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.
This repo contains code accompanying five papers describing ACE models:
- "ACE: A fast, skillful learned global atmospheric model for climate prediction" (link)
- "Application of the Ai2 Climate Emulator to E3SMv2's global atmosphere model, with a focus on precipitation fidelity" (link)
- "ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses" (link)
- "ACE2-SOM: Coupling to a slab ocean and learning the sensitivity of climate to changes in CO2" (link)
- "Applying the ACE2 Emulator to SST Green's Functions for the E3SMv3 Global Atmosphere Model" (link)
pip install fme
See complete documentation here and a quickstart guide here.
Pretrained model checkpoints, and datasets to run them, are available in the ACE Hugging Face collection.
