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Introduction to data assimilation and the EnKF

Jump right in using one of these cloud computing providers:

  • Open In Colab (requires Google login)
  • Binder (no login but can be slow to start)


  • Interactive (Jupyter notebook)
  • Contains theory, code (Python), and exercises.
  • Recommendation: work in pairs.
  • Each tutorial takes ≈75 min.
  • The tutor will circulate to assist with the exercises,
    and summarize each section after you have worked on them.

Instructions for working locally

You can also run these notebooks on your own (Linux/Windows/Mac) computer. This is a bit snappier than running them online.

  1. Prerequisite: Python 3.7.
    If you're an expert, setup a python environment however you like. Otherwise: Install Anaconda, then open the Anaconda terminal and run the following commands:

    conda create --yes --name my-env python=3.7
    conda activate my-env
    python --version

    Ensure the printed version is 3.7.
    Keep using the same terminal for the commands below.

  2. Install:

    • Download and unzip (or git clone) this repository (see the green button up top)
    • Move the resulting folder wherever you like
    • cd into the folder
    • Install requirements:
      pip install -r path/to/requirements.txt
  3. Launch the Jupyter notebooks:

    • Launch the "notebook server" by executing:
      This will open up a page in your web browser that is a file navigator.
    • Enter the folder DA-tutorials/notebooks, and click on a tutorial (T1... .ipynb).