3-4-3 Long-term Data Analysis of Ionosphere over
Syowa Station, Antarctica
MOTOBA Tetsuo
The Earth’s ionosphere is a partially ionized gas (electrons and ions) that forms several
regions between the atmosphere and space over about 70 km height. The ionosonde is one of
the radar techniques to monitor the ionospheric electron density as a function of height. The
ionosonde transmits HF radio wave (1–30 MHz) vertically and receives echoes reflected fromthe various ionized layers. The F2-layer critical frequency (foF2), which is a principal parameterobtained from the ionosondes, corresponds to F2-layer peak electron density. In this study, we
present ionospheric F2-layer variability (in particular, solar/geomagnetic activity dependence ofthe local time and seasonal behavior, and a long-term trend) over Syowa Station (69.0 ° S,
39.6° E), Antarctica, on the basis of long-term ionospheric database in 1959–2002.

Keywords
Ionospheric variability, Ionosonde, foF2, Syowa Station

1 Introduction
In the Earth’s upper atmosphere at an altitude higher than 60 km, there is a region withsignificant electrical conductivity. The ionizedregion (called the Ionosphere) is mainly produced by extreme solar ultraviolet (EUV,
10~120 nm wavelength) radiation and X-rays
that ionize the neutral atmosphere. The ionosphere is classified into several regions according to the electron density profile. The ionospheric region at an altitude ranging from 90 to
130 km is called the E region, and that ranging
from 130 to 1000 km is known as the Fregion. During the daytime, the D region
appears below the E region (at altitudes of 60
to 90 km), while the F region is divided into
the F1 region (at altitudes of 130 to 210 km)
and F2 region (at altitudes of 210 to 1,000 km)
during the daytime except in winter. The basic
plasma structure in the ionosphere is determined by the balance in the production
process due to solar radiation (particularly
EUV and X-rays), the loss process due to thephotochemical process, the recombination
process of ions and electrons, the transport
process due to gravity, diffusion and electromagnetic effects, and other factors. On theother hand, electron density in the ionosphereis up to 0.1% lower than neutral density in theupper atmosphere. In other words, the ionosphere can be called a “weakly ionized plasma
region.” Therefore, the neutral dynamics plays
an important role in ionospheric variations. In
addition, as the ionosphere is also affected bystrong coupling processes (such as solar andgeomagnetic activity) in the regions above andbelow (such as tidal waves, gravity waves, andplanetary waves), temporal, regional and seasonal variations of the ionosphere are more
complicated.
Ionospheric observation using ionosondes
has a long history. Ionosonde observation isuseful worldwide as a means of monitoring
ionospheric electron density［1］. The ionosonde(or ionospheric sounder) is a kind of radar thattransmits high frequency (HF: 1~30 MHz)
radio signals while sweeping those frequen-

MOTOBA Tetsuo447

cies, and receives the signals reflected fromthe ionosphere. The ionosonde allows thereflection height of radio waves to be determined based on the time delay in signals.
However, since the group velocity of radio
waves is slowed by any ionization, determining the reflection height based on the timedelay is not so simple. For example, if radio
waves with frequency f encounter anotherlayer whose plasma frequency is higher than
the frequency of the wave, it will be reflectedwith the return signal being further delayed as
it travels back through the underlying ionization. The apparent/virtual height h’( f ) indicated by this time delay will therefore be higher
than the true reflection altitude h( f ). Moreover, two independent types of radio waves
are transmitted: one is the left-hand ordinary
polarized mode whose reflection is determinedby local electron density, whereas the other isthe right-hand extraordinary polarized mode
whose reflection is also affected by the local
magnetic field. The first type is known as Omode (ordinary mode), while the second is
known as X-mode (extraordinary mode). The
ionosonde uses a linearly polarized wave represented by two circularly polarized waves
rotating in opposite senses.
The ionosonde on the ground can obtainelectron density profiles lower than the altitude of maximum electronic density in theionosphere (at 200 to 400 km), by transmitting
signals sweeping in frequency from 1 to 30
MHz and recording the time delay it takes thesignal to be reflected back to the receiver. The
maximum frequency (critical frequency) of
signals reflected in the ionosphere corresponds
to the maximum electron density, and signals
with even higher frequencies pass through theionosphere. Ionograms are images of frequency f versus the time delay (virtual height h’( f ))of HF echoes from the ionosphere as recordedby an ionosonde. From an ionogram, one candirectly determine the critical frequency of theF2 layer (foF2) corresponding to ordinarymode and the minimum virtual height (h’F2).
During the daytime, the critical frequencies of
the F1 layer and E layer, and the minimum

virtual heights can be determined. Note thatfoF2 can be expressed by the maximum ionospheric electron density of the F2 layer(NmF2), where NmF2 (m−3) ≈ 1.24×10 10×[foF2 (MHz)]2.
Since the International Geophysical Year
(IGY) in 1957 to 1958, steady ionosphericobservation with an ionosonde has been conducted at Syowa Station in Antarctica. During
about half a century up to the present,
ionosonde data have been almost continuously
accumulated, and play an important role inmonitoring long-term changes in the Antarctic
ionosphere. This paper describes ionosphericF2-layer variability in the auroral zone basedon long-term ionosonde foF2 data obtained
from 1959 to 2002 at Syowa Station, Antarctica (69.0° S, 39.6° E). In particular, the effects
of solar and geomagnetic activity on seasonal
and local time variations in the F2-layer electron density at Syowa, and the long-term
trends over several decades are presented.
The phenomenon of “global warming” of theearth’s surface has recently been considered amajor social issue, as it may lead to various
global-scale environmental changes and subsequent destruction. This paper also discusses
whether there are any indirect effects on theionosphere over Syowa Station, based onlong-term trend analysis.

