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EOFs Cookbook

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This Project Pythia Cookbook covers empirical orthogonal function analysis and its application to climate data.

Motivation

Empirical orthogonal function (EOF) analysis is an essential tool for studying the variability of the atmosphere-ocean system. Meteorological and oceanographic data is noisy and multidimensional, but an EOF analysis allows us to pull out patterns from the data that might otherwise be difficult to find. The goal of this cookbook is to provide background and context to the analysis alongside practical examples of carrying out the analysis using Python packages.

Authors

Robert Ford

Contributors

Structure

This cookbook currently has one section that covers the basics of EOF analysis.

Foundations

This section includes two notebooks:

  • Introduction to EOFs
  • Finding Climate Modes with EOFs

Running the Notebooks

You can either run the notebook using Binder or on your local machine.

Running on Binder

The simplest way to interact with a Jupyter Notebook is through Binder, which enables the execution of a Jupyter Book in the cloud. The details of how this works are not important for now. All you need to know is how to launch a Pythia Cookbooks chapter via Binder. Simply navigate your mouse to the top right corner of the book chapter you are viewing and click on the rocket ship icon, (see figure below), and be sure to select “launch Binder”. After a moment you should be presented with a notebook that you can interact with. I.e. you’ll be able to execute and even change the example programs. You’ll see that the code cells have no output at first, until you execute them by pressing {kbd}Shift+{kbd}Enter. Complete details on how to interact with a live Jupyter notebook are described in Getting Started with Jupyter.

Running on Your Own Machine

If you are interested in running this material locally on your computer, you will need to follow this workflow:

  1. Clone the https://github.com/ProjectPythia/eofs-cookbook repository:

     git clone https://github.com/ProjectPythia/eofs-cookbook.git
  2. Move into the eofs-cookbook directory

    cd eofs-cookbook
  3. Create and activate your conda environment from the environment.yml file

    conda env create -f environment.yml
    conda activate eofs-cookbook-dev
  4. Move into the notebooks directory and start up Jupyterlab

    cd notebooks/
    jupyter lab

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Cookbook covering empirical orthogonal function (EOF) analysis and examples of its application to geoscientific data

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