PUBLICATIONS
Journal of Geophysical Research: Space Physics
RESEARCH ARTICLE
10.1002/2013JA019212
Key Points:
• New occurrence probability of equatorial irregularities is derived
• Dependence of the irregularity occurrence on local time is identified
• The occurrence of plasma irregularities
is compared with scintillation
Correspondence to:
C.-S. Huang,
[email protected]
Citation:
Huang, C.-S., O. de La Beaujardiere, P. A.
Roddy, D. E. Hunton, J. Y. Liu, and S. P.
Chen (2014), Occurrence probability
and amplitude of equatorial ionospheric
irregularities associated with plasma
bubbles during low and moderate solar
activities (2008–2012), J. Geophys. Res.
Space Physics, 119, 1186–1199,
doi:10.1002/2013JA019212.
Received 9 JUL 2013
Accepted 6 JAN 2014
Accepted article online 8 JAN 2014
Published online 7 FEB 2014
Occurrence probability and amplitude of equatorial
ionospheric irregularities associated with
plasma bubbles during low and moderate
solar activities (2008–2012)
Chao-Song Huang1, O. de La Beaujardiere1, P. A. Roddy1, D. E. Hunton1, J. Y. Liu2,3, and S. P. Chen2
1
Air Force Research Laboratory, Kirtland AFB, New Mexico, USA, 2Institute of Space Science, National Central University,
Chung-Li, Taiwan, 3National Space Organization, Hsinchu, Taiwan
Abstract We present a statistical analysis of the occurrence probability of equatorial spread F irregularities
measured by the Communication/Navigation Outage Forecasting System satellite during 2008–2012. We use
different criteria (plasma density perturbations, ΔN, and relative density perturbations, ΔN/N0) to identify the
occurrence of ionospheric irregularities. The purpose of this study is to determine whether the occurrence
probability of irregularities is the same for different criteria, whether the patterns of irregularity occurrence
vary with solar activity and with local time, and how the patterns of irregularity occurrence are correlated
with ionospheric scintillation. It is found that the occurrence probability of irregularities and its variation with
local time are significantly different when different identification criteria are used. The occurrence probability
based on plasma density perturbations is high in the evening sector and becomes much lower after
midnight. In contrast, the occurrence probability based on relative density perturbations is low in the evening
sector but becomes very high after midnight in the June solstice. We have also compared the occurrence of
ionospheric irregularities with scintillation. The occurrence pattern of the S4 index and its variation with local
time are in good agreement with the irregularity occurrence based on plasma density perturbations but
are significantly different from those based on relative density perturbations. This study reveals that the
occurrence pattern of equatorial ionospheric irregularities varies with local time and that only the occurrence
probability of irregularities based on plasma density perturbations is consistent with the occurrence of
scintillation at all local times.
1. Introduction
A spectacular phenomenon in the nighttime equatorial ionosphere is the occurrence of large-scale plasma
bubbles [Woodman and La Hoz, 1976]. In the postsunset sector, a steep vertical gradient in the plasma density in
the bottomside equatorial F region forms because of the loss of molecular ions, and the prereversal enhancement
of the vertical plasma drift moves the F layer to high altitudes [Fejer et al., 1991, 2008]. The Rayleigh-Taylor
instability is excited in the bottomside of the lifted F layer and evolves into plasma bubbles [Kelley, 1989].
Recent measurements by the Communication/Navigation Outage Forecasting System (C/NOFS) satellite show
that plasma bubbles can be continuously generated near the sunset terminator for 12 h [Huang et al., 2012a].
Statistical studies have been conducted to determine the occurrence probability of equatorial plasma bubbles.
Oya et al. [1986] and Watanabe and Oya [1986] found that the occurrence probability of plasma bubbles has two
major peaks: one at ~22:00 LT and another at ~03:00 LT. Kil and Heelis [1998] and McClure et al. [1998] studied the
variations of the occurrence probability of plasma bubbles with latitude, longitude, and season. Huang et al. [2001,
2002] analyzed the dependence of the occurrence of plasma bubbles on geomagnetic and solar activity. Gentile
et al. [2006] derived the global distribution of equatorial plasma bubbles in the topside ionosphere. Su et al. [2008]
and Kil et al. [2009] found that the occurrence probability of plasma bubbles is correlated with the vertical plasma
drift in the postsunset sector. These statistical studies show that the occurrence probability of equatorial plasma
bubbles depends on local time, latitude, longitude, season, geomagnetic activity, and solar activity and that the
occurrence is highest at the African-Atlantic-American longitudes during the equinoctial season.
In previous studies, the standard deviation of ion density variations, σ, was used to identify the occurrence of
plasma bubbles and irregularities [Kil and Heelis, 1998; McClure et al., 1998; Su et al., 2006, 2008; Kil et al., 2009].
HUANG ET AL.
©2014. American Geophysical Union. All Rights Reserved.
