About#
Mission#
Our mission is twofold:
To support collaborative, reproducible and efficient data science in the SRM research community
To equip researchers with computational resources in the cloud
Platform Overview#
This Jupyter Book accompanies ReflectiveCloud - a powerful Jupyter notebook server providing free compute power in a Pangeo Python environment on cloud computing resources, available to the SRM research community.
Access to Platform
To apply for access, fill out the form here.
For a quick guide to starting up your server - see this video.
Available Resources#
This book contains several initial resources to get you started:
Data & Code Examples#
GeoMIP & CMIP Data: Code examples for working with data stored on the Earth System Grid (ESGF)
SAI Simulations: A new preprocessed archive of common SAI simulations
AWS ARISE: Code examples for working with the Amazon Web Services (AWS) ARISE data store
How to Contribute#
Contributions are very welcome! 🎉
Contribution Workflow#
Upload your content to the appropriate example folder in our GitHub repository
Create a pull request with a clear description of what you’re adding
Follow our guidelines for code examples, documentation, and tutorials
What We’re Looking For#
Code examples and workflows for SRM research
Tutorials and how-to guides
Documentation improvements and clarifications
Bug reports and feature suggestions
Data processing examples and best practices
Getting Started#
Open pull requests or create issues on our GitHub repository
Help this book grow with your expertise and experience
Share your knowledge with the SRM research community
Inspiration & Resources#
This book was inspired by the CryCloud project. Check out their guide for useful information on contributing to GitHub-based open source projects like this one.
Note#
This book is a work in progress and we’re actively looking for contributions from the community to help it grow! 🌱
Last updated: Aug 13, 2025