Datasets:
file stringclasses 4
values | size_bytes int64 74.1M 31.7B | description stringclasses 4
values |
|---|---|---|
data.zip | 31,673,754,818 | One month of case data |
Checkpoints.zip | 1,547,934,536 | Model weights (AERO-AIR and AERO-Surface) |
NeuralGCM_Weights.zip | 74,086,584 | NeuralGCM 1.4 degree checkpoint |
Virtual_Environment_Configuration.zip | 3,103,391,843 | Packaged Linux conda environment backup |
AERO-ODE Case Data
These files support the open-source AERO-ODE (AI-Enhanced Regional ODE Forecasting Framework) codebase. They provide one month of interpolated case data, together with pre-trained model weights and a packaged runtime environment.
Code, environment setup, inference commands, and visualization: AERO_ODE on GitHub.
Files
| File | Size (approx.) | Description |
|---|---|---|
data.zip |
31.7 GB | One month of case data |
Checkpoints.zip |
1.55 GB | Model weights (AERO-AIR & AERO-Surface) |
NeuralGCM_Weights.zip |
71 MB | NeuralGCM 1.4° checkpoint |
Virtual_Environment_Configuration.zip |
3.10 GB | Packaged Linux conda environment backup |
How to use
- Clone AERO_ODE.
- Download the zip files from this repository.
- Extract each archive into the AERO-ODE code repository root. Keep folder names unchanged.
Then follow the GitHub README for environment setup, inference, and visualization.
License
CC BY-NC 4.0. Commercial use of these models and data is prohibited.
NeuralGCM pretrained weights (NeuralGCM_Weights.zip) are released under CC BY-SA 4.0.
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