Influence of the Distortion of Vertical Wavenumber Spectra on Estimates of Turbulent Dissipation Using the Finescale Parameterization: Eikonal Calculations

The finescale parameterization, formulated on the basis of a weak nonlinear wave-wave interaction theory, is widely used to estimate the turbulent dissipation rate epsilon. However, this parameterization has previously been found to overestimate epsilon in the Antarctic Circumpolar Current (ACC). One possible reason for this overestimation is that vertical wavenumber spectra of internal wave energy are distorted from the canonical Garrett-Munk spectrum by a spectral hump at low wavenumbers (similar to 0.01 cpm). Such distorted vertical wavenumber spectra were also observed in other mesoscale eddyrich regions. In this study, using eikonal simulations, in which internal wave energy cascades are evaluated in the frequencywavenumber space, we examine how the distortion of vertical wavenumber spectra impacts the accuracy of the finescale parameterization. It is shown that the finescale parameterization overestimates epsilon for distorted spectra with a low-vertical wavenumber hump because it incorrectly takes into account the breaking of these low-vertical-wavenumber internal waves. This issue is exacerbated by estimating internal wave energy spectral levels from the low-wavenumber band rather than from the high-wavenumber band, which is often contaminated by noise in observations. Thus, to accurately estimate the distribution of epsilon in eddy-rich regions like the ACC, high-vertical-wavenumber spectral information free from noise contamination is indispensable.

Automated summary

The finescale parameterization, based on weak nonlinear wave-wave interaction theory, is commonly used to estimate turbulent dissipation rate epsilon. However, it tends to overestimate epsilon in the Antarctic Circumpolar Current (ACC) due to the distortion of vertical wavenumber spectra in low wavenumber internal waves. This distortion can also be observed in other mesoscale eddy-rich regions, highlighting the importance of accurate estimation in such areas.