Eruption Source Parameters Research Articles

How dependent are quantitative volcanic ash concentration and along‐flight dosage forecasts to model structural choices?

AbstractProducing quantitative volcanic ash forecasts is challenging due to multiple sources of uncertainty. Careful consideration of this uncertainty is required to produce timely and robust hazard warnings. Structural uncertainty occurs when a model fails to produce accurate forecasts, despite good knowledge of the eruption source parameters, meteorological conditions and suitable parameterizations of transport and deposition processes. This uncertainty is frequently overlooked in forecasting practices. Using a Lagrangian particle dispersion model, simulations with varied output spatial resolution, temporal averaging period and particle release rate are performed to quantify the impact of these structural choices. This experiment reveals that, for the 2019 Raikoke eruption, structural choices give measurements of peak ash concentration spanning an order of magnitude, significantly impacting decision‐relevant thresholds used in aviation flight planning. Conversely, along‐flight dosage estimates exhibit less sensitivity to structural choices, suggesting it is a more robust metric to use in flight planning. Uncertainty can be reduced by eliminating structural choices that do not result in a favourable level of agreement with a high‐resolution reference simulation. Reliable forecasts require output spatial resolution 80 km, temporal averaging periods 3 h and particle release rates 5000 particles/h. This suggests that simulations with relatively small numbers of particles could be used to produce a large ensemble of simulations without significant loss of accuracy. Comparison with previous Raikoke simulations indicates that the uncertainty associated with these constrained structural choices is smaller than those associated with satellite constrained eruption source parameter and internal model parameter uncertainties. Thus, given suitable structural choices, other epistemic sources of uncertainty are likely to dominate. This insight is useful for the design of ensemble methodologies which are required to enable a shift from deterministic to probabilistic forecasting. The results are applicable to other long‐range dispersion problems and to Eulerian dispersion models.

Reconstructing the Belbaşhanı Pumice Plinian eruption, Hasandağ Volcano, Turkey

Hasandağ volcano (Central Anatolia, Turkey) has recently underwent an increase in local seismicity and fumarolic activity since 2013. In the past, this volcano has produced multiple large explosive eruptions during the last million years. The Belbaşhanı Pumice is the product of a sub-Plinian to Plinian eruption dated at ~ 417 ± 20.5 ka (40Ar/39Ar). Here, we present a complete volcanological study including stratigraphy, glass chemistry, pumice morphology, geochronology, and eruption source parameters with the associated uncertainties, to characterize the Belbaşhanı Pumice eruption. The eruption involved a column of 18–29 km in height, with the main dispersal axis towards the northeast. A pumice layer up to ~ 17-m-thick accumulated in proximal deposits along the Belbaşhanı path, and up to 2-m-thick in medial-distal areas (~ 18 km northeast from the vent). The high and tubular vesicularity of the pumice clasts indicates that the Belbaşhanı eruption was predominantly magmatic. The bulk volume of the Belbaşhanı Pumice fallout deposit has been estimated as 0.5 and 8 km3 (with ~ 2 km3 being the mean value), which corresponds to Volcanic Explosivity Index (VEI) of at least 4 and up to 6. Both isopach and isopleth maps indicate that the volcanic vent may have been located at the intersection of the Tuz Gölü fault and Ulukışla caldera, within the Hasandağ volcanic complex. The glass composition of Belbaşhanı Pumice confirms that the eruption belongs to the Hasandağ magmatic system. The reconstruction of the Belbaşhanı Pumice eruption represents an essential baseline in providing volcanological constraints for further investigations of tephra fallout hazard assessment in Central Anatolia, especially considering that a new Plinian eruption cannot be ruled out at Hasandağ volcano in the future. The chemical and geochronological datasets presented here could aid in refining tephrochronological correlations, with the goal of synchronizing paleoenvironmental and paleoclimatic records alongside archaeological sites.

