| GRAPES区域集合预报尺度混合初始扰动构造的新方案 |
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| 引用本文： | 马旭林,计燕霞,周勃旸,时洋,李琳琳,郭欢.GRAPES区域集合预报尺度混合初始扰动构造的新方案[J].大气科学学报,2018,41(2):248-257. |
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| 作者姓名： | 马旭林 计燕霞 周勃旸 时洋 李琳琳 郭欢 |
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| 作者单位： | 南京信息工程大学气象灾害教育部重点实验室;广东省气象台 |
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| 基金项目： | 公益性行业（气象）科研专项（GYHY201506005）；国家自然科学基金资助项目（41275111；91437113） |
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| 摘 要： | 集合预报初始扰动能否准确反映预报误差的结构特征是决定区域集合预报质量的关键因素之一。本文针对GRAPES区域数值预报模式,发展设计了一种基于资料同化思想的混合尺度初始扰动构造新方案。该方案以全球大尺度信息为背景场,区域模式预报作为观测资料,借助GRAPES三维变分同化系统,将高质量的全球大尺度信息与区域模式预报中质量较高的中小尺度信息有效融合,构造混合尺度区域集合预报初始扰动,并通过个例试验和批量试验,比较分析了新方案和原区域集合预报的性能。试验结果表明,基于资料同化构造的初始扰动能够有效融合全球大尺度信息和中小尺度天气系统的信息,其降水概率预报更具参考价值。总体上看,区域集合预报混合初始扰动新方案能够较好地改进区域集合预报质量,尤其是对高度场和温度场效果更为显著,但对风场的集合预报性能影响略小。
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| 关 键 词： | 资料同化 GRAPES 区域集合预报 尺度混合 初始扰动 |
| 收稿时间： | 2016/1/4 0:00:00 |
| 修稿时间： | 2016/3/13 0:00:00 |
A new scheme of blending initial perturbation of the GRAPES regional ensemble prediction system |
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| MA Xulin,JI Yanxi,ZHOU Boyang,SHI Yang,LI Linlin and GUO Huan.A new scheme of blending initial perturbation of the GRAPES regional ensemble prediction system[J].大气科学学报,2018,41(2):248-257. |
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| Authors: | MA Xulin JI Yanxi ZHOU Boyang SHI Yang LI Linlin and GUO Huan |
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| Institution: | Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China;Guangdong Meteorological Observatory, Guangzhou 510080, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Nanjing University of Information Science & Technology, Nanjing 210044, China |
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| Abstract: | One of the key factors by which to determine the quality of regional ensemble forecast is whether the initial perturbation of ensemble prediction can precisely reflect the structural characteristics of the forecast errors.In the present study,based on the data assimilation method,a new scheme of blending initial perturbation on the regional ensemble prediction system is proposed for the regional numerical prediction model of GRAPES.Specifically,the new scheme first introduces the global large-scale information as the background field and regional ensemble forecasts as observational data into the GRAPES m3DVAR system,then effectively integrates the high quality meso-scale information into global large-scale information,so as to construct a multi-scale initial perturbation of regional ensemble prediction.A case experiment and batch tests are carried out to compare the performance of the new scheme and original regional ensemble forecast.The results suggest that the multi-scale initial perturbation based on the data assimilation method is able to effectively combine the global large-scale information from the global ensemble forecast with the meso-scale information from the regional ensemble forecast,thereby leading to a more reliable probabilistic precipitation prediction.Therefore,this new scheme of blending initial perturbation of the regional ensemble prediction system is proven to be efficient in improving the quality of regional ensemble forecast,especially for the geopotential height field and temperature field,yet at the same time it has a slight effect on the wind field. |
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| Keywords: | data assimilation GRAPES regional ensemble prediction blending scale initial perturbation |
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