Assessment of the Uncertainty for the Spatial Distribution of Lightning Discharge Density Based on the Smoothed Bootstrap Procedure and WWLLN Data: a Case Study

Abstract

Thunderstorm activity is the most common natural cause of forest fires. Such forest fires can affect the functioning of industrial and infrastructure facilities. An effective application of the deterministic-probabilistic approach is possible if there is a set of initial data, including cloud-to-ground lightning discharges. It is especially important to understand the boundaries of uncertainty in determining the spatial distribution of the density of lightning discharges in a controlled forest-covered area. The aim of this work is to develop a procedure for assessing the uncertainty of the spatial distribution of lightning discharge density using a smoothed bootstrap algorithm and World Wide Lightning Location Network (WWLLN) data. The novelty of the work is due to the use of WWLLN data in combination with bootstrap algorithm in order to assess uncertainty of spatial distribution of lightning activity. The main findings are: 1) algorithm of bootstrap procedure to assess uncertainty in lightning discharge density within spatial distribution; 2) program realization of this algorithm using QGIS and GRASS software; 3) case study results for the typical boreal zone, namely, Republic of Buryatia (Russian Federation). Conclusions based on the results of bootstrap assessment of lightning discharge density uncertainty are presented regarding spatial distribution of lightning discharges. These results are applicable for forest fire danger prediction in lightning activity conditions.