Estimates of the global electric circuit from global thunderstorm activity

The World Wide Lightning Location Network (WWLLN) has a global detection efficiency around 10%, however the network has been shown to identify 99% of thunderstorms (Jacobson, et al 2006, using WWLLN data from 2005). To create an estimate of the global electric circuit activity a clustering algorithm is applied to the WWLLN dataset to identify global thunderstorms from 2009 - 2013. The annual, seasonal, and regional thunderstorm activity is investigated with this new WWLLN thunderstorm dataset in order to examine the source behavior of the global electric circuit. From the clustering algorithm the total number of active thunderstorms is found every 30 minutes to create a measure of the global electric circuit source function. The clustering algorithm used is shown to be robust over parameter ranges related to real physical storm sizes and times. The thunderstorm groupings are verified with case study comparisons using satellite and radar data. It is found that there are on average 714 × 81 thunderstorms active at any given time. Similarly the highest average number of thunderstorms occurs in July (783 × 69) with the lowest in January (599 × 76). The annual and diurnal thunderstorm activity seen with the WWLLN thunderstorms is in contrast with the bimodal stroke activity seen by WWLLN. Through utilizing the global coverage and high time resolution of WWLLN, it is shown that the total active thunderstorm count is less than previous estimates based on compiled climatologies.