Radiosondaggi atmosferici nell’area etnea

RADIOSONDAGGI ATMOSFERICI NELL’AREA ETNE

A lab-scale experiment to measure terminal velocity of volcanic ash

In this paper, a novel methodology to measure trajectory and terminal velocity of volcanic ash in laboratory is presented. The methodology consists of: i) planning a lab-scale experiment in order to reproduce the sedimentation processes of fine volcanic ash based on the principle of dynamic similarity; ii) realizing the experimental set-up using a glass tank filled with glycerine, a web-cam based vision system and a dedicated image post processing tool able to estimate the position and the terminal velocity of any particle falling in the tank; iii) performing a calibration procedure to accurately estimate the uncertainty on particle velocity; iv) comparing the experimental results with estimations obtained by some particle fallout models available in literature. Our results shows that there is a good agreement between experimental terminal velocities and those obtained applying a model which includes information on particle shape. The proposed methodology allows us to investigate how the particle shape affects the sedimentation processes. Since the latter is strategic to improve the accuracy on modeling ash fallout, this work will contribute to reduce risks to aviations during explosive eruptions

NASA WEBWORLDWIND: MULTIDIMENSIONAL VIRTUAL GLOBE FOR GEO BIG DATA VISUALIZATION

In this paper, we presented a web application created using the NASA WebWorldWind framework. The application is capable of visualizing n-dimensional data using a Voxel model. In this case study, we handled social media data and Call Detailed Records (CDR) of telecommunication networks. These were retrieved from the "BigData Challenge 2015" of Telecom Italia. We focused on the visualization process for a suitable way to show this geo-data in a 3D environment, incorporating more than three dimensions. This engenders an interactive way to browse the data in their real context and understand them quickly. Users will be able to handle several varieties of data, import their dataset using a particular data structure, and then mash them up in the WebWorldWind virtual globe. A broad range of public use this tool for diverse purposes is possible, without much experience in the field, thanks to the intuitive user-interface of this web app

Video monitoring of the persistent strombolian activity of Stromboli volcano represents a window on its plumbing system and an opportunity for understanding the eruptive processes

Since 1994 a video-surveillance camera located on a peak just above the active volcanic vents of Stromboli island records the explosive activity of one of the few volcanoes on the world performing a persistent eruptive activity. From 2003, after one of the larger lava flow eruption of the last century, the video- surveillance system was enhanced with more stations having both thermal and visual cameras. The video-surveillance helps volcanologists to characterize the mild explosive activity of Stromboli named Strombolian and to distinguish between the frequent “ordinary” Strombolian explosions and the occasional “extraordinary” strong Strombolian explosions that periodically occur. A new class of extraordinary explosions was discovered filling the gap between the ordinary activity and the strong explosions named major explosions when the tephra fallout covers large areas on the volcano summit and paroxysmal ones when the bombs fall down to the inhabited area along the coast of the island. In order to quantify the trend of the ordinary Strombolian explosions and to understand the occurring of the extraordinary strong Strombolian explosions a computer assisted image analysis was developed to process the huge amount of thermal and visual images recorded in several years. The results of this complex analysis allow us to clarify the processes occurring in the upper plumbing system where the pockets/trains of bubbles coalesce and move into the active vent conduits producing the ordinary Strombolian activity, and to infer the process into the deeper part of the plumbing system where new magma supply and its evolution lead to the formation of the extraordinary strong Strombolian explosions

Monitoring and forecasting Etna volcanic plumes

In this paper we describe the results of a project ongoing at the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The objective is to develop and implement a system for monitoring and forecasting volcanic plumes of Etna. Monitoring is based at present by multispectral infrared measurements from the Spin Enhanced Visible and Infrared Imager on board the Meteosat Second Generation geosynchronous satellite, visual and thermal cameras, and three radar disdrometers able to detect ash dispersal and fallout. Forecasting is performed by using automatic procedures for: i) downloading weather forecast data from meteorological mesoscale models; ii) running models of tephra dispersal, iii) plotting hazard maps of volcanic ash dispersal and deposition for certain scenarios and, iv) publishing the results on a web-site dedicated to the Italian Civil Protection. Simulations are based on eruptive scenarios obtained by analysing field data collected after the end of recent Etna eruptions. Forecasting is, hence, supported by plume observations carried out by the monitoring system. The system was tested on some explosive events occurred during 2006 and 2007 successfully. The potentiality use of monitoring and forecasting Etna volcanic plumes, in a way to prevent threats to aviation from volcanic ash, is finally discussed

