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Daily differential emission measure (DEM) distributions of the solar corona are derived from spectra obtained by the Extreme-ultraviolet Variability Experiment (EVE) over a 4-year period starting in 2010 near solar minimum and continuing through the maximum of solar cycle 24. The DEMs are calculated using six strong emission features dominated by Fe lines of charge states VIII, IX, XI, XII, XIV, and XVI that sample the non-flaring coronal temperature range 0.3--5 MK. A proxy for the non-XVIII emission in the wavelength band around the 93.9 \AA\ line is demonstrated. There is little variability in the cool component of the corona (T $$ 2.0 MK) varies by more than an order of magnitude. A discontinuity in the behavior of coronal diagnostics in 2011 February--March, around the time of the first X-class flare of cycle 24, suggests fundamentally different behavior in the corona under solar minimum and maximum conditions. This global state transition occurs over a period of several months. The DEMs are used to estimate the thermal energy of the visible solar corona (of order $10^{31}$ erg), its radiative energy loss rate (2.5--8 $\times 10^{27}$ erg s$^{-1}$), and the corresponding energy turnover timescale (about an hour). The uncertainties associated with the DEMs and these derived values are mostly due to the coronal Fe abundance and density and the CHIANTI atomic line database., Comment: 21 pages, 15 figures, 1 table. Accepted for publication in ApJ

Using four years of full-disk-integrated coronal differential emission measures calculated in Schonfeld et al. (2017), we investigate the relative contribution of bremsstrahlung and gyroresonance emission in observations of F$_{10.7}$, the 10.7 cm (2.8 GHz) solar microwave spectral flux density and commonly used activity proxy. We determine that the majority of coronal F$_{10.7}$ is produced by the bremsstrahlung mechanism, but the variability observed over individual solar rotations is often driven by gyroresonance sources rotating across the disk. Our analysis suggests that the chromosphere may contribute significantly to F$_{10.7}$ variability and that coronal bremsstrahlung emission accounts for 14.2 $\pm$ 2.1 sfu ($\sim20\%$) of the observed solar minimum level. The bremsstrahlung emission has a power-law relationship to the total F$_{10.7}$ at high activity levels, and this combined with the observed linearity during low activity yields a continuously differentiable piecewise fit for the bremsstrahlung component as a function of F$_{10.7}$. We find that the bremsstrahlung component fit, along with the Mg II index, correlates better with the observed 5-37 nm spectrum than the common 81 day averaged F$_{10.7}$ proxy. The bremsstrahlung component of F$_{10.7}$ is also well approximated by the moderate-strength photospheric magnetic field parameterization from Henney et al. (2012), suggesting that it could be forecast for use in both atmospheric research and operational models., Comment: 11 pages, 10 figures

We detect and analyze the oscillatory behavior of waves using a coronal seismology tool on sequences of coronal images. We study extreme-ultraviolet image sequences of active and quiet Sun regions and of coronal holes we identify 3- and 5-minute periodicities. In each studied region the 3- and 5-minute periodicities are similarly frequent. The number of pixels exhibiting a 3-minute periodicity is between 6 % – 8 % and those pixels exhibiting a 5-minute periodicity is between 5 % – 9 % of the total number of observed pixels. Our results show 3-minute oscillations along coronal loop structures but do not show 5-minute oscillations along these same loop structures. The number of pixels exhibiting 3- and 5-minute periodicities in one type of region (active Sun, quiet Sun, and coronal holes) is roughly the same for all observed regions, leading us to infer that the 3- and 5-minute oscillations are the result of a global mechanism.

An application of active contours without edges is presented as an efficient and effective means of extracting and characterizing coronal holes. Coronal holes are regions of low-density plasma on the Sun with open magnetic field lines. As the source of the fast solar wind, the detection and characterization of these regions is important for both testing theories of their formation and evolution and from a space weather perspective. Coronal holes are detected in full disk extreme ultraviolet (EUV) images of the corona obtained with the Solar Dynamics Observatory Atmospheric Imaging Assembly (SDO/AIA). The proposed method detects coronal boundaries without determining any fixed intensity value in the data. Instead, the active contour segmentation employs an energy-minimization in which coronal holes are assumed to have more homogeneous intensities than surrounding active regions and quiet Sun. The segmented coronal holes tend to correspond to unipolar magnetic regions, are consistent with concurrent solar wind observations, and qualitatively match the coronal holes segmented by other methods. The means to identify a coronal hole without specification of a final intensity threshold may allow this algorithm to be more robust across multiple datasets, regardless of data type, resolution, and quality.

