Using BGC-Argo Data to Disentangle the Physical and Biogeochemical Uncertainty in the Quality of Operational Biogeochemical Products
Through the definition of different model error metrics based on comparing physical and biogeochemical model variables with Argo and BGC-Argo data, our focus is to highlight the impact of the data assimilation of physical quantities over the quality of the biogeochemical ones. In particular, for a 1-year simulation of the Mediterranean Sea biogeochemistry at 1/24 degree resolution, we clustered float profiles characterised by different impacts of physical forcing over the biogeochemical variables quality, quantified according to the RMSD of specific fields (temperature, chlorophyll, nitrate). The clustered profile metrics have been then related to specific area and season, aiming to correlate the presence of peculiar physical processes to an increase or a decrease of RMSD between model and BGC-Argo. Resulting statistics may be translated into feedbacks to physical models in the perspective view of a collaborative evolution of coupled physical–biogeochemical systems, both in terms of process modelling or coupled data assimilation.