Ai2 Climate Emulator (ACE) is a family of models designed to simulate atmospheric variability from the time scale of days to centuries.
ACE2-ERA5 is trained on the
ERA5 dataset and is described in
ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses. As part of that paper, the repository containing training and evaluation scripts and configuration files used for this model is located
here.
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Download this repository. Optionally, you can just download a subset of the forcing_data and initial_conditions for the period you are interested in.
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Update paths in the inference_config.yaml. Specifically, update experiment_dir, checkpoint_path, initial_condition.path and forcing_loader.dataset.path.
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Install code dependencies with pip install fme.
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Run inference with python -m fme.ace.inference inference_config.yaml.
