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In this dataset we provide data for 6 experimental models of caldera collapse and subsequent resurgence monitored through geophysical sensors (a force or “impact sensor”, Piezotronics PCB 104 200B02 and a Triaxial piezoelectric accelerometer, Model 356B18). The analogue modelling experiments were carried out at the TOOLab (Tectonic Modelling Laboratory), which is a joint laboratory between the Istituto di Geoscienze e Georisorse of the Consiglio Nazionale delle Ricerche, Italy and the Department of Earth Sciences of the University of Florence. The laboratory work that produced these data was partly supported by the European Plate Observing System (EPOS), by the Joint Research Unit (JRU) EPOS Italia and by the “Monitoring Earth's Evolution and Tectonics” (MEET) project (NextGenerationEU). Specifically, this work was performed in the frame of the DynamiCal project, funded by the 2° TNA-NOA call of the ILGE-MEET project.
BayStress4 is a package of MatLab routine, designed to constrain the state of stress of a volcanic system by means of posterior Probability Density Functions (PDFs) of the stress tensor components. To do so, it employs the model of three-dimensional (3D) dyke pathways developed by Mantiloni et al., 2023 (SAM: Simplified Analytical Model of dyke Pathways in Three Dimensions) to match the known locations of past eruptive vents to the known or assumed volume in the subsurface ("Dyke nucleation zone" or "D") where their parent dykes nucleated from. This is achieved by a) using SAM to backtrack dyke pathways from the vents down through the crust for a given stress model; b) quantifying the intersection between such pathways and D through a misfit function; c) using this procedure to run a Markov Chain Monte Carlo (MCMC) algorithm to sample the stress parameters' space. The posterior information provided by the stress inversions can then be used to produce forward simulations of dyke pathways with SAM and forecast the surface distribution of future eruptive vents across the volcanic system. This repository contains InVent4Cast, a package of MatLab routines designed to constrain the state of stress of a volcanic system by means of posterior Probability Density Functions (PDFs) of the stress tensor components. To do so, it employs the model of three-dimensional (3D) dyke pathways developed by Mantiloni et al., 2023a (SAM: Simplified Analytical Model of dyke Pathways in Three Dimensions) to match the known locations of past eruptive vents to the known or assumed volume in the subsurface ("Dyke nucleation zone" or "D") where their parent dykes nucleated from. This is achieved by a) using SAM to backtrack dyke pathways from the vents down through the crust for a given stress model; b) quantifying the intersection between such pathways and D through a misfit function; c) using this procedure to run a Markov Chain Monte Carlo (MCMC) algorithm to sample the stress parameters' space. The posterior information provided by the stress inversions can then be used to produce forward simulations of dyke pathways with SAM and forecast the surface distribution of future eruptive vents across the volcanic system. The repository also collects data, figures and results of the application of InVent4Cast to some of the synthetic scenarios of dyke pathways in calderas presented by Mantiloni et al., 2023a. These results were detailed and discussed by Mantiloni et al., 2024a, to which the reader is referred for further information. The synthetic scenarios include numerical models of crustal stress state, focusing on gravitational loading/unloading due to topography and tectonic processes as the dominant stress sources. These stress sources are accounted for by a set of stress parameters. Results include posterior probability density functions (PDFs) of such stress parameters after applying the stress inversion to the scenarios, as well as probability maps of eruptive vent opening across the synthetic volcanic areas. Synthetic scenarios, stress inversions and vent forecasts were produced between May 2022 and November 2023.
Here we present data on the spatiotemporal distribution of seismicity and CO2 flux from the highly active Svartsengi–Eldvörp volcanic system (hereafter referred to as Svartsengi) on the Reykjanes Peninsula. Data were collected between July and September 2024. The area is marked by repeated fissure eruptions associated with rapid magma propagation since November 2023. The eruptions are part of an ongoing volcanic sequence with intermittent pauses. The seismic and gas flux datasets support the idea, that multidisciplinary approaches are important for the identification of potential eruption sites and an improved hazard assessment in volcanic areas.
