We don’t always have direct access to volcanoes especially those located in hostile and remote areas of our planet, such as Antarctica. Moreover, the knowledge of the Antarctic continent and its volcanoes is still limited by the scarce exposure of volcanic rocks due to the extensive glacial cover, since only 1% of the total area is ice-free. Pyroclastic deposits (i.e. tephra) represent a very effective and powerful tool for petrological and volcanological studies. Through the study and characterization of tephra we can get information about the evolution of magmas, including their physical, chemical and mineralogical characteristics. Additionally, we can get a new understanding of the architecture of volcanic plumbing systems, the nature and intensity of eruptions as well as the emplacement dynamics, their aerial transportation and their impacts on Earth. This work focuses on the characterization of tephra originating from three distinct volcanoes of the Northern Victoria Land, Mount Melbourne, Mount Rittmann and The Pleiades.

According to previous studies, the activity of Mount Melbourne can be dated back to approximately 1892 CE, this is also confirmed by the presence of several tephra layers in the summit and flanks of the volcano (Lyon, 1986). Evidence for explosive eruptions of Mount Melbourne volcano between 1615 cal. yrs BP and 1677 cal. yrs BP were recently acquired (Di Roberto et al. 2023). Also, Mount Rittmann erupted in historical time (696 ± 2 cal. yrs BP) and the presence of fumaroles and summit geothermal activity indicate that the volcano is still active. However, we still know very little about the volcanic history of this volcano. The Pleiades volcanoes instead show evidence of activity during the Holocene (Di Roberto et al. 2020).

Despite the abundance of rock samples collected in this area, there is still a scarcity of both geochemical and petrological data and studies.

We analysed 23 samples that have been collected over the last 30 years during Antarctic expeditions. The analyzed data will provide a more detailed understanding of past explosive volcanic activity including source, magnitude, intensity, chemical evolution and eruptive dynamics. Finally, this will also improve the correlation between proximal and distal tephra.

In addition, an extensive database containing major and trace elements is crucial for a precise geochemical characterization to provide invaluable insights to enhance our understanding of the Northern Victoria Land.

The comprehension of Antarctic volcanism is crucial not only to understand the eruptive dynamics and plumbing system but also to build new knowledge of the history of explosive volcanic activity through time and space. This understanding is critical in evaluating and defining potential impacts associated with future eruptions, which could potentially be affected by ice dynamics and ice load covering the volcanic structures, with wider implications for our planet.

Lyon, G.L., 1986. Doi: 10.1080/00288306.1986.10427528.

Di Roberto et al. 2020. Doi: 10.1016/j.quascirev.2020.106629

Di Roberto et l. 2023. Doi: 10.1016/j.qsa.2023.100079

How to cite: Fisauli, G., Petrelli, M., Di Roberto, A., and Re, G.: Proximal tephra characterization in Northern Victoria Land, Antarctica: Insights into eruptive history and future implications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3639, https://doi.org/10.5194/egusphere-egu24-3639, 2024.

How to cite: Romano, P., De Martino, P., Di Lieto, B., Mangiacapra, A., Petrillo, Z., and Sangianantoni, A.: FEM model of surface deformation pattern and a first application on real data at Campi Flegrei caldera, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18088, https://doi.org/10.5194/egusphere-egu24-18088, 2024.

Geo-electric exploration surveys such as Electrical Resistivity Tomography (ERT) can provide valuable insights regarding the characterization of geological structures and hydrothermal systems in volcanic environments. However, while ERT is a powerful tool, its effectiveness can be limited by the inherent sensitivity of rock electrical conductivity to various parameters. These can include factors such as water content, salinity of pore water, rock temperature, or alteration. Each of these factors significantly impacts the results of an ERT survey and, if not precisely characterized, can lead to inaccurate data interpretation. As a result, ERT is often supplemented by additional costly and time-consuming in-situ measurements, such as soil temperature or diffuse soil CO₂ degassing probing, to provide a more comprehensive analysis of subsurface conditions.

The purpose of this study is to summarize the recent geophysical findings from Revil et al. (2023), where they constructed the first 3D electrical conductivity model of the Stromboli volcano in the Aeolian Islands. To build this model, Revil et al. collected and analyzed data from various sources, including self-potential, soil temperature, soil CO₂ degassing, and thermal remote sensing maps. By comparing these complementary datasets, this study aims to highlight the benefits of using Thermal Remote Sensing as a supplementary tool to analyze data from subsurface geo-electric exploration. Thermal remote sensing constitutes a practical and cost-efficient approach, allowing for systematic monitoring of Earth’s surface thermal anomalies via infrared imaging down to a spatial resolution of 30 to 15 meters.  By applying corrections and isolating surface-emitted radiance from the integrated signature received by the satellite, the average temperature of the surface is retrieved for each pixel. Thermal anomalies on the volcano are then located, and their temperatures are accurately determined through dual-band processing, which involves comparing images from Thermal Infrared and Short-Wave Infrared spectra.

The maximum remotely recorded infrared temperature is 792°C, associated with the main active volcanic vents. Considering the extreme heterogeneity in surface temperature at the scale of the pixel as well as the presence of volcanic gases, uncertainties for the remotely acquired temperature are in the range of a few degrees centigrade. The soil temperature measurements near these vents, retrieved at a depth of 30 cm, also reveal significant internal activity with temperature values reaching 100°C (the readings were taken to a tenth of a degree). This high-temperature region perfectly matches the positive anomalies of self-potential and diffuse soil CO₂ degassing associated with the vertical conductive channel (1 to 10^-1 S/m).

In conclusion, the ability to isolate the temperature associated with the thermally active component makes this approach highly promising for accurately constraining the spatial distribution of the shallow hydrothermal system, as it is manifested at the surface by high-temperature areas. Therefore, thermal remote sensing appears very useful in refining the interpretation of subsurface geophysical images.

