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"model_name": "Stormer",
"model_type": "stormer",
"architectures": [
"Stormer"
],
"framework": "PyTorch",
"domain": "atmosphere",
"task": "global-medium-range-weather-forecasting",
"implementation": {
"entry_point": "model/stormer.py",
"scope": "repository interval-conditioned forecasting implementation"
},
"architecture": {
"family": "interval-conditioned vision transformer",
"input_grid_shape": [
128,
256
],
"patch_size": 2,
"hidden_size": 1024,
"transformer_layers": 24,
"attention_heads": 16,
"mlp_ratio": 4.0,
"variable_channels": 69,
"conditioning": "adaLN-Zero forecast interval"
},
"data": {
"dataset": "ERA5",
"spatial_resolution_degrees": 1.40625,
"data_frequency_hours": 6,
"training_intervals_hours": [
6,
12,
24
],
"pressure_levels_hpa": [
50,
100,
150,
200,
250,
300,
400,
500,
600,
700,
850,
925,
1000
],
"pressure_level_variables": [
"geopotential",
"specific_humidity",
"temperature",
"u_component_of_wind",
"v_component_of_wind"
],
"surface_variable_count": 4
},
"configuration_sources": [
"conf/config.yaml",
"model/stormer.py"
]
}
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