Climate change is known to impact extreme precipitation events, but understanding how this precipitation will change at local scales that cause flooding is a challenge. Stanford researchers explain a machine learning model they developed that uses atmospheric patterns to predict extreme precipitation which may lead to flooding. This tool can be used in the short term for predicting when disaster may strike and in the long term for building infrastructure that is resilient to climate change. Read more at woods.stanford.edu/news/stanford-researchers-use-artificial-intelligence-unlock-extreme-weather-mysteries
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Original research agupubs.onlinelibrary.wiley.com/doi/10.1029/2021GL093787
Noah Diffenbaugh, Kara J Foundation Professor, Stanford Earth profiles.stanford.edu/noah-diffenbaugh
Frances Davenport, Ph.D. student, Stanford Department of Earth Systems Science profiles.stanford.edu/frances-davenport
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