New method predicts extreme events more accurately: Columbia Engineers develop machine-learning algorithm to better understand and mitigate the impact of extreme weather events, which are becoming more frequent in our warming climate.

A new study has used global storm-resolving simulations and machine learning to create an algorithm that can deal separately with two different scales of cloud organization: those resolved by a climate model, and those that cannot be resolved as they are too small. This new approach addresses the missing piece of information in traditional climate model parameterizations and provides a way to predict precipitation intensity and variability more precisely.

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Maurice Ewing ,J Lamar Worzel ,Sarah Shamekh ,Earth Environmental Sciences ,Data Science Institute ,Columbia Engineering ,Pierre Gentine ,Artificial Intelligence ,Worzel Professor ,Environmental Engineering ,Data Science ,