| --- |
| license: apache-2.0 |
| library_name: fme |
| --- |
| |
| # ACE2S-SHiELD+ |
|
|
| <img src="ACE-logo.png" alt="Logo for the ACE Project" style="width: auto; height: 50px;"> |
|
|
| Ai2 Climate Emulator (ACE) is a family of models designed to simulate |
| atmospheric variability from the time scale of days to centuries. |
|
|
| **Disclaimer: ACE models are research tools and should not be used for |
| operational climate predictions.** |
|
|
| ACE2S-SHiELD+ is an emulator of GFDL's physics-based SHiELD model, trained on a |
| combination of AMIP, equilibrium-climate, and ramped-SST-random-CO<sub>2</sub> |
| data. It has comparable skill to ACE2-SHiELD in AMIP inference and ACE2-SOM in |
| slab-ocean-coupled equilibrium-climate inference, but also can accurately |
| emulate scenarios with independent perturbations to the SST or CO<sub>2</sub>, |
| like AMIP +4 K or slab-ocean-coupled abrupt 4xCO<sub>2</sub>. It is a |
| stochastic model, which facilitates running large ensembles of simulations from |
| the same initial conditions, has an improved representation of the spherical |
| power spectrum of its predicted variables, and also includes a new constraint |
| to conserve global atmospheric total energy. |
|
|
| Quick links: |
| - 📃 [Paper](https://arxiv.org/abs/2606.07928) |
| - 💻 [Code](https://github.com/ai2cm/ace) |
| - 💬 [Docs](https://ai2-climate-emulator.readthedocs.io/en/stable/) |
| - 📂 [All Models](https://huggingface.co/collections/allenai/ace-67327d822f0f0d8e0e5e6ca4) |
|
|
| Briefly, the strengths of ACE2S-SHiELD+ are: |
| - It can accurately perform historical AMIP simulations, slab-ocean-coupled |
| simulations with constant or steadily increasing CO<sub>2</sub> between 1x |
| and 4x the concentration of the present day. |
| - Unlike prior models, it can additionally accurately separate the independent |
| effects of SST and CO<sub>2</sub> on climate, including in AMIP +4 K and |
| abrupt 4xCO<sub>2</sub> inference, notably emulating the correct radiative |
| sensitivity to changes in CO<sub>2</sub> including the implicit response of |
| clouds. |
| - In addition to conserving dry air mass and water like prior models, it also |
| is constrained to conserve global atmospheric total energy within the same |
| average residual of SHiELD. |
|
|
| Some known weaknesses are: |
| - It is trained to emulate a physics-based model and therefore inherits the |
| biases relative to observations thereof. |
| - As in the case of ACE2-SOM and SHiELD, in slab-ocean mode, sea-ice coverage, |
| ocean heat transport, and ocean mixed layer depth are prescribed based on a |
| present-day climatologies and therefore do not respond to changes in |
| CO<sub>2</sub>. Prescribed sea-ice means projections with ACE2S-SHiELD+ are |
| missing an important feedback mechanism known to amplify warming in the polar |
| regions. Due to the narrow spread in sea ice coverage in samples seen during |
| training, generalization ability to unseen sea ice coverage is limited. |
| - Similar to ACE2-SOM, abrupt regime shifts in stratospheric temperature and |
| moisture can occur in inference runs, which sometimes can affect predictions |
| of other variables. |
|
|
| Inference speed: |
| - Note that due to architectural and hyperparameter changes, inference speed with |
| ACE2S-SHiELD+ is roughly half that of ACE2-SHiELD or ACE2-SOM, but it is still |
| 68x faster than SHiELD when each are run on typical hardware. |
|
|
| ## License |
|
|
| This model is licensed under Apache 2.0. It is intended for research and |
| educational use in accordance with Ai2’s |
| [Responsible Use Guidelines](https://allenai.org/responsible-use). |
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|
