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physics.ao-ph2026
WP-MIP: An Artificial Intelligence, Hybrid, and Physically Based Model Intercomparison Project for Weather Prediction
Ron McTaggart-Cowan, Linus Magnusson, Inna Polichtchouk +57
Rapid progress in the field of machine-learning for weather prediction has led to the emergence of algorithms whose forecasting skill can exceed that of traditional physically base…
physics.ao-ph2026
Learning Data-driven Surrogate and Correction Models for Satellite Observations in Numerical Weather Prediction
Gian Luca Buono, Stefanie Hollborn, Roland Potthast +2
Satellite observations play a critical role in numerical weather prediction where they are assimilated through an observation operator that maps model states to radiances. In the t…
physics.ao-ph2024
AI-based data assimilation: Learning the functional of analysis estimation
Jan D. Keller, Roland Potthast
The integration of observational data into numerical models, known as data assimilation (DA), is fundamental for making Numerical Weather Prediction (NWP) possible, with breathtaki…