Long range infrasound monitoring of Etna volcano

Abstract

Among 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.

On The Use of Dense Seismo-Acoustic Network to Provide Timely Early Warning of Volcanic Eruptions

“…In particular, it was demonstrated that infrasound can play a key role in supporting early warning systems by notifying in near real-time the onset of explosive eruptions, thus reducing the risk of aircrafts encountering volcanic ash in poorly monitored regions. Applying the procedure described by Marchetti et al [32] , the amplitude of infrasound detections associated with the July and August eruptions are…”

“…The source amplitude is then multiplied by the normalized number of detections per minute, which reflects the time persistency of the signals recorded at the array. The derived infrasound parameter (IP) is used to define the occurrence of significant explosive volcanic activity when a fixed threshold of 60 is exceeded [32] . Figure 6 shows the IP variations at stations AMT, IS48, OHP, and IS26, color-coded according to the alert level.…”

Machine Learning in Volcanology: A Review

“…Many volcanoes are monitored by observatories that try to estimate at least the probability of the different hazardous volcanic events [3]. Different time series can be monitored and hopefully used for forecasting, including seismic data [4], geomagnetic and electromagnetic data [5], geochemical data [6], deformation data [7], infrasonic data [8], gas data [9], thermal data from satellite [10] and from the ground [11]. Whenever possible, a multiparametric approach is always advisable.…”

Continuous monitoring of the 2015–2018 Nevado del Ruiz activity, Colombia, using satellite infrared images and local infrasound records

“…The pioneer works are Passechnik (1959) at the Bezymyanny volcano (Kamchatka, Russia) and Goerke et al (1965) at the Agung volcano (Bali, Indonesia). In recent years, highperformance infrasound stations are operated as a part of the International Monitoring System (IMS) for verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) and are also used for monitoring and studying volcanic eruptions (Evers and Haak 2005;Le Pichon et al 2010;Matoza et al 2017;Marchetti et al 2019).…”