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Assimilative Mapping of Geospace Observations (AMGeO): Data Science Tools for Collaborative Geospace Systems Science
University of Colorado Boulder

Corresponding Author:tomoko.matsuo@colorado.edu

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The most dynamic electromagnetic energy and momentum exchange processes between the upper atmosphere and the magnetosphere take place in the polar ionosphere, as evidenced by the aurora. Accurate specification of the constantly changing conditions of high-latitude ionospheric electrodynamics has been of paramount interest to the geospace science community. In response this community’s need for research tools to combine heterogeneous observational data from distributed arrays of small ground-based instrumentation operated by individual investigators with global geospace data sets, an open-source Python software and associated web-applications for Assimilative Mapping of Geospace Observations (AMGeO) are being developed and deployed (https://amgeo.colorado.edu). AMGeO provides a coherent, simultaneous and inter-hemispheric picture of global ionospheric electrodynamics by optimally combining diverse geospace observational data in a manner consistent with first-principles and with rigorous consideration of the uncertainty associated with each observation. In order to engage the geospace community in the collaborative geospace system science campaigns and a science-driven process of data product validation, AMGeO software is designed to be transparent, expandable, and interoperable with established geospace community data resources and standards. This paper presents an overview of the AMGeO software development and deployment plans as part of a new NSF EarthCube project that has started in September 2019.