Geology topics

Alexa R. Van Eaton

Publications and source records attributed to Alexa R. Van Eaton.

At least 37 records · Page 2Linked to original sources

USGS2022

Volcanic electrification: Recent advances and future perspectives

The electrification of volcanic plumes has been described intermittently since at least the time of Pliny the Younger and the 79 AD eruption of Vesuvius. Although sometimes disregarded in the past as secondary effects, recent work suggests that the electrical properties of volcanic plumes reveal intrinsic and otherwise inaccessible parameters of explosive eruptions. An increasing number of volcanic lightning studies across the last decade have shown that electrification is ubiquitous in volcanic plumes. Technological advances in engineering and numerical modelling, paired with close observation of recent eruptions and dedicated laboratory studies (shock-tube and current impulse experiments), show that charge generation and electrical activity are related to the physical, chemical, and dynamic processes underpinning the eruption itself. Refining our understanding of volcanic plume electrification will continue advancing the fundamental understanding of eruptive processes to improve volcano monitoring. Realizing this goal, however, requires an interdisciplinary approach at the intersection of volcanology, atmospheric science, atmospheric electricity, and engineering. Our paper summarizes the rapid and steady progress achieved in recent volcanic lightning research and provides a vision for future developments in this growing field.

Bulletin of Volcanology↗

USGS2022

Eruption dynamics leading to a volcanic thunderstorm— The January 2020 eruption of Taal volcano, Philippines

Advances in global lightning detection have provided novel ways to characterize explosive volcanism. However, researchers are still at the early stages of understanding how volcanic plumes become electrified on different spatial and temporal scales. We deconstructed the phreatomagmatic eruption of Taal volcano (Philippines) on 12 January 2020 to investigate the origin of its powerful volcanic thunderstorm. Satellite analysis indicated that the water-rich plume rose >10 km high before creating lightning detected by Vaisala's global lightning data set (GLD360). Flash rates increased with plume heights and cloud expansion over time, producing >70 flashes min –1 . Photographs revealed a highly electrified region at the base of the umbrella cloud, where we infer strong convective updrafts and icy collisions enhanced the electrical activity. These findings inform a conceptual model with overlapping regimes of charge generation in wet eruptions—initially due to ash particle collisions near the vent, followed by thunderstorm-like electrification in icy regions of the upper plume. Despite the wide reach of Taal's ash cloud, most of the lightning occurred within 20–30 km of the volcano, producing thousands of hazardous cloud-to-ground flashes over a densely populated area. The eruption demonstrates that volcanic lightning can pose a hazard in its own right, embedded within the broader hazards of explosive volcanism in an urban setting.

Taal volcano↗

USGS2022

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.

Ilopango caldera↗

USGS2021

Impulsive volcanic plumes generate volcanic lightning and vent discharges: A statistical analysis of Sakurajima volcano in 2015

The origin of electrical activity accompanying volcanic ash plumes is an area of heightened interest in volcanology. However, it is unclear how intense an eruption needs to be to produce lightning flashes as opposed to “vent discharges,” which represent the smallest scale of electrical activity. This study targets 97 carefully monitored plumes <3 km high from Sakurajima volcano in Japan, from June 1 to 7, 2015. We use multiparametric measurements from sensors including a nine-station lightning mapping array and an infrared camera to characterize plume ascent. Findings demonstrate that the impulsive, high velocity plumes (>55 m/s) were most likely to create vent discharges, whereas lightning flashes occurred in plumes with high volume flux. We identified conditions where volcanic lightning occurred without detectable vent discharges, highlighting their independent source mechanisms. Our results imply that plume dynamics govern the charging for volcanic lightning, while the characteristics of the source explosion control vent discharges.

