A comparison of satellite MCSST with ship measured SST in the North Indian Ocean

The evaluation of Multichannel Sea Surface Temperature (MCSST) weekly charts on a global scale produced by NOAA-NESDIS has been carried out for the North Indian Ocean. It is believed that the atmospheric conditions over the North Indian Ocean affect the estimation of Sea Surface Temperature (SST) fr...

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Bibliographic Details
Published inGeocarto international Vol. 12; no. 2; pp. 13 - 22
Main Authors Rao, M.V., Nath, A.Narendra, Suhasini, T.D., Nath, D.Jogendra, Rao, K.H.
Format Journal Article
LanguageEnglish
Published Taylor & Francis Group 01.06.1997
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Summary:The evaluation of Multichannel Sea Surface Temperature (MCSST) weekly charts on a global scale produced by NOAA-NESDIS has been carried out for the North Indian Ocean. It is believed that the atmospheric conditions over the North Indian Ocean affect the estimation of Sea Surface Temperature (SST) from remotely sensed data. Hence, an attempt has been made to validate the MCSSTs with the ship observations over the North Indian Ocean. The ship observations (Total 5,350) reported in the Indian Daily Weather Reports (IDWRs) were used for comparison with the MCSSTs with an assumption that the SST will not vary much during a week (< 0.5°C) in the North Indian Ocean. The total data set has been divided into seasonal (premonsoon, monsoon and post monsoon), time of the day (0000 0600 1200 and 1800 GMT) and regions (Arabian Sea, Bay of Bengal, Lower, Middle and Upper latitudes) to study the accuracies in estimation of MCSSTs over the North Indian Ocean. This division of the data set is made since the atmospheric water vapour content is highly variable over seasons, time of day and also different geographical regions. The results revealed that the accuracies of MCSSTs are better than 1°C (RMS deviation is ± 0.7) over the North Indian Ocean. It is concluded that the split window technique provides a good estimation of SSTs even in the regions where the atmospheric water vapour content is highly variable.
ISSN:1010-6049
1752-0762
DOI:10.1080/10106049709354581