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Glacial ripping involves glaciotectonic disintegration of rock hills and extensive removal of rock at the ice-sheet bed, triggered by hydraulic jacking caused by fluctuating water pressures. Evidence from eastern Sweden shows that glacial ripping caused significant subglacial erosion during the final deglaciation of the Fennoscandian ice sheet, distinct from abrasion and plucking (quarrying). Here we analyse the ice drag forces exerted onto rock obstacles at the base of an ice sheet, and the resisting forces of such rock obstacles: glaciotectonic disintegration requires that ice drag forces exceed the resisting forces of the rock obstacle. We consider rock obstacles of different sizes, shapes and fracture patterns, informed by natural examples from eastern Sweden. Our analysis shows that limited overpressure events, unfavourable fracture patterns, low-transmissivity fractures, slow ice and streamlined rock hamper rock hill disintegration. Conversely, under fast ice flow and fluctuating water pressures, disintegration is possible if the rock hill contains subhorizontal, transmissive fractures. Rock steps on previously smooth, abraded surfaces, caused by hydraulic jacking, also enhance drag forces and can cause disintegration of a rock hill. Glacial ripping is a physically plausible erosion mechanism, under realistic glaciological conditions prevalent near ice margins.

Pyroclastic density currents (PDCs) are hazardous and destructive phenomena that pose a significant threat to communities living in the proximity of active volcanoes. PDCs are ground-hugging density currents comprised of high temperature mixtures of pyroclasts, lithics, and gas that can propagate kilometres away from their source. The physical properties of the solid particles, such as their grain size distribution, morphology, density, and componentry play a crucial role in determining the dynamics and impact of these flows. The modification of these properties during transport also records the causative physical processes such as deposition and particle fragmentation. Understanding these processes from the study of deposits from PDCs and related co-PDC plumes is essential for developing effective hazard assessment and risk management strategies. In this article, we describe the importance and relevance of the physical properties of PDC deposits and provide a perspective on the challenges associated with their measurement and characterization. We also discuss emerging topics and future research directions such as electrical charging, granular rheology, ultra-fine ash and thermal and surface properties that are underpinned by the characterization of pyroclasts and their interactions at the micro-scale. We highlight the need to systematically integrate experiments, field observations, and laboratory measurements into numerical modelling approaches for improving our understanding of PDCs. Additionally, we outline a need for the development of standardised protocols and methodologies for the measurement and reporting of physical properties of PDC deposits. This will ensure comparability, reproducibility of results from field studies and also ensure the data are sufficient to benchmark future numerical models of PDCs. This will support more accurate simulations that guide hazard and risk assessments.

Practising and testing emergency procedures are fundamental for ensuring an effective operational response to a crisis. In this presentation we will introduce a new series of exercises which have been developed to test the multi-agency response needed to produce volcanic ash forecasts at the London Volcanic Ash Advisory Centre (VAAC). Our exercises have been specifically designed to practice our ability to interpret and evaluate model simulations and observations, the pull through of international scientific expertise into the London VAAC, and decision-making procedures under uncertainty. In this presentation we will describe our exercise methodology, this includes the development of simulated observations for exercise conditions, and a framework for comparing transport and dispersion simulations generated using different model setups (multi-model ensemble). We will also discuss how we practice the necessary interactions between scientists supporting the London VAAC and external collaborators, which may include experts at volcano observatories, national/state geological or geophysical institutions, and volcano research institutions. We will present case-studies of exercises for hypothetical events in Iceland and outline the lessons learnt. Our Exercises have not only improved our ability to respond to a volcanic ash cloud event but have also driven scientific and technical improvement of the forecasts, and strengthened the relationships between collaborators and responders, with the aim of providing the best possible advice to the London VAAC.

