ELF-transients detected in the broadband recordings at the Hylaty station in Poland

Lightning acts as a natural antenna radiating electromagnetic (EM) waves in a wide frequency range. In the extremely low frequency (ELF) band (3 Hz - 3 kHz), lightning-induced EM waves suffer very weak attenuation while they propagate in the waveguide formed by the Earth’s surface and the lowest part of the ionosphere. These EM waves can travel around the Earth several times before losing most of their energy. This allows ELF-transients generated by powerful lightning discharges from around the globe to be detected at any observation site. We developed an algorithm that identifies ELF-transients in the broadband recordings at Hylaty, Poland (sampling frequency: 3004.81 Hz, antenna bandwidth: 0.02 Hz to 1.1 kHz) and finds their most probable source lightning discharge in the lightning database of the Word Wide Lightning Location Network (WWLLN) based on the technique described by Bór et al. (2022).Between July 2020 and April 2021 about 270,000 ELF-transients were found in the records from Hylaty. The most probable source of 160,000 transients was identified in the WWLLN database. Using this data set, we show that the propagation speed of broadband ELF-transients differ significantly when the propagation path is on the dayside or on the nightside of the Earth. It is also demonstrated that for lightning discharges close to Hylaty (d<2Mm), the timing and location accuracy of WWLLN has a large impact on the identification of the lightning source and on the inferred propagation speed. A convolutional neural network, trained with ELF-transients of known source location, was used to determine the distance to the lightning source in cases where the source lightning discharge could not be found in the WWLLN database. The average accuracy of the distance provided by the neural network is 700 km. No significant difference can be seen between the distribution of distances obtained by matching the source lightning stroke in the WWLLN database and that obtained using the neural network-based approach. Reference:Bór, J., Szabóné André, K., Bozóki, T., Mlynarczyk, J., Steinbach, P., Novák, A., and Lemperger, I. (2022): Estimating the Attenuation of ELF-Band Radio Waves in the Earth’s Crust by Q-Bursts. IEEE Transactions on Antennas and Propagation, 70, 8. https://doi.org/10.1109/TAP.2022.3161504