We present a new automated algorithm to identify, track, and characterize small-scale brightening associated with solar eruptive phenomena observed in H{\alpha}. 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., Comment: 22 pages, 9 figures

We present an automated system for detecting, tracking, and cataloging emerging active regions throughout their evolution and decay using SOHO Michelson Doppler Interferometer (MDI) magnetograms. The SolarMonitor Active Region Tracking (SMART) algorithm relies on consecutive image differencing to remove both quiet-Sun and transient magnetic features, and region-growing techniques to group flux concentrations into classifiable features. We determine magnetic properties such as region size, total flux, flux imbalance, flux emergence rate, Schrijver’s R-value, R � (a modified version of R), and Falconer’s measurement of non-potentiality. A persistence algorithm is used to associate developed active regions with emerging flux regions in previous measurements, and to track regions beyond the limb through multiple solar rotations. We find that the total number and area of magnetic regions on disk vary with the sunspot cycle. While sunspot numbers are a proxy to the solar magnetic field, SMART offers a direct diagnostic of the surface magnetic field and its variation over timescale of hours to years. SMART will form the basis of the active region extraction and tracking algorithm for the Heliophysics Integrated Observatory (HELIO).

We report on the detection of EUV wave reflection from a coronal hole, as observed by the Solar Terrestrial Relations Observatory mission. The EUV wave was associated with a coronal mass ejection (CME) erupting near the disk center. It was possible to measure the kinematics of the reflected waves for the first time. The reflected waves were generally slower than the direct wave. One of the important implications of the wave reflection is that the EUV transients are truly a wave phenomenon. The EUV wave reflection has implications for CME propagation, especially during the declining phase of the solar cycle when there are many low-latitude coronal holes.

Two different multi-resolution analyses are used to decompose the structure of active region magnetic flux into concentrations of different size scales. Lines separating these opposite polarity regions of flux at each size scale are found. These lines are used as a mask on a map of the magnetic field gradient to sample the local gradient between opposite polarity regions of given scale sizes. It is shown that the maximum, average and standard deviation of the magnetic flux gradient for alpha, beta, beta-gamma and beta-gamma-delta active regions increase in the order listed, and that the order is maintained over all length-scales. This study demonstrates that, on average, the Mt. Wilson classification encodes the notion of activity over all length-scales in the active region, and not just those length-scales at which the strongest flux gradients are found. Further, it is also shown that the average gradients in the field, and the average length-scale at which they occur, also increase in the same order. Finally, there are significant differences in the gradient distribution, between flaring and non-flaring active regions, which are maintained over all length-scales. It is also shown that the average gradient content of active regions that have large flares (GOES class 'M' and above) is larger than that for active regions containing flares of all flare sizes; this difference is also maintained at all length-scales., Comment: Accepted for publication in Solar Physics

Long-exposure spectro-polarimetry in the near-infrared is a preferred method to measure the magnetic field and other physical properties of solar prominences. In the past, it has been very difficult to observe prominences in this way with sufficient spatial resolution to fully understand their dynamical properties. Solar prominences contain highly transient structures, visible only at small spatial scales; hence they must be observed at sub-arcsecond resolution, with a high temporal cadence. An adaptive optics (AO) system capable of directly locking-on to prominence structure away from the solar limb has the potential to allow for diffraction-limited spectro-polarimetry of solar prominences. In this paper, the performance of the off-limb AO system and its expected performance, at the desired science wavelength {\CaII} 8542A, are shown.

