Regional Lightning Strike Prediction Using Ubiquitous and Mobile Electric Field Meter System

Lightning strikes can cause serious damage to property and can be fatal. To mitigate these risks, many efforts have been made to develop lightning strike alert mechanisms. Designing a reliable lightning strike alarm system requires studying specific factors such as the local area and time of year to determine the appropriate alert parameters. This paper proposes a methodology using ubiquitous, wide-area, and mobile Electric Field Meters (EFM) to study all covered local areas, build high-performance predictors, and apply them on demand. The methodology can be applied globally, provided there is a network of low-cost IoT mobile devices capable of measuring the atmospheric electric field. As part of a more comprehensive system, this paper introduces Thor2022, which utilizes this methodology to generate lightning alarms in designated areas of concern. Using a “nine area” approach and the trilateration concept, massive simulations demonstrate that a Predictive System (PS) based on simple test conditions can achieve a Probability of Detection (POD) greater than ${9 0 \%}$ and a False Alarm Rate (FAR) less than $10 \%$.