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Automatic Identification of Clear-Air Echoes Based on Millimeter-wave Cloud Radar Measurements

Advances in Atmospheric Sciences 2020年第8期37卷 912-924页

作者： Ling YANG Yun WANG Zhongke WANG Qian YANG Xingang FAN Fa TAO Xiaoqiong ZHEN Zhipeng YANG Electronic Engineering College Chengdu University of Information TechnologyChengdu 610225China Information Security Engineering College Chengdu University of Information TechnologyChengdu 610225China Department of Geography and Geology Western Kentucky UniversityBowling GreenKY 42101USA Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China CMA Key Laboratory of Atmospheric Sounding Chengdu University of Information TechnologyChengdu 610225China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and TechnologyNanjing210044China Meteorological Observation Centre CMABeijing 100081China

Millimeter-wave cloud radar(MMCR)provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the ***,MMCR has been widely applied in cloud ***,due to the influence of non-meteorological factors such as insects,the cloud observations are often contaminated by non-meteorological echoes in the clear air,known as clear-air *** is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather *** characteristics of clear-air echoes are studied here by combining data from four devices:an MMCR,a laser-ceilometer,an L-band radiosonde,and an all-sky *** addition,a new algorithm,which includes feature extraction,feature selection,and classification,is proposed to achieve the automatic identification of clear-air *** results show that the recognition algorithm is fairly satisfied in both simple and complex weather *** recognition accuracy can reach up to 95.86%for the simple cases when cloud echoes and clear-air echoes are separate,and 88.38%for the complicated cases when low cloud echoes and clear-air echoes are mixed.

关键词： millimeter-wave cloud radar clear-air echoes neural network laser ceilometer all-sky camera feature extraction feature selection

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