湖北农业科学 ›› 2022, Vol. 61 ›› Issue (18): 48-60.doi: 10.14088/j.cnki.issn0439-8114.2022.18.008

• 资源·环境 • 上一篇    下一篇

基于快速融合技术在武汉定量降水预报的检验与误差分析

刘佩廷1,2, 谌伟1,2, 徐迎春1, 刘火胜1, 庞晶1, 张丽1, 王瑞丽1   

  1. 1.武汉市气象局,武汉 430040;
    2.中国气象局武汉暴雨研究所暴雨监测预警湖北重点实验室,武汉 430205
  • 收稿日期:2022-05-23 出版日期:2022-09-25 发布日期:2022-10-21
  • 通讯作者: 谌 伟(1978-),男,湖北随州人,高级工程师,主要从事预报预警方法研究,(电子信箱)chenweiyy2008@163.com。
  • 作者简介:刘佩廷(1988-),男,重庆忠县人,工程师,主要从事天气预报与数值模式研究,(电话)15387037747(电子信箱)603834789@qq.com。
  • 基金资助:
    湖北省气象局科技发展基金项目(2018J01; 2022Y16); 国家自然科学基金项目(41275105)

Verification and error analysis of quantitative precipitation forecast products based on fast fusion technology in Wuhan

LIU Pei-ting1,2, CHEN Wei1,2, XU Ying-chun1, LIU Huo-sheng1, PANG Jing1, ZHANG Li1, WANG Rui-li1   

  1. 1. Wuhan Meteorological Bureau,Wuhan 430040, China;
    2. Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorologic Administration, Wuhan 430205, China
  • Received:2022-05-23 Online:2022-09-25 Published:2022-10-21

摘要: 综合利用2018年3—9月湖北天气雷达组网拼图数据和武汉及周边地面加密自动站降水观测资料,利用快速融合等技术建立适合武汉本地化光流法和TREC法动态Z-I关系,实时得到高时空分辨率雷达定量降水反演资料2 h QPF,并使用SWAN 1 h QPF资料对比分析。结果表明,总体而言,基于雷达外推与自动站快速融合技术的光流法效果最好,TS综合平均高出SWAN约3个百分点。3种方法在大雨以下量级估测能力最好,暴雨和大暴雨量级误差有所增大。3种方法QPF采用 9 点或 25 点平均后,虽然有利于改善相对和绝对误差,对提高预报准确率贡献却较小,而采用邻域法检验能够较大幅度提升预报准确率,同时也一定程度减小了空报率和漏报率。综合对比分析区域和局地分散过程,整体上在大雨以下量级,均为光流法最好,TREC法次之,SWAN效果最差。差异最大的主要集中在区域性过程。在暴雨和大暴雨量级上,尽管SWAN在区域过程中具有较高的评分,但在局地过程中表现不稳定,而光流法在局地过程中相对更稳定。

关键词: 融合技术, 2 h QPF, 光流法, TREC法, 邻域检验

Abstract: Using a combination of Hubei weather radar network puzzle data and precipitation observations from Wuhan and surrounding ground-based encrypted automatic stations from March to September 2018, fast fusion and other techniques were used to establish dynamic Z-I relationships suitable for Wuhan localized optical flow method and TREC method to obtain high spatial and temporal resolution radar quantitative precipitation inversion data 2 h QPF in real time, and the data SWAN 1 h QPF was used to compared and analyzed. The results show that, in general, the optical flow method based on radar extrapolation and automatic station fast fusion technology is the best, and the TS integrated average is about 3 percentage points higher than that of SWAN. The three methods of QPF with 9-point or 25-point averaging can improve the relative and absolute errors, but have less contribution to improving the forecast accuracy, while the neighborhood method can improve the forecast accuracy significantly and also reduce the rate of empty and missed reports to some extent. In a comprehensive comparative analysis of the regional and local dispersion processes, the optical flow method is the best, the TREC method is the second best, and the SWAN method is the least effective in the magnitude below heavy rainfall. The greatest differences are mainly concentrated in the regional processes. At the heavy rainfall and heavy rainfall magnitudes, although SWAN has higher scores in the regional processes, it performs unstable in the local processes, while the optical flow method is relatively more stable in the local processes.

Key words: fusion technology, 2 h QPF, optical flow method, TREC method, neighborhood test

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