Scale-dependent background-error covariance localisation
A new approach is presented and evaluated for efficiently applying scale-dependent spatial localisation to ensemble background-error covariances within an ensemble-variational data assimilation system. The approach is primarily motivated by the requirements of future data assimilation systems for gl...
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2015
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ftdoajarticles:oai:doaj.org/article:7fb8f337d0af40dea1b24ba7c700dae3 2023-05-15T15:09:20+02:00 Scale-dependent background-error covariance localisation Mark Buehner Anna Shlyaeva 2015-12-01T00:00:00Z https://doi.org/10.3402/tellusa.v67.28027 https://doaj.org/article/7fb8f337d0af40dea1b24ba7c700dae3 EN eng Stockholm University Press http://www.tellusa.net/index.php/tellusa/article/view/28027/pdf_61 https://doaj.org/toc/1600-0870 1600-0870 doi:10.3402/tellusa.v67.28027 https://doaj.org/article/7fb8f337d0af40dea1b24ba7c700dae3 Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 67, Iss 0, Pp 1-17 (2015) EnVar EnKF ensemble data assimilation covariance localisation sea-ice concentration Oceanography GC1-1581 Meteorology. Climatology QC851-999 article 2015 ftdoajarticles https://doi.org/10.3402/tellusa.v67.28027 2022-12-30T23:06:02Z A new approach is presented and evaluated for efficiently applying scale-dependent spatial localisation to ensemble background-error covariances within an ensemble-variational data assimilation system. The approach is primarily motivated by the requirements of future data assimilation systems for global numerical weather prediction that will be capable of resolving the convective scale. Such systems must estimate the global and synoptic scales at least as well as current global systems while also effectively making use of information from frequent and spatially dense observation networks to constrain convective-scale features. Scale-dependent covariance localisation allows a wider range of scales to be efficiently estimated while simultaneously assimilating all available observations. In the context of an idealised numerical experiment, it is shown that using scale-dependent localisation produces an improved ensemble-based estimate of spatially varying covariances as compared with standard spatial localisation. When applied to an ensemble of Arctic sea-ice concentration, it is demonstrated that strong spatial gradients in the relative contribution of different spatial scales in the ensemble covariances result in strong spatial variations in the overall amount of spatial localisation. This feature is qualitatively similar to what might be expected when applying an adaptive localisation approach that estimates a spatially varying localisation function from the ensemble itself. When compared with standard spatial localisation, scale-dependent localisation also results in a lower analysis error for sea-ice concentration over all spatial scales. Article in Journal/Newspaper Arctic Sea ice Directory of Open Access Journals: DOAJ Articles Arctic Tellus A: Dynamic Meteorology and Oceanography 67 1 28027 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
EnVar EnKF ensemble data assimilation covariance localisation sea-ice concentration Oceanography GC1-1581 Meteorology. Climatology QC851-999 |
spellingShingle |
EnVar EnKF ensemble data assimilation covariance localisation sea-ice concentration Oceanography GC1-1581 Meteorology. Climatology QC851-999 Mark Buehner Anna Shlyaeva Scale-dependent background-error covariance localisation |
topic_facet |
EnVar EnKF ensemble data assimilation covariance localisation sea-ice concentration Oceanography GC1-1581 Meteorology. Climatology QC851-999 |
description |
A new approach is presented and evaluated for efficiently applying scale-dependent spatial localisation to ensemble background-error covariances within an ensemble-variational data assimilation system. The approach is primarily motivated by the requirements of future data assimilation systems for global numerical weather prediction that will be capable of resolving the convective scale. Such systems must estimate the global and synoptic scales at least as well as current global systems while also effectively making use of information from frequent and spatially dense observation networks to constrain convective-scale features. Scale-dependent covariance localisation allows a wider range of scales to be efficiently estimated while simultaneously assimilating all available observations. In the context of an idealised numerical experiment, it is shown that using scale-dependent localisation produces an improved ensemble-based estimate of spatially varying covariances as compared with standard spatial localisation. When applied to an ensemble of Arctic sea-ice concentration, it is demonstrated that strong spatial gradients in the relative contribution of different spatial scales in the ensemble covariances result in strong spatial variations in the overall amount of spatial localisation. This feature is qualitatively similar to what might be expected when applying an adaptive localisation approach that estimates a spatially varying localisation function from the ensemble itself. When compared with standard spatial localisation, scale-dependent localisation also results in a lower analysis error for sea-ice concentration over all spatial scales. |
format |
Article in Journal/Newspaper |
author |
Mark Buehner Anna Shlyaeva |
author_facet |
Mark Buehner Anna Shlyaeva |
author_sort |
Mark Buehner |
title |
Scale-dependent background-error covariance localisation |
title_short |
Scale-dependent background-error covariance localisation |
title_full |
Scale-dependent background-error covariance localisation |
title_fullStr |
Scale-dependent background-error covariance localisation |
title_full_unstemmed |
Scale-dependent background-error covariance localisation |
title_sort |
scale-dependent background-error covariance localisation |
publisher |
Stockholm University Press |
publishDate |
2015 |
url |
https://doi.org/10.3402/tellusa.v67.28027 https://doaj.org/article/7fb8f337d0af40dea1b24ba7c700dae3 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 67, Iss 0, Pp 1-17 (2015) |
op_relation |
http://www.tellusa.net/index.php/tellusa/article/view/28027/pdf_61 https://doaj.org/toc/1600-0870 1600-0870 doi:10.3402/tellusa.v67.28027 https://doaj.org/article/7fb8f337d0af40dea1b24ba7c700dae3 |
op_doi |
https://doi.org/10.3402/tellusa.v67.28027 |
container_title |
Tellus A: Dynamic Meteorology and Oceanography |
container_volume |
67 |
container_issue |
1 |
container_start_page |
28027 |
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1766340553506553856 |