Extending the analysis on the best solar activity proxy for long-term ionospheric investigations

0574576 - ÚFA 2024 RIV GB eng J - Článek v odborném periodiku
Zossi, B.S. - Medina, F. D. - Tan Jun, G. - Laštovička, Jan - Duran, T. - Fagre, M. - Barbas, B.F.H. - Elias, A. G.
Extending the analysis on the best solar activity proxy for long-term ionospheric investigations.
Proceedings of the Royal Society A-Mathematical Physical and Engineering Sciences. Roč. 479, č. 2276 (2023), č. článku 20230225. ISSN 1364-5021. E-ISSN 1471-2946
Grant CEP: GA ČR(CZ) GA21-03295S
Institucionální podpora: RVO:68378289
Klíčová slova: solar activity proxy * foF2 modelling * ionosphere * long-term trends
Obor OECD: Meteorology and atmospheric sciences
Impakt faktor: 3.5, rok: 2022
Způsob publikování: Omezený přístup
https://royalsocietypublishing.org/doi/10.1098/rspa.2023.0225

Based on a previous study to select the best solar activity proxy for foF2 modelling, we expand the analysis to include 24 h time span, increase the spatial coverage by considering additional ionospheric stations, and update the analysis to 2021. Annual means of foF2 are analysed for 12 selected stations from Europe, Asia and Oceania, with high-quality data covering the period 1978-2021 in most of the cases, including two of the three European stations of the previous study. The same four solar proxies were used: F10.7, F30, MgII and HeII, which, based on the high linear correlation between each of them and foF2, serve to model this ionospheric parameter through a linear regression. The results of our comparative analysis, extended to more stations, all the hours and updated time series, agree with previous works, with MgII and F30 being the best solar proxies for foF2 modelling, while HeII is found to be the least effective for this purpose. The importance of the solar proxy selection to model foF2 for filtering purposes to later estimate long-term trends is highlighted considering that different solar proxies applied might result in somewhat different foF2 long-term trend values.
Trvalý link: https://hdl.handle.net/11104/0344755