Artificial intelligence nowcasting based on generative adversarial networks (GAN) has been conducted by using abundant radar echo images from 12 S-band Doppler radars in Guangdong province during the period from 2015 to 2017.Radar echo images were convoluted for 5 times in order to build the initial forecasting model.Afterwards,several confrontation trainings took place between the model images and real radar echo images,resulting in the loss function.The model was optimized constantly.Given that the model images were similar to the real radar echo images,the outputs of optimum model would be used for nowcasting.The experiments of four precipitation events in Guangdong province during 2018 suggested that the 60 min forecasted position,shape and intensity of radar echo in convective systems by GAN mostly coincide with the observations.However,the forecasted area of strong radar echo is larger than that of the observed radar echo.Furthermore,the GAN method could not forecast the precipitation caused by stratus clouds well.The GAN method could forecast moderate radar echoes quite well,while its forecast capability for strong radar echoes needs to be improved.