Aims. We study the photospheric magnetic field of 2000 active regions over solar cycle 23 to search for parameters that may be indicative of energy build-up and its subsequent release as a solar flare in the corona. Methods. We extract three sets of parameters: (1) snapshots in space and time: total flux, magnetic gradients, and neutral lines; (2) evolution in time: flux evolution; and (3) structures at multiple size scales: wavelet analysis. This work combines standard pattern recognition and classification techniques via a relevance vector machine to determine (i.e., classify) whether a region is expected to flare ( C1.0 according to GOES). We consider classification performance using all 38 extracted features and several feature subsets. Classification performance is quantified using both the true positive rate (the proportion of flares correctly predicted) and the true negative rate (the proportion of non-flares correctly classified). Additionally, we compute the true skill score which provides an equal weighting to true positive rate and true negative rate and the Heidke skill score to allow comparison to other flare forecasting work. Results. We obtain a true skill score of 0.5 for any predictive time window in the range 2 to 24 h, with a true positive rate of 0.8 and a true negative rate of 0.7. These values do not appear to depend on the predictive time window, although the Heidke skill score (

We present results from the first solar full-disk F$_{10.7}$ (the radio flux at $10.7$ cm, $2.8$ GHz) image taken with the S-band receivers on the recently upgraded Karl G. Jansky Very Large Array (VLA) in order to assess the relationship between the F$_{10.7}$ index and solar extreme ultra-violet (EUV) emission. To identify the sources of the observed $2.8$ GHz emission, we calculate differential emission measures (DEMs) from EUV images collected by the Atmospheric Imaging Assembly (AIA) and use them to predict the bremsstrahlung component of the radio emission. By comparing the bremsstrahlung prediction and radio observation we find that $8.1\pm 0.5\%$ of the variable component of the F$_{10.7}$ flux is associated with the gyroresonance emission mechanism. Additionally, we identify optical depth effects on the radio limb which may complicate the use of F$_{10.7}$ time series as an EUV proxy. Our analysis is consistent with a coronal iron abundance that is $4$ times the photospheric level., Comment: 16 pages, 5 figures

This paper investigates the possibility of automating the detection of propagating intensity perturbations in coronal loops using wavelet analysis. Two different sets of TRACE 171 A images are studied using the automated wavelet routine presented by McAteer et al. (2004). Both localised, short-lived periodicities and sustained, periodic, oscillations are picked up by the routine, with the results dependent to a large extent on the signal-to-noise ratio of the dataset. At present, the automation is only partial; the relevance of the detected periodicity and the identification of the coronal structure supporting it still have to be determined by the user, as does the judging of the accuracy of the results. Care has to be taken when interpreting the results of the wavelet analysis, and a good knowledge of all possible factors that might influence or distort the results is a necessity. Despite these limitations, wavelet analysis can play an important role in automatically identifying a variety of phenomena and in the analysis of the ever-growing (observational or simulated) datasets.

We analyse the intensity oscillations observed in the gradual phase of a white-light flare on the RS CV n binary II Peg. Fast Fourier Transform power spectra and Wavelet analysis reveal a period of 220 s. The reliability of the oscillation is tested using several criteria. Oscillating coronal loop models are used to derive physical parameters such as temperature, electron density and magnetic field strength associated with the coronal loop. The derived parameters are consistent with the near-simultaneous X-ray observations of the flare. There is no evidence for oscillations in the quiescent state of the binary.

The Solar Eclipse Corona Imaging System (SECIS) observed a strong 6-s oscillation in an active region coronal loop, during the 1999 August 11 total solar eclipse. In the present paper we show that this oscillation is associated with a fast-mode magneto-acoustic wave that travels through the loop apex with a velocity of 2100 km s−1. We use near-simultaneous SOHO observations to calculate the parameters of the loop and its surroundings such as density, temperature and their spatial variation. We find that the temporal evolution of the intensity is in agreement with the model of an impulsively generated, fast-mode wave.

