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

机译:基于模拟空气雷达反射率数据的雷暴识别算法研究

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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.
机译:在过去的几十年里,雷达反射数据已被广泛用于雷暴识别研究。已经开发出用于地面天气雷达的许多雷暴识别算法。但对于空气传播的天气雷达,由于数据的相对稀缺,雷暴识别研究不足,仍有很少有效的识别方法。机载气天雷达具有近距离检测的实现能力,但大多数现有的空气罗格没有扫描能力。本文提出了一种机载气象雷达体积扫描模式,在体积扫描中总共31个扇区扫描。并且基于该扫描策略建立了空气传播天气雷达的反射率数据仿真模型,然后使用地面的X波段雷达反射率数据作为输入以获得模拟的X波段机载雷达反射率数据。此外,本文研究了具有所提出的扫描模式的X波段机载雷达的雷暴识别算法。基于传统的SCI算法提出了一种改进的SCI(风暴电池识别)算法,其适用于S波段地基天气雷达。在模拟的空中雷达数据上进行的雷暴识别结果表明,该算法可以有效地识别成熟阶段和发展阶段的雷暴细胞。

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