Volcanic eruptions can destroy infrastructure, affect businesses and economies, and claim lives, thus having disastrous consequences for people, communities and countries. Some 19% of all active volcanoes host glaciers, and the eruptions of ice-clad volcanoes are amongst the most disruptive (e.g., Eyjafjallajökull) and deadliest (e.g., Nevado del Ruiz) of the past century. It is now becoming increasingly clear that effective volcano monitoring and eruption forecasting, including for ice-clad volcanoes, requires a multi-disciplinary approach. This raises the following question: can glaciers, whose dynamic behavior might reflect volcanic activity, become an additional, much needed, parameter to consider and monitor?

To answer this question, we present global scale analyses of glacier velocity and glacier elevation that demonstrate how these two parameters are affected by proximity to active volcanoes. Specifically, glaciers closer to volcanoes possess higher velocities and are restricted to higher elevations. This is likely due to increased basal melting in response to higher geothermal heat flux experienced on and near volcanoes. In particular, we propose that the enhanced melting negatively affects the glacier mass balance, confining them to higher elevations. It also lubricates the glacier bed thus making them move faster, relative to glaciers that are further from volcanoes. As volcanoes often “heat up” prior to an eruption, sometimes for years in advance, we anticipate that glacier elevation (in the longer term – e.g., years) and velocity (in the shorter term – e.g., months) might also change, thus providing two valuable new parameters to consider in volcano monitoring and eruption forecasting efforts.

How to cite: Spagnolo, M., Mallalieu, J., Unnsteinsson, T., Barr, I., Girona, T., Gomez-Patron, A., Martin, M., Pritchard, M., and Rea, B.: Can glaciers contribute to volcano monitoring and eruption forecasting?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1097, https://doi.org/10.5194/egusphere-egu25-1097, 2025.

Ice cores provide a valuable archive of volcanism in the pre-satellite era, which can be used to understand timing, hazards and climate impact of past explosive eruptions. Sulfur isotope analysis of volcanic aerosols deposited and preserved in ice cores are used to constrain plume heights, source latitudes and inform stratospheric sulfur loading, while identification and geochemical analysis of microscopic ash particles can link ice-core volcanic deposits to specific eruptive sources. These techniques have enabled researchers to identify eruptive sources and characteristics of numerous eruptions recorded in ice cores, often targeting large, explosive events associated with climate forcing or widespread ash dispersal. However, the vast majority of the ice core eruption archive is yet to be explored, and there is much to be done to utilise the record to benefit volcanology research.

An important period of large, climate-impacting volcanic eruptions occurs in the 7^th Century of the Common Era. Historical eruption records are poor during this time period, but by targeting prominent sulfate and tephra deposits in Greenland ice core TUNU2013, we better constrain source parameters of three major eruptions in this century. As well as providing new insights into climate-forcing eruptions occurring in 626 and 682 CE, we identify the Newberry Pumice tephra from the Big Obsidian eruptive period of Newberry Volcano (Oregon, USA). This finding provides a new and precise ice-core chronology date for the Newberry Pumice and extends the known plume transport distance to Greenland.

These results demonstrate the wealth of data about individual volcanic eruptions that can be obtained from linking an ice-core tephra to its source, including eruption timing, plume height, tephra transportation distances, grain size and abundance. Knowledge of these characteristics is key for informing plume models which reconstruct past events where historic data is not available, and strengthen future hazard predictions. These findings demonstrate the opportunity the ice core volcanic records present to the wider volcanology community.

How to cite: Innes, H., Hutchison, W., Sigl, M., McConnell, J. R., Chellman, N. J., Jensen, B. J. L., and Burke, A.: Using ice cores to constrain parameters of eruptions during the 7th Century of the Common Era: challenges and opportunities, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16918, https://doi.org/10.5194/egusphere-egu25-16918, 2025.

