Dissolved iron transport pathways in the Ross Sea : influence of tides and horizontal resolution in a regional ocean model

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2016-10
Authors
Mack, Stefanie L.
Dinniman, Michael S.
McGillicuddy, Dennis J.
Sedwick, Peter N.
Klinck, John M.
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Ross Sea
Tides
Mesoscale
Modelling
Tracers
Abstract
Phytoplankton production in the Ross Sea is regulated by the availability of dissolved iron (dFe), a limiting micro-nutrient, whose sources include Circumpolar Deep Water, sea ice melt, glacial melt, and benthic sources (sediment efflux and remineralization). We employ a passive tracer dye to model the benthic dFe sources and track pathways from deep areas of the continental shelf to the surface mixed layer in simulations with and without tidal forcing, and at 5 and 1.5km horizontal resolution. This, combined with dyes for each of the other dFe sources, provides an estimate of total dFe supply to surface waters. We find that tidal forcing increases the amount of benthic dye that covers the banks on the continental shelf. Calculations of mixed layer depth to define the surface ocean give similar average values over the shelf, but spatial patterns differ between simulations, particularly along the ice shelf front. Benthic dFe supply in simulations shows an increase with tidal forcing and a decrease with higher resolution. The changes in benthic dFe supply control the difference in total supply between simulations. Overall, the total dFe supply from simulations varies from 5.60 to 7.95 μmol m-2 yr-1, with benthic supply comprising 32-50%, comparing well with recent data and model synthesis. We suggest that including tides and using high horizontal resolution is important, especially when considering spatial variability of iron supply on the Ross Sea shelf.
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© The Author(s), 2016. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Journal of Marine Systems 166 (2017): 73-86, doi:10.1016/j.jmarsys.2016.10.008.
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