Radar echo extrapolation has been widely used in short-term heavy precipitation nowcasting. Aiming at the problem that traditional radar echo extrapolation methods do not make full use of massive historical meteorological data, which leads to low forecast accuracy, this paper proposed a new radar echo extrapolation method based on DPCNN. With the addition of dynamic probability calculation layer, DPCNN was able to calculate the corresponding probability convolution kernel for different radar echo input sequences and used it in the subsequent extrapolation calculations. Dynamic probability calculation layer enabled the network to make corresponding probability adjustments according to different input sequences in the prediction stage and enhance the connection between extrapolation and input sequences. The extrapolation experiment of short-term heavy precipitation in a certain area verifies the validity of the model from four aspects: extrapolated image, CSI, FAR, and POD.

[2021-07-05] Printed Article /doc/2020.11.0404/v2