A Statistical Approach to Evaluate the Tephra Deposit and Ash Concentration from Puff Model Forecasts

In this paper we present a new statistical approach able to provide tephra deposit load and ash concentration using PUFF, a lagrangian model widely used to forecast volcanic ash dispersal during volcanic crisis. We perform a parametric study in order to analyze the influence of each input parameter on model outputs. For this test, we simulate two eruptive scenarios like to the 2001 (Scenario 1) and 1998 (Scenario 2) Etna eruptions using high resolution weather data and a domain of 170 x 170 km. Results show that for both scenarios, we are able to calculate the tephra deposit load and ash concentration but the use of millions of particles is required. Specifically, up to 33 and 220 millions of particles were necessary to accurately predict the tephra deposit and ash concentration in air, respectively. This is approximately two orders of magnitude larger than values typically considered running PUFF. The parametric study shows that the horizontal diffusion coefficient, the time step of the simulations, the topography and the standard deviation of the particle distribution greatly affect the model outputs. We also validate the model by best fit procedures. Results show a good comparison between field data of the 2001 Etna eruption and PUFF simulations, being inside 5 and 1/5 times the observed data, comparable with results of Eulerian models. This work will allow to reliably outlining the areas of contaminated airspace using PUFF or any other lagrangian model in order to define the No Fly Zone and ensure the safety to aviation operations as required after the Eyjafjallajökull eruption

A Dynamic Bayesian Network for Mt. Etna Volcano State Assessment

Nowadays, the real-time monitoring of Mt. Etna volcano is mostly delegated to one or more human experts in volcanology, who interpret the data coming from different kind of monitoring networks. Among their duties, the evaluation of the volcano state is one of the most critical task for civil protection purposes. Unfortunately, the coupling of highly non-linear and complex volcanic dynamic processes leads to measurable effects that can show a large variety of different behaviors. Moreover, due to intrinsic uncertainties and possible failures in some recorded data the volcano state needs to be expressed in probabilistic terms, thus making the fast volcano state assessment sometimes impracticable for the personnel on duty at the 24h control room. With the aim of aiding the personnel on duty in volcano monitoring, here we present an expert system approach based on Bayesian networks to estimate automatically the ongoing volcano state from all the available different kind of measurements. A Bayesian network is a static probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph. We consider model variables both the measurements and the possible states of the volcano. In order to include the time in the model, we use a Dynamic Bayesian Network (DBN) which relates variables to each other over adjacent time steps. The model output consists of an estimation of the probability distribution of the feasible volcano states. We build the model by considering the long record of data from 2011 to 2014 and we cross-validate it by considering 3 years for parameter estimation and 1 year for testing in simulated real-time mode

Implementazione di una nuova procedura per caratterizzare la forma di particelle mediante misure al CAMSIZER e algoritmi di clustering

In this work we present the calibration phase of a new procedure for the characterization of the shape of pyroclastic particles. This research has been granted by INGV of Catania, with funds deriving from the “Progetto Giovani”, in collaboration with Retsch Technology in Haan. The innovation of this procedure arises from the use of CAMSIZER (an instrument developed by the German leader company). This instrument permits to obtain very important information both on size and shape parameters of a high number of particles (hundreds of thousands data). Moreover, we used clustering and classification algorithms in order to group particles according to their morphologic characteristics. This calibration phase has been tested only on standard materials with regular geometries such as cubes, spheres and cylinders. In the future we will apply this methodology to volcanic ash particles that, as well-known, are characterized by irregular morphologies