Analysis of Polar Ionosphere Anomaly of Interplanetary Shock Events Based on GNSS TEC

• Published in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Main Authors: Ran Cui, Jian Kong, Yibin Yao, Chen Zhou, Qingshan Shen, Qi Zhang, Jiachun An
• Format: Article in Journal/Newspaper
• Language: English
• Published: IEEE 2023
• Subjects: Global navigation satellite system (GNSS) total electronic content (TEC); interplanetary fast-forward shock; polar ionosphere anomaly; spatiotemporal characteristics; time-series analysis; Ocean engineering; TC1501-1800; Geophysics. Cosmic physics; QC801-809; Antarctic; The Antarctic; Antarc*
• Online Access: https://doi.org/10.1109/JSTARS.2023.3281591; https://doaj.org/article/d3434584404e45cab7acf72350a4a336

Using large-scope and high-accuracy global navigation satellite system (GNSS) ionospheric monitoring, this study considered the polar ionosphere anomaly morphology caused by an interplanetary shock event that occurred on September 12, 2014. First, we used the continuous observation data of GNSS stations in the Antarctic region to estimate the carrier TEC epochs variation (dTEC) that reflects ionospheric electron density changes, and the abnormal signals were extracted. Through sequence data analyses of longitudinal chain stations, we found that the influence range of this anomaly lies in the geomagnetic region between 65 $^\circ$ and 80 $^\circ$ S. Furthermore, latitude chain analyses revealed that with the continuous fluctuation of the solar wind flow pressure, the polar ionospheric geomagnetic 75 $^\circ$ S annular observation sequence gives a corresponding continuous fluctuation response with a range of 0.05–0.4 TECU and a westward anomaly trigger position. The average speed was close to the satellite speed during the study period, and it was determined that the anomaly occurred within an altitude region of 150–300 km. The physical mechanism of this anomaly is discussed in this article. Our results show that the GNSS dTEC and multisource data can accurately reflect the regional intensity, influence region, trigger source location, and velocity of the ionosphere anomaly.