File size: 1,495 Bytes
702a3cf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | 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
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