Assimilative Mapping of Geospace Observations (AMGeO): Unified Global and Local Perspectives on High-latitude Ionospheric Electrodynamics

Abstract:

The most dynamic electromagnetic energy and momentum exchange processes between the upper atmosphere and the magnetosphere take place in the polar ionosphere. Accurate specification of the constantly changing conditions of high-latitude ionospheric electrodynamics has been of paramount interest to the geospace science community. Inspired by recent advancements in high-latitude geospace observing capabilities, the goal of our NSF EarthCube Data Capabilities: Assimilative Mapping of Geospace Observations (AMGeO) project is to develop and deploy an open-source Python software and associated web-applications that are interoperable with established geospace community data resources such as AMPERE, SuperDARN, and SuperMAG, so that heterogeneous observational data from distributed arrays of small ground-based instrumentation operated by individual investigators can be optimally combined with global geospace data. New capabilities released as AMGeO v2 will include the ability to assimilate AMPERE’s Iridium magnetometer data products without reliance on the conductance assumption, and to more rigorously track uncertainty through chains of data provenance. AMGeO helps us to unravel how fine-scale transient features of high-latitude ionospheric electrodynamics are embedded in large-scale structures and gain unified global and local perspectives on high-latitude ionospheric electrodynamics, such as how fine-scale transient features of plasma flows are embedded in large-scale convection and field-aligned current patterns. This paper presents an AMGeO case study for the St. Patrick’s Day storm on March 17 2015 to highlight the latest capabilities. The current version can be downloaded from GitHub after registering at https://amgeo.colorado.edu