A thunderstorm forecasting method based on the Wavelet Neural Network optimized by the Improved Genetic Algorithm (IGA-WNN) is put forward in order to improve the accuracy of thunderstorm potential prediction.This method takes use of Cluster Analysis and Newton Iteration Method to improve the convergence direction and precision of multiple population genetic algorithm,thus avoids population homogeneity and local optimum;and employs improved Genetic Algorithm to optimize the initial weights of the threshold of wavelet neural network.The sounding data and lightning location data in Nanjing area from June to August during 2008 and 2009 were used for thunderstorm forecasting,and the convective parameters with higher degree of association,which were selected by grey correlation method,were normalized and put into the proposed model.Independent data are used to verify the forecast result.The forecasting and verification result indicate that,compared to other methods like BP neural network,IGA-WNN achieves higher prediction accuracy,and has better nonlinear processing capability as well as stronger generalization.