The study of solar eruptive events and associated phenomena is of great importance in the context of solar and heliophysics. Coronal mass ejections (CMEs) and coronal waves are energetic manifestations of the restructuring of the solar magnetic field and mass motion of the plasma. Characterising this motion is vital for deriving the dynamics of these events and thus understanding the physics driving their initiation and propagation. The development and use of appropriate methods for measuring event kinematics is therefore imperative. Traditional approaches to the study of CME and coronal wave kinematics do not return wholly accurate nor robust estimates of the true event kinematics and associated uncertainties. We highlight the drawbacks of these approaches, and demonstrate improved methods for accurate and reliable determination of the kinematics. The Savitzky-Golay filter is demonstrated as a more appropriate fitting technique for CME and coronal wave studies, and a residual resampling bootstrap technique is demonstrated as a statistically rigorous method for the determination of kinematic error estimates and goodness-of-fit tests. It is shown that the scatter on distance-time measurements of small sample size can significantly limit the ability to derive accurate and reliable kinematics. This may be overcome by (i) increasing measurement precision and sampling cadence, and (ii) applying robust methods for deriving the kinematics and reliably determining their associated uncertainties. If a priori knowledge exists and a pre-determined model form for the kinematics is available (or indeed any justified fitting-form to be tested against the data), then its precision can be examined using a bootstrapping technique to determine the confidence interval associated with the model/fitting parameters., 12 pages, 12 figures

The collisional thick target model, wherein a large number of electrons are accelerated down a flaring loop, can be used to explain many observed properties of solar flares. In this study, we focus on the sensitivity of GOES flare classification to the properties of the thick target model. Using a hydrodynamic model with RHESSI-derived electron beam parameters, we explore the effects of the beam energy flux (or total non-thermal energy), the cut-off energy, and the spectral index of the electron distribution on the soft X-rays (SXRs) observed by GOES. We conclude that (1) the GOES class is proportional to the non-thermal energy $E^{\alpha}$ for $\alpha \approx 1.7$ in the low energy passband (1-8 \AA) and $\approx 1.6$ in the high energy passband (0.5-4 \AA); (2) the GOES class is only weakly dependent on the spectral index in both passbands; (3) increases in the cut-off will increase the flux in the 0.5-4 \AA\ passband, but decrease the flux in the 1-8 \AA\ passband, while decreases in the cut-off will cause a decrease in the 0.5-4 \AA\ passband and a slight increase in the 1-8 \AA\ passband., Comment: Accepted to ApJ

The Rosse Solar-Terrestrial Observatory (RSTO; www.rosseobservatory.ie) was established at Birr Castle, Co. Offaly, Ireland (53 05'38.9", 7 55'12.7") in 2010 to study solar radio bursts and the response of the Earth's ionosphere and geomagnetic field. To date, three Compound Astronomical Low-cost Low-frequency Instrument for Spectroscopy and Transportable Observatory (CALLISTO) spectrometers have been installed, with the capability of observing in the frequency range 10-870 MHz. The receivers are fed simultaneously by biconical and log-periodic antennas. Nominally, frequency spectra in the range 10-400 MHz are obtained with 4 sweeps per second over 600 channels. Here, we describe the RSTO solar radio spectrometer set-up, and present dynamic spectra of a sample of Type II, III and IV radio bursts. In particular, we describe fine-scale structure observed in Type II bursts, including band splitting and rapidly varying herringbone features.

International audience; In Fall 2008 NASA selected a large international consortium to produce a comprehensive automated feature-recognition system for the Solar Dynamics Observatory (SDO). The SDO data that we consider are all of the Atmospheric Imaging Assembly (AIA) images plus surface magnetic-field images from the Helioseismic and Magnetic Imager (HMI). We produce robust, very efficient, professionally coded software modules that can keep up with the SDO data stream and detect, trace, and analyze numerous phenomena, including flares, sigmoids, filaments, coronal dimmings, polarity inversion lines, sunspots, X-ray bright points, active regions, coronal holes, EIT waves, coronal mass ejections (CMEs), coronal oscillations, and jets. We also track the emergence and evolution of magnetic elements down to the smallest detectable features and will provide at least four full-disk, nonlinear, force-free magnetic field extrapolations per day. The detection of CMEs and filaments is accomplished with Solar and Heliospheric Observatory (SOHO)/Large Angle and Spectrometric Coronagraph (LASCO) and ground-based Hα data, respectively. A completely new software element is a trainable feature-detection module based on a generalized image-classification algorithm. Such a trainable module can be used to find features that have not yet been discovered (as, for example, sigmoids were in the pre-Yohkoh era). Our codes will produce entries in the Heliophysics Events Knowledgebase (HEK) as well as produce complete catalogs for results that are too numerous for inclusion in the HEK, such as the X-ray bright-point metadata. This will permit users to locate data on individual events as well as carry out statistical studies on large numbers of events, using the interface provided by the Virtual Solar Observatory. The operations concept for our computer vision system is that the data will be analyzed in near real time as soon as they arrive at the SDO Joint Science Operations Center and have undergone basic processing. This will allow the system to produce timely space-weather alerts and to guide the selection and production of quicklook images and movies, in addition to its prime mission of enabling solar science. We briefly describe the complex and unique data-processing pipeline, consisting of the hardware and control software required to handle the SDO data stream and accommodate the computer-vision modules, which has been set up at the Lockheed-Martin Space Astrophysics Laboratory (LMSAL), with an identical copy at the Smithsonian Astrophysical Observatory (SAO).