1186
Journal of Geophysical Research: Space Physics
Solar Flux
240
180
The standard deviation is equivalent to relative
plasma density perturbations. A relative density
perturbation of 1% or so is relatively small and
may not represent a plasma bubble. In fact,
there is no generally accepted definition of how
deep a plasma depletion must be for being
termed a plasma bubble. In order to avoid
possible controversy of whether plasma density
perturbations with σ > 1% are plasma bubbles,
we will term the plasma density perturbations
as irregularities. We will use the two terms,
bubbles and irregularities, interchangeably.
(a)
120
60
0
Kp Index
8
(b)
6
4
2
0
2008
10.1002/2013JA019212
2009
2010
2011
2012
2013
Year
Figure 1. The 10.7 cm solar radio flux in solar flux unit (10
and the Kp index during 2008–2012.
22
Wm
2
1
Although the occurrence probability of equatorial plasma irregularities has been analyzed
extensively, several important issues require
further investigations.
Hz )
1. Most previous studies used the standard
deviation of ion density variations (equivalent to relative plasma density perturbations) to identify the occurrence of plasma irregularities [Kil and
Heelis, 1998; McClure et al., 1998; Su et al., 2006, 2008; Kil et al., 2009]. It is not known whether the patterns
of the occurrence probability will be different if other criteria are used to identify plasma irregularities.
2. The patterns of the occurrence probability in previous studies were derived primarily in the evening
sector. It is not understood whether and how the occurrence patterns vary with local time.
3. The patterns of the occurrence probability in previous studies were derived mostly under solar maximum
conditions. It is not known whether the occurrence patterns at solar minimum are the same as those at
solar maximum.
4. Ionospheric irregularities caused by plasma bubbles occur over seven orders of magnitude in spatial
scale, from hundreds of kilometers to less than 0.1 m, and produce radio signal scintillation. Global distributions of ionospheric scintillation were reported recently by Brahmanandam et al. [2012] and Carter
et al. [2013]. It is not well understood how the occurrence probability of plasma bubbles is related to
ionospheric scintillation.
In this study, we perform a statistical analysis of the occurrence probability of plasma bubbles detected by the
C/NOFS satellite. C/NOFS was launched into a low-inclination (±13° in geographic latitude) orbit in April 2008
during a deep solar minimum. The equatorial F region is, in general, quite low at solar minimum, and plasma
bubbles do not reach very high altitudes. The apogee and perigee of C/NOFS are 850 and 400 km, respectively.
The low-perigee and low-inclination orbit of C/NOFS is very suitable for studies of plasma bubbles at low solar
activity. In this study, we use different criteria to derive the occurrence probability of plasma bubbles and identify
how the occurrence patterns vary with solar activity and with local time. We will also compare the occurrence
probability of plasma bubbles with equatorial ionospheric scintillation.
2. Observations
We begin with the solar and geomagnetic activity. Figure 1 shows the 10.7 cm solar radio flux and the Kp
index during 2008–2012. The solar flux was small (70–90) and did not change much in 2008–2010. In 2011–
2012, the solar activity was enhanced, and the solar flux increased to 100–180. However, the solar flux level in
2011–2012 was still lower than that during previous solar maximum periods. We use the terms “low solar
activity” for 2008–2010 and “moderate solar activity” for 2011–2012 in this study. C/NOFS has been making
continuous measurements of the ionospheric ion density and ion drift velocity since May 2008. We will
analyze the C/NOFS data for the period of 2008–2010 and for the period of 2011–2012 separately, in order to
determine the occurrence probability of plasma bubbles at different solar activity levels. There were only a
few major magnetic storms during 2008–2012, and the Kp index was, in general, smaller than 4. The purpose
of this study is to identify the overall features of bubble occurrence at low and moderate solar activity. We will
not differentiate the bubble occurrence at different Kp levels.
HUANG ET AL.
©2014. American Geophysical Union. All Rights Reserved.
1187
Journal of Geophysical Research: Space Physics
GLat (deg)
ALT
October 17, 2011
10:06−10:37 UT
15
0
−15
700
600
(a)
500
400
Ni (m−3)
1012
1011
(b)
10.1002/2013JA019212
We use the same parameter as used by Su
et al. [2006, 2008] and Kil et al. [2009] to
identify the occurrence of equatorial ionospheric irregularities. The parameter, σ, is
defined as
h
i1=2
2
1 10
10 ∑ i¼1 ð logNi logN0i Þ
σð%Þ ¼ 100 1 10
10 ∑i¼1 logN 0i
(1)
1010
σ (%)
ΔN (x1011 m−3)
where Ni and N0i are the ion density and
the linearly fitted value at the ith data
1.5 (c)
point, respectively. Equation (1) represents
1.0
the standard deviation of ion density vari0.5
ations in logarithmic scale divided by the
mean of ion density in logarithmic scale.