The Fagradalsfjall volcano erupted on March 19, 2021, marking its first eruption in nearly 781 years. During the six-month eruption period (March–September 2021), a total of 90 Sentinel-1 synthetic aperture radar (SAR) images were collected between January and December 2021. These images consisted of 60 frames from the Sentinel-1A satellite and 30 frames from the Sentinel-1B satellite, providing a short temporal baseline of approximately 6 days between interferogram pairs. The dataset was processed using an advanced time-series InSAR technique based on the Improved Combined Scatterers Interferometry with Optimized Point Scatterers (ICOPS) algorithm, which analyzed surface deformation through a combination of Persistent Scatterer (PS) and Distributed Scatterer (DS) points, collectively referred to as Combined Scatterer (CS) points. To refine the analysis, a convolutional neural network (CNN) was applied to evaluate the temporal patterns of the CS points, and the Optimized Hot Spot Analysis (OHSA) method was employed to spatially optimize these points by identifying statistically significant patterns between hot and cold points. In detail, PS points were identified using an amplitude dispersion index threshold of 0.4, in line with standard StaMPS processing procedures. For DS points, a combination of amplitude and phase information was used: the amplitude data helped detect statistically homogeneous pixels (SHPs) through a Generalized Likelihood Ratio (GLR) test, while phase information enabled analysis of spatial and temporal coherence between each interferogram pair. By combining SHP detection with spatial and temporal coherence, the DS points were selected for further analysis as part of the CS point combination. To enhance displacement pattern reliability, a CNN was employed to assess consistency based on correlation coefficients. OHSA, using Getis-Ord Gi* statistics, was then applied to identify statistically significant hot spots by clustering data according to z-scores and p-values, determining the spatial significance of the deformation patterns. Finally, validation of ICOPS results against GNSS measurements around the deformation area demonstrated consistency in observed deformation patterns. The analysis revealed that deformation around the Fagradalsfjall volcano was primarily driven by magma reservoir activity associated with dike intrusion beneath the surface, which was accompanied by increased earthquake events. Seismic activity in the region was visualized through cross-sections of earthquake distributions during the deformation period, providing deeper insights into the volcanic activity.

Acknowledgment: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF–2023R1A2C1007742).

How to cite: Hakim, W. L., Kim, B., and Lee, C.-W.: Advanced Time-Series InSAR Analysis using ICOPS for Monitoring Surface Deformation of Fagradalsfjall Volcano during the 2021 Eruption, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2151, https://doi.org/10.5194/egusphere-egu25-2151, 2025.

Timely detection of early warning signals prior to volcanic eruptions heavily relies on remote sensing, particularly for volcanoes which are not easy to access, such as the Sunda Arc volcanoes. Girona et al. (2021) have introduced a novel method using MODIS infrared radiation data to identify a long-term, large-scale, and subtle increase in the surface temperature preceding eruptions by several months to years. This finding suggests the presence of enhanced hydrothermal activities before volcanic eruptions, complementing other monitoring data like surface deformation, gas flux, and thermal infrared hotspot. Nevertheless, when employing this methodology in volcanoes situated in regions with a variety of landuse and pronounced cloud cover, the detected surface thermal anomalies may not be controlled by volcanic activities. Our strategy involves detailed pixel labeling to improve the precise selection of pixels for background temperature, boosting volcanic thermal signal recognition.

We used MODIS cloud mask data to filter out cloudy pixels. Then, we exclude the regions that may be sensitive to climate, like water bodies and urban areas. After cleaning the data, the correlation between the surface temperature evolution and the volcanic activities becomes stronger, especially for those volcanoes with more frequent eruptions. In addition, the correlation between the thermal signal and the eruptions with significant precursors, such as surface deformation and seismic activity, is stronger than those eruptions without early warning signals. One possible explanation is that in those sealed volcanic systems, the gas is accumulated and pressurized to trigger surface displacements or seismicity. At the same time, the gas can only slowly percolate through the volcanic edifice to generate long-term, large-scale thermal anomalies. 

To explain the origination of these large-scale thermal anomalies, we further built numerical models to explore a wide range of processes that can generate surface warming, including magma intrusion, intensified degassing, and redistribution of pore fluids due to rock permeability changes. The model and data support the hypothesis that within relatively “sealed/closed” volcanic systems, volcanic gases exsolved from magma reservoirs ascend to the surface via volcanic flanks, triggering extensive surface warming and uplift. The integration between the thermal data and the numerical model allows us to assess the practical viability of these adjustments, thereby deepening our comprehension of subsurface mechanisms and improving the predictive precision for forthcoming volcanic events.

How to cite: Chenyan, W. and Zhan, Y.: Detecting and Modeling Long-Term Volcanic Thermal Unrest Captured by MODIS Data Years Before Eruption, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-751, https://doi.org/10.5194/egusphere-egu25-751, 2025.

