Determining Fireball Fates Using the α–β Criterion

As fireball networks grow, the number of events observed becomes unfeasible to manage by manual efforts. Reducing and analyzing big data requires automated data pipelines. Triangulation of a fireball trajectory can swiftly provide information on positions and, with timing information, velocities. Ho...

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Veröffentlicht in:The Astrophysical journal 2019-11, Vol.885 (2), p.115
Hauptverfasser: Sansom, Eleanor K., Gritsevich, Maria, Devillepoix, Hadrien A. R., Jansen-Sturgeon, Trent, Shober, Patrick, Bland, Phil A., Towner, Martin C., Cupák, Martin, Howie, Robert M., Hartig, Benjamin A. D.
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container_issue 2
container_start_page 115
container_title The Astrophysical journal
container_volume 885
creator Sansom, Eleanor K.
Gritsevich, Maria
Devillepoix, Hadrien A. R.
Jansen-Sturgeon, Trent
Shober, Patrick
Bland, Phil A.
Towner, Martin C.
Cupák, Martin
Howie, Robert M.
Hartig, Benjamin A. D.
description As fireball networks grow, the number of events observed becomes unfeasible to manage by manual efforts. Reducing and analyzing 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 visualization in an α – β diagram can quickly identify which fireballs are likely meteorite candidates.
doi_str_mv 10.3847/1538-4357/ab4516
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subjects Astrophysics
Bulk density
Coefficients
Deceleration
Empirical analysis
Fireballs
Mathematical analysis
Meteoroids
Meteors & meteorites
Parameters
Trajectory analysis
Triangulation
title Determining Fireball Fates Using the α–β Criterion
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