Cookbooks Gallery
Pythia Cookbooks provide example workflows on more advanced and domain-specific problems developed by the Pythia community. Cookbooks build on top of skills you learn in Pythia Foundations.
Cookbooks are created from Jupyter Notebooks that we strive to binderize so each Cookbook can be executed in the cloud with a single click from your browser, but in some instances executing a Cookbook will require running the notebooks locally.
Interested in contributing a new Cookbook or contributing to an existing Cookbook? Great! Please see the Project Pythia Cookbook Contributor’s Guide, and consider opening a discussion under the Project Pythia category of the Pangeo Discourse.

CESM LENS on AWS Cookbook
Author: the Project Pythia Community
Notebooks developed to demonstrate analysis of CESM LENS data publicly available on Amazon S3 (us-west-2 region) using Xarray and Dask.

CMIP6 Cookbook
Author: Ryan Abernathey, Henri Drake, Robert Ford
Examples of analysis of Google Cloud CMIP6 data using Pangeo tools.

HRRR-AWS-Cookbook
Author: the Project Pythia Community
A cookbook for working with AWS-served HRRR model output data.

Radar Cookbook
Author: Max Grover, Zachary Sherman
A cookbook meant to work with various weather radar data.
Intake Cookbook
Author: James Morley
This cookbook shows examples of using and creating Intake catalogs to access data.



xbatcher for Machine Learning Part 1
Author: Christopher Dupuis
A complete workflow for a convolutional neural network using xbatcher.