Estimating oceanic turbulence dissipation from seismic images
Holbrook, W. Steven
Schmitt, Raymond W.
Klymak, Jody M.
Helfrich, L. Cody
MetadataShow full item record
Seismic images of oceanic thermohaline finestructure record vertical displacements from internal waves and turbulence over large sections at unprecedented horizontal resolution. Where reflections follow isopycnals, their displacements can be used to estimate levels of turbulence dissipation, by applying the Klymak–Moum slope spectrum method. However, many issues must be considered when using seismic images for estimating turbulence dissipation, especially sources of random and harmonic noise. This study examines the utility of seismic images for estimating turbulence dissipation in the ocean, using synthetic modeling and data from two field surveys, from the South China Sea and the eastern Pacific Ocean, including the first comparison of turbulence estimates from seismic images and from vertical shear. Realistic synthetic models that mimic the spectral characteristics of internal waves and turbulence show that reflector slope spectra accurately reproduce isopycnal slope spectra out to horizontal wavenumbers of 0.04 cpm, corresponding to horizontal wavelengths of 25 m. Using seismic reflector slope spectra requires recognition and suppression of shot-generated harmonic noise and restriction of data to frequency bands with signal-to-noise ratios greater than about 4. Calculation of slope spectra directly from Fourier transforms of the seismic data is necessary to determine the suitability of a particular dataset to turbulence estimation from reflector slope spectra. Turbulence dissipation estimated from seismic reflector displacements compares well to those from 10-m shear determined by coincident expendable current profiler (XCP) data, demonstrating that seismic images can produce reliable estimates of turbulence dissipation in the ocean, provided that random noise is minimal and harmonic noise is removed.
Author Posting. © American Meteorological Society, 2013. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Atmospheric and Oceanic Technology 30 (2013): 1767–1788, doi:10.1175/JTECH-D-12-00140.1.