A New Approach for Estimating Salinity in the Southwest Atlantic and Its Application in a Data Assimilation Evaluation Experiment

Abstract

AbstractA new method for generating synthetic salinity (SS) profiles in the Southwest Atlantic was developed and applied in data assimilation experiments. This method was based on the smallest integrated values of root mean square deviation (RMSD)—with respect to observations—to infer salinity through climatological data and by regressive methods on temperature (T) using a five‐order polynomial function (P5). In the 14 delimited subregions, the averaged RMSD of P5 was 45% smaller than interpolated climatological data. However, climatological salinity presented better results in the first top layers while P5 presented smaller errors in higher depths. Therefore, by joining the best that P5 and climatology may offer, a new hybrid approach was used to generate SS based on T from XBT profiles. The SS would allow more T profiles to be employed in the Oceanographic Modeling and Observation Network (REMO) data assimilation system, called RODAS, into the Hybrid Coordinate Ocean Model (HYCOM). The use of SS estimates has potential to improve model outputs, in which the presence of the T‐S pair is quite necessary. Three integrations were performed: one run without assimilation (FREE), one assimilating sea surface temperature, Argo profilers, and sea level anomaly (RODAS) and one similar to RODAS, but with added XBTs with SS (RODAS_XBT). The inclusion of XBT data in the HYCOM + RODAS system improved the position and magnitude of the Brazil Current (BC). It was shown that SS is feasible for producing ocean reanalysis and initial conditions for ocean forecast systems requiring very low computational cost.