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Prépublication · 2026 arXiv EN

Can We Trust Evaluations of AI Weather Forecasts for Extremes? How Evaluation Protocols Shape Model Rankings

AI weather models perform competitively with traditional physics-based models at a fraction of the computational cost, and they are thus already used operationally. However, studies reach conflicting conclusions about their ability to forecast extreme weather...

Tobias Biegert, Sam Allen et al. #stat.AP

Prépublication · 2026 arXiv EN

Learning joint probabilistic weather forecasts from station observations alone

Assessing compound weather risks requires forecasts representing dependence between variables. CLARA (Calibrated Advection-Routing Attention) learns joint Gaussian predictive distributions of five surface variables from station observations alone, without nume...

Chaeyeon Yi, Yun Am Seo #stat.AP

Prépublication · 2026 arXiv EN

Statistical Oceanography of Profiling Floats and Surface Drifters

The Global Ocean Observing System is key to understanding oceanic variability and climate change. The ocean is vast and often sparsely and irregularly sampled in time and space by various instruments and systems. Statistical models, especially spatio-temporal...

Mikael Kuusela, Sofia C. Olhede et al. #stat.AP