论文

基于时域对象的网格降水预报的追踪诊断分析

  • 张宏芳 ,
  • 潘留杰 ,
  • 卢珊 ,
  • 巨晓璇 ,
  • 史月琴
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  • <sup>1.</sup>陕西省气象服务中心,陕西 西安 710014;<sup>2.</sup>陕西省气象台,陕西 西安 710014;<sup>3.</sup>中国气象科学研究院,北京 100081

收稿日期: 2019-11-25

  网络出版日期: 2021-06-28

基金资助

中国气象局关键技术项目(05-09);国家重点研发计划项目(2018YFC1507901);陕西省自然科学基金项目(2019JM-088)

Tracking Diagnosis Analysis of Grid Precipitation Forecast based on Time-Domain Object

  • Hongfang ZHANG ,
  • Liujie PAN ,
  • Shan LU ,
  • Xiaoxuan JU ,
  • Yueqin SHI
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  • <sup>1.</sup>Shaanxi Meteorological Service Centre,Xi’an 710014,Shaanxi,China;<sup>2.</sup>Shaanxi Meteorological Observatory,Xi’an 710014,Shaanxi,China;<sup>3.</sup>Chinese Academy of Meteorological Sciences,Beijing 100081,China

Received date: 2019-11-25

  Online published: 2021-06-28

摘要

检验和评估模式降水预报的时间和位置偏差对提高降水预报准确率有重要意义, 而传统点对点的检验方法对此无能为力。基于2018年和2019年6 -8月欧洲中期预报中心(ECMWF)降水预报资料, 利用面向对象时域诊断分析工具(MTD), 追踪模式降水预报对象的生命周期、 初生、 消散等预报表现。研究表明: (1)个例分析显示, 时域诊断分析工具MTD能够很好的从三维降水场中提取降水对象, 进而刻画降水对象的生命周期及开始结束时间, 对客观描述降水对象的时间偏差具有独特的优势; (2)低阈值条件下模式预报能很好地描述降水对象的空间分布, 不足在于观测降水对象较模式预报明显偏多; 随着降水阈值增大, 预报与观测降水对象的空间频次呈现出显著差异, 表明模式对强降水的位置预报仍然需要改进; (3)采用最小卷积半径和降水阈值定义降水对象, 观测和预报场中80%的降水对象生命周期小于15 h, 且生命周期随着降水阈值和卷积半径的增大而减小; (4)三维对象追踪显示, 预报对象的持续时间较观测偏短, 移动速度较观测整体偏慢。

本文引用格式

张宏芳 , 潘留杰 , 卢珊 , 巨晓璇 , 史月琴 . 基于时域对象的网格降水预报的追踪诊断分析[J]. 高原气象, 2021 , 40(3) : 559 -568 . DOI: 10.7522/j.issn.1000-0534.2020.00021

Abstract

Understanding the time and position deviation of model precipitation forecast is very important to improve the forecast accuracy, but the traditional point-to-point verify methodscan not do anything about it.Based on the precipitation forecast data of the European Center for Medium-Range Weather Forecasts (ECMWF) from June to August of 2018 and 2019, the object-based diagnostic evaluation (MODE) and time domain diagnostic analysis methods (MTD) are used to evaluate the life cycle, initial occurrence and dissipation of the model precipitation forecast objects.The main results are as follows: (1) Case analysis shows that MTD can easily extract three-dimensional precipitation objects, thereby objectively describing the start and end time of the objects, and has unique advantages in evaluating the time deviation of precipitation objects.(2) Under the low threshold, the model forecast describes the spatial distribution of precipitation objects well, but the number of objects is less than that of observations.As the precipitation threshold increases, the frequency of forecasting and observing precipitation objects shows a significant difference, indicating that the location of heavy precipitationforecast still needs to be improved.(3) The precipitation objects are defined with the minimum convolution radius and precipitation threshold, 80% of the precipitation objects last less than 15 hours, and the objects life cycle decrease with the increase of the precipitation threshold and the convolution radius.(4) Compared with observations, the duration of 3D precipitation forecast objects is shorter and the moving speed is slower.

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