Little research has been done on hail since the 1990’s according to professor, meteorologist, and climate scientist John Allen. He’s trying to change that, with the help of a team of Central Michigan University students.
His research examines how and why big hail is produced. There is little field work involved in his work. He and his team use computers to track data and trends to determine what happens on days with small hail versus days with large hail.
“Hailstones are actually reported by the public to the National Severe Storms Laboratory; that is then cataloged. So we’re using that information together with profiles from various model data sets so really the problem with working with them is a big data problem more so than actually getting out there in the field and measuring it,” he said. “The whole idea is can we get better at this because we really haven’t had that much research done since the 1990’s.”
Allen said this can better help people prepare for storms.
“If you wanted to give people a heads up ‘hey we’re expecting to get hail exceeding three inches’, which is not an uncommon thing in the United States, we don’t really have a good idea of the days that happens. That has implications for things like mitigation,” he said. “If you’re expecting three inch hail you can actually think about things like ok I am going to put my car in the garage.”
Allen said people place more attention on destruction caused by tornadoes but hail, both big and small, is the most expensive natural hazard associated with severe storms. Small hail can damage crops while large hailstones can damage cars and buildings.
“Small hail while less relevant to say damaging your roof or your car might mean that a crop gets destroyed and when we start losing large amounts of crops that has implications for us as well,” he said.
Allen estimated that over a decade, approximately $10billion per year has been lost to hail.
The project began in 2019 and will conclude in 2022. Allen said his goal for this research is for weather services to someday apply it to their own predictions.
