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毫米波测云雷达融化层自动识别技术 被引量:12

Automatic Identification Technology of Melting Layer in Millimeter Wave Cloud Radar Data
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摘要 为了充分利用雷达数据中的融化层信息,通过分析融化层在反射率因子和线性退极化比(LDR)参量中的特性,结合国内某型毫米波测云雷达的特点,提出了一种融化层边界自动识别的技术。利用2010年5—10月国内某型毫米波测云雷达在杭州的探测资料及相应的探空资料,对识别结果以及算法中参数的敏感性进行了对比和分析。对比结果表明,该方法能有效识别亮带的存在,得到的融化层上边界平均高度与实测零度层高度的误差小于100 m。参数的敏感性分析表明,融化层在反射率和LDR中的特性存在差异,其厚度在600~1500 m。毫米波测云雷达距离分辨率高、LDR对融化层敏感以及使用反射率和LDR双重约束是识别出的融化层边界误差较小的原因。 In order to take advantage of the melting layer information in radar data,an automated identification technology has been developed by analyzing the signatures of melting layer in the reflectivity and linear depolarization ratio(LDR) parameters of millimeter wave cloud radar.Radar and radiosonde data during May to October 2010 in Hangzhou are used to compare and analyze the identification results and sensitivity of the parameters in the algorithm.Results show that this technology can identify the existence of melting layer.The difference between the top boundary average heights of melting layer obtained by this technology and the measured zero level height by radiosonde is less than 100 m.Parameter sensitivity analysis shows that melting layer signatures in reflectivity and LDR are different,and the thickness of melting layer is between 600 m and 1500 m.The causes of the little difference in this identification technology are the high range resolution of millimeter wave cloud radar,LDR sensitive to melting layer and the use of reflectivity and LDR dual constraints.
出处 《气象》 CSCD 北大核心 2011年第6期720-726,共7页 Meteorological Monthly
基金 国家高技术研究发展计划机载气象雷达云雨探测系统(2007AA0619)资助
关键词 毫米波测云雷达 融化层 自动识别 技术 millimeter wave cloud radar melting layer automatic identification technology
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参考文献25

  • 1Zhang J, Langston C, Howard K. Bright band identification from vertical profile of reflectivity[C]. Preprints, the 33rd Conf on Radar Meteorology, Amer Meteor Soc, 2007, PSA. 13.
  • 2Giangrande S E, Krause J M, Ryzhkov A V. Automatic designation of the melting layer with a polarimetrie prototype of the WSR-88D radar[J].J Appl Meteor, 2008, 47:1354- 1364.
  • 3杨丹丹,申双和,邵玲玲,邹兰军.雷达资料和数值模式产品融合技术研究[J].气象,2010,36(8):53-60. 被引量:15
  • 4肖艳姣,刘黎平,李中华,王红艳.雷达反射率因子数据中的亮带自动识别和抑制[J].高原气象,2010,29(1):197-205. 被引量:29
  • 5Smith C J. The reduction of errors caused by bright bands in quantitative rainfall measurements made using radar[J]. J Atmos Oceanic Tech, 1986, 3:129-141.
  • 6Huggel A, Schmid W, Waldvogel A. Raindrop size distributions and the radar bright band[J]. J Appl Meteor, 1996, 35 : 1688-1701.
  • 7Vivekanandan J, Zrnic D S, Ellis S M, et al. Cloud micro physics retrieval using S band dualpolarization measurements [J]. BullAmer MeteorSoc, 1999, 80:381-388.
  • 8Giangrande S E, Ryzhkov A V. Polarimetric method for bright band detection[C]. Preprints, the 11th Conference on Aviation, Range and Aerospace Meteorology, Amer Meteor Soc, 2004, P5.8.
  • 9Takeda T, Fujiyoshi Y. Microphysical processes around melting layer in precipitating clouds as observed by vertically pointing radars[J]. J Meteor Soc Japan, 1978, 56:293-303.
  • 10Stewart R E, Marwitz J D, Pace J C, et al. Characteristics through the melting layer of stratiform clouds[J]. J Atmos Sci, 1984, 41:3227 -3237.

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