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Dataset . 2023
Data sources: ZENODO
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Dataset . 2023
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2023
Data sources: Datacite
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Guangdong Lightning Mapping Array: Errors Evaluation and Preliminary Results

Authors: Huiyi Zhang; Zhang, Yang;

Guangdong Lightning Mapping Array: Errors Evaluation and Preliminary Results

Abstract

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, the average horizontal error was 13 m and the average horizontal error was 41 m, consistent with the Monte Carlo results. When outside the network, The location uncertainties varied significantly with different azimuths. Location results with different error ranges were presented, showing relatively clear mapping results when the localization error is less than 300m. The location results of GDLMA and Low-to-Mid Frequency E-field Detection Array (MLFEDA) were compared, and they showed generally similar in basic structure and some lightning characteristics, such as flash area and distribution of source altitudes. However, GDLMA exhibited better channel characterization capabilities, while MFLEDA performed better in processes such as leader/return strokes.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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