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Volcanic eruptions pose a major natural hazard influencing the environment, climate and human beings at different temporal and spatial scales. Nevertheless, several volcanoes worldwide are poorly monitored and assessing the impact of their eruptions remains, in some cases, challenging. Nowadays, different numerical dispersion models are largely employed in order to evaluate the potential effects of volcanic plume dispersion due to the transport of ash and gases. On 28 August 2019, both Mt. Etna and Stromboli had eruptive activity; Mt. Etna was characterised by mild-Strombolian activity at summit craters, while at Stromboli volcano, a paroxysmal event occurred, which interrupted the ordinary typical-steady Strombolian activity. Here, we explore the spatial dispersion of volcanic sulphur dioxide (SO2) gas plumes in the atmosphere, at both volcanoes, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) considering the ground-measured SO2 amounts and the plume-height as time-variable eruptive source parameters. The performance of WRF-Chem was assessed by cross-correlating the simulated SO2 dispersion maps with data retrieved by TROPOMI and OMI sensors. The results show a feasible agreement between the modelled dispersion maps and TROPOMI satellite for both volcanoes, with spatial pattern retrievals and a total mass of dispersed SO2 of the same order of magnitude. Predicted total SO2 mass for Stromboli might be underestimated due to the inhibition from ground to resolve the sin-eruptive SO2 emission due to the extreme ash-rich volcanic plume released during the paroxysm. This study demonstrates the feasibility of a WRF-Chem model with time-variable ESPs in simultaneously reproducing two eruptive plumes with different SO2 emission and their dispersion into the atmosphere. The operational implementation of this method could represent effective support for the assessment of local-to-regional air quality and flight security and, in case of particularly intense events, also on a global scale.

Volcanic emissions (ash, gas, aerosols) dispersed in the atmosphere during explosive eruptions generate hazards affecting aviation, human health, air quality, and the environment. We document for the first time the contamination of airspace by very fine volcanic ash due to sequences of transient ash plumes from Mount Etna. The atmospheric dispersal of sub-10 μm (PM10) ash is modelled using the WRF-Chem model, coupled online with meteorology and aerosols and offline with mass eruption rates (MERs) derived from near-vent Doppler radar measurements and inferred plume altitudes. We analyze two sequences of paroxysms with widely varied volcanological conditions and contrasted meteorological synoptic patterns in October–December 2013 and on 3–5 December 2015. We analyze the PM10 ash dispersal simulation maps in terms of time-averaged columnar ash density, concentration at specified flight levels averaged over the entire sequence interval, and daily average concentration during selected paroxysm days at these flight levels. The very fine ash from such eruption sequences is shown to easily contaminate the airspace around the volcano within a radius of about 1000 km in a matter of a few days. Synoptic patterns with relatively weak tropospheric currents lead to the accumulation of PM10 ash at a regional scale all around Etna. In this context, closely interspersed paroxysms tend to accumulate very fine ash more diffusively at a lower troposphere and in stretched ash clouds higher up in the troposphere. Low-pressure, high-winds weather systems tend to stretch ash clouds into ~100 km wide clouds, forming large-scale vortices 800–1600 km in diameter. Daily average PM10 ash concentrations commonly exceed the aviation hazard threshold, up to 1000 km downwind from the volcano and up to the upper troposphere for intense paroxysms. Vertical distributions show ash cloud thicknesses in the range 0.7–3 km, and PM10 sometimes stagnates at ground level, which represent a potential health hazard.

During the autumn season, Sicily is often affected by severe weather events, such as self-healing storms called V-shaped storms. These phenomena cause significant total rainfall quantities in short time intervals in localized spatial areas. In this framework, this study analyzes the meteorological event recorded on 11–12 November 2019 in Sicily (southern Italy), using the Weather Research and Forecasting (WRF) model with a horizontal spatial grid resolution of 3 km. It is important to note that, in this event, the most significant rainfall accumulations were recorded in eastern Sicily. In particular, the weather station of Linguaglossa North Etna (Catania) recorded a total rainfall of 293.6 mm. The precipitation forecasting provided by the WRF model simulation has been compared with the data recorded by the meteorological stations located in Sicily. In addition, a further simulation was carried out using the Four-Dimensional Data Assimilation (FDDA) technique to improve the model capability in the event reproduction. In this regard, in order to evaluate which approach provides the best performance (with or without FDDA), the Root Mean Square Error (RMSE) and dichotomous indexes (Accuracy, Threat Score, BIAS, Probability of Detection, and False Alarm Rate) were calculated.

