Volcanic Ash Dispersion Research Articles

Insights into the sticking probability of volcanic ash particles from laboratory experiments

Although the characterization of the sticking and aggregation probability is essential to the description of volcanic ash dispersal and sedimentation, there is still no general model describing the sticking probability of volcanic ash. Experiments of dry particle–plate collisions in an enclosed box were carried out to characterize quantitatively the sticking efficiency of volcanic particles and silica beads in a limit case scenario where the mass of one of the particles is much greater than the others. Silica beads and volcanic particles from a Sakurajima Vulcanian eruption were filmed impacting a glass plate with a High-Speed Camera. The sticking probability is calculated from an equation depending on the particle diameter, impact velocity, and two experimental parameters (a, q). Particle size was found to dominantly control the sticking probability, with small particles more likely sticking on the glass plate than large particles. These experiments represent a significant step forward in the quantification of the sticking efficiency of fine volcanic ash (< 63 μm).

Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling

Probabilistic forecasting of volcanic ash dispersion involves simulating an ensemble of realistic event scenarios to estimate the probability of a particular hazard threshold being exceeded. Although the number of samples that make up the ensemble, how they are chosen, and the desired threshold all set the uncertainty of (or confidence in) the estimated exceedance probability, current practice does not quantify and communicate the uncertainty in ensemble predictions. In this study, we use standard statistical methods to estimate the variance in probabilistic ensembles and use this measure of uncertainty to assess different sampling strategies for the wind field, using the example of volcanic ash transport from a representative explosive eruption in Iceland. For stochastic (random) sampling of the wind field, we show how the variance is reduced with increasing ensemble size and how the variance depends on the desired hazard threshold and the proximity of a target site to the volcanic source. We demonstrate how estimated variances can be used to compare different ensemble designs, by comparing stochastic forecasts with forecasts obtained from a stratified sampling approach using a set of 29 Northern European weather regimes, known as Grosswetterlagen (GWL). Sampling wind fields from within the GWL regimes reduces the number of samples needed to achieve the same variance as compared to conventional stochastic sampling. Our results show that uncertainty in volcanic ash dispersion forecasts can be straightforwardly calculated and communicated, and highlight the need for the volcanic ash forecasting community and operational end-users to jointly choose acceptable levels of variance for ash forecasts in the future.

An automated ash dispersion forecast system: case study Popocatépetl volcano, Mexico

An operational volcanic ash dispersion forecast system was developed for Popocatépetl. It runs automatically every day developing 108 possible scenarios of ash dispersion for the following 36 h. Scenarios are simulated for three eruption column heights: 3 km, 5 km, and 10 km above the volcano’s crater level, every hour for eruptions lasting 1 h. For each hypothetical eruption that starts every hour, the dispersion during the following 8 h is modelled. The system uses the Weather Research and Forecasting (WRF) model for weather data and the Fall3D model. It includes a visualization website that displays, among other products: ground accumulation, deposit load, and concentration at relevant flight levels. Popocatépetl volcano, located ~ 60 km from Mexico Megacity was selected as a case study. A comparison from ash forecast system results and satellite observations is presented. The system developed and tested here can be adapted to be operative at any volcano.

Optimizing mass eruption rate estimates by combining simple plume models

Tephra injected into the atmosphere by volcanic ash plumes poses one of the key hazards in explosive eruptions. Forecasting the atmospheric dispersal of volcanic ash requires good knowledge of the current eruption source parameters, in particular of the mass eruption rate (MER), which quantifies the mass flow rate of gas and tephra at the vent. Since this parameter cannot be directly measured in real-time, monitoring efforts aim to assess the MER indirectly, for example, by applying plume models that link the (relatively easily detectable) plume height with the mass flux at the vent. By comparing the model estimates with independently acquired fallout measurements from the 130 eruptions listed in the Independent Volcanic Eruption Source Parameter Archive (Aubry et al., J. Volcanol. Geotherm. Res., 2021, 417), we tested the success rates of six 0D plume models along with four different modelling approaches with the aim to optimize MER prediction. According to our findings, instead of simply relying on the application of one plume model for all situations, the accuracy of MER forecast can be increased by mixing the plume models via model weight factors when these factors are appropriately selected. The optimal choice of model weight factors depends on the availability and type of volcanological and meteorological information for the eruption monitored. A decision tree is presented that assists the reader in finding the optimal modelling strategy to ascertain highest MER forecast accuracy.

