Geology topics

Larry G. Mastin

Publications and source records attributed to Larry G. Mastin.

At least 37 records · Page 2Linked to original sources

USGS2021

Evaluating the state-of-the-art in remote volcanic eruption characterization Part I: Raikoke volcano, Kuril Islands

Raikoke, a small, unmonitored volcano in the Kuril Islands, erupted in June 2019. We integrate data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System (IMS) infrasound network, and global lightning detection network (GLD360) with information from local authorities and social media to retrospectively characterize the eruptive sequence and improve understanding of the pre-, syn- and post- eruptive behavior. We observe six infrasound pulses beginning on 21 June at 17:49:55 UTC as well as the main Plinian phase on 21 June at 22:29 UTC. Each pulse is tracked in space and time using lightning and satellite imagery as the plumes drift eastward. Post-eruption visible satellite imagery shows expansion of the island's surface area, an increase in crater size, and a possibly-linked algal bloom south of the island. We use thermal satellite imagery and plume modeling to estimate plume height at 10–12 km asl and 1.5–2 × 106 kg/s mass eruption rate. Remote infrasound data provide insight into syn-eruptive changes in eruption intensity. Our analysis illustrates the value of interdisciplinary analyses of remote data to illuminate eruptive processes. However, our inability to identify deformation, pre-eruptive outgassing, and thermal signals, which may reflect the relatively short duration (~12 h) of the eruption and minimal land area around the volcano and/or the character of closed-system eruptions, highlights current limitations in the application of remote sensing for eruption detection and characterization.

Hokkaido, Sakhalin Oblast↗

USGS2021

Evaluating the state-of-the-art in remote volcanic eruption characterization Part II: Ulawun volcano, Papua New Guinea

Retrospective eruption characterization is valuable for advancing our understanding of volcanic systems and evaluating our observational capabilities, especially with remote technologies (defined here as a space-borne system or non-local, ground-based instrumentation which include regional and remote infrasound sensors). In June 2019, the open-system Ulawun volcano, Papua New Guinea, produced a VEI 4 eruption. We combined data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System infrasound network, and GLD360 globally detected lightning with information from the local authorities and social media to characterize the pre-, syn - and post-eruptive behaviour. The Rabaul Volcano Observatory recorded ~24 h of seismicity and detected SO 2 emissions ~16 h before the visually-documented start of the Plinian phase on 26 June at 04:20 UTC. Infrasound and SO 2 detections suggest the eruption started during the night on 24 June 2019 at 10:39 UTC ~38 h before ash detections with a gas-dominated jetting phase. Local reports and infrasound detections show that the second phase of the eruption started on 25 June 19:28 UTC with ~6 h of jetting. The first detected lightning occurred on 26 June 00:14 UTC, and ash emissions were first detected by Himawari-8 at 01:00 UTC. Post-eruptive satellite imagery indicates new flow deposits to the south and north of the edifice and ash fall to the west and southwest. In particular, regional infrasound data provided novel insight into eruption onset and syn -eruptive changes in intensity. We conclude that, while remote observations are sufficient for detection and tracking of syn-eruptive changes, key challenges in data latency, acquisition, and synthesis must be addressed to improve future near-real-time characterization of eruptions at minimally-monitored or unmonitored volcanoes.

Bismark volcanic arc, New Britain Island, Ulawun v↗

USGS2021

Asteroid impacts - downwind and downstream effects

For this abstract, we have selected an impact location, consistent with the PDC2021 initial scenario [1], in the San Juan Mountains, in southwestern Colorado. This is a low-density population area but is part of the watershed system within the Colorado River basin, a major source for water and power for the southwestern United States. Several large cities and major airports are potentially downwind from this area. For the PDC2021 scenario [1], a 120-meter impactor is the median expected size. We chose impactor sizes ranging from 42-meters to 600-meters, which covers the 0.1% smallest to largest cases.

