Abstract
Aiming to achieve systematic ocean forecasting for the southeastern Brazilian coast, an incremental 4D-Var data assimilation system is applied to a regional ocean model focused mainly in the Santos Basin region. This implementation is performed within the scope of The Santos Basin Ocean Observing System (or Project Azul), a pilot project designed to collect oceanographic data with enough frequency and spatial coverage so to improve regional forecasts through data assimilation. The ocean modeling and data assimilation system of Project Azul is performed with the Regional Ocean Modeling System (ROMS). The observations used in the assimilation cycles include the following: 1-day gridded, 0.1° resolution SST from POES AVHRR; 1-day gridded, 0.3° composite of the MDT SSH from AVISO; and surface and subsurface hydrographic measurements of temperature and salinity collected with gliders and ARGO floats from Project Azul and from UK Met-Office EN3 project dataset. The assimilative model results are compared to forward model results and independent observations, both from remote sensing and in situ sources. The results clearly show that 4D-Var data assimilation leads to an improvement in the skill of ocean hindcast in the studied region.