Evaluation of U.S. National Lightning Detection Network performance characteristics using rocket-triggered lightning data acquired in 2004–2009

Abstract

[1] We evaluated performance characteristics of the U.S. National Lightning Detection Network (NLDN) using rocket-triggered lightning data acquired in 2004-2009 at Camp Blanding, Florida. A total of 37 negative flashes that contained leader/return stroke sequences (a total of 139) were triggered during these years. For all the return strokes, locations of channel terminations on the ground were known exactly, and for 122 of them currents were measured directly using noninductive shunts. The NLDN recorded 105 Camp Blanding strokes in 34 flashes. The resultant flash and stroke detection efficiencies were 92% and 76%, respectively. The median absolute location error was 308 m. The median NLDN-estimated peak current error was −6.1%, while the median absolute value of current estimation error was 13%. Strokes in "classical" triggered flashes are similar to regular subsequent strokes (following previously formed channels) in natural lightning, and hence the results presented here are applicable only to regular negative subsequent strokes in natural lightning. The flash detection efficiency reported here is expected to be an underestimate of the true value for natural negative lightning flashes, since first strokes typically have larger peak currents than subsequent ones.

Analysis of lightning strokes associated with sprites observed by ISUAL in the vicinity of North America

“…The leading fast pulse with a distinct oscillatory feature (e.g., Dowden et al 2002, Fig. 2) is driven by the initial contact (i.e., return stroke) of a lightning stroke and can be used to estimate the peak current (Pessi et al 2009;Nag et al 2011). The trailing slow pulse with timescale longer than 1 ms is excited by the subsequent impulse current (Gomes and Cooray 1998), which makes the major contribution to the charge moment change (iCMC) within 2 ms after the return stroke by removing electric charge from the existing lightning channels (Lu et al 2009).…”

“…In section 3, we validated the geolocation accuracy of ISUAL relative to individual sprite observations, using the National Lightning Detection Network (NLDN) data for the parent strokes of ISUAL sprites within the detection range of NLDN (Cummins et al 1998;Cummins and Murphy 2009). In addition, the NLDN provides an estimated peak current of sprite-producing strokes (e.g., Nag et al 2011), which can be used as a dataset for us to formulate an empirical approach to estimate the peak current of other sprite-producing strokes not detected by the NLDN. The distribution of ISUAL sprites near North America produced respectively by positive and negative CG strokes is presented in section 4, showing a considerable population of negative sprites over tropical oceans.…”

The European lightning location system EUCLID – Part 2: Observations

“…LLSs operating at low frequencies (LFs) combine the best of both worlds: with baselines of a few hundred of kilometers it is possible to cover countries as well as continents (e.g. Biagi et al, 2007;Nag et al, 2011;Mallick et al, 2014;Schulz et al, 2005;Antonescu and Burcea, 2010;Enno, 2011;Mäkelä et al, 2014), while still retaining a satisfactory level of performance in terms of LA and DE. While most LLSs provide supplementary information such as polarity and peak current of the lightning discharge, it is the spatial flash incidence that remains the main objective. This continuous interest in the spatial distribution of the lightning flash density N g is not surprising as it is not only of importance for climatological studies, but plays a vital role as well in the risk analysis for protecting structures and electronic systems against damage from lightning impacts to ground (see risk management in accordance with IEC 62305-2).…”

Analysis of lightning outliers in the EUCLID network

“…During recent years the performance of LLSs has received more and more attention (Nag et al, 2015). A direct method to determine the quality of a network, and therefore the values assigned to each lightning event, is by comparing the data against so-called ground-truth observations.…”

“…Those observations provide valuable information on the DE, location accuracy and in some cases even the peak current estimates retrieved from an LLS. This is done for instance by examining direct lightning strikes to instrumented towers (Diendorfer et al, 2000a, b;Pavanello et al, 2009;Romero et al, 2011;Schulz et al, 2012Schulz et al, , 2013Cramer and Cummins, 2014;Azadifar et al, 2016) through the use of rocket-triggered lightning (Jerauld et al, 2005;Nag et al, 2011;Mallick et al, 2014a, b, c) and/or by recording lightning strikes with highspeed video and E-field (electric field) measurements in open field (Biagi et al, 2007;Poelman et al, 2013a;Schulz et al, 2016). Although they are the best methods for retrieving robust information of a networks' performance, they are quite labor intensive when used to acquire a large enough dataset for a statistically reliable output.…”