基于大气电场的雷电监测预警方法

利用大气电场强度数据设计了一种雷电监测预警方法，并对江西省南昌县2020年8月的一次雷电过程进行预测。首先对大气电场仪采集的电场数据进行去噪处理和缺失填补，然后利用经验模态分解法分解大气电场数据，得到大气电场数据的幅值和频率的分布特征，运用多元回归模型构建雷电预警模型，预测未来一段时间内的大气电场强度值。参考大气电场强度等级划分表，开展雷电监测预警。结果表明，运用模型预测的大气电场强度结果与实况之间的可决系数均在0.9以上，即大气电场强度预测结果与实况较为接近，该监测预警方法具有一定的可行性。

Thunderstorm monitoring and early warning based on the atmospheric electric field

In order to better carry out accurate lightning monitoring and early warning, a lightning monitoring and early warning method was designed based on the atmospheric electric field data of Nanchang County, Jiangxi province in August 2020. Firstly, the electric field data were denoised and interpolated. Then, the atmospheric electric field data were decomposed by the empirical mode decomposition method, so as to obtain the amplitude distribution and frequency distribution characteristics of the atmospheric electric field data. The lightning warning model was constructed by the multiple regression model to predict the lightning intensity value in the future period. Lightning monitoring and early warning were carried out by considering the classification table of lightning intensity. The results showed that there was a good correlation between the simulated results of lightning intensity and the actual results, with the correlation coefficient above 0.9. The predicted results of lightning intensity were closed to the actual situation, indicating that the monitoring and warning method was feasible.