nasa/ASDC_Data_and_User_Services: v0.1.0
Abstract
v0.1.0 (2026-01-30) - Initial Release Overview This is the first public release of the ASDC Data and User Services repository. This release introduces the core mission-focused structure and provides Jupyter notebooks, tutorials, and code examples demonstrating how to access, analyze, and visualize NASA Earth science data from the Atmospheric Science Data Center (ASDC). Highlights This initial release includes notebooks and resources for multiple NASA missions and use cases: Mission-Specific Notebooks, including TEMPO - Tutorials demonstrating access and analysis of TEMPO atmospheric composition data, including lightning event analysis DSCOVR EPIC - Exploration and visualization of EPIC UV Aerosol Index (UVAI) data, including examples from 2023 AGU poster CALIPSO - Tutorial for CALIPSO Narrow Field-of-View (NVF) data products and ozone number density data MOPITT - Examples using MOPITT CO mixing ratio products PREFIRE - Virtual datacube notebook and Level-2 cloud product visualization examples Workshop & Training Materials ARSET Training - Multiple notebooks from Applied Remote Sensing Training (ARSET) workshops, including ArcGIS Image Service integration examples STAQS Workshop - Notebooks from the Satellite-based Tools for Air Quality Science workshop WNA-Backtraj Project - Scripts for back-trajectory analysis Developer Resources Pre-commit hooks for notebook quality control Automated github.io site using Quarto with mission-organized structure Dependabot integration for automated dependency updates 📚 Documentation Reviewed notebooks are published as a browsable documentation site with: Mission-organized sections with index pages Source links in sidebar for easy GitHub navigation Workshop/tutorial categorization 👥 Contributors Thank you to all contributors who made this initial release possible: @IngridGS, @danielfromearth, @hazemmahmoudnasa, @ank1m, @gmojica-nasa, @LaramieDPlott Full Changelog: https://github.com/nasa/ASDC_Data_and_User_Services/commits/v0.1.0
Fields of Study & Subjects
Atmospheric aerosols and clouds
Scientific Computing and Data Management
Computational Physics and Python Applications
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 30 January 2026