Ecosystem model intercomparison of under‐ice and total primary production in the Arctic Ocean

Previous observational studies have found increasing primary production (PP) in response to declining sea ice cover in the Arctic Ocean. In this study, under-ice PP was assessed based on three coupled ice-ocean-ecosystem models participating in the Forum for Arctic Modeling and Observational Synthesis (FAMOS) project. All models showed good agreement with under-ice measurements of surface chlorophyll-a concentration and vertically integrated PP rates during the main under-ice production period, from mid-May to September. Further, modeled 30-year (1980–2009) mean values and spatial patterns of sea ice concentration compared well with remote sensing data. Under-ice PP was higher in the Arctic shelf seas than in the Arctic Basin, but ratios of under-ice PP over total PP were spatially correlated with annual mean sea ice concentration, with higher ratios in higher ice concentration regions. Decreases in sea ice from 1980 to 2009 were correlated significantly with increases in total PP and decreases in the under-ice PP/total PP ratio for most of the Arctic, but nonsignificantly related to under-ice PP, especially in marginal ice zones. Total PP within the Arctic Circle increased at an annual rate of between 3.2 and 8.0 Tg C/yr from 1980 to 2009. This increase in total PP was due mainly to a PP increase in open water, including increases in both open water area and PP rate per unit area, and therefore much stronger than the changes in under-ice PP. All models suggested that, on a pan-Arctic scale, the fraction of under-ice PP declined with declining sea ice cover over the last three decades.

[1]  M. Kahru,et al.  Effects of sea ice cover on satellite-detected primary production in the Arctic Ocean , 2016, Biology Letters.

[2]  William H. Lipscomb,et al.  Biogeochemistry of CICE: the Los Alamos Sea Ice Model Documentation and Software User's Manual zbgc_colpkg modifications to Version 5 , 2016 .

[3]  M. Daase,et al.  A fish-eye view on the new Arctic lightscape , 2015 .

[4]  Jinlun Zhang,et al.  The Influence of Sea Ice and Snow Cover and Nutrient Availability on the Formation of Massive Under-Ice Phytoplankton Blooms in the Chukchi Sea , 2015 .

[5]  M. Aschan,et al.  Recent warming leads to a rapid borealization of fish communities in the Arctic , 2015 .

[6]  Jinlun Zhang,et al.  The great 2012 Arctic Ocean summer cyclone enhanced biological productivity on the shelves , 2014, Journal of geophysical research. Oceans.

[7]  Ben Raymond,et al.  Light‐driven tipping points in polar ecosystems , 2013, Global change biology.

[8]  Thomas R. Anderson,et al.  MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies , 2013 .

[9]  Thomas R. Anderson,et al.  Climate change and ocean acidification impacts on lower trophic levels and the export of organic carbon to the deep ocean , 2013 .

[10]  T. Krumpen,et al.  Export of Algal Biomass from the Melting Arctic Sea Ice , 2013, Science.

[11]  R. Ji,et al.  Sea ice phenology and timing of primary production pulses in the Arctic Ocean , 2013, Global change biology.

[12]  M. Steele,et al.  Synthesis of primary production in the Arctic Ocean: I. Surface waters, 1954–2007 , 2013 .

[13]  T. R. Anderson,et al.  Regional variability of acidification in the Arctic: a sea of contrasts , 2013 .

[14]  M. Maltrud,et al.  Investigation of Arctic sea ice and ocean primary production for the period 1992–2007 using a 3-D global ice–ocean ecosystem model , 2012 .

[15]  Scott Elliott,et al.  What controls primary production in the Arctic Ocean? Results from an intercomparison of five general circulation models with biogeochemistry , 2012 .

[16]  Rick A. Reynolds,et al.  Massive Phytoplankton Blooms Under Arctic Sea Ice , 2012, Science.

[17]  K. Arrigo,et al.  Secular trends in Arctic Ocean net primary production , 2011 .

[18]  Ron Kwok,et al.  Uncertainty in modeled Arctic sea ice volume , 2011 .

[19]  M. Maltrud,et al.  Large‐scale modeling of primary production and ice algal biomass within arctic sea ice in 1992 , 2011 .

[20]  J. Lamarque,et al.  The HadGEM2-ES implementation of CMIP5 centennial simulations , 2011 .

[21]  Jinlun Zhang,et al.  Modeling the impact of declining sea ice on the Arctic marine planktonic ecosystem , 2010 .

