Barcelona Supercomputing Center, Barcelona, Spain

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.

Tephra fallout constitutes a serious threat to communities around active volcanoes. Reliable short-term 13 forecasts represent a valuable aid for scientists and civil authorities to mitigate the effects of fallout on the 14 surrounding areas during an episode of crisis. We present a platform-independent automatic procedure with Q1 15 the aim to daily forecast transport and deposition of volcanic particles. The procedure builds on a series of 16 programs and interfaces that automate the data flow and the execution and subsequent postprocess of fallout 17 models. Firstly, the procedure downloads regional meteorological forecasts for the area and time interval of 18 interest, filters and converts data from its native format, and runs the CALMET diagnostic model to obtain the 19 wind field and other micro-meteorological variables on a finer local-scale 3-D grid defined by the user. 20 Secondly, it assesses the distribution of mass along the eruptive column, commonly by means of the radial 21 averaged buoyant plume equations depending on the prognostic wind field and on the conditions at the vent 22 (granulometry, mass flow rate, etc). All these data serve as input for the fallout models. The initial version of 23 the procedure includes only two Eulerian models, HAZMAP and FALL3D, the latter available as serial and 24 parallel implementations. However, the procedure is designed to incorporate easily other models in a near 25 future with minor modifications on the model source code. The last step is to postprocess the outcomes of 26 models to obtain maps written in standard file formats. These maps contain plots of relevant quantities such 27 as predicted ground load, expected deposit thickness and, for the case of or 3-D models, concentration on air 28 or flight safety concentration thresholds

We apply a novel computational approach to assess, for the first time, volcanic ash dispersal during the Campanian Ignimbrite (Italy) super-eruption providing insights into eruption dynamics and the impact of this gigantic event. The method uses a 3D time-dependent computational ash dispersion model, a set of wind fields, and more than 100 thickness measurements of the CI tephra deposit. Results reveal that the CI eruption dispersed 250–300 km3 of ash over 3.7 million km2. The injection of such a large quantity of ash (and volatiles) into the atmosphere would have caused a volcanic winter during the Heinrich Event 4, the coldest and driest climatic episode of the Last Glacial period. Fluorine-bearing leachate from the volcanic ash and acid rain would have further affected food sources and severely impacted Late Middle-Early Upper Paleolithic groups in Southern and Eastern Europe.

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Atmospheric dispersal of a gas denser than air can threat the environment and surrounding communities if the terrain and meteorological conditions favour its accumulation in topographic depressions, thereby reaching toxic concentration levels. Numerical modelling of atmospheric gas dispersion constitutes a useful tool for gas hazard assessment studies, essential for planning risk mitigation actions. In complex terrains, microscale winds and local orographic features can have a strong influence on the gas cloud behaviour, potentially leading to inaccurate results if not captured by coarser-scale modelling. We introduce a methodology for microscale wind field characterisation based on transfer functions that couple a mesoscale numerical weather prediction model with a microscale computational fluid dynamics (CFD) model for the atmospheric boundary layer. The resulting time-dependent high-resolution microscale wind field is used as input for a shallow-layer gas dispersal model (TWODEE-2.1) to simulate the time evolution of CO2 gas concentration at different heights above the terrain. The strategy is applied to review simulations of the 1986 Lake Nyos event in Cameroon, where a huge CO2 cloud released by a limnic eruption spread downslopes from the lake, suffocating thousands of people and animals across the Nyos and adjacent secondary valleys. Besides several new features introduced in the new version of the gas dispersal code (TWODEE-2.1), we have also implemented a novel impact criterion based on the percentage of human fatalities depending on CO2 concentration and exposure time. New model results are quantitatively validated using the reported percentage of fatalities at several locations. The comparison with previous simulations that assumed coarser-scale steady winds and topography illustrates the importance of high-resolution modelling in complex terrains.

This study compares and evaluates one-dimensional (1D) and three-dimensional (3D) numerical models of volcanic eruption columns in a set of different inter-comparison exercises. The exercises were designed as a blind test in which a set of common input parameters was given for two reference eruptions, representing a strong and a weak eruption column under different meteorological conditions. Comparing the results of the different models allows us to evaluate their capabilities and target areas for future improvement. Despite their different formulations, the 1D and 3D models provide reasonably consistent predictions of some of the key global descriptors of the volcanic plumes. Variability in plume height, estimated from the standard deviation of model predictions, is within ~20% for the weak plume and ~10% for the strong plume. Predictions of neutral buoyancy level are also in reasonably good agreement among the different models, with a standard deviation ranging from 9 to 19% (the latter for the weak plume in a windy atmosphere). Overall, these discrepancies are in the range of observational uncertainty of column height. However, there are important differences amongst models in terms of local properties along the plume axis, particularly for the strong plume. Our analysis suggests that the simpli- fied treatment of entrainment in 1D models is adequate to resolve the general behaviour of the weak plume. However, it is inadequate to capture complex features of the strong plume, such as large vortices, partial column collapse, or gravitational fountaining that strongly enhance entrainment in the lower atmosphere. We conclude that there is a need to more accurately quantify entrainment rates, improve the representation of plume radius, and incorporate the effects of column instability in future versions of 1D volcanic plume models.

