Sprite Distribution of Different Polarities From ISUAL Observations With Machine Learning Method

doi:10.1029/2022JD036968

	Sprite Distribution of Different Polarities From ISUAL Observations With Machine Learning Method
	Zhang, Mao 1; Lu, Gaopeng 1,2,3; Wang, Ziyi 1; Peng, Kang-Ming 1; Huang, Hailiang 1; Ren, Huan 1; Liu, Feifan 1; Lei, Jiuhou 1
刊名	JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
	2022-10-16
卷号	127
关键词	machine learning red sprite sea-land contrast lightning
ISSN号	2169-897X
DOI	10.1029/2022JD036968
通讯作者	Lu, Gaopeng(gaopenglu@gmail.com)
英文摘要	The morphological features of sprites are closely related to the polarity of their causative lightning strokes. Using the machine learning method, we develop a model with an accuracy of 93.8% to identify the polarity of sprite-producing cloud-to-ground (CG) lightning strokes for events recorded during the Imager of Sprites and Upper Atmospheric Lightning (ISUAL) mission. Approximately 17% of the sprites are identified to be produced by negative CG lightning strokes. The global distribution of the polarity of sprite-producing CG lightning strokes suggests that the ratio of sprites produced by negative CG lightning strokes relative to sprites produced by positive ones varies with latitude and sea-land distribution. Sprites produced by negative CG lightning strokes appear to be generated in the tropical regions below 20 degrees latitude and the oceanic area. Moreover, the proportion of sprites produced by negative CG lightning strokes over Africa and North America are much smaller than that over the rest of the continents and the sea.
资助项目	CAS Project of Stable Support for Youth Team in Basic Research Field[YSBR-018] ; National Key Research and Development Program of China[2019YFC1510103] ; National Natural Science Foundation of China[41875006] ; National Natural Science Foundation of China[U1938115] ; Chinese Meridian Project ; International Partnership Program of Chinese Academy of Sciences[183311KYSB20200003]
WOS关键词	CURRENTS ; VLF
WOS研究方向	Meteorology & Atmospheric Sciences
语种	英语
出版者	AMER GEOPHYSICAL UNION
WOS记录号	WOS:000863586900001
资助机构	CAS Project of Stable Support for Youth Team in Basic Research Field ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; Chinese Meridian Project ; International Partnership Program of Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/129201]
专题	中国科学院合肥物质科学研究院
通讯作者	Lu, Gaopeng
作者单位	1.Univ Sci & Technol China, Sch Earth & Space Sci, Hefei, Peoples R China 2.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Key Lab Atmospher Opt, Hefei, Peoples R China 3.Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Mao,Lu, Gaopeng,Wang, Ziyi,et al. Sprite Distribution of Different Polarities From ISUAL Observations With Machine Learning Method[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2022,127.
APA	Zhang, Mao.,Lu, Gaopeng.,Wang, Ziyi.,Peng, Kang-Ming.,Huang, Hailiang.,...&Lei, Jiuhou.(2022).Sprite Distribution of Different Polarities From ISUAL Observations With Machine Learning Method.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,127.
MLA	Zhang, Mao,et al."Sprite Distribution of Different Polarities From ISUAL Observations With Machine Learning Method".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 127(2022).