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Diego G. Miralles

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Preprint Oct 2026

Beyond the record: evaluating probabilistic AI weather forecasts deep in the tail

Can probabilistic artificial intelligence (AI) weather forecasts retain skill beyond their training domain? We compare four state-of-the-art AI models (ArchesWeatherGen, U-Cast, WeatherNext2 and GenCast-mini) with the physics-based IFS-ENS over land in 2022, at 1.5{\deg} resolution and lead times of 2--10 days. Monthly...

Bas van Velthoven, Cas Decancq, Diego G. Miralles et al. · 0 citations

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