Machine-learned climate model corrections from a global storm-resolving model. - Anna Kwa; Spencer K. Clark; Brian Henn; Noah D. Brenowitz; Jeremy McGibbon; W. Andre Perkins; Oliver Watt-Meyer; Lucas Harris; Christopher S. Bretherton (CoRR, 2022)

ACE: A fast, skillful learned global atmospheric model for climate prediction. - Oliver Watt-Meyer; Gideon Dresdner; Jeremy McGibbon; Spencer K. Clark; Brian Henn; James Duncan 002; Noah D. Brenowitz; Karthik Kashinath; Michael S. Pritchard; Boris Bonev; Matthew E. Peters; Christopher S. Bretherton (CoRR, 2023)

ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses. - Oliver Watt-Meyer; Brian Henn; Jeremy McGibbon; Spencer K. Clark; Anna Kwa; W. Andre Perkins; Elynn Wu; Lucas Harris; Christopher S. Bretherton (CoRR, 2024)

SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators. - James Duncan 002; Elynn Wu; Surya Dheeshjith; Adam Subel; Troy Arcomano; Spencer K. Clark; Brian Henn; Anna Kwa; Jeremy McGibbon; W. Andre Perkins; William Gregory; Carlos Fernandez-Granda; et al. (CoRR, 2025)