0
Su et al. [2006, 2008] and Kil et al. [2009]
12 (d)
used the ion density data measured by
8
the first Republic of China satellite
(ROCSAT-1) to derive the occurrence of
4
plasma irregularities. In the study of Su
0
17
18
19
20
21
22
23
0
1
et al. [2006, 2008], N0i was the linearly
Local Time (hour)
fitted density over 10 s. Kil et al. [2009]
used an 11-point smoothing curve over
Figure 2. Example of equatorial ionospheric irregularities measured by the C/
100 s to calculate the mean of ion density
NOFS satellite on 17 October 2011. (a–d) The C/NOFS orbit, the ion density, the
ion density perturbations (ΔN), and the standard deviation of ion density variaand suggested that the location of plasma
tions (σ), respectively.
bubbles can be determined more accurately after detrending the data by using
the multipoint smoothing curve. In this study, we use the ion density data measured by the Planar
Langmuir Probe (PLP) on board C/NOFS. The original PLP measurements are made at 512 Hz, and the ion density data used in this study are the 1 s averages over the 512 samples per second. We use a moving average
over 60 s to calculate the mean ion density. C/NOFS has a low (13°) inclination orbit and flies almost along the
equator. The 1 s averaged data correspond to a longitudinal coverage of ~7 km. The mean ion density averaged over 60 s represents the average value over ~420 km in longitude.
Besides the standard deviation of ion density variations represented by σ, we will also use another parameter
defined by
1=2
1 10
ΔΝ ¼
∑i¼1 ðNi N0i Þ2
(2)
10
In fact, ΔN defined by equation (2) is the ion density perturbation averaged over 10 data points. Note that each
N0i is the average value at the ith data point over 60 s, and 10 successive N0i values are used to calculate each
value of ΔN. The parameter, σ, defined by equation (1) is equivalent to the relative plasma density perturbation
(ΔN/N0) and was used to calculate the occurrence probability of plasma irregularities in previous studies [Kil and
Heelis, 1998; McClure et al., 1998; Su et al., 2006, 2008; Kil et al., 2009]. We will use both σ and ΔN to derive the
patterns of the occurrence probability of ionospheric irregularities and determine whether and how significantly
the occurrence pattern depends on the choice of σ or ΔN.
Figure 2 shows an example of plasma irregularities measured by C/NOFS on 17 October 2011. In Figure 2a,
the blue line depicts the magnetic equator, the red line represents the latitude of C/NOFS, and the dashed
magenta line, labeled on the right, represents the altitude (in km) of C/NOFS. The ion density is plotted as a
function of solar local time at the satellite position in Figure 2b. A series of deep plasma depletions occurred
between 19:00 and 23:30 LT, and these depletions are plasma bubbles. Figure 2c shows the ion density perturbation, ΔN, defined by equation (2), along the satellite track. Figure 2d shows the σ value. It is clear that large
values of ΔN and σ occur in the locations of plasma bubbles.
HUANG ET AL.
©2014. American Geophysical Union. All Rights Reserved.
1188
Journal of Geophysical Research: Space Physics
10.1002/2013JA019212
There is no generally accepted definition of how large σ must be for the occurrence of plasma irregularities.
Kil and Heelis [1998] calculated the occurrence probability of irregularities for σ > 1% and 5% from data
measured by the Atmospheric Explorer-E (AE-E) satellite. McClure et al. [1998] also used AE-E data but took
σ > 0.5% to identify irregularities. Su et al. [2006, 2008] and Kil et al. [2009] used σ > 0.3% to identify the
occurrence of irregularities from ROCSAT-1 data. Obviously, higher σ value will result in lower occurrence rate.
In addition, the occurrence probability of plasma irregularities also depends on the latitudinal range of the
data coverage. Because plasma bubbles are generated near the magnetic equator and extend toward higher
latitudes when the bubbles reach higher altitudes, the irregularity occurrence probability derived using data
within a smaller latitude range from the magnetic equator will be higher than that derived using data within a
larger latitude range. C/NOFS is quite close to the magnetic equator. Its geographic latitudinal coverage is
±13°. We will use the data within ±10° magnetic latitude in this study and use σ > 1% to identify irregularities.
We first show the occurrence probability of ionospheric irregularities for σ > 1% at moderate solar activity during
2011–2012 for easy comparison with previous results that were derived under solar maximum conditions. The
altitude range of the C/NOFS orbit is between 400 and 840 km. We take the data in the altitude range of 400–
600 km for the current analysis. This is because plasma bubbles occur mostly at relatively low altitudes under low
and moderate solar activity. As mentioned earlier, we will use the data within ±10° magnetic latitude. The data
are binned by 2 h in local time and 20° in longitude. We also tried 10° bins in longitude and found that the
occurrence patterns with 10° bins, except for the appearance of some smaller-scale structures, are very similar to
those with 20° bins. We only present the results with 20° bins. We first calculate the total satellite orbits with
measurements over each LT-longitude bin for each month and the total satellite passages with occurrence of
σ > 1%. The occurrence probability is then calculated with the total occurrence passages divided by the total
satellite orbits with measurements. In the Peruvian sector, the geomagnetic equator is located at about 10°
geographic latitude, and C/NOFS samples only a few degrees, but not 10°, to the south of the magnetic equator.
