Ensemble spread‐based assessment of observation impact: application to a global ocean analysis system
Abstract This article explores an ensemble strategy for evaluating the impact of different observing networks. The impact is represented by the relative ensemble spread increase, in model space, of data‐denial ensemble simulations with respect to an ‘all‐observation’ ensemble experiment, evaluated i...
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crwiley:10.1002/qj.2071 2024-06-02T08:14:50+00:00 Ensemble spread‐based assessment of observation impact: application to a global ocean analysis system Storto, Andrea Masina, Simona Dobricic, Srdjan 2012 http://dx.doi.org/10.1002/qj.2071 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2071 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2071 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Quarterly Journal of the Royal Meteorological Society volume 139, issue 676, page 1842-1862 ISSN 0035-9009 1477-870X journal-article 2012 crwiley https://doi.org/10.1002/qj.2071 2024-05-06T07:01:30Z Abstract This article explores an ensemble strategy for evaluating the impact of different observing networks. The impact is represented by the relative ensemble spread increase, in model space, of data‐denial ensemble simulations with respect to an ‘all‐observation’ ensemble experiment, evaluated independently for each observing network. The forecast‐error covariance intercomparison reduces to the ensemble spread intercomparison; thus, the method can be applied to any assimilation system and requires only the proper construction of an ensemble system, although the impact assessment results depend on the specific configuration of the investigated analysis system. Our approach allows us to determine the impact of the observing networks in model space (unlike Observing System Experiments) and for different forecast ranges of the ocean general circulation model. No tangent‐linear and adjoint coding of the ocean model are required. The method is applied for demonstration to a large‐scale global ocean variational analysis system. The ensemble members are generated by (i) perturbing the observations within the 3D‐Var assimilation scheme, (ii) perturbing the surface forcing, and (iii) stochastically perturbing the ocean model parametrisation tendencies. The impact is calculated for CTDs, XBTs, moorings, Argo, sea‐level anomaly observations and sea‐surface temperature measurements from space‐borne microwave instruments within the three‐year period from January 2003 to December 2005. It turns out, on the global scale, that altimetry exhibits the largest impact on near‐surface temperature and sea‐surface height. In contrast, deep‐ocean impacts are led by the Argo float network. As expected, space‐borne observations (sea‐level anomaly and sea‐surface temperature observations) increase their impact in the Southern Ocean, due to the lack of a robust network of in situ observations. The results of the impact on the salinity indicate the great importance of Argo floats, especially in the northern Extratropics. Article in Journal/Newspaper Southern Ocean Wiley Online Library Southern Ocean Quarterly Journal of the Royal Meteorological Society 139 676 1842 1862 |
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Wiley Online Library |
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crwiley |
language |
English |
description |
Abstract This article explores an ensemble strategy for evaluating the impact of different observing networks. The impact is represented by the relative ensemble spread increase, in model space, of data‐denial ensemble simulations with respect to an ‘all‐observation’ ensemble experiment, evaluated independently for each observing network. The forecast‐error covariance intercomparison reduces to the ensemble spread intercomparison; thus, the method can be applied to any assimilation system and requires only the proper construction of an ensemble system, although the impact assessment results depend on the specific configuration of the investigated analysis system. Our approach allows us to determine the impact of the observing networks in model space (unlike Observing System Experiments) and for different forecast ranges of the ocean general circulation model. No tangent‐linear and adjoint coding of the ocean model are required. The method is applied for demonstration to a large‐scale global ocean variational analysis system. The ensemble members are generated by (i) perturbing the observations within the 3D‐Var assimilation scheme, (ii) perturbing the surface forcing, and (iii) stochastically perturbing the ocean model parametrisation tendencies. The impact is calculated for CTDs, XBTs, moorings, Argo, sea‐level anomaly observations and sea‐surface temperature measurements from space‐borne microwave instruments within the three‐year period from January 2003 to December 2005. It turns out, on the global scale, that altimetry exhibits the largest impact on near‐surface temperature and sea‐surface height. In contrast, deep‐ocean impacts are led by the Argo float network. As expected, space‐borne observations (sea‐level anomaly and sea‐surface temperature observations) increase their impact in the Southern Ocean, due to the lack of a robust network of in situ observations. The results of the impact on the salinity indicate the great importance of Argo floats, especially in the northern Extratropics. |
format |
Article in Journal/Newspaper |
author |
Storto, Andrea Masina, Simona Dobricic, Srdjan |
spellingShingle |
Storto, Andrea Masina, Simona Dobricic, Srdjan Ensemble spread‐based assessment of observation impact: application to a global ocean analysis system |
author_facet |
Storto, Andrea Masina, Simona Dobricic, Srdjan |
author_sort |
Storto, Andrea |
title |
Ensemble spread‐based assessment of observation impact: application to a global ocean analysis system |
title_short |
Ensemble spread‐based assessment of observation impact: application to a global ocean analysis system |
title_full |
Ensemble spread‐based assessment of observation impact: application to a global ocean analysis system |
title_fullStr |
Ensemble spread‐based assessment of observation impact: application to a global ocean analysis system |
title_full_unstemmed |
Ensemble spread‐based assessment of observation impact: application to a global ocean analysis system |
title_sort |
ensemble spread‐based assessment of observation impact: application to a global ocean analysis system |
publisher |
Wiley |
publishDate |
2012 |
url |
http://dx.doi.org/10.1002/qj.2071 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2071 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2071 |
geographic |
Southern Ocean |
geographic_facet |
Southern Ocean |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_source |
Quarterly Journal of the Royal Meteorological Society volume 139, issue 676, page 1842-1862 ISSN 0035-9009 1477-870X |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/qj.2071 |
container_title |
Quarterly Journal of the Royal Meteorological Society |
container_volume |
139 |
container_issue |
676 |
container_start_page |
1842 |
op_container_end_page |
1862 |
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1800738820103077888 |