NOTE: This project was merged into the GOES-DL project.
Since 1975, Geostationary Operational Environmental Satellites (GOES) have provided continuous imagery and data on atmospheric conditions and solar activity (space weather). They have even aided in search and rescue of people in distress. GOES data products have led to more accurate and timely weather forecasts and better understanding of long-term climate conditions. The National Aeronautics and Space Administration (NASA) builds and launches the GOES, and the National Oceanic and Atmospheric Administration (NOAA) operates them [2].
GOES-DR is an open-source Python package that streamlines the process of reading Level 2 GOES R series satellite imagery. This toolkit enables efficient reading and extraction of snapshot data segments directly from NetCDF4 files produced by GOES-R Series satellites [3].
- GOES 4th Generation (GOES-16 to GOES-18): Also known as the R to U Series, these satellites offer advanced imagery and atmospheric measurements with better spatial, spectral, and temporal resolution [3].
See NOAA Geostationary Operational Environmental Satellites (GOES) 16, 17 & 18 and NOAA GOES on AWS (CICS) for information on the GOES-R Series data available from NOAA on AWS. You can find much more detailed information about GOES-R Series data from NOAA's Geostationary Operational Environmental Satellites - R Series.
- NOAA AWS Cloud Archive: GOES-16 to GOES-18 data and GridSat-B1 Climate Data Record are accessible via the NOAA archive hosted on AWS.
Toolset for reading Level 2 GOES R series satellite imagery. Enables the extraction of snapshot data segments from NetCDF4 files containing GOES R series (GOES-16 to GOES-18) satellite imagery.
Keywords: goes, satellite, satellite-dataset, satellite-imagery, satellite-imagery-analysis, satellite-imagery-python, satellite-data, noaa, noaa-satellite, ncei, unidata, unidata-netcdf, netcdf, netcdf4, aws, open-data, open-source, open-datasets, xarray
Contributions to GOES-DR are welcome! If you'd like to contribute:
- Fork the repository.
- Create a new branch for your feature or bugfix.
- Open a pull request with a description of your changes.
Please make sure to include tests for any new functionality.
- Python 3.9+
This project is licensed under the MIT License - see the LICENSE file for details.
This package relies on data provided by NOAA’s NCEI and NOAA’s archive on AWS.
When using GOES-DR in any research, publication or website, please cite this package as:
Villamayor-Venialbo, W. (2025): GOES-DR: A Python package for reading GOES R Series Level 2 Imagery datasets (Version 0.0.0) [Software]. GitHub. git:wvenialbo/GOES-DR, [indicate access date].
Dataset Citation:
For Cloud and Moisture Imagery Products (CMIP), please cite the following:
GOES-R Algorithm Working Group, and GOES-R Series Program (2017): NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2 Cloud and Moisture Imagery Products (CMIP). [indicate subset used]. NOAA National Centers for Environmental Information, doi:10.7289/V5736P36, [access date].
For other products, please, visit NOAA National Centers for Environmental Information.
For issues, questions, or requests, feel free to open an issue on this repository or contact the author, wvenialbo at gmail.com.
- Brian Blaylock's goes2go: Download and process GOES-16 and GOES-17 data from NOAA's archive on AWS using Python. (readthedocs)
- Joao Henry's GOES: Python package to download and manipulate GOES-16/17/18 data.
- GOES-R Algorithm Working Group, and GOES-R Series Program (2017): NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2 Cloud and Moisture Imagery Products (CMIP). [indicate subset used]. NOAA National Centers for Environmental Information, doi:10.7289/V5736P36, [access date].
- GOES History. GOES-R Website, https://www.goes-r.gov/mission/history.html, retrieved on 2024.
- GOES-R Series Data Products. GOES-R Website, https://www.goes-r.gov/products/overview.html, retrieved on 2024.
- NOAA Big Data Program, NOAA Open Data Dissemination Program, https://github.com/NOAA-Big-Data-Program/bdp-data-docs, retrieved on 2024.
- Beginner’s Guide to GOES-R Series Data: How to acquire, analyze, and visualize GOES-R Series data, Resources compiled by GOES-R Product Readiness and Operations, Satellite Products and Services Division, National Oceanic and Atmospheric Administration. PDF. Last Updated on May 23, 2024, retrieved on 2024.
- GOES-R Series Data Book, GOES-R Series Program Office, Goddard Space Flight Center, National Aeronautics and Space Administration. PDF, retrieved on 2024.