How to cite: Manara, F., Gresse, M., Revil, A., Finizola, A., and Ricci, T.: Enhancing Geo-electric Exploration using Thermal Remote Sensing and Dual Band Processing – Case Study of the Stromboli Volcano (Aeolian Islands), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3878, https://doi.org/10.5194/egusphere-egu24-3878, 2024.

Etna is a very active volcano with frequent eruptions and it is well controlled through different monitoring techniques. Continuous control of ground deformation is also provided by tilt measurements especially through a network of short-base borehole sensors. Since 1996 this network has been integrated with a long-base fluid tiltmeter installed in two 80 m long tunnels present at the high altitude (2,850 m a.s.l.) volcanological observatory of Pizzi Deneri (PDN) located on the summit area of the volcano. The instrumentation was created with an innovative configuration composed of mercury, free to move along the entire length of 80 m in response to the ground tilt, and laser sensors to measure the changes of the mercury level at the ends of the length where this fluid is positioned. In this study for the first time we present the entire set of 25 years of data (1997-2022) recorded by this instrumentation. During this long time interval, the Etna volcano was characterized by numerous main eruptions due to dyke intrusions. The tilt variations recorded in the short term during the rapid intrusive phases are presented and discussed. These signals contributed to the modeling of eruptive processes, and in particular in the case of the 2002-2003 eruption they contributed to the real-time understanding of the ongoing eruptive phenomenon, supporting the correct hazard assessment. In the medium-long term (years to decades) the signal maintained a trend that cumulated approximately 200 microrads on both components during the entire observation. PDN long term is primarily affected by the dynamics of the marked sliding of the entire eastern sector of the volcano.

How to cite: Gambino, S., Privitera, L., Bonaccorso, A., Falzone, G., Laudani, G., and Ferro, A.: 25 years recording of the long-base fluid tiltmeter installed at 2.850 m a.s.l. observatory on Etna volcano, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7370, https://doi.org/10.5194/egusphere-egu24-7370, 2024.

Volcanic activity generates diverse seismic and acoustic signals that offer valuable insights into the underlying magmatic processes. Contemporary volcano monitoring relies on networks and arrays of seismic and acoustic sensors. The analysis of signals acquired by these instruments necessitates streamlined workflows and specialized software. The high sampling rates, typically exceeding 50 Hz, employed in recording seismic and acoustic waveforms by multi-station networks and dense arrays result in the swift accumulation of substantial data volumes, posing a formidable challenge in establishing efficient data analysis workflows for volcano surveillance.
In this context, we introduce MISARA (Matlab Interface for Seismo-Acoustic aRray Analysis), an open-source MATLAB graphical user interface. MISARA is meticulously crafted to furnish a user-friendly workflow for analyzing seismo-acoustic data in volcanic settings. It incorporates efficient algorithmic implementations of established techniques for seismic and acoustic data analysis, with a focus on supporting the visualization, characterization, detection, and location of volcano seismo-acoustic signals. The intuitive and modular structure of MISARA facilitates swift, semi-automated data inspection and result interpretation, thereby minimizing user effort.
Validation of MISARA involved testing it with seismo-acoustic data recorded at Etna Volcano (Italy) during 2010, 2011, and 2019. The tool is intended for educational and research purposes and is well-suited to aid routine data analysis at volcano observatories. Its open-source nature encourages collaborative development and adaptation, fostering advancements in volcano monitoring and contributing to the broader scientific community.

How to cite: Minio, V., Zuccarello, L., De Angelis, S., Di Grazia, G., and Saccorotti, G.: Matlab Interface for Seismo‐Acoustic aRray Analysis (MISARA), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7541, https://doi.org/10.5194/egusphere-egu24-7541, 2024.

The eruption of Vesuvio in 1944 commenced on the 18th of March and concluded on the 29th, encompassing both eruptive and seismic activities. After that date the activity decreased and has continued with low intensity until April 7, when the eruption was declared over, the crater was completely obstructed and the closed conduit period of the volcano began, which has lasted until now. During the paroxysm, the volcano underwent four distinct phases: effusive, lava fountaining, mixed explosions, and explosive events. In the initial phase (from the 18th to the 21st), the resulting lava field attained a total volume of 10^6 m^3 and a length of 5.6 km, distributed across various flows. The recent acquisition of a digitized pre-eruption Digital Elevation Model (DEM) for the region facilitates a more accurate estimation of the thickness of the final lava field by comparing it to post-eruptive LIDAR DEM data. Utilizing VLAVA, a simulation code designed for modeling lava flow propagation over complex topography with temperature-dependent viscosity, accurate modeling of the effusive phase has been achieved. These simulations contribute to a better characterization of the 1944 Vesuvius lava flow emplacement and a deeper understanding of lava flow rates from multiple vents and the subsequent lava propagation dynamics.

How to cite: Macedonio, G., Cordrie, L., Costa, A., Giudicepietro, F., Obrizzo, F., Cubellis, E., and Bellucci Sessa, E.: Modelling the effusive phase of the 1944’s Vesuvio eruption using VLAVA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17223, https://doi.org/10.5194/egusphere-egu24-17223, 2024.

Automated early warning systems for volcanoes, capable of early recognition of any signs of impending eruption, as well as to track the evolution of different kinds of eruptive activity in near real time, are essential to assess the volcanic hazards and mitigate the associated risk. Satellite imagery offers a systematic, synoptic framework for monitoring active volcanoes in even the most isolated corners of the Earth. 

Here we have applied a machine learning technique to automatically classify a pixel in SEVIRI imagery over an active volcano, in order to detect and characterize its eruptive activity. In particular, we have discriminated against five main classes of pixels: clear sky, cloud-contaminated, ash-contaminated, SO2-contaminated and thermal anomalies.

Due to the enormous amount of data and the difficulty in labeling it, we have used self-supervised learning to study data acquired since 2004. We have selected an area of 5x5 pixels around the active volcano under study and followed the spectral radiance variation of each pixel in the twelve bands availables. 

