Linking Broadband Magnetotelluric Impedance, Magnetic Variations, and Geoelectric Field Dynamics in Severe Storms

Geomagnetically induced currents pose a well-recognized risk to ground-based technological systems during periods of intense geomagnetic activity. A key step in quantifying this risk is the reconstruction of the storm-time geoelectric field, which is controlled by the electrical conductivity structure of the subsurface. Although long-period magnetotelluric (MT) surveys provide optimal constraints for this purpose, many regions are covered primarily by legacy broadband MT datasets acquired for geological investigations and rarely exploited in a space-weather context. In this study, we investigate whether archived broadband MT data can be effectively used to estimate geoelectric fields relevant for GIC studies. We focus on the two most severe geomagnetic storms of 2024 (May and October), combining a broadband MT impedance tensor derived from three years of observations at the Gargano station (southern Italy) with 1 Hz magnetic field measurements from the nearby Duronia geomagnetic observatory. The analysis targets the 2–8000 s period range, which dominates GIC generation. Modeled electric field components are independently evaluated by comparison with storm-time electric field measurements decomposed into intrinsic mode functions using Empirical Mode Decomposition. The consistency between modeled and observed signals is assessed through Mutual Information analysis, revealing a statistically significant correspondence, particularly during storm main phases. These results show that legacy broadband MT datasets can provide quantitative and physically meaningful estimates of storm-time geoelectric fields. Existing MT archives therefore offer a valuable and cost-effective opportunity for preliminary GIC hazard assessment and retrospective space weather analyses, especially in regions lacking dedicated long-period MT coverage. This research was funded by the Space It Up! project funded by the Italian Space Agency, ASI, and the Ministry of University and Research, MUR, under contract n. 2024-5-E.0—CUP n.I53D24000060005.