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The Campi Flegrei caldera is in an unrest phase, manifested by increasing ground uplift, seismicity and hydrothermal activity since 2005. The seismicity mainly involves the first 3 km below the main hydrothermal site of Solfatara-Pisciarelli, where an intensifying heating and pressurization phase is inferred by gas geothermobarometers. Geodetic data inversions generally localize the deformation source around this depth in the central sector of the caldera. Two driving mechanisms of magmatic and non-magmatic unrest have been proposed. Recent studies have demonstrated that the main magma storage area is localized at a depth of ~8 km and is periodically recharged by a mafic deeper source. Magmatic fluid transfer from these reservoirs toward the surface can occur through small-volume shallow intrusions, and can occasionally culminate in an eruption. In this frame, investigating the physical properties of subsurface rocks can be valuable to define the source of the current and past unrest. In fact, they can largely affect local stress and strength, controlling volcano dynamics. We explored subsurface rocks of the Campi Flegrei caldera, extracted from 3-km-deep exploratory geothermal wells. X-ray microtomography investigations were combined with in-situ mechanical experiments (4D imaging at room temperature and dry conditions) to characterize rock properties and link them with 3D microstructural changes. The cores were collected according to the most representative stratigraphic levels and are dominated by tuffs alternating with minor lavas. The mineralogical assemblage reflects different depth-dependent T-P conditions ranging from argillic alteration (150 °C) to thermometamorphism (350 °C). Their tensile strength varies between 2 and 15 MPa and shows a general increase with depth, suggesting that a similar excess pressure is required within a potential shallow chamber to drive magma transfer. Combining this preliminary data with correspondent elastic properties, it can be inferred that a volume change between 0.001 and 1 km3 is sufficient to cause rupture conditions in a sill with radius between 0.5 and 5 km, respectively. These results are in agreement with magma volumes erupted during past eruptions at Campi Flegrei caldera, and particularly consistent with volcanological and petrological data of products from small-scale events.

Active calderas are typically characterized by shallow magmatic systems associated with marked geothermal anomalies and significant fluid releases. Ground deformation are generally associated with uplift or subsidence, induced by recharges or emptying/cooling of the magmatic storage system, by expansions or contractions of hydrothermal systems, or by combinations of these factors. The pressure variations in the hydrothermal systems can lead to an increase in the fumarolic and distributed soil degassing activity or in the sudden release of gas, leading to phreatic explosions, even to violent ones.The Island of Vulcano (Italy), part of the Aeolian archipelago (southern Tyrrhenian Sea), contains an active caldera (La Fossa caldera) showing a widespread degassing and fumarolic activity, mainly localized in the main active volcano (La Fossa cone) and in other emissions zones within the caldera. The La Fossa caldera has shown signs of unrest since September 2021 and to date monitoring parameters have not returned to background levels.Accordingly, the geophysical measurements obtained through the Vulcano Island monitoring infrastructures, which include geodetic and seismic data, were analysed. GNSS and DInSAR data, the former processed using the GAMIT-GLOBK software to calculate both time series and velocities of every remote station of the 7-stations network in Vulcano and Lipari islands, the latter processed through the P-SBAS technique, were used to identify the source of deformation. The seismic network data were exploited to discriminate the seismicity induced by regional tectonics from that induced by the magmatic or hydrothermal system (VT, VLP, tremor).The inversion of the ground deformation measurements made possible to investigate the source within the hydrothermal system of the Fossa cone. Moreover. the seismic data analysis reveals the activation of regional crustal structures during the hydrothermal unrest, as well as the flow of hydrothermal fluids within the caldera structures linked to the presence of a pressurized hydrothermal system.The presented results will provide a general overview of the main findings relevant to the Vulcano Island geodetic and seismic data inversion and analysis.

