基于资料同化方法的区域集合预报尺度混合初始扰动新方案
投稿时间: 2016-01-04  最后修改时间: 2016-03-07  点此下载全文
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作者单位E-mail
马旭林 南京信息工程大学大气科学学院 xulinma@nuist.edu.cn 
计燕霞 南京信息工程大学  
周勃旸 南京信息工程大学  
时洋 广东省气象台  
李琳琳 南京信息工程大学  
郭欢 南京信息工程大学  
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
中文摘要: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。本文基于GRAPES区域数值预报模式,发展设计了一种基于资料同化方法的混合尺度初始扰动构造新方案,即以全球大尺度信息为背景场,区域模式预报作为观测资料,通过GRAPES三维变分同化系统,将高质量的全球大尺度信息有效融合进中小尺度场,构造混合尺度区域集合预报初始扰动,改进滤波方法多尺度信息混合时导致的扰动误差。通过个例试验和批量试验,对新方案和原区域集合预报的性能进行比较。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偏小。
中文关键词:数值预报  资料同化  区域集合预报  尺度混合  初始扰动
 
A new scheme of blending initial perturbation of regional ensemble prediction system based on data assimilation method
Abstract:Whether the initial perturbation of ensemble prediction can reflect the structure characteristics of forecast errors is one of the key factors which determine the quality of regional ensemble forecast. A new scheme of blending initial perturbation on regional ensemble prediction system based on data assimilation method is developed in the paper. Global information is treated as background data and regional ensemble forecast is treated as observation data in GRAPES m3DVAR system. The scheme introduces the global large-scale information into the small-scale information, construct a multi-scale initial perturbation and reduce the perturbation errors caused by the filter method. The case experiment and batch tests are performed to compare the capacity of the scheme and original regional ensemble forecast. The results suggest that the multi-scale initial perturbation can combine the global large-scale information and the small-scale information from regional ensemble forecast. The new scheme provides more significant probabilistic forecasts. In all, the blending scale initial perturbation effectively improves the quality of regional ensemble forecasts, especially for temperature and geopotential height, but has slight effect on wind.
keywords:numerical weather prediction  data assimilation  regional ensemble prediction  blending scale  initial perturbation
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