On the performance of CARISMA – Akademik Vernadsky station Schumann resonance monitoring

Abstract

The main objective of this study is to evaluate the effectiveness of the CARISMA (Canadian Array for Realtime Investigations of Magnetic Activity) – Akademik Vernadsky station (65.25°S 64.25°W, Vernadsky) Extremely Low Frequency (ELF) induction magnetometer network as a planetary monitoring system for thunderstorm activity, with observation sites located in the Arctic and Antarctic regions, respectively. To achieve this, daily ELF records from Vernadsky and Fort Churchill (FCHU, 58.76°N 94.08°W) collected in January 2022 were processed and analyzed. For CARISMA, data from the FCHU site were used due to the better signal-to-noise ratio. The horizontal magnetic components of Schumann signals obtained at Vernadsky and FCHU underwent spectral and polarization processing. ELF transients were identified, and subsequent geolocation was performed as well. Both regular (quiet) thunderstorm activity periods and an unprecedented local amplification of lightning activity near the Hunga Tonga-Hunga Ha'apai volcano during its eruption on January 15, 2022, were studied. Throughout the quiet periods, ELF signal processing yielded similar characteristics of integral lightning activity derived from CARISMA and Vernadsky records, consistent with findings in the literature and previous investigations at the Vernadsky site. On the other hand, the analysis of Schumann spectra and ELF transients during the Tonga volcano eruption confirmed that most thunderstorms were concentrated within a relatively small area around the epicenter, validating the point source model for the global lightning center. This paper demonstrates that the CARISMA and Vernadsky magnetometer network is well-suited for establishing a global lightning activity monitoring and intense lightning geolocation system. Such a system can be employed to assess and study global temperature trends, monitor the growth of lightning activity in high latitudes, and detect terrestrial, atmospheric, and geospace disaster phenomena.

Keywords

• extreme low frequency
• global climate change
• lightning detection network
• space weather
• transient event