# On the Nature of Propagating Intensity Disturbances in Polar Plumes during
the 2017 Total Solar Eclipse

Kyung-Suk Cho Space Science Division, Korea Astronomy and Space Science
Institute, Daejeon 305-348, Republic of Korea  Department of Astronomy and
Space Science, University of Science and Technology, Daejeon 305-348, Republic
of Korea  Il-Hyun Cho  School of Space Research, Kyung Hee University, Yongin,
17104, Republic of Korea  Maria S. Madjarska  Astronomy Program, Department of
Physics and Astronomy, Seoul National University, Seoul 151-742, Republic of
Korea  Max Planck Institute for Solar System Research, Justus-von-Liebig-Wig
3, 37077, G$\ddot{o}$ttingen, Germany  Valery M. Nakariakov  School of Space
Research, Kyung Hee University, Yongin, 17104, Republic of Korea  University
of Warwick, Coventry, CV4 7AL, United Kingdom  Heesu Yang  Space Science
Division, Korea Astronomy and Space Science Institute, Daejeon 305-348,
Republic of Korea  Seonghwan Choi  Space Science Division, Korea Astronomy and
Space Science Institute, Daejeon 305-348, Republic of Korea  Eun-Kyung Lim
Space Science Division, Korea Astronomy and Space Science Institute, Daejeon
305-348, Republic of Korea  Kyung-Sun Lee  Astronomy Program, Department of
Physics and Astronomy, Seoul National University, Seoul 151-742, Republic of
Korea  Jung-Jun Seough  Space Science Division, Korea Astronomy and Space
Science Institute, Daejeon 305-348, Republic of Korea  Jaeok Lee  Space
Science Division, Korea Astronomy and Space Science Institute, Daejeon
305-348, Republic of Korea  Yeon-Han Kim  Space Science Division, Korea
Astronomy and Space Science Institute, Daejeon 305-348, Republic of Korea

(Received Month day, Year; Revised Month day, Year; Accepted Month day, Year;
Accepted ApJ)

###### Abstract

The propagating intensity disturbances (PIDs) in plumes are still poorly
understood and their identity (magnetoacoustic waves or flows) remains an open
question. We investigate PIDs in five plumes located in the northern polar
coronal hole observed during the 2017 total solar eclipse. Three plumes are
associated with coronal bright points, jets and macrospicules at their base
(active plumes) and the other two plumes are not (quiet plumes). The electron
temperature at the base of the plumes is obtained from the filter ratio of
images taken with the X-ray Telescope on board Hinode and the passband ratio
around 400 nm from an eclipse instrument, the Diagnostic Coronagraph
Experiment (DICE). The phase speed ($v_{r}$), frequency ($\omega$), and
wavenumber ($k$) of the PIDs in the plumes are obtained by applying a Fourier
transformation to the space-time ($r-t$ plane) plots in images taken with the
Atmospheric Imaging Assembly (AIA) in three different wavelength channels (171
Å, 193 Å, and 211 Å). We found that the PIDs in the higher temperature AIA
channels, 193 and 211 Å, are faster than that of the cooler AIA 171 Å channel.
This tendency is more significant for the active plumes than the quiet ones.
The observed speed ratio ($\sim$1.3) between the AIA 171 and 193 Å channels is
similar to the theoretical value (1.25) of a slow magnetoacoustic wave. Our
results support the idea that PIDs in plumes represent a superposition of slow
magnetoacoustic waves and plasma outflows that consist of dense cool flows and
hot coronal jets.

