5 papers
U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster
Salva Rühling Cachay, Duncan Watson-Parris, Rose Yu
AI-based weather forecasting now rivals traditional physics-based ensembles, but state-of-the-art (SOTA) models rely on specialized architectures and massive computational budgets,…
Zephyrus: An Agentic Framework for Weather Science
Sumanth Varambally, Marshall Fisher, Jas Thakker +14
Foundation models for weather science are pre-trained on vast amounts of structured numerical data and outperform traditional weather forecasting systems. However, these models lac…
Elucidated Rolling Diffusion Models for Probabilistic Forecasting of Complex Dynamics
Salva Rühling Cachay, Miika Aittala, Karsten Kreis +4
Diffusion models are a powerful tool for probabilistic forecasting, yet most applications in high-dimensional complex systems predict future states individually. This approach stru…
DYffCast: Regional Precipitation Nowcasting Using IMERG Satellite Data. A case study over South America
Daniel Seal, Rossella Arcucci, Salva Rühling-Cachay +1
Climate change is increasing the frequency of extreme precipitation events, making weather disasters such as flooding and landslides more likely. The ability to accurately nowcast…
Probabilistic Emulation of a Global Climate Model with Spherical DYffusion
Salva Rühling Cachay, Brian Henn, Oliver Watt-Meyer +2
Data-driven deep learning models are transforming global weather forecasting. It is an open question if this success can extend to climate modeling, where the complexity of the dat…