Using Multi-Source data to Remove Non-Precipitation Echoes in Weather Radar Data.

The correct distinction between precipitation echo (PE) and non-precipitation echo (NPE) of weather radar is one of the key steps in the quantitative precipitation estimation (QPE). Based on the high spatiotemporal resolution data of the Himawari-8 satellite and the precipitation data of the rain gauge, this paper proposes a fuzzy logic algorithm (FLA) to remove NPE in weather radar data through statistically analyzing the probability density distribution of the satellite temperature of black body (TBB) according to different precipitation scenarios. Two methods, i.e. the FLA and the threshold method (TM), are compared and analyzed by using the data in August 2019. The critical success index (CSI) score of the FLA is 0.056 higher than that of the TM (0.796 vs. 0.74), and the probability of detection (POD) score is 0.058 higher than that of the TM (0.802 vs. 0.744). The results show that the proposed method can effectively improve the quality of weather radar data.