##  1 Introduction

Polar plumes are long-lasting, dense, ray-like, and relatively bright solar
corona structures, usually observed in the EUV, X-ray, and white light. They
are magnetically open linear structures extending from the Sun’s surface to
about 30 R⊙ and are known to be a source of the fast solar wind (Poletto,
2015; Zangrilli & Giordano, 2020, and the references therein). Raouafi et al.
(2008) suggested that low-rate magnetic reconnection is responsible for the
formation and sustainability of plumes. Plumes are thought to be associated
with coronal bright points (CBPs, Madjarska, 2019) that form at the boundaries
of supergranulation cells. Several observations support that polar plumes are
associated with CBPs, X-ray jets, or EUV jets in the network regions. Wang &
Sheeley (1995) suggested that the properties of a few hours-lasting and hazy
plume structure can be adequately explained by the quasi-static upward
evaporation of material heated by conduction during magnetic reconnection at
the boundary of the super-granular cells. This suggestion was supported by the
observations of a particularly bright plume taken with the Solar Heliospheric
Observatory/Coronal Diagnostic Spectrometer (SoHO/CDS). Young et al. (1999)
investigated a plume above the limb and the plume base visible on the solar
disk. They reported that the temperature of the plume above the limb is about
1 MK, and the temperature remains constant with height. They found a strong
brightening lying directly below the plume’s main body with a high temperature
of 2 MK , i.e. a CBP. They suggested that the footpoint morphology is similar
to an emerging bipole in a region of unipolar magnetic flux which is typical
for CBPs (Madjarska, 2019).

Due to the open magnetic configuration in polar coronal holes, polar plumes
could be waveguides for magnetohydrodynamic (MHD) waves (e.g. Nakariakov,
2006; Poletto, 2015). The existence of waves in plumes has been demonstrated
by observations taken with UltraViolet Coronagraph Spectrometer (UVCS, Ofman
et al., 1997), Extreme ultraviolet Imaging Telescope (EIT, DeForest & Gurman,
1998), CDS (Banerjee et al., 2000), Solar Ultraviolet Measurements of Emitted
Radiation (SUMER, Gupta et al., 2012) on board the SoHO, and by a theoretical
model for the propagation of magnetoacoustic waves in polar plumes by Ofman et
al. (1999).

Propagating intensity disturbances (PIDs) in plumes have been interpreted as
compressible, magnetoacoustic waves as their intensity enhancement coincides
with the blue-shift of the O v 629 Å line profile taken with CDS (Banerjee et
al., 2000). Banerjee et al. (2009) observed intensity oscillations with a
period of 10 to 30 min and propagation velocity from 75 to 125 km s-1,
depending on the line formation temperature. They concluded that the most
likely cause for PIDs is slow magnetoacoustic waves. This conclusion was
supported by Gupta et al. (2012) who reported a detection of simultaneous
intensity enhancement and Doppler velocities of PIDs. The observational
evidence which favours the interpretation of PIDs in terms of slow
magnetoacoustic waves is summarised in Banerjee et al. (2011). Meanwhile,
McIntosh et al. (2010) suggested that plumes are associated with high speed
jets which are multi-thermal and repeat quasi-periodically. Later, Tian et al.
(2011) supported this by showing the significant asymmetries of spectral lines
observed with the Extreme-ultraviolet Imaging Spectrometer/Hinode. On the
other hand, Verwichte et al. (2010) demonstrated that the line asymmetry is
fully consistent with the interpretation of PIDs in terms of upward
propagating compressive waves. Pucci et al. (2014) concluded that PIDs
represent plasma outflows because the expected temperature dependence of the
magnetoacoustic wave was not observed. In their data, the apparent speed (30 –
300 km s-1) is higher in the low temperature channel AIA 171 Å than those in
the high temperature channels AIA 193 and 211 Å. On the other hand, Krishna
Prasad et al. (2011) established the temperature dependence of the apparent
phase speed, theoretically predicted for slow magnetoacoustic waves. Moreover,
Gupta (2014) found that the dissipation lengths of PIDs are frequency
dependent, which is consistent with the slow wave behaviour. A recent analysis
of damping and power spectra of PIDs in coronal holes, observed with SDO/AIA,
link this phenomenon with slow magnetoacoustic waves too (Jiao et al., 2016).
In addition, similar wave motions are routinely detected in the legs of
coronal loops, and their observed properties are well described by the MHD
wave theory (e.g. De Moortel, 2009; De Moortel & Nakariakov, 2012).