2 Ionospheric variability over
Syowa Station, Antarctica
2.1 Dependence on solar activity in
foF2 relation with the solar activity
cycleThis section first describes the long-term
ionosonde dataset observed at Syowa Station.
Ionospheric parameters (such as foF2) at eachlayer can be obtained based on an ionogram’s
graphical presentation of echo virtual heightvs. sounding frequency every 15 minutes.
Figure 1 shows the rate (%) of samples of the
1-h foF2 data taken at Syowa Station for eachyear from 1959 to 2002. The rate of 100%means that foF2 data were continuously
obtained for one year (365 days). At Syowa

448 Journal of the National Institute of Information and Communications Technology Vol.56 Nos.1-4 2009

Fig.1 Distribution of annual data acquisi-

Fig.2 Monthly median values of foF2 for

Station in this figure, it is necessary to notethat there is an unfortunate data gap from1962 to 1968, probably due to suspended
ionosonde observation. The data acquisition
rate is higher through all local times after
1997 because of an instrumental change fromold analog system recording (film recording)to new digital system recording. As shown inthis figure, the data acquisition status of foF2
changes significantly according to the local
time each year. Data acquisition tends to bestable (at 60% or more) in the pre-noon to
post-evening sector (about 1000 LT to 2000LT), while it tends to decrease in the pre-midnight to morning sector (about 2200 LT to
0600 LT). In the post-midnight sector, theacquisition rate often drops below 20%. The
lower data acquisition rate in the nighttime
sector is presumably due to the depletion of Flayer electron density below the ionosonde’s
detection limit or an extreme enhancement inelectron density in the lower ionosphere (particularly the D region) caused by the precipitation of higher energy particles (10 keV ormore) during auroral activity. The enhanced
electron density in the lower ionosphere causes the absorption of HF radio waves in what iscalled a “blackout.” Moreover, the absorptionof HF radio waves is also caused by auroral
sporadic E (auroral Es). The diffusion of radio
waves that are supposed to reach the F layer
due to an abnormal ionospheric phenomenon
near the E layer that appears along with auro-

ral activity in the polar region during nighttime or auroral sporadic E (auroral Es), is
another important factor that often inhibits F
layer observation. The bottom of Fig. 1 shows
long-term changes in the annual average of
F10.7 solar radio wave flux (white line).
F10.7 is a measure of solar radio flux [1 solar
flux unit (SFU) = 10−22 Wm−2 Hz−1] with awavelength of 10.7 cm (2.8 GHz), and a proxyof changes in solar EUV radiation. The F10.7
is high for the solar maximum, while low for
the solar minimum. When comparing F10.7
with the foF2 data acquisition rate at Syowa
Station, we can see that the foF2 data acquisition rate tends to be higher for the solar maximum than the solar minimum. During thesolar maximum, since the whole ionospheric
altitude increases, ionosonde observation of
the F region is effective. In contrast, since theionospheric altitude decreases during the solar
minimum, ionosonde observation is difficult,especially at nighttime. Therefore, the dataacquisition rate is considered to be lower during the solar minimum.
Figure 2 shows the monthly median foF2
data at around local noon (1100 to 1300 LT)
from Syowa Station, Antarctica, together withthe monthly mean F10.7 data (blue line). In
this figure, note that the foF2 variation isstrongly influenced by solar activity with
about an 11-year cycle from the solar maximum to solar minimum. This result shows thattion rate (%) of foF2 data as a function of year and local time at
Syowa Station from 1959 to 2002

hours around local noon (1100 to
1300 LT) at Syowa Station as presented together with monthly
mean F10.7 values

MOTOBA Tetsuo449

the F-region electron density increases(decreases) with increasing (decreasing) solar
EUV radiation during the solar maximum(minimum).
Figure 3 shows a scatter plot of the monthly median foF2 values versus the monthly
mean F10.7 values. The red line shows a linear regression line of Y = aX + b (a = 0.026, b= 2.931), with a correlation coefficient of
0.896. The blue circles represent the mean
foF2 values, averaging foF2 as divided by
F10.7 for every 15 SFU. Error bars on the blue
circles are standard deviations. As shown in
Fig. 3, foF2 increases almost linearly with
F10.7 values lower than about 180 SFU.
However, foF2 apparently shows a saturation
effect for F10.7 values higher than about 180
SFU. Such a saturation effect of the ionosphere at higher values of F10.7 and/or sunspot
number has also been reported by previous
studies［2］–［4］. Theoretically, we expect thatthe local noon foF2 values would show a good
linear relationship with F10.7, because theionized F-region electron density (foF2) is primarily produced by solar EUV radiation.
However, foF2 is saturated for higher F10.7
values. It has been reported that the ionospheric saturation effect for higher F10.7 values isoften considerable near the equatorial anomaly
region［4］. On the other hand, some previous
studies indicate that solar EUV radiation has anonlinear relationship with F10.7, which isalso saturated for higher F10.7 values as seenFig.3 Monthly median values of foF2 plotted versus monthly mean F10.7 values［ 5］. This result sugin foF2 versus F10.7［3］gests that the F10.7 values at higher solar
activity do not quantitatively reflect solar
EUV radiation well. In other words, the ionospheric saturation effect results from the nonlinear relationship between F10.7 and solar
EUV, and we need to be especially carefulwhen quantitatively discussing the effect ofsolar activity on ionospheric variation. Section
2.3 gives a detailed description of a betterproxy representing solar EUV radiation thanF10.7.

2.2 Seasonal and local time variations
This section describes the seasonal andlocal time variations in foF2 at Syowa Station,
Antarctica. Daily variation in the E-region
electron density has a peak around noon, andthe electron density lowers toward the nighttime. This is because the E-region electron
density at middle and low latitudes is primarily controlled by a balance between the ionization process due to solar radiation and the loss
process (recombination). In contrast, daily
variation in F2-region electron density is notas simple as that in the E region, but in fact
much more complicated. This is because theF2-region electron density is not only affectedby the ionization and loss process mentioned
above, but also greatly influenced by neutral
wind dynamics in the thermosphere. Seasonalvariation in F2-region electron density is
known to have annual and semiannual variations. In seasonal variation, the neutral composition changes in the thermosphere (particularly the ratio of oxygen atoms to nitrogenmolecules ([O]/[N2])) have implications for
the F-region electron density［6］. In addition to
the composition and dynamics of the thermosphere (i.e., neutral particles), the precipitationof charged particles and electromagnetic energy from the magnetosphere also play important roles regarding ionospheric variation in
the auroral zone (where Syowa Station is
located). Moreover, ionospheric variation is
also affected by wave activity (tides, gravity
waves and planetary waves) propagating fromthe lower atmosphere［7］.

