The different morphologies of lightning channels are caused by different electrical environments within the cloud, the charge distribution determines the lightning channel morphology, and the lightning morphology can reflect the charge structure to some extent. The distribution of charges is mainly determined by the dynamics and microphysical conditions in clouds, and turbulence plays a significant role in the distribution of charges. Due to the dependence of lightning morphology on the distribution of thunderstorm charges, which is regulated by thunderstorm dynamic effects, a relationship can be established between lightning morphology and thunderstorm dynamic effects. In this study, the lightning channel was obtained from three-dimensional radiation source localization data from the Lightning Mapping Array at the Langmuir Laboratory of the New Mexico Institute of Mining and Technology. The fractal dimension was used to characterize the complexity of lightning channels, which was calculated by the box-counting method. The S-band dual-polarization Doppler radar data was used to estimate the cube root of the eddy dissipation rate (EDR, the EDR was estimated using the Python Turbulence Detection Algorithm). The EDR and radar radial velocity were used to represent the thunderstorm dynamic characteristics. Superimposing EDR and radar radial velocities with LMA radiation sources, our analysis shows that the overall morphology and detailed morphology of the lightning channel correspond to different EDR characteristics. Lightning with complex channel morphology has a larger average FD and occurs in regions with large EDRs. In single lightning events, channels that extend directly within a certain height range without significant bifurcation and turning tend to propagate in the direction of decreasing EDRs, while channel bifurcations and turns usually occur in regions with large radial velocity gradients and large EDRs. This study shows the relationship between channel morphology and thunderstorm dynamics and provides a new method for the direct application of channel-level localization data to understand thunderstorm dynamics characteristics.
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Li et al. (2024) studied this question.
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