Our technique has been applied to several active volcanoes within the SEVIRI disk, including Etna, Nyiragongo, Stromboli, Nabro, La Palma and Fogo.

How to cite: Spina, M., Bilotta, G., Cappello, A., Dozzo, M., Guardo, R., Spina, F., Zuccarello, F., and Ganci, G.: Volcanic activity classification trough Self-Supervised Learning applied to satellite radiance time series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8046, https://doi.org/10.5194/egusphere-egu24-8046, 2024.

Volcanic risks cannot be stopped or eliminated, but their effects can be minimized by applying new methods and providing data to support decision-making processes. Etna is one of the most active volcanoes in the world, producing both effusive and explosive eruptions, together with very intense seismic activity, which significantly influence the territory and society. The PANACEA project intends to address some issues that are still open in the modeling and integration of risks deriving from seismic and volcanic hazards, in order not to be caught unprepared and implement proactive risk reduction policies. In particular, the project has focused on the: (i) classification and statistical analysis of the historical eruptions of Etna; (ii) revision of the historical earthquake catalogue and the related database of macroseismic intensities; (iii) assessment of the long-term probability of vent opening based on historical eruptions and seismicity; (iv) extraction of the input parameters to run numerical simulations; (v) physics-based modeling of complex geophysical flows; (vi) probabilistic hazard mapping for single eruptive products, i.e. lava, tephra fallout and PDCs; (vii) probabilistic seismic hazard assessment; (viii) harmonization of the different hazards in a single long-term hazard map; (ix) analysis of the possible interactions at the hazard and the vulnerability levels, in order to quantitatively update hazard and risk estimations; (x) exposure and vulnerability assessment of elements at risk; (xi) multi-risk analysis by combining multi-hazards, exposure and vulnerability assessment. The results of PANACEA demonstrate that a better understanding of geophysical flow mechanisms, as well as improvements in knowledge in volcanic and seismic multi-hazard and multi-risk assessment, both in conceptual and technological terms, provide a powerful tool to develop effective and operational strategies, improving safety and reducing the impact of Etna's eruptive events.

How to cite: Cappello, A. and the PANACEA team: The PANACEA project: Probabilistic AssessmeNt of volCano-related multi-hazard and multi-risk at Mount EtnA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5354, https://doi.org/10.5194/egusphere-egu24-5354, 2024.

The THERESA project, which stands for THErmal infRarEd SBG Algorithms, seeks to improve algorithms for processing data obtained from the SBG-TIR (Surface Biology and Geology – Thermal InfraRed) mission. By leveraging the mission's technical features, THERESA aims to improve and adapt specific algorithms to study geological processes and develop new ones that could get advantages by using SBG-TIR spectral channels in the VIS and MIR-TIR range. Over the two-year duration of the project, THERESA will play a vital role in advancing the study of terrestrial phenomena also considering the high revisit time of SBG, which will be of 3 days worldwide over land.

SBG-TIR data will benefit diverse thematic areas, ranging from vegetation analysis to monitoring volcanic eruptions and fires. The project aims to derive several key parameters, including the estimation of ash and SO2 emissions from volcanoes, surface temperature, detection of hotspots, and the calculation of FRP (Fire Radiative Power) during High Temperature Events (HTEs). THERESA distinguishes itself through its innovative algorithmic advancements, providing comprehensive support to the SBG-TIR mission. Finally, suitable sites for CAL/VAL activities will be identified, and measurement campaigns will be conducted coinciding with the passages of currently operational TIR satellites for the validation of the algorithms under study.

How to cite: Silvestri, M., Buongiorno, M. F., and Romaniello, V.: THERESA project: a study to enhance algorithms for processing data from the SBG-TIR mission in volcanological field, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4989, https://doi.org/10.5194/egusphere-egu24-4989, 2024.

The evolution of cost-efficient Global Navigation Satellite System (GNSS) equipment sparked increasing scientific interest to use this technology for precise geophysical measurements. In this research, we investigate the use of cost-effective GNSS units for deformation monitoring on the island of Saba in the Caribbean Netherlands. Saba hosts Mt. Scenery, an active but quiescent stratovolcano in the Lesser Antilles Volcanic Arc. The most recent eruption of the 887 metres high volcano occurred around 1640.

In February 2022, four cost-effective GNSS units were installed on the island to densify the existing Royal Netherlands Meteorological Institute (KNMI) GNSS network of four permanent GNSS stations. While the equipment costs of a permanent GNSS station quickly exceeds 10.000 Euro, the cost-efficient units come at a price of about 1000 Euro. The cost-effective unit’s design includes all necessities for independent operation: Solar charger, microcontroller, cellular data transmission, as well as remote connection via the cellular 4G connection. Compared to permanent GNSS stations, the cost-effective unit’s installation time in the field is significantly reduced.

We present the GNSS unit’s design and first deformation monitoring results of the deployed stations. The data is validated by comparing data of a cost-effective unit with those from a permanent GNSS station next to it. The GNSS units are well suited to monitor ground deformation on Saba as their daily positioning precision is similar to those of permanent GNSS stations. The cost-efficient GNSS units can therefore be used i) to expand existing deformation monitoring networks, ii) in stand-alone areas where the installation of conventional GNSS is deemed too costly, or iii) in risk-prone areas where rapid installation of expendable equipment is necessary.

How to cite: Krietemeyer, A. and de Zeeuw-van Dalfsen, E.: Advancing Volcano Monitoring Capabilities: Deployment of Cost-Efficient GNSS Units in the Lesser Antilles on Mt. Scenery, Saba, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8653, https://doi.org/10.5194/egusphere-egu24-8653, 2024.

The Campi Flegrei caldera, located in Southern Italy, is one of the most hazardous volcanoes in the world. Seismic activity in the caldera has increased in the last year due to a new unrest phase of the volcano. This has driven the attention of the scientific community and both local and national media. The Campi Flegrei area is densely populated, with a very low signal-to-noise ratio, making the detection of small earthquakes or the recognition of non-seismic events more challenging.

