| { |
| "model_name": "ClimODE", |
| "model_type": "climode", |
| "architectures": [ |
| "ClimODE", |
| "ClimateEncoderFreeUncertain" |
| ], |
| "framework": "PyTorch", |
| "domain": "atmosphere", |
| "task": "global-weather-forecasting-with-neural-odes", |
| "implementation": { |
| "entry_point": "model/climode.py", |
| "scope": "OneScience adapter of the physics-informed neural transport ODE with optional attention and probabilistic output; it is not an AutoModel-compatible Transformers implementation" |
| }, |
| "architecture": { |
| "family": "physics-informed neural ODE with advective transport and convolutional velocity/noise networks", |
| "input_format": "BCHW", |
| "input_grid_shape": [ |
| 32, |
| 64 |
| ], |
| "input_channels": 5, |
| "output_channels": 5, |
| "time_step_hours": 6, |
| "solver": "euler", |
| "absolute_tolerance": 0.005, |
| "relative_tolerance": 0.005, |
| "use_attention": true, |
| "use_uncertainty": true, |
| "use_positional_encoder": false, |
| "resnet_repetitions": [ |
| 5, |
| 3, |
| 2 |
| ], |
| "resnet_hidden_channels": [ |
| 128, |
| 64, |
| 10 |
| ], |
| "history_frames_for_context": 3 |
| }, |
| "data": { |
| "dataset": "ERA5", |
| "source_grid_shape": [ |
| 721, |
| 1440 |
| ], |
| "model_grid_shape": [ |
| 32, |
| 64 |
| ], |
| "regrid_method": "bilinear with periodic longitude handling", |
| "variables": [ |
| "z", |
| "t", |
| "t2m", |
| "u10", |
| "v10" |
| ], |
| "variable_sources": { |
| "z": "geopotential_500", |
| "t": "temperature_850", |
| "t2m": "2m_temperature", |
| "u10": "10m_u_component_of_wind", |
| "v10": "10m_v_component_of_wind" |
| }, |
| "input_steps": 1, |
| "output_steps": 1, |
| "normalization": "ClimODE min-max normalization; source statistics are loaded from the configured static directory", |
| "uncertainty_output": "mean and standard deviation fields when use_uncertainty is enabled" |
| }, |
| "configuration_sources": [ |
| "conf/config.yaml", |
| "model/climode.py", |
| "scripts/data_loader.py", |
| "scripts/train.py" |
| ] |
| } |
|
|
