Dynamics of Large, Wet Volcanic Clouds : The 25.4 ka Oruanui Eruption of Taupo Volcano, New Zealand

This work investigates the dynamics of large-scale, ‘wet’ volcanic eruption clouds generated by the interaction of silicic magma with external water. The primary case study draws from a detailed record of non-welded pyroclastic deposits from the ~25.4 ka Oruanui eruption of Taupo volcano, New Zealand, one of the largest phreatomagmatic eruptions documented worldwide. This research uses a three-pronged approach, integrating results from (i) field observations and textural data, (ii) mesoscale numerical modeling of volcanic plumes, and (iii) analogue laboratory experiments of volcanic ash aggregation. This interdisciplinary approach provides a new understanding of dynamic and microphysical interactions between collapsing and buoyant columns, and how this behavior controls the large-and small-scale nature of phreatoplinian eruption clouds. Stratigraphic field studies examine the styles of dispersal and emplacement of deposits from several phases of the Oruanui eruption (primarily phases 2, 3, 5, 6, 7 and 8). Detailed stratigraphic observations and laser diffraction particle size analysis of ash aggregates in these deposits clarify the evolution of aggregation mechanisms with time through the relevant eruption phase, and with distance from vent. Deposits of the wettest phase (3) show the key role of turbulent lofting induced by pyroclastic density currents in forming aggregates, particularly those with ultrafine ash rims (30-40 vol.% finer than 10 μm) which are uniquely formed in the ultrafine ash-dominated clouds above the currents. Drier deposits of phases 2 and 5, which also saw lower proportions of material emplaced by pyroclastic density currents, contain fewer aggregates that are related to low water contents in the medial to distal plume. Discovery and documentation of high concentrations of diatom flora in the Oruanui deposits indicates efficient fragmentation and incorporation of paleo-lake Taupo sediments during the eruption. This highlights the potential for incidental contamination of volcanic deposits with broader implications for correlation of distal tephras and possible contamination of paleoenvironmental records due to incorporation of diachronous populations of volcanically-dispersed diatoms. The impact of extensive surface water interaction on large-scale volcanic eruptions (>108 kg s-1 magma) is examined by employing the first 2-D large-eddy simulations of ‘wet’ volcanic plumes that incorporate the effects of microphysics. The cloud-resolving numerical model ATHAM was initialized with field-derived characteristics of the Oruanui case study. Surface water contents were varied from 0-40 wt.% for eruptions with equivalent magma eruption rates of c. 1.3 x108 and 1.1 x109 kg s-1. Results confirm that increased surface water has a pronounced impact on column stability, leading to unstable column behavior and hybrid clouds resulting from simultaneous ascent of material from stable columns and pyroclastic density currents (PDCs). Contrary to the suggestion of previous studies, however, abundant surface water does not systematically lower the spreading level or maximum height of volcanic clouds, owing to vigorous microphysics-assisted lofting of PDCs. Key processes influencing the aggregation of volcanic ash and hydrometeors (airborne water phases) are examined with a simple and reproducible experimental method employing vibratory pan agglomeration. Aggregation processes in the presence of hail and graupel, liquid water (<30 wt.%), and mixed water phases are investigated at temperatures from 18 to -20 °C. Observations from impregnated thin sections, SEM images and x-ray computed microtomography of these experimental aggregates closely match natural examples from phreatomagmatic phases of the ~25.4 ka Oruanui and Eyjafjallajökull (May 2010) eruptions. These experiments demonstrate that the formation of concentric, ultrafine rims comprising the outer layers of rim-type accretionary lapilli requires recycled exposure of moist, preexisting pellets to regions of volcanic clouds that are relatively dry and dominated by ultrafine (<31 μm) ash. This work presents the first experimentally-derived aggregation coefficients that account for changing liquid water contents and sub-zero temperatures, and indicates that dry conditions (<10 wt.% liquid) promote the strongly size-selective collection of sub-31 μm particles into aggregates (given by aggregation coefficients >1). These quantitative relationships may be used to predict the timescales and characteristics of aggregation, such as aggregate size spectra, densities and constituent particle size characteristics, when the initial size distribution and hydrometeor content of a volcanic cloud are known. The integration of numerical modeling, laboratory experimentation and field data lead to several key conclusions. (1) The importance of the microphysics of ash-water interactions in governing the eruption cloud structure, boosting the dispersal power of the cloud and controlling aggregate formation in response to differing water contents and eruption rates. (2) Recognition of the contrasting roles of differential aggregation versus cloud grain size in controlling the formation and nature of aggregate particles, notably those with characteristic ultrafine outer rims. (3) The importance of pyroclastic density currents as triggers for convection and aggregation processes in the eruption cloud

