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Sea Surface Salinity (SSS) is an increasingly-used Essential Ocean and Climate Variable. The SMOS, Aquarius, and SMAP satellite missions all provide SSS measurements, with very different instrumental features leading to specific measurement characteristics. The Climate Change Initiative Salinity project (CCI+SSS) aims to produce a SSS Climate Data Record (CDR) that addresses well-established user needs based on those satellite measurements. To generate a homogeneous CDR, instrumental differences are carefully adjusted based on in-depth analysis of the measurements themselves, together with some limited use of independent reference data Boutin et al., 2021. An optimal interpolation in the time domain without temporal relaxation to reference data or spatial smoothing is applied. This allows preserving the original datasets variability. SSS CCI fields are well-suited for monitoring weekly to interannual signals, at spatial scales ranging from 50 km to the basin scale. In this poster, we review recent advances of the CCI+SSS phase 2 project and the performances of the last (version 4) CCI+SSS product which covers the 2010-2022 period. With respect to global CCI+SSS v3 dataset, CCI+SSS v4 dataset includes the following updates. According to several users recommendations, global fields are now on a rectangular 0.25grid, and polar fields on EASE polar grid are also delivered. The ice filtering has been refined (it was too strong in CCI v3). A correction for contamination by radio frequency interferences has been developed and applied around Samoa island, Barbados island and in the Gulf of Guinea. Latitudinal-seasonal corrections have been applied on SMOS, Aquarius and SMAP SSS. SSS changes related to SMOS direct models updates (wind, dielectric constant, rain) have also been taken into account. This leads to significant improvements at high latitudes, allowing to monitor the interannual SSS variability in the Barents Sea, or the spatio-temporal evolution of a fresh event west of Greenland in Fall 2021. In the tropics, we show that the RFI contamination correction allows to restore the interannual SSS variability related to ENSO which was completely masked by RFI contamination around the island of Samoa. We also illustrate how the CCI+SSS fields have been used to assess model results, at global scale with or without data assimilation (GLORYS model), and in the Amazone plume (NEMO-PISCES biogeochemical model). References Boutin, J., et al. (2021), Satellite-Based Sea Surface Salinity Designed for Ocean and Climate Studies, Journal of Geophysical Research: Oceans, 126(11), e2021JC017676, doi:https://doi.org/10.1029/2021JC017676. Gvaudan et al. (2022). Influence of the Amazon-Orinoco discharge interannual variability on the western tropical Atlantic salinity and temperature. Journal of Geophysical Research: Oceans, 127, e2022JC018495. https://doi.org/10.1029/2022JC018495
Boutin et al. (Fri,) studied this question.