35 research outputs found
Horizontal flow fields observed in Hinode G-band images IV. Statistical properties of the dynamical environment around pores
The extensive database of high-resolution G-band images observed with the
Hinode/SOT is a unique resource to derive statistical properties of pores using
advanced digital image processing techniques. The study is based on two data
sets: (1) Photometric and morphological properties inferred from single G-band
images cover almost seven years from 2006 October 25 to 2013 August 31. (2)
Horizontal flow fields have been derived from 356 one-hour sequences of G-band
images using LCT for a shorter period of time from 2006 November 3 to 2008
January 6 comprising 13 active regions.
A total of 7643/2863 (single/time-averaged) pores builds the foundation of
the statistical analysis. Pores are preferentially observed at low latitudes in
the southern hemisphere during the deep minimum of solar cycle No. 23. This
imbalance reverses during the rise of cycle No. 24, when the pores migrate from
high to low latitudes. Pores are rarely encountered in quiet-Sun G-band images,
and only about 10% of pores exists in isolation. In general, pores do not
exhibit a circular shape. Typical aspect ratios of the semi-major and -minor
axes are 3:2 when ellipses are fitted to pores. Smaller pores (more than
two-thirds are smaller than 5~Mm^2) tend to be more circular, and their
boundaries are less corrugated. Both area and perimeter length of pores obey
log-normal frequency distributions. The frequency distribution of the intensity
can be reproduced by two Gaussians representing dark and bright components.
Bright features resembling umbral dots and even light-bridges cover about 20%
of the pore's area. Averaged radial profiles show a peak of the intensity at
normalized radius R_N = r /R_pore = 2.1, followed by maxima of the divergence
at R_N= 2.3 and the radial component of the horizontal velocity at R_N= 4.6.
The divergence is negative within pores.Comment: 14 pages, 13 figures, Accepted for publication in Astronomy and
Astrophysic
Velocity fields in and around sunspots at the highest resolution
The flows in and around sunspots are rich in detail. Starting with the
Evershed flow along low-lying flow channels, which are cospatial with the
horizontal penumbral magnetic fields, Evershed clouds may continue this motion
at the periphery of the sunspot as moving magnetic features in the sunspot
moat. Besides these well-ordered flows, peculiar motions are found in complex
sunspots, where they contribute to the build-up or relaxation of magnetic
shear. In principle, the three-dimensional structure of these velocity fields
can be captured. The line-of-sight component of the velocity vector is
accessible with spectroscopic measurements, whereas local correlation or
feature tracking techniques provide the means to assess horizontal proper
motions. The next generation of ground-based solar telescopes will provide
spectropolarimetric data resolving solar fine structure with sizes below 50 km.
Thus, these new telescopes with advanced post-focus instruments act as a "zoom
lens" to study the intricate surface flows associated with sunspots.
Accompanied by "wide-angle" observations from space, we have now the
opportunity to describe sunspots as a system. This review reports recent
findings related to flows in and around sunspots and highlights the role of
advanced instrumentation in the discovery process.Comment: 6 pages, 1 figure, to be published in "Physics of Sun and star
spots", Proc. IAU Symp. 273, D.P. Choudhary and K.G. Strassmeier (eds.
Spectral Background-Subtracted Activity Maps
High-resolution solar spectroscopy provides a wealth of information from
photospheric and chromospheric spectral lines. However, the volume of data
easily exceeds hundreds of millions of spectra on a single observation day.
Therefore, methods are needed to identify spectral signatures of interest in
multidimensional datasets. Background-subtracted activity maps (BaSAMs) have
previously been used to locate features of solar activity in time series of
images and filtergrams. This research note shows how this method can be
extended and adapted to spectral data.Comment: 3 pages, 1 figure, initial version submitted to Research Notes of the
AA