The best solar activity proxy for long-term ionospheric investigations

doi:10.1016/j.asr.2021.06.032

Advances in Space Research

Volume 68, Issue 6, 15 September 2021, Pages 2354-2360

https://doi.org/10.1016/j.asr.2021.06.032 Get rights and content

Highlights

•
The relationship between ionospheric parameters and solar activity proxies is investigated.
•
The best solar proxies are Mg II and F30 for foF2 and F10.7 for foE.
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Evolution of yearly average values of foF2 and foE is almost fully described by a linear dependence on the best solar proxies.
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Selection of a solar proxy used has impact on calculated long-term trends of both foF2 and foE.

Abstract

To select the best solar activity proxy is important for long-term trend or climatological studies of ionospheric parameters as well as for modeling. We deal with solar proxies for foF2 and foE analyses. The yearly average and monthly median values of foF2 and yearly values of foE of selected European stations with long and high-quality data series are used. Four solar proxies are utilized: F10.7, F30, Mg II and He II. Mg II and F30 are found to be the best solar proxies for both yearly and monthly foF2 values as well as for years of deep solar minima (2008–09, 2018–19). On the other hand, F10.7 is found to be the best solar proxy for yearly values of foE. The variability of yearly values of foF2 and foE is almost fully described by solar proxies and this relation is highly linear. Different solar proxies applied might result in somewhat different long-term trends of both foF2 and foE. All the results were derived for the European area.

Introduction

The ionosphere is created mainly by the solar ionizing flux. However, long and homogeneous datasets of the solar ionizing flux required for long-term trend studies are not available. Therefore solar proxies have to be used. However, there are various solar proxies and their application leads to somewhat different results. So we have to select the best solar proxy.

The problem of the best solar proxy has been studied to some extent. In the past the sunspot number R was often used. Laštovička et al., 2006, Mielich and Bremer, 2013 came to conclusion that for investigating long-term trends in foF2, F10.7 is better than R but they used R values before their re-evaluation. However, Deminov et al., 2020, Laštovička, 2021 used re-evaluated sunspot numbers (e.g., Clette et al., 2016) and came to the same conclusion for foF2 as well as foE. F10.7 replaced R in most of more recent long-term trend studies. On the other hand, Perna and Pezzopane (2016) recommend Mg II index for description of foF2 behavior in the deep solar minimum 2008/2009. Laštovička (2021) used F10.7, Mg II, R and solar H Lyman-alpha flux and came to conclusion that the optimum solar proxy for yearly average values of foF2 is Mg II followed by F10.7, whereas F10.7 outperforms Mg II for foE, whereas R and Lyman-alpha flux perform less well, even though not poorly.

Lean et al., 2011, Lastovicka et al., 2017 found Mg II to slightly outperform F10.7 for studying long-term changes of the global total electron content (G-TEC). Goncharenko et al. (2021) presented a new high-resolution empirical model for the ionospheric TEC based on data over 2000–2019. They used several solar proxies and based on daily values they found the solar EUV 0.05–105.05 nm flux from the FISM2 (Flare Irradiance Spectral Model) to be the best closely followed by Mg II. FISM2 is described by Chamberlin et al. (2020); it is based on SORCE XPS L4, SDO EVE, and SORCE SOLSTICE data, and extended in time using solar proxies like F10.7 or Mg II. However, non-extended FISM-2 flux are available only over a limited time interval. There are also other sophisticated solar EUV proxies like EUV flux proxy based on GOLD (Global‐scale Observations of the Limb and Disk) observations (Schmöller et al., 2021) used in TEC analyses but they are available usually over time interval insufficient for long-term trend studies. Gulyaeva et al. (2018) recommend Mg II as the best solar proxy for ionospheric modeling. Dudok de Wit and Bruinsma (2017) claim that F30, which correlates with Mg II better than F10.7, is more appropriate solar proxy for thermospheric mass density than F10.7. Vaishnav et al. (2019) used 12 different solar proxies and G-TEC derived from IGS maps over 1999–2017. They found that on time scales of 16–32 and 32–64 days, He II is the best solar proxy followed by Mg II, Lyman-alpha flux and F30 as the seconds, all with time delay of one day. Therefore it is necessary to check if He II and F30 perform better than Mg II and F10.7 for foF2 and foE long-term studies.

