132 citations · 274 across the 8 of their papers we have counts for
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physics.ao-ph2020★ 39 cited
Machine Learning Climate Model Dynamics: Offline versus Online Performance
Noah D. Brenowitz, Brian Henn, Jeremy McGibbon +5
Climate models are complicated software systems that approximate atmospheric and oceanic fluid mechanics at a coarse spatial resolution. Typical climate forecasts only explicitly r…
physics.ao-ph2020★ 68 cited
Interpreting and Stabilizing Machine-learning Parametrizations of Convection
Noah D. Brenowitz, Tom Beucler, Michael Pritchard +1
Neural networks are a promising technique for parameterizing sub-grid-scale physics (e.g. moist atmospheric convection) in coarse-resolution climate models, but their lack of inter…