Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic
International audience Given the recent focus on developing new data assimilation systems for biological models, we present in this study the application of a newly developed state-parameters estimation tool for a marine ecosystem model. The data assimilation scheme is based on the original Ensemble...
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Online Access: | https://hal.science/hal-02960626 https://doi.org/10.1016/j.jmarsys.2016.12.003 |
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ftutoulouse3hal:oai:HAL:hal-02960626v1 2023-12-17T10:46:29+01:00 Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic Gharamti, M.E. Samuelsen, A. Bertino, L. Simon, Ehouarn Korosov, A. Daewel, Ute Nansen Environmental and Remote Sensing Center Bergen (NERSC) National Center for Atmospheric Research Boulder (NCAR) Algorithmes Parallèles et Optimisation (IRIT-APO) Institut de recherche en informatique de Toulouse (IRIT) Université Toulouse Capitole (UT Capitole) Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J) Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP) Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI) Université Toulouse - Jean Jaurès (UT2J) Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole) Université de Toulouse (UT) Institut National Polytechnique (Toulouse) (Toulouse INP) 2017-04 https://hal.science/hal-02960626 https://doi.org/10.1016/j.jmarsys.2016.12.003 en eng HAL CCSD Elsevier info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmarsys.2016.12.003 hal-02960626 https://hal.science/hal-02960626 doi:10.1016/j.jmarsys.2016.12.003 ISSN: 0924-7963 Journal of Marine Systems https://hal.science/hal-02960626 Journal of Marine Systems, 2017, 168, pp.1-16. ⟨10.1016/j.jmarsys.2016.12.003⟩ https://www.sciencedirect.com/science/article/pii/S0924796316304407?via%3Dihub Biogeochemical parameters State-parameters estimation Nutrients profiles and chlorophyll-a Filtering and smoothing OSA-EnKF [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry [INFO]Computer Science [cs] info:eu-repo/semantics/article Journal articles 2017 ftutoulouse3hal https://doi.org/10.1016/j.jmarsys.2016.12.003 2023-11-22T18:06:32Z International audience Given the recent focus on developing new data assimilation systems for biological models, we present in this study the application of a newly developed state-parameters estimation tool for a marine ecosystem model. The data assimilation scheme is based on the original Ensemble Kalman Filter (EnKF) algorithm and further applies a One-Step-Ahead smoothing to the state variables. The state-parameters estimation scheme, referred to as OSA-EnKF, further transforms the state variables, parameters and observations to a Gaussian space using a predefined anamorphosis formulation, before applying the update. The performance of the OSA-EnKF is tested against the standard Joint- and Dual-EnKF schemes using a one-dimensional configuration of the coupled General Ocean Turbulence Model and the Norwegian Ecological Model (GOTM-NORWECOM) in the North Atlantic. Nutrient profile data (up to 2000 m deep) and surface chlorophyll-a measurements at Mike weather station (station M: 66° N, 2° E) are used to estimate selected biogeochemical parameters for phytoplankton and zooplankton. The filters are analyzed in terms of computational complexity and accuracy of the state and parameters estimates. Assimilation results suggest that the OSA-EnKF is capable of providing more accurate and dynamically consistent state and parameters estimates compared to the two other ensemble schemes. Convergence and interdependence features of the estimated parameters in relation to the major biological processes are thoroughly discussed. The optimized parameters are assessed and found useful, enhancing the prediction capability and the seasonal variability of the coupled GOTM-NORWECOM system by up to 30%. Article in Journal/Newspaper North Atlantic Université Toulouse III - Paul Sabatier: HAL-UPS Journal of Marine Systems 168 1 16 |
institution |
Open Polar |
collection |
Université Toulouse III - Paul Sabatier: HAL-UPS |
op_collection_id |
ftutoulouse3hal |
language |
English |
topic |
Biogeochemical parameters State-parameters estimation Nutrients profiles and chlorophyll-a Filtering and smoothing OSA-EnKF [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry [INFO]Computer Science [cs] |
spellingShingle |
