论文

基于BGM的对流尺度集合预报试验及其检验

  • 马申佳 ,
  • 陈超辉 ,
  • 何宏让 ,
  • 李湘 ,
  • 李毅
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  • 国防科技大学气象海洋学院, 江苏 南京 211101

收稿日期: 2017-06-07

  网络出版日期: 2018-04-28

基金资助

北极阁开放研究基金项目(NJCAR2016MS02);国家重点基础研究发展计划(973计划)项目(2017YFC1501800);国家自然科学基金项目(41205073,41675007)

Experiment and Verification of the Convective-Scale Ensemble Forecast Based on BGM

  • MA Shenjia ,
  • CHEN Chaohui ,
  • HE Hongrang ,
  • LI Xiang ,
  • LI Yi
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  • College of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, Jiangsu, China

Received date: 2017-06-07

  Online published: 2018-04-28

摘要

基于增长模繁殖法,考虑对流尺度高度非线性特征和精细化预报要求,对一次强飑线天气过程进行了集合预报试验,引入概率匹配平均法对集合预报结果进行对比分析,并通过偏差和公平技巧评分对降水进行了预报效果检验。试验结果表明,BGM法应用到对流尺度集合预报中能够生成代表大气不确定性的快速增长扰动。集合预报结果相比控制预报更加准确,传统集合平均对较小降水强度的预报更加准确,概率匹配平均法对大量级降水的预报能力明显占优。降水评分检验表明,集合平均对小量级降水的预报技巧最高,概率匹配平均法对极端降水事件的预报技巧有明显优势。对流尺度集合预报能够提高降水预报技巧,并对高影响对流天气事件的预报有指导意义。

本文引用格式

马申佳 , 陈超辉 , 何宏让 , 李湘 , 李毅 . 基于BGM的对流尺度集合预报试验及其检验[J]. 高原气象, 2018 , 37(2) : 495 -504 . DOI: 10.7522/j.issn.1000-0534.2017.00073

Abstract

Based on breeding of growing modes (BGM) method, an ensemble forecast experiment was tested for a strong squall line considering the highly non-linear feature and detailed forecast requirement in convective-scale weather systems. The probability matched mean (PMM) method was used to analysis contrastively the results of the ensemble forecast, and the effect of precipitation forecast was verified by the bias score and equitable threat score (ETS). The results indicate that BGM method applied to the convective-scale ensemble forecast could generate the rapid growth perturbations that represent atmospheric uncertainties. The results of the ensemble forecast were more accurate than the control forecast, the traditional ensemble mean (EM) method was more accurate on the smaller intensity forecast, and the PMM method was more skillful at forecasting the large intensity events. The results of the verification in precipitation forecast demonstrated that the EM method had the highest forecasting skill of the small magnitude precipitation. And the PMM method had obvious advantages in the forecasting techniques of extreme precipitation events. Convective-scale ensemble forecast can improve the forecasting skill of precipitation forecast, and provide a guidance for the high-impact convective weather events.

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