LAUSR

Calculating the motion vectors based on the infrared observations can complement the gaps of the passive microwave and radar observations. So, it is an essential step in numerical weather models and other meteorological applications. FengYun-4A (FY4A) geosynchronous satellite was launched in 2016 by the Chinese government. Carrying on board the Advanced Geosynchronous Radiation Imager (AGRI), FY4A can provide instantaneous observations from visible to infrared wavelength. However, the ability of FY4A to capture precipitation motions still needs to be explored, and the optimal scale for generating the motion vectors remains unclear. In this study, a reasonable sliding window strategy is applied to calculate the correlation coefficients (CCs) between two image sequences to determine the motion vectors. Based on this, the China Merged Precipitation Analysis (CMPA) data are recognized as the true precipitation data and are compared with the 10.7- $\mu \text{m}$ observations of AGRI aboard FY4A. The results in August 2018 show that based on the quantified directions of the motion vectors between the CMPA and FY4A-TBB (the Temperature of Black Body from FY4A), the CC and root mean square error (RMSE) are about 0.64 and 2.1, respectively, which are acceptable at the resolution of 0.5°. The result indicates that FY4A can capture precipitation motions. Meanwhile, as the resolution becomes lower, the probability distributions of the motion vectors in FY4A-TBB are more similar to those in CMPA, and they become stable at 0.5°. Therefore, 0.5° is considered the optimal resolution to generate the motion vectors for FY4A-TBB. The study results have great potentials for precipitation estimate retrieval and fusion for FY4A and also FY4B.