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Dhruv Balwada, Joseph H. LaCasce, Kevin G. Speer, and Raffaele Ferrari

-frequency wave-like motions that do not cause much lateral dispersion, we anticipate the impact of this high-frequency vertical shear on most of the dispersion metrics to be small. Further, the mean vertical shear in this region is approximately O (10 −4 ) s −1 ( Balwada et al. 2016a ), which can result in a net dispersion on the order of 10 km 2 in 10 days and 10 3 km 2 in 100 days, which is negligible compared to the observed relative dispersion ( Fig. 5 ). The corresponding particle analysis was

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J. R. Ledwell, L. C. St. Laurent, J. B. Girton, and J. M. Toole

remain sparse and mostly limited to mid- and low latitudes ( Gregg et al. 1973 ; Toole et al. 1994 ; Gregg et al. 2003 ; Klymak et al. 2006 ). Measurements of vertical shear and strain at scales of tens of meters, from which mixing estimates can be inferred, are more widespread, but formulations relating these internal wave characteristics to dissipation rates and diapycnal diffusivity are subject to a number of added approximations ( Gregg 1989 ; Kunze et al. 2006 ). The Southern Ocean is a

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Jesse M. Cusack, Alberto C. Naveira Garabato, David A. Smeed, and James B. Girton

open to alternative interpretations, as the unambiguous observation of lee waves in the Southern Ocean has remained elusive. It has been appreciated in the atmospheric literature that lee waves, or mountain waves, play an important role in the momentum budget and influence aspects of the general circulation (e.g., Fritts 2003 ) and that the results of general circulation models are improved when their effects are accounted for ( McFarlane 1987 ). The dominant momentum balance in the Antarctic

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Michael Bates, Ross Tulloch, John Marshall, and Raffaele Ferrari

Marshall (2013 ; see also Fig. 1 , red). b. The role of eddy propagation in modulating mixing Mixing by geostrophic eddies and turbulence can be strongly modulated by interactions with the mean flow. This notion is well established in the atmospheric literature and was pioneered by Bretherton (1966) , Green (1970) , and Stone (1972) . There is a growing, parallel literature in the ocean context (e.g., Bower 1991 ; Lozier and Bercovici 1992 ; Bower and Lozier 1994 ; Smith and Marshall 2009

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Louis-Philippe Nadeau and Raffaele Ferrari

proportional to the wind stress magnitude τ 0 and inversely proportional to the effective eddy diffusivity κ , a measure of the eddy intensity. Thus, we infer that in our flat channel simulations the eddy diffusivity increases as κ ~ τ 0.8 , so as to give . When a ridge is added, the dynamics change in a fundamental way. The leading-order balance of zonal momentum is between the surface wind stress and the topographic form drag at the ridge. A large-scale standing wave pattern in the form of a

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Emma J. D. Boland, Emily Shuckburgh, Peter H. Haynes, James R. Ledwell, Marie-José Messias, and Andrew J. Watson

, found using tracer observations, models, or a combination of both ( McKeague et al. 2005 ; Garabato et al. 2007 ; Zika et al. 2009 ; Abernathey et al. 2010 ), broadly consistent with the indicative value 10 3 m 2 s −1 used by Garrett (1983) . Our primary concern in this paper is not K h but the submesoscale diffusivity K s . Uncertainty continues over the processes that control the magnitude of K s . Young et al. (1982) suggested shear dispersion by inertial waves as an important

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Dhruv Balwada, Kevin G. Speer, Joseph H. LaCasce, W. Brechner Owens, John Marshall, and Raffaele Ferrari

time scale. The analytical integral of this chosen autocorrelation function gives an effective Lagrangian integral time scale: Klocker et al. (2012) applied the mixing suppression theory ( Ferrari and Nikurashin 2010 ) to particles instead of tracers and derived an autocorrelation function of the same form as (7) . This links physical processes to the presence of the two scales using dynamical arguments. Their theory was derived for a randomly forced Rossby wave solution to a quasigeostrophic

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Matthew R. Mazloff, Raffaele Ferrari, and Tapio Schneider

adjusting the atmospheric driving and initial conditions using an adjoint model. A cost function compares the model state to in situ observations (Argo float profiles, CTD synoptic sections, seal-mounted SEaOS instrument profiles, and XBTs), altimetric observations [ Envisat , Geosat , Jason, Ocean Topography Experiment (TOPEX)/Poseidon)], and other datasets (e.g., sea surface temperatures inferred from infrared and microwave radiometers). In contrast to other data assimilation approaches, no spurious

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Ross Tulloch, Raffaele Ferrari, Oliver Jahn, Andreas Klocker, Joseph LaCasce, James R. Ledwell, John Marshall, Marie-Jose Messias, Kevin Speer, and Andrew Watson

. The average length of the mooring data is 320 days. The black line with the largest EKE in the model is from the northernmost mooring location. One possible reason for the energy level mismatch is due to missing ocean physics. While the model resolves mesoscale eddies, bottom boundary layer turbulence ( Kantha and Clayson 2000 ) and lee-wave generation ( Nikurashin and Ferrari 2011 ; Nikurashin et al. 2013 ) are not well resolved, so the modeled eddies experience too little bottom dissipation. It

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