Observations and modeling insights from a massive collection of lightning-induced ionospheric disturbances

The stochastic behavior of lightning, combined with our largely indirect measurements of the ionosphere, makes it difficult to analyze interactions between lightning strokes and the ionosphere at a statistically large scale. We attempt to address this by developing a classifier to detect lightning-generated ionospheric disturbances automatically from VLF signal measurements. Our efforts have resulted in a large database of ionospheric disturbances in two categories: early VLF events (direct heating), and lightning-induced electron precipitation events (which remove trapped radiation belt electrons). With this database we can observe patterns in event behavior with a greater precision than previous studies. These include confirming asymmetry of event occurrence between positive and negative polarity strokes, along with insights into the geometry of event occurrence and observability. We present recent efforts to leverage this database to better quantity the relationship between lightning and ionosphere and the radiation belts. Previous models, such as the WIPP ray-tracing algorithm, have been able to accurately characterize the process behind lightning-induced ionospheric disturbances, when applied to individual case studies. We apply these models over our full database and seek to best fit the physical parameters to our observations, with the goal of developing stronger insight towards the physics of the ionosphere and near-Earth space environment.