| project: | |
| name: PBL-Emulator | |
| format_version: "1.0" | |
| seed: 19 | |
| independent_code_license: Apache-2.0 | |
| paper_specification: | |
| title: Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model | |
| doi: 10.5194/gmd-12-4261-2019 | |
| dimensions: {input: 16, levels: 17, variables_per_level: 5} | |
| output_variables: [U, V, W, tk, QVAPOR] | |
| architectures: {FFN_hidden_dense: 34, hierarchical_hidden_dense_per_level: 3, width: 16} | |
| training: {optimizer: Adam, learning_rate: 0.001, epochs: 1000, batch_size: 64, early_stopping_patience: 10} | |
| temporal_protocol: "3-hourly input and same-timestamp diagnostic output" | |
| engineering_assumptions: | |
| default_architecture: HAC | |
| synthetic_data: "structured engineering data, not WRF observations or paper data" | |
| split: "chronological 70/15/15 percent" | |
| vertical_order: bottom_to_top | |
| paths: | |
| data: data/pbl_emulator_synthetic.npz | |
| checkpoint: result/checkpoints/pbl_emulator.pt | |
| training_metrics: result/training/metrics.json | |
| predictions: result/output/predictions.npz | |
| evaluation_metrics: result/evaluation/metrics.json | |
| figure: result/evaluation/profiles.png | |
| data: | |
| samples: 768 | |
| seed: 7 | |
| interval_hours: 3 | |
| model: | |
| architecture: HAC | |
| width: 16 | |
| levels: 17 | |
| output_variables: 5 | |
| training: | |
| epochs: 6 | |
| batch_size: 64 | |
| learning_rate: 0.001 | |
| early_stopping_patience: 10 | |
| seed: 19 | |
| resume: false | |
| num_workers: 0 | |
| paper_model: | |
| epochs: 1000 | |
| batch_size: 64 | |
| width: 16 | |