An Improved Algorithm of Radar Image Extrapolation Based on Recurrent Neural Network
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Abstract:
The purpose of precipitation nowcasting is to predict the distribution of local precipitation intensity within the coming two hours, and accurate extrapolation radar images can provide accurate spacetime data reference for nowcasting. The application of Recurrent Neural Network (RNN) to meteorological radar image extrapolation has brought better results in recent two years. Based on the analysis of convLSTM and TrajLSTM, the extrapolation model is improved from two aspects: the number of layers of radar data and the loss function, and the experiment is carried out with Chengdu and Yueyang radar data and an open competition data set. The experimental results show that the improved model can better capture the spacetime correlation and keep more image details.