Accurate 3D fireball trajectory and orbit calculation using the 3D-firetoc automatic Python code

The disruption of asteroids and comets produces cm-sized meteoroids that end up impacting the Earth's atmosphere and producing bright fireballs that might have associated shock waves or, in geometrically favourable occasions excavate craters that put them into unexpected hazardous scenarios. The astrometric reduction of meteors and fireballs to infer their atmospheric trajectories and heliocentric orbits involves a complex and tedious process that generally requires many manual tasks. To streamline the process, we present a software package called SPMN 3D Fireball Trajectory and Orbit Calculator (3D-firetoc), an automatic Python code for detection, trajectory reconstruction of meteors, and heliocentric orbit computation from video recordings. The automatic 3D-firetoc package comprises of a user interface and a graphic engine that generates a realistic 3D representation model, which allows users to easily check the geometric consistency of the results and facilitates scientific content production for dissemination. The software automatically detects meteors from digital systems, completes the astrometric measurements, performs photometry, computes the meteor atmospheric trajectory, calculates the velocity curve, and obtains the radiant and the heliocentric orbit, all in all quantifying the error measurements in each step. The software applies corrections such as light aberration, refraction, zenith attraction, diurnal aberration, and atmospheric extinction. It also characterizes the atmospheric flight and consequently determines fireball fates by using the α - β criterion that analyses the ability of a fireball to penetrate deep into the atmosphere and produce meteorites. We demonstrate the performance of the software by analysing two bright fireballs recorded by the Spanish Fireball and Meteorite Network (SPMN).JMT-R, EPA, and AR acknowledge financial support from the Spanish Ministry (PGC2018-097374-B-I00 funded by MCI-AEI-FEDER, PI: JMT-R; CTQ2017-89132-P, PI: AR). MG acknowledges support from the Academy of Finland project no. 325806, and the Russian Foundation for Basic Research, project nos. 18-08-00074 and 19-05-00028. AR is indebted to the ‘Ramón y Cajal’ program and DIUE (project 2017SGR1323). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 865657) for the project ‘Quantum Chemistry on Interstellar Grains’ (QUANTUMGRAIN)