Volcanic hazard assessment for tephra fallout in Martinique

Mount Pelée (Martinique) is one of the most active volcanoes in the Lesser Antilles arc with more than 34 magmatic events in the last 24,000 years, including the deadliest eruption of the 20th century. The current volcanic hazard map used in the civil security plan puts the emphasis on the volcanic hazard close to the volcano. This map is however based on an incomplete eruptive history and does not take into account the variability of the expected source conditions (mass eruption rate, total erupted mass, and grain-size distribution) or the wind effect on ash dispersal. We propose here to refine the volcanic hazard map for tephra fallout by using the 2-D model of ash dispersal HAZMAP. We first simulate the maximum expected eruptive scenario at Mount Pelée (i.e., the P3 eruption) using a seasonal wind profile. Building upon the good agreement with field data, we compute probability maps based on this maximum expected scenario, which show that tephra fallout hazard could threaten not only areas close to the volcano but also the southern part of Martinique. We then use a comprehensive approach based on 16 eruptive scenarios that include new field constraints obtained in the recent years on the past Plinian eruptions of Mount Pelée volcano. Each eruptive scenario considers different values of total erupted mass and mass eruption rate, and is characterized by a given probability of occurrence estimated from the refined eruptive history of the volcano. The 1979-2019 meteorological ERA-5 database is used to further take into account the daily variability of winds. These new probability maps show that the area of probable total destruction is wider when considering the 16 scenarios compared to the maximum expected scenario. The southern part of Martinique, although less threatened than when considering the maximum expected scenario, would still be impacted both by tephra fallout and by its high dependence on the water and electrical network carried from the northern part of the island. Finally, we show that key infrastructures in Martinique (such as the international airport) have a non-negligible probability of being impacted by a future Plinian eruption of the Mount Pelée. These results provide strong arguments for and will support significant and timely reconceiving of the emergency procedures as the local authorities have now placed Mount Pelée volcano on alert level yellow (vigilance) based on increased seismicity and tremor-type signals.

Assessing potential impact of explosive volcanic eruptions from Jan Mayen Island (Norway) on aviation in the North Atlantic

Volcanic eruptions are amongst the most jeopardizing natural events due to their potential impacts on life, assets, and environment. In particular, atmospheric dispersal of volcanic tephra and aerosols during the explosive eruptions poses a serious threat to life and has significant consequences for infrastructures and global aviation safety. The volcanic island of Jan Mayen, located in the North Atlantic under trans-continental air traffic routes, is considered the northernmost active volcanic area in the world, with at least five eruptive periods recorded during the last 200 years. However, quantitative hazard assessments on the possible consequences for air traffic of a future ash-forming eruption are nonexistent. This study presents the first comprehensive long-term volcanic hazard assessment for Jan Mayen volcanic island in terms of ash dispersal and airborne tephra concentration at different flight levels. In order to delve in the characterization and modelling of that potential impact, a probabilistic approach based on merging a large number of numerical simulations is adopted, varying the volcano’s Eruptive Source Parameters (ESPs) and meteorological scenario. Each ESP value is randomly sampled following a continuous Probability Density Function (PDF) defined from the Jan Mayen geological record. Over 20 years of climatic data are considered in order to explore the natural variability associated with meteorological conditions and used to run thousands of simulations of the ash dispersal model FALL3D on a 2 km-resolution grid. The simulated scenarios are combined to produce probability maps of airborne ash concentration, arrival time and persistence at different flight levels in the atmosphere. The resulting maps represent an aid to civil protection, decision makers and aviation stakeholders in assessing and preventing the potential impact from a future eruption at Jan Mayen.

The fate of volcanic ash: premature or delayed sedimentation?

A large amount of volcanic ash produced during explosive volcanic eruptions has been found to sediment as aggregates of various types that typically reduce the associated residence time in the atmosphere (i.e., premature sedimentation). Nonetheless, speculations exist in the literature that aggregation has the potential to also delay particle sedimentation (rafting effect) even though it has been considered unlikely so far. Here, we present the first theoretical description of rafting that demonstrates how delayed sedimentation may not only occur but is probably more common than previously thought. The fate of volcanic ash is here quantified for all kind of observed aggregates. As an application to the case study of the 2010 eruption of Eyjafjallajökull volcano (Iceland), we also show how rafting can theoretically increase the travel distances of particles between 138–710 μm. These findings have fundamental implications for hazard assessment of volcanic ash dispersal as well as for weather modeling.

