Abstract's details
Intrinsic low-frequency (co)variability of SLA, MOC, and SST: impacts of mesoscale turbulence and wind forcing.
CoAuthors
Event: 2014 Ocean Surface Topography Science Team Meeting
Session: Science Results from Satellite Altimetry: Regional and basin-scale processes and sea level rise
Presentation type: Type Poster
Contribution: PDF file
Abstract:
At low resolution, idealized ocean circulation models forced by differential surface heat fluxes generate intrinsic multidecadal variability depending critically on eddy diffusivity coefficients. A series of numerical simulations with resolution increasing up to eddy resolving ones (10 km) and various diapycnal diffusivities shows that this multidecadal intrinsic variability is a generic ubiquitous feature. When mesoscale eddies are resolved, the interdecadal variability appears even more robust to low vertical diffusivity and overturning. The mechanism previously proposed for these oscillations, involving westward propagating Rossby waves in the subpolar region and its feedback on the mean circulation (e.g. Sévellec and Fedorov, 2012), appears unaffected by mesoscale turbulence: it remains centered on the polar front, which is displaced to the south.
Adding a constant, North Atlantic-like, idealized wind forcing has a strong impact on the mean circulation and the variability: the eddy-driven intrinsic variability in that case consists in a distinct large-amplitude pattern at interannual period. Periods in the 20-30 yr range remain present, but the location of SST and SLA multidecadal variability shifts from a large northern region to the intergyre: large-scale SST/SLA anomalies propagate eastward at the intergyre then cyclonically around the subpolar gyre, i.e. along a realistic path (see Sutton & Allen, 1997; Vianna & Menezes, 2013)
Adding complexity (i.e. eddies, wind forcing) into idealized simulations reveals key processes producing intrinsic variability, and progressively improves agreement with observations. Such experiments also complement experiments where the complexity of realistic OGCM simulations is progressively decreased (e.g. suppression of mesoscale, interannual forcing); this is how the CHAOCEAN project expects to improve our understanding of intrinsic variability in the real ocean and its imprint of observational datasets.
Huck, T., O. Arzel, and F. Sévellec, 2014: Multidecadal variability of the overturning circulation in presence of eddy turbulence. J. Phys. Oceanogr., submitted.
Sévellec, F., A.V. Fedorov, 2013: The Leading, Interdecadal Eigenmode of the Atlantic Meridional Overturning Circulation in a Realistic Ocean Model. J. Climate, 26, 2160-2183.
Adding a constant, North Atlantic-like, idealized wind forcing has a strong impact on the mean circulation and the variability: the eddy-driven intrinsic variability in that case consists in a distinct large-amplitude pattern at interannual period. Periods in the 20-30 yr range remain present, but the location of SST and SLA multidecadal variability shifts from a large northern region to the intergyre: large-scale SST/SLA anomalies propagate eastward at the intergyre then cyclonically around the subpolar gyre, i.e. along a realistic path (see Sutton & Allen, 1997; Vianna & Menezes, 2013)
Adding complexity (i.e. eddies, wind forcing) into idealized simulations reveals key processes producing intrinsic variability, and progressively improves agreement with observations. Such experiments also complement experiments where the complexity of realistic OGCM simulations is progressively decreased (e.g. suppression of mesoscale, interannual forcing); this is how the CHAOCEAN project expects to improve our understanding of intrinsic variability in the real ocean and its imprint of observational datasets.
Huck, T., O. Arzel, and F. Sévellec, 2014: Multidecadal variability of the overturning circulation in presence of eddy turbulence. J. Phys. Oceanogr., submitted.
Sévellec, F., A.V. Fedorov, 2013: The Leading, Interdecadal Eigenmode of the Atlantic Meridional Overturning Circulation in a Realistic Ocean Model. J. Climate, 26, 2160-2183.