Validation for computational modelling of volcanic ballistic projectiles (VBPs) has often been accomplished by replication of field-surveyed VBP distributions. However, a range of ejection parameters can result in the same impact location, with differing impact energies and therefore hazard implications. Ballistic hazard models must accurately represent the whole trajectory to better estimate ballistic energy and interpret eruption dynamics. We examine model performance by directly measuring Strombolian VBP ejection parameters and trajectories from high-speed video and comparing with modelled trajectories using the same parameters. We illustrate the effects of velocity and size on drag. We synthesize and investigate different methods by which the Reynolds number ( Re ) - drag coefficient (C D ) relationship is incorporated into models and how this affects modelling results. Our computational model allows for application of different existing Re -C D methods and direct comparison to tracked trajectories on the metrics of impact distance and peak height. Even with validated ejection parameters and appropriate Re -C D relationships, the model rarely accurately reproduces both height and distance within a 5% threshold. The most common scenario is model overestimation of both metrics. The gas jet is the largest factor contributing to this discrepancy. Significant slowing of VBPs in excess of gravity is observed while bombs are rising (and within the gas jet radius) but not while falling. Slowing in the gas jet is potentially caused by friction with ash and lapilli, surface temperature effects, or other fluid dynamics effects. • Drag affects small, fast volcanic bombs more. • Models often overestimate the height and impact distance of bomb paths. • The gas jet above the vent slows bombs down. • Slowdown might be due to friction with ash, denser gases, or the hot bomb surface.
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A. Sork
L. Watson
B. Kennedy
Journal of Volcanology and Geothermal Research
University of Canterbury
Istituto Nazionale di Geofisica e Vulcanologia
GNS Science
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Sork et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69a75b7bc6e9836116a22ddd — DOI: https://doi.org/10.1016/j.jvolgeores.2026.108543
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