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基于Ka波段毫米波云雷达资料对水凝物相态的识别研究
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  • 英文篇名:Recognition research of hydrometeor phase based on Ka-band millimeter wave cloud radar data
  • 作者:李玉莲 ; 孙学金 ; 周永波 ; 王可 ; 梁垚
  • 英文作者:LI Yulian;SUN Xuejin;ZHOU Yongbo;WANG Ke;LIANG Yao;College of Meteorology and Oceanography, National University of Defense Technology;
  • 关键词:毫米波云雷达 ; 模糊逻辑算法 ; 水凝物相态
  • 英文关键词:millimeter-wave cloud radar;;fuzzy logic algorithm;;hydrometeor phases
  • 中文刊名:QXKX
  • 英文刊名:Journal of the Meteorological Sciences
  • 机构:国防科技大学气象海洋学院;
  • 出版日期:2019-03-06 10:18
  • 出版单位:气象科学
  • 年:2019
  • 期:v.39
  • 基金:国家自然科学基金资助项目(41575020)
  • 语种:中文;
  • 页:QXKX201901004
  • 页数:8
  • CN:01
  • ISSN:32-1243/P
  • 分类号:38-45
摘要
利用不同水凝物相态下反射率因子、多普勒径向速度、谱宽、线性退偏比等云雷达探测参量以及温度的阈值,采用不对称的T型成员函数,建立了识别水凝物相态的模糊逻辑算法,可识别的水凝物类型包括雪花、冰晶、混合相态、液态云滴、毛毛雨滴、雨滴。利用分级逐库订正法衰减订正后的Ka波段双偏振雷达探测数据和ECMWF再分析资料温度廓线数据对水凝物相态进行了识别研究。结果表明,识别出的水凝物相态结果基本合理,反映出了空中水凝物相态的演变过程,可进一步应用于降水微物理过程研究和人工影响降水应用研究。
        This paper uses the reflectivity factor, Doppler radial velocity, spectral width, linear deviation ratio and other cloud radar detection parameters and temperature thresholds in different water condensate phases, and asymmetric T-member function to establish the fuzzy logic algorithm for identification of water condensation. The identifiable types of water condensate include snowflake, ice crystal, mixed phase, liquid cloud droplet, drizzle, raindrop. This paper uses the Ka-band dual-polarized radar detection data after attenuation correction by hierarchical bin-by-bin algorithm and the ECMWF reanalysis data temperature profile data to identify the phases of the water condensate. The results show that the identified phase results of water condensate are basically reasonable, reflecting the evolution process of the phase state of air condensate, which can be further applied to the study of precipitation microphysical processes and applications of artificial influence on precipitation.
引文
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