With the help of Northeastern, Tennessee Valley Authority experiments with a new forecast model to better predict extreme rainfalls

In collaboration with a Northeastern researcher, the Tennessee Valley Authority this summer plans to test an AI-generated weather forecasting model to see if it will do a better job of predicting extreme rainfalls than traditional models.

With climate change creating more intense precipitation events and flash floods, “you need to have the information right away,” says Puja Das, a senior Ph.D. candidate in interdisciplinary engineering at Northeastern University’s Sustainability and Data Sciences Laboratory.

She says some existing models take four to six hours to generate forecasts, while others generate hourly predictions that aren’t all that accurate, providing wrong information about the intensity or location of the precipitation.

“Their performance is not up to the mark,” which doesn’t help warn the public about the potential for flash flooding such as a deluge in 2021 that killed 20 individuals in Waverly, Tennessee, Das says.

Her research project explores deep generative models that look at the past 90 minutes of high resolution radar data to generate new forecasts every 10 minutes within a three-hour period.

Das and other Northeastern researchers, including her collaborator August Posch at Northeastern’s Institute for Experiential AI, traveled to Knoxville, Tennessee last year to present the NASA-funded project, called RAIN for Remote-sensing data driven Artificial Intelligence for precipitation-Nowcasting at TVA headquarters.

---

Continue reading at Northeastern Global News.