2.4 Circulation and Water Mass Variability in the South Atlantic

Monday, 11 January 2016: 4:45 PM
La Nouvelle A ( New Orleans Ernest N. Morial Convention Center)
Renellys Christine Perez, NOAA/AOML, Miami, Florida; and R. Msadek, S. Garzoli, R. Matano, and C. Meinen

Most observational and modeling efforts on the Atlantic meridional overturning circulation (AMOC) have been focused on the North Atlantic and the Southern Oceans, which are the preferential sites for deep-water formation. There are, in contrast, fewer studies on the South Atlantic Ocean, which actively transforms AMOC-relevant water masses as they transit the basin. In this presentation, we characterize the modes of variability associated with the AMOC in the South Atlantic. We examine the interannual-to-multidecadal variability of sea level anomalies, water mass properties, and meridional volume transport of the regional boundary currents (Brazil Current, North Brazil Current, Deep Western Boundary Current, and Benguela Current) and determine whether the primary mechanisms responsible for the variability of each of those fields are related to the mechanisms that govern the AMOC variability. Our analysis is based on models and observations. The model results include state-of-the-art eddy-permitting to eddyresolving NOAA/GFDL climate simulations, ocean-only model simulations forced with CORE interannual forcing, and process-oriented numerical experiments using the Regional Ocean Modeling System. The observations include time series measurements of water mass properties and velocities inferred from moorings along 34.5°S, hydrographic transects, gridded temperature and salinity data sets, gridded sea level anomalies, sea surface temperature, surface currents, and winds obtained from satellite and satellite-in situ blended products. We will examine the extent to which a better representation of meso-scale features, which are key contributors to the variability of the South Atlantic circulation, can affect the representation of the AMOC in global climate models and hence yields a better comparison with observations.
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