The BGC-Argo floats: a new tool to validate ocean biogeochemical models

Alexandre Mignot1, Herve Claustre2, Gianpiero Cossarini3, Fabrizio D'Ortenzio4, Elodie Gutknecht5, Lamouroux Julien1, Paolo Lazzari3, Coralie Perruche6, Stefano Salon3, Raphaelle Sauzede7, Vincent Taillander8 and Anna Teruzzi3, (1)Mercator Océan International, Ramonville-Saint-Agne, France, (2)Sorbonne Université, CNRS, Laboratoire d’Océanographie de Villefranche (LOV), Villefranche-sur-mer, France, (3)National Institute of Oceanography and Applied Geophysics (OGS), Italy, (4)Observatoire Océanologique de Villefranche, Villefranche Sur Mer, France, (5)Mercator Océan International, Ramonville Saint Agne, France, (6)Mercator Océan International, Ramonville Saint-Agne, France, (7)Sorbonne Université, CNRS, Institut de la Mer de Villefranche (IMEV), Villefranche-sur-mer, France, (8)Villefranche Oceanographic Laboratory, Villefranche Sur Mer Cedex, France
Numerical models of ocean biogeochemistry are becoming a major tool to detect and predict the impact of climate change on marine resources. The validation of such models is strongly limited by the availability of data as it relies principally on comparison with climatologies, few permanent fixed oceanic stations and surface chlorophyll-a concentrations from satellite. Therefore, with these datasets, it is not possible to evaluate, how models represent many climate-relevant biogeochemical processes. These limitations have now been overcome with the availability of a large number of vertical profiles of light, pH, oxygen, nitrate and chlorophyll-a concentrations acquired by the Biogeochemical-Argo (BGC-Argo) floats network. Additionally, other key biogeochemical variables such as dissolved inorganic carbon and alkalinity, not measured by the floats, can be predicted by neural network methods from the float oxygen concentrations. In this presentation, we show an overview of the new validation capabilities that are now possible thanks to BGC-Argo floats observations.