DocumentCode :
42753
Title :
Sea Surface Salinity Estimation in the Bay of Bengal Using Multisatellite Measurements
Author :
Prakash, S. ; Gairola, R.M. ; Thapliyal, P.K.
Author_Institution :
Atmos. & Oceanic Sci. Group, Indian Space Res. Organ., Ahmedabad, India
Volume :
10
Issue :
3
fYear :
2013
fDate :
May-13
Firstpage :
525
Lastpage :
527
Abstract :
An algorithm is developed to estimate sea surface salinity (SSS) from the combined use of outgoing longwave radiation and freshwater flux derived by the First Generation Meteosat Visible and InfraRed Imager and Tropical Rainfall Measuring Mission data sets, respectively. A preliminary assessment of the estimated SSS is carried out in the Bay of Bengal during the southwest monsoon season (June-September). The monthly estimated SSS at 1° × 1° spatial resolution shows a significant correlation ranging from 0.83 to 0.93 and a root-mean-square error of 0.4- 0.5 psu with the in situ-based objectively analyzed SSS from the Japan Agency for Marine-Earth Science and Technology (JAMSTEC). The independent SSS estimated from the present algorithm would provide supplementary information to verify the spatiotemporal variability of SSS along with the comprehensive SSS maps by the two recent salinity satellite missions.
Keywords :
atmospheric humidity; mean square error methods; oceanographic regions; oceanographic techniques; seawater; Bay of Bengal; First Generation Meteosat Visible and InfraRed Imager; JAMSTEC; Japan Agency for Marine-Earth Science and Technology; SSS spatiotemporal variability; Tropical Rainfall Measuring Mission data sets; freshwater flux; multisatellite measurements; outgoing longwave radiation; root-mean-square error; salinity satellite missions; sea surface salinity estimation; southwest monsoon season; spatial resolution; Estimation; Ocean temperature; Sea measurements; Sea surface salinity; Spatial resolution; Freshwater flux; multisatellite measurements; outgoing longwave radiation (OLR); sea surface salinity (SSS); southwest monsoon;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
Publisher :
ieee
ISSN :
1545-598X
Type :
jour
DOI :
10.1109/LGRS.2012.2212176
Filename :
6302174
Link To Document :
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