Sakurajima volcano↗

USGS2021

The Independent Volcanic Eruption Source Parameter Archive (IVESPA, version 1.0): A new observational database to support explosive eruptive column model validation and development

Eruptive column models are powerful tools for investigating the transport of volcanic gas and ash, reconstructing past explosive eruptions, and simulating future hazards. However, the evaluation of these models is challenging as it requires independent estimates of the main model inputs (e.g. mass eruption rate) and outputs (e.g. column height). There exists no database of independently estimated eruption source parameters (ESPs) that is extensive, standardized, maintained, and consensus-based. This paper introduces the Independent Volcanic Eruption Source Parameter Archive (IVESPA, ivespa.co.uk), a community effort endorsed by the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) Commission on Tephra Hazard Modelling. We compiled data for 134 explosive eruptive events, spanning the 1902-2016 period, with independent estimates of: i) total erupted mass of fall deposits; ii) duration; iii) eruption column height; and iv) atmospheric conditions. Crucially, we distinguish plume top versus umbrella spreading height, and the height of ash versus sulphur dioxide injection. All parameter values provided have been vetted independently by at least two experts. Uncertainties are quantified systematically, including flags to describe the degree of interpretation of the literature required for each estimate. IVESPA also includes a range of additional parameters such as total grain size distribution, eruption style, morphology of the plume (weak versus strong), and mass contribution from pyroclastic density currents, where available. We discuss the future developments and potential applications of IVESPA and make recommendations for reporting ESPs to maximize their usability across different applications. IVESPA covers an unprecedented range of ESPs and can therefore be used to evaluate and develop eruptive column models across a wide range of conditions using a standardized dataset.

Journal of Volcanology and Geothermal Research↗

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

A physical model for volcanic eruption tremor

Seismic waves are commonly used to monitor unrest before, during, and after volcanic eruptions. The source of seismic tremor during a sustained explosive volcanic eruption is not well understood. Recent observations of the 2016 eruption of Pavlof Volcano, Alaska, revealed a change in the relationship (hysteresis) between ash plume height and seismic amplitude over time. Based on similarities in physical processes and observed seismic tremor in rivers, we explore two key sources of seismic energy in the volcanic conduit: (1) forces exerted by particle impacts and (2) dynamic pressure changes by the turbulent flow. We develop a physical model calculating the seismic power spectral density (PSD), where forces on the conduit wall are convolved with the Green's function for Rayleigh waves. Using reasonable eruption parameters, the model is able to reproduce the frequency spectrum from the Pavlof eruption, although the modeled amplitudes are generally lower. We test the relative importance of different eruption parameters, including grain size, velocity, and conduit dimensions. We find that turbulence generally dominates over particle impacts. However, to reach the PSD amplitude during the Pavlof eruption, large grain sizes are required, as they have the greatest relative influence on the modeled amplitude. The hysteresis between plume height and seismic amplitude can then potentially be explained by grain size changes. The PSD shape is mostly determined by the Rayleigh-wave quality factor Q, and substantial variations in seismic amplitude can be modeled assuming a constant mass eruption rate.

JGR Solid Earth↗

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

Satellite observations of the 2016–2017 eruption of Bogoslof volcano: Aviation and ash fallout hazard implications from a water-rich eruption

Satellite data (GOES, VIIRS, MODIS, AVHRR) were used in near real-time during the 2016–2017 eruption of Bogoslof volcano, Alaska, to detect explosive eruptive activity and to characterize the resulting volcanic clouds. This study examines satellite data to estimate volcanic cloud heights and mass eruption rates for 47 of the 70 explosive events. Eighteen of the volcanic clouds reached an altitude in excess of 8.5 km asl, where they posed a potential hazard to aviation. We estimate eruption rates were in the range of 10 4 –10 7 kg/s. Eruption durations were available for 28 events, and the total mass of these events was 5.7 × 10 10 kg. Most of the explosions occurred from submarine vents, producing volcanic clouds with water-rich characteristics in satellite data. We infer that these water-rich (phreatomagmatic) events contained ice-coated ash particles, which changed their visible and multispectral characteristics. Only two of the explosions produced clouds with satellite characteristics that would be considered ash-rich. We conclude that these events were relatively dry eruptions with limited access to ocean water. Although some of the explosive events transitioned from submarine to subaerial vents, we observed no change in the character of the volcanic clouds during these transitions. We speculate that enhanced removal of fine-grained volcanic ash likely occurred due to aggregation, with implications for modeling ash transport and fallout. We conclude that the majority of Bogoslof’s water-rich volcanic clouds did contain volcanic ash despite the lack of conventional “ash signature” in satellite data. This has implications for satellite monitoring of future water-rich/shallow submarine eruptions.

