Non‐Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models

Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resulting in reduced trustworthiness in these methods. Here, we...

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Vydané v:Journal of advances in modeling earth systems Ročník 14; číslo 8; s. e2022MS003130 - n/a
Hlavní autori: Behrens, Gunnar, Beucler, Tom, Gentine, Pierre, Iglesias‐Suarez, Fernando, Pritchard, Michael, Eyring, Veronika
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States John Wiley & Sons, Inc 01.08.2022
American Geophysical Union (AGU)
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ISSN:1942-2466, 1942-2466
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