Successive Injection of Opposite Magnetic Helicity in Solar Active Region NOAA 11928

TL;DR

This study investigates the evolution of magnetic helicity in a solar active region, revealing a sign reversal during emergence and linking it to coronal activity and complex flux rope structures.

Contribution

It introduces a method to analyze helicity flux with corrected connectivity, showing how helicity sign reversal correlates with coronal dynamics in AR 11928.

Findings

Helicity flux changes sign during active region emergence.

Coronal helicity is positive initially, then approaches a potential state.

Helicity cancelation correlates with increased coronal activity.

Abstract

Understanding the nature and evolution of the photospheric helicity flux transfer is a key to reveal the role of magnetic helicity in coronal dynamics of solar active regions. Using SDO/HMI photospheric vector magnetograms and the derived flow velocity field, we computed boundary driven helicity flux with a 12 minute cadence during the emergence of AR 11928. Accounting the foot point connectivity defined by non-linear force-free magnetic extrapolations, we derived and analyzed the corrected distribution of helicity flux maps. The photospheric helicity flux injection is found to changes sign during the steady emergence of the AR. This reversal is confirmed with the evolution of the photospheric electric currents and with the coronal connectivity as observed in EUV wavelengths with SDO/AIA. During about the three first days of emergence, the AR coronal helicity is positive while later on the field configuration is close to a potential field. As theoretically expected, the magnetic helicity cancelation is associated to enhanced coronal activity. The study suggests a boundary driven transformation of the chirality in the global AR magnetic structure. This may be the result of the emergence of a flux rope with positive twist around its apex while it has negative twist in its legs. The origin of such mixed helicity flux rope in the convective zone is challenging for models.