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气象:2021,47(5):529-538
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短时强降水概率预报的多模式集成技术研究
赵渊明,漆梁波
(上海中心气象台,上海 200030)
Multi-Model Integration Technology for Probabilistic Forecasting of Short-Time Severe Rainfall
ZHAO Yuanming,QI Liangbo
(Shanghai Central Meteorological Observatory, Shanghai 200030)
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投稿时间:2019-10-09    修订日期:2021-03-18
中文摘要: 利用2018年4—8月格点降水分析资料和4个业务高分辨率区域模式降水预报资料,应用分位数频率匹配法对模式1 h降水预报分别订正;基于上游关键区域的检验结果,采用动态权重多模式集成技术,探讨了多模式集成技术在短时强降水概率预报中的应用前景。结果表明:分位数频率匹配法对强降水预报改进具有正效果,可以减少模式的系统性偏差,提高模式降水预报的准确率。在短时临近时效内,上游关键区域降水信息对下游地区降水预报具有指示意义,基于上游关键区实况检验的动态权重多模式降水概率预报较简单集成概率具有更高的预报准确率,预报效果也更为稳定。个例分析也表明该技术对短时临近时效内的短时强降水预报预警有较好的指导作用。
Abstract:Based on the grided precipitation analysis data from April to August in 2018, and precipitation forecast data of four regional high-resolution models, percentile frequency matching is applied to calibrate the hourly precipitation frequency of each model. Based on the verification of key areas, the technology of dynamic weighted multi-model integration shows its application in probabilistic forecasting of short-time severe rainfall. The results demonstrate that percentile frequency matching displays positive effects in heavy rain precipitation, which can reduce the systematic forecast bias of the model and improve the accuracy of precipitation forecasting. In the nowcasting leadtime, the precipitation information of the upstream key areas is suggestive of the precipitation forecast in the downstream area. The dynamic weighted integration provides more skillful and stable performance in probabilistic forecasting than the equally weighted integration. The case also illustrates that the new technology performs well on the short-time severe precipitation forecasting and early warning within the nowcasting lead time.
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基金项目:国家重点研发计划(2018YFC1507606)、中国气象局气象预报业务关键技术发展专项[YBGJXM(2018)1A]和上海市气象局研究型专项(YJ201601)共同资助
引用文本:
赵渊明,漆梁波,2021.短时强降水概率预报的多模式集成技术研究[J].气象,47(5):529-538.
ZHAO Yuanming,QI Liangbo,2021.Multi-Model Integration Technology for Probabilistic Forecasting of Short-Time Severe Rainfall[J].Meteor Mon,47(5):529-538.