| GRAPES-GFS模式暴雨预报天气学检验特征 |
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| 引用本文： | 宫宇,代刊,徐珺,杨舒楠,唐健,张芳,胡宁,张夕迪,沈晓琳.GRAPES-GFS模式暴雨预报天气学检验特征[J].气象,2018,44(9):1148-1159. |
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| 作者姓名： | 宫宇 代刊 徐珺 杨舒楠 唐健 张芳 胡宁 张夕迪 沈晓琳 |
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| 作者单位： | 国家气象中心;中国科学院生态与地理研究所荒漠与绿洲生态国家重点实验室;中国科学院大学 |
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| 基金项目： | 中国气象局预报员专项(CMAYBY2018-091)和中国气象局数值预报(GRAPES)发展专项资助 |
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| 摘 要： | 本文采用天气学检验方法,对2016年度国家气象中心GRAPES全球数值预报系统(GRAPES-GFS)业务预报暴雨过程及2013-2015年部分回算个例进行了检验,并结合对比欧洲中期天气预报中心确定性预报模式(EC模式)和国家气象中心全球谱模式T639L60(T639模式)降水预报,梳理总结业务GRAPES-GFS模式预报性能优势和系统性偏差特征。被检验暴雨过程共38次,其中南方暴雨过程20次,北方暴雨过程6次,热带扰动或台风降水过程12次。依靠预报员主观天气学检验分析,从降水预报效果检验出发,结合主要影响天气系统和示踪物理量检验,梳理总结模式预报系统性偏差,以期全面发掘该业务预报模式性能。结果表明对短期时效内的降水预报,GRAPES-GFS模式预报稳定性较好,整体明显优于T639模式。但还存在诸如对对流性降水预报较实况偏北或对主雨带南侧暖区降水预报不足的偏差特征;另对弱高空波动背景下的对流性降水预报偏弱;而在降水预报强度大致正确的情况下,对降水系统南侧偏南气流控制区域预报湿度偏大,对副热带地区的低涡系统预报偏强。
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| 关 键 词： | GRAPES-GFS模式，模式天气学检验，暴雨 |
| 收稿时间： | 2017/6/17 0:00:00 |
| 修稿时间： | 2018/2/27 0:00:00 |
Synoptic Verification Characteristics of Operational GRAPES-GFS Model Heavy Rain Event Forecast |
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| GONG Yu,DAI Kan,XU Jun,YANG Shunan,TANG Jian,ZHANG Fang,HU Ning,ZHANG Xidi and SHEN Xiaolin.Synoptic Verification Characteristics of Operational GRAPES-GFS Model Heavy Rain Event Forecast[J].Meteorological Monthly,2018,44(9):1148-1159. |
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| Authors: | GONG Yu DAI Kan XU Jun YANG Shunan TANG Jian ZHANG Fang HU Ning ZHANG Xidi and SHEN Xiaolin |
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| Institution: | National Meteorological Centre, Beijing 100081; State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011; University of Chinese Academy of Sciences, Beijing 100049,National Meteorological Centre, Beijing 100081,National Meteorological Centre, Beijing 100081,National Meteorological Centre, Beijing 100081,National Meteorological Centre, Beijing 100081,National Meteorological Centre, Beijing 100081,National Meteorological Centre, Beijing 100081,National Meteorological Centre, Beijing 100081 and National Meteorological Centre, Beijing 100081 |
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| Abstract: | This study verified the whole 2016 year real time forecast and parts of 2013-2015 reforecast of heavy rain events and compared them with EC model and T639 model forecasts by using synoptic verification method. After summarizing up all verification results into several systematic biases, some conclusions were excavated to help improve the GRAPES GFS developments and operational applications. 38 heavy rainfall events were verified. Starting from the forecast quality of precipitation, synoptic weather systems and atmospheric physical factors were checked to find the direct causes of the precipitation biases and differences between other operational models. The results showed that some advances have been made in short range precipitation forecast, but still north bias exists in some convective rainband forecasts. Precipitation forecasts are weaker than observation in some convective cases which are under weak high level synoptic system background. Wet bias northern to the rainband and strong bias of subtropical vortex were also found in some cases while the precipitation was not over estimated. |
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| Keywords: | GRAPES-GFS model synoptic verification for model heavy rain event |
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