However, the total number of C/NOFS orbits used to calculate the irregularity occurrence is still very large in this
longitudinal sector and ~500 for each monthly LT-longitude bin over a period of 4 years, so the statistical result
should be reliable.
Figure 3 shows the longitude-month distribution of the occurrence probability of ionospheric irregularities
during 2011–2012. The occurrence pattern varies significantly with local time. The occurrence probability at
19:00–21:00 LT (Figure 3a) is large only in October–November and at a few spots in other months. The pattern
of irregularity occurrence at 21:00–23:00 LT in Figure 3b is similar to that reported by [Gentile et al., 2006, their
Figures 3–5] and by [Kil et al., 2009, Figure 6]. The similarity between our results and the previous studies provide
confidence that the new results derived from C/NOFS measurements are reliable. However, the patterns of
irregularity occurrence at later local times become significantly different. At later local times in Figures 3c–3e,
high occurrence probability exists primarily between 60° and 60°. The variation of the occurrence pattern with
local time was not addressed in previous studies.
Figure 4 shows the occurrence probability of ionospheric irregularities at low solar activity during May 2008 to
December 2010. A surprising feature is that the occurrence probability is very low at 19:00–21:00 LT (Figure 4a)
but becomes very high at most longitudes after 23:00 LT in May–August (Figures 4c–4e). Equatorial plasma
bubbles occurred frequently after midnight in June 2008 and were detected by C/NOFS [e.g., Burke et al., 2009;
de La Beaujardière et al., 2009; Kelley et al., 2009; Heelis et al., 2010; Pfaff et al., 2010; Dao et al., 2011; Huang et al.,
2011, 2012b], which is represented by the high occurrence probability around the June solstice in the average
patterns. The low occurrence rate at early local times and the high occurrence rate at later local times may be
related to the local time variation of the ambient plasma density. The ambient plasma density is high in the
evening sector and decreases with local time at night. The relative density perturbations are small in the regions
with high ambient density but become large in the regions with low ambient density. The low altitude of the F
layer and the slow growth of plasma bubbles at solar minimum may be also a factor contributing to the high
occurrence of irregularities detected by C/NOFS after midnight. For example, the F peak altitude over Jicamarca
was ~300 km over the entire night during June 2008. Plasma bubbles could be excited in the evening sector but
could not reach the topside F layer in the evening sector. Instead, the bubbles might become fully developed
and reach the C/NOFS altitudes (400 km and higher) after midnight [Huang et al., 2011, 2012b]. The patterns of
irregularity occurrence and their variations with local time in Figure 4 are remarkably different from those in
Figure 3, suggesting that the occurrence pattern based on the standard deviation of ion density variations varies
significantly with solar activity.
HUANG ET AL.
©2014. American Geophysical Union. All Rights Reserved.
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Journal of Geophysical Research: Space Physics
10.1002/2013JA019212
(c) 23:00−01:00 LT
C/NOFS Measurements
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Plasma Density Irregularity Occurrence Probability
σ > 1.0%
Year: 2011−2012
Latitudinal Range: ±10o Magnetic Latitude
Longitudinal Bin: 20o
Altitude Range: 400−600 km
0
20
40
60
80
100
−180 −150 −120 −90 −60 −30
Occurrence Probability (%)
0
30
60
90 120 150 180
60
90 120 150 180
60
90 120 150 180
Longitude
(a) 19:00−21:00 LT
(d) 01:00−03:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
(b) 21:00−23:00 LT
(e) 03:00−05:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
Figure 3. The longitude-month distribution of occurrence probability of equatorial ionospheric irregularities for σ > 1% during 2011–2012.
We want to mention that we also used the relative perturbation of ion density (ΔN/N0) to calculate the occurrence probability of ionospheric irregularities. We used ΔN/N0 > 10% in linear scale to identify the irregularity
occurrence and found that the patterns of the occurrence probability based on the relative ion density perturbation (ΔN/N0) is exactly the same as those shown in Figures 3 and 4. As can be seen in equation (1), σ is
defined as the average value of the relative variations of the ion density over 10 data points. In contrast, ΔN/N0 is
the value at each data point without averaging. However, the occurrence probability based on the standard
deviation of ion density variations (σ) is the same as that based on the relative ion density perturbation (ΔN/N0)
because the occurrence probability is the average value over hundreds or even thousands of satellite passages.
For the calculation of the occurrence probability of ionospheric irregularities, the method using the standard
deviation of ion density variations is equivalent to the method using the relative ion density perturbation. We
will use the term, “relative density perturbation (ΔN/N0)”, to describe the standard deviation of ion density
variations σ thereafter. Throughout this paper, “relative density perturbation” means “relative perturbation of
the plasma/ion density”.
The patterns of the occurrence probability in Figures 3 and 4 are derived for σ > 1%. We now use the plasma
density perturbations, defined by equation (2), to calculate the occurrence probability of ionospheric irregularities. In fact, the plasma density perturbations, rather than the relative plasma density perturbations, are
HUANG ET AL.
