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Published April 2017 | Published
Journal Article Open

Eddy Memory Mode of Multidecadal Variability in Residual-Mean Ocean Circulations with Application to the Beaufort Gyre

Abstract

Mesoscale eddies shape the Beaufort Gyre response to Ekman pumping, but their transient dynamics are poorly understood. Climate models commonly use the Gent–McWilliams (GM) parameterization, taking the eddy streamfunction  to be proportional to an isopycnal slope s and an eddy diffusivity K. This local-in-time parameterization leads to exponential equilibration of currents. Here, an idealized, eddy-resolving Beaufort Gyre model is used to demonstrate that  carries a finite memory of past ocean states, violating a key GM assumption. As a consequence, an equilibrating gyre follows a spiral sink trajectory implying the existence of a damped mode of variability—the eddy memory (EM) mode. The EM mode manifests during the spinup as a 15% overshoot in isopycnal slope (2000 km3 freshwater content overshoot) and cannot be explained by the GM parameterization. An improved parameterization is developed, such that  is proportional to an effective isopycnal slope , carrying a finite memory γ of past slopes. Introducing eddy memory explains the model results and brings to light an oscillation with a period  ≈ 50 yr, where the eddy diffusion time scale TE ~ 10 yr and γ ≈ 6 yr are diagnosed from the eddy-resolving model. The EM mode increases the Ekman-driven gyre variance by γ/TE ≈ 50% ± 15%, a fraction that stays relatively constant despite both time scales decreasing with increased mean forcing. This study suggests that the EM mode is a general property of rotating turbulent flows and highlights the need for better observational constraints on transient eddy field characteristics.

Additional Information

© 2017 American Meteorological Society. Manuscript received 23 August 2016, in final form 4 February 2017. Published online: 12 April 2017. GEM acknowledges the Stanback Postdoctoral Fellowship Fund at Caltech and the Howland Postdoctoral Program Fund at WHOI. MAS was supported by NSF Grants PLR-1415489 and OCE-1232389. AFT acknowledges support from NSF OCE-1235488. GEM thanks Glenn Flierl for discussions during the 2014 Geophysical Fluid Dynamics Summer School at WHOI. The authors acknowledge the high-performance computing support from Yellowstone provided by the NCAR CIS Laboratory, sponsored by the NSF. This work used the Extreme Science and Engineering Discovery Environment (XSEDE; Towns et al. 2014), which is supported by NSF Grant Number ACI-1053575.The manuscript benefited from discussions at the annual Forum for Arctic Modeling and Observing Synthesis (FAMOS) funded by the NSF OPP Awards PLR-1313614 and PLR-1203720.

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August 22, 2023
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