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Random forest constraints on fine ash concentration and charging processes from experimentally generated volcanic discharges Rayborn, Lindsey Kate

Abstract

Explosive volcanic plume rise is governed by the rate at which ambient air is ingested and heated by turbulent entrainment and mixing processes. A daunting observational challenge is to constrain the character of the underlying physical processes and their dependence on complex particle-particle and particle-gas interactions. Important clues may lie in the particle-particle momentum exchange that gives rise to lightning flashes and related electrical discharges near the vent during supersonic eruptions where they occur. Recent laboratory studies of positive and negative shock tube-generated volcanic discharges show a correlation between fine ash concentration and the magnitude and number of positive discharges [22]. Charge generation via collisions (triboelectrification) is hypothesized to be more efficient with high ash concentrations and at high decompression rates because collisions between particles become more frequent under these conditions [22]. To test this hypothesis and understand the experimental data in greater detail, we develop and implement a regression-based random forest algorithm to quantitatively constrain concentrations of fine ash using discharge count, magnitude and polarity as predictors. We bin experiments into subsets containing 1. all (ALL), 2. low (< 10 MPa) and high (≥ 10 MPa) pressure, and 3. low (≤ 22 g) and high (> 22 g) mass experiments. We define a metric for variable importance and find in ALL, HP, and HM subsets that positive discharge properties are more important predictors of fine ash concentration than negative discharge properties, consistent with triboelectrification as the predominant process under these conditions. This mechanism is not constrained for LP conditions, suggesting a potential threshold decompression rate condition for this class of charging and insight into why near-vent lightning is not a ubiquitous feature of explosive eruptions.

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Attribution-NonCommercial-NoDerivatives 4.0 International