Initial atmospheric conditions control transport of volcanic volatiles, forcing and impacts

Abstract. Volcanic eruptions impact the climate and environment. The volcanic forcing is determined by eruption source parameters, including the mass and composition of volcanic volatiles, eruption season, eruption latitude, and injection altitude. Moreover, initial atmospheric conditions of the climate system play an important role in shaping the volcanic forcing and response. However, our understanding of the combination of these factors, the distinctions between tropical and extratropical volcanic eruptions, and the co-injection of sulfur and halogens remains limited. Here, we perform ensemble simulations of volcanic eruptions at 15 and 64° N in January, injecting 17 Mt of SO2 together with HCl and HBr at 24 km altitude. Our findings reveal that initial atmospheric conditions control the transport of volcanic volatiles from the first month and modulate the subsequent latitudinal distribution of sulfate aerosols and halogens. This results in different volcanic forcing, surface temperature and ozone responses over the globe and Northern Hemisphere extratropics (NHET) among the model ensemble members with different initial atmospheric conditions. NH extratropical eruptions exhibit a larger NHET mean volcanic forcing, surface cooling and ozone depletion compared with tropical eruptions. However, tropical eruptions lead to more prolonged impacts compared with NH extratropical eruptions, both globally and in the NHET. The sensitivity of volcanic forcing to varying eruption source parameters and model dependency is discussed, emphasizing the need for future multi-model studies to consider the influence of initial conditions and eruption source parameters on volcanic forcing and subsequent impacts.

The 23–24 March 2021 lava fountain at Mt Etna, Italy

In 2021, more than 50 paroxysmal episodes occurred at the South-East Crater (SEC) of Mt Etna, Italy. The 23–24 March lava fountain was one of the longest episodes and began with weak Strombolian explosions, gradually transitioning to lava fountaining. The eruption intensity then dropped more slowly than in previous episodes, resulting in pulsating Strombolian explosions dominated by ash emission. Thirty-four tephra samples were used to reconstruct the fallout dispersal and estimate the total erupted mass. Grain size, textural, petrological and geochemical analyses indicate different features and were compared with the gas phase (SO2 and HCl) in the volcanic plume. By applying stochastic global optimization to simulations of the temporal evolution of the eruption column height and tephra dispersal and deposition, the total erupted mass retrieved (6.76 × 108 kg) matches well the total erupted mass estimation by the ground-based deposit (8.03 ± 2.38 × 108 kg), reducing the column height throughout the episode from 6.44 to 4.5 km above sea level and resulting in a mass eruption rate ranging from 1.96 × 105 to 8.18 × 103 kg/s. The unusual duration of the March episode and the characteristics of the erupted products point to the change in explosive style and magma fragmentation from fountaining to ash emission phases, associated with a slower magma supply inducing a change in magma rheology and a final, prolonged ash generation. Furthermore, this study showed that using observational data and the variation in eruption source parameters for numerical simulations can improve the accuracy of predicting the dispersal plume, thus mitigating the potential impact of longer paroxysmal episodes.

Monitoring Volcanic Plumes and Clouds Using Remote Sensing: A Systematic Review

Volcanic clouds pose significant threats to air traffic, human health, and economic activity, making early detection and monitoring crucial. Accurate determination of eruptive source parameters is crucial for forecasting and implementing preventive measures. This review article aims to identify the most common remote sensing methods for monitoring volcanic clouds. To achieve this, we conducted a systematic literature review of scientific articles indexed in the Web of Science database published between 2010 and 2022, using multiple query strings across all fields. The articles were reviewed based on research topics, remote sensing methods, practical applications, case studies, and outcomes using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our study found that satellite-based remote sensing approaches are the most cost-efficient and accessible, allowing for the monitoring of volcanic clouds at various spatial scales. Brightness temperature difference is the most commonly used method for detecting volcanic clouds at a specified temperature threshold. Approaches that apply machine learning techniques help overcome the limitations of traditional methods. Despite the constraints imposed by spatial and temporal resolution and optical limitations of sensors, multiplatform approaches can overcome these limitations and improve accuracy. This study explores various techniques for monitoring volcanic clouds, identifies research gaps, and lays the foundation for future research.

