Displays

Processes related to magma formation, transport, emplacement, and eruption at volcanoes are linked by structures that transect the entire crust, but imaging the mid- to lower-crustal portions of these magmatic systems has been a longstanding challenge. Tomography, local seismic source studies, geodetic, and geochemical constraints are typically most sensitive to shallow storage and/or have insufficient resolution at these depths. Scattered wave seismic imaging techniques, particularly receiver function analyses, provide a promising pathway towards imaging the mid- to deep-crustal magmatic structure beneath volcanoes with only a modest number of broadband seismic instruments (N < 10). Using seismic data from two recently-active volcanoes in Alaska’s Aleutian arc, Akutan and Cleveland, we demonstrate the feasibility of seismically imaging crustal magmatic structure with only three and seven local broadband seismometers at each volcano, respectively. The two volcanoes have significantly differing eruptive histories: Akutan last erupted in 1992 and has since experienced only experienced a shallow dike intrusion in 1996, whereas Cleveland is one of the most frequently-erupting volcanoes in the Aleutian arc. Both also have significantly different depths-to-slab, with Cleveland representing one of the global shallow end members at ~ 70 km depth, and a more globally-average depth of 85 km at Akutan. Receiver functions reveal different underlying crustal magmatic structures, with a mid-crustal sill-like structure that has a well-defined top and base beneath Akutan, and a thicker and deeper magmatic region with less abrupt boundaries beneath Cleveland. Future work using similar approaches will enable an unprecedented comparative examination of magmatic systems beneath sparsely instrumented volcanoes globally.

How to cite: Janiszewski, H., Wagner, L., and Roman, D.: Mid-crustal magma reservoirs at Cleveland and Akutan Volcano imaged through novel receiver function analyses, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6156, https://doi.org/10.5194/egusphere-egu2020-6156, 2020.

Oldoinyo Lengai volcano, located in the Natron Basin (Tanzania), is the only active natrocarbonatite volcano world-wide. As such, it presents an important endmember magmatic system, which occurs in a young rift segment (~3 Ma) of the East African Rift System. At this volcano, effusive episodes of long-duration are interrupted by short-duration explosive eruptions. At the end of February 2019, we installed a dense seismic network and four infrasound stations as part of the SEISVOL - Seismic and Infrasound Networks to Study the Volcano Oldoinyo Lengai - project. The seismic network spans an area of 30 x 30 km and encompasses Oldoinyo Lengai volcano, the extinct 1 Ma-old Gelai shield volcano, the active Naibor Soito monogenetic cone field and surrounding fault population. Here, we present temporal earthquake distributions combined with 2D absorption and scattering imaging.

On average, we report up to 34 earthquakes per day within and in the vicinity of our network. Given the dense station spacing, we are able to lower the detection threshold to -1.0 M_L with a M_C of -0.3. During the first months of data acquisition, the seismicity is clustered in distinct areas as background seismicity and in intermittent seismic swarms:

To image the magmatic plumbing system, we map scattering and absorption of the seismic dataset using the MuRAT (Multi-Resolution Attenuation Tomography) code. Our preliminary results show two well-resolved high-absorption and high-scattering anomalies below Oldoinyo Lengai and the Gelai intrusion in 2007 at all frequencies. With decreasing frequency (increasing depth) the anomalies converge, suggesting a link of the plumbing systems at depth.

How to cite: Reiss, M. C., De Siena, L., Rümpker, G., and Kazimoto, E. O.: Imaging active magmatic systems at Oldoinyo Lengai volcano (Tanzania) via earthquake distribution and seismic scattering and absorption mapping, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2419, https://doi.org/10.5194/egusphere-egu2020-2419, 2020.

The major part of the Northern group of volcanoes (NGV) in Kamchatka is occupied by the Klyuchevskoy group, which is a unique cluster of more than thirteen volcanos having exceptionally diverse eruption styles and compositions. The NGV also includes Shiveluch volcano to the north and Kizimen volcano to the south, both andesitic strongly explosive volcanoes. The crustal structure beneath the Klyuchevskoy group was previously explored using data of the permanent stations and several temporary networks; however, for studying the mantle structures, no high-quality data was available. To close this gap, a temporary seismic KISS network was installed throughout the NGV by an international consortium from August 2015 to July 2016. Together with 22 permanent stations, it included more than 100 simultaneously operating seismic stations. Based on the KISS data, we manually picked more than 43,000 arrival times of the P and S waves from 665 events (65 picks per event on average). Furthermore, this dataset was supplemented with the arrival times from the slab-related seismicity recorded by permanent stations during long-term observations. Several resolution tests have demonstrated that this dataset allows very high quality recoveries of the anomaly both laterally and in the vertical direction. The distributions of seismic anomalies in the uppermost mantle (50 km depth) show clear connection with the composition of the volcanoes. All the andesitic volcanoes (Kizimen, Udina, Zimina, Bezymyanny, Zarechny, Kharchenko and Shiveluch) are located above prominent low-velocity anomalies, whereas the basaltic volcanoes (Nikolka, Tolbachinsky Dol, Ostry and Plosky Tolbachik, Ushkovsky and numerous monogenic cones) are mostly associated with higher velocities in the mantle. This correlation might be explained by the effect of the mantle temperature to the rheological properties of the crust. Over the hot mantle, the crust becomes ductile, and it favors for forming intermediate crustal reservoirs, where magma is accumulated and separated for long time making it more felsic. Above the colder mantle, the crust is brittle and may be fractured by ascending mafic intrusions. In this case, mantle material quickly penetrates through the crust and reaches the surface producing fissure basaltic eruptions and shield volcanoes. Another important conclusion follows from the interpretation of the vertical section throughout the NGV from Kizimen to Shiveluch. Along this section, the only one deep low-velocity anomaly reaching depths of more than 100 km is located beneath Shiveluch, which perfectly coincides with the gap in the Pacific slab imaged by other studies. Further to the south, the low-velocity anomaly is observable in the uppermost mantle down to 60-70 km. This result shows that all the volcanoes of the NGV are fed from a single source associated with the ascent of the hot asthenosphere though the slab window beneath Shiveluch. Then the hot asthenospheric material spreads southward along the crust bottom. This flow heats the mantle wedge, which is highly contaminated with volatiles coming from the slab, and leads to active melting and forming magma sources. This may explain exceptional activity and diversity of the volcanoes in this zone.

How to cite: Koulakov, I., Shapiro, N., Gordeev, E. I., Sens-Schoenfelder, C., Abkadyrov, I., Senyukov, S., Luehr, B., Bushenkova, N., Jakovlev, A., Stupina, T., and Novgorodova, A.: Mantle feeding sources of the Northern group of volcanoes in Kamchatka inferred from the tomographic inversion of travel time data of the KISS network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4015, https://doi.org/10.5194/egusphere-egu2020-4015, 2020.

Tenerife and La Palma are active volcanic islands belonging to the Canarian archipelago. The island of La Palma is the most occidental and volcanically active island of the archipelago. The youngest volcanic rocks are located in the Cumbre Vieja volcanic complex, a fast-growing North-South ridge in the southern half part of the island. On the other hand, the central part of Tenerife island hosts the Teide composite volcano, the third tallest volcano on Earth measured from the ocean floor. The volcanic system of the island extends along three radial dorsals, where most of the historical eruptions occurred. Those two volcanic islands have potential geothermal resources that could be exploited to increase the percentage of renewable energy in the Canary Islands.

The main objective of this work is the use of Ambient Noise Tomography (ANT) to determine high-resolution seismic velocity and attenuation models of the first few kilometres of the crust, in order to detect anomalies potentially related to active geothermal reservoirs. In the case of Tenerife, previous tomographic studies were performed on the island using active seismic data. They allowed to image the structure of the first 8 km depth. However, for the purpose of geothermal exploration, a higher spatial resolution is needed for the first few kilometres and the determination of the shear wave velocity has a particular importance when searching for fluid reservoirs. In the case of La Palma, no seismic tomography was performed yet.

To realize the ANT, we deployed temporary broadband seismic networks in the two islands. In total, we deployed seismic stations on 41 measurements points in Tenerife and 23 points in La Palma. The campaigns lasted at least 1 month, using jointly the permanent seismic network Red Sísmica Canaria (C7) operated by INVOLCAN. After performing standard data processing to retrieve Green’s functions from cross-correlations of ambient noise, we retrieved the dispersion curves using the FTAN (Frequency Time ANalysis) technique. The inversion of dispersion curves to obtain group velocity maps was performed using a novel non-linear multiscale tomographic approach. The forward modelling of surface waves traveltimes was implemented using a shortest-path algorithm which takes the topography into account. The method consists of progressive non-linear inversion steps at increasing resolution. This technique allows retrieving 2D group velocity models in presence of strong velocity contrasts with up to 100% of relative variation.

In parallel with velocity model, we retrieved maps of seismic attenuation (i.e. quality factor Q) retrieved from the coda envelope decay of noise cross-correlations (Q-coda). For each source-receiver pair, a Q-coda value was calculated, and mapped to the target area by using 2D empirical sensitivity kernels for diffusion (Del Pezzo and Ibañez, 2019). We compared 2D velocity and attenuation images at different dominant periods, evidencing structural features for Tenerife and La Palma islands which seem to be relevant for the purpose of geothermal exploration.

How to cite: Cabrera, I., Soubestre, J., D'Auria, L., Del Pezzo, E., Barrancos, J., Padilla, G. D., Cervigón, G., Przeor, M., Bidaurrazaga-Aguirre, G., Martínez van Dorth, D., Martín-Lorenzo, A., and Pérez, N. M.: Velocity and attenuation models of Tenerife and La Palma (Canary Islands, Spain) through Ambient Noise Tomography. , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-318, https://doi.org/10.5194/egusphere-egu2020-318, 2020.

The accuracy of elastic analytical solutions and numerical models, widely used in volcanology to interpret surface ground deformation, depends heavily on the Young’s modulus chosen to represent the medium. The paucity of laboratory studies that provide Young’s moduli for volcanic rocks, and studies that tackle the topic of upscaling these values to the relevant lengthscale, has left volcano modellers ill-equipped to select appropriate Young’s moduli for their models. Here we present a wealth of laboratory data and suggest tools, widely used in geotechnics but adapted here to better suit volcanic rocks, to upscale these values to the scale of a volcanic rock mass. We provide the means to estimate upscaled values of Young’s modulus, Poisson’s ratio, shear modulus, and bulk modulus for a volcanic rock mass that can be improved with laboratory measurements and/or structural assessments of the studied area, but do not rely on them. In the absence of information, we estimate upscaled values of Young’s modulus, Poisson’s ratio, shear modulus, and bulk modulus for volcanic rock with an average porosity and an average fracture density/quality to be 5.4 GPa, 0.3, 2.1 GPa, and 4.5 GPa, respectively. The proposed Young’s modulus for a typical volcanic rock mass of 5.4 GPa is much lower than the values typically used in volcano modelling. We also offer two methods to estimate depth-dependent rock mass Young’s moduli, and provide two examples, using published data from boreholes within Kīlauea volcano (USA) and Mt. Unzen (Japan), to demonstrate how to apply our approach to real datasets. It is our hope that our data and analysis will assist in the selection of elastic moduli for volcano modelling. To this end, our new publication (Heap et al., 2019), which outlines our approach in detail, also provides a Microsoft Excel© spreadsheet containing the data and necessary equations to calculate rock mass elastic moduli that can be updated when new data become available. The selection of the most appropriate elastic moduli will provide the most accurate model predictions and therefore the most reliable information regarding the unrest of a particular volcano or volcanic terrain.

Heap, M.J., Villeneuve, M., Albino, F., Farquharson, J.I., Brothelande, E., Amelung, F., Got, J.L. and Baud, P., 2019. Towards more realistic values of elastic moduli for volcano modelling. Journal of Volcanology and Geothermal Research, https://doi.org/10.1016/j.jvolgeores.2019.106684.

How to cite: Heap, M., Villeneuve, M., Albino, F., Farquharson, J., Brothelande, E., Amelung, F., Got, J.-L., and Baud, P.: Towards more realistic values of elastic moduli for volcano modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7111, https://doi.org/10.5194/egusphere-egu2020-7111, 2020.

