Tech

Massive Hailstone Collection Unlocks Secrets of Storm Behavior

Weighing a Hailstone
A hailstone, flecked with black paint to assist in 3D scanning, is weighed as part of processing for the library. Credit: The University of Queensland

University of Queensland researchers are enhancing storm predictions by creating a ‘hailstone library’ with real hailstones, revealing significant variations in storm behavior and aiming to improve safety and industry resilience.

A global library, filled with hailstones rather than books, is aiding researchers in improving their understanding and prediction of damaging storms.

Dr. Joshua Soderholm, an Honorary Senior Research Fellow from UQ’s School of the Environment, and lead researcher PhD candidate Yuzhu Lin from Penn State in the US, have found storm modeling outcomes change significantly when using real hailstones.

Key points:

  • Researchers are measuring and scanning samples for a global ‘hailstone library’
  • Storm simulations using 3D modeling of real hailstones show they behave differently than spherical hail shapes
  • Data from the hail library could lead to more accurate storm forecasts

“People tend to think of a hailstone as a perfect sphere, like a golf ball or cricket ball,” Dr. Soderholm said.

“But hail can be all sorts of weird shapes, from oblong to a flat disc or have spikes coming out – no two pieces of hail are the same. Conventional scientific modeling of hail assumes spherical hailstones, and we wanted to know if that changed when non-spherical, natural hail shapes are used.”

Dramatic Findings in Hail Simulation

Ms. Lin said they found the differences were dramatic.

“Modelling of the more naturally shaped hail showed it took different pathways through the storm, experienced different growth, and landed in different places,” Ms. Lin said.

“It also affected the speed and impact the hail had on the ground. This way of modeling had never been done before, so it’s exciting science.”

Dr. Soderholm said building a ‘hailstone library’ was critical to further fine-tuning hailstorm simulations.

“This is effectively a dataset to represent the many and varied shapes of hailstones, to make weather modeling more accurate,” he said.

“Our study used data from 217 hail samples, which were 3D scanned and then sliced in half, to tell us more about how the hailstone formed. This data is now part of a global library, as we try and get a really clear picture of hailstone shape and structure.”

Dr. Soderholm said the research has significant potential.

“At the moment, the modeling is specifically for scientists studying storms, but the end game is to be able to predict in real-time how big hail will be, and where it will fall,” he said.

“More accurate forecasts would of course warn the public so they can stay safe during hailstorms and mitigate damage. But it could also significantly benefit industries such as insurance, agriculture, and solar farming which are all sensitive to hail.”

Reference: “Modeling non-spherical hailstones” by Yuzhu Lin, Matthew R. Kumjian, Joshua Soderholm and Ian Giammanco, 31 July 2024, Journal of the Atmospheric Sciences.
DOI: 10.1175/JAS-D-23-0231.1

Some hail samples for the UQ data set were provided by Higgins Storm Chasing.

Funding: NSF Grant AGS, Insurance Institute for Business and Home Safety


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