{
  "model_name": "FengWu-W2S",
  "model_type": "fengwu_w2s",
  "architectures": [
    "FengWuW2S"
  ],
  "framework": "PyTorch",
  "domain": "coupled-atmosphere-ocean-land",
  "task": "seamless-weather-to-subseasonal-forecasting",
  "implementation": {
    "entry_point": "model/fengwu_w2s.py",
    "scope": "compact coupled weather, ocean, and land model with stochastic perturbations for autoregressive rollout"
  },
  "architecture": {
    "family": "coupled branch encoders with latent fusion and perturbation module",
    "input_steps": 2,
    "rollout_steps": 2,
    "inference_steps": 4,
    "input_channels": 78,
    "atmosphere_channels": 65,
    "ocean_channels": 4,
    "land_channels": 9,
    "hidden_channels": 32,
    "latent_channels": 64,
    "patch_size": 4,
    "blocks": 2,
    "perturbation_scale": 0.01
  },
  "data": {
    "dataset": "ERA5 with coupled ocean and land fields",
    "spatial_resolution_degrees": 0.25,
    "time_step_hours": 6,
    "protocol": "78-channel weather-to-subseasonal contract"
  },
  "configuration_sources": [
    "conf/config.yaml",
    "model/fengwu_w2s.py",
    "scripts/data_loader.py",
    "scripts/train.py"
  ]
}