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Strong winds at sea and the secondary disasters caused by them are the main factors leading to marine meteorological disasters. Radar observation data is one of the main reference data for proximity prediction，accurate radar extrapolation data is very important for improving the ability of predicting the approaching strong convective gales at sea. Facing the demand of offshore gale forecast, improve ConvLSTM from two aspects of input data format and loss function, ConvLSTM network based on self coding is constructed, Training the model by four years historical radar echo data of Cangzhou,the radar echo extrapolation model that can predict the future 1h radar echo intensity and shape using the historical 1h radar echo is obtained. Test set and case test results show that improved model has better extrapolation effect in strong echo prediction.