齐玥, 杨庆, 王科, 胡逸, 徐肖伟. 基于山区大气电场演变特征与雷电定位数据的雷电临近预警方法[J]. 高电压技术, 2024, 50(10): 4760-4771. DOI: 10.13336/j.1003-6520.hve.20240204
引用本文: 齐玥, 杨庆, 王科, 胡逸, 徐肖伟. 基于山区大气电场演变特征与雷电定位数据的雷电临近预警方法[J]. 高电压技术, 2024, 50(10): 4760-4771. DOI: 10.13336/j.1003-6520.hve.20240204
QI Yue, YANG Qing, WANG Ke, HU Yi, XU Xiaowei. Lightning Warning Methodology Based on Evolution Characteristics of Atmospheric Electric Field and Lightning Location Data in Mountainous Regions[J]. High Voltage Engineering, 2024, 50(10): 4760-4771. DOI: 10.13336/j.1003-6520.hve.20240204
Citation: QI Yue, YANG Qing, WANG Ke, HU Yi, XU Xiaowei. Lightning Warning Methodology Based on Evolution Characteristics of Atmospheric Electric Field and Lightning Location Data in Mountainous Regions[J]. High Voltage Engineering, 2024, 50(10): 4760-4771. DOI: 10.13336/j.1003-6520.hve.20240204

基于山区大气电场演变特征与雷电定位数据的雷电临近预警方法

Lightning Warning Methodology Based on Evolution Characteristics of Atmospheric Electric Field and Lightning Location Data in Mountainous Regions

  • 摘要: 由于高原山区雷暴活动具有尺度小、离散性强的特点,实现山区重点资源区域的雷电灾害准确预警存在较大困难。考虑到雷暴时空演变与地面大气电场特征的关联关系,提出了一种基于大气电场监测数据与实时雷电定位信息的山区雷电临近预警方法。通过分析典型高原山区不同雷暴发展情况下的大气电场演化特性,发现山区大气电场可作为雷电定位数据的补充源,充分表征雷云剧烈放电和雷暴临近发展的特征信息。在预警过程中,首先将大气电场形态学梯度提取的快速抖动、暂态突变特征与时空匹配的地闪活动特征输入堆叠稀疏自编码器网络模型,判断监测区域附近是否出现雷云放电迹象,再利用雷暴距离变化或者电场波形变化判断雷电活动的临近趋势,最后综合两者的结果完成半径15 km监测区域的雷电活动短时预警。在2023年云南山区雷雨季节的雷暴算例分析中,通过双源数据共同提取的山区雷暴活动预警特征的有效识别,可以实现预警准确率为90%,约44%的警报提前时间不小于30 min。

     

    Abstract: Due to the small scale and strong dispersion of lightning activity in plateau mountainous regions, it is difficult to implement accurate early warning of lightning disaster for key resource areas. Therefore, the correlation between the spatial and temporal evolution of thunderstorms and the characteristics of ground atmospheric electric field is taken into consideration, and a lightning warning methodology in mountainous regions based on ground atmospheric electric field apparatus and real-time lightning location system is proposed. By analyzing the evolution characteristics of atmospheric electric field under different thunderstorm development conditions in typical plateau mountainous regions, it is found that the atmospheric electric field can be used as a supplement to lightning location data, which fully represents the characteristics of severe discharge of thunderclouds and approaching development of thunderstorms. In the early warning process, the fast jitter and transient change characteristics from the morphological gradient of atmospheric electric field as well as the matched spatial and temporal distribution of cloud-to-ground lightning flash are input into the stacked sparse auto-encoder model, to indicate whether there is the existence of electrification in nearby thunderclouds. Secondly, the approaching trend of thunderstorm activity is determined by the thunderstorm distance variation or the electric field waveform pattern. Finally, the upcoming lightning activity in a localized area with a radius of 15 km is forecast based on the combined results. The case study in the mountainous regions of Yunnan province during the thunderstorm season of 2023 reveals that the effective identification of the early warning features of lightning activity extracted from the dual-source data can achieve the early warning accuracy of 90%, and about 44% of the warning time leads at least 30 min.

     

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