Aeolus winds impact on volcanic ash early warning systems for aviation

Forecasting volcanic ash atmospheric pathways is of utmost importance for aviation. Volcanic ash can interfere with aircraft navigational instruments and can damage engine parts. Early warning systems, activated after volcanic eruptions can alleviate the impacts on aviation by providing forecasts of the volcanic ash plume dispersion. The quality of these short-term forecasts is subject to the accuracy of the meteorological wind fields used for the initialization of regional models. Here, we use wind profiling data from the first high spectral resolution lidar in space, Aeolus, to examine the impact of measured wind fields on regional NWP and subsequent volcanic ash dispersion forecasts, focusing on the case of Etna’s eruption on March 2021. The results from this case study demonstrate a significant improvement of the volcanic ash simulation when using Aeolus-assimilated meteorological fields, with differences in wind speed reaching up to 8 m/s when compared to the control run. When comparing the volcanic ash forecast profiles with downwind surface-based aerosol lidar observations, the modeled field is consistent with the measurements only when Aeolus winds are assimilated. This result clearly demonstrates the potential of Aeolus and highlights the necessity of future wind profiling satellite missions for improving volcanic ash forecasting and hence aviation safety.

Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure

Abstract. A large volcanic eruption can generate large amounts of ash which affect the socio-economic activities of surrounding areas, affecting airline transportation, socio-economics activities, and human health. Accumulated ashfall has devastating impacts on areas surrounding the volcano and in other regions, and eruption scale and weather conditions may escalate ashfall hazards to wider areas. It is crucial to discover places with a high probability of exposure to ashfall deposition. Here, as a reference for ashfall disaster countermeasures, we present a dataset containing the estimated distributions of the ashfall deposit and airborne ash concentration, obtained from a simulation of ash dispersal following a large-scale explosive volcanic eruption. We selected the Taisho (1914) eruption of the Sakurajima volcano, as our case study. This was the strongest eruption in Japan in the last century, and our study provides a baseline for a worst-case scenario. We employed one eruption scenario (OES) approach by replicating the actual event under various extended weather conditions to show how it would affect contemporary Japan. We generated an ash dispersal dataset by simulating the ash transport of the Taisho eruption scenario using a volcanic ash dispersal model and meteorological reanalysis data for 64 years (1958–2021). We explain the dataset production and provide the dataset in multiple formats for broader audiences. We examine the validity of the dataset, its limitations, and its uncertainties. Countermeasure strategies can be derived from this dataset to reduce ashfall risk. The dataset is available at the DesignSafe-CI Data Depot: https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-2848v2 or through the following DOI: https://doi.org/10.17603/ds2-vw5f-t920 by selecting Version 2 (Rahadianto and Tatano, 2020).

Growth of complex volcanic ash aggregates in the Tierra Blanca Joven eruption of Ilopango Caldera, El Salvador

Aggregation processes control both the residence time and dispersal of volcanic ash during eruptions yet remain incompletely understood. The products of aggregation vary from simple ash clusters to large, complexly layered accretionary lapilli. Here we detail the micro-stratigraphy of a single population of accretionary lapilli that grew during the ∼431 CE Tierra Blanca Joven eruption from Ilopango Caldera, El Salvador. The accretionary lapilli were sampled 10 km from the caldera source within a sequence of ash-rich pyroclastic density current deposits and intercalated fall material, known as unit D, which is traceable >40 km from Ilopango. Scanning electron microscopy and image analysis reveal common facies that form distinct layers within the accretionary lapilli. Each facies is distinguished by quantitative and qualitative variations in particle size distribution, porosity, and particle fabric. We infer that these textures resulted from aggregation conditions that differed in terms of liquid water availability, particle concentration and grain size distributions. In our proposed model, a characteristic sequence of facies accreted from core to rim in the accretionary lapilli during passage through ash clouds generated by vent-derived plumes and pyroclastic density currents. The accretionary lapilli are mostly composed of smaller aggregates (ash clusters, ash pellets) and grew predominantly by accretion of already-formed aggregates, rather than by grain-by-grain accretion of individual particles. This finding is consistent with observations of rapid aggregate growth in volcanic plumes, suggesting a common evolutionary pathway for accretionary lapilli formation across diverse eruptions.

