Abstract

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.

中文翻译：

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基于模拟机载气象雷达反射率数据的雷暴识别算法研究

摘要

在过去的几十年中，雷达反射率数据已广泛用于雷暴识别研究中。已经开发了许多用于地面气象雷达的雷暴识别算法。但是对于机载气象雷达，由于数据相对稀少，雷暴识别研究不足，有效的识别方法还很少。机载气象雷达具有近距离探测的实现能力，但是大多数现有的机载气象雷达都没有扫描能力。本文提出了一种机载气象雷达体量扫描模式，在该模式下，体量扫描中在31个海拔高度上总共进行了31次扇区扫描。基于这种扫描策略，建立了机载气象雷达的反射率数据仿真模型，然后将地面X波段雷达反射率数据用作输入，以获得模拟的X波段机载雷达反射率数据。此外，本文还针对所提出的扫描模式，研究了X波段机载雷达的雷暴识别算法。在传统的SCI算法的基础上，提出了一种适用于S波段地面气象雷达的改进的SCI算法。对模拟机载雷达数据进行雷暴识别的结果表明，该算法可以有效识别成熟期和发展期的雷暴细胞。在传统SCI算法的基础上，提出了一种改进的SCI算法，适用于S波段地面气象雷达。对模拟机载雷达数据进行雷暴识别的结果表明，该算法可以有效识别成熟期和发展期的雷暴细胞。在传统SCI算法的基础上，提出了一种改进的SCI算法，适用于S波段地面气象雷达。对模拟机载雷达数据进行雷暴识别的结果表明，该算法可以有效识别成熟期和发展期的雷暴细胞。