©2014. American Geophysical Union. All Rights Reserved.
1190
Journal of Geophysical Research: Space Physics
10.1002/2013JA019212
(c) 23:00−01:00 LT
C/NOFS Measurements
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Plasma Density Irregularity Occurrence Probability
σ > 1.0%
Year: 2008−2010
Latitudinal Range: ±10o Magnetic Latitude
Longitudinal Bin: 20o
Altitude Range: 400−600 km
0
20
40
60
80
100
Occurrence Probability (%)
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
60
90 120 150 180
60
90 120 150 180
Longitude
(a) 19:00−21:00 LT
(d) 01:00−03:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
(b) 21:00−23:00 LT
(e) 03:00−05:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
Figure 4. The longitude-month distribution of occurrence probability of equatorial ionospheric irregularities for σ > 1% during May 2008 to
December 2010.
directly related to ionospheric scintillation. The square of the scintillation intensity index (S4) measured on
the ground is proportional to the variance of path-integrated plasma density perturbations [Rino, 1979a, 1979b;
Wernik et al., 2007]. Basu et al. [1976] found that the percentage occurrence contours of ΔN > 1 × 1010 m3
represent the worldwide equatorial morphology of percentage occurrence of scintillation ≥ 4.5 dB at 140 MHz.
Accordingly, we use ΔN > 1 × 1010 m3 as the criterion for identifying the occurrence of ionospheric irregularities.
Figure 5 shows the occurrence probability of ionospheric irregularities with ΔN > 5 × 1010 m3 during 2011–
2012. When we used ΔN > 1 × 1010 m3 to calculate the occurrence of irregularities, the occurrence probability is close to 100% at early local times for most longitudes and seasons during 2011–2012. Therefore, we
use a larger threshold of ΔN for 2011–2012 because plasma density perturbations are relatively strong at
moderate solar activity. The pattern of irregularity occurrence at 21:00–23:00 LT in Figure 5b is again very
similar to those at solar maximum reported by Gentile et al. [2006] and Kil et al. [2009]. However, the occurrence probability becomes much lower after 01:00 LT (Figures 5d and 5e). Figure 6 shows the occurrence
probability of ionospheric irregularities with ΔN > 1 × 1010 m3 during May 2008 to December 2010. The solar
activity was very low during this period, and ionospheric plasma perturbations were, in general, weak. Therefore,
we choose a smaller threshold (ΔN > 1 × 1010 m3) for 2008–2010. The longitude-month distribution of the
HUANG ET AL.
©2014. American Geophysical Union. All Rights Reserved.
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Journal of Geophysical Research: Space Physics
10.1002/2013JA019212
(c) 23:00−01:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
0
20
40
60
80
100
−180 −150 −120 −90 −60 −30
Occurrence Probability (%)
0
30
60
90 120 150 180
60
90 120 150 180
60
90 120 150 180
Longitude
(a) 19:00−21:00 LT
(d) 01:00−03:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
(b) 21:00−23:00 LT
(e) 03:00−05:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
10
Figure 5. The longitude-month distribution of occurrence probability of equatorial ionospheric irregularities for ΔN > 5 × 10 m
2011–2012.
3
during
occurrence probability and its variation with local time at low solar activity during 2008–2010 in Figure 6 are
similar to those at moderate solar activity during 2011–2012 in Figure 5. Because of this similarity, we can calculate the mean occurrence probability for the 5 year period (2008–2012). The data coverage for each longitude-month bin is increased, and the accuracy of the occurrence probability is improved. Figure 7 shows the
occurrence probability of ionospheric irregularities with ΔN > 1 × 1010 m3 for 2008–2012.
The occurrence probability at 19:00–21:00 LT in Figure 7a is high at almost all longitudes in the equinoctial
months (February–April and September–November). Huang et al. [2012a] found that plasma bubbles can be
continuously generated near the sunset terminator over a large longitudinal range covering Asia, Africa, and
the Atlantic region at equinox when the vertical ion drift at the prereversal enhancement is large enough. The
statistical pattern in Figure 7a represents this feature. The occurrence probability is low during the June solstice
except for longitudes near 0° and between 120° and 180°. The pattern at 21:00–23:00 LT in Figure 7b is similar to
that in Figure 7a. In Figure 7c, the occurrence probability at 23:00–01:00 LT remains high in the African-AtlanticAmerican sector (120° through 30°) during January–March and during October–December, but becomes
much lower at other longitudes except for a spot at 120–180° around April, another one around 0–30° in May,
and one at 150°–180° around September. At later local times (Figures 7d and 7e), the occurrence pattern
HUANG ET AL.
©2014. American Geophysical Union. All Rights Reserved.
