A new method for automated detection of polar coronal holes is presented. This method, called perimeter tracing, uses a series of 171, 195, and 304 Å full disk images from the Extreme ultraviolet Imaging Telescope (EIT) on SOHO over solar cycle 23 to measure the perimeter of polar coronal holes as they appear on the limbs. Perimeter tracing minimizes line-of-sight obscurations caused by the emitting plasma of the various wavelengths by taking measurements at the solar limb. Perimeter tracing also allows for the polar rotation period to emerge organically from the data as 33 days. We have called this the Harvey rotation rate and count Harvey rotations starting 4 January 1900. From the measured perimeter, we are then able to fit a curve to the data and derive an area within the line of best fit. We observe the area of the northern polar hole area in 1996, at the beginning of solar cycle 23, to be about 4.2% of the total solar surface area and about 3.6% in 2007. The area of the southern polar hole is observed to be about 4.0% in 1996 and about 3.4% in 2007. Thus, both the north and south polar hole areas are no more than 15% smaller now than they were at the beginning of cycle 23. This compares to the polar magnetic field measured to be about 40% less now than it was a cycle ago.

Abstract. This paper presents SunPy (version 0.5), a community-developed Python package for solar physics. Python, a free, cross-platform, general-purpose, highlevel programming language, has seen widespread adoption among the scientific community, resulting in the availability of a large number of software packages,

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The goal of the SunPy project is to facilitate and promote the use and development of community-led, free, and open source data analysis software for solar physics based on the scientific Python environment. The project achieves this goal by developing and maintaining the sunpy core package and supporting an ecosystem of affiliated packages. This paper describes the first official stable release (version 1.0) of the core package, as well as the project organization and infrastructure. This paper concludes with a discussion of the future of the SunPy project.

We present spectral energy distributions (SEDs) of 41 active galactic nuclei, derived from multiwavelength photometry and archival spectroscopy. All of the SEDs span at least 0.09 to 30 µm, but in some instances wavelength coverage extends into the X-ray, far-infrared and radio. For some AGNs we have fitted the measured far-infrared photometry with greybody models, while radio flux density measurements have been approximated by power-laws or polynomials. We have been able to fill some of the gaps in the spectral coverage using interpolation or extrapolation of simple models. In addition to the 41 individual AGN SEDs, we have produced 72 Seyfert SEDs by mixing SEDs of the central regions of Seyferts with galaxy SEDs. Relative to the literature, our templates have broader wavelength coverage and/or higher spectral resolution. We have tested the utility of our SEDs by using them to generate photometric redshifts for 0 < z ≤ 6.12 AGNs in the Boötes field (selected with X-ray, IR and optical criteria) and, relative to SEDs from the literature, they produce comparable or better photometric redshifts with reduced flux density residuals.

We report on the physical properties of solar sequential chromospheric brightenings (SCBs) observed in conjunction with moderate-sized chromospheric flares with associated CMEs. To characterize these ephemeral events, we developed automated procedures to identify and track subsections (kernels) of solar flares and associated SCBs using high resolution Hα images. Following the algorithmic identification and a statistical analysis, we compare and find the following: SCBs are distinctly different from flare kernels in their temporal characteristics of intensity, Doppler structure, duration, and location properties. We demonstrate that flare ribbons are themselves made up of subsections exhibiting differing characteristics. Flare kernels are measured to have a mean propagation speed of 0.2 km s −1 and a maximum speed of 2.3 km s −1 over a mean distance of 5 × 10 3 km. Within the studied population of SCBs, different classes of characteristics are observed with coincident negative, positive, or both negative and positive Doppler shifts of a few km s −1 . The appearance of SCBs precede peak flare intensity by ≈ 12 minutes and decay ≈ 1 hour later. They are also found to propagate laterally away from flare center in clusters at 41 km s −1 or 89 km s −1 . Given SCBs distinctive nature compared to flares, we suggest a different physical mechanism relating to their origin than the associated flare. We present a heuristic model of the origin of SCBs.

Small-scale magnetic reconnection processes, in the form of nanoflares, have become increasingly hypothesized as important mechanisms for the heating of the solar atmosphere, for driving propagating disturbances along magnetic field lines in the Sun's corona, and for instigating rapid jet-like bursts in the chromosphere. Unfortunately, the relatively weak signatures associated with nanoflares places them below the sensitivities of current observational instrumentation. Here, we employ Monte Carlo techniques to synthesize realistic nanoflare intensity time series from a dense grid of power-law indices and decay timescales. Employing statistical techniques, which examine the modeled intensity fluctuations with more than 10 7 discrete measurements, we show how it is possible to extract and quantify nanoflare characteristics throughout the solar atmosphere, even in the presence of significant photon noise. A comparison between the statistical parameters (derived through examination of the associated intensity fluctuation histograms) extracted from the Monte Carlo simulations and SDO/AIA 171Å and 94Å observations of active region NOAA 11366 reveals evidence for a flaring power-law index within the range of 1.82 ≤ α ≤ 1.90, combined with e-folding timescales of 385 ± 26 s and 262 ± 17 s for the SDO/AIA 171Å and 94Å channels, respectively. These results suggest that nanoflare activity is not the dominant heating source for the active region under investigation. This opens the door for future dedicated observational campaigns to not only unequivocally search for the presence of small-scale reconnection in solar and stellar environments, but also quantify key characteristics related to such nanoflare activity.

We present a new automated algorithm to identify, track, and characterize small-scale brightening associated with solar eruptive phenomena observed in Hα. The temporal spatially-localized changes in chromospheric intensities can be separated into two categories: flare ribbons and sequential chromospheric brightenings (SCBs). Within each category of brightening we determine the smallest resolvable locus of pixels, a kernel, and track the temporal evolution of the position and intensity of each kernel. This tracking is accomplished by isolating the eruptive features, identifying kernels, and linking detections between frames into trajectories of kernels. We fully characterize the evolving intensity and morphology of the flare ribbons by observing the tracked flare kernels in aggregate. With the location of SCB and flare kernels identified, they can easily be overlaid on top of complementary data sets to extract Doppler velocities and magnetic field intensities underlying the kernels. This algorithm is adaptable to any dataset to identify and track solar features.