Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO(3)), mixed layer depth (MLD), euphotic layer depth (Z(eu)), and sea ice con...

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Published in:Journal of Geophysical Research: Oceans
Main Authors: Lee, Younjoo J., Matrai, Patricia A., Friedrichs, Marjorie A. M., Saba, Vincent S., Aumont, Olivier, Babin, Marcel, Buitenhuis, Erik T., Chevallier, Matthieu, de Mora, Lee, Dessert, Morgane, Dunne, John P., Ellingsen, Ingrid H., Feldman, Doron, Frouin, Robert, Gehlen, Marion, Gorgues, Thomas, Ilyina, Tatiana, Jin, Meibing, John, Jasmin G., Lawrence, Jon, Manizza, Manfredi, Menkes, Christophe E., Perruche, Coralie, Le Fouest, Vincent, Popova, Ekaterina E., Romanou, Anastasia, Samuelsen, Annette, Schwinger, Jörg, Séférian, Roland, Stock, Charles A., Tjiputra, Jerry, Tremblay, L. Bruno, Ueyoshi, Kyozo, Vichi, Marcello, Yool, Andrew, Zhang, Jinlun
Format: Text
Language:English
Published: 2016
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430529/
https://doi.org/10.1002/2016JC011993
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spelling ftpubmed:oai:pubmedcentral.nih.gov:7430529 2023-05-15T14:29:16+02:00 Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models Lee, Younjoo J. Matrai, Patricia A. Friedrichs, Marjorie A. M. Saba, Vincent S. Aumont, Olivier Babin, Marcel Buitenhuis, Erik T. Chevallier, Matthieu de Mora, Lee Dessert, Morgane Dunne, John P. Ellingsen, Ingrid H. Feldman, Doron Frouin, Robert Gehlen, Marion Gorgues, Thomas Ilyina, Tatiana Jin, Meibing John, Jasmin G. Lawrence, Jon Manizza, Manfredi Menkes, Christophe E. Perruche, Coralie Le Fouest, Vincent Popova, Ekaterina E. Romanou, Anastasia Samuelsen, Annette Schwinger, Jörg Séférian, Roland Stock, Charles A. Tjiputra, Jerry Tremblay, L. Bruno Ueyoshi, Kyozo Vichi, Marcello Yool, Andrew Zhang, Jinlun 2016-11-14 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430529/ https://doi.org/10.1002/2016JC011993 en eng http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430529/ http://dx.doi.org/10.1002/2016JC011993 This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. CC-BY-NC-ND J Geophys Res Oceans Article Text 2016 ftpubmed https://doi.org/10.1002/2016JC011993 2020-08-23T00:35:12Z The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO(3)), mixed layer depth (MLD), euphotic layer depth (Z(eu)), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959–2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO(3), MLD, and Z(eu) throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO(3) was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling. Text Arctic Basin Arctic Arctic Ocean Beaufort Sea Chukchi Greenland Phytoplankton Sea ice Zooplankton PubMed Central (PMC) Arctic Arctic Ocean Greenland Journal of Geophysical Research: Oceans 121 12 8635 8669
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Article
spellingShingle Article
Lee, Younjoo J.
Matrai, Patricia A.
Friedrichs, Marjorie A. M.
Saba, Vincent S.
Aumont, Olivier
Babin, Marcel
Buitenhuis, Erik T.
Chevallier, Matthieu
de Mora, Lee
Dessert, Morgane
Dunne, John P.
Ellingsen, Ingrid H.
Feldman, Doron
Frouin, Robert
Gehlen, Marion
Gorgues, Thomas
Ilyina, Tatiana
Jin, Meibing
John, Jasmin G.
Lawrence, Jon
Manizza, Manfredi
Menkes, Christophe E.
Perruche, Coralie
Le Fouest, Vincent
Popova, Ekaterina E.
Romanou, Anastasia
Samuelsen, Annette
Schwinger, Jörg
Séférian, Roland
Stock, Charles A.
Tjiputra, Jerry
Tremblay, L. Bruno
Ueyoshi, Kyozo
Vichi, Marcello
Yool, Andrew
Zhang, Jinlun
Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models
topic_facet Article
description The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO(3)), mixed layer depth (MLD), euphotic layer depth (Z(eu)), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959–2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO(3), MLD, and Z(eu) throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO(3) was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.
format Text
author Lee, Younjoo J.
Matrai, Patricia A.
Friedrichs, Marjorie A. M.
Saba, Vincent S.
Aumont, Olivier
Babin, Marcel
Buitenhuis, Erik T.
Chevallier, Matthieu
de Mora, Lee
Dessert, Morgane
Dunne, John P.
Ellingsen, Ingrid H.
Feldman, Doron
Frouin, Robert
Gehlen, Marion
Gorgues, Thomas
Ilyina, Tatiana
Jin, Meibing
John, Jasmin G.
Lawrence, Jon
Manizza, Manfredi
Menkes, Christophe E.
Perruche, Coralie
Le Fouest, Vincent
Popova, Ekaterina E.
Romanou, Anastasia
Samuelsen, Annette
Schwinger, Jörg
Séférian, Roland
Stock, Charles A.
Tjiputra, Jerry
Tremblay, L. Bruno
Ueyoshi, Kyozo
Vichi, Marcello
Yool, Andrew
Zhang, Jinlun
author_facet Lee, Younjoo J.
Matrai, Patricia A.
Friedrichs, Marjorie A. M.
Saba, Vincent S.
Aumont, Olivier
Babin, Marcel
Buitenhuis, Erik T.
Chevallier, Matthieu
de Mora, Lee
Dessert, Morgane
Dunne, John P.
Ellingsen, Ingrid H.
Feldman, Doron
Frouin, Robert
Gehlen, Marion
Gorgues, Thomas
Ilyina, Tatiana
Jin, Meibing
John, Jasmin G.
Lawrence, Jon
Manizza, Manfredi
Menkes, Christophe E.
Perruche, Coralie
Le Fouest, Vincent
Popova, Ekaterina E.
Romanou, Anastasia
Samuelsen, Annette
Schwinger, Jörg
Séférian, Roland
Stock, Charles A.
Tjiputra, Jerry
Tremblay, L. Bruno
Ueyoshi, Kyozo
Vichi, Marcello
Yool, Andrew
Zhang, Jinlun
author_sort Lee, Younjoo J.
title Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models
title_short Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models
title_full Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models
title_fullStr Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models
title_full_unstemmed Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models
title_sort net primary productivity estimates and environmental variables in the arctic ocean: an assessment of coupled physical-biogeochemical models
publishDate 2016
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430529/
https://doi.org/10.1002/2016JC011993
geographic Arctic
Arctic Ocean
Greenland
geographic_facet Arctic
Arctic Ocean
Greenland
genre Arctic Basin
Arctic
Arctic Ocean
Beaufort Sea
Chukchi
Greenland
Phytoplankton
Sea ice
Zooplankton
genre_facet Arctic Basin
Arctic
Arctic Ocean
Beaufort Sea
Chukchi
Greenland
Phytoplankton
Sea ice
Zooplankton
op_source J Geophys Res Oceans
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430529/
http://dx.doi.org/10.1002/2016JC011993
op_rights This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
op_rightsnorm CC-BY-NC-ND
op_doi https://doi.org/10.1002/2016JC011993
container_title Journal of Geophysical Research: Oceans
container_volume 121
container_issue 12
container_start_page 8635
op_container_end_page 8669
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