Geomagnetic control of the <i>fo</i>F2 long-term trends

Abstract

Abstract. Further development of the method proposed by Danilov and Mikhailov is presented. The method is applied to reveal the foF2 long-term trends on 30 Northern Hemisphere ionosonde stations. Most of them show signi®cant foF2 trends. A pronounced dependence of trend magnitude on geomagnetic (invariant) latitude is con®rmed. Periods of negative/positive foF2 trends corresponding to the periods of long-term increasing/ decreasing geomagnetic activity are revealed for the ®rst time. Pronounced diurnal variations of the foF2 trend magnitude are found. Strong positive foF2 trends in the post-midnight-early-morning LT sector and strong negative trends during daytime hours are found on the sub-auroral stations for the period with increasing geomagnetic activity. On the contrary middle and lower latitude stations demonstrate negative trends in the earlymorning LT sector and small negative or positive trends during daytime hours for the same period. All the morphological features revealed of the foF2 trends may be explained in the framework of contemporary F2-region storm mechanisms. This newly proposed F2-layer geomagnetic storm concept casts serious doubts on the hypothesis relating the F2-layer parameter long-term trends to the thermosphere cooling due to the greenhouse eect.

Ionospheric Trend Over Wuhan During 1947–2017: Comparison Between Simulation and Observation

“…This is probably due to the fact that some other factors not considered could result in ionospheric variations. These factors include the long-term geomagnetic activity variations (Mikhailov & Marin, 2000), the long-term gravity wave variations (Hoffmann et al, 2011), and even volcanic eruptions (Zhang, 2017;Zhang & Holt, 2013). In addition, the NCAR-TIEGCM model was used in the simulation in this study.…”

“…Their study shows that the thermosphere will cool by about 10 K as the CO 2 mixing ratio is doubled. After that, huge efforts have been made on the long-term trend study in the ionosphere, thermosphere, and even mesosphere-lower-thermosphere (MLT) region through data analysis (Bremer, 2001;Danilov & Mikhailov, 2001;Emmert et al, 2012;Fang et al, 2012;Mikhailov & Marin, 2000;Ogawa et al, 2014;Yue et al, 2006;Zhang et al, 2016;Zhang & Holt, 2013) or theoretical simulation (Cnossen et al, 2011;Qian et al, 2011;Rishbeth & Roble, 1992;Solomon et al, 2015;Yue et al, 2008) or theoretical analysis (Akmaev, 2012;Elias, 2009). The community has achieved a common view regarding the long-term trend of a variety of physical parameters and their drivers in the upper atmosphere through comprehensive data analysis and simulations as summarized in several review papers (e.g., Laštovička et al, 2006Laštovička et al, , 2012Qian et al, 2011).…”

Geomagnetic control of the midlatitude foF1 and foF2 long‐term variations: Recent observations in Europe

“…The next step was done by Mikhailov and Marin [2000] who have confirmed the dependence of f o F 2 trends on geomagnetic (invariant) latitude both for daytime and nighttime hours and have shown, for the first time, that there exist periods with negative and positive f o F 2 trends, which correspond to the periods of long-term increasing/decreasing geomagnetic activity. It was shown that trends (the sign) were strongly depended on the phase (rising/falling) of long-term varying geomagnetic activity, the 11 year running mean Ap index was considered as an indicator of these variations.…”

An Interactive Data Language software package to calculate ionospheric conductivity by using numerical models

“…In the case of the ionosphere, the long-term trends in electron density, and ion composition and temperature have been associated with three possible causes: increasing greenhouse gases (Robre and Dickinson [2], Hall and Cannon [3]), long-term variation in geomagnetic activity (Danilov and Mikhailov [4], Mikhailov and Marin [5]), and secular variation in Earth's magnetic field (Foppiano et al [6], Cnossen and Richmond [7]). Thus, long-term upper atmospheric observational data are necessary to understand the physical mechanism of the long-term variation in the upper atmosphere.…”