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Alexa R. Van Eaton

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

At least 19 recordsLinked to original sources
USGS2025

Monitoring lightning and electrification in volcanic plumes

Detection of the electrical discharges and, more fundamentally, the electrification from volcanic plumes is an emerging capability for volcano monitoring. In addition to being able to detect an explosive eruption, such measurements also provide insight into volcanic processes. Volcanic lightning monitoring can be achieved through varying levels of complexity. At the lowest complexity, an observatory can use low-cost global lightning data sets for eruption detection and characterization, while at the highest complexity local lightning sensors can be installed to improve the level of observational detail and response times. This chapter provides background about volcanic lightning and plume electrification, information concerning the relevant instrumentation to detect lightning and electrified plumes, examples of how lightning can be used to understand eruptive processes, and a guide to implementing volcanic lightning detection into a monitoring scheme.

Book chapter↗
USGS2025

Characteristics of volcanic ash reveal changes in fragmentation and eruption dynamics at Poás volcano, Costa Rica, 2016–2019

Determining whether fresh magma has reached the surface during a volcanic eruption can provide important information for forecasts of future activity, especially in the early stages of an eruption. However, identifying fresh, juvenile pyroclasts in tephra fall deposits can be challenging and inconclusive. We studied the products of explosions at Poás volcano, Costa Rica, in 2016–2019, a period during which the volcano transitioned from a pressurized, hydrothermally sealed state to an open conduit with increased degassing to the atmosphere. The activity consisted of semi-continuous explosions producing <500-m-high plumes, with the exception of explosions on April 14 and 22, 2017, that produced 4-km-high plumes. We analyzed the grain size distribution, componentry, and particle density of the products of twenty explosions, and collected groundmass glass composition on juvenile particles for three of them. Our work demonstrates varying degrees of magma involvement with the hydrothermal system through time, with juvenile material representing a wide range of abundance (~10–70 vol.%) in deposits of individual explosions. Before early April 2017, we infer that small phreatomagmatic explosions were triggered by contact between magmatic fluids and/or magma and the hydrothermal system, based on the presence of abundant hydrothermal fragments and minor juvenile magma. Concurrent with decreasing hydrothermal component in the deposits, explosions in April–May 2017 eroded the walls of the shallow plumbing system, evidenced by an increase in wall-rock lithics in the deposits. These changes coincided with drying of the crater lake, leading to several magmatic explosions in April-September 2017, whose juvenile-rich deposits are consistent with primary fragmentation of fresh magma in the conduit. The eruptive activity changed after this magmatic phase, and in 2019, small explosions mostly recycled the heterogeneous deposits of previous events, producing fine material with high proportions of recycled particles. All explosions from 2016–2019 remobilized already-emplaced magma from the 1953–1955 eruptive period, although distinct glass compositions between explosions suggest difference in crystallization or they tapped different portions of this magma body. Our work sheds light on the eruption dynamics and shallow plumbing system of this persistently active volcano and provides a case study for understanding the variable efficiency of phreatomagmatic fragmentation.

Poás volcano↗
USGS2025

How did westward volcaniclastic deposits accumulate in the deep sea following the January 2022 eruption of Hunga Volcano ?

Most volcanic eruptions on Earth take place below the ocean surface and remain largely unobserved. Reconstruction of past submerged eruptions has thus primarily been based on the study of seafloor deposits. Rarely before the 15 January 2022 eruption of Hunga volcano (Kingdom of Tonga) have we been able to categorically link deep-sea deposits to a specific volcanic source. This eruption was the largest in the modern satellite era, producing a 58-km-tall plume, a 20-m high tsunami, and a pressure wave that propagated around the world. The eruption induced the fastest submarine density currents ever measured, which destroyed submarine telecommunication cables and traveled at least 85 km to the west to the neighboring Lau Basin. Here we report findings from a series of remotely operated vehicle dives conducted 4 months after the eruption along the Eastern Lau Spreading Center-Valu Fa Ridge. Hunga-sourced volcaniclastic deposits 7–150 cm in thickness were found at nine sites, and collected. Study of the internal structure, grain size, componentry, glass chemistry, and microfossil assemblages of the cores show that these deposits are the distal portions of at least two ∼100-km-runout submarine density currents. We identify distinct physical characteristics of entrained microfossils that demonstrate the dynamics and pathways of the density currents. Microfossil evidence suggests that even the distal parts of the currents were erosive, remobilizing microfossil-concentrated sediments across the Lau Basin. Remobilization by volcaniclastic submarine density currents may thus play a greater role in carbon transport into deep sea basins than previously thought.

