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