Utilising a multi-proxy to model comparison to constrain the season and regionally heterogeneous impacts of the Mt Samalas 1257 eruption

Abstract. The Mt Samalas eruption, thought to have occurred in summer 1257, ranks as one of the most explosive sulfur-rich eruptions of the Common Era. Despite recent convergence, several dates have been proposed for the eruption ranging between 1256–1258, with, as of yet, no single combination of evidence that has been able to robustly distinguish between and exclude the other dates proposed for the Mt Samalas eruption. Widespread surface cooling and hydroclimate perturbations following the eruption have been invoked as contributing to a host of 13th century social and economic crises, although regional-scale variability in the post-eruption climate response remains uncertain. In this study we run ensemble simulations using the UK Earth System Model (UKESM1) with a range of eruption scenarios and initial conditions in order to compare our simulations with the most complete globally resolved multi-proxy database for the Mt Samalas eruption to date, incorporating tree rings, ice cores, and historical records. This allows more precise constraints to be placed on the year and season of the Mt Samalas eruption, as well as an investigation into the regionally heterogeneous post-eruption climate response. Using a multi-proxy to model comparison, we are able to robustly distinguish between July 1257 and January 1258 eruption scenarios, where the July 1257 ensemble simulation achieves considerably better agreement with spatially averaged and regionally resolved proxy surface temperature reconstructions. These reconstructions suggest the onset of significant cooling across Asia and Europe in 1258 and thus support the plausibility of previously inferred historical connections. Model-simulated temperature anomalies also point to severe surface cooling across the Southern Hemisphere with as of yet unexplored historical implications for impacted civilisations. Model simulations of polar sulfate deposition also reveal distinct differences in the timing of ice sheet deposition between the two simulated eruption dates, although comparison of the magnitude or asymmetric deposition of sulfate aerosol remains limited by large inter-model differences and complex intra-model dependencies. Overall, the multi-proxy to model comparison employed in this study has strong potential in constraining similar uncertainties in eruption source parameters for other historical eruptions for which sufficient coincident proxy records are available, although care is needed to avoid the pitfalls of model–multi-proxy comparison.

Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modeling using VolcanicAshInversion v1.2.1, within the operational eEMEP (emergency European Monitoring and Evaluation Programme) volcanic plume forecasting system (version rv4_17)

Abstract. Accurate modeling of ash clouds from volcanic eruptions requires knowledge about the eruption source parameters including eruption onset, duration, mass eruption rates, particle size distribution, and vertical-emission profiles. However, most of these parameters are unknown and must be estimated somehow. Some are estimated based on observed correlations and known volcano parameters. However, a more accurate estimate is often needed to bring the model into closer agreement with observations. This paper describes the inversion procedure implemented at the Norwegian Meteorological Institute for estimating ash emission rates from retrieved satellite ash column amounts and a priori knowledge. The overall procedure consists of five stages: (1) generate a priori emission estimates, (2) run forward simulations with a set of unit emission profiles, (3) collocate/match observations with emission simulations, (4) build system of linear equations, and (5) solve overdetermined systems. We go through the mathematical foundations for the inversion procedure, performance for synthetic cases, and performance for real-world cases. The novelties of this paper include a memory efficient formulation of the inversion problem, a detailed description and illustrations of the mathematical formulations, evaluation of the inversion method using synthetic known-truth data as well as real data, and inclusion of observations of ash cloud-top height. The source code used in this work is freely available under an open-source license and is able to be used for other similar applications.

Modelling Paroxysmal and Mild-Strombolian Eruptive Plumes at Stromboli and Mt. Etna on 28 August 2019

