{
  "model_name": "RF-ClimParam",
  "model_type": "joint-multi-output-random-forest-regressor",
  "architectures": ["JointRandomForestRegressor"],
  "framework": "PyTorch",
  "domain": "earth-science",
  "task": "multi-resolution-subgrid-parameterization",
  "implementation": {
    "entry_point": "model/rf_climparam.py",
    "scope": "independent paper-method 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": {
    "family": "bootstrapped extra-random regression forest",
    "rf_tend_input": 145,
    "rf_tend_output": 144,
    "rf_diff_input": 62,
    "rf_diff_output": 17,
    "joint_multi_output_leaves": true,
    "scales": ["x4", "x8", "x16", "x32"]
  },
  "paper_model": {
    "trees": 10,
    "min_samples_leaf": {"x4": 20, "x8": 20, "x16": 20, "x32": 7},
    "training_samples": {"x4": 5000000, "x8": 5000000, "x16": 5000000, "x32": "not_reported"},
    "max_depth": "not_reported",
    "max_features": "not_reported",
    "bootstrap": "not_reported",
    "split_criterion": "not_reported",
    "implementation": "scikit-learn-0.21.2-RandomForestRegressor"
  },
  "data": {
    "protocol": "rf_climparam_v2",
    "format": "NPZ",
    "high_resolution": {"km": 12, "grid": [576, 1440], "vertical_levels": 48},
    "coarse_grids": {
      "x4": {"km": 48, "grid": [144, 360]},
      "x8": {"km": 96, "grid": [72, 180]},
      "x16": {"km": 192, "grid": [36, 90]},
      "x32": {"km": 384, "grid": [18, 45], "online_native_grid": [18, 48]}
    },
    "domain_km": [6912, 17280],
    "snapshot_hours": 3,
    "default_timestep_seconds": 24,
    "coarsening": "N by N horizontal average",
    "synthetic_layout": "one complete C-order flattened structured snapshot per coarse scale",
    "default_training_sampling": "one longitude column per latitude"
  },
  "paper": {
    "arxiv": "2001.03151",
    "doi": "10.1038/s41467-020-17142-3",
    "official_code_data_osf_doi": "10.17605/OSF.IO/36YPT"
  },
  "configuration_sources": [
    "conf/config.yaml", "model/rf_climparam.py", "scripts/fake_data.py",
    "scripts/train.py", "scripts/inference.py", "scripts/result.py"
  ]
}