About AMGeO

What is AMGeO?

AMGeO is a collaborative data science platform for the geospace science community for bringing together a diverse set of heterogeneous geospace observations from NSF-funded facility programs and individual community users to obtain complete maps of high-latitude ionospheric electrodynamics for scientific discovery and space weather research. The platform is made of the AMGeO open-source software and web application services that facilitate the data acquisition and pre-processing steps that are otherwise prohibitively labor-intensive. It is developed at the University of Colorado Boulder by the AMGeO Team, with support from the NSF Earth Cube program.


The AMGeO open-source software is designed to streamline data access, collection, preprocessing, and quality control steps with data assimilation analysis steps to support accessible, reproducible and transparent data science practices in the geospace science community. AMGeO helps accelerate data science processes by transforming raw data into discovery enabling forms. AMGeO implements data assimilation analysis steps expanded, as summarized in Matsuo (ISSI Scientific Report Series, 2020), from the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) procedure originally developed by Richmond and Kamide (JGR, 1988). AMGeO's web application services facilitate the data acquisition of plasma drift data distributed from the SuperDARN Website, ground-based magnetometer data distributed from the SuperMAG Website, and space-based magnetometer data distributed from the AMPERE Website in the form expected by the AMGeO software.

Frequently Asked Questions


Please contact the AMGeO Team at for any questions.


AMGeO is supported by the NSF EarthCube grants ICER 1928403 to the University of Colorado Boulder, ICER 1928327 to the Virginia Tech, and ICER 1928358 to the Johns Hopkins University Applied Physics Laboratory. We are grateful for the community data providers (NASA SPDF, SuperMAG, SuperDARN, and AMPERE) for providing data for the community such that they can be used in AMGeO. Special thanks to SuperMAG, SuperDARN, and AMPERE for working with the AMGeO Team to establish API access to their data services.