Seismic and acoustic signals are important for remote real time and post-eruption analysis of volcanic eruptions. To properly interpret these signals it is critical to connect their characteristics with eruption parameters. In this study, we present an analysis of the infrasound emissions by the sustained lava fountain at Fissure 8 during the 2018 eruption of Kilauea Volcano, Hawaii. This eruption was one of the largest and most destructive events in Hawaii’s historic times. Large (35.5 km2) lava flows covered much of the Lower East Rift Zone (LERZ) and destroyed property and infrastructure. This activity was dominated by high lava effusion rates at Fissure 8 and lava fountains up to 80 m tall. The energetic output of gas and lava produced sustained, broadband acoustic waves which were recorded by a four-element infrasound array deployed 0.6 km northwest of the fountain. The spectrum of the infrasound is similar to that of man-made jets and is termed volcanic jet noise. We compare the spectrum of the recorded infrasound signal with models developed for man-made jets such as rockets and jet engines. These models predict different spectral shapes for fine scale turbulence (FST), produced by incoherent movement of the gases, and large scale turbulence (LST), produced by coherent instability waves. The dominance of one or the other turbulent noise source is highly directional. We compare the infrasonic signals with observations of fountain properties, such as pyroclast velocity and height, to help understand the jet noise signals and determine quantitative fountain properties from the infrasound. The results of this work will contribute to the understanding of the physics of lava fountain sound generation, its dependence on eruption parameters, and ultimately provide a tool for rapid assessment of eruption style and dynamics.

How to cite: Gestrich, J., Fee, D., Lyons, J., Patrick, M., Parcheta, C., Kueppers, U., and Cigala, V.: Volcanic Jet Noise from the Kilauea Fissure 8 Lava Fountain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11001, https://doi.org/10.5194/egusphere-egu2020-11001, 2020.

The recent lava lake activity at Masaya volcano, Nicaragua, provided an ideal and rare moment to investigate dynamic and rapid magmatic processes. A multiparametric and low-cost approach which combined high time resolution gas, thermal, and video of the rapidly convecting lava lake was used. Gas measurements were conducted using DOAS (Differential Optical Absorption Spectroscopy) by traversing beneath the plume and Raspberry Pi ultraviolet (UV) cameras. Temperature measurements of the lake were made using a Raspberry Pi near infrared thermal camera approach. Video footage of the lava lake allowed the determination of the unusually rapid lake velocity, and crucially the generation of activity statistics such as location and frequency of the frequent small (spherical-cap) bubble bursts at the surface. Contemporaneously acquired UV and thermal datasets also allowed the assessment of a detected oscillation in the sulphur dioxide degassing data. By combing all these data streams, the unique fluid dynamics of lava lake activity at this location is highlighted.

How to cite: Pering, T. D., Ilanko, T., Wilkes, T. C., Stanger, L., Willmott, J. R., and McGonigle, A. J. S.: Multiparametric measurements of the lava lake at Masaya volcano, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11939, https://doi.org/10.5194/egusphere-egu2020-11939, 2020.

We present a method to jointly invert muographic and gravimetric data to infer the 3D density structure of volcanoes.

Muography and gravimetry are two independent methods that are sensitive to the density distribution. The gravimetric inversion allows to reconstruct the 3D density variations but the process is well-known to be ill-posed leading to non unique solutions. Muography provides 2D images of mean densities from the detection of high energy atmospheric muons crossing the volcanic edifice. Several muographic images can be used to reconstruct the 3D density distribution but the number of imagdes is generally limited by instrumentation and field contstraints.

The joint inversion of muographic and gravimetric data aims at reconstructing the 3D density structure of an edifice, benefiting from the advantages of both methods. We developed a robust inversion scheme based on a Bayesian formalism. This approach takes into account the data errors and a priori information on the density distribution with a spatial covariance so that smooth models are obtained. The a priori density standard deviation and the spatial correlation length are the two hyperparameters that tune the regularization, hence that control the inversion result. The optimal set of hyperparameters is determined in a systematic way using Leave One Out (LOO) and Cross Validation Sum of Squares (CVSS) criteria (Barnoud et al., GJI 2019). The method also allows to automatically determine a constant density offset between gravimetry and muography to overcome a potential bias in the measurements (Lelièvre et al., GJI 2019).

The case of the Puy de Dôme volcano (French Massif Central) is studied as proof of principle as high quality data are available for both muography (Le Ménédeu et al., EGU 2016; Cârloganu et al., EGU 2018) and gravimetry (Portal et al., JVGR 2016). We develop and validate the method using synthetic data computed from a model based on the Puy de Dôme topography and acquisition geometry, as well as on real data.

How to cite: Barnoud, A., Cayol, V., Lelièvre, P., Niess, V., Cârloganu, C., and Le Ménédeu, E.: Bayesian joint inversion of muographic and gravimetric data for the 3D imaging of volcanoes, case study of the Puy de Dôme, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13978, https://doi.org/10.5194/egusphere-egu2020-13978, 2020.

Characterizing volcano-hydrothermal activity is crucial for understanding the dynamics of volcanos and the relation between surface observations and deep magmatic activity. It may be also relevant for detecting precursors to magmatic and phreatic eruptions. Traditional monitoring tools such as seismicity and deformation are not always sensitive to hydrothermal activity, therefore it is important to explore new tools that can provide complementary information about the system.

Muon imaging is increasingly used as a novel tool to complement standard geophysical methods in volcanology, allowing to image large volumes of a geological body from a single observation point. Continuous measurements of the muon flux enable to infer density changes in the system. In volcanic hydrothermal systems, this approach helps to characterize processes of steam formation, condensation, water infiltration and storage. Here we present the results of a combined study in the La Soufrière de Guadeloupe volcano (West Indies, France) where continuous measurements of muon tomography were acquired simultaneously to seismic noise. The combination of these two methods helps to characterize a short-term, shallow hydrothermal event, its localization, and the involved volumes in the volcano. The deployment of networks of various sensors including temperature probes, seismic antennas and cosmic muon telescopes around volcanoes could valuably contribute to detect precursors to more hazardous hydrothermal events.

How to cite: Rosas-Carbajal, M., Le Gonidec, Y., Gibert, D., de Bremond d'Ars, J., Ianigro, J.-C., and Marteau, J.: Hydrothermal activity in a lava dome detected by combined seismic and muon monitoring, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13307, https://doi.org/10.5194/egusphere-egu2020-13307, 2020.

Since May 2018, the Mayotte Island (Comoros archipelago) is ongoing the largest basaltic eruption of the three last centuries, with up to several km3 deduced from modeling and direct seafloor observations. During this volcano tectonic crisis, we performed a land and shallow marine Magnetotelluric (MT) survey on the island the closest to the new volcano. Initially designed for shallow geothermal exploration (<2km depth), we extended the duration of the measurements to perform deep MT soundings (>10km depth) and get some insight into the geo-electric structure of the Mayotte island.

The analysis of the MT data shows a deep geo-electrical anisotropy in the W-NW E-SE direction that is coherent with the expected orientation of the oceanic ridge between the Somalian and the Lwandle plate. Additionally, the 3D inversion of the data shows that a massive conductive body is present at great depth (>15km), possibly related to the presence of partial melt. Interestingly, this conductor seems to become shallower in the direction of the new volcano.

After the survey, we installed two permanent MT stations in Petite Terre and Grande Terre islands to monitor possible time-lapse conductive anomaly related to fluid migration. We will show the results and discuss the Time Lapse MT strategy, challenges and observations.

How to cite: Wawrzyniak, P., Darnet, M., Hautot, S., and Tarits, P.: The 2018-2019 Mayotte volcano-tectonic crisis: insights from electromagnetic experiments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20669, https://doi.org/10.5194/egusphere-egu2020-20669, 2020.

The 65 km² Bárdarbunga caldera is located in the NW part of the Vatnajökull glacier in central Iceland.  The caldera floor lies under 500-800 m thick ice and the rims are fully subglacial as well.  The caldera subsided by 65 m during the Bárdarbunga-Holuhraun eruption in 2014-2015, when about 2 km³ of magma drained out from a magma reservoir at ~10 km depth leading to the largest eruption in Iceland since Laki in 1783.  Deformation surveys outside the caldera have indicated inflation since soon after the end of the eruption in February 2015 and seismicity has been elevated.  The extensive ice cover precludes conventional microgravity surveys or detailed surveys of caldera floor elevation.  However, we have studied gravity changes by comparing results of repeated Bouguer anomaly surveys.  We perform a full Bouguer correction using detailed DEMs of both the ice surface and the ice-radar-derived bedrock.  Ice surface changes are also mapped, allowing the removal of effects on gravity by ice mass changes.  Possible sources of significant anomalies are either changes in bedrock elevation between surveys, other more deep-seated mass changes beneath the volcano, or changes in the water table and pore pressure.  Surveys were carried out using a Scintrex CG-5 in 2015, 2016, 2018 and 2019, with measurements done at 25-50 locations each time.  As no benchmarks exist on the ice the spatial difference in station location of 10-20 m exists between survey years.   However, post-processing provides kinematic GPS position and elevation accuracy better than 0.1 m. Analysis of the data and error sources indicate an accuracy in estimates of changes of 50-100 µGal. The results obtained indicate change with an amplitude of a few hundred µGals; over the four years between 2015-2019 a clear Bouguer anomaly increase is recorded over the caldera relative to the surrounding area. Sharp gradients in the gravity difference near the caldera boundary point to a shallow source, consistent with the gravity signal arising from or near the ice-bedrock boundary.  This indicates fast resurgence at Bárdarbunga since 2015. The elevation of bed reflections delineated from radio echo sounding profiles (~2 MHz), measured within the caldera in June 2015 and accurately repeated in June 2019, further supports this.  The suggested deformation mechanisms can be compared to geodetic observations outside the caldera for further evaluation. If all the signal is interpreted in terms of magma movements, a rise of the caldera floor by several meters and the inflow of 0.2-0.3 km³ of new magma is inferred.

How to cite: Gudmundsson, M. T., Högnadóttir, T., Sigmundsson, F., Geirsson, H., Li, S., Reynolds, H. I., Magnússon, E., and Pálsson, F.: Rapid resurgence of the subglacial Bárdarbunga caldera following collapse in 2014-2015, quantified with repeated Bouguer gravity surveys, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18744, https://doi.org/10.5194/egusphere-egu2020-18744, 2020.

Identifying the observables that warn of volcanic unrest and impending eruptions is one of the greatest challenges in the management of natural disasters. An important but scarcely explored observable is diffuse heating, that is, the heat released passively through the ground. Diffuse heating represents one of the major energy sources in active volcanoes during inter-eruptive periods, and can dominate over the elastic energy released during seismic and deformation events. However, many questions remain open: Is there a direct correlation between diffuse heating and the subsurface processes that precede volcanic eruptions? To what extent are volcanic eruptions preceded by an enhancement of the diffuse emissions of heat? We address these questions by analyzing 16.5 years of long-wavelength (10.780 – 11.280 μm) thermal infrared radiance data recorded over nine volcanoes by the moderate-resolution imaging spectroradiometers (MODIS instruments) aboard NASA's Terra and Aqua satellites; this amounts to >35 TB of data and >210,000 MODIS scenes. Our statistical analysis reveals that volcanic edifices get warm for several years before magmatic, phreatic and hydrothermal eruptions. This pre-eruptive warming has been observed at Ontake (Japan), Ruapehu (New Zealand), Domuyo (Argentina), Calbuco (Chile), Redoubt and Okmok (Alaska), Pico do Fogo (Cape Verde), El Hierro (Spain), and Agung (Indonesia) volcanoes. In particular, we found pre-eruptive increases of up to ~1.5 K in the median temperature of the volcanic edifices; this, based on an energy balance, reflects increases of heat flux of up to 10 W/m². We theorize that the pre-eruptive surface warming of volcanoes is the surface manifestation of shallow hydrothermal activity. Our retrospective analysis is especially relevant, since several of the eruptions analyzed did occur with little or no warning (e.g., the 2014 phreatic eruption of Ontake and the 2015 magmatic eruption of Calbuco). The possibility of tracking temporal changes of diffuse heating using satellite data opens new horizons to study the thermal reactivation of magma reservoirs and improve the forecasting of volcanic eruptions.

How to cite: Girona, T., Realmuto, V., and Lundgren, P.: Pre-eruptive diffuse heating of volcanoes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12683, https://doi.org/10.5194/egusphere-egu2020-12683, 2020.

The use of polar-orbiting satellite instruments to monitor volcanoes has been an established technique for decades. However, a major limitation is the temporal resolution provided by these satellite platforms. For UV instruments, one or occasionally two observations per day are possible for tropical latitudes, though an improved temporal resolution is seen at high latitudes. The SO₂ altitude within the atmospheric column is usually highly unconstrained and is one of the largest sources of uncertainty within the SO₂ retrieval. This method assigns a best-fit altitude to each pixel, instead of using a single value for the whole plume.

TROPOMI is an UV spectrometer, launched on the Sentinel-5P platform in October 2017. The instrument has a swath of 2600 km and a spatial resolution of 5.5x7.5 km (improving to 3.5x7.5 km from August 2019). Sentinel-5P flies with the A-Train constellation, with an equatorial overpass time of 13:30 local time.

Applying the NOAA HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) back trajectory model, the injection time, injection and measurement altitudes of the SO₂ in each pixel within the satellite image is derived. Back trajectories are run for each pixel at a range of altitudes. The natural variability in the wind field at different altitudes (wind shear) means that only some of those trajectories will return to the volcano, constraining the measurement altitude to those trajectories. The SO₂ concentration is interpolated to this altitude. Finding the point in the trajectory when it most closely approaches the volcano provides the time and altitude of injection.

