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

被引:2
|
作者
Yang, Ling [1 ,5 ]
Wang, Yun [1 ,5 ]
Wang, Zhongke [2 ]
Yang, Qian [1 ,5 ]
Fan, Xingang [1 ,3 ]
Tao, Fa [1 ,6 ,7 ]
Zhen, Xiaoqiong [1 ,4 ,5 ]
Yang, Zhipeng [1 ,5 ]
机构
[1] Chengdu Univ Informat Technol, Elect Engn Coll, Chengdu 610225, Peoples R China
[2] Chengdu Univ Informat Technol, Informat Secur Engn Coll, Chengdu 610225, Peoples R China
[3] Western Kentucky Univ, Dept Geog & Geol, Bowling Green, KY 42101 USA
[4] Chinese Acad Sci, Inst Atmospher Phys, Beijing 100029, Peoples R China
[5] Chengdu Univ Informat Technol, CMA Key Lab Atmospher Sounding, Chengdu 610225, Peoples R China
[6] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing 210044, Peoples R China
[7] CMA, Meteorol Observat Ctr, Beijing 100081, Peoples R China
基金
国家重点研发计划;
关键词
millimeter-wave cloud radar; clear-air echoes; neural network; laser ceilometer; all-sky camera; feature extraction; feature selection; BOUNDARY-LAYER; DOPPLER RADAR; TURBULENCE; ALGORITHM;
D O I
10.1007/s00376-020-9270-z
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
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 clouds. Therefore, MMCR has been widely applied in cloud observations. However, 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 echoes. It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background. The 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 camera. In addition, a new algorithm, which includes feature extraction, feature selection, and classification, is proposed to achieve the automatic identification of clear-air echoes. The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions. The 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.
引用
收藏
页码:912 / 924
页数:13
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