Probabilistic Emulation of a Global Climate Model with Spherical DYffusion

Data-driven deep learning models are transforming global weather forecasting. It is an open question if this success can extend to climate modeling, where the complexity of the data and long inference rollouts pose significant challenges. Here, we present the first conditional generative model that...

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Hauptverfasser:	Cachay, Salva Rühling, Henn, Brian, Watt-Meyer, Oliver, Bretherton, Christopher S, Yu, Rose
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning Physics - Atmospheric and Oceanic Physics Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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