Advances in Geosciences www.adv-geosci.net 1680-7340 1680-7359 26 11th EGU Plinius Conference on Mediterranean Storms (2009) 2010 10.5194/adgeo-26-1-2010 http://www.adv-geosci.net/26/1/2010/ http://www.adv-geosci.net/26/1/2010/adgeo-26-1-2010.html http://www.adv-geosci.net/26/1/2010/adgeo-26-1-2010.pdf 1 6 2010-06-30 Study of the precipitation evolution in Catalonia using a mesoscale model (1971–2000) A. Barrera-Escoda tbarrera@meteo.cat J. Cunillera Meteorological Service of Catalonia, Applied Research and Modelling Team, Department of the Environment and Housing, Government of Catalonia, C. Berlín 38–48, 4a planta, 08029 Barcelona, Spain In this work the MM5 mesoscale model is used in order to analyse the temporal evolution of the precipitation for the period 1971–2000 in Catalonia (NE Iberian Peninsula). Three one-way nested domains with 135, 45 and 15 km horizontal grid resolution and 23 vertical levels have been used. The simulation is performed nesting MM5 into the ERA40 reanalyses. Dynamical nudging is applied to the first domain. However, nudging is not applied in the second and third domains. In order to assess the performance of the developed methodology (main spatio-temporal precipitation characteristics), the results obtained in each simulation are compared with those obtained from ERA40 and observational data. <br><br> The results show a climatologically reliable distribution of the simulated precipitation spatial patterns for annual, semi-annual, spring and summer precipitation compared to those obtained from 1100 rain gauges covering the whole study area. For winter and autumn the goodness of the results is much lower. Furthermore, the results for 15-km outputs are better than the 45-km ones. The simulations also reproduce well the evolution of annual anomalies for Catalonia and the probability density function (PDF) of monthly mean precipitation. They also improve the precipitation outputs from ERA40, which present an important negative trend and a drier PDF for the period 1971–2000. On the other hand, extreme values are not well reproduced by the simulation. Despite this fact, hydric extremes derived from extreme values (i.e. extreme rainy days and flood records) are well captured by the model. Altava-Ortiz, V.: Caracterització i monitoratge de les sequeres a Catalunya i nord del Pa\'is Valencià. Càlcul d'escenaris climàtics per al segle XXI (Characterising and monitoring droughts in Catalonia and Northern Valencian Country. Calculation of climatic scenarios for the 21st century), Ph.D. Thesis, Internal Publication, University of Barcelona, Barcelona, Spain, 2010. Barrera, A., Llasat, M. C., and Barriendos, M.: Estimation of extreme flash flood evolution in Barcelona County from 1351 to 2005, Nat. Hazards Earth Syst. Sci., 6, 505–518, doi:10.5194/nhess-6-505-2006, 2006. Barrera-Escoda, A.: Evolución de los extremos h\'idricos en Catalunya en los últimos 500 años y su modelización regional (Evolution of hydric extremes in Catalonia during the last 500 years and its regional modelling), Ph.D. Thesis, Internal Publication, University of Barcelona, Barcelona, Spain, prefixhttp://www.zucaina.net/Publicaciones/Barrera-Escoda-TESIS-200% 8.pdf, 2008. Dudhia, J.: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46, 3077–3107, 1989. Dudhia, J.: A multi-layer soil temperature model for MM5, in: Preprints, The Sixth PSU/NCAR Mesoscale Model Users Workshop (Boulder, Colorado, USA, 22–24 July 1996), 49–50, available online at: prefixhttp://www.mmm.ucar.edu/mm5/mm5v2/whatisnewinv2.html, 1996. Dudhia, J., Gill, D., Manning, K., Wang, W., and Bruyere, C.: PSU/NCAR Mesoscale Modeling System Tutorial Class Notes and Users' Guide (MM5 Modeling System Version 3), Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, Boulder, Colorado, USA, prefixhttp://www.mmm.ucar.edu/mm5/documents/tutorial-v3-notes.html, 2005. Fernández, J., Montávez, J \relax P., Sáenz, J., González-Rouco, J \relax F., and Zorita, E.: Sensitivity of the MM5 mesoscale model to physical parameterizations for regional climate studies: Annual cycle, J. Geophys. Res.-Atmos., 112, D04101, \doi10.1029/2005JD006649, 2007. Fowler, H \relax J., Blenkinsop, S., and Tebaldi, C.: Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling, Int. J. Climatol., 27, 1547–1578, \doi10.1002/joc.1556, 2007. Grell, G A.: Prognostic evaluation of assumptions used by cumulus parameterizations, Mon. Weather Rev., 121, 764–787, 1993. Grell, G \relax A., Dudhia, J., and Stauffer, D \relax R.: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5), NCAR Technical Note 398, Mesoscale and Microscale Meteorology Division, 1994. Hong, S \relax Y. and Pan, H L.: Nonlocal boundary layer vertical diffusion in a medium-range forecast model, Mon. Weather Rev., 124, 2322–2339, 1996. IPCC: Climate change 2007: the physical science basis; Contribution of Working Group I to the fourth Assessment Report of the Intergovenmental Panel on Climate Change, Cambridge University Press, UK and USA, prefixhttp://www.ipcc.ch/publications_and_data/publications_ipcc_fo% urth_assessment_report_wg1_report_the_physical_science_basis.htm, 2007. Kunkel, K \relax E., Andsager, K., and Easterling, D \relax R.: Long-term trends in extreme precipitation events over the conterminous United States and Canada, J. Climate, 12, 2515–2527, 1999. Liebmann, B., Vera, C \relax S., Carvalho, L. \relax M \relax V., Camilloni, I \relax A., Hoerling, M \relax P., Allured, D., Barros, V \relax R., Báez, J., and Bidegain, M.: An observed trend in central South American precipitation, J. Climate, 17, 4357–4367, \doi10.1175/3205.1, prefixhttp://journals.ametsoc.org/doi/pdf/10.1175/3205.1, 2004. Livezey, R \relax E. and Chen, W \relax Y.: Statistical field significance and its determination by Monte Carlo techniques, Mon. Weather Rev., 111, 46–59, 1983. Salathé~Jr, E \relax P., Mote, P \relax W., and Wiley, M \relax W.: Review of scenario selection and downscaling methods for the assessment of climate change impacts on hydrology in the United States pacific northwest, Int. J. Climatol., 27, 1611–1621, \doi10.1002/joc.1540, 2007. Salathé~Jr, E \relax P., Steed, R., Mass, C \relax F., and Zahn, P \relax H.: A high-resolution climate model for the US Pacific Northwest: Mesoscale feedbacks and local responses to climate change, J. Climate, 21, 5708–5726, \doi10.1175/2008JCLI2090.1, prefixhttp://journals.ametsoc.org/doi/pdf/10.1175/2008JCLI2090.1, 2008. Uppala, S \relax M., Kållberg, P \relax W., Simmons, A \relax J., Andrae, U., da~Costa~Bechtold, V., Fiorino, M., Gibson, J \relax K., Haseler, J., Hernández, A., Kelly, G \relax A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R \relax P., Andersson, E., Arpe, K., Balmaseda, M \relax A., Beljaars, A. \relax C \relax 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 \relax J., Isaksen, L., Janssen, P. \relax A. \relax E \relax M., Jenne, R., McNally, A \relax P., Mahfouf, J.-F., Morcrette, J.-J., Rayner, N \relax A., Saunders, R \relax W., Simon, P., Sterl, A., Trenberth, K \relax E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40 re-analysis, Q. J. Roy. Meteorol. Soc., 131, 2961–3012, \doi10.1256/qj.04.176, 2005.