Studia Geophysica et Geodaetica

, Volume 54, Issue 2, pp 313–332 | Cite as

Model ALADIN as regional climate model for Central and Eastern Europe

  • Aleš Farda
  • Michel Déué
  • Samuel Somot
  • András Horányi
  • Valery Spiridonov
  • Helga Tóth
Article

Abstract

Results obtained with two versions of the Limited Area Model (LAM) ALADIN over differently sized integration domains (large, intermediate and small) in the European area are presented in order to investigate both the general model performance and the influence of domain choice on the quality of obtained results. The aim is also to illustrate the issues related to the strategy of selection of the optimal integration domain. Each of these studies has been performed with two versions of the ALADIN model: the first one is ALADIN-CLIMATE developed at CNRM/Météo-France, the second one is ALADIN-CLIMATE/CZ prepared at the Czech Hydrometeorological Institute (CHMI). This leaves us with total of six experiments forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-40 reanalysis data. The west Balkan domain covering Bulgaria is used as an evaluation region for investigation of the temporal and spatial properties of simulated precipitation and temperature fields. This region has been selected for its challenging orography making the results obtained here a valuable source for studies leading to further developments in climate modeling. It was found that size of the domain strongly affects the quality of obtained results. We have found that the largest domain reproduces the spatial characteristics of climate (such as bias) very well, but its use results in a poor representation of temporal aspects, which are however captured very well in experiments over both smaller domains. Our findings suggest that there is no optimal choice of domain size, securing the best results for both spatial and temporal evaluation.

Our study also proves that model ALADIN can be efficiently used for climate research purposes, which together with its modest computational demands should make it as an attractive modeling choice for the Central and Eastern European climate research community.

