| project: | |
| name: PrecipDD | |
| format_version: precipdd_v1 | |
| seed: 23 | |
| license: Apache-2.0 | |
| paths: | |
| data: data/daily_precip_anomaly.npz | |
| checkpoint: result/checkpoints/precipdd.pt | |
| training_metrics: result/training/metrics.json | |
| predictions: result/output/predictions.npz | |
| evaluation_metrics: result/evaluation/metrics.json | |
| comparison_figure: result/evaluation/comparison.png | |
| data: | |
| layout: NCHW | |
| input_shape: [1, 55, 160] | |
| latitude_range: [-60.0, 75.0] | |
| latitude_note: 55 engineering grid centers at 2.5 degree spacing; the paper text reports inconsistent endpoints alongside 55 points | |
| longitude_range: [0.0, 397.5] | |
| longitude_note: 0-360 E plus repeated 0-40 E extension | |
| normalization: daily climatology anomaly divided by zonal-mean anomaly standard deviation at each latitude | |
| train_samples: 96 | |
| validation_samples: 32 | |
| test_days_per_year: 6 | |
| test_years: [1980, 2020] | |
| synthetic_members: 8 | |
| paper_members: 80 | |
| paper_period: [1850, 2100] | |
| paper_train_days: 730000 | |
| paper_validation_days: 146000 | |
| model: | |
| filters: [8, 8, 16, 16, 16] | |
| kernel_size: 3 | |
| dense_units: 32 | |
| conv_activation: tanh | |
| dense_activation: sigmoid | |
| output_activation: linear | |
| expected_feature_shape: [16, 14, 40] | |
| flattened_features: 8960 | |
| training: | |
| ensemble_members: 2 | |
| paper_ensemble_members: 5 | |
| epochs: 3 | |
| batch_size: 8 | |
| learning_rate: 0.001 | |
| l2_weight_decay: 0.0001 | |
| loss: MAE | |
| optimizer: Adam | |
| initialization: Xavier-uniform | |
| num_workers: 0 | |
| runtime: | |
| device: auto | |
| ddp_backend_gpu: nccl | |
| ddp_backend_cpu: gloo | |
| evaluation: | |
| emergence_threshold_c: 0.42 | |
| occlusion_patch: 7 | |
| occlusion_stride: 8 | |
| occlusion_max_days: 12 | |