Volcanic eruptions pose a major natural hazard influencing the environment, climate and human beings at different temporal and spatial scales. Nevertheless, several volcanoes worldwide are poorly monitored and assessing the impact of their eruptions remains, in some cases, challenging. Nowadays, different numerical dispersion models are largely employed in order to evaluate the potential effects of volcanic plume dispersion due to the transport of ash and gases. On 28 August 2019, both Mt. Etna and Stromboli had eruptive activity; Mt. Etna was characterised by mild-Strombolian activity at summit craters, while at Stromboli volcano, a paroxysmal event occurred, which interrupted the ordinary typical-steady Strombolian activity. Here, we explore the spatial dispersion of volcanic sulphur dioxide (SO2) gas plumes in the atmosphere, at both volcanoes, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) considering the ground-measured SO2 amounts and the plume-height as time-variable eruptive source parameters. The performance of WRF-Chem was assessed by cross-correlating the simulated SO2 dispersion maps with data retrieved by TROPOMI and OMI sensors. The results show a feasible agreement between the modelled dispersion maps and TROPOMI satellite for both volcanoes, with spatial pattern retrievals and a total mass of dispersed SO2 of the same order of magnitude. Predicted total SO2 mass for Stromboli might be underestimated due to the inhibition from ground to resolve the sin-eruptive SO2 emission due to the extreme ash-rich volcanic plume released during the paroxysm. This study demonstrates the feasibility of a WRF-Chem model with time-variable ESPs in simultaneously reproducing two eruptive plumes with different SO2 emission and their dispersion into the atmosphere. The operational implementation of this method could represent effective support for the assessment of local-to-regional air quality and flight security and, in case of particularly intense events, also on a global scale.

Assessment of eruption source parameters using infrasound and plume modelling: a case study from the 2021 eruption of Mt. Etna, Italy

Atmospheric injection of volcanic ash during eruptions is a threat to aviation. Reliable forecast of airborne ash dispersal relies on empirical and numerical models. Key inputs into these models are so-called eruption source parameters such as the rate at which pyroclastic material is ejected from the vent and the maximum height of eruptive columns. Here, we use infrasound data recorded during eruptive activity in June 2021 at Mt. Etna, Italy, to demonstrate its potential for assessment of eruption rates in near-real time. We calculate a time series of flow velocity at the vent using data corrected for topographic scattering, and the effect of vent geometry on the acoustic source radiation. We obtain values of flow velocity of 50–125 m/s during a period of sustained, paroxysmal, activity. We use independent estimates from other ground-based remote sensing data to validate our results. Further, we use the infrasound-derived flow velocities as input into a 1D plume model to estimate the maximum height of the eruption column. Our results suggest that infrasound technology holds promise to assess eruption rates and inform modelling of volcanic plumes. We anticipate that implementation of real-time operational workflows based on infrasound data and plume modelling will impact decision-making and risk mitigation at active volcanoes.

SPATIAL ANALYSIS OF VOLCANIC ASH DISTRIBUTION DUE TO VOLCANIC ERUPTION IN JAVA ISLAND

Abstract. Indonesia is located on the Ring of Fire with the most geologically active than any other countries, which makes it vulnerable due to the massive earthquakes and volcanic eruptions. Java Island has the most active volcano with high risks such as human risk and infrastructure from volcanic ash because of volcanic eruptions. The availability of the map of potential volcanic hazards is important to help mitigate the risk caused by volcanic eruptions. However, to the best of the author's knowledge, the distribution of volcanic ash has never been assessed in detail in the disaster-prone hazard map published by the Centre for Volcanology and Geological Hazard Mitigation (CVGHM), Indonesia. This research reported the potential distribution of volcanic ash due to volcanic eruptions in the future in Java island. Following the principles of Probabilistic Hazard Assessment and TephraProb software, the modeling of volcanic ash potential was performed using various parameters such as historical data, eruption source parameter, total grain-size distribution, tephra2 parameter, and the wind speed around the volcanoes as an input. The map shows the distribution of volcanic ash based on the volcanic ash accumulation (kg/m2) and the volcanic ash hazard map is classified into three classes. There are 19 models of volcanic ash distribution with various probabilities of exceedance based on 19 A-type volcanoes on Java Island. This volcano's distribution of volcanic ash tends to the southwest as the wind speed and direction.

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.

