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A long-term trend in the F2-layer critical frequency as observed at Alma-Ata ionosonde station
© Gordiyenko et al.; licensee Springer. 2014
- Received: 31 March 2014
- Accepted: 3 September 2014
- Published: 17 October 2014
In this study, we combine monthly median values for the F2-layer critical frequency (foF2), measured at Alma-Ata ionosonde station [43.25°N, 76.92°E] between 1000 and 1400 (local time), with historical data on the monthly mean values for solar radio flux at 10.7 cm (F10.7) and the geomagnetic activity index (Ap) (available at http://www.swpc.noaa.gov/), over the period from 1957 to 2012. These data are used to derive long-term trends in the upper ionosphere and to discuss their importance in the context of coupling between solar and geomagnetic activity in the ionosphere at middle latitudes.
- Upper ionosphere
- Long-term changes (trends)
- Solar-ionosphere interactions
List of authors who derived long-term trends in foF2 and their findings
Site: name or number ( N) of stations
Years of observation
Trends (MHz y-1)
Sverdlovsk [56.43°N, 58.57°E]
N = 21, φ > 30°
N = 12
-0.024 (1400 local time), -0.054 (after sunset)
Mielich and Bremer (2013)
N = 124
-0.003 to 0.0038
Yue et al. (2006)
N = 19, [42.9°S to 62.0°N, ca. 130°E]
Juliusruh [54.6°N, 13.4°E]
-0.01 to -0.02
Ghabahou et al. (2013)
Ouagadougou [12.4°N, 358.5°E]
Khaitov et al. (2012)
Tomsk [56.5°N, 84.9°E]
-0.008 to -0.014
Slough [51.48°N, -0.57°E]
Potential drivers of long-term trends in foF2 are widely discussed by Yue et al. (2006), Lastovicka (2009), Danilov (2012), and references therein and include long-term variations in solar and geomagnetic activity, increasing concentrations of greenhouse gases (e.g., CO2, CH4) and anthropogenic changes to the ozone layer and the distribution of water vapor. Our study focuses on the role of solar and geomagnetic activity in long-term foF2 trends, using foF2 data routinely measured over Kazakhstan at the Alma-Ata ionosonde station [43.25°N, 76.92°E]. Data used in this study cover about five solar cycles between 1957 and 2012. Data measured at the Alma-Ata station between 1958 and 1994 have already been used to derive long-term trends, independent of geomagnetic activity (e.g., Danilov 2003). However, this study is the first to use the extended dataset up to the year 2012 to derive long-term trends in foF2 (we assume the trend is a long-term linear change in foF2 over the period between 1957 and 2012).
A higher-order (cubic) regression, as used by Chen et al. (2014), does not provide any significant improvement to the fit: R2 = 0.810324 for a second-order regression versus R2 = 0.810385 for a third-order regression). The regression defined in Equation 1 was then used to remove variations in foF2 related to the solar activity effect, allowing monthly absolute deviations (defined as ∆foF2 = foF2 - foF2′), which can potentially reveal long-term trends in foF2, to be calculated (Figure 2b). However, Figure 2b shows that the correlation between foF2 and F10.7 determined via Equation 1 only accounts for around 80% (R2 = 0.810324), of the variations in foF2 and the majority of the ∆foF2 variability linked to the 11-year solar cycle. Therefore, to obtain an independent picture of long-term trends in the upper ionosphere, the 11-year (132 months) running mean values of the monthly absolute deviations (∆foF2 132 ) were calculated over the entire dataset according to the method set out by Mikhailov (2006). This 11-year smoothing technique was also applied to the F10.7 and Ap datasets but reduced the available period for study to between 1962 and 2006.
Figure 5 displays the observed Ap values (black crosses) versus F10.7, together with the linear regression line (solid line), the variations in Ap related to solar forcing, and the variations in ∆Ap with time. Approximately 16% of the variations in the geomagnetic field can be explained by the linear relationship between geomagnetic and solar activities (R2 = 0.15798, Figure 5a) and the majority variations in ∆Ap are linked to the 11-year solar circle. Peaks in ∆Ap are slightly shifted (by about 2 to 3 years) relative to the falling phase of the 11-year solar cycle (Figure 5c). Taking this shift into account for the regression calculation did not result in a significantly better fit (R2 = 0.1698). These results show that the geomagnetic activity (described by Ap) is strongly linked to the solar cycle phase (solar activity is described by F10.7) and in this study, we were unable to exclude variations in foF2 related to geomagnetic activity. Analyzing geomagnetic data observed at Kakioka (Japan) and Gnangara (Australia) over almost five solar cycles, Yamazaki and Yumoto (2012) recently found that solar activity controls not only the stationary component of the geomagnetic solar quiet daily variation field (S q ) but also the annual and semi-annual components. They report that all three components have a positive linear correlation with sunspot numbers. Thus, the positive linear correlation between Ap and F10.7 found in this study confirms Yamazaki and Yumoto's findings and shows the existence of a long-term coupling between solar and geomagnetic activity that could be used to further our understanding of solar-terrestrial relations.
