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Advances in Atmospheric Sciences

, Volume 36, Issue 4, pp 346–362 | Cite as

Seasonal Variations of Observed Raindrop Size Distribution in East China

  • Long Wen
  • Kun ZhaoEmail author
  • Mengyao Wang
  • Guifu Zhang
Original Paper
  • 17 Downloads

Abstract

Seasonal variations of rainfall microphysics in East China are investigated using data from the observations of a two-dimensional video disdrometer and a vertically pointing micro rain radar. The precipitation and rain drop size distribution (DSD) characteristics are revealed for different rain types and seasons. Summer rainfall is dominated by convective rain, while during the other seasons the contribution of stratiform rain to rainfall amount is equal to or even larger than that of convective rain. The mean mass-weighted diameter versus the generalized intercept parameter pairs of convective rain are plotted roughly around the “maritime” cluster, indicating a maritime nature of convective precipitation throughout the year in East China. The localized rainfall estimators, i.e., rainfall kinetic energy–rain rate, shape–slope, and radar reflectivity–rain rate relations are further derived. DSD variability is believed to be a major source of diversity of the aforementioned derived estimators. These newly derived relations would certainly improve the accuracy of rainfall kinetic energy estimation, DSD retrieval, and quantitative precipitation estimation in this specific region.

Key words

raindrop size distribution precipitation microphysics disdrometer seasonal variation East China 

摘 要

本研究利用二维视频雨滴谱仪和垂直指向的微降雨雷达观测资料, 分析了中国东部地区降水雨滴谱分布的季节变化特征, 揭示了不同类型降水的雨滴谱特征在不同季节均存在不同程度的差异. 夏季对流性降水对总降水的贡献约为77.5%, 而其他季节中层云降水的贡献则等于或超过对流性降水. 四个季节对流性降水的质量加权平均粒径–归一化截断参数值均位于“海洋性”对流区附近, 表明中国东部地区全年的对流性降水均具有海洋性特征. 本研究还拟合了本地化的降水估计关系, 包括降雨动能–降水率关系, 斜率–形状参数关系, 雷达反射率–降水率关系等, 有助于提高中国东部地区降雨动能估计, 雨滴谱反演和定量降水估计的精度. 分析也表明, 雨滴谱分布的变化特征是这些拟合关系出现差异的主要原因.

关键词

雨滴谱分布 降水微物理 雨滴谱仪 季节变化 中国东部地区 

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Notes

Acknowledgements

This work was primarily supported by the National Key Research and Development Program of China (Grant No. 2017YFC1501703), the National Natural Science Foundation of China (Grant Nos. 41875053, 41475015 and 41322032), and the National Fundamental Research 973 Program of China (Grant Nos. 2013CB430101 and 2015CB452800). The observational data used in this study were collected by a National 973 Project (Grant No. 2013CB430101), and any requests for the data can be made at https://doi.org/scw973.nju.edu.cn/ or by contacting the project office at yang.zhengwei@nju.edu.cn.

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Copyright information

© Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Long Wen
    • 1
    • 2
    • 3
  • Kun Zhao
    • 1
    • 2
    Email author
  • Mengyao Wang
    • 1
  • Guifu Zhang
    • 1
    • 4
  1. 1.Key Laboratory of Mesoscale Severe Weather of Ministry of Education and School of Atmospheric SciencesNanjing UniversityNanjingChina
  2. 2.State Key Laboratory of Severe Weather and Joint Center for Atmospheric Radar Research of China Meteorological Administration and Nanjing UniversityChinese Academy of Meteorological SciencesBeijingChina
  3. 3.Xichang Satellite Launch CenterXichangChina
  4. 4.School of Meteorology and Center for Analysis and Prediction of StormsUniversity of OklahomaNormanUSA

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