450 Journal of the National Institute of Information and Communications Technology Vol.56 Nos.1-4 2009

The upper panels in Fig. 4 show the average seasonal and local time dependent variations in foF2 at Syowa Station, Antarctica, forsolar minimum (F10.7 < 100, left panel) andfor solar maximum (F10.7 > 150, right panel),respectively. White contours are plotted insteps of 0.5 MHz. The black dashed curves
represent the respective times at sunrise andsunset. At Syowa Station located in the Southern Hemisphere, the months of November to
February correspond to summer, March to

April to autumn, May to August to winter, andSeptember to October to spring. Therefore,
months on the X-axis are shifted ahead by six
months to match the four seasons in the
Northern Hemisphere. The middle and lower
panels in Fig. 4 show the average seasonal andlocal time dependent variations in foF2 at
Wakkanai in Hokkaido (45.2° N, 141.8° E;
1960 to 2003) and at Kokubunji in Tokyo(35.7° N, 139.5° E; 1959 to 2003), which arelocated at the middle and low latitudes in

Fig.4 Average seasonal and local time variations in foF2 during the solar minimum period (F10.7< 100 in the left figure) and maximum period (F10.7 > 150 in the right figure)[Top panels] Syowa Station, Antarctica; [middle panels] Wakkanai; [bottom panels] Kokubunji

MOTOBA Tetsuo

451

Japan, respectively. The major features of
foF2 variations seen at Wakkanai andKokubunji are as follows:(1) For daytime from 0600 to 1800 LT,
semiannual variation with the equinox
peaks in spring (March) and autumn(October) exists in foF2 during boththe solar maximum and solar minimum. In contrast, for nighttime from1800 to 0600 LT, annual variation witha peak in summer (May to June) isremarkable.
(2) Both in the solar maximum and solar
minimum, foF2 peaks around noon
(1200 LT) in autumn, winter andspring, and it tends to become lower
toward midnight.
(3) During the summer at Wakkanai, two
foF2 peaks appear between 0600 and
0800, and between 1800 and 2000,
respectively. At Kokubunji, similar
foF2 peaks also appear during the solar
minimum period.
(4) During the solar maximum, a considerable foF2 peak around 1200 LT is seen
only during summer at Kokubunji,
with a structure of multiple peaks
formed together with the peak ataround midnight.
The seasonal changes and local timechanges in foF2 at Syowa Station have bothsimilarities and dissimilarities relative to thoseat the middle and low latitudes. From Fig. 4,
we can see major two differences: first, thefoF2 value at Syowa Station is generally about
70% to 80% lower than that at Wakkanai andKokubunji; secondly, the foF2 variation at
Syowa Station shows a quite different tendency during the solar minimum. The main characteristics of seasonal changes and local timechanges in foF2 at Syowa Station are as follows:(1) The foF2 value during the solar minimum shows annual variations, rising insummer and declining in winter.

(2) The daytime foF2 value during thesolar maximum shows semiannual
variation with peaks in autumn (April)and spring (September).
(3) The daytime foF2 value during thesolar maximum is higher in winter thanin summer.
(4) The nighttime foF2 value during thesolar maximum shows annual variation
where it rises in summer and declines
in winter.
(5) The peak in the diurnal variation of foF2
changes with the seasons. The peakoccurs around 1000 to 1100 LT in summer,
1500 to 1600 LT in spring and autumn, and1300 to 1400 LT in winter.
The common feature at three observatories
is that the daytime foF2 is higher in winterthan in summer during the solar maximum.
This is presumably due to a rise in the[O]/[N2] ratio caused by the transport of oxygen atoms from the summer hemisphere to thewinter hemisphere［8］. In summer, the oxygen
atom density that contributes to ionization
decreases, while the density of nitrogen molecules contributing to loss increases. As aresult, the [O]/[N2] ratio in summer decreases
considerably. Moreover, the oxygen atoms at
F-layer altitudes indicate semiannual variation
with peaks in spring and autumn. As solar
activity rises, oxygen atom density tends toincrease as well. As a result, the daytime foF2
value during the solar maximum presumablyshows semiannual variation where it declines
in summer, and peaks in spring and autumn.
During the solar minimum, however, only
Syowa Station shows a different tendency
where foF2 is higher in summer than in winter. Considering the sunrise and sunset times
indicated in broken lines, we find that the
local time and season of the higher foF2 values correspond to the daylight hours. One canconsider that the higher foF2 in summer during the solar minimum as seen only at Syowa
Station is overwhelmingly more affected byionization due to longer daylight effects athigh latitude, rather than the effects of compo-

452 Journal of the National Institute of Information and Communications Technology Vol.56 Nos.1-4 2009

sition changes of the neutral atmosphere. This
foF2 feature at Syowa Station is quite different from that at middle and low latitudes.
Figure 5 shows the average seasonalchanges and local time changes in foE at
Syowa Station, Wakkanai, and Kokubunji forreference purposes. However, the data period
for foE at Syowa Station is from 1969 to
1979. In general, the foE value corresponds tothe peak in the E region electron density. The
format of this figure is the same as shown in

Fig. 4, except that the contour interval is set to0.25 MHz. From this figure, one can see thatchanges in foE at the three observation points
are virtually governed by the hours of daylightprovided by the sun. However, on the nightside of Syowa Station located in the auroralzone, foE rises around spring and autumn.
This tendency may be related to geomagnetic
activity that peaks in spring and autumn. In
other words, enhanced geomagnetic activity
leads to more auroral particle precipitation,

Fig.5 Average seasonal and local time variations in foE during the solar minimum (F10.7 < 100 in
the left figure) and maximum (right figure: F10.7 > 150) at Syowa Station[Top panels], Antarctica, Wakkanai [middle panels], and Kokubunji [bottom panels]