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Journal of Geophysical Research: Space Physics
10.1002/2013JA019212
(c) 23:00−01:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
0
20
40
60
80
100
−180 −150 −120 −90 −60 −30
Occurrence Probability (%)
0
30
60
90 120 150 180
60
90 120 150 180
60
90 120 150 180
Longitude
(a) 19:00−21:00 LT
(d) 01:00−03:00 LT
Dec
Nov
Oct
Sep
Aug
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
0
30
Longitude
Longitude
(b) 21:00−23:00 LT
(e) 03:00−05:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
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Jan
−180 −150 −120 −90 −60 −30
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30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
10
Figure 6. The longitude-month distribution of occurrence probability of equatorial ionospheric irregularities for ΔN > 1 × 10 m
May 2008 to December 2010.
3
during
becomes rather irregular, and there is relatively high occurrence probability between 60° and 30° around
November. The overall occurrence probability decreases with local time. This decrease is related to the variation of
the ambient plasma density. The ambient plasma density is high at early local times near sunset and becomes very
low near dawn, and the amplitude of plasma density perturbations (ΔN) also decreases with local time at night.
The most important feature shown in Figure 7 is that the pattern of the occurrence probability varies with
local time. The occurrence probability does not decay with local time uniformly at all longitude. Instead, it
decreases much faster at some longitudes than other longitudes. The occurrence probability between 120°
and 30° remains high from 19:00 to 01:00 LT in January–March and in October–December (Figures 7a–7c). In
contrast, the occurrence probability at 30°–180° is high in equinoctial months at 19:00–21:00 LT but becomes
much lower at later local times. The occurrence probability is high between 90° and 180° in February–April at
19:00–21:00 LT (Figure 7a). However, this spot of high occurrence is in March–April at 21:00–23:00 LT
(Figure 7b) and further shifts to April–May at 23:00–01:00 LT (Figure 7c). An apparent minimum in the occurrence probability occurs at 60°–90° in Figures 7b–7e.
Shown in Figure 7 is the occurrence probability of irregularities for ΔN > 1 × 1010 m3 during 2008–2012.
Figure 8 shows the average amplitude of plasma density perturbations for ΔN > 1 × 1010 m3 for the same
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(c) 23:00−01:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
0
20
40
60
80
100
−180 −150 −120 −90 −60 −30
Occurrence Probability (%)
0
30
60
90 120 150 180
60
90 120 150 180
60
90 120 150 180
Longitude
(a) 19:00−21:00 LT
(d) 01:00−03:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
(b) 21:00−23:00 LT
(e) 03:00−05:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
10
Figure 7. The longitude-month distribution of occurrence probability of equatorial ionospheric irregularities for ΔN > 1 × 10 m
May 2008 to December 2012.
3
during
period. The patterns of the perturbation amplitude in Figure 8 are similar to the patterns of the occurrence
probability in Figure 7. The regions where large-amplitude perturbations occur frequently are the regions
where the occurrence probability is high. The patterns of the perturbation amplitude become more irregular
after 01:00 LT (Figures 8d–8e). This is because large-amplitude perturbations occur less frequently at later
local times. The data used in this study were measured by C/NOFS at different altitudes (between 400 and
600 km) and different latitudes (between ±10° magnetic latitudes). The ionospheric ion density has large
variations over this latitude-altitude range. When only limited events are available for calculating the average
value, it may have large variations.
Ionospheric irregularities cause radio scintillation, and the amplitude of ionospheric irregularities is directly related to the strength of scintillation. We now examine the occurrence of scintillation and use the S4 index to
represent the strength of scintillation. The S4 index data used in this study were derived from the signal-to-noise
ratio intensity fluctuations of the L1 channel of GPS radio occultation signals using FORMOSAT-3/COSMIC (F3/C)
satellites consisting of six identical microsatellites. F3/C were launched into a circular, 72° inclination orbit
at an altitude of 512 km in April 2006 and gradually dispersed into the final orbits at 800 km altitude during
the first 17 months [Cheng et al., 2006]. The procedure of deriving the S4 index from F3/C data and the
HUANG ET AL.
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(c) 23:00−01:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
10
10.5
11
11.5
−180 −150 −120 −90 −60 −30
log10(ΔN)
0
30
60
90 120 150 180
60
90 120 150 180
60
90 120 150 180
Longitude
(a) 19:00−21:00 LT
(d) 01:00−03:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
(b) 21:00−23:00 LT
(e) 03:00−05:00 LT
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
−180 −150 −120 −90 −60 −30
0
30
60
90 120 150 180
−180 −150 −120 −90 −60 −30
Longitude
0
30
Longitude
Figure 8. The longitude-month distribution of the average amplitude of equatorial ionospheric plasma density perturbations with
10
3
ΔN > 1 × 10 m during May 2008 to December 2012.
characteristics of the S4 index during 2008 were described by Brahmanandam et al. [2012]. They derived
the global S4 index maps in the altitude range of 0–800 km during different seasons and found that the
maximum S4 index near the magnetic equator (±5°) occurs in the altitude range of 200–400 km and below
the F peak at most times.
