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Investigating Ionospheric TEC Variations in Solar and Geomagnetic Influences Across Solar Activity Phases

Ziyadat Hassan, Zamri Zainal Abidin, Affan Adly Nazri, Nursyazela Badrina Baharin

TL;DR

This work investigates how ionospheric VTEC responds to solar and geomagnetic forcing across solar cycles 23–25, addressing gaps in phase-resolved and lagged behavior. By combining CASG global VTEC maps with OMNI solar–geophysical indices, it quantifies Pearson correlations and time-lag relationships, revealing that solar proxies $F_{10.7}$ and the R sunspot number show the strongest, most consistent links to VTEC, particularly during ascending/descending phases with an approximate $2$-day lag. Geomagnetic indices exhibit weaker, more phase-dependent correlations, while direct solar-wind–VTEC links are weak and mediated through geomagnetic activity with substantial regional variability. The findings underscore the need to embed solar-phase and lag dynamics in ionospheric forecasting, and motivate high-resolution, region-specific analyses to capture localized responses to solar–geomagnetic forcing.

Abstract

This study examines the variability of ionospheric total electron content (VTEC) in response to solar and geomagnetic drivers across solar cycles 23 to 25. While the dominant effect of solar radiation on VTEC is well-known, a comprehensive understanding of how these relationships and their time-lags vary across distinct solar cycle phases and across cycles of differing intensity has been lacking. Using global VTEC data from the Chinese Academy of Sciences Global Ionospheric Maps (CASG) and solar-geophysical indices from NASA's OMNI dataset spanning from 1998 to 2025, this study bridges that gap by quantifying correlation strengths and time-lag relationships between VTEC and parameters such as $F_{10.7}$ solar flux, R sunspot number, Kp, Ap, and Dst indices, and solar wind properties. Results show that solar proxies, particularly $F_{10.7}$ and R sunspot number, exhibit the strongest, most consistent correlations with VTEC, especially during the ascending and descending phases of the solar cycle, with a characteristic $\sim2$-day lag attributed to thermospheric oxygen dynamics and ionospheric recombination processes. In contrast, geomagnetic indices exhibit weaker and phase-dependent correlations, while direct correlations between solar wind parameters and global VTEC are weak, as their influence is primarily mediated by geomagnetic activity and exhibits strong regional and temporal heterogeneity. Phase-resolved analyses further reveal that geomagnetic activity plays a more prominent role during transitional phases, while maximum and minimum periods are dominated by EUV variability and non-solar drivers, respectively. These findings highlight the necessity of incorporating solar phase and time-lag dependencies in ionospheric modelling and forecasting efforts.

Investigating Ionospheric TEC Variations in Solar and Geomagnetic Influences Across Solar Activity Phases

TL;DR

This work investigates how ionospheric VTEC responds to solar and geomagnetic forcing across solar cycles 23–25, addressing gaps in phase-resolved and lagged behavior. By combining CASG global VTEC maps with OMNI solar–geophysical indices, it quantifies Pearson correlations and time-lag relationships, revealing that solar proxies and the R sunspot number show the strongest, most consistent links to VTEC, particularly during ascending/descending phases with an approximate -day lag. Geomagnetic indices exhibit weaker, more phase-dependent correlations, while direct solar-wind–VTEC links are weak and mediated through geomagnetic activity with substantial regional variability. The findings underscore the need to embed solar-phase and lag dynamics in ionospheric forecasting, and motivate high-resolution, region-specific analyses to capture localized responses to solar–geomagnetic forcing.

Abstract

This study examines the variability of ionospheric total electron content (VTEC) in response to solar and geomagnetic drivers across solar cycles 23 to 25. While the dominant effect of solar radiation on VTEC is well-known, a comprehensive understanding of how these relationships and their time-lags vary across distinct solar cycle phases and across cycles of differing intensity has been lacking. Using global VTEC data from the Chinese Academy of Sciences Global Ionospheric Maps (CASG) and solar-geophysical indices from NASA's OMNI dataset spanning from 1998 to 2025, this study bridges that gap by quantifying correlation strengths and time-lag relationships between VTEC and parameters such as solar flux, R sunspot number, Kp, Ap, and Dst indices, and solar wind properties. Results show that solar proxies, particularly and R sunspot number, exhibit the strongest, most consistent correlations with VTEC, especially during the ascending and descending phases of the solar cycle, with a characteristic -day lag attributed to thermospheric oxygen dynamics and ionospheric recombination processes. In contrast, geomagnetic indices exhibit weaker and phase-dependent correlations, while direct correlations between solar wind parameters and global VTEC are weak, as their influence is primarily mediated by geomagnetic activity and exhibits strong regional and temporal heterogeneity. Phase-resolved analyses further reveal that geomagnetic activity plays a more prominent role during transitional phases, while maximum and minimum periods are dominated by EUV variability and non-solar drivers, respectively. These findings highlight the necessity of incorporating solar phase and time-lag dependencies in ionospheric modelling and forecasting efforts.
Paper Structure (14 sections, 3 equations, 4 figures, 3 tables)

This paper contains 14 sections, 3 equations, 4 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Methodology
  3. CAS Global Ionospheric Map Data
  4. NASA OMNI Solar and Geomagnetic Parameters
  5. Data Analysis
  6. VTEC and OMNI Data Averaging
  7. Quantifying Correlation
  8. Time Lag Calculations
  9. Results and Discussion
  10. Ionospheric, Solar, and Geomagnetic Parameters Temporal Variations
  11. Correlations and Non-correlations
  12. Solar Activity Phase Dependence
  13. Time Lag Characteristics
  14. Conclusion

Figures (4)

  • Figure 1: Long-term variation of VTEC across multiple solar cycles (1998 -- 2025). Black, blue, and red lines represent the daily, weekly, and (calendar) monthly averaged VTEC values, with the grey region denoting the VTEC standard deviation on a specific day. The lower two frames show the traditional solar phases (Asc: Ascending, Max: Maximum, Des: Descending, Min: Minimum) and solar cycles.
  • Figure 2: Long-term variation of the solar and geomagnetic parameters in comparison with VTEC. The points in each plot show the monthly averaged data with error bars signifying the standard deviation of the respective parameters. The lowest two frames depict the traditional solar phases (Asc: Ascending, Max: Maximum, Des: Descending, Min: Minimum) and solar cycles.
  • Figure 3: Comparison of VTEC with solar and geomagnetic parameters. The Pearson's correlation coefficient for each relationship is shown in the top left of each plot. The values shown in the brackets correspond to the base-10 logarithm of the respective p-values. For relations with a correlation coefficient of $r > 0.5$, a dashed line depicts a linear regression fitted to said data.
  • Figure 4: Dependence of the correlation of solar and geomagnetic parameters with VTEC on the VTEC time lag in days. The red dashed vertical line shows the time lag at which the maximum (absolute) correlation coefficient occurs. In cases where the correlations are uniformly weak (e.g. proton density), this peak should not be interpreted as evidence of a meaningful lagged relationship.