This study introduces a novel approach to the detecting and clustering of seismic signals. Unlike conventional methods that primarily focus on the regularity of seismic patterns, our research pivots towards a complexity-centric perspective using the Multiscale Entropy (MSE) algorithm, in conjunction with the Self-Organized Map (SOM) algorithm for effective data clustering. This methodological shift allows for a more nuanced exploration of the intricate dynamics inherent in seismic activities.

Seismic signals are not random or chaotic but rather complex structures that vary across different scales. By employing the MSE algorithm, we unravel these complex patterns, offering insights into the seismic behaviours that traditional methods may overlook. Our findings indicate a significant correlation between the complexity of seismic signals and key geophysical events related to the dynamic of the volcano, suggesting that complexity analysis could be a significant tool in seismic monitoring and prediction.

The analysed dataset is a six-month long continuous signals recorded in period at the V0102 temporary seismic station installed by the INGV-Osservatorio Vesuviano close to the Pisciarelli area, located in the Campi Flegrei caldera. MSE has been applied to one-minute-long traces of signal and clusterized through the application of the SOM analysis, revealing hidden layers of complexity across multiple scales.

Moreover, the study explores the potential of integrating MSE analysis with other seismic analysis techniques to enhance the accuracy of seismic interpretations. By combining complexity analysis with traditional approaches, we aim to develop a more deep and comprehensive understanding of seismic signals, potentially leading to an improvement of the seismic risk assessment.

How to cite: Grimaldi, A., Scarpetta, S., Amoroso, O., Convertito, V., Galluzzo, D., Messuti, G., Napolitano, F., Gaudiosi, G., Nardone, L., and Capuano, P.: Multiscale Entropy (MSE) and Self Organizing Map (SOM): two useful tools for the interpretation of seismic signals in the Campi Flegrei Caldera, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8686, https://doi.org/10.5194/egusphere-egu24-8686, 2024.

Monitoring volcanic activity is a complex task, given the intricate nature of volcanic processes and the diverse eruptive styles exhibited by different volcanoes. Early Detection (ED) systems have emerged as indispensable tools for mitigating potential risks associated with volcanic eruptions. The effectiveness of these systems is contingent upon their ability to provide timely and accurate alerts, as false alarms or missed warnings can lead to economic repercussions and pose risks to infrastructure and human safety. Evaluating the reliability of the ED systems may be paramount not only for effective hazard mitigation but also for facilitating the implementation and optimization of an ED model. However, developing an ED model is a challenging and labor-intensive endeavor, also requiring a deep understanding of advanced techniques and a meticulous calibration of various parameters. 

In response to these challenges, we present the Framework for Evaluation of Early Detection Systems (FEEDS). FEEDS is a comprehensive Python-based package designed to automatically assess the generalization capability of generic ED systems through cross-validation. The framework introduces a generic class representing the ED model identified solely through data, enabling a systematic assessment based on essential predictive parameters, including True Positive Rate, False Discovery Rate, prediction time, and Fraction of Time in Alarm, by performing a simulation. 

To validate the effectiveness of FEEDS, we utilized tiltmeter and strainmeter data recorded at Stromboli volcano between 2007 and 2019. These datasets, managed by Istituto Nazionale di Geofisica e Vulcanologia and Università di Firenze, were employed to implement FEEDS with a customized model for the early detection of the paroxysmal activity affecting the volcano during the period of the study, demonstrating the practical applicability and reliability of this framework in real-world volcanic monitoring scenarios.

FEEDS may represent a valuable contribution to the ongoing efforts to enhance ED systems and their application in mitigating volcanic hazards. The development of a robust framework that automates the standard evaluation process not only streamlines system implementation but also reduces user efforts and establishes a common ground for assessing the reliability and performance of different ED models, contributing significantly to the advancement of volcanic monitoring capabilities.

How to cite: Cannavo, F., Minio, V., Privitera, E., Di Lieto, B., Romano, P., Innocenti, L., Lacanna, G., and Ripepe, M.: FEEDS: Validation of the Framework for Evaluation of Early Detection Systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10514, https://doi.org/10.5194/egusphere-egu24-10514, 2024.

It has been established through geochemical and geophysical models that, in Iceland, unloading of the Pleistocene ice sheet at the end of the last glacial period resulted in a peak in magma production and volcanic activity. Environmental differences are recorded in volcanic products, but mostly between discrete monogenetic glaciovolcanoes and postglacial lava flows. In areas of frequent and persistent activity, the way in which physical eruption styles evolved with changing ice thickness and glacial hydrology has received less attention. We examine a sequence of volcanic products exposed in the dissected flanks of Katla and Eyjafjallajökull, two ice-capped volcanoes that have been active beneath fluctuating glacial cover from the Pleistocene to present day. We use traditional geological mapping combined with photogrammetry surveys, major element geochemistry, paleomagnetic techniques and radiometric dating to determine how volcanic eruption processes have evolved with the eruptive environment throughout this period.

A wide diversity in the physical volcanology of deposits and major element geochemistry indicates a rich eruptive history alongside changes in glacial configuration and meltwater availability in this area. Volcanic products include pillow lavas, pillow breccias, tuff sheets 50-100 m thick, tuff mountains containing crystal-rich intrusions, lobate lava, entablature lava and compound pahoehoe lava. Evidence for glaciofluvial processes, including debris flow deposits, diamictite, and possible flood-formed canyons demonstrate additional processes that have shaped this landscape. Recognition of volcanic, constructive processes vs remobilisation and erosive processes is vital for accurately determining the distribution and source of products, particularly since edifice morphology is commonly used to characterise glaciovolcanoes.

