Meetings: Documents

SMOS Salinity: A New View of the Ocean Surface
[03-Dec-12] Boutin, J., Martin, N., Reverdin, G P., and Yin, X.
Presented at the 2012 AGU Fall Meeting
The ESA/SMOS (European Space Agency/Soil Moisture and Ocean Salinity) satellite mission provides measurements of the Sea Surface Salinity (SSS) using L-band interferometric radiometry since end of 2009. It is the first time that this technology is used for measuring SSS from space, providing global ocean coverage every 3 to 5 days and a spatial resolution of up to 40km.
In this presentation, we first assess the accuracy of the SMOS SSS recently reprocessed by ESA (version 5), and then illustrate the additional information these new satellite products bring, with respect to in situ measurements, for ocean surface processes studies.
At global scale, the spatial variability of SMOS SSS is in relatively good agreement with the one derived from traditional in situ measurements. In tropical and subtropical regions, the rms error of SMOS SSS averaged over 10 days and 100x100km2 with respect to ARGO SSS is on the order of 0.3-0.4.
On monthly average, SMOS SSS are systematically fresher than ARGO SSS in the tropical Pacific Intertropical Convergence Zone. We demonstrate that this mean difference is due to SMOS SSS freshening correlated with rainy events. Since satellite L-band radiometers sense salinity in the first centimetre of the sea surface while ARGO upper salinity are measured at about 5m depth, this effect is likely to be partly a salinity stratification effect between 1cm and 5m depth, an important feature for air-sea interactions studies. We will discuss this hypothesis in view of the salinity variability recently sampled in situ in the upper 50cm of the sea surface by surface autonomous drifters.
With respect to existing in situ measurements, SMOS provides a much better synoptic coverage of the ocean surface at the expense of the SSS spatial resolution and accuracy. We will show some examples of frontal regions where SMOS SSS provides new information about SSS variability.