Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events

Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events

Abstract The parameterization of moist convection contributes to uncertainty in climate modeling and numerical weather prediction. Machine learning (ML) can be used to learn new parameterizations directly from high‐resolution model output, but it remains poorly understood how such parameterizations...

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Bibliographic Details
Main Authors: Paul A. O'Gorman, John G. Dwyer
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2018-10-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
subgrid modeling
machine learning
moist convection
climate change
extreme events
parameterization
Online Access:https://doi.org/10.1029/2018MS001351

Internet

https://doi.org/10.1029/2018MS001351

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