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

气象与环境学报 ›› 2016, Vol. 32 ›› Issue (1): 9-15.doi: 10.11927/j.issn.1673-503X.2016.01.002

• 论文 • 上一篇    下一篇

廊坊地区5种数值模式降水预报性能检验与评估

许敏1, 丛波1, 刘艳杰1, 王洁2, 张绍恢1, 田晓飞1   

  1. 1. 廊坊市气象局, 河北廊坊 065000;
    2. 永清县气象局, 河北永清 065600
  • 收稿日期:2014-09-08 修回日期:2015-03-24 出版日期:2016-02-28 发布日期:2016-02-28
  • 作者简介:许敏,女,1983年生,工程师,主要从事短期天气预报研究,E-mail:hblfxm@163.com。
  • 基金资助:
    河北省气象局科研开发项目(14ky26)和廊坊市气象局科研开发项目(201202)共同资助。

Verification and assessment of precipitation forecast by five numerical models in Langfang

XU Min1, CONG Bo1, LIU Yan-jie1, WANG Jie2, ZHANG Shao-hui1, TIAN Xiao-fei1   

  1. 1. Langfang Meteorological Service, Langfang 065000, China;
    2. Yongqing Meteorological Service, Yongqing 065600, China
  • Received:2014-09-08 Revised:2015-03-24 Online:2016-02-28 Published:2016-02-28

PDF (PC)

682

被引次数

5

摘要： 为了提高廊坊地区降水预报数值产品的释用能力,利用廊坊市9个气象观测站24 h的实况降水资料和日本(JPN)、德国(GER)、GRAPES、T639及MM 5模式的降水预报产品资料,对目前降水预报业务中广泛使用的5种数值模式的预报效果进行检验分析。结果表明:日本(JPN)和德国(GER)模式对≥10.0 mm及≥25.0 mm量级降水预报的TS评分比其他模式高10.0%-40.0%,夏季MM 5模式对≥50.0 mm量级降水的预报表现出一定的优越性;T639、GRAPES模式分别对大雨及以上量级的降雨和小雪预报效果较好,日本、德国模式对中雪和大雪的预报表现出一定的优势,T639模式对暴雪预报的TS评分达33.3%,高于其他模式。

关键词: 降水, 数值模式, 预报效果, 检验, 评估

Abstract: In order to improve the application of precipitation forecast products from numerical models, forecast results were tested using observed precipitation from 9 weather stations of Langfang and forecast products from five numerical models, namely, Japan, Germany, T639, GRAPES and MM 5 models.The results indicate that TS scores of Japan and Germany models for more than or equal to 10 mm and 25 mm precipitation are 10.0%-40.0% higher than those from the other models.The MM 5 model for more than or equal to 50 mm precipitation has better forecast results in summer.T639 and GRAPES models show better prediction ability for heavy rain or more grade and light snow, while Japan and Germany models are better for moderate and heavy snow.TS score of T639 for rainstorm reaches 33.3% and higher than those of the other models.

Key words: Precipitation, Numerical models, Forecast effect, Verification, Assessment

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