人工智能在短临降水预报中应用研究综述

短临降水预报是一项重要且具有挑战性的世界性难题.研究人员曾尝试使用各种技术预报降水，但是由于降水本身具有高度非线性、随机性和复杂性的特性，使得降水预测精确度并不高.近年来，随着人工智能技术的迅猛发展，其日渐渗透到人们生活的方方面面，气象领域也因此得益.人工神经网络能够对非线性系统进行建模，因此相比于传统方法，如数值天气预报法和光流法等，人工智能方法使得降水预报的准确率大大提高.本文介绍了传统降水预报的方法，着重总结概括了用于短临降水预报的各种最新人工智能方法，并对各研究方向进行归纳分析，为各类研究人员研究提供有益参考和借鉴.

Survey on the application of artificial intelligence in precipitation nowcasting

Precipitation nowcasting is an important and challenging worldwide problem.Various techniques have been used to predict precipitation,but the accuracy of precipitation nowcasting is not high due to the highly nonlinear,random,and complex nature of precipitation.In recent years,with the rapid development of artificial intelligence technology,it has gradually penetrated into all aspects of people''s lives,and the meteorological fields are no exception.Compared to traditional methods,such as numerical weather forecasting and optical flow methods,artificial neural networks can model non-linear systems,which makes the accuracy of precipitation nowcasting being greatly improved.In this article,we review the traditional methods and summarize the latest artificial intelligence methods used for short-term precipitation forecasting,and analyze the research directions to provide useful references for various types of researchers.