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The characterization of volcano state is not a simple task due the complexity of physics processes underway. Understanding their evolution prior to and during eruptions is a critical point for identifying transitions in volcanic state. Recent developments in the field of Machine Learning (ML) have proven to be very useful and efficient for automatic discrimination, decision, prediction, clustering and information extraction in many fields, including volcanology. In Romano et al. (2022) the use of ML algorithms led to classify strain VLP families related with changes in volcano dynamics prior of paroxysmal eruptions: algorithms have been able to discriminate little differences in VLPs shape and to find a correspondence among a higher number of families and volcanic phenomenologies. For paroxysmal events occurring outside any long-lasting eruption, the initial success of our approach, although applied only to the few available examples, could permit us to anticipate the time of alert to several days, instead of few minutes, by detecting medium-term strain anomalies: this could be crucial for risk mitigation for inhabitants and tourists. The neural network method used in previous analysis has been extended to a wider (2007-2022) period to verify that families found in the previous narrower time interval were still present. We tried, then, to associate families with volcanic activity, confirming the conceptual model previously introduced (Mattia et al., 2021 and Romano et al., 2022), capable of explaining the changes found. Our innovative analysis of dynamic strain, systematically conducted on several years of available data, may be used to provide an early-warning system also on other open conduit active volcanoes.Valuable information is embedded in the data used in the current work, which could be used not only for scientific purposes but also by civil protection for monitoring reasons. Such a variety of possible usage needs the setting of principles and legal arrangements to be implemented in order to ensure that data will be properly and ethically managed and in turn can be used and accessed by the scientific community.

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.

Since 2004 a research project has been developed to monitor subsurface deformation of Italian volcanoes using borehole strainmeters and long-baseline tiltmeters. Six Sacks-Evertson dilatometers were installed around Campi Flegrei caldera and Vesuvius during 2004–2005 (Scarpa et al., 2007), and in 2008 these instruments were supplemented by two arrays of 28–280 m long water-tube tiltmeters in underground tunnels. Relevant strainmeter and tiltmeter data have been collected and analysed from the instruments installed near Campi Flegrei caldera during the recent unrest episodes. In the period 2004–2005 strain, tilt and GPS data from Campi Flegrei indicate the onset of surface deformation that accompanied a low rate of vertical displacement that continued to 2006, corresponding to an increase of CO2 emission. This strain episode preceded caldera microseismic activity by a few months, as was observed also during a significant inflation episode in 1982. Other transient strain episodes occurred in October 2006, which were accompanied by a swarm of VT (Volcano-Tectonic) and LP (Long Period) events, in 2009, at the time of renewed gas emission activity at Solfatara, and again in March 2010, several minutes before a seismic swarm. The time scale of these transient strain events ranges from some hours to several days, putting tight constraints on the origin of ground uplifts at Campi Flegrei. Their location is compatible with a source inferred from long term deformation signals, located about 4 km beneath Pozzuoli. A proposed mechanism for these aseismic strain episodes is that they are associated with magma growth in reservoirs with occasional pressure relief associated with the leakage of gas.

Two paroxysmal explosions occurred at Stromboli volcano in the Summer 2019, the first of which, on July 3, caused one fatality and some injuries. Within the 56 days between the two paroxysmal explosions, effusive activity from vents located in the summit area of the volcano occurred. No significant changes in routinely monitored parameters were detected before the paroxysmal explosions. However, we have calculated the polarization and the fractal dimension time series of the seismic signals from November 15, 2018 to September 15, 2019 and we have recognized variations that preceded the paroxysmal activity. In addition, we have defined a new parameter, based on RSAM estimation, related to the Very Long Period events, called VLP size, by means of which we have noticed significant variations through the whole month preceding the paroxysm of July 3. In the short term, we have analyzed the signals of a borehole strainmeter installed on the island, obtaining automatic triggers 10 minutes and 7.5 minutes before the July 3 and the August 28 paroxysms, respectively. The results of this study highlight mid-term seismic precursors of paroxysmal activity and provide valuable evidence for the development of an early warning system for paroxysmal explosions based on strainmeter measurements.

