Four-dimensional variational data assimilation for a limited area model
A 4-dimensional variational data assimilation (4D-Var) scheme for the HIgh Resolution Limited Area Model (HIRLAM) forecasting system is described in this article. The innovative approaches to the multi-incremental formulation, the weak digital filter constraint and the semi-Lagrangian time integrati...
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| Autor*in: |
Sigurdur Thorsteinsson [verfasserIn] Tomas Wilhelmsson [verfasserIn] Ole Vignes [verfasserIn] Magnus Lindskog [verfasserIn] Kristian Mogensen [verfasserIn] Xiaohua Yang [verfasserIn] Xiang-Yu Huang [verfasserIn] Nils Gustafsson [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2012 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Tellus: Series A, Dynamic Meteorology and Oceanography ; 64(2012), 0, Seite 29 volume:64 ; year:2012 ; number:0 ; pages:29 |
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| Links: |
Link aufrufen |
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| DOI / URN: |
10.3402/tellusa.v64i0.14985 |
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DOAJ04043513X |
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| 520 | |a A 4-dimensional variational data assimilation (4D-Var) scheme for the HIgh Resolution Limited Area Model (HIRLAM) forecasting system is described in this article. The innovative approaches to the multi-incremental formulation, the weak digital filter constraint and the semi-Lagrangian time integration are highlighted with some details. The implicit dynamical structure functions are discussed using single observation experiments, and the sensitivity to various parameters of the 4D-Var formulation is illustrated. To assess the meteorological impact of HIRLAM 4D-Var, data assimilation experiments for five periods of 1 month each were performed, using HIRLAM 3D-Var as a reference. It is shown that the HIRLAM 4D-Var consistently out-performs the HIRLAM 3D-Var, in particular for cases with strong mesoscale storm developments. The computational performance of the HIRLAM 4D-Var is also discussed.The review process was handled by Subject Editor Abdel Hannachi | ||
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verfasserin |
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four-dimensional variational data assimilation for a limited area model |
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GC1-1581 |
| title_auth |
Four-dimensional variational data assimilation for a limited area model |
| abstract |
A 4-dimensional variational data assimilation (4D-Var) scheme for the HIgh Resolution Limited Area Model (HIRLAM) forecasting system is described in this article. The innovative approaches to the multi-incremental formulation, the weak digital filter constraint and the semi-Lagrangian time integration are highlighted with some details. The implicit dynamical structure functions are discussed using single observation experiments, and the sensitivity to various parameters of the 4D-Var formulation is illustrated. To assess the meteorological impact of HIRLAM 4D-Var, data assimilation experiments for five periods of 1 month each were performed, using HIRLAM 3D-Var as a reference. It is shown that the HIRLAM 4D-Var consistently out-performs the HIRLAM 3D-Var, in particular for cases with strong mesoscale storm developments. The computational performance of the HIRLAM 4D-Var is also discussed.The review process was handled by Subject Editor Abdel Hannachi |
| abstractGer |
A 4-dimensional variational data assimilation (4D-Var) scheme for the HIgh Resolution Limited Area Model (HIRLAM) forecasting system is described in this article. The innovative approaches to the multi-incremental formulation, the weak digital filter constraint and the semi-Lagrangian time integration are highlighted with some details. The implicit dynamical structure functions are discussed using single observation experiments, and the sensitivity to various parameters of the 4D-Var formulation is illustrated. To assess the meteorological impact of HIRLAM 4D-Var, data assimilation experiments for five periods of 1 month each were performed, using HIRLAM 3D-Var as a reference. It is shown that the HIRLAM 4D-Var consistently out-performs the HIRLAM 3D-Var, in particular for cases with strong mesoscale storm developments. The computational performance of the HIRLAM 4D-Var is also discussed.The review process was handled by Subject Editor Abdel Hannachi |
| abstract_unstemmed |
A 4-dimensional variational data assimilation (4D-Var) scheme for the HIgh Resolution Limited Area Model (HIRLAM) forecasting system is described in this article. The innovative approaches to the multi-incremental formulation, the weak digital filter constraint and the semi-Lagrangian time integration are highlighted with some details. The implicit dynamical structure functions are discussed using single observation experiments, and the sensitivity to various parameters of the 4D-Var formulation is illustrated. To assess the meteorological impact of HIRLAM 4D-Var, data assimilation experiments for five periods of 1 month each were performed, using HIRLAM 3D-Var as a reference. It is shown that the HIRLAM 4D-Var consistently out-performs the HIRLAM 3D-Var, in particular for cases with strong mesoscale storm developments. The computational performance of the HIRLAM 4D-Var is also discussed.The review process was handled by Subject Editor Abdel Hannachi |
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Four-dimensional variational data assimilation for a limited area model |
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https://doi.org/10.3402/tellusa.v64i0.14985 https://doaj.org/article/b4ede5707e924360a5642092f5acd4ea http://www.tellusa.net/index.php/tellusa/article/view/14985/pdf_1 https://doaj.org/toc/0280-6495 https://doaj.org/toc/1600-0870 |
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| author2 |
Tomas Wilhelmsson Ole Vignes Magnus Lindskog Kristian Mogensen Xiaohua Yang Xiang-Yu Huang Nils Gustafsson |
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Tomas Wilhelmsson Ole Vignes Magnus Lindskog Kristian Mogensen Xiaohua Yang Xiang-Yu Huang Nils Gustafsson |
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GC - Oceanography |
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10.3402/tellusa.v64i0.14985 |
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| up_date |
2024-07-03T14:50:36.238Z |
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