Evaluation and fusion of SST data from MTSAT and TMI in East China Sea, Yellow Sea and Bohai Sea in 2008 |
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| Authors: | Yumei Wu Hui Shen Xuesen Cui Shenglong Yang Wei Fan |
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| Institution: | 1, 1 Key Laboratory of Marine and Estuarine Fisheries, Ministry of Agriculture, East China Sea Fisheries Research Institute, Shanghai 200090, China 2 Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China |
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| Abstract: | Two typical satellite sea surface temperature (SST) datasets, from the Multi-functional Transport Satellite (MTSAT) and Tropical Rainfall Measuring Mission Microwave Imager (TMI), were evaluated for the East China Sea, Yellow Sea, and Bohai Sea throughout 2008. Most monthly-mean availabilities of MTSAT are higher than those of TMI, whereas the seasonal variation of the latter is less than that of the former. The analysis on the one-year data shows that the annual mean availability of MTSAT (61%) is greater than that of TMI (56%). This is mainly because MTSAT is a geostationary satellite, which achieves longer observation than the sun-synchronous TMI. The daily availability of TMI (28%–75%) is more constant than that of MTSAT (9%–93%). The signal of infrared sensors on MTSAT is easily disturbed on cloudy days. In contrast, the TMI microwave sensor can obtain information through clouds. Based on in-situ SSTs, the SST accuracy of TMI is superior to that of MTSAT. In 2008, the root mean square (RMS) error of TMI and MTSAT were 0.77 K and 0.84 K, respectively. The annual mean biases were 0.14 K (TMI) and -0.31 K (MTSAT). To attain a high availability of SSTs, we propose a fusion method to merge both SSTs. The annual mean availability of fusion SSTs increases 17% compared to MTSAT. In addition, the availabilities of the fusion SSTs become more constant. The annual mean RMS and bias of fusion SSTs (0.78 K and -0.06 K, respectively) are better than those of MTSAT (0.84 K and -0.31 K). |
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| Keywords: | satellite SST availability fusion root mean square bias |
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