CODAR data assimilation into an integrated ocean forecasting system for the Brazilian Southeastern coast

Abstract

Near real-time surface current measurements from shore-based high-frequency (HF) radars have increasingly proved to be an essential observation for ocean data assimilation (DA) into operational forecasting systems. For the first time in Brazil, a high-resolution operational system was developed assimilating HF ocean currents data. The system comprises a well known ocean model, the Regional Ocean Modeling System (ROMS), applied to the Southeastern Brazilian shelf and oceanic regions. The ROMS Restricted B-preconditioned Lanczos 4D-variational DA method is employed using real-time coastal radar, remote sensing, and in situ observations, and the DA solution is used as initial fields to produce hourly forecasts for the next two days. The performance of the system in providing accurate forecasts by using this source of initial condition (IC) was evaluated in an experiment in which multiple sources of IC were used. In situ and remote sensing data were used to assess the quality of predictions obtained in the forecasting experiments. The results indicate that the employed DA technique significantly reduced the misfit between model and assimilated observations, leading to improved forecast results. By using this IC, the system was capable to provide forecasts with errors reduced by up to 85%, 14%, and 12%, respectively for sea surface temperature, velocities, and heights, compared to forecasts based on global models. The system was also able to accurately predict the positioning and intensity of the Brazil Current flow and its spatiotemporal variability along the studied region.