Nowcasting of cloud-to-ground lightning location and frequency based on a deep learning techniqueOA
Predicting lightning that can cause power grid trips is significant for disaster prevention.This paper integrates cloud-to-ground lightning detection,water vapor and infrared channel as well as channel differences from the Himawari satellite,to nowcast lightning locations and frequencies in Central China based on deep learning.The model utilized is Convolutional Gated Recurrent Unit with attention mechanisms.Unlike previous studies that typically predict lightning locations and probabilities,this study forecasts both lightning locations and frequencies.Evaluation of the model test set shows that(1)within a lead time of 0 to 120 min,the average probability of detection(POD)is 0.439 and the average critical success index(CSI)is 0.207;(2)as the lead time extends from 10to 120 min,the performance gradually declines,with the accuracy(ACC)decreasing from 0.993 to 0.987,POD decreasing from 0.586 to 0.371,false alarm rate(FAR)increasing from 0.543 to 0.771,CSI decreasing from 0.336to 0.132,and mean absolute error(MAE)increasing from 0.01 to 0.014;and(3)the model performs well for organized storms but faces challenges with isolated cells or new cells near the domain boundary.The constructed warm-season lightning nowcasting model for Central China is tested with a winter thunderstorm in Central China and a spring tornadic storm in South China that caused transmission line trip incidents.The model has strong generalization capabilities over time and space,providing practical value in mitigating lightning-induced power grid trips.
Fengquan Li;Jian Li;Shanqiang Gu;Yu Wang;Zhe Li;Lei Zhang;Ze Liu;Bingjie Bai;Zhibo Jiang
NARI Group Corporation Ltd.,Nanjing,China China Meteorological Administration Tornado Key Laboratory,Foshan,China Wuhan NARI Limited Liability Company,State Grid Electric Power Research Institute,Wuhan,China National Energy Key Laboratory of Lightning Disaster Detection,Early Warning and Safety Protection,Wuhan,China Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan,ChinaNARI Group Corporation Ltd.,Nanjing,China Wuhan NARI Limited Liability Company,State Grid Electric Power Research Institute,Wuhan,China National Energy Key Laboratory of Lightning Disaster Detection,Early Warning and Safety Protection,Wuhan,China Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan,ChinaNARI Group Corporation Ltd.,Nanjing,China Wuhan NARI Limited Liability Company,State Grid Electric Power Research Institute,Wuhan,China National Energy Key Laboratory of Lightning Disaster Detection,Early Warning and Safety Protection,Wuhan,China Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan,ChinaNARI Group Corporation Ltd.,Nanjing,China Wuhan NARI Limited Liability Company,State Grid Electric Power Research Institute,Wuhan,China National Energy Key Laboratory of Lightning Disaster Detection,Early Warning and Safety Protection,Wuhan,China Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan,ChinaNARI Group Corporation Ltd.,Nanjing,China Wuhan NARI Limited Liability Company,State Grid Electric Power Research Institute,Wuhan,China National Energy Key Laboratory of Lightning Disaster Detection,Early Warning and Safety Protection,Wuhan,China Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan,ChinaNARI Group Corporation Ltd.,Nanjing,China Wuhan NARI Limited Liability Company,State Grid Electric Power Research Institute,Wuhan,China National Energy Key Laboratory of Lightning Disaster Detection,Early Warning and Safety Protection,Wuhan,China Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan,ChinaNARI Group Corporation Ltd.,Nanjing,China Wuhan NARI Limited Liability Company,State Grid Electric Power Research Institute,Wuhan,China National Energy Key Laboratory of Lightning Disaster Detection,Early Warning and Safety Protection,Wuhan,China Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan,ChinaNARI Group Corporation Ltd.,Nanjing,China Wuhan NARI Limited Liability Company,State Grid Electric Power Research Institute,Wuhan,China National Energy Key Laboratory of Lightning Disaster Detection,Early Warning and Safety Protection,Wuhan,China Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan,ChinaNARI Group Corporation Ltd.,Nanjing,China Wuhan NARI Limited Liability Company,State Grid Electric Power Research Institute,Wuhan,China National Energy Key Laboratory of Lightning Disaster Detection,Early Warning and Safety Protection,Wuhan,China Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan,China
天文与地球科学
Lightning frequency nowcastingDeep learningConv-GRU-attentionGeneralization capabilitiesPower gridTornadic storm
《Atmospheric and Oceanic Science Letters》 2026 (3)
P.1-6,6
supported by a Hubei Provincial Natural Science Foundation Joint Fund for Innovation and Development project[grant number 2022CFD124]the China Meteorological Administration Tornado Key Laboratory[grant number TKL202305]。
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