Reliable dating from independent sources is necessary to determine the chronology of events and the timescale of volcano evolution. Identification of the Þórsmörk ignimbrite within the stratigraphy indicates a timescale spanning > 55 ka as well as a period of ice-free conditions. Additional age constraints from deposits in the area include a ⁴⁰Ar/³⁹Ar date from basaltic lava of < 20 ka and the identification of reworked Vedde-like pumice (< 12 ka). The sequence is capped by the 2010 Fimmvörðuháls lava. We are testing the use of paleomagnetic dating to refine the dates that have higher uncertainty and to provide additional ages for intercalated lavas that cannot be dated by radiometric isotope systems.

Given the ongoing changes in global glacier extent, it is critical to understand how glaciated volcanoes will behave physically. We are building an age-constrained eruptive history and record of eruptive environment from one of the most volcanically productive areas of Iceland to inform our understanding of the influence a changing environment has on volcanism.

How to cite: Cole, R., Gudmundsson, M. T., Piispa, E., Óskarsson, B., Gallagher, C., Jicha, B., and Farnsworth, W.: Volcanic eruption styles in changing environments at Katla and Eyjafjallajökull volcanoes, south Iceland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11452, https://doi.org/10.5194/egusphere-egu24-11452, 2024.

The 2022 Mauna Loa eruption began on November 27 23:21 HST (November 28 9:21 UTC) at the summit, based on the onset of seismic tremor and visual observations of nighttime incandescence from lava viewed by webcameras.  Continued visual observations noted early southwestward migration of the summit flows followed by dike propagation and new fissures on the northeast rift zone in the early hours of November 28^th HST.   Northeast rift zone activity subsequently settled into persistent activity primarily from Fissure 3 (located about 7 km from the Summit) until the eruption stagnated by December 9^th HST.

This contribution provides a detailed retrospective assessment of the performance of four Hawaiian Volcano Observatory (HVO) infrasound arrays (AIND, AHUD, MENE, SHEEP) and an International Monitoring System array operated by the University of Hawaii Infrasound (I59US) data during the onset and progression of the eruption.  We use results from a standard least-squares beamforming algorithm which is widely used for infrasound processing across the USGS Volcano Science Center and compare other multidisciplinary observations such as visual and seismic amplitude.

We find that that the standard array processing approach performed adequately as a real-time assessment tool with high correlation back-azimuth computations in reasonable agreement with visual observations.  High winds associated with storms impacted the quality of our results, particularly toward the end of the eruption when infrasound signals were comparably small.  It was possible to distinguish between summit and rift fissure activity using the three long-term arrays operated by HVO, despite the large source to receiver distance.  The SHEEP array (on the south flank of Mauna Kea) was established in response to the Mauna Loa eruption and only recorded the waning phase of the eruption.  Regardless, the new array should further improve azimuthal coverage for future Mauna Loa eruptive activity.

How to cite: Jolly, A., Iezzi, A., Patrick, M., Wech, A., Thelen, W., Lyons, J., and Chang, J.: Summit and rift vent progression captured by infrasound during the 2022 Mauna Loa eruption, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12280, https://doi.org/10.5194/egusphere-egu24-12280, 2024.

La Palma Island, spanning 708.32 km², resides at the north-western edge of the Canary Archipelago and is among the youngest within this group. In the last 123,000 years, volcanic activity has been exclusive to Cumbre Vieja in the island's southern region. The last volcanic activity (Tajogaite eruption) took place at the west flank of Cumbre Vieja from 19 September to 13 December 2021. It was a fissure and powerful strombolian eruption with a magnitude VEI = 3 (Bonadonna et al., 2022). Due to the absence of visible geothermal manifestations, recent decades have witnessed a burgeoning interest in studying diffuse degassing as a vital tool for volcano monitoring. With the aim of strengthening the geochemical monitoring of Cumbre Vieja volcanic activity, we have conducted on a weekly basis from October 2017 to the present, two distinct studies for volcano monitoring. Firstly, we monitored physical-chemical parameters and the chemical/isotopic composition and dissolved gases in the groundwater of two galleries (Peña Horeb and Trasvase Oeste) and three water wells (Las Salinas, Charco Verde, and San Isidro) before, during, and after the Tajogaite Volcano eruption at Cumbre Vieja from September 19 to December 13, 2021. We observed significant temporal variations in pH, EC, ion content, pCO₂, and δ¹³C-CO₂, correlating with interactions between deep volcanic fluids and groundwater. These changes showed good temporal agreement with the eruption and seismic swarms leading up to it. Simultaneously, we established a network of 21 closed static chambers to measure soil CO₂ effluxes. Before the eruption (October 2017 to December 2020), the recorded soil CO₂ efflux averaged 7.30 g·m^-2·d^-1 across Cumbre Vieja (7.48, 7.35, and 7.11 g·m^-2·d^-1 in the north, east, and west, respectively). Post-eruption (March 2022 to present), it averaged 7.51 g·m^-2·d^-1 (8.09, 7.58, and 6.99 g·m^-2·d^-1). The absence of data during this crucial period impedes direct comparisons and assessment of volcanic activity using this specific monitoring tool.

These methods underscore an approach to bolster volcanic surveillance on La Palma Island. Our study emphasizes the importance of monitoring the chemical and isotopic composition of groundwaters linked to active volcanic systems. Such evaluations offer critical insights into magmatic gas input within aquifers, despite limitations encountered during eruptive phases, as witnessed in the case of Cumbre Vieja in 2021.

Bonadonna et al. (2022). J.  Geophys. Res: Solid Earth, 127, e2022JB025302.

How to cite: Arencibia Hernández, M., Feraco, R., O'Shea, S., Cartaya, S., Rodríguez, F., Melián, G. V., Asensio-Ramos, M., Padrón, E., Pérez, N. M., Hernández, P. A., and Padilla, G. D.: Hydrogeochemical and soil CO2 efflux weekly monitoring network for the surveillance of Cumbre Vieja volcano, La Palma, Canary Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15102, https://doi.org/10.5194/egusphere-egu24-15102, 2024.

