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Journal of Atmospheric and Solar-Terrestrial Physics 179 (2018) 165–173
Contents lists available at ScienceDirect
Journal of Atmospheric and Solar-Terrestrial Physics
journal homepage: www.elsevier.com/locate/jastp
Coherent changes of solar and ionospheric activity during long-lived coronal
mega-hole from Carrington rotation CR2165 to CR2188
T
T.L. Gulyaeva∗, R.A. Gulyaev
IZMIRAN, Troitsk, 108840, Moscow, Russia
A R T I C LE I N FO
A B S T R A C T
Keywords:
Coronal hole
Solar wind
Ionosphere critical frequency
TEC and GEC
Correlations of solar and ionospheric activity are investigated during the long-lived coronal mega-hole (CMH)
for 24 solar rotations at the decline phase of SC24 from June, 2015, to March, 2017. Pch index (Luo et al., 2008)
which is a function of the intensity in the central area developed for forecasting of daily solar wind speed (Vsw)
is used as characteristic of efficiency of CMH. The solar activity indices Pch, SSN2, F10.7, Lyman-α, MgII, Vsw,
and the ionospheric indices – global electron content GEC and global noon TECgn index averaged from data of
288 IGS observatories are analyzed. Sporadic disturbances in solar and ionospheric data are smoothed by the
time-weighted exponential accumulation of their history with the persistence factor τ (0 ≤τ < 1) for the
preceding 27 days. Growing coronal hole power Pch(τ) during the CMH life is observed while all other solar and
ionospheric indices are decreasing at the decreasing phase of SC24. The solar wind speed near the Earth is
diminishing from CR2165 to CR2174 but growing afterwards. Delayed correlation of solar wind speed Vsw(τ)
with Pch(τ) shows lag (delay) of Vsw(τ) by 4 days relative Pch(τ) index while the ionospheric data don't show
any delay. Examination of relations of the ionosphere activity with the solar and ionospheric global indices is
made with noon measurements of the foF2 critical frequency and total electron content TEC at eight observatories (4 from the northern hemisphere and 4 from the southern hemisphere). The best linear correlation of
foF2(τ) and TEC(τ) at selected sites is obtained with GEC(τ) and TECgn(τ) indices (the correlation coefficient ρ
from 0.7 to 0.9 in the most cases) so that TECgn(τ) and GEC(τ) global indices could serve as potential candidates
for driving the ionospheric model in the real time regime.
1. Introduction
It has been known since the work of Wang and Sheeley (1990) that
both fast and slow solar winds originate from coronal holes and that
their speed is related to the rate at which the open field lines diverge
close to the Sun. More studies have been conducted to establish the
empirical relations between the wind speed and the coronal hole for the
forecasting of high-speed wind streams and associated geomagnetic
activity (Krieger et al., 1973; Belov et al., 2006; Veselovsky et al., 2006;
Vršnak et al., 2007a, b; Luo et al., 2008; Obridko and Shelting, 2009,
2011; Verbanac et al., 2011; Rotter et al., 2012; Garton et al., 2018). A
considerable correlation has been found between the solar wind speed
Vsw and the coronal hole (CH) area on the visible side of the Sun,
showing quantitative improvement of forecasting accuracy in low CME
activity periods (Vršnak et al., 2007a; Luo et al., 2008). The coronal
holes are observed in EUV and soft X-ray images as the regions of reduced density and low temperature in the solar corona produced by
quasi-open magnetic field lines enabling plasma to freely escape into
∗
space. They generate so-called high speed solar wind streams (HSS)
while the slow solar wind escapes from the total solar surface towards
the outer space. The slow solar wind, formed above active regions,
interacts with the fast wind and form stream interaction regions (SIRs)
or, when persistent over several solar rotations, corotating interaction
regions (CIRs).
Coronal holes (CHs) play a significant role in making the Earth geomagnetically active during the declining and minimum phases of the
solar cycles 22–24 (Kamide, 2001; Lukianova et al., 2017; Prabhu et al.,
2018). It has been revealed that the extended minimum of Solar Cycle
23 has shown unusual characteristics in the number of persistent coronal holes in the mid- and low-latitude regions of the Sun. The latitude
distribution of the recurrent coronal holes (RCHs) has shown that most
of them are appeared between ± 20° latitudes. In this period, more
number of recurring coronal holes appeared in and around 100° and
200° Carrington longitudes. The large sized coronal holes lived for
shorter period and they appeared close to the equator (Prabhu et al.,
2018). The coronal holes can be observed in the both polar regions of
Corresponding author.
E-mail address: gulyaeva@izmiran.ru (T.L. Gulyaeva).
https://doi.org/10.1016/j.jastp.2018.07.007
Received 20 February 2018; Received in revised form 2 July 2018; Accepted 18 July 2018
Available online 20 July 2018
1364-6826/ © 2018 Elsevier Ltd. All rights reserved.
