地形影响的水平相关模型在CMA-MESO中的应用  

Application of Topographic Impact Horizontal Correlation Model to CMA-MESO System

作　　者：庄照荣[1,2,3] 李兴良[1,2,3] 王瑞春[1,2,3] 高郁东 Zhuang Zhaorong;Li Xingliang;Wang Ruichun;Gao Yudong(CMA Earth System Modeling and Prediction Center,Beijing 100081;State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing 100081;CMA Key Laboratory of Earth System Modeling and Prediction,Beijing 100081;Chongqing Institute of Meteorological Sciences,Chongqing 401147;Key Laboratory of Core Tech on NWP-AI Integrated Forecast for Hazardous Precipitation,Chongqing 401147)

机构地区：[1]中国气象局地球系统数值预报中心,北京100081 [2]中国气象科学研究院灾害天气国家重点实验室,北京100081 [3]中国气象局地球系统数值预报重点开放实验室,北京100081 [4]重庆市气象科学研究所,重庆401147 [5]致灾降水数值模式与人工智能融合预报关键技术研究重点实验室,重庆401147

出　　处：《应用气象学报》2024年第4期414-428,共15页Journal of Applied Meteorological Science

基　　金：国家自然科学基金面上项目(42375154,42275168);国家重点研发计划(2022YFC3004002,2021YFC3000902)。

摘　　要：在背景误差水平相关模型中引入地形作用,研究复杂地形下近地面观测资料同化对分析和预报的影响。CMAMESO三维变分系统中背景误差水平相关关系采用高斯相关模型描述,观测信息在高度追随坐标的模式面上各向同性传播。然而在地形复杂的近地面层,观测信息传播受到山脉阻挡,因而其背景误差协方差非均匀且各向异性,观测信息传播应随地形高度变化。为此,采用美国国家气象中心NMC方法统计复杂地形下背景误差水平相关结构,构建包含地形高度和地形梯度影响的高斯相关模型,并将改进的水平相关模型应用于CMA-MESO三维变分分析。理想试验表明:考虑地形项的水平相关模型方案使观测信息以随地形高度变化的各向异性形式传播,越过大地形观测信息影响明显减弱,分析增量更加合理。我国北方一次强降水过程分析预报试验表明:随地形高度变化的水平相关模型方案使地面观测信息各向异性传播,削弱了大地形处近地面的分析增量,对降水预报略有正贡献。针对华东地区降水过程进行5 d逐小时快速更新分析预报循环试验结果表明,随地形变化的水平相关模型方案对10 m风场和24 h时效内降水预报有正贡献。The impact of near-surface observations on analysis and forecasting in complex terrain is studied by introducing the role of terrain in the background error horizontal correlation model.Observation information propagates isotropically on the model level in the height-based terrain-following coordinates since the background error horizontal correlation in CMA-MESO 3DVar system is characterized by an isotropic Gaussian correlation model.However,in the near-surface layer with complex topography,the propagation of observation information is blocked by mountain ranges,and thus its background error covariance is inhomogeneous and anisotropic,and furthermore,the propagation of observation information should vary with topography.The background error horizontal correlation coefficients in complex terrain are computed using NMC method by National Meteorological Center of USA.Results show that the blocking of large terrain causes the background error horizontal correlation coefficients to decrease more rapidly across mountain ranges,where the near-surface wind field is more localized than the temperature and humidity fields,with smaller horizontal correlation characteristic length scales,and the wind field information propagates over a closer distance.Based on the actual statistical structure,a Gaussian correlation model that includes effects of terrain height and terrain gradient is constructed,and the newly constructed horizontal correlation model accurately characterizes the decrease after mountain ranges are blocked.In CMA-MESO 3DVar analysis,the impact of terrain on the propagation of observational information is effectively incorporated by including a terrain height error term in the background error level correlation model.Idealized experiments show that the horizontal correlation modeling scheme that considering the terrain height error term allows the observation information to propagate anisotropically with the effect of observation information significantly diminishing across large terrain and the analysis increm

关 键 词：背景误差 水平相关模型 地形 三维变分 CMA-MESO 

分 类 号：P456.7[天文地球—大气科学及气象学]