Facial recognition could help identify hailstorms. By using the same technology, scientists can now predict the size and severity of hail.
According to a new study conducted by National Center for Atmospheric Research (NCAR), the same technology used in facial recognition could also be used to help scientists improve their prediction of hailstorms.
Researchers have recently identified a method of recognising storm indicators that affect the formation and size of hailstones. The method is based around facial recognition technology. Instead of focusing on facial features, scientists have trained a deep learning model, called a convolutional neural network, in order to recognise features of individual storms.
NCAR scientist David John Gagne, led the research team. Gagne said:”We know that the structure of a storm affects whether the storm can produce hail…A supercell is more likely to produce hail than a squall line, for example. But most hail forecasting methods just look at a small slice of the storm and can’t distinguish the broader form and structure”
This research was supported by the National Science Foundation (NSF).
Nick Anderson, NSF program officer, said:”Hail – particularly large hail – can have significant economic impacts on agriculture and property…Using these deep learning tools in unique ways will provide additional insight into the conditions that favor large hail, improving model predictions. This is a creative, and very useful, merger of scientific disciplines.”
Gagne continued:”The shape of the storm is really important…In the past we have tended to focus on single points in a storm or vertical profiles, but the horizontal structure is also really important.”
“I think this new method has a lot of promise to help forecasters better predict a weather phenomenon capable of causing severe damage…We are excited to continue testing and refining the model with observations of real storms.”
This research is an important gateway to understanding storm behaviour. Given the current environmental climate, understanding extreme weather is more important than ever.