Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System
A short‐range high‐resolution sea ice prediction system has been developed at Environment Canada. This study describes the first steps towards transitioning this system from a simple deterministic data assimilation system based on the three‐dimensional variational (3D‐Var) approach into a data assim...
Published in: | Quarterly Journal of the Royal Meteorological Society |
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Online Access: | http://dx.doi.org/10.1002/qj.2712 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2712 https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2712 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.2712 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2712 |
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crwiley:10.1002/qj.2712 2024-06-02T08:14:16+00:00 Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System Shlyaeva, Anna Buehner, Mark Caya, Alain Lemieux, Jean‐François Smith, Gregory C. Roy, François Dupont, Frédéric Carrieres, Tom 2016 http://dx.doi.org/10.1002/qj.2712 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2712 https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2712 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.2712 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2712 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Quarterly Journal of the Royal Meteorological Society volume 142, issue 695, page 1090-1099 ISSN 0035-9009 1477-870X journal-article 2016 crwiley https://doi.org/10.1002/qj.2712 2024-05-03T12:04:22Z A short‐range high‐resolution sea ice prediction system has been developed at Environment Canada. This study describes the first steps towards transitioning this system from a simple deterministic data assimilation system based on the three‐dimensional variational (3D‐Var) approach into a data assimilation system based on an ensemble of ensemble‐variational (EnVar) analyses. First, an ensemble of 3D‐Var analyses using static background‐error covariances is implemented and used to evaluate different strategies for simulating model uncertainties during the ensemble forecast step; these range from perturbing parameters within the sea ice model to completely disabling the sea ice dynamics or thermodynamics in some of the ensemble members. The experiments show a good ensemble spread–error relationship in areas with low or high ice concentration, though more work is needed to better simulate uncertainties in areas with intermediate ice concentration. Second, results from idealized experiments with EnVar analyses using ensemble covariances are presented. They demonstrate the potential improvement of sea ice analyses from using state‐dependent multivariate ensemble covariances when assimilating ice concentration observations to correct both ice concentration and unobserved variables such as ice thickness and ocean temperature. Article in Journal/Newspaper Sea ice Wiley Online Library Canada Quarterly Journal of the Royal Meteorological Society 142 695 1090 1099 |
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Open Polar |
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Wiley Online Library |
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crwiley |
language |
English |
description |
A short‐range high‐resolution sea ice prediction system has been developed at Environment Canada. This study describes the first steps towards transitioning this system from a simple deterministic data assimilation system based on the three‐dimensional variational (3D‐Var) approach into a data assimilation system based on an ensemble of ensemble‐variational (EnVar) analyses. First, an ensemble of 3D‐Var analyses using static background‐error covariances is implemented and used to evaluate different strategies for simulating model uncertainties during the ensemble forecast step; these range from perturbing parameters within the sea ice model to completely disabling the sea ice dynamics or thermodynamics in some of the ensemble members. The experiments show a good ensemble spread–error relationship in areas with low or high ice concentration, though more work is needed to better simulate uncertainties in areas with intermediate ice concentration. Second, results from idealized experiments with EnVar analyses using ensemble covariances are presented. They demonstrate the potential improvement of sea ice analyses from using state‐dependent multivariate ensemble covariances when assimilating ice concentration observations to correct both ice concentration and unobserved variables such as ice thickness and ocean temperature. |
format |
Article in Journal/Newspaper |
author |
Shlyaeva, Anna Buehner, Mark Caya, Alain Lemieux, Jean‐François Smith, Gregory C. Roy, François Dupont, Frédéric Carrieres, Tom |
spellingShingle |
Shlyaeva, Anna Buehner, Mark Caya, Alain Lemieux, Jean‐François Smith, Gregory C. Roy, François Dupont, Frédéric Carrieres, Tom Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System |
author_facet |
Shlyaeva, Anna Buehner, Mark Caya, Alain Lemieux, Jean‐François Smith, Gregory C. Roy, François Dupont, Frédéric Carrieres, Tom |
author_sort |
Shlyaeva, Anna |
title |
Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System |
title_short |
Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System |
title_full |
Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System |
title_fullStr |
Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System |
title_full_unstemmed |
Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System |
title_sort |
towards ensemble data assimilation for the environment canada regional ice prediction system |
publisher |
Wiley |
publishDate |
2016 |
url |
http://dx.doi.org/10.1002/qj.2712 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2712 https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2712 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.2712 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2712 |
geographic |
Canada |
geographic_facet |
Canada |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Quarterly Journal of the Royal Meteorological Society volume 142, issue 695, page 1090-1099 ISSN 0035-9009 1477-870X |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/qj.2712 |
container_title |
Quarterly Journal of the Royal Meteorological Society |
container_volume |
142 |
container_issue |
695 |
container_start_page |
1090 |
op_container_end_page |
1099 |
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1800738046937661440 |