Lagrangian coherent structures in photospheric flows and their implications for coronal magnetic structure^⋆

¹ Department of Mathematical Sciences, Durham University, Durham, DH1 3LE, UK
e-mail: anthony.yeates@durham.ac.uk
² Division of Mathematics, University of Dundee, Dundee, DD1 4HN, UK
e-mail: gunnar@maths.dundee.ac.uk
³ Space Sciences Laboratory, University of California, Berkeley, CA 94720, USA
e-mail: welsch@ssl.berkeley.edu

Received: 14 October 2011
Accepted: 17 December 2011

Abstract

Aims. We show how the build-up of magnetic gradients in the Sun’s corona may be inferred directly from photospheric velocity data. This enables computation of magnetic connectivity measures such as the squashing factor without recourse to magnetic field extrapolation.

Methods. Assuming an ideal evolution in the corona, and an initially uniform magnetic field, the subsequent field line mapping is computed by integrating trajectories of the (time-dependent) horizontal photospheric velocity field. The method is applied to a 12 h high-resolution sequence of photospheric flows derived from Hinode/SOT magnetograms.

Results. We find the generation of a network of quasi-separatrix layers in the magnetic field, which correspond to Lagrangian coherent structures in the photospheric velocity. The visual pattern of these structures arises primarily from the diverging part of the photospheric flow, hiding the effect of the rotational flow component: this is demonstrated by a simple analytical model of photospheric convection. We separate the diverging and rotational components from the observed flow and show qualitative agreement with purely diverging and rotational models respectively. Increasing the flow speeds in the model suggests that our observational results are likely to give a lower bound for the rate at which magnetic gradients are built up by real photospheric flows. Finally, we construct a hypothetical magnetic field with the inferred topology, that can be used for future investigations of reconnection and energy release.