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 ρagg, and a log-normal size distribution with median μagg and standard deviation σagg. 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 μagg and σagg, holding ρagg constant at 600 kgm-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 μagg ranged narrowly between ∼2.3 and 2.7φ (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 ( \u3c 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

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

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 (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

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, 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 modelling demonstrate that hail-forming processes in the eruption plume triggered aggregation of ∼95% of the fine ash and stripped much of the erupted mass out of the atmosphere within 30 min. Based on these findings, we propose a mechanism of hail-like ash aggregation that contributes to the anomalously rapid fallout of fine ash and occurrence of concentrically layered aggregates in volcanic deposits.AVE acknowledges NSF Postdoctoral Fellowship EAR1250029 and a seed grant from NASA Ames Supercomputing Center. Integrated Data Viewer (IDV) software from UCAR/Unidata was used in the analysis and visualization of the large-eddy simulation. ASTER GDEM is a product of NASA and METI. NCAR Reanalysis data provided by the NOAA/OAR/ESRL Physical Sciences Division, Boulder, Colorado, USA. We acknowledge Victoria University of Wellington, New Zealand, for access to the laser particle size analyzer, and Matt Rogers at University of Alaska, Anchorage for use of the freeze dryer. Rick Hoblitt is thanked for discussions and comments on the manuscript.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/ncomms886

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

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

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

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

Electrification Processes and Lightning Generation in Volcanic Plumes—Observations from Recent Eruptions

Lightning in volcanic plumes provides a promising way to monitor ash-producing eruptions and investigate their dynamics. Among the many methods of lightning detection are global networks of sensors that detect electromagnetic radiation in the very low frequency band (3–30 kHz), including the World Wide Lightning Location Network. These radio waves propagate thousands of kilometers at the speed of light, providing an opportunity for rapid detection of explosive volcanism anywhere in the world. Lightning is particularly valuable as a near real-time indicator of ash-rich plumes that are hazardous to aviation. Yet many fundamental questions remain. Under what conditions does electrical activity in volcanic plumes become powerful, detectable lightning? And conversely, can we use lightning to illuminate eruption processes and hazards? This study highlights recent observations from the eruptions of Redoubt (Alaska, 2009), Kelud (Indonesia, 2014), Calbuco (Chile, 2015), and Bogoslof (Alaska, 2017) to examine volcanic lighting from a range of eruption styles (Surtseyan to Plinian) and mass eruption rates from 10^5 to 10^8 kg/s. It is clear that lightning stroke-rates do not scale in a simple way with mass eruption rate or plume height across different eruptions. However, relative changes in electrical activity through individual eruptions relate to changes in eruptive intensity, ice content, and volcanic plume processes (fall vs. flow)

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 ρagg, and a log-normal size distribution with median μagg and standard deviation σagg. 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 μagg and σagg, holding ρagg constant at 600 kgm-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 μagg ranged narrowly between ∼2.3 and 2.7φ (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 ( \u3c 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

Volcanic Lightning as a Monitoring Tool during the 2016-2017 Eruption of Bogoslof Volcano, AK

Volcanic lightning commonly occurs during powerful, ash-producing eruptions. Bogoslof Volcano in the Aleutian Islands of Alaska erupted from December 12th 2016 to August 30th 2017. There were 64 explosive events generating ash clouds, some of which impacted aviation and local communities. Approximately half of the eruptions produced volcanic lightning detectable by the World Wide Lightning Location Network (WWLLN). Detections were provided in near-real-time to the U.S. Geological Survey (USGS), representing the first time volcanic lightning has been used in operational monitoring efforts nationwide. Lightning activity was later verified in post-analysis by the Vaisala Global Lightning Dataset (GLD360). In this study, we examine volcanic lightning detected by both networks, and analyze the travel direction of the lightning. Our analysis shows that lightning azimuths matched the ash dispersal direction from satellite 64% of the time, and Ash3d model trajectories 78% of the time. This suggests that lightning travel direction can be a useful proxy for ash cloud dispersal in the early stages of eruption detection