A Regional Climate Model Simulation for EURO-CORDEX with the WRF Model

  • Kirsten Warrach-Sagi
  • Thomas Schwitalla
  • Hans-Stefan Bauer
  • Volker-Wulfmeyer
Conference paper

Abstract

In order to provide high-resolution ensembles and comparisons of regional climate simulations, the World Climate Research Program (WCRP) initiated the COordinated Regional climate Downscaling Experiment (CORDEX). CORDEX is performed in preparation of the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC AR5) (Giorgi et al., WMO Bull 58:175–183, 2009). Verification runs for CORDEX are performed for most continents for a 20-year period (1989–2009) driven by ERA-interim data from the European Centre for Medium Range Weather Forecast (ECMWF). For Europe (EURO-CORDEX, http://www.euro-cordex.net) an ensemble of regional climate model simulations from 1989 to 2008 on 0. 11, 0. 22 and 0. 44 has been completed in May 2012. The University of Hohenheim contributed to EURO-CORDEX with a simulation with Weather Research and Forecast (WRF) model on the CRAY XE6 of the High Performance Computing Center Stuttgart (HLRS) of the University of Stuttgart. The model consists of a spatial grid of 424*412*54 grid cells and is run with a timestep of 60 s on 1,280 processors. Three-hourly output of the atmospheric and terrestrial variables is written to daily netcdf-files each of the size of 8.5 GB. The simulations’ set up is described and a comparison of the results to an observational precipitation data set for Germany is shown.

Keywords

Regional Climate Model Regional Climate Model Simulation Regional Climate Simulation World Climate Research Program Regional Climate Projection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

Kirsten Warrach-Sagi thanks the German Science Foundation for her funding within the frame of the integrated research project PAK 346/FOR 1695 Structure and function of agricultural landscapes under global climate change – Processes and projections on a regional scale. Further we acknowledge the REGNIE data from the German Weather Service. The authors thank the HLRS staff for the permission and support of the simulations on the High Performance Computer in Stuttgart. The simulations were carried out in collaboration with the WESS (Water and Earth System Science) Consortium funded by the BMBF and UFZ Leipzig.

