Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data
International audience In spite of recent advances, biogeochemical models are still unable to represent the full complexity of natural ecosystems. Their formulations are mainly based on empirical laws involving many parameters. Improving biogeochemical models therefore requires to properly character...
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ftccsdartic:oai:HAL:insu-01351649v1 2023-05-15T17:34:21+02:00 Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data Garnier, Florent Brankart, Jean-Michel Brasseur, Pierre Cosme, Emmanuel Laboratoire de glaciologie et géophysique de l'environnement (LGGE) Observatoire des Sciences de l'Univers de Grenoble (OSUG ) 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 Grenoble Alpes 2016-2019 (UGA 2016-2019 )-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 Grenoble Alpes 2016-2019 (UGA 2016-2019 )-Centre National de la Recherche Scientifique (CNRS) 2016-03 https://hal-insu.archives-ouvertes.fr/insu-01351649 https://doi.org/10.1016/j.jmarsys.2015.10.012 en eng HAL CCSD Elsevier info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmarsys.2015.10.012 insu-01351649 https://hal-insu.archives-ouvertes.fr/insu-01351649 doi:10.1016/j.jmarsys.2015.10.012 ISSN: 0924-7963 Journal of Marine Systems https://hal-insu.archives-ouvertes.fr/insu-01351649 Journal of Marine Systems, Elsevier, 2016, 155, pp.59-72. ⟨10.1016/j.jmarsys.2015.10.012⟩ [SDE]Environmental Sciences info:eu-repo/semantics/article Journal articles 2016 ftccsdartic https://doi.org/10.1016/j.jmarsys.2015.10.012 2021-11-07T04:15:59Z International audience In spite of recent advances, biogeochemical models are still unable to represent the full complexity of natural ecosystems. Their formulations are mainly based on empirical laws involving many parameters. Improving biogeochemical models therefore requires to properly characterize model uncertainties and their consequences. Subsequently, this paper investigates the potential of using random processes to simulate some uncertainties of the 1/4° coupled Physical–Biogeochemical NEMO/PISCES model of the North Atlantic ocean.Starting from a deterministic simulation performed with the original PISCES formulation, we propose a generic method based on AR(1) random processes to generate perturbations with temporal and spatial correlations. These perturbations are introduced into the model formulations to simulate 2 classes of uncertainties: the uncertainties on biogeochemical parameters and the uncertainties induced by unresolved scales in the presence of non-linear processes. Using these stochastic parameterizations, a probabilistic version of PISCES is designed and a 60-member ensemble simulation is performed.With respect to the simulation of chlorophyll, the relevance of the probabilistic configuration and the impacts of these stochastic parameterizations are assessed. In particular, it is shown that the ensemble simulation is in good agreement with the SeaWIFS ocean color data. Using these observations, the statistical consistency (reliability) of the ensemble is evaluated with rank histograms. Finally, the benefits expected from the probabilistic description of uncertainties (model error) are discussed in the context of future ocean color data assimilation. Article in Journal/Newspaper North Atlantic Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Journal of Marine Systems 155 59 72 |
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Open Polar |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
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ftccsdartic |
language |
English |
topic |
[SDE]Environmental Sciences |
spellingShingle |
[SDE]Environmental Sciences Garnier, Florent Brankart, Jean-Michel Brasseur, Pierre Cosme, Emmanuel Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data |
topic_facet |
[SDE]Environmental Sciences |
description |
International audience In spite of recent advances, biogeochemical models are still unable to represent the full complexity of natural ecosystems. Their formulations are mainly based on empirical laws involving many parameters. Improving biogeochemical models therefore requires to properly characterize model uncertainties and their consequences. Subsequently, this paper investigates the potential of using random processes to simulate some uncertainties of the 1/4° coupled Physical–Biogeochemical NEMO/PISCES model of the North Atlantic ocean.Starting from a deterministic simulation performed with the original PISCES formulation, we propose a generic method based on AR(1) random processes to generate perturbations with temporal and spatial correlations. These perturbations are introduced into the model formulations to simulate 2 classes of uncertainties: the uncertainties on biogeochemical parameters and the uncertainties induced by unresolved scales in the presence of non-linear processes. Using these stochastic parameterizations, a probabilistic version of PISCES is designed and a 60-member ensemble simulation is performed.With respect to the simulation of chlorophyll, the relevance of the probabilistic configuration and the impacts of these stochastic parameterizations are assessed. In particular, it is shown that the ensemble simulation is in good agreement with the SeaWIFS ocean color data. Using these observations, the statistical consistency (reliability) of the ensemble is evaluated with rank histograms. Finally, the benefits expected from the probabilistic description of uncertainties (model error) are discussed in the context of future ocean color data assimilation. |
author2 |
Laboratoire de glaciologie et géophysique de l'environnement (LGGE) Observatoire des Sciences de l'Univers de Grenoble (OSUG ) 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 Grenoble Alpes 2016-2019 (UGA 2016-2019 )-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 Grenoble Alpes 2016-2019 (UGA 2016-2019 )-Centre National de la Recherche Scientifique (CNRS) |
format |
Article in Journal/Newspaper |
author |
Garnier, Florent Brankart, Jean-Michel Brasseur, Pierre Cosme, Emmanuel |
author_facet |
Garnier, Florent Brankart, Jean-Michel Brasseur, Pierre Cosme, Emmanuel |
author_sort |
Garnier, Florent |
title |
Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data |
title_short |
Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data |
title_full |
Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data |
title_fullStr |
Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data |
title_full_unstemmed |
Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data |
title_sort |
stochastic parameterizations of biogeochemical uncertainties in a 1/4° nemo/pisces model for probabilistic comparisons with ocean color data |
publisher |
HAL CCSD |
publishDate |
2016 |
url |
https://hal-insu.archives-ouvertes.fr/insu-01351649 https://doi.org/10.1016/j.jmarsys.2015.10.012 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
ISSN: 0924-7963 Journal of Marine Systems https://hal-insu.archives-ouvertes.fr/insu-01351649 Journal of Marine Systems, Elsevier, 2016, 155, pp.59-72. ⟨10.1016/j.jmarsys.2015.10.012⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmarsys.2015.10.012 insu-01351649 https://hal-insu.archives-ouvertes.fr/insu-01351649 doi:10.1016/j.jmarsys.2015.10.012 |
op_doi |
https://doi.org/10.1016/j.jmarsys.2015.10.012 |
container_title |
Journal of Marine Systems |
container_volume |
155 |
container_start_page |
59 |
op_container_end_page |
72 |
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1766133142452699136 |