| { |
| "model_name": "GraphDOP", |
| "model_type": "graphdop", |
| "architectures": [ |
| "GraphDOP" |
| ], |
| "framework": "PyTorch", |
| "domain": "climate-and-atmosphere", |
| "task": "observation-driven-medium-range-weather-forecasting", |
| "implementation": { |
| "entry_point": "model/graphdop.py", |
| "scope": "pure-PyTorch minimal reproduction using gridded ERA5 placeholders and fixed regular-mesh graphs instead of the paper's irregular Level-1 observations and dynamic graphs" |
| }, |
| "architecture": { |
| "family": "GNN encoder-Transformer processor-GNN decoder", |
| "input_format": "B T C H W", |
| "encoder": "per-grid-cell MLP, adaptive pooling to the latent mesh, then residual mean-aggregation GNN layers", |
| "processor": "pre-normalized Transformer encoder over latent-mesh tokens with learned positional embeddings", |
| "decoder": "latent-mesh GNN, bilinear upsampling, and a per-grid-cell output MLP", |
| "edge_features": [ |
| "forward bearing", |
| "Haversine distance" |
| ], |
| "activation": "GELU", |
| "normalization": "LayerNorm", |
| "loss": "channel-weighted mean squared error", |
| "repository_default_config": { |
| "purpose": "connectivity validation with synthetic gridded data", |
| "grid_shape": [ |
| 32, |
| 32 |
| ], |
| "mesh_shape": [ |
| 8, |
| 8 |
| ], |
| "in_channels": 6, |
| "out_channels": 6, |
| "input_steps": 2, |
| "output_steps": 2, |
| "latent_dim": 64, |
| "num_encoder_layers": 2, |
| "num_decoder_layers": 2, |
| "num_processor_blocks": 1, |
| "attention_heads": 4, |
| "hidden_dim": 64, |
| "channel_weights": [ |
| 1, |
| 1, |
| 1, |
| 1, |
| 1, |
| 1 |
| ] |
| }, |
| "paper_reference_config": { |
| "latent_grid": "O96 reduced Gaussian grid with 40320 nodes", |
| "latent_dim": 1024, |
| "observation_graph": "dynamic graph over irregular Level-1 observations", |
| "training_steps": 70000, |
| "training_hardware": "64 H100 GPUs" |
| } |
| }, |
| "data": { |
| "dataset": "ERA5", |
| "role": "regular-grid placeholder for the paper's multi-instrument observations", |
| "variables": [ |
| "atms_brightness_temperature", |
| "gpsro_bending_angle", |
| "ascat_sigma0", |
| "significant_wave_height", |
| "2m_temperature", |
| "10m_wind_speed" |
| ], |
| "time_step_hours": 6, |
| "input_length": 2, |
| "output_length": 2, |
| "channels": 6, |
| "spatial_size": [ |
| 32, |
| 32 |
| ], |
| "storage_format": "HDF5 fields with T C H W layout", |
| "train_years": [ |
| 1951, |
| 1952 |
| ], |
| "validation_years": [ |
| 1953 |
| ], |
| "test_years": [ |
| 1954 |
| ] |
| }, |
| "configuration_sources": [ |
| "README.md", |
| "conf/config.yaml", |
| "model/graphdop.py", |
| "scripts/train.py", |
| "scripts/inference.py", |
| "scripts/fake_data.py", |
| "configuration.json" |
| ] |
| } |
|
|
