Articles | Volume 19, issue 19
https://doi.org/10.5194/gmd-19-9831-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-9831-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
13 Oct 2026
Model evaluation paper |
| 13 Oct 2026
| 13 Oct 2026
Physics vs. AI in weather prediction: evaluating GraphCast, AIFS, and FuXi against an observation-corrected WRF model for flash floods
Haseeb ur Rehman
CORRESPONDING AUTHOR
Department of Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, 2 Avenue de l'Université, 4365 Esch-sur-Alzette, Luxembourg
Félicia Norma Rebecca Teferle
Department of Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, 2 Avenue de l'Université, 4365 Esch-sur-Alzette, Luxembourg
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Short summary
Artificial intelligence (AI) weather models are now competing with traditional physics-based models for flood forecasting. We tested three of them and a physics-based model against observations from three flood events in Luxembourg. The AI models detected light rain and predicted temperatures better, but the physics-based model was more skilful at the heavy rainfall that actually causes floods. One AI model kept its skill on an event after its training period.
Artificial intelligence (AI) weather models are now competing with traditional physics-based...
