the position of the BH is reproduced well, but the NL is shifted towards the interior of the continent. To the east of Andes, the RegCM3 simulates a weaker low level jet and a weaker basic flow from the tropical Atlantic to Amazonia while they are stronger in the EtaClim. In general, the RegCM3 and EtaClim show, respectively a negative and positive bias in the surface temperature in almost all regions of South America. For both models, the correlation coefficients between the simulated precipitation and the GPCP data are high over most of South America. Although the RegCM3 and EtaClim overestimate the precipitation in the Andes region they show a negative bias in general over the entire South America. The simulations of upper and lower level circulations and precipitation fields in EtaClim were better than that of the RegCM3. In central Amazonia both models were unable to simulate the precipitation correctly. The results showed that although the RegCM3 and EtaClim are capable of simulating the main climatological features of the summer climate over South America, there are areas which need improvement. This indicates that the models must be more adequately tuned in order to give reliable predictions in the different regions of South America.

  11. Nested High Resolution Modeling of the Impact of Urbanization on Regional Climate in Three Vast Urban Agglomerations in China

    Science.gov (United States)

    Wang, Jun; Feng, Jinming; Yan, Zhongwei; Hu, Yonghong; Jia, Gensuo

    2013-04-01

    In this paper, the Weather Research and Forecasting (WRF) model coupled to the Urban Canopy Model (UCM) is employed to simulate the impact of urbanization on the regional climate over three vast city agglomerations in China. Based on high resolution land use and land cover data, two scenarios are designed to represent the non-urban and current urban land use distributions. By comparing the results of two nested, high resolution numerical experiments, the spatial and temporal changes on surface air temperature, heat stress index, surface energy budget and precipitation due to urbanization are analyzed and quantified. Urban expansion increases the surface air temperature in urban areas by about 1? and this climatic forcing of urbanization on temperature is more pronounced in summer and nighttime than other seasons and daytime. The heat stress intensity, which reflects the combined effects of temperature and humidity, is enhanced by about 0.5 units in urban areas. The regional incoming solar radiation increases after urban expansion, which may be caused by the reduction of cloud fraction. The increased temperature and roughness of the urban surface lead to enhanced convergence. Meanwhile, the planetary boundary layer is deepened and water vapor is mixed more evenly in the lower atmosphere. The deficit of water vapor leads to less convective available potential energy and more convective inhibition energy. Finally, these combined effects may reduce the rainfall amount over urban area mainly in summer and change the regional precipitation pattern to a certain extent.

  12. Nested high-resolution modeling of the impact of urbanization on regional climate in three vast urban agglomerations in China

    Science.gov (United States)

    Wang, Jun; Feng, Jinming; Yan, Zhongwei; Hu, Yonghong; Jia, Gensuo

    2012-11-01

    In this paper, the Weather Research and Forecasting Model, coupled to the Urban Canopy Model, is employed to simulate the impact of urbanization on the regional climate over three vast city agglomerations in China. Based on high-resolution land use and land cover data, two scenarios are designed to represent the nonurban and current urban land use distributions. By comparing the results of two nested, high-resolution numerical experiments, the spatial and temporal changes on surface air temperature, heat stress index, surface energy budget, and precipitation due to urbanization are analyzed and quantified. Urban expansion increases the surface air temperature in urban areas by about 1°C, and this climatic forcing of urbanization on temperature is more pronounced in summer and nighttime than other seasons and daytime. The heat stress intensity, which reflects the combined effects of temperature and humidity, is enhanced by about 0.5 units in urban areas. The regional incoming solar radiation increases after urban expansion, which may be caused by the reduction of cloud fraction. The increased temperature and roughness of the urban surface lead to enhanced convergence. Meanwhile, the planetary boundary layer is deepened, and water vapor is mixed more evenly in the lower atmosphere. The deficit of water vapor leads to less convective available potential energy and more convective inhibition energy. Finally, these combined effects may reduce the rainfall amount over urban areas, mainly in summer, and change the regional precipitation pattern to a certain extent.

  13. Aerosol modelling for regional climate studies: application to anthropogenic particles and evaluation over a European/African domain

    International Nuclear Information System (INIS)

    Solmon, F.; Giorgi, F.; Liousse, C.

    2006-01-01

    A simplified anthropogenic aerosol model for use in climate studies is developed and implemented within the regional climate model RegCM. The model includes sulphur dioxide, sulphate, hydrophobic and hydrophilic black carbon (BC) and organic carbon (OC) and is run for the winter and summer seasons of 2000 over a large domain extending from northern Europe to south tropical Africa. An evaluation of the model performance is carried out in terms of surface concentrations and aerosol optical depths (AODs). For sulphur dioxide and sulphate concentration, comparison of simulated fields and experimental data collected over the EMEP European network shows that the model generally reproduces the observed spatial patterns of near-surface sulphate. Sulphate concentrations are within a factor of 2 of observations in 34% (JJA) to 57% (DJF) of cases. For OC and BC, simulated concentrations are compared to different datasets. The simulated and observed values agree within a factor of 2 in 56% (DJF) to 62% (JJA) of cases for BC and 33% (JJA) to 64% (DJF) for OC. Simulated AODs are compared with ground-based (AERONET) and satellite (MODIS, MISR, TOMS) AOD datasets. Simulated AODs are in the range of AERONET and MISR data over northern Europe, and AOD spatial patterns show consistency with MODIS and TOMS retrievals both over Europe and Africa. The main model deficiencies we find are: (i) an underestimation of surface concentrations of sulphate and OC during the summer and especially over the Mediterranean region and (ii) a general underestimation of AOD, most pronounced over the Mediterranean basin. The primary factors we identify as contributing to these biases are the lack of natural aerosols (in particular, desert dust, secondary biogenic aerosols and nitrates), uncertainties in the emission inventories and aerosol cycling by moist convection. Also, in view of the availability of better observing datasets (e.g. as part of the AMMA project), we are currently working on improving

  14. Spatial and temporal characteristics of heat waves over Central Europe in an ensemble of regional climate model simulations

    Czech Academy of Sciences Publication Activity Database

    Lhotka, Ondřej; Kyselý, Jan

    2015-01-01

    Roč. 45, č. 9 (2015), s. 2351-2366 ISSN 0930-7575 R&D Projects: GA ČR GAP209/10/2265 EU Projects: European Commission(XE) 505539 - ENSEMBLES Program:FP6 Institutional support: RVO:68378289 Keywords : heat waves * regional climate models * land–atmosphere coupling * spatial characteristics * interannual variability * ENSEMBLES project Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 4.708, year: 2015 http://link.springer.com/article/10.1007%2Fs00382-015-2475-7

  15. Oblique radiation lateral open boundary conditions for a regional climate atmospheric model

    Science.gov (United States)

    Cabos Narvaez, William; De Frutos Redondo, Jose Antonio; Perez Sanz, Juan Ignacio; Sein, Dmitry

    2013-04-01

    The prescription of lateral boundary conditions in regional atmospheric models represent a very important issue for limited area models. The ill-posed nature of the open boundary conditions makes it necessary to devise schemes in order to filter spurious wave reflections at boundaries, being desirable to have one boundary condition per variable. On the other side, due to the essentially hyperbolic nature of the equations solved in state of the art atmospheric models, external data is required only for inward boundary fluxes. These circumstances make radiation lateral boundary conditions a good choice for the filtering of spurious wave reflections. Here we apply the adaptive oblique radiation modification proposed by Mikoyada and Roseti to each of the prognostic variables of the REMO regional atmospheric model and compare it to the more common normal radiation condition used in REMO. In the proposed scheme, special attention is paid to the estimation of the radiation phase speed, essential to detecting the direction of boundary fluxes. One of the differences with the classical scheme is that in case of outward propagation, the adaptive nudging imposed in the boundaries allows to minimize under and over specifications problems, adequately incorporating the external information.

  16. Regional Highlights of Climate Change

    Science.gov (United States)

    David L. Peterson; J.M. Wolken; Teresa Hollingsworth; Christian Giardina; J.S. Littell; Linda Joyce; Chris Swanston; Stephen Handler; Lindsey Rustad; Steve McNulty

    2014-01-01

    Climatic extremes, ecological disturbance, and their interactions are expected to have major effects on ecosystems and social systems in most regions of the United States in the coming decades. In Alaska, where the largest temperature increases have occurred, permafrost is melting, carbon is being released, and fire regimes are changing, leading to a...

  17. Evaluation of high intensity precipitation from 16 Regional climate models over a meso-scale catchment in the Midlands Regions of England

    Science.gov (United States)

    Wetterhall, F.; He, Y.; Cloke, H.; Pappenberger, F.; Freer, J.; Wilson, M.; McGregor, G.

    2009-04-01

    Local flooding events are often triggered by high-intensity rain-fall events, and it is important that these can be correctly modelled by Regional Climate Models (RCMs) if the results are to be used in climate impact assessment. In this study, daily precipitation from 16 RCMs was compared with observations over a meso-scale catchment in the Midlands Region of England. The RCM data was provided from the European research project ENSEMBLES and the precipitation data from the UK MetOffice. The RCMs were all driven by reanalysis data from the ERA40 dataset over the time period 1961-2000. The ENSEMBLES data is on the spatial scale of 25 x 25 km and it was disaggregated onto a 5 x 5 km grid over the catchment and compared with interpolated observational data with the same resolution. The mean precipitation was generally underestimated by the ENSEMBLES data, and the maximum and persistence of high intensity rainfall was even more underestimated. The inter-annual variability was not fully captured by the RCMs, and there was a systematic underestimation of precipitation during the autumn months. The spatial pattern in the modelled precipitation data was too smooth in comparison with the observed data, especially in the high altitudes in the western part of the catchment where the high precipitation usually occurs. The RCM outputs cannot reproduce the current high intensity precipitation events that are needed to sufficiently model extreme flood events. The results point out the discrepancy between climate model output and the high intensity precipitation input needs for hydrological impact modelling.

  18. Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment

    Directory of Open Access Journals (Sweden)

    Alex C. Ruane

    2017-03-01

    Full Text Available Abstract We present the Representative Temperature and Precipitation (T&P GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP to select a practical subset of global climate models (GCMs for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

  19. Using Social Media to Expand Peer-to-Peer Discussion in an Online Course about Regional Climate Modeling

    Science.gov (United States)

    Yarker, M. B.; Mesquita, M. D. S.

    2015-12-01

    The goal of this project is to make knowledge about regional climate modeling accessible to anyone in any location, regardless of their resources. We accomplish this through the development of a free online course, which introduces novice model users to an educational version of the Weather Research and Forecasting model (e-WRF). These courses are grounded in education theory and have been described in detail at prior AGU meetings (Kelsey et al. 2014, Walton et al. 2014, Yarker & Mesquita 2013). Research indicates that effective dialogue is an important component for successful learning to occur and displays the following elements: asking complex questions, deep discussion, and use of evidence to construct arguments (Benus et al. 2013). These can happen between the student and tutor, but peer-to-peer interaction is especially important as well as the most difficult aspect of social constructivism to meet, especially in an online setting. In our online courses, standard course forums were underutilized and generally only used to ask the tutor clarifying questions or troubleshoot error messages. To rectify this problem, we began using social media to facilitate conversation and notice vast improvement in peer-to-peer communication. Moreover, we created a community of over 700 regional climate modelers from around the world, sharing information, asking questions, and creating research projects relating to climate change. Data was gathered by qualitatively analyzing forum and Facebook posts and quantitatively analyzing survey data from participants in both courses. Facebook participants posted on the group more often about a wider variety of topics than the forum participants. Additionally, there were statistically significant increase ('student' t test and Mann-Whitney test) in the elements of effective dialogue. We conclude that social media can serve as a possible tool in the development of online learning, especially for difficult concepts like regional climate

  20. Climate Impacts of Deforestation/Land-Use Changes in Central South America in the PRECIS Regional Climate Model: Mean Precipitation and Temperature Response to Present and Future Deforestation Scenarios

    OpenAIRE

    Pablo O. Canziani; Gerardo Carbajal Benitez

    2012-01-01

    Deforestation/land-use changes are major drivers of regional climate change in central South America, impacting upon Amazonia and Gran Chaco ecoregions. Most experimental and modeling studies have focused on the resulting perturbations within Amazonia. Using the Regional Climate Model PRECIS, driven by ERA-40 reanalysis and ECHAM4 Baseline model for the period 1961–2000 (40-year runs), potential effects of deforestation/land-use changes in these and other neighboring ecoregions are evaluated....

  1. Detection and Attribution of Regional Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Bala, G; Mirin, A

    2007-01-19

    We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and ocean circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.

  2. Numerical simulation of surface solar radiation over Southern Africa. Part 1: Evaluation of regional and global climate models

    Science.gov (United States)

    Tang, Chao; Morel, Béatrice; Wild, Martin; Pohl, Benjamin; Abiodun, Babatunde; Bessafi, Miloud

    2018-02-01

    This study evaluates the performance of climate models in reproducing surface solar radiation (SSR) over Southern Africa (SA) by validating five Regional Climate Models (RCM, including CCLM4, HIRHAM5, RACMO22T, RCA4 and REMO2009) that participated in the Coordinated Regional Downscaling Experiment program over Africa (CORDEX-Africa) along with their ten driving General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 over SA. The model simulated SSR was thereby compared to reference data from ground-based measurements, satellite-derived products and reanalyses over the period 1990-2005. Results show that (1) the references obtained from satellite retrievals and reanalyses overall overestimate SSR by up to 10 W/m2 on average when compared to ground-based measurements from the Global Energy Balance Archive, which are located mainly over the eastern part of the southern African continent. (2) Compared to one of the satellite products (Surface Solar Radiation Data Set—Heliosat Edition 2; SARAH-2): GCMs overestimate SSR over SA in terms of their multi-model mean by about 1 W/m2 (compensation of opposite biases over sub-regions) and 7.5 W/m2 in austral summer and winter respectively; RCMs driven by GCMs show in their multimodel mean underestimations of SSR in both seasons with Mean Bias Errors (MBEs) of about - 30 W/m2 in austral summer and about - 14 W/m2 in winter compared to SARAH-2. This multi-model mean low bias is dominated by the simulations of the CCLM4, with negative biases up to - 76 W/m2 in summer and - 32 W/m2 in winter. (3) The discrepancies in the simulated SSR over SA are larger in the RCMs than in the GCMs. (4) In terms of trend during the "brightening" period 1990-2005, both GCMs and RCMs (driven by European Centre for Medium-Range Weather Forecasts Reanalysis ERA-Interim, short as ERAINT and GCMs) simulate an SSR trend of less than 1 W/m2 per decade. However, variations of SSR trend exist among different references data

  3. Regional climate change mitigation analysis

    Energy Technology Data Exchange (ETDEWEB)

    Rowlands, Ian H [UNEP Collaborating Centre on Energy and Environment, and Univ. of Waterloo (Canada)

    1998-10-01

    The purpose of this paper is to explore some of the key methodological issues that arise from an analysis of regional climate change mitigation options. The rationale for any analysis of regional mitigation activities, emphasising both the theoretical attractiveness and the existing political encouragement and the methodology that has been developed are reviewed. The differences arising from the fact that mitigation analyses have been taken from the level of the national - where the majority of the work has been completed to date - to the level of the international - that is, the `regional` - will be especially highlighted. (EG)

  4. Regional climate change mitigation analysis

    International Nuclear Information System (INIS)

    Rowlands, Ian H.

    1998-01-01

    The purpose of this paper is to explore some of the key methodological issues that arise from an analysis of regional climate change mitigation options. The rationale for any analysis of regional mitigation activities, emphasising both the theoretical attractiveness and the existing political encouragement and the methodology that has been developed are reviewed. The differences arising from the fact that mitigation analyses have been taken from the level of the national - where the majority of the work has been completed to date - to the level of the international - that is, the 'regional' - will be especially highlighted. (EG)

  5. Potential changes in the extreme climate conditions at the regional scale: from observed data to modelling approaches and towards probabilistic climate change information

    International Nuclear Information System (INIS)

    Gachon, P.; Radojevic, M.; Harding, A.; Saad, C.; Nguyen, V.T.V.

    2008-01-01

    The changes in the characteristics of extreme climate conditions are one of the most critical challenges for all ecosystems, human being and infrastructure, in the context of the on-going global climate change. However, extremes information needed for impacts studies cannot be obtained directly from coarse scale global climate models (GCMs), due mainly to their difficulties to incorporate regional scale feedbacks and processes responsible in part for the occurrence, intensity and duration of extreme events. Downscaling approaches, namely statistical and dynamical downscaling techniques (i.e. SD and RCM), have emerged as useful tools to develop high resolution climate change information, in particular for extremes, as those are theoretically more capable to take into account regional/local forcings and their feedbacks from large scale influences as they are driven with GCM synoptic variables. Nevertheless, in spite of the potential added values from downscaling methods (statistical and dynamical), a rigorous assessment of these methods are needed as inherent difficulties to simulate extremes are still present. In this paper, different series of RCM and SD simulations using three different GCMs are presented and evaluated with respect to observed values over the current period and over a river basin in southern Quebec, with future ensemble runs, i.e. centered over 2050s (i.e. 2041-2070 period using the SRES A2 emission scenario). Results suggest that the downscaling performance over the baseline period significantly varies between the two downscaling techniques and over various seasons with more regular reliable simulated values with SD technique for temperature than for RCM runs, while both approaches produced quite similar temperature changes in the future from median values with more divergence for extremes. For precipitation, less accurate information is obtained compared to observed data, and with more differences among models with higher uncertainties in the

  6. Establishing Design Storm Values from Climate Models in Coastal Regions: Challenges and Opportunities

    Science.gov (United States)

    Dynamic interactions of atmospheric and hydrological processes result in large spatiotemporal changes of precipitation and wind speed in coastal storm events under both current and future climates. This variability can impact the design and sustainability of water infrastructure ...

