Microbaroms are atmospheric pressure oscillations radiated from non-linear ocean surface wave interactions. Large regions of interacting high-energetic ocean waves, e.g., ocean swell and marine storms, radiate almost continuously acoustic energy. Microbaroms dominate the infrasound ambient noise field, which makes them a preferred source for passive atmospheric probing. Microbarom are simulated using a two-fluid model, representing an atmosphere over a finite-depth ocean and a coupled ocean-wave model providing the sea state. Air-sea coupling is crucial due to the two-way interaction between surface winds and ocean waves. In this study, a detailed overview is given on how global microbarom simulations are obtained, including a sensitivity analysis of the various model input data and parameterizations. Simulations are validated by infrasound array observations of the International Monitoring Systems (IMS) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). An brief demonstration is given on the added value of global microbarom simulationsfor infrasound studies and how to obtain these source simulations.
Skip Nav Destination
Article navigation
May 2017
Meeting abstract. No PDF available.
May 01 2017
Simulating global atmospheric microbaroms from 2010 onward
Pieter Smets;
Pieter Smets
R&D Dept. of Seismology and Acoust., KNMI, PO Box 201, De Bilt 3730 AE, Netherlands, [email protected]
Search for other works by this author on:
Jelle Assink;
Jelle Assink
R&D Dept. of Seismology and Acoust., KNMI, PO Box 201, De Bilt 3730 AE, Netherlands, [email protected]
Search for other works by this author on:
Läslo Evers
Läslo Evers
R&D Dept. of Seismology and Acoust., KNMI, PO Box 201, De Bilt 3730 AE, Netherlands, [email protected]
Search for other works by this author on:
J. Acoust. Soc. Am. 141, 3628 (2017)
Citation
Pieter Smets, Jelle Assink, Läslo Evers; Simulating global atmospheric microbaroms from 2010 onward. J. Acoust. Soc. Am. 1 May 2017; 141 (5_Supplement): 3628. https://doi.org/10.1121/1.4987802
Download citation file:
93
Views
Citing articles via
A survey of sound source localization with deep learning methods
Pierre-Amaury Grumiaux, Srđan Kitić, et al.
Rapid detection of fish calls within diverse coral reef soundscapes using a convolutional neural network
Seth McCammon, Nathan Formel, et al.
Related Content
Global infrasound monitoring—Research issues
J Acoust Soc Am (October 2002)
Infrasonic interferometry of stratospherically refracted microbaroms—A numerical study
J. Acoust. Soc. Am. (October 2013)
Uncertainties associated with parameter estimation in atmospheric infrasound arrays
J Acoust Soc Am (December 2003)
In situ calibration of atmospheric-infrasound sensors including the effects of wind-noise-reduction pipe systems
J. Acoust. Soc. Am. (September 2011)
The radiation of atmospheric microbaroms by ocean waves
J. Acoust. Soc. Am. (May 2006)