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Astron. Astrophys. 355, 1152-1159 (2000)
3. Results
First we will discuss the results from the dataset s16834r00,
during which we detected the macro-spicule. In Figs. 2 & 3,
we show time slices of the observed O V
629 Å and Mg IX
368 Å respectively. In these plots, the solar
north-south ( ) direction is in the
vertical axis, the horizontal axis is time. To bring out details in
the intensity map a contrast enhanced map is shown in the lower
panels. This technique has been explained in detail in Doyle et al.
(1999). Note that the macro-spicule event occurs between 53 to 58
minutes into the observing sequence. Although the
Mg IX image (Fig. 3), is noisy due to low
counting statistics, one can still see a bright jet like
structure.
![[FIGURE]](img14.gif) |
Fig. 2. The space-time behaviour of the intensity in the O V 629 Å line in the s16834r00 dataset. The gray scale coding has the most intense regions as dark. The lower image is contrast enhanced.
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In Fig. 4, we show the temporal evolution map of the
macro-spicule intensity and velocity in O V . The
contours are those of the O V intensities. Note
that in the intensity map, the macro-spicule shows extremely bright
emission at its base. The brightest pixel in the velocity map shows a
red shift of 130 km s-1.
The emission from the brightest region in the macro-spicule shows
predominantly red shifted velocities, i.e., they are directed away
from the observer. The left side shows much smaller velocities, and
some positions on this side of the feature also show blue shifts, e.g.
at positions 8-9 pixels and a time of 54 minutes. In Fig. 5 we
show the line profile corresponding to pixel position 8 and time 54
minute, fitted with a Gaussian. It indicates a blue shift of 22 km
s-1. Note that at a later phase of the evolution of the
macro-spicule, pixel position 11 and time 55.2 min, we find an average
red shift of 92 km s-1 after fitting the line profile with
a single Gaussian (see Fig. 6). Bear in mind that this is not a
spatial map, rather a temporal map, thus it implies that in the
initial phases of the macro-spicule we had strong blue-shifts,
followed by red shifts in the decaying phase. This can be interpreted
as a rotating feature - a sort of solar tornado as named by
Pike & Mason (1998).
![[FIGURE]](img19.gif) |
Fig. 4. Velocity and intensity temporal map for the event in s16834r00 as observed in O V 629Å. The contour shows peak O V intensities.
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![[FIGURE]](img21.gif) |
Fig. 5. For O V 629 Å line, a single broad Gaussian is fitted to the line corresponding to spatial pixel 8 and time 54 mins (see Fig. 4 for an overview of the location).
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![[FIGURE]](img23.gif) |
Fig. 6. For O V 629 Å line, a two component Gaussian is fitted to the data at spatial pixel 11 and time 55.2 mins (see Fig. 4 for an overview of the location).
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For a closer inspection of the intensity and velocity at individual
locations in the , we plot the data
for a series of pixels in Fig. 7. This can also be viewed as
horizontal slices of the `space-time' plot and provides information
about the radial dependence of intensity and velocity. The solid line
represents the total counts and the dashed line represents the
velocity. Note that pixel 4, which marks the limb, shows blue shifts
during the event and as we progressively go outside the limb we have
pronounced red shifts. This might indicate the presence of a double
sided jet. Furthermore, the increase in Doppler velocities with height
can be due to plasma accelerating outwards. There is clear evidence of
acceleration of plasma from a distance of 20 to 45 arc sec above the
limb (see 4th to 9th pixels). Above that altitude it tends to a
constant apparent velocity. Thus a rotating accelerating plasma could
explain the observation.
![[FIGURE]](img28.gif) |
Fig. 7. The evolution of the macro-spicule event as observed in O V 629 Å intensity (solid line) and velocity (dashed line) at different positions.