Mt. Stromboli is an active volcano, located near the coasts of Sicily (Italy), in the Mediterranean Sea. Its volcanic activity is characterized by mild and frequent explosions, sometimes interrupted by occasional episodes of more vigorous activity, which can be accompanied by lava flows and more energetic eruptions, known as “major” or “paroxysmal” eruptions, according to the energy dissipated during the event.Stromboli produced vulcanian eruptions in 2003, 2007 and July-August 2019, which were well recorded by the INGV monitoring network. In particular the last three events are studied through records from borehole strainmeters, which allow us to infer many details of source dynamics. These events are clearly preceded by a slow strain buildup, starting several minutes before the paroxysms, which can be used in future for civil protection purposes. The eruptions then consist of two or more pulses, with oscillations ranging from several seconds, as in 2007, to some minutes, such as in 2019 and lasting from several minutes to one hour after the explosions.Mechanisms involved in the triggering process of the vulcanian explosions include an increase of magma flux ascending from sources located from 2 to 5-7 km depths and morphological complexity in the upper feeding system.A preliminary early-warning algorithm, based on an evaluation of strain rate change, has been defined: it has shown itself capable of ascertain the occurring eruptions minutes before their summit onset.Valuable information are embedded in the data used in the current work, which could be used not only for scientific purposes but also from civil protection for monitoring reasons. Such a variety of possible usage needs the setting of principles and legal arrangements to be implemented in order to ensure that data will be properly and ethically managed and in turn can be used and accessed from the scientific community.Particular care is needed in order to harmonize the different rules regarding use of data/information, to identify any potential legal issues related to Intellectual Property (IP) and to set up clear and consistent principles related to IP Rights.

In summer 2019, two paroxysmal explosions occurred in Stromboli. The first one occurred on July 3, when the Strombolian ordinary eruptive activity did not show a significant intensification. The explosion formed an eruptive column more than 3 km high. A pyroclastic flow ran down the “Sciara del Fuoco” slope causing a victim and some injuries. Moreover, the pyroclastic flow spread over the sea surface for about one kilometer. On August 28, a second paroxysmal explosion occurred, similar to the previous one. Also in this case the eruption formed an eruptive column of more than 3 km and a pyroclastic flow that expanded along the “Sciara del Fuoco” slope and traveled about 1 km on the sea surface. In the period between the two paroxysms, effusive activity occurred from the summit crater area. The eruptive phase of summer 2019, which began with the paroxysm of 3 July, was not preceded by significant changes in the routinely monitored parameters, such as the hourly frequency (daily average) of the VLP events (typical of Stromboli) and the amplitude of the seismic signal (RSAM). For this reason, we have analyzed the seismic and dilatometric data, which were recorded by the INGV geophysical network in the period November 2018 - September 2019, focusing our attention on other parameters that can give indications on the activity state of the volcano. In particular, we analyzed the data of the broadband seismic stations, equipped with the Guralp CMG40T sensors, and the data of one Sacks-Evertson borehole strainmeter. We defined the "VLP size", which takes into account the waveform of the VLP events, in terms of both amplitude and duration. We also applied time varying Fractal Dimension (FD) analysis to the seismograms of a seismic station close to the crater area and we analyzed the polarization of the same signal. We carried out the polarization analysis both without applying a filter and by filtering the seismic signal in the typical frequency bands of the Stromboli volcanic tremor (1-3 Hz) and of the VLPs (0.5-0.05 Hz). We found that the "VLP size", the FD and the polarization parameters showed significant changes about one month before the paroxysm of July 3. In the short term, we applied an appropriately tuned STA/LTA algorithm to the data of the borehole strainmeter, which is installed on the island at about 2km from the craters, and we obtained an automatic detection of the paroxysmal events 10 and 7.5 minutes before the explosion of July 3 and August 28, respectively.

