Global sensitivity analysis of a one-dimensional ocean biogeochemical model
<jats:p>Ocean biogeochemical (BGC) models are a powerful tool for investigating ocean biogeochemistry and the global carbon cycle. The potential benefits emanating from BGC simulations and predictions are broad, with significant societal impacts from fisheries management to carbon dioxide remo...
Published in: | Socio-Environmental Systems Modelling |
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Wageningen University and Research
2023
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ftawi:oai:epic.awi.de:58261 2024-03-24T09:03:52+00:00 Global sensitivity analysis of a one-dimensional ocean biogeochemical model Mamnun, Nabir Völker, Christoph Krumscheid, Sebastian Vrekoussis, Mihalis Nerger, Lars 2023-10-06 application/pdf https://epic.awi.de/id/eprint/58261/ https://epic.awi.de/id/eprint/58261/1/Mamnun_etal_SESMO5_18613_2023.pdf https://doi.org/10.18174/sesmo.18613 https://hdl.handle.net/10013/epic.d1404fe9-4eff-46a7-884c-b6aaae1d670f unknown Wageningen University and Research https://epic.awi.de/id/eprint/58261/1/Mamnun_etal_SESMO5_18613_2023.pdf Mamnun, N. , Völker, C. orcid:0000-0003-3032-114X , Krumscheid, S. , Vrekoussis, M. and Nerger, L. orcid:0000-0002-1908-1010 (2023) Global sensitivity analysis of a one-dimensional ocean biogeochemical model , Socio-Environmental Systems Modelling, 5 , pp. 1-30 . doi:10.18174/sesmo.18613 <https://doi.org/10.18174/sesmo.18613> , hdl:10013/epic.d1404fe9-4eff-46a7-884c-b6aaae1d670f EPIC3Socio-Environmental Systems Modelling, Wageningen University and Research, 5, pp. 1-30, ISSN: 2663-3027 Article peerRev 2023 ftawi https://doi.org/10.18174/sesmo.18613 2024-02-27T09:55:26Z <jats:p>Ocean biogeochemical (BGC) models are a powerful tool for investigating ocean biogeochemistry and the global carbon cycle. The potential benefits emanating from BGC simulations and predictions are broad, with significant societal impacts from fisheries management to carbon dioxide removal and policy-making. These models contain numerous parameters, each coupled with large uncertainties, leading to significant uncertainty in the model outputs. This study performs a global sensitivity analysis (GSA) of an ocean BGC model to identify the uncertain parameters that impact the variability of model outputs most. The BGC model Regulated Ecosystem Model 2 is used in a one-dimensional configuration at two ocean sites in the North Atlantic (BATS) and the Mediterranean Sea (DYFAMED). Variance-based Sobol' indices are computed to identify the most influential parameters for each site for the quantities of interest (QoIs) commonly considered for the calibration and validation of BGC models. The most sensitive parameters are the chlorophyll to nitrogen ratio, chlorophyll degradation rate, zooplankton grazing and excretion parameters, photosynthesis parameters, and nitrogen and carbon remineralization rate. Overall, the sensitivities of most QoIs were similar across the two sites; however, some differences emerged because of different mixed layer depths. The results suggest that implementing multiple zooplankton function types in BGC models can improve BGC predictions. Further, explicitly implementing heterotrophic bacteria in the model can better simulate the carbon export production and CO2 fluxes. The study offers a comprehensive list of the most important BGC parameters that need to be quantified for future modeling applications and insights for BGC model developments. </jats:p> Article in Journal/Newspaper North Atlantic Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Socio-Environmental Systems Modelling 5 18613 |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
op_collection_id |
ftawi |
language |
unknown |
description |
<jats:p>Ocean biogeochemical (BGC) models are a powerful tool for investigating ocean biogeochemistry and the global carbon cycle. The potential benefits emanating from BGC simulations and predictions are broad, with significant societal impacts from fisheries management to carbon dioxide removal and policy-making. These models contain numerous parameters, each coupled with large uncertainties, leading to significant uncertainty in the model outputs. This study performs a global sensitivity analysis (GSA) of an ocean BGC model to identify the uncertain parameters that impact the variability of model outputs most. The BGC model Regulated Ecosystem Model 2 is used in a one-dimensional configuration at two ocean sites in the North Atlantic (BATS) and the Mediterranean Sea (DYFAMED). Variance-based Sobol' indices are computed to identify the most influential parameters for each site for the quantities of interest (QoIs) commonly considered for the calibration and validation of BGC models. The most sensitive parameters are the chlorophyll to nitrogen ratio, chlorophyll degradation rate, zooplankton grazing and excretion parameters, photosynthesis parameters, and nitrogen and carbon remineralization rate. Overall, the sensitivities of most QoIs were similar across the two sites; however, some differences emerged because of different mixed layer depths. The results suggest that implementing multiple zooplankton function types in BGC models can improve BGC predictions. Further, explicitly implementing heterotrophic bacteria in the model can better simulate the carbon export production and CO2 fluxes. The study offers a comprehensive list of the most important BGC parameters that need to be quantified for future modeling applications and insights for BGC model developments. </jats:p> |
format |
Article in Journal/Newspaper |
author |
Mamnun, Nabir Völker, Christoph Krumscheid, Sebastian Vrekoussis, Mihalis Nerger, Lars |
spellingShingle |
Mamnun, Nabir Völker, Christoph Krumscheid, Sebastian Vrekoussis, Mihalis Nerger, Lars Global sensitivity analysis of a one-dimensional ocean biogeochemical model |
author_facet |
Mamnun, Nabir Völker, Christoph Krumscheid, Sebastian Vrekoussis, Mihalis Nerger, Lars |
author_sort |
Mamnun, Nabir |
title |
Global sensitivity analysis of a one-dimensional ocean biogeochemical model |
title_short |
Global sensitivity analysis of a one-dimensional ocean biogeochemical model |
title_full |
Global sensitivity analysis of a one-dimensional ocean biogeochemical model |
title_fullStr |
Global sensitivity analysis of a one-dimensional ocean biogeochemical model |
title_full_unstemmed |
Global sensitivity analysis of a one-dimensional ocean biogeochemical model |
title_sort |
global sensitivity analysis of a one-dimensional ocean biogeochemical model |
publisher |
Wageningen University and Research |
publishDate |
2023 |
url |
https://epic.awi.de/id/eprint/58261/ https://epic.awi.de/id/eprint/58261/1/Mamnun_etal_SESMO5_18613_2023.pdf https://doi.org/10.18174/sesmo.18613 https://hdl.handle.net/10013/epic.d1404fe9-4eff-46a7-884c-b6aaae1d670f |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
EPIC3Socio-Environmental Systems Modelling, Wageningen University and Research, 5, pp. 1-30, ISSN: 2663-3027 |
op_relation |
https://epic.awi.de/id/eprint/58261/1/Mamnun_etal_SESMO5_18613_2023.pdf Mamnun, N. , Völker, C. orcid:0000-0003-3032-114X , Krumscheid, S. , Vrekoussis, M. and Nerger, L. orcid:0000-0002-1908-1010 (2023) Global sensitivity analysis of a one-dimensional ocean biogeochemical model , Socio-Environmental Systems Modelling, 5 , pp. 1-30 . doi:10.18174/sesmo.18613 <https://doi.org/10.18174/sesmo.18613> , hdl:10013/epic.d1404fe9-4eff-46a7-884c-b6aaae1d670f |
op_doi |
https://doi.org/10.18174/sesmo.18613 |
container_title |
Socio-Environmental Systems Modelling |
container_volume |
5 |
container_start_page |
18613 |
_version_ |
1794404880833576960 |