Colorado↗

USGS2020

A probabilistic assessment of tephra-fall hazards at Hanford, Washington, from a future eruption of Mount St. Helens

Hanford, Washington (USA) is the construction site of a multi-billion-dollar high-level nuclear waste treatment facility. This site lies 200 kilometers (km) east of Mount St. Helens (MSH), the most active volcano in the contiguous United States. Tephra from a future MSH eruption could pose a hazard to the air intake and filtration systems at this plant. In this report, we present a probabilistic estimate of the amount of tephra that could fall, and the concentrations of airborne ash that could occur at the Hanford Site during a future eruption. Mount St. Helens has produced four large explosive eruptions in approximately the past 500 years, suggesting that its annual probability of eruption ( P 1 ) is roughly 4/500=0.008. Assuming that a large eruption occurs, we calculate the probability ( P 3|1 ) of a given fall deposit thickness or airborne concentration at Hanford by running about 10,000 simulations of ash-producing eruptions using the atmospheric transport model Ash3d. In each simulation, we calculate the pattern of tephra dispersal, deposit thickness at Hanford, and airborne ash concentration at ground level. As input for each simulation, we choose meteorological conditions from a randomly chosen time in the historical record between 1980 and 2010, using data from the European Centre for Medium-Range Weather Forecasting (ECMWF) Reanalysis (ERA) Interim model. The volume (dense-rock equivalent) of each simulated eruption is randomly chosen from a uniform probability distribution on a log scale from the range of magma volumes (0.008–2.3 cubic kilometers [km 3 ]) estimated for late Holocene eruptions at MSH. Plume heights and durations of each eruption are chosen using empirical correlations between volume, height, and eruption rate, which account for the fact that larger eruptions have higher plumes and last longer. We construct summary tables of final deposit thickness ( T ), maximum ground-level airborne concentration ( C max ), and average ground-level airborne concentration ( C avg ) during tephra-fall for each run. Each table is sorted and ranked by decreasing value of T , C max , or C avg . Conditional probabilities ( P 3|1 ) are derived by dividing rank by n+1, where n is the total number of successful runs. For example, a deposit thickness of 5.10 centimeters (cm) from run 446 is ranked 123 of 9,785 successful runs, yielding P 3|1 =123/9,786=0.01257. Its annual probability is P = P 1 · P 3|1 =0.008×0.01257=0.000101. By interpolation, the deposit thickness ( T 10k ) having an annual probability of 1 in 10,000 ( P = 0.0001) is 5.11 cm. Analogous concentration values are C max,10k =3,819 and C avg,10k =1,513 milligrams per cubic meter (mg/m 3 ), respectively. Independent calculations using the known mass accumulation rate of the deposit (=0.001–0.006 kilograms per square meter per second [kg/m 2 /s]), aggregate fall velocities ( u =0.3–0.8 meters per second [m/s]), and the simple formula , yield similar results, although highly variable fall velocities add significant uncertainty. This formula implies that deposit accumulation rates of millimeters (mm) to greater than 1 cm per hour, which are not uncommon during heavy ash fall, are associated with airborne concentrations of 10 2 –10 3 milligrams per cubic meter (mg/m 3 ). These concentrations are much higher than published measurements (10 -3 –10 1 mg/m 3 ), which record only suspended particles sampled in sheltered areas. During heavy ashfall, most fine ash falls as aggregates. Whether such aggregates will be ingested into air ducts will depend on the aggregate size and fall rate, the fragility of the aggregates, the air duct geometry, intake velocity, and other factors.