Coronal mass ejections (CMEs) are large-scale eruptions of plasma and magnetic feld that can produce adverse space weather at Earth and other locations in the Heliosphere. Due to the intrinsic multiscale nature of features in coronagraph images, wavelet and multiscale image processing techniques are well suited to enhancing the visibility of CMEs and supressing noise. However, wavelets are better suited to identifying point-like features, such as noise or background stars, than to enhancing the visibility of the curved form of a typical CME front. Higher order multiscale techniques, such as ridgelets and curvelets, were therefore explored to characterise the morphology (width, curvature) and kinematics (position, velocity, acceleration) of CMEs. Curvelets in particular were found to be well suited to characterising CME properties in a self-consistent manner. Curvelets are thus likely to be of benefit to autonomous monitoring of CME properties for space weather applications., Comment: Accepted for publication in Advances in Space Research (3 April 2010)

A new method for automated coronal loop tracking, in both spatial and temporal domains, is presented. Applying this technique to TRACE data, obtained using the 171 Angstrom filter on 1998 July 14, we detect a coronal loop undergoing a 270s kink-mode oscillation, as previously found by Aschwanden et al. (1999). However, we also detect flare-induced, and previously unnoticed, spatial periodicities on a scale of 3500km, which occur along the coronal-loop edge. Furthermore, we establish a reduction in oscillatory power for these spatial periodicities of 45% over a 222s interval. We relate the reduction in detected oscillatory power to the physical damping of these loop-top oscillations., 7 pages, 11 figures

Magnetohydrodynamic turbulence is thought to be responsible for producing complex, multiscale magnetic field distributions in solar active regions. Here we explore the multiscale properties of a number of evolving active regions using magnetograms from the Michelson Doppler Imager (MDI) on the Solar and Heliospheric Observatory (SOHO). The multifractal spectrum was obtained by using a modified box-counting method to study the relationship between magnetic-field multifractality and region evolution and activity. The initial emergence of each active region was found to be accompanied by characteristic changes in the multifractal spectrum. Specifically, the range of multifractal structures (D div) was found to increase during emergence, as was their significance or support (C div). Following this, a decrease in the range in multifractal structures occurred as the regions evolved to become large-scale, coherent structures. From the small sample considered, evidence was found for a direct relationship between the multifractal properties of the flaring regions and their flaring rate. © 2007 Springer Science+Business Media B.V.

Flows in the photosphere of solar active regions are turbulent in nature. Because magnetic fields are frozen into the plasma on the solar surface, magnetograms can be used to investigate the processes responsible for structuring active regions. Here, a continuous wavelet technique is developed, analyzed, and used to investigate the multiscale structure of an evolving active region using magnetograms obtained by the Michelson Doppler Imager (MDI) onboard the Solar and Heliospheric Observatory (SOHO). The multiscale structure was measured using a 2D continuous wavelet technique to extract the energy spectrum of the region over the time scale of 13 days. Preliminary evidence of an inverse cascade in active region NOAA 10488 is presented as well as a potential relationship between energy scaling and flare productivity. © 2007 Springer Science+Business Media B.V.