After a period of mild eruptive activity, Stromboli showed between 2017 and 2018 a reawakening phase, with an increase in the eruptive activity starting in May 2017. The alert level of the volcano was raised from “green” (base) to “yellow” (attention) on 7 December 2017, and a small lava overflowed the crater rim on 15 December 2017. Between July 2017 and August 2018 the monitoring networks recorded nine major explosions, which are a serious hazard for Stromboli because they affect the summit area, crowded by tourists. We studied the 2017–2018 eruptive phase through the analysis of multidisciplinary data comprising thermal video-camera images, seismic, geodetic and geochemical data. We focused on the major explosion mechanism analyzing the well-recorded 1 December 2017 major explosion as a case study. We found that the 2017–2018 eruptive phase is consistent with a greater gas-rich magma supply in the shallow system. Furthermore, through the analysis of the case study major explosion, we identified precursory phases in the strainmeter and seismic data occurring 77 and 38 s before the explosive jet reached the eruptive vent, respectively. On the basis of these short-term precursors, we propose an automatic timely alarm system for major explosions at Stromboli volcano.

This study performs a detailed reconstruction of the rupture mechanism of the 1980 Campania–Lucania (southern Italy) earthquake. This is achieved by relocation of the main event through computation of fault-plane solutions of the aftershocks, P-wave velocity inversion, and analysis of post-seismic ground deformation, which provide an overall picture of the faulting mechanism. All of these data are in favor of a complex rupture mechanism, as already identified by many studies, which consists of three separate events. The present study defines a graben-like rupture, with the first event rupturing a (>20-km-long) segment of a large, high-angle, NE-dipping, SE-NW-striking, normal fault. The two successive ruptures occurred separately, the first along the southern segment, and the second along the northern segment, of a complementary SW-dipping, normal fault. This mechanism is well evidenced by the revised location of the hypocenter of the main event, and the location of the aftershocks and their fault-plane solutions, as well as by the underlying three-dimensional P-wave velocity structure. The model proposed by Amoruso et al. [2005a] that was based on the inversion of co-seismic vertical displacement data is confirmed by the present analyses, as it satisfies all of the available experimental observations, and better constrains the location and fault-plane solutions of the aftershocks, the velocity discontinuities, and the rupture observations at the surface. This conclusion is also supported by analyses of the post-seismic data.

Between December 2004 and August 2005, more than 50, 000 long-period events (LP) accompanied by very-long period pulses (VLP) were recorded at Mt. Etna, encompassing the effusive eruption which started in September 2004. The observed activity can be explained by the injection of a gas slug formed within the magmatic column into an overlying cavity filled by either magmatic or hydrothermal fluids, thus triggering cavity resonance. Although a large number of LP events exhibit similar waveforms before the eruption, they change significantly during and after the eruption. We study the temporal evolution of the LP-VLP activity in terms of the source movement, change of the waveforms, temporal evolution of the dominant resonance frequencies and the source Q factor and changes in the polarization of the signal. The LP source locations before and after the eruption, respectively, do not move significantly, while a slight movement of the VLP source is found. The intensity of the LP events increases after the eruption as well as their dominant frequency and Q factor, while the polarization of the signals changes from predominantly transversal to pure radial motion. Although in previous studies a link between the observed LP activity and the eruption was not found, these observations suggest that such a link was established at the latter end of the eruptive sequence, most likely as a consequence of a reestablishment of the pressure balance in the plumbing system, after it was undermined due to the discharge of large amounts of resident magma during the eruption. Based on the polarization properties of the signal and geological setting of the area, a fluid-filled crack is proposed as the most likely source geometry. The spectral analysis based on the autoregressive-models (SOMPI) is applied to the signals in order to analyse the resonance frequencies and the source Q-factors. The results suggest water and basalt at low gas volume fraction as the most likely fluids involved in the source process. Using theoretical relations for the “ slow waves” radiated from the fluid-filled crack, we also estimate the crack size for both fluids, respectively.