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Ongoing resurgence affects Campi Flegrei caldera (Italy) via bradyseism, i.e. a series of ground deformation episodes accompanied by increases in shallow seismicity. In this study, we perform a mathematical analysis of the GPS and seismic data in the instrumental catalogs from 2000 to 2020, and a comparison of them to the preceding data from 1983 to 1999. We clearly identify and characterize two overlying trends, i.e. a decennial-like acceleration and cyclic oscillations with various periods. In particular, we show that all the signals have been accelerating since 2005, and 90–97% of their increase has occurred since 2011, 40–80% since 2018. Nevertheless, the seismic and ground deformation signals evolved differently—the seismic count increased faster than the GPS data since 2011, and even more so since 2015, growing faster than an exponential function The ground deformation has a linearized rate slope, i.e. acceleration, of 0.6 cm/yr 2 and 0.3 cm/yr 2 from 2000 to 2020, respectively for the vertical (RITE GPS) and the horizontal (ACAE GPS) components. In addition, all annual rates show alternating speed-ups and slow-downs, consistent between the signals. We find seven major rate maxima since 2000, one every 2.8–3.5 years, with secondary maxima at fractions of the intervals. A cycle with longer period of 6.5–9 years is also identified. Finally, we apply the probabilistic failure forecast method, a nonlinear regression that calculates the theoretical time limit of the signals going to infinity (interpreted here as a critical state potentially reached by the volcano), conditional on the continuation of the observed nonlinear accelerations. Since 2000, we perform a retrospective analysis of the temporal evolution of these forecasts which highlight the periods of more intense acceleration. The failure forecast method applied on the seismic count from 2001 to 2020 produces upper time limits of [0, 3, 11] years (corresponding to the 5th, 50th and 95th percentiles, respectively), significantly shorter than those based on the GPS data, e.g. [0, 6, 21] years. Such estimates, only valid under the model assumption of continuation of the ongoing decennial-like acceleration, warn to keep the guard up on the future evolution of Campi Flegrei caldera.

Since early 2021, peculiar Volcano-Tectonic (VT) seismic sequences with very short inter-event times have become increasingly frequent and evident in the Campi Flegrei caldera (Italy), which has been experiencing a long-term unrest since 2005. During the same period the ground deformation (uplift), seismicity and gas emission that characterize the current unrest showed an acceleration. Within this type of seismic sequence, we identify burst-like swarms, characterized by inter-event times so short that they are often not easily recognizable. Here we show that these sequences are located in an area encompassing the main hydrothermal field and a zone affected by a geodetic anomaly (a region that uplifts less rapidly than the surroundings), which became evident in 2021. This type of seismicity has been associated with phreatic explosions and critical phases of unrest in other volcanoes and currently characterizes the state of activity of Campi Flegrei caldera. During the long-term unrest of the Campi Flegrei caldera, burst-like seismic swarms are observed and associated with an increase in hydrothermal activity and an anomaly in the ground deformation pattern recorded since 2021.

Conduit geometry affects magma ascent dynamics and, consequently, the style and evolution of volcanic eruptions. However, despite geological evidences support the occurrence of conduit widening during most volcanic eruptions, the factors controlling conduit enlargement are still unclear, and the effects of syn-eruptive variations of conduit geometry have not been investigated in depth yet. Based on numerical modeling and the application of appropriate stability criteria, we found out a strong relationship between magma rheology and conduit stability, with significant effects on eruptive dynamics. Indeed, in order to be stable, conduits feeding dacitic/rhyolitic eruptions need larger diameters respect to their phonolitic/trachytic counterparts, resulting in the higher eruption rates commonly observed in dacitic/rhyolitic explosive events. Thus, in addition to magma source conditions and viscosity-dependent efficiency for outgassing, we suggest that typical eruption rates for different magma types are also controlled by conduit stability. Results are consistent with a compilation of volcanological data and selected case studies. As stability conditions are not uniform along the conduit, widening is expected to vary in depth, and three axisymmetric geometries with depth-dependent radii were investigated. They are able to produce major modifications in eruptive parameters, suggesting that eruptive dynamics is influenced by syn-eruptive changes in conduit geometry.

