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Satellite‐Based Sea Surface Salinity Designed for Ocean and Climate Studies

Boutin, J.; Reul, N.; Koehler, J.; Martin, A.; Catany, R.; Guimbard, S.; Rouffi, F.; Vergely, J. L.; Arias, M.; Chakroun, M.; Corato, G.; Estella‐Perez, V.; Hasson, A.; Josey, S. ORCID: https://orcid.org/0000-0002-1683-8831; Khvorostyanov, D.; Kolodziejczyk, N.; Mignot, J.; Olivier, L.; Reverdin, G.; Stammer, D.; Supply, A.; Thouvenin‐Masson, C.; Turiel, A.; Vialard, J.; Cipollini, P.; Donlon, C.; Sabia, R.; Mecklenburg, S.. 2021 Satellite‐Based Sea Surface Salinity Designed for Ocean and Climate Studies. Journal of Geophysical Research: Oceans, 126 (11). https://doi.org/10.1029/2021jc017676

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Abstract/Summary

Sea Surface Salinity (SSS) is an increasingly used Essential Ocean and Climate Variable. The Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active Passive (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. 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. They display large year-to-year seasonal variations over the 2010–2019 decade, sometimes by more than ±0.4 over large regions. The robust standard deviation of the monthly CCI SSS minus in situ Argo salinities is 0.15 globally, while it is at least 0.20 with individual satellite SSS fields. r2 is 0.97, similar or better than with original datasets. The correlation with independent ship thermosalinographs SSS further highlights the CCI data set excellent performance, especially near land areas. During the SMOS-Aquarius period, when the representativity uncertainties are the largest, r2 is 0.84 with CCI while it is 0.48 with the Aquarius original data set. SSS CCI data are freely available and will be updated and extended as more satellite data become available.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1029/2021jc017676
ISSN: 2169-9275
Date made live: 15 Mar 2022 13:10 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/532181

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