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8791cfe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | {
"model_name": "NNCAM",
"model_type": "nncam",
"architectures": ["NNCAM"],
"framework": "PyTorch",
"domain": "atmospheric-physics",
"task": "climate-model-subgrid-parameterization",
"implementation": {
"entry_point": "model/nncam.py",
"scope": "core-method and full-column reduced-sample 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_shape": ["B", 94],
"output_shape": ["B", 65],
"engineering_depth": 4,
"engineering_width": 32,
"paper_depth": 9,
"paper_width": 256,
"activation": "LeakyReLU"
},
"data": {
"dataset": "SPCAM aquaplanet simulation",
"format_version": "1.0",
"vertical_levels": 30,
"input_variables": ["T", "Q", "V", "Ps", "Sin", "H", "E"],
"output_variables": ["dT", "dQ", "SWtoa", "SWsfc", "LWtoa", "LWsfc", "P"],
"input_layout": "NF",
"synthetic": true
},
"configuration_sources": [
"conf/config.yaml",
"model/nncam.py",
"scripts/fake_data.py",
"scripts/train.py",
"scripts/inference.py",
"scripts/result.py"
]
}
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