We present an analysis of Global Navigation Satellite System (GNSS) and seismic data collected in the last decade in northeastern Sicily and the Aeolian Islands (Italy). During this period, La Fossa Caldera at Vulcano showed a significant phase of unrest since September 2021. Based on the analysis of GNSS time series and velocity fields, we found evidence of changes in the deformation pattern of the Peloritani area, which is located about 40 km south of Vulcano Island in northeastern Sicily. These changes occurred about seven months before the Vulcano unrest and were accompanied by an increase in seismic strain, which was released at increasingly shallower depths. This suggests a temporal correlation between the deformations detected in the Peloritani area and the volcanic activity of Vulcano Island, which was further investigated by analyzing another phase characterized by an increase in the areal variation measured at La Fossa Caldera in 2018.   This study presents a new perspective for understanding the geodynamic, volcanic, and seismic phenomena in the investigated area, with particular attention to the Vulcan unrest between September and November 2021.

How to cite: Messina, D., Barberi, G., Bruno, V., Mattia, M., Patanè, D., Pepe, F., Rossi, M., and Scarfì, L.: Relationships between geodynamics of Northern Sicily (Italy) and volcanic activity at Vulcano Island (Aeolian Islands, Sicily, Italy) from GNSS and seismic data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16106, https://doi.org/10.5194/egusphere-egu24-16106, 2024.

Tenerife, with 2034 km², isthe largest active volcanic island of the Canarian archipelago and boasts over 1,000 galleries used for groundwater explotation, enabling access to the aquifer at varying depths and elevations. From mid-2016 to present, we've diligently sampled two important galleries - Fuente del Valle and San Fernando - on a weekly basis for volcanic monitoring. On-site measurements of water's physicochemical parameters such as temperature (ºC), pH, and electrical conductivity (E.C., µS·cm^-1) were conducted at each sampling point. Subsequently, the water's chemical/isotopic composition and dissolved gases were analyzed in the laboratory. Noteworthy trends in certain parameters, including increased conductivity, sulfate (SO₄^2-) concentration, chloride, bicarbonate, and the SO₄^2-/Cl^- molar ratio, suggest an infiltration of deep-seated gases into the groundwater. Isotopic data further revealed a robust interaction with endogenous gases like CO₂, H₂S, H₂, etc. Additionally, correlations were discerned between specific hydrogeochemical parameters in the gallery groundwaters, correlating with observed seismic activity changes. This study underscores the sensitivity of monitoring the chemical and isotopic composition of groundwater in Fuente del Valle and San Fernando galleries to fluctuations in volcanic activity on Tenerife. Exploring groundwater associated with a volcanic system offers insights into magmatic gas input into the aquifer, models groundwater flow within the edifice, and provides vital geochemical information potentially indicating an imminent eruption.

Concurrently, a cost-effective method to gauge CO₂ fluxes using alkaline traps has significantly contributed to Tenerife's volcanic surveillance. In the summer of 2016, a network of 31 closed alkaline traps was strategically placed across Tenerife's three volcanic rifts (NE, NW, and NS) and at Cañadas Caldera, persisting until the present. The weekly replacement of alkaline solutions facilitated subsequent laboratory titration analysis of the trapped CO₂, expressed as weekly integrated CO₂ efflux. Across the study period, the average CO₂ efflux stood at 6.41 g·m^-2·d^-1, with variations across regions: 8.41 g·m^-2·d^-1 for the NE rift-zone, 5.11 g·m^-2·d^-1 for Cañadas Caldera, 6.36 g·m^-2·d^-1 for NW rift-zone, and 6.35 g·m^-2·d^-1 for NS rift-zone. Notably elevated CO₂ effluxes were observed in the NE rift-zone, exhibiting maximum values. While the temporal evolution of CO₂ efflux estimated by closed alkaline traps exhibited minimal variation during the study, seasonal fluctuations were noted. The systematic use of closed static chamber alkaline traps proves to be a straightforward and economical method aiding volcanic surveillance, especially in areas lacking visible volcanic gas manifestations.

This comprehensive approach using chemical analysis of groundwater and CO₂ flux monitoring through alkaline traps showcases their combined efficacy in advancing Tenerife's volcanic surveillance, potentially serving as a crucial precursor to future volcanic activity.

How to cite: Cartaya Arteaga, S., Isfort, C., Lobanov, L.-A., Mcknight, C., Arencibia, M., Asensio-Ramos, M., Rodríguez, F., González-Cantero, J., Melián, G. V., Padrón, E., Padilla, G. D., Pérez, N. M., and Hernández, P. A.: Groundwater and soil CO2 efflux weekly monitoring network for the volcanic surveillance of Tenerife, Canary Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16290, https://doi.org/10.5194/egusphere-egu24-16290, 2024.

The prediction of the spatial and temporal evolution of ash dispersal and concentrations during an explosive volcanic eruption is crucial for crisis management. Satellite observations of volcanic ash clouds have enabled an important advance in the near-real-time quantification of the dynamic parameters of the volcanic umbrella propagating in the atmosphere. However, the link between these observations and the estimation of the eruptive source parameters (ESPs), such as the mass eruption rate (MER), remains a scientific obstacle to be overcome.

Previous studies developed methods to estimate the MER based on the temporal evolution of the volcanic umbrella obtained by visible images. The accuracy of the predictions however strongly depends on the physical model used to link the measurements made on the umbrella to the source conditions. These methods are reliable for eruptions where the impact of wind is low on the vertical plume (i.e., producing “strong plumes”), but are less suitable for weaker eruptions and/or occurring under strong wind conditions (thus producing “weak plumes”), which are much more frequent. In this study, we use the 1-D volcanic column model PPM for the estimation of ESPs based on umbrella measurements from strong to weak plumes. PPM takes into account the precise effects of wind and particle sedimentation on the plume dynamics, and has already been validated with natural data on Plinian eruptions.

