Sea surface temperature retrieval using TRMM microwave imager satellite data in the South China Sea
The passive microwave TRMM Microwave Imager (TMI) sensor which is one of the payloads of the Tropical Rainfall Measurement Mission (TRMM) satellite was launched in 1997 by the National Aeronautics and Space Administration (NASA) and National Space Development Agency of Japan (NASDA). The TMI provide...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/1940/1/ISG04Prof.Ibrahim.pdf http://eprints.utm.my/id/eprint/1940/ http://www.voronoi.com/isg2013/Home.html |
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| Summary: | The passive microwave TRMM Microwave Imager (TMI) sensor which is one of the payloads of the Tropical Rainfall Measurement Mission (TRMM) satellite was launched in 1997 by the National Aeronautics and Space Administration (NASA) and National Space Development Agency of Japan (NASDA). The TMI provides daily maps, 3 day average, weekly and monthly binary data via internet that can be used to retrieve geophysical parameters such as sea surface temperature (SST), 10 meter surface wind speed using 11 GHz channel, 10 meter surface wind speed using 37 GHz channel, atmospheric water vapour, liquid cloud water and precipitation rates. The SST study over the South China Sea was carried out using the 10.7 GHz channel of the TMI. The advantage of using this data is that the SST can be measured through clouds that are nearly transparent on this channel. This is a distinct advantage over the traditional infrared SST observations that require a cloud-free field of view. In this study, multitemporal TMI binary data were processed using FORTRAN Programming Language to evaluate the SST variations with time over the study area. The 3-day, weekly and monthly binary files are similar to the daily TMI binary files. All data consists of six maps with grid size of 0.25o by 0.25o and each file can be read as a 1440, 320, 6 array. For the data processing, the data values fall between 0 and 250 that need to be scaled to obtain meaningful geophysical data. The TMI scanning system causes striping that contains 0 or invalid data. In-situ temperature values were taken at locations where useful satellite data are available i.e. no striping. Regression analysis was carried out using the SST from TMI data and in-situ data obtained from the Meteorological Department of Malaysia. The two-dimensional scatter plot between TMI data and in-situ data gives a R2 value of 0.92 and RMSE of 0.3oC. The SST during the north east monsoon period was slightly lower than the SST during the south west monsoon. The study shows that TMI satellite data can be used to derive SST over large areas of the sea. |
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