_toc.yml

# Table of contents
# Learn more at https://jupyterbook.org/customize/toc.html

format: jb-book
root: intro
parts:
  - caption: Lorenz-96 and General Circulation Models
    chapters:
      - file: notebooks/L96-two-scale-description.ipynb
      - file: notebooks/gcm-analogue.ipynb
      - file: notebooks/gcm-parameterization-problem.ipynb
      - file: notebooks/estimating-gcm-parameters.ipynb
  - caption: Neural Networks with Lorenz-96
    chapters:
      - file: notebooks/intro_ML_and_NNs.ipynb
      - file: notebooks/L96_offline_training_NN.ipynb
      - file: notebooks/L96_online_implement_NN.ipynb
      - file: notebooks/L96_online_training_NN.ipynb
      - file: notebooks/Improving_Neural_networks.ipynb
      - file: notebooks/Neural-Network-Interpretation.ipynb
      - file: notebooks/constraints.ipynb
  - caption: Data Assimilation with Lorenz-96
    chapters:
      - file: notebooks/DA_demo_L96.ipynb
      - file: notebooks/Learning-DA-increments.ipynb
  - caption: Equation Discovery with Lorenz-96
    chapters:
      - file: notebooks/symbolic_methods_comparison.ipynb
      - file: notebooks/sindy_L96_2scale.ipynb
      - file: notebooks/symbolic_vs_nn_multiscale_L96.ipynb
  - caption: Other ML approaches for Lorenz-96
    chapters:
      - file: notebooks/random_forest_parameterization.ipynb
      - file: notebooks/GP_lorenz96.ipynb
      - file: notebooks/local_map_L96_and_Burgers.ipynb
      - file: notebooks/L96_ResNet_RNN.ipynb
  - caption: End Matter
    chapters:
      - file: notebooks/closing_remarks.ipynb
      - file: notebooks/citing.ipynb
      - file: bibliography.md