Vortices in the solar photosphere can be linked to a wide range of events, such as small-scale solar eruptions, wave excitation, and heating of the upper part of the solar atmosphere. Despite their importance in solar physics, most of the current studies on photospheric vortices are based on methods that are not invariant under time-dependent translations and rotations of the reference frame and are Eulerian; i.e., they are based on single snapshots of a velocity field and, therefore, do not convey information on the true long-term motion of fluid particles on a time-varying field. Another issue with methods for vortex detection is that typically they provide false identifications in highly compressible flows. This Letter presents a novel criterion that effectively removes wrong detections based on the geometry of the streamlines of the displacement vector of fluid elements and can be readily applied to other astrophysical flows. The new criterion is applied to the Lagrangian-averaged vorticity deviation (LAVD), which is a recently developed frame invariant vortex detection method. The advantage of LAVD is that it delimits the vortices’ outer boundaries precisely by following up the trajectories of fluid elements in space and time. The proposed method is compared with two other techniques using horizontal velocity fields extracted from Hinode satellite data.

This article provides observational evidence for the direct relation between current sheets, multifractality and fully developed turbulence in the solar wind. In order to study the role of current sheets in extreme-value statistics in the solar wind, the use of magnetic volatility is proposed. The statistical fits of extreme events are based on the peaks-over-threshold (POT) modelling of Cluster 1 magnetic field data. The results reveal that current sheets are the main factor responsible for the behaviour of the tail of the magnetic volatility distributions. In the presence of current sheets, the distributions display a positive shape parameter, which means that the distribution is unbounded in the right tail. Thus the appearance of larger current sheets is to be expected and magnetic reconnection events are more likely to occur. The volatility analysis confirms that current sheets are responsible for the −5/3 Kolmogorov power spectra and the increase in multifractality and non-Gaussianity in solar wind statistics. In the absence of current sheets, the power spectra display a −3/2 Iroshnikov–Kraichnan law. The implications of these findings for the understanding of intermittent turbulence in the solar wind are discussed.

Magnetic coherent vortical structures are ubiquitous in space and astrophysical plasmas and their detection is key to understanding the nature of the intrinsic turbulence in those conducting fluids. A recently developed method to detect magnetic vortices is explored in problems of two-and three-dimensional magnetohydrodynamic simulations. The integrated averaged current deviation, the normed difference of the current density at a point and the mean current density in the domain, integrated along a magnetic field line, is proved to be objective, i.e., invariant under rotations and translations of the observer. The method is shown to detect accurately the boundary of magnetic vortices in two-dimensional simulations, as well as magnetic flux ropes in three dimensions.

In this work, a multifractal framework is proposed to investigate the effects of current sheets in solar wind turbulence. By using multifractal detrended fluctuation analysis coupled with surrogate methods and volatility, two solar wind magnetic field time series are investigated, one with current sheets and one without current sheets. Despite the lack of extreme-events intermittent bursts in the current sheet-free series, both series are shown to be strongly multifractal, although the current sheet-free series displays an almost linear behavior for the scaling exponent of structure functions. Long-range correlations are shown to be the main source of multifractality for the series without current sheets, while a combination of heavy-tail distribution and nonlinear correlations are responsible for multifractality in the series with current sheets. The multifractality in both time series is formally shown to be associated with an energy-cascade process using the p-model.