Darkflight estimates of meteorite fall positions: issues and a case study using the Murrili meteorite fall
M.C. Towner, T. Jansen-Sturgeon, M. Cupak, E.K. Sansom, H.A.R., Devillepoix, P.A. Bland, R.M Howie, J.P. Paxman, G.K. Benedix, B.A.D. Hartig

TL;DR
This paper discusses the complexities of darkflight modeling for meteorite recovery, highlighting how factors like shape and density influence impact position predictions, exemplified by the Murrili meteorite case study.
Contribution
It introduces the Desert Fireball Network's approach to darkflight modeling, addressing shape, mass, and density effects, and demonstrates these with a detailed case study.
Findings
Shape and density significantly affect fall position predictions.
Spherical models can lead to substantial errors in impact location.
Well-observed cases like Murrili highlight modeling challenges.
Abstract
Fireball networks are used to recover meteorites, with the context of orbits. Observations from these networks cover the bright flight, where the meteoroid is luminescent, but to recover a fallen meteorite, these observations must often be predicted forward in time to the ground to estimate an impact position. This darkflight modelling is deceptively simple, but there is hidden complexity covering the precise interactions between the meteorite and the (usually active) atmosphere. We describe the method and approach used by the Desert Fireball Network, detailing the issues we have addressed, and the impact that factors such as shape, mass and density have on the predicted fall position. We illustrate this with a case study of Murrili meteorite fall that occurred into Lake Eyre-Kati Thanda in 2015. The fall was very well observed from multiple viewpoints, and the trajectory was steep,…
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Taxonomy
TopicsAstro and Planetary Science · Isotope Analysis in Ecology · Planetary Science and Exploration