In this study, using the tephra dispersal model HAZMAP, we investigate the effect of using different meteorological datasets and eruption source parameters on tephra fallout hazard assessment for a sub-Plinian eruption of Vesuvius, which is considered as a reference case for hazard assessment analysis. We analyze the effect of using different meteorological data, from: i) radio-sounding carried out at the meteorological station of Brindisi (Italy) between 1962 and 1976 and between 1996 and 2012, and at Pratica di Mare (Rome, Italy) between 1995 and 2013; ii) meteorological models of the National Oceanic and Atmospheric Administration (NOAA), and of the European Centre for Medium-Range Weather Forecasts (ECMWF). Furthermore, we consider the effects of perturbing reference eruptive source parameters. In particular, we vary the total mass, the total grain-size distribution, the column height, and the effective atmospheric diffusion coefficient to evaluate how these parameters affect the hazard probability maps. Moreover, the effect of the seasonal variation of the wind field and the effect of the rain on the deposit loading are considered. Results show that the parameter that mostly affects hazard maps is, as expected, the total erupted mass; furthermore, keeping constant the erupted mass, the most important control on hazard is due to the particle terminal settling velocity distribution which is a function of the total grain-size distribution, particle density and shape. Within the considered range variations, the hazard depends less on the use of different meteorological datasets, column height and effective diffusion coefficient.

Accurate tracking and forecasting of ash dispersal in the atmosphere and quantification of its uncertainty are of fundamental importance for volcanic risk mitigation. Numerical models and satellite sensors offer two complementary ways to monitor ash clouds in real time, but limits and uncertainties affect both techniques. Numerical forecasts of volcanic clouds can be improved by assimilating satellite observations of atmospheric ash mass load. In this paper, we present a data assimilation procedure aimed at improving the monitoring and forecasting of volcanic ash clouds produced by explosive eruptions. In particular, we applied the Local Ensemble Transform Kalman Filter (LETKF) to the results of the Volcanic Ash Transport and Dispersion model HYSPLIT. To properly simulate the release and atmospheric transport of volcanic ash particles, HYSPLIT has been initialized with the results of the eruptive column model PLUME-MoM. The assimilation procedure has been tested against SEVIRI measurements of the volcanic cloud produced during the explosive eruption occurred at Mt. Etna on 24 December 2018. The results show how the assimilation procedure significantly improves the representation of the current ash dispersal and its forecast. In addition, the numerical tests show that the use of the sequential Ensemble Kalman Filter does not require a precise initialization of the numerical model, being able to improve the forecasts as the assimilation cycles are performed.

Computational fluid dynamics (CFD) for fluidization is reaching maturity (Roco, 1998). It has become common practice to compare time‐averaged solid velocities and concentrations to measurements of fluxes and densities. The dynamic behavior of the riser, however, has not been previously compared to experiments. This article shows that the dynamics of solids flow in the riser is in the form of clusters, but the time‐averaged particle concentrations and fluxes give us the core‐annular flow regime in agreement with measurements. The computed clusters, which are essentially compressible gravity waves, produce major frequencies of density oscillations in agreement with measurements. The model and the CFD code compute granular temperature distributions, agreeing qualitatively with data. For volume fraction around 3–4%, which is the average particle concentration in the riser, the computed viscosity agrees with our experimental measurements.

Stromboli volcano (Italy), always active with low energy explosive activity, is a very attractive place for visitors, scientists, and inhabitants of the island. Nevertheless, occasional more intense eruptions can present a serious danger. This study focuses on the modeling and estimation of their inter-event time and temporal rate. With this aim we constructed a new historical catalog of major explosions and paroxysms through a detailed review of scientific literature of the last ca. 140 years. The catalog includes the calendar date and phenomena descriptions for 180 explosive events, of which 36 were paroxysms. We evaluated the impact of the main sources of uncertainty affecting the historical catalog. In particular, we categorized as uncertain 45 major explosions that reportedly occurred before 1985 and tested the effect of excluding these events from our analysis. Moreover, after analyzing the entire record in the period [1879, 2020], we separately considered, as sequences, events in [1879, 1960] and in [1985, 2020] because of possible under recording issues in the period [1960, 1985]. Our new models quantify the temporal rate of major explosions and paroxysms as a function of time passed since the last event occurred. Recurrence hazard levels are found to be significantly elevated in the weeks and months following a major explosion or paroxysm, and then gradually decrease over longer periods. Computed hazard functions are also used to illustrate a methodology for estimating order-of-magnitude individual risk of fatality under certain basis conditions. This study represents a first quantitatively formal advance in determining long-term hazard levels at Stromboli.

