3 papers
cs.LG2025
On Global Applicability and Location Transferability of Generative Deep Learning Models for Precipitation Downscaling
Paula Harder, Christian Lessig, Matthew Chantry +2
Deep learning offers promising capabilities for the statistical downscaling of climate and weather forecasts, with generative approaches showing particular success in capturing fin…
cs.LG2025
Causal Climate Emulation with Bayesian Filtering
Sebastian Hickman, Ilija Trajkovic, Julia Kaltenborn +6
Traditional models of climate change use complex systems of coupled equations to simulate physical processes across the Earth system. These simulations are highly computationally e…
cs.CV2025
RainShift: A Benchmark for Precipitation Downscaling Across Geographies
Paula Harder, Luca Schmidt, Francis Pelletier +5
Earth System Models (ESM) are our main tool for projecting the impacts of climate change. However, running these models at sufficient resolution for local-scale risk-assessments is…