{
  "model_name": "NeuralGCM",
  "model_type": "neuralgcm",
  "architectures": [
    "PressureLevelModel"
  ],
  "framework": "JAX with Haiku and Gin",
  "domain": "atmosphere-and-climate",
  "task": "global-weather-forecasting-and-climate-simulation",
  "implementation": {
    "entry_point": "model/NeuralGCM.py",
    "scope": "vendored NeuralGCM pressure-level inference and training facade with differentiable dynamics and neural parameterizations"
  },
  "architecture": {
    "family": "hybrid differentiable general circulation model",
    "dynamical_core": "spectral atmospheric dynamics",
    "learned_components": [
      "encoder",
      "decoder",
      "subgrid physical parameterizations"
    ],
    "input_format": "xarray pressure-level fields",
    "grid_shape_order": [
      "longitude",
      "latitude"
    ],
    "time_step_hours": 6,
    "pressure_level_count": 37,
    "dynamic_variable_count": 7,
    "forcing_variable_count": 2,
    "flattened_input_channels": 261,
    "profiles": {
      "weather_forecast": {
        "type": "deterministic weather forecast",
        "resolution_degrees": 0.7,
        "grid_shape": [
          512,
          256
        ],
        "checkpoint": "weight/models_v1_deterministic_0_7_deg.pkl"
      },
      "climate_scale": {
        "type": "deterministic climate simulation",
        "resolution_degrees": 1.4,
        "grid_shape": [
          256,
          128
        ],
        "checkpoint": "weight/models_v1_deterministic_1_4_deg.pkl"
      },
      "forecast_2_8_deg": {
        "type": "deterministic weather forecast",
        "resolution_degrees": 2.8,
        "grid_shape": [
          128,
          64
        ],
        "checkpoint": "weight/models_v1_deterministic_2_8_deg.pkl"
      },
      "stochastic_1_4_deg": {
        "type": "stochastic weather forecast",
        "resolution_degrees": 1.4,
        "grid_shape": [
          256,
          128
        ],
        "checkpoint": "weight/models_v1_stochastic_1_4_deg.pkl"
      }
    }
  },
  "data": {
    "dataset": "ERA5",
    "source_grid_shape": [
      721,
      1440
    ],
    "time_step_hours": 6,
    "input_steps": 1,
    "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
    ],
    "input_variables": [
      "geopotential",
      "specific_humidity",
      "temperature",
      "u_component_of_wind",
      "v_component_of_wind"
    ],
    "optional_input_variables": [
      "specific_cloud_ice_water_content",
      "specific_cloud_liquid_water_content"
    ],
    "forcing_variables": [
      "sea_ice_cover",
      "sea_surface_temperature"
    ],
    "protocol": "era5_37_pressure_levels_261_channel"
  },
  "weights": {
    "license": "CC BY-SA 4.0",
    "source": "gs://neuralgcm/models/v1/"
  },
  "configuration_sources": [
    "conf/config.yaml",
    "configuration.json",
    "model/NeuralGCM.py",
    "model/legacy",
    "model/reference_code",
    "scripts/common.py"
  ]
}