Hunga volcano↗
USGS2024

Special topic—Eruption plumes and clouds

Introduction Explosive eruptions create plumes of volcanic ash and gas that can rise more than 30,000 feet (9.1 kilometers [km]) above sea level within minutes of eruption onset. The resulting clouds disperse under prevailing winds and may cause hazardous conditions hundreds to thousands of kilometers from the volcano, including in international airspace. Rapid detection and characterization of explosive activity is vital to mitigate the wide-ranging effects of volcanic ash. Ashfall thicknesses as small as a millimeter or so on the ground can affect infrastructure, agriculture, and air quality, requiring extensive clean-up procedures (Schuster, 1981; Warrick and others, 1981, U.S. Geological Survey, 2022). Volcanic clouds also pose substantial threats to aircraft. Since 1953, 88 encounters between airplanes and ash clouds have been documented worldwide (International Civil Aviation Organization, 2015, appendix F), resulting in aircraft damage and, in 9 cases, engine failure (Guffanti and others, 2010). In 1982, two large passenger planes suffered complete engine failure owing to eruptions in Indonesia (Global Volcanism Program, 1982) and a similar incident occurred over Alaska in 1989 (Casadevall, 1994). In all three cases, they were able to restart some engine capability and land safely once they emerged from the ash clouds, although with substantial damage (Guffanti and others, 2010). The clear threat to aviation has led to establishment of nine Volcanic Ash Advisory Centers (VAAC) around the world to monitor and rapidly disseminate information about volcanic eruptions to the aviation community. U.S. Geological Survey (USGS) volcano observatories issue the Volcano Observatory Notice for Aviation that informs of preeruptive unrest or eruptive activity. When ash-producing eruptions do occur, volcano observatories work closely with their regional VAAC to ensure consistency and accuracy in eruption onset time, cloud altitude, ash production, and duration as reported in Volcanic Ash Advisories. Explosive volcanism in the United States and Commonwealth of the Northern Mariana Islands prompts 50–100 such advisories in any given year (table J1). This collaborative effort is greatly aided by USGS detection and monitoring of eruption clouds to ensure a timely and coordinated response. To support these efforts to provide guidance on ash transport and fallout, the USGS developed the Ash3d volcanic ash dispersion model ( https://vsc-ash.wr.usgs.gov/ash3d-gui ) (Schwaiger and others, 2012). Automated simulations are run daily by the USGS for volcanoes that are in elevated states of unrest, and in response mode when eruptions occur. During eruptions, the model output is provided to local National Weather Service Weather Forecast Offices to guide them in the issuance of their information products (such as special weather statements, ashfall advisories, or ashfall warnings), as well as to State and local governments and the public. Characterization of the eruption source is needed to estimate the parameters used to initialize the Ash3d model, and by the Anchorage and Washington VAACs to initialize other dispersion models that inform forecasts for the airborne volcanic cloud. The source parameters that can be provided by observation during an eruption include eruption start time, eruption cloud height over time, and eruption duration. Other, nonobservable source parameters, such as mass eruption rate and grain-size distribution, are based on empirical correlations and study of historical deposits. The goal is to provide a time series of cloud heights, mass eruption rates, and particle-size distributions that accurately reflects current conditions. When feasible, the USGS also provides guidance on the nature of ongoing eruptions and forecasts future activity using petrologic monitoring of collected tephra samples. The aims of providing accurate observable parameters are achieved through analysis of (1) near-real-time meteorological satellite data, (2) ground-based cameras (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–G, 11 p., https://doi.org/10.3133/sir20245062g.">chapter G , this volume; Orr and others, 2024), (3) weather radar, (4) volcanic lightning detection, and (5) ground-based ash sensors and sampling. Explosive eruptions can be detected by a variety of geophysical monitoring, including infrasound (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–C, 11 p., https://doi.org/10.3133/sir20245062c.">chapter C , this volume; Lyons and others, 2024) and seismicity (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–B, 9 p., https://doi.org/10.3133/sir20245062b.">chapter B , this volume; Thelen and others, 2024). However, those methods cannot quantify the altitude, ash content, and dispersal dynamics of resulting volcanic clouds. Ideally, all available sources of monitoring data are synthesized to develop a coherent understanding of eruptive activity. The guidance summarized here provides a framework for characterizing volcanic clouds in the atmosphere and tracking the evolution of explosive eruption dynamics.

