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Ai2 Climate Emulator (ACE) is a fast machine learning model that simulates global atmospheric variability in a changing climate over time scales ranging from hours to centuries.
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This repo contains code accompanying four papers describing ACE models:
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This repo contains code accompanying five papers describing ACE models:
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- "ACE: A fast, skillful learned global atmospheric model for climate prediction" ([link](https://arxiv.org/abs/2310.02074))
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- "Application of the Ai2 Climate Emulator to E3SMv2's global atmosphere model, with a focus on precipitation fidelity" ([link](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2024JH000136))
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- "ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses" ([link](https://arxiv.org/abs/2411.11268))
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- "ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses" ([link](https://www.nature.com/articles/s41612-025-01090-0))
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- "ACE2-SOM: Coupling to a slab ocean and learning the sensitivity of climate to changes in CO2" ([link](https://arxiv.org/abs/2412.04418))
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- "Applying the ACE2 Emulator to SST Green's Functions for the E3SMv3 Global Atmosphere Model" ([link](https://arxiv.org/abs/2505.08742))
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