Journal of Atmospheric and Solar-Terrestrial Physics 179 (2018) 165–173
T.L. Gulyaeva, R.A. Gulyaev
2008). To exclude sporadic changes of the solar and ionospheric indices
we apply the time-weighted accumulation of the indices so that a daily
index is converted to a new proxy index integrating its history with the
persistence factor τ (0 ≤τ < 1) for the preceding 27 days (Wrenn,
1987).
The ionospheric plasma is product of the ionization and dissociation
of the upper atmosphere species induced by the energy input from EUV
and soft X rays wavelengths in the solar electromagnetic spectrum from
5 to 400 nm. Accordingly, we will make a comparison of the solar and
ionospheric proxy indices introduced recently into the International
Reference Ionosphere and Plasmasphere IRI-Plas model in order to find
out the best solar activity proxies for the model operation (Gulyaeva
et al., 2018). The climatic ionosphere models IRI, IRI-Plas, Ne-Quick,
SMI are driven by 12-months smoothed solar and ionospheric indices
centered on a given month (Gulyaeva and Bilitza, 2012; Brown et al.,
2017). Hence, the ‘observed’ indices are available no longer than before
six months prior to current time. The model execution during the last
six months prior to current day and predictions onwards rely on prediction of solar activity proxies. The results of model output may suffer
due to uncertainty/errors of solar proxy predictions. To mitigate the
problem with solar activity driving the ionosphere model, the different
solar proxies have been proposed (Liu and Chen, 2009; Maruyama,
2010, 2011; Lukianova and Mursula, 2011; Perna and Pezzopane, 2016;
Shubin, 2017). One of the goals of the present study is to identify relevant solar proxy (proxies) for driving the ionosphere model in realtime regime.
The correlations between the solar activity indices SSN2, F10.7,
Lyman-α, MgII, Vsw and Pch index and the ionospheric indices – global
electron content GEC and global noon TECgn index averaged from data
of 288 IGS observatories during the life of the CMH are analyzed.
Examination of the ionosphere activity and its relation to the solar and
ionospheric global proxy indices during the CMH observation is made
using the noon measurements of the foF2 critical frequency and the
total electron content TEC at eight observatories (4 from the northern
hemisphere and 4 from the southern hemisphere). Data and method of
analysis are provided in Section 2. Results are described in Section 3
with concluding remarks in Section 4.
the Sun as well as in the non-polar regions. The differences in polar and
non-polar coronal holes have been investigated by Navarro-Peralta and
Sanchez-Ibarra (1994) and Bilenko and Tavastsherna (2016). It was
found that the non-polar coronal hole follows configuration changes in
the global magnetic-field structure. The systematic study of the longlived coronal holes has been carried out by Kahler and Hudson (2002).
Crooker and Cliver (1994) pointed out that it is CIRs rather than
HSS from the coronal holes alone, that are responsible for the recurrent
geomagnetic activity. The occurrence rate of the interplanetary coronal
mass ejections (ICME) is shown to follow the sunspot cycle, while
strong CIRs are most predominant during the declining phase and the
minimum of solar activity cycle due to the presence of large polar
coronal holes (Kamide, 2001). The CIRs are the most important factor
affecting the thermosphere–ionosphere and geomagnetic field response
as follows from the comparative studies of effects of CIR/HSS/ICME on
the geomagnetic and ionospheric storms (Tsurutani et al., 2006a,
2006b; Burns et al., 2012; Chen et al., 2012; Buresova et al., 2014).
The correlations of CHs with the solar wind and the geomagnetic
disturbances are substantially investigated (Belov et al., 2006; Vršnak
et al., 2007b; Luo et al., 2008; Obridko and Shelting, 2009, 2011;
Verbanac et al., 2011; Rotter et al., 2012; Garton et al., 2018).
Knowledge of effects of the solar wind on the ionosphere storms has
reached a mature stage of development of a practical tool for the ionosphere forecasting (Tsagouri et al., 2009, 2018). The present study
allows shed light on an existence of a straightforward link between the
CHs and the ionosphere activity. This task is attempted here for the first
time in literature by analysis of the relation between the Pch index as
the CH's identifier and the ionospheric parameters.
The unusual long-living Coronal Mega-Hole (CMH) has been observed by Andreeva et al. (2017) and Akhtemov et al. (2017) during
twenty four Carrington rotations from CR2165 to CR2188. The outstanding feature of this CMH is its duration from June, 2015, to March,
2017. The long-lived CMH is located near the North Pole of the Sun
expanding towards the equator until 30°S at the peak of its development. The evolution of the area and intensity of the CMH and datamodel comparisons of the CMH area in the photosphere are analyzed by
Andreeva et al. (2017). The intensity of the magnetic field of the CMH is
proved to decrease by a factor of about 20 (Akhtemov et al., 2017). The
CMH's impact on the origination of the fast solar wind and subsequent
efficiency in the interplanetary and near-Earth space are known to
occur at moments of its crossing the Earth-facing central meridian on
the disk (Wang and Sheeley, 1990; Veselovsky et al., 2006; Vršnak
et al., 2007a; Luo et al., 2008). The characteristics of the solar atmosphere near the center of the disk allow investigate the behavior of
subsequent disturbances in the interplanetary space and space weather
(Belov et al., 2006; Vršnak et al., 2007b; Luo et al., 2008; Obridko and
Shelting, 2009, 2011; Verbanac et al., 2011; Rotter et al., 2012).