Washington↗

USGS2020

Comparing simulations of umbrella-cloud growth and ash transport with observations from Pinatubo, Kelud, and Calbuco volcanoes

The largest explosive volcanic eruptions produce umbrella clouds that drive ash radially outward, enlarging the area that impacts aviation and ground-based communities. Models must consider the effects of umbrella spreading when forecasting hazards from these eruptions. In this paper we test a version of the advection–dispersion model Ash3d that considers umbrella spreading by comparing its simulations with observations from three well-documented umbrella-forming eruptions: (1) the 15 June 1991 eruption of Pinatubo (Philippines); (2) the 13 February 2014 eruption of Kelud (Indonesia); and (3) phase 2 of the 22–23 April 2015 eruption of Calbuco (Chile). In volume, these eruptions ranged from several cubic kilometers dense-rock equivalent (DRE) for Pinatubo to about one tenth for Calbuco. In mass eruption rate (MER), they ranged from 10 8 –10 9 kg s −1 at Pinatubo to 9–16 × 10 6 kg s −1 at Calbuco. For each case we ran simulations that considered umbrella growth and ones that did not. All umbrella-cloud simulations produced a cloud whose area was within ~25% of the observed cloud by the end of the eruption. By the eruption end, the simulated areas of the Pinatubo, Kelud, and Calbuco clouds were 851, 53.2, and 100 × 10 3 km 2 respectively. These areas were 2.2, 2.2, and 1.5 times the areas calculated in simulations that ignored umbrella growth. For Pinatubo and Kelud, the umbrella simulations provided better agreement with the observed cloud area than the non-umbrella simulations. Each of these simulations extended 24 h from the eruption start. After the eruption ended, the difference in cloud area (umbrella minus non-umbrella) at Pinatubo persisted for many hours; at Kelud it diminished and became negative after 14 h and at Calbuco it became negative after ~23 h. The negative differences were inferred to result from the fact that non-umbrella simulations distributed ash over a wider vertical extent in the plume, and that wind shear spread the cloud out in multiple directions. Thus, for some smaller eruptions, wind shear can produce a larger cloud than might be produced by umbrella spreading alone.

Calbuco volcano, Kelud volcano, Pinatubo volcano↗

USGS2020

Did ice-charging generate volcanic lightning during the 2016–2017 eruption of Bogoslof volcano, Alaska?

The 2016–2017 shallow submarine eruption of Bogoslof volcano in Alaska injected plumes of ash and seawater to maximum heights of ~ 12 km. More than 4550 volcanic lightning strokes were detected by the World Wide Lightning Location Network (WWLLN) and Vaisala’s Global Lightning Dataset (GLD360) over 9 months. Lightning assisted monitoring efforts by confirming ash-producing explosions in near-real time, but only 32 out of the 70 explosive events produced detectable lightning. What led to electrical activity within some of the volcanic plumes, but not others? And why did the lightning intensity wax and wane over the lifetime of individual explosions? We address these questions using multiparametric observations from ground-based lightning sensors, satellite imagery, photographs, acoustic signals, and 1D plume modeling. Detailed time-series of monitoring data show that the plumes did not produce detectable lightning until they rose higher than the atmospheric freezing level (approximated by − 20 °C temperatures). For example, on 28 May 2017 (event 40), the delayed onset of lightning coincides with modeled ice formation in upper levels of the plume. Model results suggest that microphysical conditions inside the plume rivaled those of severe thunderstorms, with liquid water contents > 5 g m −3 and vigorous updrafts > 40 m s −1 in the mixed-phase region where liquid water and ice coexist. Based on these findings, we infer that ‘thunderstorm-style’ collisional ice-charging catalyzed the volcanic lightning. However, charge mechanisms likely operated on a continuum, with silicate collisions dominating electrification in the near-vent region, and ice charging taking over in the upper-level plumes. A key implication of this study is that lightning during the Bogoslof eruption provided a reliable indicator of sustained, ash-rich plumes (and associated hazards) above the atmospheric freezing level.

