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DOI | 10.1029/2017JD027529 |
A Multigrid Nonlinear Least Squares Four-Dimensional Variational Data Assimilation Scheme With the Advanced Research Weather Research and Forecasting Model | |
Zhang, Hongqin1,2; Tian, Xiangjun1,2,3 | |
2018-05-27 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
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ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2018 |
卷号 | 123期号:10页码:5116-5129 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China |
英文摘要 | The motions of the atmosphere have multiscale properties in space and/or time, and the background error covariance matrix (B) should thus contain error information at different correlation scales. To obtain an optimal analysis, the multigrid three-dimensional variational data assimilation scheme is used widely when sequentially correcting errors from large to small scales. However, introduction of the multigrid technique into four-dimensional variational data assimilation is not easy due to its strong dependence on the adjoint model, which has high computational costs in data coding, maintenance, and updating, especially for large-scale, complex problems. In this study, the multigrid technique was introduced into the nonlinear least squares four-dimensional variational assimilation (NLS-4DVar) method, which is an advanced four-dimensional ensemble-variational method that can be applied without invoking the adjoint models. The multigrid NLS-4DVar (MG-NLS-4DVar) scheme uses the number of grid points to control the scale, with doubling of this number when moving from coarser to finer grid levels. Furthermore, the MG-NLS-4DVar scheme not only retains the advantages of NLS-4DVar but also sufficiently corrects multiscale errors to achieve a highly accurate analysis. The effectiveness and efficiency of the proposed MG-NLS-4DVar scheme were evaluated by one group of single-observation experiments and one group of comprehensive evaluation experiments using the Advanced Research Weather Research and Forecasting Model. MG-NLS-4DVar outperformed NLS-4DVar, with a lower computational cost. |
英文关键词 | data assimilation multigrid NLS-4DVar WRF |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000435445600020 |
WOS关键词 | OPERATIONAL IMPLEMENTATION ; LOCALIZATION APPROACH ; MESOSCALE ; SYSTEM |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/32288 |
专题 | 气候变化 |
作者单位 | 1.Chinese Acad Sci, Inst Atmospher Phys, Int Ctr Climate & Environm Sci, Beijing, Peoples R China; 2.Univ Chinese Acad Sci, Beijing, Peoples R China; 3.Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing, Jiangsu, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Hongqin,Tian, Xiangjun. A Multigrid Nonlinear Least Squares Four-Dimensional Variational Data Assimilation Scheme With the Advanced Research Weather Research and Forecasting Model[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2018,123(10):5116-5129. |
APA | Zhang, Hongqin,&Tian, Xiangjun.(2018).A Multigrid Nonlinear Least Squares Four-Dimensional Variational Data Assimilation Scheme With the Advanced Research Weather Research and Forecasting Model.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,123(10),5116-5129. |
MLA | Zhang, Hongqin,et al."A Multigrid Nonlinear Least Squares Four-Dimensional Variational Data Assimilation Scheme With the Advanced Research Weather Research and Forecasting Model".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 123.10(2018):5116-5129. |
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