Determining Atlantic Ocean province contrasts and variations

Smyth, Tim; Quartly, Graham; Jackson, Thomas; Tarran, Glen; Woodward, Malcolm; Harris, Carolyn; Gallienne, Chris; Thomas, Rob; Airs, Ruth; Cummings, Denise; Brewin, Robert; Kitidis, Vassilis; Stephens, John; Zubkov, Mike; Rees, Andrew. 2017 Determining Atlantic Ocean province contrasts and variations. Progress in Oceanography, 158. 19-40.

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© 2017 Elsevier B.V. This is the author’s version of a work that was accepted for publication in Progress in Oceanography. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was published in Progress in Oceanography doi:10.1016/j.pocean.2016.12.004
Smyth et al. AMT PiO SI all_edits.docx - Accepted Version

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The Atlantic Meridional Transect (AMT) series of twenty-five cruises over the past twenty years has produced a rich depth-resolved biogeochemical in situ data resource consisting of a wealth of core variables. These multiple core datasets, key to the operation of AMT, such as temperature, salinity, oxygen and inorganic nutrients, are often only used as ancillary measurements for contextualising hypothesis-driven process studies. In this paper these core in situ variables, alongside data drawn from satellite Earth Observation (EO) and modelling, have been analysed to determine characteristic oceanic province variations encountered over the last twenty years on the AMT through the Atlantic Ocean. The EO and modelling analysis shows the variations of key environmental variables in each province, such as surface currents, the net heat flux and subsequent large scale biological responses, such as primary production. The in situ core dataset analysis allows the variation in features such as the tropical oxygen minimum zone to be quantified as well as showing clear contrasts between the provinces in nutrient stoichiometry. Such observations and relationships can be used within basin scale biogeochemical models to set realistic variation ranges.

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 00796611
Date made live: 19 Dec 2017 14:28 +0 (UTC)

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