We describe the construction of a highly reliable sample of ∼7,000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 deg 2 of northern sky. The majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than for most other wide-angle surveys; the photometric errors range from ∼0.03 mag at r = 15 to ∼0.20 mag at r = 18. Light curves include on average 250 -2data points, collected over about a decade. Using SDSS-based photometric recalibration of the LINEAR data for about 25 million objects, we selected ∼200,000 most probable candidate variables with r < 17 and visually confirmed and classified ∼7,000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a catalog of variable stars from the SDSS Stripe 82 region, and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3,900 RR Lyrae stars and 2,700 eclipsing binary stars of all subtypes, and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, 2MASS and WISE photometry, and with LINEAR light curve features. We find that combination of light curve features and colors enables classification schemes much more powerful than when colors or light curves are each used separately. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars (β Lyrae and W UMa): as the color-based spectral type varies from K4 to F5, the median period increases from 5.9 hours to 8.8 hours. These large samples of robustly classified variable stars will enable detailed statistical studies of the Galactic structure and physics of binary and other stars, and we make them publicly available.

Abstract. We present a statistical analysis of 545 flare-associated CMEs and 104 non-flare CMEs observed in the heliocentric distance range 2-30 solar radii. We found that both data sets show quite similar characteristics, contradicting the concept of two distinct (flare/non-flare) types of CMEs. In both samples there is a significant fraction of CMEs showing a considerable acceleration or deceleration and both samples include a comparable ratio of fast and slow CMEs. We present kinematical curves of several fast non-flare CMEs moving at a constant speed or decelerating, i.e., behaving as expected for flare-associated CMEs. Analogously, we identified several slow flare-CMEs showing the acceleration peak beyond a height of 3 solar radii. On the other hand, it is true that CMEs associated with major flares are on average faster and broader than non-flare CMEs and small-flare CMEs. There is a well-defined correlation between the CME speed and the importance of the associated flare. In this respect, the non-flare CMEs show characteristics similar to CMEs associated with flares of soft X-ray class B and C, which is indicative of a "continuum" of events rather than supporting the existence of two distinct CME classes. Furthermore, we inferred that CMEs whose source region cannot be identified with either flares or eruptive prominences are on average slowest. The results indicate that the magnetic reconnection taking place in the current sheet beneath the CME significantly influences the CME dynamics.

Abstract. Kinematics of more than 5000 coronal mass ejections (CMEs) measured in the distance range 2-30 solar radii is investigated. A distinct anticorrelation between the acceleration, a, and the velocity, v, is found. In the linear form, it can be represented as a = −k 1 (v − v 0 ), where v 0 = 400 km s −1 , i.e., most of CMEs faster than 400 km s −1 decelerate, whereas slower ones generally accelerate. After grouping CMEs into the width and mean-distance bins, it was found that the slope k 1 depends on these two parameters: k 1 is smaller for CMEs of larger width and mean-distance. Furthermore, the obtained CME subsets show distinct quadratic-form correlations, of the form a = −k 2 (v − v 0 )|v − v 0 |. The value of k 2 decreases with increasing distance and width, whereas v 0 increases with the distance and is systematically larger than the slow solar wind speed by 100-200 km s −1 . The acceleration-velocity relationship is interpreted as a consequence of the aerodynamic drag. The excess of v 0 over the solar wind speed is explained assuming that in a certain fraction of events the propelling force is still acting in the considered distance range. In most events the inferred propelling force acceleration at 10 solar radii ranges between a L = 0 and 10 m s −2 , being on average smaller at larger distances. However, there are also events that show a L > 50 m s −2 , as well as events indicating a L < 0. Implications for the interplanetary motion of CMEs are discussed, emphasizing the prediction of the 1 a.u. arrival time.

The extended Greenwich data set consisting of positions of sunspot groups is used for the investigation of cycle-related variations of the solar rotation in the years 1874 -1981. Applying the residual method, which yields a single number for each year describing the average deviation from the mean value of the solar rotation, the dependence of the rotation velocity residual on the phase of the solar cycle is investigated. A secular deceleration of the solar rotation was found: the slope being statistically significant at the 3σ level. Periods of 33, 22, 11, 5.2, and 3.5 years can be identified in the power spectra. The rotation velocity residuals were averaged for all years with the same solar cycle phase relative to the nearest preceding sunspot minimum. The variation pattern reveals a higher than average rotation velocity in the minimum of activity and, to a lesser extent, also around the maximum of activity. The analysis was repeated with several changes in the reduction method, such as elimination of the secular trend, application of statistical weights, different cutoffs of the central meridian distance, division of the latitude into subregions and treating data from the years of activity minima separately. The results obtained are compared with those from the literature, and an interpretation of the observed phenomena is proposed.

Context. Basic observational parameters of a coronal mass ejection (CME) are its speed and angular width. Measurements of the CME speed and angular width are severely influenced by projection effects. Aims. The goal of this paper is to investigate a statistical relationship between the plane-of-sky speeds of CMEs and the direction of their propagation, hopefully providing an estimate of the true speeds of CMEs. Methods. We analyze the correlation between the plane-of-sky velocity and the position of the CME source region, employing several non-halo CME samples. The samples are formed applying various restrictions to avoid crosstalk of relevant parameters. For example, we select only CMEs observed to radial distances larger than 10 solar radii; we omit CMEs showing a considerable acceleration in the considered distance range and treat CMEs of different angular widths separately. Finally, we combine these restriction criteria, up to the limits beyond which the statistical significance of the results becomes ambiguous. Results. A distinct anti-correlation is found between the angular width of CMEs and their source-region position, clearly showing an increasing trend towards the disc center. Similarly, all of the considered subsamples show a correlation between the CME projected speed and the distance of the source region from the disc center. On average, velocities of non-halo limb-CMEs are 1.5−2 times higher than in the case of non-halo CMEs launched from regions located close to the disc center. Conclusions. Unfortunately, the established empirical relationships provide only a rough estimate of the velocity correction as a function of the source-region location. To a certain degree, the results can be explained in terms of CME cone models, but only after taking crosstalk of various parameters and observational artifacts into account.