摘要
上行雷(Upward Lightning,UL)因其突发性与破坏性,成为电力与高层建筑防雷中的关键挑战。传统识别方法在复杂气象条件下存在误报率高、识别率低等问题。提出一种基于雷暴环境特征与随机森林算法的UL识别方法,融合垂直速度、风切变、对流有效位能、整层可降水量等六类关键气象因子,建立多变量判别模型,并通过逐日留一交叉验证提升时间泛化能力。模型输出采用概率判别机制,结合ROC与多指标阈值曲线动态优化识别性能。实验基于我国某地区247个UL样本开展,结果显示模型的准确率(91%)、召回率(87%)、精确率(84%)、F1分数(85%)及AUC(0.93)等指标均表现优异。变量重要性分析揭示垂直速度与风切变为UL发生的主导因子。该方法可为UL预警建模提供高效、可解释的技术路径,具有显著工程应用价值。
Upward lightning(UL),due to its abrupt nature and destructive potential,poses a critical challenge in lightning protection for power systems and high-rise structures.Traditional identification methods often suffer from high false alarm rates and poor recognition accuracy under complex meteorological conditions.This study proposes a UL identification approach based on thunderstorm environmental features and the random forest algorithm.Six key meteorological variables—vertical velocity,wind shear,convective available potential energy(CAPE),precipitable water vapor(PWV),and others—are integrated into a multivariate classification model.A Leave-One-Day-Out cross-validation strategy is adopted to enhance temporal generalization capability.The model outputs probabilistic predictions,and its performance is further optimized through ROC curve analysis and multi-metric threshold tuning.Experiments conducted on 247 UL samples in a selected region of eastern China demonstrate the model’s strong performance,achieving an accuracy of 91%,recall of 87%,precision of 84%,F1 score of 85%,and AUC of 0.93.Variable importance analysis indicates that vertical velocity and wind shear are the dominant factors influencing UL occurrence.This approach provides an efficient and interpretable pathway for UL early warning modeling,offering substantial practical value in engineering applications.
作者
陈钰文
陈寅生
胡斯格
CHEN Yuwen;CHEN Yinsheng;HU Sige(Huadian Electric Power Research Institute Co.,Ltd.,Hangzhou 310030,China)
出处
《电气应用》
2025年第8期86-93,共8页
Electrotechnical Application
关键词
上行雷
雷暴环境
随机森林算法
逐日留一交叉验证
upward lightning
thunderstorm environment
random forest
leave-one-day-out cross validation
