Is the Relation Between Ionospheric Parameters and Solar Proxies Stable?

Abstract

The relationship between ionospheric parameters and solar activity proxies is important for long-term studies as ionospheric climatology or long-term trends and for modeling. It has been broadly assumed that this relationship is stable with time. Using foF2 and foE of four European stations with long (1976-2014) data series, Juliusruh, Pruhonice, Rome, and Slough/Chilton, we show that it is not quite correct assumption. The dependence of yearly average values of ionospheric parameters on solar activity proxies appears to be steeper in 1996-2014 than in 1976-1995 for foF2 and steeper after 2000 for foE. Also, the relationships among solar activity proxies seem to change. Yearly values of foF2 and foE are very predominantly controlled by solar activity represented by proxies. Plain Language SummaryThe ionosphere is created by solar ionizing radiation. However, its continuous measurements for long-term studies of the ionosphere are not available; therefore, we use various proxies of solar activity. It has been broadly assumed that the relationship between ionospheric parameters and solar activity proxies is stable with time. Here we show that this is not the case. This relationship changed since the beginning of the 21st century. This should be taken into account in studies of ionospheric climatology and long-term trends and in ionospheric modeling.

On the relation between ionospheric parameters and sunspot number

“…For the high-latitude F2-layer, there is a distinct increase in dependence of critical frequency on sunspotnumber in 1996, in full agreement with similar observations at mid-latitude (Lastovicka, 2019). A somewhat gradual decrease in dependence can be seen between 1960 and 1995.…”

“…For each parameter, the solar dependence is demonstrated by a linear regression including the 95% confidence limits (Working & Hotelling, 1929): 2.1 AE 0.1 MHz/100 sunspots, for foF2 and a high degree of confidence; 0.2 AE 0.1 MHz/100 sunspots, for foE and a considerably lower degree of confidence. The latter, foE, demonstrates the much weaker dependence compared with foF2 as shown by Lastovicka (2019), but considerably more variable, reflecting the mechanisms in the auroral zone. A caveat here is that sunspot-number can be used as a proxy for f10.7 flux, although Lastovicka (2019) suggests this may not be as well defined as hitherto assumed.…”

“…The latter, foE, demonstrates the much weaker dependence compared with foF2 as shown by Lastovicka (2019), but considerably more variable, reflecting the mechanisms in the auroral zone. A caveat here is that sunspot-number can be used as a proxy for f10.7 flux, although Lastovicka (2019) suggests this may not be as well defined as hitherto assumed.…”

“…Centre row: regressions on yearly total sunspot numbers obtained from WDC SILSO, Royal Observatory of Belgium; dashed lines show the 95% confidence limits and annotation shows the slopes of the regression and 1-σ uncertainty. Bottom row: 11-year running regression on corresponding sunspot number, replicating the approach of Lastovicka (2019); vertical bars and shading indicate 1-σ uncertainties.…”

“…Upper atmosphere trends or change can reflect corresponding ones in the troposphere (Hall et al, 2007;Roble & Dickinson, 1989), but at an altitude not directly influenced by local short-term effects. One endeavours to establish the mechanisms responsible for observed trends, one contender being solar forcing: the focus of this study and that of Lastovicka (2019). Once this effect has been removed, it may be possible to identify others, including anthropogenic causes, if any.…”