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The Review of Hydrometeor Phase Identification Technology based on Dual-polarization Weather Radar |
Qingyun Lin(),Jianxin He(),Hao Wang,Zhao Shi,Wanting Chen |
Chengdu University of Information Technology, Chengdu 610225, China |
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Abstract The Hydrometeor Classification Algorithm(HCA) is one of the main vegetation research direction to analyze weather characteristics from microphysical perspective. The hydrometeor classification algorithm is of great significance for the observation of hail, rainfall and snowfall. This paper reviewed the advantages of the classical Fuzzy logic Hydrometeor Classification (FHC),including Neuro-Fuzzy Hydrometeor Classification (NF-HC), Support Vector Machine Hydrometeor Classification (SVM-HC) and deep learning methods. We also introduced the details of the application of hydrometeor classification in the hail, rainfall and snowfall and summarized the verification method, including aircraft measurement verification, numerical simulation verification, and ground observation comparison. In addition, the current problems of FHC are proposed, including the setting of membership function parameters and the hydrometeor phase identification of ice phase particles. The current research lacks an effective and convenient method for HCA, which limits the application of dual-polarization weather radar. Finally, directions for future research to HCA were forecasted.
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Received: 27 April 2019
Published: 10 July 2020
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Corresponding Authors:
Jianxin He
E-mail: 51018526@qq.com;hjx@cuit.edu.cn
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