seed: 2026
data:
  path: data/fuxi_ocean_tiles.npz
  format_version: fuxi_ocean_sampled_tiles_v2
  input_shape: [4, 105, 2160, 4320]
  atmosphere_shape: [5, 2160, 4320]
  output_shape: [105, 2160, 4320]
  global_height: 2160
  global_width: 4320
  history_steps: 4
  ocean_channels: 105
  atmosphere_channels: 5
  time_step_hours: 6
  tile_height: 16
  tile_width: 16
  tile_overlap: 4
  train_samples: 4
  test_samples: 2
  depth_levels_m: [0, 2, 4, 6, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 200, 300, 400, 500, 600, 800, 1000, 1250, 1500]
model:
  embed_dim: 24
  patch_size: 2
  encoder_levels: 2
  attention_layers: 2
  attention_heads: 4
  epsilon: 0.000001
training:
  epochs: 1
  batch_size: 1
  learning_rate: 0.0005
  weight_decay: 0.00001
  multistep_rollout: 2
runtime:
  device: auto
  ddp_backend: gloo
  num_threads: 2
inference:
  rollout_steps: 3
paper_model:
  paper_determined:
    input_shape: [4, 105, 2160, 4320]
    atmosphere_shape: [5, 2160, 4320]
    output_shape: [105, 2160, 4320]
    ocean_channel_groups: {S: 26, T: 26, U: 26, V: 26, SSH: 1}
    atmosphere_variables: [U10M, V10M, MSL, T2M, D2M]
    shared_convolutional_patch_encoder: true
    spatiotemporal_prior_network: true
    history_fusion: four encodings concatenated then 1x1 convolution
    low_resolution_attention: stacked attention with AdaLN and FFN
    shared_transposed_convolution_decoder: true
    skip_connections: true
    depth_dependent_land_sea_mask: true
    loss: latitude-weighted Charbonnier
    training_stages: single-step pretraining then multi-step fine-tuning
    metrics: [latitude-weighted RMSE, MBE, persistence]
  missing_architecture:
    patch_size: MISSING
    hidden_width: MISSING
    attention_layer_count: MISSING
    attention_head_count: MISSING
    exact_prior_network: MISSING
    normalization_statistics: MISSING
    optimizer_and_schedule: MISSING
    batch_size_and_epochs: MISSING
    multistep_finetuning_horizon: MISSING
  rollout_steps: 40
  time_step_hours: 6
paths:
  checkpoint: result/checkpoints/fuxi_ocean.pt
  training_metrics: result/training/metrics.json
  inference: result/output/predictions.npz
  inference_metadata: result/output/metadata.json
  evaluation_metrics: result/evaluation/metrics.json
  evaluation_plot: result/evaluation/lead_metrics.png