Author

Christopher A. T. Ferro

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Preprint Oct 2026

Value of Adding AI Weather Model Ensembles to a Multi-model Probabilistic Blend

Many weather forecasting organizations use a multi-model blend of ensemble members from different prediction systems to obtain a more accurate forecast. Recent studies have shown that blending deterministic AI-based models alongside physics-based models improves the overall forecast skill. However, the incorporation of...

Harris Sop Nkuiate, G. Evans, Christopher A. T. Ferro et al. · 0 citations

Preprint Oct 2026

Probabilistic AI models outperform numerical weather prediction models on record breaking heat extremes

AI weather prediction (AIWP) models have emerged as a key complement to physics-based numerical weather prediction (NWP) models, and now often outperform them on aggregate skill. Yet, several studies report that physics-based models still forecast extreme events better, in particular record-breaking extremes, based on...

J. Wessel, F. Spuler, Christopher A. T. Ferro et al. · 0 citations