Our results also show that foF2 strongly depends on solar activity and shows a negative temporal trend between 1957 and 2012 (about -0.0038 MHz y-1), although the magnitude of this trend is probably too small value to be of practical use. However, it should be noted that the sign of the deduced trend can be dependent on choice of time period for trend analysis. Periods of increasing solar activity (1970-1984) are seen to correspond to positive trends in foF2 and periods of decreasing solar activity (1956-1968, 1986-2004) to negative trends in foF2 (Figure 3). Therefore, periods of several solar-cycle observations should be used to obtain reliable trend estimates from the data series.
In addition to the material presented above, we derived a picture of long-term changes in the upper ionosphere using annual mean values for Ap and F10.7 (Ap(12) and F10.7(12)) and annual median values for foF2 (foF2(12)). Following a similar method to that described above, Figure 4a,b shows the variations in the 11-year running means foF2(12) 132 , F10.7(12) 132 , and Ap(12) 132 for the analyzed period. Figure 4b shows that long-term trends are similar to those seen in Figure 3, which supports our conclusion that variations in Ap and foF2 are dominantly affected by solar cycles as represented by F10.7. One exception to this conclusion is the somewhat higher foF2 trend (-0.0075 MHz y-1) than that found using the regression method and including an F10.7 correction (-0.0038 MHz y-1). Table 1 shows that the higher foF2 trend is close to those calculated by Danilov (2002, 2003), Lastovicka et al. (2006, 2008b), Khaitov et al. (2012), and Ghabahou et al. (2013), whereas the weaker foF2 trend more closely matches that calculated by Mielich and Bremer (2013). Here, we can only note that twice removing the solar element of variations in foF2 (using the regression method and the 11-year running mean) provides a weaker foF2 trend than that obtained using only the 11-year smoothing.
In this study, we derived a picture of long-term trends in foF2 for the ionosphere, using data from the mid-latitude ionosonde station at Alma-Ata [43.25°N, 76.92°E] observed over about five solar cycles between 1957 and 2012. We showed that solar activity (as represented by F10.7) is significantly correlated with variations in foF2 and Ap. In addition to the well-known 11-year solar cycle, the Sun also exhibits a cycle of about 30-32 years, which matches the period of trends observed in Ap and foF2. A negative trend is seen in long-term variations in foF2 between 1957 and 2012, and the magnitude of this trend was found to be -0.0038 and -0.0075 MHz y-1 for monthly absolute deviations (∆foF2) and annual mean median foF2, respectively. This trend is considered too small to have practical meaning. It was found that 95% and 99% of the total variation in foF2(12) 132 could be explained by linear relationships between foF2(12) 132 and F10.7(12) 132 for periods increasing and decreasing solar activity, respectively. The remaining variations in foF2(12) 132 cannot be explained by solar activity.
We thank two anonymous reviewers for their careful reviews that helped significantly improve this manuscript. This research was supported by the Kazakhstan National Center for Space Research and Technology and funded through the Institute of Ionosphere (Research Project 011200290).
