Ocean acoustic wave propagation and ray method correspondence: internal wave fine structure
Katherine C. Hegewisch, Nicholas R. Cerruti, Steven Tomsovic
Abstract
Acoustic wave fields propagating long ranges through the ocean are refracted by the inhomogeneities in the ocean's sound speed profile. Intuitively, for a given acoustic source frequency, the inhomogeneities become ineffective at refracting the field beyond a certain fine scale determined by the acoustic wavelength. On the other hand, ray methods are sensitive to infinitely fine features. Thus, it is possible to complicate arbitrarily the ray dynamics, and yet have the wave field propagate unchanged. This feature raises doubts about the ray/wave correspondence. Given the importance of various analyses relying on ray methods, a proper model should, at a minimum, exclude all of the fine structure that does not significantly alter the propagated wave field when the correspondence to the ray dynamics is integral. We develop a simple, efficient, smoothing technique to be applied to the inhomogeneities - a low pass filtering performed in the spatial domain - and give a characterization of its necessary extent as a function of acoustic source frequency. We indicate how the smoothing improves the ray/wave correspondence, and show that the so-called ``ray chaos'' problem remains above a very low frequency (about 15-25 Hz).
Create a lesson
Related papers
Unreported large errors from two PAMGuard three-dimensional localizers of whale calls
Maya Mathur, Luke Stoner-Eby, Devin Pascoe et al.
A more predictable Madden-Julian Oscillation index derived from Koopman spectral analysis
Claire Valva, Edwin P. Gerber
"La Ola-MJO": a public-friendly nickname for the Madden-Julian Oscillation
Takeshi Izumo, Bastien Pagli, Claire Rocuet et al.
Disentangled Fingerprints suggest no historical weakening of Atlantic Overturning and Subpolar Gyre
Bahar Emirzade, Jade Ajagun-Brauns, Maya Ben-Yami et al.
How Much Hyperspectral Information Does Chlorophyll Retrieval Really Need?
Abed Hammoud, Xuerong Sun, Bianca Champenois et al.
Butterfly Effect and the Kinetic Energy Cascade in Probabilistic Machine Learning Weather Prediction Models
Jiakai Chen, Joel Oskarsson, Simon Driscoll et al.