Written by Jon Parsons. This is an excerpt from an article originally published on Waterloo News.
PhD student Fraser King brings computer science to study of precipitation
But a PhD student in the Department of Geography and Environmental Management (GEM) at the University of Waterloo is taking the Canadian obsession with weather to a whole new level.
Fraser King is studying the ways machine learning can be applied to predicting patterns of precipitation, and especially annual snowfall and snowmelt in the context of climate change.
In his latest study, which he undertook with a team of researchers including his PhD supervisor Professor Christopher Fletcher, he puts forward his new weather modelling program under the name DeepPrecip.
“In this new research we’ve been working to develop a model, which is a deep learning computational network,” King says. “It’s difficult to accurately measure snow. There have been other models but they have some limitations. Our new model is helping to move things forward.”
DeepPrecip takes the mountains of data that exist from radar readings of snowfall and then builds predictive models. Such research is extremely valuable in an era of climate change.
"I feel like we have a responsibility as Canadians to make sure we’re taking care of the land and monitoring it, because it’s going to have global impacts as the climate continues to warm,"
- Fraser King, PhD Candidate
“One of the big questions in atmospheric sciences is understanding changes in snowfall. It’s quite a dynamic process and it’s not one that’s well understood. Any progress we can make in this area is beneficial.”