
Enhancements on the latitudinal and seasonal bias corrections in the SMOS Debiased non-Bayesian Sea Surface Salinity retrieval
Author(s) -
A. Garcia-Espriu,
E. Olmedo,
V. Gonzalez-Gambau,
C. Gonzalez-Haro,
A. Turiel,
Y. Rey-Ricord,
E. Jeansou,
R. Sabia,
R. Crapolicchio,
R. Oliva
Publication year - 2025
Publication title -
ieee journal of selected topics in applied earth observations and remote sensing
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 1.246
H-Index - 88
eISSN - 2151-1535
pISSN - 1939-1404
DOI - 10.1109/jstars.2025.3575473
Subject(s) - geoscience , signal processing and analysis , power, energy and industry applications
The Soil Moisture and Ocean Salinity (SMOS) satellite mission, launched in 2009, provides global measurements of Sea Surface Salinity (SSS) using L-band radiometry. In this paper, we revisit the algorithms to empirically correct the residual latitudinal and seasonal biases seen in the Debiased non-Bayesian (DNB) retrieval algorithm. We characterize these biases that affect the retrieved SSS and derive empirical corrections to mitigate them. We also revisit the filtering criteria for the new release of Brightness Temperature (v724). We compare the SSS retrieved by using different DNB filtering configurations with in-situ Argo measurements and discuss the importance of these corrections and the optimal configuration parameters for the generation of the Level 3 SSS maps. We observe significant improvements in the retrieved SSS when compared to the ones retrieved in the Barcelona Expert Center global SSS product v2
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