Sprite Distribution of Different Polarities From ISUAL Observations With Machine Learning Method-Reference-Cited by-同舟云学术

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

Published:2022-09-30 Issue:19 Volume:127 Page:
ISSN:2169-897X
Container-title:Journal of Geophysical Research: Atmospheres
language:en
Short-container-title:JGR Atmospheres

Author:

Zhang Mao¹^ORCID,Lu Gaopeng¹²³^ORCID,Wang Ziyi¹^ORCID,Peng Kang‐Ming¹,Huang Hailiang¹,Ren Huan¹,Liu Feifan¹^ORCID,Lei Jiuhou¹^ORCID

Affiliation:

1. School of Earth and Space Sciences University of Science and Technology of China Hefei China

2. Key Laboratory of Atmospheric Optics Anhui Institute of Optics and Fine Mechanics HFIPS Chinese Academy of Sciences Hefei China

3. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing China

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022JD036968

Reference39 articles.

1. Why is lightning more intense over the oceans?

2. Optically perceptible characteristics of sprites observed in Central Europe in 2007–2009

3. Global distributions and occurrence rates of transient luminous events

4. On negative Sprites and the Polarity Paradox

5. Why do oceanic negative cloud‐to‐ground lightning exhibit larger peak current values?

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Global and regional chemical influence of sprites: reconciling modelling results and measurements;Atmospheric Chemistry and Physics;2024-03-22