3 papers
physics.ao-ph2026
Disentangling the effects of sea surface temperature and CO in global machine learned weather-climate emulators
Spencer K. Clark, Troy Arcomano, James P. C. Duncan +8
While previous versions of the Ai2 Climate Emulator (ACE) have been trained with CO as a forcing, they are only accurate within a narrow range of scenarios, for example climate…
physics.ao-ph2026
HiRO-ACE: Fast and skillful AI emulation and downscaling trained on a 3 km global storm-resolving model
W. Andre Perkins, Anna Kwa, Jeremy McGibbon +5
Kilometer-scale simulations of the atmosphere are an important tool for assessing local weather extremes and climate impacts, but computational expense limits their use to small re…
physics.ao-ph2024
ACE2-SOM: Coupling an ML atmospheric emulator to a slab ocean and learning the sensitivity of climate to changed CO
Spencer K. Clark, Oliver Watt-Meyer, Anna Kwa +6
While autoregressive machine-learning-based emulators have been trained to produce stable and accurate rollouts in the climate of the present-day and recent past, none so far have…