Spatially resolved measurements of the solar photospheric oxygen abundance

TL;DR

This study introduces a novel, spatially resolved method to measure the solar photospheric oxygen abundance, utilizing high-resolution observations and Bayesian modeling to improve robustness against systematic uncertainties.

Contribution

It presents a new approach combining spatially resolved observations, inversions, and hierarchical Bayesian modeling to determine the solar oxygen abundance more reliably.

Findings

Oxygen abundance is consistent across different spatial regions within uncertainties.

Granules show slightly higher oxygen abundance than intergranular lanes, indicating potential systematic effects.

The combined measurement yields an oxygen abundance of log(ε_O)=8.80 ± 0.03.

Abstract

Aims. We report the results of a novel determination of the solar oxygen abundance using spatially resolved observations and inversions. We seek to derive the photospheric solar oxygen abundance with a method that is robust against uncertainties in the model atmosphere. Methods. We use observations with spatial resolution obtained at the Vacuum Tower Telescope (VTT) to derive the oxygen abundance at 40 different spatial positions in granules and intergranular lanes. We first obtain a model for each location by inverting the Fe I lines with the NICOLE inversion code. These models are then integrated into a hierarchical Bayesian model that is used to infer the most probable value for the oxygen abundance that is compatible with all the observations. The abundance is derived from the [O I] forbidden line at 6300 {\AA} taking into consideration all possible nuisance parameters that can affect the abundance. Results. Our results show good agreement in the inferred oxygen abundance for all the pixels analyzed, demonstrating the robustness of the analysis against possible systematic errors in the model. We find a slightly higher oxygen abundance in granules than in intergranular lanes when treated separately (log(\epsilon_O) = 8.83 \pm 0.02 vs log(\epsilon_O) = 8.76 \pm 0.02), which is a difference of approximately 2-{\sigma}. This tension suggests that some systematic errors in the model or the radiative transfer still exist but are small. When taking all pixels together, we obtain an oxygen abundance of log(\epsilon_O)=8.80 \pm 0.03, which is compatible with both granules and lanes within 1-{\sigma}. The spread of results is due to both systematic and random errors.