Identifying Pc2 Geomagnetic Pulsation through Magnetotelluric Data Quality Analysis in Dead Band Frequencies

Identifying geomagnetic pulsations is crucial for monitoring and issuing early warnings of space weather hazards that threaten modern technological infrastructure. This study examines the relationship between variations in magnetotelluric data quality and geomagnetic disturbances, aiming to develop an early space weather warning system utilizing existing magnetotelluric station networks. Magnetotelluric surveys measure natural electromagnetic signals to study subsurface structures, but signal quality in the 0.1–10 Hz frequency range—known as the dead band—is typically poor during geomagnetically quiet periods due to weak source fields. Geomagnetic disturbances significantly enhance signal strength in this band, markedly improving measurement quality. We developed a parameter called the linearity ratio, based on electromagnetic field linearity, to automatically detect geomagnetic disturbances. Additional metrics including phase differences and energy are used to comprehensively monitor data quality changes. Compared to traditional methods, this approach requires minimal computational resources, enables real-time monitoring, directly utilizes existing magnetotelluric infrastructure, and provides physically meaningful indicators. Analysis of two representative events using data from the Memambetsu station in Japan demonstrates that this method reliably identifies geomagnetic activity with minute-scale temporal resolution. Geomagnetic storms comprise initial, main, and recovery phases, with the main phase posing the greatest threat to critical infrastructure. Our approach complements existing geomagnetic storm forecasts by detecting the initial phase, providing early warning before the most hazardous conditions develop. This offers a cost-effective space weather monitoring solution by repurposing established ground-based electromagnetic observation networks.