An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models
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 (SS...
Published in: | Journal of Geophysical Research: Oceans |
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Online Access: | https://hdl.handle.net/20.500.11937/41645 https://doi.org/10.1002/2015JC011018 |
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ftcurtin:oai:espace.curtin.edu.au:20.500.11937/41645 2023-06-11T04:08:46+02:00 An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models Lee, Y. Matrai, P. Friedrichs, M. Saba, V. Antoine, David Ardyna, M. Asanuma, I. Babin, M. Belanger, S. Benoit-Gagne, M. Devred, E. Fernandez-Mendez, M. Gentili, B. Hirawake, T. Kang, S. Kameda, T. Katlein, C. Lee, S. Lee, Z. Melin, F. Scardi, M. Smyth, T. Tang, S. Turpie, K. Waters, K. Westberry, T. 2015 fulltext https://hdl.handle.net/20.500.11937/41645 https://doi.org/10.1002/2015JC011018 unknown Wiley-Blackwell Publishing http://hdl.handle.net/20.500.11937/41645 doi:10.1002/2015JC011018 Journal Article 2015 ftcurtin https://doi.org/20.500.11937/4164510.1002/2015JC011018 2023-05-30T19:42:03Z 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 Curtin University: espace Arctic Arctic Ocean Journal of Geophysical Research: Oceans 120 9 6508 6541 |
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Open Polar |
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Curtin University: espace |
op_collection_id |
ftcurtin |
language |
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description |
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. |
format |
Article in Journal/Newspaper |
author |
Lee, Y. Matrai, P. Friedrichs, M. Saba, V. Antoine, David Ardyna, M. Asanuma, I. Babin, M. Belanger, S. Benoit-Gagne, M. Devred, E. Fernandez-Mendez, M. Gentili, B. Hirawake, T. Kang, S. Kameda, T. Katlein, C. Lee, S. Lee, Z. Melin, F. Scardi, M. Smyth, T. Tang, S. Turpie, K. Waters, K. Westberry, T. |
spellingShingle |
Lee, Y. Matrai, P. Friedrichs, M. Saba, V. Antoine, David Ardyna, M. Asanuma, I. Babin, M. Belanger, S. Benoit-Gagne, M. Devred, E. Fernandez-Mendez, M. Gentili, B. Hirawake, T. Kang, S. Kameda, T. Katlein, C. Lee, S. Lee, Z. Melin, F. Scardi, M. Smyth, T. Tang, S. Turpie, K. Waters, K. Westberry, T. An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models |
author_facet |
Lee, Y. Matrai, P. Friedrichs, M. Saba, V. Antoine, David Ardyna, M. Asanuma, I. Babin, M. Belanger, S. Benoit-Gagne, M. Devred, E. Fernandez-Mendez, M. Gentili, B. Hirawake, T. Kang, S. Kameda, T. Katlein, C. Lee, S. Lee, Z. Melin, F. Scardi, M. Smyth, T. Tang, S. Turpie, K. Waters, K. Westberry, T. |
author_sort |
Lee, Y. |
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 |
Wiley-Blackwell Publishing |
publishDate |
2015 |
url |
https://hdl.handle.net/20.500.11937/41645 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_relation |
http://hdl.handle.net/20.500.11937/41645 doi:10.1002/2015JC011018 |
op_doi |
https://doi.org/20.500.11937/4164510.1002/2015JC011018 |
container_title |
Journal of Geophysical Research: Oceans |
container_volume |
120 |
container_issue |
9 |
container_start_page |
6508 |
op_container_end_page |
6541 |
_version_ |
1768382264798871552 |