In view of CMH location near the North Pole, only small part of it
expands through the center of the solar disk so one could rarely expect
appreciable effects of CMH on the high speed solar wind and the space
weather disturbances near the Earth. The Pch index ((Luo et al., 2008)
is capable to represent the more general CHs' power including both the
polar origin CHs (such and CMH under consideration) so the non-polar
CHs with the most of them appearing between ± 20° latitudes (Prabhu
et al., 2018). Hence, it is worth comparing the Pch index for the intermediate-term variation of solar and ionospheric parameters. Our
study is focused during the CMH life at the declining phase of SC24
when the particular ionosphere behavior is not masked by the extreme
ionospheric characteristics observed at solar maximum and minimum.
Such results could complement the comparisons made for the high solar
activity at the peak of SC21 by Tobiska and Bouwer (1989) who compared the solar Lyman-α emission, the MgII core-to-wing ratio, the
10.7-cm radio flux F10.7 and the 1–8 Å X rays. Their power spectral
analysis indicates that all four fluxes have 27-day periodicities due to
solar rotation. The 27-day periodicity of the global average of total
electron content is well correlated (ρ = 0.90) with MgII index (Hocke,
2. Data and method of analysis
In order to adapt the International Reference Ionosphere and
Plasmasphere model to the recent recalibration of the sunspot number
time series SSN2 (Clette et al., 2014), eight 12-monthly smoothed solar
and ionospheric proxy indices have been introduced into IRI-Plas
system as the model driving parameters: SSN1, SSN2, F10.7, MgII,
Lyman-α, TEC-noon global averaged from data of 288 IGS observatories, Global electron content GEC, and foF2-noon based IG index
(Gulyaeva, 2016; Gulyaeva et al., 2018; Sezen et al., 2018). The set of
288 observatories from IGS network selected for producing TECgn
index are shown in Fig. 1. These stations are providing the most data for
JPL GIM-TEC construction (Mannucci et al., 1998). In a case of missing
TEC-noon value for a particular station it is replaced by relevant value
extracted/interpolated from GIM-TEC map.
The long-lived CMH has been observed since June, 2015, the time
when re-calibration of the sunspot numbers (Clette et al., 2014) has
been adopted. Since June, 2015, production of SSN1 is terminated, so in
the present study we use SSN2 time series as the sunspot numbers. The
ionospheric IG index is not used in our analysis below because it is not
produced in daily regime which is the time scale for the present study.
Hence, the following daily indices are used in the present study as
proxies of solar activity:
(1) the Coronal Hole Pch index, originated in the solar corona (Luo
et al., 2008);
(2) re-calibrated sunspot number time series, SSN2, originated in the
photosphere;
166
Journal of Atmospheric and Solar-Terrestrial Physics 179 (2018) 165–173
T.L. Gulyaeva, R.A. Gulyaev
Fig. 1. The set of 288 observatories of IGS network providing TEC-noon measurements for producing global noon TECgn index.
(3) solar index of 10.7 cm microwave radio flux, F10.7, originated in
the solar corona;
(4) the core–to–wing ratio of the magnesium ion h and k lines at 279.56
and 280.27 nm, MgII, in the chromosphere (Vierek et al., 2004);
(5) the hydrogen Lyman-α emission at 121.6 nm in the chromosphere
(Woods et al., 2000);
(6) the total electron content in the ionosphere and plasmasphere of the
Earth, TECgn (TEC global noon), averaged from data of 288 IGS
observatories all over the world;
(7) the global electron content in the ionosphere and plasmasphere of
the Earth, GEC;
(8) the solar wind speed Vsw measured by the ACE satellite near the
Earth.
Fig. 2. Fe XII 193 Å image of the solar corona with the rectangular area for Pch
evaluation at the day 2016.10.26 of the CMH crossing the central meridian in
CR2184.
Table 1
List of Carrington rotations (CR) of the Sun during observations of Coronal
Mega-Hole (CMH). Date of CR start and day (t1) of CMH passing the central
meridian (CMH_t1). Power index of central coronal hole (Pch) on day t1
(CMH_t1) and peak daily speed of the solar wind, Vsw, during 5 days after t1.