Using numerical modelling, we study the influence of lava rheology (described by Newtonian, Bingham or Herschel-Bulkley fluids) on lava flow advancement and flow morphology. Numerical simulations were conducted using a three-dimensional fluid dynamics model as well as a depth-averaged model based on the shallow water approximation. In the case of isothermal flow models, we have shown that the increased yield strength significantly influences lava flow morphology by restricting flow advance and promoting upward growth of lava flows. In the case of temperature-dependent rheological models, the Newtonian and Bingham fluids demonstrate similar lava flow morphologies and thickness distributions. The viscosity values in both cases vary from about 10^2.7 – 10⁶ Pa s across the central part of the lava flow to about 10¹² Pa s near the lava flow margins. The Herschel-Bulkley model exhibits the viscosity values of 10⁹ Pa swithin the flow and reaches the highest viscosity values, up to 10¹⁶ Pa s along the lava flow margins resulting in the shortest lava flow. We simulate the emplacement of a natural lava flow using observational data from the December 2015 eruption at Mount Etna. All thermal rheological models approximate the real lava flow width accurately, with the Newtonian model providing the best match for flow extent and developing the same morphological features as the real lava emplacement. While the Herschel-Bulkley model shows a slight deviation in the lava flow length, the Bingham model fits well the main flow branch, with minor divergence in the upper branches.

How to cite: Ismail-Zadeh, A., Zeinalova, N., and Tsepelev, I.: Influence of rheology on lava flow dynamics inferred from numerical modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5227, https://doi.org/10.5194/egusphere-egu25-5227, 2025.

In recent years, Etna's primary eruptive activity has been marked by extended sequences of lava fountain episodes. Lava fountains are explosive events involving intense jets of gas and solid particles, which significantly impact air traffic and urban areas due to ash dispersal and fallout. The development of a lava fountain at Etna typically follows a gradual progression: it begins with weak Strombolian activity, transitions to a characteristic lava jet, and culminates in the formation of a sustained eruptive column. These events generally last from several minutes to a few hours. During such eruptions, the interaction between magma and surrounding rock induces very small deformations that can be detected by a Sacks-Evertson strainmeter. This instrument measures the volumetric deformation of the surrounding rock with high resolution and across a broad frequency range. Analyzing strain data helps determine the timing of events, assess the fountain's magnitude, and estimate the volume of material erupted.

In this study, we propose a time-dependent model of shallow reservoir withdrawal, incorporating fluid dynamics within the conduit and associated pressure variations. The resulting variations of the strain field in the surrounding rocks is compared with data collected at Etna during lava fountaining episodes.

How to cite: Macedonio, G., Bonaccorso, A., Carleo, L., Costa, A., Currenti, G., and Giudicepietro, F.: Modeling the dynamics of lava fountains at Etna, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17539, https://doi.org/10.5194/egusphere-egu25-17539, 2025.

The 10 February 2022 pyroclastic avalanche at Mt. Etna represents a significant example of high-mobility granular flow occurring at basaltic volcanoes. While such phenomena are typically associated with more explosive volcanic systems, their occurrence at Etna underlines their relevance for hazard assessment in volcanic environments dominated by effusive and mildly explosive eruptions.

This study focuses on a pyroclastic avalanche triggered by the gravitational collapse of the Southeast Crater’s (SEC) during an intense lava fountaining episode. The event produced a reddish-brown deposit that extended up to 1.4 km southward, covering part of the 2002–2003 scoria cone. Stratigraphic analysis revealed four distinct units, ranging from fine ash to blocks, with variations in granulometry and thickness.

A multidisciplinary approach was applied to unravel the trigger of the avalanche, combining field surveys, granulometric and textural analyses on products collected from the deposit and remote sensing data, supported by the numerical modeling to better constrain the flow propagation dynamics. Our results highlight how these pre-collapse factors, including the elevated residual temperature and the fast accumulation of ultra-proximal pyroclastic fall deposit during the previous lava fountaining episodes, played a crucial role in enhancing the partial collapse.

The findings of this study contribute to a deeper understanding of pyroclastic avalanche behavior in basaltic volcanic systems, offering valuable insights into the mechanisms controlling these hazardous flows in volcanic regions like Mt. Etna, where eruptions frequently interact with human activity and infrastructure.

