globalchange  > 气候减缓与适应
DOI: 10.1029/2017JD027529
Scopus记录号: 2-s2.0-85047487339
论文题名:
A Multigrid Nonlinear Least Squares Four-Dimensional Variational Data Assimilation Scheme With the Advanced Research Weather Research and Forecasting Model
作者: Zhang H.; Tian X.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2018
卷: 123, 期:10
起始页码: 5116
结束页码: 5129
语种: 英语
英文关键词: data assimilation ; multigrid ; NLS-4DVar ; WRF
英文摘要: The motions of the atmosphere have multiscale properties in space and/or time, and the background error covariance matrix (Β) 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. ©2018. The Authors.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/113854
Appears in Collections:气候减缓与适应

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作者单位: International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China

Recommended Citation:
Zhang H.,Tian X.. 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,2018-01-01,123(10)
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