MOTOBA Tetsuo453

thereby ionizing neutral particles in the nightside E region.
2.3 Dependence on solar and geomagnetic activity
As stated in Section 2.1, foF2 becomessaturated at high levels of F10.7. One presumable cause is that F10.7—a kind of solar activity index—does not completely reproduce thechanges in solar EUV radiation that mostaffects ionospheric generation. Reference［9］compares the four solar activity indexes,
sunspot number (SSN), F10.7, MgII (Mg II
core-to-wing ratio), and He I (1083) brightline with the solar EUV radiation observed bya satellite. “Sunspot number” means observed
portions of the sun that look like black dots orpieces of mass, and is also referred to simply
sunspots. These portions actually radiate light
as well but appear dark because they emit
weaker light than surrounding areas. Sunspots
are lower in temperature and also provide
stronger magnetic fields than the surrounding
areas. MgII is an index that represents theamount of radiation with a wavelength ofbright emission lines of magnesium (near 280nm) in the ultraviolet region［10］. MgII data
connect solar UV radiation data observed bydifferent satellites equipped with different
types of observation equipment, thereby building up a long-term database spanning morethan 30 years, from November 1978 to thepresent. The He I (1083) bright line has equivalent width for infrared absorption rays (1083nm) and is determined from solar surface
images observed on the ground［11］. He I
(1083) is known to reproduce more time serieschanges in solar UV radiation than F10.7 andSSN［12］. The SOHO satellite—a solar observation satellite launched in 1995—is equippedwith equipment (solar EUV monitor SEM) for
measuring solar EUV radiation, which is considered the most important of all solar radiations contributing to the generation of ionospheric electron density. By comparing thechanges in solar EUV radiation observed by
SEM with changes in the solar activity indexes of F10.7 and MgII, we have found that

MgII is a better indicator of changes in solar［13］. Figure 6 is
EUV radiation than F10.7［9］taken from Reference［9］ as an example. This
figure compares MgII during about fourmonths (from October 1996 to January 1997)
with changes in solar EUV radiation, SSN,
and F10.7 as observed with SEM. As is evident from this figure, F10.7 and sunspot number have not well reproduced short-termchanges and their amplitudes in solar EUV
radiation over a period of about 27 days,
which is the rotation period of the sun. Conversely, MgII well reproduced the timechanges in short-term solar EUV radiation.
MgII is disadvantageous, however, in thatits data period is limited to 1978 and later. To
compare it with long-term data from theionosphere available in and after 1959, it isnecessary to provide solar activity index data
for long periods just like F10.7. Recently, anattempt was made to derive a new solar activity index known as C10.7 (corrected solar flux
index) from long-term time series data ofF10.7 based on an experience model adopting

Fig.6 Comparison of MgII, solar EUV radi-

ation, SSN, and F10.7 during fourmonths from October 1996 to January 1997 (revised version of Fig. 5 ofReference［9］)454 Journal of the National Institute of Information and Communications Technology Vol.56 Nos.1-4 2009a neutral network［14］. C10.7 is an index
derived by separating the solar rotation change
component of 27 days and the gradual change
component from F10.7 based on the statisticalnature of F10.7 and solar EUV radiation, forcomparison with the changes in solar EUV
radiation observed by the SEM of SOHO.
Still in the development stage, C10.7 is beingenhanced to better approximate itself withchanges in solar EUV radiation. Here, the firststep is to compare the first version of C10.7
with MgII, thereby validating the propriety ofC10.7. Figure 7 is a scatter diagram of F10.7
and MgII, and C10.7 and MgII from 1979 to
2002. The correlation with MgII is higher inC10.7 than F10.7 and the square root (RMSE)
of average square error—an indicator of thedegree of data variance—is also small. Moreover, as F10.7 rises, we can see that MgII
becomes saturated. In contrast, C10.7 exhibits
no such thing.
The first version of C10.7 or continuous
solar activity index data over long periods that

better represents changes in solar EUV radiation was therefore used to again investigate
the dependence of foF2 on solar activity from1969 to 2002. In this analysis based on a data
set consisting of three data items [foF2 (theaverage from 1100 to 1300 LT), F10.7, andC10.7], the response differences in daytime
foF2 to F10.7 and to C10.7 were examined,
respectively. The top and bottom panels in
Fig. 8 show scatter diagrams (the gray circle)
representing the relation between F10.7 and
foF2, and that between C10.7 and foF2. The
straight line indicated in each diagram is a linear regression straight line. The correlation
factor between F10.7 and foF2 during thisdata period was 0.686. As shown in Fig. 3, asF10.7 rises, the foF2 value can be seen
becoming saturated. Moreover, F10.7 shows
large variances in foF2 between 150 and 200
SFU, with many values showing particularlyhigh foF2 (more than 10 MHz). In contrast,
the correlation factor between C10.7 and foF2
was 0.716, or a little higher than in the case of

Fig.7 [Top panel] Comparison of F10.7

Fig.8 [Top panel] Comparison of F10.7

and MgII from 1979 to 2002; [bottom panel] comparison of C10.7
and MgII during same period

and foF2 from 1969 to 2002; [bottom panel] comparison of C10.7
and foF2 during same period

MOTOBA Tetsuo455

F10.7. Unlike the case of F10.7, foF2 shows
little saturation effect when C10.7 is high, andis generally known to exhibit an almost linear
relation. Moreover, RMSE indicates that
C10.7 shows smaller variances (error) thanF10.7.
Next, we have examined the dependenceof geomagnetic activity on foF2. Here, the Kindex of Syowa Station is used as an indicatorof geomagnetic activity. The K-index indicates geomagnetic activity using numbers
from 0 to 9 every three hours based on horizontal magnetic field changes in geomagnetism at each magnetic observation point. For
example, the K-index is low during quiet periods of geomagnetic activity, and becomes highduring more intense activity. The blue and red
circles in the figure denote differences in thedependence of foF2 on solar activity due to
geomagnetic activity. The blue circle indicatesa quiet activity level (with a K-index of 0 to2); the red circle indicates a moderate activity
level (with a K-index of 2 to 4). Both are used
to express the average foF2 when divided foreach 15 SFU. In the case of F10.7, foF2 tends
to show lower saturation effect at quiet geomagnetism than at geomagnetic disturbance.
At 200 SFU or more, however, a slight saturation effect is seen (blue circle in top panel ofthe figure). Conversely, in the case of C10.7,
foF2 shows hardly any saturation effect atquiet geomagnetic activity, thereby suggestingan almost linear relation between C10.7 andfoF2 (blue circle in bottom panel of the figure). Even when C10.7 is low (up to 180) at
geomagnetic disturbance, it changes almost
linearly at the same level as at a quiet level.
However, when C10.7 is high (180 or more),
foF2 exhibits its saturation effect and becomes
lower by about 1 to 2 MHz than at periods ofquiet geomagnetic activity. As describedabove, since C10.7 and solar EUV radiation
show almost the same changes, the saturation
effect of foF2 seen in the case of C10.7 is presumably due to geomagnetic disturbance.
When geomagnetic activity is high (such as
auroral activity or a magnetic storm), the electromagnetic energy flowing from the magne-

