Ionospheric foF2 variability over the Southeast Asian sector

Abstract

This paper presents the diurnal, seasonal, and solar activity impacts on the variability of ionospheric foF2 over the Southeast Asian sector. Data from three ionosonde stations, namely, Manila (14.7°N, 121.1°E, dip 14.7°N), Okinawa (26.3°N, 127.8°E, dip 36.8°N), and Vanimo (2.7°S, 141.3°E, dip 22.5°S), were used for the investigation via the standard deviation approach. The diurnal analysis revealed that foF2 is more susceptible to variability during the nighttime than the daytime. The observed variability is characterized by two peaks: a postsunset peak (15%–50%; corresponding to 3–14 MHz for the mean foF2 values) and a postmidnight peak (18%–68%; corresponding to 2–9 MHz for the mean foF2 values). Seasonally, the trend of the foF2 variability maximum does not follow any typical pattern (no particular season has a leading edge over others) for all levels of solar activity. On average the foF2 variability maximum was observed at the Vanimo station during low‐ and high‐solar‐activity years (1986 and 1989, respectively). During the moderate‐solar‐activity year (1983), the foF2 variability maximum was observed at the Manila station. With the exception of the Okinawa data, where little or no difference in the foF2 variability peaks during the low‐ and moderate‐solar‐activity years was noticed, foF2 variability increases with decreasing solar activity at all stations.

Variability of foF2 over Rome and Gibilmanna during three solar cycles (1976‐2000)

“…On the contrary, percentage ionospheric variability is always greater for LSA in the hourly ranges 08:00–16:00 UT and 15:00–21:00 UT in winter and equinoctial months respectively, and in the hourly ranges 00:00–03:00 UT and 17:00–23:00 UT during summer months. These results agree with the outcome of several low latitude investigations [ Bilitza et al , 2004; Ezquer et al , 2004; Akala et al , 2010] where it is shown that ionospheric variability increases as solar activity decreases.…”

“…In order to widen this investigation, according to Bilitza et al [2004] and Akala et al [2010], the following relative standard deviation ( σ r.s.d. ) was also calculated: In addition, starting from the relative standard deviation, the following monthly averages were calculated: and a new index, similar to those defined in and , was defined to explore again f o F 2 variability on a monthly basis.…”

“…From a careful comparison between Figures 4 and 7, it comes out that for many cases the variability peaks do not clearly emerge from the diurnal trends depicted in Figure 4. This because absolute standard deviation is used instead of normalized standard deviation [ Bilitza et al , 2004; Akala et al , 2010], which has the effect of highlighting day‐to‐night differences. In fact, when the relative standard deviation is employed several variability peaks, especially before sunrise, and not observed with the absolute standard deviation, are highlighted for almost all months.…”

“…Therefore, standard deviation seems to be appropriate to identify periods in which the observed variations of f o F 2 are not significant. For these reasons, this parameter was widely used to investigate ionospheric variability [ Forbes et al , 2000; Rishbeth and Mendillo , 2001; Bilitza et al , 2004; Akala et al , 2010].…”

On the Sources of the Ionospheric Variability in the South American Magnetic Anomaly During Solar Minimum

“…In order to quantify the ionospheric variability over Santa Maria, which is the focus of this paper, we use two methods for analyzing the data: (1) using the mean values approach and (2) using the CV, also known as relative standard deviation, as an index of variability. The CV has been used for several authors to express the variability in the ionospheric parameters (Akala et al, ; Forbes et al, ; Rishbeth & Mendillo, ; Somoye & Akala, ; Tsagouri et al, ; Zhang & Holt, , among others). The CV is statistically defined in Equation as …”