Fitting jet noise similarity spectra to volcano infrasound data
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Abstract
Infrasound (low-frequency acoustic waves) has proven useful to detect and characterize subaerial volcanic activity, but understanding the infrasonic source during sustained eruptions is still an area of active research. Preliminary comparison between acoustic eruption spectra and the jet noise similarity spectra suggests that volcanoes can produce an infrasonic form of jet noise from turbulence. The jet noise similarity spectra, empirically derived from audible laboratory jets, consist of two noise sources: large-scale turbulence (LST) and fine-scale turbulence (FST). We fit the similarity spectra quantitatively to eruptions of Mount St. Helens in 2005, Tungurahua in 2006, and Kīlauea in 2018 using nonlinear least squares fitting. By fitting over a wide infrasonic frequency band (0.05–10 Hz) and restricting the peak frequency above 0.15 Hz, we observe a better fit during times of eruption versus non-eruptive background noise. Fitting smaller overlapping frequency bands highlights changes in the fit of LST and FST spectra, which aligns with observed changes in eruption dynamics. Our results indicate that future quantitative spectral fitting of eruption data will help identify changes in eruption source parameters such as velocity, jet diameter, and ash content which are critical for effective hazard monitoring and response.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Fitting jet noise similarity spectra to volcano infrasound data |
| Series title | Earth and Space Science |
| DOI | 10.1029/2021EA001894 |
| Volume | 8 |
| Issue | 11 |
| Year Published | 2021 |
| Language | English |
| Publisher | American Geophysical Union |
| Contributing office(s) | Volcano Science Center |
| Description | e2021EA001894, 16 p. |
| Google Analytic Metrics | Metrics page |