Scientific Investigations Report↗
USGS2024

Did steam boost the height and growth rate of the giant Hunga eruption plume?

The eruption of Hunga volcano on 15 January 2022 produced a higher plume and faster-growing umbrella cloud than has ever been previously recorded. The plume height exceeded 58 km, and the umbrella grew to 450 km in diameter within 50 min. Assuming an umbrella thickness of 10 km, this growth rate implied an average volume injection rate into the umbrella of 330–500 km 3 s −1 . Conventional relationships between plume height, umbrella-growth rate, and mass eruption rate suggest that this period of activity should have injected a few to several cubic kilometers of rock particles (tephra) into the plume. Yet tephra fall deposits on neighboring islands are only a few centimeters thick and can be reproduced using ash transport simulations with only 0.1–0.2 km 3 erupted volume (dense-rock equivalent). How could such a powerful eruption contain so little tephra? Here, we propose that seawater mixing at the vent boosted the plume height and umbrella growth rate. Using the one-dimensional (1-D) steady plume model Plumeria, we find that a plume fed by ~90% water vapor at a temperature of 100 °C (referred to here as steam) could have exceeded 50 km height while keeping the injection rate of solids low enough to be consistent with Hunga’s modest tephra-fall deposit volume. Steam is envisaged to rise from intense phreatomagmatic jets or pyroclastic density currents entering the ocean. Overall, the height and expansion rate of Hunga’s giant plume is consistent with the total mass of fall deposits plus underwater density current deposits, even though most of the erupted mass decoupled from the high plume. This example represents a class of high (> 10 km), ash-poor, steam-driven plumes, that also includes Kīlauea (2020) and Fukutoku-oka-no-ba (2021). Their height is driven by heat flux following well-established relations; however, most of the heat is contained in steam rather than particles. As a result, the heights of these water-rich plumes do not follow well-known relations with the mass eruption rate of tephra.

Bulletin of Volcanology↗
USGS2023

A one-dimensional volcanic plume model for predicting ash aggregation

During 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.

JGR Solid Earth↗
USGS2023

New insights into the relationship between mass eruption rate and volcanic column height based on the IVESPA dataset

Rapid 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.

Geophysical Research Letters↗
USGS2023

Lightning rings and gravity waves: Insights into the giant eruption plumefrom Tonga’s Hunga Volcano on 15 January 2022

On 15 January 2022, Hunga Volcano in Tonga produced the most violent eruption in the modern satellite era, sending a water-rich plume at least 58 km high. Using a combination of satellite- and ground-based sensors, we investigate the astonishing rate of volcanic lightning (>2,600 flashes min −1 ) and what it reveals about the dynamics of the submarine eruption. In map view, lightning locations form radially expanding rings. We show that the initial lightning ring is co-located with an internal gravity wave traveling >80 m s −1 in the stratospheric umbrella cloud. Buoyant oscillations of the plume's overshooting top generated the gravity waves, which enhanced turbulent particle interactions and triggered high-current electrical discharges at unusually high altitudes. Our analysis attributes the intense lightning activity to an exceptional mass eruption rate (>5 × 10 9 kg s −1 ), rapidly expanding umbrella cloud, and entrainment of abundant seawater vaporized from magma-water interaction at the submarine vent.

Hunga Volcano↗
USGS2023

Flow development and entrainment in turbulent particle-laden jets

Explosive eruptions expel volcanic gases and particles at high pressures and velocities. Within this multiphase fluid, small ash particles affect the flow dynamics, impacting mixing, entrainment, turbulence, and aggregation. To examine the role of turbulent particle behavior, we conducted an analogue experiment using a particle-laden jet. We used compressed air as the carrier fluid, considering turbulent conditions at Reynolds numbers from approximately 5,000 to 20,000. Two different particles were examined: 14-μm diameter solid nickel spheres and 13-μm diameter hollow glass spheres. These resulted in Stokes numbers between 1 and 35 based on the convective scale. The particle mass percentage in the mixture is varied from 0.3% to more than 20%. Based on a 1-D volcanic plume model, these Stokes numbers and mass loadings corresponded to millimeter-scale particle diameters at heights of 4–8 km above the vent during large, sustained eruptions. Through particle image velocimetry, we measured the mean flow behavior and the turbulence statistics in the near-exit region, primarily focusing on the dispersed phase. We show that the flow behavior is dominated by the particle inertia, with high Stokes numbers reducing the entrainment by more than 40%. When applied to volcanic plumes, these results suggest that high-density particles can greatly increase the probability of column collapse.