Volcano Observatories (VOs) around the world are required to maintain surveillance of their volcanoes and inform civil protection and aviation authorities about impending eruptions. They often work through consolidated procedures to respond to volcanic crises in a timely manner and provide a service to the community aimed at reducing the potential impact of an eruption. Within the International Airways Volcano Watch (IAVW) framework of the International Civil Aviation Organisation, designated State Volcano Observatories (SVOs) are asked to operate a colour coded system designed to inform the aviation community about the status of a volcano and the expected threats associated. Despite the IAVW documentation defining the different colour-coded levels, operating the Aviation Colour Code (ACC) in a standardised way is not easy, as sometimes, different SVOs adopt different strategies on how, when, and why to change it. Following two European VOs and Volcanic Ash Advisory Centres (VAACs) workshops, the European VOs agreed to present an overview on how they operate the ACC. The comparative analysis presented here reveals that not all VOs in Europe use the ACC as part of their operational response, mainly because of a lack of volcanic eruptions since the ACC was officially established, or the absence of a formal appointment as an SVO. We also note that the VOs, which do regularly adopt ACC, operate differently depending on the frequency and styles of eruptions, the historical eruptive activity, the nature of the unrest, the monitoring level, and also on the agreement they may have with the local Air Transport Navigation providers. This study shows that even though the ACC system was designed to provide a standard, its usage strongly depends on the evaluation of the actors responding to the volcano emergencies. Some common questions have been identified across the different (S)VOs that will need to be addressed by ICAO in order to have a more harmonised approach and usage of the ACC.

The atmospheric dispersion of gases (of natural or industrial origins) can be very hazardous to life and the environment if the concentration of some gas species overcome specie-specific thresholds. In this context, the natural variability associated to the natural phenomena has to be explored to provide robust probabilistic gas dispersion hazard assessments. VIGIL-1.3 (automatic probabilistic VolcanIc Gas dIspersion modeLling) is a Python simulation tool born to automatize the complex and time-consuming simulation workflow required to process a large number of gas dispersion numerical simulations. It is interfaced with two models: a dilute (DISGAS) and a dense gas (TWODEE-2) dispersion model. The former is used when the density of the gas plume at the source is lower than the atmospheric density (e.g. fumaroles), the latter when the gas density is higher than the atmosphere and the gas accumulates on the ground and may flow due to the density contrast with the atmosphere to form a gravity current (e.g. cold CO2 flows).In the enhancement of the code towards a higher-scale computing, here we present the ongoing improvements aimed to extend some code functionalities such as memory management, modularity revision, and full-ensemble uncertainty on gas dispersal scenarios (e.g. sampling techniques for gas fluxes and source locations).Optimizations are also provided in terms of tracking errors, redesignation of the input file, validation of data provided by the users, and addition of the Latin hypercube sampling (LHS) for the post-processing of model outputs.All these new features will be issued in the future release of the code (VIGIL-2.0) in order to facilitate the users which could run VIGIL on laptops or large supercomputer, and to widen the spectrum of model applications from routinely operational forecast of volcanic gas to long-term hazard and/or risk assessments purposes.

A Digital Twin Component (DTC) provides users with digital replicas of different components of the Earth system through unified frameworks integrating real-time observations and state-of-the-art numerical models. Scenarios of extreme events for natural hazards can be studied from the genesis to propagation and impacts using a single DTC or multiple coupled DTCs. The EU DT-GEO project (2022-2025) is implementing a prototype digital twin on geophysical extremes consisting of 12 interrelated Digital Twin Components, intended as self-contained and containerised software entities embedding numerical model codes, management of real-time data streams and data assimilation methodologies. DTCs can be deployed and executed in centralized High Performance Computing (HPC) and cloud computing Research Infrastructures (RIs). In particular, the DTC-V2 is implementing an ensemble-based automated operational system for deterministic and probabilistic forecast of long-range ash dispersal and local-scale tephra fallout. The system continuously screens different ground-based and satellite-based data sources and a workflow is automatically triggered by a volcanic eruption to stream and pre-process data, its ingestion into the FALL3D dispersal model, a centralized or distributed HPC model execution, and the post-processing step. The DTCs will provide capability for analyses, forecasts, uncertainty quantification, and "what if" scenarios for natural and anthropogenic hazards, with a long-term ambition towards the Destination Earth mission-like initiative.

