GOES GLM, Biased Bolides, and Debiased Distributions

Abstract

The large combined field of view of the Geostationary Lightning Mapper (GLM) instruments onboard the GOES weather satellites makes them useful for studying the population of other atmospheric phenomena, such as bolides. Being a lightning mapper, GLM has many detection biases when applied to non-lightning and these systematics must be studied and properly accounted for before precise measurements of bolide flux can be ascertained. We developed a Bayesian Poisson regression model which simultaneously estimates instrumental biases and our statistic of principal interest: the latitudinal variation of bolide flux. We find that the estimated bias due to the angle of incident light upon the instrument corresponds roughly with the known sensitivity of the GLM instruments. We compare our latitudinal flux variation estimates to existing theoretical models and find our estimates consistent with GLM being strongly biased towards high-velocity bolides.

To be published in Icarus vol. 408, 2024

References in corpus (6)

• Sparsity information and regularization in the horseshoe and other shrinkage priors
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• NEOMOD: A New Orbital Distribution Model for Near Earth Objects
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Cited by in corpus (3)

• Bolide infrasound signal morphology and yield estimates: A case study of two events detected by a dense acoustic sensor network
• BLADE: An Automated Framework for Classifying Light Curves from the Center for Near-Earth Object Studies (CNEOS) Fireball Database
• Comparing Monte Carlo Models of Impact Alteration of Planetary Atmospheres