Inferring Fireball Velocity Profiles and Characteristic Parameters of Meteoroids From Incomplete Data Sets

Abstract Extracting additional information from old or incomplete fireball data sets remains a challenge. To address missing point‐by‐point observations, we introduce a method for estimating atmospheric flight parameters of meteoroids using metaheuristic optimization techniques. Using a fireball catalog from the European Fireball Network (EN), we reconstruct velocity profiles, meteoroid bulk densities, mass loss rates, and ablation and ballistic coefficients, based on the initial and terminal points' height, velocity, and mass with the purely dynamical ‐ model. Additionally, the method's performance is compared to the Meteorite Observation and Recovery Project (MORP) derived fits, confirming the robustness of the computed parameters for objects with asteroidal compositions. Our findings show that ‐ model yields parameters consistent with the photometric and dynamic mass estimates in the EN catalog for type I events. However, in the implementation proposed here, ‐ model encounters limitations in accurately representing the final deceleration of more fragile high‐velocity meteoroids. This is likely due to challenges in representing complex fragmentation processes by fitting only two points, even when initial and terminal residuals are minimal. The retrieved ‐ distribution differs from the one derived from MORP data, likely due to the imposed mass constraints, which strongly influence the results, especially the bulk density. The results suggest that constraints reduce fitting accuracy (from 90% to 44%), while flexibility and freedom from assumptions improve ‐ performance. The method yields 26% of the events compatible with the catalog classification. Our approach is well‐suited for interpreting historical or sparse data sets.

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Institutions

Publication Details

Journal
Journal of Geophysical Research Planets
Published
2025-05-01
DOI
https://doi.org/10.1029/2024je008382
Citations
2
Primary Topic
Astro and Planetary Science
Type
article
Field-Weighted Citation Impact
2.31

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article

Inferring Fireball Velocity Profiles and Characteristic Parameters of Meteoroids From Incomplete Data Sets

Maria Gritsevich, Eloy Peña‐Asensio
2 citations
Journal of Geophysical Research Planets
Astro and Planetary Science
2.31
article

Inferring Fireball Velocity Profiles and Characteristic Parameters of Meteoroids From Incomplete Data Sets

Maria Gritsevich, Eloy Peña‐Asensio
article en
2 citations

Abstract

Abstract Extracting additional information from old or incomplete fireball data sets remains a challenge. To address missing point‐by‐point observations, we introduce a method for estimating atmospheric flight parameters of meteoroids using metaheuristic optimization techniques. Using a fireball catalog from the European Fireball Network (EN), we reconstruct velocity profiles, meteoroid bulk densities, mass loss rates, and ablation and ballistic coefficients, based on the initial and terminal points' height, velocity, and mass with the purely dynamical ‐ model. Additionally, the method's performance is compared to the Meteorite Observation and Recovery Project (MORP) derived fits, confirming the robustness of the computed parameters for objects with asteroidal compositions. Our findings show that ‐ model yields parameters consistent with the photometric and dynamic mass estimates in the EN catalog for type I events. However, in the implementation proposed here, ‐ model encounters limitations in accurately representing the final deceleration of more fragile high‐velocity meteoroids. This is likely due to challenges in representing complex fragmentation processes by fitting only two points, even when initial and terminal residuals are minimal. The retrieved ‐ distribution differs from the one derived from MORP data, likely due to the imposed mass constraints, which strongly influence the results, especially the bulk density. The results suggest that constraints reduce fitting accuracy (from 90% to 44%), while flexibility and freedom from assumptions improve ‐ performance. The method yields 26% of the events compatible with the catalog classification. Our approach is well‐suited for interpreting historical or sparse data sets.

Journal of Geophysical Research PlanetsVol. 130(5)
Ural Federal University (RU), Swedish Institute of Space Physics (SE), University of Helsinki (FI), Institute of Physics and Technology (RU), Politecnico di Milano (IT)
Agenzia Spaziale Italiana
Openalex Percentile: Top 12%
Astro and Planetary Science
2.31
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