Paper Info
Title
Sea Surface Skin Temperature Retrieval from FY-3C/VIRR
Abstract
The visible and infrared scanning radiometer (VIRR) onboard the Fengyun-3C (FY-3C) meteorological satellite has 11 mu m and 12 mu m 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 mu m and 12 mu m 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 degrees. The bias is -0.12 degrees C, and the standard deviation is 0.52 degrees 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 degrees C and the standard deviation of 0.55 degrees C. The results indicate that the VIRR SSTskin are consistent with AVHRR SSTskin and buoy SST.
Year
DOI
Venue
2022
10.3390/rs14061451
REMOTE SENSING
Keywords
DocType
Volume
FY-3C/VIRR, radiative transfer modeling, optimal estimation, Bayesian cloud detection, sea surface skin temperature
Journal
14
Issue
ISSN
Citations 
6
2072-4292
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Zhuomin Li100.34
Mingkun Liu202.37
Sujuan Wang300.68
Liqin Qu400.34
Lei Guan523.79