Journal of Geophysical Research: Atmospheres↗
USGS2023

Remote characterization of the 12 January 2020 eruption of Taal Volcano, Philippines, using seismo-acoustic, volcanic lightning, and satellite observations

On 12 January 2020, an eruption began on the shores of the Main Crater Lake (MCL) of Taal Volcano—a caldera system on the southern end of Luzon Island in the Philippines. Taal, one of the most active volcanoes in the Philippines, is located 30 km south of Manila—a major metropolitan area with a population of 13.5 million people. Eruptive activity intensified throughout the day on 12 January, producing prolific volcanic lightning, ashfall, and a sustained plume that reached 16–17 km altitude. The chronology of events was well documented by the Philippine Institute of Volcanology and Seismology and the Tokyo Volcanic Ash Advisory Center. The wealth of data collected during the eruption provides a unique opportunity to investigate how the combination of different remote sensing methods may complement local observations and monitoring. Remote systems tend to provide lower resolution data but are also less likely to be compromised by the eruptive activity, thus providing continuous records of eruptive processes. Here, we present a postevent analysis of the 12 January activity, including data from long‐range lightning, infrasound, and seismic arrays located at distances up to several thousands of kilometers from the volcano. By combining these datasets, we distinguish five phases of activity and infer a major shift in eruption behavior around 12:00 on 12 January (UTC). The remote observations suggest that the most of the water within the MCL ( ⁠∼42 million m 3⁠ ) was vaporized and incorporated into the volcanic plume within the first 12 hr of the eruption.

Taal Volcano↗
USGS2023

Dynamics of the December 2020 ash-poor plume formed by lava-water interaction at the summit of Kilauea Volcano, Hawaii

On 20 December 2020, after more than 2 years of quiescence at Kīlauea Volcano, Hawaiʻi, renewed volcanic activity in the summit crater caused boiling of the water lake over a period of ∼90 min. The resulting water-rich, electrified plume rose to 11–13 km above sea level, which is among the highest plumes on record for Kīlauea. Although conventional models would infer a high mass flux from explosive magma-water interaction, the plume was not associated with an infrasound signal indicative of “explosive” activity, nor did it produce a measurable ash-fall deposit. We use multisensor data to characterize lava-water interaction and plume generation during this opening phase of the 2020–21 eruption. Satellite, weather radar, and eyewitness observations revealed that the plume was rich in water vapor and hydrometeors but transported less ash than expected from its maximum height. Volcanic lightning flashes detected by ground-based cameras were confined to freezing altitudes of the upper cloud, suggesting that the ice formation drove the electrification of this plume. The low acoustic energy from lava-water interaction points to a weakly explosive style of hydrovolcanism. Heat transfer calculations show that the lava to water heat flux was sufficient to boil the lake within 90 min. Limited mixing of lava and water inhibited major steam explosions and fine fragmentation. Results from one-dimensional plume modeling suggest that the models may underpredict plume height due to overestimation of crosswind air-entrainment. Our findings shed light on an unusual style of volcanism in which weakly explosive lava-water interaction generated an outsized plume.

Hawaii↗
USGS2023

Ash aggregate-rich pyroclastic density currents of the 431 CE Tierra Blanca Joven eruption, Ilopango caldera, El Salvador

