{
  "model_name": "ClimateBench",
  "model_type": "climatebench",
  "architectures": ["ClimateBench", "ClimateBenchBranch"],
  "framework": "PyTorch",
  "domain": "climate-emulation",
  "task": "annual-spatial-climate-response-emulation",
  "license": "Apache-2.0",
  "implementation": {
    "entry_point": "model/climatebench.py",
    "train_script": "scripts/train.py",
    "inference_script": "scripts/inference.py",
    "evaluation_script": "scripts/result.py",
    "synthetic_data_script": "scripts/fake_data.py"
  },
  "architecture": {
    "per_target": "TimeDistributed Conv2d(4,20,3,same)+ReLU+AvgPool2d(2)+global spatial average+ReLU-LSTM(20,25)+Dense(25,13824)",
    "parameters_per_target": 364764,
    "targets": ["tas", "dtr", "pr", "pr90"],
    "independent_branches": 4
  },
  "data": {
    "format": "NPZ",
    "stored_input_layout": "NTCHW",
    "paper_input_layout": "NTHWC",
    "recommended_input_shape": ["B", 10, 4, 96, 144],
    "output_shape": ["B", 4, 96, 144],
    "channels": ["co2_cumulative", "ch4", "so2", "bc"],
    "temporal_resolution": "annual",
    "protocol": "climatebench_annual_npz_v1"
  },
  "configuration_sources": [
    "conf/config.yaml",
    "model/climatebench.py",
    "scripts/fake_data.py",
    "scripts/train.py",
    "scripts/inference.py",
    "scripts/result.py"
  ]
}