Linear Meta-Model optimization for regional  climate models (LiMMo version 1.0)

Petrov, Sergei; Will, Andreas; Geyer, Beate

doi:https://doi.org/10.5194/gmd-18-6177-2025

Articles | Volume 18, issue 18

https://doi.org/10.5194/gmd-18-6177-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-18-6177-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 18

Methods for assessment of models

|

22 Sep 2025

Methods for assessment of models |

| 22 Sep 2025

Linear Meta-Model optimization for regional climate models (LiMMo version 1.0)

Sergei Petrov, Andreas Will, and Beate Geyer

Data sets

ICON release 2024.07 ICON partnership (DWD, MPI-M, DKRZ, KIT, C2SM) https://doi.org/10.35089/WDCC/IconRelease2024.07

Fifth generation of ECMWF atmospheric reanalyses of the global climate H. Hersbach et al. https://doi.org/10.24381/cds.143582cf

E-OBS daily gridded meteorological data for Europe from 1950 to present derived from in-situ observations Copernicus Climate Change Service, Climate Data Store https://doi.org/10.24381/cds.151d3ec6

Monthly and 6-hourly total column water vapour over ocean from 1988 to 2020 derived from satellite observations Copernicus Climate Change Service https://doi.org/10.24381/cds.92db7fef

Model code and software

LiMMo (Linear Meta-Model optimization for regional climate model) Sergei Petrov and Andreas Will https://doi.org/10.5281/zenodo.14662292

SPICE (Starter Package for ICON-CLM Experiments) Burkhardt Rockel and Beate Geyer https://doi.org/10.5281/zenodo.10047021

Short summary

This study introduces a new method that helps improve the accuracy of climate models by automatically selecting the best parameters to match real-world observations. Instead of manually adjusting many parameters, the method uses a mathematical tool to find the most appropriate settings for the model. It can be especially helpful for researchers who introduce new physical parameters into climate models to assess their impact on model results and optimize them along with the old ones.