Radars are widely used to obtain echo information for effective prediction, such as precipitation nowcasting. In this paper, recent relevant scientific investigation and practical efforts using Deep Learning (DL) models for weather radar data analysis and pattern recognition have been reviewed; particularly, in the fields of beam blockage correction, radar echo extrapolation, and precipitation nowcast. Compared to traditional approaches, present DL methods depict better performance and convenience but suffer from stability and generalization. In addition to recent achievements, the latest advancements and existing challenges are also presented and discussed in this paper, trying to lead to reasonable potentials and trends in this highly-concerned field.

翻译：雷达被广泛用于获取回波信息以实现有效预测，例如降水临近预报。本文综述了近年来利用深度学习模型进行气象雷达数据分析与模式识别的相关科学研究和实际应用，重点关注波束遮挡校正、雷达回波外推及降水临近预报等领域。与传统方法相比，当前深度学习方法展现出更优的性能与便利性，但在稳定性和泛化能力方面仍存在不足。除近期成果外，本文还介绍并讨论了该领域的最新进展与现有挑战，试图引导这一高度关注领域的合理发展潜力与趋势。