tosphere into the polar ionosphere generally
increases. At times of such a rising influx ofelectromagnetic energy, the polar thermosphere will experience changes in atmosphericcomposition accompanied by higher neutral
atmospheric temperature and a lower [O]/[N2]ratio, thereby reducing the electron density at
F layer altitude and resulting in a decline in
foF2 (see negative ionospheric storm in Reference［6］). Therefore, in order to maximize theremoval of changes in foF2 stemming fromgeomagnetic disturbance (or an ionosphericstorm stemming therefrom) based on longterm time series data on foF2, it is necessary
to only select data obtained at periods of quiet
geomagnetism (with a K-index of 2 or less).
This is related to the method of extracting
foF2 long-term trends described in the next
section.

3 Long-term trend-relation with
global warming
3.1 Review of long-term trend studies
During the late-1980s, a theory was proposed to the effect that an increase in greenhouse gases emitted from the ground surface
would warm up the troposphere, while coolingthe stratosphere, mesosphere, and thermosphere. Carbon dioxide—a representative
greenhouse gas—absorbs and radiates theearth’s radiation (infrared rays). Greenhousegases in the troposphere absorb large quantities of infrared rays radiated by the earth,
thereby heating up the atmosphere. In contrast, the middle and upper atmosphere havemuch lower quantities of infrared rays due tothe earth's radiation, so that more radiation isemitted into space than the amount of infrared
rays absorbed, thereby resulting in a cooling
effect. Moreover, cooling in the stratosphere is
not only affected by the direct effects of thesegreenhouse gases but also by indirect effects
due to the decline and loss of ozone caused bychlorine-based compounds. Ozone depletion
reduces the heating effect due to the solar
ultraviolet absorption of stratospheric ozone.
If greenhouse gases continue rising at present

456 Journal of the National Institute of Information and Communications Technology Vol.56 Nos.1-4 2009levels, not only will cooling be promoted in
the middle and upper atmosphere, but also
concerns raised about the various possible
changes in the earth’s surrounding environment, such as changes in neutral atmosphericdensity, the denaturing of the atmosphericcomposition, and the plasma environment.
Therefore, it is necessary to clarify what kindof changes occurred in the “field” of the upper
atmosphere and ionosphere over a long-term
scale of several past decades, and quantitatively understand the effects stemming from natural sources (such as solar and geomagnetic
activity) included in long-term change trends
and those (such as greenhouse gases) attributed to human sources.
Reference［15］describes the use of a global mean (one-dimensional) atmosphericmodel, consisting of the mesosphere, thermosphere and ionosphere as a connection system,
to quantitatively estimate for the first time theeffects of rising greenhouse gases on theatmospheric environment at altitudes of 60 to
500 km. In this numerical simulation, doubling the concentration of greenhouse gases at
an altitude of 60 km (as projected to bereached by the end of the 21st century) would
result in a predicted drop in temperature by
about 10 to 15K at mesospheric altitudes, andabout 20 to 50K at thermospheric altitudes.
At the same time, atmospheric shrinking
occurs with cooling and the density of nitrogen molecules, oxygen molecules and atoms—
the main components of the atmosphere in thethermosphere—declines by about 30% to50%. In connection with changes in the upper
atmosphere accompanied by such a rise ingreenhouse gases, a decline in ionospheric
altitude accompanied by atmospheric shrinking, changes in ionospheric electron density
accompanied by changes in the density ratioof oxygen atoms and nitrogen molecules, arise in methane and water steam density, andmore frequent formation of noclilucent clouds
accompanied by lower temperature at themesospheric interface are projected to occur.
Reference［16］describes the use of numerical calculation prediction taken from

Reference［15］ and standard ionospheric theory to roughly estimate the effects of risinggreenhouse gases on the ionosphere. Based ona doubling of the amount of greenhouse gasesin the future, it was estimated that the electron
density peak altitudes of the ionospheric E
layer and F2 layer would drop by about 2 km
and 15 to 20 km, respectively. Conversely,
hardly any change is seen in electron density
not over-sensitively reactive to temperaturechanges in the neutral atmosphere. The effects
on the global ionosphere were then verified byusing a three-dimensional thermosphereionosphere integration model. Next, similar to
the estimates described above, along with the
doubling of greenhouse gas concentrations,the peak altitude of the ionospheric F2 layer
would drop globally by about 10 to 20 km［17］,a finding that began drawing public attention
to the effects of greenhouse gases on theionosphere. If such ionospheric changes do
indeed occur in the future, serious concerns
will be raised over the effects on radio wave
communications and related fields already put
to practical use.
The neutral atmospheric density of thethermosphere can be estimated by determining
the rate of change in the orbital radius due toatmospheric drag imposed on satellites asbased on orbital data obtained from low-altitude satellites orbiting at thermospheric altitudes. Reference［18］ clarified that the atmospheric density at altitudes of 300 to 400 km
declines by about 0.45% per year on averagebased on satellite orbits during the three previous minimal periods (in 1976, 1986 and 1996)of solar activity. If the thermospheric atmospheric density declines linearly at this rate of
decline, the end of the 21st century will see adrop in the thermosphere by as much as about
40 km due to cooling. This high decline inthermospheric density receives hardly any
influence from geomagnetic activity, local
time and season, but does tend to depend on
altitude and solar activity. For example, thedecline in atmospheric density tends to begreater at higher altitudes, and the decline inatmospheric density tends to be higher during

