- RESEARCH BRIEFINGS
An innovative artificial-intelligence application enhances weather forecasting in the difficult subseasonal range, providing accurate forecasts of precipitation, temperature and pressure 3–5 weeks in advance. The tool refines both physics- and AI-based weather models and improves the early prediction of extremes of heat, cold, rainfall and flooding.
This is a summary of: Guan, H. et al. Advancing subseasonal forecasting with machine learning. Nature 658, 951–957 (2026).
doi: https://doi.org/10.1038/d41586-026-03077-0
‘Expert opinion’ is published under a CC BY 4.0 licence and Figure 1 is published under a CC BY-NC-ND 4.0 licence.
References
Cohen, J. et al. WIREs Clim. Change 10, e00567 (2018).
Nathaniel, J. et al. Adv. Neural Inf. Process. Syst. 37, 43715–43729 (2024).
Hwang, J., Orenstein, P., Cohen, J., Pfeiffer, K. & Mackey, L. In Proc. 25th ACM SIGKDD Int. Conf. Knowledge Discovery Data Mining (eds Teredesai, A. & Kumar, V.) 2325–2335 (ACM, 2019).
Mouatadid, S. et al. Adv. Neural Inf. Process. Syst. 36, 7960–7992 (2023).
Mouatadid, S. et al. Nature Commun. 14, 3482 (2023).
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