| { |
| "model_name": "FourCastNet v2", |
| "model_type": "fourcastnet_v2", |
| "architectures": [ |
| "FourCastNetV2" |
| ], |
| "framework": "PyTorch", |
| "domain": "atmosphere", |
| "task": "global-weather-forecasting", |
| "implementation": { |
| "entry_point": "model/fourcastnet_v2.py", |
| "scope": "adapter for the bundled NVIDIA FourCastNet v2 SFNO network" |
| }, |
| "architecture": { |
| "family": "spherical Fourier neural operator", |
| "grid_shape": [ |
| 721, |
| 1440 |
| ], |
| "input_channels": 73, |
| "output_channels": 73, |
| "spectral_transform": "sht", |
| "filter_type": "non-linear", |
| "scale_factor": 6, |
| "embedding_size": 256, |
| "layers": 12, |
| "blocks_per_layer": 8, |
| "normalization": "instance_norm", |
| "mlp_mode": "distributed", |
| "spectral_layers": 3, |
| "complex_activation": "real", |
| "hard_thresholding_fraction": 1.0 |
| }, |
| "data": { |
| "dataset": "ERA5", |
| "spatial_resolution_degrees": 0.25, |
| "time_step_hours": 6, |
| "input_steps": 1, |
| "output_steps": 1, |
| "protocol": "synthetic_era5" |
| }, |
| "configuration_sources": [ |
| "conf/config.yaml", |
| "model/fourcastnet_v2.py", |
| "model/fcnv2" |
| ] |
| } |
|
|
