一种暴雨回波识别算法研究

An Algorithm of Quantitative Identifying Rainstorm Echo

基于我国新一代多普勒天气雷达反射率因子资料,推导β中尺度暴雨回波最大降水量算法;利用该算法,开发暴雨回波客观定量识别产品,其实现步骤包括β中尺度回波系统的分割、跟踪和最大降水量计算等。选取湖北省江汉平原以东地区4次强降水过程,对武汉单站多普勒天气雷达暴雨识别结果进行暴雨、大暴雨和特大暴雨分级评估。评估结果表明,该产品对暴雨回波定量监测、预警有一定参考作用,暴雨、大暴雨、特大暴雨分级识别临界成功指数范围分别为0.73～0.85、0.63～0.71、0.20～0.52。

Based on the two-dimensional reflectivity factor data of a new generation Doppler radar, an algorithm of maximum precipitation for the β mesoscale heavy rain echo is studied. The algorithm is used to develop the automatic rainstorm recognition products, which include the goal segmentation and tracking of β mesoscale heavy rain echo and the calculation of maximum precipitation. By selecting four heavy rain events occurred in the eastern part of Hubei province, the grading estimations on the rainstorm recognition results from Wuhan Doppler weather radar are performed according to different precipitation level （more than 20mm, 45mm, 75mm）. The results indicate that the critical success index is in the range of 0.73-0.85, 0.63-0.71 and 0.20-0.52 respectively. The products play an important role in the rainstorm-echo quantitative monitoring and early warning.