A coronal hole Pch index represents a function of the intensity in the
central area ([10°E, 10°W], [30°N, 30°S]) derived from SOHO EIT 284 Å
images of the solar corona (Luo et al., 2008). Pch = Σ1/b, in which b is
the brightness of the pixels inside the selected area on the visible side of
the Sun (see Fig. 1). A good correlation is found by Luo et al. (2008)
between the Pch factor and the 3-day-lag solar wind velocity Vsw
probed by the ACE spacecraft so that the Pch index allows predict the
daily solar wind speed 3 days in advance. The Pch factor reflects both
the area and brightness effects of CHs. It shows that in periods of low
CME activity the Pch factor can improve Vsw forecasting accuracy. The
Pch index can eliminate an important bias in the forecasting process,
which is present in the methods using CH area as input parameter
(Vršnak et al., 2007a; Verbanac et al., 2011) due to the fact that the CH
boundary cannot be unambiguously determined from observations,
since Pch does not depend on the CH boundary determination. The Pch
index is provided by the Space Environment Prediction Centre, SEPC
(Liu and Gong, 2015) at http://eng.sepc.ac.cn/CHI.php based on SDO/
AIA images of the Fe XII 193 Å in solar corona once a day, and the area
of each coronal hole is given in percentage of the visible disk. Fig. 2
presents an example of the Fe XII 193 Å image of the solar corona with
the rectangular area for Pch evaluation at the day 2016.10.26 of peak of
the CMH crossing the central meridian in CR2184 (Pch = 925.32 i. u.,
index units).
The Carrington rotations from CR2165 to CR2188 during observation of the CMH are listed in Table 1. The start day and time (UT) of CRs
are provided, and the day, t1, for the CMH crossing the central meridian. The Pch index is given for day t1. Though the 3-days lag of solar
wind velocity Vsw is estimated as an average time after the enhanced
Pch index (Luo et al., 2008) some cases can show the Vsw enhancement
during 4 or 5 days. Hence, the maximum value of the solar wind speed
Vsw is provided during 5-day-lag after t1 in Table 1. The peak of CMH
development illustrated in Fig. 1 is indicated by Pch index in bold for
nn
CR
CR start
UT
CMH_t1
Pch
Vsw
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
2165
2166
2167
2168
2169
2170
2171
2172
2173
2174
2175
2176
2177
2178
2179
2180
2181
2182
2183
2184
2185
2186
2187
2188
2015.06.17
2015.07.14
2015.08.11
2015.09.07
2015.10.04
2015.10.31
2016.11.28
2015.12.25
2016.01.21
2016.02.18
2016.03.16
2016.04.12
2016.05.10
2016.06.06
2016.07.03
2016.07.30
2016.08.26
2016.09.23
2016.10.20
2016.11.16
2016.12.14
2017.01.10
2017.02.06
2017.03.06
1518
2004
0115
0707
1339
2040
0403
1147
1952
0403
1154
1853
0048
0553
1038
1536
2111
0328
1020
1735
0110
0907
1719
0122
2015.06.23
2015.07.21
2015.08.18
2015.09.12
2015.10.12
2015.11.07
2015.12.04
2015.12.30
2016.01.26
2016.02.24
2016.03.25
2016.04.21
2016.05.17
2016.06.13
2016.07.11
2016.08.06
2016.09.01
2016.09.26
2016.10.26
2016.11.21
2016.12.19
2017.01.16
2017.02.08
2017.03.10
269.50
211.32
310.10
314.56
609.75
621.49
509.81
528.38
481.85
393.44
538.44
502.23
392.51
570.94
492.14
439.83
546.41
727.98
925.32
650.01
681.40
805.28
515.18
413.97
626
446
488
542
534
669
590
458
357
387
520
520
584
606
635
611
668
680
681
633
633
592
456
467
CR2184 in Table 1.
To exclude sporadic changes of the solar and ionospheric indices (1)
to (8) we apply the time-weighted accumulation of the indices so that a
daily index is converted to a new proxy index integrating its history
with the persistence factor τ (0 ≤τ < 1) for the preceding 27 days
(Wrenn, 1987; De Franceschi et al., 2001; Shubin, 2017).
One of proposed time series accumulation of a selected index Z
which stands for any index from (1) to (8), starts from the Z0 value for
the current day and includes also a number of daily indices for the
preceding days. Wrenn (1987) introduced the following time series
167
Journal of Atmospheric and Solar-Terrestrial Physics 179 (2018) 165–173
T.L. Gulyaeva, R.A. Gulyaev
accumulation of the ap index (designated by Z in our case):
Z(τ)=(1-τ) (Z0+(τ)Z-1 +(τ)2 Z-2 + …)
(1)
where Z0 is the index value for the current day, Z-1, Z-2 … are the Z
values for the preceding days, d: -1d, -2d, …etc. The attenuation multiplier, or persistence factor τ (0 ≤τ < 1) determines how Z(τ) will
depend on the past history of the Z index, and the term (1-τ) normalizes
the summation. The persistence factor τ is expressed as:
τ = e−1/(nd−1)
(2)
In our case, τ = 0.9623 for days number nd = 27d referring to the
27 days' history. As a persistent factor, τ determines how Z(τ) will depend on the past history of the Z index. The bigger the value of τ, the
more dependence of Z(τ) will have upon his history. The persistence time
tp (in days) is approximately given by the relation tp = ts/(1-τ) where ts
is the time scale or temporal interval (expressed in days in our case) for
which the index Z is defined (e.g. ts = 1d for Z). The persistence time
can be also considered as the time required for 1/e decay of Z(τ).
