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Published July 23, 2019 | Supplemental Material + Published
Journal Article Open

Advantages of Geostationary Satellites for Ionospheric Anomaly Studies: Ionospheric Plasma Depletion Following a Rocket Launch

Abstract

In this study, we analyzed signals transmitted by the U.S. Wide Area Augmentation System (WAAS) geostationary (GEO) satellites using the Variometric Approach for Real-Time Ionosphere Observation (VARION) algorithm in a simulated real-time scenario, to characterize the ionospheric response to the 24 August 2017 Falcon 9 rocket launch from Vandenberg Air Force Base in California. VARION is a real-time Global Navigation Satellites Systems (GNSS)-based algorithm that can be used to detect various ionospheric disturbances associated with natural hazards, such as tsunamis and earthquakes. A noise reduction algorithm was applied to the VARION-GEO solutions to remove the satellite-dependent noise term. Our analysis showed that the interactions of the exhaust plume with the ionospheric plasma depleted the total electron content (TEC) to a level comparable with nighttime TEC values. During this event, the geometry of the satellite-receiver link is such that GEO satellites measured the depleted plasma hole before any GPS satellites. We estimated that the ionosphere relaxed back to a pre-perturbed state after about 3 h, and the hole propagated with a mean speed of about 600 m/s over a region of 700 km in radius. We conclude that the VARION-GEO approach can provide important ionospheric TEC real-time measurements, which are not affected by the motion of the ionospheric pierce points (IPPs). Furthermore, the VARION-GEO measurements experience a steady noise level throughout the entire observation period, making this technique particularly useful to augment and enhance the capabilities of well-established GNSS-based ionosphere remote sensing techniques and future ionospheric-based early warning systems.

Additional Information

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Received: 29 June 2019; Accepted: 20 July 2019; Published: 23 July 2019. Author Contributions: Conceptualization, G.S., A.K. and M.C.; methodology, G.S.; software, G.S.; validation, G.S., A.K., E.S., P.V., M.R., O.V., X.M. and M.C.; formal analysis, G.S.; investigation, G.S.; resources, A.K.; data curation, G.S.; writing—original draft preparation, G.S.; writing—review and editing, G.S., A.K., E.S., P.V., M.R., O.V., X.M. and M.C.; visualization, G.S.; supervision, A.K.; project administration, G.S.; and funding acquisition, G.S. and A.K. This research was supported by an appointment for G. Savastano to the NASA Postdoctoral Program at the NASA Jet Propulsion Laboratory, California Institute of Technology, administered by Universities Space Research Association through a contract with NASA. Portions of this research were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. This research was partially supported by the University of Rome "La Sapienza" through the PhD fellowship for M. Ravanelli and a competitive grant for starting PhD Candidates obtained by M. Ravanelli. G. Savastano thanks Balthasar Kenda for beneficial discussions. The authors declare no conflict of interest.

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Supplemental Material - remotesensing-11-01734-s001.pdf

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August 22, 2023
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