Biogeosciences
Biogeosciences
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Articles | Volume 23, issue 14
Articles | Volume 23, issue 14
https://doi.org/10.5194/bg-23-4967-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-23-4967-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 14
Research article
 | 
21 Jul 2026
Research article |  | 21 Jul 2026

High-dimensional parameter optimization of a biogeochemical model: a multi-variable BGC-Argo data assimilation approach

Quentin Hyvernat, Alexandre Mignot, Elodie Gutknecht, Giovanni Ruggiero, Coralie Perruche, Guillaume Samson, Raphaëlle Sauzède, Olivier Aumont, Hervé Claustre, and Fabrizio D'Ortenzio

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Short summary
We introduce an iterative Importance Sampling framework to optimize the Pelagic Interaction Scheme for Carbon and Ecosystem Studies (PISCES) model using 20 metrics from Biogeochemical-Argo data. Three strategies are compared: 29 main-effect, 66 including interaction effects, and all 95 parameters. All yield statistically indistinguishable skill gains, reducing error by 54–56 %. Optimizing all 95 parameters is recommended for comprehensive uncertainty quantification. The optimized set also improves skill in a three-dimensional regional simulation.
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