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Register a new userIdentification of a Minimoon Fireball
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Objects gravitationally captured by the Earth-Moon system are commonly called temporarily captured orbiters (TCOs), natural Earth satellites, or minimoons. TCOs are a crucially important subpopulation of near-Earth objects (NEOs) to understand because they are the easiest targets for future sample-return, redirection, or asteroid mining missions. Only one TCO has ever been observed telescopically, 2006 RH 120, and it orbited Earth for about 11 months. Additionally, only one TCO fireball has ever been observed prior to this study. We present our observations of an extremely slow fireball (codename DN160822_03) with an initial velocity of around 11.0 km s-1 that was detected by six of the high-resolution digital fireball observatories located in the South Australian region of the Desert Fireball Network. Due to the inherent dynamics of the system, the probability of the meteoroid being temporarily captured before impact is extremely sensitive to its initial velocity. We examine the sensitivity of the fireballs orbital history to the chosen triangulation method. We use the numerical integrator REBOUND to assess particle histories and assess the statistical origin of DN160822_03. From our integrations we have found that the most probable capture time, velocity, semimajor axis, NEO group, and capture mechanism vary annually for this event. Most particles show that there is an increased capture probability during Earths aphelion and perihelion. In the future, events like these may be detected ahead of time using telescopes like the Large Synoptic Survey Telescope, and the pre-atmospheric trajectory can be verified.
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The worlds meteorite collections contain a very rich picture of what the early Solar System would have been made of, however the lack of spatial context with respect to their parent population for these samples is an issue. The asteroid population is equally as rich in surface mineralogies, and mapping these two populations (meteorites and asteroids) together is a major challenge for planetary science. Directly probing asteroids achieves this at a high cost. Observing meteorite falls and calculating their pre-atmospheric orbit on the other hand, is a cheaper way to approach the problem. The Global Fireball Observatory (GFO) collaboration was established in 2017 and brings together multiple institutions (from Australia, USA, Canada, Morocco, Saudi Arabia, the UK, and Argentina) to maximise the area for fireball observation time and therefore meteorite recoveries. The members have a choice to operate independently, but they can also choose to work in a fully collaborative manner with other GFO partners. This efficient approach leverages the experience gained from the Desert Fireball Network (DFN) pathfinder project in Australia. The state-of-the art technology (DFN camera systems and data reduction) and experience of the support teams is shared between all partners, freeing up time for science investigations and meteorite searching. With all networks combined together, the GFO collaboration already covers 0.6% of the Earths surface for meteorite recovery as of mid-2019, and aims to reach 2% in the early 2020s. We estimate that after 5 years of operation, the GFO will have observed a fireball from virtually every meteorite type. This combined effort will bring new, fresh, extra-terrestrial material to the labs, yielding new insights about the formation of the Solar System.
We report on our detailed characterization of Earths second known temporary natural satellite, or minimoon, asteroid 2020 CD3. An artificial origin can be ruled out based on its area-to-mass ratio and broadband photometry, which suggest that it is a silicate asteroid belonging to the S or V complex in asteroid taxonomy. The discovery of 2020 CD3 allows for the first time a comparison between known minimoons and theoretical models of their expected physical and dynamical properties. The estimated diameter of 1.2+0.4-0.2 m and geocentric capture approximately a decade after the first known minimoon, 2006 RH120, are in agreement with theoretical predictions. The capture duration of 2020 CD3 of at least 2.7 yr is unexpectedly long compared to the simulation average, but it is in agreement with simulated minimoons that have close lunar encounters, providing additional support for the orbital models. 2020 CD3s atypical rotation period, significantly longer than theoretical predictions, suggests that our understanding of meter-scale asteroids needs revision. More discoveries and a detailed characterization of the population can be expected with the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time.
On May 30th, 2017 at about 21h 09m 17s UTC a green bright fireball crossed the sky of north-eastern Italy. The fireball path was observed from some all-sky cameras starting from a mean altitude of $81.1 pm 0.2$ km (Lat. $44.369^{circ} pm 0.002^{circ}$ N; Long. $11.859^{circ} pm 0.002^{circ}$ E) and extinct at $23.3 pm 0.2$ km (Lat. $45.246^{circ} pm 0.002^{circ}$ N; Long. $12.046^{circ} pm 0.002^{circ}$ E), between the Italian cities of Venice and Padua. In this paper, on the basis of simple physical models, we will compute the atmospheric trajectory, analize the meteoroid atmospheric dynamics, the dark flight phase (with the strewn field) and compute the best heliocentric orbit of the progenitor body. Search for meteorites on the ground has not produced any results so far.
Despite ablation and drag processes associated with atmospheric entry of meteoroids were a subject of intensive study over the last century, little attention was devoted to interpret the observed fireball terminal height. This is a key parameter because it not only depends on the initial mass, but also on the bulk physical properties of the meteoroids and hence of their ability to ablate in the atmosphere. In this work we have developed a new approach that is tested using the fireball terminal heights observed by the Meteorite Observation and Recovery Project operated in Canada between 1970-1985 (hereafter referred as MORP). We then compare them to the calculation made. Our results clearly show that the new methodology is able to forecast the degree of deepening of meteoroids in the Earths atmosphere. Then, this approach has important applications in predicting the impact hazard from cm- to meter-sized bodies that are represented, in part, in the MORP bolide list.
Meteorites with known orbital origins are key to our understanding of Solar System formation and the source of life on Earth. However, these pristine samples of space material are incredibly rare. Less than 40 of the 60,000 meteorites held in collections around the world have known dynamical origins. Fireball networks have been developed globally in a unified effort to increase this number by using multiple observatories to record, triangulate, and dynamically analyse ablating meteoroids as they enter our atmosphere. The accuracy of the chosen meteoroid triangulation method directly influences the accuracy of the determined orbit and the likelihood of possible meteorite recovery. There are three leading techniques for meteoroid triangulation discussed in the literature: the Method of Planes, the Straight Line Least Squares method, and the Multi-Parameter Fit method. Here we describe an alternative method to meteoroid triangulation, called the Dynamic Trajectory Fit. This approach uses the meteoroids 3D dynamic equations of motion to fit a realistic trajectory directly to multi-sensor line-of-sight observations. This method has the ability to resolve fragmentation events, fit systematic observatory timing offsets, and determine mass estimates of the meteoroid along its observable trajectory. Through a comprehensive Monte-Carlo analysis of over 100,000 trajectory simulations, we find this new method to more accurately estimate meteoroid trajectories of slow entry events ($<$25,km/s) and events observed from low convergence angles ($<$10$^{circ}$) compared to existing meteoroid triangulation techniques. Additionally, we triangulate an observed fireball event with visible fragmentation using the various triangulation methods to show that the proposed Dynamic Trajectory Fit implementing fragmentation to best match the captured multi-sensor line-of-sight data.
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