{
  "format_version": "2.0",
  "model_name": "AtmosphericDA-DModel",
  "model_type": "dense-analysis-increment-correction",
  "architectures": ["DModel", "HybridSurrogate", "TwoLayerQG"],
  "framework": "PyTorch",
  "paper_framework": "TensorFlow",
  "domain": "earth-science",
  "task": "two-layer-streamfunction-model-error-correction",
  "license": "Apache-2.0",
  "implementation": {
    "entry_point": "model/atmosphericda_dmodel.py",
    "train_script": "scripts/train.py",
    "inference_script": "scripts/inference.py",
    "evaluation_script": "scripts/result.py",
    "synthetic_data_script": "scripts/fake_data.py"
  },
  "architecture": {
    "family": "D model linear Dense analysis-increment correction",
    "input_shape": ["B", 2, 20, 40],
    "output_shape": ["B", 2, 20, 40],
    "state_layout": "BCYX",
    "state_size": 1600,
    "hidden_size": 8,
    "activation": "linear",
    "target": "x_a_{k+1} - M_o(x_a_k)"
  },
  "data": {
    "protocol": "hybrid_qg_analysis_increment_npz_v2",
    "state_shape": [2, 20, 40],
    "observation_shape_per_window": [12, 50],
    "observation_operator": "bilinear at random off-grid locations",
    "observation_covariance": "0.1 I"
  },
  "configuration_sources": ["conf/config.yaml", "model/atmosphericda_dmodel.py", "scripts/fake_data.py", "scripts/train.py", "scripts/inference.py", "scripts/result.py"]
}