Figure 9 shows the longitude-month distribution of the maximum S4 index between 200 and 400 km in altitude
during May 2008 to December 2012. In order to compare with the occurrence of ionospheric irregularities
measured by C/NOFS, the S4 index data used in Figure 9 are also taken within ±10° magnetic latitudes with a
longitudinal bin of 20° for the same period as the C/NOFS data presented in Figures 7 and 8. It can be seen in
Figure 9 that the S4 index is large at 19:00–23:00 LT and becomes much smaller after 01:00 LT and that the
pattern of the S4 index varies with local time. The longitude-month distribution of the S4 index in Figure 9 is
very similar to that of irregularity occurrence probability and amplitude in Figures 7 and 8. Note that the S4
index shown in Figure 9 is the maximum S4 index. Scintillation occurs at all altitudes if plasma irregularities exist.
However, scintillation is the strongest at the altitude range with the maximum S4 index and becomes much
weaker at other altitudes [Brahmanandam et al., 2012]. The longitude-month distribution of the maximum S4
index in Figure 9 represents the distribution of equatorial ionospheric scintillation.
HUANG ET AL.
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Figure 9. The longitude-month distribution of the maximum S4 index derived from the measurements of the COSMIC F3 satellite during
May 2008 to December 2012.
The C/NOFS data used in this study were taken in the altitude range of 400–600 km. The perigee of C/NOFS is
400 km, and no data are available below 400 km in C/NOFS measurements. The high ambient plasma density
and its large variance caused by plasma bubbles produce high scintillation close and below the F layer peak.
The pattern of the occurrence probability and its variation with local time in Figures 7 and 8 are in good
agreement with those of the S4 index in Figure 9. This agreement occurs because the strength of scintillation
is related to the variance of plasma density perturbations [Rino, 1979a, 1979b; Wernik et al., 2007].
Although the plasma irregularities detected by C/NOFS and the maximum scintillation may exist at different
altitudes, the irregularities and scintillation have the same source: plasma bubbles. Plasma bubbles start to form
in the bottom side of the F layer. When plasma bubbles rise through the F peak and are detected by C/NOFS,
the lower portion of the same bubbles still exist in the bottom side of the F layer. In other words, most bubblerelated irregularities exist nearly simultaneously in the bottom and top side of the F layer. Statistically, the
topside and bottomside irregularities should have the same occurrence probability, and a strong correlation
between scintillation below the F peak and plasma irregularities above the F peak is expected, as evidenced in
Figures 7 and 9.
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3. Discussion
This study reveals new features of irregularity occurrence in the equatorial ionosphere. Figure 4 shows that
the occurrence probability based on relative density perturbations (ΔN/N0) is very high at late local times
(near and after midnight) at solar minimum during 2008–2010. The high relative density perturbations at late
local times are related to the low ambient plasma density. The occurrence probability is particularly high at
African-Asian-Pacific longitudes around the June solstice, which may suggest that the ambient plasma
density is very low at these longitudes during this season at deep solar minimum.
As the solar activity strengthens, the pattern of irregularity occurrence and its local time variation become
different. Figure 3 shows the occurrence probability, also based on relative density perturbations, at
moderate solar activity during 2011–2012. The high occurrence probability primarily exists at the AfricanAtlantic-American longitudes. These are the regions where spread F irregularities occur frequently, as presented
in previous studies [Gentile et al., 2006; Kil et al., 2009]. The previous studies show that the occurrence probability
has a minimum in the June solstice. In Figure 3 of our study, the occurrence probability at moderate solar activity also shows a minimum at early local times in the June solstice (Figures 3a and 3b). However, the occurrence
probability at these longitudes during this season becomes quite high near and after midnight (Figures 3c–3e).
The relative density perturbation used to calculate the occurrence probability in Figures 3 and 4 is the same
as the one used in previous studies [Kil and Heelis, 1998; McClure et al., 1998; Su et al., 2006, 2008; Kil et al.,
2009]. In this study, we also use a new method, the plasma density perturbation (ΔN) defined by equation (2),
to calculate the occurrence probability of ionospheric irregularities. The patterns of irregularity occurrence
based on plasma density perturbations are shown in Figures 5–7. The patterns of occurrence probability
based on relative density perturbations are substantially different from those based on plasma density perturbations. The occurrence probability based on relative density perturbations increases with local time, but
the occurrence probability based on plasma density perturbations decreases with local time. The occurrence
probability based on relative density perturbations has a large enhancement over most longitudes in the
June solstice, but the occurrence probability based on plasma density perturbations does not have such an
enhancement in this season.
Although both plasma density perturbations and relative density perturbations can be used as a measure for
the occurrence of ionospheric irregularities, only the pattern of irregularity occurrence based on plasma
density perturbations (ΔN) is consistent with the occurrence of scintillation. The patterns of irregularity occurrence and its variation with local time in Figure 7 are very similar to those of the S4 index in Figure 9. In
contrast, the pattern of the occurrence probability based on relative density perturbations shown in Figures 3
and 4 is significantly different from the pattern of the S4 index in two aspects. First, the strength of scintillation (the S4 index) decreases with local time, while the occurrence probability based on relative density
perturbations increases with local time. Second, the scintillation does not show large enhancements at AsianPacific longitudes in the June solstice, while the occurrence probability based on relative density
perturbations does.
