Improving Climate Bias and Variability via CNN‐Based State‐Dependent Model‐Error Corrections

Abstract We develop an approach to correct biases in the atmospheric component of the Community Earth System Model using convolutional neural networks (CNNs) to create a corrective model parameterization for online bias reduction. By predicting systematic nudging increments derived from nudging towa...

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Bibliographic Details

Published in:	Geophysical Research Letters
Main Authors:	William E. Chapman, Judith Berner
Format:	Article
Language:	English
Published:	Wiley 2025-03-01
Subjects:	Madden Julian Oscillation machine learning climate modeling
Online Access:	https://doi.org/10.1029/2024GL114106