Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean
International audience Abstract. Satellite-derived surface chlorophyll data are assimilated daily into a three-dimensional 24-member ensemble configuration of an online-coupled NEMO (Nucleus for European Modeling of the Ocean)–PISCES (Pelagic Interaction Scheme of Carbon and Ecosystem Studies) model...
Published in: | Ocean Science |
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Main Authors: | , , , |
Other Authors: | , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2020
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Online Access: | https://hal-cnrs.archives-ouvertes.fr/hal-03366945 https://hal-cnrs.archives-ouvertes.fr/hal-03366945/document https://hal-cnrs.archives-ouvertes.fr/hal-03366945/file/os-16-1297-2020.pdf https://doi.org/10.5194/os-16-1297-2020 |
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Open Polar |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
op_collection_id |
ftccsdartic |
language |
English |
topic |
[SDU]Sciences of the Universe [physics] [SDE]Environmental Sciences |
spellingShingle |
[SDU]Sciences of the Universe [physics] [SDE]Environmental Sciences Brasseur, Pierre Santana-Falcón, Yeray Brankart, Jean Michel Garnier, Florent Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean |
topic_facet |
[SDU]Sciences of the Universe [physics] [SDE]Environmental Sciences |
description |
International audience Abstract. Satellite-derived surface chlorophyll data are assimilated daily into a three-dimensional 24-member ensemble configuration of an online-coupled NEMO (Nucleus for European Modeling of the Ocean)–PISCES (Pelagic Interaction Scheme of Carbon and Ecosystem Studies) model for the North Atlantic Ocean. A 1-year multivariate assimilation experiment is performed to evaluate the impacts on analyses and forecast ensembles. Our results demonstrate that the integration of data improves surface analysis and forecast chlorophyll representation in a major part of the model domain, where the assimilated simulation outperforms the probabilistic skills of a non-assimilated analogous simulation. However, improvements are dependent on the reliability of the prior free ensemble. A regional diagnosis shows that surface chlorophyll is overestimated in the northern limit of the subtropical North Atlantic, where the prior ensemble spread does not cover the observation's variability. There, the system cannot deal with corrections that alter the equilibrium between the observed and unobserved state variables producing instabilities that propagate into the forecast. To alleviate these inconsistencies, a 1-month sensitivity experiment in which the assimilation process is only applied to model fluctuations is performed. Results suggest the use of this methodology may decrease the effect of corrections on the correlations between state vectors. Overall, the experiments presented here evidence the need of refining the description of model's uncertainties according to the biogeochemical characteristics of each oceanic region. |
author2 |
Laboratoire des Écoulements Géophysiques et Industriels Grenoble (LEGI) Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ) Université Grenoble Alpes (UGA) Laboratoire de glaciologie et géophysique de l'environnement (LGGE) Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG) Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS) Institut des Géosciences de l’Environnement (IGE) Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ) Centre national de recherches météorologiques (CNRM) Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS) Université Toulouse 1 Capitole (UT1) Université Fédérale Toulouse Midi-Pyrénées |
format |
Article in Journal/Newspaper |
author |
Brasseur, Pierre Santana-Falcón, Yeray Brankart, Jean Michel Garnier, Florent |
author_facet |
Brasseur, Pierre Santana-Falcón, Yeray Brankart, Jean Michel Garnier, Florent |
author_sort |
Brasseur, Pierre |
title |
Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean |
title_short |
Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean |
title_full |
Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean |
title_fullStr |
Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean |
title_full_unstemmed |
Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean |
title_sort |
assimilation of chlorophyll data into a stochastic ensemble simulation for the north atlantic ocean |
publisher |
HAL CCSD |
publishDate |
2020 |
url |
