Articles | Volume 19, issue 12
https://doi.org/10.5194/gmd-19-5439-2026
https://doi.org/10.5194/gmd-19-5439-2026
Methods for assessment of models
 | 
24 Jun 2026
Methods for assessment of models |  | 24 Jun 2026

Optimisation of ICON-CLM for the EURO-CORDEX domain: developments, sensitivities, tuning

Beate Geyer, Angelo Campanale, Evgenii Churiulin, Hendrik Feldmann, Klaus Goergen, Stefan Hagemann, Ha Thi Minh Ho-Hagemann, Muhammed Muhshif Karadan, Klaus Keuler, Pavel Khain, Divyaja Lawand, Patrick Ludwig, Vera Maurer, Sergei Petrov, Stefan Poll, Christopher Purr, Emmanuele Russo, Martina Schubert-Frisius, Jan-Peter Schulz, Shweta Singh, Christian Steger, Heimo Truhetz, and Andreas Will

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Cited articles

Anders, I., Brienen, S., Demuzere, M., Bucchignani, E., Ferrone, A., Geyer, B., Keuler, K., Lüthi, D., Mertens, M., Osterried, K., Panitz, H.-J., Saeed, S., Sørland, S. L., and Schulz, J.-P.: Evaluation Report COSMO-CLM5.0, Zenodo, https://doi.org/10.5281/zenodo.14515358, 2024. a
Andersson, A., Fennig, K., Klepp, C., Bakan, S., Graßl, H., and Schulz, J.: The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS-3, Earth Syst. Sci. Data, 2, 215–234, https://doi.org/10.5194/essd-2-215-2010, 2010. a
Andersson, A., Graw, K., Schröder, M., Fennig, K., Liman, J., Bakan, S., Hollmann, R., and Klepp, C.: Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS 4.0, Satellite Application Facility on Climate Monitoring (CM SAF) [data set], https://doi.org/10.5676/EUM_SAF_CM/HOAPS/V002, 2017. a
Avgoustoglou, E., Carmona, I., Voudouri, A., Levi, Y., Will, A., and Bettems, J.-M.: Calibration of COSMO model in the Central-Eastern Mediterranean area adjusted over the domains of Greece and Israel, Atmos. Res., 279, 106362, https://doi.org/10.1016/j.atmosres.2022.106362, 2022. a
Bechtold, P., Köhler, M., Jung, T., Doblas-Reyes, F., Leutbecher, M., Rodwell, M. J., Vitart, F., and Balsamo, G.: Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales, Q. J. Roy. Meteor. Soc., 134, 1337–1351, https://doi.org/10.1002/qj.289, 2008. a, b
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Short summary
Complex models in environmental science typically have a lot of tuning parameters, which has to be set by the users depending on the application. This study presents a new method of objective tuning of a huge number of parameters, by combining expert judgement with automated tuning called Linear Meta-Model optimisation (LiMMo). The method is successfully applied to the regional climate model named ICON (Icosahedral Non-hydrostatic)-CLM (Climate Limited-area Modelling) over Europe.
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