The model allows predicting the plume geometry as seen from space, but close to the eruptive vent. These predictions are then used to link the MER to the umbrella geometry far from the source via an empirical factor  that connects the conditions at the neutral buoyancy height to those at the source of the umbrella cloud. The model is calibrated and tested using Meteosat-SEVIRI (MSG) images via the HOTVOLC system of paroxysms from Mt Etna (2015-2022) and from the Soufriere Saint Vincent (2021). The model allows estimating the temporal evolution of the MER during the Soufriere Saint Vincent eruption, with values consistent with those estimated in the field. The model also provides a theoretical framework to explain the geometry of weak plumes from Mt Etna. Ultimately, this study will provide a robust tool for a rapid interpretation of satellite data in terms of source conditions, which are necessary inputs for volcanic ash transport and dispersion models, such as those used by the Volcanic Ash Advisory Centers.

How to cite: Michaud-Dubuy, A., Gouhier, M., and Guéhenneux, Y.: Near real-time retrieval of weak plume source parameters: Insights from physical modeling and Meteosat data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17989, https://doi.org/10.5194/egusphere-egu24-17989, 2024.

Paleoclimate records show that Iceland was at times fully covered during Pleistocene glaciations. Models and data for the last glacial maximum indicate that the ice sheet at this time extended several tens of kilometers beyond the present coast. In contrast, much is known about the extent of the ice sheet during other times of the Weichselian glaciation, and very little information exists on possible variations of earlier glaciations. The regions near Þórisvatn, Jökulheimar, and Bláfjöll in the south-central highland of Iceland contain many outcrops of Pleistocene pillow lavas. The volatile contents in the glassy rims of pillow lavas may record the ambient pressure during eruption. This could offer insight into syn-eruptive glacier thickness. 15 samples were collected from three sample locations near Þórisvatn, one near Jökulheimar, and four near Bláfjöll from August 14 to August 15, 2023. Samples were crushed and sieved into 0.5-2.0 mm grains, and the glassiest grains were double polished with thicknesses between 88–219 µm for FTIR analysis. The spectra showed strong similarity to FTIR spectra of Holuhraun samples of similar thickness. H₂O contents of the samples varied between 0.22–0.32 wt%, with a median of 0.30 wt%. CO₂ was under the detection limit of the FTIR analyses. This may be an artifact of polishing grains too thin, and thus separate analyses with thicker grains will be carried out to accurately assess ambient pressure due to pressure model sensitivity to CO₂. Further analysis will include S concentrations, which will be used alongside H₂O and CO₂ to calculate a precise ambient pressure with the Sulfur_X model (Ding et al., 2023). The derived parameters will be used to estimate glacier thickness.

How to cite: Collins, H., Bali, E., and Gudmundsson, M. T.: Estimating Pleistocene ice thickness from pillow lava melt inclusions in the south-central highland of Iceland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18052, https://doi.org/10.5194/egusphere-egu24-18052, 2024.

Forecasting the location of future volcanic eruptions is one of the most critical and challenging issues when assessing volcanic hazard. A long-term hazard assessment approach based on past eruptive behaviour is of utmost importance for dormant or low-activity volcanoes, on which sound land-use policies and risk mitigation plans should be based.
São Miguel Island in the Azores Archipelago hosts three active central volcanoes (Sete Cidades, Fogo, and Furnas) that produced a large variety of eruptions in the last millennia and even in historical times, including trachytic explosive and effusive events and basaltic flank eruptions. 
Although these volcanoes are currently in a repose period, the likelihood of future eruptions should not be neglected.  
This study focuses on the estimation of the spatial probability of vent opening at the Sete Cidades, Fogo, and Furnas volcanoes separately, using the kernel method. Here, we used the location of past basaltic and trachytic emission centres, in the form of vents or fissures, of each volcano, to explore different kernel functions (Gaussian, Cauchy, Exponential, and Uniform) and calculate the best degree of clustering of vents given by a smoothing parameter (h). This approach was applied to each volcano by considering (1) basaltic and trachytic emission centres (fissures and/or vents) and (2) only trachytic emission centres (vents). This allowed us to estimate the pair (kernel function and h-value) that best fits the empirical cumulative distribution function of the minimum distance between emission centres and compute the final vent opening probability maps conditional to an eruption (or susceptibility maps).
For Sete Cidades, the results show that when considering basaltic and trachytic emission centres together, the southeast and west flanks of the volcano have a higher likelihood of hosting a new vent; however, when considering trachytic vents alone, the higher probability is at the west flank and southern sector of the caldera. The susceptibility map generated using Fogo’s basaltic and trachytic emission centres indicates a higher likelihood of hosting a new vent at the northwest flank of the volcano and southeast sector of the caldera. When only trachytic vents are considered, the southeastern sector of the caldera is more likely to host a new vent. For Furnas volcano, the results show that the northwestern part of the caldera has a higher likelihood of hosting a future basaltic or trachytic vent.

How to cite: Aguiar, S., Sandri, L., Pimentel, A., Oliveira, S., and Pacheco, J.: Spatial probability of vent opening at the active central volcanoes of São Miguel (Azores), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18410, https://doi.org/10.5194/egusphere-egu24-18410, 2024.