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Now we turn our attention to the s16834r01 dataset, which was taken
4 seconds after the s16834r00
sequence and almost in the same location as s16834r00. The observation
was programmed in such a way that the next sequence automatically
traces back to the same location as the previous one. Therefore,
within pointing errors we can assume that it is in the same part of
the coronal plume plasma. Furthermore since we bin our data across 3
original pixels 5 arc sec, any
difference in pointing should be minimum. In this part of the analysis
we will study the oscillations in the plume plasma and also try to
find out whether there is any effect of the macro-spicule on the plume
oscillations.
A rotating plasma will also tend to asymmetrically broaden the line
profiles. In order to examine this more closely, we attempted to fit
two Gaussians to the profiles at several locations, particularly
during the event when the single profile width was generally greater
than the background. As an example of this we can look again at
spatial pixel 11 at time 55.2 mins which is plotted in Fig. 6. At
this location the observed line profile shows an asymmetric
significantly broadened profile. If a single Gaussian is fitted the
maximum red shift superficially corresponds to a redshift of around 92
km s-1 (as noted above). However, fitting with a two
component Gaussian results in a blue shift of 37 km s-1 for
one component and red shift of 158 km s-1 for the other,
relative to the background.
3.1. Fourier transform
In the top left panel of Fig. 8, we show time slices of the
observed O V 629 Å line in
dataset s16834r01. Fluctuations in the bright features are clearly
visible and their appearance seems periodic. These structures are so
bright that in a gray scale presentation it is difficult to identify
weakly emitting structures. To bring out details in the intensity map
we use a technique based on enhancing the contrast of these
structures, thereby filtering out the bright components in the
brightness evolution displays (as done for the lower panels of
Figs. 2 & 3).
![[FIGURE]](img30.gif) |
Fig. 8. The gray scale plots show the space-time behaviour of the intensity in the O V 629 Å line for the s16834r01 dataset. The gray scale coding has the most intense regions as dark. The upper right-hand panel show the counts summed over all time against the slit locations. The lower right-hand panel shows the power above the significance level as a function of frequency of oscillation and spatial position along the slit.
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The contrast enhanced space time behaviour is shown in the lower
left panel. It clearly shows the periodic brightening of features with
a periodicity of 25 minutes. The
power spectra of the observed intensities at individual pixels along
the slit, obtained from the Fourier transform are shown in the right
lower panel of Fig. 8. The total number of counts in a pixel
(summed counts) during the observation is shown in the upper
right-hand panel, and is useful in identifying the solar limb and the
plume. The O V power shows strong peaks between
0.2 to 1 mHz. From the overlay of EIT images and slit and also from
the intensity variation across the slit we identify the 9th pixel (in
our binned scale) to be just inside the plume structure. Thus we will
now concentrate on this pixel and study its power spectra in greater
detail.
In Fig. 10, the O V intensity and velocity
power spectrum in a typical plume structure (9th pixel in the binned
scale) is shown in panels (a) and (c) respectively. The lighter and
the darker line correspond to the unsmoothed and smoothed power
spectra respectively. The solid and dashed horizontal lines represent
the 99.9% significance level of the unsmoothed power and the smoothed
power respectively. The corresponding intensity and velocity
variations with time are plotted in panels (b) and (d) respectively.
The velocity oscillations are shown before (the lighter continuous
line) and after a low-pass filter of everything above 4 mHz has been
applied (the darker line). The O V intensity power
shows a strong peak between 0.7 and 0.8 mHz, whereas the velocity
power shows a peak at 1 mHz and a second peak around 0.6 mHz. Though
on an average outside the limb the line shift should be zero, we do
find the presence of a small blue shift (see Fig. 10d). We also
find an anti-correlation between velocity and peak intensity as shown
in Fig. 11. The ordinate have been normalized to arbitrary units
for the overlay of intensity and velocity. Note that for the first 60
minutes of the observing sequence, when there is a peak in intensity
the plasma is generally blue shifted (particularly when the
oscillations are more prominent). Oscillation of long periods, are
clearly visible in the light curves of Fig. 9. In this plot we
show the light curves for the two consecutive time series s16834r00
and s16834r01. In principle these two light curves could be combined
and one could then view it as a continuous time series of 227 minutes.
