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CMIP6 Cookbook

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This Project Pythia Cookbook covers examples of analysis of Google Cloud CMIP6 data using Pangeo tools.

Motivation

From the CMIP6 website:

The simulation data produced by models under previous phases of CMIP have been used in thousands of research papers ... and the multi-model results provide some perspective on errors and uncertainty in model simulations. This information has proved invaluable in preparing high profile reports assessing our understanding of climate and climate change (e.g., the IPCC Assessment Reports).

With such a large amount of model output produced, moving the data around is inefficient. In this collection of notebooks, you will learn how to access cloud-optimized CMIP6 datasets, in addition to a few examples of using that data to analyze some aspects of climate change.

Authors

Ryan Abernathey, Henri Drake, Robert Ford, Max Grover

Contributors

Structure

Foundations

This section includes three variations of accessing CMIP6 data from cloud storage.

Example workflows

There are currently four examples of using this data to

  • Estimate equilibrium climate sensitivity (ECS)
  • Plot global mean surface temperature under two different Shared Socioeconomic Pathways
  • Plot changes in precipitation intensity under the SSP585 scenario
  • Calculate changes in ocean heat uptake after regridding with xESMF

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/cmip6-cookbook repository:

     git clone https://github.com/ProjectPythia/cmip6-cookbook.git
  2. Move into the cmip6-cookbook directory

    cd cmip6-cookbook
  3. Create and activate your conda environment from the environment.yml file

    conda env create -f environment.yml
    conda activate cmip6-cookbook-dev
  4. Move into the notebooks directory and start up Jupyterlab

    cd notebooks/
    jupyter lab

At this point, you can interact with the notebooks! Make sure to check out the "Getting Started with Jupyter" content from the Pythia Foundations material if you are new to Jupyter or need a refresher.

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Examples of analysis of Google Cloud CMIP6 data using Pangeo tools

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