MOTOBA Tetsuo457

a minimal period rather than a maximum period of solar activity［19］. These trends agree
well in qualitative terms with the results estimated based on the model described in Reference［17］, though the magnitude of the decline
in density estimated from observations is a little greater than reported in the model results.
Since the model study presented in Reference［17］, higher activity has been seen instudies attempting to detect long-term ionospheric trends based on ground-based observational data. The method of multiple regression
analysis is often used in many cases whenlong-term trends of the ionosphere are detected. Multiple regression analysis is a method of
examining the relation between dependent
variables and one or more independent
descriptive variables considered to affect thosevariables, in order to determine their interrelational equation (multiple regression equation). Reference［20］ reported observation
results that for the first time support a decline
in ionospheric altitude caused by cooling of
the super-high layer atmosphere as predictedfrom model calculations. Reference［20］ used
long-term (1957−1990) data observed with anionosonde at medium altitudes since IGY inorder to clarify that the peak altitude of theionospheric F2 layer has shown a gradual
downward trend over the past three decades.
Moreover, the annual decline in peak altitudeof this ionospheric F2 layer turned out to be
more considerable in winter (−0.45 km/yr)
than in summer ( −0.12 km/yr). Ionosondedata observed in and after 1958, in Northern
Europe at Sodankyla, Finland (latitude
67° north, longitude 27° east), was then used
to again report that the peak altitude of theionospheric F2 layer has been falling over［22］.
long periods［21］Reference［23］ used long-term ionosondedata taken at Tromsø, Norway (latitude 69°
north, longitude 19° east) from 1935 to 2001
to demonstrate a long-term downward trend in
foF2 (−0.0078 MHz/yr). Reference［23］ considered that this downward trend in foF2 wasdue to a rise in greenhouse gases, as well aschanges in oxygen atoms and nitrogen mole-cules. Reference［24］used data obtained froman observation network of multiple ionosondes located in the Northern Hemisphere toinvestigate altitude changes in long-term
trends in foF2. While the long-term trends in
foF2 show a downward trend at most observation points, another trend showed that the rateof decline in long-term trends in foF2 rises as
altitude increases. This dependence of theselong-term trends in foF2 on altitude is interpreted to mean the effects of ionosphericstorms due to geomagnetic activity.
Analysis conducted with a multi-point
observation network of ionosondes installed invarious parts of the world, however, reportsthat long-term trends at the peak altitude of
the F2 layer do not reflect globally monotonous negative trends, although some positive
trends are seen at certain observation
points［25］–［27］. Reference［27］ shows theworld distribution of trends in F2 layer peak
altitude and points out that, although thegrowth trends of F2 layer peak altitudes are
not dependent on latitude or longitude, thesetrends do reflect a certain degree of regionality. The mechanism to describe this regionality, however, has yet to be understood. Such acomplex trend distribution contradicts thenumerical model results given in Refer［17］that predict cooling of the global
ences［15］super-high layer atmosphere due to risinggreenhouse gases. For that reason, some studies have even reported that long-term trends inF2 layer peak altitudes are not due to coolingof the upper atmosphere caused by risinggreenhouse gases, but due to long-term［28］.
changes in geomagnetic activity［24］The reality is that no uniform view has yet
been obtained about the long-term trends ofthe ionospheric F2 layer as determined using
ionosondes, unlike the long-term trends ofglobal thermospheric atmospheric density
based on satellite orbital data.
3.2 Long-term ionospheric trends
observed at Syowa Station
The previous studies described above
attempted to estimate long-term ionospheric

458 Journal of the National Institute of Information and Communications Technology Vol.56 Nos.1-4 2009

trends by using various methods. The mostimportant thing in estimating long-term ionospheric trends is finding a way to remove a
component that depends on solar and geomagnetic activity from the variable components of
the ionosphere. The effects of geomagnetic
activity are particularly pronounced at Syowa
Station, which is located in the auroral zone.
What is common to most of the previous longterm trend studies is that a linear relation isassumed between foF2 and the solar activity
indexes (SSN and F10.7) when expressing thechanges in foF2 stemming from solar activity.
However, as shown in Figs. 3 and 8, when
F10.7 is high, foF2 becomes higher in termsof saturation effect, resulting in a degradedlinear relation. For that reason, when using
SSN and F10.7, one cannot well expresschanges in foF2 dependent on solar activity.
And as described in Section 2.3, foF2
becomes higher in saturation effect along withrising geomagnetic activity (see Fig. 8). This
analysis therefore used C10.7—an index that
better reproduces changes in solar EUV radiation—as a solar activity index. Only those
items of data obtained during quiet periods ofgeomagnetic activity (0 ≦ K-index ≦ 2) from1100 to 1300 at the local time each day wereused for foF2, thereby minimizing the effectof geomagnetic disturbance. It is known that
ionospheric disturbance generally continues
with a certain time constant even after a geomagnetic disturbance. However, its effect isignored here. From these two conditions, thelong-term trends in foF2 from 1969 to 2002
(where the K-index can be used) were first
derived. The following gives a detailed
description of the method used for derivation:(1) From the foF2 data observed (foF2obs),
select only the data obtained during
quiet periods of geomagnetic activity(0 ≦ K-index ≦ 2).
(2) Assume a linear relation between
C10.7 and foF2, and determine thecomponent that changes depending
only on solar activity (foF2 mod = a1 •C10.7 + b1) from foF2 observed.
(3) Subtract foF2 mod from the observed