Large explosive volcanic eruptions can generate ash clouds from rising plumes that spread in the atmosphere around a Neutral Buoyancy Level (NBL). These ash clouds spread as inertial intrusions and are advected by atmospheric winds. For low mass flow rates, tephra transport is mainly dictated by wind advection, because ash cloud spreading due to gravity current effects is negligible (passive transport). For large mass flow rates, gravity-driven transport at the NBL can be the dominant transport mechanism. Conditions under which the passive transport assumption is valid have not yet been critically studied. We analyze the conditions when gravity-driven transport is dominant in terms of the cloud Richardson number. Moreover, we couple an analytical model that describes cloud spreading as a gravity current with an advection-diffusion model. This coupled model is used to simulate the evolution of the volcanic cloud during the climatic phase of the 1991 Pinatubo eruption. Citation: Costa, A., A. Folch, and G. Macedonio (2013), Density-driven transport in the umbrella region of volcanic clouds: Implications for tephra dispersion models.

We carry out a parametric study in order to identify and quantify the effects of uncertainties on pivotal parameters controlling the dynamics of volcanic plumes. The study builds upon numerical simulations using FPLUME, an integral steady-state model based on the Buoyant Plume Theory generalized in order to account for volcanic processes (particle fallout and re-entrainment, water phase changes, effects of wind, etc). As reference cases for strong and weak plumes, we consider the cases defined during the IAVCEI Commission on tephra hazard modeling inter-comparison study (Costa et al., 2016). The parametric study quantifies the effect of typical uncertainties on total mass eruption rate, column height, mixture exit velocity, temperature and water content, and particle size. Moreover, a sensitivity study investigates the role of wind entrainment and intensity, atmospheric humidity, water phase changes, and particle fallout and re-entrainment. Results show that the leading-order parameters that control plume height are the mass eruption rate and the air entrainment coefficient, especially for weak plumes.

Because the large emission of gas and solid particles into the atmosphere, the volcanic eruptions represent one of the most important source of natural pollution. Among different gases (mainly H2O, CO2, SO2 and HCl), the volcanic clouds contain a mix of silicate-bearing ash particles in the size range 0.1μm to mm size or larger. Interest in determining the properties, movement and extent of volcanic ash clouds is an important scientific, economic, and public safety issue because the effects on environment, public health and aviation. In particular the problem to track in real time and forecast the volcanic cloud transport is the key task for the aviation safety problems and for the political decision making. Several encounters of en-route aircrafts with volcanic ash clouds have demonstrated the harming effects of ash particles on modern aircrafts (loss of power, failure of high-bypass turbine engines, abrasion of turbine blades, windscreens, fuselage, and Pitot static tubes). Alongside these considerations also the economical problem induced by an airport closure must be taken into account. Both security and economical requirements make essential a great effort to realize robust and affordable ash cloud detection and trajectory forecasting, combining remote sensing and modeling. In this work a quantitative comparison between Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of volcanic ash cloud mass and Aerosol Optical Depth (AOD) with the FALL3D ash dispersal model has been performed. MODIS, aboard the NASA-Terra and NASA-Aqua polar satellites is a multispectral instrument with 36 spectral bands in the wavelength range from Visible (VIS) to Thermal InfraRed (TIR) and spatial resolution varying between 250 and 1000 m at nadir. The channels centered around 11 and 12 micron have been used for the ash retrievals through the Brightness Temperature Difference algorithm and MODTRAN simulations. FALL3D is a 3-D time-dependent Eulerian model for the transport and deposition of volcanic particles that outputs, among other variables, cloud column mass and AOD. In this work the Mt. Etna volcano 2002 eruptive event has been considered as test case. The results indicate a general good agreement between the mean AOT retrieved and the spatial ash dispersion in the different images, while the modeled FALL3D total mass retrieved result significantly overestimated.

Volcanic activity occurring in tropical moist atmospheres can promote deep convection and trigger volcanic thunderstorms. These phenomena, however, are rarely observed to last continuously for more than a day and so insights into the dynamics, microphysics and electrification processes are limited. Here we present a multidisciplinary study on an extreme case, where volcanically-triggered deep convection lasted for six days. We show that this unprecedented event was caused and sustained by phreatomagmatic activity at Anak Krakatau volcano, Indonesia during 22-28 December 2018. Our modelling suggests an ice mass flow rate of ~5 × 106 kg/s for the initial explosive eruption associated with a flank collapse. Following the flank collapse, a deep convective cloud column formed over the volcano and acted as a 'volcanic freezer' containing ~3 × 109 kg of ice on average with maxima reaching ~1010 kg. Our satellite analyses reveal that the convective anvil cloud, reaching 16-18 km above sea level, was ice-rich and ash-poor. Cloud-top temperatures hovered around -80 °C and ice particles produced in the anvil were notably small (effective radii ~20 µm). Our analyses indicate that vigorous updrafts (>50 m/s) and prodigious ice production explain the impressive number of lightning flashes (~100,000) recorded near the volcano from 22 to 28 December 2018. Our results, together with the unique dataset we have compiled, show that lightning flash rates were strongly correlated (R = 0.77) with satellite-derived plume heights for this event.