Assimilative Mapping of Geospace Observations (AMGeO): Data Science Tools for Collaborative Geospace Systems Science Journal Article uri icon

Overview

abstract

  • 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.

publication date

  • June 23, 2020

has restriction

  • hybrid

Date in CU Experts

  • November 11, 2020 11:18 AM

Full Author List

  • MATSUO T

author count

  • 1

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