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20232026
most citedStable Machine-Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection-Permitting Simulations

6 citations · 19 across the 6 of their papers we have counts for

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physics.ao-ph2025

Crowdsourcing the Frontier: Advancing Hybrid Physics-ML Climate Simulation via a $50,000 Kaggle Competition

Jerry Lin, Zeyuan Hu, Tom Beucler +24

Subgrid machine-learning (ML) parameterizations have the potential to introduce a new generation of climate models that incorporate the effects of higher-resolution physics without…