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@@ -12,18 +12,21 @@ Ai2 Climate Emulator (ACE) is a family of models designed to simulate atmospheri
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  ACE2-ERA5 is trained on the [ERA5 dataset](https://rmets.onlinelibrary.wiley.com/doi/10.1002/qj.3803) and will be described in a forthcoming paper.
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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 ACE2-ERA5 are:
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  - accurate atmospheric warming response to combined increase of sea surface temperature and CO2 over last 80 years
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  - highly accurate atmospheric response to El Niño sea surface temperature variability
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- - good representation of geographic distribution of tropical cyclones
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  - accurate Madden Julian Oscillation variability
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  - realistic stratospheric polar vortex strength and variability
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  - exact conservation of global dry air mass and moisture
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  Some known weaknesses are:
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- - the individual sensitivities to increased sea surface temperature and CO2 are not entirely realistic
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  - the medium-range (3-10 day) weather forecast skill is not state of the art
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- - not expected to generalize accurately for large perturbations of inputs (e.g. doubling of CO2)
 
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  ACE2-ERA5 is trained on the [ERA5 dataset](https://rmets.onlinelibrary.wiley.com/doi/10.1002/qj.3803) and will be described in a forthcoming paper.
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+ Quick links:
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+ - 📃 Paper (coming soon)
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+ - 💻 [Code](https://github.com/ai2cm/ace)
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+ - 💬 [Docs](https://ai2-climate-emulator.readthedocs.io/en/stable/)
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+ - 📂 [All Models](https://huggingface.co/collections/allenai/ace-67327d822f0f0d8e0e5e6ca4)
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  Briefly, the strengths of ACE2-ERA5 are:
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  - accurate atmospheric warming response to combined increase of sea surface temperature and CO2 over last 80 years
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  - highly accurate atmospheric response to El Niño sea surface temperature variability
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+ - good representation of the geographic distribution of tropical cyclones
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  - accurate Madden Julian Oscillation variability
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  - realistic stratospheric polar vortex strength and variability
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  - exact conservation of global dry air mass and moisture
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  Some known weaknesses are:
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+ - the individual sensitivities to changing sea surface temperature and CO2 are not entirely realistic
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  - the medium-range (3-10 day) weather forecast skill is not state of the art
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+ - not expected to generalize accurately for large perturbations of certain inputs (e.g. doubling of CO2)