In recent years, there has been a growing interest in ensemble approaches for modelling the atmospheric transport of volcanic aerosol, ash, and lapilli (tephra). The development of such techniques enables the exploration of novel methods for incorporating real observations into tephra dispersal models. However, traditional data assimilation algorithms, including ensemble Kalman filter (EnKF) methods, can yield suboptimal state estimates for positive-definite variables such as those related to volcanic aerosols and tephra deposits. This study proposes two new ensemble-based data assimilation techniques for semi-positive-definite variables with highly skewed uncertainty distributions, including aerosol concentrations and tephra deposit mass loading: the Gaussian with non-negative constraints (GNC) and gamma inverse-gamma (GIG) methods. The proposed methods are applied to reconstruct the tephra fallout deposit resulting from the 2015 Calbuco eruption using an ensemble of 256 runs performed with the FALL3D dispersal model. An assessment of the methodologies is conducted considering two independent datasets of deposit thickness measurements: an assimilation dataset and a validation dataset. Different evaluation metrics (e.g. RMSE, MBE, and SMAPE) are computed for the validation dataset, and the results are compared to two references: the ensemble prior mean and the EnKF analysis. Results show that the assimilation leads to a significant improvement over the first-guess results obtained from the simple ensemble forecast. The evidence from this study suggests that the GNC method was the most skilful approach and represents a promising alternative for assimilation of volcanic fallout data. The spatial distributions of the tephra fallout deposit thickness and volume according to the GNC analysis are in good agreement with estimations based on field measurements and isopach maps reported in previous studies. On the other hand, although it is an interesting approach, the GIG method failed to improve the EnKF analysis.

This article presents findings from two episodes of seismicity and gas emission that occurred on 7 October 2015 and 6 December 2019 in Campi Flegrei caldera. This caldera has been affected by long-term unrest since 2004. The 6 December 2019 episode, consisting of a swarm of 38 earthquakes (maximum duration magnitude 3.1, the largest between 1984 and March 2020), occurred at the end of a one month period characterized by an increase in the ground uplift rate from 0.19±0.01 to 0.72±0.05 mm/day. A sudden increase in the fumarolic tremor amplitude, which is a proxy of gas emission-related parameters recorded at Solfatara–Pisciarelli hydrothermal area (e.g., CO2 air concentration), was observed during the seismicity episode. The uplift rate decreased immediately after the swarm (0.10±0.01 mm/day), whereas the fumarolic tremor amplitude remained higher than that observed prior to the swarm. Through analyzing the time series of uplift recorded in Pozzuoli (central area of the caldera) from differential measurements on tide gauges, we were able to identify the 2015 episode. This episode was characterized by increasing uplift rates that culminated in a seismic swarm of 33 earthquakes on 7 October, which was followed by decreasing uplift rates. We computed double-difference locations of earthquakes from the two swarms and found that they located along a conduit-like path, coinciding with a high-resistivity contrast zone, previously identified by audiomagnetotelluric measurements. The focal mechanisms of the major earthquakes of both swarms indicate fault planes radial with respect to the maximum uplift area. These phenomena can be interpreted as episodes of the volcanic and (or) hydrothermal system pressurization that culminate in an injection of fluids along the conduit-like path, which behaves as a valve that allows fluid discharge and the temporary depressurization of the source region.

We show the equivalence of earthquake-induced ground acceleration and water-pressure waveforms for the case of collocated hydrophones and seafloor seismometers installed in shallow water. In particular, the comparison of the waveforms and amplitude spectra of the acceleration and water-pressure signals confirms the existence of a frequency range of “forced oscillations” in which the water-pressure variations are proportional to the vertical component of the ground acceleration. We demonstrate the equivalence of the acceleration and water-pressure signals for a set of local earthquakes (epicenter distance of a few tens of kilometers) and regional earthquakes with a wide range of magnitude (2.7