This paper is the final paper of series of three papers dealing with solar proxies for ionospheric studies. Laštovička (2019) found that the relationship between solar proxies is not stable with time; the dependence on solar proxies is steeper than before for foF2 after ~1996 and for foE after ~2000. Laštovička (2021) used solar proxies F10.7, F30, Mg II and solar H Lyman-aplha flux and found Mg II to be the best solar proxy for foF2 and F10.7 for foE. Here we extend these investigations by including two other solar proxies, which are potential candidates for the best proxy according to Dudok de Wit and Bruinsma (2017) – F30 - and Vaishnav et al. (2019) – He II. Moreover I analyze not only yearly average values as in my previous papers but for foF2 also monthly median values and conditions of very deep solar activity minima, when the ionosphere can behave in a specific way (e.g., Buresova et al., 2014).

The objective of this study is to find the best solar proxies for long-term foF2 and foE investigations. Specifically answers to three questions are searched for:

(1) What is the best solar proxy for studying long-term evolution of yearly average values of foF2 and foE?

(2) What is the best solar proxy for reproducing foF2 yearly values in deep solar minima?

(3) What is the best solar proxy for season-representing monthly values of foF2 (January, April, July, October)?

For this purpose we use foF2 from three representative European ionospheric stations and foE with long and homogeneous data series, and four solar proxies F10.7, F30, He II and Mg II. Whereas for foF2 we will deal with all three questions, for foE we will only deal with question (1). For (2), July data on foE are less reliable due to the often presence of screening Es layer, i.e. missing foE. As for (3), foE recent data from the studied period suffer with data problems (Laštovička et al., 2016, Laštovička, 2019, Araujo-Pradere et al., 2019).

Section 2 describes data and methods used, section 3 deals with results and discussion for foF2, section 4 deals with results and discussion for foE, and section 5 contains conclusions.

Section snippets

Data and methods

The F2-layer critical frequency foF2 data of a north–south chain of European stations Juliusruh (54.6^oN, 13.4^oW), Pruhonice (49.98^oN, 14.55°E) and Rome (41.8^oN, 12.5^oE) and the E-layer critical frequency foE of Juliusruh and Slough/Chilton (51.5^oN, 1.3^oW) are used. Historical foF2 data were taken from http://www.ukssdc.ac.uk/wdcc1/iono_menu.html, more recent data from http://spidr.ionosonde.net/spidr and http://giro.uml.edu/ except for Rome, where data were taken from //www.eswua.ingv.it/ingv/i_rom.php

Results and discussion – foF2

Equation (1) may be used only if it describes a large majority of total variance of ionospheric parameters studied. Table 1 presents the percentage of the total variance of yearly average values of foF2, calculated as square of correlation coefficient. 98% and more of the total variance of yearly values of foF2 are described by equation (1) with Mg II, F30 and F10.7. This means that we may use Eq. (1), that the solar activity quite dominantly controls the yearly values of foF2, and that the

Results and discussion – foE

Table 4 shows that Eq. (1) can be well used for yearly average values, as it describes 99% of the total variance of foE with F10.7 for both stations Juliusruh and Slough/Chilton. It also reveals F10.7 as candidate for the best solar proxy for foE.

Another criterion is to use the mean absolute differences between observed and model (Eq. (1)) values of foE in MHz for Juliusruh and Slough/Chilton, 1976–1999 in a similar way as for foF2 in Table 2. Table 5 shows the mean absolute differences for

Conclusions

This paper finalizes a series of papers (Laštovička, 2019, Laštovička, 2021) dealing with dependence of ionospheric parameters, particularly of foF2, on solar activity proxies using a long data series (1976–2014) for selected European ionosonde stations and six solar activity proxies. The main relevant conclusions of the previous two papers based on yearly average values and four solar proxies are as follows:

(a)
The dependence of foF2 on solar activity proxies differs in periods 1976–1995 and

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

Support by the Czech Science Foundation under grants 18‐01625S and 21-03295S is acknowledged. Thanks to all those who contributed to creation of long‐term series of ionospheric data and solar proxies.

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View full text

The best solar activity proxy for long-term ionospheric investigations

Highlights

Abstract

Introduction

Section snippets

Data and methods

Results and discussion – foF2

Results and discussion – foE

Conclusions

Declaration of Competing Interest

Acknowledgements

Adv. Space Res.

J. Atmos. Sol.-Terr. Phys.

Adv. Space Res.

J. Atmos. Sol.-Terr. Phys.

J. Atmos. Sol.-Terr. Phys.

Critical issues in ionospheric data quality and implications for scientific studies

Radio Sci.

Preface to topical issue: recalibration of the sunspot number

Solar Phys.

Solar activity indices for ionospheric parameters in the 23rd and 24th cycles

Geomagn. Aeron.

Solar activity indices for ionospheric parameters in the 23^rd and 24^th cycles