Estimation of the magnetic flux emergence rate in the quiet Sun from Sunrise data

TL;DR

This study measures the magnetic flux emergence rate in the quiet Sun using Sunrise data, revealing that small-scale features significantly contribute to magnetic flux and that measurement techniques greatly influence FER estimates.

Contribution

First to account for small flux features in FER calculations using Sunrise data, providing more comprehensive flux emergence rate estimates in the quiet Sun.

Findings

FER of 1100 Mx cm^-2 day^-1 from Sunrise data

Small flux features dominate magnetic flux contribution

Measurement techniques cause large discrepancies in FER estimates

Abstract

Small-scale internetwork (IN) features are thought to be the major source of fresh magnetic flux in the quiet Sun. During its first science flight in 2009, the balloon-borne observatory Sunrise captured images of the magnetic fields in the quiet Sun at a high spatial resolution. Using these data we measure the rate at which the IN features bring magnetic flux to the solar surface. In a previous paper it was found that the lowest magnetic flux in small-scale features detected using the Sunrise observations is 9 x 10^14 Mx. This is nearly an order of magnitude smaller than the smallest fluxes of features detected in observations from the Hinode satellite. In this paper, we compute the flux emergence rate (FER) by accounting for such small fluxes, which was not possible before Sunrise. By tracking the features with fluxes in the range 10^15-10^18 Mx, we measure an FER of 1100 Mx cm^-2 day^-1. The smaller features with fluxes less than or equal to 10^16 Mx are found to be the dominant contributors to the solar magnetic flux. The FER found here is an order of magnitude higher than the rate from Hinode, obtained with a similar feature tracking technique. A wider comparison with the literature shows, however, that the exact technique of determining the rate of the appearance of new flux can lead to results that differ by up to two orders of magnitude, even when applied to similar data. The causes of this discrepancy are discussed and first qualitative explanations proposed.