Assessing the extended-range predictability of the ocean model HYCOM with the REMO ocean data assimilation system (RODAS) in the South Atlantic

Abstract

ABSTRACT The Brazilian Oceanographic Modeling and Observation Network (REMO, acronym for ‘Rede de Modelagem e Observação Oceanográfica’ in Portuguese) has developed the REMO Ocean Data Assimilation System (RODAS). It is based on an Ensemble Optimal Interpolation scheme applied into the Hybrid Coordinate Ocean Model (HYCOM). This study aims to investigate the extended-range predictability of the HYCOM + RODAS System over the western South Atlantic by using its analyses as initial condition for 48 hindcasts, each covering 30 days. The outputs were compared to persistence (no change from the initial condition) and to a model free run. The hindcasts had the lowest root mean square difference (RMSD) and highest correlation of sea surface temperature (SST) and sea level anomaly (SLA) at all lead times. By the 30th day, persistence RMSD reached 1.09°C and 0.08 m for SST and SLA, respectively, while the hindcast RMSD reached 0.46°C and 0.05 m. The free run RMSD was almost constant with an average of 0.88°C and 0.13 m. In the subsurface, hindcast RMSD increase was even lower. The results suggest that HYCOM + RODAS predictive skill extends for more than a month and the thermohaline state of the ocean was consistently improved with respect to the free model run.