GraphCast / config.json
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{
"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"
]
}