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Guangdong Lightning Mapping Array: Errors Evaluation and Preliminary Results

Authors: Huiyi Zhang; Zhang, Yang; Yanfeng Fan; Yijun Zhang; Krehbiel, Paul R.; Weitao Lyu;

Guangdong Lightning Mapping Array: Errors Evaluation and Preliminary Results

Abstract

The attached is the dataset assoicated with the paper titled "Guangdong Lightning Mapping Array: Errors Evaluation and Preliminary Results" which was submitted to Journal of Earth and Space Science. The Guangdong Lightning Mapping Array (GDLMA), as the first LMA in China, was deployed in Guangzhou, Guangdong province, China, in November 2018 by the Chinese Academy of Meteorological Sciences (CAMS) and New Mexico Institute of Mining and Technology (NMT). An evaluation was conducted using Monte Carlo and an aircraft track. The average timing uncertainty of GDLMA is 35 ns based on the distributions of reduced chi-square values. The detection efficiency of radiation sources within a 100 km range of the center of GDLMA exceeds 90%. Based on the aircraft track, at an altitude of 4-5 km within the network, the average horizontal error was 13 m and the average horizontal error was 41 m, consistent with the Monte Carlo results. Location errors outside the network exhibit noticeable directionality. The ability to characterize lightning channels varies with different location errors. In locations that are far from the network center, only the basic structure of lightning flash can be presented, while closer to the network, the flash channel structure can be mapped well. Compared with Low-to-Mid Frequency E-field Detection Array (MLFEDA), they were generally similar in overall structure, and some lightning flash characteristics such as flash duration and convex hull area exhibited consistency. However, GDLMA demonstrated better channel characterization capability, while MFLEDA performed better in processes such as leader/return strokes.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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