We estimate the morphology of near-side active regions using near-side helioseismology. Active regions from two data sets, Air Force Data Assimilative Photospheric flux Transport synchronic maps and Global Oscillation Network Group near-side helioseismic maps, were matched and their morphologies compared. Our algorithm recognizes 382 helioseismic active regions between 2002 April 25 and 2005 December 31 and matches them to their corresponding magnetic active regions with 100% success. A magnetic active region occupies 30% of the area of its helioseismic signature. Recovered helioseismic tilt angles are in good agreement with magnetic tilt angles. Approximately 20% of helioseismic active regions can be decomposed into leading and trailing polarity. Leading polarity components show no discernible scaling relationship, but trailing magnetic polarity components occupy approximately 25% of the area of the trailing helioseismic component. A nearside phase-magnetic calibration is in close agreement with a previous far-side helioseismic calibration and provides confidence that these morphological relationships can be used with far-side helioseismic data. Including far-side active region morphology in synchronic maps will have implications for coronal magnetic topology predictions and solar wind forecasts.

SECIS observations of the June 2001 total solar eclipse were taken using an Fe XIV 5303 A filter. Existing software was modified and new code was developed for the reduction and analysis of these data. The observations, data reduction, study of the atmospheric and instrumental effects, together with some preliminary results are discussed. Emphasis is given to the techniques used for the automated alignment of the 8000 images, the software developed for the automated detection of intensity oscillations using wavelet analysis and the application of the Monte Carlo randomisation test as a means of checking the reliability of those detections. In line with findings from the 1999 SECIS total eclipse observations, intensity oscillations with periods in the range of 7–8 s, lying outside coronal loops were also detected.

The dynamics of regions of the solar corona are investigated using Atmospheric Imaging Assembly 171 A and 193 A data. The coronal emission from the quiet Sun, coronal loop footprints, coronal moss, and from above a sunspot is studied. It is shown that the mean Fourier power spectra in these regions can be described by a power law at lower frequencies that tails to a flat spectrum at higher frequencies, plus a Gaussian-shaped contribution that varies depending on the region studied. This Fourier spectral shape is in contrast to the commonly held assumption that coronal time series are well described by the sum of a long timescale background trend plus Gaussian-distributed noise, with some specific locations also showing an oscillatory signal. The implications of the observed spectral shape on the fields of coronal seismology and the automated detection of oscillations in the corona are discussed. The power-law contribution to the shape of the Fourier power spectrum is interpreted as being due to the summation of a distribution of exponentially decaying emission events along the line of sight. This is consistent with the idea that the solar atmosphere is heated everywhere by small energy deposition events.

The processes governing energy storage and release in the Sun are both related to the solar magnetic field. We demonstrate the existence of a magnetic connection between the energy released by a flare and increased oscillatory power in the lower solar atmosphere. The oscillatory power in active regions tends to increase in response to explosive events at other locations, but not in the active region itself. We carry out timing studies and show that this effect is probably caused by a large-scale magnetic connection between the regions, instead of a globally-propagating wave. We show that oscillations tend to exist in longer-lived wave trains with short periods (P < 200 s) at the time of a flare. These wave trains may be mechanisms by which flare energy can be redistributed throughout the solar atmosphere.

PUBLISHED, One of the mechanisms proposed for heating the corona above solar active regions is the damping of magnetohydrodynamic (MHD) waves. Continuing on previous work, we provide observational evidence for the existence of high-frequency MHD waves in coronal loops observed during the August 1999 total solar eclipse. A wavelet analysis is used to identify twenty 4?4 arcsec2 areas showing intensity oscillations. All detections lie in the frequency range 0.15?0.25 Hz (7?4 s), last for at least 3 periods at a confidence level of more than 99% and arise just outside known coronal loops. This leads us to suggest that they occur in low emission-measure or different temperature loops associated with the active region., The authors would like to thank K. J. H. Phillips for his collaboration on the SECIS project. ACK acknowledges funding by the Leverhume Trust via grant F00203/A. DRW acknowledges a CAST studentship funded by the Department of Employment & Learning and the Rutherford Appleton Laboratory. JMCA acknowledges CAST studentship funded by DEL and QUB. ACK & DRW would like to thank Valery Nakariakov and Temury Zaqarashvili for useful discussions