INFRASOUND AS A METHOD OF CHARACTERIZING ATMOSPHERIC OBJECTS

Low frequency acoustic waves or infrasound can be generated by natural and artificial objects entering the Earth’s atmosphere. The analysis of infrasound signals can help in the characterization of these objects which is important for improving the flux estimates and evaluating impact risk. Bolides can have a destructive potential, a notable example of which is the energetic event over Chelyabinsk in 2013. Recent cases of re-entering space debris and space junk landing on the surface further attest to the need to better characterize such events. However, though infrasound signals from some of these sources, bolides in particular, are generated relatively frequently, they are recorded less often and analyzed even less. In order to search for infrasound detections on infrasound stations, it is important to collect as much ground truth as possible. This is then used to estimate signal’s back-azimuth and arrival times. Currently, there is no singular source that provides the needed ground truth. Instead, the information is scattered across various databases, announcements and press releases. One of the first steps is data mining to find reliable sources with metadata and records of atmospheric events that may have produced the desired signals. Once data are gathered, events undergo quality control, and are then classified based on the event type, as well as the completeness and comprehensiveness of initial parameters of interest. The metadata are fed into software which outputs predicted infrasound back- azimuths and arrival times on global infrasound stations. Those outputs are then analyzed and used to evaluate the probability of generating detectable infrasound before the search for signals is conducted. This work aims to improve infrasound monitoring efforts and further our understanding of atmospheric entry.

SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.