Alaska↗

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

Constraints on eruption processes and event masses for the 2016–2017 eruption of Bogoslof volcano, Alaska, through evaluation of IASI satellite SO2 masses and complementary datasets

Bogoslof volcano, Alaska, experienced at least 70 explosive eruptions between 12 December 2016 and 31 August 2017. Due to its remote location and limited local monitoring network, this eruption was monitored and characterized primarily using remote geophysical and satellite techniques. SO 2 emissions from Bogoslof were persistently detected by the Infrared Atmospheric Sounding Interferometer (IASI) satellite sensors. Of Bogoslof’s 70 explosive events, 50% produced measurable SO 2 masses ranging from 0.1 to 21.5 kt, with a median and standard deviation of 0.7 ± 4.0 kt SO 2 , respectively. Here, we compare IASI-derived SO 2 masses from Bogoslof events to complementary geophysical datasets to provide insights into eruption source processes, namely the degree of seawater scrubbing of water-soluble SO 2 and variations in magma flux. Correlations with the number of lightning strokes and infrasound energy are expected to indicate magma-flux as a controlling process, while correlations with infrasound frequency index are expected to indicate variations in vent-water content as a controlling factor. These comparisons suggest that the measured SO 2 masses are primarily a function of eruption magnitude (degassed magma mass) and that scrubbing of SO 2 emissions by vent seawater may have exerted a minor effect on the observed SO 2 masses. SO 2 masses were combined with petrologic constraints on melt inclusion and matrix glass S concentrations to calculate degassed magma masses and volumes. The cumulative SO 2 -derived degassed magma mass and estimated volume (dense-rock equivalent) for the full Bogoslof eruption were found to be 2.8 × 10 10 kg and 9.3 × 10 6 m 3 , respectively. When individual event masses are compared against event masses calculated using an empirical plume-height method, a strong correlation is found ( R 2 = 0.83), with better than order-of-magnitude agreement in most cases. These estimates of eruption masses provide useful information on the magnitude, behavior, and associated hazards of the 2016–2017 eruption, and potentially future unrest at Bogoslof volcano.

Alaska↗

USGS2020

Characteristics of thunder and electromagnetic pulses from volcanic lightning at Bogoslof volcano, Alaska

We combine global detections of volcanic lightning with acoustic and hydroacoustic data to investigate novel indications of plume electrification in ground-based, geophysical data streams during the 2016–2017 eruption of Bogoslof volcano, Alaska. Such signals offer additional ways to diagnose the occurrence of volcanic lightning and confirm whether eruptive activity is producing significant amounts of ash. We discuss three signatures of lightning activity: volcanic thunder, electromagnetic pulses arising from lightning-induced voltages in cabling, and hydroacoustic signals associated with volcanic lightning. Observations of these phenomena provide additional insights into volcanic lightning activity and reveal several periods of electrical activity that were not otherwise detected during the Bogoslof eruption.

Alaska↗

USGS2020

Combining ash analyses with remote sensing to identify juvenile magma involvement and fragmentation mechanisms during the 2018/19 small eruption of Peteroa volcano (Southern Andes)