Modelling the Effect of Electrification on Volcanic Ash Aggregation

The fine ash released into the atmosphere (particles <63 μm) during explosive volcanic eruptions represents a significant threat for both the ecosystem and many sectors of society. In order to mitigate the associated impact, ash dispersal models need to accurately estimate ash concentration through time and space. Since most fine ash sediments in the form of aggregates, ash dispersal models require a quantitative description of ash aggregation. The physical and chemical processes involved in the collision and sticking of volcanic ash have been extensively studied in the last few decades. Among the different factors affecting volcanic particle aggregation (e.g., turbulence, particle-particle adhesion, presence of liquid and solid water), the charge carried by volcanic particles has been found to play a crucial role. However, Coulomb interactions are not yet taken into account in existing models. In order to fill this gap, we propose a strategy to take charge into account. In particular, we introduce a quantitative model for aggregation of oppositely charged micron—to millimetre-sized objects settling in still air. Our results show that the presence of charge considerably enhances the collision efficiency when one of the colliding objects is very small (<20 µm), and that the sticking efficiency is not affected by particle charge if colliding objects are either small enough (<20 µm) or large enough (>200 µm). Besides providing a theoretical framework to quantify the effect of charge, our findings demonstrate that aggregation models that do not account for electrification significantly underestimate the amount of fine ash that sediments in the form of aggregates, leading to an overestimation of the residence time of fine ash in the atmosphere after explosive volcanic eruptions.

Ensemble-Based Data Assimilation of Volcanic Ash Clouds from Satellite Observations: Application to the 24 December 2018 Mt. Etna Explosive Eruption

Accurate tracking and forecasting of ash dispersal in the atmosphere and quantification of its uncertainty are of fundamental importance for volcanic risk mitigation. Numerical models and satellite sensors offer two complementary ways to monitor ash clouds in real time, but limits and uncertainties affect both techniques. Numerical forecasts of volcanic clouds can be improved by assimilating satellite observations of atmospheric ash mass load. In this paper, we present a data assimilation procedure aimed at improving the monitoring and forecasting of volcanic ash clouds produced by explosive eruptions. In particular, we applied the Local Ensemble Transform Kalman Filter (LETKF) to the results of the Volcanic Ash Transport and Dispersion model HYSPLIT. To properly simulate the release and atmospheric transport of volcanic ash particles, HYSPLIT has been initialized with the results of the eruptive column model PLUME-MoM. The assimilation procedure has been tested against SEVIRI measurements of the volcanic cloud produced during the explosive eruption occurred at Mt. Etna on 24 December 2018. The results show how the assimilation procedure significantly improves the representation of the current ash dispersal and its forecast. In addition, the numerical tests show that the use of the sequential Ensemble Kalman Filter does not require a precise initialization of the numerical model, being able to improve the forecasts as the assimilation cycles are performed.

Volcanic ash forecast using ensemble-based data assimilation: an ensemble transform Kalman filter coupled with the FALL3D-7.2 model (ETKF–FALL3D version 1.0)

Quantitative volcanic ash cloud forecasts are prone to uncertainties coming from the source term quantification (e.g., the eruption strength or vertical distribution of the emitted particles), with consequent implications for an operational ash impact assessment. We present an ensemble-based data assimilation and forecast system for volcanic ash dispersal and deposition aimed at reducing uncertainties related to eruption source parameters. The FALL3D atmospheric dispersal model is coupled with the ensemble transform Kalman filter (ETKF) data assimilation technique by combining ash mass loading observations with ash dispersal simulations in order to obtain a better joint estimation of the 3-D ash concentration and source parameters. The ETKF–FALL3D data assimilation system is evaluated by performing observing system simulation experiments (OSSEs) in which synthetic observations of fine ash mass loadings are assimilated. The evaluation of the ETKF–FALL3D system, considering reference states of steady and time-varying eruption source parameters, shows that the assimilation process gives both better estimations of ash concentration and time-dependent optimized values of eruption source parameters. The joint estimation of concentrations and source parameters leads to a better analysis and forecast of the 3-D ash concentrations. The results show the potential of the methodology to improve volcanic ash cloud forecasts in operational contexts.

Experimental High-Resolution Forecasting of Volcanic Ash Hazard at Sakurajima, Japan

A high-resolution forecast methodology for the ash hazard at Sakurajima volcano, Japan, is presented. The methodology employs a combined modeling approach and utilizes eruption source parameters estimated by geophysical observations from Sakurajima, allowing for a proactive approach in forecasting. The Weather Research and Forecasting (WRF) model is used to downscale Japan Meteorological Agency (JMA) forecast data over the area of interest. The high-resolution meteorological data are then used in FALL3D model to provide a forecast for the ash dispersal and deposition. The methodology is applied for an eruption that occurred on June 16, 2018. Disdrometer observations of ashfall are used along with ash dispersal modeling to inform the choice of the total grain size distribution (TGSD). A series of pseudo-forecast ash dispersal simulations are then carried out using the proposed methodology and estimated TGSD, initialized with meteorological forecast data released up to ∼13 hours before the eruption, with results showing surprising consistency up to ∼10 hours before the eruption. Using forecast data up to 4 hours before the eruption was seen to constrain observation to model ratios within a factor of 2–4 depending on the timing of simulation and location. A number of key future improvements for the methodology are also highlighted.