Keywords

ALADIN climate modeling domain size ECMWF ERA-40 reanalysis 

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References

  1. Bhaskaran B., Jones R.G., Murphy J.M. and Noguer M., 1996. Simulations of the Indian summer monsoon using a nested regional climate model: Domain size experiments. Clim. Dyn., 12, 573–587.Google Scholar
  2. Bougeault P., 1985. A simple parameterization of the large-scale effects of cumulus convection. Mon. Weather Rev., 113, 2108–2121.CrossRefGoogle Scholar
  3. Bubnová R., Hello G., Bénard P. and Geleyn J.-F., 1995. Integration of the fully elastic equations cast in the hydrostatic pressure terrain-following coordinate in the framework of ARPEGE/Aladin NWP system. Mon. Weather Rev., 123, 515–535.CrossRefGoogle Scholar
  4. Davies H.C., 1976. A lateral boundary formulation for multi level prediction models. Q. J. R. Meteorol. Soc., 102, 405–418.Google Scholar
  5. de Elia R., Plummer D., Caya D., Frigon A., Côté H., Giguère M., Paquin D., Biner S. and Harvey R., 2008. Evaluation of uncertainties in the CRCM-simulated North American climate: nesting-related issues. Clim. Dyn., 30, 113–132.CrossRefGoogle Scholar
  6. Déqué M., 2007. Frequency of precipitation and temperature extremes over France in an anthropogenic scenario: model results and statistical correction according to observed values. Glob. Planet. Change, 57, 16–26.CrossRefGoogle Scholar
  7. Dimitrijevic M. and Laprise R., 2005. Validation of the nesting technique in a regional climate model and sensitivity tests to the resolution of the lateral boundary conditions during summer. Clim. Dyn., 25, 550–580.CrossRefGoogle Scholar
  8. Douville H., Royer J.-F. and Mahfouf J.-F., 1995. A new snow parametrization for the Météo-France climate model. Part I: Validation in stand-alone experiments. Clim. Dyn., 12, 21–35.CrossRefGoogle Scholar
  9. Farda A., Štěpánek P., Halenka T., Skalák P. and Belda M., 2007. Model ALADIN in climate mode forced with ERA-40 reanalysis (coarse resolution experiment). Meteorological Journal, 10, 123–130.CrossRefGoogle Scholar
  10. Gerard L., 2001. Physical parameterizations in ARPÉGE-ALADIN operational model. ALADIN Documentation, Météo-France, 130 pp.Google Scholar
  11. Hewitt C.D and Griggs D.J., 2004. Ensembles-based predictions of climate changes and their impacts. Eos Trans. AAGU, 85, 566.Google Scholar
  12. Horányi A., Ihász I. and Radnóti G., 1996. ARPEGE/ALADIN: A numerical weather predicition model for Central-Europe with the participation of the Hungarian Meteorological Service. Időjárás, 100, 277–300.Google Scholar
  13. Huth R., 2002. Statistical downscaling of daily temperature in central Europe. J. Climate, 15, 1731–1742.CrossRefGoogle Scholar
  14. Jacob D., Bärring L., Christensen O.B., Christensen J.H., de Castro M., Déqué M., Giorgi F., Hagemann S., Hirschi M., Jones R., Kjellström E., Lenderink G., Rockel B., Sànchez E.S., Schär C., Seneviratne S.I., Somot S., van Ulden A. and van den Hurk B., 2007. An intercomparison of regional climate models for Europe: Model performance in Present-Day Climate. Clim. Change, 81,Supplement 1, 31–52, doi: 10.1007/s10584-006-9213-4.CrossRefGoogle Scholar
  15. Janišková M., 1995. Study of the systematic errors in ALADIN associated to the physical part of the model. Note ALADIN n°7, CNRM, Météo-France, 82.Google Scholar
  16. Jones R.G., Murphy J.M. and Noguer M., 1995. Simulation of climate change over Europe using a nested regional climate model. Part I: assessment of control climate, including sensitivity to location of lateral boundaries. Q. J. R. Meteorol. Soc., 121, 1413–1449.Google Scholar
  17. Leduc M. and Laprise R., 2009. Regional climate model sensitivity to domain size. Clim. Dyn., 32, 833–854, doi: 10.1007/s00382-008-0400-z.CrossRefGoogle Scholar
  18. Lucas-Picher P., Caya D., de Elia R. and Laprise R., 2008. Investigation of regional climate models’ internal variability with a ten-member ensemble of ten years over a large domain. Clim. Dyn., 31, 927–940, doi: 10.1007/s00382-008-0384-8.CrossRefGoogle Scholar
  19. Malkmus W., 1967. Random Lorentz band model with exponential-tailed S-1 line-intensity distribution function. J. Opt. Soc. Am., 57, 323–329.CrossRefGoogle Scholar
