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| GFS对我国南方两次持续性降水过程的预报技巧评估 | |
| 引用本文： | 董颜,刘寿东,王东海,赵艳风.GFS对我国南方两次持续性降水过程的预报技巧评估[J].气象,2015,41(1):45-51. |
| 作者姓名： | 董颜 刘寿东 王东海 赵艳风 |
| 作者单位： | 1. 南京信息工程大学应用气象学院，南京 210044; 北京市气象服务中心，北京 100089 2. 南京信息工程大学应用气象学院,南京,210044 3. 中国气象科学研究院灾害天气国家重点实验室,北京,100081 |
| 基金项目： | 国家重点基础研究发展计划(973计划)(2012CB417204)、公益性行业（气象）科研专项(GYHY201006014和GYHY201206039)和国家自然科学基金项目(40875022和41175064)共同资助 |
| 摘 要： | 采用美国全球预报系统（Global Forecasting System，GFS）资料，利用谐波滤波提取空间长波、超长波分量，检验评估了GFS对2012年7月11—31日东亚地区大气环流场和降水的可预报能力。结果表明：GFS模式对东亚地区的中低层高度场预报可靠时效维持6 d以上，高层预报可靠时效可达10 d；长波、超长波的可预报效果显著，其中高度场长波5～8波的预报效果好于3～6波，风场则相反；GFS对我国南方两次持续性降水过程的可预报天数维持在8 d左右，并可提前2天预报出强降水带位置；模式对持续性降水过程预报相对站点观测降水量整体偏强。 |
| 关 键 词： | GFS 滤波 大气环流场 持续性降水 误差 评分 |
| 收稿时间： | 2013/12/28 0:00:00 |
| 修稿时间： | 2014/6/11 0:00:00 |
Assessment on Forecasting Skills of GFS Model for Two Persistent Rainfalls over Southern China |
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| DONG Yan,LIU Shoudong,WANG Donghai and ZHAO Yanfeng.Assessment on Forecasting Skills of GFS Model for Two Persistent Rainfalls over Southern China[J].Meteorological Monthly,2015,41(1):45-51. | |
| Authors: | DONG Yan LIU Shoudong WANG Donghai and ZHAO Yanfeng |
| Institution: | College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044; Beijing Meteorological Service Centre, Beijing 100089;College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044;State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081;State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081 |
| Abstract: | This study aims at assessing the predictability capacity of the Global Forecasting System (GFS) for the atmospheric circulation features and precipitation over East Asia during 11-31 July 2012 by using the GFS data and the extracted components of long wave and ultra long wave via the harmonic filtering. The results show that the GFS model can predict the mid and lower heights over East Asia with reliable lead time of 6 d, and up to 10 d for the higher heights. The predictability for long wave and ultra long wave components is more significant, of which the 5-8 wave band forecast is better than the 3-6 wave one in terms of the forecasting skill for height. However, the forecast result is reversed for the wind filed. In addition, the predictability of the model for the two persistent rainfalls maintains 8 d or so, and moreover it can tell the location of severe rainfall band ahead of 2 d. In general, the GFS model is stronger in forecasting the persistent precipitation process than the observed fields. |
| Keywords: | global forecasting system (GFS) filtering atmospheric circulation features persistent rainfall error score |
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