How to cite: Zuccarello, F., Andronico, D., Behncke, B., Cappello, A., Ciancitto, F., Del Carlo, P., de’ Michieli Vitturi, M., Di Roberto, A., Esposti Ongaro, T., and Gaetana, G.: A multidisciplinary investigation of the 10 February 2022 pyroclastic avalanches at Mt. Etna, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16736, https://doi.org/10.5194/egusphere-egu25-16736, 2025.

During volcanic eruptions, a variety of metals and metalloids are emitted along with gases and particulate matter. These elements are released in trace amounts, often bound to volcanic ash, gases, and aerosols, and can be transported over long distances by wind currents. Some of the key metals and metalloids commonly found in volcanic emissions include Arsenic (As), Cadmium (Cd), Chromium (Cr), Lead (Pb), Selenium (Se), Thallium (Tl), Tungsten (W), Antimony (Sb), Beryllium (Be) and Copper (Cu). These elements are of concern because several of them, such as As, Cd, Pb, and Cr, are toxic and pose significant risks to both human health and the environment. Their presence in volcanic emissions contributes to air and water pollution, with potential long-term effects on ecosystems and populations living in affected areas.

During the Tajogaite eruption (2021) at Cumbre Vieja volcano (La Palma, Canary Islands), a substantial amount of CO₂ and SO₂ was released into the atmosphere. Throughout this eruption observations of SO₂ emissions were made using ground-based instruments, in transverse mode, as well as by numerous satellite instruments. Data from the Sentinel-5P instrument TROPOMI was combined with the PlumeTraj back-trajectory analysis toolkit to produce sub-daily SO₂ fluxes that can be directly compared to the ground-based miniDOAS observations (Hayer et al., 2022). Daily OP-FTIR volcanic gas composition measurements throughout the 2021 Tajogaite eruption revealed consistently high CO₂/SO₂ ratios in the plume (Asensio-Ramos et al., 2025). Combined with the estimated SO₂, ~1,6 Mt (Albertos et al. 2022; Esse B. et al. 2025), the total amount of CO₂ emitted during the 2021 eruption was estimated to be ~28 Mt CO₂ (Burton et al., 2023).

Daily aerosol samples, or particulate matter smaller than 10 microns (PM10), were collected on 150 mm quartz microfiber filters at a flow rate of 30 m³/h in the western part of La Palma Island during the Tajogaite eruption. The elemental composition of the aerosols was determined through acid digestion (HF:HClO₄:HNO₃) followed by analysis using ICP-MS and ICP-OES. Additionally, daily PM10 samples were collected on 47 mm quartz filters according to the UNE EN 12341:2015 standard, which outlines the standard gravimetric method for measuring the PM10 or PM2.5 mass concentration. The various metals in the samples were then analyzed in the laboratory following the UNE-EN 14902:2005 standard.

In this study, we present the estimated trace element emission rates from the Tajogaite eruption plume by combining the observed Xi/SO₂ ratios in aerosols and PM10 particles (where Xi represents a trace metal) with the measured SO₂ emission rate. Preliminary results of trace element emissions range from 0.04 to 14.02 t·d^-1 for As, 0.05 to 7.85 t·d^-1 for Cd, and 0.30 to 78.88 t·d^-1 for Pb, spanning from September 29 to November 11, 2021

References
Albertos, V. T., Recio, G., Alonso, M., et al. (2022). https://doi.org/10.5194/egusphere-egu22-5603
Asensio-Ramos, M., Pardo Cofrades, A., Burton, M. et al. (2025), https://doi.org/10.1016/j.chemgeo.2024.122605
Burton, M., Aiuppa, A., Allard, P. et al. (2023), https://doi.org/10.1038/s43247-023-01103-x
Esse, B., Burton, M., Hayer, C. et al (2025) submitted to Bull. Volcano.
Hayer, C., Barrancos, J., Burton, M. et al. (2022), https://doi.org/10.5194/egusphere-egu22-12201

How to cite: Pérez, N. M., Burton, M., Rodríguez, S., Vilches Sarasate, J., Hernández, P. A., Esse, B., López Darias, J., Melián, G. V., Hayer, C., de la Rosa, J., Padrón, E., and Asensio-Ramos, M.: Trace Element Emissions from the Tajogaite Eruption Plume, La Palma, Canary Islands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13986, https://doi.org/10.5194/egusphere-egu25-13986, 2025.

