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

Petrov, Sergei; Will, Andreas; Geyer, Beate

doi: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

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Apr 2025	238	36	10	284
May 2025	112	32	12	156
Jun 2025	60	12	6	78
Jul 2025	76	28	12	116
Aug 2025	860	6	2	868
Sep 2025	3,321	23	16	3,360
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Nov 2025	145	21	15	181
Dec 2025	155	51	22	228
Jan 2026	277	60	26	363
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May 2026	224	52	8	284
Jun 2026	6	3	3	12

Cumulative views and downloads (calculated since 15 Apr 2025)

Month	HTML	PDF	XML	Total
Apr 2025	238	36	10	284
May 2025	112	32	12	156
Jun 2025	60	12	6	78
Jul 2025	76	28	12	116
Aug 2025	860	6	2	868
Sep 2025	3,321	23	16	3,360
Oct 2025	199	47	11	257
Nov 2025	145	21	15	181
Dec 2025	155	51	22	228
Jan 2026	277	60	26	363
Feb 2026	303	45	14	362
Mar 2026	237	71	13	321
Apr 2026	102	36	4	142
May 2026	224	52	8	284
Jun 2026	6	3	3	12

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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.