Dark-flight Estimates of Meteorite Fall Positions: Issues and a Case Study Using the Murrili Meteorite Fall

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 dark-flight modeling 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, with a low-altitude endpoint, such that the dark flight was relatively short. Murrili is 1.68 kg with a typical ordinary chondrite density but with a somewhat flattened shape compared to a sphere, such that there are discrepancies between sphere-based predictions and the actual recovery location. It is notable that even in this relatively idealized dark-flight scenario, modeling using spherically shaped projectiles resulted in a significant distance between predicted fall position and recovered meteorite.

Trajectory, recovery, and orbital history of the Madura Cave meteorite

“…Using these atmosphere models, we can then propagate bright flight observations to the ground using the darkflight model of Towner et al. (2021). In Fig.…”

The Winchcombe fireball—That lucky survivor

“…The 12:00 UTC wind model was used to predict where meteorites would land, based on the last observed bright flight state vector (see the Trajectory section), using the method of Towner et al. (2022; code openly available at https://github.com/desertfireballnetwork/DFN_darkflight). We create Monte Carlo clones by varying the final observed state vector within uncertainty (see the Trajectory section), as well as meteorite physical parameters such as mass, shape, and density (fixed at 2090 kg m −3 based on recovered meteorite properties King et al., 2022).…”

Near-Earth object 2022 EB5: From atmospheric entry to physical properties and orbit

“…The vector r is the radius vector of the object in the Earthcentered inertial (ECI) coordinate system, whereas its norm is denoted as r. In addition, µ denotes the standard gravitational parameter of the Earth and m is the mass of the object. The symbol F D represents the atmospheric drag to the object and can be calculated via (Towner et al 2022):…”