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Assessment of seasonal and year-to-year surface salinity signals retrieved from SMOS and Aquarius missions in the Bay of Bengal

DRS at CSIR-National Institute of Oceanography

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Title Assessment of seasonal and year-to-year surface salinity signals retrieved from SMOS and Aquarius missions in the Bay of Bengal
 
Creator Akhil, V.P.
Lengaigne, M.
Durand, F.
Vialard, J.
Chaitanya, A.V.S.
Keerthi, M.G.
Gopalakrishna, V.V.
Boutin, J.
de Boyer, M.C.
 
Subject OCEANOGRAPHY AND LIMNOLOGY
METEOROLOGY AND CLIMATOLOGY
METEOROLOGY AND CLIMATOLOGY
OCEANOGRAPHY AND LIMNOLOGY
 
Description The Bay of Bengal (BoB) exhibits a wide range of sea surface salinity (SSS), with very fresh water induced by heavy monsoonal precipitation and river run-offs to the north, and saltier water to the south. This is a particularly challenging region for the application of satellite-derived SSS measurements because of the potential pollution of the SSS signal by radio frequency interference (RFI) and land-induced contamination in this semi-enclosed basin. The present study validates recent level-3 monthly gridded (1° × 1°) SSS products from Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions to an exhaustive in situ SSS product for the BoB. Current SMOS SSS retrievals do not perform better than existing climatologies. This is in stark contrast to Aquarius, which outperforms SMOS and available SSS climatologies everywhere in the BoB. While SMOS only captures the SSS seasonal evolution in the northern part of the Bay, Aquarius accurately captures the seasonal signal in the entire basin. The Aquarius product is also able to capture SSS non-seasonal anomalies, with an approximate correlation (r) of 0.75 with box-averaged in situ data in the northern, central, and western parts of the Bay. Aquarius can, thus, be confidently used to monitor large-scale year-to-year SSS variations in the BoB
 
Date 2016-04-11T07:29:58Z
2016-04-11T07:29:58Z
2016
 
Type Journal Article
 
Identifier International Journal of Remote Sensing, vol.37(5); 2016; 1089-1114
http://drs.nio.org/drs/handle/2264/4949
 
Language en
 
Rights The final and definitive form of the preprint has been published in the "International Journal Of Remote Sensing" © 2016 Taylor & Francis; "International Journal Of Remote Sensing" is available online at http://www.tandfonline.com with open URL of article : http://dx.doi.org/10.1080/01431161.2016.1145362. The term & condition associated with this preprint is at http://www.tandfonline.com/page/terms-and-conditions
 
Publisher Taylor & Francis