Ensemble Kalman filter tutorial

This repository is a practical of ensemble Kalman filter that is derived from DARC training course material for data assimilation. The practical is in the Jupyter notebook Controls_L96_Enkf_MFC.ipynb.

Running the Jupyter notebok

There are three ways to run the jupyter notebook:

Using binder

• Open the link for binder: https://mybinder.org/v2/gh/darc-reading/MFC_intro.git/HEAD

Using Google Colab

• Open the link for Google Colab: https://colab.research.google.com/github/darc-reading/MFC_intro/:
  • Adding these two lines at the start of the notebook

       !git clone https://github.com/darc-reading/MFC_intro.git
       %cd MFC_intro
    

On local laptop (Python version >= 3.8):

• obtain the code:
  • directly download the code as zip
  • using git: git clone https://github.com/darc-reading/MFC_intro.git
• change your working directory to MFC_intro
• create a virtual environment in your Python in your terminal: python -m venv mfc_enkf
• activate the virtual environment:
  • Linux/Mac source mfc_enkf/bin/activate
  • Windows command prompt: mfc_enkf/Scripts/activate.bat
  • Windows powershell: mfc_enkf/Scripts/Activate.ps1
• install dependencies: pip install -r requirements.txt
• open jupyter notebook: jupyter notebook