Ensemble spread-based assessment of observation impact: Application to a global ocean analysis system
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 independen...
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ftingv:oai:www.earth-prints.org:2122/8587 2023-05-15T18:25:55+02:00 Ensemble spread-based assessment of observation impact: Application to a global ocean analysis system Storto, A. Masina, S. Dobricic, S. Storto, A.; CMCC Masina, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia Dobricic, S.; CMCC CMCC Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia 2013 http://hdl.handle.net/2122/8587 https://doi.org/10.1002/qj.2071 en eng Quaterly Journal ot the Royal Meteorological Society /139 (2013) http://hdl.handle.net/2122/8587 doi:10.1002/qj.2071 restricted ocean modeling data assimilation 03. Hydrosphere::03.01. General::03.01.04. Ocean data assimilation and reanalysis article 2013 ftingv https://doi.org/10.1002/qj.2071 2022-07-29T06:06:28Z 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. Published 1842–1862 ... Article in Journal/Newspaper Southern Ocean Earth-Prints (Istituto Nazionale di Geofisica e Vulcanologia) Southern Ocean Quarterly Journal of the Royal Meteorological Society 139 676 1842 1862 |
institution |
Open Polar |
collection |
Earth-Prints (Istituto Nazionale di Geofisica e Vulcanologia) |
op_collection_id |
ftingv |
language |
English |
topic |
ocean modeling data assimilation 03. Hydrosphere::03.01. General::03.01.04. Ocean data assimilation and reanalysis |
spellingShingle |
ocean modeling data assimilation 03. Hydrosphere::03.01. General::03.01.04. Ocean data assimilation and reanalysis Storto, A. Masina, S. Dobricic, S. Ensemble spread-based assessment of observation impact: Application to a global ocean analysis system |
topic_facet |
ocean modeling data assimilation 03. Hydrosphere::03.01. General::03.01.04. Ocean data assimilation and reanalysis |
description |
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. Published 1842–1862 ... |
author2 |
Storto, A.; CMCC Masina, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia Dobricic, S.; CMCC CMCC Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia |
format |
Article in Journal/Newspaper |
author |
Storto, A. Masina, S. Dobricic, S. |
author_facet |
Storto, A. Masina, S. Dobricic, S. |
author_sort |
Storto, A. |
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 |
publishDate |
2013 |
url |
http://hdl.handle.net/2122/8587 https://doi.org/10.1002/qj.2071 |
geographic |
Southern Ocean |
geographic_facet |
Southern Ocean |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_relation |
Quaterly Journal ot the Royal Meteorological Society /139 (2013) http://hdl.handle.net/2122/8587 doi:10.1002/qj.2071 |
op_rights |
restricted |
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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1766207635880673280 |