Due to the overlapping of the plume structures with fore- and background
emission and the lack of observations with a sufficiently high spatial
resolution, the polar plume’s triggering mechanism is still not well
understood. For this reason, the observations of the footpoints of the polar
plumes are vital as they can give a clear connection from the bipole emergence
through the H$\alpha$/EUV/X-ray jets to the polar plumes. In this study, we
investigate plumes in a polar coronal hole to inspect PIDs and their
relationship with activities at the base of the plumes. For this, we analyze
polar plumes that are found in an image taken at the 2017 total solar eclipse
by using the Diagnostic Coronagraph experiment (DICE), Hinode/XRT, SDO/AIA,
and SoHO/LASCO images. We divide the plumes into active and quiet ones, and
derive the wavenumber and frequency of PIDs by using the Fourier component
analysis to investigate a phase speed dependency on the temperature.

The following Section describes observation and data processing. In Section 3,
we present space-time plots of plumes and dispersion relations of the
propagation in the plumes. Finally, we summarize and discuss our results in
Section 4.

##  2 Observations and Data Processing

The observation targets are plumes observed at the north polar limb during the
total solar eclipse (TSE) on 2017 August 21 at a nearby Jackson hole, Wyoming.
The obtained data from the eclipse observation are white light (WL) images and
narrow-band polarization images around 400 nm. The WL images were taken using
a simple camera system consisting of a Canon 400 mm lens with a 2X extender.
During the TSE, we took WL images with different exposure times from 0.15 ms
to 0.25 s to acquire features from the chromosphere to the outer corona ( $>$
3 R⊙). After the image alignment and rotation, we applied the Multi-scale
Gaussian Normalization method (Morgan & Druckmüller, 2014) to the WL images.
This processing dramatically enhances the faint plume intensity signal at a
high altitude. The pixel resolution of the WL images is about 1.03 arcsec.
Narrow-band images were taken using the Diagnostic Coronagraph experiment
(DICE) consisting of an optical assembly, a filter wheel, a polarizer unit,
and a CCD camera. Since the temperature determines the shape of the coronal
spectrum (Thompson-scattered photospheric light), we used the polarization
intensity ratio at the temperature-sensitive wavelengths at 393.9 and 402.5
nm, and determined the coronal temperature by applying the method suggested by
Cram (1976). The pixel size of the polarization data is about 12.7 arcsec, and
we used 3 by 3 data binning of stacked images after aligning the images for
specific filters and polarization angles to obtain a temperature map. The
temperature measurements using the pass-band ratio imaging has been conducted
during the TSE (Reginald et al., 2017) and Balloon mission (Gopalswamy et al.,
2020). More detailed description of the DICE instrument and data reduction can
be found in Cho et al. (2020). First from the DICE observations we identified
regions of enhanced emission associated with CBPs and their temperature was
first determined. To verify the CBPs and the temperature at the base of the
plumes, we also checked data taken with the X-ray telescope (XRT, Golub et
al., 2007) on board Hinode (Kosugi et al., 2007) during the eclipse time. It
was noted that the temperature structures in the DICE data are generally
similar to those in the XRT images but CBPs could not be seen in the DICE data
due to occulting the solar disk by the moon. We used level 1 data of XRT
processed by xrt_prep.pro. The pixel resolution of the XRT images is about 1
arcsec. By taking a full-Sun image observed at 16:43 UT, we calculated the
electron temperature by applying the xrt_teem.pro to the ‘Al-poly’ and ‘Al-
mesh’ filter data pair, which is sensitive for temperatures from Log T = 5.5
up to Log T = 6.3 (Narukage et al., 2014).

We also used SoHO (Domingo et al., 1995)/LASCO C2 (Brueckner et al., 1995) and
SDO (Pesnell et al., 2012) /AIA (Lemen et al., 2012) data to inspect the off-
limb plume structure and dynamics. The level 0.5 data of LASCO C2 from 16:00
UT to 20:00 UT were used to produce an imaging data cube. We normalized the
data set in a temporal direction by subtracting a background image, including
the F coronal and the instrument stray light. We calculated all pixel median
values between 2.2 R⊙ and 5.8 R⊙ in a temporal direction. We subtracted this
value from the data set and divided by the corresponding standard absolute
deviation. We took an averaged image from the processed data cube after
removing the blinking due to frame-to-frame variation in exposure time and
spikes (stars) in the data. The AIA 171, 193, 211, and 304 Å data with a 12 s
time cadence, and a 0.6$\arcsec$ per pixel scale were used to inspect the
dynamics of the plume footpoints within the range from 1 to 1.26 R⊙. To
produce a space-time image $I(r,t)$, we defined slit cuts along the plume
lengths in the AIA data. The position of a slit was determined by a linear
fitting from the visually determined locations. Thus, the inclined distance of
the slits represents the distance from the solar surface. The intensities
along the slits, and time are used to investigate the plume dynamics. For a
given distance, we divided the original time series by its temporal average
and took the first order time-difference that is obtained by subtracting the
previous intensity from the current one. Then we applied a median filter with
the 3 minutes by 1.5 Mm to eliminate the noise. In case of AIA 304 Å, the
space-time image is subtracted and then divided by the temporal mean and
standard deviation to remove the background (Morgan et al., 2006).

