Articles | Volume 23, issue 14
https://doi.org/10.5194/bg-23-4967-2026
https://doi.org/10.5194/bg-23-4967-2026
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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Cited articles

Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. 
Bendtsen, J., Vives, C. R., and Richardson, K.: Primary production in the North Atlantic estimated from in situ water column data observed by Argo floats and remote sensing, Front. Mar. Sci., 10, https://doi.org/10.3389/fmars.2023.1062413, 2023. 
Bittig, H. C., Steinhoff, T., Claustre, H., Fiedler, B., Williams, N. L., Sauzède, R., Körtzinger, A., and Gattuso, J.-P.: An Alternative to Static Climatologies: Robust Estimation of Open Ocean CO2 Variables and Nutrient Concentrations From T, S, and O2 Data Using Bayesian Neural Networks, Front. Mar. Sci., 5, https://doi.org/10.3389/fmars.2018.00328, 2018. 
Bock, N., Cornec, M., Claustre, H., and Duhamel, S.: Biogeographical Classification of the Global Ocean From BGC-Argo Floats, Global Biogeochem. Cy., 36, e2021GB007233, https://doi.org/10.1029/2021GB007233, 2022. 
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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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