The normalising factor Sτ = (1-τ) is valid for infinite (or very long)
series of terms included in the sum of Eqn. (1). In practice, we select 27
terms (27 daily values of any particular index Z: Z0, Z-1, …, Z-26) in Eqn.
(1) to account for the 27-days solar rotation. So by using a limited
number of terms (n) in eq. (1), the normalising factor Sτ should be
modified as
Sτ = (1-τ)/(1-τ n).
Fig. 3. Variation of Pch index at the central rectangle ([10°E, 10°W], [30°N,
30°S]) and the surface area of total CMH (Andreeva et al., 2017) derived from
SDO/AIA Fe XII 193 Å images for the dates of CMH crossing the central meridian for the CR2165 to CR2188.
crossing the central meridian (see Table 1) are plotted in Fig. 3 for the
CR2165 to CR2188 (red line with circles). Note that Pch index depicts
features of central CH area within the frame of ([10°E, 10°W], [30°N,
30°S]) on the disk facing the Earth. The surface area of the total CMH
for the same dates (t1) when the CMH crosses the central meridian is
plotted for a comparison (blue line with triangles) as it is evaluated by
Andreeva et al. (2017). The both curves are derived from SDO/AIA Fe
XII 193 Å images. Very good resemblance of the both curves is seen
except for the few differences owing to the different areas on the solar
image evaluated with the two methods.
Cross-correlation coefficient ρ has been produced for the solar and
ionospheric proxy indices Z(τ) converted with Eqs. (1)–(4) from the
daily data where Z stands for the index (1) to (8). Results are provided
in Table 3. The best ρ for each proxy index is given in bold along relevant column. The best correlation coefficient ρ = 0.85 is obtained for
SSN2 with F10.7; the best ρ = 0.97 is obtained for F10.7 with MgII; the
best ρ = 0.99 is obtained for Lyman-α with MgII and vice versa; the best
ρ = 0.56 is obtained for Vsw with Pch; the best ρ = −0.94 is obtained
for Pch with Lyman-α; the best ρ = 0.94 is obtained for GEC with
TECgn and vice versa.
Temporal variations of the solar and ionospheric proxies Z(τ) during
CMH life from June, 2015, to March, 2017, are illustrated in Figs. 4–9.
Day-to-day accumulated SSN2(τ) is plotted in Fig. 4a; F10.7(τ) is
plotted in Fig. 4b; Lyman-α(τ) is plotted in Fig. 4c; MgII(τ) is plotted in
Fig. 4d. Similarity of all four parameters and their linear trend of diminution at the declining phase of the SC24 are clearly seen from
Fig. 4a–d. This similarity is confirmed by their high cross-correlation
coefficients listed in Table 3.
Fig. 5 provides day-to-day accumulated global electron content
GEC(τ) and globally averaged noon TECgn(τ) proxy indices. Their
variations are highly correlated (ρ = 0.94) showing trend of diminution
at the declining phase of the SC24 similar to solar proxies shown in
Fig. 4a–d.
Quite different temporal variations are observed with Pch(τ) and
Vsw(τ) proxy indices plotted in Fig. 6. First, the growing central coronal
hole intensity is observed with Pch(τ) index (Fig. 6, lower curve, right
hand scale) as opposite to the decreasing solar activity at the declining
phase of SC24 (Figs. 4–5). The trend of the total growth of Pch(τ) looks
as contradiction to the original Pch index variation at the days of
crossing central meridian by the CMH shown in Fig. 3. However, there
is no contradiction: the results of Pch(τ) consist of mixture of contributions of all CHs passing through the center of the solar disc including those located in the North solar corona (like CMH), located in
(3)
Then Eqn. (1) becomes:
Z(τ)=(1-τ)/(1-τn) (Z0+(τ) Z-1 + (τ)2 Z-2 + … +(τ)n−1 Z-n-1)
(4)
With the above modification the greatest weight (equal to 1) is
given to the Z0 value for the current day. Eqs. (1)–(4) can be used to
produce solar and ionospheric Z(τ) proxy indices in day-to-day regime
starting from −26th day preceding a current day. Since the 12-monthly
smoothed ‘observed’ solar proxy indices are available no longer than
before six months prior to current time, the model execution during the
last six months prior to current day could rely on daily proxy Z(τ)
evaluation of solar activity proxies.