From the AIA slit images, we derived the properties of localized moving
features in the plumes using Fourier transformation. To calculate the
propagation speed, we applied the Fourier transformation to the space-time
image. The propagating feature in $I(r,t)$ appears in the Fourier power
($|F(k_{r},w)|^{2}$), and its phase speed could be defined as
($-\omega$/$k_{r}$). Hence, a positively propagating feature in $I(r,t)$
appears as a prominent power in the second and forth quadrants in the Fourier
space (e.g., Appendix in DeForest et al., 2014). We set a slit along the
plumes in the AIA channels to track the PIDs and generate an $I(r,t)$ image
that contains both the temporal and spatial information of the propagation. A
Fourier transformation is applied to the $I(r,t)$ image to obtain its
conjugate ($k_{r}$, $\omega$) plane. This results in the observational
dispersion relationship for the frequency ($\omega$) as a function of
wavenumber ($k_{r}$). Since moving features with a speed in the $I(r,t)$ plane
are transformed to features lying along a diagonal line in the ($k_{r}$,
$\omega$), we can derive a particular speed of the propagation features by
measuring the slope ($\omega$/$k_{r}$) of the diagonal line (e.g., Figure 1 in
DeForest et al., 2014).

##  3 Results

For tracing the plumes to the solar surface, we used the SDO/AIA, SOHO/LASCO
C2, and the eclipse data. Figure 1 shows the WL eclipse image that is composed
of SDO/AIA 171 Å in the low corona and LASCO C2 images in the upper corona.
The polar coronal hole in the northern hemisphere contains dense and
relatively bright plumes extending from the solar surface to about 5.5 R⊙. We
used the eclipse image that fills a gap between the low corona ($<$ 1.2 R⊙)
and the upper corona (2.5 R⊙ $\leq$ R $\leq$ 5.5 R⊙). In this study, we
selected the plumes whose connection from the higher corona to the surface is
clear and then marked them with arrows and labels as shown in Figure 1. It is
noted from the eclipse and LASCO images that the plumes (L1, C, and R1) in the
middle are brighter and more extended into the higher corona than the others
(L2 and R2). The plumes, ‘L1’, ‘C’, and ‘R1’ correspond to the coronal fine
structures, ‘3’, ‘2’, and ‘1’, respectively, in the Figure 1 of Hanaoka et al.
(2018).

We inspected the location where these plumes are rooted in the AIA images to
study the physical properties of the plasma at the plume footpoints. Figure 2
shows the averaged intensity maps of AIA 171, 193, 211, and 304 Å channels,
from top to bottom respectively. These maps are obtained from the AIA images
with 12 seconds cadence during 100 minutes from 16:00 UT to 17:40 UT. Except
for the AIA 304 Å channel, plume structures are seen in all AIA channels. The
plumes in the AIA 171 Å channel (maximum response temperature, Te $\sim$0.7
$\times$ 106 K from the Fe ix line, O’Dwyer et al., 2010) are brighter and
denser than those seen in the AIA 191 and 211 Å channels. The plumes are also
detected in the high-temperature channels of AIA 193 ( 0.7 $\times$ 106 $\leq$
Te $\leq$ 1.6 $\times$ 106 K) and AIA 211 Å (Te $\sim$1.1 $\times$ 106 K and
1.4 $\times$ 106 K for Fe x and Fe xi lines, respectively). In this study, we
will refer to the high temperature channels AIA 193 and 211 Å as AIAH and to
the low temperature channel the AIA 171 Å as AIAC. As it can be noted from
Figure 2, cool and hot plasma co-exist in plumes. From the animation of Figure
2, we identified apparent outflows in the plumes in AIAH and AIAC, and
recurrent spicules and macro-spicules in the base of the plumes from the 304 Å
channel animation. In AIAH, EUV jets are identified in the plumes ‘L1’, ‘C’,
and ‘R1’ which have CBPs in their footpoints, and extend to the higher corona
with brighter structures seen in the LASCO C2 FOV as shown in Figure 1.