The VEI 6, Tierra Blanca Joven pyroclastic sequence (30–90 km 3 DRE volume), erupted from Ilopango caldera, El Salvador, in 431 CE, is the product of one of the largest eruptions of the last two millennia. The eruption devastated Central America's Mayan civilization. The eruption began with a short-lived phase of ash and pumice fall deposition and transitioned to a ‘wet’ explosive phase during which pyroclastic density currents flowed >40 km from the caldera. Detailed field and sedimentological analyses are provided for the deposits of ash-aggregate-rich pyroclastic density currents generated during early phases of the eruption. The first phase of pyroclastic density current inundation incinerated forests and deposited up to 30 m of, non-welded, ash-rich ignimbrite in proximal regions, along with ash fall layers of co-ignimbrite origin. Following fallout of a thin layer of pumice and lithic lapilli, a second phase of pyroclastic density current inundation and co-ignimbrite ash fall commenced. A range of ash aggregate types is present in the pyroclastic density current deposits and interbedded co-ignimbrite ash fall layers. Whole and broken concentrically layered ash aggregates (accretionary lapilli) reach >50 vol% in some horizons within some beds in the pyroclastic density current deposits. The evidence indicates that the ash aggregates grew within overriding co-ignimbrite ash plumes and subsequently fell into ground-hugging currents. Our findings suggest that the aggregate-rich nature of the pyroclastic density current deposits originated through incorporation of lake water into eruptive plumes, which in turn triggered rapid, pervasive aggregation within ash clouds and co-ignimbrite plumes.

Ilopango caldera↗
USGS2022

Understanding and modeling tephra transport: Lessons learned from the 18 May 1980 eruption of Mount St. Helens

Discoveries made during the 18 May 1980 eruption of Mount St. Helens advanced our understanding of tephra transport and deposition in fundamental ways. The eruption enabled detailed, quantitative observations of downwind cloud movement and particle sedimentation, along with the dynamics of co-pyroclastic-density current (PDC) clouds lofted from ground-hugging currents. The deposit was mapped and sampled over more than 150,000 km 2 within days of the event and remains among the most thoroughly documented tephra deposits in the world. Abundant observations were made possible by the large size of the eruption, its occurrence in good weather during daylight hours, cloud movement over a large, populated continent, and the availability of images from recently deployed satellites. These observations underpinned new, quantitative models for the rise and growth of volcanic plumes, the importance of umbrella clouds in dispersing ash, and the roles of particle aggregation and gravitational instabilities in removing ash from the atmosphere. Exceptional detail in the eruption chronology and deposit characterization helped identify the eruptive phases contributing to deposition in different sectors of the distal deposit. The eruption was the first to significantly impact civil aviation, leading to the earliest documented case of in-flight engine damage. Continued eruptive activity in 1980 also motivated pioneering use of meteorological models to forecast ash-cloud movement. In this paper, we consider the most important discoveries and how they changed the science of tephra transport.

Washington↗
USGS2022

Spatial analysis of globally detected volcanic lightning from the June 2019 eruption of Raikoke volcano, Kuril Islands

The 21–22 June 2019 eruption of Raikoke volcano, Russia, provided an opportunity to explore how spatial trends in volcanic lightning locations provide insights into pulsatory eruption dynamics. Using satellite-derived plume heights, we examine the development of lightning detected by Vaisala’s Global Lightning Dataset (GLD360) from eleven, closely spaced eruptive pulses. Results from one-dimensional plume modeling show that the eruptive pulses with maximum heights 9–16.5 km above sea level were capable of producing ice in the upper troposphere, which contributed variably to electrification and volcanic lightning. A key finding is that lightning locations not only followed the main dispersal direction of these ash plumes, but also tracked a lower-level cloud derived from pyroclastic density currents. We show a positive relationship between umbrella cloud expansion and the area over which lightning occurs (the ‘lightning footprint’). These observations suggest useful metrics to characterize ongoing eruptive activity in near real-time.

Kuril Islands, Raikoke volcano↗
USGS2022

Discriminating types of volcanic electrical activity: Toward an eruption detection algorithm

We present a method for classification of the two distinct types of electrical activity that occur during an explosive volcanic eruption: vent discharges and lightning. Vent discharges occur at the onset of an explosion and create a distinctive radio frequency signature called continual radio frequency. Seconds to minutes after the onset of the eruption, lightning begins to occur throughout the eruption column. We use logistic regression to classify a radio frequency impulse as being part of either a lightning flash or a period of continual radio frequency. The classifier uses the number of peaks in the amplitude envelope from 1 ms windows before and after the impulsive very high frequency waveform, with an average accuracy of 97.9%. We propose that this method could be used in an algorithm to determine when explosive eruptions occurred by identification of the distinctive signatures of vent discharges and lightning.

Geophysical Research Letters↗
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↗