Researchers at the China National Energy Key Laboratory of Lightning Disaster Detection, Early Warning and Safety Protection and the Laboratory of Lightning Monitoring and Protection Technology of State Grid Corporation of China have developed a deep learning-based nowcasting lightning model. This research has been published in Atmospheric and Oceanic Science Letters.
Data for the deep learning model
The research team used wide-area lightning monitoring data from the State Grid Corporation of China and geostationary satellite imagery, combined with convolutional gated recurrent unit (Conv-GRU) networks and attention mechanism modules, to develop the lightning nowcasting model. As a result, the model can predict the location and frequency trends of organized thunderstorms, providing robust support for predicting lightning risks to power grids.
Optimized lightning prediction
“Our model not only accurately predicts where lightning will occur but also forecasts its frequency. It has shown excellent performance in predicting a winter thunderstorm in Central China and a spring-tornadic thunderstorm in South China,” said Dr Fengquan Li, the first author of the paper.
Dr Jian Li, the academic leader of the laboratory, said, “In the future, we plan to enhance the accuracy of our lightning prediction model by integrating more data sources related to lightning formation, and further optimizing the model framework. This will better support the prediction of, and protection against, lightning disasters affecting power grids.”
In related news, the Department of Commerce and NOAA announced US$250,000 in funding to support the development of an artificial intelligence (AI) model, which is expected to improve fire weather forecasts through better lightning prediction. Click here to read the full story.
