Neural‐Network Parameterization of Subgrid Momentum Transport in the Atmosphere

Abstract Attempts to use machine learning to develop atmospheric parameterizations have mainly focused on subgrid effects on temperature and moisture, but subgrid momentum transport is also important in simulations of the atmospheric circulation. Here, we use neural networks to develop a subgrid mom...

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Bibliographic Details
Main Authors: Janni Yuval, Paul A. O’Gorman
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2023-04-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
Online Access:https://doi.org/10.1029/2023MS003606