Abstract
In this study we present results of uncertainty analysis in eight regional climate model (RCM) outputs over the area of the Czech Republic. The RCM simulations come from the EU 5th Framework program project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). Using the analysis of variance we have found that the main source of uncertainty in projected changes of mean seasonal air temperature is the driving global climate model. In case of precipitation changes, the RCM is the largest source of uncertainty in all seasons except for the spring. With the second method, the Reliability Averaging method, we have focused on the uncertainty coming from the RCM itself. The results of both methods showed that the relative contribution of the regional climate model to the uncertainty of simulated mean seasonal air temperature and precipitation changes is largest in summer and smallest in winter.
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Annan J.D. and Hargreaves J.C., 2007. Efficient estimation and ensemble generation in climate modelling. Phil. Trans. R. Soc. A, 365, 2077–2088.
Cahynová M. and Huth R., 2009. Changes of atmospheric circulation in central Europe and their influence on climatic trends in the Czech Republic. Theor. Appl. Climatol., 96, 57–68, doi: 10.1007/s00704-008-0097-2.
Christensen J.H. and Christensen O.B., 2007. A summary of the PRUDENCE model projectionsof changes in European climate by the end of this century. Clim. Change, 81, 7–30.
Collins M., 2007. Ensembles and probabilities: a new era in the prediction of climate change. Phil. Trans. R. Soc. A, 365, 1957–1970.
Černochová E., 2007. Uncertainties in climate model outputs. In: Šafránková J. and Pavlů J. (Eds.), WDS’07 Proceedings of Contributed Papers: Part III — Physics. Matfyzpress, Prague, Czech Republic, 156–160, ISBN 978-80-7378-025-8.
Déqué M., Rowell D.P., Lüthi D., Giorgi F., Christensen J.H., Rockel B., Jacob D., Kjellström E., de Castro M. and van den Hurk B., 2007. An intercomparison of regional climate simulations for Europe: assessing uncertainties in model projections. Clim. Change, 81, 53–70.
Giorgi F. and Mearns L.O., 2002. Calculation of average, uncertainty range and reliability of regional climate changes from AOGCM simulation via the Reliability Ensemble Averaging (REA) method. J. Climate, 15, 11141–1157.
Gordon C., Cooper C., Senior C.A., Banks H., Gregory J.M., Johns T.C., Mitchell J.F.B. and Wood R.A., 2000. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Center coupled model without flux adjustments. Clim. Dyn., 16, 147–168.
Goswami B.N. and Ajaya Mohan R.S., 2001. Estimate of predictability of monthly means in tropics from observations. Curr. Sci., 80, 56–63.
Hagedorn R., Doblas-Reyes F.J. and Palmer T.N., 2005. The rationale behind the success of multi-model ensembles in seasonal forecasting. Part I: Basic concept. Tellus A, 57, 219–233.
Haylock M.R., Hofstra N., Klein Tank A.M.G., Klok E.J., Jones P.D. and New M., 2008. A European daily highresolution gridded data set of surface temperature and precipitation for 1950–2006. J. Geophys. Res., 113, D20119, doi: 10.1029/2008JD010201.
Hunt B.G. and Elliot T.I., 2006. Climatic trends. Clim. Dyn., 26, 567–585.
Jacob D., Christensen O.B., Doblas-Reyes F.J., Goodess C., Klein Tank A.M.G., Lorenz P. and Roeckner E., 2008. Information on Observations, Global and Regional Modelling Data Availability and Statistical Downscaling. ENSEMBLES Technical Report No. 4. (online at http://ensembles-eu.metoffice.com/tech_reports/ETR_4_vn1.pdf).
Kalvová J., Halenka T., Bezpalcová K. and Nemešová I., 2003. Köppen climate types in observed and simulated climates. Stud. Geophys. Geod., 47, 185–202.
Kalvová J., Holtanová E., Mikšovský J., Motl M., Pišoft P., Raidl A., Farda A., Kliegrová S. and Metelka L., 2009. Selection of global climate models for assessment of uncertainties related to estimates of future climate changes in the Czech Republic. Meteorological Bulletin, 62, 97–106 (in Czech).
