Author: Bhanupriya, Madhuri Singh, Kalpana Maski and S.K. Vijay
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In the present study, a single station spectra model of the F-region foF2 for the low latitude station Brisbane (27.47S,153.02E) is developed for the years 2008-2017 of the 24th solar cycle. In this work, regression analysis is performed to explore the solar and geomagnetic correlation of foF2, and Fourier analysis method is employed to illustrate the diurnal fluctuation. A polynomial formula is utilized to include the sunspot number (R.no) into both models to represent the dependency of foF2 on solar activity. The results shows that linear and quadratic regression models have a high correlation with the observed valued, but the multiple regression model has to be modified. Modifications are also required for the Fourier expansion model to minimize the percentage error in order to move towards perfection
Spectra model, regression analysis, fourier expansion model, sunspot number, foF2, low latitude
This study explored the relationship between solar and geomagnetic activity and the monthly median foF₂ values at the low-latitude ionosonde station in Brisbane during Solar Cycle 24. Several modeling techniques were employed to evaluate how well different statistical and empirical methods represent foF₂ variability under varying solar conditions. The findings indicate that the monthly median foF₂ response to solar activity, represented by the monthly mean sunspot number (R), exhibits both linear and nonlinear characteristics at local times 0 and 12 hours. While linear and quadratic regression models largely followed the observed trends in foF₂, the multiple regression model displayed inconsistent patterns, suggesting that refinements are needed to improve its fit and reliability. Further, diurnal variations in foF₂ were assessed using a Fourier analysis approach over the period 2008–2017. Notably, larger percentage errors were observed during specific time intervals between 4–8 LT, 11–12 LT, and 20–22 LT indicating limitations in the model’s accuracy during these periods. To enhance its precision, adjustments to the Fourier model are necessary, particularly to reduce errors during these peak fluctuation times. Beyond these model-specific insights, the study addresses several critical issues in ionospheric modeling. Most notably, low-latitude regions like Brisbane remain significantly underrepresented in the global modeling landscape, despite their distinctive electrodynamic behaviors influenced by the equatorial ionization anomaly. Moreover, Solar Cycle 24’s relatively weak and irregular nature adds complexity to foF₂ modeling, underscoring the need for cycle-specific analyses. A further limitation identified is the insufficient integration of multiple geophysical indices such as F10.7, F30, Ap, and Kp into current predictive frameworks. Existing models often rely on single-proxy inputs, which may not adequately capture the multifactorial influences on ionospheric conditions. While machine learning approaches such as LSTM and Informer models offer high predictive accuracy, their lack of interpretability presents challenges for scientific understanding and validation. In conclusion, the study highlights the need for more refined, interpretable, and region-specific foF₂ models. Improving model accuracy during critical local time intervals, integrating multiple geophysical indices, and addressing the modeling gaps specific to low-latitude regions like Brisbane are essential steps toward advancing ionospheric science and operational forecasting
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Bhanupriya, Madhuri Singh, Kalpana Maski and S.K. Vijay (2025). Spectra Model of foF2 for Low Latitude Station during the 24th Solar Cycle. International Journal of Theoretical & Applied Sciences, 17(2): 22–30.
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