Statistics of shear and turbulent dissipation profiles in random internal wave fields

MC Gregg, HE Seim… - Journal of physical …, 1993 - journals.ametsoc.org
MC Gregg, HE Seim, DB Percival
Journal of physical oceanography, 1993journals.ametsoc.org
Because breaking internal waves produces most of the turbulence in the thermocline, the
statistics of ε, the rate of turbulent dissipation, cannot be understood apart from the statistics
of internal wave shear. The statistics of ε and shear are compared for two sets of profiles
from the northeast Pacific. One set, PATCHEX, has internal wave shear close to the Garrett
and Munk model, but the other set, PATCHEX north, has average 10-m shear squared,〈 S 2
10〉, about four times larger than the model. The 10-m, shear components, S x and S y, were …
Abstract
Because breaking internal waves produces most of the turbulence in the thermocline, the statistics of ε, the rate of turbulent dissipation, cannot be understood apart from the statistics of internal wave shear. The statistics of ε and shear are compared for two sets of profiles from the northeast Pacific. One set, PATCHEX, has internal wave shear close to the Garrett and Munk model, but the other set, PATCHEX north, has average 10-m shear squared, 〈 S 2 10 〉, about four times larger than the model.
The 10-m, shear components, S x and S y , were measured between 1 and 9 MPa and referenced to a common stratification by WKB scaling. The scaled components, S ^ x and S ^ y , are found to be independent and normally distributed with zero means, as assumed by Garrett and Munk. This readily leads to analytic forms for the probability densities of S ^ 2 10 and S ^ 4 10 . The observed probability densities of S ^ 2 10 and S ^ 4 10 are close to the predicted forms, and both are strongly skewed. Moreover, σ ln S ^ 2 10 and σ ln S ^ 4 10 are constants, independent of the standard deviations of S ^ x and S y . The probability density of the inverse Richardson number, Ri −1 10S 2 10 /〈 N 2 〉, is a scaled version of the probability density of S 2 10 . The PATCHEX distribution cuts off near Ri −1 10 = 4, as found by Eriksen, but the PATCHEX north distribution extends to higher values, as predicted analytically. Consequently, a cutoff at Ri −1 10 = 4 is not a universal constraint.
Over depths where 〈 N 2 〉 is nearly uniform, the probability density of 0.5-m ε can be approximated, to varying degrees of accuracy, as the sum of a noise variate with an empirically determined distribution and a lognormally distributed variate whose parameters can be estimated using a minimum chi-square fitting procedure. The 0.5-m ε, however, are far from being uncorrelated, a circumstance not considered by Baker and Gibson in their analysis of microstructure statistics. Obtaining approximately uncorrelated samples requires averaging over 10 m for PATCHEX and 15 m for PATCHEX north. These lengths correspond approximately to reciprocals of the wavenumbers at which the respective shear spectra roll off. After correcting the uncorrelated ε samples for noise and then scaling to remove the dependence on stratification, the scaled dissipation rates, ε^ ≡ ε( N 2 0 /〈 N 2 〉), are lognormally distributed. (Without noise correction and 〈 N 2 〉 scaling the data are not lognormal; e.g., noise correction and scaling with 〈 N 1 〉 and 〈 N 3/2 〉 do not produce lognormality.)
It is hypothesized that the approximate lognormality of bulk ensembles of ε^ results from generation of turbulence in proportion to S 4 10 . Lognormality is well established for isotropic homogeneous turbulence (Gurvich and Yaglom), and Yamazaki and Lueck show …
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