Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciarán published in npj Climate and Atmospheric Science.

Andrew J. Charlton-Perez and co-authors, including Simon Driscoll, investigate the ability of many of the world’s leading NWP and AI weather forecasting models in their ability to simulate Storm Ciaran. AI models are essentially indistinguishable from NWP models in the storm track and MSLP fields analysed, and many important dynamical features are well captured by the AI models. However, the AI models fail to produce other features, and notably had substantially weaker peak surface wind speeds that led to the most severe impacts.

https://doi.org/10.1038/s41612-024-00638-w

_Fig.4 (from J. Charlton-Perez, F. Dacre, Driscoll et al.):Near-surface wind and MSLP structure of Storm Ciarán at 00 UTC on 2 November 2023 from reanalysis and forecasts. Maps of 10-m wind speed (shading) and MSLP (contours) from a ERA5 and b–f forecasts, initialised at 00 UTC 31 October 2023, from the b IFS HRES model and c–f ML models, as labelled.