Abstract

Subsurface salinity profiles in the Indian Ocean have been constructed using a combined empirical orthogonal function analysis technique and a nonlinear data-fitting algorithm, which is known as a genetic algorithm. The purpose is to establish a methodology to generate a 3-D structure of salinity using satellite-derived surface observations, which will be useful for assimilating in numerical models. This acquires greater significance in view of the upcoming satellite salinity missions. In this letter, we have been able to generate vertical profiles of salinity using a combination of sea surface temperature derived by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager onboard TRMM and sea surface salinity from Argo floats. The root mean square error of the retrieved salinity varies from less than 0.05 psu-78 at the surface to about 0.15 psu-78 at greater depths. A sensitivity study of the retrieval algorithm with the anticipated uncertainties in surface salinity from the European Soil Moisture and Ocean Salinity satellite has also been carried out

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