基于机器学习算法的雷达估测降水技术研究  

Research on Radar Precipitation Estimation Technology Based on Machine Learning Algorithm

作　　者：张伟 全志伟[1] ZHANG Wei;QUAN Zhiwei(Lanzhou Central Meteorological Observatory,Lanzhou Gansu 730000)

机构地区：[1]兰州中心气象台,甘肃兰州730000

出　　处：《河南科技》2021年第26期26-28,共3页Henan Science and Technology

摘　　要：通过对多普勒天气雷达数据进行预处理,生成大量的雷达回波图像,并构造了雷达回波序列图像库,为机器学习提供训练样本集。基于机器学习算法时空预测神经网络(PredRNN++)建立雷达估测降水识别模型,实现0~3 h雷达回波预测。结果表明:将时空预测神经网络方法应用于雷达回波识别,可突破传统1 h预报预警时效,与传统的深度学习算法相比效果较好。By preprocessing doppler weather radar data, a large number of radar echo images are generated, and a radar echo sequence image library is constructed to provide training sample set for machine learning, the recognition model of radar precipitation estimation is established based on machine learning Algorithm time-space prediction neural network(PredRNN++) to realize 0~3 h radar echo prediction. The results show that the method of time-space prediction neural network applied to radar echo recognition can break through the traditional time-effect of 1 h prediction and has better effect than the traditional depth-learning Algorithm.

关 键 词：机器学习 雷达 估测降水 

分 类 号：P412.25[天文地球—大气科学及气象学]