Gliders Deepwater Hurricane Reconnaissance in the Gulf of Mexico

Abstract

The proposed study will use broadband deep-water ambient sound field information collected by stationary and mobile (Slocum glider’s reconnaissance flights) passive acoustic monitoring platforms during a major hurricane passage to reconstruct the storm wind speed distributions and to quantify changes in oceanographic and acoustic environments during storms. Based on the newly collected data and Bayesian inversion technique, a highly range dependent surface source model relevant to hurricane conditions and the frequency-dependent sound attenuation model due to bubble clouds in the high-wind environment will be developed. A model for the acoustic source requires a parameterized model of the winds over the ocean surface. Estimation of the source model parameters from the collected soundscapes will lead to wind speed estimates. In addition, sensitivity of the measured soundscapes to the local water depths, bottom properties, and receiver depths will be assessed. The data collection will be conducted in the northern Gulf of Mexico which is frequently impacted by major storms, for which independent atmospheric measurements, collected during the NOAA reconnaissance flights, and historic ambient noise acoustic data for calibration are available. Directly collected atmospheric data will provide independent validation of the accuracy of reconstructed wind speed distributions. The efficacy of gliders to potentially provide real-time reporting of local wind speeds will be one of the important outcomes of the project. The nature of the collected broadband acoustic data will also offer opportunities for collaborative work to advance detection of submarine landslides, often associated with storm systems. The project aims to advance the science of the air-sea interaction and to enhance the safety of the underwater infrastructure, and the robustness of operations and communications during a major storm passage. In the future, underwater reconnaissance could provide a safe and cost-efficient alternative to the expensive and risky NOAA reconnaissance flights into the hurricane eye.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 21, 2022
Source ID
FA95502110215

Entities

People

  • Natalia Sidorovskaia

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of Louisiana at Lafayette

Tags

Fields of Study

  • Environmental science

Readers

  • Acoustics.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Oceanography.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Autonomy