The Geostationary Lightning Mapper (GLM) instrument onboard the GOES 16 and 17 satellites can be used to detect bolides in the atmosphere. This capacity is unique because GLM provides semi-global, continuous coverage and releases its measurements publicly. Here, six filters are developed that are aggregated into an automatic algorithm to extract bolide signatures from the GLM level 2 data product. The filters exploit unique bolide characteristics to distinguish bolide signatures from lightning and other noise. Typical lightning and bolide signatures are introduced and the filter functions are presented. The filter performance is assessed on 144845 GLM L2 files (equivalent to 34 days-worth of data) and the algorithm selected 2252 filtered files (corresponding to a pass rate of 1.44%) with bolide-similar signatures. The challenge of identifying frequent but small, decimeter-sized bolide signatures is discussed as GLM reaches its resolution limit for these meteors. The effectiveness of the algorithm is demonstrated by its ability to extract confirmed and new bolide discoveries. We provide discovery numbers for November 2018 when seven likely bolides were discovered of which four are confirmed by secondary observations. The Cuban meteor on Feb 1st 2019 serves as an additional example to demonstrate the algorithms capability and the first light curve as well as correct ground track was available within 8.5 hours based on GLM data for this event. The combination of the automatic bolide extraction algorithm with GLM can provide a wealth of new measurements of bolides in Earth’s atmosphere to enhance the study of asteroids and meteors.

A set of 50,000 artificial Earth impacting asteroids was used to obtain, for the first time, information about the dominance of individual impact effects such as wind blast, overpressure shock, thermal radiation, cratering, seismic shaking, ejecta deposition, and tsunami for the loss of human life during an impact event for impactor sizes between 15 and 400 m and how the dominance of impact effects changes over size. Information about the dominance of each impact effect can enable disaster managers to plan for the most relevant effects in the event of an asteroid impact. Furthermore, the analysis of average casualty numbers per impactor shows that there is a significant difference in expected loss for airburst and surface impacts and that the average impact over land is an order of magnitude more dangerous than one over water.

Asteroids that could collide with the Earth are listed on the publicly available Near-Earth object (NEO) hazard web sites maintained by the US and European space agencies (NASA and ESA). The impact probability distribution of 69 potentially threatening NEOs from these lists that produce 261 dynamically distinct impact instances, or Virtual Impactors (VIs), were calculated using the Asteroid Risk Mitigation and Optimization Research (ARMOR) tool in conjunction with OrbFit. ARMOR projected the impact probability of each VI onto the surface of the Earth as a spatial probability distribution. The projection considers orbit solution accuracy and the global impact probability. The method of ARMOR is introduced and the tool is validated against two asteroid-Earth collision cases with objects 2008 TC3 and 2014 AA. In the analysis, the natural distribution of impact corridors is contrasted against the impact probability distribution to evaluate the distributions conformity with the uniform impact distribution assumption. The distribution of impact corridors is based on the NEO population and orbital mechanics. The analysis shows that the distribution of impact corridors matches the common assumption of uniform impact distribution and the result extends the evidence base for the uniform assumption from qualitative analysis of historic impact events into the future in a quantitative way. This finding is confirmed in a parallel analysis of impact points belonging to a synthetic population of 10006 VIs. Taking into account the impact probabilities introduced significant variation into the results and the impact probability distribution, consequently, deviates markedly from uniformity. The concept of impact probabilities is a product of the asteroid observation and orbit determination technique and, thus, represents a man-made component that is largely disconnected from natural processes.Comment: Published in Icarus, 9 pages, 8 figure

An asteroid impact is a low probability event with potentially devastating consequences. The Asteroid Risk Mitigation Optimization and Research (ARMOR) software tool calculates whether a colliding asteroid experiences an airburst or surface impact and calculates effect severity as well as reach on the global map. To calculate the consequences of an impact in terms of loss of human life, new vulnerability models are derived that connect the severity of seven impact effects (strong winds, overpressure shockwave, thermal radiation, seismic shaking, ejecta deposition, cratering, and tsunamis) with lethality to human populations. With the new vulnerability models, ARMOR estimates casualties of an impact under consideration of the local population and geography. The presented algorithms and models are employed in two case studies to estimate total casualties as well as the damage contribution of each impact effect. The case studies highlight that aerothermal effects are most harmful except for deep water impacts, where tsunamis are the dominant hazard. Continental shelves serve a protective function against the tsunami hazard caused by impactors on the shelf. Furthermore, the calculation of impact consequences facilitates asteroid risk estimation to better characterize a given threat, and the concept of risk as well as its applicability to the asteroid impact scenario are presented.

No abstract