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Identification of Gale Weather with Doppler Weather Radar Data

机译:用多普勒天气雷达数据识别大雾天气

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With high temporal and spatial resolution, Doppler weather radars are important means for revealing structures and revolution of meso-micro scale weather processes. This article uses reflectivity characteristics to identify convective gale weather. 6 promising identification parameters are proposed (CR, VIL, DVIL, SWP, DCRH and SPEED), and an automated identification algorithm for convective gale is established based on fuzzy logic principles. 6 typical cases are used to obtain probability distribution characters based on the statistics of volume scan data, and then it is determined that CR, VIL, DVIL and SWP that have more concentrated probability densities are used as the input variables of the fuzzy logic technique for the identification of the convective gale. According to the statistics, these parameters can effectively identify convective gale. The algorithm identifies 150 from 174 gale wind events in 6 weather processes, with a POD probability 86.21%.
机译:具有高时空和空间分辨率,多普勒天气雷达是揭示中文微尺度天气过程的结构和旋转的重要手段。本文使用反思特性来识别对流大风天气。提出了有希望的识别参数(CR,VIL,DVIL,SWP,DCRH和速度),基于模糊逻辑原理建立了一种自动识别识别算法。 6典型情况用于获得基于体积扫描数据的统计数据的概率分布字符,然后确定具有更多集中概率密度的CR,VIL,DVIL和SWP作为模糊逻辑技术的输入变量对流大风的鉴定。根据统计数据,这些参数可以有效地识别对流大风。该算法在6天气过程中从174个大势风事件中识别150,POD概率为86.21%。

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