Based on the multi-site WL observations during the 2017 TSE, Hanaoka et al.
(2018) reported that these plumes are associated with the coronal (eclipse)
jets, while the L2 plume is not accompanied by WL jets seen during the
eclipse. According to their study, the jets associated with the plumes were
upwardly ejected with an apparent speed of about 450 km s-1 beyond 2 R⊙. The
R2 plume that has no jets, macrospicules, and a CBP, is not studied in their
work.

As suggested by Wang & Sheeley (1995), the plumes’ hazy structures in high-
temperature imaging channels may be due to quasi-static upward evaporation
heated by thermal conduction following magnetic reconnection. This suggestion
led us to inspect the temperature structure at the base of the plumes. The
temperature was estimated from the Hinode/XRT and the DICE data by applying
the methods described in the previous section. Figure 3 shows EUV and soft
X-ray intensity images and temperature maps from XRT and DICE. The XRT image
was taken with the ‘Al-poly’ filter. It shows that EUV brightenings at the
base of the plumes (L1, C, R1), are consistent with CBPs, and the temperature
structures from XRT and DICE look similar to each other. It reveals that the
plumes (L1, C, R1) that have jets are associated with CBPs in their bases.
Their temperature ranges between 1 MK and 1.5 MK (Figure 3 (c) and (d)). The
other plumes, L2 and R2, have no CBPs at their bases, and their temperatures
are not significantly high.

Flows of hot and cool plasmas in the plumes were investigated by using space-
time plots along the plumes tracing them from the limb. By using the method
described in Section 2, we produced space-time plots over the dashed bars in
Figure 2 as shown in Figure 4. In Figure 4, the oblique alternating bright and
dark stripes represent the intensity disturbances that propagate upwardly
along the plumes. The strips in AIAH look similar, and are more prominent in
AIA 193 Å due to a lower signal-to-noise of AIA 211 Å. Most of the strips in
AIAC coincide with those in AIAH. However, we find that some faint AIAC strips
between 17:00 UT and 17:10 UT are missing in AIAH as denoted by arrows on the
panel of L1 plume in Figure 4, and vice versa (e.g., the jet in AIAH at 17:00
UT as marked by an arrow on the panel of the R1 plume). In the jets associated
plumes (L1, C, and R1), we find a macro-spicules that rise to up to 50″ and
later fall back (AIA 304 panels of Figure 4). There is a difference between
the jet and the macrospicule activities. For instance, the bright jet (black
dashed line) in the C plume is associated with a weak macrospicule, while the
big macrospicule at $\sim$17:00 UT is associated with a weak PID in AIAH and
AIAC. The one-to-one connection between the macro-spicules and the jets has
ambiguity. It is quite clear for the L1 and R1 plumes, but not for the C
plume.

Macro-spicules in Plume C ($\sim$17:10 UT) and L1 ($\sim$17:20 UT) coincide
with jets. However, the jet at $\sim$17:00 UT in the plume R1 occurs after the
rising of the macro-spicule ($\sim$16:20 UT). It is likely that the
macrospicules are related to the CBPs in general.

As marked with the black dashed line in Figure 4, the inclination of a strip
for the time axis can be used to estimate the individual strip speed. Since we
are interested in statistics of the PID speed at the different channels of
AIA, we performed a Fourier transformation to the space-time data and obtained
a dispersion relation, as shown in Figure 5. The Fourier transformation
localizes moving features, and the features with speed in the space-time
$I(r,t)$ plane are transformed to features lying along the diagonal line in
the dispersion ($k_{r}$, $\omega$) plane. Non-moving and quasi-stationary
features exist at low $\omega$, and the noise sources are distributed
isotropically.