Combining the corrected SO₂ concentrations with the injection time produces the SO₂ flux that generated the observed SO₂ cloud, and with the injection altitude to calculate the mass eruption rate. These parameters can also be used to improve eruption plume modelling by improving the constraints on the eruption column characteristics.

The method is applied to the December 2019 eruption of White Island, New Zealand.

How to cite: Hayer, C. and Burton, M.: Application of back trajectory modelling to TROPOMI SO2 observations to retrieve sub-daily volcanic fluxes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17999, https://doi.org/10.5194/egusphere-egu2020-17999, 2020.

A combination of aerogeophysics, seismic observations and direct observation from ice cores and subglacial sampling has revealed at least 21 sites under the West Antarctic Ice sheet consistent with active volcanism (where active is defined as volcanism that has interacted with the current manifestation of the West Antarctic Ice Sheet). Coverage of these datasets is heterogenous, potentially biasing the apparent distribution of these features. Also, the products of volcanic activity under thinner ice characterized by relatively fast flow are more prone to erosion and removal by the ice sheet, and therefore potentially underrepresented. Unsurprisingly, the sites of active subglacial volcanism we have identified often overlap with areas of relatively thick ice and slow ice surface flow, both of which are critical conditions for the preservation of volcanic records. Overall, we find the majority of active subglacial volcanic sites in West Antarctica concentrate strongly along the crustal thickness gradients bounding the central West Antarctic Rift System, complemented by intra-rift sites associated with the Amundsen Sea to Siple Coast lithospheric transition.

How to cite: Blankenship, D., Quatini, E., and Young, D.: Active subglacial volcanism in West Antarctica as assessed by airborne geophysics: Distribution and context, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21391, https://doi.org/10.5194/egusphere-egu2020-21391, 2020.

Seismic tomography is the state-of-the-art technique for imaging the Earth. When applied to magmatic systems, phase-dependent imaging (e.g. travel-time tomography or noise interferometry) has shown the potential to broadly resolve magmatic anomalies. Here, I show recent advances in tomographic imaging of collisional continental structures at the upper mantle scale in SE Asia, with their influence on the distribution of magmatic systems. Then, I focus on the latest results of seismic attenuation (amplitude) tomography applied to crustal magmatic systems using both coherent waves and the stochastic signature of heterogeneities on seismic wavefields. The development of sensitivity kernels modeled using a multiple scattering description of seismic wavefields provide improved models of heterogeneous structures and better connections with alternative volcanological observations. The examples provided will span the Cascadian Arc (Mount St. Helens), Campi Flegrei caldera (Southern Italy) and Deception Island (Antarctica). Advanced imaging techniques, as full-waveform inversions and amplitude interferometry, remain biased in magmatic systems, without an improved understanding of the physics underlying anisotropy, multiple-scattering propagation and shallow-heterogeneity interaction, even if coverage substantially improves.

How to cite: De Siena, L.: Seismic imaging of magmatic systems from the upper mantle to the surface with attenuation and scattering, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1736, https://doi.org/10.5194/egusphere-egu2020-1736, 2020.

Several observables from geological, geophysical and geochemical studies (e.g., seismic velocities, seismic amplitudes/attenuation, isotopic ratios, and gas composition from fumaroles) have indicated that activities at active volcanoes change over different time scales. We have modelled the cause of this spatiotemporal evolution of deformation and seismicity at Campi Flegrei caldera (southern Italy) as two high coda wave attenuation anomalies (at ~ 1 km and ~2-3 km, respectively) separated by ca 0.5-km-thick low seismic attenuation layer “caprock”, which acts as a major blocking interface for the uprising hot magmatic fluids. We have used these observations along with rock physics data as constraints to conduct fluid flow simulation studies to gain more insights into how this active volcano works. We adopt a coupled modelling approach using mechanical (deformation) and fluid low simulators (TOUGH2-FLAC^3D) to simulate seismic slips in the caldera’s computational domain both in isothermal and non-isothermal modes. The method allows us to investigate the roles of both hydromechanical and thermal effects of fluid injections in triggering seismicity at the caldera. The magnitudes of seismicity generated are comparable to the field observations and records of the major seismicity for the caldera in the 1980s.

How to cite: Akande, W. G., Gan, Q., Cornwell, D. G., and De Siena, L.: Modelling Fluid Migration and Seismicity in an Active Volcano: A Case Study of Campi Flegrei Caldera, Southern Italy, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3163, https://doi.org/10.5194/egusphere-egu2020-3163, 2020.

Tacora Volcano (17º43’S – 69º46’W) is a composite stratovolcano that lies at the southernmost end of a 10 km-long volcanic lineament that extends between Chile and Perú. Around Tacora volcano, current thermal manifestations are two active fumarolic fields located at the western flank of the stratovolcano and at the volcano summit, indicating active magma degassing in a shallow hydrothermal system. Beneath Tacora volcano is located the NW Challaviento reverse fault that belongs to the Incapuquio - Challaviento fault system of Middle Eocene age. To complement previous exploration results and conceptual modeling developed by INFINERGEO SPA, seventeen short period seismic stations were installed around Tacora volcano, between August and December 2014. Using the P and S wave arrival times of locally recorded seismicity, a 3D velocity model was determined through a travel time tomography. According with the results, we interpreted high Vp /Vs values as water-saturated areas, corresponding to the recharge zone of Tacora hydrothermal system. In addition, low values of ΔVp/Vp (%) and Vp/Vs ratio represent the location of a gas-saturated magmatic reservoir between sea level and 2 km depth and circulation networks of magmatic-hydrothermal fluids. Low Vp/Vs volumes (magma reservoir / high temperature hydrothermal fluids), the presence of fumarolic fields and surface hydrothermal alteration have a spatial correlation. The above suggests a structural control of the Challaviento fault in the hydrothermal flow as well as a primary influence in the emplacement and location of the magmatic-hydrothermal reservoir. Finally, we present a cluster analysis using the ΔVp/Vp (%) parameter. Through this analysis, we found a method for the identification of a key structure in depth composed by the magma reservoir (low Vp/Vs ratios, low ΔVp/Vp (%)), clay level areas (intermediate values of ΔVp/Vp (%)), and degasification zones (low values of ΔVp/Vp (%)) directly related with the surface thermal manifestations.

How to cite: Comte, D., Pavez, C., Gutierrez, F., and Gaytan, D.: Analysis of the Magmatic – Hydrothermal Volcanic Field of Tacora Volcano, Northern Chile, using Travel Time Tomography, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2028, https://doi.org/10.5194/egusphere-egu2020-2028, 2020.

In this study, we have mapped for the first time robustly the 3D structure of two upper-crustal magmatic reservoirs beneath the active volcanoes Avacha and Koryaksky, which are called “home volcanoes” for Petropavlovsk-Kamchatsky, the main city of Kamchatka (~200,000 inhabitants). These volcanoes represent a serious potential hazard for the city, because they are located at a distance of 25–30 km from the populated areas. A new tomographic model (V_P, V_S, V_P/V_S ratio) was built, for which we used the arrival times of seismic P- and S-waves from almost 5,000 local events, recorded by a permanent network of seismic stations during 2009–2018.The resolution of the derived models was carefully tested by a series of synthetic simulations. Prominent anomalies with extremely high V_P/V_S ratios (up to 2.4) were retrieved directly beneath both volcanoes and interpreted as magma reservoirs containing high degrees of partial melt and/or fluids. Beneath Avacha, the upper limit of the anomaly is located at the depth of ~2 km below the surface. The reservoir appears to be connected to the surface by a neck-shaped anomaly of high V_P/V_S ratio associated with active seismicity, which is interpreted as a magma and fluid conduit. Beneath Koryaksky, the magma related anomaly is deeper: its upper limit is located at a depth of ~ 7 km below the surface. This anomaly is connected with the volcanic coneby a vertical seismicity cluster, which possibly marks the pathway of fluid ascent and degassing. Between the volcanoes, a 2–3 km thick layer of very low V_P and V_S is interpreted as deposits of volcanoclastic sediments. Generally low Vp/Vs ratios in the area between the volcanoes show that the magma reservoirs in the upper crust are not interconnected.

This study was partially supported by the RFBR project # 18-55-52003.

How to cite: Bushenkova, N., Koulakov, I., Senyukov, S., Gordeev, E. I., Huang, H.-H., El Khrepy, S., and Al Arifi, N.: Tomographic images of Avacha and Koryaksky volcanoes in Kamchatka, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4539, https://doi.org/10.5194/egusphere-egu2020-4539, 2020.

Volcanoes and volcanic systems are very dynamic. The influx of new magma, changes in the hydrothermal system, and eruptions produce large changes in the velocity structure. Such changes can be inferred using Time-Dependent Seismic Tomography (TDST), as has been done by multiple authors (e.g. Koulakov et al. 2013, Hobé et al. 2020). Due to the nature of the inversion process inherent to tomographic methods, it is difficult to discern between real and artificial differences between epochs. In TDST, such artificial differences can arise from differences in raypath-geometry (due to differences in station and earthquake distributions), the employed regularization in the inversion process, and errors due to multiple sources (e.g. travel-time picks, and assumptions in the forward model). This study provides two novel ways of inferring the influence of these artificial sources of velocity change in tomographic models: a baseline reconstruction (Hobé et al. 2020) and time-varying reconstructions. These reconstructions are produced for the Krysuvik volcanic system. The velocity differences produced by the "true" data are then compared to those produced in the synthetic reconstructions. We show that the differences in the obtained models cannot solely have been produced artificially and therefore that there must have been significant velocity changes in the area.

References:

Hobé et al. (2020): Imaging the 2010-2011 inflationary source at Krysuvik, SW Iceland, using time-dependent Vp/Vs tomography, WGC 2020, forthcoming

Koulakov et al. (2013): Rapid changes in magma storage beneath the Klyuchevskoy group of volcanoes inferred from time-dependent seismic tomography, J. Volcanol. Geotherm. Res.

How to cite: Hobé, A., Tryggvason, A., and Gudmundsson, O. and the SIL Seismological Group: Discerning Between Real and Artificial Velocity Change in Time-Dependent Seismic Tomography, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20013, https://doi.org/10.5194/egusphere-egu2020-20013, 2020.

Villarrica is one of the most active and dangerous volcanoes in Chile. During the last decade it consisted of a single open vent hosting an active lava lake which produced mild stombolian explosions, persistent tremor and continuous degassing.

We present an analysis of the seismic activity of Villarrica between 2010 and 2012. Periods of increased lava lake activity are characterized by numerous small transient events which exibit a variety of waveforms and spectral characteristics. Statistical analysis of interevent times revealed a periodic occurrence. At comparable volcanic systems (Stromboli, Erebus), such distributions of events indicated unusual periods of activity corresponding to magma injection. Methods of blind signal separation (ICA, PCA) were used to analyse the wavefield. While regional and local tectonic earthquakes can easily be separated, the tremor and transient events from the crater can not.

How to cite: Lehr, J. and Rabbel, W.: Characteristics of seismic activity of Villarrica Volcano, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15005, https://doi.org/10.5194/egusphere-egu2020-15005, 2020.

Passive seismology in volcanically active locations provides a valuable insight into the structural and evolutionary characteristics of subsurface magmatic features. The Irazú-Turrialba Volcanic Complex (ITVC) consists of a twin-system of volcanoes in Costa Rica, located at the south-eastern end of the Central American Volcanic Arc (CAVA). The ITVC represents a noticeable delineation of this subduction arc sequence, influenced by the formation of the Panama microplate and potentially driven by the Central Costa Rican Deformation belt (CCRDB). This volcanic arc is formed by the subduction of the Cocos Plate, beneath the Caribbean plate. This is an interesting twin-volcanic system consisting of the close-system of Irazú, and actively-venting open-system of Turrialba. Utilizing ambient noise tomography (ANT), 3D shear-wave velocity models are retrieved and compared to previously determined major tectonic features at both regional and local scales

Data were collected from 20 temporary broadband seismic stations, forming a network around the ITVC, and supplemented by 45 permanent stations from the regional networks (OVSICORI & RSN). We used the continuous noise readings from vertical components to compute cross-correlation functions. We then used Rayleigh wave group-velocity dispersion curves to perform an inversion to obtain 2D group velocity maps at both regional and local scales. A further inversion step was undertaken to obtain 3D shear-wave velocity models of the regional features of the Central American Volcanic Arc and more local-scale features of the plumbing system beneath the ITVC. Features determined in the inversions are compared to the literature-established, large-scale and local tectonic features, creating an image of the twin-system complex. In particular, we compare the subsurface magmatic features of the ITVC to establish the impact of local and regional faulting on the shape of the internal plumbing structure, and to determine whether ANT can effectively constrain these known tectonic features.