Alaska↗

USGS2020

Mechanisms for ballistic block ejection during the 2016–2017 shallow submarine eruption of Bogoslof volcano, Alaska

Ejection of ballistic blocks was a characteristic feature of the 2016–2017 Bogoslof eruption. High-resolution satellite images acquired throughout the duration of the 9-month long eruptive period permitted the recognition and mapping of ballistic blocks on the surface of Bogoslof Island. Many of the satellite images recorded the accumulation of ballistic material over several individual eruptive events, but a few images recorded the effects of a single event. The nonuniform spatial distribution of blocks suggests that some of the eruption columns were inclined. Ballistic trajectories were estimated using the Eject! model and indicate that accumulation of blocks on Bogoslof Island required launch angles of 45–80° and initial velocities of 50–100 ms −1 to reproduce observed travel distances. The amount of ballistic fallout observed in satellite data indicates that there must have been a shallow submarine source of rock within the conduit/upper edifice system. Dense, accidental cryptodome trachyandesite, and juvenile basalt to trachybasalt scoria make up the bulk of the surface ejecta. Abundant accidental fragments and inclined eruption columns point to periodic vent-wall collapse and jetting around edges of temporarily blocked vents as the likely cause of ballistic ejection.

Alaska↗

USGS2019

Investigating the accuracy of one‐dimensional volcanic plume models using laboratory experiments and field data

During volcanic eruptions, model predictions of plume height are limited by the accuracy of entrainment coefficients used in many plume models. Typically, two parameters are used, α and β , which relate the entrained air speed to the jet speed in the axial and cross‐flow directions, respectively. To improve estimates of these parameters, wind tunnel experiments have been conducted for a range of cross‐wind velocities and turbulence conditions. Measurements are compared directly to computations from the 1‐D plume model, Plumeria, in the near‐field, bending region of the jet. Entrainment coefficients are determined through regression analysis, demonstrating optimal combinations of effective α and β values. For turbulent conditions, all wind speeds overlapped at a single combination, α = 0.06 and β =0.46, each of which are slightly reduced from standard values. Refined coefficients were used to model plume heights for 20 historical eruptions. Model accuracy improves modestly in most cases, agreeing to within 3 km with observed plume heights. For weak eruptions, uncertainty in field measurements can outweigh the effects of these refinements, illustrating the challenge of applying plume models in practice.

Journal of Volcanology and Geothermal Research↗

USGS2019

Laboratory experiments of volcanic ash resuspension by wind

Fresh volcanic eruption deposits tend to be loose, bare, and readily resuspended by wind. Major resuspension events in Patagonia, Iceland, and Alaska have lofted ash clouds with potential to impact aircraft, infrastructure, and downwind communities. However, poor constraints on this resuspension process limit our ability to model this phenomenon. Here, we present laboratory experiments measuring threshold shear velocities and emission rates of resuspended ash under different environmental conditions, including relative humidity of 25–75% and simulated rainfall with subsequent drying. Eruption deposits were replicated using ash collected from two major eruptions: the 18 May 1980 eruption of Mount St. Helens and the 1912 eruption of Novarupta, in Alaska's Valley of Ten Thousand Smokes. Samples were conditioned in a laboratory chamber and prepared with bulk deposit densities of 1,300–1,500 kg/m 3 . A control sample of dune sand was included for comparison. The deposits were subjected to different wind speeds using a modified PI‐SWERL® instrument. Under a constant relative humidity of 50% and shear velocities 0.4–0.8 m/s, PM 10 emission by resuspension ranged from 10 to >100 mg·m −2 ·s −1 . Addition of liquid water equivalent to 5 mm of rainfall had little lasting effect on Mount St. Helens wind erosion potential, while the Valley of Ten Thousand Smokes deposits exhibited lower emissions for at least 12 days. The results indicate that particle resuspension due to wind erosion from ash deposits potentially exceeds that of most desert surfaces and approaches some of the highest emissions ever measured.