References

  1. 1.
    Beniston, M., D.B. Stephenson, O.B. Christensen, C.A.T. Ferro, C. Frei, S. Goyette, K. Halsnaes, T. Holt, K. Jylhü, B. Koffi, J. Palutikoff, R. Schöll, T. Semmler, and K. Woth, 2007: Future extreme events in European climate; an exploration of Regional Climate Model projections. Climatic Change 81, 71–95.CrossRefGoogle Scholar
  2. 2.
    Behrendt, A., S. Pal, F. Aoshima, M. Bender, A. Blyth, U. Corsmeier, J. Cuesta, G. Dick, M. Dorninger, C. Flamant, P. Di Girolamo, T. Gorgas, Y. Huang, N. Kalthoff, S. Khodayar, H. Mannstein, K. Träumner, A. Wieser, and V. Wulfmeyer, 2011: Observation of Convection Initiation Processes with a Suite of State-of-the-Art Research Instruments during COPS IOP8b. COPS Special Issue of the Q. J. R. Meteorol. Soc. 137, 81–100, DOI:10.1002/qj.758.CrossRefGoogle Scholar
  3. 3.
    Brockhaus, P., D. Lüthi, and C. Schär, 2008. Aspects of the Diurnal Cycle in a Regional Climate Model. Meteorol. Z., 17 (4), 433–443.CrossRefGoogle Scholar
  4. 4.
    Chen, F., and J. Dudhia, 2001a. Coupling an advanced landsurface/ hydrology model with the penn state NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon Weather Rev, 129, 569–585.CrossRefGoogle Scholar
  5. 5.
    Chen, F. and J. Dudhia,2001b. Coupling an advanced landsurface/ hydrology model with the penn state NCAR MM5 modeling system. Part II: Preliminary model validation. Mon Weather Rev, 129, 587–604.CrossRefGoogle Scholar
  6. 6.
    Corsmeier, U., N. Kalthoff, Ch. Barthlott, A. Behrendt, P. Di Girolamo, M. Dorninger, F. Aoshima, J. Handwerker, Ch. Kottmeier, H. Mahlke, St. Mobbs, G. Vaughan, J. Wickert, and V. Wulfmeyer, 2011: Driving processes for deep convection over complex terrain: A multi-scale analysis of observations from COPS-IOP 9c. COPS Special Issue of the Q. J. R. Meteorol. Soc. 137, 137–155, DOI:10.1002/qj.754.Google Scholar
  7. 7.
    Christensen, J.H., and O.B. Christensen, 2007: A summary of the PRUDENCE model projections of changes in European climate by the end of this century. Climatic Change 81, 7–30.CrossRefGoogle Scholar
  8. 8.
    Christensen, J.H., T.R. Carter, M. Rummukainen and G. Amanatidis, 2007: Evaluating the performance and utility of regional climate models: the PRUDENCE project. Climatic Change 81, 1–6.CrossRefGoogle Scholar
  9. 9.
    Dee, D.P. et al., 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597.CrossRefGoogle Scholar
  10. 10.
    Déqué, M., D.P. Rowell, D. Lüthi, F. Giorgi, J.H. Christensen, B. Rockel, D. Jacob, E. Kjellström, M. De Castro, and B. van den Hurk, 2007: An intercomparison of regional climate simulations for Europe: assessing uncertainties in model projections. Climatic Change 81, 53–70.CrossRefGoogle Scholar
  11. 11.
    Doherty, S.J., S. Bojinski, A. Henderson-Sellers, K. Noone, D. Goodrich, N.L. Bindoff, J.A. Church, K.A. Hibbard, T.R. Karl, L. Kajfez-Bogataj, A.H. Lynch, D.E. Parker, I.C. Prentice, V. Ramaswamy, R.W. Saunders, M.S. Smith, K. Steffen, T.F. Stocker, P.W. Throne, K.E. Trenberth, M.M. Verstraete, and F.W. Zwiers, 2009: Lessons learned from IPCC AR4: Scientific Developments Needed to Understand, predict and respond to climate change. Bull. Amer. Meteor. Soc., 90, 497–513.CrossRefGoogle Scholar
  12. 12.
    Ehret, U., E. Zehe, V.Wulfmeyer, K. Warrach-Sagi, J. Liebert, 2012: HESS Opinions - Should we apply Bias Correction to Global and Regional Climate Model Data? Hydrol. Earth Syst. Sci. Discuss. 9, 5355–5387.CrossRefGoogle Scholar
  13. 13.
    Feldmann, H., B. Früh, G. Schädler, H.-J. Panitz, K. Keuler, D. Jacob, and P. Lorenz, 2008. Evaluation of the Precipitation for South-western Germany from High Resolution Simulations with Regional Climate Models. Meteorologische Zeitschrift 17, 455–465.CrossRefGoogle Scholar
  14. 14.
    Früh, B., H. Feldmann, H.-J. Panitz, G. Schädler, D. Jacob, P. Lorenz, and K. Keuler, 2010: Determination of precipitation return values in complex terrain and their evaluation. J. Climate 23, 2257–2274. doi: 10.1175/2009JCLI2685.1.CrossRefGoogle Scholar
  15. 15.
    Giorgi, F., C. Jones, and G. Asrar, 2009: Addressing climate information needs at the regional level: The CORDEX framework. WMO Bulletin 58, 175–183.Google Scholar
  16. 16.