foF2 obs to obtain the residual error
component (∆foF2 = foF2obs – foF2mod)as a change independent of solar andgeomagnetic activity.
(4) Determine the linear regression equation [∆foF2 = A + B* (year – 1969)]
and regard its inclination B as the longterm trend of foF2.
Figure 9 (a) shows the change (foF2obs:
gray circle) in foF2 observed from 1969 to
2002 and the component (foF2mod: blue line)of foF2 dependent on solar activity as
obtained by using F10.7. Moreover, Fig. 9 (b)shows the residual error in foF2 (∆foF2: graycircle) and the linear trend obtained therefrom(blue line). In contrast, Fig. 9 (c) and (d) show
the component (foF2mod: red line) of foF2 that
depends on solar activity when using C10.7
and the linear trend obtained therefrom (redline). The linear trend of foF2 from 1969 to
2002 showed a tendency where a decline
occurs by −0.0002 ± 0.0018 MHz per year
when using F10.7. However, in that case,since the trend component is smaller than theerror, the long-term trend component can be
regarded as almost zero. Conversely, whenC10.7 is used, the long-term trend of foF2
declined by −0.0012 ± 0.0017 MHz per year,
thereby marking an approximate sixfold
increase in the rate of decline (inclination) as
compared with F10.7. From this result, one
can also see that long-term trends vary according to the solar activity index selected. Thissuggests that previous analysis methods need
to be reconsidered. In the case of C10.7 aswell, since the trend component is slightly
smaller than the error, one cannot necessarily
assert that foF2 showed a significantly downward trend from 1969 to 2002. Although thisis a different method, it yields a different
result than that described in Reference［23］where a trend showing a significant decline in
foF2 (annual decline of –0.0078 ± 0.0041
MHz) was derived from foF2 long-term dataobtained at Tromsø from 1935 to 2001.
Next, the author examined how much thelong-term trends of foF2 derived are affectedby different methods of extracting trends, the

MOTOBA Tetsuo459

Fig.9 (a) Changes (foF2abs: gray circle) in foF2 observed from 1969 to 2002 and the foF2 component (foF2mod: blue line) dependent on solar activity as obtained by using F10.7 (b)Residual component of foF2 (∆foF2: gray circle) and linear trend (blue line) (c) Changes
in foF2 observed from 1969 to 2002 (foF2obs: gray circle) and the foF2 component(foF2mod: red line) dependent on solar activity as observed by using C10.7 (d) Residualcomponent of foF2 (∆foF2: gray circle) and linear trend (red line)

data period, and solar activity indexes used.
Solar activity indexes (F10.7 and C10.7) andgeomagnetic activity indexes (K-index and ap
index) were used as the data. The ap index is avalue measured every three hours to represent
the activity of geomagnetism based on observations taken at geomagnetic observatories in
12 countries around the world, and is divided
into 28 sections between 0 and 400 nT. In thisanalysis, quiet geomagnetism was defined as alevel where the ap index was 10 nT or less.
Table 1 summarizes the long-term trend values of foF2. Three cases were considered forthe model value of foF2 (foF2mod). In model 1,
the component dependent on solar and geomagnetic activity was expressed as foF2mod =a1.(solar activity index) + b 1.(geomagnetic
activity index: ap index) + c1; the trend component was determined by subtracting bothindexes from the observation values. This is
one of the methods used in previous long-term

trend studies of the ionosphere. Models 2 and3 were judged by using the ap index (of 10 orless) and K-index (of 2 or less), respectively,in order to extract only the foF2 at quiet geomagnetic activity. The method used for that
purpose was the same method as indicated at
the beginning. As can be seen from Table 1,
regardless of the method used, the long-term
trend component of foF2 shows a downward
trend, but the rate of decline in that trend
varies greatly in line with differences in theobservation data period, solar activity index,
and method of trend extraction. The method
using model 2 showed the greatest downward
trend, followed by the method in model 1.
According to the method in model 3, the longterm trend in foF2 is almost zero. The longterm trends from 1959 to 2002 showed nosuch major differences due to differences inthe solar activity index, but those differences
become much more pronounced when divided

460 Journal of the National Institute of Information and Communications Technology Vol.56 Nos.1-4 2009

Table 1 Long-term trends in foF2 at Syowa Station derived from differences in method of trend
extraction, data period, and solar activity index

by the data periods from 1969 to 2002.
The findings above provide important tips
on proceeding with long-term trend analyses
in the future. In deriving global long-term
trends of the ionosphere, it is vital to conduct
revalidation after establishing: (1) an alignment of data observation periods at respective
observation points, (2) a method of removing
the component dependent on solar and geomagnetic activity, and (3) selecting solar andgeomagnetic activity indexes, and related factors.

4 Conclusion
The ionosphere is a region that exercises
an important influence on communications
and radio wave propagation. It is affected byboth top and bottom, and its daily changes,
seasonal changes, and other changes behave in
a complex manner. In recent years, someresearchers have pointed out the possibility
that a rise in greenhouse gases attributed tohuman activity may be playing an importantrole in changes occurring in the earth's superhigh layer atmosphere (ionosphere) over along time scale. As such, the ionosphere isvery important as a boundary region in the
top-bottom connection of the earth’s atmosphere.
This paper introduced various changes in
the ionospheric F2 layer in the auroral zone

based on long-term observation data takenfrom 1959 to 2002 using an ionosonde at
Syowa Station, Antarctica (69.0° S, 39.6° E).
The average local time and seasonal changes
in foF2 show complex changes that can also
be seen at other observation points, and were
found to greatly affect solar and geomagnetic
activity. Moreover, the long-term trends in theionosphere considered to affect global warming are issues of great concern in social aswell as scientific terms. In the future, it will benecessary to continue ionospheric observations at Syowa Station and clarify ionosphericchanges over an even longer time scale, while
taking an approach based on a numericalmodel in order to understand the physicalprocesses behind those changes.

Acknowledgments
The National Geophysical Data Center(NGDC), NOAA, provided the F10.7 indexand MgII. Mamoru Ishii, director of the
Applied Electromagnetic Research Center,
National Institute of Information and Communications Technology (NICT), and Maho
Nakamura, chief researcher, Light and SpaceTime Standards Group, also of NICT, provided the ionosonde data obtained from Syowa
Station in Antarctica. The author also wishes
to express profound thanks to seniorresearcher Takaue Maruyama and chief

MOTOBA Tetsuo461

researcher Maho Nakamura of NICT for thevaluable advice they provided. The author also
thanks Ms. Fukushima of NICT for having
taken the readings of ionogram data from
Syowa Station for many long years. Last but

not least, the author thanks all the Antarctic
observation team members engaged ininstalling and maintaining the ionosonde
observation equipment at Syowa Station.

