44 citations · 171 across the 16 of their papers we have counts for
4 papers · 1 filter
SEEDS: Emulation of Weather Forecast Ensembles with Diffusion Models
Lizao Li, Rob Carver, Ignacio Lopez-Gomez +2
Uncertainty quantification is crucial to decision-making. A prominent example is probabilistic forecasting in numerical weather prediction. The dominant approach to representing un…
Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations
Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Núñez +5
We introduce a data-driven learning framework that assimilates two powerful ideas: ideal large eddy simulation (LES) from turbulence closure modeling and neural stochastic differen…
Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models
Zhong Yi Wan, Ricardo Baptista, Yi-fan Chen +4
We introduce a two-stage probabilistic framework for statistical downscaling using unpaired data. Statistical downscaling seeks a probabilistic map to transform low-resolution data…
Accelerating large-eddy simulations of clouds with Tensor Processing Units
Sheide Chammas, Qing Wang, Tapio Schneider +3
Clouds, especially low clouds, are crucial for regulating Earth's energy balance and mediating the response of the climate system to changes in greenhouse gas concentrations. Despi…