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Abstract Volcano-seismic signals can help for volcanic hazard estimation and eruption forecasting. However, the underlying mechanism for their low frequency components is still a matter of debate. Here, we show signatures of dynamic strain records from Distributed Acoustic Sensing in the low frequencies of volcanic signals at Vulcano Island, Italy. Signs of unrest have been observed since September 2021, with CO2 degassing and occurrence of long period and very long period events. We interrogated a fiber-optic telecommunication cable on-shore and off-shore linking Vulcano Island to Sicily. We explore various approaches to automatically detect seismo-volcanic events both adapting conventional algorithms and using machine learning techniques. During one month of acquisition, we found 1488 events with a great variety of waveforms composed of two main frequency bands (from 0.1 to 0.2 Hz and from 3 to 5 Hz) with various relative amplitudes. On the basis of spectral signature and family classification, we propose a model in which gas accumulates in the hydrothermal system and is released through a series of resonating fractures until the surface. Our findings demonstrate that fiber optic telecom cables in association with cutting-edge machine learning algorithms contribute to a better understanding and monitoring of volcanic hydrothermal systems.

On 21 May 2023, a hidden eruption occurred at the Southeast Crater (SEC) of Etna (Italy); indeed, bad weather prevented its direct and remote observation. Tephra fell toward the southwest, and two lava flows propagated along the SEC’s southern and eastern flanks. The monitoring system of the Istituto Nazionale di Geofisica e Vulcanologia testified to its occurrence. We analyzed the seismic and infrasound signals to constrain the temporal evolution of the fountain, which lasted about 5 h. We finally reached Etna’s summit two weeks later and found an unexpected pyroclastic density current (PDC) deposit covering the southern lava flow at its middle portion. We performed unoccupied aerial system and field surveys to reconstruct in 3D the SEC, lava flows, and PDC deposits and to collect some samples. The data allowed for detailed mapping, quantification, and characterization of the products. The resulting lava flows and PDC deposit volumes were (1.54 ± 0.47) × 106 m3 and (1.30 ± 0.26) × 105 m3, respectively. We also analyzed ground-radar and satellite data to evaluate that the plume height ranges between 10 and 15 km. This work is a comprehensive analysis of the fieldwork, UAS, volcanic tremor, infrasound, radar, and satellite data. Our results increase awareness of the volcanic activity and potential dangers for visitors to Etna’s summit area.

Abstract Infrasound is increasing applied as a tool to investigate magma dynamics at active volcanoes, especially at open-vent volcanoes, such as Mt. Etna (Italy), which are prodigious sources of infrasound. Harmonic infrasound signals have been used to constrain crater dimensions and track the movement of magma within the shallow plumbing system. This study interprets the remarkable systematic change in monotonic infrasound signals preceding a lava fountaining episode at Mt. Etna on 20 February 2021. We model the changing tones (0.7 to 3 Hz fundamental frequency) as a rise in the magma column from 172 ± 25 m below the crater rim to 78 ± 8 m over the course of 24 h. The infrasonic gliding disappears approximately 4 h before the onset of lava fountaining as the magma column approaches the flare of the crater and acoustic resonance is no longer supported. The featured 20 February event was just one of 52 lava fountain episodes that occurred at Mt. Etna over the course of 9 months in 2021 and was the only lava fountain episode where dramatic gliding was observed as a subsequent partial collapse of the crater prevented future resonance. The results presented here demonstrate that analysis of infrasonic gliding can be used to track the position of the magma free surface and hence may provide information on the processes taking place within the plumbing system before eruptive activity.

In September 2021, the La Fossa crater at Vulcano, in Italy, entered a new phase of unrest. We discuss a set of monitoring parameters included in the INGV surveillance network, which closely tracked the sequence of effects related to the crisis. The low-frequency local seismicity sharply increased, while the GPS and tiltmeter networks recorded the inflation of the cone, as an effect of fluid expansion in the hydrothermal system. Gravity variations were probably the effects of fast processes within shallow sources. The anomalies in soil CO2 flux, fumarole temperature, and in plume SO2 flux marked the strong increase in the vapor output from crater fumaroles. The signs of the impending crisis had been evident in the chemical and isotopic composition of fumarole gases since July 2021. These geochemical anomalies were clearly indicative of the enhanced input of gases from a magmatic source. In October, the massive degassing also influenced the areas at the base of the cone. In some areas, soil CO2 degassing and the thermal aquifer recorded strong anomalies. By early November, the crisis reached its acme. Afterward, the monitored parameters started a slow and discontinuous decreasing trend although remaining, some of them, sensibly above the background for several months. The multidisciplinary approach proved decisive for the interpretation of the underlying processes acting in the different phases of the unrest, thus allowing a consistent evaluation of the multiple hazards.

