We describe a new volcanic hotspot detection system, named Middle InfraRed Observation of Volcanic Activity (MIROVA), based on the analysis of infrared data acquired by the Moderate Resolution Imaging Spectroradiometer sensor (MODIS). MIROVA uses the middle infrared radiation (MIR), measured by MODIS, in order to detect and measure the heat radiation deriving from volcanic activity. The algorithm combines spectral and spatial principles, allowing the detection of heat sources from 1 megawatt (MW) to more than 10 gigawatt (GW). This provides a unique opportunity to: (i) recognize small-scale variations in thermal output that may precede the onset of effusive activity; (ii) track the advance of large lava flows; (iii) estimate lava discharge rates; (iv) identify distinct effusive trends; and, lastly, (v) follow the cooling process of voluminous lava bodies for several months. Here we show the results obtained from data sets spanning 14 years recorded at the Stromboli and Mt Etna volcanoes, Italy, and we investigate the above aspects at these two persistently active volcanoes. Finally, we describe how the algorithm has been implemented within an operational near-real-time processing chain that enables the MIROVA system to provide data and infrared maps within 1 -4 h of the satellite overpass.

Effusive eruptions are explained as the mechanism by which volcanoes restore the equilibrium perturbed by magma rising in a chamber deep in the crust. Seismic, ground deformation and topographic measurements are compared with effusion rate during the 2007 Stromboli eruption, drawing an eruptive scenario that shifts our attention from the interior of the crust to the surface. The eruption is modelled as a gravity-driven drainage of magma stored in the volcanic edifice with a minor contribution of magma supplied at a steady rate from a deep reservoir. Here we show that the discharge rate can be predicted by the contraction of the volcano edifice and that the very-long-period seismicity migrates downwards, tracking the residual volume of magma in the shallow reservoir. Gravity-driven magma discharge dynamics explain the initially high discharge rates observed during eruptive crises and greatly influence our ability to predict the evolution of effusive eruptions.

Keywords: ash eruptions plume height mass eruption rate infrasound a b s t r a c t During operational ash-cloud forecasting, prediction of ash concentration and total erupted mass directly depends on the determination of mass eruption rate (MER), which is typically inferred from plume height. Uncertainties for plume heights are large, especially for bent-over plumes in which the ascent dynamics are strongly affected by the surrounding wind field. Here we show how uncertainties can be reduced if MER is derived directly from geophysical observations of source dynamics. The combination of infrasound measurements and thermal camera imagery allows for the infrasonic type of source to be constrained (a dipole in this case) and for the plume exit velocity to be calculated (54-142 m/s) based on the acoustic signal recorded during the 2010 Eyjafjallajökull eruption from 4 to 21 May. Exit velocities are converted into MER using additional information on vent diameter (50 710 m) and mixture density (5.4 7 1.1 kg/m 3 ), resulting in an average $ 9 Â 10 5 kg/s MER during the considered period of the eruption. We validate our acoustic-derived MER by using independent measurements of plume heights (Icelandic Meteorological Office radar observations). Acoustically derived MER are converted into plume heights using field-based relationships and a 1D radially averaged buoyant plume theory model using a reconstructed total grain size distribution. We conclude that the use of infrasonic monitoring may lead to important understanding of the plume dynamics and allows for real-time determination of eruption source parameters. This could improve substantially the forecasting of volcano-related hazards, with important implications for civil aviation safety.