The performance of the solar and ionospheric proxies are compared
with the noon daily values of the ionosphere critical frequency, foF2,
and noon daily measurements of total electron content, TEC, at eight
locations listed with geographic and geomagnetic coordinates in
Table 2. Four stations are selected in the Northern hemisphere (Tromso,
Moscow, Chilton and Okinawa) and four stations in the Southern
hemisphere (Darwin, Grahamstown, Port Stanley and Mawson). The
noon measurements of foF2 and TEC for the period of CMH existence
(June, 2015, to March, 2017) have been converted to foF2(τ) and
TEC(τ) with Eqs. (1)–(4). Results of analysis are provided in the next
Section.
3. Results
Variation of Pch index measured by SEPC for the dates t1 of CMH
Table 2
Geographic and geomagnetic coordinates of eight observatories used for analysis.
Station
Glat
Glon
Mlat
Mlon
Tromso
Moscow
Chilton
Okinawa
Darwin
Grahamstown
Port Stanley
Mawson
69.7
55.5
51.6
26.3
−12.2
−33.3
−51.7
−67.6
19.0
37.3
358.7
127.8
130.9
26.5
302.2
62.9
67.3
51.1
53.5
17.0
−21.0
−34.1
−42.1
−73.2
115.8
121.6
83.7
199.2
204.7
92.7
12.4
112.8
168
Journal of Atmospheric and Solar-Terrestrial Physics 179 (2018) 165–173
T.L. Gulyaeva, R.A. Gulyaev
Table 3
The correlation coefficient between solar and ionospheric proxy indices Z(τ) during the life of CMH (06.2015–03.2017). Maximum absolute value is indicated with
bold along each column.
Index
SSN2
SSN2
F10.7
Lymα
MgII
Vsw
Pch
GEC
TEC
0.853
0.848
0.852
−0.412
−0.819
0.630
0.744
F10.7
Lymα
MgII
Vsw
Pch
GEC
TEC
0.853
0.848
0.957
0.852
0.971
0.990
−0.412
−0.393
−0.473
−0.440
−0.819
−0.893
−0.939
−0.926
0.559
0.630
0.588
0.635
0.632
−0.461
−0.538
0.744
0.737
0.769
0.765
−0.522
−0.708
0.941
0.957
0.971
−0.393
−0.893
0.588
0.737
0.990
−0.473
−0.939
0.635
0.769
−0.440
−0.926
0.632
0.765
the South solar corona, and non-polar CHs located near the center of the
solar disk. So we resume that the total trend of growing CHs towards
the solar minimum is a natural process testifying that more ‘coronal
holes’ are born on the Sun when the solar activity is decreasing. The
increasing trend of Pch(τ) yields the negative correlation with all other
solar and ionospheric Z(τ) proxies except for the correlation with the
solar wind speed (Table 3). The absolute values of correlation coefficient between Pch(τ) and other proxies are high which confirms close
relations of the observed Pch index as a measure of CH's intensity
congruent with other proxies of solar and ionospheric activity.
The more surprising is variation of the solar wind speed Vsw(τ)
during the life of CMH (Fig. 6, upper curve). Here we observe decreasing trend of Vsw(τ) from CR2165 (June, 2015) to CR2175 (March,
2016) replaced by the growing trend afterwards. These two branches
are relevant to two-phase CMH surface area (Fig. 3) and CMH's intensity as estimated by [Andreeva et al., 2017). One could assume that
two opposite trends are due to first the dominant impact of solar activity outside of the center of solar disk (such as CME) on the solar wind
speed which is replaced afterwards by the dominant impact of growing
central CHs on the high speed solar wind streams, HSS. Whatever it be,
the two-trends solar wind speed results in low correlation of Vsw(τ)
with all the rest parameters during the total life-time of CMH (Table 3).
We proceed to evaluation of temporal variation and trends of the
0.559
−0.461
−0.522
−0.538
−0.708
0.941
Fig. 5. Day-to-day accumulated ionospheric global indices TECgn and GEC for
the period of CMH life.
local noon foF2(τ) and TEC(τ) at eight selected locations during the
CMH lifetime (Table 2). Fig. 7 illustrates diminution trend of foF2(τ) at
the declining phase of SC24. Similar trends of the local noon TEC(τ) are
Fig. 4. Day-to-day accumulated indices for the period of CMH life: (a) SSN2(τ); (b) F10.7(τ); (c) Lyman-α(τ); (d) MgII(τ).
169
Journal of Atmospheric and Solar-Terrestrial Physics 179 (2018) 165–173
T.L. Gulyaeva, R.A. Gulyaev
in Fig. 9a,b,c. The correlation coefficient ρ(Δt) between the solar activity and ionosphere global proxies Z(τ) vs Pch(τ) are plotted in
Fig. 9a. There is no delayed response of the indices under investigation:
the absolute value of correlation coefficient |ρ| is decreasing with
growing time lag Δt relative Pch(τ) except for the solar wind Vsw(τ).
