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 ›› 2018, Vol. 34 ›› Issue (4): 11-17.doi: 10.3969/j.issn.1673-503X.2018.04.002

• 论文 • 上一篇    下一篇

频率匹配法在海河流域ECMWF集合预报融合产品中的应用研究

徐姝1 尉英华1 熊明明2 魏琳3   

  1. 1. 天津市气象台，天津 300074；2. 天津市气候中心，天津 300074；3. 水利部海河水利委员会水文局，天津 300170
  • 收稿日期:2017-03-27 修回日期:2017-06-16 出版日期:2018-08-31 发布日期:2018-09-03

Application of Frequency-Matching method to ECMWF ensemble statistic fusing prediction products in the Haihe River basin

XU Shu1 WEI Ying-hua1 XIONG Ming-ming2 WEI Lin3   

  1. 1. Tianjin Meteorological Observatory, Tianjin 300074, China; 2. Tianjin Climate Center, Tianjin 300074, China; 3. Bureau of Hydrology, Haihe Water Conservancy Commission, Tianjin 300170, China
  • Received:2017-03-27 Revised:2017-06-16 Online:2018-08-31 Published:2018-09-03

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285

摘要：

针对ECMWF（European Centre for Medium-range Weather Forecasts）集合预报融合降水产品在海河流域的偏差特征，展开了基于频率匹配法的降水偏差订正，并对订正前后降水评分结果进行了系统检验。结果表明：经过2016年5—8月逐日试验分析结果表明，改进后的ECMWF集合预报融合产品显著改善了原产品降水量和雨区范围偏大的特征，订正后降水预报的平均强度与实况更接近，且预报时效越长、降水量级越大、预报偏差越大改进效果越明显；改进后ECMWF的集合预报融合产品降水预报的TS评分均有一定程度的提高，降水预报的Bias评分更接近1，特别是对于小雨和暴雨、大暴雨量级的改进尤其明显，消除了大片降水虚报区；降水预报的空报率明显减小，但漏报率有所增加。

关键词: ECMWF, 集合预报, 频率匹配法, 降水偏差, 订正

Abstract:

Based on the bias characteristics of the ECMWF (European Centre for Medium-range Weather Forecasts) ensemble statistic fusing prediction products in the Haihe River basin, the frequency matching method was used to correct the precipitation bias. The performance before and after the correction was examined. Using the results from four months（May-August, 2016）experiment, we demonstrate t that the positive biases in the precipitation level and range from the original products can  be significantly improved using the improved fusion products. The average intensity of the modified precipitation forecasts is closer to observations. The longer the valid forecast time, the greater the precipitation level, and the bigger the prediction bias , the better the improvement effect. To some extent, the scores of TS (threat score) and Bias of the improved fusion products are improved, especially for the light rain, rainstorm and the heavy rain cases. It eliminates the large false areas and reduces  the false-alarm  rates  significantly.  However, the missing- rates are slightly increased.

Key words:  ECMWF, Ensemble forecast, Frequency-Matching Method, Precipitation bias, Correction

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