Enhanced short-term prediction of first cloud-to-ground lightning strikes in convective season thunderstorms

Cloud-to-ground (CG) lightning strikes pose challenges for airports, their infrastructure, and their personnel. Critical infrastructure such as transmission systems or substations but also open-air events are affected by thunderstorms and lightning activity. While existing weather forecasting models can predict thunderstorms with a certain degree of temporal and spatial accuracy, short-term forecasts of the first CG lightning strike in a specific area remain imprecise. This issue is further complicated by the increasing trend toward remote tower operations and the absence of on-site meteorologists at airports, which makes operational decisions challenging. By combining data from an electric field meter network installed around Graz Airport, data from the Austrian Lightning Detection and Information System (ALDIS), and weather radar data from Austro Control GmbH (ACG), these challenges are addressed effectively. From this combined dataset, parameters were developed to predict the first CG lightning strike in the observed area. The analyzed dataset includes 45 thunderstorms from the convective thunderstorm seasons of 2022, 2023, and 2024, each producing at least one CG lightning strike within a 5 km radius of Graz Airport. Utilizing a method combining the derived parameters, effective alarms and warning times for CG lightning occurrence at Graz airport could be achieved, whereby a median shutdown lead time of 12.59 minutes was calculated for the first CG lightning strike within the 5 km radius. This enables successful short-term forecasting to support decision making for meteorologists and enhance personnel safety.