This dataset comprises 3D X-ray computed tomography (XCT) scans of eight rock cores (15 mm diameter) prepared from two gabbroic nodules collected at Gígöldur, Central Iceland. The scans are provided in the Tagged Image File Format (*.tif). Data were acquired using a Carl Zeiss Xradia Versa-410 3D X-ray microscope at the Istituto Nazionale di Geofisica e Vulcanologia – Sezione di Napoli, Osservatorio Vesuviano (INGV-OV), Italy. Data collection was carried out under Trans-National Access support through EXCITE (EC H2020 INFRAIA, grant agreement No. 101005611).
The Geldingadalir 2021 eruption in Iceland started on 19 March and ended on 18 September. It featured nearly 9000 lava fountain episodes of minute to day duration that were all accompanied by seismic tremor. We measured the duration, repose time, tremor amplitude and shape using seismometers from the University of Potsdam. We publish the corresponding catalogs that contain information about these episodes. Periodically, aerial surveys were conducted by the University of Iceland using unoccupied aerial systems (UAS). These surveys lead to digital surface models (DSM), orthomosaics, and 3D models. These products were used to supplement the seismic observations.
This data publication provides data from 39 experiments performed in 2021 to 2022 in the Gas-mixing lab at the Ludwig Maximilian University of Munich (Germany). The experiments were conducted to investigate the charging and discharging potential of decompressed soda-lime glass beads in varying enveloping gas composition and two different transporting gas species (argon and nitrogen). The experimental setup is a modified version of an apparatus first developed by Alidibirov and Dingwell (1996) and further modified by Cimarelli et al. (2014), Gaudin and Cimarelli (2019), and Stern et al. (2019) to enable the detection and quantification of discharges caused by the interaction of the discharging particles. The latest modifications enable the setup to perform experiments under gas-tight conditions allowing to test different atmospheric composition and pressure and to sample the gas within the particle collector tank. The sample material was ejected from the autoclave into the particle collector tank that is insulated from the autoclave and works as a Faraday cage. Discharges going from the jet to the nozzle were recorded by a datalogger. Additionally, the ejection of the decompressed material was recorded by a high-speed camera. The gas composition in the collector tank was changed from air to CO2 and a mixture of CO2 and CO. The particle collector tank was conditioned in two different modes: purging three times the tank with the desired gas composition or three times of purging and applying a vacuum in between. Analysis of gas samples taken from the collector tank before conducting the experiments revealed that in both cases a complete removal of the air was not achieved, but significantly reduced by the evacuation-purging method. Two gases were used to pressurize the sample within the autoclave: Nitrogen and Argon. The experimental results were compared to previous experiments (Springsklee et al., 2022a; Springsklee et al., 2022b).
These data files contain short periods of electrical data recorded at Stromboli volcano, Italy, in 2019 and 2020 using a prototype version of the Biral Thunderstorm Detector BTD-200. This sensor consists of two antennas, the primary and secondary antenna, which detect slow variations in the electrostatic field resulting from charge neutralisation due to electrical discharges. The sensor recorded at three different locations: BTD1 (38.79551°N, 15.21518°E), BTD2 (38.80738°N, 15.21355°E) and BTD3 (38.79668°N, 15.21622°E). Electrical data of the following explosions is provided (each in a separate data file): - Three Strombolian explosions on 12 June 2019 at 12:46:53, 12:49:27 and 12:56:10 UTC, respectively. - A major explosion on 25 June 2019 at 23:03:08 UTC. - A major explosion on 19 July 2020 at 03:00:42 UTC. - A major explosion on 16 November 2020 at 09:17:45 UTC. - A paroxysmal event at 3 July 2019 at 14:45:43 UTC. Each filename indicates the location of the BTD, the starting date and time of the file in UTC, and a short description of the three data columns inside the file (unixtime, primary, secondary). The first column provides the Unix timestamp of each data point, which is the time in seconds since 01/01/1970. All time is provided in UTC. The second column provides the measured voltage [V] recorded by the primary antenna. The third column provides the measured voltage [V] recorded by the secondary antenna.
