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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)

Overview

  • 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>=3.6.
    If you're not a python expert:
    1a. Install Python via Anaconda.
    1b. Use the Anaconda terminal to run the commands below.
    1c. (Optional) Create & activate a new Python environment. If the installation (below) fails, try doing step 1c first.

  2. Install:
    Run these commands in the terminal (excluding the $ sign):
    $ git clone https://github.com/nansencenter/DA-tutorials.git
    $ pip install -r DA-tutorials/requirements.txt

  3. Launch the Jupyter notebooks:
    $ jupyter-notebook
    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).

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Course on data assimilation (DA)

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  • Jupyter Notebook 78.4%
  • Python 21.1%
  • Shell 0.5%