摘要
为实现机场雷暴的精准检测,设计一种基于大气电场的机场雷暴监测预警方法。通过大气电场仪采集电场大数据,并实施缺失数据填补、干扰数据去噪处理。利用经验模态分解法分解大气电场数据,实现大气电场数据的频率分布和幅值分布特征提取。基于多元回归模型构建预测模型,以特征为输入,预测未来一段时间内的雷暴强度值。参考雷暴强度等级划分表,实现不同程度的机场雷暴监测预警。结果表明:雷暴强度预测结果与实际结果之间的可决系数均在0.9以上,比较接近1,说明雷暴强度预测结果与实际情况较为接近,证明所研究方法的监测预警效果较好。
In order to realize the accurate detection of airport thunderstorm,an airport thunderstorm monitoring and early warning method based on atmospheric electric field is designed.It collects the big data of electric field through the atmospheric electric field instrument,fills in the missing data and denoises the interference data.The empirical mode decomposition method is used to decompose the atmospheric electric field data to extract the characteristics of frequency distribution and amplitude distribution of atmospheric electric field data.Based on the multiple regression model,a prediction model is constructed to predict the thunderstorm intensity in the future.It refers to the thunderstorm intensity classification table to realize different degrees of airport thunderstorm monitoring and early warning.The results show that the decisive coefficients between the thunderstorm intensity prediction results and the actual results are more than 0.9,which is close to 1,indicating that the thunderstorm intensity prediction results are close to the actual situation,which proves that the monitoring and early warning effect of the research method is better.
作者
谢克勇
吴凡
岳旭
陶昕宇
谢佳杏
XIE Ke-yong;WU Fan;YUE Xu;TAO Xin-yu;XIE Jia-xing(Meteorological Service Center of Jiangxi Province,Nanchang 330096 China)
出处
《自动化技术与应用》
2024年第3期66-69,共4页
Techniques of Automation and Applications
基金
江西省气象局重点项目(JX2021Z07)。
关键词
大气电场
机场雷暴
特征提取
监测预警
atmospheric electric field
airport thunderstorm
feature extraction
early warning monitoring