Since September 2021, Vulcano Island was affected by a volcanic unrest crisis with an increase in fumarolic activity at La Fossa crater, seismic activity and ground deformations. A contemporary strong increase in the soil CO₂ flux was observed both at the base of La Fossa cone and in some zones of Vulcano Porto settlement. The gas hazard also increased because the massive gas plume (mainly CO₂ and SO₂) descended the crater rim, particularly during night, investing the resident areas. The first civil protection measures adopted to face the health risk at Vulcano Porto included the evacuation of the houses most exposed to the gas and the night time ban of all houses. The long-term gas risk reduction was then achieved with the establishment of a continuous monitoring network for air gas concentration, equipped with an alert system. Also the INGV volcanic gas monitoring network of Vulcano Porto was strengthened. An ad-hoc appointed scientific commission, chaired by DPC and composed by all national and local authorities expert of health, environmental and volcanic hazard, suggested the continuous monitoring of volcanic gases both outdoor and indoor. Two dedicated networks were then built, installed and managed by Arpa Sicilia. The outdoor Arpa network, operational since March 2022 with two mobile labs, since February 2023 includes 6 stations with continuous monitoring of air CO₂, H₂S and SO₂ concentration of which 1 for monitoring also CO, NO₂, PM, C₆H₆, O₃ concentration. The regulatory references of the limit values ​​and alarm thresholds are those provided for by Legislative Decree 13 August 2010, n. 155 - Implementation of Directive 2008/50/EC, as well as the values ​​identified by the WHO global air quality guidelines and in the ISTISAN Report 16/15. The recorded monitoring data show the occasional exceeding of the outdoor thresholds for CO₂, H₂S and SO₂. The pilot indoor network, started in December 2023, is fully operational since June 2024 and currently monitors 33 buildings selected on a voluntary basis. The alert thresholds for indoor monitoring have been identified in agreement with the Regional Department of Civil Protection and the ISS - Istituto Superiore di Sanità. Some indoor stations, located in the most critical sectors of Vulcano Porto (Faraglione and Camping Sicilia) show the recurrence of anomalous CO₂ values (and sporadically of H₂S), especially during night time. The anomalous degassing affecting Vulcano Porto slowly decreased returning in January 2025 to background values. In conclusion, we stress the importance of finally having a risk mitigation tool for volcanic gases at Vulcano Porto, which will allow addressing the gas hazard both in condition of ordinary degassing and in possible future unrest crises. The Vulcano Porto air gas concentration monitoring networks represent one of the few examples present on active volcanoes in Europe together with those of Sao Miguel (Azores, Portugal) and La Palma (Canary Islands, Spain).

How to cite: Carapezza, M. L., Abita, A., Antero, R., Basiricò, L., Di Gangi, F., Pampalone, V., Ranaldi, M., Tarchini, L., and Tirone, N.: The continuous monitoring network of air gas concentration at Vulcano Porto (Aeolian Island, Italy), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12609, https://doi.org/10.5194/egusphere-egu25-12609, 2025.

Surface heat transfer is a continuous process reflecting the dynamic equilibrium between the magmatic system and the surrounding rock. In volcanic systems, part of the energy transferred from magma drives fluid convection, increasing ground temperatures. Total heat transfer occurs through three primary mechanisms: conduction, convection, and radiation. Each of these mechanisms plays a distinct role in volcanic systems and requires specific detection methods. Convective heat flow is observed in fumaroles and steaming ground; moderate thermal anomalies indicate conductive heat transfer; radiative heat flow is detected via multispectral instruments measuring surface thermal anomalies.

On Vulcano Island (Italy), a continuous monitoring network has detected transient variations in heat flow released by the active cone, which are correlated with increased seismic activity and ground deformation. Contact sensors monitor temporal variations in high-temperature fumaroles, while other sensors measure heat flux variations in areas of diffuse degassing. Long-term time series data have captured several episodes of volcanic unrest (e.g., Diliberto 2021; Federico et al., 2023).

