The complementary role of SMOS sea surface salinity observations for estimating global ocean salinity state

Abstract

Abstract Salinity is a key ocean state property, changes in which reveal the variation of the water cycle and the ocean thermohaline circulation. However, prior to this century, in situ salinity observations were extremely sparse, which decreased the reliability of simulations of ocean general circulation by ocean and climate models. In 2009, sea surface salinity (SSS) observations covered the global ocean via the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission, and several versions of global SSS products were subsequently released. How can these data benefit model performance? Previous studies found contradictory results. In this work, we assimilated SMOS‐SSS data into the LASG/IAP Climate system Ocean Model (LICOM) using the Ensemble Optimum Interpolation (EnOI) assimilation scheme. To assess and quantify the contribution of SMOS‐SSS data to model performance, several tests were conducted. The results indicate that the CECOS/CATDS 2010.V02 SMOS‐SSS product can significantly improve model simulations of sea surface/subsurface salinity fields. This study provides the basis for the future assimilation of SMOS‐SSS data for short‐range climate forecasting.