| 20 Aug 2026
Influence of solar, solar wind, and geomagnetic activity on the ionospheric propagation factor M(3000)F2 over Ouagadougou in the African equatorial sector
Abstract. This study examines how solar, solar wind, and geomagnetic activity influence the ionospheric propagation factor M(3000)F2 over Ouagadougou (12.4° N, 358.5° E; dip latitude +1.45°), an equatorial station in the African sector. Hourly ionosonde observations from 1976 to 1997, spanning Solar Cycles 21 and 22, were analysed to investigate diurnal, seasonal, solar cycle, and storm-time variability of M(3000)F2. Representative years of high (1991), moderate (1993), and low (1995) solar activity were selected for climatological analyses, while seven geomagnetic storm events were examined to assess storm-time responses. Relationships between annual mean M(3000)F2 and selected solar, solar wind, and geomagnetic parameters were evaluated using correlation and linear regression analyses. M(3000)F2 exhibits pronounced diurnal and seasonal variability, characterised by higher nighttime and early-morning values, lower daytime values, and distinct equinoctial and solstitial differences associated with equatorial electrodynamics and thermospheric dynamics. An inverse dependence on solar activity is observed, with the highest M(3000)F2 values occurring during solar minimum. The strongest correlation is with the solar radio flux F10.7 (R = -0.810, R² = 0.657, p < 0.001), followed by the interplanetary magnetic field magnitude (B) (R = -0.689, R² = 0.475, p < 0.001) and the disturbance storm time (Dst) index (R = 0.527, R² = 0.277, p = 0.0117). Relationships with the planetary (Ap) index, the southward component of the interplanetary magnetic field (Bz), solar wind dynamic pressure (Psw), and solar-wind speed (Vsw) are weak and not statistically significant. During geomagnetic storms, M(3000)F2 generally decreases during the daytime main phase and recovers within one to two days, depending on storm intensity and background ionospheric conditions. The results indicate that long-term variability of M(3000)F2 over the African equatorial sector is primarily controlled by solar activity, with geomagnetic disturbances providing secondary modulation during storm periods. These findings contribute to a better understanding of equatorial ionospheric variability and provide useful information for HF radio wave propagation, empirical ionospheric modelling, and space weather applications.
The manuscript “Influence of solar, solar wind, and geomagnetic activity on the ionospheric propagation factor M(3000)F2 over Ouagadougou in the African equatorial sector” analyses long‑term ionosonde observations from Ouagadougou (1976–1997) together with solar, solar‑wind, and geomagnetic indices. The author investigates diurnal, seasonal, solar‑cycle, and storm‑time variability of M(3000)F2 and uses linear regression to quantify relationships between yearly mean M(3000)F2 and several geophysical drivers.
The topic is relevant to HF propagation, empirical ionospheric modelling, and equatorial space‑weather studies, and the long data record from a data‑poor region is valuable. However, several methodological and interpretational issues need clarification before the manuscript can be considered for publication.
Major comments
Daily values are defined as arithmetic means over all hourly M(3000)F2 observations, which are then averaged to obtain monthly and yearly means. At the same time, the author explicitly notes frequent missing nighttime and early‑morning observations and restricts the storm‑time analysis to daytime hours. This implies that “daily averages” may in practice be daytime‑weighted means rather than true 24‑hour averages, which can bias monthly and yearly means at an equatorial station where M(3000)F2 shows strong nighttime and early‑morning maxima. The author should quantify local‑time data coverage, demonstrate whether missing hours affect long‑term averages, and consistently reflect these limitations in the climatological (diurnal, seasonal, solar‑cycle) analysis as well as in the storm‑time section.
Seasonal variability is analysed using a modified Lloyd classification: March equinox (March–April), June solstice (May–August), September equinox (September–October), and December solstice (November–February). While this scheme is referenced to earlier work, the manuscript does not clearly articulate a physical hypothesis for why these four seasons are the most appropriate framework for M(3000)F2 at a near‑equatorial station. The results show December solstice as having the highest mean M(3000)F2, with more modest differences among other seasons, yet the manuscript speaks of “marked seasonal variability”. The author should (i) explicitly state the expected seasonal differences and their physical basis, (ii) assess whether seasonal differences are statistically significant compared to day‑to‑day variability, and (iii) clarify why this particular seasonal grouping is optimal in the equatorial context.
The time series of monthly mean M(3000)F2 and F10.7 for 1976–1997 and the strong negative correlation of yearly means (R = −0.81, R² = 0.657) support an overall inverse relationship, and the author concludes that F10.7 is the dominant driver of long‑term M(3000)F2 variability. However, there are extended intervals where the behaviour is not strictly inverse—for example, around the maximum of Solar Cycle 21, F10.7 peaks around 1980 while M(3000)F2 rises from a minimum towards a higher value around 1981, during persistently high F10.7. These intervals suggest phase lags or additional influences and should be explicitly discussed. I recommend examining lagged correlations, highlighting periods where the inverse behaviour breaks down, and moderating the conclusion about F10.7 as the “dominant driver”, framing it as the parameter with the strongest statistical association among several coupled processes.
The storm‑time analysis is based on seven geomagnetic storms in three representative years (1991, 1993, 1995), with some phases missing due to data gaps. Despite this small and incomplete sample, the manuscript generalises that geomagnetic disturbances “generally” cause daytime depletion during the main phase and recovery over one to two days. These generalisations appear too strong for a limited set of case studies. The author should clearly state the selection criteria for storms, emphasise the case‑study nature of the results, and either expand the storm sample (if possible) or restrict conclusions to the analysed events without implying a robust climatology. Given that the analysis is restricted to daytime hours, the text should consistently refer to “daytime storm‑time response” and avoid suggesting that full diurnal behaviour has been characterised.
Recommendation
The manuscript addresses an important topic and makes good use of a valuable long‑term dataset, but the issues above require substantial revision. I therefore recommend publication after major revision, provided that the author can address the concerns regarding data gaps and averaging procedures, the physical motivation and significance of seasonal variability, the interpretation of the M(3000)F2–F10.7 relationship, and the limitations of the storm‑time analysis.