the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Aug 2024
Long-term changes in the dependence of NmF2 on solar flux at Juliusruh
Abstract. Understanding the ionospheric dependence on solar activity is crucial for the comprehension of the upper atmosphere. The response of the ionosphere to solar EUV flux has been previously considered stable. Subsequent studies have revealed long-term changes that are not yet fully understood. This work evaluates the stability of the NmF2 dependence on solar EUV indices throughout different solar cycles.
Hourly values of the peak electron density of the ionospheric F2-layer (NmF2) from Juliusruh station (54.6° N, 13.4° E) are analysed between 1957 and 2023. Geomagnetic perturbations are removed. Third-degree polynomial fit models are dependent on different solar EUV proxies (MgII, F30, and F10.7) and generated separately for each solar cycle and season separately.
The saturation effect is visible in our data and starts at lower F30 values in the ascending phase than in the descending phase. A well-pronounced local time dependence in January with the R2 value being maximum around noon hours has been observed. The correlation is highest for F30 and MgII especially during winter noon conditions, supporting recent studies that they are the best solar flux proxies for describing the NmF2 dependence at all LT hours. Most importantly, the response of NmF2 to solar flux shows a clear long-term change as the slope of the model curves decreases with time for each solar cycle. Between SC20 and SC24, the observed decrease is consistently higher than 16 %, reaching 24 % at 90 sfu which means a decal reduction of 3–4.4 % between 1954 and 2019.
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RC1: 'Comment on angeo-2024-11', Anonymous Referee #1, 13 Aug 2024
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Reviewer comments to the paper by Rios et al.
The work studies the long-term change in the ionosphere at Juliusruh station by parametrization of the ionospheric response to solar activity. The variations in NmF2 with solar EUV proxies are analyzed for hourly values of each month from 1957 to 2023.
A brief description of each solar proxy used in the study is given in subsection 2.1. A special attention is paid to getting rid of wrong data in NmF2 related to human errors or to geomagnetic disturbances. The authors call the process as “cleaning”. The cleaning consisted of two steps. In the first step, the values “that fall far outside the natural range of NmF2” were deleted. In the second step, the effects of geomagnetically disturbed days were withdrawn. The results of the cleaning are shown in Table 2. It shows that the number of points left for the analysis is 65.5% of the initial number of points.
The authors compare the results of using three solar proxies (F30, Ly-a and MgII) and conclude that F30 is the best. That agrees with the opinion of many researchers.
The following method was used for the analysis. The hourly NmF2 values were presented as a third-degree polynomial of the corresponding solar proxy. The quality of that presentation was estimated by the correlation coefficient squared which actually is the determination coefficient of the Fisher F-test. Figure 2 shows the dependence of NmF2 on F30 for particular conditions (14 LT, January) in solar cycle 22. It shows a linear and polynomial approximation of the data and the deviations of the points with a small (less than 10) number of points in the bin.
Analysis of the seasonal effects shows (subsection 3.1) that there is a well pronounced dependence of the R2 value on LT in winter months (January is shown as an illustration), but there is no such dependence in equinox and winter months. That exactly agrees with the results obtained by the analysis of the foF2 data at 11 stations of the Northern and Southern hemispheres. (Geomagnetism and Aeronomy, 2024, Vol. 64, No. 2, pp. 224–234).
In subsection 3.2, the changes in the NmF2 dependence on solar proxies in various SA cycles are analyzed. Fig. 5 shows that there is a clear tendency in the curves for later cycles to go below the curves for early cycles. In my opinion, the most interesting is the left panel of Fig. 6 that demonstrates that for the same value of the solar proxy, the NmF2 values for cycle 24 are lower than for cycle 20.
The authors analyze the so-called “hysteresis effect”. First, they show that the effect does exist even if the geomagnetically disturbed days are withdrawn from the analysis. But the authors conclude that it does not influence substantially the final results.
Figures of the Fig. 6 type make it possible to derive trends in NmF2 (foF2). The authors compare their results with some estimates of the trends in NmF2 and foF2 published by other groups and conclude that there is a reasonable agreement.
Important conclusion of the paper is that the trends in NmF2 (foF2) depend on the SA level. The trends are the lowest at low activity and the highest at high one.
I consider the paper as an important contribution to the studies (currently very popular) of the long-term changes in the dependence of ionospheric parameters on SA and the corresponding trends in these parameters first of all, in NmF2 (foF2). I recommend publishing the paper with minor revision. My comments are the following.
- “Figure 2. Juliusruh ionosonde hourly observations of NmF2”. What is shown actually? If the monthly mean values, then for which month? Do the data present daily averaging?
- In my opinion, the paper is overloaded by figures. I recommend withdrawing Figs 12 and 13. It could be done without a serious revision of the text.
Citation: https://doi.org/10.5194/angeo-2024-11-RC1
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