Journal of Geophysical Research - Atmospheres↗

USGS2019

Modeling ash dispersal from future eruptions of Taupo supervolcano

Hazard analysis at caldera volcanoes is challenging due to the wide range of eruptive and environmental conditions that can plausibly occur during renewed activity. Taupo volcano, New Zealand, is a frequently active and productive rhyolitic caldera volcano that has hosted the world's youngest known supereruption and numerous smaller explosive events. To assess ashfall hazard from future eruptions, we have simulated atmospheric ash dispersal using the Ash3d model. We consider five eruption scenarios spanning magma volumes of 0.1–500 km 3 and investigate the main factors governing ash dispersal in modern atmospheric conditions. Our results are examined in the context of regional synoptic weather patterns (Kidson types) that provide a framework for assessing the variability of ashfall distribution in different wind fields. For the smallest eruptions (~0.1‐km 3 magma), ashfall thicknesses >1 cm are largely confined to the central North Island, with dispersal controlled by day‐to‐day weather and the dominance of westerly winds. With increasing eruptive volume (1–5‐km 3 magma), ashfall thicknesses >1 cm would likely reach major population centers throughout the North Island. Dispersal is less dependent on weather patterns as the formation of a radially expanding umbrella cloud forces ash upwind or crosswind, although strong stratospheric winds significantly restrict umbrella spreading. For large eruptions (50–500‐km 3 magma), powerful expansion of the umbrella cloud results in widespread ashfall at damaging thicknesses (>10 cm) across most of the North Island and top of the South Island. Synoptic climatology may prove a useful additional technique for long‐term hazard planning at caldera volcanoes.

Taupo volcano↗

USGS2019

Globally detected volcanic lightning and umbrella dynamics during the 2014 eruption of Kelud, Indonesia

Volcanic lightning shows considerable promise as a monitoring and research tool to characterize explosive eruptions. Its key strengths are rapid and remote detection, because the radio signals produced by lightning can propagate thousands of km at the speed of light. Despite these tantalizing properties, the scientific work on volcanic lightning has only recently started gaining momentum. Much more is needed to understand what lightning reveals about the evolution of an eruption in near-real time. Here we examine the timing and energy release of lightning generated by the eruption of Kelud volcano in Indonesia on 13 February 2014, as detected by the World Wide Lightning Location Network (WWLLN). The eruption column reached at least 26 km above sea level, representing the highest plume since the advent of global lightning networks in the last decade. Therefore, it provides valuable constraints on the electrification of end-member, sustained Plinian columns. We investigate the lightning in context with satellite images, photographs, and other published studies. Results show that the earliest satellite-detected activity was a thermal anomaly at ~15:46 UTC, corresponding to a directed blast at the onset of eruption (and only a few lightning strokes). Following a brief pause, the eruption produced a sustained column and umbrella cloud that spread outward into the tropical stratosphere. Rates of umbrella expansion provide an average mass eruption rate (MER) in the range of 8 × 10 7 –1 × 10 8 kg s −1 . A more nuanced picture emerges from the time-varying MERs (determined between each satellite pass), which show rapid intensification during the first hour of eruption, followed by constant MER for about an hour, and waning toward the end (after ~17:50 UTC). At this stage, decreasing flux into the umbrella cloud coincides with column instability and formation of pyroclastic density currents, as recorded by photos from the ground ~17:45 UTC. We infer that some of the erupted mass partitioned into ground-hugging currents, leading to a lower apparent MER. Interestingly, there is not a 1:1 correlation between lightning intensity and MER over the course of eruption. Stroke rates increase sharply within the first 30–40 min (during rapid intensification of the plume), and then drop below 2 strokes per min once the MER remains constant. This suggests that electrification was controlled by the rate of increase in MER—in other words, the acceleration of particles out of the vent. We also show that lightning stroke-rates and energies are greatest within 50 km of the vent, even when the ash cloud extends >200 km downwind, indicating that lightning was focused in the regions of highest particle concentration and turbulence. Overall, we conclude that abrupt changes in lightning rates are clearly linked to changes in eruption behavior, and that rapid detection could aid monitoring efforts to characterize eruption rates or styles.