Probabilistic volcanic hazard assessment is a standard methodology based on running a deterministic hazard quantification tool multiple times to explore the full range of uncertainty in the input parameters and boundary conditions, in order to probabilistically quantify the variability of outputs accounting for such uncertainties. Nowadays, different volcanic hazards are quantified by means of this approach. Among these, volcanic gas emission is particularly relevant given the threat posed to human health if concentrations and exposure times exceed certain thresholds. There are different types of gas emissions but two main scenarios can be recognized: hot buoyant gas emissions from fumaroles and the ground and dense gas emissions feeding density currents that can occur, e.g., in limnic eruptions. Simulation tools are available to model the evolution of critical gas concentrations over an area of interest. Moreover, in order to perform probabilistic hazard assessments of volcanic gases, simulations should account for the natural variability associated to aspects such as seasonal and daily wind conditions, localized or diffuse source locations, and gas fluxes. Here we present VIGIL (automatized probabilistic VolcanIc Gas dIspersion modeLling), a new Python tool designed for managing the entire simulation workflow involved in single and probabilistic applications of gas dispersion modelling. VIGIL is able to manage the whole process from meteorological data processing, needed to run gas dispersion in both the dilute and dense gas flow scenarios, to the post processing of models' outputs. Two application examples are presented to show some of the modelling capabilities offered by VIGIL., Fabio Dioguardi (FD) has been supported from UK National Capability funding (BGS Innovation Flexible Fund). This funding supported the code preparation, testing and publishing. Fabio Dioguardi (FD), Silvia Massaro (SM), Laura Sandri (LS), Jacopo Selva (JS), Giovanni Macedonio (GM) and Antonio Costa (AC) have also been supported by the European Union’s Horizon 2020 project EUROVOLC (grant agreement no 731070). This funding supported the initial idea and the interaction among the co‑authors. We thank John A. Stevenson (British Geological Survey) for his technical support in the development of VIGIL and its repository. This work is published with permission of the Executive Director of British Geological Survey (UKRI)

Two paroxysmal explosions occurred on Stromboli in the summer of 2019 (July 3 and August 28). The first of these explosions resulted in the death of one person. Furthermore, an effusive phase began on July 3 and lasted until August 30, 2019. This dangerous eruptive phase of Stromboli was not preceded by evident variations in the geophysical parameters routinely monitored, therefore the volcano was considered to be in a state of normal activity.To investigate the precursors of the 2019 eruptive crisis and explain the absence of variations in the parameters routinely monitored, we analyzed the seismo-acoustic signals with an unsupervised neural network capable of discovering hidden structures of the data. We clustered about 14,200 seismo-acoustic events recorded in 10 months (November 15, 2018 - September 15, 2019) using a Self-Organizing Map (SOM). Then we compared the clustering result with the images of visible and thermal monitoring cameras, that were installed and managed by the Istituto Nazionale di Geofisica e Vulcanologia, Italy, and with the Ground-Based Interferometric Synthetic Aperture Radar displacement measurements of the summit area of the volcano recorded by BGInSAR devices, which were installed and managed by Università Degli Studi di Firenze, Italy.The SOM analysis of the seismo-acoustic features associated with the selected dataset of explosions allowed us to recognize three main clusters in the period November 15, 2018 - September 15, 2019. We named these three clusters Red, Blue, and Green. The analysis of a subset of the selected explosions (approximately 180 events) through the videos of the visible and thermal monitoring cameras allowed us to associate distinct explosive types to the three main seismo-acoustic clusters. In particular, the cluster Red was associated with explosions characterized by well collimated oriented jets of ~ 200 m height, which eject incandescent ballistics and produce a significant infrasonic transient. The cluster Blue was associated with gas explosions with a height of 10 - 20 m and with little or no ash and pyroclastic fragment ejection. These types of explosions may not be detected by the camera recordings and infrasonic sensors. On the contrary, they are well recorded in the VLP seismic signals (filtered in the 0.05 - 0.5 Hz frequency band). The cluster Green includes explosions characterized by the emission of incandescent spatter-like fragments, with a wide range of ejection angles and hemispherical shape. The explosions of the cluster Red are mainly generated in the NE vent region, whereas the explosions of clusters Blue and Green are generally located in the central and SW vent regions.Comparing these results with the temporal evolution of the displacement of the summit area measured by the GBInSAR device, we discovered that the variations of the eruptive style that were highlighted by the SOM clustering of the seismic-acoustic features are recognizable in the ground deformation temporal pattern. Our findings are relevant for the improvement of monitoring of volcanoes with persistent activity and volcano early warning.

In the context of recent developments in volcanic muography, we describe an experiment at Vesuvius, the volcano near Naples that destroyed Pompeii and Herculaneum (Italy) in 79 CE. This volcano is about 1,200 m high with a typical summit caldera formed by Mount Somma. Vesuvius is among the highest-risk volcanoes in the world due to its highly explosive eruptive style and the high population density of the area where it is located. Volcanoes are generally fragile geological structures, prone to produce partial collapse and large landslides that can affect the style of eruptions. Moreover, the knowledge of the internal structure is fundamental for understanding past eruption activity and for constraining eruption models. For these reasons, studying the internal structure of the “Gran Cono” (great cone) of Vesuvius and the physical characteristics of its rock is important and led us to design a muography experiment at Vesuvius. This experiment, which is currently in progress, is based on three scintillator detectors with a surface of 1 m 2 each. These detector features have been implemented to overcome the problems related to the large thickness of rock that form the “Gran Cono” of Vesuvius and the effects that can be a source of error in data processing. These aspects represent an open challenge for the muography of large volcanoes, which today constitutes the frontier of research in the field of volcanic muography.

