An OSSE-Based Evaluation of Hybrid Variational-Ensemble Data Assimilation for the NCEP GFS. Part II: 4DEnVar and Hybrid Variants
An OSSE-Based Evaluation of Hybrid Variational-Ensemble Data Assimilation for the NCEP GFS. Part II: 4DEnVar and Hybrid Variants
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DOI：
10.1175/mwr-d-13-00350.1
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发表时间：
2015-02
影响因子：
3.2
通讯作者：
D. Kleist;K. Ide
中科院分区：
文献类型：
--
作者：
D. Kleist;K. Ide
AbstractThis工作描述了一个混合四维集合-变分（4DEnVar）算法和初始化选项内使用的国家环境预报中心全球数据同化系统的制定。提出的方案是使用切线线性正常模式约束，弱约束数字滤波器，和组合。观测系统仿真实验进行评估的影响，利用混合4DEnVar与各种初始化技术。实验利用双分辨率配置，其中合奏运行在大约一半的确定性组件的分辨率。据发现，从3D到4D，分析误差减少了大多数变量和水平。当在没有基于正态模式的强约束的情况下使用时，包含时不变的静态协方差被发现对分析有一个小的、积极的影响。实验结果表明，弱约束数字滤波器具有良好的降阶性能。
AbstractThis work describes the formulation of a hybrid four-dimensional ensemble--variational (4DEnVar) algorithm and initialization options utilized within the National Centers for Environmental Prediction global data assimilation system. Initialization schemes that are proposed for use are the tangent-linear normal mode constraint, weak constraint digital filter, and a combination thereof.An observing system simulation experiment is carried out to evaluate the impact of utilizing hybrid 4DEnVar with various initialization techniques. The experiments utilize a dual-resolution configuration, where the ensemble is run at roughly half the resolution of the deterministic component. It is found that by going from 3D to 4D, analysis error is reduced for most variables and levels. The inclusion of a time-invariant static covariance when used without a normal mode–based strong constraint is found to have a small, positive impact on the analysis. The experiments show that the weak constraint digital filter degra...