Climate Dynamics

, Volume 40, Issue 1–2, pp 511–529 | Cite as

Regional climate modelling over complex terrain: an evaluation study of COSMO-CLM hindcast model runs for the Greater Alpine Region

  • Klaus Haslinger
  • Ivonne Anders
  • Michael Hofstätter


In this study the results of the regional climate model COSMO-CLM (CCLM) covering the Greater Alpine Region (GAR, 4°–19°W and 43°–49°N) were evaluated against observational data. The simulation was carried out as a hindcast run driven by ERA-40 reanalysis data for the period 1961–2000. The spatial resolution of the model data presented is approx. 10 km per grid point. For the evaluation purposes a variety of observational datasets were used: CRU TS 2.1, E-OBS, GPCC4 and HISTALP. Simple statistics such as mean biases, correlations, trends and annual cycles of temperature and precipitation for different sub-regions were applied to verify the model performance. Furthermore, the altitude dependence of these statistical measures has been taken into account. Compared to the CRU and E-OBS datasets CCLM shows an annual mean cold bias of −0.6 and −0.7 °C, respectively. Seasonal precipitation sums are generally overestimated by +8 to +23 % depending on the observational dataset with large variations in space and season. Bias and correlation show a dependency on altitude especially in the winter and summer seasons. Temperature trends in CCLM contradict the signals from observations, showing negative trends in summer and autumn which are in contrast to CRU and E-OBS.


Climate Research Unit Cold Bias Observational Dataset Precipitation Bias Altitude Dependence 
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.



The regional climate simulations described in this study were conducted within the framework of the RECLIP:CENTURY project, funded by the Austrian Climate Research Programme. The analysis of the simulation results was carried out in the course of the EVACLIM project, founded by the Austrian Federal Ministry of Science and Research. The authors would like to thank the COSMO-CLM community for providing access to and support for the model, as well as Klaus Keuler for his comments on our simulation results. The R DEVELOPMENT CORE TEAM is acknowledged for providing the statistics package “R”. Finally, the authors would like to thank two anonymous reviewers for their valuable comments which improved the manuscript substantially.


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Klaus Haslinger
    • 1
  • Ivonne Anders
    • 1
  • Michael Hofstätter
    • 1
  1. 1.Climate Research DepartmentZentralanstalt für Meteorologie und Geodynamik (ZAMG)ViennaAustria

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