We establish an improved understanding of the ITVC whole-system plumbing, and the regional velocity anomalies attributed to other Costa Rican volcanic systems within the Central American Volcanic Arc and relation to the tectonics.

How to cite: Jiwani-Brown, E. A., Planes, T., Francisco Pacheco, J., Mora, M., and Lupi, M.: Using ambient noise tomography to image tectonic and magmatic features of the Irazú-Turrialba volcanic complex at regional and local scales, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17795, https://doi.org/10.5194/egusphere-egu2020-17795, 2020.

The anelastic attenuation of rocks strongly depends on the contained fluid physical state and saturation. Furthermore, it is more sensitive than elastic parameters to changes in the physical state of materials. In a geologically complex  volcanic context, where fluids play a very important role, anelastic imaging of the subsoil is therefore a very powerful tool for a better understanding of its dynamics.

In this study we present a robust workflow aimed at retrieve accurate 1-D and 3-D anelastic models from the processing of active seismic data, in terms of lateral and depth variations of P-wave quality factors Q_P. This methodology has been applied to data collected during a high resolution active seismic experiment in a very small-scale volcanic volume, the Solfatara crater, within Campi Flegri caldera, Southern Italy. The presented methodology is developed in three distinct steps: 1) the active seismic data have been properly processed and analyzed for measuring the t* attenuation parameter for all possible source-receivers couples. First, the source contribution has been removed by cross-correlating the recorded signal with the sweep function of the Vibroseis, which was the adopted active seismic source. Then, the spectral decay method has been applied in order to compute the t* values. 2) A reference 1-D attenuation model has been retrieved by means of a grid search procedure aiming at finding the 1-D Qp structure that minimizes the residual between the average observed t* and the theoretical t* distributions. The obtained starting reference model allowed to build a preliminary map of t* residuals through which the retrieved t* dataset has been validated. 3) The 15,296 t* measurements have been inverted by means of a linearized, perturbative approach, in a 160 x 160 x 45 m³ tomographic grid.

The retrieved 3-D attenuation model describes the first 30 m depths of Solfatara volcano as composed of very high attenuating materials, with Qp values ranging between 5 and 40. The very low Qp values, correlated with low Vp values retrieved by a previous tomographic work carried out in the area, indicate the low consolidation degree of very superficial volcanic materials of Solfatara volcano. Finally, in the NE part of the crater, lower attenuating bodies have been imaged: it is a further hint for characterizing this area of the volcano as the shallow release of the CO₂ plume through the main fumaroles of the crater.

How to cite: Russo, G., Serlenga, V., De Landro, G., Amoroso, O., Festa, G., and Zollo, A.: High Resolution Attenuation Images From Active Seismic Data: The Case Study of Solfatara Volcano (Southern Italy), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10847, https://doi.org/10.5194/egusphere-egu2020-10847, 2020.

Fogo and Brava are part of the south-western chain of the Cape Verde archipelago, which is believed to originate from a mantle plume. The two islands are located about 18 km apart from each other. Only Fogo experienced historic eruptions at intervals of about 20 years, with the last eruption from November 2014 to February 2015. In contrast to Fogo, Brava shows a high seismic activity. In our study we focus on the characterization of the seismicity in the region. We employ multi-array techniques to study the seismic activity, as many events are located offshore. Additionally, arrays are well suited for the analysis of volcano-related seismic signals without clear onset of phases. From January 2017 to January 2018 we operated a network of three seismic arrays (two on Fogo, one on Brava) and seven single short-period stations (five on Fogo, two on Brava). The arrays consist of 4 broad-band and 6 short-period stations each and are shaped circularly with an aperture of approximately 700 m. We apply a time-domain array analysis to locate seismic events. This approach is computationally more expensive than a traditional f-k analysis, but allows for a higher flexibility in the selection of relevant time windows to calculate the beam energy. For the analysis in the time-domain, traces are first shifted and then cut to suitable time windows to determine the energy stack as a function of horizontal slowness.

For a single array, epicentral distances can be estimated from arrival-time differences between S- and P-waves, by assuming a suitable velocity structure. However, with two or more arrays, epicenters can be obtained directly from the intersecting beams. The technique is applied to earthquakes as well as to hybrid events. During 2017 the seismicity is clearly dominated by volcano-tectonic earthquakes, mainly originating beneath and around Brava. Additionally we observe hybrid events on Fogo, which are characterized by a transition from high (20-40 Hz) to low (1-10 Hz) frequencies. The events lack clear phases, although they often exhibit a relatively sharp onset. These features provide ideal conditions for the application of the multi-array analysis. The hybrid events originate in the Chã das Caldeiras region, a collapse scar surrounding the present-day Fogo volcano, and are likely related to rock-fall events.

How to cite: Leva, C., Rümpker, G., and Wölbern, I.: Analyzing earthquakes and hybrid events on Fogo and Brava, Cape Verde, with multiple arrays, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2676, https://doi.org/10.5194/egusphere-egu2020-2676, 2020.

Previous studies have found discrepancies concerning the seismic radiation between planar and curved faults; moment tensor (MT) interpretations, seismic moment estimation and waveforms change dramatically when the rupture is not planar. Therefore, assuming a point source on a planar fault for earthquakes in volcanic environments can be an oversimplification that needs to be addressed if we observe some seismological clues. First, we study waveforms for LP events at Etna. To explain these waveforms we propose a full-ring rupture with an inner net movement of magma, in in contrast to the planar fault approach that returns a pulsating rupture. Second, we study MT inversions for the biggest earthquakes during the 2014-2015 collapse of the Bardarbunga caldera, which show non-double couple solutions, with vertical compression axis. We calculate synthetic seismograms for partial-ring ruptures using an “ideal” seismic network, and one emulating the existing monitoring network at Bardarbunga. Observations using distal stations can return a better-constrained seismic moment, but they fail to characterise the dynamics involved. On the other hand, using proximal stations we obtain a reliable representation of the forces involved; however, the seismic moment is systematically overestimated due to the proximity to the curved source and the corresponding focussing effects. Finally, we correct the area of rupture due to fault shape to estimate the real cumulative seismic moment during the caldera collapse. The result shows a closer relationship between seismic and geodetic moment.

How to cite: Contreras Arratia, R. and Neuberg, J.: Applying seismic ring-fault models to real case scenarios, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-552, https://doi.org/10.5194/egusphere-egu2020-552, 2020.

The signals preceding and accompanying phreatic eruptions, although observed on many volcanoes, are still not very well understood. As this type of eruption can have severe consequences, we need to understand the processes and the observed seismic signals leading up to these eruptions. Using seismic broadband instruments, we can detect signals in a wide frequency range, and careful analysis and modelling of these data can help us understand these processes. Phreatic eruptions are often accompanied, and sometimes preceded, by Very Long Period (VLP) seismic signals. These signals are caused by sudden pressure changes inside the volcanic system and in hydrothermal environments these pressure changes and, therefore, observed VLPs are attributed to the sudden expansion of water-filled cracks by vapourisation due to heat flow from the underlying magma body. 
However previous studies consider pure water-water systems which sometimes assume unrealistic pressure-temperature changes in the system to produce a violent phase change from water to vapour. As there are instances of significant amounts of CO₂ measured within hydrothermal systems, we model how a sudden injection of CO₂ into the hydrothermal system, which would easily allow for explosive phase change could trigger the observed VLPs. Further, we show how poroelastic medium responds to such a source.

How to cite: Sindija, D. and Neuberg, J.: Seismo-volcanic source mechanism in White Island's hydrothermal system, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5737, https://doi.org/10.5194/egusphere-egu2020-5737, 2020.

Ebeko is a small (1156 m a.s.l) andesitic volcano located in the northern part of Paramushir island of Kurile Island Arc. It is not well studied but in fact represents the most active volcano of the Kuriles  with > 10 eruptions recorded in the 20th century.  All historical eruptions of the volcano had similar style. They were purely explosive, mild (VEI 1 – 2) series of frequent short-lived outbursts of ash and bombs with eruptive clouds up to 3 km high. Some of the outbursts were more extended in time (lasted minutes-hours) and produced mostly fine ash. Common explosions occurred in the summit area of the volcano which characterized by strong hydrothermal activity and multiple fumaroles depositing sulfur. Each eruption produced broad, shallow craters surrounded by low rims of the ejected material. Commonly the craters are later occupied by shallow lakes.

 In 2019 we realized a field work to investigate the most recent eruptive activity of Ebeko that commenced in 2016.  We installed seismometers, monitoring cameras and recorded the terrain using unmanned aerial systems (UAS) together with optical and infrared cameras. The drone data shows dimensions and structures of the newly forming crater and shows deposition of erupted materials. Ejected material was probed and analysed. It is represented by ash and bread crust bombs composed of moderately vesicular two pyroxene andesite with glassy crusts. We found evidence for recycling and rewelding of ash shown by the clastic domains, which are enclosed / mantled by coherent lava. The eruptions of Ebeko volcano were in part phreatic (hydrothermal) and in part magmatic / phreatomagmatic (vulcanian in a broad sense). Mechanism of this (and probably of some other eruptions) can be explained by shallow intrusions of small batches of strongly crystallized andesitic magma into water-saturated hydrothermally altered rocks composing the volcano summit. We suggest a model of the Ebeko eruptions, where new batches of fresh magma incorporate and amalgamate previously erupted fresh material.

How to cite: Belousov, A., Belousobva, M., Walter, T., and Auer, A.: Vulcanian/hydrothermal eruptions of Ebeko volcano, Kurile Islands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6027, https://doi.org/10.5194/egusphere-egu2020-6027, 2020.

Currently thousands of seismic sensors, managed by different national and international institutions, are deployed throughout the planet. In the last decades, thanks to scientific and technological advances, broadband sensors are being produced at costs affordable for most institutions that operate a seismic network. At the same time, advances in nanotechnology led to the development of MEMS sensors which allowed the development of accelerometers of very reduced dimensions and low costs. The seismic data obtained by the commercial MEMS sensors, can be sampled, synchronized, stored and transmitted through low cost microcontrollers such as RaspberryPi or Arduino. This allows the development of a complete seismic station of very small size and cost with respect to the traditional ones, although of lower sensitivity and quality.

Since 2019, Instituto Volcanológico de Canaria (INVOLCAN) is developing a low cost seismic network: the Red Sísmica Escolar Canaria (RESECAN, Scholar Canarian Seismic Network) with multiple purposes. The main aims of RESECAN are:

• supporting the teaching of geosciences
• promoting the scientific vocation
• strengthening the resilience of the Canarian communities by improving awareness of the Canary volcanism and the associated hazards.

The project aims at realizing and distributing low-cost stations in various educational institutions of the Canary Islands, complementing them with didactic material on the topics of seismology and volcanology. Each school will be able to access the data of its own station, as well as other centers, being able to locate some of the recorded earthquakes. The data recorded by RESECAN will be fully integrated with the data of the Red Sísmica Canaria (C7), a permanent broadband seismic network operated by INVOLCAN. This will make RESECAN also an instrument of scientific interest able to contribute effectively to the volcanic monitoring of the Canary Islands, strengthening its resilience in facing future volcanic emergencies.

How to cite: Domínguez, V., Barrancos, J., D'Auria, L., and Peréz, N. M.: The scholar seismic network of Tenerife: technical and scientific issues, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4796, https://doi.org/10.5194/egusphere-egu2020-4796, 2020.

Since 2004, the Instituto Tecnológico y de Energías Renovables (ITER) in collaboration, since 2011, with the Instituto Volcanológico de Canarias (INVOLCAN), are monitoring Canary Islands archipelago with a network of more than 30 differential GPS stations. Specifically, in Tenerife island alone there are 12 permanent GPS receivers. Data are processed automatically using Bernese software, constituting an important tool for the geodetic monitoring of Tenerife.

Since 2016, the volcanic system of Tenerife is experiencing a hydrothermal unrest, with a marked increase of the diffuse CO₂ flux from the crater of Mt. Teide, the major volcanic edifice of the island. This increased flux is likely to be related to the injection of fluids of magmatic origin within the hydrothermal system of Tenerife. The subsequent pressurization of this system is reflected also by the increase in the background microseismicity observed since July 2017. Until now, the GPS network has not recorded significant ground deformation above the instrumental error.

With the aim of improving the geodetic monitoring of Tenerife, detecting possible small ground deformation below the sensitivity of the GPS network, INVOLCAN has recently started deploying, since June 2019, high-gain tiltmeters (Jewell Instruments A603-C) in the surrounding of Mt. Teide. Currently the tiltmetric network consists of 3 tiltmeters, located close to existing seismic or GPS stations. Data are automatically downloaded via UMTS connection and processed daily.

