Impact of geomagnetic storms on ionospheric TEC at high latitude stations: a comparative analysis of GPS observations and the IRI-2016 model

This work investigates the effects of two intense geomagnetic storms on Total Electron Content (TEC) in the ionosphere at high latitude stations situated in different hemispheres. Using ground-based GNSS receivers and the IRI-2016 model, the study analyzes TEC data collected from Kerguelen station (55.78°S, 133.44°E) in the southern hemisphere and Sodankyla station (63.83°N, 118.27°E) in the northern hemisphere. Substantial TEC fluctuations were observed during both geomagnetic storms, with more pronounced variations recorded over the Sodankyla station. Interestingly, during these storm events, nighttime TEC closely reached the daytime TEC levels, implying the inflow of additional plasma from higher latitudes in to the region. Through a comparative analysis using change in TEC (dTEC), it was found that Kerguelen station, situated farther from the geomagnetic polar region, exhibited more significant TEC alterations compared to the closer, Sodankyla station. While the observational measurement exhibited a positive ionospheric effect to the intense storms at both stations, IRI-2016 model showed negative responses during the initial, main, and recovery phases. Despite the significant correlation between IRI-TEC and GPS-TEC, error percentage and Root Mean Square Deviation (RMSD) plots represented that the IRI model struggled to accurately capture TEC fluctuations across various storm phases. Furthermore, the study examined the relative contributions of storm-induced changes in ionospheric O and N2 using the global map of Oxygen to Nitrogen ratio (O/N2) obtained from Thermosphere/Ionosphere Plasmasphere (CTIP) model, revealing a higher impact over Kerguelen station in comparison to Sodankyla station. Overall, this work helps to advance our understanding of geomagnetic storms impact on ionospheric TEC at high latitudes and highlights the current limitations in modeling approaches for accurately predicting ionospheric behavior during such dynamic events.