| { |
| "model_name": "ScaleAdaptiveCM", |
| "model_type": "scale_adaptive_cm", |
| "architectures": ["ScaleAdaptiveCM"], |
| "framework": "PyTorch", |
| "domain": "climate", |
| "task": "probabilistic-precipitation-downscaling", |
| "implementation": { |
| "entry_point": "model/scale_adaptive_cm.py", |
| "scope": "core-method, full-spatial-dimension reduced-model engineering reproduction", |
| "train_script": "scripts/train.py", |
| "inference_script": "scripts/inference.py", |
| "evaluation_script": "scripts/result.py", |
| "synthetic_data_script": "scripts/fake_data.py" |
| }, |
| "architecture": {"input_channels": 1, "output_channels": 1, "engineering_channels": [4, 8, 16], "paper_channels": [128, 128, 256, 256], "scale_factor": 4}, |
| "data": {"dataset": "ERA5 and ESM precipitation", "format_version": "scale_adaptive_cm_v1", "low_shape": ["B", 1, 60, 96], "high_shape": ["B", 1, 240, 384], "unit": "mm day-1", "synthetic": true}, |
| "configuration_sources": ["conf/config.yaml", "model/scale_adaptive_cm.py", "scripts/fake_data.py", "scripts/train.py", "scripts/inference.py", "scripts/result.py"] |
| } |
|
|