  7. Regional integrated modelling of climate change impacts on natural resources and resource usage in semi-arid Norhteast Brazil

    NARCIS (Netherlands)

    Krol, Martinus S.; Bronstert, Axel

    2007-01-01

    Semi-arid regions are characterised by a high vulnerability of natural resources to climate change, pronounced climatic variability and often by water scarcity and related social stress. The analysis of the dynamics of natural conditions and the assessment of possible strategies to cope with

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

    Energy Technology Data Exchange (ETDEWEB)

    Hall, Alex [University of California, Los Angeles, CA (United States). Joint Institute for Regional Earth System Science and Engineering

    2013-07-24

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

  9. Involving regional expertise in nationwide modeling for adequate prediction of climate change effects on different demands for fresh water

    Science.gov (United States)

    de Lange, W. J.

    2014-05-01

    Wim J. de Lange, Geert F. Prinsen, Jacco H. Hoogewoud, Ab A Veldhuizen, Joachim Hunink, Erik F.W. Ruijgh, Timo Kroon Nationwide modeling aims to produce a balanced distribution of climate change effects (e.g. harm on crops) and possible compensation (e.g. volume fresh water) based on consistent calculation. The present work is based on the Netherlands Hydrological Instrument (NHI, www.nhi.nu), which is a national, integrated, hydrological model that simulates distribution, flow and storage of all water in the surface water and groundwater systems. The instrument is developed to assess the impact on water use on land-surface (sprinkling crops, drinking water) and in surface water (navigation, cooling). The regional expertise involved in the development of NHI come from all parties involved in the use, production and management of water, such as waterboards, drinking water supply companies, provinces, ngo's, and so on. Adequate prediction implies that the model computes changes in the order of magnitude that is relevant to the effects. In scenarios related to drought, adequate prediction applies to the water demand and the hydrological effects during average, dry, very dry and extremely dry periods. The NHI acts as a part of the so-called Deltamodel (www.deltamodel.nl), which aims to predict effects and compensating measures of climate change both on safety against flooding and on water shortage during drought. To assess the effects, a limited number of well-defined scenarios is used within the Deltamodel. The effects on demand of fresh water consist of an increase of the demand e.g. for surface water level control to prevent dike burst, for flushing salt in ditches, for sprinkling of crops, for preserving wet nature and so on. Many of the effects are dealt with by regional and local parties. Therefore, these parties have large interest in the outcome of the scenario analyses. They are participating in the assessment of the NHI previous to the start of the analyses

  10. Evaluating precipitation in a regional climate model using ground-based radar measurements in Dronning Maud Land, East Antarctica

    Science.gov (United States)

    Gorodetskaya, Irina; Maahn, Maximilan; Gallée, Hubert; Souverijns, Niels; Gossart, Alexandra; Kneifel, Stefan; Crewell, Susanne; Van Lipzig, Nicole

    2017-04-01

    Occasional very intense snowfall events over Dronning Maud Land (DML) region in East Antarctica, contributed significantly to the entire Antarctic ice sheet surface mass balance (SMB) during the last years. The meteorological-cloud-precipitation observatory running at the Princess Elisabeth station (PE) in the DML escarpment zone since 2009 (HYDRANT/AEROCLOUD projects), provides unique opportunity to estimate contribution of precipitation to the local snow accumulation and new data for evaluating precipitation in climate models. Our previous work using PE measurements showed that occasional intense precipitation events determine the total local yearly SMB and account for its large interannual variability. Here we use radar measurements to evaluate precipitation in a regional climate model with a special focus on intense precipitation events together with the large-scale atmospheric dynamics responsible for these events. The coupled snow-atmosphere regional climate model MAR (Modèle Atmosphérique Régional) is used to simulate climate and SMB in DML at 5-km horizontal resolution during 2012 using initial and boundary conditions from the European Centre for Medium-range Weather Forecasts (ECMWF) Interim re-analysis atmospheric and oceanic fields. Two evaluation approaches are used: observations-to-model and model-to-observations. In the first approach, snowfall rate (S) is derived from the MRR (vertically profiling 24-GHz precipitation radar) effective reflectivity factor (Ze) at 400 m agl using various Ze-S relationships for dry snow. The uncertainty in Ze-S relationships is constrained using snow particle size distribution from Snow Video Imager - Precipitation Imaging Package (SVI/PIP) and information about particle shapes. For the second approach we apply the Passive and Active Microwave radiative TRAnsfer model (PAMTRA), which allows direct comparison of the radar-measured and climate model-based vertical profiles of the radar Ze and Doppler velocity. In MAR

  11. High Artic Glaciers and Ice Caps Ice Mass Change from GRACE, Regional Climate Model Output and Altimetry.

    Science.gov (United States)

    Ciraci, E.; Velicogna, I.; Fettweis, X.; van den Broeke, M. R.

    2016-12-01

    The Arctic hosts more than the 75% of the ice covered regions outside from Greenland and Antarctica. Available observations show that increased atmospheric temperatures during the last century have contributed to a substantial glaciers retreat in all these regions. We use satellite gravimetry by the NASA's Gravity Recovery and Climate Experiment (GRACE), and apply a least square fit mascon approach to calculate time series of ice mass change for the period 2002-2016. Our estimates show that arctic glaciers have constantly contributed to the sea level rise during the entire observation period with a mass change of -170+/-20 Gt/yr equivalent to the 80% of the total ice mass change from the world Glacier and Ice Caps (GIC) excluding the Ice sheet peripheral GIC, which we calculated to be -215+/-32 GT/yr, with an acceleration of 9+/-4 Gt/yr2. The Canadian Archipelago is the main contributor to the total mass depletion with an ice mass trend of -73+/-9 Gt/yr and a significant acceleration of -7+/-3 Gt/yr2. The increasing mass loss is mainly determined by melting glaciers located in the northern part of the archipelago.In order to investigate the physical processes driving the observed ice mass loss we employ satellite altimetry and surface mass balance (SMB) estimates from Regional climate model outputs available for the same time period covered by the gravimetry data. We use elevation data from the NASA ICESat (2003-2009) and ESA CryoSat-2 (2010-2016) missions to estimate ice elevation changes. We compare GRACE ice mass estimates with time series of surface mass balance from the Regional Climate Model (RACMO-2) and the Modèle Atmosphérique Régional (MAR) and determine the portion of the total mass change explained by the SMB signal. We find that in Iceland and in the and the Canadian Archipelago the SMB signal explains most of the observed mass changes, suggesting that ice discharge may play a secondary role here. In other region, e.g. in Svalbar, the SMB signal

  12. Characterization of the rainy season in Burkina Faso and it's representation by regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Ibrahim, B.; Karambiri, H. [Institut International d' Ingenierie de l' Eau et de l' Environnement (2iE), Ouagadougou 01 (Burkina Faso); Polcher, J. [Laboratoire de Meteorologie Dynamique du CNRS, Institut Pierre Simon Laplace, Paris Cedex 05 (France); Rockel, B. [Helmholtz-Zentrum Geesthacht Institute of Coastal Research/Group Regional Atmospheric Modeling, Geesthacht (Germany)

    2012-09-15

    West African monsoon is one of the most challenging climate components to model. Five regional climate models (RCMs) were run over the West African region with two lateral boundary conditions, ERA-Interim re-analysis and simulations from two general circulation models (GCMs). Two sets of daily rainfall data were generated from these boundary conditions. These simulated rainfall data are analyzed here in comparison to daily rainfall data collected over a network of ten synoptic stations in Burkina Faso from 1990 to 2004. The analyses are based on a description of the rainy season throughout a number of it's characteristics. It was found that the two sets of rainfall data produced with the two driving data present significant biases. The RCMs generally produce too frequent low rainfall values (between 0.1 and 5 mm/day) and too high extreme rainfalls (more than twice the observed values). The high frequency of low rainfall events in the RCMs induces shorter dry spells at the rainfall thresholds of 0.1-1 mm/day. Altogether, there are large disagreements between the models on the simulate season duration and the annual rainfall amounts but most striking are their differences in representing the distribution of rainfall intensity. It is remarkable that these conclusions are valid whether the RCMs are driven by re-analysis or GCMs. In none of the analyzed rainy season characteristics, a significant improvement of their representation can be found when the RCM is forced by the re-analysis, indicating that these deficiencies are intrinsic to the models. (orig.)

  13. Assessing the effectiveness of RegCM4 regional climate model in simulating the aerosol optical depth patterns over the region of Eastern Mediterranean

    Science.gov (United States)

    Georgoulias, Aristeidis K.; Tsikerdekis, Athanasios; Ntogras, Christos; Zanis, Prodromos

    2014-05-01

    In this work, the ability of the regional climate model RegCM4 to simulate the aerosol optical depth (AOD) patterns over the region of Eastern Mediterranean is assessed. Three separate runs were implemented within the framework of the QUADIEEMS project for the time period 2000-2010 at a horizontal resolution of 50km covering the region of Europe. ERA-interim data were used as lateral boundary conditions while the model was driven by emissions from CMIP5. In the first case, the total of the aerosol types that RegCM4 accounts for were included (sulfate, black carbon, sea salt, dust), while in the other two cases only anthropogenic and dust particles were taken into account, respectively. The total AOD patterns were compared against level-2 satellite observations from MODIS TERRA and AQUA and ground-based measurements from 12 AERONET sites located in the region. In addition, the RegCM4 anthropogenic and dust AOD patterns were compared against the anthropogenic and dust component of MODIS AOD which was calculated using a combination of various satellite, model and reanalysis products. Our results indicate a significant underestimation of the anthropogenic AOD, while, on the contrary, the dust AOD fields are simulated in a more efficient way. The QUADIEEMS project is co-financed by the European Social Fund (ESF) and national resources under the operational programme Education and Lifelong Learning (EdLL) within the framework of the Action "Supporting Postdoctoral Researchers".

  14. Downscaling with a nested regional climate model in near-surface fields over the contiguous United States: WRF dynamical downscaling

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jiali [Environmental Science Division, Argonne National Laboratory, Argonne Illinois USA; Kotamarthi, Veerabhadra R. [Environmental Science Division, Argonne National Laboratory, Argonne Illinois USA

    2014-07-27

    The Weather Research and Forecasting (WRF) model is used for dynamic downscaling of 2.5 degree National Centers for Environmental Prediction-U.S. Department of Energy Reanalysis II (NCEP-R2) data for 1980-2010 at 12 km resolution over most of North America. The model's performance for surface air temperature and precipitation is evaluated by comparison with high-resolution observational data sets. The model's ability to add value is investigated by comparison with NCEP-R2 data and a 50 km regional climate simulation. The causes for major model bias are studied through additional sensitivity experiments with various model setup/integration approaches and physics representations. The WRF captures the main features of the spatial patterns and annual cycles of air temperature and precipitation over most of the contiguous United States. However, simulated air temperatures over the south central region and precipitation over the Great Plains and the Southwest have significant biases. Allowing longer spin-up time, reducing the nudging strength, or replacing the WRF Single-Moment 6-class microphysics with Morrison microphysics reduces the bias over some subregions. However, replacing the Grell-Devenyi cumulus parameterization with Kain-Fritsch shows no improvement. The 12 km simulation does add value above the NCEP-R2 data and the 50 km simulation over mountainous and coastal zones.

  15. Black carbon concentration and deposition estimations in Finland by the regional aerosol–climate model REMO-HAM

    Directory of Open Access Journals (Sweden)

    A. I. Hienola

    2013-04-01

    Full Text Available The prediction skill of the regional aerosol–climate model REMO-HAM was assessed against the black carbon (BC concentration measurements from five locations in Finland, with focus on Hyytiälä station for the year 2005. We examined to what extent the model is able to reproduce the measurements using several statistical tools: median comparison, overlap coefficient (OVL; the common area under two probability distributions curves and Z score (a measure of standard deviation, shape and spread of the distributions. The results of the statistics showed that the model is biased low. The local and regional emissions of BC have a significant contribution, and the model tendency to flatten the observed BC is most likely dominated by the lack of domestic burning of biofuel in the emission inventories. A further examination of the precipitation data from both measurements and model showed that there is no correlation between REMO's excessive precipitation and BC underestimation. This suggests that the excessive wet removal is not the main cause of the low black carbon concentration output. In addition, a comparison of wind directions in relation with high black carbon concentrations shows that REMO-HAM is able to predict the BC source directions relatively well. Cumulative black carbon deposition fluxes over Finland were estimated, including the deposition on snow.

  16. CARICOF - The Caribbean Regional Climate Outlook Forum

    Science.gov (United States)

    Van Meerbeeck, Cedric

    2013-04-01

    Regional Climate Outlook Forums (RCOFs) are viewed as a critical building block in the Global Framework for Climate Services (GFCS) of the World Meteorological Organization (WMO). The GFCS seeks to extend RCOFs to all vulnerable regions of the world such as the Caribbean, of which the entire population is exposed to water- and heat-related natural hazards. An RCOF is initially intended to identify gaps in information and technical capability; facilitate research cooperation and data exchange within and between regions, and improve coordination within the climate forecasting community. A focus is given on variations in climate conditions on a seasonal timescale. In this view, the relevance of a Caribbean RCOF (CARICOF) is the following: while the seasonality of the climate in the Caribbean has been well documented, major gaps in knowledge exist in terms of the drivers in the shifts of amplitude and phase of seasons (as evidenced from the worst region-wide drought period in recent history during 2009-2010). To address those gaps, CARICOF has brought together National Weather Services (NWSs) from 18 territories under the coordination of the Caribbean Institute for Meteorology and Hydrology (CIMH), to produce region-wide, consensus, seasonal climate outlooks since March 2012. These outlooks include tercile rainfall forecasts, sea and air surface temperature forecasts as well as the likely evolution of the drivers of seasonal climate variability in the region, being amongst others the El Niño Southern Oscillation or tropical Atlantic and Caribbean Sea temperatures. Forecasts for both the national-scale forecasts made by the NWSs and CIMH's regional-scale forecast amalgamate output from several forecasting tools. These currently include: (1) statistical models such as Canonical Correlation Analysis run with the Climate Predictability Tool, providing tercile rainfall forecasts at weather station scale; (2) a global outlooks published by the WMO appointed Global Producing

  17. Simulation of Relationship between ENSO and winter precipitation over Western Himalayas: Application of Regional climate model (RegT-Band)

    Science.gov (United States)

    Tiwari, P. R.; Mohanty, U. C.; Dey, S.; Acharaya, N.; Sinha, P.

