Publications

An, N; Shang, HZ; Lesi, W; Ri, X; Shi, C; Tana, G; Bao, YH; Zheng, ZJ; Xu, N; Chen, L; Zhang, P; Ye, LM; Letu, H (2023). A Cloud Detection Algorithm for Early Morning Observations From the FY-3E Satellite. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 61, 4104815.

Abstract
Accurate cloud detection via satellites is important for cloud radiative forcing estimation and disaster weather monitoring. Current polar-orbiting satellite cloud observations are limited during early morning orbit and contain notable uncertainty due to dimness measurements in visible bands. FY-3E\MERSI-LL is the first early morning orbit satellite worldwide and can realize global cloud observation under early morning scenarios. In this study, a dynamic threshold cloud detection algorithm is proposed based on the FY-3E\MERSI-LL infrared channel, combined with auxiliary data such as sea surface temperature (SST), land surface temperature (LST), snow cover mask (SCM), and terrain elevation. The algorithm can detect clouds against a complex land surface background, but faces classification difficulties over some plateau, high-latitude, and snow surface regions, especially during early morning observation periods. Compared to coincident Himawari-8 and Geostationary Operational Environmental Satellite (GOES)-16 cloud measurements in the Eastern and Western Hemispheres, respectively, our algorithm recognizes reasonable cloud distributions. Furthermore, Himawari-8 and GOES-16 cloud products are used for quantitative cloud algorithm evaluation. The results show that at low-middle latitudes (60 degrees N-60 degrees S), the average cloud and clear hit rates (HRs) during the various seasons are 73.24% and 76.46%, respectively, the cloud leakage and false alarm rates (FARs) are 14.46% and 8.15%, respectively, and the total accuracy (cloud and clear) is 77.33%. The algorithm performance is better over the ocean than over land. Ground site MPLCMASK products are also used to verify the FY-3E cloud results in middle- and high-latitude areas. This algorithm provides a cloud detection reference during early morning orbit based on infrared channels.

DOI:
10.1109/TGRS.2023.3304985

ISSN:
1558-0644