3 papers
physics.ao-ph2025
Data-driven multiscale modeling for correcting dynamical systems
Karl Otness, Laure Zanna, Joan Bruna
We propose a multiscale approach for predicting quantities in dynamical systems which is explicitly structured to extract information in both fine-to-coarse and coarse-to-fine dire…
physics.ao-ph2024
A stable implementation of a data-driven scale-aware mesoscale parameterization
Pavel Perezhogin, Cheng Zhang, Alistair Adcroft +2
Ocean mesoscale eddies are often poorly represented in climate models, and therefore, their effects on the large scale circulation must be parameterized. Traditional parameterizati…
cs.LG2024
ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation
Sungduk Yu, Zeyuan Hu, Akshay Subramaniam +44
Modern climate projections lack adequate spatial and temporal resolution due to computational constraints, leading to inaccuracies in representing critical processes like thunderst…