    2012-12-01

    Precipitation over the Western Himalayas region during winter is mainly associated with the passage of midlatitude synoptic systems known as western disturbances (WDs). Recently, many observational and modeling studies reported that the relationship of the Indian southwest monsoon rainfall with El Niño- Southern Oscillation (ENSO) has weakened since around 1980. But, in contrast, only very few observational studies are reported so far to examine the relationship between ENSO and the winter precipitation over the Western Himalayas region from December to February (DJF). But there is a huge gap of modeling this phenomenon. So keeping in view of the absence of modeling studies, an attempt is made to simulate the relationship between wintertime precipitations associated with large scale global forcing of ENSO over the Western Himalayas. In the present study, RegT-Band, a tropical band version of the regional climate model RegCM4 is integrated for a set of 5 El Niño (1986-87, 1991-92, 1997-98, 2002-03, 2009-10) and 4 La Niña (1984-85, 1988-89, 1999-2000, 2007-08) years with the observed sea-surface temperature and lateral boundary condition. The domain extends from 50° S to 50° N and covers the entire tropics at a grid spacing of about 45 km, i.e. it includes lateral boundary forcing only at the southern and northern boundaries. The performance evaluation of the model in capturing the large scale fields followed by ENSO response with wintertime precipitation over the Western Himalayas region has been carried out by using National Center for Environmental Prediction (NCEP)-Department of Energy (DOE) reanalysis 2 (NNRP2) data (2.5° x 2.5°) and Aphrodite precipitation data (0.25° x 0.25°). The model is able to delineate the mean circulation associated with ENSO over the region during DJF reasonably well and shows strong southwesterly to northwesterly wind flow, which is there in verification analysis also. The vertical structure of the low as well as upper level

  18. The role of lateral boundary conditions in simulations of mineral aerosols by a regional climate model of Southwest Asia

    Energy Technology Data Exchange (ETDEWEB)

    Marcella, Marc Pace [Ralph M. Parsons Laboratory, Department of Civil and Environmental Engineering, Cambridge, MA (United States); Massachusetts Institute of Technology, Cambridge, Massachusetts (United States); Eltahir, Elfatih A.B. [Massachusetts Institute of Technology, Cambridge, Massachusetts (United States)

    2012-01-15

    The importance of specifying realistic lateral boundary conditions in the regional modeling of mineral aerosols has not been examined previously. This study examines the impact of assigning values for mineral aerosol (dust) concentrations at the lateral boundaries of Regional Climate Model version 3 (RegCM3) and its aerosol model over Southwest Asia. Currently, the dust emission module of RegCM3 operates over the interior of the domain, allowing dust to be transported to the boundaries, but neglecting any dust emitted at these points or from outside the domain. To account for possible dust occurring at, or entering from the boundaries, mixing ratios of dust concentrations from a larger domain RegCM3 simulation are specified at the boundaries of a smaller domain over Southwest Asia. The lateral boundary conditions are monthly averaged concentration values ({mu}g of dust per kg of dry air) resolved in the vertical for all four dust bin sizes within RegCM3's aerosol model. RegCM3 simulations with the aerosol/dust model including lateral boundary conditions for dust are performed for a five year period and compared to model simulations without prescribed dust concentrations at the boundaries. Results indicate that specifying boundary conditions has a significant impact on dust loading across the entire domain over Southwest Asia. More specifically, a nearly 30% increase in aerosol optical depth occurs during the summer months from specifying realistic dust boundary conditions, bringing model results closer to observations such as MISR. In addition, smaller dust particles at the boundaries have a more important impact than large particles in affecting the dust loading within the interior of this domain. Moreover, increases in aerosol optical depth and dust concentrations within the interior domain are not entirely caused by inflow from the boundaries; results indicate that an increase in the gradient of concentration at the boundaries causes an increase of

  19. Med-CORDEX: a first coordinated inter-comparison of high-resolution and fully coupled regional climate models for the Mediterranean

    Science.gov (United States)

    Somot, Samuel

    2015-04-01

    Due to its geographical, meteorological and oceanographic features, the Mediterranean region can be considered as one of the best place to test and use regional climate modelling tools. It has been chosen as one of the CORDEX sub-domain (MED) leading to the Med-CORDEX initiative. This open and voluntary initiative, financially supported by MISTRALS/HyMeX, has been proposed by the Mediterranean climate modelling research community as a follow-up of previous initiatives. In addition to the CORDEX-like simulations (Atmosphere-RCM, 50 km, ERA-Interim and GCM driven runs), Med-CORDEX includes additional simulations to experiment some of the regional climate modelling current challenges. We present here the status and results of these additional simulations dedicated to the use of (1) very high-resolution Regional Climate Models (RCM, up to 10 km) and (2) fully coupled Regional Climate System Models (RCSM), coupling the various components of the regional climate (atmosphere, land surface and hydrology, river and ocean). Today, Med-CORDEX gathers 23 different modelling groups from 9 different countries (France, Italy, Spain, Serbia, Turkey, Greece, Tunisia, Germany, Hungary) in Europe, Middle-East and North-Africa. They use 12 different atmosphere RCMs including land-surface representation, 4 river models, 10 regional ocean models and 12 different Regional Climate System Models. Almost all the simulations planned (Evaluation, Historical and Scenarios modes) have been completed by the modelling teams. More than half of the runs are archived and freely available for non-commercial use through a dedicated database hosted at ENEA at www.medcordex.eu in common and standardized netcdf format (265,000 files and 3.6 Tb uploaded). This includes atmosphere-only, ocean-only and fully coupled regional climate models. In particular multi-model regional ocean simulations have been archived in a common and standardized format for the first time in the history of the Mediterranean Sea

  20. Assessment of two versions of regional climate model in simulating the Indian Summer Monsoon over South Asia CORDEX domain

    Science.gov (United States)

    Pattnayak, K. C.; Panda, S. K.; Saraswat, Vaishali; Dash, S. K.

    2018-04-01

    This study assess the performance of two versions of Regional Climate Model (RegCM) in simulating the Indian summer monsoon over South Asia for the period 1998 to 2003 with an aim of conducting future climate change simulations. Two sets of experiments were carried out with two different versions of RegCM (viz. RegCM4.2 and RegCM4.3) with the lateral boundary forcings provided from European Center for Medium Range Weather Forecast Reanalysis (ERA-interim) at 50 km horizontal resolution. The major updates in RegCM4.3 in comparison to the older version RegCM4.2 are the inclusion of measured solar irradiance in place of hardcoded solar constant and additional layers in the stratosphere. The analysis shows that the Indian summer monsoon rainfall, moisture flux and surface net downward shortwave flux are better represented in RegCM4.3 than that in the RegCM4.2 simulations. Excessive moisture flux in the RegCM4.2 simulation over the northern Arabian Sea and Peninsular India resulted in an overestimation of rainfall over the Western Ghats, Peninsular region as a result of which the all India rainfall has been overestimated. RegCM4.3 has performed well over India as a whole as well as its four rainfall homogenous zones in reproducing the mean monsoon rainfall and inter-annual variation of rainfall. Further, the monsoon onset, low-level Somali Jet and the upper level tropical easterly jet are better represented in the RegCM4.3 than RegCM4.2. Thus, RegCM4.3 has performed better in simulating the mean summer monsoon circulation over the South Asia. Hence, RegCM4.3 may be used to study the future climate change over the South Asia.

  1. Inclusion of climatic and touristic factors in the analysis and modelling of the municipal water demand in a Mediterranean region

    Science.gov (United States)

    Toth, Elena; Bragalli, Cristiana; Neri, Mattia

    2017-04-01

    In Mediterranean regions, inherently affected by water scarcity conditions, the gap between water availability and demand may further increase in the near future due to both climatic and anthropogenic drivers. In particular, the high degree of urbanization and the concentration of population and activities in coastal areas is often severely impacting the water availability also for the residential sector. It is therefore crucial analysing the importance of both climatic and touristic factors as drivers for the water demand in such areas, to better understand and model the expected consumption in order to improve the water management policies and practices. The study presents an analysis referred to a large number of municipalities, covering almost the whole Romagna region, in Northern Italy, representing one of the most economically developed areas in Europe and characterized by an extremely profitable tourist industry, especially in the coastal cities. For this region it is therefore extremely important to assess the significance of the drivers that may influence the demand in the different periods of the year, that is climatic factors (rainfall depths and occurrence, temperature averages and extremes), but also the presence of tourists, in both official tourist accommodation structures and in holidays homes (and the latter are very difficult to estimate). Analyses on the Italian water industry at seasonal or monthly time scale has been so far, extremely limited in the literature by the scarce availability of data on the water demands, that are made public only as annual volumes. All the study municipalities are supplied by the same water company, who provided monthly consumption volumes data at the main inlet points of the entire distribution network for a period of 7 years (2009-2015). For the same period, precipitation and temperature data have been collected and summarised in indexes representing monthly averages, days of occurrence and over threshold values

  2. Climate models and scenarios

    Energy Technology Data Exchange (ETDEWEB)

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

    1996-12-31

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

  3. Climate models and scenarios

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-12-31

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

  4. Evaluation of regional climate simulations over the Great Lakes region driven by three global data sets

    Science.gov (United States)

    Shiyuan Zhong; Xiuping Li; Xindi Bian; Warren E. Heilman; L. Ruby Leung; William I. Jr. Gustafson

    2012-01-01

    The performance of regional climate simulations is evaluated for the Great Lakes region. Three 10-year (1990-1999) current-climate simulations are performed using the MM5 regional climate model (RCM) with 36-km horizontal resolution. The simulations employed identical configuration and physical parameterizations, but different lateral boundary conditions and sea-...

  5. Evaluating impacts of climate change on future water scarcity in an intensively managed semi-arid region using a coupled model of biophysical processes and water rights

    Science.gov (United States)

    Han, B.; Flores, A. N.; Benner, S. G.

    2017-12-01

    In semiarid and arid regions where water supply is intensively managed, future water scarcity is a product of complex interactions between climate change and human activities. Evaluating future water scarcity under alternative scenarios of climate change, therefore, necessitates modeling approaches that explicitly represent the coupled biophysical and social processes responsible for the redistribution of water in these regions. At regional scales a particular challenge lies in adequately capturing not only the central tendencies of change in projections of climate change, but also the associated plausible range of variability in those projections. This study develops a framework that combines a stochastic weather generator, historical climate observations, and statistically downscaled General Circulation Model (GCM) projections. The method generates a large ensemble of daily climate realizations, avoiding deficiencies of using a few or mean values of individual GCM realizations. Three climate change scenario groups reflecting the historical, RCP4.5, and RCP8.5 future projections are developed. Importantly, the model explicitly captures the spatiotemporally varying irrigation activities as constrained by local water rights in a rapidly growing, semi-arid human-environment system in southwest Idaho. We use this modeling framework to project water use and scarcity patterns under the three future climate change scenarios. The model is built using the Envision alternative futures modeling framework. Climate projections for the region show future increases in both precipitation and temperature, especially under the RCP8.5 scenario. The increase of temperature has a direct influence on the increase of the irrigation water use and water scarcity, while the influence of increased precipitation on water use is less clear. The predicted changes are potentially useful in identifying areas in the watershed particularly sensitive to water scarcity, the relative importance of

  6. Downscaling of Short-Term Precipitation from Regional Climate Models for Sustainable Urban Planning

    Directory of Open Access Journals (Sweden)

    Holger Hoppe

    2012-05-01

    Full Text Available A framework for downscaling precipitation from RCM projections to the high resolutions in time and space required in the urban hydrological climate change impact assessment is outlined and demonstrated. The basic approach is that of Delta Change, developed for both continuous and event-based applications. In both cases, Delta Change Factors (DCFs are calculated which represent the expected future change of some key precipitation statistics. In the continuous case, short-term precipitation from climate projections are analysed in order to estimate DCFs associated with different percentiles in the frequency distribution of non-zero intensities. The DCFs may then be applied to an observed time series, producing a realisation of a future time series. The event-based case involves downscaling of Intensity-Duration-Frequency (IDF curves based on extreme value analysis of annual maxima using the Gumbel distribution. The resulting DCFs are expressed as a function of duration and frequency (i.e., return period and may be used to estimate future design storms. The applications are demonstrated in case studies focusing on the expected changes in short-term precipitation statistics until 2100 in the cities of Linz (Austria and Wuppertal (Germany. The downscaling framework is implemented in the climate service developed within the EU-project SUDPLAN.

  7. Drought mitigation in perennial crops by fertilization and adjustments of regional yield models for future climate variability

    Science.gov (United States)

    Kantola, I. B.; Blanc-Betes, E.; Gomez-Casanovas, N.; Masters, M. D.; Bernacchi, C.; DeLucia, E. H.

    2017-12-01

    Increased variability and intensity of precipitation in the Midwest agricultural belt due to climate change is a major concern. The success of perennial bioenergy crops in replacing maize for bioethanol production is dependent on sustained yields that exceed maize, and the marketing of perennial crops often emphasizes the resilience of perennial agriculture to climate stressors. Land conversion from maize for bioethanol to Miscanthus x giganteus (miscanthus) increases yields and annual evapotranspiration rates (ET). However, establishment of miscanthus also increases biome water use efficiency (the ratio between net ecosystem productivity after harvest and ET), due to greater belowground biomass in miscanthus than in maize or soybean. In 2012, a widespread drought reduced the yield of 5-year-old miscanthus plots in central Illinois by 36% compared to the previous two years. Eddy covariance data indicated continued soil water deficit during the hydrologically-normal growing season in 2013 and miscanthus yield failed to rebound as expected, lagging behind pre-drought yields by an average of 53% over the next three years. In early 2014, nitrogen fertilizer was applied to half of mature (7-year-old) miscanthus plots in an effort to improve yields. In plots with annual post-emergence application of 60 kg ha-1 of urea, peak biomass was 29% greater than unfertilized miscanthus in 2014, and 113% greater in 2015, achieving statistically similar yields to the pre-drought average. Regional-scale models of perennial crop productivity use 30-year climate averages that are inadequate for predicting long-term effects of short-term extremes on perennial crops. Modeled predictions of perennial crop productivity incorporating repeated extreme weather events, observed crop response, and the use of management practices to mitigate water deficit demonstrate divergent effects on predicted yields.

  8. Spatiotemporal Variability and Covariability of Temperature, Precipitation, Soil Moisture, and Vegetation in North America for Regional Climate Model Applications

    Science.gov (United States)

    Castro, C. L.; Beltran-Przekurat, A. B.; Pielke, R. A.

    2007-05-01

    Previous work has established that the dominant modes of Pacific SSTs influence the summer climate of North America through large-scale forcing, and this effect is most pronounced during the early part of the season. It is hypothesized, then, that land surface influences become more dominant in the latter part of the season as remote teleconnection influences diminish. As a first step toward investigation of this hypothesis in a regional climate model (RCM) framework, the statistically signficant spatiotemporal patterns of variability and covariability in North American precipitation (specified by the standardized precipitation index, or SPI), soil moisture, and vegetation are determined for timescales from a month to six months. To specify these respective data we use: CPC gauge- derived precipitation (1950-2000), Variable Infiltration Capacity (VIC) Model and NOAH Model NLDAS soil moisture and temperature, and the Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS-NDVI). The principal statistical tool used is multiple taper frequency singular value decomposition (MTM-SVD), and this is supplemented by wavelet analysis for specific areas of interest. The significant interannual variability in all of these data occur at a timescale of about 7 to 9 years and appears to be the integrated effect of remote SST forcing from the Pacific. Considering the entire year, the spatial pattern for precipitation resembles the typical ENSO winter signature. If the summer season is considered seperately, the out of phase relationship between precipitation anomalies in the central U.S. and core monsoon region is apparent. The largest soil moisture anomalies occur in the central U.S., since precipitation in this region has a consistent relationship to Pacific SSTs for the entire year. This helps to explain the approximately 20 year periodicity in drought conditions there. Unlike soil moisture, the largest anomalies in vegetation occur in the

  9. Recent greenland accumulation estimated from regional climate model simulations and ice core analysis

    DEFF Research Database (Denmark)

    Dethloff, K.; Schwager, M.; Christensen, J. H.

    2002-01-01

    to precipitation. Maxima of precipitation and accumulation occur at the southwestern and southeastern coasts of Greenland and are connected with cyclonic activity and the main storm tracks around Greenland. The central region of the Greenland ice sheet acts as a blocking barrier on moving weather systems...... and prohibits cyclones moving from west to east across this region and, thus prevents moisture transports....

  10. Reconstruction of regional climate and climate change in past decades

    Science.gov (United States)

    von Storch, H.; Feser, F.; Weisse, R.; Zahn, M.

    2009-12-01

    Regional climate models, which are constrained by large scale information (spectral nudging) provided by re-analyses, allow for the construction of a mostly homogeneous description of regional weather statistics since about 1950. The potential of this approach has been demonstrated for Northern Europe. That data set, named CoastDat, does not only contain hourly data on atmospheric variables, in particular wind, but also on marine weather, i.e., short term water level, current and sea state variations. Another example is the multi-decadal variability of Polar Lows in the subarctic waters. The utility of such data sets is broad, from risk assessments related to coastal wind and wave conditions, assessment of determining the causes for regional climate change, a-posteriori analysis of the efficiency of environmental legislation (example: lead). In the paper, the methodology is outlined, examples are provided and the utility of the product discussed.

  11. Regional Climate Simulations of the Hydrological Cycle in the Iberian Peninsula with a Coupled WRF-HYDRO Model

    Science.gov (United States)

    Rios-Entenza, A.; Miguez-Macho, G.

    2008-12-01

    Land-atmosphere water exchanges and heat fluxes play an important role in climate and particularly in controlling precipitation in water-limited regions. One of such regions is the Iberian Peninsula, and in this study we examine the relevance of water recycling in convective precipitation regimes of the Fall and Spring there, when rainfall is critical for agriculture and many other human activities. We conducted simulations with WRF-ARW model at 5 km horizontal resolution, using a 1500 km x 1500 km nested grid that covers the Iberian Peninsula, with a parent domain that uses spectral nudging in order to avoid the distortion of the large-scale circulation caused by the interaction of the modeled flow with the lateral boundaries of the nested grid. For land-surface interactions we coupled WRF with the LEAF-HYDRO land surface model, which includes water table dynamics. We use therefore a tool that simulates the entire water cycle, including the water table, which has been reported to be critical for soil moisture dynamics in semi-arid regions like the Iberian Peninsula. For each one of the events that we selected, we performed two simulations: a control one, where all land-atmosphere feedbacks are taken into account, and the experiment, where infiltration of the precipitated water into the soil was suppressed. In this manner we explore the role of upward latent and sensible heat fluxes and evapotranspiration in precipitation dynamics. Preliminary results suggest that water recycling is a key factor in extending convective precipitation during several days, and that the total new water added in the area as a whole is only a fraction of the total measured rainfall. An estimation of this fraction is very important to better understanding the water budget and for hydrological planning in this water-stressed region.

