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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Published in:Quarterly Journal of the Royal Meteorological Society
Main Authors: Storto, Andrea, Masina, Simona, Dobricic, Srdjan
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2012
Subjects:
Online Access:http://dx.doi.org/10.1002/qj.2071
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spelling 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
institution Open Polar
collection Wiley Online Library
op_collection_id 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
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