A One‐Dimensional Volcanic Plume Model for Predicting Ash Aggregation

AbstractDuring explosive volcanic eruptions, volcanic ash is ejected into the atmosphere, impacting aircraft safety and downwind communities. These volcanic clouds tend to be dominated by fine ash (<63 μm in diameter), permitting transport over hundreds to thousands of kilometers. However, field observations show that much of this fine ash aggregates into clusters or pellets with faster settling velocities than individual particles. Models of ash transport and deposition require an understanding of aggregation processes, which depend on factors like moisture content and local particle collision rates. In this study, we develop a Plume Model for Aggregate Prediction, a one‐dimensional (1D) volcanic plume model that predicts the plume rise height, concentration of water phases, and size distribution of resulting ash aggregates from a set of eruption source parameters. The plume model uses a control volume approach to solve mass, momentum, and energy equations along the direction of the plume axis. The aggregation equation is solved using a fixed pivot technique and incorporates a sticking efficiency model developed from analog laboratory experiments of particle aggregation within a novel turbulence tower. When applied to the 2009 eruption of Redoubt Volcano, Alaska, the 1D model predicts that the majority of the plume is over‐saturated with water, leading to a high rate of aggregation. Although the mean grain size of the computed Redoubt aggregates is larger than the measured deposits, with a peak at 1 mm rather than 500 μm, the present results provide a quantitative estimate for the magnitude of aggregation in an eruption.

New Insights Into the Relationship Between Mass Eruption Rate and Volcanic Column Height Based On the IVESPA Data Set

AbstractRapid and simple estimation of the mass eruption rate (MER) from column height is essential for real‐time volcanic hazard management and reconstruction of past explosive eruptions. Using 134 eruptive events from the new Independent Volcanic Eruption Source Parameter Archive (IVESPA, v1.0), we explore empirical MER‐height relationships for four measures of column height: spreading level, sulfur dioxide height, and top height from direct observations and as reconstructed from deposits. These relationships show significant differences and highlight limitations of empirical models currently used in operational and research applications. The roles of atmospheric stratification, wind, and humidity remain challenging to detect across the wide range of eruptive conditions spanned in IVESPA, ultimately resulting in empirical relationships outperforming analytical models that account for atmospheric conditions. This finding highlights challenges in constraining the MER‐height relation using heterogeneous observations and empirical models, which reinforces the need for improved eruption source parameter data sets and physics‐based models.

Unsuspected explosive activity of Montagne Pelée (Lesser Antilles) during the 25–10 ka period

The recent eruptive history of Montagne Pelée volcano was dominated by a period of vigorous basaltic andesitic magma production (36−25 ka) followed by a long period of lower activity (i.e., with less frequent and less voluminous eruptions) and a renewal of felsic magma production in the last 10 ka. The temporal succession of volcanic events that occurred during the 25−10 ka period and the timing of felsic magma production are currently poorly constrained. This study focuses on the stratigraphy and eruptive dynamics of the pyroclastic deposits emplaced immediately after 25 ka. New on-land stratigraphic correlations and radiocarbon dating measurements allow us identifying six major explosive eruptions. We use field data on tephra dispersal, thickness and grain-size distribution together with physical models of explosive volcanic plumes to estimate the eruption source parameters. Our results show that these events are VEI 4 eruptions with intermediate magnitudes (from M = 4.2 to M = 5.1) and intensities (from I = 10.6 to I = 11.6). These eruptions share several characteristics with the most recent Plinian eruptions of Montagne Pelée volcano (i.e., mass eruption rate, maximum column height, runout of pyroclastic density currents, glass composition). The tephra succession documents two phases of magma production rates. The first phase from 25 to 14 ka corresponds to a period of low activity with a magma production rate of 0.04 km3 kyr−1. The second phase from 14 to 10 ka is characterized by a significant increase of the volcanic activity with a magma production rate of 0.4 km3 kyr−1, consistent with previous estimates.

