Investigating GAIM's Capability to Ingest Data of Ionospheric Irregularities via Walker Satellite Constellations

GAIM is a modularized physics based data assimilation model, which ingests data from multiple data sources. One data source is slant total electron content (TEC) from a ground station network to satellites, and along the occultation path between multiple satellites. This study examines GAIM's capability to sense a depleted region in the ionosphere, overlaid on an IFM electron density grid, from simulated satellite constellations ingesting the slant TEC values into GAIM. Satellite constellations were developed in an extension of MATLAB called STK. A real ground station network, generated from IGSS, was ingested into STK, to compute access times to the satellite constellation, and use the access data to compute the slant TEC values on the perturbed IFM grid. It was discovered that a Walker constellation would give the most frequent revisit time to the depleted region, which corotate with the Earth, capturing both the day and nightside ionosphere throughout the evaluation period (96 hrs). The size of the feature was varied along with the number of satellites in the Walker constellation. 25 different scenarios with these parameters varied were created to determine the sensitivity of GAIM to sense the feature. A simple heuristic algorithm was applied comparing the truth data, in this case the perturbed IFM grid, to the GAIM output in each scenario for the depleted grid points only.