One of the most important challenges in atmospheric science and, in particular, in numerical weather predictions (NWP), is to forecast extreme weather events. These events affect very localized areas in space, recording high pluviometric accumulations in short time intervals. In this context, with the present study, we aim to analyze the extreme meteorological event that occurred in the northwestern and eastern parts of Sicily on 15 July 2020, by using the weather research and forecasting (WRF) model. In particular, during the afternoon, several storms affected those areas, causing intense precipitation, with maximum rainfall concentrated on the city of Palermo and in the Etna area. The rainfall at the end of the event reached 134 mm in Palermo and 49 mm in Catania, recorded by the Sicilian network meteorological stations. Because the event at Palermo was strongly localized, the analyses have been carried out by employing different sets of numerical simulations, by means of the WRF model, with horizontal spatial grid resolutions of 9, 3, and 1 km. Furthermore, the output of the performed simulation has been used to assess the thermodynamic profile and atmospheric instability indices. It allowed us to check the adopted parameters against those usually implemented in the flash flood scenario. By using the finest grid resolutions (3 and 1 km), the WRF model was able to provide more accurate predictions of the rainfall accumulation, even if they were strongly localized. Conversely, the implementation of less-refined spatial domain (9 km) did not allow us to obtain predictive estimates of precipitation.

The aim of this paper is to verify the applicability of the Rayleigh-Lamb equation to drops having different diameters and, specifically, with diameters of the order of magnitude of centimeters (macro drops), millimeters or micrometers (micro drops). On this purpose three experiments have been taken into account. A completely new fact is constituted by the following question: it is possible to apply the Rayleigh-Lamb equation to a heterogeneous drop like that represented by a soap bubble, characterized by a surface tension different from the substance constituting the drop's mass (air)? The results reported in this paper seem to confirm that this is possible. The order of magnitude of the calculated autofrequencies is comparable to that observed experimentally. The limitations of the experiments are the geometry of the system. The Rayleigh-Lamb equation applies, strictly speaking, to a free drop not subjected to the action of external forces. This would be possible through the use of special devices, i.e. the Acoustical Levitated. Therefore, it was decided to carry out the experiments with drops bound by viscous adhesion to the respective supports. It is evident that the geometry of the drop is no longer perfectly spherical, however the results obtained do not seem to have suffered greatly from this limitation.

A didactic multiscale approach for drone modeling is proposed. Specifically, we investigate the drone structure at both macroscopic and microscopic scales, by making use of finite element and atomistic simulations, respectively. The structural analysis is performed with the aim to equip the drone with specific sensors and measuring instruments capable to detect the existence of volcanic ash, SO_2, CO_2 and other pollutants in the atmosphere after a vulcanic eruption. We show that, by modeling the tubular structure of the drone with a sandwich constituted by a a polystyrene core, carbon fiber skins and epoxy matrix, a weight saving of 7 grams for each drone arm can be obtained, in comparison to the standard commercial drones, although a slight worsening of the mechanical performances is observed. In addition, the molecular structure of the polystyrene chains has been investigated by using atomistic Molecular Dynamics simulations, providing further information on the local structure of the polymer chains. Additional improvements of the weight saving could be obtained by means of the the topological optimization techniques on the body of the drone and on the supports for landing.

We propose a didactic approach to use the Machine Learning protocol in order to perform weather forecast. This study is motivated by the possibility to apply this method to predict weather conditions in proximity of the Etna and Stromboli volcanic areas, located in Sicily (south Italy). Here the complex orography may significantly influence the weather conditions due to Stau and Foehn effects, with possible impact on the air traffic of the nearby Catania and Reggio Calabria airports. We first introduce a simple thermodynamic approach, suited to provide information on temperature and pressure when the Stau and Foehn effects take place. Then, in order to gain information also on the rainfall accumulation, the Machine Learning approach is presented: according to this protocol, the model is able to "learn'' from a set of input data constituted by the meteorological conditions (in our case dry, light rain, moderate rain and heavy rain) associated to the rainfall, measured in mm. We observe that, since in the input dataset provided by the Salina weather station the dry condition was the most common, the algorithm is very accurate in predicting it. Further improvements can be obtained by increasing the number of considered weather stations and the time interval.