  12. SUNYA Regional Climate Model Simulations of East Asia Summer Monsoon: Effects of Cloud Vertical Structure on the Surface Energy Balance

    Directory of Open Access Journals (Sweden)

    Wei Gong and Wei-Chyung Wang

    2007-01-01

    Full Text Available We used the State University of New York at Albany (SUNYA regional climate model to study the effect of cloud vertical distribution in affecting the surface energy balance of the East Asia summer monsoon (EASM. Simulations were conducted for the summers of 1988 and 1989, during which large contrast in the intra-seasonal cloud radiative forcing (CRF was observed at the top of the atmosphere. The model results indicate that both the high and low clouds are persistent throughout the summer months in both years. Because of large cloud water, low clouds significantly reduce the solar radiation flux reaching the surface, which nevertheless still dominate the surface energy balance, accounting for more than 50% of the surface heating. The low clouds also contribute significantly the downward longwave radiation to the surface with values strongly dependent on the cloud base temperature. The presence of low clouds effectively decreases the temperature and moisture gradients near surface, resulting in a substantial decrease in the sensible and latent heat fluxes from surface, which partially compensate the decrease of the net radiative cooling of the surface. For example, in the two days, May 8 and July 11 of 1988, the total cloud cover of 80% is simulated, but the respective low cloud cover (water was 63% (114 gm-2 and 22% (21 gm-2. As a result, the downward solar radiation is smaller by 161 Wm-2 in May 8. On the other hand, the cloud temperature was _ lower, yielding 56 Wm-2 smaller downward longwave radiation. The near surface temperature and gradient is more than _ smaller (and moisture gradient, leading to 21 and 81 Wm-2 smaller sensible heat and latent heat fluxes. It is also demonstrated that the model is capable to reproduce the intraseasonal variation of shortwave CRF, and catches the relationship between total cloud cover and SW CRF. The model results show the dominance of high cloud on the regional mean longwave CRF and low cloud on the intra

  13. Future climate and surface mass balance of Svalbard glaciers in an RCP8.5 climate scenario: a study with the regional climate model MAR forced by MIROC5

    Science.gov (United States)

    Lang, C.; Fettweis, X.; Erpicum, M.

    2015-05-01

    We have performed a future projection of the climate and surface mass balance (SMB) of Svalbard with the MAR (Modèle Atmosphérique Régional) regional climate model forced by MIROC5 (Model for Interdisciplinary Research on Climate), following the RCP8.5 scenario at a spatial resolution of 10 km. MAR predicts a similar evolution of increasing surface melt everywhere in Svalbard followed by a sudden acceleration of melt around 2050, with a larger melt increase in the south compared to the north of the archipelago. This melt acceleration around 2050 is mainly driven by the albedo-melt feedback associated with the expansion of the ablation/bare ice zone. This effect is dampened in part as the solar radiation itself is projected to decrease due to a cloudiness increase. The near-surface temperature is projected to increase more in winter than in summer as the temperature is already close to 0 °C in summer. The model also projects a stronger winter west-to-east temperature gradient, related to the large decrease of sea ice cover around Svalbard. By 2085, SMB is projected to become negative over all of Svalbard's glaciated regions, leading to the rapid degradation of the firn layer.

  14. Impact of absorbing aerosols on the simulation of climate over the Indian region in an atmospheric general circulation model

    Directory of Open Access Journals (Sweden)

    A. Chakraborty

    2004-04-01

    Full Text Available The impact of anthropogenic absorbing aerosols (such as soot on the climate over the Indian region has been studied using the NCMRWF general circulation model. The absorbing aerosols increase shortwave radiative heating of the lower troposphere and reduce the heating at the surface. These effects have been incorporated as heating of the lower troposphere (up to 700hPa and cooling over the continental surface based on INDOEX measurements. The heating effect is constant in the pre-monsoon season and reduces to zero during the monsoon season. It is shown that even in the monsoon season when the aerosol forcing is zero, there is an overall increase in rainfall and a reduction in surface temperature over the Indian region. The rainfall averaged over the Tropics shows a small reduction in most of the months during the January to September period. The impact of aerosol forcing, the model's sensitivity to this forcing and its interaction with model-physics has been studied by changing the cumulus parameterization from the Simplified Arakawa-Schubert (SAS scheme to the Kuo scheme. During the pre-monsoon season the major changes in precipitation occur in the oceanic Inter Tropical Convergence Zone (ITCZ, where both the schemes show an increase in precipitation. This result is similar to that reported in Chung2002. On the other hand, during the monsoon season the changes in precipitation in the continental region are different in the SAS and Kuo schemes. It is shown that the heating due to absorbing aerosols changes the vertical moist-static stability of the atmosphere. The difference in the precipitation changes in the two cumulus schemes is on account of the different responses in the two parameterization schemes to changes in vertical stability. Key words. Atmospheric composition and structure (aerosols and particles – Meteorology and atmospheric dynamics (tropical meteorology; precipitation

  15. Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

    Energy Technology Data Exchange (ETDEWEB)

    Robertson, William [Univ. of Texas, El Paso, TX (United States)

    2016-11-18

    RASM is a multi-disciplinary project, which brings together researchers from six state universities, one military postgraduate school, and one DoE laboratory to address the core modeling objectives of the arctic research community articulated in the Arctic System Modeling report by Roberts et al. (2010b). This report advocates the construction of a regional downscaling tool to generate probabilistic decadal projections of Greenland ice sheet retreat, evolution of arctic sea ice cover, changes in land surface vegetation, and regional processes leading to arctic amplification. Unified coupled models such as RASM are ideal for this purpose because they simulate fine-scale physics, essential for the realistic representation of intra-annual variability, in addition to processes fundamental to long term climatic shifts (Hurrell et al. 2009). By using RASM with boundary conditions from a global model, we can generate many-member ensembles essential for understanding uncertainty in regional climate projections (Hawkins and Sutton 2009). This probabilistic approach is computationally prohibitive for high-resolution global models in the foreseeable future, and also for regional models interactively nested within global simulations. Yet it is fundamental for quantifying uncertainty in decadal forecasts to make them useful for decision makers (Doherty et al. 2009). For this reason, we have targeted development of ensemble generation techniques as a core project task (Task 4.5). Environmental impact assessment specialists need high-fidelity regional ensemble projections to improve the accuracy of their work (Challinor et al. 2009; Moss et al. 2010). This is especially true of the Arctic, where economic, social and national interests are rapidly reshaping the high north in step with regional climate change. During the next decade, considerable oil and gas discoveries are expected across many parts of the marine and terrestrial Arctic (Gautier et al. 2009), the economics of the

  16. An evaluation of Arctic cloud and radiation processes during the SHEBA year: simulation results from eight Arctic regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Wyser, K.; Willen, U. [Rossby Centre, SMHI, Norrkoeping (Sweden); Jones, C.G.; Du, P.; Girard, E.; Laprise, R. [Universite du Quebec a Montreal, Canadian Regional Climate Modelling and Diagnostics Network, Montreal (Canada); Cassano, J.; Serreze, M.; Shaw, M.J. [University of Colorado, Cooperative Institute for Research in Environmental Sciences and Department of Atmospheric and Oceanic Sciences, Boulder, CO (United States); Christensen, J.H. [Danish Meteorological Institute, Copenhagen (Denmark); Curry, J.A. [School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA (United States); Dethloff, K.; Rinke, A. [Alfred Wegener Institute for Polar and Marine Research, Research Unit, Potsdam (Germany); Haugen, J.-E.; Koeltzow, M. [Norwegian Meteorological Institute, Oslo (Norway); Jacob, D.; Pfeifer, S. [Max Planck Institute for Meteorology, Hamburg (Germany); Lynch, A. [Monash University, School of Geography and Environmental Science, Melbourne (Australia); Tjernstroem, M.; Zagar, M. [Stockholm University, Department of Meteorology, Stockholm (Sweden)

    2008-02-15

    Eight atmospheric regional climate models (RCMs) were run for the period September 1997 to October 1998 over the western Arctic Ocean. This period was coincident with the observational campaign of the Surface Heat Budget of the Arctic Ocean (SHEBA) project. The RCMs shared common domains, centred on the SHEBA observation camp, along with a common model horizontal resolution, but differed in their vertical structure and physical parameterizations. All RCMs used the same lateral and surface boundary conditions. Surface downwelling solar and terrestrial radiation, surface albedo, vertically integrated water vapour, liquid water path and cloud cover from each model are evaluated against the SHEBA observation data. Downwelling surface radiation, vertically integrated water vapour and liquid water path are reasonably well simulated at monthly and daily timescales in the model ensemble mean, but with considerable differences among individual models. Simulated surface albedos are relatively accurate in the winter season, but become increasingly inaccurate and variable in the melt season, thereby compromising the net surface radiation budget. Simulated cloud cover is more or less uncorrelated with observed values at the daily timescale. Even for monthly averages, many models do not reproduce the annual cycle correctly. The inter-model spread of simulated cloud-cover is very large, with no model appearing systematically superior. Analysis of the co-variability of terms controlling the surface radiation budget reveal some of the key processes requiring improved treatment in Arctic RCMs. Improvements in the parameterization of cloud amounts and surface albedo are most urgently needed to improve the overall performance of RCMs in the Arctic. (orig.)

  17. Regionální klimatický model ALARO-CLIMATE, validace experimentu s rozlišením 25 km

    Czech Academy of Sciences Publication Activity Database

    Pokorná, Lucie; Kliegrová, S.; Brožková, R.; Štěpánek, Petr; Skalák, Petr; Belda, M.; Farda, Aleš; Metelka, L.; Huth, Radan

    2015-01-01

    Roč. 68, č. 2 (2015), s. 33-43 ISSN 0026-1173 R&D Projects: GA ČR(CZ) GAP209/11/2405 Institutional support: RVO:68378289 ; RVO:67179843 Keywords : ALARO-Climate * regional climate model * precipitation * temperature * validation Subject RIV: DG - Athmosphere Sciences, Meteorology http://www.chmi.cz/files/portal/docs/reditel/SIS/casmz/2015_2.pdf

  18. Representation of monsoon intraseasonal oscillations in regional climate model: sensitivity to convective physics

    KAUST Repository

    Umakanth, U.; Kesarkar, Amit P.; Attada, Raju; Vijaya Bhaskar Rao, S.

    2015-01-01

    combinations of Grell (G) and Emanuel (E) cumulus schemes namely, RegCM-EG, RegCM-EE and RegCM-GE have been used. The model is initialized at 1st January, 2000 for a 13-year continuous simulation at a spatial resolution of 50 km. The models reasonably simulate

  19. Antarctic 20th Century Accumulation Changes Based on Regional Climate Model Simulations

    Directory of Open Access Journals (Sweden)

    Klaus Dethloff

    2010-01-01

    investigated on the basis of ERA-40 data and HIRHAM simulations. It is shown that the regional accumulation changes are largely driven by changes in the transient activity around the Antarctic coasts due to the varying AAO phases. During positive AAO, more transient pressure systems travelling towards the continent, and Western Antarctica and parts of South-Eastern Antarctica gain more precipitation and mass. Over central Antarctica the prevailing anticyclone causes a strengthening of polar desertification connected with a reduced surface mass balance in the northern part of East Antarctica.

  20. The NOW regional coupled model: Application to the tropical Indian Ocean climate and tropical cyclone activity

    Digital Repository Service at National Institute of Oceanography (India)

    Samson, G.; Masson, S.; Lengaigne, M.; Keerthi, M.G.; Vialard, J.; Pous, S.; Madec, G.; Jourdain, N.C.; Jullien, S.; Menkes, C.; Marchesiello, P.

    with the Indian Ocean Dipole (IOD) and the delayed basin-wide warming/cooling induced by the El Nino Southern Oscillation (ENSO). The timing of IOD occurrence in the ~ model generally matches that of the observed events, confirming the influence of ENSO on the IOD...

  1. Climatic Effects of Regional Nuclear War

    Science.gov (United States)

    Oman, Luke D.

    2011-01-01

    We use a modern climate model and new estimates of smoke generated by fires in contemporary cities to calculate the response of the climate system to a regional nuclear war between emerging third world nuclear powers using 100 Hiroshima-size bombs (less than 0.03% of the explosive yield of the current global nuclear arsenal) on cities in the subtropics. We find significant cooling and reductions of precipitation lasting years, which would impact the global food supply. The climate changes are large and longlasting because the fuel loadings in modern cities are quite high and the subtropical solar insolation heats the resulting smoke cloud and lofts it into the high stratosphere, where removal mechanisms are slow. While the climate changes are less dramatic than found in previous "nuclear winter" simulations of a massive nuclear exchange between the superpowers, because less smoke is emitted, the changes seem to be more persistent because of improvements in representing aerosol processes and microphysical/dynamical interactions, including radiative heating effects, in newer global climate system models. The assumptions and calculations that go into these conclusions will be described.

  2. Climate Prediction Center - Monitoring and Data - Regional Climate Maps:

    Science.gov (United States)

    National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site government Web resources and services. HOME > Monitoring and Data > U.S. Climate Data > ; Precipitation & Temperature > Regional Climate Maps: USA Menu Weekly 1-Month 3-Month 12-Month Weekly

  3. Potential future changes in the characteristics of daily precipitation in Europe simulated by the HIRHAM regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    May, Wilhelm [Danish Meteorological Institute, Danish Climate Centre, Copenhagen (Denmark)

    2008-05-15

    In this study the potential future changes in various aspects of daily precipitation events over Europe as a consequence of the anticipated future increase in the atmospheric greenhouse gas concentrations are investigated. This is done by comparing two 3-member ensembles of simulations with the HIRHAM regional climate model for the period 1961-1990 and 2071-2100, respectively. Daily precipitation events are characterized by their frequency and intensity, and heavy precipitation events are described via 30-year return levels of daily precipitation. Further, extended periods with and without rainfall (wet and dry spells) are studied, considering their frequency and length as well as the average and extreme amounts of precipitation accumulated during wet spells, the latter again described via 30-year return levels. The simulations show marked changes in the characteristics of daily precipitation in Europe due to the anticipated greenhouse warming. In winter, for instance, the frequency of wet days is enhanced over most of the European continent except for the region on the Norwegian west coast and the Mediterranean region. The changes in the intensity and the 30-year return level of daily precipitation are characterized by a similar pattern except for central Europe with a tendency of decreased 30-year return levels and increased precipitation intensity. In summer, on the other hand, the frequency of wet days is decreased over most of Europe except for northern Scandinavia and the Baltic Sea region. In contrast, the precipitation intensity and the 30-year return level of daily precipitation are increased over entire Scandinavia, central and eastern Europe. The changes in the 30-year return level of daily precipitation are generally stronger than the corresponding changes in the precipitation intensity but can have opposite signs in some regions. Also the distribution of wet days is changed in the future. During summer, for instance, both the frequency and the length

  4. Climate change adaptation planning for the Skeena region of British Columbia, Canada: A combined biophysical modelling, social science, and community engagement approach

    Science.gov (United States)

    Melton, J. R.; Kaplan, J. O.; Matthews, R.; Sydneysmith, R.; Tesluk, J.; Piggot, G.; Robinson, D. C.; Brinkman, D.; Marmorek, D.; Cohen, S.; McPherson, K.

