Publications

Liu, X; Wang, Y; Huang, J; Yu, TL; Jiang, NH; Yang, J; Zhan, W (2022). Assessment and calibration of FY-4A AGRI total precipitable water products based on CMONOC. ATMOSPHERIC RESEARCH, 271, 106096.

Abstract
FengYun 4A (FY-4A) is the first flight unit of the second-generation geostationary meteorological satellite in China (FengYun 4 series, FY-4 series). The Advanced Geostationary Radiation Imager (AGRI) onboard it can provide high spatial resolution precipitable water vapor (PWV) products. This study used Global Navigation Satellite System (GNSS) observations from 230 ground-based GNSS stations within the Crustal Movement Observation Network of China (CMONOC) from March 1, 2019 to February 29, 2020 to obtain PWV, also called total precipitable water (TPW). The Chinese mainland was divided into 13 regions based on climate classifica-tion, latitude, and altitude, and GNSS PWV was used to verify the FY-4A AGRI TPW and make calibrations when necessary. The results reveal that the accuracy of FY-4A AGRI TPW shows significant spatial and temporal dif-ferences in mainland China. Overall, FY-4A AGRI TPW and GNSS PWV are strongly positively correlated over China, and the correlation coefficients (R) between the two PWV products are highest in autumn (0.78-0.972) while lowest in winter (0.556-0.956). FY-4A AGRI TPW is underestimated in most regions, and the mean bias (MB) values are higher in regions with high PWV content. The root means square error (RMSE) of FY-4A AGRI TPW in all regions are highest in summer (3.34-9.05 mm) and lowest in winter (0.87-3.83 mm). The accuracy of FY-4A AGRI TPW exhibits significant regional and seasonal differences, with higher R, RMSE, and MB in wet seasons and regions, while lower R, RMSE, and MB in dry seasons and regions. This study constructed the calibration model of FY-4A AGRI TPW was based on GNSS PWV in 13 regions. After calibration, the RMSEs can be reduced by 6.6% -32.1%, 5.1% -45%, 5.7% -31.6%, and 7.1% -30.8% in four seasons, respectively, and the MB mainly fluctuates around 0. The accuracy of generated FY-4A AGRI TPW is further improved on the basis of the high resolution.

DOI:
10.1016/j.atmosres.2022.106096

ISSN:
1873-2895