A Study of Acoustic Fluctuations from Basin-Scale Pulse Transmissions

Abstract

LONG-TERM GOAL. The long-term goal of this research is to develop our understanding of long-range oceanic pulse propagation through random sound speed fields, like those caused by internal waves, so that we can use acoustic fluctuations like temporal, vertical, and horizontal coherence to infer average internal-wave spectral parameters. SCIENTIFIC OBJECTIVES. The scientific objective of this work is to develop analytical expressions for temporal, vertical, and horizontal coherence of the acoustic field as a function of internal-wave model parameters and compare these analytic model predictions to data and numerical models. Analytical results for these second moments are important because they eliminate the need for time-consuming Monte-Carlo runs and they allow an efficient treatment of the inverse problem[1]. A key element of this work is to understand the limits of geometrical optics (GO) at frequencies of order 75-Hz, and to evaluate the relative contributions of medium decoherence and intermittent structure[2] on the acoustic coherence functions. It has been shown that acoustic fluctuations from energy which has ensonified the upper few hundred meters of the ocean cannot be explained using the Garrett-Munk (GM) internal wave model[1], so a secondary, oceanographic objective of this work is to explore upper ocean internal-wave models.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 1999
Accession Number
ADA629650

Entities

People

  • John A. Colosi

Organizations

  • Woods Hole Oceanographic Institution

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Calorific Value
  • Data Analysis
  • Engineering
  • Frequency
  • Information Operations
  • Internal Waves
  • Inverse Problems
  • Observation
  • Observatories
  • Signal Processing
  • Travel Time
  • Two Dimensional
  • Waves

Fields of Study

  • Physics

Readers

  • Acoustical Oceanography.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference