Model‐Based Analysis of Ionospheric TEC Disturbances Over China and Adjacent Regions During the May 2024 Super Geomagnetic Storm
Heng Xu, Wengeng Huang, Jiayue Yang, Hua Shen, Lei Zhang, Xin WangAbstract
This study uses observation data from multi‐constellation (GPS/GLONASS/Galileo/BeiDou) ground‐based Global Navigation Satellite Systems (GNSS) networks and a non‐integrated spherical harmonic function modeling methodology to develop an ionospheric Total Electron Content (TEC) model with high spatiotemporal resolution (1° × 1° in longitude and latitude, and 15 min in time) over China and adjacent regions. The response of regional ionospheric TEC during the May 2024 super geomagnetic storm was then investigated using this model. The results indicate that the model can accurately capture the spatiotemporal variation characteristics of regional ionospheric TEC during this geomagnetic storm. During the main and early recovery phases of the geomagnetic storm, positive and negative ionospheric disturbances occurred simultaneously. During the late recovery phases of the storm, long‐lasting negative ionospheric disturbances dominated, causing a substantial TEC decrease, with a maximum decrease of about 70 TECU and a relative decrease of up to 80%. The daytime ionospheric TEC on 12 May was almost comparable to the typical night‐time value. Additionally, ionospheric response exhibited east‐west differences. Furthermore, during certain periods of the superstorm's recovery phase, positive ionospheric disturbances occurred against an overall negative storm background at middle and low latitudes; this non‐locally generated disturbance spans 20°N–40°N with its center near 30°N (projected radius ∼10°), propagates westward at ∼140 ± 8 m/s, and shows no obvious spatial contraction but a gradual intensity weakening with differential total electron content decreasing from ∼30 TECU to 2∼3 TECU. These phenomena indicated that the ionosphere over China and adjacent regions experienced complex variations during this super geomagnetic storm.