Determining Fireball Fates Using the α–β Criterion

Abstract

As fireball networks grow, the number of events observed becomes unfeasible to manage by manual efforts. Reducing and analysing big data requires automated data pipelines. Triangulation of a fireball trajectory can swiftly provide information on positions and, with timing information, velocities. However, extending this pipeline to determine the terminal mass estimate of a meteoroid is a complex next step. Established methods typically require assumptions to be made of the physical meteoroid characteristics (such as shape and bulk density). To determine which meteoroids may have survived entry there are empirical criteria that use a fireball's final height and velocity -low and slow final parameters are likely the best candidates. We review the more elegant approach of the dimensionless coefficient method. Two parameters, α (ballistic coefficient) and β (mass-loss), can be calculated for any event with some degree of deceleration, given only velocity and height information. α and β can be used to analytically describe a trajectory with the advantage that they are not mere fitting coefficients; they also represent the physical meteoroid properties. This approach can be applied to any fireball network as an initial identification of key events and determine on which to concentrate resources for more in depth analyses. We used a set of 278 events observed by the Desert Fireball Network to show how visualisation in an α -β diagram can quickly identify which fireballs are likely meteorite candidates.

Murrili meteorite’s fall and recovery from Kati Thanda

“…2012; Sansom et al. 2019a). The dimensionless ballistic (α) and mass loss (β) parameters calculated for this fireball are α = 8.34 and β = 1.063 (Fig.…”

Physically based alternative to the PE criterion for meteoroids

“…Finally, the values of α or β can be also retrieved accurately under certain meteoroid atmospheric fragmentation scenarios (see Gritsevich 2008a;Moreno-Ibáñez 2018). It has been demonstrated that these parameters can be used to identify meteorite-producing fireballs as well as to predict formation of impact craters for larger impactors (Gritsevich et al 2012;Turchak & Gritsevich 2014;Sansom et al 2019). On one hand, this allows for the new criterion to be used for meteoritedroppers (and not only to disintegrating fireballs); and on the other hand, it provides a reliable classification for the atmospheric behaviour of meter-sized projectiles.…”

“…The suitability to use the parameters α and β to classify meteoroid impacts was introduced by Gritsevich, Stulov & Turchak (2009, 2012 and was recently demonstrated on a large observational dataset by Sansom et al (2019). In particular, using this approach Sansom et al (2019) identify meteorite-producing fireballs illustrating their 'clustering' on the α-β plot. It was suggested in Moreno-Ibáñez, Gritsevich & Trigo-Rodríguez (2015, 2017, as a prospect for future research, that the mathematical combination of α and β could also lead to the revision of the PE criterion.…”

A Numerical Approach to Study Ablation of Large Bolides: Application to Chelyabinsk

“…We then apply our numerical model to the Chelyabinsk superbolide in order to study its dynamical behavior. For the sake of simplicity, our model considers a constant ablation coefficient and the shape factor, even though these parameters could vary in different ablation stages [33][34][35].…”