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Takeyoshi Nagai, Amit Tandon, Eric Kunze, and Amala Mahadevan

unforced front can lose power from balanced circulations to near-inertial waves of O (0.36) TW. However, most of this is reabsorbed into the balanced flows with relatively little lost to explicit model dissipation O (0.001–0.047) TW. Several studies have pointed out that fronts can spontaneously generate inertia–gravity waves. Using a two-dimensional numerical model, Snyder et al. (1993) showed that atmospheric fronts forced out of balance by frontogenetic confluence can spontaneously radiate

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Nicolas Grisouard and Leif N. Thomas

ageostrophic instability that is particularly effective at removing kinetic energy from geostrophic frontal flows is symmetric instability (SI). SI forms in the surface boundary layer of ocean fronts when the stratification is weakened by winds or sea-to-air heat transfer such that the Richardson number of the balanced flow is less than one ( Haine and Marshall 1998 ; Taylor and Ferrari 2009 ; Thomas and Taylor 2010 ; Thomas et al. 2013 ). In the absence of destabilizing atmospheric forcing, SI

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Jörn Callies and Raffaele Ferrari

1. Introduction Oceanographers have long debated how energy is transferred from large to dissipative scales. Much progress has been made in describing the energy pathways from basin to mesoscales and then from scales on the order of 1 km down to millimeter scales. 1 But our understanding of the transfer in between, in the submesoscale range, is still rudimentary. 2 A major question is whether the energy fluxes in the submesoscale are dominated by internal waves and other unbalanced motions or

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Sean Haney, Baylor Fox-Kemper, Keith Julien, and Adrean Webb

instability leads to a forward energy cascade. These submesoscale flows are typically restricted to the mixed layer of the ocean because strong forcing from wind and strain by mesoscale features creates fast flows over short length scales [where Ro ~ O (1)]. Convection and wind also make the near-surface stratification very weak (Ri ≲ 1). Since submesoscale flows occur at the upper boundary layer, they coexist with wind and wave forcing. Despite having a partially geostrophically balanced state, these

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Ryan Abernathey and Paola Cessi

us to consider H 1,2 to be also slowly varying in y . The wave response can be easily obtained by parameterizing the time-mean transient eddy PV fluxes as downgradient diffusion of PV, that is, The parameterization [ (29) ] ensures that the transient eddies act to damp the standing waves, as found in atmospheric models ( Held and Ting 1990 ). It is also consistent with the diagnosed fluxes in the primitive equation results, although the diffusivity K is spatially variable in the

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Carlowen A. Smith, Kevin G. Speer, and Ross W. Griffiths

spectral slopes at wavenumber greater than k ρ follow roughly a − slope ( Fig. 13 ). At the high-wavenumber end of the spectrum, the effective Rossby number is large, consistent with internal wave–related turbulence. Some evidence exists for a − spectrum in ocean observations, at lower (relative to internal wave scales) wavenumbers ( Klymak and Moum 2007 ; Holbrook 2005 ). This may be consistent with atmospheric observations ( Gage and Nastrom 1986 ), although the slopes are not expected to be

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Peter E. Hamlington, Luke P. Van Roekel, Baylor Fox-Kemper, Keith Julien, and Gregory P. Chini

National Center for Atmospheric Research. REFERENCES Adcroft , A. , and Coauthors , 2014 : The MITgcm user manual. Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, 470 pp. [Available online at .] Alves , J. , M. Banner , and I. Young , 2003 : Revisiting the Pierson–Moskowitz asymptotic limits for fully developed wind waves . J. Phys. Oceanogr. , 33 , 1301

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Katherine McCaffrey, Baylor Fox-Kemper, and Gael Forget

not fully describe the composite nature of observed variability seen in real ocean data. Macroturbulence as defined above includes mesoscale eddy activity, internal waves, and other signals such as responses to atmospheric forcing. A complementary approach is to distinguish among observed macroturbulence according to its spatial scale. To this end, structure functions provide an adequate tool that is here applied to in situ profiles of salinity collected by the global array of Argo floats. a

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R. M. Holmes and L. N. Thomas

, doi: 10.1029/95JC00305 . Seo , H. , M. Jochum , R. Murtugudde , A. Miller , and J. Roads , 2007 : Feedback of tropical instability-wave-induced atmospheric variability onto the ocean . J. Climate , 20 , 5842 – 5855 , doi: 10.1175/JCLI4330.1 . Shchepetkin , A. , and J. McWilliams , 2005 : The Regional Oceanic Modeling System (ROMS): A split-explicit, free-surface, topography-following-coordinate oceanic model . Ocean Modell. , 9 , 347 – 404 , doi: 10.1016/j.ocemod.2004

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Jonathan Gula, M. Jeroen Molemaker, and James C. McWilliams

Scatterometer (QuikSCAT) scatterometer winds [Scatterometer Climatology of Ocean Wind (SCOW); Risien and Chelton 2008 ]. Heat and freshwater atmospheric forcing are from the Comprehensive Ocean–Atmosphere Data Set (COADS; Silva et al. 1994 ). Freshwater atmospheric forcing has an additional restoring tendency to prevent surface salinity from drifting away from climatological values. This weak restoring is toward climatological monthly surface salinity from the World Ocean Atlas ( WOA ; Conkright et al

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