Skip to main content
Astrophysical JournalVolume 885, Issue 2, 10 November 2019, Article number 115

Determining Fireball Fates Using the α-β Criterion(Article)(Open Access)

  • Sansom, E.K.,
  • Gritsevich, M.,
  • Devillepoix, H.A.R.,
  • Jansen-Sturgeon, T.,
  • Shober, P.,
  • Bland, P.A.,
  • Towner, M.C.,
  • Cupák, M.,
  • Howie, R.M.,
  • Hartig, B.A.D.
  Save all to author list
  • aSpace Science and Technology Centre, Curtin University, GPO Box U1987, Perth, WA 6845, Australia
  • bDepartment of Physics, Helsinki University, Finland
  • cFinnish Geospatial Research Institute (FGI), Masala, Finland
  • dInstitute of Physics and Technology, Ural Federal University, Ekaterinburg, Russian Federation

Abstract

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. © 2019. The American Astronomical Society. All rights reserved.

Funding details

Funding sponsor Funding number Acronym
Australian Research Council
See opportunities by ARC
DP170102529ARC
Academy of Finland325806AKA
  • ISSN: 0004637X
  • Source Type: Journal
  • Original language: English
  • DOI: 10.3847/1538-4357/ab4516
  • Document Type: Article
  • Publisher: Institute of Physics Publishing


© Copyright 2019 Elsevier B.V., All rights reserved.

Cited by 26 documents

Peña-Asensio, E. , Visuri, J. , Trigo-Rodríguez, J.M.
Oort cloud perturbations as a source of hyperbolic Earth impactors
(2024) Icarus
Kyrylenko, I. , Golubov, O. , Slyusarev, I.
The First Instrumentally Documented Fall of an Iron Meteorite: Orbit and Possible Origin
(2023) Astrophysical Journal
Coleman, A. , Eser, J. , Mayotte, E.
Ultra high energy cosmic rays The intersection of the Cosmic and Energy Frontiers
(2023) Astroparticle Physics
View details of all 26 citations
{"topic":{"name":"Meteoroids; Fireballs; Minor Planets","id":1923,"uri":"Topic/1923","prominencePercentile":86.71615,"prominencePercentileString":"86.716","overallScholarlyOutput":0},"dig":"f062404d98a1ff25eba8636a01701dc3a18bfd2f4c621f3c3c3e2f1612ca6300"}

SciVal Topic Prominence

Topic:
Prominence percentile: