Thunderstorm identification algorithm research based on simulated airborne weather radar reflectivity data

In the past few decades, radar reflectivity data have been widely used in thunderstorm identification research. Many thunderstorm identification algorithms for ground-based weather radar have been developed. But for airborne weather radar, due to the relative scarcity of data, the thunderstorm identification research is insufficient and there are still few effective identification methods. Airborne weather radar has the realization capability of close-range detection, but most existing airborne weather radars do not have scanning capability. This paper proposes an airborne weather radar volume scan mode, under which there is a total of 31 sector scans at 31 elevations in a volume scan. And a reflectivity data simulation model of the airborne weather radar is established based on this scan strategy, then the ground-based X-band radar reflectivity data are used as input to obtain the simulated X-band airborne radar reflectivity data. Moreover, this paper studies a thunderstorm identification algorithm for the X-band airborne radar with the proposed scan mode. An improved SCI (storm cell identification) algorithm is proposed on the basis of the traditional SCI algorithm which is applicable to S-band ground-based weather radar. The results of thunderstorm identification carried out on the simulated airborne radar data show that the algorithm can effectively identify the thunderstorm cells in the mature stage and the developing stage.