Data‐Driven Equation Discovery of a Cloud Cover Parameterization
Arthur Grundner,
Tom Beucler,
Pierre Gentine
et al.
Abstract:A promising method for improving the representation of clouds in climate models, and hence climate projections, is to develop machine learning‐based parameterizations using output from global storm‐resolving models. While neural networks (NNs) can achieve state‐of‐the‐art performance within their training distribution, they can make unreliable predictions outside of it. Additionally, they often require post‐hoc tools for interpretation. To avoid these limitations, we combine symbolic regression, sequential fea… Show more
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