Articles | Volume 15, issue 1
https://doi.org/10.5194/bg-15-73-2018
https://doi.org/10.5194/bg-15-73-2018
Research article
 | 
04 Jan 2018
Research article |  | 04 Jan 2018

Assimilating bio-optical glider data during a phytoplankton bloom in the southern Ross Sea

Daniel E. Kaufman, Marjorie A. M. Friedrichs, John C. P. Hemmings, and Walker O. Smith Jr.

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Cited articles

Arrigo, K. R. and McClain, C. R.: Spring phytoplankton production in the western Ross Sea, Science, 266, 261–263, https://doi.org/10.1126/science.266.5183.261, 1994.
Arrigo, K. R. and van Dijken, G. L.: Annual changes in sea-ice, chlorophyll a, and primary production in the Ross Sea, Antarctica, Deep-Sea Res. Pt. II, 51, 117–138, https://doi.org/10.1016/j.dsr2.2003.04.003, 2004.
Arrigo, K. R., Robinson, D. H., Worthen, D. L., Schieber, B., and Lizotte, M. P.: Bio-optical properties of the southwestern Ross Sea, J. Geophys. Res.-Oceans, 103, 21683–21695, https://doi.org/10.1029/98JC02157, 1998.
Arrigo, K. R., van Dijken, G. L., and Bushinsky, S.: Primary production in the Southern Ocean, 1997–2006, J. Geophys. Res., 113, 1–27, https://doi.org/10.1029/2007JC004551, 2008.
Asper, V. L. and Smith, W. O.: Particle fluxes during austral spring and summer in the southern Ross Sea, Antarctica, J. Geophys. Res., 104, 5345–5359, https://doi.org/10.1029/1998JC900067, 1999.
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Short summary
Computer simulations of the highly variable phytoplankton in the Ross Sea demonstrated how incorporating data from different sources (satellite, ship, or glider) results in different system interpretations. For example, simulations assimilating satellite-based data produced lower carbon export estimates. Combining observations with models in this remote, harsh, and biologically variable environment should include consideration of the potential impacts of data frequency, duration, and coverage.
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