Modelling atmospheric dispersal of volcanic ash and aerosols is becoming increasingly valuable for assessing the potential impacts of explosive volcanic eruptions on infrastructures, air quality, and aviation. Management of volcanic risk and reduction of aviation impacts can strongly benefit from quantitative forecasting of volcanic ash. However, an accurate prediction of volcanic aerosol concentrations using numerical modelling relies on proper estimations of multiple model parameters which are prone to errors. Uncertainties in key parameters such as eruption column height, physical properties of particles or meteorological fields, represent a major source of error affecting the forecast quality. The availability of near-real-time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context by incorporating observations into numerical models. Specifically, ensemble-based filters aim at converting a prior ensemble of system states into an analysis ensemble by assimilating a set of noisy observations. Previous studies dealing with volcanic ash transport have demonstrated that a significant improvement of forecast skill can be achieved by this approach. In this work, we present a new implementation of an ensemble-based Data Assimilation (DA) method coupling the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The FALL3D+PDAF system runs in parallel, supports online-coupled DA and can be efficiently integrated into operational workflows by exploiting high-performance computing (HPC) resources. Two numerical experiments are considered: (i) a twin experiment using an incomplete dataset of synthetic observations of volcanic ash and, (ii) an experiment based on the 2019 Raikoke eruption using real observations of SO2 mass loading. An ensemble-based Kalman filtering technique based on the Local Ensemble Transform Kalman Filter (LETKF) is used to assimilate satellite-retrieved data of column mass loading. We show that this procedure may lead to nonphysical solutions and, consequently, conclude that LETKF is not the best approach for the assimilation of volcanic aerosols. However, we find that a truncated state constructed from the LETKF solution approaches the real solution after a few assimilation cycles, yielding a dramatic improvement of forecast quality when compared to simulations without assimilation.

Volcanic eruptions are amongst the most jeopardizing natural events due to their potential impacts on life, assets, and environment. In particular, atmospheric dispersal of volcanic tephra and aerosols during the explosive eruptions poses a serious threat to life and has significant consequences for infrastructures and global aviation safety. The volcanic island of Jan Mayen, located in the North Atlantic under trans-continental air traffic routes, is considered the northernmost active volcanic area in the world, with at least five eruptive periods recorded during the last 200 years. However, quantitative hazard assessments on the possible consequences for air traffic of a future ash-forming eruption are nonexistent. This study presents the first comprehensive long-term volcanic hazard assessment for Jan Mayen volcanic island in terms of ash dispersal and airborne tephra concentration at different flight levels. In order to delve in the characterization and modelling of that potential impact, a probabilistic approach based on merging a large number of numerical simulations is adopted, varying the volcano’s Eruptive Source Parameters (ESPs) and meteorological scenario. Each ESP value is randomly sampled following a continuous Probability Density Function (PDF) defined from the Jan Mayen geological record. Over 20 years of climatic data are considered in order to explore the natural variability associated with meteorological conditions and used to run thousands of simulations of the ash dispersal model FALL3D on a 2 km-resolution grid. The simulated scenarios are combined to produce probability maps of airborne ash concentration, arrival time and persistence at different flight levels in the atmosphere. The resulting maps represent an aid to civil protection, decision makers and aviation stakeholders in assessing and preventing the potential impact from a future eruption at Jan Mayen.