https://hal-cnrs.archives-ouvertes.fr/hal-03366945 https://hal-cnrs.archives-ouvertes.fr/hal-03366945/document https://hal-cnrs.archives-ouvertes.fr/hal-03366945/file/os-16-1297-2020.pdf https://doi.org/10.5194/os-16-1297-2020 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
ISSN: 1812-0784 EISSN: 1812-0792 Ocean Science https://hal-cnrs.archives-ouvertes.fr/hal-03366945 Ocean Science, European Geosciences Union, 2020, 16 (5), pp.1297-1315. ⟨10.5194/os-16-1297-2020⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/os-16-1297-2020 hal-03366945 https://hal-cnrs.archives-ouvertes.fr/hal-03366945 https://hal-cnrs.archives-ouvertes.fr/hal-03366945/document https://hal-cnrs.archives-ouvertes.fr/hal-03366945/file/os-16-1297-2020.pdf doi:10.5194/os-16-1297-2020 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/os-16-1297-2020 |
container_title |
Ocean Science |
container_volume |
16 |
container_issue |
5 |
container_start_page |
1297 |
op_container_end_page |
1315 |
_version_ |
1766122874154778624 |
spelling |
ftccsdartic:oai:HAL:hal-03366945v1 2023-05-15T17:29:13+02:00 Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean Brasseur, Pierre Santana-Falcón, Yeray Brankart, Jean Michel Garnier, Florent Laboratoire des Écoulements Géophysiques et Industriels Grenoble (LEGI) Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ) Université Grenoble Alpes (UGA) Laboratoire de glaciologie et géophysique de l'environnement (LGGE) Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG) Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS) Institut des Géosciences de l’Environnement (IGE) Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ) Centre national de recherches météorologiques (CNRM) Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS) Université Toulouse 1 Capitole (UT1) Université Fédérale Toulouse Midi-Pyrénées 2020 https://hal-cnrs.archives-ouvertes.fr/hal-03366945 https://hal-cnrs.archives-ouvertes.fr/hal-03366945/document https://hal-cnrs.archives-ouvertes.fr/hal-03366945/file/os-16-1297-2020.pdf https://doi.org/10.5194/os-16-1297-2020 en eng HAL CCSD European Geosciences Union info:eu-repo/semantics/altIdentifier/doi/10.5194/os-16-1297-2020 hal-03366945 https://hal-cnrs.archives-ouvertes.fr/hal-03366945 https://hal-cnrs.archives-ouvertes.fr/hal-03366945/document https://hal-cnrs.archives-ouvertes.fr/hal-03366945/file/os-16-1297-2020.pdf doi:10.5194/os-16-1297-2020 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 1812-0784 EISSN: 1812-0792 Ocean Science https://hal-cnrs.archives-ouvertes.fr/hal-03366945 Ocean Science, European Geosciences Union, 2020, 16 (5), pp.1297-1315. ⟨10.5194/os-16-1297-2020⟩ [SDU]Sciences of the Universe [physics] [SDE]Environmental Sciences info:eu-repo/semantics/article Journal articles 2020 ftccsdartic https://doi.org/10.5194/os-16-1297-2020 2021-11-06T23:33:02Z International audience Abstract. Satellite-derived surface chlorophyll data are assimilated daily into a three-dimensional 24-member ensemble configuration of an online-coupled NEMO (Nucleus for European Modeling of the Ocean)–PISCES (Pelagic Interaction Scheme of Carbon and Ecosystem Studies) model for the North Atlantic Ocean. A 1-year multivariate assimilation experiment is performed to evaluate the impacts on analyses and forecast ensembles. Our results demonstrate that the integration of data improves surface analysis and forecast chlorophyll representation in a major part of the model domain, where the assimilated simulation outperforms the probabilistic skills of a non-assimilated analogous simulation. However, improvements are dependent on the reliability of the prior free ensemble. A regional diagnosis shows that surface chlorophyll is overestimated in the northern limit of the subtropical North Atlantic, where the prior ensemble spread does not cover the observation's variability. There, the system cannot deal with corrections that alter the equilibrium between the observed and unobserved state variables producing instabilities that propagate into the forecast. To alleviate these inconsistencies, a 1-month sensitivity experiment in which the assimilation process is only applied to model fluctuations is performed. Results suggest the use of this methodology may decrease the effect of corrections on the correlations between state vectors. Overall, the experiments presented here evidence the need of refining the description of model's uncertainties according to the biogeochemical characteristics of each oceanic region. Article in Journal/Newspaper North Atlantic Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Ocean Science 16 5 1297 1315 |