Abstract
AbstractVolcanic lightning—a near ubiquitous feature of explosive volcanic eruptions—possesses great potential for the analysis of volcanic plume dynamics. To date, the lack of quantitative knowledge on the relationships between plume characteristics hinders efficient data analysis and application of the resulting parameterizations. We use a shock‐tube apparatus for rapid decompression experiments to produce particle‐laden jets. We have systematically and independently varied the water content (0–27 wt%) and the temperature (25–320 °C) of the particle‐gas mixture. The addition of a few weight percent of water is sufficient to reduce the observed electrification by an order of magnitude. With increasing temperature, a larger number of smaller discharges are observed, with the overall amount of electrification staying similar. Changes in jet dynamics are proposed as the cause of the temperature‐dependence, while multiple factors (including the higher conductivity of wet ash) can be seen responsible for the decreased electrification in wet experiments.
Highlights
Volcanic lightning is the result of ash electrification in volcanic plumes
A furnace is placed around the autoclave to heat the samples to temperatures relevant for volcanic plumes
We observe the introduction of dominantly negative charge into the Faraday cage (FC) that is neutralized by discharges of opposite polarity (Figure 2c)
Summary
Volcanic lightning is the result of ash electrification in volcanic plumes. It has been observed at volcanoes all around the world, representing a large variety of magma compositions and eruptive styles (Mather & Harrison, 2006; McNutt & Williams, 2010; Nicoll et al, 2019). It is associated with several geophysical signals that can be used for volcano monitoring from a safe distance and especially in unfavorable weather conditions (Behnke & McNutt, 2014). F. Anderson et al, 2018; Cimarelli et al, 2016; Haney et al, 2018; Smith et al, 2017), high‐speed video recordings (Cimarelli et al, 2016), magnetotelluric measurements (Aizawa et al, 2010; Aizawa et al, 2016), and seismic data (Smith et al, 2018)
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