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Decameter-sized Earth Impactors -- II: A Bayesian Inference Approach to Meteoroid Ablation Modeling

Ian Chow, Peter G. Brown

TL;DR

The paper introduces a Bayesian inference framework using dynamic nested sampling to recover meteoroid physical properties from USG fireball light curves, validated against seven ground-truth events. It then applies the method to 13 decameter-size impactors, uncovering three structural classes (weak homogeneous, heterogeneous, strong aggregates) and revealing a two-stage fragmentation process with distinct pressure regimes. Key findings show general agreement with prior entry analyses for main fragmentation dynamics, while highlighting potential overestimation of peak dynamic pressure due to trailing emission, and providing population-level insights into strength scaling and source regions. The methodology offers a robust, uncertainty-quantified tool for characterizing meteoroid material strength and fragmentation behavior, with direct implications for planetary defense modeling and future analyses of large fireballs.

Abstract

Small asteroids and large meteoroids frequently impact the Earth, though their physical and material properties remain poorly understood. When observed as fireballs in Earth's atmosphere, these properties can be inferred from their ablation and fragmentation behavior. The 2022 release of previously classified United States Government (USG) satellite sensor data has provided hundreds of new fireball light curves, allowing for more detailed analysis. Here we present a new Bayesian inference method based on dynamic nested sampling that can robustly estimate these objects' physical parameters from their observed light curves, starting from relatively uninformative, flat priors. We validate our method against seven USG sensor-observed fireballs with independent ground-based observations and demonstrate that our results are consistent with previous estimates. We then apply our technique to $13$ decameter-size Earth impactors to conduct the most detailed population-level study of their structure and material strength to date. We identify three structurally distinct groups within the decameter impactors. The first group are primarily structurally homogeneous, weak objects which catastrophically disrupt below $\sim1.5$ MPa. The second group are heterogeneous objects which progressively fragment starting from $\sim1$ MPa typically up to $\sim3-8$ MPa. The third group are strong aggregates which remain mostly intact until $9-10$ MPa. Our results also suggest that decameter-size asteroids fragment in two distinct phases: an initial phase at $\sim0.04-0.09$ MPa and a second at $\sim1-4$ MPa. While decimeter- to meter-size objects typically lose most of their mass in the initial phase, larger decameter-size objects instead lose most of their mass in the second phase.

Decameter-sized Earth Impactors -- II: A Bayesian Inference Approach to Meteoroid Ablation Modeling

TL;DR

The paper introduces a Bayesian inference framework using dynamic nested sampling to recover meteoroid physical properties from USG fireball light curves, validated against seven ground-truth events. It then applies the method to 13 decameter-size impactors, uncovering three structural classes (weak homogeneous, heterogeneous, strong aggregates) and revealing a two-stage fragmentation process with distinct pressure regimes. Key findings show general agreement with prior entry analyses for main fragmentation dynamics, while highlighting potential overestimation of peak dynamic pressure due to trailing emission, and providing population-level insights into strength scaling and source regions. The methodology offers a robust, uncertainty-quantified tool for characterizing meteoroid material strength and fragmentation behavior, with direct implications for planetary defense modeling and future analyses of large fireballs.

Abstract

Small asteroids and large meteoroids frequently impact the Earth, though their physical and material properties remain poorly understood. When observed as fireballs in Earth's atmosphere, these properties can be inferred from their ablation and fragmentation behavior. The 2022 release of previously classified United States Government (USG) satellite sensor data has provided hundreds of new fireball light curves, allowing for more detailed analysis. Here we present a new Bayesian inference method based on dynamic nested sampling that can robustly estimate these objects' physical parameters from their observed light curves, starting from relatively uninformative, flat priors. We validate our method against seven USG sensor-observed fireballs with independent ground-based observations and demonstrate that our results are consistent with previous estimates. We then apply our technique to decameter-size Earth impactors to conduct the most detailed population-level study of their structure and material strength to date. We identify three structurally distinct groups within the decameter impactors. The first group are primarily structurally homogeneous, weak objects which catastrophically disrupt below MPa. The second group are heterogeneous objects which progressively fragment starting from MPa typically up to MPa. The third group are strong aggregates which remain mostly intact until MPa. Our results also suggest that decameter-size asteroids fragment in two distinct phases: an initial phase at MPa and a second at MPa. While decimeter- to meter-size objects typically lose most of their mass in the initial phase, larger decameter-size objects instead lose most of their mass in the second phase.
Paper Structure (21 sections, 4 equations, 12 figures, 4 tables)

This paper contains 21 sections, 4 equations, 12 figures, 4 tables.

Figures (12)

  • Figure 1: a): The model light curve of intensity versus height plotted over the USG sensor-recorded fireball light curve (red dots) for the 18 January 2000 Tagish Lake meteorite-producing fireball. Here the black shaded regions illustrate the $1\sigma$, $2\sigma$ and $3\sigma$ distributions for the light curve solutions derived from nested sampling. The maximum log-likelihood solution obtained by nested sampling is plotted as the blue line. The intensity is given in units of absolute stellar magnitudes assuming a bolometric power of $3030$ W at zero magnitude. The detection limit of USG sensors at absolute magnitude $-16.5$ is marked by the vertical red line. b): The marginal $2$D posterior distributions of dynamic pressure against mass released for each fragmentation point (colors) identified from the USG light curve and mass remaining at peak dynamic pressure (black). Contours show the $1\sigma$, $2\sigma$ and $3\sigma$ bounds of the posterior distributions. Also marked on the plot are the dynamic pressure vs. mass released at the main fragmentation point (yellow dot) and at peak dynamic pressure (red dot) previously estimated by brown_entry_2002.
  • Figure 2: a): The observed light curve and corresponding model fit for the 6 May 2000 Morávka fireball, similar to Figure \ref{['fig:tagish_lake_lc']}a). Evidence of extended luminosity possibly produced by dust left behind by the bolide after its final fragmentation is visible as an inflection in the light curve at $\sim31$ km. b): Comparison of the posterior distributions for dynamic pressure against mass released at the main fragmentation and mass remaining at peak dynamic pressure to previous estimates by borovicka_moravka_2003, similar to Figure \ref{['fig:tagish_lake_lc']}b).
  • Figure 3: a): The observed light curve and corresponding model fit for the 27 March 2003 Park Forest fireball, similar to Figure \ref{['fig:tagish_lake_lc']}a). b): Comparison of the posterior distributions for dynamic pressure against mass released at the main fragmentation and mass remaining at peak dynamic pressure to previous estimates by brown_orbit_2004, similar to Figure \ref{['fig:tagish_lake_lc']}b).
  • Figure 4: a): The observed light curve and corresponding model fit for the 28 February 2010 Košice fireball, similar to Figure \ref{['fig:tagish_lake_lc']}a). b): Comparison of the posterior distributions for dynamic pressure against mass released at the main fragmentation and mass remaining at peak dynamic pressure to previous estimates by borovicka_kosice_2013, similar to Figure \ref{['fig:tagish_lake_lc']}b).
  • Figure 5: a): The observed light curve and corresponding model fit for the 7 January 2015 Romanian superbolide, similar to Figure \ref{['fig:tagish_lake_lc']}a). Similar to Figure \ref{['fig:moravka_lc']}a), extended luminosity appears as an inflection in the light curve at $\sim35$ km. b): Comparison of the posterior distributions for dynamic pressure against mass released at main fragmentation and mass remaining at peak dynamic pressure to previous estimates by borovicka_january_2017, similar to Figure \ref{['fig:tagish_lake_lc']}b).
  • ...and 7 more figures