An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models
International audience We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea...
Published in: | Journal of Geophysical Research: Oceans |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , |
Other Authors: | , , , , , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2015
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Subjects: | |
Online Access: | https://hal.science/hal-03502725 https://hal.science/hal-03502725/document https://hal.science/hal-03502725/file/JGR%20Oceans%20-%202015%20-%20Lee%20-%20An%20assessment%20of%20phytoplankton%20primary%20productivity%20in%20the%20Arctic%20Ocean%20from%20satellite%20ocean.pdf https://doi.org/10.1002/2015JC011018 |
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ftunivnantes:oai:HAL:hal-03502725v1 |
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record_format |
openpolar |
institution |
Open Polar |
collection |
Université de Nantes: HAL-UNIV-NANTES |
op_collection_id |
ftunivnantes |
language |
English |
topic |
[SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography |
spellingShingle |
[SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography Lee, Younjoo J. Matrai, Patricia A. Friedrichs, Marjorie A. M. Saba, Vincent S. Antoine, David Ardyna, Mathieu Asanuma, Ichio Babin, Marcel Bélanger, Simon Benoit-Gagne, Maxime Devred, Emmanuel Fernández-Méndez, Mar Gentili, Bernard Hirawake, Toru Kang, Sung-Ho Kameda, Takahiko Katlein, Christian Lee, Sang H. Lee, Zhongping Mélin, Frédéric Scardi, Michele Smyth, Tim J. Tang, Shilin Turpie, Kevin R. Waters, Kirk J. Westberry, Toby K. An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models |
topic_facet |
[SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography |
description |
International audience We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters. |
author2 |
Bigelow Laboratory for Ocean Sciences Virginia Institute of Marine Science (VIMS) Laboratoire d'océanographie de Villefranche (LOV) Observatoire océanologique de Villefranche-sur-mer (OOVM) Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS) Takuvik Joint International Laboratory ULAVAL-CNRS Université Laval Québec (ULaval)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS) Université du Québec à Rimouski (UQAR) Fisheries and Oceans Canada (DFO) Norwegian Polar Institute Hokkaido University Sapporo, Japan KIOST Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) European Commission - Joint Research Centre Ispra (JRC) Università degli Studi di Roma Tor Vergata Roma Plymouth Marine Laboratory (PML) NASA Department of Botany and Plant Pathology Oregon State University (OSU) |
format |
Article in Journal/Newspaper |
author |
Lee, Younjoo J. Matrai, Patricia A. Friedrichs, Marjorie A. M. Saba, Vincent S. Antoine, David Ardyna, Mathieu Asanuma, Ichio Babin, Marcel Bélanger, Simon Benoit-Gagne, Maxime Devred, Emmanuel Fernández-Méndez, Mar Gentili, Bernard Hirawake, Toru Kang, Sung-Ho Kameda, Takahiko Katlein, Christian Lee, Sang H. Lee, Zhongping Mélin, Frédéric Scardi, Michele Smyth, Tim J. Tang, Shilin Turpie, Kevin R. Waters, Kirk J. Westberry, Toby K. |
author_facet |
Lee, Younjoo J. Matrai, Patricia A. Friedrichs, Marjorie A. M. Saba, Vincent S. Antoine, David Ardyna, Mathieu Asanuma, Ichio Babin, Marcel Bélanger, Simon Benoit-Gagne, Maxime Devred, Emmanuel Fernández-Méndez, Mar Gentili, Bernard Hirawake, Toru Kang, Sung-Ho Kameda, Takahiko Katlein, Christian Lee, Sang H. Lee, Zhongping Mélin, Frédéric Scardi, Michele Smyth, Tim J. Tang, Shilin Turpie, Kevin R. Waters, Kirk J. Westberry, Toby K. |
author_sort |
Lee, Younjoo J. |
title |
An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models |
title_short |
An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models |
title_full |
An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models |
title_fullStr |
An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models |
title_full_unstemmed |
An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models |
title_sort |
assessment of phytoplankton primary productivity in the arctic ocean from satellite ocean color/in situ chlorophyll-a based models |
publisher |
HAL CCSD |
publishDate |
2015 |
url |
https://hal.science/hal-03502725 https://hal.science/hal-03502725/document https://hal.science/hal-03502725/file/JGR%20Oceans%20-%202015%20-%20Lee%20-%20An%20assessment%20of%20phytoplankton%20primary%20productivity%20in%20the%20Arctic%20Ocean%20from%20satellite%20ocean.pdf https://doi.org/10.1002/2015JC011018 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean Phytoplankton Sea ice |
genre_facet |
Arctic Arctic Ocean Phytoplankton Sea ice |
op_source |
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS https://hal.science/hal-03502725 JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2015, 120 (9), pp.6508-6541. ⟨10.1002/2015JC011018⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1002/2015JC011018 hal-03502725 https://hal.science/hal-03502725 https://hal.science/hal-03502725/document https://hal.science/hal-03502725/file/JGR%20Oceans%20-%202015%20-%20Lee%20-%20An%20assessment%20of%20phytoplankton%20primary%20productivity%20in%20the%20Arctic%20Ocean%20from%20satellite%20ocean.pdf doi:10.1002/2015JC011018 |
op_rights |
http://hal.archives-ouvertes.fr/licences/copyright/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1002/2015JC011018 |
container_title |
Journal of Geophysical Research: Oceans |
container_volume |
120 |
container_issue |
9 |
container_start_page |
6508 |
op_container_end_page |
6541 |
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1766323093517631488 |
spelling |
ftunivnantes:oai:HAL:hal-03502725v1 2023-05-15T14:51:57+02:00 An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models Lee, Younjoo J. Matrai, Patricia A. Friedrichs, Marjorie A. M. Saba, Vincent S. Antoine, David Ardyna, Mathieu Asanuma, Ichio Babin, Marcel Bélanger, Simon Benoit-Gagne, Maxime Devred, Emmanuel Fernández-Méndez, Mar Gentili, Bernard Hirawake, Toru Kang, Sung-Ho Kameda, Takahiko Katlein, Christian Lee, Sang H. Lee, Zhongping Mélin, Frédéric Scardi, Michele Smyth, Tim J. Tang, Shilin Turpie, Kevin R. Waters, Kirk J. Westberry, Toby K. Bigelow Laboratory for Ocean Sciences Virginia Institute of Marine Science (VIMS) Laboratoire d'océanographie de Villefranche (LOV) Observatoire océanologique de Villefranche-sur-mer (OOVM) Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS) Takuvik Joint International Laboratory ULAVAL-CNRS Université Laval Québec (ULaval)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS) Université du Québec à Rimouski (UQAR) Fisheries and Oceans Canada (DFO) Norwegian Polar Institute Hokkaido University Sapporo, Japan KIOST Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) European Commission - Joint Research Centre Ispra (JRC) Università degli Studi di Roma Tor Vergata Roma Plymouth Marine Laboratory (PML) NASA Department of Botany and Plant Pathology Oregon State University (OSU) 2015 https://hal.science/hal-03502725 https://hal.science/hal-03502725/document https://hal.science/hal-03502725/file/JGR%20Oceans%20-%202015%20-%20Lee%20-%20An%20assessment%20of%20phytoplankton%20primary%20productivity%20in%20the%20Arctic%20Ocean%20from%20satellite%20ocean.pdf https://doi.org/10.1002/2015JC011018 en eng HAL CCSD info:eu-repo/semantics/altIdentifier/doi/10.1002/2015JC011018 hal-03502725 https://hal.science/hal-03502725 https://hal.science/hal-03502725/document https://hal.science/hal-03502725/file/JGR%20Oceans%20-%202015%20-%20Lee%20-%20An%20assessment%20of%20phytoplankton%20primary%20productivity%20in%20the%20Arctic%20Ocean%20from%20satellite%20ocean.pdf doi:10.1002/2015JC011018 http://hal.archives-ouvertes.fr/licences/copyright/ info:eu-repo/semantics/OpenAccess JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS https://hal.science/hal-03502725 JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2015, 120 (9), pp.6508-6541. ⟨10.1002/2015JC011018⟩ [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography info:eu-repo/semantics/article Journal articles 2015 ftunivnantes https://doi.org/10.1002/2015JC011018 2023-01-11T00:04:59Z International audience We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters. Article in Journal/Newspaper Arctic Arctic Ocean Phytoplankton Sea ice Université de Nantes: HAL-UNIV-NANTES Arctic Arctic Ocean Journal of Geophysical Research: Oceans 120 9 6508 6541 |