SMOS salinity in the subtropical north Atlantic salinity maximum: 1. Comparison with Aquarius and in situ salinity

• Published in: Journal of Geophysical Research: Oceans
• Main Authors: Hernandez, Olga, Boutin, Jacqueline, Kolodziejczyk, Nicolas, Reverdin, Gilles, Martin, Nicolas, Gaillard, Fabienne, Reul, Nicolas, Vergely, J. L.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Amer Geophysical Union 2014
• Subjects: SMOS; salinity; remote sensing; subtropical North Atlantic; North Atlantic
• Online Access: https://archimer.ifremer.fr/doc/00210/32150/34082.pdf; https://doi.org/10.1002/2013JC009610; https://archimer.ifremer.fr/doc/00210/32150/

Sea surface salinity (SSS) measured from space by the Soil Moisture and Ocean Salinity (SMOS) mission is validated in the subtropical North Atlantic Ocean. 39 transects of ships of opportunity equipped with thermosalinographs (TSG) crossed that region from 2010 to 2012, providing a large database of ground truth SSS. SMOS SSS is also compared to Aquarius SSS. Large seasonal biases remain in SMOS and Aquarius SSS. In order to look at the capability of satellite SSS to monitor spatial variability, especially at scales less than 300 km (not monitored with the Argo network), we first apply a monthly bias correction derived from satellite SSS and In Situ Analysis System (ISAS) SSS differences averaged over the studied region. Ship SSS averaged over 25 km is compared with satellite and ISAS SSS. Similar statistics are obtained for SMOS, Aquarius and ISAS products (root mean square error of about 0.15 and global correlation coefficient r of about 0.92). However, in the above statistics, SSS varies due to both large scale and mesoscale (here, for scales around 100 km) variability. In order to focus on mesoscale variability, we consider SSS anomalies with respect to a monthly climatology. SMOS SSS and Aquarius SSS anomalies are more significantly correlated (r > 0.5) to TSG SSS anomaly than ISAS. We show the effective gain of resolution and coverage provided by the satellite products over the interpolated in situ data. We also show the advantage of SMOS (r=0.57) over Aquarius (r=0.52) to reproduce SSS mesoscale features.