    2011-12-01

    The Skeena region of British Columbia, Canada is among the world's most important commercial forest production areas, a key transportation corridor, and provides critical habitat for salmon and other wildlife. Climate change compounds threats to the region from other local environmental and social challenges. To aid local communities in adaptive planning for future climate change impacts, our project combined biophysical modelling, social science, and community engagement in a participatory approach to build regional capacity to prepare and respond to climate change. The sociological aspect of our study interviewed local leaders and resource managers (both First Nations and settlers groups in three communities) to examine how perceptions of environmental and socioeconomic issues have changed in the recent past, and the values placed on diverse natural resources at the present. The three communities differed in their perception of the relative value and condition of community resources, such as small business, natural resource trade, education and local government. However, all three communities regarded salmon as their most important and threatened resource. The most important future drivers of change in the study region were perceived to be: "aboriginal rights, title and treaty settlements", "availability of natural resources", "natural resource policies", and the "global economy". Climate change, as a potential driver of change in the region, was perceived as less important than other socio-economic factors; even though climate records for the region already demonstrate warmer winters, decreased snowfall, and decreased spring precipitation over the last half century. The natural science component of our project applies a regional-scale dynamic vegetation model (LPJ-GUESS) to simulate the potential future of forest ecosystems, with a focus on how climate change and management strategy interact to influence forest productivity, disturbance frequency, species

  5. A regional climate model for the Arctic and the North Atlantic; Ein regionales Klimamodell fuer die Arktis und den Nordatlantik

    Energy Technology Data Exchange (ETDEWEB)

    Berndt, H

    2001-07-01

    The Arctic and the subpolar region of the North Atlantic with their complex net of mechanisms and feedbacks play an important role in the climate system. Because of the sparse observations and the low resolution of the global models the high-resolution regional climate model REMO provides an improved tool to investigate arctic processes. REMO is based on the former numerical weather prediction model EM of the German Weather Service (DWD) and was further developed at the Max-Planck-Institute for Meteorology (MPIfM) in Hamburg. It has two different parameterization schemes - the original one called DWD-physics and additionally the ECHAM4-physics from MPIfM. The dynamical scheme is in both cases identical. In a first step REMO is adapted to the new domain. This configuration covers the Arctic and the North Atlantic down to 40 N with a horizontal resolution of 0.5 x 0.5 and 121 x 145 grid points. Different periods are simulated with DWD- and ECHAM4-Physics in forecast - as well as in climate-mode. Lateral boundary conditions are taken from NCEP/NCAR-reanalysis. Comparing REMO with ship observations in the Labrador Sea yields a better correspondence than the reanalysis data. Simulated precipitation is overestimated most probably due to unrealistic high humidity in the NCEP/NCAR-reanalysis. Observed sensible heat fluxes are much lower than the REMO and NCEP/NCAR simulated fluxes. REMO simulations in climate- and forecast-mode with ECHAM4-parameterizations are compared with measured surface temperatures and precipitation distributions. While there are numerically generated spectral spikes in the NCEP/NCAR precipitation fields in the Arctic, they are not found in the REMO results. In a sensitivity study the impact of higher surface roughness in the marginal ice zone is investigated. Ensemble experiments show the high internal variability masking any signals due to the changed roughness length. This high internal variability is mostly due to the large model domain and the

  6. Variability of wet troposphere delays over inland reservoirs as simulated by a high-resolution regional climate model

    Science.gov (United States)

    Clark, E.; Lettenmaier, D. P.

    2014-12-01

    Satellite radar altimetry is widely used for measuring global sea level variations and, increasingly, water height variations of inland water bodies. Existing satellite radar altimeters measure water surfaces directly below the spacecraft (approximately at nadir). Over the ocean, most of these satellites use radiometry to measure the delay of radar signals caused by water vapor in the atmosphere (also known as the wet troposphere delay (WTD)). However, radiometry can only be used to estimate this delay over the largest inland water bodies, such as the Great Lakes, due to spatial resolution issues. As a result, atmospheric models are typically used to simulate and correct for the WTD at the time of observations. The resolutions of these models are quite coarse, at best about 5000 km2 at 30˚N. The upcoming NASA- and CNES-led Surface Water and Ocean Topography (SWOT) mission, on the other hand, will use interferometric synthetic aperture radar (InSAR) techniques to measure a 120-km-wide swath of the Earth's surface. SWOT is expected to make useful measurements of water surface elevation and extent (and storage change) for inland water bodies at spatial scales as small as 250 m, which is much smaller than current altimetry targets and several orders of magnitude smaller than the models used for wet troposphere corrections. Here, we calculate WTD from very high-resolution (4/3-km to 4-km) simulations of the Weather Research and Forecasting (WRF) regional climate model, and use the results to evaluate spatial variations in WTD. We focus on six U.S. reservoirs: Lake Elwell (MT), Lake Pend Oreille (ID), Upper Klamath Lake (OR), Elephant Butte (NM), Ray Hubbard (TX), and Sam Rayburn (TX). The reservoirs vary in climate, shape, use, and size. Because evaporation from open water impacts local water vapor content, we compare time series of WTD over land and water in the vicinity of each reservoir. To account for resolution effects, we examine the difference in WRF

  7. An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

    Science.gov (United States)

    Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

    2013-12-01

    This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen

  8. Ecosystem feedbacks to climate change in California: Development, testing, and analysis using a coupled regional atmosphere and land-surface model (WRF3-CLM3.5)

    Energy Technology Data Exchange (ETDEWEB)

    Subin, Z.M.; Riley, W.J.; Kueppers, L.M.; Jin, J.; Christianson, D.S.; Torn, M.S.

    2010-11-01

    A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California's climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California's climate was assessed by comparing simulations by WRF3-CLM3.5 and WRF3-Noah to observations from 1982 to 1991. Using WRF3-CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1). The land-cover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario. Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of -0.7 to +1 C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.2-1.2 C reductions in summer daily-mean 2-m air temperature and 2.0-3.7 C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those

  9. A fully coupled Mediterranean regional climate system model: design and evaluation of the ocean component for the 1980–2012 period

    Directory of Open Access Journals (Sweden)

    Florence Sevault

    2014-11-01

    Full Text Available A fully coupled regional climate system model (CNRM-RCSM4 dedicated to the Mediterranean region is described and evaluated using a multidecadal hindcast simulation (1980–2012 driven by global atmosphere and ocean reanalysis. CNRM-RCSM4 includes the regional representation of the atmosphere (ALADIN-Climate model, land surface (ISBA model, rivers (TRIP model and the ocean (NEMOMED8 model, with a daily coupling by the OASIS coupler. This model aims to reproduce the regional climate system with as few constraints as possible: there is no surface salinity, temperature relaxation, or flux correction; the Black Sea budget is parameterised and river runoffs (except for the Nile are fully coupled. The atmospheric component of CNRM-RCSM4 is evaluated in a companion paper; here, we focus on the air–sea fluxes, river discharges, surface ocean characteristics, deep water formation phenomena and the Mediterranean thermohaline circulation. Long-term stability, mean seasonal cycle, interannual variability and decadal trends are evaluated using basin-scale climatologies and in-situ measurements when available. We demonstrate that the simulation shows overall good behaviour in agreement with state-of-the-art Mediterranean RCSMs. An overestimation of the shortwave radiation and latent heat loss as well as a cold Sea Surface Temperature (SST bias and a slight trend in the bottom layers are the primary current deficiencies. Further, CNRM-RCSM4 shows high skill in reproducing the interannual to decadal variability for air–sea fluxes, river runoffs, sea surface temperature and salinity as well as open-sea deep convection, including a realistic simulation of the Eastern Mediterranean Transient. We conclude that CNRM-RCSM4 is a mature modelling tool allowing the climate variability of the Mediterranean regional climate system to be studied and understood. It is used in hindcast and scenario modes in the HyMeX and Med-CORDEX programs.

  10. Assessing the Climate Change Impact on Snow-Glacier Melting Dominated Basins in the Greater Himalaya Region Using a Distributed Glacio-Hydrologic Model

    Science.gov (United States)

    Wi, S.; Yang, Y. C. E.; Khalil, A.

    2014-12-01

    Glacier and snow melting is main source of water supply making a large contribution to streamflow of major river basins in the Greater Himalaya region including the Syr Darya, the Amu Darya, the Indus, the Ganges and the Brahmaputra basins. Due to the critical role of glacier and snow melting as water supply for both food production and hydropower generation in the region (especially during the low flow season), it is important to evaluate the vulnerability of snow and glacier melting streamflow to different climate conditions. In this study, a distributed glacio-hydrologic model with high resolution climate input is developed and calibrated that explicitly simulates all major hydrological processes and the glacier and snow dynamics for area further discretized by elevation bands. The distributed modeling structure and the glacier and snow modules provide a better understanding about how temperature and precipitation alterations are likely to affect current glacier ice reserves. Climate stress test is used to explore changes in the total streamflow change, snow/glacier melting contribution and glacier accumulation and ablation under a variety of different temperature and precipitation conditions. The latest future climate projections provided from the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) is used to inform the possibility of different climate conditions.

  11. Evaluation of surface air temperature and urban effects in Japan simulated by non-hydrostatic regional climate model

    Science.gov (United States)

    Murata, A.; Sasaki, H.; Hanafusa, M.; Kurihara, K.

    2012-12-01

    We evaluated the performance of a well-developed nonhydrostatic regional climate model (NHRCM) with a spatial resolution of 5 km with respect to temperature in the present-day climate of Japan, and estimated urban heat island (UHI) intensity by comparing the model results and observations. The magnitudes of root mean square error (RMSE) and systematic error (bias) for the annual average of daily mean (Ta), maximum (Tx), and minimum (Tn) temperatures are within 1.5 K, demonstrating that the temperatures of the present-day climate are reproduced well by NHRCM. These small errors indicate that temperature variability produced by local-scale phenomena is represented well by the model with a higher spatial resolution. It is also found that the magnitudes of RMSE and bias in the annually-average Tx are relatively large compared with those in Ta and Tn. The horizontal distributions of the error, defined as the difference between simulated and observed temperatures (simulated minus observed), illustrate negative errors in the annually-averaged Tn in three major metropolitan areas: Tokyo, Osaka, and Nagoya. These negative errors in urban areas affect the cold bias in the annually-averaged Tx. The relation between the underestimation of temperature and degree of urbanization is therefore examined quantitatively using National Land Numerical Information provided by the Ministry of Land, Infrastructure, Transport, and Tourism. The annually-averaged Ta, Tx, and Tn are all underestimated in the areas where the degree of urbanization is relatively high. The underestimations in these areas are attributed to the treatment of urban areas in NHRCM, where the effects of urbanization, such as waste heat and artificial structures, are not included. In contrast, in rural areas, the simulated Tx is underestimated and Tn is overestimated although the errors in Ta are small. This indicates that the simulated diurnal temperature range is underestimated. The reason for the relatively large

  12. Sensitivity of global and regional terrestrial carbon storage to the direct CO2 effect and climate change based on the CMIP5 model intercomparison.

    Science.gov (United States)

    Peng, Jing; Dan, Li; Huang, Mei

    2014-01-01

    Global and regional land carbon storage has been significantly affected by increasing atmospheric CO2 concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we investigate sensitivities of land carbon storage to rising atmospheric CO2 concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO2 concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04 PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO) and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet). The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics.

  13. Sensitivity of global and regional terrestrial carbon storage to the direct CO2 effect and climate change based on the CMIP5 model intercomparison.

    Directory of Open Access Journals (Sweden)

    Jing Peng

    Full Text Available Global and regional land carbon storage has been significantly affected by increasing atmospheric CO2 concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5, we investigate sensitivities of land carbon storage to rising atmospheric CO2 concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO2 concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04 PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet. The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics.

  14. The increased atmospheric greenhouse effect and regional climate change

    Energy Technology Data Exchange (ETDEWEB)

    Groenaas, S. [Bergen Univ. (Norway)

    1996-03-01

    This paper was read at the workshop ``The Norwegian Climate and Ozone Research Programme`` held on 11-12 March 1996. The main information for predicting future climate changes comes from integrating coupled climate models of the atmosphere, ocean and cryosphere. Regional climate change may be studied from the global integrations, however, resolution is coarse because of insufficient computer power. Attempts are being made to get more regional details out of the global integrations by ``downscaling`` the latter. This can be done in two ways. Firstly, limited area models with high resolution are applied, driven by the global results as boundary values. Secondly, statistical relationships have been found between observed meteorological parameters, like temperature and precipitation, and analyzed large scale gridded fields. The derived relations are then used on similar data from climate runs to give local interpretations. A review is given of literature on recent observations of climate variations and on predicted regional climate change. 18 refs., 4 figs.

  15. Modelling the regional climate and isotopic composition of Svalbard precipitation using REMOiso: a comparison with available GNIP and ice core data

    NARCIS (Netherlands)

    Divine, D.V.; Sjolte, J.; Isaksson, E.; Meijer, H.A.J.; van de Wal, R.S.W.; Martma, T.; Pohjola, V.; Sturm, C.; Godtliebsen, F.

    2011-01-01

    Simulations of a regional (approx. 50 km resolution) circulation model REMOiso with embedded stable water isotope module covering the period 1958-2001 are compared with the two instrumental climate and four isotope series (δ18O) from western Svalbard. We examine the data from ice cores drilled on

  16. Modelling the regional climate and isotopic composition of Svalbard precipitation using REMOiso : a comparison with available GNIP and ice core data

    NARCIS (Netherlands)

    Divine, D. V.; Sjolte, J.; Isaksson, E.; Meijer, H. A. J.; van de Wal, R. S. W.; Martma, T.; Pohjola, V.; Sturm, C.; Godtliebsen, F.

    2011-01-01

    Simulations of a regional (approx. 50 km resolution) circulation model REMOiso with embedded stable water isotope module covering the period 1958-2001 are compared with the two instrumental climate and four isotope series (d18O) from western Svalbard. We examine the data from ice cores drilled on

  17. Recent changes in energy and freshwater budgets for the Godthåbsfjord catchment simulated in a 5 km regional climate model

    DEFF Research Database (Denmark)

    Langen, P. L.; Mottram, R.; Christensen, J. H.

    2014-01-01

    Freshwater input to the Godthåbsfjord (Southwest Greenland) is analyzed with special attention on the melt and runoff from the ice sheet. We use the high resolution (5.5 km) HIRHAM5 regional climate model covering all of Greenland, forced by the ERA-Interim reanalysis at the lateral boundaries ov...

  18. The impact of land-cover modification on the June meteorology of China since 1700, simulated using a regional climate model

    NARCIS (Netherlands)

    Wang, H.; Pitman, A.J.; Zhao, M.; Leemans, R.

    2003-01-01

    A series of simulations was conducted using a regional climate model with a domain covering mainland China. Simulations were conducted for a single June using estimated land cover for 1700, 1750, 1800, 1850, 1900, 1950, 1970 and 1990. The conversion of land cover between these periods was extensive

  19. Vegetation-climate feedback causes reduced precipitation and tropical rainforest cover in CMIP5 regional Earth system model simulation over Africa

    Science.gov (United States)

    Wu, M.; Smith, B.; Samuelsson, P.; Rummukainen, M.; Schurgers, G.

    2012-12-01

    We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feed back to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feed back to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical

  20. Atmospheric circulation in regional climate models over Central Europe: links to surface air temperature and the influence of driving data

    International Nuclear Information System (INIS)

    Plavcova, Eva; Kysely, Jan

    2012-01-01

    The study examines simulation of atmospheric circulation, represented by circulation indices (flow direction, strength and vorticity), and links between circulation and daily surface air temperatures in regional climate models (RCMs) over Central Europe. We explore control simulations of five high-resolution RCMs from the ENSEMBLES project driven by re-analysis (ERA-40) and the same global climate model (ECHAM5 GCM) plus of one RCM (RCA) driven by different GCMs. The aims are to (1) identify errors in RCM-simulated distributions of circulation indices in individual seasons, (2) identify errors in simulated temperatures under particular circulation indices, and (3) compare performance of individual RCMs with respect to the driving data. Although most of the RCMs qualitatively reflect observed distributions of the airflow indices, each produces distributions significantly different from the observations. General biases include overestimation of the frequency of strong flow days and of strong cyclonic vorticity. Some circulation biases obviously propagate from the driving data. ECHAM5 and all simulations driven by ECHAM5 underestimate frequency of easterly flow, mainly in summer. Except for HIRHAM, however, all RCMs driven by ECHAM5 improve on the driving GCM in simulating atmospheric circulation. The influence on circulation characteristics in the nested RCM differs between GCMs, as demonstrated in a set of RCA simulations with different driving data. The driving data control on circulation in RCA is particularly weak for the BCM GCM, in which case RCA substantially modifies (but does not improve) the circulation from the driving data in both winter and summer. Those RCMs with the most distorted atmospheric circulation are HIRHAM driven by ECHAM5 and RCA driven by BCM. Relatively strong relationships between circulation indices and surface air temperatures were found in the observed data for Central Europe. The links differ by season and are usually stronger for

  1. Atmospheric circulation in regional climate models over Central Europe: links to surface air temperature and the influence of driving data

    Energy Technology Data Exchange (ETDEWEB)

    Plavcova, Eva [Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague 4 (Czech Republic); Technical University, Department of Applied Mathematics, Liberec (Czech Republic); Charles University, Faculty of Mathematics and Physics, Prague (Czech Republic); Kysely, Jan [Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague 4 (Czech Republic); Technical University, Department of Applied Mathematics, Liberec (Czech Republic)

    2012-10-15

    The study examines simulation of atmospheric circulation, represented by circulation indices (flow direction, strength and vorticity), and links between circulation and daily surface air temperatures in regional climate models (RCMs) over Central Europe. We explore control simulations of five high-resolution RCMs from the ENSEMBLES project driven by re-analysis (ERA-40) and the same global climate model (ECHAM5 GCM) plus of one RCM (RCA) driven by different GCMs. The aims are to (1) identify errors in RCM-simulated distributions of circulation indices in individual seasons, (2) identify errors in simulated temperatures under particular circulation indices, and (3) compare performance of individual RCMs with respect to the driving data. Although most of the RCMs qualitatively reflect observed distributions of the airflow indices, each produces distributions significantly different from the observations. General biases include overestimation of the frequency of strong flow days and of strong cyclonic vorticity. Some circulation biases obviously propagate from the driving data. ECHAM5 and all simulations driven by ECHAM5 underestimate frequency of easterly flow, mainly in summer. Except for HIRHAM, however, all RCMs driven by ECHAM5 improve on the driving GCM in simulating atmospheric circulation. The influence on circulation characteristics in the nested RCM differs between GCMs, as demonstrated in a set of RCA simulations with different driving data. The driving data control on circulation in RCA is particularly weak for the BCM GCM, in which case RCA substantially modifies (but does not improve) the circulation from the driving data in both winter and summer. Those RCMs with the most distorted atmospheric circulation are HIRHAM driven by ECHAM5 and RCA driven by BCM. Relatively strong relationships between circulation indices and surface air temperatures were found in the observed data for Central Europe. The links differ by season and are usually stronger for

  2. The 1988-2003 Greenland ice sheet melt extent using passive microwave satellite data and a regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Fettweis, Xavier; Ypersele, Jean-Pascal van [Universite Catholique de Louvain, Institut d' Astronomie et de Geophysique de G. Lemaitre, Louvain-La-Neuve (Belgium); Gallee, Hubert [CNRS, Laboratoire de Glaciologie et Geophysique de l' Environnement, Grenoble (France); Lefebre, Filip [Vito-IMS (Flemish Institute for Technological Research-Integral Environmental Studies), Mol (Belgium)

    2006-10-15

    Measurements from ETH-Camp and JAR1 AWS (West Greenland) as well as coupled atmosphere-snow regional climate simulations have highlighted flaws in the cross-polarized gradient ratio (XPGR) technique used to identify melt from passive microwave satellite data. It was found that dense clouds (causing notably rainfall) on the ice sheet severely perturb the XPGR melt signal. Therefore, the original XPGR melt detection algorithm has been adapted to better incorporate atmospheric variability over the ice sheet and an updated melt trend for the 1988-2003 period has been calculated. Compared to the original algorithm, the melt zone area increase is eight times higher (from 0.2 to 1.7% year{sup -1}). The increase is higher with the improved XPGR technique because rainfall also increased during this period. It is correlated to higher atmospheric temperatures. Finally, the model shows that the total ice sheet runoff is directly proportional to the melt extent surface detected by satellites. These results are important for the understanding of the effect of Greenland melting on the stability of the thermohaline circulation. (orig.)

