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

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

doi:10.5194/bg-23-4967-2026

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

Supplement

https://doi.org/10.5194/bg-23-4967-2026-supplement

Data sets

Argo float data and metadata from Global Data Assembly Centre (Argo GDAC) A. Povl et al. https://doi.org/10.17882/42182

Global Ocean Biogeochemistry Analysis and Forecast E.U. Copernicus Marine Service Information (CMEMS) https://doi.org/10.48670/moi-00170

Nutrient and carbon profiles vertical distribution E.U. Copernicus Marine Service Information (CMEMS) https://doi.org/10.48670/moi-00015

Global Ocean Colour (Copernicus-GlobColour), Bio-Geo-Chemical, L4 (monthly and interpolated) from Satellite Observations (1997-ongoing) E.U. Copernicus Marine Service Information (CMEMS) https://doi.org/10.48670/moi-00281

Global Ocean 3D Chlorophyll-a concentration, Particulate Backscattering coefficient, Particulate Organic Carbon, Downwelling Photosynthetic Available Radiation and downwelling irradiance at three different wavelengths (ED380, ED412 and ED490) E.U. Copernicus Marine Service Information (CMEMS) https://doi.org/10.48670/moi-00046

Model code and software

NEMO ocean engine G. Madec et al. https://doi.org/10.5281/zenodo.6334656

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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.