Abstract
Tweek atmospherics are ELF/VLF pulse signals with frequency dispersion characteristics that originate from lightning discharges and propagate in the Earth-ionosphere waveguide over long distances. In this paper, we developed an automatic method to recognize tweek atmospherics and diagnose the lower ionosphere based on the machine learning method. The differences (automatic-manual) of each ionosphere parameter between the automatic method and the manual method are 0.07 2.73 km, 0.03 0.92 cm-3, and 91 1068 km for h, Ne, and d, respectively. Moreover, the automatic method is capable of recognizing higher harmonic tweek sferics as well. These evaluation results of the model suggest that the automatic method is a powerful tool to investigate the long-term variations of the lower ionosphere.
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