Identifying analogues for data-limited volcanoes using hierarchical clustering and expert knowledge: a case study of Melimoyu (Chile)

Determining the eruption frequency-Magnitude (f-M) relationship for data-limited volcanoes is challenging since it requires a comprehensive eruption record of the past eruptive activity. This is the case for Melimoyu, a long-dormant and data-limited volcano in the Southern Volcanic Zone (SVZ) in Chile with only two confirmed Holocene eruptions (VEI 5). To supplement the eruption records, we identified analogue volcanoes for Melimoyu (i.e., volcanoes that behave similarly and are identified through shared characteristics) using a quantitative and objective approach. Firstly, we compiled a global database containing 181 variables describing the eruptive history, tectonic setting, rock composition, and morphology of 1,428 volcanoes. This database was filtered primarily based on data availability into an input dataset comprising 37 numerical variables for 438 subduction zone volcanoes. Then, we applied Agglomerative Nesting, a bottom-up hierarchical clustering algorithm on three datasets derived from the input dataset: 1) raw data, 2) output from a Principal Component Analysis, and 3) weighted data tuned to minimise the dispersion in the absolute probability per VEI. Lastly, we identified the best set of analogues by analysing the dispersion in the absolute probability per VEI and applying a set of criteria deemed important by the local geological service, SERNAGEOMIN, and VB. Our analysis shows that the raw data generate a low dispersion and the highest number of analogues (n = 20). More than half of these analogues are in the SVZ, suggesting that the tectonic setting plays a key role in the clustering analysis. The eruption f-M relationship modelled from the analogue’s eruption data shows that if Melimoyu has an eruption, there is a 49% probability (50th percentile) of it being VEI≥4. Meanwhile, the annual absolute probability of a VEI≤1, VEI 2, VEI 3, VEI 4, and VEI≥5 eruption at Melimoyu is 4.82 × 10−4, 1.2 × 10−3, 1.45 × 10−4, 9.77 × 10−4, and 8.3 × 10−4 (50th percentile), respectively. Our work shows the importance of using numerical variables to capture the variability across volcanoes and combining quantitative approaches with expert knowledge to assess the suitability of potential analogues. Additionally, this approach allows identifying groups of analogues and can be easily applied to other cases using numerical variables from the global database. Future work will use the analogues to populate an event tree and define eruption source parameters for modelling volcanic hazards at Melimoyu.

Corrigendum: 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

CORRECTION article Front. Earth Sci., 06 April 2023Sec. Volcanology Volume 11 - 2023 | https://doi.org/10.3389/feart.2023.1182638

A New Radar‐Based Statistical Model to Quantify Mass Eruption Rate of Volcanic Plumes

AbstractAccurate forecasting of volcanic particle (tephra) dispersal and fallout requires a reliable estimation of key Eruption Source Parameters (ESPs) such as the Mass Eruption Rate (QM). QM is usually estimated from the Top Plume Height (HTP) using empirical and analytical models. For the first time, we combine estimates of HTP and QM derived from the same sensor (radar) with mean wind velocity values (vW) for lava‐fountain fed tephra plumes associated with 32 paroxysms of Mt. Etna (Italy) to develop a new statistical model based on a Markov Chain Monte Carlo approach for model parameter estimation. This model is especially designed for application to radar data to quickly infer QM from observed HTP and vW, and estimate the associated uncertainty. It can be easily applied and adjusted to data retrieved by radars worldwide, improving our capacity to quickly estimate QM and related uncertainties required for the tephra dispersal hazard.

Towards real-time probabilistic ash deposition forecasting for New Zealand

Volcanic ashfall forecasts are highly dependent on eruption source parameters (ESPs) and synoptic weather conditions at the time and location of the eruption. In New Zealand, MetService and GNS Science have been jointly developing an ashfall forecast system that incorporates four-dimensional high-resolution numerical weather prediction (NWP) and ESPs into the HYSPLIT model, a state-of-the art hybrid Eulerian and Lagrangian dispersion model widely used for volcanic ash. However, these forecasts are based on discrete ESPs combined with a deterministic weather forecast and thus provide no information on output uncertainty. This shortcoming hinders stakeholder decision making, particularly near the geographical margin of forecasted ashfall and in areas with large gradients in forecasted ash deposition. Our study presents a new approach that incorporates uncertainty from both eruptive and meteorological inputs to deliver uncertainty in the model output. To this end, we developed probability density functions (PDFs) for three key ESPs (plume height, mass eruption rate, eruption duration) tailored to New Zealand’s volcanoes and combine them with NWP ensemble datasets to generate probabilistic ashfall forecasts using the HYSPLIT model. We show that the Latin Hypercube Sampling (LHS) technique can be used to representatively span this four-dimensional parameter space and allow us to add uncertainty quantification to rapid response forecast systems. For a case study of a hypothetical eruption at Tongariro, New Zealand we suggest that large parts of New Zealand’s North Island would not receive adequate warning for potential ashfall if uncertainties were not included in the forecasts. We also propose new probabilistic summary products to support public information and emergency responders decision making.

