| Summary: | European Geosciences Union General Assembly 2014 (EGU2014), 27 april - 2 may 2014, Vienna, Austria.-- 2 pages Temperature-Salinity (TS) diagrams emphasize the mutual variability of ocean temperature and salinity values, relating them to the corresponding density. Canonically used in oceanography, they provide a means to characterize and trace ocean water masses. In [1], a first attempt to estimate surface-layer TS diagrams based on satellite measurements has been performed, profiting from the recent availability of spaceborne salinity data. In fact, the Soil Moisture and Ocean Salinity (SMOS, [2]) and the Aquarius/SAC-D [3] satellite missions allow to study the dynamical patterns of Sea Surface Salinity (SSS) for the first time on a global scale. In [4], given SMOS and Aquarius salinity estimates, and by also using Sea Surface Temperature (SST) from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA, [5]) effort, experimental satellite-based TS diagrams have been routinely derived for the year 2011. They have been compared with those computed from ARGO-buoys interpolated fields, referring to a customised partition of the global ocean into seven regions, according to the water masses classification of [6]. In [7], moreover, besides using TS diagrams as a diagnostic tool to evaluate the temporal variation of SST and SSS (and their corresponding density) as estimated by satellite measurements, the emphasis was on the interpretation of the geographical deviations with respect to the ARGO baseline (aiming at distinguishing between the SSS retrieval errors and the additional information contained in the satellite data with respect to ARGO). In order to relate these mismatches to identifiable oceanographic structures and processes, additional satellite datasets of ocean currents, evaporation/precipitation fluxes, and wind speed have been super-imposed. Currently, the main focus of the study deals with the exploitation of these TS diagrams as a prognostic tool to derive water masses formation areas. ...
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