Flash Cell Identification, Tracking and Nowcasting with Lightning Data

Lightning, accompanying with convective storms in the whole lifecycle, can reflect the development of storms effectively. The national lightning detection network makes it possible to get lightning location data instantly all over China, which would be highly valuable in convective system monitoring. A new method for flash cell identification, tracking and nowcasting is proposed. Using cloud-to-ground lightning location data over China, a new cluster algorithm of fast searching and density peaks identifying, is utilized to recognize the flash cells by clustered flashes. Time and area distribution characteristics of flashes are used in identification. Second, Kalman filtering is used to track the moving path of cells, considering cell spitting and merging conditions. Finally, based on the previous path, the linear moving path in next 60 min is predicted with Kalman filtering.lightning location data in 2013 are analyzed by this method. Doppler radar data are applied to evaluate its performance, which proves its effectiveness on identification and track for thunderstorm split and merge. The overall performance is as better as TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting) for thunderstorm nowcasting in 60 minutes, and even better from some aspects. The probability of detection of nowcasting for 10 min is about 0.7, about 0.6 for 30 min and 0.2 for 60 min, respectively. The probability of detection and critical success index decrease dramatically with time, and the false alarm rate increases rapidly in 60 min. All of those mean that the linear nowcasting would be more reliable in near time, and it is meaningful in 0-60 min forecast.One case is analyzed in detail, which shows that flashes only appear in deep convective systems that usually companies with severe weather. Furthermore, flashes disappears obviously in the dissipative stage of storms, which would be an indicator for predicting the end of convective systems.