Objective Analysis of SMOS and SMAP Sea Surface Salinity to Reduce Large-Scale and Time-Dependent Biases from Low to High Latitudes

Abstract Ten years of L-band radiometric measurements have proven the capability satellite sea surface salinity (SSS) to resolve large-scale-to-mesoscale SSS features in tropical subtropical ocean. In mid-to-high latitudes, still suffer from large-scale and time-varying errors. Here, a simple method is proposed mitigate First, an optimal interpolation using large correlation scale (~500 km) used map independently Soil Moisture Ocean Salinity (SMOS) Active Passive (SMAP) level-3 (L3) data. The mapping compared with equivalent situ observations estimate seasonal biases. A second performed on adjusted at SMOS/SMAP spatial resolution (~45 km). This procedure merges both products increases signal-to-noise ratio absolute estimates, reducing root-mean-square difference by about 26%–32% mid- high respectively, comparison existing SMOS SMAP L3 products. However, Arctic Ocean, some issues retrieved related to, for example, radio frequency interferences, land–sea contamination, ice–sea contamination remain challenging reduce given low sensitivity cold water. Using International Thermodynamic Equation Of Seawater—2010 (TEOS-10), resulting level-4 product combined satellite-microwave SST density, spiciness, haline contraction thermal expansion coefficients. For first time, we illustrate how useful these satellite-derived parameters are fully characterize ocean water masses mesoscale.