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Dong L. Wu and Stephen D. Eckermann

America, Antarctica, and the Southern Ocean. Figure 9 shows a time series of monthly zonal mean σ 2 A ( n ) and σ 2 D ( n ) and their difference as a function of latitude at selected altitudes. The major annual and vertical variations are controlled by seasonally varying background winds, which filter some GWs and refract others via Eq. (3) to long (short) vertical wavelengths that are more (less) visible to the instrument ( Alexander 1998 ). Although MLS GW variances are dominated by these

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Paul D. Williams, Thomas W. N. Haine, and Peter L. Read

1. Introduction Inertia–gravity waves are observed ubiquitously throughout the stratified parts of the atmosphere (e.g., Eckermann and Vincent 1993 ; Sato et al. 1997 ; Dalin et al. 2004 ) and ocean (e.g., Thorpe 2005 ). Orthodox mechanisms for inertia–gravity wave generation include dynamical instability (e.g., Kelvin–Helmholtz shear instability; Chandrasekhar 1961 ), which is a known source of atmospheric gravity waves ( Fritts 1982 , 1984 ). Another possible mechanism is the

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Chris Snyder, David J. Muraki, Riwal Plougonven, and Fuqing Zhang

spontaneously from the larger-scale jet. We examine that possibility in the present paper using numerical simulations of a dipole vortex in a rotating, stratified fluid. Because it possesses a localized jet between the two counter-rotating constituent vortices, the dipole vortex is a natural idealization of atmospheric “jet streaks” ( Houghton et al. 1981 ; Van Tuyl and Young 1982 ; Cunningham and Keyser 2004 ). Large-scale atmospheric and oceanic flows outside the Tropics are nearly balanced; that is

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John A. Knox, Donald W. McCann, and Paul D. Williams

between regions of maximum TKE dissipation and PIREPs of turbulence is considerable, especially given the relative sparseness and inhomogeneity of pilot reports. Also of note is the null report of turbulence made in a region of minimal TKE dissipation rates. By comparison, the 25-hPa layer (200–225 hPa) bulk Richardson number ( Fig. 2b ) indicates very broad regions of Ri < 1 across much of Illinois, southern Wisconsin, and parts of Michigan. This is the classic problem of overprediction of CAT that

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