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

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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
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Subjects
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
Advisors
Date of Issue
2016-12
Date
Publisher
AGU Publications
Language
Abstract
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.
Type
Article
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.
URI
https://hdl.handle.net/10945/57111
Series/Report No
Department
Oceanography
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
National Aeronautics and Space Agency (NASA)
Ocean Biology and Biogeochemistry (OBB)
The project ‘‘Green Mercator’’
National Program CNRS/LEFE/INSU.
NSF Office of Polar Programs
FP7 MyOcean2
PAVE (Polish-Norwegian Research Program)
Norwegian Supercomputing Project (NOTUR2)
Research Council of Norway funded project ORGANIC
NASA Cryosphere program
CNRM-CM climate model
Météo-France/DSI supercomputing
Funder
Ocean Biology and Biogeochemistry (OBB) NNX13AE81G
NSF Office of Polar Programs PLR- 1417925
NSF Office of Polar Programs PLR-1416920
FP7 MyOcean2 (project number 283367)
Research Council of Norway funded project ORGANIC (239965/RU)
NASA Cryosphere program (NNX15AG68G).
Format
35 p.
Citation
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.
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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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