Researchers from EPFL’s School of Engineering and Electromagnetic Compatibility Laboratory have created an artificial intelligence (AI) system that can predict lightning strikes. The system can predict lightning strikes within a 30 km (18.64 mile) radius to the nearest 10 to 30 minutes.

The system uses a combination of standard meteorological data and artificial intelligence to make its predictions.

Current systems are slow and complex, and require expensive external data from a radar or satellite. The new method uses data from weather stations. This allows the system to cover remote areas that are out of the range of radars and satellites. Data for the system is acquired easily and in real-time, which enables the system to send out weather alerts before lightning strikes.

The machine-learning algorithm was trained to recognize conditions that lead to lightning. To train the AI, researchers collected data from 12 Swiss weather stations from urban and mountainous environments for 10 years.

The algorithm took four parameters into consideration when making a prediction: atmospheric pressure, air temperature, relative humidity and wind speed. These parameters correlated with recordings from lightning detection and location systems. During training, the system learned the conditions through which lightning occurs.

The team tested its system and found success. After training, the system made correct predictions 80% of the time. This was the first time a system based on simple meteorological data has been used to predict lightning strikes with real-time calculations.

A paper on the technology was published in Climate and Atmosphere Science.