Articles | Volume 18, issue 8
https://doi.org/10.5194/essd-18-5773-2026
https://doi.org/10.5194/essd-18-5773-2026
Data description article
 | 
07 Aug 2026
Data description article |  | 07 Aug 2026

Corrected event dataset of FengYun-4A Lightning Mapping Imager (FY-4A LMI), 2019–2023

Yuansheng Zhang, Xiushu Qie, Rubin Jiang, Dongjie Cao, Jing Yang, Dongfang Wang, Mingyuan Liu, Dongxia Liu, Zhuling Sun, Hongbo Zhang, and Shanfeng Yuan

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Cited articles

Abarca, S. F., Corbosiero, K. L., and Galarneau, T. J.: An evaluation of the worldwide lightning location network (wwlln) using the national lightning detection network (nldn) as ground truth, J. Geophys. Res.-Atmos., 115, 2009JD013411, https://doi.org/10.1029/2009JD013411, 2010. 
Brune, W. H., Mcfarland, P. J., Bruning, E., Waugh, S., Macgorman, D., Miller, D. O., Jenkins, J. M., Ren, X., Mao, J., and Peischl, J.: Extreme oxidant amounts produced by lightning in storm clouds, Science, 372, 711–715, https://doi.org/10.1126/science.abg0492, 2021. 
Buechler, D., Varghese, T., Armstrong, P., Bremer, J., Lamb, R., Fulbright, J., Goodman, S., Butler, J. J., Xiong, X. J., and Gu, X.: On-orbit validation of the geolocation accuracy of goes-16 geostationary lightning mapper (glm) flashes using ground-based laser beacons, in: Earth Observing Systems XXIII, SPIE, 2018/1/1, 107640J, 2018. 
Cao, D.: The development of product algorithm of the fengyun-4 geostationary lightning mapping imager, Adv. Meteorol. Sci. Techol., 6, 94–98, 2016. 
Cao, D., Lu, F., Zhang, X., and Yang, J.: Lightning activity observed by the fengyun-4a lightning mapping imager, Remote Sens., 13, 3013, https://doi.org/10.3390/rs13153013, 2021.  
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This study presents a corrected 2019–2023 dataset for the FengYun-4A Lightning Mapping Imager, with geolocation accuracy better than 15 km, referenced to the World Wide Lightning Location Network. This open‑access resource enhances lightning monitoring and atmospheric research.
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