Snow scientists have identified a need for better ways to share research outputs and data, following NASA's push for more open and collaborative science. While many Python scripts and tutorials for studying snow exist on GitHub, a centralized resource is still needed. This presentation describes SnowPit, a collaborative project that brings together snow scripts and tutorials in a single cloud-based location.

SnowPit is developing two key outputs: (i) a guide that explains best practices for sharing scientific research and code openly with the broader community, and (ii) a collection of tutorials that help researchers access and analyze snow data from multiple sources, including satellites, weather stations, and aircraft. These tools will help scientists study important snow measurements with greater ease, thereby lowering the barrier to understanding changes in water resources. Both the guide and the tutorial collection will be freely available to anyone.