Long-term behavior of annual and semi-annual Sq variations
© The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS); The Seismological Society of Japan; The Volcanological Society of Japan; The Geodetic Society of Japan; The Japanese Society for Planetary Sciences; TERRAPUB 2012
Received: 12 April 2010
Accepted: 31 January 2011
Published: 27 July 2012
We have examined the long-term behavior (solar-cycle time scale) of annual and semi-annual Sq variations. We analyzed geomagnetic data observed at locations that were roughly geographically conjugate in the west Pacific region (Kakioka and Gnangara) during the last five solar cycles (1953–2006). Three-year compound data were constructed for each station for each year. The stationary component , annual component , and the semi-annual component , of the Sq variations were derived from the compound data. The solar-activity dependence of the derived three components was evaluated in comparison with the sunspot number . It was found that the amplitudes of all three components ( and ) have a positive linear correlation with the sunspot number. The most remarkable result is that the linear regression coefficient for is much bigger than those of and . The physical mechanisms involved are yet to be understood.
Key wordsS q ionosphere ionospheric current ionospheric conductivity solar activity sunspot number geomagnetism geomagnetic field
Since Wolf’s discovery, in 1859, of the dependence of Sq amplitudes on the sunspot number, this relation has been extensively studied. It is known that there exists an almost linear relationship between the sunspot number and Sq amplitudes. The early work on this subject was summarized by Chapman and Bartels (1940). Yacob and Prabhavalkar (1965) and, in the following year, Yacob and Radhakrishna Rao (1966) examined Sq(H), as observed at Alibag (18.6° north in geographic coordinates) from 1905 to 1960, and concluded that the increase of daily Sq(H) amplitudes with increasing solar activity is due to the effect of solar activity on the ionization intensity. They also pointed out that solar activity controls not only the amplitudes but also controls the phase of the diurnal Sq(H) component, that is, the maximum of the Sq(H) tends to occur at a later time of the day in greater-sunspot years. Rastogi and Iyer (1976) explained this as a combination effect of ionospheric conductivity and electric field. Later, Vikramkumar et al. (1984) supported their idea after examining VHF back-scatter radar data. Briggs (1984) pointed out that Sq amplitudes correlate with the solar radio emission at 10.7 cm (F10.7). He also showed evidence for the effect of 27-day solar rotation on the Sq amplitude. Takeda (1999, 2002a) found that the intensity of the equivalent Sq current system at a solar maximum is about twice as large as that at a solar minimum. Takeda (2002b) showed that the solar-activity dependence of the Sq variation is explained as an effect of the local ionospheric conductivity.
It has been known for many decades that the Sq field shows annual and semi-annual variations. The annual and semi-annual Sq variations have been observed worldwide (e.g., Wagner, 1969; Campbell, 1982; Rastogi et al., 1994; Yamazaki et al., 2009). Rastogi and Iyer (1976), and Rastogi et al. (1994) demonstrated a linear relationship between the yearly-averaged Sq(H) range and the amplitude of semi-annual Sq variations at the dip-equatorial latitudes, which indicates a significant influence of solar activity on the semi-annual Sq variations. They did not produce any evidence for a dependence on solar activity for the amplitudes of the annual Sq variations at these latitudes. Briggs (1984) and Hibberd (1985) analyzed the difference value of the H component of the geomagnetic field, as observed at two observatories having in the same longitude but different latitudes. This method enabled them to estimate ionospheric current intensities even for magnetically-disturbed days. They could also find evidence of a dependence on solar activity for the semi-annual Sq variation. Vertlib and Wagner (1977) examined the latitudinal distributions of annual and semi-annual Sq variations. They pointed out that an increase of solar activity causes an increase in the amplitude for both annual and semi-annual components, but almost no change in their latitudinal distributions. Campbell and Matsushita (1982) showed that the semi-annual Sq variations are distinct only during solar maximum periods by comparing external equivalent currents during maximum and minimum solar activity. Later, Stening (1995) showed that semi-annual variations exist in the strength of the Sq current system even during solar minimum periods. Stening (1991) found that the semi-annual Sq variation near the dip equator is clear in the morning hours, but practically disappears in the afternoon.
2. Data Set and Analysis
A list of the magnetic observatories used in this study, with geographic and geomagnetic coordinates and the period for which data are available.
3. Results of Data Analysis
The slope a and intercept b of the best-fit linear regression line with their 95% confidence interval.
a (aup − alow) ×104
b (bup − blow)
When we compare the slope a at Kakioka with that at Gnangara, it can be seen that the slope a at Kakioka is a little smaller than that at Gnangara for all three components ( , and ). This is expected, as Kakioka is located at a slightly higher geographic latitude than Gnangara. The lower-latitude ionosphere can receive more EUV flux in a year. Earlier, Rastogi et al. (1994) pointed out greater solar cycle effects with decreasing latitude. We found this feature holds true for the annual and semi-annual Sq components as well as the stationary component.