Forecasting and communicating the dispersion and fallout of ash during volcanic eruptions: lessons from the September 20, 2020 eruptive pulse at Sangay volcano, Ecuador

Volcanic ash is a hazard to human health and activities. Accurate and timely forecasts coupled with effective communication about the dispersion and fallout of volcanic ash during explosive events are essential to reduce impacts on local communities and limit economic losses. In this study, we present the first detailed description of an eruptive pulse at Sangay volcano and its eruption source parameters. The eruptive pulse on September 20, 2020, started at about 9:20 UTC and lasted between 90 and 100 min, producing an eruptive column that rapidly separated into (1) a higher (15.2 km above sea level, asl), gas-rich cloud moving east-southeast and (2) a lower (12.2 km asl), ash-rich cloud moving west and causing ash fallout up to 280 km from the volcano. Field data collected immediately after the event allow estimating the volume of bulk tephra to be between 1.5 and 5.0 × 106 m3, corresponding to a volcanic explosivity index of 2. The eruptive pulse, identified as violent Strombolian, emitted andesitic ash that was more mafic than products ejected by Sangay volcano in recent decades. Component analysis and glass chemistry of juvenile particles support the hypothesis that this event excavated deeper into the upper conduit compared to typical Strombolian activity at Sangay volcano, while grain-size analysis allows reconstruction of the total grain-size distribution of the fallout deposit. The discrepancies between the ash fallout simulations performed with the Ash3D online tool and the actual deposit are mainly the result of inaccurate pre- and syn-eruptive configurations and highlight the importance of additional processes such as aggregation. Communication products issued during the event included (1) several standard short reports, (2) volcano observatory notices for aviation, (3) social media posts, and (4) a special report providing the results of the ash fallout simulation. Although communication was effective with the authorities and the connected population, an effort must be made to reach the most vulnerable isolated communities for future events. This study shows that forecasting ash dispersion and fallout during volcanic eruptions can guide early warnings and trigger humanitarian actions, and should become a standard in volcano observatories worldwide.

Using an Ensemble Filter to Improve the Representation of Temporal Source Variations in a Volcanic Ash Forecasting System

The use of ensemble models to forecast the dispersion and transport of airborne volcanic ash in operational contexts is increasingly being explored. The ensemble members are usually constructed to represent a priori uncertainty estimates in meteorological fields and volcanic ash source parameters. Satellite data can be used to further filter ensemble members within an analysis time window by rejecting poorly performing members, leading to improved forecasts. In this study, the ensemble filtering technique is used to improve the representation of temporal source variations. Ensemble members are initially created by representing the source time variations as random functions of time that are modulated by crude initial estimates of the variations estimated from satellite imagery. Ensemble filtering is then used to remove members whose fields match poorly with observations within a specified analysis time window that are represented by satellite retrievals of volcanic ash properties such as mass load, effective radius, and cloud top height. The filtering process leads to an ensemble with statistics in closer agreement with the observations. It is shown in the context of the 30 May 2014 Sangeang Api eruption case study that this method leads to significantly enhanced forecasting skill beyond the analysis time window—about 20% improvement on average—when compared to a system that assumes constant emission rates for the duration of the eruption, as is the case in many operational volcanic ash forecasting systems.

Recognition of the Airspace Affected by the Presence of Volcanic Ash from Popocatepetl Volcano Using Historical Satellite Images

A volcanic eruption can produce large ash clouds in the atmosphere around a volcano, affecting commercial aviation use of the airspace around the volcano. Encountering these ash clouds can cause severe damage to different parts of the aircraft, mainly the engines. This work seeks to contribute to the development of methods for observing the dispersion of volcanic ash and to complement computational methods that are currently used for the prediction of ash dispersion. The method presented here is based on the frequency of occurrence of the regions of airspace areas affected by ash emission during a volcanic eruption. Popocatepetl volcano, 60 km east of Mexico City is taken as a case study. A temporal wind analysis was carried out at different atmospheric levels, to identify the direction towards which the wind disperses ash at different times of the year. This information showed two different trends, related to seasons in the direction of dispersion: the first from November to May and the second from July to September. To identify the ash cloud and estimate its area, a set of 920 MODIS images that recorded Popocatepetl volcanic activity between 2000 and 2021 was used. These satellite images were subjected to a semi-automatic, digital pre-processing of binarization by thresholds, according to the level of the brightness temperature difference between band 31 (11 µm) and band 32 (12 µm), followed by manual evaluation of each binarized image. With the information obtained by the processing of the MODIS image, an information table was built with the geographical position of each pixel characterized by the presence of ash for each event. With these data, the areas around Popocatepetl volcano with the highest frequency of affectation by ash emissions were identified during the period analyzed. This study seeks to complement the results obtained by numerical models that make forecasts of ash dispersions and that are very important for the prevention of air navigation risks.

