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 (NO3), mixed layer depth (MLD), euphotic layer depth (Z(eu)), and sea ice conce...
Published in: | Journal of Geophysical Research: Oceans |
---|---|
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Amer Geophysical Union
2016
|
Subjects: | |
Online Access: | https://archimer.ifremer.fr/doc/00373/48441/69564.pdf https://doi.org/10.1002/2016JC011993 https://archimer.ifremer.fr/doc/00373/48441/ |
id |
ftarchimer:oai:archimer.ifremer.fr:48441 |
---|---|
record_format |
openpolar |
spelling |
ftarchimer:oai:archimer.ifremer.fr:48441 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, Jorg Seferian, Roland Stock, Charles A. Tjiputra, Jerry Tremblay, Bruno Ueyoshi, Kyozo Vichi, Marcello Yool, Andrew Zhang, Jinlun 2016-12 application/pdf https://archimer.ifremer.fr/doc/00373/48441/69564.pdf https://doi.org/10.1002/2016JC011993 https://archimer.ifremer.fr/doc/00373/48441/ eng eng Amer Geophysical Union https://archimer.ifremer.fr/doc/00373/48441/69564.pdf doi:10.1002/2016JC011993 https://archimer.ifremer.fr/doc/00373/48441/ info:eu-repo/semantics/openAccess restricted use Journal Of Geophysical Research-oceans (2169-9275) (Amer Geophysical Union), 2016-12 , Vol. 121 , N. 12 , P. 8635-8669 text Publication info:eu-repo/semantics/article 2016 ftarchimer https://doi.org/10.1002/2016JC011993 2021-09-23T20:29:18Z 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 (NO3), 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 NO3, 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 NO3 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. Article in Journal/Newspaper Arctic Basin Arctic Arctic Ocean Beaufort Sea Chukchi Greenland Phytoplankton Sea ice Zooplankton Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) Arctic Arctic Ocean Greenland Journal of Geophysical Research: Oceans 121 12 8635 8669 |
institution |
Open Polar |
collection |
Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) |
op_collection_id |
ftarchimer |
language |
English |
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 (NO3), 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 NO3, 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 NO3 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 |
Article in Journal/Newspaper |
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, Jorg Seferian, Roland Stock, Charles A. Tjiputra, Jerry Tremblay, Bruno Ueyoshi, Kyozo Vichi, Marcello Yool, Andrew Zhang, Jinlun |
spellingShingle |
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, Jorg Seferian, Roland Stock, Charles A. Tjiputra, Jerry Tremblay, 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 |
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, Jorg Seferian, Roland Stock, Charles A. Tjiputra, Jerry Tremblay, 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 |
publisher |
Amer Geophysical Union |
publishDate |
2016 |
url |
https://archimer.ifremer.fr/doc/00373/48441/69564.pdf https://doi.org/10.1002/2016JC011993 https://archimer.ifremer.fr/doc/00373/48441/ |
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 |
Journal Of Geophysical Research-oceans (2169-9275) (Amer Geophysical Union), 2016-12 , Vol. 121 , N. 12 , P. 8635-8669 |
op_relation |
https://archimer.ifremer.fr/doc/00373/48441/69564.pdf doi:10.1002/2016JC011993 https://archimer.ifremer.fr/doc/00373/48441/ |
op_rights |
info:eu-repo/semantics/openAccess restricted use |
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 |
_version_ |
1766303325505978368 |