The nominal sensitivity of such instruments is less than 2.5 nradians, hence their installation and calibration require very careful operations. The sensors are equipped with leveling worm-gear feet to guarantee a perfect levelling. However, the high sensitivity of the instrumentation makes adjustments made manually totally useless. The tilt change caused by the weight of the human operator during the levelling is enough to drive the instrument out of scale. For this reason, INVOLCAN developed a robotic system to perform the required adjustments from remote. The system is based on Arduino Mega 2560, driving two servomotors to adjust the leveling worm-gears. Another servomotor allows switching the gain level. The system can be accessed and operated through an internal web page, which allows driving the servomotors and checking the leveling of the tiltmeter platform by using an Arduino Ethernet.

How to cite: Barrancos, J., Przeor, M., D'Auria, L., Cabrera, I., Montañez, A. C., Hernández, P. A., and Pérez, N. M.: The new tiltmetric network of Tenerife: technical and scientific issues, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4819, https://doi.org/10.5194/egusphere-egu2020-4819, 2020.

Nowadays, scientific surveys to evaluate the thermal energy release from volcanoes are very tedious and involve performing numerous measure points to determine the heat flux of a specific area. This study tests a new method to calculate the heat flux from Teide inner crater using thermal images without the need for on-site heat flow campaigns. So far, panoramic infrared images of the study area and infrared images of thermal anomaly zones at a distance of 1 meter have been carried out in a monthly basis with a FLIR T660 thermal camera. Soil temperature of study area was also measured with a K-type thermocouple in order to compare the results between the temperature measured with the thermocouple and the one obtained by the thermal camera. The method developed in Marotta et al. 2019 to determine the heat flux from thermal images will be adapted to the peculiarities of the Teide stratovolcano, such as the topography of the inner crater. To check the reliability of the method, values obtained with a heat flux sensor, by means of the temperature gradient and those resulting from the application of the developed method are compared. Finally, the error associated to the use of thermography at a greater distance to calculate heat flux is analysed by comparing the results obtained when applying the method with thermographic images taken at 1 meter with the results obtained when applying it with the panoramic thermal images of the crater, taken at approximately 50 metres.

How to cite: Montañez Hernández, A. C., Marotta, E., Padilla, G. D., Peluso, R., Hernández, P. A., Prieto, A., Morales González, F. A., Domínguez, V., Barrancos Martínez, J., Peréz, N. M., and D'Auria, L.: Heat flux measurements at Teide Volcano, Tenerife, Canary Islands, by means of thermal imaging, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4692, https://doi.org/10.5194/egusphere-egu2020-4692, 2020.

In the previous EGU 2019 we presented the different data acquired by the multi-disciplinary deformation networks during the eruption of Etna on 24 December 2018, when the volcano was suddenly penetrated by a violent dyke intrusion. An eruptive fissure opened and continued to propagate southward for more than 10 hours. The situation created the fear of possible serious consequences of feeding a lava flow even at medium-low altitudes, therefore potentially hazardous for the villages and infrastructures located there. However, the propagation stopped and lava flows finished on 25 December.

In this updated study we present the effort made to model the complex eruptive process characterized by two attempts of intrusion. We inferred a first dyke starting from the sea level depth with an increasing of its dimension in the shallower part. Successively and until the early hours of 25 December, we revealed a second attempt of intrusion characterized by a dyke with a powerful opening with respect to the first dyke but that, fortunately, did not reach the free surface. We describe how different types of continuous deformation data provide complementary information on the ongoing process allowing us to model the fast intrusive process. In particular, the high-precision borehole instruments (strainmeters and tiltmeters) provided a robust early warning; the displacement field measured by high-rate GPS allowed obtaining an early but also reliable model of the source. Finally, the integration of all the continuous data constrained a more detailed and complete model and its time evolution able to represent the complex process leading to this flank eruption.

How to cite: Aloisi, M., Bonaccorso, A., Cannavò, F., Currenti, G., and Gambino, S.: Modeling of the Dec 24, 2018 eruptive intrusion at Etna volcano by data of multi-disciplinary continuous deformation networks (CGPS, borehole strainmeters and tiltmeters), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2962, https://doi.org/10.5194/egusphere-egu2020-2962, 2020.

GNSS campaign measurements are often used for also volcano monitoring. The most important reason for this is that the permanent stations near the volcano are costly and likely to be damaged after the eruption. Often, even campaign measurements are risky near an active volcano. On the other hand, it would be low risky and low costly to make campaign measurements distant from volcano activities and eruptions. In this study, in order to expound the analysis results, we constituted our global test area using five IGS stations around five active volcano eruptions over 2019 via the Smithsonian Institute Global Volcanism Program. The data archives of the International GNSS service (IGS) and the time series of the Jet Propulsion Laboratory (JPL) were used for the purpose. And then we decimated the continuous data down to monthly and four monthly sampled GPS campaign time series. We also generated random values of ±3 mm for possible antenna setup errors. We tested whether the velocities obtained from monthly and four monthly solutions differ significantly from the velocities derived from daily solutions. As a result, we concluded on monthly velocities that horizontal components are compatible completely and 80% of the vertical components are compatible. We also concluded on four monthly velocities that 65% of the horizontal components are compatible and vertical components are compatible completely. We explained the utilization of campaign measurements in volcano monitoring by examining the effect of the distance between the stations and volcanoes on the results obtained.

Keywords: Volcano Monitoring, GNSS Campaign Measurements.

How to cite: Turen, Z., Turen, Y., and Erol, T.: Usability of velocities of GNSS campaign measurements on volcano monitoring depending distance between station and volcano, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4119, https://doi.org/10.5194/egusphere-egu2020-4119, 2020.

Since 2000 an intense development of remote stations, transmission device, data processing software and tools for time series analysis aimed to high rate GNSS surveillance and monitoring of active Italian volcanoes has been realized or implemented at INGV. Since the very first case study (the 2001 Mt.Etna’s eruption) to the 2019 paroxysms of Stromboli, many observations and a lot of specific experience has been achieved on Italian active volcanoes (Etna, Stromboli) to track rapidly developing deformation patterns associated to different volcanic processes, as dike intrusions or explosive activity. Moreover, we here describe the hardware and software improvements for High Rate GNSS monitoring network with a specific attention to the recently realized network in the densely populated area of the Campi Flegrei caldera.

How to cite: Mattia, M., Bruno, V., Cannavò, F., Rossi, M., Pellegrino, D., Pulvirenti, M., Pandolfo, F., Dolce, M., and De Martino, P.: High Rate Real Time GNSS monitoring of active volcanoes: 20 years of applications to Italian volcanoes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4646, https://doi.org/10.5194/egusphere-egu2020-4646, 2020.

RATIONALE

Gravity investigation of volcanoes is difficult due to their usual location in rugged topographic areas, where lack of access hardly offers possibility for adequate observations coverage.

In the absence of appropriate constraints this might have important consequences on the interpretation of the survey results.

BACKGROUND

Located in the inner part of the bending zone of East Carpathians, Romania, Ciomadul volcano represents the end member of the Neogene to Quaternary volcanism in the Carpathian - Pannonian Region. This cluster of dacitic domes last erupted about 30 ka ago, and there are authors claiming it might become active, based on indirect evidence on the presence of a magma chamber in the upper crust beneath it.

Inversion of relatively recent acquired gravity data outlined an extended mass deficit below central volcano initially interpreted as a magma chamber, in apparent agreement with previous MTS works unveiling an electrical resistivity low beneath volcano. The gradual decrease of density towards the inner (hotter?) part of the source seems to be consistent with hypothesis of a cooling body.

However, the overall geometry and in-depth extent of the density zone with values corresponding to volcanic rocks is not consistent with accepted structural models for such volcanoes, mainly developed on the topography.

Besides, the extreme density values predicted were never encountered on samples collected from outcrops, and according to literature there is no increase in temperature able to provide the density lowering shown by inversion.

Finally, the idea of magma chamber at relatively shallow depths may be hardly accepted because it would generate strong geothermal manifestations at the surface (e.g. geysers), nowhere encountered.

APPROACH & RESULTS

For better understanding/interpreting the inversion results, limitations of the approach were studied by computing/inverting the gravity effect of synthetic sources. Fluid-filled vertical volcano conduits of variable size/content (but always dimensioned bellow the sampling step of the gravity signal provided by the survey coverage) were subject to study.

The research showed that inversion was not able to accurately predict the parameters of the source in any simulation. Basic 2D geometry of the volcano conduit with step density change along the edges is replaced by a 3D broadly extended body with gradual decrease of density towards its inner part. The larger the cavity, the smaller densities may occur. Some densities outside the source model range are also predicted, and a pseudo-mass excess may be inappropriately generated above the upper end of the conduit.

CONSEQUENCES

Following the simulations, the density model of Ciomadul volcano was fully revised by using an iterative 3D forward modelling. The new model unveils peculiarities of a largely developed plumbing system, partly open to magma access, but does not support any longer the hypothesis of a magma reservoir in the upper crust beneath Ciomadul.

SPECULATIONS

Given the above-mentioned aspects, we may assume that former solution of the MT data inversion was also biased by data scarcity that inherently led to the integration of local effects of several narrow fluid-filled conduits into a unique electrical resistivity anomaly interpreted as a magma chamber.

How to cite: Besutiu, L., Zlagnean, L., Isac, A., and Romanescu, D.: Implications of the observations scarcity on the gravity data inversion within volcanic areas. Ciomadul volcano, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1371, https://doi.org/10.5194/egusphere-egu2020-1371, 2020.

Muography is the technique to observe the inner density structure of volcano by using cosmic-ray muons. In previous study, three-dimensional density reconstruction was attempted by using muography data from multiple directions (Tanaka et al., 2010, Rosas-Carbajal et al., 2017), but they could only get a few hundred meters of spatial resolution. To improve the spatial resolution, Nagahara and Miyamoto (2018) suggested omni-directional muography, putting ten or more observation points to surround the volcano.

  There are two types of three-dimensional density reconstruction methods from omni-directional muography observations, the linear inversion method (Rosas-Carbajal et al., 2017) and the filtered back projection (FBP) method (Nagahara and Miyamoto, 2018). The former is applicable even when the number of observation points is small, but requires many arbitrary parameters, while the latter has the characteristic that no arbitrary parameters are required but a certain number of observation points is required.

In this presentation, we show the results of a comparison between the two methods in simulation.

How to cite: Miyamoto, S. and Nagahara, S.: Three-dimensional Density Reconstruction Analysis Method for Omni-directional Muography, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13356, https://doi.org/10.5194/egusphere-egu2020-13356, 2020.

Muography is the method of determining inner bulk density structures of volcano by using cosmic-ray muons. When we get muography image from one direction, there is no spatial resolution along muon path. However, by observing from multiple directions, three-dimensional density structure can be obtained. In recent years, three-dimensional density reconstruction using two or three muographic images has been performed (Tanaka et al., 2010, Rosas-Carbajal et al., 2017), but they obtained three-dimensional density structure with only several hundreds of meters spatial resolution due to lack of information. To improve the spatial resolution, we suggested “omni-directional muography”, putting ten or more observation points to surround the volcano (Nagahara and Miyamoto, 2018), and we estimated its feasibility by simulation. On the other hand, in recent years, detectors for muography have become larger (Morishima et al., 2018, Olah et al., 2019), and a detector necessary for omni-directional muography can be prepared. Therefore, we demonstrated omni-directional muography in Omuro-yama Scoria cone, Izu, Japan.

Omuro-yama is a scoria cone formed by a single eruption. The mountain baseline diameter is about 1 kilometer and the height from base is 300 meters. The eruption has been investigated by sediment surveys (Koyano et al.,1996). This mountain has many advantages that are suitable for omnidirectional muography. 1) no mountains around Omuroyama, so no contamination of muon path except in the Omuroyama body. 2) easy to access the detector sites, 3) enough statistics of penetrating muons because of size. We started observing Omuro-yama in 2018. In 2018, we observed for two months from three directions using a 0.01 square meter emulsion detector. In 2019, we performed a three-month observation from eight directions using a 0.02 square meter emulsion detector. As a result of preliminary three-dimensional density reconstruction using the analysis method of Nishiyama et al. (2014), a region with a low density over 200 m in diameter was found under the crater. Currently, we are considering this result carefully. We plan to observe from 30 directions by 2021, including 11 points.

In this presentation, we report the latest analysis results of observation results from 11 directions and future plan.

How to cite: Nagahara, S., Miyamoto, S., Morishima, K., Nakano, T., Koyama, M., and Suzuki, Y.: Demonstration of 11-directional muography in Omuro-yama Scoria cone, Izu, Japan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12807, https://doi.org/10.5194/egusphere-egu2020-12807, 2020.

The Dutch islands of Saba and St. Eustatius are located in the far north of the Lesser Antilles arc, a subduction zone hosting seventeen active volcanoes. The volcanoes of Saba and St. Eustatius: Mount Scenery and The Quill, are currently monitored using a ground based network, operated by KNMI, comprising broadband seismometers, continuous GNNS stations and a temperature sensor in the hotspring on Saba. Satellite observations are complementary to these ground based measurements and are especially useful for these volcanoes as they are located in a remote area.