This study presents results from the integration of artificial intelligence techniques with monitoring procedures, including:
a) Ground temperature measurements via contact sensors at selected sites;
b) Fumarole extent analysis;
c) Thermal and environmental indices derived from satellite imagery.

Specifically, a Semi-Supervised Generative Adversarial Network (SGAN) model was employed to automatically classify different volcanic states (baseline activity, transient degassing, and increased degassing). The model leverages direct temperature measurements from contact sensors (installed on the ground-based network on the La Fossa cone), land surface temperature anomalies (from MODIS), the Normalized Thermal Index (from VIIRS), and environmental indices such as NDVI, NDWI, and NDMI (from Landsat 8).

Preliminary results indicate that the SGAN model achieves an accuracy exceeding 0.89 for nearly all analyzed periods.

How to cite: Spina, F., Diliberto, I. S., Bilotta, G., Dozzo, M., Nastasi, D., and Ganci, G.: Integration of Ground-Based and Satellite Data Using a Semi-Supervised GAN Model on Vulcano Island, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12193, https://doi.org/10.5194/egusphere-egu25-12193, 2025.

The island of Vulcano, part of the Aeolian Archipelago, is a significant volcanic edifice in Italy. Its active geothermal system and frequent volcanic unrest, particularly the ongoing phase, since September 2021, marked by high fumarole temperatures, changes in gas composition, ground deformation, and micro-seismicity, underscore the importance of understanding the subsurface processes driving volcanic and geothermal phenomena.

The present study, using TOUGH2 code (Pruess et al., 1999), aims to enhance our understanding of the active geothermal system of Vulcano. A highly constrained petrophysical model of the island, derived from a 3D resistivity structure obtained from a magnetotelluric (MT) survey (Di Giuseppe et al., 2023), was used to simulate heat flow and fluid flow (H₂O and CO₂) for the time required to reach the natural thermodynamic state of the system. The numerical modelling results were analyzed by examining the fluid distributions in terms of pressure, temperature and CO₂ partial pressure. Pressure increases linearly with depth, as expected in a hydrostatic system, while temperature and CO₂ partial pressure show more complex distributions. These observations are consistent with a developed heterogeneous model that incorporates structural and petrophysical data from the MT model, providing a more realistic thermodynamic representation of the Vulcano geothermal system. In particular, the simulated temperature and CO₂ partial pressure distributions show a clear differentiation between the central-northern and southern parts of the island, in agreement with literature and empirical data.

These results offer new insights into the system’s behavior, significantly enhancing our understanding of its current dynamics and providing a robust foundation for predicting its future evolution. This could potentially lead to more accurate predictive models and hazard scenarios.   

How to cite: Califano, C., Salone, R., Troiano, A., Di Giuseppe, M. G., Isaia, R., and Di Maio, R.: Advancing knowledge of thermo-fluid dynamic processes in Vulcano's geothermal system through numerical simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17887, https://doi.org/10.5194/egusphere-egu25-17887, 2025.

Most climate projections represent volcanic eruptions as a constant forcing based on historical averages. This constant forcing approach ignores the sporadic nature of eruptions, preventing a full quantification of uncertainties in climate projections. Here we show that the contribution of volcanic forcing uncertainty to the overall uncertainty in global mean surface air temperature projections reaches up to 49%, and is comparable or greater than that from internal variability throughout the 21st century. Furthermore, compared to a constant volcanic forcing, employing a stochastic volcanic forcing (i) reduces the probability of exceeding 1.5 ºC warming above pre-industrial level by at least 5% for high climate mitigation scenario (SSP1-1.9) in this century; (ii) enhances the probability of negative decadal temperature trends by up to 8%; and (iii) increases the likelihood of short-term surface cooling and warming events. Intermediate to higher climate mitigation scenarios are particularly sensitive to the choice of volcanic forcing implementation in climate projections. Using a stochastic volcanic forcing approach also enables assessment of the associated climate risks and socio-economic impacts. We recommend improved volcanic forcing approaches for future climate model experiments.

How to cite: Chim, M. M. M., Aubry, T., Smith, C., and Schmidt, A.: Neglecting future sporadic volcanic eruptions underestimates climate uncertainty, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4244, https://doi.org/10.5194/egusphere-egu25-4244, 2025.

