| --- |
| license: mit |
| tags: |
| - climate |
| - weather-forecasting |
| - swin-transformer |
| - flow-matching |
| --- |
| |
| # ArchesClimate-SSP |
|
|
| Deep-learning climate emulator (Swin-Transformer-based, autoregressive) |
| trained to reproduce IPSL-CM6A-LR and CanESM5 monthly climate states |
| conditioned on external forcings (GHGs, aerosols, ozone, solar irradiance). |
| Generates unseen SSP scenario trajectories cheaply, without rerunning the |
| full Earth System Model. |
|
|
| Code: https://github.com/gclyne/ArchesClimate (see `INFERENCE.md` there for |
| the full inference recipe). |
|
|
| ## What's in this repo |
|
|
| Only what's needed to instantiate and load the network — weights + the |
| Hydra config each checkpoint was trained with: |
|
|
| ``` |
| <run_name>/ |
| step-step=NNNNNN.ckpt # model weights (raw + EMA) |
| config.yaml # exact training-time Hydra config |
| ``` |
|
|
| ## Required companion data |
|
|
| This repo does **not** include initial conditions, forcing (boundary |
| condition) trajectories, static fields, or normalization stats — those |
| live in the paired dataset repo: |
| [gclyne/ArchesClimateDataset](https://huggingface.co/datasets/gclyne/ArchesClimateDataset). |
|
|
| See `INFERENCE.md` in the code repo for exactly which files from that |
| dataset repo are needed for a given checkpoint, and how to run a rollout. |
|
|
| ## Runs currently published here |
|
|
| | Run | Steps | Notes | |
| |---|---|---| |
| | `pf2_emafix_step40000` | 40,000 | Pushforward-length-2 energy-score deterministic model, EMA weights | |
|
|
