| { |
| "format_version": "1.0", |
| "model_name": "FuXi-Ocean", |
| "model_type": "fuxi_ocean", |
| "architectures": ["FuXiOcean"], |
| "framework": "PyTorch", |
| "domain": "earth-science-ocean", |
| "license": "Apache-2.0", |
| "paper": { |
| "title": "A deep learning global ocean forecasting model with sub-daily and eddy-resolving resolution", |
| "doi": "10.1038/s41612-026-01444-2", |
| "paper_license": "CC-BY-4.0" |
| }, |
| "implementation": { |
| "entry_point": "model/fuxi_ocean.py", |
| "train_script": "scripts/train.py", |
| "inference_script": "scripts/inference.py", |
| "evaluation_script": "scripts/result.py", |
| "synthetic_data_script": "scripts/fake_data.py" |
| }, |
| "scientific_grid": { |
| "history": 4, |
| "ocean_channels": 105, |
| "atmosphere_channels": 5, |
| "height": 2160, |
| "width": 4320, |
| "hours_per_step": 6, |
| "forecast_steps": 40 |
| }, |
| "execution_protocol": "Tiles retain all 105 channels, physical coordinates, and indices into the unchanged 2160x4320 global grid. Tile dimensions are not the scientific grid dimensions." |
| } |
|
|
