Seasonal variation and solar activity dependence of the quiet-time ionospheric trough

2014 ◽  
Vol 119 (8) ◽  
pp. 6774-6783 ◽  
Author(s):  
T. Ishida ◽  
Y. Ogawa ◽  
A. Kadokura ◽  
Y. Hiraki ◽  
I. Häggström
2017 ◽  
Vol 122 (10) ◽  
pp. 10,796-10,810 ◽  
Author(s):  
Atsuki Shinbori ◽  
Yukinobu Koyama ◽  
Masahito Nosé ◽  
Tomoaki Hori ◽  
Yuichi Otsuka

2021 ◽  
Vol 5 (4) ◽  
pp. 1-9
Author(s):  
K. K. Ajith ◽  
◽  
S. Tulasi Ram ◽  
GuoZhu Li ◽  
M. Yamamoto ◽  
...  

2021 ◽  
Vol 39 (5) ◽  
pp. 929-943
Author(s):  
Adriane Marques de Souza Franco ◽  
Rajkumar Hajra ◽  
Ezequiel Echer ◽  
Mauricio José Alves Bolzan

Abstract. Seasonal features of geomagnetic activity and their solar-wind–interplanetary drivers are studied using more than five solar cycles of geomagnetic activity and solar wind observations. This study involves a total of 1296 geomagnetic storms of varying intensity identified using the Dst index from January 1963 to December 2019, a total of 75 863 substorms identified from the SuperMAG AL/SML index from January 1976 to December 2019 and a total of 145 high-intensity long-duration continuous auroral electrojet (AE) activity (HILDCAA) events identified using the AE index from January 1975 to December 2017. The occurrence rates of the substorms and geomagnetic storms, including moderate (-50nT≥Dst>-100nT) and intense (-100nT≥Dst>-250nT) storms, exhibit a significant semi-annual variation (periodicity ∼6 months), while the super storms (Dst≤-250 nT) and HILDCAAs do not exhibit any clear seasonal feature. The geomagnetic activity indices Dst and ap exhibit a semi-annual variation, while AE exhibits an annual variation (periodicity ∼1 year). The annual and semi-annual variations are attributed to the annual variation of the solar wind speed Vsw and the semi-annual variation of the coupling function VBs (where V = Vsw, and Bs is the southward component of the interplanetary magnetic field), respectively. We present a detailed analysis of the annual and semi-annual variations and their dependencies on the solar activity cycles separated as the odd, even, weak and strong solar cycles.


2018 ◽  
Vol 8 ◽  
pp. A45 ◽  
Author(s):  
Yury V. Yasyukevich ◽  
Anna S. Yasyukevich ◽  
Konstantin G. Ratovsky ◽  
Maxim V. Klimenko ◽  
Vladimir V. Klimenko ◽  
...  

For the first time, by using a regression procedure, we analyzed the solar activity dependence of the winter anomaly intensity in the ionospheric F2-layer peak electron density (Nm F2) and in the Total Electron Content (TEC) on a global scale. We used the data from global ionospheric maps for 1998–2015, from GPS radio occultation observations with COSMIC, CHAMP, and GRACE satellites for 2001–2015, and ground-based ionosonde data. The fundamental features of the winter anomaly in Nm F2 and in TEC (spatial distribution and solar activity dependence) are similar for these parameters. We determined the regions, where the winter anomaly may be observed in principle, and the solar activity level, at which the winter anomaly may be recorded in different sectors. A growth in geomagnetic disturbance or in the solar activity level is shown to facilitate the winter anomaly intensity increase. Longitudinal variations in the winter anomaly intensity do not conform partly to the generally accepted Rishbeth theory. We consider the obtained results in the context of spatial and solar cycle variations in O/N2 ratio and thermospheric meridional wind. Additionally, we briefly discuss different definitions of the winter anomaly.


2016 ◽  
Vol 34 (12) ◽  
pp. 1191-1196 ◽  
Author(s):  
Jan Laštovička ◽  
Dalia Burešová ◽  
Daniel Kouba ◽  
Peter Križan

Abstract. Global climate change affects the whole atmosphere, including the thermosphere and ionosphere. Calculations of long-term trends in the ionosphere are critically dependent on solar activity (solar cycle) correction of ionospheric input data. The standard technique is to establish an experimental model via calculating the dependence of ionospheric parameter on solar activity from the whole analysed data set, subtract these model data from observed data and analyse the trend of residuals. However, if the solar activity dependence changes with time, the solar correction calculated from the whole data set may result in miscalculating the ionospheric trends. To test this, data from two European ionospheric stations – Juliusruh and Slough/Chilton – which provide long-term reliable data, have been used for the period 1975–2014. The main result of this study is the finding that the solar activity correction used in calculating ionospheric long-term trends need not be stable, as was assumed in all previous investigations of ionospheric trends. During the previous solar cycle 23 and the current solar cycle 24, the solar activity correction appears to be different from that for the previous period and the Sun seems to behave in a different way than throughout the whole previous era of ionospheric measurements. In future ionospheric trend investigations the non-stability of solar activity correction has to be very seriously taken into account, because it can substantially affect calculated long-term trends of ionospheric parameters.


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