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Sea Surface Skin Temperature Retrieval from FY-3C/VIRR

Authors :
Zhuomin Li
Mingkun Liu
Sujuan Wang
Liqin Qu
Lei Guan
Source :
Remote Sensing, Vol 14, Iss 6, p 1451 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

The visible and infrared scanning radiometer (VIRR) onboard the Fengyun-3C (FY-3C) meteorological satellite has 11 μm and 12 μm channels, which are capable of sea surface temperature (SST) observations. This study is based on atmospheric radiative transfer modeling (RTM) by applying Bayesian cloud detection theory and optimal estimation (OE) to obtain sea surface skin temperature (SSTskin) from VIRR in the Northwest Pacific. The inter-calibration of FY-3C/VIRR 11 μm and 12 μm brightness temperature (BT) is carried out using the Moderate Resolution Imaging Spectroradiometer (MODIS) as the reference sensor. Bayesian cloud detection and OE SST retrieval with the calibration BT data is performed to obtain SSTskin. The SSTskin retrievals are compared with the buoy SST with a temporal window of 1 h and a spatial window of 0.01°. The bias is −0.12 °C, and the standard deviation is 0.52 °C. Comparisons of the retrieved SSTskin with the AVHRR (Advanced Very High Resolution Radiometer) SSTskin from European Space Agency Sea Surface Temperature Climate Change Initiative (ESA SST CCI) project show the bias of 0.08 °C and the standard deviation of 0.55 °C. The results indicate that the VIRR SSTskin are consistent with AVHRR SSTskin and buoy SST.

Details

Language :
English
ISSN :
20724292
Volume :
14
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.47bc8528386f4165bc635ed57e6c38a5
Document Type :
article
Full Text :
https://doi.org/10.3390/rs14061451