Climate Dynamics

, Volume 37, Issue 9–10, pp 1889–1907 | Cite as

COSMO-CLM2: a new version of the COSMO-CLM model coupled to the Community Land Model

  • Edouard L. DavinEmail author
  • Reto Stöckli
  • Eric B. Jaeger
  • Samuel Levis
  • Sonia I. Seneviratne


This study presents an evaluation of a new biosphere-atmosphere Regional Climate Model. COSMO-CLM2 results from the coupling between the non-hydrostatic atmospheric model COSMO-CLM version 4.0 and the Community Land Model version 3.5 (CLM3.5). In this coupling, CLM3.5 replaces a simpler land surface parameterization (TERRA_ML) used in the standard COSMO-CLM. Compared to TERRA_ML, CLM3.5 comprises a more complete representation of land surface processes including hydrology, biogeophysics, biogeochemistry and vegetation dynamics. Historical climate simulations over Europe with COSMO-CLM and with the new COSMO-CLM2 are evaluated against various data products. The simulated climate is found to be substantially affected by the coupling with CLM3.5, particularly in summer. Radiation fluxes as well as turbulent fluxes at the surface are found to be more realistically represented in COSMO-CLM2. This subsequently leads to improvements of several aspects of the simulated climate (cloud cover, surface temperature and precipitation). We show that a better partitioning of turbulent fluxes is the central factor allowing for the better performances of COSMO-CLM2 over COSMO-CLM. Despite these improvements, some model deficiencies still remain, most notably a substantial underestimation of surface net shortwave radiation. Overall, these results highlight the importance of land surface processes in shaping the European climate and the benefit of using an advanced land surface model for regional climate simulations.


Regional Climate Models Land Surface Models Land-atmosphere interactions European climate 



We are grateful to Daniel Luethi for his technical help regarding the simulation setup. We appreciated the valuable comments from Juergen Helmert and Hermann Asensio concerning TERRA_ML. We would like to thank the following FLUXNET PIs for providing access to their data: Michael Marek (CZBK1), Riccardo Valentini (ITAmp), André Granier (FRHes), Timo Vesala (FIHyy), Tuomas Laurila (FIKaa, FISod), Serge Rambal (FRPue), Stefano Minerbi (ITRen), Marc Aubinet (BEVie), and Martin Heimann (RUFyo). We also acknowledge the use of ferret and R for plots. The computing time was provided by the Swiss National Supercomputing Centre (CSCS). This research has been supported by the Competence Center Environment and Sustainability of the ETH Domain (CCES) through the MAIOLICA project. The National Center for Atmospheric Research is sponsored by the US National Science Foundation.


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Edouard L. Davin
    • 1
    Email author
  • Reto Stöckli
    • 1
    • 2
  • Eric B. Jaeger
    • 1
  • Samuel Levis
    • 3
  • Sonia I. Seneviratne
    • 1
  1. 1.Institute for Atmospheric and Climate ScienceETH ZurichZurichSwitzerland
  2. 2.Climate Services, Climate AnalysisMeteoSwissZurichSwitzerland
  3. 3.Climate and Global Dynamics DivisionNational Center for Atmospheric ResearchBoulderUSA

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