- Chen Y, Liu L, Le H, Wan W: How does ionospheric TEC vary if solar EUV irradiance continuously decreases? Earth Planets Space 2014, 66: 52. http://www.earth-planets-space.com/content/66/1/52 10.1186/1880-5981-66-52View ArticleGoogle Scholar
- Clilverd MA, Clark TDG, Clarke E, Rishbeth H: Increased magnetic storm activity from 1868 to 1995. J Atmos Solar-Terr Phys 1998, 60: 1047–1056. 10.1016/S1364-6826(98)00049-2View ArticleGoogle Scholar
- Clúa de Gonzalez AL, Gonzalez WD, Dutra SLG, Tsurutani BT: Periodic variation in the geomagnetic activity: a study based on the Ap index. J Geophys Res 1993, 98: 9215. 10.1029/92JA02200View ArticleGoogle Scholar
- Danilov AD: The method of determination of the long-term trends in the F2 region independent of geomagnetic activity. Ann Geophys 2002, 20: 511–521. doi:10.5194/angeo-20–511–2002 doi:10.5194/angeo-20-511-2002 10.5194/angeo-20-511-2002View ArticleGoogle Scholar
- Danilov AD: Long-term trends of fo F2 independent of geomagnetic activity. Ann Geophys 2003, 21: 1167–1176. doi:10.5194/angeo-21–1167–2003 doi:10.5194/angeo-21-1167-2003 10.5194/angeo-21-1167-2003View ArticleGoogle Scholar
- Danilov AD: Changes in the upper atmosphere and ionosphere over the last decades (Review, in Russian). á…Ÿ 2012. http://vestnik.geospace.ru/issues/iss1/article2.pdfGoogle Scholar
- Danilov AD: Trends in the F2 -layer parameters at the end of the 1990s and the beginning of the 2000s. J Geophys Res 2013, 118: 3712–3718. doi:10.1002/jgra.50352 doi:10.1002/jgra.50352Google Scholar
- Echer E, Rigozo NR, Nordemann DJ R, Vieira LEA: Prediction of solar activity on the basis of spectral characteristics of sunspot number. Ann Geophys 2004, 22: 2239–2243. SRef-ID: 1432–0576/ag/2004–22–2239 SRef-ID: 1432-0576/ag/2004-22-2239 10.5194/angeo-22-2239-2004View ArticleGoogle Scholar
- Ghabahou DA, Ehias G, Ouattara F: Long-term trend of foF2 at a West African equatorial station. J Geophys Res 2013, 118: 3909–3913. doi:10.1002/jgra.50381 doi:10.1002/jgra.50381 10.1002/jgra.50381View ArticleGoogle Scholar
- Khaitov R, Kolesnik S, Sarychev V: Seasonal, diurnal variations critical frequency in the F2 -layer over middle latitudes. Paper presented at the 7th IAGA/ICMA/CAWSES Workshop on Long-Term Changes and Trends in the Atmosphere, Buenos Aires, 11–14 September 2012.Google Scholar
- Lastovicka J: Global pattern of trends in the upper atmosphere and ionosphere: recent progress. J Atmos Solar-Terr Phys 2009, 71: 1514–1528. 10.1016/j.jastp.2009.01.010View ArticleGoogle Scholar
- Lastovicka J, Mikhailov AV, Ulich T, Bremer J, Elias AG, Ortis de Adler N, Jara V, Abarca del Rio R, Foppiano AP, Ovalle E, Danilov AD: Long-term trends in fo F2: a comparison of various methods. J Atmos Solar-Terr Phys 2006, 68: 1854–1870. 10.1016/j.jastp.2006.02.009View ArticleGoogle Scholar
- Lastovicka J, Akmaev RA, Beig G, Bremer J, Emmert JT, Jacobi C, Jarvis MJ, Nedoluha G, Portnyagin YI, Ulich T: Emerging pattern of global change in the upper atmosphere and ionosphere. Ann Geophys 2008, 26: 1255–1268. 10.5194/angeo-26-1255-2008View ArticleGoogle Scholar
- Lastovicka J, Yue X, Wan W: Long-term trends in foF2 : their estimating and origin. Ann Geophys 2008, 26: 593–598. 10.5194/angeo-26-593-2008View ArticleGoogle Scholar
- Mielich J, Bremer J: Long-term trends in the ionospheric F2 region with different solar activity indices. Ann Geophys 2013, 31: 291–303. 10.5194/angeo-31-291-2013View ArticleGoogle Scholar
- Mikhailov AV: Ionospheric long-term trends: can the geomagnetic control and the greenhouse hypotheses be reconciled? Ann Geophys 2006, 24: 2533–2541. 10.5194/angeo-24-2533-2006View ArticleGoogle Scholar
- Raspopov OM, Shumilov OI, Kasatkina EA, Turunen E, Lindholm M: 35-year climatic Bruckner cycle-solar control of climate variability. In Paper presented at the 1st Solar and space weather euro conference. “The Solar Cycle and Terrestrial Climate”, Santa Cruza de Tenerife, Tenerife, Spain; 2000:2000.Google Scholar
- Rishbeth H: A greenhouse effect in the ionosphere? Planet Space Sci 1990, 38: 945–948. 10.1016/0032-0633(90)90061-TView ArticleGoogle Scholar
- Rishbeth H, Roble RG: Cooling of the upper atmosphere by enhanced greenhouse gases – modelling of the thermospheric and ionospheric effects. Planet Space Sci 1992, 40: 1011–1026. 10.1016/0032-0633(92)90141-AView ArticleGoogle Scholar
- Yamazaki Y, Yumoto K: Long-term behavior of annual and semi-annual S q variations. Earth Planets Space 2012, 64: 417–423. 10.5047/eps.2011.01.014View ArticleGoogle Scholar
- Yue X, Wan W, Liu L, Ning B, Zhao B: Applying artificial neural network to derive long-term fo F2 trends in the Asia/Pacific sector from ionosonde observations. J Geophys Res 2006, 111: A10303. doi:10.1029/2005JA011577View ArticleGoogle Scholar
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