JOURNAL ARTICLE
Diurnal and semidiurnal atmospheric solar tides during June solstice: A numerical study.
Published In: Journal of Earth System Science, 2025, v. 134, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Reddimalla, Naresh; Vichare, Geeta; Ramana Murthy, J V 3 of 3
Abstract
The current paper investigates the atmospheric diurnal and semidiurnal solar tides during the June solstice. It utilizes a tidal model that considers both dissipation effects and background zonal wind disturbances. The study numerically solves the equations governing atmospheric wind and temperature oscillations, incorporating solar heating caused due to the absorption of solar radiation in the atmosphere by H2O, O3, and O2. The results for tidal oscillations during the June solstice are compared with those from the Global Scale Wave Model (GSWM) and the March equinox. Large hemispheric differences for the semidiurnal component are observed in the horizontal winds and temperature perturbations as compared to those for the diurnal component. Considerable seasonal differences are seen in the horizontal wind’s diurnal and semidiurnal components above 110 km. Research highlights: The large hemispheric differences in the semidiurnal component are observed in the horizontal winds, in contrast to the diurnal component; a similar trend is noted in GSWM-00. At higher altitudes, diurnal and semidiurnal components of the zonal wind perturbations exhibit significant seasonal variations. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Earth System Science. 2025/12, Vol. 134, Issue 4, p1
- Document Type:Article
- Subject Area:Astronomy and Astrophysics
- Publication Date:2025
- ISSN:0253-4126
- DOI:10.1007/s12040-025-02693-0
- Accession Number:190501553
- Copyright Statement:Copyright of Journal of Earth System Science is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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