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

Younjoo J. Lee, Patricia A. Matrai, Marjorie A. M. Friedrichs, Vincent S. Saba, Olivier Aumont, Marcel Babin, Erik T. Buitenhuis, Matthieu Chevallier, Lee de Mora, Morgane Dessert, John P. Dunne, Ingrid Ellingsen, Doron Feldman, Robert Frouin, Marion Gehlen, Thomas Gorgues, Tatiana Ilyina, Meibing Jin, Jasmin G. John, Jonathan LawrenceManfredi Manizza, Christophe Eugène Menkes, Coralie Perruche, Vincent Le Fouest, Ekaterina Popova, Anastasia Romanou, Jörg Schwinger, Roland Séférian, Charles A. Stock, Jerry Tjiputra, L. Bruno Tremblay, Kyozo Ueyoshi, Marcello Vichi, Andrew Yool, Jinlun Zhang, Annette Samuelsen

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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 vs. ice-influenced) and bottom depth (shelf vs. deep ocean). The models performed relatively well for the most recent decade and towards 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.
Original languageEnglish
Pages (from-to)8635–8669
Number of pages35
JournalJournal of Geophysical Research - Oceans
Volume121
Issue number12
Early online date9 Dec 2016
DOIs
Publication statusPublished - Dec 2016

Keywords

  • Arctic Ocean
  • net primary productivity
  • model skill assessment
  • nutrients
  • coupled physical-biogeochemical models
  • Earth System Models

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