Campi Flegrei is an active volcano located in one of the most densely inhabited areas in Europe and under high-traffic air routes. There, the Vesuvius Observatory’s surveillance system, which continuously monitors volcanic seismicity, soil deformations and gas emissions, highlights some variations in the state of the volcanic activity. It is well known that fragmented magma injected into the atmosphere during an explosive volcanic eruption poses a threat to human lives and air-traffic. For this reason, powerful tools and computational resources to generate extensive and high-resolution hazard maps taking into account a wide spectrum of events, including those of low probability but high impact, are important to provide decision makers with quality information to develop short- and long- term emergency plans. To this end, in the framework of the Center of Excellence for Exascale in Solid Earth (ChEESE), we show the potential of HPC in Probabilistic Volcanic Hazard Assessment. On the one hand, using the ChEESE's flagship Fall3D numerical code and taking advance of the PRACE-awarded resources at CEA/TGCC-HPC facility in France, we perform thousands of simulations of tephra deposition and airborne ash concentration at different flight levels exploring the natural variability and uncertainty on the eruptive conditions on a 3D-grid covering a 2 km-resolution 2000 km x 2000 km computational domain. On the other hand, we create short- and long-term workflows, by updating current Bayesian-Event-Tree-Analysis-based prototype tools, to make them capable of analyze the large amount of information generated by the Fall3D simulations that finally gives rise to the hazard maps for Campi Flegrei.

The emission of volcanic gases can occur both during volcanic eruptions and in quiescent stages of the volcanic activity. This process can affect the air quality in the areas downwind; in fact, many gas species can be a threat to human health and even life at concentrations and doses above species-specific thresholds. Gas emissions can be of different types, the two main categories being dilute passive degassing and heavy gas flow. The former occurs when the gas concentration is low and/or temperature is high, hence its density is lower than the atmospheric density; the latter takes place when the gas density is higher than the atmosphere and the gas accumulates onto the ground and may flow as a gravity current more or less affected by the wind. Examples of the first and second types of emissions are fumaroles and limnic explosions, respectively.Numerical modelling is one of the approaches used to quantify the hazard related to these processes. Ideally, for hazard quantification purposes numerous simulations originating from varying the most important input parameters (e.g. wind field, emission rates, etc.) in their range of uncertainty should be carried out. The whole process of gas dispersion modelling is time consuming, since it starts with the assessment of the wind field with an ad-hoc meteorological model, proceeds with the actual gas dispersion simulation and concludes with the post-processing stage. In order to simplify the whole workflow with the final aim to manage numerous simultaneous simulations for hazard assessment applications, we created APVGDM (Automatic Probabilistic Volcanic Gas Dispersion Modelling), a simulation tool made of a collection of Python scripts. APVGDM is interfaced with two dispersion models that can be selected by the user depending on the application of interest: a dilute (DISGAS) and a dense gas (TWODEE) dispersion model. The post-processing script is capable of building Empirical Cumulative Distribution Functions (ECDF) of the gas concentrations combining the outputs of multiple simulations; the ECDF can be interrogated by the user to produce outputs at the desired exceedance probability. Here we present APVGDM and some application examples showing the wide range of options that the tool offers.

Episodes of slow uplift and subsidence of the ground, called bradyseism, characterize the recent dynamics of the Campi Flegrei caldera (Italy). In the last decades two major bradyseismic crises occ...

Jan Mayen Island (Norway), located in the North Atlantic, is considered the world’s northernmost active subaerial volcano, with at least five eruptive periods recorded during the last 200 years. Explosive activity of the volcano may seriously affects the nearby important air traffic routes. However, no quantitative studies on the possible impact of a new explosive volcanic eruption on the air traffic have been conducted. In this work, we statistically characterise the spatial and temporal distribution of airborne volcanic ash cloud and its persistence at different flight levels. Since current operational forecast products do not always meet the requirements of the aviation sector and related stakeholders (using coarse time and space scales, with outputs on a 40 km horizontal resolution grid and 6 hour time averages), and they neglect epistemic/aleatory uncertainties in quantitative forecasts on real time, we propose hourly high resolution hazard maps over a 3D-grid covering a 2 km-resolution spatial domain 2000 km x 2000 km wide. We present the use of high-performance computing (HPC) to overcome the computational limitations associated with unbiased long-term probabilistic volcanic hazard assessment (PVHA) .Considering a continuum of possible combinations of Eruptive Source Parameters (ESP) to assess and quantify the uncertainty, and the natural variability associated with wind fields over 20 years of data, from 1999 to 2019, we run thousands of analytical solutions (numerical simulations) using the most recent version of the FALL3D model. As a result, the first comprehensive long-term PVHA for Jan Mayen volcanic island is presented.

