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- # ACE2-ERA5
 
 
 
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  Ai2 Climate Emulator (ACE) is a family of models designed to simulate atmospheric variability from the time scale of days to centuries.
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  **Disclaimer: ACE models are research tools and should not be used for operational climate predictions.**
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- ACE-climSST is the original `ACE' model, as described in [ACE: A fast, skillful learned global atmospheric model for climate prediction](https://arxiv.org/abs/2310.02074).
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  It is trained on output from the FV3GFS atmospheric model forced with annually-repeating climatological sea surface temperature.
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  Code for doing inference with ACE models can be found here: [https://github.com/ai2cm/ace](https://github.com/ai2cm/ace)
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- with corresponding documentation here: [https://ai2-climate-emulator.readthedocs.io/en/stable/](https://ai2-climate-emulator.readthedocs.io/en/stable/)
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  Briefly, the strengths of ACE-climSST are:
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  - long-term stability
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  - very fast inference compared to typical physics-based atmospheric models
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  Some known weaknesses are:
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- - responses to more El Niño-like sea surface temperature and long-term warming trends are not accurately captured
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  - small but non-zero drifts in total dry air mass of the atmosphere
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- Refer to [published manuscript](https://arxiv.org/abs/2310.02074) for more details.
 
 
 
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+ ---
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+ license: apache-2.0
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+ ---
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+ # ACE-climSST
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  Ai2 Climate Emulator (ACE) is a family of models designed to simulate atmospheric variability from the time scale of days to centuries.
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  **Disclaimer: ACE models are research tools and should not be used for operational climate predictions.**
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+ ACE-climSST is the original ACE model, as described in [ACE: A fast, skillful learned global atmospheric model for climate prediction](https://arxiv.org/abs/2310.02074).
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  It is trained on output from the FV3GFS atmospheric model forced with annually-repeating climatological sea surface temperature.
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  Code for doing inference with ACE models can be found here: [https://github.com/ai2cm/ace](https://github.com/ai2cm/ace)
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+ with corresponding documentation here: [https://ai2-climate-emulator.readthedocs.io/en/stable/](https://ai2-climate-emulator.readthedocs.io/en/stable/).
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  Briefly, the strengths of ACE-climSST are:
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  - long-term stability
 
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  - very fast inference compared to typical physics-based atmospheric models
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  Some known weaknesses are:
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+ - responses to El Niño-like sea surface temperature and long-term warming trends are not accurately captured
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  - small but non-zero drifts in total dry air mass of the atmosphere
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+ Refer to [published manuscript](https://arxiv.org/abs/2310.02074) for more details.
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+
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+ Note the checkpoint provided here is the same as the one in [this Zenodo repository](https://zenodo.org/records/10791087), just with the optimizer state removed to decrease the checkpoint size.