A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics

The weather and climate domains are undergoing a significant transformation thanks to advances in AI-based foundation models such as FourCastNet, GraphCast, ClimaX and Pangu-Weather. While these models show considerable potential, they are not ready yet for operational use in weather forecasting or...

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Veröffentlicht in:	arXiv.org 2024-07
Hauptverfasser:	Yin, Junqi, Liang, Siming, Liu, Siyan, Bao, Feng, Chipilski, Hristo G, Lu, Dan, Zhang, Guannan
Format:	Artikel
Sprache:	eng
Schlagworte:	Climate models Cyclones Data assimilation Kalman filters Predictions Real time operation Supercomputers Turbulence Weather forecasting Workflow
Online-Zugang:	Volltext
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