Refining an ensemble of volcanic ash forecasts using satellite retrievals: Raikoke 2019

Abstract. Volcanic ash advisories are produced by specialised forecasters who combine several sources of observational data and volcanic ash dispersion model outputs based on their subjective expertise. These advisories are used by the aviation industry to make decisions about where it is safe to fly. However, both observations and dispersion model simulations are subject to various sources of uncertainties that are not represented in operational forecasts. Quantification and communication of these uncertainties are fundamental for making more informed decisions. Here, we develop a data assimilation method that combines satellite retrievals and volcanic ash transport and dispersion model (VATDM) output, considering uncertainties in both data sources. The methodology is applied to a case study of the 2019 Raikoke eruption. To represent uncertainty in the VATDM output, 1000 simulations are performed by simultaneously perturbing the eruption source parameters, meteorology, and internal model parameters (known as the prior ensemble). The ensemble members are filtered, based on their level of agreement with the ash column loading, and their uncertainty, of the Himawari–8 satellite retrievals, to produce a constrained posterior ensemble. For the Raikoke eruption, filtering the ensemble skews the values of mass eruption rate towards the lower values within the wider parameters ranges initially used in the prior ensemble (mean reduces from 1 to 0.1 Tg h−1). Furthermore, including satellite observations from subsequent times increasingly constrains the posterior ensemble. These results suggest that the prior ensemble leads to an overestimate of both the magnitude and uncertainty in ash column loadings. Based on the prior ensemble, flight operations would have been severely disrupted over the Pacific Ocean. Using the constrained posterior ensemble, the regions where the risk is overestimated are reduced, potentially resulting in fewer flight disruptions. The data assimilation methodology developed in this paper is easily generalisable to other short duration eruptions and to other VATDMs and retrievals of ash from other satellites.

Using Eruption Source Parameters and High-Resolution Grain-Size Distributions of the 7.7 ka Cleetwood Eruption of Mount Mazama (Oregon, United States) to Reveal Primary and Secondary Eruptive Processes

Numerical simulations of real-time volcanic ash dispersal forecasts and ensuing tephra hazard assessments rely on field-derived Eruption Source Parameters (ESPs) such as plume height, erupted volume, mass eruption rate and the Total Grain-Size Distribution (TGSD) of particles ejected from a volcano into the atmosphere. Here we calculate ESPs for the ∼7.7 ka Cleetwood eruption of Mount Mazama (Crater Lake/giiwas, Oregon, United States) that immediately preceded the caldera-forming eruption. We also introduce a novel approach to produce high-resolution grain-size distributions (GSDs) of individual samples over a wide range of particle sizes (0.00035–35 mm) by combining laser diffraction with dynamic image analysis. Detailed field analysis allows us to divide the Cleetwood eruptive sequence into a series of two distinct and consecutive VEI 4 eruptions: the lower (∼0.98 km3) and upper (∼0.20 km3) Cleetwood units. The lower Cleetwood was the most intense with a plume height of ∼19 km and an average mass discharge rate of ∼3.1 × 107 kg s−1. Its TGSD yields a fractal dimension D∼3.1, like other similar eruptions. All twelve high-resolution GSDs produced in this study exhibit two systematic breaks in slope from a power-law relationship at ∼0.125 and ∼0.510 mm. These breaks in slope create three segments: S1 (&amp;lt;0.125 mm), S2 (0.125–0.510 mm), and S3 (&amp;gt;0.510 mm) that can be fit by power-law relationships with fractal dimensions of D1 = 2.5 ± 0.2, D2 = 0.5 ± 0.1, and D3 = 3.6 ± 1.1, respectively. Together with ESPs and detailed componentry, D values at various locations give insight into magma fragmentation and tephra transport. We find that D1 values are positively correlated with the median grain-size and are similar to values found in rapid decompression magma fragmentation experiments. We infer that D1 values reflect the size distribution of the primary products of magma fragmentation and could thus be used to infer the potential energy at fragmentation. We interpret the relatively low values of D2 to an increase in dense components due to particle rafting. Our work shows that comparing high-resolution GSDs at several locations on the dispersal axis can further constrain primary and secondary eruptive processes, which prove crucial to improving tephra hazard assessments and dispersal forecasting.

