Author

S. Driscoll

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#machine learning Preprint Sep 2026

Evaluating Dynamical Fidelity through Predictive Structure in Physical Representations

A practical framework for evaluating dynamical fidelity through predictive structure in physical representation spaces is introduced and demonstrated in atmospheric forecasting using ERA5 representations of planetary-wave activity and Northern Annular Mode evolution and evaluates Pangu-Weather, GraphCast, and FengWu.

Oskar Bohn Lassen, Joao Paulo de Souza Boger, S. Driscoll et al. · 0 citations

#machine learning Preprint Sep 2026

Butterfly Effect and the Kinetic Energy Cascade in Probabilistic Machine Learning Weather Prediction Models

The results show that MLWP models can misrepresent the known scale transfer of kinetic energy despite producing skilful weather forecasts.

Jia-Kai Chen, Joel Oskarsson, S. Driscoll et al. · 0 citations