  3. A relationship between regional and global GCM surface air temperature changes and its application to an integrated model of climate change

    International Nuclear Information System (INIS)

    Jonas, M.; Ganopolski, A.V.; Krabec, J.; Olendrzyski, K.; Petoukhov, V.K.

    1994-01-01

    This study outlines the advantages of combining the Integrated Model to Assess the Greenhouse affect (IMAGE, an integrated quick turnaround, global model of climate change) with a spatially detailed General Circulation Model (GCM), in this case developed at the Max Planck Institute for Meteorology (MPI) in Hamburg. The outcome is a modified IMAGE model that simulates the MPI GCM projections of annual surface air temperature change globally and regionally. IMAGE thus provides policy analysts with integrated and regional information about global warming for a great range of policy-dependent greenhouse gas emission or concentration scenarios, while preserving its quick turnaround time. With the help of IMAGE various regional temperature response simulations have been produced. None of these simulations has yet been performed by any GCM. The simulations reflect the uncertainty range of a future warming. In this study the authors deal only with a simplified subsystem of such an integrated model of climate change, which begins with policy options, neglects the societal component in the greenhouse gas accounting tool, and ends with temperature change as the only output of the climate model. The model the authors employ is the Integrated Model to Assess the Greenhouse Effect (IMAGE, version 1.0), which was developed by the Netherlands National Institute of Public Health and Environmental Protection (RIVM). IMAGE is a scientifically based, parameterized simulation policy model designed to calculate the historical and future effects of greenhouse gases on global surface and surface air temperatures and sea-level rise

  4. Current and future carbon budget at Takayama site, Japan, evaluated by a regional climate model and a process-based terrestrial ecosystem model.

    Science.gov (United States)

    Kuribayashi, Masatoshi; Noh, Nam-Jin; Saitoh, Taku M; Ito, Akihiko; Wakazuki, Yasutaka; Muraoka, Hiroyuki

    2017-06-01

    Accurate projection of carbon budget in forest ecosystems under future climate and atmospheric carbon dioxide (CO 2 ) concentration is important to evaluate the function of terrestrial ecosystems, which serve as a major sink of atmospheric CO 2 . In this study, we examined the effects of spatial resolution of meteorological data on the accuracies of ecosystem model simulation for canopy phenology and carbon budget such as gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) of a deciduous forest in Japan. Then, we simulated the future (around 2085) changes in canopy phenology and carbon budget of the forest by incorporating high-resolution meteorological data downscaled by a regional climate model. The ecosystem model overestimated GPP and ER when we inputted low-resolution data, which have warming biases over mountainous landscape. But, it reproduced canopy phenology and carbon budget well, when we inputted high-resolution data. Under the future climate, earlier leaf expansion and delayed leaf fall by about 10 days compared with the present state was simulated, and also, GPP, ER and NEP were estimated to increase by 25.2%, 23.7% and 35.4%, respectively. Sensitivity analysis showed that the increase of NEP in June and October would be mainly caused by rising temperature, whereas that in July and August would be largely attributable to CO 2 fertilization. This study suggests that the downscaling of future climate data enable us to project more reliable carbon budget of forest ecosystem in mountainous landscape than the low-resolution simulation due to the better predictions of leaf expansion and shedding.

  5. On the development of a coupled regional climate-vegetation model RCM-CLM-CN-DV and its validation in Tropical Africa

    Science.gov (United States)

    Wang, Guiling; Yu, Miao; Pal, Jeremy S.; Mei, Rui; Bonan, Gordon B.; Levis, Samuel; Thornton, Peter E.

    2016-01-01

    This paper presents a regional climate system model RCM-CLM-CN-DV and its validation over Tropical Africa. The model development involves the initial coupling between the ICTP regional climate model RegCM4.3.4 (RCM) and the Community Land Model version 4 (CLM4) including models of carbon-nitrogen dynamics (CN) and vegetation dynamics (DV), and further improvements of the models. Model improvements derive from the new parameterization from CLM4.5 that addresses the well documented overestimation of gross primary production (GPP), a refinement of stress deciduous phenology scheme in CN that addresses a spurious LAI fluctuation for drought-deciduous plants, and the incorporation of a survival rule into the DV model to prevent tropical broadleaf evergreens trees from growing in areas with a prolonged drought season. The impact of the modifications on model results is documented based on numerical experiments using various subcomponents of the model. The performance of the coupled model is then validated against observational data based on three configurations with increasing capacity: RCM-CLM with prescribed leaf area index and fractional coverage of different plant functional types (PFTs); RCM-CLM-CN with prescribed PFTs coverage but prognostic plant phenology; RCM-CLM-CN-DV in which both the plant phenology and PFTs coverage are simulated by the model. Results from these three models are compared against the FLUXNET up-scaled GPP and ET data, LAI and PFT coverages from remote sensing data including MODIS and GIMMS, University of Delaware precipitation and temperature data, and surface radiation data from MVIRI and SRB. Our results indicate that the models perform well in reproducing the physical climate and surface radiative budgets in the domain of interest. However, PFTs coverage is significantly underestimated by the model over arid and semi-arid regions of Tropical Africa, caused by an underestimation of LAI in these regions by the CN model that gets exacerbated

  6. Analysis of Current and Future SPEI Droughts in the La Plata Basin Based on Results from the Regional Eta Climate Model

    Directory of Open Access Journals (Sweden)

    Alvaro Sordo-Ward

    2017-11-01

    Full Text Available We identified and analysed droughts in the La Plata Basin (divided into seven sub-basins for the current period (1961–2005 and estimated their expected evolution under future climate projections for the periods 2011–2040, 2041–2070, and 2071–2099. Future climate projections were analysed from results of the Eta Regional Climate Model (grid resolution of approximately 10 km forced by the global climate model HadGEM2-ES over the La Plata basin, and considering a RCP4.5 emission scenario. Within each sub-basin, we particularly focused our drought analyses on croplands and grasslands, due to their economic relevance. The three-month Standardized Precipitation Evapotranspiration Index (SPEI3 was used for drought identification and characterization. Droughts were evaluated in terms of time (percentage of time from the total length of each climate scenario, space (percentage of total area, and severity (SPEI3 values of cells characterized by cropland and grassland for each sub-basin and climate scenario. Drought-severity–area–frequency curves were developed to quantitatively relate the frequency distribution of drought occurrence to drought severity and area. For the period 2011–2040, droughts dominate the northern sub-basins, whereas alternating wet and short dry periods dominate the southern sub-basins. Wet climate spread from south to north within the La Plata Basin as more distant future scenarios were analysed, due to both a greater number of wet periods and fewer droughts. The area of each sub-basin affected by drought in all climate scenarios was highly varied temporally and spatially. The likelihood of the occurrence of droughts differed significantly between the studied cover types in the Lower Paraguay sub-basin, being higher for cropland than for grassland. Mainly in the Upper Paraguay and in the Upper Paraná basins the climate projections for all scenarios showed an increase of moderate and severe droughts over large regions

  7. Regional decadal predictions of coupled climate-human systems

    Science.gov (United States)

    Curchitser, E. N.; Lawrence, P.; Felder, F.; Large, W.; Bacmeister, J. T.; Andrews, C.; Kopp, R. E.

    2016-12-01

    We present results from a project to develop a framework for investigating the interactions between human activity and the climate system using state-of-the-art multi-scale, climate and economic models. The model is applied to the highly industrialized and urbanized coastal region of the northeast US with an emphasis on New Jersey. The framework is developed around the NCAR Community Earth System Model (CESM). The CESM model capabilities are augmented with enhanced resolution of the atmosphere (25 km), land surface (I km) and ocean models (7 km) in our region of interest. To the climate model, we couple human activity models for the utility sector and a 300-equation econometric model with sectorial details of an input-output model for the New Jersey economy. We will present results to date showing the potential impact of climate change on electricity markets on its consequences on economic activity in the region.

  8. Regional climate services: A regional partnership between NOAA and USDA

    Science.gov (United States)

    Climate services in the Midwest and Northern Plains regions have been enhanced by a recent addition of the USDA Climate Hubs to NOAA’s existing network of partners. This new partnership stems from the intrinsic variability of intra and inter-annual climatic conditions, which makes decision-making fo...

  9. Forecasting carbon budget under climate change and CO2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

    Science.gov (United States)

    Zhu, Q.; Jiang, H.; Liu, J.; Peng, C.; Fang, X.; Yu, S.; Zhou, G.; Wei, X.; Ju, W.

    2011-01-01

    The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr-1 during the last half of the 21st century. An NPP increase of about 24 Mt C by the end of the 21st century was estimated with the combined effects of increasing CO2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr-1. NEP will increase to about 5 Mt C yr-1 by the end of the 21st century with the increasing atmospheric CO2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO2 concentration will have little

  10. Web-based Data Visualization of the MGClimDeX Climate Model Output: An Integrated Perspective of Climate Change Impact on Natural Resources in Highly Vulnerable Regions.

    Science.gov (United States)

    Martinez-Rey, J.; Brockmann, P.; Cadule, P.; Nangini, C.

    2016-12-01

    Earth System Models allow us to understand the interactions between climate and biogeological processes. These models generate a very large amount of data. These data are usually reduced to a few number of static figures shown in highly specialized scientific publications. However, the potential impacts of climate change demand a broader perspective regarding the ways in which climate model results of this kind are disseminated, particularly in the amount and variety of data, and the target audience. This issue is of great importance particularly for scientific projects that seek a large broadcast with different audiences on their key results. The MGClimDeX project, which assesses the climate change impact on La Martinique island in the Lesser Antilles, will provide tools and means to help the key stakeholders -responsible for addressing the critical social, economic, and environmental issues- to take the appropriate adaptation and mitigation measures in order to prevent future risks associated with climate variability and change, and its role on human activities. The MGClimDeX project will do so by using model output and data visualization techniques within the next year, showing the cross-connected impacts of climate change on various sectors (agriculture, forestry, ecosystems, water resources and fisheries). To address this challenge of representing large sets of data from model output, we use back-end data processing and front-end web-based visualization techniques, going from the conventional netCDF model output stored on hub servers to highly interactive web-based data-powered visualizations on browsers. We use the well-known javascript library D3.js extended with DC.js -a dimensional charting library for all the front-end interactive filtering-, in combination with Bokeh, a Python library to synthesize the data, all framed in the essential HTML+CSS scripts. The resulting websites exist as standalone information units or embedded into journals or scientific

  11. Analysis of high-resolution simulations for the Black Forest region from a point of view of tourism climatology - a comparison between two regional climate models (REMO and CLM)

    Science.gov (United States)

    Endler, Christina; Matzarakis, Andreas

    2011-03-01

    An analysis of climate simulations from a point of view of tourism climatology based on two regional climate models, namely REMO and CLM, was performed for a regional domain in the southwest of Germany, the Black Forest region, for two time frames, 1971-2000 that represents the twentieth century climate and 2021-2050 that represents the future climate. In that context, the Intergovernmental Panel on Climate Change (IPCC) scenarios A1B and B1 are used. The analysis focuses on human-biometeorological and applied climatologic issues, especially for tourism purposes - that means parameters belonging to thermal (physiologically equivalent temperature, PET), physical (precipitation, snow, wind), and aesthetic (fog, cloud cover) facets of climate in tourism. In general, both models reveal similar trends, but differ in their extent. The trend of thermal comfort is contradicting: it tends to decrease in REMO, while it shows a slight increase in CLM. Moreover, REMO reveals a wider range of future climate trends than CLM, especially for sunshine, dry days, and heat stress. Both models are driven by the same global coupled atmosphere-ocean model ECHAM5/MPI-OM. Because both models are not able to resolve meso- and micro-scale processes such as cloud microphysics, differences between model results and discrepancies in the development of even those parameters (e.g., cloud formation and cover) are due to different model parameterization and formulation. Climatic changes expected by 2050 are small compared to 2100, but may have major impacts on tourism as for example, snow cover and its duration are highly vulnerable to a warmer climate directly affecting tourism in winter. Beyond indirect impacts are of high relevance as they influence tourism as well. Thus, changes in climate, natural environment, demography, tourists' demands, among other things affect economy in general. The analysis of the CLM results and its comparison with the REMO results complete the analysis performed

  12. Paleoclimate validation of a numerical climate model

    International Nuclear Information System (INIS)

    Schelling, F.J.; Church, H.W.; Zak, B.D.; Thompson, S.L.

    1994-01-01

    An analysis planned to validate regional climate model results for a past climate state at Yucca Mountain, Nevada, against paleoclimate evidence for the period is described. This analysis, which will use the GENESIS model of global climate nested with the RegCM2 regional climate model, is part of a larger study for DOE's Yucca Mountain Site Characterization Project that is evaluating the impacts of long term future climate change on performance of the potential high level nuclear waste repository at Yucca Mountain. The planned analysis and anticipated results are presented

  13. Quality assessment of atmospheric surface fields over the Baltic Sea from an ensemble of regional climate model simulations with respect to ocean dynamics

    Directory of Open Access Journals (Sweden)

    H. E. Markus Meier

    2011-05-01

    Full Text Available Climate model results for the Baltic Sea region from an ensemble of eight simulations using the Rossby Centre Atmosphere model version 3 (RCA3 driven with lateral boundary data from global climate models (GCMs are compared with results from a downscaled ERA40 simulation and gridded observations from 1980-2006. The results showed that data from RCA3 scenario simulations should not be used as forcing for Baltic Sea models in climate change impact studies because biases of the control climate significantly affect the simulated changes of future projections. For instance, biases of the sea ice cover in RCA3 in the present climate affect the sensitivity of the model's response to changing climate due to the ice-albedo feedback. From the large ensemble of available RCA3 scenario simulations two GCMs with good performance in downscaling experiments during the control period 1980-2006 were selected. In this study, only the quality of atmospheric surface fields over the Baltic Sea was chosen as a selection criterion. For the greenhouse gas emission scenario A1B two transient simulations for 1961-2100 driven by these two GCMs were performed using the regional, fully coupled atmosphere-ice-ocean model RCAO. It was shown that RCAO has the potential to improve the results in downscaling experiments driven by GCMs considerably, because sea surface temperatures and sea ice concentrations are calculated more realistically with RCAO than when RCA3 has been forced with surface boundary data from GCMs. For instance, the seasonal 2 m air temperature cycle is closer to observations in RCAO than in RCA3 downscaling simulations. However, the parameterizations of air-sea fluxes in RCAO need to be improved.

  14. Impact of improved Greenland ice sheet surface representation in the NASA GISS ModelE2 GCM on simulated surface mass balance and regional climate

    Science.gov (United States)

    Alexander, P. M.; LeGrande, A. N.; Fischer, E.; Tedesco, M.; Kelley, M.; Schmidt, G. A.; Fettweis, X.