The principal source of the quiet daily variation of the geomagnetic field (Sq variation) is the electric current flowing in the ionospheric E region (90–150 km), which is generated by the movement of conducting air across the Earth’s main field (Richmond, 1979, 1989, 1998). Although the ionospheric current can induce secondary currents in the conducting earth, the secondary current does not make any difference to the solar-activity dependence of the Sq field because the intensity of the secondary current proportionally increases with increasing ionospheric current intensity (Malin et al., 1975).
It is also known that the daily geomagnetic field variation is modulated, depending on the position of the Moon. This effect is probably due to the modulation of the ionospheric dynamo by the Moon’s gravitational forces. The equivalent current derived from this geomagnetic effect is called the L current and its magnitude is about one tenth of the Sq current (Campbell, 1980). The solar-activity dependence of the L current is still controversial (Chapman et al., 1971; Malin et al., 1975). Since our analysis is based on three-year compound data, the L effect should be averaged out.
Residual effects of geomagnetic disturbances might affect our result. It is known that semi-annual variations exist in the geomagnetic activity. These variations are a result of a semi-annual variation of the southward component of the solar-wind magnetic field and is known as the Russell-McPherron effect (Russell and McPherron, 1973). It does not seem, however, that the semi-annual variation due to the Russell-McPherron effect is correlated with solar activity, and the expected phase, as predicted by this mechanism (5 April), is different from the observed phase (before March 21). Le Mouël et al. (2004) examined the long-term behavior of the semi-annual component of the geomagnetic activity index (aa-index). They reported that the phase of the semi-annual component of the aa-index is likely to occur between 21 March and 5 April, which is obviously different from ours. Therefore, the contribution of the residual geomagnetic disturbance to our results is expected to be small.
It has been known for a long time that the diurnal tidal wind field plays a primary role in the formation of the two-vortex pattern of the equivalent Sq current system (Maeda, 1955; Kato, 1956). Yamazaki et al. (2009) found that the equivalent Sq current system undergoes semi-annual variations keeping its two-vortex pattern. Thus, they naturally concluded that the diurnal tidal wind field causes the semi-annual Sq variations. For the annual Sq variations, Yamazaki et al. (2009) pointed out that the equivalent Sq current system for the annual Sq variations is characterized by a single-vortex pattern (see Fig. 1 of this paper). The single-vortex pattern for the annual component is consistent with the result by Winch (1981). Probably, the single vortex pattern for the annual component results from the greater intensity of Sq currents in the summer hemisphere than the winter hemisphere: During the June solstice, the higher-latitude annual currents are westward in the Northern Hemisphere and eastward in the Southern Hemisphere, and thus the northern Sq current vortex is strengthened and the southern Sq current vortex is weakened. During the December solstice, the higher-latitude annual currents are eastward in the Northern Hemisphere and westward in the Southern Hemisphere, and thus the northern Sq current vortex is weakened and the southern Sq current vortex is strengthened. Seasonal variations of the ionospheric conductivity and winds contribute to the annual variation of Sq currents. Although it seems that the neutral wind plays a very important role in the seasonal change of the equivalent Sq current system, the solar-cycle variations of neutral winds and electric fields in the dynamo region have not, unfortunately, been observationally established. Such information is required in order to separate their contributions from the local ionospheric conductivity effect.
What is established in this study is that the solar activity controls not only the stationary component of the Sq fields, but also their annual and semi-annual components. All three components ( , and ) have a positive linear correlation with the sunspot number. It is remarkable that the linear-regression coefficient for is much bigger than those of and . This difference in the solar-activity dependence of the stationary and seasonal Sq components may be directly related to physical mechanisms causing them. In addition, the linear-regression coefficients for and are similar in magnitude, which suggests that there is a common physical mechanism behind the dependences of and on solar activity. The physical mechanisms behind the solar-activity dependence of the seasonal Sq components are yet to be understood.
The present study has greatly enhanced our knowledge of the dependence of Sq fields on solar activity. Currently, the sunspot number is widely used for monitoring solar activity. However, as the sunspot number is based on a visual count of the number of individual spots, Sq field components may be able to monitor solar activity more accurately than current methods using the sunspot number. Such a practical use of Sq fields for space weather monitoring is worthy of further development.
The authors wish to thank Kakioka Magnetic Observatory (http://www.kakioka-jma.go.jp/en/index.html) for providing geomagnetic field data observed at Kakioka. We also thank the World Data Center (WDC), Kyoto for providing geomagnetic field data observed at Gnangara. The sunspot number is produced by the Solar Influences Data Analysis Center (SIDC), World Data Center for the Sunspot Index, at the Royal Observatory of Belgium. The Kp index is provided by the German Research Center for Geosciences (GFZ) and can be downloaded from http://www-app3.gfz-potsdam.de/kp index/index.html. The first author is supported by a grant from the Research Fellowship of the Japan Society for the Promotion of Science (JSPS) for Young Scientists.
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