The results of this paper have significant implications on low-latitude ionospheric space weather and applications. Plasma bubbles and related spread F irregularities are the most significant perturbations in the
nighttime low-latitude ionosphere and produce radio signal scintillation. Severe scintillation causes degradation or disruption of communication, navigation, and surveillance systems. Empirical patterns of irregularity occurrence, once parameterized with appropriate driving parameters (such as solar activity, solar wind,
and geomagnetic activity), can be used to predict the occurrence of ionospheric irregularities when the external driving parameters are known. This study reveals that we may not use the same longitude-month
pattern to describe and predict the occurrence of ionospheric irregularities at different local times and that
only the occurrence probability of ionospheric irregularities based on plasma density perturbations (ΔN),
rather than relative density perturbations (ΔN/N0), can be used to predict ionospheric scintillation.
However, it should be mentioned that the pattern of the occurrence probability based on relative density
perturbations at 21:00–23:00 LT (Figure 3b) is similar to that based on plasma density perturbations at this
local time (Figure 7b). The pattern of irregularity occurrence in Figure 3b is derived from the data at moderate
solar activity during 2011–2012. Previous studies mostly focused on solar maximum. Kil and Heelis [1998],
McClure et al. [1998], and Su et al. [2006, 2008] derived the longitude/seasonal variations of irregularity
HUANG ET AL.
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occurrence. Gentile et al. [2006] and Kil et al. [2009] derived the longitude-month patterns of the occurrence
probability in the evening sector. The occurrence patterns of Gentile et al. [2006] and Kil et al. [2009] are similar
to those of Figure 3b based on relative density perturbations and Figure 7b based on plasma density perturbations at 21:00–23:00 LT. Although the irregularity occurrence probability in the previous studies was mostly
derived from relative density perturbations, the longitude-month pattern of irregularity occurrence in the evening sector at solar maximum is still consistent with the occurrence of ionospheric scintillation. However, only
the occurrence probability of ionospheric irregularities based on plasma density perturbations and its variation
with local time are consistent with the occurrence of scintillation at other local times.
Broad plasma decreases over thousands of kilometers in longitude were detected by C/NOFS near dawn at
solar minimum. There are two types of broad plasma decreases: One type almost does not include any smallerscale structures or plasma bubbles [Huang et al., 2009], and the other type consists of plasma bubbles [Huang
et al., 2011, 2012b]. In this study, we calculate plasma density perturbations or relative density perturbations
with respect to the average value over 1 min, corresponding to 420 km in longitude. If the broad plasma
decreases vary smoothly over thousands of kilometers [Huang et al., 2009], no, or very small, plasma density
perturbations will be identified over a distance of 420 km. These broad plasma decreases also do not cause
scintillation because they do not have small-scale irregularities. On the other hand, if the broad plasma
decreases consist of plasma bubbles at smaller scales [Huang et al., 2011, 2012b], plasma density perturbations will be identified and calculated over a distance of 420 km, and these smaller-scale irregularities will
cause scintillation. Therefore, the calculations of plasma density perturbations or relative density perturbations with our method are consistent with the occurrence of scintillation for the cases of broad plasma
decreases, and the conclusions are not changed no matter whether broad plasma decreases exist.
4. Conclusions
In this study, we have derived the occurrence probability of equatorial ionospheric irregularities measured by
the C/NOFS satellite during the period of low and moderate solar activity over 2008–2012. We use two different
methods to identify the occurrence of ionospheric irregularities. One is the relative density perturbation (ΔN/N0),
and the other is the amplitude of plasma density perturbations (ΔN). The longitude-month patterns of the occurrence probability derived with either method vary with local time, and the patterns based on plasma density
perturbations are significantly different from those based on relative density perturbations. The occurrence
probability based on plasma density perturbations is high at early local time and becomes very low after midnight. In contrast, the occurrence probability based on relative density perturbations is low at early local time
and becomes very high after midnight.
Although both plasma density perturbations and relative density perturbations can be used to characterize
the occurrence of ionospheric irregularities, only the patterns of the occurrence probability based on plasma
density perturbations are consistent with the occurrence of ionospheric scintillation, as derived from FORMOSAT3/COSMIC (F3/C) satellites. We have presented the longitude-month distribution of the S4 index derived from
measurements of F3/C during 2008–2012. The occurrence pattern of the S4 index and its variation with local time
are in good agreement with the irregularity occurrence based on plasma density perturbations (ΔN) but are
significantly different from those based on relative density perturbations (ΔN/N0). Scintillation is directly related to
plasma density perturbations but not to relative density perturbations.
Acknowledgments
The C/NOFS mission is supported by the
Air Force Research Laboratory, the SMC
Defense Weather Systems Directorate,
the Department of Defense Space Test
Program, the National Aeronautics and
Space Administration, the Naval
Research Laboratory, and The
Aerospace Corporation.
Robert Lysak thanks the reviewers for
their assistance in evaluating this paper.
HUANG ET AL.
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