Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 18
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

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Revised manuscript under review for WES
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Cited articles

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Avgoustoglou, E., Carmona, I., Voudouri, A., Levi, Y., Will, A., and Bettems, J.: 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, b, c, d, e
Bellprat, O., Kotlarski, S., Lüthi, D., and Schär, C.: Objective calibration of regional climate models, J. Geophys. Res.-Atmos., 117, https://doi.org/10.1029/2012JD018262, 2012. a, b, c, d, e, f
Bellprat, O., Kotlarski, S., Lüthi, D., Elía, R., Frigon, A., Laprise, R., and Schär, C.: Objective Calibration of Regional Climate Models: Application over Europe and North America, J. Climate, 29, 151211135749001, https://doi.org/10.1175/JCLI-D-15-0302.1, 2015. a
Broyden, C. G.: The Convergence of a Class of Double-Rank Minimization Algorithms 2. The New Algorithm, IMA J. Appl. Math., 6, 222–231, https://doi.org/10.1093/imamat/6.3.222, 1970. a
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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.
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