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Fraser King is studying what deep learning algorithms can teach us about snow, especially annual snowfall and snowmelt in the context of climate change. In his latest study, which he undertook with a team of researchers that included Christopher Fletcher, his PhD supervisor and Waterloo Climate Institute member, he put 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. 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,” King says.
“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.”
Learn more about how King is disseminating his research and check out the program which is available and open source on GitHub.
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