To obtain the PID general properties, we obtained the mean Fourier powers of
the intensity disturbances in all the plumes for the different AIA channels.
Figure 6 shows the dispersion relationships of all plumes in the various
filters, in which the power is enhanced, and the noise is reduced. To obtain
an average speed of propagating packets with different wave number and
frequency, we set a diagonal dashed line laid along the features as shown in
Figure 6, and obtained the propagation speed ($v_{r}$ = $-\omega$ / $k_{r}$)
from the slop of the diagonal line. When we visually set the line that passes
through zero $\omega$ and $k_{r}$, we did not use the peaks of the power of
plumes located at a small wave number and low frequency because they can be
related to the jets. In other words, we determined the velocity of the PIDs by
considering the features in the high frequency (10 – 20 min periods) rather
than low frequency (20 – 30 min periods) as in the previous reports by
DeForest & Gurman (1998) and Banerjee et al. (2000). For example, $\sim$166 km
s-1 in AIA 193 is calculated from wavenumber of -0.01 Mm-1 (wavelength of 100
Mm) and frequency of 0.1 min-1 (period of 10 min) as shown in the upper right
panel of Figure 6. For the different AIA channels, the disturbance speeds
($v_{r}$) are not the same but increase as the temperature increases. In the
cooler channel (AIA 171 Å), the speed is about 120 km s-1. The wavenumber
($k$) is shorter than $\sim$66 Mm, and its frequency ($\omega$) is longer than
10 minutes. In comparison to the cool channel, the wave speeds in hot channels
are faster, and their wavelengths ($\sim$142 Mm) are longer. The wave speeds
in the AIA 193 and 211 Å channels are $\sim$162 km s-1 and $\sim$211 km s-1,
respectively. The quasi-stationary features that exist at zero $\omega$ and
$k_{r}$ in AIAC disappear in AIAH. Our method contains the measurement errors
determined from 10 estimations of the speeds for the different channels. The
estimated mean speeds are $\sim$123 km s-1, $\sim$172 km s-1, and $\sim$232 km
s-1, and their standard deviation errors are $\pm$3 km s-1, $\pm$6 km s-1, and
$\pm$24 km s-1 for 171, 193, and 211 A, respectively.

We classified the plumes into two groups: active (L1, C, R1) and quiet plumes
(L2, R2). We added the Fourier power for the active plumes (group I: L1, C,
R1) and the quiet plumes (group II: L2 and R2), and investigated their
dispersion relations in the AIA 171 Å and AIA 193 Å channels. Figure 7 shows
the relationship between the two groups in the low and high AIA temperature
channels, AIAC and AIAH. In AIAC, the wavenumber and frequency of both groups
have a similar trend, but the speed of group I ($\sim$130 km s-1) is higher
than that of group II ($\sim$116 km s-1). However, the wavenumber and
frequency in AIA 193 Å are different for groups I and II. The power of AIA 193
Å of group I is concentrated at low frequency ($\sim$30 min) and low
wavenumber, while that of group II has a broad range of frequencies and
wavenumbers as like AIA 171 Å in group I. In AIAH, the speed ($\sim$185 km
s-1) of group I is higher than the speed of group II ($\sim$152 km s-1).

PIDs are detected not only in plumes, but also in interplume regions (e.g.,
Gupta et al., 2010). Thus, we also checked whether PIDs in the interplume
regions have speed temperature dependency by applying the same method as for
PIDs in plume regions. As shown in Figure 8, we took three interplume strips
as far as possible from the plumes, and then inspected the PIDs and derived
their Fourier powers for the different channels. As a result, we cannot
identify any clear signature of speed dependency on the temperature from PIDs
in the interplume regions. This may due to the low signal to noise ratio
because of the low intensity in the interplume regions, especially in the AIAH
channels. Other possibilities are thermal misbalance (e.g., Zavershinskii et
al., 2019) and steady upflows which is a property of the equilibrium (e.g.,
Cho et al., 2020) in the interplume regions, which could affect the apparent
phase speed of slow waves. It is also noteworthy that the slow waves seen in
the structures of different temperature propagate along different paths in the
interplume regions.