Starting from February 2021, Mt. Etna (Italy) experienced a period of intense explosive activity with 17 lava fountain episodes between 16 February and 1 April 2021. During the eruptive cycle, the Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE) issued 62 alert notifications known as VONAs (Volcano Observatory Notice for Aviation) to inform the aeronautical authorities about the volcanic activity. We present an automated VONA-based workflow aimed at real-time assessment of the volcanic hazard due to tephra fallout at Mt. Etna. When a VONA reporting tephra emission is issued by INGV-OE, numerical simulations accounting for atmospheric and eruptive uncertainties are automatically initialized to produce probabilistic hazard maps of tephra fallout and atmospheric dispersal. We applied the workflow to three lava fountains that occurred during the 2021 eruptive cycle. To test the modelling results, we compared the simulated ground load with field data, and the extent and position of the simulated volcanic cloud with the observed or estimated volcanic cloud from the Toulouse Volcanic Ash Advisory Center. Overall, we found a good match between simulated and observed quantities (tephra loads and volcanic cloud position), especially when accurate information on eruptive conditions (column height and duration) are supplied by the VONAs. Finally, through a statistical analysis, we found that column height and wind field are fundamental in determining tephra ground accumulation. For this reason, these parameters should be constrained by observational data as accurately as possible when performing numerical simulations, especially in the line of developing operational workflows.

We describe a method for calculating the probability that a distal geographic location is impacted by a pyroclastic density current (PDC) of a given size, considering the key related uncertainties. Specifically, we evaluate the minimum volume and mass of a PDC generated at the Aso caldera (Japan) that might affect each of five distal infrastructure (marker) sites, with model input parameter uncertainties derived from expert judgment. The 5 marker sites are all located 115–145 km from the caldera; as these lie in well-separated directions, we can test the effects of the different topographic shielding effects in each case. To inform our probabilistic analysis, we apply alternative kinetic energy assessment approaches, i.e., rock avalanche and density current dynamics. In the latter formulation, the minimum mass needed to reach the markers ranges between median values of ∼153×1012 and ∼465×1012 kg (M 7.2–7.7), depending on the site. Rock avalanche dynamics modeling indicates that a ∼3-times greater mass would be required to reach the marker sites with 50 % probability, while the hypothetical scenario of a relatively dilute distal ash cloud would require ∼3-times less mass. We compare our results with the largest recorded Aso eruption, showing that a catastrophic eruption, similar to Aso-4, ≈ M8, would present a significant conditional probability of PDCs reaching the marker sites, in the density current formulation and contingent on uncertainty in the erupted mass and on marker site direction.

Sangay volcano (Ecuador) shows a quasi-continuous activity at least since the seventeenth century and has produced several eruptions which affected towns and cities at considerable distance (up to > 170 km). For this reason, despite its remote location, recent efforts were aimed at reviewing its volcanic history, quantifying the occurrence probability of four eruptive scenarios of different magnitude (Strong Ash Venting, Violent Strombolian, sub-Plinian, and Plinian) and the associated uncertainty, and, for each eruptive scenario, estimating the probability distribution of key eruptive source parameters (fallout volume, average plume height, and eruption duration). In this study, we utilize such information to produce probabilistic hazard maps and curves. To this aim, we use coupled plume and dispersal models (PLUME-MOM-TSM and HYSPLIT, respectively) with the application of a novel workflow for running an ensemble of thousands of simulations following a stochastic sampling of input parameters. We produced probabilistic hazard maps for each scenario by considering four ground load thresholds (i.e., 0.1, 1, 10, and 100 kg/m 2 ) and two types of model initialization strategies, based on the elicited total deposit volume and on the elicited plume height, respectively, which produced non-negligible differences. In addition, we produced hazard curves for nine sites of interest from a risk perspective, corresponding to towns/cities potentially affected by tephra accumulation. Finally, we also derived combined maps by merging maps of single scenarios with their probability of occurrence as obtained from expert elicitation. Results indicate that in case of a future eruption, even for a moderate-scale one (Violent Strombolian), probability of tephra accumulation larger than 1 kg/m 2 is relatively high (from 21 to 24% considering different model initializations) in the town of Guamote, i.e., the most severely affected site among those tested (43 km W of Sangay). For larger-scale events (i.e., sub-Plinian), the impact of tephra accumulation results to be significant even for the city of Guayaquil (176 km W of Sangay), with probability of tephra accumulation larger than 1 kg/m 2 from 3 to 22% considering different model initializations. For maps combining single maps of historically observed scenarios, the probability (% - [5 th -Mean-95 th ]) of having ≥ 10 kg/m 2 for Guamote is [4-13-25] as maximum values.