Objective analysis of SMOS and SMAP Sea Surface Salinity to reduce large scale and time dependent biases from low to high latitudes

Type Article
Date 2021-03
Language English
Author(s) Kolodziejczyk NicolasORCID4, Hamon Michel1, Boutin Jacqueline2, Vergely Jean-Luc3, Reverdin Gilles2, Supply Alexandre2, Reul NicolasORCID1
Affiliation(s) 1 : University of Brest, LOPS Laboratory, IUEM, UBO-CNRS-IRD-Ifremer, rue Dumont D’Urville, Plouzané, 29280, France
2 : Sorbonne University, LOCEAN Laboratory, CNRS-IRD-MNHM, Paris, France
3 : ACRI-ST, Guyancourt, France
4 : University of Brest, LOPS Laboratory, IUEM, UBO-CNRS-IRD-Ifremer, rue Dumont D’Urville, Plouzané, 29280, France
Source Journal Of Atmospheric And Oceanic Technology (0739-0572) (American Meteorological Society), 2021-03 , Vol. 38 , N. 3 , P. 405-421
DOI 10.1175/JTECH-D-20-0093.1
Keyword(s) Ocean, Salinity, In situ oceanic observations, Satellite observations, Surface observations, Interpolation schemes
Abstract

Ten years of L-Band radiometric measurements have proven the capability of satellite Sea Surface Salinity (SSS) to resolve large scale to mesoscale SSS features in tropical to subtropical ocean. In mid to high latitude, L-Band measurements still suffer from large scale and time systematic errors. Here, a simple method is proposed to mitigate the large scale and seasonal varying biases. First, an Optimal Interpolation (OI) using a large correlation scale (~500 km) is used to map independently Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) Level 3 data. The mapping is compared to the equivalent mapping of in situ observations to estimate the large scale and seasonal biases. A second mapping is performed on adjusted SSS at the scale of SMOS/SMAP spatial resolution (~45 km). This procedure merges both products, and increases the signal to noise ratio of the absolute SSS estimates, reducing the RMSD of in situ-satellite products by about 26-32% from mid to high latitude, respectively, in comparison to the existing SMOS and SMAP L3 products. However, in the Arctic Ocean, some issues on satellite retrieved SSS related to e.g. radio frequency interferences, land-sea contamination, ice-sea contamination remain challenging to reduce given the low sensitivity of L-Band radiometric measurements to SSS in cold water. Using the thermodynamic equation of state (TEOS-10), the resulting L4 SSS satellite product is combined with satellite-microwave SST products to estimate sea surface density, spiciness, haline contraction and thermal expansion coefficients. For the first time, we illustrate how useful are these satellite derived parameters to fully characterize the surface ocean water masses at large mesoscale.

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Kolodziejczyk Nicolas, Hamon Michel, Boutin Jacqueline, Vergely Jean-Luc, Reverdin Gilles, Supply Alexandre, Reul Nicolas (2021). Objective analysis of SMOS and SMAP Sea Surface Salinity to reduce large scale and time dependent biases from low to high latitudes. Journal Of Atmospheric And Oceanic Technology, 38(3), 405-421. Publisher's official version : https://doi.org/10.1175/JTECH-D-20-0093.1 , Open Access version : https://archimer.ifremer.fr/doc/00665/77702/