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Title: Comparative study of predominantly daytime and nighttime lightning occurrences and their impact on ionospheric disturbances
Authors: Osei-Poku, L 
Tang, L
Chen, W 
Chen, M 
Acheampong, AA
Issue Date: Jul-2022
Source: Remote Sensing, July 2022, v. 14, no. 13, 3209
Abstract: Space weather events adversely impact the operations of Global Navigation Satellite Systems (GNSS). Understanding space weather mechanisms, interactions in the atmosphere, and the extent of their impact are useful in developing prediction and mitigation models. In this study, the hourly lightning occurrence and its impact on ionospheric disturbances, quantified using the Rate of Total electron content Index (ROTI), were assessed. The linear correlation between diurnal lightning activity and ROTI in the coastal region of southern China where lightning predominates in the daytime was initially negative contrary to a positive correlation in southern Africa where lighting predominates in the evening. After appreciating and applying the physical processes of gravity waves, electromagnetic waves and the Trimpi effect arising from lightning activity, and the time delay impact they have on the ionosphere, the negative correlation was overturned to a positive one using cross-correlation. GNSS has demonstrated its capability of revealing the impact lightning has on the ionosphere at various times of the day.
Keywords: Daytime
GNSS
Gravity wave
Lightning
Nighttime
ROTI
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Remote sensing 
EISSN: 2072-4292
DOI: 10.3390/rs14133209
Rights: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Osei-Poku, L., Tang, L., Chen, W., Chen, M., & Acheampong, A. A. (2022). Comparative Study of Predominantly Daytime and Nighttime Lightning Occurrences and Their Impact on Ionospheric Disturbances. Remote Sensing, 14(13), 3209 is available at https://doi.org/10.3390/rs14133209.
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