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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 5, issue 3
Geosci. Model Dev., 5, 683–707, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 5, 683–707, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 15 May 2012

Model description paper | 15 May 2012

The role of phytoplankton dynamics in the seasonal and interannual variability of carbon in the subpolar North Atlantic – a modeling study

S. R. Signorini1,9, S. Häkkinen2, K. Gudmundsson3, A. Olsen4,5,*, A. M. Omar4,5, J. Olafsson6, G. Reverdin7, S. A. Henson8, C. R. McClain9, and D. L. Worthen2,10 S. R. Signorini et al.
  • 1Science Applications International Corp., Beltsville, Maryland, USA
  • 2NASA Goddard Space Flight Center, Cryospheric Sciences Branch, Greenbelt, Maryland, USA
  • 3Marine Research Institute, P.O. Box 1390, 121, Reykjavik, Iceland
  • 4Uni Bjerknes Centre, Allégaten 55, 5007 Bergen, Norway
  • 5Bjerknes Centre for Climate Research, Allégaten 55, 5007 Bergen, Norway
  • 6University of Iceland and Marine Research Institute, Reykjavik, Iceland
  • 7Laboratoire d'Océanographie Dynamique et de Climatologie, IPSL, Boîte 100, 4, Place Jussieu 75252, Paris
  • 8National Oceanography Centre, European Way, Southampton, SO14 3ZH, UK
  • 9NASA Goddard Space Flight Center, Ocean Ecology Branch, Greenbelt, Code 614.2, Maryland, USA
  • 10Wyle Information Systems Group, McLean, Virginia, USA
  • *now at: Institute of Marine Research, P.O. Box 1870 Nordnes, 5817 Bergen, Norway

Abstract. We developed an ecosystem/biogeochemical model system, which includes multiple phytoplankton functional groups and carbon cycle dynamics, and applied it to investigate physical-biological interactions in Icelandic waters. Satellite and in situ data were used to evaluate the model. Surface seasonal cycle amplitudes and biases of key parameters (DIC, TA, pCO2, air-sea CO2 flux, and nutrients) are significantly improved when compared to surface observations by prescribing deep water values and trends, based on available data. The seasonality of the coccolithophore and "other phytoplankton" (diatoms and dinoflagellates) blooms is in general agreement with satellite ocean color products. Nutrient supply, biomass and calcite concentrations are modulated by light and mixed layer depth seasonal cycles. Diatoms are the most abundant phytoplankton, with a large bloom in early spring and a secondary bloom in fall. The diatom bloom is followed by blooms of dinoflagellates and coccolithophores. The effect of biological changes on the seasonal variability of the surface ocean pCO2 is nearly twice the temperature effect, in agreement with previous studies. The inclusion of multiple phytoplankton functional groups in the model played a major role in the accurate representation of CO2 uptake by biology. For instance, at the peak of the bloom, the exclusion of coccolithophores causes an increase in alkalinity of up to 4 μmol kg−1 with a corresponding increase in DIC of up to 16 μmol kg−1. During the peak of the bloom in summer, the net effect of the absence of the coccolithophores bloom is an increase in pCO2 of more than 20 μatm and a reduction of atmospheric CO2 uptake of more than 6 mmol m−2 d−1. On average, the impact of coccolithophores is an increase of air-sea CO2 flux of about 27%. Considering the areal extent of the bloom from satellite images within the Irminger and Icelandic Basins, this reduction translates into an annual mean of nearly 1500 tonnes C yr−1.

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