The Hunga Tonga-Hunga Ha’apai volcano (Pacific Ocean) generated a cataclysmic explosion on 15 January 2022, triggering several atmospheric disturbances at a global scale, as a huge increase in the total electron content (TEC) in the ionosphere, and a pressure wave travelling in the troposphere. We collected and analysed data over the Mediterranean to study these disturbances, and in particular, (i) data from the barometric and infrasonic stations installed on Italian active volcanoes by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) for investigating the tropospheric pressure waves; (ii) barometric data from the INGV-TROPOMAG and SIAS (Sicilian Agro-meteorological Information System) networks, for investigating the interaction between the orography and pressure waves; (iii) ionograms from the Advanced Ionospheric Sounder-INGV ionosonde at Gibilmanna (Sicily, Italy); (iv) data from the RING (Rete Italiana Integrata GNSS) network, to retrieve the ionospheric TEC; (v) soil CO2 flux data from the INGV surveillance network of Vulcano Island. The analysis of the ground-level barometric data highlights that pressure waves were reflected and diffracted by the topographic surface, creating a complex space–time dynamic of the atmospheric disturbances travelling over Sicily, driven by the interference among the different wavefronts. The ionograms show that a medium-scale travelling ionospheric disturbance (MSTID), with a horizontal wavelength of about 220 km and a period of about 35 min, propagated through the ionospheric plasma in the correspondence of the first barometric variations. Moreover, comparing detrended TEC and barometric data, we further confirmed the presence of the aforementioned MSTID together with its close relation to the tropospheric disturbance.

Between 13 December 2020 and 21 February 2022, Etna volcano produced a sequence of 66 paroxysmal explosive eruptions, with Strombolian activity at the summit craters climaxing in lava fountains and eruption columns extending several kilometers above the craters, accompanied by minor and short-lasting lava flows from the crater rim. We selected three of these episodes that occurred within a short space of time, between 13 December 2020 and 12 March 2021, of different magnitude (i.e., erupted volume) and intensity (i.e., mass eruption rate or instantaneous eruption rate), and analyzed them from a multidisciplinary perspective. The aim was to gain insights into those parameters that mostly reveal the eruptive process for hazard assessment purposes. The multidisciplinary data consist of calibrated visible images, thermal images, seismic and infrasound data, ground deformation detected from the strainmeters, as well as satellite SEVIRI images. From these data, we obtained the timing of each paroxysmal event, the erupted volume in terms of tephra and lava flows, and the corresponding deflation of the source region, together with the development of the lava fountains and eruption columns with time. The results enabled determining that the smallest episode was that of 13 December 2020, which comprised three distinctive pulses but did not produce an eruptive column detectable from either monitoring cameras or satellites. The 28 February 2021 episode was remarkable for the short amount of time required to reach the climax, and was the most intense, whereas the 12 March 2021 event showed the longest duration but with an intensity between that of the previous two. Our results show that these three paroxysmal events display a typical trend, with the first event also being the smallest in terms of both erupted volume and intensity, the second being the most intense, and the third the one of greatest magnitude but less intense than the second. This is coherent with the end of the first paroxysmal phase on 1 April 2021, which was followed by 48 days of eruptive pause before starting again. In this context, the end of the paroxysmal phase was anticipated by a more effusive episode, thus heralding a temporary decline in the gas content within the feeding magma batch.

Infrasonic signals investigation plays a fundamental role for both volcano monitoring purpose and the study of the explosion dynamics. Proper and reliable detection of weak signals is a critical issue in active volcano monitoring. In particular, in volcanic acoustics, it has direct consequences in pinpointing the real number of generated events (amplitude transients), especially when they exhibit low amplitude, are close in time to each other, and/or multiple sources exist. To accomplish this task, several algorithms have been proposed in literature; in particular, to overcome limitations of classical approaches such as short-time average/long-time average and cross-correlation detector, in this paper a subspace-based detection technique has been implemented. Results obtained by applying subspace detector on real infrasound data highlight that this method allows sensitive detection of lower energy events. This method is based on a projection of a sliding window of signal buffer onto a signal subspace that spans a collection of reference signals, representing similar waveforms from a particular infrasound source. A critical point is related to subspace design. Here, an empirical procedure has been applied to build the signal subspace from a set of reference waveforms (templates). In addition, in order to determine detectors parameters, such as subspace dimension and detection threshold, even in presence of overlapped noise such as infrasonic tremor, a statistical analysis of noise has been carried out. Finally, the subspace detector reliability and performance, have been assessed by performing a comparison among subspace approach, cross-correlation detector and short-time average/long-time average detector. The obtained confusion matrix and extrapolated performance indices have demonstrated the potentiality, the advantages and drawbacks of the subspace method in tracking volcanic activity producing infrasound events. This method revealed to be a good compromise in detecting low-energy and very close in time events recorded during Strombolian activity.

In July and August 2019, Stromboli volcano underwent two dangerous paroxysms previously considered “unexpected” because of the absence of significant changes in usually monitored parameters. We applied a multidisciplinary approach to search for signals able to indicate the possibility of larger explosive activity and to devise a model to explain the observed variations. We analysed geodetic data, satellite thermal data, images from remote cameras and seismic data in a timespan crossing the eruptive period of 2019 to identify precursors of the two paroxysms on a medium-term time span (months) and to perform an in-depth analysis of the signals recorded on a short time scale (hours, minutes) before the paroxysm. We developed a model that explains the observations. We call the model “push and go” where the uppermost feeding system of Stromboli is made up of a lower section occupied by a low viscosity, low density magma that is largely composed of gases and a shallower section occupied by the accumulated melt. We hypothesize that the paroxysms are triggered when an overpressure in the lower section is built up; the explosion will occur at the very moment such overpressure overcomes the confining pressure of the highly viscous magma above it.