The data drop out and the macro-spicule that occurred in dataset
s16834r00 have been taken out and a linear interpolation applied for
those time intervals between 36.4-43.8 and 53.5-60.4 minutes. These
interpolated regions are shown (plotted in Fig. 9) as the
straight line sections between these times. The consecutive
light-curves suggest that the macro-spicule has not affected the
oscillations of the plume plasma. Furthermore the transit of the
macro-spicule has not affected the periodicity of the plume plasma as
it is still oscillating with a long period afterwards. This tends to
indicate that although the macro-spicule has come across our field of
view, while observing this particular north polar coronal plume, the
macro-spicule is not connected with the plume structure.
![[FIGURE]](img33.gif) |
Fig. 9. The light curves corresponding to pixel position 9 in the two time series s16834r00 (left) and s16834r01(right). Note the clear presence of a long periodicity. In the left panel the data drop out and the macro-spicule has been taken out and the data linearly interpolated. These interpolated regions are plotted as the straight line sections between the times of 36.4-43.8 and 53.5-60.4 minutes.
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![[FIGURE]](img35.gif) |
Fig. 10a - d. For pixel position 9 in the s16834r01 dataset & O V 629 Å line, a & c shows the intensity and velocity power spectra respectively. The lighter lines correspond to unsmoothed data and the darker lines correspond to the smoothed data. The solid and the dashed horizontal lines represent 99.9% significance levels for the unsmoothed and smoothed power respectively. Panel b shows the variation of intensity with time (light curve) while d shows the velocity oscillation. The velocity oscillations are shown before (the lighter continuous line) and after a low-pass filter of everything above 4 mHz has been applied (the darker line).
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![[FIGURE]](img37.gif) |
Fig. 11. For O V 629 Å line, the variation of intensity (solid line) and velocity (dashed line) with time corresponding to pixel position 9 of s16834r01 dataset.
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3.2. Wavelet transform
The localised nature of time series analysis by wavelets makes them
ideal for the data in s16834r00/r01. We should point out that wavelet
transforms suffer from edge effects at both ends of the time series.
The region in which these effects are important are defined by the
`cone of influence' (COI). The COI is an approximate measure that
indicates the locations at which the results become unreliable due to
these edge effects. We use the definition of COI given by Torrence
& Compo (1998) but see also Meyers et al. (1993) for an alternate
discussion.
In Figs. 12 & 13 we present the wavelet analysis for the
intensity and the velocity respectively, corresponding to the second
time series s16834r01. The COI is marked as cross-hatched and any
power over the 99.9% significance level is marked by continuous black
line contours. On the right of these figures is plotted the global
wavelet spectrum, which is just the average of the wavelet power
spectrum over time. The dotted line in the global wavelet spectrum is
again the 99.9% significance level. Torrence & Compo (1998) have
pointed out that as the Fourier spectrum is smoothed, it approaches
more and more closely the global wavelet spectrum. For the sake of
comparison we present the results for the same 9th pixel as done
previously for the Fourier analysis (see Fig. 10). The time
frequency phase plot of the light-curve does indicate strong localised
power between 0.7 mHz and 0.8 mHz during the major part of the time
sequence. In comparison the velocity power is significant around 0.6
and 1 mHz. Note that the power is not significant during the last 20
minutes of the observing sequence, in either the intensity or the
velocity.
![[FIGURE]](img39.gif) |
Fig. 12. The wavelet analysis for O V in the plume at the same location as in Fig. 10. The left panel shows the time frequency phase plane plot of the light-curve. The right panel shows the average of the wavelet power spectrum over time. The thick contour encloses regions of greater than 99.9% confidence. Cross-hatched regions, on either side indicate the `cone of influence' where the edge effects become important. Note that maximum intensity power lies between 0.7-0.8 mHz (20-24 min periodicity).
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![[FIGURE]](img41.gif) |
Fig. 13. Wavelet analysis for the O V 629Å velocity, same as in Fig. 12. Maximum power lies around 0.65 mHz (25 min periodicity)
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© European Southern Observatory (ESO) 2000
Online publication: March 21, 2000
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