The purpose of the present paper is to investigate the effects of variable eruption source parameters on volcanic plume transport in the Mediterranean basin after the paroxysm of Mount Etna on 23 November 2013. This paroxysm was characterized by a north-east transport of ash and gas, caused by a low-pressure system in northern Italy. It is evaluated here in a joint approach considering the WRF-Chem model configured with eruption source parameters (ESPs) obtained elaborating the raw data from the VOLDORAD-2B (V2B) Doppler radar system. This allows the inclusion of the transient and fluctuating nature of the volcanic emissions to accurately model the atmospheric dispersion of ash and gas. Two model configurations were considered: the first with the climax values for the ESP and the second with the time-varying ESP according to the time profiles of the mass eruption rate recorded by the V2B radar. It is demonstrated that the second configuration produces a considerably better comparison with satellite retrievals from different sensors platforms (Ozone Mapping and Profiler Suite, Meteosat Second-Generation Spinning Enhanced Visible and Infrared Imager, and Visible Infrared Imaging Radiometer Suite). In the context of volcanic ash transport dispersion modeling, our results indicate the need for (i) the use of time-varying ESP, and (ii) a joint approach between an online coupled chemical transport model like WRF-Chem and direct near-source measurements, such as those carried out by the V2B Doppler radar system.

Optimizing the physical parametrizations of the Weather Research and Forecasting (WRF) model is one of the most challenging and complex tasks. In fact, it is not a simple operation to optimize the performance of a meteorological model capable of forecasting meteorological events, even extreme ones, in complex orographic areas such as that of Sicily. In this reference framework, the research activity of the group of meteorology and environmental modeling, established at the Department of Mathematics and Computer Sciences, Physical Sciences and Earth Sciences (MIFT) of the University of Messina, focuses on the development of a physical-mathematical model for the meteorological forecast. The WRF prediction model is evaluated on the ability to predict the development and evolution of a thunderstorm cell. After the definition of the domain under study and the choice of spatial resolution to be used, it was proceeded to the optimization of the physical parametrizations. In particular, in this paper, the performance improvements of the WRF model were evaluated, obtained by optimizing the convective parametrizations. As a case study, the meteorological event recorded in Sicily on 9 June 2016 was examined.

Numerical weather predictions (NWP) play a fundamental role in air quality management. The transport and deposition of all the pollutants (natural and/or anthropogenic) present in the atmosphere are strongly influenced by meteorological conditions such as, for example, precipitation and winds. Furthermore, the presence of particulate matter in the atmosphere favors the physical processes of nucleation of the hydrometeors, thus increasing the risk of even extreme weather events. In this framework of reference, the present work aimed to improve the quality of weather forecasts related to extreme events through the optimization of the weather research and forecasting (WRF) model. For this purpose, the simulation results obtained using the WRF model, where physical parametrizations of the cumulus scheme can be optimized, are reported. As a case study, we considered the extreme meteorological event recorded on 25 November 2016, which affected the whole territory of Sicily and, in particular, the area of Sciacca (Agrigento). In order, to evaluate the performance of the proposed approach, we compared the WRF model outputs with data obtained by a network of radar and weather stations. The comparison was performed through statistical methods on the basis of a “contingency table”, which allowed for ascertaining the best suited physical parametrizations able to reproduce this event.

The aim of the present work is to utilize a new functionality within the Weather Research and Forecasting model coupled with Chemistry (WRF–Chem) that allows simulating emission, transport, and settling of pollutants released during the Etna 2015 volcanic activities. This study constitutes the first systematic application of the WRF–Chem online-based approach to a specific Etna volcanic eruption, with possible effects involving the whole Mediterranean area. In this context, the attention has been focused on the eruption event, recorded from 3–7 December 2015, which led to the closure of the nearby Catania International Airport. Quantitative meteorological forecasts, analyses of Etna volcanic ash transport, and estimates of the ash ground deposition have been performed. In order to test the performance of the proposed approach, the model outputs have been compared with data provided by satellite sensors and Doppler radars. As a result, it emerges that, as far as the selected eruption event is concerned, the WRF–Chem model reasonably reproduces the distribution of SO2 and of volcanic ash. In addition, this modeling system may provide valuable support both to airport management and to local stakeholders including public administrations.

The development of numerical models for meteorological analysis is often based on nonlinear equations systems describing complex fluids, having more components and for which generalized Navier-Stokes equations are used. In several real cases it is necessary to use numerical calculation approaches in which the equations are discretized. The aim of this contribution is working out results regarding the optimization of the performance of a mathematical-physical model, formulated for meteorology forecasts in limited and high resolution area, and obtained by interdisciplinary studies. In particular, in order to test the validity of the presented model, different microphysical parameterizations have been analyzed, every one taking into account different hydrometeor nucleation processes.