Journal of Volcanology and Geothermal Research↗

USGS2017

Turbulence, entrainment and low-order description of a transitional variable-density jet

Geophysical flows occur over a large range of scales, with Reynolds numbers and Richardson numbers varying over several orders of magnitude. For this study, jets of different densities were ejected vertically into a large ambient region, considering conditions relevant to some geophysical phenomena. Using particle image velocimetry, the velocity fields were measured for three different gases exhausting into air – specifically helium, air and argon. Measurements focused on both the jet core and the entrained ambient. Experiments considered relatively low Reynolds numbers from approximately 1500 to 10 000 with Richardson numbers near 0.001 in magnitude. These included a variety of flow responses, notably a nearly laminar jet, turbulent jets and a transitioning jet in between. Several features were studied, including the jet development, the local entrainment ratio, the turbulent Reynolds stresses and the eddy strength. Compared to a fully turbulent jet, the transitioning jet showed up to 50 % higher local entrainment and more significant turbulent fluctuations. For this condition, the eddies were non-axisymmetric and larger than the exit radius. For turbulent jets, the eddies were initially smaller and axisymmetric while growing with the shear layer. At lower turbulent Reynolds number, the turbulent stresses were more than 50 % higher than at higher turbulent Reynolds number. In either case, the low-density jet developed faster than a comparable non-buoyant jet. Quadrant analysis and proper orthogonal decomposition were also utilized for insight into the entrainment of the jet, as well as to assess the energy distribution with respect to the number of eigenmodes. Reynolds shear stresses were dominant in Q1 and Q3 and exhibited negligible contributions from the remaining two quadrants. Both analysis techniques showed that the development of stresses downstream was dependent on the Reynolds number while the spanwise location of the stresses depended on the Richardson number.

Journal of Fluid Mechanics↗

USGS2017

New Zealand supereruption provides time marker for the Last Glacial Maximum in Antarctica

Multiple, independent time markers are essential to correlate sediment and ice cores from the terrestrial, marine and glacial realms. These records constrain global paleoclimate reconstructions and inform future climate change scenarios. In the Northern Hemisphere, sub-visible layers of volcanic ash (cryptotephra) are valuable time markers due to their widespread dispersal and unique geochemical fingerprints. However, cryptotephra are not as widely identified in the Southern Hemisphere, leaving a gap in the climate record, particularly during the Last Glacial Maximum (LGM). Here we report the first identification of New Zealand volcanic ash in Antarctic ice. The Oruanui supereruption from Taupo volcano (25,580 ± 258 cal. a BP) provides a key time marker for the LGM in the New Zealand sector of the SW Pacific. This finding provides a high-precision chronological link to mid-latitude terrestrial and marine sites, and sheds light on the long-distance transport of tephra in the Southern Hemisphere. As occurred after identification of the Alaskan White River Ash in northern Europe, recognition of ash from the Oruanui eruption in Antarctica dramatically increases the reach and value of tephrochronology, providing links among climate records in widely different geographic areas and depositional environments.

Scientific Reports↗

USGS2017

Ongoing efforts to make ash-cloud model forecasts more accurate

The 2010 eruption of Eyjafjallajökull volcano in Iceland changed the rules for air travel in Europe and introduced the use of restricted fly zones based on ash-cloud concentrations calculated by dispersion models. This change prompted a sustained effort to improve the accuracy of ash-cloud model forecasts. In this paper we describe how this goal is being advanced on three fronts: (1) assessing current capabilities and establishing best practices; (2) improving the accuracy of model inputs; and (3) developing strategies to automatically compare model output with observations and adjust inputs to produce the best match. Progress has been made on all three fronts. A key lesson is that accuracy can only be quantified by comparison with reliable observations, which are often elusive. Model improvements will have to be made in tandem with new technologies to observe and measure.

