Author

D. Rolnick

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#machine learning Preprint Sep 2026

RainAtlas: A Multi-Continental Dataset for Precipitation Downscaling

Extreme rainfall events are increasing in intensity and frequency as climate change accelerates. While kilometer-scale precipitation forecasts are critical for supporting local decision-making, the limited availability of high-resolution precipitation observations hinders their accuracy, especially in under-resourced r...

Pierre Lemaire, Luca Schmidt, Wietze Suijker et al. · 0 citations

#machine learning Preprint Sep 2026

Learning Hierarchical Causal Representations of the Effects of Forcings on Temperature in Climate Models

Machine learning (ML) emulators provide a fast and cost-effective method to simulate climate change scenarios after being trained on Earth System Models projections. However, the black-box nature of those data-driven approaches limit the usability and trustworthiness of their outputs and in particular their use as caus...

Shan Zhao, Ilija Trajković, Julia Kaltenborn et al. · 0 citations