References
01 Rishbeth, H., "The centenary of solar-terrestrial physics," J. Atmos. Solar Terr. Phys., 63, 1883–1890,
2001.

02 Lakshmi, D. R., B. M. Reddy, and R. S. Dabas, "On the possible use of recent EUV data for ionosphericpredictions," J. Atmos. Terr. Phys., 50, 207–213, 1988.

03 Balan, N., G. J. Bailey, B. Jenkins, P. B. Rao, and R. J. Moffett, "Variations of Ionospheric Ionization and
Related Solar Fluxes During an Intense Solar Cycle," J. Geophys. Res., 99(A2), 2243–2253, 1994.

04 Liu, J. Y., Y. I. Chen, and J. S. Lin, "Statistical investigation of the saturation effect in the ionosphericfoF2 versus sunspot, solar radio noise, and solar EUV radiation," J. Geophys. Res., 108(A2), 1067, doi:
10.1029/2001JA007543, 2003.

05 Richards, P. G., J. A. Fennelly, and D. G. Torr, "EUVAC: A Solar EUV Flux Model for Aeronomic Calculations," J. Geophys. Res., 99(A5), 8981–8992, 1994.

06 Rishbeth, H., "How the thermospheric composition affects the ionospheric F2-layer," J. Atmos. Solar
Terr. Phys., 60, 1385–1402, 1998.

07 Rishbeth, H. and M. Mendillo, "Patterns of F2-layer variability," J. Atmos. Solar Terr. Phys., 63,
1661–1680, 2001.

08 Torr, M. R. and D. G. Torr, "The seasonal behaviour of the F2-layer of the ionosphere," J. Atmos. Terr.
Phys., 35, 2237–2251,1973.

09 Floyd, L., J. Newmark, J. Cook, L. Herring, and D. McMullin, "Solar EUV and UV spectral irradiances andsolar indices," J. Atmos. Solar Terr. Phys., 67, 3 –15, 2005.

10 Heath, D. F., and B. M. Schlesinger, "The Mg 280 nm doublet as a monitor of changes in the solar ultraviolet irradiance," J. Geophys. Res., 91, 8672–8682, 1986.

11 Harvey, J. W. and W. C. Livingston, "Variability of the solar He I 10830 angstrom triplet, IAU Symposium
154, Infrared Solar Physics," 59, 1994.

12 Donnelly, R. F., T. P. Repoff, J. W. Harvey, and D. F. Heath, "Temporal characteristics of the solar UV
flux and He I line at 1083 nm," J. Geophys. Res., 90, 6267–6273, 1985.

13 Viereck, R., L. Puga, D. McMullin, D. Judge, M. Weber, and W. K. Tobiska, "The Mg II index: A proxy forsolar EUV," Geophys. Res. Lett., 28(7), 1343–1346, 2001.

14 Maruyama T., "Regional Reference Total Electron Content Model over Japan Using Solar EUV Proxies,"
Special issue of this NICT Journal, 3–3–5, 2009.

15 Roble, R. G. and R. E. Dickinson, "How will changes in carbon dioxide and methane modify the mean
structure of the mesosphere and thermosphere ?," Geophys. Res. Lett., 16, 1441–1444, 1989.

16 Rishbeth, H., "A greenhouse effect in the ionosphere ?," Planet. Space Sci., 38, 945–948, 1990.
17 Rishbeth, H. and R. G. Roble, "Cooling of the upper atmosphere by enhanced greenhouse gases -Modeling of thermospheric and ionospheric effects," Planet. Space Sci., 40, 1011–1026, 1992.

18 Keating, G. M., R. H. Tolson, and M. S. Bradford, "Evidence of long term global decline in the Earth's
thermospheric densities apparently related to anthropogenic effects," Geophys. Res. Lett., 27(10),1523–1526, 2000.

462 Journal of the National Institute of Information and Communications Technology Vol.56 Nos.1-4 2009

19 Emmert, J. T., J. M. Picone, J. L. Lean, and S. H. Knowles, "Global change in the termosphere: Compelling evidence of a secular decrease in density," J. Geophys. Res., 109, A02301, doi:
10.1029/2003JA010176, 2004.

20 Bremer, J., "Ionospheric trends in mid-latitudes as a possible indicator of the atmospheric greenhouseeffect," J. Atmos. Terr., Phys., 54, 1505–1511, 1992.

21 Ulich, T. and E. Turunen, "Evidence for long-term cooling of the upper atmosphere in ionosonde data,"
Geophys. Res. Lett., 24, 1103–1106, 1997.

22 Ulich, T., M. Cliverd, and H. Rishbeth, "Determining long-term change in the ionosphere," EOS, 84, 581,
2003.

23 Hall, C. M. and P. S. Cannon, "Trends in foF2 above Tromsø(69°N 19°E)," Geophys. Res. Lett., 29, 2128,
doi: 10.1029/2002GL016259, 2002.

24 Mikhailov, A. V. and D. Marin, "Geomagnetic control of the foF2 long-term trends," Ann. Geophys., 18,
653–665, 2000.

25 Bremer, J., "Trends in the ionospheric E and F regions over Europe," Ann. Geophys., 16, 986-996, 1998.
26 Upadhyay, H. O. and K. K. Mahajan, "Atmospheric greenhouse effect and ionospheric trends," Geophys. Res. Lett., 25, 3375-3378, 1998.

27 Bremer, J., "Investigations of long-term trends in the ionosphere with world-wide ionosonde Observations," Adv. Radio Sci., 2, 253–258, 2004.

28 Mikhailov, A. V., and D. Marin, "An interpretation of the foF2 and hmF2 long-term trends in the frameworkof the geomagnetic control concept," Ann. Geophys., 19, 733–748, 2001.

MOTOBA Tetsuo, Dr. Sci.
Project Researcher, Space and Upper
Atmospheric Sciences Group, National
Institute of Polar Research
Upper Atmospheric Physics

MOTOBA Tetsuo463