The atmospheric dispersion of gases (of natural or industrial origins) can be very hazardous to life and the environment if the concentration of some gas species overcome specie-specific thresholds. In this context, the natural variability associated to the natural phenomena has to be explored to provide robust probabilistic gas dispersion hazard assessments. VIGIL-1.3 (automatic probabilistic VolcanIc Gas dIspersion modeLling) is a Python simulation tool born to automatize the complex and time-consuming simulation workflow required to process a large number of gas dispersion numerical simulations. It is interfaced with two models: a dilute (DISGAS) and a dense gas (TWODEE-2) dispersion model. The former is used when the density of the gas plume at the source is lower than the atmospheric density (e.g. fumaroles), the latter when the gas density is higher than the atmosphere and the gas accumulates on the ground and may flow due to the density contrast with the atmosphere to form a gravity current (e.g. cold CO2 flows). In the enhancement of the code towards a higher-scale computing, here we present the ongoing improvements aimed to extend some code functionalities such as memory management, modularity revision, and full-ensemble uncertainty on gas dispersal scenarios (e.g. sampling techniques for gas fluxes and source locations). Optimizations are also provided in terms of tracking errors, redesignation of the input file, validation of data provided by the users, and addition of the Latin hypercube sampling (LHS) for the post-processing of model outputs. All these new features will be issued in the future release of the code (VIGIL-2.0) in order to facilitate the users which could run VIGIL on laptops or large supercomputer, and to widen the spectrum of model applications from routinely operational forecast of volcanic gas to long-term hazard and/or risk assessments purposes.

Probabilistic volcanic hazard assessment is a standard methodology based on running a deterministic hazard quantification tool multiple times to explore the full range of uncertainty in the input parameters and boundary conditions, in order to probabilistically quantify the variability of outputs accounting for such uncertainties. Nowadays, different volcanic hazards are quantified by means of this approach. Among these, volcanic gas emission is particularly relevant given the threat posed to human health if concentrations and exposure times exceed certain thresholds. There are different types of gas emissions but two main scenarios can be recognized: hot buoyant gas emissions from fumaroles and the ground and dense gas emissions feeding density currents that can occur, e.g., in limnic eruptions. Simulation tools are available to model the evolution of critical gas concentrations over an area of interest. Moreover, in order to perform probabilistic hazard assessments of volcanic gases, simulations should account for the natural variability associated to aspects such as seasonal and daily wind conditions, localized or diffuse source locations, and gas fluxes. Here we present VIGIL (automatized probabilistic VolcanIc Gas dIspersion modeLling), a new Python tool designed for managing the entire simulation workflow involved in single and probabilistic applications of gas dispersion modelling. VIGIL is able to manage the whole process from meteorological data processing, needed to run gas dispersion in both the dilute and dense gas flow scenarios, to the post processing of models’ outputs. Two application examples are presented to show some of the modelling capabilities offered by VIGIL.

Glacial ripping involves glaciotectonic disintegration of rock hills and extensive removal of rock at the ice-sheet bed, triggered by hydraulic jacking caused by fluctuating water pressures. Evidence from eastern Sweden shows that glacial ripping caused significant subglacial erosion during the final deglaciation of the Fennoscandian ice sheet, distinct from abrasion and plucking (quarrying). Here we analyse the ice drag forces exerted onto rock obstacles at the base of an ice sheet, and the resisting forces of such rock obstacles: glaciotectonic disintegration requires that ice drag forces exceed the resisting forces of the rock obstacle. We consider rock obstacles of different sizes, shapes and fracture patterns, informed by natural examples from eastern Sweden. Our analysis shows that limited overpressure events, unfavourable fracture patterns, low-transmissivity fractures, slow ice and streamlined rock hamper rock hill disintegration. Conversely, under fast ice flow and fluctuating water pressures, disintegration is possible if the rock hill contains subhorizontal, transmissive fractures. Rock steps on previously smooth, abraded surfaces, caused by hydraulic jacking, also enhance drag forces and can cause disintegration of a rock hill. Glacial ripping is a physically plausible erosion mechanism, under realistic glaciological conditions prevalent near ice margins.

