Improving a precipitation nowcasting algorithm based on the SWAN system and related application assessment

In order to improve the capability of precipitation nowcasting of the SWAN (Severe Weather Automatic Nowcasting) operational system, research on the improvement and evaluation of precipitation nowcasting algorithms is carried out, and a new QPF (Quantitative Precipitation Forecast) module is implemented. Firstly, minute rainfall observations are used to increase the frequency of QPE (Quantitative Precipitation Estimation) correction and a correction technology based on rain clusters is proposed to improve the rainfall field. The echo motion vector is then optimized by DIS (Dense Inverse Search) optical flow technology. Finally, precipitation nowcasting is produced by both the improved rainfall field and the optimized echo extrapolation vector. Through the national 1 km resolution echo and precipitation nowcasting test evaluation and case analysis in July 2021, it is found that: (1) The optimized echo motion vector based on DIS optical flow technology can capture different scales of echo motion. The results have better consistency and smoothness, which leads to an improvement of extrapolation. (2) Compared with the SWAN operational system, the TS score of the new QPF module is relatively improved by more than 50% in the 0—1 h forecast, and the bias is much closer to 1; in the 1—2 h forecast, except for heavy rainfall like that of 20 mm/h, the TS score increases by about 20%, and the bias decreases by 1—3. In summary, the proposed QPF module based on the SWAN algorithm development kit has significantly improved the forecast skill compared to the SWAN in both 0—1 h and 1—2 h leading time, and can be applied to operational nowcasting directly.