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Article Dans Une Revue Ocean Modelling Année : 2019

Towards operational 3D-Var assimilation of chlorophyll Biogeochemical-Argo float data into a biogeochemical model of the Mediterranean Sea

Résumé

The emerging availability of Biogeochemical-Argo (BGC-Argo) float data creates new opportunities to combine models and observations in investigations of the interior structures and dynamics of marine ecosystems. An existing variational data assimilation scheme (3DVarBio) has been upgraded and coupled with the Copernicus Marine Environment Monitoring Service biogeochemical model of the Mediterranean Sea to assimilate BGC-Argo chlorophyll profile observations. Our results show that the assimilation of BGC-Argo float data is feasible. Moreover, the proposed data assimilation framework provides significant corrections to the chlorophyll concentrations and is able to consistently readjust the shapes of chlorophyll profiles during surface blooms occurring in winter vertically mixed conditions, and in the case of the summer deep chlorophyll maxima. Sensitivity analysis and diagnostic metrics have been applied to evaluate the impact of assimilation and the relevance of different factors of the 3DVarBio method. A key factor is the observation error that has been tuned on a monthly basis to incorporate the representation error. Different frequencies of the assimilation cycle have been tested: daily or 3-day assimilation fosters the highest skill performances despite the reduced impacts and the increase of computational burden. Considering the present size of the BGC-Argo Mediterranean network (about 15 floats) and the estimated non-homogeneous correlation radius length scale (15.2 km on average), the chlorophyll assimilation can constrain the phytoplankton dynamics along the whole water column over an area up to 10% of the Mediterranean Sea.
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hal-02376060 , version 1 (25-11-2020)

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G. Cossarini, L. Mariotti, L. Feudale, A. Mignot, S. Salon, et al.. Towards operational 3D-Var assimilation of chlorophyll Biogeochemical-Argo float data into a biogeochemical model of the Mediterranean Sea. Ocean Modelling, 2019, 133, pp.112-128. ⟨10.1016/j.ocemod.2018.11.005⟩. ⟨hal-02376060⟩
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