  20. Mellor G.L. and Yamada T., 1982. Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys. Space Phys., 20, 851–875.CrossRefGoogle Scholar
  21. Mitchell T.D., Carter T.R., Jones P.D., Hulme M. and New M., 2004. A comprehensive set of high-resolution grids of monthly climate for Europe and the globe: the observed record (1901–2000) and 16 scenarios (2001–2100). Tyndall Centre for Climate Change Research, Working Paper 55 (http://www.ipcc-data.org/docs/tyndall_working_papers_wp55.pdf).
  22. Morcrette J.-J., 1989. Description of the Radiation Scheme in the ECMWF Model. Technical Memorandum 165, ECMWF, 26 pp.Google Scholar
  23. Noilhan J. and Planton S., 1989. A simple parameterization of land surface processes for meteorological models. Mon. Weather Rev., 117, 536–549.CrossRefGoogle Scholar
  24. Radu R., Somot S. and Déqué M., 2008. Spectral nudging in a spectral regional climate model. Tellus Ser. A — Dyn. Meteorol. Oceanol., 60, 898–910.Google Scholar
  25. Rauscher S.A., Seth A., Qian J.-H. and Camargo S.J., 2006. Domain choice in an experimental nested modeling prediction system for South America. Theor. Appl. Climatol., 86, 229–246.CrossRefGoogle Scholar
  26. Ricard J.-L. and Royer J.-F., 1993. A statistical cloud scheme for use in an AGCM. Ann. Geophys. — Atmos. Hydrosph. Space Sci., 11, 1095–1115.Google Scholar
  27. Ritter B. and Geleyn J.-F., 1992. A comprehensive radiation scheme of numerical weather prediction with potential application to climate simulations. Mon. Weather Rev., 120, 303–325.CrossRefGoogle Scholar
  28. Sanchez-Gomez E., Somot S. and Déqué M., 2009. Ability of an ensemble of regional climate models to reproduce the weather regimes during the period 1961–2000. Clim. Dyn., 33, 723–736.CrossRefGoogle Scholar
  29. Taylor K.E., 2001. Summarizing multiple aspects of model performance in single diagram. J. Geophys. Research, 106(D7), 7183–7192.CrossRefGoogle Scholar
  30. Tegen I., Hollrig P., Chin M., Fung I., Jacob D. and Penner J., 1997. Contribution of different aerosol species to the global aerosol extinction optical thickness: estimates from model results. J. Geophys. Res., 102, 23895–23915.CrossRefGoogle Scholar
  31. Temperton C., Hortal M. and Simmons A.J., 2001. A two-time-level semi-Lagrangian global spectral model. Q. J. R. Meteorol. Soc., 127, 111–128.CrossRefGoogle Scholar
  32. Uppala S.M., Kållberg P.W., Simmons A.J., Andrae U., da Costa Bechtold V., Fiorino M., Gibson J.K., Haseler J., Hernandez A., Kelly, G.A., Li, X., Onogi K., Saarinen S., Sokka N., Allan R.P., Andersson E., Arpe K., Balmaseda M.A., Beljaars A.C.M., van de Berg L., Bidlot J., Bormann N., Caires S., Chevallier F., Dethof A., Dragosavac M., Fisher M., Fuentes M., Hagemann S., Hólm E., Hoskins B.J., Isaksen L., Janssen P.A.E.M., Jenne R., McNally A.P., Mahfouf J.-F., Morcrette J.-J., Rayner N.A., Saunders R.W., Simon P., Sterl A., Trenberth K.E., Untch A., Vasiljevic D., Viterbo P. and Woollen J., 2005. The ERA-40 re-analysis. Q. J. R. Meteorol. Soc., 131, 2961–3012.CrossRefGoogle Scholar
  33. Váña F., Benard P., Geleyn J.-F., Simon A. and Seity Y., 2008. Semi-Lagrangian advection scheme with controlled damping — an alternative way to nonlinear horizontal diffusion in a numerical weather prediction model. Accepted by Q. J. R. Meteorol. Soc., 134, 523–537.CrossRefGoogle Scholar
  34. von Storch H., Langenberg H. and Feser F., 2000. A spectral nudging technique for dynamical downscaling purposes. Mon. Weather Rev., 128, 3664–3673.CrossRefGoogle Scholar
  35. Wilby R.L., Wigley T.M.L., Conway D., Jones P.D., Hewitson B.C., Main J. and Wilks D.S., 1998. Statistical downscaling of general circulation model output, a comparison of Methods. Water Resour. Res., 34, 2995–3008.CrossRefGoogle Scholar

Copyright information

© Institute of Geophysics of the ASCR, v.v.i 2010

Authors and Affiliations

  • Aleš Farda
    • 1
  • Michel Déué
    • 2
  • Samuel Somot
    • 2
  • András Horányi
    • 3
  • Valery Spiridonov
    • 4
  • Helga Tóth
    • 3
  1. 1.Czech Hydrometeorological InstitutePragueCzech Republic
  2. 2.Centre National de Recherches Météorologiques (Météo France/CNRS)GAME/CNRMToulouseFrance
  3. 3.Hungarian Meteorological ServiceBudapestHungary
  4. 4.National Institute of Meteorology and HydrologySofiaBulgaria

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