Character, mass, distribution, and origin of tephra-fall deposits from the 2009 eruption of Redoubt Volcano, Alaska—Highlighting the significance of particle aggregation

Wallace, Kristi L.; Schaefer, J. R.; Coombs, Michelle L.

doi:10.1016/j.jvolgeores.2012.09.015

Cited by 60 publications

(102 citation statements)

References 34 publications

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“…3a, 4a) is consistent with the distribution of tephra-fall deposits measured for these events ( Fig. 5; Wallace et al 2013). Estimated plume distributions calculated using the US Standard Atmosphere remain fixed over the vent and overshoot the measured plume heights in excess of 1500 m.…”

Section: Resultssupporting

confidence: 84%

Using infrasound to constrain ash plume rise

2015

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Airborne volcanic ash advisories are currently based on analyses of satellite imagery with relatively low temporal resolution, and numerical simulations of atmospheric plume dispersion. These simulations rely on key input parameters such as the maximum height of eruption plumes and the mass eruption rate at the vent, which remain loosely constrained. In this study, we present a proof-of-concept workflow that incorporates the analysis of volcanic infrasound with numerical modelling of volcanic plume rise in a realistic atmosphere. We analyse acoustic infrasound records from two explosions during the 2009 eruption of Mt. Redoubt, USA, that produced plumes reaching heights of 12-14 km. We model the infrasonic radiation at the source under the assumptions of linear acoustic theory and calculate variations in mass ejection velocity at the vent. The estimated eruption velocities serve as the input for numerical models of plume rise. The encouraging results highlight the potential for infrasound measurements to be incorporated into numerical modelling of ash dispersion, and confirm their value for volcano monitoring operations.

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Section: Resultssupporting

confidence: 84%

Using infrasound to constrain ash plume rise

2015

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“…Other works employing Eulerian models to simulate ash deposition from the same eruptive event had similar issues for many model runs in the far field using a similar model set-up [44,51]. Potential sources of error for all studies include distinguishing between ash layers from different eruptive events in the field [43], issues with wind field resolution through high elevation regions, and ash aggregation effects (discussed below in detail) that are not currently treated by any volcanic transport model.…”

Section: Constraining Vatdmsmentioning

confidence: 97%

“…Error can be introduced when determining the height of the plume, which is often deduced from seismic data or reported by pilots in the area. Another technique that is often used involves erupted masses determined from mapped deposits and the seismic durations of eruptive events [43,44], but this technique relies on the assumption that MFR is constant over the entire duration of the eruptive episode. The success of this method hinges upon a thorough and timely sampling of the eruptive deposits, including only ash deposited from the relevant eruptive event.…”

Section: Constraining Vatdmsmentioning

confidence: 99%

“…The success of this method hinges upon a thorough and timely sampling of the eruptive deposits, including only ash deposited from the relevant eruptive event. Because of the large uncertainties that go into any MFR calculation, independent estimates of MFR for a given eruptive event can vary over orders of magnitude [43][44][45]. There are not many good estimates of MFR for Arctic eruptions due to the remote locations of many volcanoes, making MFR a poorly constrained parameter to which advection-diffusion models can exhibit a high degree of sensitivity [46].…”

Section: Constraining Vatdmsmentioning

confidence: 99%

“…This assumption can be made because the larger particles are relatively low in abundance and are concentrated in regions close to the vent [43]. Ash refractive indices for a given composition can be taken from previous laboratory studies, where available (e.g., [34]).…”

Section: Constraining a Radiative Model For Volcanic Ash Depositsmentioning

confidence: 99%

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Radiative Impacts of Volcanic Aerosol in the Arctic

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Updates in Volcanology - From Volcano Modelling to Volcano Geology

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Modeling ash fall distribution from a Yellowstone supereruption

Mastin

Eaton

Lowenstern

2014

Geochem Geophys Geosyst

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We used the volcanic ash transport and dispersion model Ash3d to estimate the distribution of ashfall that would result from a modern-day Plinian supereruption at Yellowstone volcano. The simulations required modifying Ash3d to consider growth of a continent-scale umbrella cloud and its interaction with ambient wind fields. We simulated eruptions lasting 3 days, 1 week, and 1 month, each producing 330 km 3 of volcanic ash, dense-rock equivalent (DRE). Results demonstrate that radial expansion of the umbrella cloud is capable of driving ash upwind (westward) and crosswind (N-S) in excess of 1500 km, producing more-or-less radially symmetric isopachs that are only secondarily modified by ambient wind. Deposit thicknesses are decimeters to meters in the northern Rocky Mountains, centimeters to decimeters in the northern Midwest, and millimeters to centimeters on the East, West, and Gulf Coasts. Umbrella cloud growth may explain the extremely widespread dispersal of the 640 ka and 2.1 Ma Yellowstone tephra deposits in the eastern Pacific, northeastern California, southern California, and South Texas.

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Character, mass, distribution, and origin of tephra-fall deposits from the 2009 eruption of Redoubt Volcano, Alaska—Highlighting the significance of particle aggregation

Cited by 60 publications

References 34 publications

Using infrasound to constrain ash plume rise

Using infrasound to constrain ash plume rise

Radiative Impacts of Volcanic Aerosol in the Arctic

Modeling ash fall distribution from a Yellowstone supereruption

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