Elsevier

Atmospheric Research

Volume 247, 1 January 2021, 105139
Atmospheric Research

A new approach to map lightning channels based on low-frequency interferometry

https://doi.org/10.1016/j.atmosres.2020.105139Get rights and content

Highlights

  • A purely interferometric imaging algorithm for locating low-frequency lightning sources in 3D has been developed.

  • The algorithm is able to locate more lightning sources than the hybrid interferometric-TOA algorithm.

  • The imaging algorithm is capable of resolving multiple concurrent lightning sources.

Abstract

A purely interferometric algorithm, named imaging algorithm, has been developed for mapping lightning in the low-frequency band. The imaging algorithm locates a lightning source by computing the three-dimensional correlation of the lightning signals arriving at a pair of lightning sensors, and then summing the correlations of all antenna pairs. This algorithm does not locate the source by solving the non-linear time-of-arrival (TOA) equations, instead the source is located at the global maxima of the total correlation. The lightning map produced by the imaging algorithm for one intracloud flash was compared with that of the hybrid interferometric-TOA algorithm. The imaging algorithm can locate more sources than the hybrid algorithm and produce more complete lightning maps. We also demonstrated that the imaging algorithm can locate multiple concurrent lightning sources even though the recorded signals from the pulses overlap in time at some stations, which is not possible with a traditional TOA-based technique.

Introduction

Lightning produces electromagnetic radiation over a wide spectral range, extending from just a few hertz up into the x-ray band. Ground-based systems that locate this lightning emission usually operate in the very low frequency (VLF, 3–30 kHz), low frequency (LF, 30–300 kHz), or very high frequency (VHF, 30–300 MHz) bands. The processes that involve transient high current propagating along a pre-existing channel (e.g. return strokes or K-changes) tend to produce strong emission in the VLF/LF range while the electrical breakdown into virgin air produces strong VHF emission (Cummins and Murphy, 2009). VLF/LF systems are routinely used to locate lightning pulses over regional or even global areas by networks of lightning sensors separated by baselines of hundreds of kilometers, such as U.S. National Lightning Detection Network (NLDN, Cummins et al., 1998) and Earth Networks Total Lightning Network (ENTLN, Zhu et al., 2017). VHF lightning mapping systems offer substantially higher detail over a much smaller area using networks of sensors separated by baselines of a few tens of kilometers (e.g., the Lightning Mapping Array (LMA), Rison et al., 1999; Thomas et al., 2004). In addition to their more limited range, VHF mapping systems have several other limitations. Since the VHF radiation is associated with streamer development (Shi et al., 2019; Hare et al., 2020), VHF measurements cannot be used to determine quantities such as peak current or charge moment for processes in a flash. VHF mapping systems also tend not to locate sources very close to the ground, and so cannot normally be used to determine the ground strike locations of lightning flashes (e.g., Bitzer et al., 2013; Lang et al., 2017). For these reasons, a lightning mapping system which operates at low frequency is desired.

A number of short-baseline, LF lightning locating networks have been developed in the past decade to map lightning in 3D (e.g., Shao et al., 2006; Bitzer et al., 2013; Karunarathne et al., 2013; Lyu et al., 2014; Yoshida et al., 2014; Wang et al., 2016; Shi et al., 2017; Wu et al., 2018). Bitzer et al. (2013) and Yoshida et al. (2014) both used a network of electric field change antennas and located lightning sources using a traditional peak-finding-time-of-arrival (TOA) technique. Three-dimensional maps of lightning were produced, but with fewer and more sporadic sources than the maps produced by an LMA in the VHF band. Lyu et al. (2014) were the first to utilize a hybrid interferometric-TOA algorithm to locate lightning. Here they applied the interferometric cross-correlation techniques used in broadband VHF interferometry (e.g., Sun et al., 2013; Stock et al., 2014; Wang et al., 2020) to the signals recorded by a network of LF magnetic antennas. The maxima of the cross-correlations were used to determine the time difference between pairs of antennas in the array, and then the source was located by solving the non-linear time-difference-of-arrival (TDOA) equations. The advantage of this hybrid processing algorithm is that it can map both discrete and continuous emissions, and thus produce a more complete map of a lightning flash (Lyu et al., 2014). More recently, the Fast Antenna Lightning Mapping Array (FALMA), which also uses a hybrid location technique, has been demonstrated to locate lightning in detail rivaling that of VHF systems including the LMA (Wu et al., 2018, Wu et al., 2019).

In this paper, a purely interferometric algorithm for lightning mapping in the LF is presented. We will refer to this algorithm as the imaging algorithm for simplicity thereafter in this paper since it locates lightning by producing the image of the total correlations for each lightning source. The imaging algorithm was briefly introduced by Stock et al. (2016), but details on the method or performance of the algorithm were omitted. This paper serves to present the imaging algorithm in detail, and compare the lightning maps produced by it with those produced by the hybrid interferometric-TOA technique developed by Zhu et al., (2020). The data used for imaging in this study was obtained from the Córdoba, Argentina Marx Meter Array (CAMMA) during the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign in Argentina. The CAMMA consists of ten sensors with a typical baseline of 30–60 km. Each sensor is equipped with two (slow and fast) channels for measuring electric field changes produced by lightning at different frequency ranges. The fast channel is much more sensitive than the slow channel and is dedicated to lightning mapping. The lightning maps presented in this paper were produced using the fast channel. The bandwidth for the fast channel is 1.6 kHz to 2.5 MHz with a time decay constant of 100 μs. More detailed information about the CAMMA can be found in Zhu et al. (2020).

Section snippets

Location algorithm

The imaging algorithm locates lightning in an entirely different manner than TOA, TDOA, or hybrid-TOA algorithms. Unlike time-of-arrival algorithms, no feature needs to be identified in the recorded signals to locate it. To locate a source, the signals arriving at each pair of antennas are correlated, and then these correlations are projected into a volume containing the source. The source is located at the point of maximum total correlation. The algorithm is similar to the VHF interferometric

An inverted intracloud flash mapped by imaging algorithm

An inverted intracloud flash mapped by the imaging algorithm is shown in Fig. 4b. This flash initiated at a height of 4.8 km (the flash origin is marked in Fig. 4b) and propagated bi-directionally, although the inferred positive leader that moved towards the northeast appears to be not very active. In contrast, the negative leader was moving continuously at a lower altitude towards the southeast. Near the end of the flash, a faster recoil negative leader initiated at the tip of the remnants of

Summary

The imaging algorithm, a purely interferometric lightning location algorithm that can be used in low-frequency lightning mapping, was presented in this paper. Unlike traditional TOA-based location algorithms that send the arrival times or arrival time differences into a non-linear minimizer to determine the location of the source, the imaging algorithm determines the location of a lightning source by computing the three-dimensional total correlation of lightning signals at different stations

Declaration of Competing Interest

None.

Acknowledgment

This research was supported by U.S. National Science Foundation grants AGS-1654576 and AGS- 1661785. The authors thank Jeff Burchfield, Lawrence Carey, Bruno Medina, Jacquelyn Ringhausen, Lena Heuscher for operating the array in the field campaign.

Author statement

M. Stock and Y. Zhu conceived the idea for this study. Y. Zhu developed the processing code. Y. Zhu and M. Stock drafted the manuscript. P. Bitzer led the instrument development and obtained the data for this study. All authors contributed to the discussion of the results and preparation of the manuscript.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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