For the purpose of studying the lightning nowcasting early warning model of artificial intelligence, by relying on the convolutional neural network model and combining the radar data (MCR, VIL, ET) and lightning data of multiple time series, we conduct the application of the lightning nowcasting prediction method based on the structure of convolutional neural network. In addition, taking the radar and lightning data of Fujian Province in 2017 and 2018 as samples, we also finish the training and prediction research of the model. The training results show that the test set accuracy of 15-30 min model training samples is 0.798 〖KG-*5〗5. The verification analysis of the 20 lightning processes in Fujian Province in 2019 indicates that the TS score of the 15-30 min model for the nowcasting early warning of the dynamic-lift lightning process is 0.716, and the TS score of the localized thermal thunderstorm nowcasting warning in summer is 0.694. Compared with the conventional lightning warning algorithm which uses radar and lightning threshold control, these values have a certain improvement in accuracy, so having certain practical significance.