Sulfur dioxide (SO₂) emissions from volcanic activity have significant impacts on human health, society, aviation, and atmospheric composition in general. While nadir-viewing satellites have delivered decades of valuable information on the SO₂ Vertical Column Density (VCD), accurate retrieval of its Layer Height (LH) remains a major challenge, yet critical to further understand volcanic events and refine estimates of SO₂ emissions, which play a key role on climate. Indeed, current UV retrieval techniques often face limitations in sensitivity and computational efficiency, particularly in aerosol-rich conditions.

Here, we present an enhanced SO₂ height and column density retrieval algorithm developed from the high-resolution TROPOspheric Monitoring Instrument (TROPOMI). Our approach focuses on the second UV spectral band (BD2), which benefits from a strong SO₂ absorption, rather than the third band (BD3) commonly used for sulfur dioxide retrievals.

Sensitivity analyses were first carried out on a set of synthetic spectra representative of TROPOMI observations with the Look-Up Table Covariance-Based Retrieval Algorithm (LUT-COBRA) [1, 2]. The impact of atmospheric, spectroscopic and observation conditions on the retrieval quality has been thoroughly studied, highlighting the considerable effect of ozone. Furthermore, results indicate that BD2 retrievals provide more accurate SO₂ LHs and VCDs, with much lower retrieval errors, especially in the Upper Troposphere/Lower Stratosphere (UTLS).

The algorithm was then applied to real TROPOMI observations of different volcanic eruptions (e.g., Ruang, Etna). In comparison to BD3 retrievals, our method leads to a better sensitivity, with less noise and a detection limit as low as 2.0 DU, outperforming the current operational TROPOMI SO₂ product. Moreover, our plume height estimates align well with independent measurements from IASI, CALIOP, and OMPS-LP, confirming the reliability of our results. 

[1] N. Theys et al., Atmospheric Chemistry and Physics, 21(22):16727–16744, 2021.

[2] N. Theys et al., Atmospheric Measurement Techniques, 15(16):4801–4817, 2022.

How to cite: Fabris, L., Theys, N., Clarisse, L., Franco, B., Brenot, H., Vlietinck, J., Danckaert, T., Yu, H., van Gent, J., and Van Roozendael, M.: Enhanced TROPOMI SO2 height and density retrievals applied to eruptions in 2023-2024, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8314, https://doi.org/10.5194/egusphere-egu25-8314, 2025.

Volcanic eruptions inject large amounts of particles and gases into the atmosphere. The detection of volcanic constituents is crucial to support aviation safety and to quantify their impact on human health, environment and climate. Detection of volcanic clouds represents a key input for retrieval algorithms such as VPR (Volcanic Plume Retrieval) and LUT (Look-Up Tables), which are applied to get information on particles and SO2 total mass. 

The detection of volcanic clouds using satellite data is challenging, particularly in the presence of high quantities of water vapor. This latter, in combination with ash particles, can turn into water droplets and ice. This physical phenomenon supposes a limitation for the detection of volcanic clouds.

Mount Etna (Italy), between 2020 and 2022, has produced 66 lava fountain events. These events have generated volcanic clouds mixed with ash, ice and SO2, with a top height ranging between 4 and 13 km. In this work a Machine Learning-Based approach to detect the volcanic clouds generated during these Etna’s lava fountain events is carried out. The models have been trained and validated by exploiting a dataset that covers the 66 lava fountains observed by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument, on board of Meteosat Second Generation (MSG) geostationary satellite, aiming to get insights for the discrimination of ash, ice, and SO2 in the volcanic clouds. The results are promising for the automatic detection of volcanic clouds in near-real time.

How to cite: Naranjo, C., Guerrieri, L., Corradini, S., Merucci, L., Stelitano, D., and Picchiani, M.: Leveraging Machine Learning techniques and SEVIRI data to detect volcanic clouds composed of ash, ice, and SO2 during the 2020-2022 Etna eruption activity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10309, https://doi.org/10.5194/egusphere-egu25-10309, 2025.

How to cite: Payet--Clerc, M., Carazzo, G., Moreland, W. M., Höskuldsson, Á., Thordarson, T., and Valdimarsdottir, I. K.: Volcanic hazards associated with explosive basaltic eruptions in Iceland: A case study of the Veiðivötn 1477 CE Eruption in Central Iceland., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12005, https://doi.org/10.5194/egusphere-egu25-12005, 2025.