4-9 September 2022, Bonn, Germany
EMS Annual Meeting Abstracts
Vol. 19, EMS2022-643, 2022, updated on 17 Apr 2023
https://doi.org/10.5194/ems2022-643
EMS Annual Meeting 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

The COPAT2 initiative of the CLM-Community: towards a recommended configuration of COSMO-CLM and ICON-CLM new model versions

Emmanuele Russo1, Christian Steger2, Beate Geyer3, Ronny Petrik3, Klaus Keuler4, Burkhardt Rockel3, Klaus Görgen5, Patrick Ludwig6, Hendrik Feldmann6, Mauro Sulis7, Bijan Fallah8, Heimo Truhetz9, Ha Hagemann3, Jan-Peter Schulz2, and Praveen Pothapakula10
Emmanuele Russo et al.
  • 1ETH Zurich, Institute for Atmospheric and Climate Science, Zurich, Switzerland (emmanuele.russo@env.ethz.ch)
  • 2Deutscher Wetterdienst (DWD), Offenbach, Germany
  • 3Helmholtz-Zentrum Hereon, Institute of Coastal Systems-Analysis and Modeling, Geesthacht, Germany
  • 4Brandenburg University of Technology, Cottbus, Germany
  • 5Research Centre Jülich (FZJ), Institute of Bio- and Geosciences (Agrosphere, IBG-3), Jülich, Germany
  • 6Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research, Karlsruhe, Germany
  • 7Luxembourg Institute of Science and Technology, Environmental Research and Innovation Department, Esch-sur-Alzette, Luxembourg
  • 8Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany
  • 9University of Graz, Wegener Center for Climate and Global Change, Graz, Austria
  • 10Goethe University, Institute for Atmospheric and Environmental Sciences, Frankfurt am Main, Germany

The structural uncertainty of a climate model is defined as the range of outcomes that can be obtained through different representations of physical processes of the climate system, the selection of different unconstrained parameter values and different choices for the numerical solution of underlying fundamental equations. Exploring the range of these outcomes with the goal of determining a model configuration that produces results in closer agreement with observational data is defined as model calibration or tuning.

In this study, the preliminary results of the Coordinated Parameter Testing 2 (COPAT2) initiative of the CLM-Community are presented. In COPAT2, volunteer members of the community join forces together, with the objective of testing and providing recommended configurations for the new and final version of COSMO-CLM (6.0), as well as for the newly released regional climate model ICON-CLM, for climate modeling applications over the European CORDEX domain. 

A series of sensitivity tests is performed in which various configurations of the models are explored. The aspects that are tested have been carefully selected, based on expert judgment. In the case of COSMO-CLM 6.0, the primary focus is on newly introduced and recently updated parameterizations and physical schemes. For ICON-CLM, these  tests are the first ever conducted with the climate version of the model and are based on the operational configuration and on information of experiments performed for the development of the NWP mode of ICON.

The simulations are conducted at a horizontal resolution of approximately 12 km over Europe, using ERA5 reanalysis data as boundary conditions. In a first step, a series of relatively short tests is conducted over a 7-year period, from 1979 to 1985. Successively, depending on the sensitivity of the model to the applied changes in its configuration, a sub-set of simulations is extended over a total period of 12 years. The results are systematically analyzed with an evaluation suite that has been further developed and extended for COPAT2. The standardized analysis and condensation of results in very few indices summarizing the models performance allow for an easy and fast comparison of the quality of the different simulations.  

Beside introducing preliminary results of the conducted sensitivity tests, an overview of the calibration strategy followed in COPAT2 will be presented, including information on the selected metrics, employed observational data sets and further details inherent to the ranking of the different experiments.  



How to cite: Russo, E., Steger, C., Geyer, B., Petrik, R., Keuler, K., Rockel, B., Görgen, K., Ludwig, P., Feldmann, H., Sulis, M., Fallah, B., Truhetz, H., Hagemann, H., Schulz, J.-P., and Pothapakula, P.: The COPAT2 initiative of the CLM-Community: towards a recommended configuration of COSMO-CLM and ICON-CLM new model versions, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-643, https://doi.org/10.5194/ems2022-643, 2022.

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