线状中尺度对流系统自动识别

在使用动态模板法识别中尺度对流系统(Mesoscale Convective System,MCS)的算法中引入风暴单体识别跟踪算法(Strom Cell Identification and Tracking,SCIT),实现对MCS内部对流单体的定位,进一步计算出MCS的长宽比。利用该方法对20个多种类型中尺度天气过程进行处理,在选取不同识别阈值情况下对比评估动态模板法。结果表明:(1)动态模板函数、由SCIT得到的平均距离长宽比Wave和最大距离长宽比Wmax均能表征MCS长宽比,且在不同阈值情况下有较好的相关性;(2)动态模板函数与Wave和Wmax变化不一致的时刻是由于质心代表性不足和风暴单体较少引起的趋势变化波动较大造成;(3)综合分析结果表明动态模板函数法识别结果稳定可靠,与实际情况较为一致。

Automatic Identification of Linear Mesoscale Convective Systems

The SCIT (Strom Cell Identification and Tracking) algorithm is introduced by means of the dynamic template function method for automatically identifying the linear MCS to locate storm cells, further to calculate RLW (Ratio of Length to Width) of MCS. The method is used in more than 20 different types of convections cases with different thresholds. The results demonstrate that the dynamic template function, average RLW and maximum RLW from SCIT can present the linear status of MCS, which are well correlated in the case of different thresholds. The inconsistency is resulted from that the centroid has not enough representativeness and much less storms cells to cause large fluctuation in average RLW and maximum RLW. Comprehensive analysis results show that the dynamic template function method is more stable and reliable, and coincident with the actual situation.