InSAR observations can be used to monitor surface deformation of volcanoes. Because considerable areas are observed with each satellite passing, subtle signals, which may be missed by continuously recording ground based GNSS stations, may be picked up. However, research using TerraSAR X-band and Sentinel-1 C-band data in the Caribbean region has shown that monitoring with InSAR is hampered due to the loss of radar coherence caused by tropical rain forest covering the Caribbean islands. Moreover many of the islands have steep slopes resulting in layover and shadowing effects. We generate interferograms and time series of ALOS-2 L-band data and Sentinel C-band data to identify which mission is more suitable for long term monitoring of the volcanoes on Saba and St. Eustatius.

The Terra satellite carries five instruments that take coincident measurements of the Earth system, among those is MODIS: a Moderate Resolution Imaging Spectroradiometer. MODIS data are used by MIROVA (Middle Infrared Observation of Volcanic Activity): an automatic volcano hot spot detection system, able to detect, locate and quantify thermal anomalies in near real-time, by providing, infrared images and thermal flux time-series on over 200 volcanoes worldwide (www.mirovaweb.it). A volcano in a non-eruptive state such as Mount Scenery on Saba would typically be checked on a monthly basis. As Saba is a very small island (12 km2) automatic triggering is challenging and therefore observations are still in a test phase.

Satellite observations can be a useful addition to the ground based monitoring of small island volcanoes although small adaptions to currently used techniques may be needed. As such they may be crucial for timely warning of local authorities in case of unrest at a remote volcano.

How to cite: de Zeeuw - van Dalfsen, E., Korevaar, A., van Leijen, F., Sleeman, R., and Coppola, D.: Satellite observations as a tool to monitor the volcanoes of Saba and St. Eustatius, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3439, https://doi.org/10.5194/egusphere-egu2020-3439, 2020.

Located about 30 km north of the city of Yogyakarta, Merapi is considered as one of the most dangerous volcano of Indonesia with 3000 to 5000 fatalities since 1672 and about two million people living at less than 30 km from the crater. The recent eruptive history of Merapi is characterized by two eruptive styles: 1) recurrent effusive growth of viscous lava domes, with gravitational collapses producing pyroclastic flows known as « Merapi-type nuées ardentes » (VEI 2); 2) more exceptional explosive eruptions of relatively large size (VEI 3-4), associated with column collapse pyroclastic flows reaching distances larger than 15 km from the summit. The eruptive periodicity is 4 to 5 years for the effusive events and 50 to 100 years for the explosive ones. The last explosive events (VEI 3-4) occurred in November 2010 and opened a 500m wide and 250m deep crater. After the 2010 eruption, the activity has been reduced. We used TerraSAR-X data to characterize eruptive deposits emplaced during the 2010 event as well as sudden destabilization of crater walls. The activity increased significantly during the spring of 2018 when several phreatic eruptions were recorded with ash emission reaching an elevation of more than 5 kilometers. The 11^th of August 2018 a new dome was observed inside the summit crater, thus marking the start of a new phase of effusive activity. It is essential to be able to quantitatively follow the temporal evolution of the dome shape and volume through time as its potential destabilisation would produce pyroclastic flow on the volcano flank. A time series of five tri-stereo Pleiades optical images, acquired between February and September 2019, is used to produce High Resolution DEMs of Merapi summit area with a spatial resolution of 3 m and a vertical precision of 1 m. By using a DEM derived from Pleiades stereo images acquired in April 2013 as a reference, the dome volume evolution through time is estimated. We show that the dome had already reached a volume around 0.5 Mm³ (+- 0.02Mm³) end of February 2019 corresponding to a mean effusive rate of 3000 m³/day during 6 months and that its size remained constant after February 2019. These results are consistent with volume estimations derived from drone measurements. However DEMs derived from Pleiades images enable to monitor a larger area and reveal accumulation of eruptive deposits due to dome destabilization a few hundreds of meters below the dome. The magma effusive rate thus remained significant but was reduced to 250 m³/day from February to September 2019.

How to cite: Pinel, V., Putra, R., Solikhin, A., Beauducel, F., Santoso, A. B., and Humaida, H.: Tracking the evolution of the Merapi volcano crater area by high-resolution satellite imagery, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5415, https://doi.org/10.5194/egusphere-egu2020-5415, 2020.

Growing volcanic islands and lava domes become structurally unstable, associated with sectoral collapses, explosive volcanism and related hazards. We present the rare case of a growing and collapsing lava dome at Kadovar Volcano. This small inhabited volcanic island is part of the Schouten Islands, at the western end of the Bismarck Volcanic Arc, north of Papua New Guinea. The first confirmed historical eruption at Kadovar began on 5 January 2018 and was monitored by synthetic aperture radar (SAR), thermal and optical satellite sensors. Our analysis of the different remote sensing data shows that Kadovar began a new episode of volcanic activity at the central crater and then also at the eastern coast of the island, where we monitored the birth of a new emerging lava dome. We analyse changes occurring on the island and the littoral lava dome and identify that after dome growth (with an area of ~2,000 m² area week), parts of the island and about 80% of the littoral lava dome collapsed eastwardly into the ocean on 9 February 2018. This collapse caused small tsunami waves that hit the neighbouring islands. The littoral lava dome then re-grew at a slower rate (of ~285 m² per week) and reached a final area of ~40,000 m² by 2 May 2018, which corresponds to an estimated subaerial volume of the lava dome of ~400,000 m³. This study provides details on the rapid growth and collapse of a peripheral lava dome and a destabilization episode in an island and dome sector. The importance of remote sensing data for the monitoring and investigation of remote volcanic islands is demonstrated.

How to cite: Plank, S., Walter, T., Martinis, S., and Cesca, S.: Multi-sensor satellite imagery analysis of the growth and collapse of a littoral lava dome during the 2018/19 eruption of Kadovar Volcano, Papua New Guinea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1423, https://doi.org/10.5194/egusphere-egu2020-1423, 2020.

Abstract:

A major landslide occurred in 2014 on the east flank of the inner Askja caldera, Iceland, causing massive material redistributions and a tsunami hazard that affected even opposite shores of the caldera lake. The landslide has left a scar on the caldera wall, and was followed by mud flows, depositing mixed materials and un-roofing hydrothermally active sites. In an attempt to analyze the lithological and geomorphological consequences of the 2014 Askja landslide, we have realized a series of unmanned aerial system (UAS) surveys 2015-2019 carrying different sensors. From these drone campaigns we investigated the RGB, RedEdge, Near Infrared and thermal Infrared imagery. In addition, ground-based hyperspectral measurements in the wavelength range 350-2500 nm were acquired in 2019 with a field spectroradiometer to get more detailed spectral information of the surface materials. Here we proposed a geo-data-science approach to map and identify different types of deposits and structures by using Principal Component Analysis (PCA) and classification approaches. Specifically, we tested different supervised and unsupervised classification methods to identify the different types of materials found in the landslide area. For the supervised classification approaches, we defined regions of interest (ROI) to train the classifier and to detect those regions with similar patterns and materials. At the end, we can clearly distinguish 5-6 different classes in the UAS data and compare to ground-based spectral and thermal infrared signals. Results suggest that the 2014 landslide source region is composed of a mixed material class, with sharp contrasts in the north, reaching the lake in the west. This re-deposited material is located in an area of hydrothermal alteration and also encircled by the material class associated with thermal anomalies. By comparing the results from the classifications to the in-situ spectral measurements, we were able to further interpret on the involved types of materials and the degree of hydrothermal alteration. At distance to the landslide we find that the materials differ, signaling virtual absence of major landslides entering the lake and minor alteration. As the study demonstrates the success of the supervised classification approach for material mobilization in the inner caldera wall and identification of mixed and non-mixed materials, important implications for hazard assessment in the Askja caldera and elsewhere can be drawn.

How to cite: Marzban, P., Mueller, D., Klos, F., Hildebrand, C., Bredemeyer, S., Witt, T., Walter, T. R., and Chabrillat, S.: Detailed Spectral Analysis of Askja 2014 Landslide Area: From Satellites to the Ground-based Measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4910, https://doi.org/10.5194/egusphere-egu2020-4910, 2020.

Since its last flank eruption in 2011-2012, the activity of Nyamulagira volcano (Virunga Volcanic Province, DR Congo) has been characterized by pit crater collapse, lava fountaining and intermittent lava lake activity. No more flank eruption occurred since this concentration of the eruptive activity at the summit. As Nyamulagira is located in a remote area of the Virunga National Park, field observations remain limited. As a consequence, observations of the ongoing changes at the summit of the volcano mostly rely on satellite observations. Time-series of very-high to high resolution optical and SAR amplitude images for instance provide the required information to follow the evolution of the pit crater, from the first signs of collapse to its filling by lava. Hotspot detection from the combination of MODIS and Landsat-type images (including Sentinel-2) allows detecting the first appearance of lava in the pit crater and describing the intermittence of the lava lake activity that has developed since 2014. The OMI and TROPOMI instruments allow measuring the evolution of SO₂ emissions. Thanks to few aerial surveys and the use of Unoccupied Aerial Systems (UAS or “drone”), the volume of lava accumulated within the pit crater since 2014 was measured. All these satellite and drone-based observations were finally compared with the known historical eruptive activity, in terms of lava and gas discharge rates and type of summit eruptive activity. The presented work shows how combining various remote sensing techniques that make use of recent generations of satellite images and UAS acquisitions allow a detailed interpretation of the evolution of the volcano, even when field access is an issue.

How to cite: Smets, B., Subira, J., Dille, A., Theys, N., Broekmans, F., Nobile, A., d'Oreye, N., and Kervyn, F.: Study of the 2012-2020 pit crater evolution in the summit caldera of Nyamulagira volcano using multiple satellite sensors and UAS-based photogrammetry, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19354, https://doi.org/10.5194/egusphere-egu2020-19354, 2020.

Volcanoes are increasingly better monitored around the world. Nonetheless, the detection and monitoring of volcanic ash plumes remains difficult, especially in remote areas. Intense electrical activity and lightning in volcanic plumes suggests that electrical monitoring of active volcanoes can aid the detection of ash emissions in near real-time. Current very low frequency and wide-band thunderstorm networks have proven to be able to detect plumes of large magnitude. However, the time delay and the relatively high number of non-detected explosive episodes show that the applicability of these systems to the detection of smaller (and often more frequent) ash-rich explosive events is limited. Here we use a different type of thunderstorm detector to observe electrical discharges generated by the persistent Vulcanian activity of Minamidake crater at Sakurajima volcano in Japan. The sensors consist of two antennas that measure the induced current due to the change in electric field with time. In contrast to the current thunderstorm networks, these sensors measure within the extremely low frequency range (1-45 Hz) and can detect lightning up to 35 kilometres distance.

Two detectors were installed at a distance of 3 and 4 kilometres from Minamidake crater and recorded almost continuously since July 2018. Within this period, the ash plumes reached a maximum height of 5.5 kilometres above the crater rim. Using a volcanic lightning detection algorithm and the catalogue of volcanic explosions compiled by the Japan Meteorological Agency (JMA), the number of electrical discharges was determined for each individual explosive event. In addition, the start of electrical discharges was compared to the eruption onset estimated by the JMA.

Preliminary results show that the detector closest to the crater had the highest detection efficiency. It detected electrical discharges during 60% of the eruptions listed by the JMA. This is significantly higher than for the World Wide Lightning Location Network, which detected electrical discharges (in the very low frequency range) within 20 kilometres of Sakurajima for less than 0.005% of the eruptions. Furthermore, the results show that for 40% of the detected eruptions, electrical discharges were detected before the estimated JMA timing. Hence, electrical discharges can mark the inception of the explosion with a higher precision and are an indication of ash emission. This demonstrates the value of the cost-effective sensors used here as a monitoring tool at active volcanoes.

How to cite: Vossen, C. E. J., Cimarelli, C., Bennett, A. J., Geisler, A., Gaudin, D., Miki, D., Iguchi, M., and Dingwell, D. B.: Extremely low frequency detection of electrical discharges at Minamidake crater (Sakurajima volcano, Japan), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5298, https://doi.org/10.5194/egusphere-egu2020-5298, 2020.

The Colima Volcanic Complex is located within the central portion of the Colima Rift in the occidental part of Mexico. This volcanic structure is composed of two stratovolcanoes; the extinct Nevado de Colima and Volcán de Fuego. The latter is considered the most active volcano in the country which volcanism is related to the subduction of two oceanic plates with different slab angles that cause a gap between them just beneath the complex. Different methodologies have been carried out in this zone; seismic tomography and potential field data modelling to constraint a geophysical model that contributes the better understanding of the magmatic system and the geothermal energy potential.