On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi Flegrei

For active volcanoes, knowledge about probabilities of eruption and impacted areas becomes valuable information for decision-makers to develop short- and long-term emergency plans, for which probabilistic volcanic hazard assessment (PVHA) is needed. High-resolution or spatially extended PVHA requires extreme-scale high-performance computing systems. Within the framework of ChEESE (Center of Excellence for Exascale in Solid Earth; www.cheese-coe.eu), an effort was made to generate exascale-suitable codes and workflows to collect and process in some hours the large amount of data that a quality PVHA requires. To this end, we created an optimized HPC-based workflow coined PVHA_HPC-WF to develop PVHA for a volcano. This tool uses the Bayesian event tree methodology to calculate eruption probabilities, vent-opening location(s), and eruptive source parameters (ESPs) based on volcano history, monitoring system data, and meteorological conditions. Then, the tool interacts with the chosen hazard model, performing a simulation for each ESP set or volcanic scenario (VS). Finally, the resulting information is processed by proof-of-concept-subjected high-performance data analytics (HPDA) scripts, producing the hazard maps which describe the probability over time of exceeding critical thresholds at each location in the investigated geographical domain. Although PVHA_HPC-WF can be adapted to other hazards, we focus here on tephra (i.e., lapilli and ash) transport and deposition. As an application, we performed PVHA for Campi Flegrei (CF), Italy, an active volcano located in one of the most densely inhabited areas in Europe and under busy air traffic routes. CF is currently in unrest, classified as being in an attention level by the Italian Civil Protection. We consider an approximate 2,000 × 2,000 × 40 km computational domain with 2 km grid resolution in the horizontal and 40 vertical levels, centered in CF. To explore the natural variability and uncertainty of the eruptive conditions, we consider a large number of VSs allowing us to include those of low probability but high impact, and simulations of tephra dispersal are performed for each of them using the FALL3D model. Results show the potential of HPC to timely execute a vast range of simulations of complex numerical models in large high-resolution computational domains and analyze great volumes of data to obtain quality hazard maps.

Modelling the transport and deposition of ash following a magnitude 7 eruption: the distal Mazama tephra

Volcanic ash transport and dispersion models (VATDMs) are necessary for forecasting tephra dispersal during volcanic eruptions and are a useful tool for estimating the eruption source parameters (ESPs) of prehistoric eruptions. Here we use Ash3D, an Eulerian VATDM, to simulate the tephra deposition from the ~ 7.7 ka climactic eruption of Mount Mazama. We investigate how best to apply a VATDM using the ESPs characteristic of a large magnitude eruption (M ≥ 7). We simplify the approach to focus on the distal deposit as if it were formed by a single phase of Plinian activity. Our results demonstrate that it is possible to use modern wind profiles to simulate the tephra dispersal from a prehistoric eruption; however, this introduces an inherent uncertainty to the subsequent simulations where we explore different ESPs. We show, using the well-documented distal Mazama tephra, that lateral umbrella cloud spreading, rather than advection–diffusion alone, must be included in the VATDM to reproduce the width of the isopachs. In addition, the Ash3D particle size distribution must be modified to simulate the transport and deposition of distal fine-grained (< 125 µm) Mazama ash. With these modifications, the Ash3D simulations reproduce the thickness and grain size of the Mazama tephra deposit. Based on our simulations, however, we conclude that the exact relationship between mass eruption rate and the scale of umbrella cloud spreading remains unresolved. Furthermore, for ground-based grain size distributions to be input directly into Ash3D, further research is required into the atmospheric and particle processes that control the settling behaviour of fine volcanic ash.