Despite that old saying, lightning can—and often does—strike the same area twice. It’s detrimental to farmers as lightning causes fires that can destroy millions of dollars’ worth of crops. And, it kills more people each year than tornadoes or hurricanes.
But right now, our only real warning system is storm clouds.
Simply put: we have difficulty predicting exactly when these giant electrical charges will strike. In Switzerland, a team of researchers from École Polytechnique Fédérale de Lausanne may have an answer: artificial intelligence.
Using standard meteorological data and machine learning, the scientists came up with a relatively simple and cheap system that can predict lightning strikes down to the nearest 10 to 30 minutes inside a 30-kilometer radius (about 18.6 miles).
“We have used machine learning techniques to successfully hindcast nearby and distant lightning hazards by looking at single-site observations of meteorological parameters,” the authors wrote in a new paper published earlier this month in the journal Climate and Atmospheric Science.
Hindcasting, as opposed to forecasting, is a way to test mathematical models. Known or estimated inputs of past events are used in a model to see how well that output matches known results. If the model’s output matches the known output, it’s correct. In this case, the researchers were able to use data about past lightning strikes to build an algorithm that could then make predictions about new lightning strikes.