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声信息,以便进行有效预测,例如现在的降水预报; 本文审查了利用深学习模型进行气象雷达数据分析和模式识别的最新相关科学研究和实际努力; 特别是在梁阻隔校正、雷达回声外推法和现在播送的降水等领域; 与传统方法相比,目前的DL方法说明更好的性能和方便,但有稳定性和普遍性; 除了最近的成就外,本文件还介绍和讨论了最新进展和现有挑战,试图在这一高度受关注的领域产生合理的潜力和趋势。