    Greve, P., K. Warrach-Sagi and V. Wulfmeyer, 2013: Evaluating Soil Water Content in a WRF-NOAH Downscaling Experiment. J. Applied Met. and Climatol., submitted.Google Scholar
  17. 17.
    IPCC, 2007: Climate change 2007: The physical science basis. Solomon, S., D. Qin, M. Manning, L. Chen, M. Marquis, K.B. Avery, M. Tignor, and H.L. Miller (eds.), Cambridge University Press, Cambridge, 996pp.Google Scholar
  18. 18.
    Jacob, D., L. Bähring, O.B. Christensen, J.H. Christensen, S. Hagemann, M. Hirschi, E. Kjellström, G. Lenderink, B. Rockel, C. Schär, S.I. Seneviratne, S. Somot, A. van Ulden, and B. van den Hurk, 2007: An intercomparison of regional climate models for Europe: Design of the experiments and model performance. PRUDENCE special issue, Climatic Change, 81, Supplement 1, May 2007.Google Scholar
  19. 19.
    Jaeger, E.B., I. Anders, D. Lüthi, B. Rockel, C. Schär, and S. I. Seneviratne, 2008: Analysis of ERA40-driven CLM simulations for Europe. Meteorol. Z. 17, 349–367.CrossRefGoogle Scholar
  20. 20.
    Morrison, H. and A. Gettelman, 2008: A new two-moment bulk stratiform cloud microphysics scheme in the Community Atmosphere Model, version 3 (CAM3). Part I: Description and numerical tests. J. Climate, 21, 3642–3659.Google Scholar
  21. 21.
    Schwitalla, T., H.-S. Bauer, V. Wulfmeyer, and F. Aoshima, 2011: High-resolution simulation over central Europe: Assimilation experiments with WRF 3DVAR during COPS IOP9c. Q. J. R. Meteorol. Soc. 137, 156–175, DOI:10.1002/qj.721.CrossRefGoogle Scholar
  22. 22.
    Skamarock, W.C., J.B. Klemp, J. Dudhia, D.O. Gill, D.M. Barker, M.G. Duda, X.-Y. Huang, W. Wang, and J.G. Powers, 2008: A description of the Advanced Research WRF version 3. NCAR Tech Note, TN-475 + STR, 113pp.Google Scholar
  23. 23.
    Thuburn, T.: Some conservation issues for dynamical cores of NWP and climate models. J. Comp. Phys., 227 (2008), 3715–3730.MathSciNetCrossRefMATHGoogle Scholar
  24. 24.
    Richter D. (1995) Ergebnisse methodischer Untersuchungen zur Korrektur des systematischen Messfehlers des Hellmann-Nie-derschlagsmessers. Berichte des Deutschen Wetterdienstes 194: 93 ppGoogle Scholar
  25. 25.
    Vautard, R., A. Gobiet, D. Jacob, M. Belda, A. Colette, M. Deque, J. Fernandez, M. Garcia-Diez, K. Goergen, I. Guettler, T. Halenka, K. Keuler, S. Kotlarski, G. Nikulin, M. Patarcic, M. Suklitsch, C. Teichmann, K. Warrach-Sagi, V. Wulfmeyer and P. Yiou, 2013: The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project, Climate Dynamics, 10.1007/s00382-013-1714-z.Google Scholar
  26. 26.
    Warrach-Sagi, K., T. Schwitalla, V. Wulfmeyer and H.-S. Bauer, 2013: Evaluation of a CORDEX-Europe simulation with WRF: precipitation in Germany, Climate Dynamics, DOI 10.1007/s00382-013-1727-7Google Scholar
  27. 27.
    WMO, 2010: Strategic plan for implementation of WMO’s World Weather Research Programm 2009–2017. World Meteorological Organization, Geneva, Switzerland. Available online at: http://www.wmo.int/pages/prog/arep/wwrp/new/documents/final_WWRP_SP_6_Oct.pdf.
  28. 28.
    Wulfmeyer, V., A. Behrendt, Ch. Kottmeier, U. Corsmeier, C. Barthlott, G.C. Craig, M. Hagen, D. Althausen, F. Aoshima, M. Arpagaus, H.-S. Bauer, L. Bennett, A. Blyth, C. Brandau, C. Champollion, S. Crewell, G. Dick, P. Di Girolamo, M. Dorninger, Y. Dufournet, R. Eigenmann, R. Engelmann, C. Flamant, T. Foken, T. Gorgas, M. Grzeschik, J. Handwerker, C. Hauck, H. Höller, W. Junkermann, N. Kalthoff, C. Kiemle, S. Klink, M. König, L. Krauss, C.N. Long, F. Madonna, S. Mobbs, B. Neininger, S. Pal, G. Peters, G. Pigeon, E. Richard, M.W. Rotach, H. Russchenberg, T. Schwitalla, V. Smith, R. Steinacker, J. Trentmann, D.D. Turner, J. van Baelen, S. Vogt, H. Volkert, T. Weckwerth, H. Wernli, A. Wieser, and M. Wirth, 2011: The Convective and Orographically Induced Precipitation Study (COPS): The Scientific Strategy, the Field Phase, and First Highlights. COPS Special Issue of the Q. J. R. Meteorol. Soc. 137, 3–30, DOI:10.1002/qj.752.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Kirsten Warrach-Sagi
    • 1
  • Thomas Schwitalla
    • 1
  • Hans-Stefan Bauer
    • 1
  • Volker-Wulfmeyer
    • 1
  1. 1.Institut für Physik und MeteorologieUniversität HohenheimStuttgartGermany

Personalised recommendations