2 papers
physics.ao-ph2026
Hierarchical Testing of a Hybrid Machine Learning-Physics Global Atmosphere Model
Ziming Chen, L. Ruby Leung, Wenyu Zhou +9
Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predi…
cs.LG2025
Retrofitting Earth System Models with Cadence-Limited Neural Operator Updates
Aniruddha Bora, Shixuan Zhang, Khemraj Shukla +3
Coarse resolution, imperfect parameterizations, and uncertain initial states and forcings limit Earth-system model (ESM) predictions. Traditional bias correction via data assimilat…