The solar wind speed Vsw(τ) shows lag (delay) Δt of 3–4 days when the
best correlation |ρ| is reached which is consistent with well-known
delayed response of the HSS to the CHs (Wang and Sheeley, 1990; Belov
et al., 2006; Vršnak et al., 2007a; Luo et al., 2008). Absence of the
delayed response of the ionospheric global proxies GEC(τ) and TECgn
(τ) to Pch(τ) unlike to Vsw(τ) delay of 3–4 days after Pch(τ) suggests
that there is a need for the more investigations of the solar wind –
ionosphere relations because one could expect a contribution of the
solar wind to the ionosphere plasma density which could comprise
about 25% of UV/EUV irradiance (Lal, 1997).
Delayed correlation of the local foF2(τ) with Pch(τ) is plotted in
Fig. 9b and that of TEC(τ) with Pch(τ) in Fig. 9c. Again, there is no
appreciable lag (delay) between the local ionosphere parameters relative to Pch(τ) index. Note, that the correlation coefficient is shown
negative in Fig. 9b and c. The absolute value of |ρ| is small for the most
of cases except for Moscow with ρ(TEC,Pch) = −0.89, Chilton with
ρ(TEC,Pch) = −0.85 and Tromso with ρ(TEC,Pch) = −0.8. The weak
correlation in the most cases testifies on weak straightforward impact of
the coronal hole intensity on the local plasma density and electron
content. Again, an impact of the solar wind on the ionosphere should be
considered as an intermediate mechanism between the CHs and the
ionosphere.
Since the Vsw(τ) during the CMH period shows weak correlation
with the local foF2(τ) and TEC(τ) parameters (Tables 4 and 5) one
cannot assume to apply Vsw proxy index for driving the ionosphere
model in the real-time regime. As mentioned above, the ionospheric
global proxies GEC(τ) and TECgn(τ) are the best candidates for the realtime proxy of solar activity (Tables 4 and 5). The global electron content GEC itself is a product of the IRI-Plas system (Gulyaeva and
Veselovsky, 2014) which means that the daily GEC for the current day
is not available until execution of the IRI-Plas in real-time regime. So
the best candidate for the ionospheric proxy of solar activity in the realtime mode is left TECgn(τ) index. The delayed correlation of the local
foF2(τ) and TEC(τ) with TECgn(τ) index is presented in Fig. 10a and b,
respective. Again, there is no lag (delay) of the correlation between the
said pairs of parameters. The correlation is the best for the current day
(Δt = 0) then it is decreasing slowly with supposed time lag, Δt, from 1
to 10 days. The slow decrease of ρ with Δt means that missing TECgn
index for the current day (Δt = 0) it can be substituted with the index
Fig. 6. Day-to-day accumulated Pch(τ) and Vsw(τ) proxy indices for the period
of CMH life.
observed in Fig. 7. The correlation coefficients between foF2(τ) and Z
(τ) for 8 locations are listed in Table 4, and correlation coefficients
between TEC(τ) and Z(τ) for 8 locations are listed in Table 5. The best ρ
are given in bold for each site. There is no wonder that the best correlation is observed for foF2(τ) and TEC(τ) with the global ionospheric
GEC and TECgn proxy indices with exceptions for Moscow ρ(TEC,
F10.7) = 0.90 and Chilton ρ(TEC, MgII) = 0.88. The results for Tromso
in the North high latitude differ from other locations with peak correlation ρ(foF2, Pch) = - 0.64 and ρ(TEC, Pch) = - 0.8 while the South
high latitude results for Mawson are close to those for other locations.
Thus, the daily trend accumulating the history of the given parameter
for the preceding solar rotation suggests implementation of the ionosphere/plasmasphere GEC(τ) or TECgn(τ) as an ionosphere model
driving solar proxy in near real-time regime.
Relevant sliding data sets of 654 days period (from 2015.06.17 to
2017.03.31 during CMH's life) are extracted from all solar and ionospheric data sets to calculate the solar - ionospheric delayed correlation
and the time lag Δt, days, of the solar wind and the ionosphere response
delay regarding the solar proxy indices. The delayed correlation between two variables, CX/Y(Δt) corresponds to the correlation coefficient
between the variable Y(t + Δt) and the variable X(t). Similar approach
has been used by Liu et al. (2007) in investigation of time delay of the
ionospheric total electron content responses to geomagnetic disturbances. The time lag, Δt, varying from 1 to 10 days has been probed.
The delayed correlation results relative to Pch(τ) index are provided
Fig. 7. Day-to-day temporal variation and trends of the local noon foF2(τ) at eight selected locations during the CMH lifetime.
