39 citations · 87 across the 6 of their papers we have counts for
4 papers · 1 filter
Improving the predictions of ML-corrected climate models with novelty detection
Clayton Sanford, Anna Kwa, Oliver Watt-Meyer +4
While previous works have shown that machine learning (ML) can improve the prediction accuracy of coarse-grid climate models, these ML-augmented methods are more vulnerable to irre…
Machine-learned climate model corrections from a global storm-resolving model
Anna Kwa, Spencer K. Clark, Brian Henn +6
Due to computational constraints, running global climate models (GCMs) for many years requires a lower spatial grid resolution ( km) than is optimal for accurately res…
Emulating Fast Processes in Climate Models
Noah D. Brenowitz, W. Andre Perkins, Jacqueline M. Nugent +6
Cloud microphysical parameterizations in atmospheric models describe the formation and evolution of clouds and precipitation, a central weather and climate process. Cloud-associate…
Productive Performance Engineering for Weather and Climate Modeling with Python
Tal Ben-Nun, Linus Groner, Florian Deconinck +11
Earth system models are developed with a tight coupling to target hardware, often containing specialized code predicated on processor characteristics. This coupling stems from usin…