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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 browswer. See documentation here for details. In some instances executing a Cookbook will require downloading the Notebook to your local laptop or desktop as described here.

Interested in contributing a new Cookbook or contributing to an existing Cookbook? Great! Please see the Project Pythia Contributor’s Guide and Cookbook-specific information here.

Submit a new Cookbook

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.

climate intake-esm
nightly-build Binder

CMIP6 Cookbook

Author: Ryan Abernathey, Henri Drake, Robert Ford


Examples of analysis of Google Cloud CMIP6 data using Pangeo tools.

climate intake-esm
nightly-build Binder

HRRR-AWS-Cookbook

Author: the Project Pythia Community


A cookbook for working with AWS-served HRRR model output data.

AWS-cloud HRRR-model xarray zarr
nightly-build Binder

Radar Cookbook

Author: Max Grover, Zachary Sherman


A cookbook meant to work with various weather radar data.

Py-Art radar
nightly-build Binder
NCAR
Unidata
UAlbany

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© 2022. By the Project Pythia Community. Last updated on 10 August 2022.

This material is based upon work supported by the National Science Foundation under Grant Nos. 2026863 and 2026899. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.