Biogeochemical parameters State-parameters estimation Nutrients profiles and chlorophyll-a Filtering and smoothing OSA-EnKF [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry [INFO]Computer Science [cs] Gharamti, M.E. Samuelsen, A. Bertino, L. Simon, Ehouarn Korosov, A. Daewel, Ute Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic |
topic_facet |
Biogeochemical parameters State-parameters estimation Nutrients profiles and chlorophyll-a Filtering and smoothing OSA-EnKF [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry [INFO]Computer Science [cs] |
description |
International audience Given the recent focus on developing new data assimilation systems for biological models, we present in this study the application of a newly developed state-parameters estimation tool for a marine ecosystem model. The data assimilation scheme is based on the original Ensemble Kalman Filter (EnKF) algorithm and further applies a One-Step-Ahead smoothing to the state variables. The state-parameters estimation scheme, referred to as OSA-EnKF, further transforms the state variables, parameters and observations to a Gaussian space using a predefined anamorphosis formulation, before applying the update. The performance of the OSA-EnKF is tested against the standard Joint- and Dual-EnKF schemes using a one-dimensional configuration of the coupled General Ocean Turbulence Model and the Norwegian Ecological Model (GOTM-NORWECOM) in the North Atlantic. Nutrient profile data (up to 2000 m deep) and surface chlorophyll-a measurements at Mike weather station (station M: 66° N, 2° E) are used to estimate selected biogeochemical parameters for phytoplankton and zooplankton. The filters are analyzed in terms of computational complexity and accuracy of the state and parameters estimates. Assimilation results suggest that the OSA-EnKF is capable of providing more accurate and dynamically consistent state and parameters estimates compared to the two other ensemble schemes. Convergence and interdependence features of the estimated parameters in relation to the major biological processes are thoroughly discussed. The optimized parameters are assessed and found useful, enhancing the prediction capability and the seasonal variability of the coupled GOTM-NORWECOM system by up to 30%. |
author2 |
Nansen Environmental and Remote Sensing Center Bergen (NERSC) National Center for Atmospheric Research Boulder (NCAR) Algorithmes Parallèles et Optimisation (IRIT-APO) Institut de recherche en informatique de Toulouse (IRIT) Université Toulouse Capitole (UT Capitole) Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J) Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP) Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI) Université Toulouse - Jean Jaurès (UT2J) Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole) Université de Toulouse (UT) Institut National Polytechnique (Toulouse) (Toulouse INP) |
format |
Article in Journal/Newspaper |
author |
Gharamti, M.E. Samuelsen, A. Bertino, L. Simon, Ehouarn Korosov, A. Daewel, Ute |
author_facet |
Gharamti, M.E. Samuelsen, A. Bertino, L. Simon, Ehouarn Korosov, A. Daewel, Ute |
author_sort |
Gharamti, M.E. |
title |
Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic |
title_short |
Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic |
title_full |
Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic |
title_fullStr |
Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic |
title_full_unstemmed |
Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic |
title_sort |
online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: application to a one-dimensional model in the north atlantic |
publisher |
HAL CCSD |
publishDate |
2017 |
url |
https://hal.science/hal-02960626 https://doi.org/10.1016/j.jmarsys.2016.12.003 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
ISSN: 0924-7963 Journal of Marine Systems https://hal.science/hal-02960626 Journal of Marine Systems, 2017, 168, pp.1-16. ⟨10.1016/j.jmarsys.2016.12.003⟩ https://www.sciencedirect.com/science/article/pii/S0924796316304407?via%3Dihub |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmarsys.2016.12.003 hal-02960626 https://hal.science/hal-02960626 doi:10.1016/j.jmarsys.2016.12.003 |
op_doi |
https://doi.org/10.1016/j.jmarsys.2016.12.003 |
container_title |
Journal of Marine Systems |
container_volume |
168 |
container_start_page |
1 |
op_container_end_page |
16 |
_version_ |
1785569986663677952 |