9 citations · 15 across the 7 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
physics.geo-ph2024★ 1 cited
A Generative Machine Learning Approach for Improving Precipitation from Earth System Models
Philipp Hess, Niklas Boers
Quantifying the impacts of anthropogenic global warming requires accurate Earth system model (ESM) simulations. Statistical bias correction and downscaling can be applied to reduce…
physics.geo-ph2024★ 2 cited
Conditional diffusion models for downscaling and bias correction of Earth system model precipitation
Michael Aich, Philipp Hess, Baoxiang Pan +3
Climate change exacerbates extreme weather events like heavy rainfall and flooding. As these events cause severe socioeconomic damage, accurate high-resolution simulation of precip…
physics.ao-ph2024
Fast, Scale-Adaptive, and Uncertainty-Aware Downscaling of Earth System Model Fields with Generative Machine Learning
Philipp Hess, Michael Aich, Baoxiang Pan +1
Accurate and high-resolution Earth system model (ESM) simulations are essential to assess the ecological and socio-economic impacts of anthropogenic climate change, but are computa…