In our original paper (Buono et al., 2020), we investigated the dynamics of degassing (e.g., bubble nucleation and growth, degassing styles and regimes) of H2O-, CO2- and H2O-CO2-rich evolved alkaline melts over a wide range of variables (final pressures, decompression rates, volatile compositions and contents, temperatures) through a comprehensive review of previous and new HP (high pressure)-HT (high temperature) decompression experiments. The criticism of Allabar and Nowak regards a restricted part of our results, i.e., those concerning homogeneous bubble nucleation from our new experiments on H2O-rich melts. Their aim is refusing the classical nucleation theory (CNT), widely accepted in literature to explain homogeneous bubble nucleation in magmas, for evolved alkaline melts in favour of the spinodal decomposition. We found that the Authors of the Comment do not provide any new evidence in support of their thesis, but they keep only arbitrary and erroneous conjectures of our new experimental data. As we stated in our original paper, the evaluation of the specific bubble nucleation mechanism (CNT vs. spinodal decomposition) is beyond the scope of our research, as appropriate studies on both experimental and natural products would be necessary to shed light on this complex issue.

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.

This manuscript presents different application cases and validation results of the latest version release of the FALL3D-8.0 model, an open-source atmospheric transport model. The code has been redesigned from scratch to incorporate different categories of species and to overcome legacy issues that precluded its preparation towards extreme-scale computing. Validation results are shown for long-range dispersal of fine volcanic ash and SO2 clouds, tephra fallout deposits and dispersal and ground deposition of radionuclides. The first two examples (i.e. the 2011 Puyehue-Cordón Caulle and 2019 Raikoke eruptions) make use of geostationary satellite retrievals for two purposes: first, to furnish an initial data insertion condition for the model; and second, to validate the time series of model outputs against the satellite retrievals. The metrics used to validate the model simulations of volcanic ash and SO2 are the Structure, Amplitude and Location (SAL) metric and the Figure of Merit in Space (FMS). The other two application cases are validated with scattered ground-based observations of deposit load and local particle grain size distributions from the 23 February 2013 Mt. Etna eruption and with measurements from the Radioactivity Environmental Monitoring (REM) database during the 1986 Chernobyl nuclear accident. Simulation results indicate that FALL3D-8.0 outperforms previous code versions both in terms of model accuracy and code performance. We also find that simulations initialised with the new data insertion scheme consistently improve agreement with satellite retrievals at all lead times out to 48 hours for both SO2 and long-range fine ash simulations.

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.

During a volcanic eruption, one of the most relevant threat for civil aviation is the dispersion of volcanic ash in the atmosphere. All the aircraft are susceptible to suffer damages from volcanic ash even at low concentrations. The economy of Canary Islands (Spain) strongly depends on tourism, so it is of fundamental importance to estimate the consequences of a possible eruptive scenario of the air traffic in the archipelago and consequently on the tourism. We made an exhaustive study about the impact of volcanic ashes on aviation for one of the most important islands in the archipelago: Tenerife.We developed a large set of numerical simulations of small-magnitude eruptions in Tenerife, which are the most probable eruptive scenario in this island. Our main goal is to develop a probabilistic approach to evaluate the airports most affected by dispersion and fallout of volcanic ash. We carried out more than a thousand simulations with the software FALL3D using supercomputing facilities of Teide-HPC from the Instituto Tecnológico y de Energías Renovables (ITER). In order to model the small-magnitude eruptions, we calculated datasets of total mass of volcanic ash erupted and eruption lengths using a bivariate empirical probability density function obtained using Kernel Density Estimation (KDE) from data of historical eruptions in Tenerife. The vent positions were selected following the density of vents related to Holocene eruptions. Granulometries were chosen following Bi-Gaussian distribution of particle size ranging from Φ=-1 to Φ=12, where Φ=-log2d (diameter in mm). The number of eruptive phases within each eruption is selected randomly. We have split equally the total eruptive duration into these eruptive phases and we set a gaussian distribution in the centre of each division. After that, the intersection between each eruptive phase is chosen taking into account these gaussian distributions to have eruptive phases with different duration.All the simulations are coupled with ERA-Interim meteorological reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). We have implemented a probabilistic procedure to map in 3D the hazard associated to volcanic ash. For this purpose, we calculated concentration percentiles (P25, P50 and P75) and time intervals of high concentrations of volcanic ash to evaluate the hazard of suspended ash in the volume surrounding the major airports in Tenerife.