LAUSR

Abstract In this paper, the wavelet packet transform (WPT) is applied to analyze the time-frequency features of three kinds of lightning events (the cloud pulse, the return stroke and the stepped leader) and a new identification method based on WPT is proposed. The magnetic-field data used in this paper were recorded by Nanjing Lightning Location Network in 2018. Firstly, the wavelet spectra of three typical lightning events are given and it is found that spectral ranges of these three events are different. The predominant radiation frequency of the stepped leader is the highest and that of the return strokes is the lowest. A total of 232 cloud pulses, 876 return strokes and 373 stepped leaders are analyzed by WPT in order to investigate their behavior in time-frequency domain. The statistical result shows that the cloud pulse, return stroke and stepped leader radiate predominantly in the frequency range 9–56 kHz, 2–14 kHz and 52–236 kHz, respectively. According to the energy distribution characteristics, three indices are proposed to distinguish the different lightning events. It is found that the recognition rate of return stroke is 91% and that of stepped leader is up to 93%.