    2017-12-01

    Towards achieving coupled simulations between the NASA Goddard Institute for Space Studies (GISS) ModelE2 general circulation model (GCM) and ice sheet models (ISMs), improvements have been made to the representation of the ice sheet surface in ModelE2. These include a sub-grid-scale elevation class scheme, a multi-layer snow model, a time-variable surface albedo scheme, and adjustments to parameterization of sublimation/evaporation. These changes improve the spatial resolution and physical representation of the ice sheet surface such that the surface is represented at a level of detail closer to that of Regional Climate Models (RCMs). We assess the impact of these changes on simulated Greenland Ice Sheet (GrIS) surface mass balance (SMB). We also compare ModelE2 simulations in which winds have been nudged to match the European Center for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis with simulations from the Modèle Atmosphérique Régionale (MAR) RCM forced by the same reanalysis. Adding surface elevation classes results in a much higher spatial resolution representation of the surface necessary for coupling with ISMs, but has a negligible impact on overall SMB. Implementing a variable surface albedo scheme increases melt by 100%, bringing it closer to melt simulated by MAR. Adjustments made to the representation of topography-influenced surface roughness length in ModelE2 reduce a positive bias in evaporation relative to MAR. We also examine the impact of changes to the GrIS surface on regional atmospheric and oceanic climate in coupled ocean-atmosphere simulations with ModelE2, finding a general warming of the Arctic due to a warmer GrIS, and a cooler North Atlantic in scenarios with doubled atmospheric CO2 relative to pre-industrial levels. The substantial influence of changes to the GrIS surface on the oceans and atmosphere highlight the importance of including these processes in the GCM, in view of potential feedbacks between the ice sheet

  15. Climate and chemistry effects of a regional scale nuclear conflict

    OpenAIRE

    Stenke A.; Hoyle C. R.; Luo B.; Rozanov E.; Groebner J.; Maag L.; Broennimann S.; Peter T.

    2013-01-01

    Previous studies have highlighted the severity of detrimental effects for life on Earth after an assumed regionally limited nuclear war. These effects are caused by climatic, chemical and radiative changes persisting for up to one decade. However, so far only a very limited number of climate model simulations have been performed, giving rise to the question how realistic previous computations have been. This study uses the coupled chemistry climate model (CCM) SOCOL, which belongs to a...

  16. Understanding and simulating the link between African easterly waves and Atlantic tropical cyclones using a regional climate model: the role of domain size and lateral boundary conditions

    Energy Technology Data Exchange (ETDEWEB)

    Caron, Louis-Philippe [MISU, Stockholm University, Stockholm (Sweden); Universite du Quebec a Montreal, CRCMD Network, Montreal, QC (Canada); Jones, Colin G. [Swedish Meterological and Hydrological Institute, Rossby Center, Norrkoeping (Sweden)

    2012-07-15

    Using a suite of lateral boundary conditions, we investigate the impact of domain size and boundary conditions on the Atlantic tropical cyclone and african easterly Wave activity simulated by a regional climate model. Irrespective of boundary conditions, simulations closest to observed climatology are obtained using a domain covering both the entire tropical Atlantic and northern African region. There is a clear degradation when the high-resolution model domain is diminished to cover only part of the African continent or only the tropical Atlantic. This is found to be the result of biases in the boundary data, which for the smaller domains, have a large impact on TC activity. In this series of simulations, the large-scale Atlantic atmospheric environment appears to be the primary control on simulated TC activity. Weaker wave activity is usually accompanied by a shift in cyclogenesis location, from the MDR to the subtropics. All ERA40-driven integrations manage to capture the observed interannual variability and to reproduce most of the upward trend in tropical cyclone activity observed during that period. When driven by low-resolution global climate model (GCM) integrations, the regional climate model captures interannual variability (albeit with lower correlation coefficients) only if tropical cyclones form in sufficient numbers in the main development region. However, all GCM-driven integrations fail to capture the upward trend in Atlantic tropical cyclone activity. In most integrations, variations in Atlantic tropical cyclone activity appear uncorrelated with variations in African easterly wave activity. (orig.)

  17. European Corn Borer life stage model: Regional estimates of pest development and spatial distribution under present and future climate

    Czech Academy of Sciences Publication Activity Database

    Trnka, M.; Muška, F.; Semerádová, Daniela; Dubrovský, Martin; Kocmánková, E.; Žalud, Z.

    2007-01-01

    Roč. 207, 2-4 (2007), s. 61-84 ISSN 0304-3800 R&D Projects: GA MZe QG60051; GA ČR(CZ) GA522/05/0125 Grant - others:6th FP EU(XE) GOCE 037005 Institutional research plan: CEZ:AV0Z30420517 Keywords : Corn borer * ECAMON * GCMs * Degree day model * Climate change impacts Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.077, year: 2007

  18. Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

    Science.gov (United States)

    Sanchez-Gomez, Emilia; Somot, S.; Déqué, M.

    2009-10-01

    One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.

  19. Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

    Energy Technology Data Exchange (ETDEWEB)

    Somot, S.; Deque, M. [Meteo-France CNRM/GMGEC CNRS/GAME, Toulouse (France); Sanchez-Gomez, Emilia

    2009-10-15

    One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation. (orig.)

  20. Modeling glacial climates

    Science.gov (United States)

    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. Assessment of gridded observations used for climate model validation in the Mediterranean region: the HyMeX and MED-CORDEX framework

    International Nuclear Information System (INIS)

    Flaounas, Emmanouil; Drobinski, Philippe; Borga, Marco; Calvet, Jean-Christophe; Delrieu, Guy; Morin, Efrat; Tartari, Gianni; Toffolon, Roberta

    2012-01-01

    This letter assesses the quality of temperature and rainfall daily retrievals of the European Climate Assessment and Dataset (ECA and D) with respect to measurements collected locally in various parts of the Euro-Mediterranean region in the framework of the Hydrological Cycle in the Mediterranean Experiment (HyMeX), endorsed by the Global Energy and Water Cycle Experiment (GEWEX) of the World Climate Research Program (WCRP). The ECA and D, among other gridded datasets, is very often used as a reference for model calibration and evaluation. This is for instance the case in the context of the WCRP Coordinated Regional Downscaling Experiment (CORDEX) and its Mediterranean declination MED-CORDEX. This letter quantifies ECA and D dataset uncertainties associated with temperature and precipitation intra-seasonal variability, seasonal distribution and extremes. Our motivation is to help the interpretation of the results when validating or calibrating downscaling models by the ECA and D dataset in the context of regional climate research in the Euro-Mediterranean region. (letter)

  2. Analysis of regional climate strategies in the Barents region

    Energy Technology Data Exchange (ETDEWEB)

    Himanen, S.; Inkeroeinen, J.; Latola, K.; Vaisanen, T.; Alasaarela, E.

    2012-11-15

    Climate change is a global phenomenon with especially harsh effects on the Arctic and northern regions. The Arctic's average temperature has risen at almost twice the rate as elsewhere in the past few decades. Since 1966, the Arctic land area covered by snow in early summer has shrunk by almost a fifth. The Barents Region consists of the northern parts of Norway, Sweden, Finland and Russia (i.e. the European part of Russia). Climate change will cause serious impacts in the Barents Region because of its higher density of population living under harsh climatic conditions, thus setting it apart from other Arctic areas. In many cases, economic activities, like tourism, rely on certain weather conditions. For this reason, climate change and adaptation to it is of special urgency for the region. Regional climate change strategies are important tools for addressing mitigation and adaptation to climate change as they can be used to consolidate the efforts of different stakeholders of the public and private sectors. Regional strategies can be important factors in achieving the national and international goals. The study evaluated how the national climate change goals were implemented in the regional and local strategies and programmes in northern Finland. The specific goal was to describe the processes by which the regional strategies were prepared and implemented, and how the work was expanded to include the whole of northern Finland. Finally, the Finnish preparatory processes were compared to case examples of processes for preparing climate change strategies elsewhere in the Barents Region. This analysis provides examples of good practices in preparing a climate change strategy and implementing it. (orig.)

  3. Climate Model Diagnostic Analyzer

    Science.gov (United States)

    Lee, Seungwon; Pan, Lei; Zhai, Chengxing; Tang, Benyang; Kubar, Terry; Zhang, Zia; Wang, Wei

    2015-01-01

    The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

  4. Great plains regional climate assessment technical report

    Science.gov (United States)

    The Great Plains region (GP) plays important role in providing food and energy to the economy of the United States. Multiple climatic and non-climatic stressors put multiple sectors, livelihoods and communities at risk, including agriculture, water, ecosystems and rural and tribal communities. The G...

  5. CLIMATE IMPACTS ON REGIONAL WATER

    Science.gov (United States)

    The New England region (including the 6 New Englandstates plus upstate New York) offers a very diverse geography,matched by an equally diverse economy and humanpopulation. Livelihoods throughout the region are basedon service industries that depend heavily on comm...

  6. Regional projection of climate impact indices over the Mediterranean region

    Science.gov (United States)

    Casanueva, Ana; Frías, M.; Dolores; Herrera, Sixto; Bedia, Joaquín; San Martín, Daniel; Gutiérrez, José Manuel; Zaninovic, Ksenija

    2014-05-01

    Climate Impact Indices (CIIs) are being increasingly used in different socioeconomic sectors to transfer information about climate change impacts and risks to stakeholders. CIIs are typically based on different weather variables such as temperature, wind speed, precipitation or humidity and comprise, in a single index, the relevant meteorological information for the particular impact sector (in this study wildfires and tourism). This dependence on several climate variables poses important limitations to the application of statistical downscaling techniques, since physical consistency among variables is required in most cases to obtain reliable local projections. The present study assesses the suitability of the "direct" downscaling approach, in which the downscaling method is directly applied to the CII. In particular, for illustrative purposes, we consider two popular indices used in the wildfire and tourism sectors, the Fire Weather Index (FWI) and the Physiological Equivalent Temperature (PET), respectively. As an example, two case studies are analysed over two representative Mediterranean regions of interest for the EU CLIM-RUN project: continental Spain for the FWI and Croatia for the PET. Results obtained with this "direct" downscaling approach are similar to those found from the application of the statistical downscaling to the individual meteorological drivers prior to the index calculation ("component" downscaling) thus, a wider range of statistical downscaling methods could be used. As an illustration, future changes in both indices are projected by applying two direct statistical downscaling methods, analogs and linear regression, to the ECHAM5 model. Larger differences were found between the two direct statistical downscaling approaches than between the direct and the component approaches with a single downscaling method. While these examples focus on particular indices and Mediterranean regions of interest for CLIM-RUN stakeholders, the same study

  7. Alternative Parameterization of the 3-PG Model for Loblolly Pine: A Regional Validation and Climate Change Assessment on Stand Productivity

    Science.gov (United States)

    Yang, J.; Gonzalez-Benecke, C. A.; Teskey, R. O.; Martin, T.; Jokela, E. J.

    2015-12-01

    Loblolly pine (Pinus taeda L.) is one of the fastest growing pine species. It has been planted on more than 10 million ha in the southeastern U.S., and also been introduced into many countries. Using data from the literature and long-term productivity studies, we re-parameterized the 3-PG model for loblolly pine stands. We developed new functions for estimating NPP allocation dynamics, canopy cover and needlefall dynamics, effects of frost on production, density-independent and density-dependent tree mortality, biomass pools at variable starting ages, and the fertility rating. New functions to estimate merchantable volume partitioning were also included, allowing for economic analyses. The fertility rating was determined as a function of site index (mean height of dominant trees at age=25 years). We used the largest and most geographically extensive validation dataset for this species ever used (91 pots in 12 states in U.S. and 10 plots in Uruguay). Comparison of modeled to measured data showed robust agreement across the natural range in the U.S., as well as in Uruguay, where the species is grown as an exotic. Using the new set of functions and parameters with downscaled projections from twenty different climate models, the model was applied to assess the impact of future climate change scenarios on stand productivity in the southeastern U.S.

  8. Climatic change impacts in Lombardia region

    International Nuclear Information System (INIS)

    Fiorese, G.; Gatto, M.; De Leo, G.

    2008-01-01

    Climatic change will change significantly our Country through impacts of natural and physical systems, on human health and the productive sectors. This article describes the expected impacts in Lombardia region [it

  9. CLIMATIC JUMP IN THE POLAR REGION (I)

    OpenAIRE

    ヤマモト, リョウザブロウ; イワシマ, タツヤ; ホシアイ, マコト; Ryozaburo, YAMAMOTO; Tatsuya, IWASHIMA; Makoto, HOSHIAI

    1987-01-01

    From the analysis of the climatic elements over Japan, we can detect the "climatic jumps" around the years 1920 and 1950,which is a new concept in the climatic diagnosis proposed by the present authors (R. YAMAMOTO et al. : J. Meteorol. Soc. Jpn., 63,1157,1985,64,273,1986). Taking account of several results which show the simultaneous occurrence of the climatic jumps of the surface air temperature, precipitation, etc., in the other regions by the other investigators, we may infer the "climati...

  10. Regional climate modeling: Should one attempt improving on the large scales? Lateral boundary condition scheme: Any impact?

    Energy Technology Data Exchange (ETDEWEB)

    Veljovic, Katarina; Rajkovic, Borivoj [Belgrade Univ. (RS). Inst. of Meteorology; Fennessy, Michael J.; Altshuler, Eric L. [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); Mesinger, Fedor [Maryland Univ., College Park (United States). Earth System Science Interdisciplinary Center; Serbian Academy of Science and Arts, Belgrade (RS)

    2010-06-15

    A considerable number of authors presented experiments in which degradation of large scale circulation occurred in regional climate integrations when large-scale nudging was not used (e.g., von Storch et al., 2000; Biner et al., 2000; Rockel et al., 2008; Sanchez-Gomez et al., 2008; Alexandru et al., 2009; among others). We here show an earlier 9-member ensemble result of the June-August precipitation difference over the contiguous United States between the ''flood year'' of 1993 and the ''drought year'' of 1988, in which the Eta model nested in the COLA AGCM gave a rather accurate depiction of the analyzed difference, even though the driver AGCM failed in doing so to the extent of having a minimum in the area where the maximum ought to be. It is suggested that this could hardly have been possible without an RCM's improvement in the large scales of the driver AGCM. We further revisit the issue by comparing the large scale skill of the Eta RCM against that of a global ECMWF 32-day ensemble forecast used as its driver. Another issue we are looking into is that of the lateral boundary condition (LBC) scheme. The question we ask is whether the almost universally used but somewhat costly relaxation scheme is necessary for a desirable RCM performance? We address this by running the Eta in two versions differing in the lateral boundary scheme used. One of these is the traditional relaxation scheme and the other is the Eta model scheme in which information is used at the outermost boundary only and not all variables are prescribed at the outflow boundary. The skills of these two sets of RCM forecasts are compared against each other and also against that of their driver. A novelty in our experiments is the verification used. In order to test the large scale skill we are looking at the forecast position accuracy of the strongest winds at the jet stream level, which we have taken as 250 hPa. We do this by calculating bias adjusted

  11. Evaluation of uncertainties in regional climate change simulations

    DEFF Research Database (Denmark)

    Pan, Z.; Christensen, J. H.; Arritt, R. W.

    2001-01-01

    , an atmosphere-ocean coupled general circulation model (GCM) current climate, and a future scenario of transient climate change. Common precipitation climatology features simulated by both models included realistic orographic precipitation, east-west transcontinental gradients, and reasonable annual cycles over...... to different subgrid scale processes in individual models. The ratio of climate change to biases, which we use as one measure of confidence in projected climate changes, is substantially larger than 1 in several seasons and regions while the ratios are always less than 1 in summer. The largest ratios among all...... regions are in California. Spatial correlation coefficients of precipitation were computed between simulation pairs in the 2x3 set. The climate change correlation is highest and the RCM performance correlation is lowest while boundary forcing and intermodel correlations are intermediate. The high spatial...

  12. A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

    Science.gov (United States)

    Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

    2015-04-01

    The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

  13. Coupled atmosphere ocean climate model simulations in the Mediterranean region: effect of a high-resolution marine model on cyclones and precipitation

    Directory of Open Access Journals (Sweden)

    A. Sanna

    2013-06-01

    Full Text Available In this study we investigate the importance of an eddy-permitting Mediterranean Sea circulation model on the simulation of atmospheric cyclones and precipitation in a climate model. This is done by analyzing results of two fully coupled GCM (general circulation models simulations, differing only for the presence/absence of an interactive marine module, at very high-resolution (~ 1/16°, for the simulation of the 3-D circulation of the Mediterranean Sea. Cyclones are tracked by applying an objective Lagrangian algorithm to the MSLP (mean sea level pressure field. On annual basis, we find a statistically significant difference in vast cyclogenesis regions (northern Adriatic, Sirte Gulf, Aegean Sea and southern Turkey and in lifetime, giving evidence of the effect of both land–sea contrast and surface heat flux intensity and spatial distribution on cyclone characteristics. Moreover, annual mean convective precipitation changes significantly in the two model climatologies as a consequence of differences in both air–sea interaction strength and frequency of cyclogenesis in the two analyzed simulations.

