The Polarization Signature of Photospheric Magnetic Fields in 3D MHD Simulations and Observations at Disk Center

Abstract

Abstract Before using three-dimensional (3D) magnetohydrodynamical (MHD) simulations of the solar photosphere in the determination of elemental abundances, one has to ensure that the correct amount of magnetic flux is present in the simulations. The presence of magnetic flux modifies the thermal structure of the solar photosphere, which affects abundance determinations and the solar spectral irradiance. The amount of magnetic flux in the solar photosphere also constrains any possible heating in the outer solar atmosphere through magnetic reconnection. We compare the polarization signals in disk-center observations of the solar photosphere in quiet-Sun regions with those in Stokes spectra computed on the basis of 3D MHD simulations having average magnetic flux densities of about 20, 56, 112, and 224 G. This approach allows us to find the simulation run that best matches the observations. The observations were taken with the Hinode SpectroPolarimeter (SP), the Tenerife Infrared Polarimeter (TIP), the Polarimetric Littrow Spectrograph (POLIS), and the GREGOR Fabry–Pèrot Interferometer (GFPI), respectively. We determine characteristic quantities of full Stokes profiles in a few photospheric spectral lines in the visible (630 nm) and near-infrared (1083 and 1565 nm). We find that the appearance of abnormal granulation in intensity maps of degraded simulations can be traced back to an initially regular granulation pattern with numerous bright points in the intergranular lanes before the spatial degradation. The linear polarization signals in the simulations are almost exclusively related to canopies of strong magnetic flux concentrations and not to transient events of magnetic flux emergence. We find that the average vertical magnetic flux density in the simulation should be less than 50 G to reproduce the observed polarization signals in the quiet-Sun internetwork. A value of about 35 G gives the best match across the SP, TIP, POLIS, and GFPI observations.