Data assimilation of volcanic aerosol observations using FALL3D+PDAF

Abstract. Modelling atmospheric dispersal of volcanic ash and aerosols is becoming increasingly valuable for assessing the potential impacts of explosive volcanic eruptions on buildings, air quality, and aviation. Management of volcanic risk and reduction of aviation impacts can strongly benefit from quantitative forecasting of volcanic ash. However, an accurate prediction of volcanic aerosol concentrations using numerical modelling relies on proper estimations of multiple model parameters which are prone to errors. Uncertainties in key parameters such as eruption column height and physical properties of particles or meteorological fields represent a major source of error affecting the forecast quality. The availability of near-real-time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context by incorporating observations into numerical models. Specifically, ensemble-based filters aim at converting a prior ensemble of system states into an analysis ensemble by assimilating a set of noisy observations. Previous studies dealing with volcanic ash transport have demonstrated that a significant improvement of forecast skill can be achieved by this approach. In this work, we present a new implementation of an ensemble-based data assimilation (DA) method coupling the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The FALL3D+PDAF system runs in parallel, supports online-coupled DA, and can be efficiently integrated into operational workflows by exploiting high-performance computing (HPC) resources. Two numerical experiments are considered: (i) a twin experiment using an incomplete dataset of synthetic observations of volcanic ash and (ii) an experiment based on the 2019 Raikoke eruption using real observations of SO2 mass loading. An ensemble-based Kalman filtering technique based on the local ensemble transform Kalman filter (LETKF) is used to assimilate satellite-retrieved data of column mass loading. We show that this procedure may lead to nonphysical solutions and, consequently, conclude that LETKF is not the best approach for the assimilation of volcanic aerosols. However, we find that a truncated state constructed from the LETKF solution approaches the real solution after a few assimilation cycles, yielding a dramatic improvement of forecast quality when compared to simulations without assimilation.

Probabilistic Hazard Maps of Volcanic Ash Dispersion and Fallout from Lascar Volcano: Implications for Argentine Territory and Surroundings Areas

Probabilistic Hazard Maps of Volcanic Ash Dispersion and Fallout from Lascar Volcano: Implications for Argentine Territory and Surroundings Areas

Simulation Of The Volcanic Ash Dispersion During The June 2019 Sinabung Eruption

The eruption of Sinabung on June 9, 2019, was categorized as a red code in the warning report for flights. Volcanic ash from volcanic eruptions is a serious threat in the world of aviation with the most dangerous ash particles are 6-10 μm and 37 μm in diameter. To enrich our understanding and modeling performances of the volcanic ash dispersion for the Sinabung eruption case, it is necessary to simulate the dispersion of volcanic ash in those particular sizes to see its distribution which can impact flight routes. The method used was the analysis of the direction and dispersion of the particular volcanic ash using Weather Research Forecast-Chemistry (WRF-Chem) and compared it with the volcanic ash warning information on flight routes issued by Volcanic Ash Advisory Centers (VAAC)-Darwin. In general, WRF-Chem can simulate the distribution of volcanic ash from the eruption of Sinabung at the two-particle sizes at different heights, and found the difference in the distribution direction of the two groups of the particle sizes. Comparison results with warning information from VAAC-Darwin and previous study, WRF-Chem simulation shows a good concordance in the dispersion direction.

The volcanic ash dispersion simulation of Soputan with PUFF Lagrangian method

Volcanic ash is dangerous for aviation because it can harm the plane engine. This study built a simulation of volcanic ash dispersion of Soputan in Indonesia, which erupted in December 2018 with the combination of the PUFF and Lagrangian methods. These combination methods gave a better result because it included the advection, diffusion, sedimentation vector, the geographic factor, wind area, eruption time and duration, and lifetime particle in the air. The simulation result was compared with the satellite image from Volcanic Ash Advisory and calculated the area ratio (AR) as well as the angular deviation (α).

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.

FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 2: Model validation

Abstract. This paper presents model validation results for the latest version release of the FALL3D atmospheric transport model. The code has been redesigned from scratch to incorporate different categories of species and to overcome legacy issues that precluded its preparation towards extreme-scale computing. The model validation is based on the new FALL3D-8.0 test suite, which comprises a set of four real case studies that encapsulate the major features of the model; namely, the simulation of long-range fine volcanic ash dispersal, volcanic SO2 dispersal, tephra fallout deposits and the dispersal and deposition of radionuclides. The first two test suite cases (i.e. the June 2011 Puyehue-Cordón Caulle ash cloud and the June 2019 Raikoke SO2 cloud) are validated against geostationary satellite retrievals and demonstrate the new FALL3D data insertion scheme. The metrics used to validate the volcanic ash and SO2 simulations are the structure, amplitude and location (SAL) metric and the figure of merit in space (FMS). The other two test suite cases (i.e. the February 2013 Mt. Etna ash cloud and associated tephra fallout deposit, and the dispersal of radionuclides resulting from the 1986 Chernobyl nuclear accident) are validated with scattered ground-based observations of deposit load and local particle grain size distributions and with measurements from the Radioactivity Environmental Monitoring database. For validation of tephra deposit loads and radionuclides, we use two variants of the normalised root-mean-square error metric. We find that FALL3D-8.0 simulations initialised with data insertion consistently improve agreement with satellite retrievals at all lead times up to 48 h for both volcanic ash and SO2 simulations. In general, SAL scores lower than 1.5 and FMS scores greater than 0.40 indicate acceptable agreement with satellite retrievals of volcanic ash and SO2. In addition, we show very good agreement, across several orders of magnitude, between the model and observations for the 2013 Mt. Etna and 1986 Chernobyl case studies. Our results, along with the validation datasets provided in the publicly available test suite, form the basis for future improvements to FALL3D (version 8 or later) and also allow for model intercomparison studies.

ТРАЕКТОРНОЕ МОДЕЛИРОВАНИЕ СРЕДНЕЙ АТМОСФЕРЫ

A short description and some applications of the trajectory and dispersion models developed in Central Aerological Observatory (CAO) for studying the stratospheric and tropospheric transport of pollutants are presented. The TRACAO trajectory model is applied to investigate the processes related to the ozone depletion in the winter polar stratosphere, in order to study the mid-latitude stratosphere-troposphere exchange, as well as to analyze balloon and aircraft (M55 “Geophysics,” Yak-42D “Roshydromer”) observations. Then based on the TRACAO, the GLADIM dispersion model that simulates trajectories of the set of particles with the eddy diffusion parameterization and determines the pollutant concentration at the regular grid points, was developed. The dispersion model was applied to simulate volcanic ash dispersion and carbon dioxide profile reconstruction. The model validation was done by comparisons with the results of the widely used FLEXPART model. Nowadays these models are used at the “Middle Atmosphere” Regional Information and Analytic Center established in CAO.

Message from the Winner

A volcanic eruption is a phenomenon in which ballistic bombs, lapilli, volcanic ash, lava, and gas are discharged. Volcanic ash and gas are carried by the wind, and pyroclastic flows and lava flows are carried away by the force of gravity. These cause disasters of various forms in the areas around volcanoes, sometimes far from eruptive center. Accordingly, volcanic countries, particularly Asian countries such as Japan, Indonesia, and the Philippines, have been the scenes of volcanic disasters. We conducted the research project “Integrated study on mitigation of multimodal disasters caused by the ejection of volcanic products” with the Center for Volcanology and Geological Hazard Mitigation and other institutes in Indonesia under the SATREPS project from FY2013 to 2018. The aim of the project was to advance volcanic hazard mitigation, and I served as the guest editor of “Special Issue on Integrated Study on Mitigation of Multimodal Disasters Caused by Ejection of Volcanic Products” (2016) and “Special Issue on Integrated Study on Mitigation of Multimodal Disasters Caused by Ejection of Volcanic Products: Part 2” (2019) of the Journal of Disaster Research. The articles in the Special Issues have been downloaded by many researchers. The Special Issues cover many topics related to volcanic disasters, but the main theme is how to forecast real-time volcanic hazards using data monitoring, since it is this monitoring that triggers the issuing of warnings. I have studied the volcanic activity of Sakurajima, the most active volcano in Japan, for 40 years, primarily to forecast its eruptions. Forecasting the eruptions is not as important as forecasting the hazards and risks posed by volcanic actions. Research done on the mitigation of the volcanic hazards of Sakurajima as well as Indonesian volcanoes has been enhanced by interaction. The cumulative volume of magma stored in the past 100 years indicates that Sakurajima has the potential for a large-scale eruption (VEI &gt; 4). An eruption and its dispersal of volcanic ash in particular would cause a variety of disasters over a wide area, as described in the other issues of Journal of Disaster Research. I hope that the research results will be utilized for hazard mitigation in the event of future large-scale eruptions. The research could be advanced through collaboration with studies aimed at the enhancement of resilience and recovery.