主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

气象与环境学报 ›› 2018, Vol. 34 ›› Issue (4): 18-25.doi: 10.3969/j.issn.1673-503X.2018.04.003

• 论文 • 上一篇    下一篇

基于雷达组网拼图的定量降水反演I—动态Z-I关系法

纪永明1  蒋大凯2  陈传雷1  任志杰3  孟莹3  才奎志1  胡鹏宇1  张硕1   

  1. 1. 辽宁省气象灾害监测预警中心,辽宁 沈阳 110166;2. 辽宁省气象局,辽宁 沈阳 110166;3. 中国气象局气象干部培训学院辽宁分院,辽宁 沈阳 110166
  • 收稿日期:2017-06-04 修回日期:2018-01-22 出版日期:2018-08-31 发布日期:2018-09-03

Quantitative precipitation inversion algorithm based on the multi-radar mosaic I: dynamic Z-I relationships

JI Yong-ming1  JIANG Da-kai2  CHEN Chuan-lei REN Zhi-jie3  MENG Ying3  CAI Kui-zhi1  HU Peng-yu1  ZHANG Shuo1   

  1. 1. Liaoning Meteorological Disaster Monitoring and Early Warning Center, Shenyang 110166,China; 2. Liaoning Meteorological Administration, Shenyang 110166,China; 3. Liaoning Branch, China Meteorological Administration Training Center, Shenyang 110166,China
  • Received:2017-06-04 Revised:2018-01-22 Online:2018-08-31 Published:2018-09-03

摘要:

综合利用辽宁省及周边区域9部多普勒天气雷达组网拼图资料与地面加密自动气象站降水观测资料,通过最优化法,建立适合辽宁本地区的动态Z-I关系,实时得到高时空分辨率雷达定量降水反演资料。结果表明:对2011年台风“米雷”和2012年台风“达维”降水反演表明,动态Z-I关系法可以反演地面降水的主要空间分布特征,但反演的强降水中心存在较大偏差;动态Z-I关系法定量降水反演能力整体优于固定Z-I关系法,但存在高估小雨强度和抑制大雨强度的系统性偏差,特别是对于20.0 mm•h-1以上量级的强降水,平均误差达-10.0 mm以上,平均相对误差超过70.0%;各量级降水样本所占比例的差异与地理区域气候条件的差异是动态Z-I关系法反演降水产生误差的两个主要原因,为下一步优化雷达定量降水反演方案提供了思路。

关键词: 雷达, 动态Z-I关系法, 最优化法, 台风, 误差

Abstract:

Using the Doppler multi-radar mosaic data and surface precipitation data of encryption automatic stations in Liaoning province, the local dynamic Z-I relationships were established based on the optimization method to get the quantitative precipitation retrieval data with a real-time high spatiotemporal resolution. The method is used to retrieve the precipitation fields produced by typhoon " Meari" in 2011 and "Damrey" in 2012. The results show that the quantitative precipitation retrieval method can reproduce the main spatial distribution characteristics of the precipitation. . However, there is a large bias  in the strong precipitation center. In general, the retrieval  ability of quantitative precipitation for the local dynamic Z-I method is better than the fixed Z-I method. There is still systematic bias in the inversion data, i.e., overestimating the light rain and underestimating the heavy rain. For the heavy precipitation above 20.0 mm•h-1, the average error is greater than -10.0 mm and the average relative error is greater than 70.0%. Further analysis shows that the differences in the proportion of different magnitudes of precipitation and the differences in the regional climate conditions are the two main reasons for the precipitation inversion error. This knowledge provides a way for the improvement of radar quantitative precipitation inversion in the future.

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