##  4 Summary and Discussion

Five plumes in the polar coronal hole in the northern hemisphere observed
during the TSE 2017 have been investigated using the LASCO C2, SDO/AIA,
Hinode/XRT, and DICE data. The plumes were traced back from the high corona
($\sim$5.5 R⊙ in LASCO C2 FOV) to the chromosphere (AIA 304 Å), and the
footpoints of the plumes were investigated. We applied 2D Fourier
transformation to the space-time plot of the plumes in the AIA 171, 193, and
211 Å channels, and obtained an empirical dispersion relation of PIDs in the
plumes. From the dispersion relation, we found that in all analysed plumes,
PIDs show a temperature dependence of their speed (i.e., AIAH propagation
speed is larger than that of AIAC one). This tendency is more evident when we
added the Fourier power of all plumes in the different channels. AIAC has
broader ranges of frequencies ($\omega$) and wavenumbers ($k$) than those of
AIAH. The non-moving features located at zero-frequency and zero-wave numbers
in AIAC disappear in AIAH, in which high power signals are located in the
lower frequency and wavenumber.

The quasi-periodic intensity change in Figure 4 is similar to the reported by
Tian et al. (2011) who concluded that the intensity change represents outflow
(jets) because they did not find an obvious increasing trend in the speed with
the increasing temperature. Pucci et al. (2014) reported that the
perturbations in AIAC have a higher speed than those in AIAH. They concluded
that the radiation variation in the plumes represents outflow material since
their events did not show the temperature dependence which is expected from
the magnetoacoustic wave hypothesis. In this study, we have found a
temperature dependence of the speed by applying the Fourier transformation. In
addition, we found that the observed ratio ($\sim$1.3) of the speeds in the
AIA 171 and 193 Å channels are similar to the expected theoretical values
(1.25, Nakariakov, 2006; Pucci et al., 2014). These results could be an
evidence that supports the wave hypothesis.

The events studied here may differ in their properties from those of Pucci et
al. (2014), who studied cooler plumes (see, Figure 1 in Pucci et al., 2014).
Here, we have investigated two groups of plumes that have different
properties. By measuring temperatures from the XRT and DICE observations, we
divided plumes depending on the existence of the high-temperature CBPs. Active
plumes are bright and associated with jets and macrospicules ejected from
high-temperature CBPs. These plumes extend as brighter (denser) structure into
the higher corona ($\sim$5.5 R⊙). The quiet plumes are less bright, diffuse,
and quasi-stable structures and possibly represent the decay stage of the
plume evolution. Propagation speeds of PIDs in active plumes are higher than
those of the quiet plumes, and this tendency is more significant in AIAH. The
active and quiet plumes have different wavenumbers and frequency patterns in
AIAH, but their difference is not discernible in AIAC. It is noteworthy
mentioning that the active plumes associated with CBPs may be an early stage
of the plume’s evolution ([see][]2003A&A...398..743D). The disturbance speed
in AIAC is lower than that of AIAH, but the difference is not more significant
than active plumes (group I). From the AIAH movie from August 19 to 23, it is
noted that the CBP in the foopoints of quiet plume L2 disappeared and the
plume became quieter by the time of the eclipse observations on August 21. The
footpoint behavior of R2 could not be inspected because the footpoint of R2
plume moves behind the limb.

Our results lead us to conclude that the emission intensity variations in the
studied plumes represent slow magnetio-acoustic waves. However, we cannot rule
out the co-existence of plasma outflows with slow waves. The plumes’ flows are
likely to consist of cool and dense material from macrospicules and high
temperature jets from CBPs. The flows seen in the low temperature channels may
be plasma flows produced by quasi-static upward evaporation heated by thermal
conduction during magnetic reconnection at the boundary of the
supergranulation cell (Wang & Sheeley, 1995).

Due to the overlapping of plume structure with fore- and background, and the
lack of the observations at higher resolution, the triggering mechanism of the
polar plume is still not well understood. Together with the new opportunity
with next generation coronagraph, CODEX (Coronal Diagonostic Experiment) that
provides electron temperature and speed structure of plumes (Cho et al.,
2017), imaging and spectroscopic observations using high-resolution telescopes
from the ground (e.g., Goode Solar Telescope (GST) in Big Bear Solar
Observatory) and space (e.g., Interface Region Imaging Spectrograph (IRIS))
focusing on the plumes’ roots in polar coronal holes is essential to address a
new model for understanding the physical mechanisms that take place in active
plumes.