 To reduce non-uniqueness of the previous models, a campaign was realized in September 2019 where 10 broadband magnetotelluric soundings were acquired and further process and inversion in conjunction with previous data was done. The distortion analysis for the data set presented a 1D behavior for the first kilometers and 2D and 3D behavior at higher depths suggesting the need of a 2D or 3D approach for the inversion. The electric strike calculation suggests the rotation of the impedance tensor so that the non-linear conjugated gradients algorithm of Rodi & Mackie (2001) was applied along three profiles perpendicular to the principal structures to obtain 2D resistivity models.

The inversion results range from 3.4 to 5.6 RMS error and show for all the profiles good correlation for the surface lithology, the principal normal faults which define the graben structures filled with pyroclastic deposits and alluvial sediments and a high resistive basement. For major depths, the northern profile shows a vertical extensive conductive body which connect to an upper conductive layer. So do the central profile, south the Volcán de Fuego vent but the superficial body is more conductive which can correlate with previous models as a magma reservoir approximately at a 2 km depth.

How to cite: Romo Lozano, H. M. and Arzate Flores, J. A.: Resistivity model for the Colima Volcanic Complex from magnetotelluric observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6188, https://doi.org/10.5194/egusphere-egu2020-6188, 2020.

Detect, locate and characterize eruptions in real-time is fundamental to monitor volcanic activity. Here we present an automatic system able to discover and identify the main types of eruptive activities by exploiting infrared images acquired by the thermal cameras installed around Mount Etna volcano. The system, which employs the machine learning approach, is based on a decision tree tool and a bag of words-based classifier. The decision tree provides information on the visibility level of the monitored area, while the bag of words-based classifiers detects the onset of the eruptive activity and recognize the eruption type among either explosion and/or lava flow or plume. Thus, applied to each image of all thermal cameras over Etna in real-time, the proposed system provides two outputs, namely the visibility level and the recognized activity status. By merging the outcomes coming from each thermal camera, the monitored phenomena can be fully described from different perspectives getting deeper information in real-time and in an automatic way.   

How to cite: Corradino, C., Ganci, G., Bilotta, G., Cappello, A., and Del Negro, C.: Machine learning approach for multi-perspective volcanic eruption recognition using thermal infrared images, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8600, https://doi.org/10.5194/egusphere-egu2020-8600, 2020.

The 3 July 2019 explosive paroxysm at Stromboli volcano (Italy) caused severe concern in the local population and media, and killed one tourist hiking the volcano. The great explosion formed a 4-km-high eruptive cloud, and its partial collapse ignited the dry vegetation and caused hot rock avalanches spreading along the northern slope to the sea and triggering a small tsunami wave. This paroxysm was followed by 56 days of lava flow effusion, and another explosive paroxysm occurred on 28 August 2019. Also this explosive event caused an eruptive column of about 4 km and hot avalanches spreading on the north flank of the volcano and on the sea surface. Here we use effusion rate time-series derived from MODIS and SLSTR data to follow the different thermal phases of this eruption and compute the dense rock equivalent volume emitted. At the same time we computed four digital elevation models from Pleiades triplets acquired on June, July, August and October 2019 in order to map the morphological changes occurred during the eruption. By differencing pre, syn and post eruptive topographies we computed the bulk lava volume at the different stages. Combining tri-stereo Pleiades results with MODIS and SLSTR ones, beside giving insights in the characterization of volcanic deposits, provides important constraints in the conversion between radiant heat flux and TADR, and demonstrates the powerful merging capability of multi-platform remote sensing data.

How to cite: Ganci, G., Bilotta, G., Calvari, S., Cappello, A., Corradino, C., and Del Negro, C.: Integrating tri-stereo Pleiades images with infrared satellite data to monitor volcanoes: the 2019 Stromboli eruption, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16172, https://doi.org/10.5194/egusphere-egu2020-16172, 2020.

In February 2019 we completed the installation of a ten instrument network at Sakurajima volcano, Japan. The network includes three Doppler radar systems to record eruption velocities and amount of ejected material at Minamidake crater. Those instruments are located to the East of the volcano at a distance of about 4.5 km to the vent. We also installed three field mills to measure the electric field that is generated during an eruption due to charging of the volcanic plume. Those instruments are located to the East, North and West of the volcano at different distances. The network is completed by a weather station to monitor environmental conditions, an absolute pressure sensor for recording infrasound data, and a broadband seismometer. As an additional instrument we installed a thunderstorm detector BTD300.

In a first step we use the infrasound data (complemented by four stations from the japanese network) to generate an event catalog. The main reason for doing this is the fact that the Japanese Meteorological Society (responsible for monitoring) only reports eruptions higher than 1000 m above the vent, but there are certainly more but smaller eruptions. The event catalog based on infrasound data is complemented by the events detected by our radar systems and the field mills. In the presentation we will discuss the detection limits of the network as well as the observed electrification of the volcanic cloud that may lead to lightning, which leaves a clear signal in the electric field data. We will present some initial numerical simulations on where the strongest electric field in an eruption column occurs and discuss the impact of charging due to fractoemission and triboelectrification. Using the measured data and our initial numerical model calculations we explore which dynamic conditions appear to be favorable for lightning to occur and which not.

How to cite: Geisler, A., Seelmann, B., Hort, M., Bülow, J., Scharff, L., Iguchi, M., and Miki, D.: Quantitative observations and numerical modeling of charge development in volcanic eruption clouds, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18638, https://doi.org/10.5194/egusphere-egu2020-18638, 2020.

Volcanic ash suspended in the atmosphere can pose a significant hazard to aviation, with the potential to cause severe damage or shutdown of jet engines. Forecasts of ash contaminated airspace are generated using atmospheric transportation and dispersion models, among the inputs to these models are eruption source parameters such as cloud-top height and cloud volume. A potential method to measure these source parameters is space carving – a technique to generate 3D hull reconstructions of clouds using multi-angle imagery.

This paper investigates the potential for 3D space carving reconstruction using multi-angle satellite imagery.  This builds on previous work where the authors have applied this technique to ground-based and drone-based imagery. A satellite-based imaging platform has advantages such as global coverage and being safely removed from any damaging effects of a volcanic eruption. However, the accuracy of any potential reconstruction will be affected by the distances and restricted viewing angles of a satellite in orbit.

To assess the general suitability of a satellite-based system for reconstruction, as well as different configurations of the system, a method for simulating satellite imagery and applying a space carving reconstruction scheme was developed. This method allows the analysis of the effects of orbital dynamics (altitude, inclination, etc.), spatial resolutions, and imaging rates on the efficacy of the 3D reconstruction of ash clouds. The model utilises an input ‘ground-truth’ voxel-based plume model as the imaging target and generates simulated satellite images based on the user defined orbital and camera properties. These simulated images are then used for reconstruction and the resultant plume can be compared against the ground-truth model.

A range of possible observation schemes (controlling number and distribution of images and limits on viewing angles) have been modelled over a range of possible orbital paths and the accuracy of the space carving reconstruction has been measured. Spatial resolution limits for the accurate reconstruction of various plume sizes can be calculated. Limitations of the model are presented, including the sensitivity to the size and shape of the input plume model and the impact of the perfect feature identification in the simulated images. Further work includes the use of additional input models and improvements and validation of the image simulation method.

The methods presented in this study demonstrate the potential of satellite-based 3D reconstruction methods in the forecasting of ash dispersion, leading to potential improvements in airspace management and aviation safety.

How to cite: Etchells, T., Berthoud, L., Calway, A., and Watson, M.: 3D Reconstruction of Volcanic Ash Clouds Using Simulated Satellite Imagery, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20566, https://doi.org/10.5194/egusphere-egu2020-20566, 2020.

Many (about 250) volcanoes worldwide are occupied by glaciers. This can be problematic for volcano monitoring because glacier ice potentially masks evidence of volcanic activity. Both the deadliest and most costly volcanic eruptions of the last 100 years involved volcano-glacier interactions. The 1985 eruption of Nevado del Ruiz killed 23000 people, and the 2010 eruption of Eyjafjallajökull led to the closure of many European airports. Therefore, improving methods for monitoring glacier-clad volcanoes is of clear societal benefit. Amongst several methods, satellite based remote sensing techniques are perhaps most promising, since they frequently have a relatively high temporal and spatial resolution, and are mostly freely available. They can help to identify the effects of volcanic activity on glaciers, including ice fracturing, ice surface subsidence and glacier acceleration potentially due to subglacial melt or subglacial dome growth. This study aims to link pre-, syn- and post-eruption glacier behavior to the type and timing of volcanic activity, and to develop a satellite based predictive tool for monitoring future eruptions. Despite several studies that link volcanic activity and changing glacier behavior, the potential of using the latter to predict the former has yet to be systematically tested. Our approach is to use satellite imagery to observe how glaciers responded to past volcanic events, and to build a training database of examples for automated detection and forecasting.

How to cite: Martin, M., Barr, I., Edwards, B., Symeonakis, E., and Spagnolo, M.: Using glaciers to identify, monitor, and predict volcanic activity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5678, https://doi.org/10.5194/egusphere-egu2020-5678, 2020.

The nine active volcanoes of the sub-Antarctic South Sandwich Islands are a particularly remote region of active volcanism. Remote sensing methods, including satellite monitoring and aerial surveys, besides rare ship visits during austral summers, are the only means of investigating the uninhabited and largely ice-covered volcanoes. Mount Michael volcano on Saunders Island hosts a permanent active lava lake within its summit crater, a sure indicator of the existence of a shallow magmatic storage and transport system of unknown architecture and depth. Also, more than 75 % of the island’s area is glacier covered, which makes the island an important study site for investigating volcano-glacier interactions in the sub-Antarctic climate zone.

We describe new data for the active Mount Michael volcano on Saunders Island, including marine bathymetric and satellite-derived observational data, UAV-derived topographic data, and infra-red camera observations. This data together provide a much higher resolution understanding of the topography, geomorphology, glacial state and dynamics, as well as status of volcanic activity than has been previously achieved. We present a geomorphological and structural analysis of the outer subaerial and shallower submarine flanks of Saunders Island, estimate glacier volumes, morphologies and motion rates, and relate this to the underlying volcano morphology, structural architecture, and edifice stability. All of this is pioneer work at a remote volcano that can be largely regarded as terra incognita. With this study we highlight the unprecedented detail and the valuable information that can be retrieved from modern generation satellites, such as TerraSAR-X and Sentinel-2, as well as UAV-based photogrammetry in particularly remote and inaccessible locations on Earth.

How to cite: Richter, N., Leat, P., Derrien, A., Wintersteller, P., Meschede, M., and Walter, T. R.: Geophysical and geomorphological observations of the glacier-covered, subantarctic Mount Michael volcano (Saunders Island), South Sandwich Islands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13472, https://doi.org/10.5194/egusphere-egu2020-13472, 2020.

The North East Rift volcanic Zone (NERZ) of Tenerife Island is one of the three volcanic rift-zones of the island, oriented NW-SE (NWRZ), NE-SW (NERZ) and a more scattered area on the south (NSRZ). From a volcano-structural point of view, NERZ is more complex than NW or NS rifts due the existence of Pedro Gil stratovolcano that broke the main NE-SW structure. Pedro Gil Caldera was formed  0.8  Ma ago by a vertical collapse of this stratovolcano. The most recent eruptive activity along the NERZ took place during 1704 and 1705 along a 13 km of fissural eruption of Arafo-Fasnia-Siete Fuentes. Diffuse CO₂ emission surveys have been undertaken in a yearly basis since 2001 in order to provide a multidisciplinary approach to monitor potential volcanic activity changes at the NERZ. The aim of this study is to report the results of the last soil CO₂ efflux survey undertaken in summer 2019, with 639 measuring sites homogeneously distributed in an area of 210 km². In-situ measurements of CO₂ efflux from the surface environment of NERZ were performed by means of a portable non-dispersive infrared spectrophotometer (NDIR) following the accumulation chamber method. Soil CO₂ efflux contour maps were constructed to identify spatio-temporal anomalies and to quantify the total CO₂ emission using the sequential Gaussian simulation (sGs) interpolation method. The CO₂ efflux values ranged from non-detectable (0.5 g m^-2 d^-1) up to 72,3 g m^-2 d^-1, with an average value of 10,9 g m^-2 d^-1. Statistical-graphical analysis of the 2019 data show two different geochemical populations; background (B) and peak (P) represented by 70.4% and 1.9% of the total data, respectively. The geometric means of the B and P populations are 0.4 and 4.3 g m^-2 d^-1, respectively. The diffuse CO₂ emission rate was estimated in 2,205 t d^-1. Studying the long-term variations on the diffuse CO₂ emission since 2001, two main pulses are identified: one in 2007 and a second one sustained over time between 2014 and 2019. Enhanced endogenous contributions of deep-seated CO₂ might have been responsible for the higher CO₂ emissions values observed during those pulses. The 2014-2019 pulse appears to be related to the seismic activity that started taking place in Tenerife at the end of 2016. This study denotes the importance of soil CO₂ efflux surveys at the NERZ volcano of Tenerife Island as an effective volcanic monitoring tool.