  14. Inflated Uncertainty in Multimodel-Based Regional Climate Projections

    Science.gov (United States)

    Madsen, Marianne Sloth; Langen, Peter L.; Boberg, Fredrik; Christensen, Jens Hesselbjerg

    2017-11-01

    Multimodel ensembles are widely analyzed to estimate the range of future regional climate change projections. For an ensemble of climate models, the result is often portrayed by showing maps of the geographical distribution of the multimodel mean results and associated uncertainties represented by model spread at the grid point scale. Here we use a set of CMIP5 models to show that presenting statistics this way results in an overestimation of the projected range leading to physically implausible patterns of change on global but also on regional scales. We point out that similar inconsistencies occur in impact analyses relying on multimodel information extracted using statistics at the regional scale, for example, when a subset of CMIP models is selected to represent regional model spread. Consequently, the risk of unwanted impacts may be overestimated at larger scales as climate change impacts will never be realized as the worst (or best) case everywhere.

  15. Improving snow albedo processes in WRF/SSiB regional climate model to assess impact of dust and black carbon in snow on surface energy balance and hydrology over western U.S.

    OpenAIRE

    Oaida, CM; Xue, Y; Flanner, MG; Skiles, SMK; De Sales, F; Painter, TH

    2015-01-01

    © 2015. American Geophysical Union. All Rights Reserved. Two important factors that control snow albedo are snow grain growth and presence of light-absorbing impurities (aerosols) in snow. However, current regional climate models do not include such processes in a physically based manner in their land surface models. We improve snow albedo calculations in the Simplified Simple Biosphere (SSiB) land surface model coupled with the Weather Research and Forecasting (WRF) regional climate model (R...

  16. Applying a regional hydrology model to evaluate locations for groundwater replenishment with hillslope runoff under different climate and land use scenarios in an agricultural basin, central coastal California

    Science.gov (United States)

    Beganskas, S.; Young, K. S.; Fisher, A. T.; Lozano, S.; Harmon, R. E.; Teo, E. K.

    2017-12-01

    We are applying a regional hydrology model, Precipitation-Runoff Modeling System (PRMS), to evaluate locations for groundwater replenishment with hillslope runoff in the Pajaro Valley Groundwater Basin (PVGB), central coastal California. Stormwater managed aquifer recharge (MAR) projects collect hillslope runoff before it reaches a stream and infiltrate it into underlying aquifers, improving groundwater supply. The PVGB is a developed agricultural basin where groundwater provides >85% of water for irrigation and municipal needs; stormwater-MAR projects are being considered to address chronic overdraft and saltwater intrusion. We are applying PRMS to assess on a subwatershed scale (10-100 ha; 25-250 acres) where adequate runoff is generated to supply stormwater-MAR in coincidence with suitable conditions for infiltration and recharge. Data from active stormwater-MAR projects in the PVGB provide ground truth for model results. We are also examining how basinwide hydrology responds to changing land use and climate, and the potential implications for future water management. To prepare extensive input files for PRMS models, we developed ArcGIS and Python tools to delineate a topographic model grid and incorporate high-resolution soil, vegetation, and other physical data into each grid region; we also developed tools to analyze and visualize model output. Using historic climate records, we generated dry, normal, and wet climate scenarios, defined as having approximately 25th, 50th, and 75th percentile annual rainfall, respectively. We also generated multiple land use scenarios by replacing developed areas with native vegetation. Preliminary results indicate that many parts of the PVGB generate significant runoff and have suitable infiltration/recharge conditions. Reducing basinwide overdraft by 10% would require collecting less than 5% of total hillslope runoff, even during the dry scenario; this demonstrates that stormwater-MAR could be an effective water management

  17. Collaborative Project. Understanding the effects of tides and eddies on the ocean dynamics, sea ice cover and decadal/centennial climate prediction using the Regional Arctic Climate Model (RACM)

    Energy Technology Data Exchange (ETDEWEB)

    Hutchings, Jennifer [Univ. of Alaska, Fairbanks, AK (United States); Joseph, Renu [Univ. of Alaska, Fairbanks, AK (United States)

    2013-09-14

    The goal of this project is to develop an eddy resolving ocean model (POP) with tides coupled to a sea ice model (CICE) within the Regional Arctic System Model (RASM) to investigate the importance of ocean tides and mesoscale eddies in arctic climate simulations and quantify biases associated with these processes and how their relative contribution may improve decadal to centennial arctic climate predictions. Ocean, sea ice and coupled arctic climate response to these small scale processes will be evaluated with regard to their influence on mass, momentum and property exchange between oceans, shelf-basin, ice-ocean, and ocean-atmosphere. The project will facilitate the future routine inclusion of polar tides and eddies in Earth System Models when computing power allows. As such, the proposed research addresses the science in support of the BER’s Climate and Environmental Sciences Division Long Term Measure as it will improve the ocean and sea ice model components as well as the fully coupled RASM and Community Earth System Model (CESM) and it will make them more accurate and computationally efficient.

  18. Ensemble-based Regional Climate Prediction: Political Impacts

    Science.gov (United States)

    Miguel, E.; Dykema, J.; Satyanath, S.; Anderson, J. G.

    2008-12-01

    Accurate forecasts of regional climate, including temperature and precipitation, have significant implications for human activities, not just economically but socially. Sub Saharan Africa is a region that has displayed an exceptional propensity for devastating civil wars. Recent research in political economy has revealed a strong statistical relationship between year to year fluctuations in precipitation and civil conflict in this region in the 1980s and 1990s. To investigate how climate change may modify the regional risk of civil conflict in the future requires a probabilistic regional forecast that explicitly accounts for the community's uncertainty in the evolution of rainfall under anthropogenic forcing. We approach the regional climate prediction aspect of this question through the application of a recently demonstrated method called generalized scalar prediction (Leroy et al. 2009), which predicts arbitrary scalar quantities of the climate system. This prediction method can predict change in any variable or linear combination of variables of the climate system averaged over a wide range spatial scales, from regional to hemispheric to global. Generalized scalar prediction utilizes an ensemble of model predictions to represent the community's uncertainty range in climate modeling in combination with a timeseries of any type of observational data that exhibits sensitivity to the scalar of interest. It is not necessary to prioritize models in deriving with the final prediction. We present the results of the application of generalized scalar prediction for regional forecasts of temperature and precipitation and Sub Saharan Africa. We utilize the climate predictions along with the established statistical relationship between year-to-year rainfall variability in Sub Saharan Africa to investigate the potential impact of climate change on civil conflict within that region.

  19. World Regionalization of Climate Change(1961–2010)

    Institute of Scientific and Technical Information of China (English)

    Peijun; Shi; Shao; Sun; Daoyi; Gong; Tao; Zhou

    2016-01-01

    Traditional climate classification or regionalization characterizes the mean state of climate condition, which cannot meet the demand of addressing climate change currently. We have developed a climate change classification method, as well as the fundamental principles, an indicator system, and mapping techniques of climate change regionalization. This study used annual mean temperature and total precipitation as climatic indices, and linear trend and variation change as change indices to characterize climate change quantitatively. The study has proposed a scheme for world climate change regionalization based on a half century of climate data(1961–2010). Level-I regionalization divides the world into 12 tendency zones based on the linear trend of climate, level-II regionalization resulted in 28 fluctuation regions based on the variation change of climate. Climate change regionalization provides a scientific basis for countries and regions to develop plans for adapting to climate change, especially for managing climate-related disaster or environmental risks.

  20. Regional climate scenarios - A study on precipitation

    International Nuclear Information System (INIS)

    Hesselbjerg Christensen, J.; Boessing Christensen, O.

    2001-01-01

    A set of nested climate change simulations for the Nordic region and Denmark has been revisited. In the present work we have re-examined the results of CCMB and MBC with special emphasis on precipitation intensity frequencies, in particular the more extreme part of the frequency distribution. It has been demonstrated that the role of extreme precipitation events appears to be more realistically described in a high-resolution model, in terms of numerical agreement as well as seasonal variation. This is mainly due to a better simulation of deep low-pressure systems and mesoscale circulation. Generally, the analysis has confirmed the results from CCMB, but furthermore a resolution effect has been identified which seems essential to the understanding of climate change effects on the extreme end of the precipitation intensity distribution. In order to analyse the role of the model resolution we have aggregated both the nested model data and observational records to the GCM grid from the driving AOGCM. It was found that, in spite of changes in absolute numbers, the seasonal behaviour of decay constants does not change appreciably because of the aggregation. The RCM results show a seasonal behaviour very similar to an observed data set. It is therefore concluded that the GCM has an unrealistic simulation of the dependence of heavy precipitation on climate, as manifested in seasonal variation. In contrast, the regional simulations remain close to observation in this respect. Furthermore, they agree on a conclusion that extreme precipitation generally scales with average precipitation (no significant change in decay constants were detected), but that crucial summer season may be an exception, exhibiting an anomalous increase in heavy precipitation due to the anthropogenic greenhouse effect. The analysis has only been performed over Denmark due to lack of daily observational data for other regions. It is, however, necessary to extend the work to other areas, for instance

  1. Regional climate modeling over the Maritime Continent: Assessment of RegCM3-BATS1e and RegCM3-IBIS

    Science.gov (United States)

    Gianotti, R. L.; Zhang, D.; Eltahir, E. A.

    2010-12-01

    Despite its importance to global rainfall and circulation processes, the Maritime Continent remains a region that is poorly simulated by climate models. Relatively few studies have been undertaken using a model with fine enough resolution to capture the small-scale spatial heterogeneity of this region and associated land-atmosphere interactions. These studies have shown that even regional climate models (RCMs) struggle to reproduce the climate of this region, particularly the diurnal cycle of rainfall. This study builds on previous work by undertaking a more thorough evaluation of RCM performance in simulating the timing and intensity of rainfall over the Maritime Continent, with identification of major sources of error. An assessment was conducted of the Regional Climate Model Version 3 (RegCM3) used in a coupled system with two land surface schemes: Biosphere Atmosphere Transfer System Version 1e (BATS1e) and Integrated Biosphere Simulator (IBIS). The model’s performance in simulating precipitation was evaluated against the 3-hourly TRMM 3B42 product, with some validation provided of this TRMM product against ground station meteorological data. It is found that the model suffers from three major errors in the rainfall histogram: underestimation of the frequency of dry periods, overestimation of the frequency of low intensity rainfall, and underestimation of the frequency of high intensity rainfall. Additionally, the model shows error in the timing of the diurnal rainfall peak, particularly over land surfaces. These four errors were largely insensitive to the choice of boundary conditions, convective parameterization scheme or land surface scheme. The presence of a wet or dry bias in the simulated volumes of rainfall was, however, dependent on the choice of convection scheme and boundary conditions. This study also showed that the coupled model system has significant error in overestimation of latent heat flux and evapotranspiration from the land surface, and

  2. Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR

    Directory of Open Access Journals (Sweden)

    X. Fettweis

    2013-03-01

    Full Text Available To estimate the sea level rise (SLR originating from changes in surface mass balance (SMB of the Greenland ice sheet (GrIS, we present 21st century climate projections obtained with the regional climate model MAR (Modèle Atmosphérique Régional, forced by output of three CMIP5 (Coupled Model Intercomparison Project Phase 5 general circulation models (GCMs. Our results indicate that in a warmer climate, mass gain from increased winter snowfall over the GrIS does not compensate mass loss through increased meltwater run-off in summer. Despite the large spread in the projected near-surface warming, all the MAR projections show similar non-linear increase of GrIS surface melt volume because no change is projected in the general atmospheric circulation over Greenland. By coarsely estimating the GrIS SMB changes from GCM output, we show that the uncertainty from the GCM-based forcing represents about half of the projected SMB changes. In 2100, the CMIP5 ensemble mean projects a GrIS SMB decrease equivalent to a mean SLR of +4 ± 2 cm and +9 ± 4 cm for the RCP (Representative Concentration Pathways 4.5 and RCP 8.5 scenarios respectively. These estimates do not consider the positive melt–elevation feedback, although sensitivity experiments using perturbed ice sheet topographies consistent with the projected SMB changes demonstrate that this is a significant feedback, and highlight the importance of coupling regional climate models to an ice sheet model. Such a coupling will allow the assessment of future response of both surface processes and ice-dynamic changes to rising temperatures, as well as their mutual feedbacks.

  3. Assimilation of radar altimeter data in numerical wave models: an impact study in two different wave climate regions

    Directory of Open Access Journals (Sweden)

    G. Emmanouil

    2007-03-01

    Full Text Available An operational assimilation system incorporating significant wave height observations in high resolution numerical wave models is studied and evaluated. In particular, altimeter satellite data provided by the European Space Agency (ESA-ENVISAT are assimilated in the wave model WAM which operates in two different wave climate areas: the Mediterranean Sea and the Indian Ocean. The first is a wind-sea dominated area while in the second, swell is the principal part of the sea state, a fact that seriously affects the performance of the assimilation scheme. A detailed study of the different impact is presented and the resulting forecasts are evaluated against available buoy and satellite observations. The corresponding results show a considerable improvement in wave forecasting for the Indian Ocean while in the Mediterranean Sea the assimilation impact is restricted to isolated areas.

  4. A diagnostic carbon flux model to monitor the effects of disturbance and interannual variation in climate on regional NEP.

    Science.gov (United States)

    D.P. Turner; W.D. Ritts; J.M. Styles; Z. Yang; W.B. Cohen; B.E. Law; P.E. Thornton

    2006-01-01

    Net ecosystem production (NEP) was estimated over a 10.9 x 104 km2 forested region in western Oregon USA for 2 yr (2002-2003) using a combination of remote sensing, distributed meteorological data, and a carbon cycle model (CFLUX). High spatial resolution satellite data (Landsat, 30 m) provided information on land cover and...

  5. Climate impacts of deforestation/land-use changes in Central South America in the PRECIS regional climate model: mean precipitation and temperature response to present and future deforestation scenarios.

    Science.gov (United States)

    Canziani, Pablo O; Carbajal Benitez, Gerardo

    2012-01-01

    Deforestation/land-use changes are major drivers of regional climate change in central South America, impacting upon Amazonia and Gran Chaco ecoregions. Most experimental and modeling studies have focused on the resulting perturbations within Amazonia. Using the Regional Climate Model PRECIS, driven by ERA-40 reanalysis and ECHAM4 Baseline model for the period 1961-2000 (40-year runs), potential effects of deforestation/land-use changes in these and other neighboring ecoregions are evaluated. Current 2002 and estimated 2030 land-use scenarios are used to assess PRECIS's response during 1960-2000. ERA-40 and ECHAM4 Baseline driven runs yield similar results. Precipitation changes for 2002 and 2030 land-use scenarios, while significant within deforested areas, do not result in significant regional changes. For temperature significant changes are found within deforested areas and beyond, with major temperature enhancements during winter and spring. Given the current climate, primary effects of deforestation/land-use changes remain mostly confined to the tropical latitudes of Gran Chaco, and Amazonia.

  6. Potential regulation on the climatic effect of Tibetan Plateau heating by tropical air-sea coupling in regional models

    Science.gov (United States)

    Wang, Ziqian; Duan, Anmin; Yang, Song

    2018-05-01

    Based on the conventional weather research and forecasting (WRF) model and the air-sea coupled mode WRF-OMLM, we investigate the potential regulation on the climatic effect of Tibetan Plateau (TP) heating by the air-sea coupling over the tropical Indian Ocean and western Pacific. Results indicate that the TP heating significantly enhances the southwesterly monsoon circulation over the northern Indian Ocean and the South Asia subcontinent. The intensified southwesterly wind cools the sea surface mainly through the wind-evaporation-SST (sea surface temperature) feedback. Cold SST anomaly then weakens monsoon convective activity, especially that over the Bay of Bengal, and less water vapor is thus transported into the TP along its southern slope from the tropical oceans. As a result, summer precipitation decreases over the TP, which further weakens the TP local heat source. Finally, the changed TP heating continues to influence the summer monsoon precipitation and atmospheric circulation. To a certain extent, the air-sea coupling over the adjacent oceans may weaken the effect of TP heating on the mean climate in summer. It is also implied that considerations of air-sea interaction are necessary in future simulation studies of the TP heating effect.

  7. Assessing the impact of climatic change in cold regions

    Energy Technology Data Exchange (ETDEWEB)

    Parry, M L; Carter, T R [eds.

    1984-01-01

    The report describes the use of models to predict the consequences of global warming in particular (cold) regions. The workshop focused on two related issues: (a) the current sensitivity of ecosystems and farming systems to climatic variability, and (b) the range of impacts likely for certain changes of climate. This report addresses four broad themes: (1) the nature of the research problem; (2) methods of evaluating sensitivity to climatic variability; (3) methods of measuring the impact of climate change; and (4) how these methods might be refined. (ACR)

  8. A Dynamic Evaluation Of A Model And An Estimate Of The Air Quality And Regional Climate Impacts Of Enhanced Solar Power Generation

    Science.gov (United States)

    Millstein, D.; Brown, N. J.; Zhai, P.; Menon, S.

    2012-12-01

    We use the WRF/Chem model (Weather Research and Forecasting model with chemistry) and pollutant emissions based on the EPA National Emission Inventories from 2005 and 2008 to model regional climate and air quality over the continental United States. Additionally, 2030 emission scenarios are developed to investigate the effects of future enhancements to solar power generation. Modeling covered 6