The Planchón Peteroa Volcanic Complex (PPVC) is located on the border of Chile and Argentina, and is one of the most active volcanic systems in the Andes. Holocene activity has included magma-water interaction with an evolving series of crater lakes, mainly sourced from Peteroa volcano. This study examines data from the 2018/19 eruption, together with the volcanic history of the PPVC, to elucidate the complex interplay between magmatic activity and summit water and ice. From February 2016 to mid-2019, three seismic swarms occurred in the PPVC, preceding the explosive eruption from September 2018 to April 2019. The activity originated from a small vent nested within the easternmost crater, the most active portion of the complex (Peteroa). The explosions interacted with a crater lake, producing ash plumes up to 2 km above the crater and building a small tephra cone. To investigate the eruption mechanisms, we performed remote sensing analysis of plume dispersal, thermal anomalies and ground deformation, and characterized the volcanic products, including grain size, componentry, morphology, internal textures, composition and mineralogy. Our results suggest that the precursory seismicity beginning in 2016 was related to the intrusion of a new magma batch that reached the surface during the 2018/19 eruption. The eruption was also preceded by thermal anomalies, geomorphic changes and increased hydrothermal activity at the surface, though without any ground deformation recognized through radar interferometry (InSAR). The eruption initially produced predominantly recycled ash (phreatic activity), then evolved to increasing proportions of juvenile magma (phreatomagmatic) by April 2019. The juvenile clasts had a trachyandesite composition (~59 wt% SiO 2 ), with vesicular and dense scoria containing plagioclase and pyroxene. The ash surfaces show external quenching cracks and step fractures consistent with phreatomagmatic fragmentation within the active crater lake. Textural characteristics also point to a slowly ascending batch of magma that was relatively viscous by the time it interacted with water in the crater lake. Notably, these juvenile particles are distinctive from the pre-2018 products. Ash erupted from 2010/11 did not contain recognizable juvenile material, and is inferred to have been a mainly phreatic eruption. Our findings suggest that the interplay between phreatic and phreatomagmatic eruptions fed by small magma batches intruding at shallow levels characterize much of the eruptive behavior of the PPVC during the last three decades. Multi-parametric assessment is a powerful tool to discriminate between phreatic and phreatomagmatic eruptions.

Southern Andes↗

USGS2019

Seismo-acoustic evidence for vent drying during shallow submarine eruptions at Bogoslof volcano, Alaska

Characterizing the state of the volcanic vent is key for interpreting observational datasets and accurately assessing volcanic hazards. This is particularly true for remote, complex eruptions such as the 2016–2017 Bogoslof volcano, Alaska eruption sequence. Bogoslof’s eruptions in this period were either shallow submarine or subaerial, or some combination of both. Our results demonstrate how low-frequency sound waves (infrasound), integrated with seismic and satellite data, can provide unique insight into shallow vent processes, otherwise not available. We use simple metrics, such as the infrasound frequency index (FI), event duration, and acoustic-seismic amplitude ratio, to look at changes in the elastic energy radiation and infer changes in seawater access to the vent. Satellite imagery before and after selected eruptions is used to ground-truth inferences on vent conditions. High FI and gradual increases in infrasound frequency content at Bogoslof correspond with transitions from submarine to subaerial vent conditions and a diminished or absent role of water, likely resulting in a drying out of the vent region. Event durations generally correlate with high FI and the range of FI values for each event, suggesting long duration events were more effective at drying out the vent region. A trend from low to high acoustic-seismic amplitude ratios for some long duration events also suggests an increase in acoustic efficiency as the vent dried out. We demonstrate that infrasound can serve as a robust indicator of seawater involvement for Bogoslof and other shallow submarine eruptions that may not be inferable from other datasets, particularly in near-real-time.

Alaska↗

USGS2019

Field trip guide to Mount St. Helens, Washington—Recent and ancient volcaniclastic processes and deposits

This field guide explores volcanic effusions, sediments, and landforms at Mount St. Helens in Washington. A detailed synopsis outlines the eruptive history of Mount St. Helens from about 300,000 years ago through 1980 and beyond. The five days in the field include about 28 stops and 12 potential stops. Exposures in valleys surrounding Mount St. Helens reveal records of diverse Pleistocene and Holocene processes including debris avalanche, lahar, huge water wave on a nearby lake, pyroclastic density currents (surge and flow), tephra fall, lava flow, the growth of domes, and Pleistocene glaciation. Many of the stops explore effects of the several catastrophes that constituted the 18 May 1980 eruption and made Mount St. Helens famous.

Washington↗

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↗