AVHRR SST retrieval using variation algorithm and evaluation

Chen Jingyang; Chen Yaodeng; Shi Chunxiang; Li Xu; Xu Bin

doi:10.3969/j.issn.0253-4193.2018.02.003

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Chen Jingyang, Chen Yaodeng, Shi Chunxiang, Li Xu, Xu Bin. AVHRR SST retrieval using variation algorithm and evaluation[J]. Haiyang Xuebao, 2018, 40(2): 30-42. doi: 10.3969/j.issn.0253-4193.2018.02.003

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Chen Jingyang, Chen Yaodeng, Shi Chunxiang, Li Xu, Xu Bin. AVHRR SST retrieval using variation algorithm and evaluation[J]. Haiyang Xuebao, 2018, 40(2): 30-42. doi: 10.3969/j.issn.0253-4193.2018.02.003

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AVHRR SST retrieval using variation algorithm and evaluation

doi: 10.3969/j.issn.0253-4193.2018.02.003

1.
Key Laboratory of Meteorological Disaster of Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China
2.
National Meteorological Information Center, Beijing 100081
3.
Research and Data Systems Corporation, NOAA Science Center, Maryland 20746-4304, USA

Received Date: 2017-01-22

Abstract

Abstract

METOP-A/AVHRR sea surface temperature (SST) retrieved by using variation algorithm. SST retrieval was done for one month. In this paper, the result of variation retrieval (VAR SST) was evaluated by the product which retrieved by using regression algorithm of the same sensor and satellite (GBL SST), OISST and the buoy observation. This evaluation was done in the global regional and the weather system active regional. According to the evaluation index, we know that VAR SST is better than GBL SST when they are compared with OISST and worse than it when they are compared with buoy observation. In addition, the VAR SST also improved the GBL SST shortcomings about time fluctuations. When the VAR SST and the GBL SST compared with OISST in different latitude zones, we discovered that the VAR SST, which with higher accuracy, is better than GBL SST in the low latitudes and the middle latitude of Southern Hemisphere. According to the research, variation algorithm can correct the atmospheric attenuation in satellite remote sensing more effectively and get a higher accurate SST, especially in the area of the complex weather system. That's because the atmospheric temperature and water vapor mixing ratio were considered in this algorithm.
- sea surface temperature,
- retrieval,
- variation algorithm,
- statistical regression,
- AVHRR

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References(30)

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