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. Stromboli (Aeolian Archipelago, Italy) is an open conduit volcano with persistent explosive activity. It is located in the Mediterranean Sea, not far from the coasts of Sicily and Calabria (Fig. 1). The persistent explosive Strombolian activity consists of several hundred of moderate-intensity events per day. Typical Strombolian explosions eject pyroclastic fragments at the height of some tens of meters, which fall a short distance from the eruptive vent. Explosions occur in numerous eruptive vents located in the summit area of the volcano that can change over time both in number and position. However, the eruptive vents can be grouped into three areas (Fig. 1), northeast (NE), central (C) and southwest (SW), and are distributed along the dominant structural direction (NE-SW) of a graben-like collapsed area at the top of the volcanic edifice 1-3. Major explosions 4,5 eject pyroclastic material over a hundred meters high, which can fall outside the crater terrace in the area visited by tourists. The frequency of these phenomena varies in time, with an average of 2 events per year 5-7. Paroxysms, violent explosions that produce eruptive columns more than 3 km high and are often accompanied by pyroclastic flows, can also occur at Stromboli 8-13. Ballistic blocks associated with these explosions can reach up to 2 m in diameter. Strombolian paroxysms are rare and their occurrence frequency varies over time.

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[1] Infrasonic and seismic waveforms were collected during violent strombolian activity at Yasur Volcano (Vanuatu). Averaging~3000 seismic events showed stable waveforms, evidencing a low-frequency (0.1-0.3 Hz) signal preceding 5-6 s the explosion. Infrasonic waveforms were mostly asymmetric with a sharp compressive (5-106 Pa) onset, followed by a small long-lasting rarefaction phase. Regardless of the pressure amplitude, the ratio between the positive and negative phases was constant. These waveform characteristics closely resembled blast waves. Infrared imagery showed an apparent cold spherical front~20 m thick, which moved between 342 and 405 m/s before the explosive hot gas/fragments cloud. We interpret this cold front as that produced by the vapor condensation induced by the passage of the shock front. We suggest that violent strombolian activity at Yasur was driven by supersonic dynamics with gas expanding at 1.1 Mach number inside the conduit.

Open-conduit volcanic systems are typically characterized by unsealed volcanic conduits feeding permanent or quasi-permanent volcanic activity. This persistent activity limits our ability to read changes in the monitored parameters, making the assessment of possible eruptive crises more difficult. We show how an integrated approach to monitoring can solve this problem, opening a new way to data interpretation. The increasing rate of explosive transients, tremor amplitude, thermal emissions of ejected tephra, and rise of the very-long- period (VLP) seismic source towards the surface are interpreted as indicating an upward migration of the magma column in response to an increased magma input rate. During the 2014 flank eruption of Stromboli, this magma input pre- ceded the effusive eruption by several months. When the new lateral effusive vent opened on the Sciara del Fuoco slope, the effusion was accompanied by a large ground deflation, a deepening of the VLP seismic source, and the cessation of summit explosive activity. Such observations suggest the drainage of a superficial magma reservoir confined between the crater terrace and the effusive vent. We show how this model successfully reproduces the measured rate of effusion, the observed rate of ground deflation, and the deepening of the VLP seismic source. This study also demonstrates the ability of the geophysical network to detect superficial magma recharge within an open-conduit system and to track magma drainage during the effusive crisis, with a great impact on hazard assessment

Explosive volcanic eruptions can eject large amounts of ash into the atmosphere, posing a serious threat to populations living near the volcano. The abrupt occurrence of such events requires a rapid response and proper volcanic hazard evaluation. Current monitoring procedures still require human intervention, which often results in significant delays between the occurrence of an eruption and notifications being dispatched. We show how dedicated infrasound array processing can be used to detect and notify the authorities, automatically and in real time, of the onset of explosive eruptions. Conceptually, our method relies on the strong coupling between infrasound and the explosive process, and it is not based on probabilistic considerations but on the ability infrasound has to detect the early stage of the explosive phase. This procedure has been tested for the last 8 years, and it is currently applied to issue early warnings for explosive eruptions at Etna Volcano. We show that the system is able to provide a prealert ~1 hr before the eruption, and it has a 96.6% success rate, with only 1.7% false positive alerts and no false negative alerts. This is, to our knowledge, the first example of an operational early warning system totally based on an unsupervised algorithm that provides automatic notifications of eruptions to a government agency. We show that the same early warning concept might be applicable to arrays at large distances (>500 km), suggesting that infrasound could be successfully used to issue automatic notifications of ongoing eruptions at regional to global scales.