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 Copyright policy )AbstractAmong ground-based volcano monitoring techniques, infrasound is the only one capable of detecting explosive eruptions from distances of thousands of kilometers. We show how infrasound array analysis, using acoustic amplitude and detection persistency, allows automatic, near-real-time identification of eruptions of Etna volcano (Italy), for stations at distances greater than 500 km. A semi-empirical attenuation relation is applied to recover the pressure time history at the source using infrasound recorded at global scale (>500 km). An infrasound parameter (IP), defined as the product between the number of detections, filtered for the expected back-azimuth of Etna volcano, and range corrected amplitude, is compared with the explosive activity at Etna volcano that was associated with aviation color code RED warnings. This shows that, during favourable propagation conditions, global arrays are capable of identifying explosive activity of Etna 87% of the period of analysis without negative false alerts. Events are typically not detected during unfavourable propagation conditions, thus resulting in a time variable efficiency of the system. We suggest that infrasound monitoring on a global scale can provide timely input for Volcanic Ash Advisory Centres (VAAC) even when a latency of ~1 hour, due to propagation time, is considered. The results highlight the capability of infrasound for near-real-time volcano monitoring at a regional and global scale.
Infrasound, volcano, alert, Article
Infrasound, volcano, alert, Article
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 24 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% | 
