New Model May Predict Tornadoes Months or Seasons in Advance
A new model from the University of Toronto Scarborough may forecast tornado activity months or seasons in advance by predicting how atmospheric conditions during a thunderstorm will affect the risk of a tornado forming.
Vincent Cheng, lead developer of the model, studied similar variables used by weather forecasters to better understand the trends and probabilities of tornadoes, according to a report in Zee News. His research found that there's a much higher risk of a tornado taking place when air rises quickly and wind speed drastically changes at various heights above the ground.
Current tornado warnings have a 13-minute average lead time and a 70% false alarm rate, said Zee News, and this new method may provide insight to offer increased lead time and fewer false alarms in scenarios where every minute counts.
"The aim is to predict ahead to the following year or subsequent years about whether we'll get above or below average tornado activity in a given area," said Cheng.
Cheng's method also discusses the lack of accurate tornado recordings, which rely on eyewitness observations. His model bypasses that by showing the strong relationship between atmospheric variables and actual tornado occurrences in both populated regions, as well as more desolate areas where sightings aren't as frequent.
The model was explained in a research paper published in the journal Nature Communications.
