Implementing a variational data assimilation system in an operational 1/4 degree global ocean model
Abstract This article describes the implementation of an incremental first guess at an appropriate time three‐dimensional variational (3 DVAR ) data assimilation scheme, NEMOVAR , in the Met Office's operational 1/4 degree global ocean model. NEMOVAR assimilates observations of sea‐surface temp...
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crwiley:10.1002/qj.2388 2024-06-23T07:56:42+00:00 Implementing a variational data assimilation system in an operational 1/4 degree global ocean model Waters, Jennifer Lea, Daniel J. Martin, Matthew J. Mirouze, Isabelle Weaver, Anthony While, James Met Office 2014 http://dx.doi.org/10.1002/qj.2388 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2388 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2388 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Quarterly Journal of the Royal Meteorological Society volume 141, issue 687, page 333-349 ISSN 0035-9009 1477-870X journal-article 2014 crwiley https://doi.org/10.1002/qj.2388 2024-06-13T04:19:49Z Abstract This article describes the implementation of an incremental first guess at an appropriate time three‐dimensional variational (3 DVAR ) data assimilation scheme, NEMOVAR , in the Met Office's operational 1/4 degree global ocean model. NEMOVAR assimilates observations of sea‐surface temperature ( SST ), sea‐surface height ( SSH ), in situ temperature and salinity profiles and sea ice concentration. The Met Office is the first centre to implement NEMOVAR at 1/4 degree and the required developments are discussed, with particular focus on the specification of the background‐error covariances. Background‐error correlations in NEMOVAR are modelled using a diffusion operator. The horizontal background‐error correlations for temperature, salinity and sea ice concentration are parametrized using the Rossby radius, which produces relatively short correlation length‐scales at mid to high latitudes, while a flow‐dependent mixed‐layer depth parametrization is used to define the vertical length‐scales for the 3D variables. Results from a one‐year reanalysis with NEMOVAR are presented and compared with the preceding operational data assimilation scheme at the Met Office. NEMOVAR is shown to provide significant improvements to SST , SSH and sea ice concentration fields, with the largest improvements seen in regions of high variability such as eddy shedding and frontal regions and the marginal ice zone. This improvement is associated with shorter correlation length‐scales in the extratropics and an improved fit to observations in NEMOVAR . Some degradation to subsurface temperature and salinity fields where data are sparse is identified and this will be the focus of future improvements to the system. Article in Journal/Newspaper Sea ice Wiley Online Library Quarterly Journal of the Royal Meteorological Society 141 687 333 349 |
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Wiley Online Library |
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English |
description |
Abstract This article describes the implementation of an incremental first guess at an appropriate time three‐dimensional variational (3 DVAR ) data assimilation scheme, NEMOVAR , in the Met Office's operational 1/4 degree global ocean model. NEMOVAR assimilates observations of sea‐surface temperature ( SST ), sea‐surface height ( SSH ), in situ temperature and salinity profiles and sea ice concentration. The Met Office is the first centre to implement NEMOVAR at 1/4 degree and the required developments are discussed, with particular focus on the specification of the background‐error covariances. Background‐error correlations in NEMOVAR are modelled using a diffusion operator. The horizontal background‐error correlations for temperature, salinity and sea ice concentration are parametrized using the Rossby radius, which produces relatively short correlation length‐scales at mid to high latitudes, while a flow‐dependent mixed‐layer depth parametrization is used to define the vertical length‐scales for the 3D variables. Results from a one‐year reanalysis with NEMOVAR are presented and compared with the preceding operational data assimilation scheme at the Met Office. NEMOVAR is shown to provide significant improvements to SST , SSH and sea ice concentration fields, with the largest improvements seen in regions of high variability such as eddy shedding and frontal regions and the marginal ice zone. This improvement is associated with shorter correlation length‐scales in the extratropics and an improved fit to observations in NEMOVAR . Some degradation to subsurface temperature and salinity fields where data are sparse is identified and this will be the focus of future improvements to the system. |
author2 |
Met Office |
format |
Article in Journal/Newspaper |
author |
Waters, Jennifer Lea, Daniel J. Martin, Matthew J. Mirouze, Isabelle Weaver, Anthony While, James |
spellingShingle |
Waters, Jennifer Lea, Daniel J. Martin, Matthew J. Mirouze, Isabelle Weaver, Anthony While, James Implementing a variational data assimilation system in an operational 1/4 degree global ocean model |
author_facet |
Waters, Jennifer Lea, Daniel J. Martin, Matthew J. Mirouze, Isabelle Weaver, Anthony While, James |
author_sort |
Waters, Jennifer |
title |
Implementing a variational data assimilation system in an operational 1/4 degree global ocean model |
title_short |
Implementing a variational data assimilation system in an operational 1/4 degree global ocean model |
title_full |
Implementing a variational data assimilation system in an operational 1/4 degree global ocean model |
title_fullStr |
Implementing a variational data assimilation system in an operational 1/4 degree global ocean model |
title_full_unstemmed |
Implementing a variational data assimilation system in an operational 1/4 degree global ocean model |
title_sort |
implementing a variational data assimilation system in an operational 1/4 degree global ocean model |
publisher |
Wiley |
publishDate |
2014 |
url |
http://dx.doi.org/10.1002/qj.2388 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2388 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2388 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Quarterly Journal of the Royal Meteorological Society volume 141, issue 687, page 333-349 ISSN 0035-9009 1477-870X |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/qj.2388 |
container_title |
Quarterly Journal of the Royal Meteorological Society |
container_volume |
141 |
container_issue |
687 |
container_start_page |
333 |
op_container_end_page |
349 |
_version_ |
1802649984817954816 |