Etna is one of the most active volcanoes in the world, with almost continuous eruptive activity from its four summit craters resulting in frequent morphological variation of its upper area. The summit area is frequently site of effusive and explosive activity, but also of local flank collapses of the summit cones and pyroclastic flows with different triggering mechanisms. Such a dynamic environment requires a thorough understanding of its temporal evolution in order to properly assess the state of the volcano over time, and infer further insight into its potential hazard. Voragine (VOR), formerly called the Central Crater, is the oldest and has been depicted on topographic maps since at least 1865; the NE-Crater (NEC) cone was born in 1911; the Bocca Nuova started as a pit crater next to Voragine in 1968, and the SE-Crater (SEC) cone started in 1971. Since 2011, a new cone grew on the SEC eastern lower flank during a series of paroxysmal episodes and it progressive coalesced with the SEC cone. To properly model the temporal changes of the summit area, we exploited archival topographic maps and aerial photogrammetric stereo-pairs. This reconstruction started from the digitising and processing of topographic maps that were produced on 1897, 1932, and 1985. We also processed aerial stereo-images acquired since 1954. From these datasets we extracted Digital Elevation Models (DEMs) with 5-10 m pixel size. We integrated historical data with already available DEMs: the 1998 and 2001, interpolated from vector maps; the 2005, obtained from aerial photogrammetry; and the 2012, 2014 and 2015 derived from helicopter-acquired data. Finally, between 2017 and 2023 we performed UAS (unoccupied aerial systems) surveys to derive high-resolution DEMs and orthomosaics with sub-meter pixel size. This new multi-temporal Digital Elevation Models (DEMs), from ancient topographic maps and aerial photo as well as from recent and current UAS data, have been analysed through the ESRI ArcGIS software to reconstruct the topography and quantify the main morphological changes of Etna summit area. Our modelling increases the knowledge about the evolution and the behaviour of a frequently active volcano, thus enabling to mitigate the associated risks.

How to cite: Massimo, C., Emanuela, D. B., Cristina, P., Fabio Luca, B., Domenico, P., Riccardo, C., and Mario, P.: 150 years of Etna Summit Craters through a photogrammetry-based time machine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19010, https://doi.org/10.5194/egusphere-egu24-19010, 2024.

Askja, an active volcano in Iceland’s Northern Volcanic Zone, has experienced over 70 centimetres of uplift since August 2021, following several decades of ground surface deflation. In the same month that surface uplift began, there was also an overall increase in shallow microseismicity. This overlap suggests that there is a link between the shallow seismicity and re-inflation, but much more information is needed to constrain an exact mechanism.

To gain more insight into the stresses driving seismicity beneath Askja, and how they may have changed with the onset of uplift, moment tensor solutions were constructed from a subset of events within the Askja caldera, both before and after the start of re-inflation. The goal is to uncover any dominant earthquake slip orientation patterns, and how they have changed post August 2021. Cambridge’s Volcano Seismology Group has maintained a dense seismic network surrounding and within Askja from July 2007 to the present day, which provides sufficient data to produce well constrained moment tensor solutions, even for events as small as magnitude 0.5.

Moment tensor solutions constructed from the first year of inflation suggest that the direction of slip along faults encircling the crater lake Öskjuvatn did not change when Askja switched from deflation to re-inflation; however, data from a longer recording period is needed to provide a definitive conclusion. With another 12 months of data from the main network now downloaded, as well as additional data from a supplementary dense network of seismic nodes within the Askja caldera from July 2023 to September 2023, a more in-depth analysis of the moment tensor solutions for shallow microearthquakes underneath the region of uplift through time is now possible. The preliminary results of this analysis will be presented, along with plans for future interrogation of this enhanced dataset.

How to cite: Siggers, I., Winder, T., Rawlinson, N., White, R. S., and Brandsdóttir, B.: Earthquake focal mechanisms before and after the onset of re-inflation at Askja caldera, Iceland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19414, https://doi.org/10.5194/egusphere-egu24-19414, 2024.

Identifying the observable signals that warn against volcanic unrest and impending eruptions is one of the greatest challenges in the management of natural disasters. In this regard, satellite data has become a strong focus of global interest, offering abundant datasets from multi-missions and valuable tools to study Earth and improve physical models.

The SAFARI project aims at developing a comprehensive space-based strategy for next-generation quantitative volcano hazard monitoring integrating the most recent satellite imagery capabilities and the relative products with the newest technologies mainly in the field of Machine Learning (ML) and Soft Computing. The main objectives of SAFARI include: (i) following the manifestations of unrests and impending eruptions, as well as (ii) forecasting the areas potentially threatened by volcanic products through eruptive scenarios. For this purpose, SAFARI intends to characterize the state of volcanic activity (quiet, unrest and eruptive phases) by taking advantage of a variety of satellite data, including active and passive sensors ranging from optical to microwave frequencies, and to extract quantitative satellite-derived input parameters to physical models for rapid and accurate scenario forecasting during eruptions. 

Well-established products from space-based volcano monitoring such as: (i) volcanic radiative power, (ii) surface displacement and (iii) volcanic gas emission (e.g., SO2, BrO) time series are processed jointly and supported by less frequently used but still informative time series such as (iv) ground skin temperature of the volcanic edifices, (v) change detection time series, (vi) time-varying volcanic ash indices, (vii) ash top height time series, (viii) gravity field variation and also (ix) time varying indices giving information about deformation phases of the volcanic edifice (i.e., inflation/deflation) as well as (x) crucial parameters related to the volcanic source (e.g., depth, volume variation) by using data assimilation to deformation models. SAFARI merges and assembles the latest developments from different INGV teams, in a way to analyze Earth observation (EO) data with a retrospective and multi-disciplinary approach, employing traditional statistical or numerical analysis, latest generation Graphic Processing Units (GPUs) architectures and newer and more sophisticated ML algorithms to classify time series, detect anomalies, and predict or estimate significant parameter values. 

The methodologies in SAFARI are developed and verified at four active volcanoes worldwide: Etna and Vulcano (Italy), continuously monitored by dense ground based networks managed by INGV, which will provide a first controlled experiment, and Nyiragongo (D.R. Congo) and Sangay (Ecuador), characterized by high volcanic hazard but with modest permanent monitoring networks, where satellite remote sensing is a key monitoring tool.

The results of the SAFARI project and its underlying data source and methodologies, as well as the potential of the whole integrated processing chain, aim at becoming an effective tool for volcanic hazard analysis and impact quantification never used to date in volcanology, improving safety and reducing risk associated to eruptive events worldwide.

How to cite: Ganci, G., Bilotta, G., Pignatelli, A., Scollo, S., and Trasatti, E. and the SAFARI team: The SAFARI project: An Artificial Intelligence-based strategy for volcano hazard monItoring from space, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8200, https://doi.org/10.5194/egusphere-egu24-8200, 2024.