How to cite: Sáez-Gabarrón, L., Beeck, J., Reilly, S., Alonso, M., Ortega-Ramos, V., Padrón, E., Melián, G. V., Rodríguez, F., Hernández, P. A., and Pérez, N. M.: Surface diffuse degassing monitoring of the Tenerife Northeastern Rift Zone (NERZ) volcano, Canary Islands , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11604, https://doi.org/10.5194/egusphere-egu2020-11604, 2020.

Carbon dioxide (CO₂) is one of the first gases to escape from the magmatic environment due to its low solubility in basaltic magmas at low pressures. Monitoring of volcanic gases in Tenerife Island (2,304 km²) has been focused mainly on diffuse CO₂ degassing and other volatiles due to the absence of visible gas manifestations except fumaroles at the summit of Teide volcano. An inexpensive method to determine CO₂ fluxes based in the absorption of CO₂ through an alkaline medium followed by titration analysis has been used with the aim of contributing to the volcanic surveillance of Tenerife. During summer 2016, a network of 31 closed alkaline traps was deployed along the three volcanic rifts of Tenerife (NE, NW and NS) and at Cañadas Caldera. To do so, an aliquot of 50 mL of 0.1N KOH solution is placed inside the chamber at each station to absorb the CO₂ released from the soil. The solution is replaced in a weekly basis and the trapped CO₂ is later analyzed at the laboratory by titration. Values are expressed as weekly integrated CO₂ efflux. We present herein the results of one year CO₂ efflux estimated by closed alkaline traps. The CO₂ efflux values ranged from 1.0 to 14.5 g·m^-2·d^-1, with average values of 8.5 g·m^-2·d^-1 for the NE rift-zone, 5.2 g·m^-2·d^-1 for Cañadas Caldera, 6.4 g·m^-2·d^-1 for NW rift-zone and 6.1 g·m^-2·d^-1 for NS rift-zone. The estimated CO₂ efflux values were of the same order than the observed ones in 2016. Relatively high CO₂ efflux values were observed at the NE rift-zone, where maximum values were measured. The temporal evolution of CO₂ efflux estimated by closed alkaline traps did not show significant variations during 2019. However, small seasonal variations are observed during the period 2016 – 2019. To investigate the origin of the soil CO₂, soil gas samples were weekly sampled on the head space of the closed chambers. Chemical and isotopic composition of C in the CO₂ were analysed in the gas samples. The concentration of CO₂ on the head space of the closed chambers showed a range of 355-50,464 ppm, with an average value of 1,850 ppmV, while the isotopic composition expressed as d¹³C-CO₂ showed a range from -5.03 to -30.44 ‰, with an average value of -15.9 ‰. The heaviest values of d¹³C-CO₂ are in the NW rift-zone. The systematics of closed static chambers alkaline traps can be a simple and economical tool with volcanic surveillance purposes in system where visible volcanic gases manifestations are absence.

How to cite: Albertos, V. T., Graham, C. M., Cabassa, L., Borges da Cruz, T., Melián, G. V., Pérez, N. M., Cordero-Vaca, M., Amonte, C., Asensio-Ramos, M., and Hernández, P. A.: Soil carbon dioxide efflux weekly monitoring network for the volcanic surveillance of Tenerife, Canary Islands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11762, https://doi.org/10.5194/egusphere-egu2020-11762, 2020.

Tenerife (2,034 km²) is the largest of the Canary Islands and the North South Rift Zone (NSRZ) is one of the three active volcanic rift-zones of the island. The NSRZ (325 km²) is characterized mainly by effusive activity of basaltic lavas forming spatter and cinder cones and comprises 139 monogenetic cones representing the most common eruptive activity occurred on the island during the last 1Ma. In order to provide a multidisciplinary approach to monitor potential volcanic activity changes at the NSRZ volcano, diffuse CO₂ emission surveys have been undertaken since 2002. This study shows the results of the last soil CO₂ efflux survey undertaken in summer 2019, with ⁓600 soil gas sampling sites homogenously distributed in the study area. Soil CO₂ efflux measurements were performed at the surface environment by means of a portable non-dispersive infrared spectrophotometer (NDIR) LICOR Li820 following the accumulation chamber method. Soil CO₂ efflux values ranged from non-detectable (⁓0.5 g m^-2 d^-1) up to 30 g m^-2 d^-1, with an average value of 2.6 g m^-2 d^-1. In order to distinguish the existence of different geochemical populations on the soil CO₂ efflux data, a Sinclair graphical analysis was done. The average value of background population was 2.1 g m^-2 d^-1 and that of peak population was 18.5 g m^-2 d^-1, representing the 97% and the 1% of the total data, respectively. To quantify the total CO₂ emission rate from the NSRZ volcano a sequential Gaussian simulation (sGs) was used as interpolation method. The diffuse CO₂ emission rate for the studied area was estimated in 2019 in 819 ± 18 t d^-1, ranging from 466 to 819 t d^-1 between 2002 and 2019, with the highest value measured in 2015 (707 t d^-1). The temporal evolution of diffuse CO₂ emission at the NSRZ shows a clear relationship with the volcano seismic activity in and around Tenerife Island, which started to taking place from the end of 2016. This study demonstrates the importance of studies of soil CO₂ efflux at the NSRZ volcano of Tenerife island as an effective volcanic monitoring tool, especially in areas where there is no visible degassing (fumaroles, etc.)

How to cite: Cordero-Vaca, M., Figueiredo, C. A., Czwakiel, N. L., Padrón, E., Melián, G. V., Alonso, M., Asensio-Ramos, M., Hernández-Ramos, W., Hernández, P. A., and Pérez, N. M.: Diffuse CO2 degassing monitoring of the Tenerife North–South Rift Zone (NSRZ) volcano, Canary Islands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12067, https://doi.org/10.5194/egusphere-egu2020-12067, 2020.

Precise knowledge of the location and height of the volcanic sulfur dioxide (SO₂) plume is essential for accurate determination of SO₂ emitted by volcanic eruptions. So far, UV based SO₂ plume height retrieval algorithms are very time-consuming and therefore not suitable for near-real-time applications like aviation control. We have therefore developed the Full-Physics Inverse Learning Machine (FP_ILM) algorithm for extremely fast and accurate retrieval of volcanic SO₂ layer heights based on the UV satellite instruments Sentinel-5 Precursor/TROPOMI and MetOp/GOME-2.

In this presentation, we will present the FP-ILM algorithm and show results of the 2019 Raikoke eruption; a strong volcanic eruption which has emitted a huge ash cloud accompanied by more than 1300 DU of SO₂, which could be detected  even two months after the end of eruptive event. We will also present first results of the recent Taal volcanic eruption on 13 January 2020 in Indonesia, which has injected a huge ash and SO₂ plume into the upper atmosphere, with plume heights of up to 20km. 

The algorithm is developed in the framework of ESA's  "Sentinel-5p+ Innovation: SO₂ Layer Height project" (S5P+I: SO2 LH),  dedicated to the generation of an SO₂ LH product and its extensive verification with collocated ground- and space-born measurements.

The high-resolution UV spectrometer GOME-2 aboard the three EPS MetOp-A, -B, and –C satellites perform global daily atmospheric trace-gas measurements with a spatial resolution of  40x40km² at an overpass time of 8:30h local time. The UV spectrometer TROPOMI aboard the ESA Sentinel-5P satellite provides a much higher spatial resolution of currently 5.6x3.6km² per ground pixel, at an overpass time of 13:30h. In the future, also UV instruments aboard the Sentinel-4 (geostationary) and Sentinel-5 will complement the satellite-based global monitoring of atmospheric trace gases.

How to cite: Hedelt, P., Koukouli, M., Taylor, I., Balis, D., Grainger, D., Efremenko, D., and Loyola, D.: Extremely fast retrieval of volcanic SO2 layer heights from UV satellite data using inverse learning machines, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6991, https://doi.org/10.5194/egusphere-egu2020-6991, 2020.

One of the main compounds emitted by volcanoes or volcanic fields is CO₂. This is not only emitted from localized craters, but can emerge as distributed and fugitive emission from extended volcanic regions. In this situation it is of interest to explore the distribution and horizontal concentration profiles of the CO₂-emissions.     

For this purpose new dropsondes for sensor measurements of CO₂ emissions are under development at the Duesseldorf  University of Applied Sciences. These dropsondes are designed to be dropped from aircraft or drones over volcanic areas in order to map the distributed CO₂ concentrations over longer times in an unattended way. They are very lightweight and cheap, so that a large number of dropsondes might be deployed even over remote areas or regions with difficult access. The data are transmitted with GSM broadcasting and can be visualized on a geographical map.

The dropsondes use an NDIR CO₂ sensor as a basis for the measurement unit. Additionally to the concentration of CO₂ the atmospheric pressure, temperature and humidity are measured. The sensor unit is mounted in a special shock absorbing housing, which is designed to absorb impacts from the touch down after dropping of the sensor and is able to resist even adverse weather conditions.

First measurement results and more details of the design of the sensor unit are presented in this contribution.

How to cite: Weber, K., Fischer, C., and Amend, D.: Design and development of lightweight dropsondes for the monitoring of fugitive CO2-emissions from volcanic regions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13706, https://doi.org/10.5194/egusphere-egu2020-13706, 2020.

Orbital remote sensing is the only tool allowing global, systematic monitoring of all 1500+ active volcanoes (based on the Smithsonian Holocene catalog). A specialized archive has been developed at the Jet Propulsion Laboratory: the ASTER Volcano Archive (AVA). AVA is comprised of over 200,000 ASTER frames spanning 20 years of the NASA’s Terra platform mission. The ASTER Volcano Archive (AVA: http://ava.jpl.nasa.gov) is the world's largest (at 100+Tb), and the only high spatial resolution (15-30-90m/pixel), multi-spectral (VNIR-SWIR-TIR), downloadable (kml enabled) dedicated archive of volcano imagery. The system is designed to facilitate parameter-based data mining, and for the implementation of archive-wide data analysis algorithms. Results include thermal anomaly detection and mapping, the temporal variability of individual volcanic emissions, as well as the detection of SO₂ plumes from both explosive eruptions and from passive emissions. A major expansion of the archive was implemented with the ingest of the full 1972-present Landsat dataset. In addition, the archive includes NASA Earth Observing-1 (EO-1) multispectral and hyperspectral imagery (10-30 m/pixel) of a subset of the Holocene catalog volcanoes obtained between 2004 and 2017. The newest version of AVA has been ported to the Amazon Web Services cloud and managed by the Jet Propulsion Laboratory’s Hybrid Science Data System (HySDS). This migration provides all of the previous capabilities, providing a stable, fast platform for rapid access to data. The system is updated with new data daily, with a latency of a few days following data acquisition. Currently we are developing a new user interface to facilitate easy, fast and efficient access to the archive. This work was performed at the Jet Propulsion Laboratory, California Institute of Technology under contract to NASA. © 2020 Caltech.

How to cite: Abrams, M., Torres, A., and Davies, A.: The ASTER Volcano Archive (AVA): Twenty years of global monitoring of active volcanoes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3133, https://doi.org/10.5194/egusphere-egu2020-3133, 2020.

Knowledge of the rates of Earth volcanism and their variability is critical in many fields involving global assessments, such as plate tectonics and associated rates of crustal formation and consumption, large-scale volcanic hazards, climate change, etc. Global rates also provide the base rate to which regional or individual volcano data can be compared, in order to quantify differences and similarities providing guidance in the identification of volcanoes with overall analogue behaviors. While global volcanic eruption databases, such as the Smithsonian Global Volcanism Project database or the Large Magnitude Explosive Volcanic Eruptions database at BGS, provide the required basic knowledge, substantial deterioration of the geologic information with age has been a serious obstacle to a comprehensive picture. Recent understanding that global eruption inter-event times are exponentially distributed, that being the essential character of Poisson distributed events, is leading to a general model for the global eruption behavior of the Earth. Exponential distributions are entirely characterized by one single rate parameter. Comparing the rate parameters for different VEI classes of eruptions, as well as analyzing the distribution of individual eruption volumes within and across different VEI classes, reveals that relative frequencies for the explosive eruptions with VEI higher than 2 distribute as a power law. This knowledge is employed a) to quantify the global volcanic hazard, in particular in relation to the occurrence of globally impacting eruptions, comparing with known hazards from many well-known adverse events; and b) within a Monte Carlo simulation of the eruptive history of the Earth, allowing us to quantify the distribution of volcanic eruption rates, both in number and volume, and globally or for each given VEI class or group of VEI classes, over different observational time windows from 1 to 100,000 years.

How to cite: Papale, P., Marzocchi, W., and Garg, D.: Global rates of continental volcanism on Earth, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19414, https://doi.org/10.5194/egusphere-egu2020-19414, 2020.