Probabilistic volcanic hazard assessment is a standard methodology based on running a deterministic hazard quantification tool multiple times to explore the full range of uncertainty in the input parameters and boundary conditions, in order to probabilistically quantify the variability of outputs accounting for such uncertainties. Nowadays, different volcanic hazards are quantified by means of this approach. Among these, volcanic gas emission is particularly relevant given the threat posed to human health if concentrations and exposure times exceed certain thresholds. There are different types of gas emissions but two main scenarios can be recognized: hot buoyant gas emissions from fumaroles and the ground and dense gas emissions feeding density currents that can occur, e.g., in limnic eruptions. Simulation tools are available to model the evolution of critical gas concentrations over an area of interest. Moreover, in order to perform probabilistic hazard assessments of volcanic gases, simulations should account for the natural variability associated to aspects such as seasonal and daily wind conditions, localized or diffuse source locations, and gas fluxes. Here we present VIGIL (automatized probabilistic VolcanIc Gas dIspersion modeLling), a new Python tool designed for managing the entire simulation workflow involved in single and probabilistic applications of gas dispersion modelling. VIGIL is able to manage the whole process from meteorological data processing, needed to run gas dispersion in both the dilute and dense gas flow scenarios, to the post processing of models' outputs. Two application examples are presented to show some of the modelling capabilities offered by VIGIL.

Large‐scale experiments generating ground‐hugging multiphase flows were carried out with the aim of modelling the rate of sedimentation, of pyroclastic density currents. The current was initiated by the impact on the ground of a dense gas‐particle fountain issuing from a vertical conduit. On impact, a thick massive deposit was formed. The grain size of the massive deposit was almost identical to that of the mixture feeding the fountain, suggesting that similar layers formed at the impact of a natural volcanic fountain should be representative of the parent grain‐size distribution of the eruption. The flow evolved laterally into a turbulent suspension current that sedimented a thin, tractive layer. A good correlation was found between the ratio of transported/sedimented load and the normalized Rouse number of the turbulent current. A model of the sedimentation rate was developed, which shows a relationship between grain size and flow runout. A current fed with coarser particles has a higher sedimentation rate, a larger grain‐size selectivity and runs shorter than a current fed with finer particles. Application of the model to pyroclastic deposits of Vesuvius and Campi Flegrei of Southern Italy resulted in sedimentation rates falling inside the range of experiments and allowed definition of the duration of pyroclastic density currents which add important information on the hazard of such dangerous flows. The model could possibly be extended, in the future, to other geological density currents as, for example, turbidity currents.

1.X-Ray computed microtomography is a non-destructive 3D imaging technique that can be used for the investigation of both the morphology and internal structures of a solid object. Thanks to its versatility, it is currently of common use in many research fields and applications, from medical science to geosciences. The latter include volcanology, where this analytical technique is becoming increasingly popular, in particular for quantifying the shape as well as the internal structure of particles constituting tephra deposits. Particle morphology plays a major role in controlling the mobility of pyroclastic material in the atmosphere and particle-laden flows, while the internal structure (e.g. vesicles and crystal content) is of importance for constraining the processes occurring in magmatic chamber or volcanic conduits. In this paper, we present results of X-Ray microtomography morphological and textural analyses on volcanic particles carried out to study how particle shape is influenced by their internal structures. Particles were selected from tephra generated during explosive eruptions of different magnitude and composition. Results show how particle morphology is strongly influenced by their internal structure, which is characterized by textural features like vesicularity, vesicle and solid structure distribution, vesicles inter-connection and distance between adjacent vesicles. These have been found to vary with magma composition, vesiculation and crystallization history. Furthermore, our results confirm that X-Ray microtomography is a powerful tool for investigating shape and internal structure of particles. It both allows us to characterize the particle shape by means of tridimensional shape parameters and to relate them to their internal structures.