An 11-year study on the characteristic parameters of negative cloud-to-ground multiple ground strike point lightning flashes in Guangdong Province of China

Abstract

This study aims to comprehensively and deeply analyze characteristic parameters of negative cloud-to-ground (CG) multiple ground strike point (GSP) lightning flashes for designing and optimizing lightning protection systems. Thus, based on the RS data from the Guangdong lightning location system (GDLLS), the lightning characteristic parameters were extracted from RSs detected between 2010 and 2020 by the k-means clustering algorithm developed based on Python. The attention is focused on the lightning current, the number of GSPs per flash, the number of RSs per GSP, and the interval time between RSs contacting the same GSP, and is to distinguish characteristic parameters in the first and subsequent GSP. In addition, spatial visualization of lightning characteristic parameters was completed through the Geopandas library in Python. The correlation between CG flash density traditionally used to assess lightning risk and characteristic parameters of multiple GSP lightning flashes was analyzed. The lightning current, interval time, and GSP correlate positively with CG flash density, while RS is negatively correlated. The aerosol content and lightning leader channel charge in different regions explain this phenomenon.