Infrasound signals of fireballs detected by the Geostationary Lightning Mapper

Abstract

Context. Fireballs are particularly bright meteors produced by large meteoroids or small asteroids that enter the Earth’s atmosphere. These objects, of sizes from some tens of centimetres to a few metres, are difficult to record with typical meteor detection methods. Therefore, their characteristics and fluxes are still not well known. Infrasound signals can travel particularly well through the atmosphere over large distances. Impacting meteoroids and asteroids can produce those signals, as well as space-detectable optical signatures. Aims. This paper aims to study and compare fireball data from the Geostationary Lightning Mappers (GLMs) on board the two Geostationary Observational Environmental Satellites (GOES-16 and GOES-17) and the data from the infrasound stations of the International Monitoring System of the Comprehensive Nuclear-Test-Ban Treaty Organisation (Vienna, Austria). The overall goal is a more accurate energy estimation of meteoroids and asteroids as well as a better understanding of both methods. Methods. The data consist of the brightest 50 events in the GLM database, as identified by recorded peak energy. For 24 of those fireballs, a significant signature could be identified in infrasound data. The data are supplemented by, if available, optical fireball data based on US government sensors on satellites provided by NASA’s Center for Near-Earth Object Studies (CNEOS). Results. The energies as computed from the GLM data range from 3.17 × 107 J up to 1.32 × 1012 J with a mean of 1.65 × 1011 J. The smallest meteoroid recorded by infrasound had an energy of about 1.8 × 109 J, the largest one of about 9.6 × 1013 J, and the mean energy is 5.2 × 1012 J. For 19 events, data were simultaneously available from all three data sources. A comparison between the energy values for the same event as determined from the different data sources indicates that CNEOS tends to give the lowest energy estimations. Analysis of infrasound data results in the largest derived energies. Conclusions. The energies derived using the three methods often deviate from one another by as much as an order of magnitude. This indicates a potential observational bias and highlights uncertainties in fireball energy estimation. By determining the fireball energy with another independent method, this study can help to better quantify and address this range of uncertainty.

Exclusive Seismoacoustic Detection and Characterization of an Unseen and Unheard Fireball Over the North Atlantic

“…Ott et al. (2021) noted a similar discrepancy, and we speculate whether it relates to a physical difference in optical and acoustic energy release along the trajectory of meteoroids. Such systemic infrasound‐optical energy discrepancies should be taken into account by future studies on fireballs that utilize lightning mapper data.…”

“…Conversely, secondary arrivals at IS42 and SJ1 are modeled as stratospheric‐ducted rays with a surface reflection. Finally, the weak third infrasound arrival refracts at the base of the thermosphere (Figure 4b), where strong attenuation explains the low amplitude (Figure 2b) (Ott et al., 2021). Our raytracing model is not able to provide an explanation on the higher amplitude of the second arrival recorded at SJ1.…”

“…We can also use the luminous energy from the GLM-derived light curve (Figure S5 in Supporting Information S1) by converting luminous energy into visual magnitude and impact energy, accounting for the GLM passband and the altitude of the source. We follow the method described by Ott et al (2021), adapted from Jenniskens et al (2018). We estimate an energy of 1.35 × 10 −4 kT TNT equivalent.…”

Exclusive Seismoacoustic Detection and Characterization of an Unseen and Unheard Fireball Over the North Atlantic

“…Conversely, secondary arrivals at IS42 and SJ1 are modelled as stratospheric-ducted rays with a surface reflection. Finally, the weak third infrasound arrival reflects at the base of the thermosphere (Figure 4b), where strong attenuation explains the low amplitude (Figure 2b) (Ott et al, 2021).…”

“…We can also use the luminous energy from the GLM-derived light curve (Figure S5) by converting luminous energy into visual magnitude and impact energy, accounting for the GLM passband and the altitude of the source. We follow the method described by Ott et al (2021), adapted from Jenniskens et al (2018). We estimate an energy of 1.35x10 -4 kT TNT equivalent.…”