This data publication provides data from 13 experiments performed in 2022 in the Gas-mixing lab at the Ludwig Maximilian University of Munich (Germany). The experiments were conducted to investigate the charging and discharging potential of material collected from a mud volcano from the Salton Sea (GPS-Data 33°12'2.7"N 115°34'41.4"W). The sample material was used in decompression experiments. The material was pressurized with argon gas instead of methane to assure safety conditions while running the experiments in the laboratory. The experimental setup is a modified version first developed by Alidibirov and Dingwell (1996) and further modified by Cimarelli et al. (2014); Gaudin and Cimarelli (2019); Stern et al. (2019) to enable the detection and quantification of discharges caused by the interaction of the discharging particles. The material was ejected from the autoclave into a Faraday cage, that is insulated from the autoclave and discharges going from the jet to the nozzle were recorded by a datalogger. Additionally, the eruption of the decompressed material was recorded by a high-speed camera. In the experiments, the influence of humidity and grain size distribution were tested. The influence of humidity was tested by using the material as wet as collected but also dried and milled and later exposed to varying but controlled humidity conditions. The grain size distribution was tested by mixing the dried and milled mud sample with 10, 50 and 90% of sea sand.
This data publication provides data from 96 experiments from 2020 to 2022 in the gas-mixing lab at the Ludwig-Maximilians-Universität München (Germany). The experiments were conducted to investigate the influence of grain size distribution, especially the influence of very fines [<10 µm] on the generation of experimental volcanic lightning (VL). The influence of grain size distribution was tested for three different materials. Experimental discharges during rapid decompression were evaluated by their number and their total magnitude. The three materials used in this study are a tholeiitic basalt (TB), industrial manufactured soda-lime glass beads (GB) and a phonolitic pumice from the lower Laacher See unit (LSB). The samples were sieved into several grain size fractions, and coarse and fines were mixed to test the influence of the added fines on the discharge behaviour. For the tholeiitic basalt, the coarse grain size fraction is 180-250 µm, for the glass beads 150-250 µm and for the phonolitic pumice, two coarse grain size fractions, 180-250 µm and 90-300 µm were tested. The experiments were carried out in a new experimental setup, a modification of the shock tube experiments first described by Alidibirov and Dingwell (1996) and its further modifications (Cimarelli et al., 2014; Gaudin & Cimarelli, 2019; Stern et al., 2019). A mixture of coarse and fine sample material is placed into an autoclave and continuously set under pressure with argon gas up to the desired decompression pressure (⁓10 MPa). Then, rapid decompression is initialized, and the sample material is ejected from the autoclave through a nozzle into a gas-tight particle collector tank. The particle collector tank is insulated from the nozzle and the ground and serves as a Faraday cage (FC). All discharges going from the erupting gas-particle mixture, the jet, to the nozzle will be recorded by a datalogger. All the discharges measured during the first 5 ms of ejection were taken into the evaluation of the discharge behaviour. The raw signals of the experiments were evaluated by a processing code developed by Gaudin and Cimarelli (2019). Additionally, the jet behaviour was recorded by a high-speed camera: the gas-exit angle and the exit angle of the gas-particle mixture were determined. The background of the high-speed video was divided into a black side and a white side. The gas-exit angle and the exit angle gas-particle-mixture were determined as the mean of the deviation angle of a straight trajectory angle of both sides.
Active volcanoes frequently show substantial topographic changes and variable eruption intensity, style and/or directionality. Here we provide high-resolution photogrammetric data sets of Stromboli’s crater terrace collected during 5 field campaigns between May 2019 and January 2020 supporting the publication Schmid, M, Kueppers U, Ricci T, Taddeucci J, Civico R and Dingwell DB (2021) “Characterizing Vent and Crater Shape Changes at Stromboli: Implications for Risk Areas”. The aerial imagery for the photogrammetric reconstruction of the crater terrace geometry was acquired by UAVs (DJI Phantom 4Pro+ & Mavic 2 Pro) and processed with the commercial software Metashape by Agisoft. The created digital elevation models (DEMs), orthomosaics and 3D models were used to characterize vent and crater shape and their changes through time. The activity during the observational period was characterized by elevated Strombolian activity and two paroxysms on 3 July and 28 August 2019. Our study revealed significant changes to crater terrace morphology and vent geometry on various time scales and the strong control of vent geometry on the directionality of explosions.
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