{
  "model_name": "GraphCast",
  "model_type": "graphcast",
  "architectures": [
    "GraphCastNet"
  ],
  "framework": "PyTorch",
  "domain": "atmosphere",
  "task": "global-weather-forecasting",
  "implementation": {
    "entry_point": "model/graph_cast_net.py",
    "scope": "repository mesh message-passing implementation"
  },
  "architecture": {
    "family": "multimesh graph neural network",
    "input_grid_shape": [
      721,
      1440
    ],
    "mesh_refinement_level": 6,
    "multimesh": true,
    "grid_node_input_size": 237,
    "grid_node_output_size": 227,
    "hidden_size": 512,
    "processor_layers": 16,
    "processor_type": "MessagePassing",
    "aggregation": "sum",
    "activation": "silu",
    "normalization": "LayerNorm"
  },
  "data": {
    "dataset": "ERA5",
    "spatial_resolution_degrees": 0.25,
    "time_step_hours": 6,
    "climate_channels": 227,
    "static_channels": 5,
    "pressure_levels_hpa": [
      1,
      2,
      3,
      5,
      7,
      10,
      20,
      30,
      50,
      70,
      100,
      125,
      150,
      175,
      200,
      225,
      250,
      300,
      350,
      400,
      450,
      500,
      550,
      600,
      650,
      700,
      750,
      775,
      800,
      825,
      850,
      875,
      900,
      925,
      950,
      975,
      1000
    ],
    "pressure_level_variables": [
      "geopotential",
      "relative_humidity",
      "temperature",
      "u_component_of_wind",
      "v_component_of_wind",
      "vertical_wind_speed"
    ]
  },
  "configuration_sources": [
    "conf/config.yaml",
    "model/graph_cast_net.py"
  ]
}