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

the flow variability and stirring in the DIMES region we use several different metrics. We start by quantifying the flow variability at different scales using Lagrangian frequency spectra and second-order structure functions in section 3 . Stirring or particle dispersion is a result of the integrated effect of the flow variability, and is usually quantified and categorized as local versus nonlocal using metrics that either quantify temporal evolution or spatial structure ( Table 1 ). The pair

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J. Alexander Brearley, Katy L. Sheen, Alberto C. Naveira Garabato, David A. Smeed, and Stephanie Waterman

the forthcoming analysis focuses on , which captures the temporal variability in mixing (see section 3b ) but is not reliant on the accuracy of the parameterization [see Kunze et al. (2002) and Klymak et al. (2008) for examples of regions where finescale methods can underestimate the real value of turbulent dissipation]. As the parameterization assumes a stationary internal wave field and the individual 30-min resolution profiles are noisy, it was decided to average together spectra over 1

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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

. Incidentally, variations among profiles of the vertical distribution were small enough that the estimate by Ledwell et al. (2011) of the diapycnal diffusivity, and its uncertainty, in the region between the injection location and the US2 survey area were accurate, despite the variability of column integral within the patch and the failure of the survey to delimit the patch. Figure 2 shows column-integrated tracer concentrations divided by the total amount of tracer released (circles; units m −2 ) for

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Alberto C. Naveira Garabato, Kurt L. Polzin, Raffaele Ferrari, Jan D. Zika, and Alexander Forryan

this dataset, the presence of at least two other classes of flows with distinct scales is suggested in the θ – S diagram: a large-scale background with vertical scales of O (100–1000) m, which is laterally coherent on horizontal scales of O (100) km, is largely stable on time scales of years to decades and is associated with the general circulation; and finescale structure with vertical scales of O (10–100) m, which is laterally incoherent on horizontal scales of O (1–10) km, is variable on

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Matthew R. Mazloff, Raffaele Ferrari, and Tapio Schneider

–2006: Seasonal and decadal variability . J. Phys. Oceanogr. , 39 , 351 – 368 . Wüst , G. , 1935 : Zur Frage des indischen Tiefenstroms. Naturwissenschaften, 23, 137–139. (In English, 1978: The Stratosphere of the Atlantic Ocean. W. J. Emery, Ed., Amerind, 112 pp.) 1 Throughout this paper, we use the south to north plotting convention, such that a clockwise overturning cell consists of northward flow of relatively buoyant waters and southward flow of less buoyant waters. In the SO, a clockwise

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Louis-Philippe Nadeau and Raffaele Ferrari

variability of the Southern Ocean . J. Phys. Oceanogr. , 36 , 1626 – 1645 , doi: 10.1175/JPO2934.1 . Johnson , G. C. , and H. Bryden , 1989 : On the strength of the circumpolar current . Deep-Sea Res. , 36 , 39 – 53 , doi: 10.1016/0198-0149(89)90017-4 . Leith , C. E. , 1967 : Diffusion approximation to inertial energy transfer in isotropic turbulence. Phys. Fluids , 10 , 1409 – 1416 , doi: 10.1063/1.1762300 . Marshall , J. , and T. Radko , 2003 : Residual-mean solutions for the

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

from constant in space or time but instead exhibits considerable variability (e.g., Davis 1991 ; Holloway 1986 ; Ledwell et al. 1998 ; Marshall et al. 2006 ; Abernathey et al. 2010 ; Naveira Garabato et al. 2011 ). Eddy transfer is thought to be of leading order importance in dynamical balances in the ocean and the distribution of tracers therein, particularly in the Southern Ocean (see Marshall and Speer 2012 ). Therefore, coarse-resolution models that do not resolve mesoscale eddies must

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