170
Journal of Atmospheric and Solar-Terrestrial Physics 179 (2018) 165–173
T.L. Gulyaeva, R.A. Gulyaev
Fig. 8. Day-to-day temporal variation and trends of the local noon TEC(τ) at eight selected locations during the CMH lifetime.
for the preceding day (t0 – Δt), without essential loss of correlation, etc.
to the CH's activity is the solar wind speed
v The global mean noon TECgn(τ) index can be used as the ionospheric proxy of solar activity for driving the ionosphere model in
real-time regime.
vi More studies are needed to explain why the solar wind near the
Earth shows 3-day-lag after CHs while the ionosphere does not.
4. Conclusions
The analysis of the solar and ionospheric parameters during the life
of the coronal mega-hole, CMH, from June, 2015, to March, 2017, is
made with Pch, Vsw, SSN2, F10.7, Lyman-α, MgII, ionospheric global
GEC and TECgn indices. Sporadic disturbances in solar and ionospheric
data are smoothed out by the time-weighted exponential accumulation
of their history with the persistence factor τ (0 ≤τ < 1) for the preceding 27 days.
The main findings from this study:
Acknowledgements
Coronal Hole Pch index is provided by Space Environment
Prediction Centre at http://eng.sepc.ac.cn/CHI.php. The solar images
SDO/AIA are provided at https://m.solarmonitor.org/. The solar wind
data are provided by OMNI at https://omniweb.gsfc.nasa.gov/. SSN2
sunspot numbers are provided at http://sidc.oma.be/. The solar radio
flux F10.7 index is provided at ftp://ftp.geolab.nrcan.gc.ca/data/solar_
flux/. Bremen composite MgII index is provided at http://www.iup.unibremen.de/UVSAT/Datasets/mgii). Composite Layman_α index is provided at http://lasp.colorado.edu/lisird/tss/composite_lyman_alpha.
html. TEC data are provided by JPL at ftp://sideshow.jpl.nasa.gov/
pub/iono_daily/. The ionosonde foF2 data are provided at https://
i Intensity of CHs is increasing towards the solar minimum
ii Solar wind speed shows double-trend at the CMH time – first decreasing till March, 2016, but increasing afterwards similar to Pch
index
ii Coherent variations are observed between solar and ionospheric
parameters both in global and local collection
iv The only parameter which reveals the delayed response by 3–4 days
Fig. 9. The delayed correlation results relative to Pch(τ) index: (a) solar activity and global ionospheric proxy indices; (b) the local noon foF2(τ) at eight selected
locations; (c) the local noon TEC(τ) at eight selected locations.
171
Journal of Atmospheric and Solar-Terrestrial Physics 179 (2018) 165–173
T.L. Gulyaeva, R.A. Gulyaev
Table 4
The correlation coefficient between noon foF2(τ) critical frequency at eight observatories and solar and ionospheric proxy indices Z(τ) during the observation of CMH
(06.2015–03.2017).
Station
SSN2
F10.7
Lymα
MgII
Vsw
Pch
GEC
TEC
Tromso
Moscow
Chilton
Okinawa
Darwin
Grahamstown
Port Stanley
Mawson
0.578
0.651
0.544
0.380
0.464
0.599
0.482
0.360
0.526
0.623
0.498
0.292
0.395
0.498
0.343
0.244
0.585
0.672
0.546
0.315
0.428
0.545
0.359
0.287
0.557
0.683
0.558
0.295
0.407
0.522
0.339
0.280
−0.505
−0.426
−0.389
−0.367
−0.388
−0.498
−0.277
−0.379
−0.636
−0.557
−0.432
−0.282
−0.343
−0.483
−0.265
−0.187
0.366
0.938
0.933
0.818
0.877
0.912
0.803
0.751
0.605
0.878
0.838
0.813
0.820
0.918
0.705
0.616
Table 5
The correlation coefficient between noon total electron content TEC(τ) at eight observatories and solar and ionospheric proxy indices Z(τ) during the observation of
CMH (06.2015–03.2017).
Station
SSN2
F10.7
Lymα
MgII
Vsw
Pch
GEC
TEC
Tromso
Moscow
Chilton
Okinawa
Darwin
Grahamstown
Port Stanley
Mawson
0.644
0.791
0.782
0.620
0.423
0.562
0.373
0.383
0.750
0.898
0.880
0.590
0.348
0.426
0.252
0.266
0.739
0.895
0.868
0.595
0.412
0.486
0.301
0.341
0.735
0.902
0.882
0.581
0.401
0.475
0.296
0.3320
−0.415
−0.464
−0.446
−0.467
−0.382
−0.440
−0.292
−0.368
−0.796
−0.886
−0.855
0.573
−0.301
−0.399
−0.184
−0.226
0.256
0.558
0.595
0.800
0.936
0.958
0.908
0.879
0.555
0.783
0.808
0.915
0.794
0.869
0.745
0.696
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TEC(τ) at eight selected locations.
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study and the valuable comments inspiring improvements to the paper.
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