Articles | Volume 7, issue 3
https://doi.org/10.5194/wcd-7-1307-2026
https://doi.org/10.5194/wcd-7-1307-2026
Research article
 | 
24 Jul 2026
Research article |  | 24 Jul 2026

Intraseasonal prediction of monthly storminess in the North Sea with the ACE2 atmospheric emulator and Random Forests

Proshonni Aziz, Birgit Hünicke, and Eduardo Zorita

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Short summary
By analysing data from 1940 to 2024, we found that upper atmosphere conditions in early winter directly influence the number of North Sea storms occurring weeks or months later. We used a climate model and machine learning to improve these forecasts. Results show that December patterns can predict January storminess with high accuracy, with effects persisting for up to 60 d. Stratospheric data and machine learning together improve winter storm prediction for this region.
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