Conference Paper↗

USGS2016

Adjusting particle-size distributions to account for aggregation in tephra-deposit model forecasts

Volcanic ash transport and dispersion (VATD) models are used to forecast tephra deposition during volcanic eruptions. Model accuracy is limited by the fact that fine-ash aggregates (clumps into clusters), thus altering patterns of deposition. In most models this is accounted for by ad hoc changes to model input, representing fine ash as aggregates with density ρ agg , and a log-normal size distribution with median μ agg and standard deviation σ agg . Optimal values may vary between eruptions. To test the variance, we used the Ash3d tephra model to simulate four deposits: 18 May 1980 Mount St. Helens; 16–17 September 1992 Crater Peak (Mount Spurr); 17 June 1996 Ruapehu; and 23 March 2009 Mount Redoubt. In 192 simulations, we systematically varied μ agg and σ agg , holding ρ agg constant at 600 kg m −3 . We evaluated the fit using three indices that compare modeled versus measured (1) mass load at sample locations; (2) mass load versus distance along the dispersal axis; and (3) isomass area. For all deposits, under these inputs, the best-fit value of μ agg ranged narrowly between ∼ 2.3 and 2.7 φ (0.20–0.15 mm), despite large variations in erupted mass (0.25–50 Tg), plume height (8.5–25 km), mass fraction of fine ( < 0.063 mm) ash (3–59 %), atmospheric temperature, and water content between these eruptions. This close agreement suggests that aggregation may be treated as a discrete process that is insensitive to eruptive style or magnitude. This result offers the potential for a simple, computationally efficient parameterization scheme for use in operational model forecasts. Further research may indicate whether this narrow range also reflects physical constraints on processes in the evolving cloud.

Atmospheric Chemistry and Physics↗

USGS2016

Volcanic lightning and plume behavior reveal evolving hazards during the April 2015 eruption of Calbuco volcano, Chile

Soon after the onset of an eruption, model forecasts of ash dispersal are used to mitigate the hazards to aircraft, infrastructure and communities downwind. However, it is a significant challenge to constrain the model inputs during an evolving eruption. Here we demonstrate that volcanic lightning may be used in tandem with satellite detection to recognize and quantify changes in eruption style and intensity. Using the eruption of Calbuco volcano in southern Chile on 22-23 April 2015, we investigate rates of umbrella cloud expansion from satellite observations, occurrence of lightning, and mapped characteristics of the fall deposits. Our remote-sensing analysis gives a total erupted volume that is within uncertainty of the mapped volume (0.56 ±0.28 km3 bulk). Observations and volcanic plume modeling further suggest that electrical activity was enhanced both by ice formation in the ash clouds >10 km asl and development of a low-level charge layer from ground-hugging currents.

Calbuco volcano↗

USGS2016

Results of the eruptive column model inter-comparison study

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 simplified 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.

Journal of Volcanology and Geothermal Research↗

USGS2015

Hail formation triggers rapid ash aggregation in volcanic plumes

During explosive eruptions, airborne particles collide and stick together, accelerating the fallout of volcanic ash and climate-forcing aerosols. This aggregation process remains a major source of uncertainty both in ash dispersal forecasting and interpretation of eruptions from the geological record. Here we illuminate the mechanisms and timescales of particle aggregation from a well-characterized ‘wet’ eruption. The 2009 eruption of Redoubt Volcano in Alaska incorporated water from the surface (in this case, a glacier), which is a common occurrence during explosive volcanism worldwide. Observations from C-band weather radar, fall deposits, and numerical modeling demonstrate that volcanic hail formed rapidly in the eruption plume, leading to mixed-phase aggregation of ~95% of the fine ash and stripping much of the cloud out of the atmosphere within 30 minutes. Based on these findings, we propose a mechanism of hail-like aggregation that contributes to the anomalously rapid fallout of fine ash and the occurrence of concentrically-layered aggregates in volcanic deposits.

Alaska↗