Madden R.A., 1976. Estimates of the natural variability of time-averaged sea level pressure. Mon. Weather Rev., 104, 942–952.
Meehl G.A., Stocker T.F., Collins W.D., Friedlingstein P., Gaye A.T., Gregory J.M., Kitoh A., Knutti R., Murphy J.M., Noda A., Raper S.C.B., Watterson I.G., Weaver A.J. and Zhao Z.-C., 2007. Global Climate Projections. In: Solomon S., Qin D., Manning M., Chen Z., Marquis M., Averyt K.B., Tignor M. and Miller H.L (Eds.), Climate Change 2007: The Physical Science Basis. Cambridge University Press, Cambridge, U.K., 747–846.
Moss R., Babiker M., Brinkman S., Calvo E., Carter T., Edmonds J., Elgizouli I., Emori S., Erda L., Hibbard K., Jones R., Kainuma M., Kelleher J., Lamarque J.F., Manning M., Matthews B., Meehl J., Meyer L., Mitchell J., Nakicenovic N., O’Neill B., Pichs R., Riahi K., Rose S., Runci P., Stouffer R., van Vuuren D., Weyant J., Wilbanks T., van Ypersele J.P., Zurek M., 2008. Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts, and Response Strategies. Intergovernmental Panel on Climate Change, Geneva, Switzerland, 132 pp.
Murphy J.M., Sexton D.M.H., Barnett D.N., Jones G.S., Webb M.J., Collins M. and Stainforth D.A., 2004. Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature, 430, 768–772.
Nakicenovic N. and Swart R. (Eds.), 2000. Emissions Scenarios. Cambridge University Press, Cambridge, U.K.
Nemešová I., Kalvová J. and Dubrovský M., 1999. Climate change projections based on GCM simulated daily data. Stud. Geophys. Geod., 43, 201–222.
New M., Hulme M. and Jones P.D., 1999. Representing twentieth century space-time climate variability. Part 1: development of a 1961–90 mean monthly terrestrial climatology. J. Climate, 12, 829–856.
Pope V.D., Gallani M., Rowntree P.R. and Stratton R.A., 2000: The impact of new physical parametrizations in the Hadley Centre climate model — HadAM3. Clim. Dyn., 16, 123–146.
Räisänen J., 2007. How reliable are climate models? Tellus A, 59, 2–29.
Roeckner E., Arpe K., Bengtsson L., Christoph M., Claussen M., Dumenil L., Esch M., Giorgetta M., Schlese U. and Schulzwieda U., 1996. The Atmospheric General Circulation Model ECHAM-4: Model Description and Simulation of Present-Day Climate. Report No. 218, Max-Planck-Institude für Meteorologie, Hamburg, Germany, 90 pp.
Shea D.J. and Madden R.A., 1990. Potential for long-range prediction of monthly mean surface temperatures over North America. J. Climate, 3, 1444–1451.
Skalák P., Štěpánek P. and Farda A., 2008. Validation of ALADIN-Climate/CZ for present climate (1961–1990) over the Czech Republic. Idojaras, 112, 191–201.
Tebaldi C. and Knutti R., 2007. The use of the multi-model ensemble in probabilistic climate projections. Phil. Trans. R. Soc. A, 365, 2053–2075.
Van Ulden A., Lenderink G., Van den Hurk B. and Van Meijgaard E., 2007. Circulation statistics and climate change in Central Europe: PRUDENCE simulations and observations. Clim. Change, 81, 179–192.
Weigel A.P., Liniger M.A. and Appenzeller C., 2008. Can multi-model combination really enhance the prediction skill of probabilistic ensemble forecasts? Q. J. R. Meteorol. Soc., 134, 241–260.
Zhang R. and Delworth T.L., 2005. Simulated tropical response to a substantial weakening of the Atlantic thermohaline circulation. J. Climate, 18, 1853–1860.
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Holtanová, E., Kalvová, J., Mikšovský, J. et al. Analysis of uncertainties in regional climate model outputs over the Czech Republic. Stud Geophys Geod 54, 513–528 (2010). https://doi.org/10.1007/s11200-010-0030-x
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DOI: https://doi.org/10.1007/s11200-010-0030-x