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Methodologies

We enter now in a new era of global SSS observing systems from space with the recent successfull launch of the ESA Soil Moisture and Ocean Salinity mission, and the future NASA Aquarius/SAC-D mission.  These new satellite SSS observing systems are as well complemented by an increased number of devices deployed in situ.

In Reul et al. 2009, we have moreover demonstrated that Sea Surface Salinity (SSS) in the Amazon Plume area
 can be already retrieved from Space combining the vertically polarized C and X-bands brightness temperature (Tbs)
data from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) satellite.
The difference dTv between the vertically polarized C and X-bands Tb's estimated at surface level is used in that
method to isolate SSS signatures, minimizing the competing sea surface roughness and temperature impacts. For
that purpose, we used the AMSR-E L1A TB antenna data that were corrected for atmospheric effects to estimate the C
and X-band emission in vertical polarization from the ocean surface. These atmospheric corrections were evaluated using
the radiative transfer forward model (RTM) given in AMSR algorithm (Wentz and Meissner [2000]) applied to the co-
incident AMSR-E Level2B water vapour, cloud liquid water and surface wind speed products. In addition, the Reynolds
et al. [2007]'s AVHRR/AMSR analyzed products were used to characterize the sea surface temperature. The result-
ing surface reflectivities at each frequency were then combined to estimate the difference dTv in surface brightness
temperature between 6.9 and 10.7 GHz vertical polarization channels. The latter dTb quantity includes the sum of two
contributions. The first one is the difference in the perfectly smooth surface ocean reflectivity between the two channels
(drflat) which only depends on the sea surface temperature and salinity through the differing dielectric constant at the
two frequencies. The second term is due to a possibly differing surface roughness impact on the reflectivity (drrough)
at the two frequencies. In the North Western Tropical Atlantic, we found in Reul et al. [2009] that drrrough ~ 0 in
the dominant wind conditions between 4 m/s and 10 m/s. The SSS retrieval methodology from the estimated
dTv thus follows. Model predictions of drflat were estimated using a low microwave frequency dielectric constant
model (Klein and Swift [1977]) applied to the SST fields and for arbitrary salinity values ranging from 0 to 40 psu.
The retrieved SSS along swath was then determined by minimizing the difference between the Klein and Swift [1977]'s
model prediction and the AMSR-E dTv's, assuming a negligible roughness impact on dTv. Swath retrieved SSS were
then mapped onto a 0.5° resolution grid, averaged over 15 days or 1 month periods and spatially smoothed by a 1° by
1° moving average. Comparison with coincident in situ sea surface salinity measurements (mainly from ARGO floats
and Thermo-salinograph data) reveal a root-mean square (rms) difference between all in situ and satellite observations of ~ 1.5 psu. The rms within +-2-psu bins extending from 19 to 39 psu was also evaluated: it decreases from about
3-5 psu at the lowest SSS down to about 1 psu, achieved for salinities higher than about 35 psu.

The demonstration was performed for the year 2003 in the North-Western Tropical Atlantic Ocean over the spatial domain
 bounded by latitudes between 20°S and 20° N and longitudes between 70° W and 20° W.
Due the Amazon Plume seasonal extent, this area is associated with seasonally varying very strong and large-scale
 horizontal SSS gradients. In warm waters, the latter SSS frontal zones were shown to be clearly detectable using AMSR-E C and X-band brightness temperature data, depsite a much weaker sensitivity to SSS than the SMOS and Aquarius L-band sensors.
 With this method, we are now in an excellent position to revisit the SSS observed in the warm seas of the tropical seas with a multi-year time series of excellent remote sensing and concurrent in situ observations.

This is presented here for two specific areas: the Tropical Atlantic Ocean and the North Indian Ocean.
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