[22]  Jinlun Zhang,et al.  Sea Ice Response to Atmospheric and Oceanic Forcing in the Bering Sea , 2010 .

[23]  Stephen G. Yeager,et al.  The global climatology of an interannually varying air–sea flux data set , 2009 .

[24]  R. Gradinger.  Sea-ice algae: Major contributors to primary production and algal biomass in the Chukchi and Beaufort Seas during May/June 2002 , 2009 .

[25]  K. Arrigo,et al.  Primary production in the Arctic Ocean, 1998–2006 , 2008 .

[26]  John P. Dunne,et al.  A synthesis of global particle export from the surface ocean and cycling through the ocean interior and on the seafloor , 2007 .

[27]  Julia C. Hargreaves,et al.  Assessing the potential long-term increase of oceanic fossil fuel CO 2 uptake due to CO 2 -calcification feedback , 2007 .

[28]  M. Holland,et al.  Global atmospheric forcing data for Arctic ice-ocean modeling , 2007 .

[29]  Michael Steele,et al.  Effect of vertical mixing on the Atlantic Water layer circulation in the Arctic Ocean , 2007 .

[30]  Yasuhiro Yamanaka,et al.  NEMURO—a lower trophic level model for the North Pacific marine ecosystem , 2007 .

[31]  S. Saitoh,et al.  Ice‐associated phytoplankton blooms in the southeastern Bering Sea , 2007 .

[32]  Ron Lindsay,et al.  Assimilation of Ice Concentration in an Ice–Ocean Model , 2006 .

[33]  David M. Nelson,et al.  Simulation of upper-ocean biogeochemistry with a flexible-composition phytoplankton model: C, N and Si cycling and Fe limitation in the Southern Ocean , 2006 .

[34]  N. Hirose,et al.  Feasible Method for the Assimilation of Satellite-Derived SST with an Ocean Circulation Model , 2005 .

[35]  Keith Lindsay,et al.  Upper ocean ecosystem dynamics and iron cycling in a global three‐dimensional model , 2004 .

[36]  Peter R. Gent,et al.  Anisotropic Gent–McWilliams Parameterization for Ocean Models , 2004 .

[37]  William H. Lipscomb,et al.  Modeling Sea Ice Transport Using Incremental Remapping , 2004 .

[38]  D. A. Rothrock,et al.  Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates , 2003 .

[39]  David Archer,et al.  Association of sinking organic matter with various types of mineral ballast in the deep sea: Implications for the rain ratio , 2002 .

[40]  William H. Lipscomb,et al.  An energy-conserving thermodynamic model of sea ice , 1999 .

[41]  E. Hunke,et al.  An Elastic–Viscous–Plastic Model for Sea Ice Dynamics , 1996 .

[42]  W. Large,et al.  Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterization , 1994 .

[43]  R. C. Malone,et al.  Parallel ocean general circulation modeling , 1992 .

[44]  Philippe Gaspar,et al.  A simple eddy kinetic energy model for simulations of the oceanic vertical mixing: Tests at Station Papa and long-term upper ocean study site , 1990 .

[45]  A. E. Gill.  Atmosphere-Ocean Dynamics , 1982 .

[46]  William D. Hibler,et al.  Modeling a variable thickness sea ice cover , 1980 .

[47]  W. Hibler.  A Dynamic Thermodynamic Sea Ice Model , 1979 .

[48]  A. Semtner.  A MODEL FOR THE THERMODYNAMIC GROWTH OF SEA ICE IN NUMERICAL INVESTIGATIONS OF CLIMATE , 1975 .

[49]  Corinne Le Quéré,et al.  iMarNet : an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework , 2014 .

[50]  Jia Wang,et al.  Controls of the landfast ice–ocean ecosystem offshore Barrow, Alaska , 2006, Annals of Glaciology.

[51]  Valérie Dulière,et al.  On the representation of high latitude processes in the ORCA-LIM global coupled sea ice–ocean model , 2005 .

[52]  S. Wakeham,et al.  A new, mechanistic model for organic carbon fluxes in the ocean based on the quantitative association of POC with ballast minerals , 2001 .

[53]  Frank Röske.  An atlas of surface fluxes based on the ECMWF Re-Analysis- a climatological dataset to force global ocean general circulation models , 2001 .

[54]  S. Doney,et al.  An intermediate complexity marine ecosystem model for the global domain , 2001 .

[55]  P. Delecluse,et al.  OPA 8.1 Ocean General Circulation Model reference manual , 1998 .