Determining Atlantic Ocean province contrasts and variations. (November 2017)

• Record Type: Journal Article
• Authors: 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
• Is Part Of: Progress in oceanography. Volume 158(2017:Nov.)
• Page Start: 19
• Page End: 40
• Publication Date: 2017-11
• Subjects: Oceanography -- Periodicals; 551.4605
• DOI: 10.1016/j.pocean.2016.12.004
• Languages: English
• ISSNs: 0079-6611

Abstract

Highlights: Atlantic Ocean province variations described using AMT core observations. Analyses highlight tropical oxygen minimum zone. Clear province contrasts observed in nutrient stoichiometry. Observations and relationships useful for basin scale biogeochemical models. Abstract: 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.