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

The article of record as published may be found at http://dx.doi.org/10.1002/2016JC011993 Upon publication, the in situ data will be available for academic purposes through the NASA SeaWiFS Bio-optical Archive and Storage System (http:// seabass.gsfc.nasa.gov/), including NPP, NO3, and Zeu. The rela...

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Main Authors: Lee, Younjoo J., Matrai, Patricia A., Friedrichs, Marjorie A.M., Saba, Vincent S., Aumount, 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, Gorguess, 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
Other Authors: Naval Postgraduate School (U.S.), Oceanography
Format: Article in Journal/Newspaper
Language:unknown
Published: AGU Publications 2016
Subjects:
Online Access:https://hdl.handle.net/10945/57111
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record_format openpolar
spelling ftnavalpschool:oai:calhoun.nps.edu:10945/57111 2024-06-09T07:42:21+00:00 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. Aumount, 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 Gorguess, 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 Naval Postgraduate School (U.S.) Oceanography 2016-12 35 p. application/pdf https://hdl.handle.net/10945/57111 unknown AGU Publications Lee, Younjoo J., et al. "Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical‐biogeochemical models." Journal of Geophysical Research: Oceans 121.12 (2016): 8635-8669. https://hdl.handle.net/10945/57111 This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. Arctic models underestimated net primary productivity (NPP) but overestimated nitrate mixed layer depth and euphotic depth Arctic NPP model skill was greatest in low production regions Arctic NPP model skill was constrained by different environmental factors in different Arctic Ocean regions Article 2016 ftnavalpschool 2024-05-15T00:57:20Z The article of record as published may be found at http://dx.doi.org/10.1002/2016JC011993 Upon publication, the in situ data will be available for academic purposes through the NASA SeaWiFS Bio-optical Archive and Storage System (http:// seabass.gsfc.nasa.gov/), including NPP, NO3, and Zeu. 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 (Zeu), 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 Zeu 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. Ocean Biology and Biogeochemistry (OBB) NNX13AE81G NSF Office of Polar Programs PLR- 1417925 NSF Office of ... Article in Journal/Newspaper Arctic Arctic Basin Arctic Arctic Ocean Beaufort Sea Chukchi Greenland Phytoplankton Sea ice Zooplankton Naval Postgraduate School: Calhoun Arctic Arctic Ocean Greenland
institution Open Polar
collection Naval Postgraduate School: Calhoun
op_collection_id ftnavalpschool
language unknown
topic Arctic models underestimated net primary productivity (NPP) but overestimated nitrate
mixed layer depth
and euphotic depth
Arctic NPP model skill was greatest in low production regions
Arctic NPP model skill was constrained by different environmental factors in different Arctic Ocean regions
spellingShingle Arctic models underestimated net primary productivity (NPP) but overestimated nitrate
mixed layer depth
and euphotic depth
Arctic NPP model skill was greatest in low production regions
Arctic NPP model skill was constrained by different environmental factors in different Arctic Ocean regions
Lee, Younjoo J.
Matrai, Patricia A.
Friedrichs, Marjorie A.M.
Saba, Vincent S.
Aumount, 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
Gorguess, 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 Arctic models underestimated net primary productivity (NPP) but overestimated nitrate
mixed layer depth
and euphotic depth
Arctic NPP model skill was greatest in low production regions
Arctic NPP model skill was constrained by different environmental factors in different Arctic Ocean regions
description The article of record as published may be found at http://dx.doi.org/10.1002/2016JC011993 Upon publication, the in situ data will be available for academic purposes through the NASA SeaWiFS Bio-optical Archive and Storage System (http:// seabass.gsfc.nasa.gov/), including NPP, NO3, and Zeu. 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 (Zeu), 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 Zeu 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. Ocean Biology and Biogeochemistry (OBB) NNX13AE81G NSF Office of Polar Programs PLR- 1417925 NSF Office of ...
author2 Naval Postgraduate School (U.S.)
Oceanography
format Article in Journal/Newspaper
author Lee, Younjoo J.
Matrai, Patricia A.
Friedrichs, Marjorie A.M.
Saba, Vincent S.
Aumount, 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
Gorguess, 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.
Aumount, 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
Gorguess, 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
publisher AGU Publications
publishDate 2016
url https://hdl.handle.net/10945/57111
geographic Arctic
Arctic Ocean
Greenland
geographic_facet Arctic
Arctic Ocean
Greenland
genre Arctic
Arctic Basin
Arctic
Arctic Ocean
Beaufort Sea
Chukchi
Greenland
Phytoplankton
Sea ice
Zooplankton
genre_facet Arctic
Arctic Basin
Arctic
Arctic Ocean
Beaufort Sea
Chukchi
Greenland
Phytoplankton
Sea ice
Zooplankton
op_relation Lee, Younjoo J., et al. "Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical‐biogeochemical models." Journal of Geophysical Research: Oceans 121.12 (2016): 8635-8669.
https://hdl.handle.net/10945/57111
op_rights This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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