Evaluation of sea surface temperature from FY-3C data

ABSTRACT

The daily sea surface temperatures (SSTs) derived from the visible and infrared scanning radiometer (VIRR) and microwave radiation imager (MWRI) aboard the Fengyun-3C (FY-3C) satellite are evaluated against the measurements of in-situ SST and Reynolds optimum interpolation daily 0.25° SST (OISST) products. Statistical results for 2015 reveal a mean bias ± standard deviation of error () for the daytime VIRR SST, night-time VIRR SST, daytime MWRI SST (MWRID), and night-time MWRI SST (MWRIN) of 0.5877 ± 1.3279°C, −0.4801 ± 1.2588°C, 0.6044 ± 3.9064°C, and 0.7653 ± 3.7307°C, respectively. According to the SST bias performance of each product for different periods and latitudes, it is clear that the SST biases of the VIRR products are the largest at low latitudes and are relatively lower at mid-high latitudes and that negative SST biases in the VIRR increase with varying time. Large abnormal SST biases from MWRI products occur in Time III (the 211th to 319th day of 2015), and the average values of the SST biases are 3.6010°C and 3.7822°C for the MWRID and MWRIN, respectively. We expect that our validation results for VIRR and MWRI products can help algorithm developers further enhance the accuracy of SST retrievals while also helping sensor designers improve the performance of sensors for the next generation of FY satellites.

Acknowledgments

The authors thank NESDIS/STAR, NOAA/NCDC, and NSMC of China for providing the in-situ and SST products in the study. This work was supported by the National Natural Science Foundation of China: [Grant Numbers 41476154, 41371385, and 41671401] and the National key research and development programme of China: [Grant Number 2016YFA0600304].

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China: [Grant Numbers 41476154, 41371385, and 41671401] and the National key research and development program of China: [Grant Number 2016YFA0600304]).