Abstract
One of the most interesting attributes of Lightning Location Systems (LLSs) data is that they can be analyzed in several ways according to the objectives of the study. However, the quality of the data is governed by the system performance and has some limitations when analyzed at different temporal/spatial scales, and these limitations will depend on the analysis method. This work focuses on approaches to minimize the variations associated with LLS performance. In this way, specific network configurations for the Brazilian Lightning Detection Network (BLDN) were obtained through the reprocessing of selected sensor data, resulting in three distinct datasets. Each dataset was then evaluated using different procedures: trimmed flash (exclusion of low current discharges), thunderstorm days (TDs), and thunderstorm hours (THs). The comparison between TDs obtained from the LLS and TDs available from surface stations shows consistent results with a good correlation of those datasets. An 11-yr analysis of BLDN data also shows that improvement (over time) of the system sensitivity has led to the detection of an increasing number of low peak current events. By eliminating low peak current discharges (less than 19 kA), the sensitivity variation was significantly reduced, partially “normalizing” long-term performance. TDs and THs were the most effective method to normalize temporal variations of the lightning activity, overcoming most of the network performance variations. From the spatial perspective, TDs and THs also seem to produce the most reliable lightning distribution. These results might guide long-term temporal and spatial analysis of lightning data, providing a more stable approach that is independent of system performance.
