Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere–ocean model
Operational forecasting centres are currently developing data assimilation systems for coupled atmosphere–ocean models. Strongly coupled assimilation, in which a single assimilation system is applied to a coupled model, presents significant technical and scientific challenges. Hence weakly coupled a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Stockholm University Press
2015-07-01
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| Series: | Tellus: Series A, Dynamic Meteorology and Oceanography |
| Subjects: | |
| Online Access: | http://www.tellusa.net/index.php/tellusa/article/view/27025/pdf_47 |
| _version_ | 1818572030904107008 |
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| author | Polly J. Smith Alison M. Fowler Amos S. Lawless |
| author_facet | Polly J. Smith Alison M. Fowler Amos S. Lawless |
| author_sort | Polly J. Smith |
| collection | DOAJ |
| description | Operational forecasting centres are currently developing data assimilation systems for coupled atmosphere–ocean models. Strongly coupled assimilation, in which a single assimilation system is applied to a coupled model, presents significant technical and scientific challenges. Hence weakly coupled assimilation systems are being developed as a first step, in which the coupled model is used to compare the current state estimate with observations, but corrections to the atmosphere and ocean initial conditions are then calculated independently. In this paper, we provide a comprehensive description of the different coupled assimilation methodologies in the context of four-dimensional variational assimilation (4D-Var) and use an idealised framework to assess the expected benefits of moving towards coupled data assimilation. We implement an incremental 4D-Var system within an idealised single-column atmosphere–ocean model. The system has the capability to run both strongly and weakly coupled assimilations as well as uncoupled atmosphere- or ocean-only assimilations, thus allowing a systematic comparison of the different strategies for treating the coupled data assimilation problem. We present results from a series of identical twin experiments devised to investigate the behaviour and sensitivities of the different approaches. Overall, our study demonstrates the potential benefits that may be expected from coupled data assimilation. When compared to uncoupled initialisation, coupled assimilation is able to produce more balanced initial analysis fields, thus reducing initialisation shock and its impact on the subsequent forecast. Single observation experiments demonstrate how coupled assimilation systems are able to pass information between the atmosphere and ocean and therefore use near-surface data to greater effect. We show that much of this benefit may also be gained from a weakly coupled assimilation system, but that this can be sensitive to the parameters used in the assimilation. |
| first_indexed | 2024-12-14T18:52:00Z |
| format | Article |
| id | doaj.art-8e56ef4c81e645639da4ee7b6c1d3a8e |
| institution | Directory Open Access Journal |
| issn | 1600-0870 |
| language | English |
| last_indexed | 2024-12-14T18:52:00Z |
| publishDate | 2015-07-01 |
| publisher | Stockholm University Press |
| record_format | Article |
| series | Tellus: Series A, Dynamic Meteorology and Oceanography |
| spelling | doaj.art-8e56ef4c81e645639da4ee7b6c1d3a8e2022-12-21T22:51:14ZengStockholm University PressTellus: Series A, Dynamic Meteorology and Oceanography1600-08702015-07-0167012510.3402/tellusa.v67.2702527025Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere–ocean modelPolly J. Smith0Alison M. Fowler1Amos S. Lawless2 School of Mathematical and Physical Sciences, University of Reading, Reading, UK School of Mathematical and Physical Sciences, University of Reading, Reading, UK School of Mathematical and Physical Sciences, University of Reading, Reading, UKOperational forecasting centres are currently developing data assimilation systems for coupled atmosphere–ocean models. Strongly coupled assimilation, in which a single assimilation system is applied to a coupled model, presents significant technical and scientific challenges. Hence weakly coupled assimilation systems are being developed as a first step, in which the coupled model is used to compare the current state estimate with observations, but corrections to the atmosphere and ocean initial conditions are then calculated independently. In this paper, we provide a comprehensive description of the different coupled assimilation methodologies in the context of four-dimensional variational assimilation (4D-Var) and use an idealised framework to assess the expected benefits of moving towards coupled data assimilation. We implement an incremental 4D-Var system within an idealised single-column atmosphere–ocean model. The system has the capability to run both strongly and weakly coupled assimilations as well as uncoupled atmosphere- or ocean-only assimilations, thus allowing a systematic comparison of the different strategies for treating the coupled data assimilation problem. We present results from a series of identical twin experiments devised to investigate the behaviour and sensitivities of the different approaches. Overall, our study demonstrates the potential benefits that may be expected from coupled data assimilation. When compared to uncoupled initialisation, coupled assimilation is able to produce more balanced initial analysis fields, thus reducing initialisation shock and its impact on the subsequent forecast. Single observation experiments demonstrate how coupled assimilation systems are able to pass information between the atmosphere and ocean and therefore use near-surface data to greater effect. We show that much of this benefit may also be gained from a weakly coupled assimilation system, but that this can be sensitive to the parameters used in the assimilation.http://www.tellusa.net/index.php/tellusa/article/view/27025/pdf_47incremental four-dimensional variational data assimilationsingle-column modelKPP mixed layer modelinitialisationstrongly coupledweakly coupled |
| spellingShingle | Polly J. Smith Alison M. Fowler Amos S. Lawless Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere–ocean model Tellus: Series A, Dynamic Meteorology and Oceanography incremental four-dimensional variational data assimilation single-column model KPP mixed layer model initialisation strongly coupled weakly coupled |
| title | Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere–ocean model |
| title_full | Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere–ocean model |
| title_fullStr | Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere–ocean model |
| title_full_unstemmed | Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere–ocean model |
| title_short | Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere–ocean model |
| title_sort | exploring strategies for coupled 4d var data assimilation using an idealised atmosphere ocean model |
| topic | incremental four-dimensional variational data assimilation single-column model KPP mixed layer model initialisation strongly coupled weakly coupled |
| url | http://www.tellusa.net/index.php/tellusa/article/view/27025/pdf_47 |
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