This work was supported the Korea Astronomy and Space Science Institute under
the R&D program (2020-1-850-07). IHC acknowledges a support from the National
Research Foundation of Korea (NRF-2019R1C1C1006033). MM was supported by the
Brain Pool Program of the National Research Foundation of Korea
(NRF-2019H1D3A2A01099143). KSL was supported by the National Research
Foundation of Korea (NRF-2020R1A2C2004616).

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Figure 1:  A composite image of LASCO C2 (R $>$ 2.5 R⊙), White Light (WL)
image (1.1 R⊙ $\leq$ R $\leq$ 2.5 R⊙), and AIA 171 Å (R $<$ 1.10 R⊙). The WL
image is produced by using the WL images taken by Cannon 400 mm camera during
the total eclipse of 2017 August 21 (17:35 UT - 17:37 UT), and the AIA 171 Å
was obtained at 17:45 UT. The LASCO C2 image is the mean intensity between
16:00 UT and 20:00 UT. Arrows denote the plumes in the north coronal Hole (CH)
for this study.  Figure 2:  Averaged SDO/AIA images between 16:00 UT and 17:40
UT to enhance the structure of plumes denoted by arrows in Figure 1. The AIA
171, 193, 211, and 304 Å are plotted in the panels from the top to the bottom.
Dotted slots along the plumes are used to inspect activities at the bottom of
the plumes and to trace flows in the plumes marked with arrows in Figure 1.
See the accompanying animation from 16:00 UT to 17:40 UT, which shows outflows
and jets in the plumes, and recurrent spicules and macro-spicules in the base
of the plumes. An animation of this figure is available in the online journal.
Figure 3:  EUV and X-ray images together with coronal temperature maps from
Hinode/XRT and 2017 total solar eclipse experiment, DICE. (a) AIA 171 Å image
taken 17:36 UT, (b) Hinode XRT/Al-poly image before the eclipse, (c)
temperature map calculated by the ratio method using Al-mesh and Al-poly data,
(d) temperature map calculated by the ratio method using polarized brightness
images taken 3934 Å and 4025 Å. The dashed slot denote the same locations in
Figure 2.

Figure 4:  Space-time plots of the de-trended AIA 171, 193, 211, 304 Å images
from top to bottom. From the left to the right panels, the space-time plots
are displayed for the regions of L2, L1, C, R1, R2 in Figure 3(b). Dashed line
denotes an example of strips, and arrows indicate AIAC strips are missing in
AIAH, and vice versa (see text).  Figure 5:  Wave number - frequency
($k-\omega$) maps for the five plumes (from the left to the right) and three
AIA channels of 171, 193, and 211 Å (from the top to the bottom).

Figure 6:  Averaged wave number - frequency ($k-\omega$) maps for all plumes
in the AIA 171, 193, 211, and 304 Å channels for both groups I and II. The
slop of the diagonal dashed line is used to obtain the propagation speed.

Figure 7:  Averaged wave number - frequency ($k-\omega$) maps of AIA 171 and
193 Å for plumes with active foot-points (upper panels) and quiet foot-points
(lower panels). The slop of the diagonal dashed line is used to obtain a
propagation speed.

Figure 8:  Locations of three interplumes (‘A’, ‘B’, ‘C’) and their PIDs
properties. (a) AIA 171 Å image is denoted with interplumes’ locations, (b)
space-time plots of the AIA 171, 193, 211, and 304 Å images from top to
bottom, and (c) wave number - frequency ($k-\omega$) maps of AIA 171, 193 and
211 Å for the interplumes. The last column of the wave number - frequency maps
is the mean power map of the all interplumes.

Table 1: Activities of the plumes | L2 | L1 | C | R1 | R2
---|---|---|---|---|---
Jets occurrence | no | yes | yes | yes | no
Macro spicule | quiet | active | active | active | quiet
Foot-point Temp | low | high | high | high | low
Plume activity | quiet | active | active | active | quiet