Volume 643, November 2020
|Number of page(s)||12|
|Section||The Sun and the Heliosphere|
|Published online||17 November 2020|
Spatially resolved measurements of the solar photospheric oxygen abundance
Instituto de Astrofísica de Canarias (IAC), Avda Vía Láctea s/n, 38200 La Laguna, Tenerife, Spain
2 Departamento de Astrofísica, Universidad de La Laguna, 38205 La Laguna, Tenerife, Spain
Accepted: 27 August 2020
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 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 Å 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(ϵO) = 8.83 ± 0.02 vs. log(ϵO) = 8.76 ± 0.02), which is a difference of approximately 2-σ. 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(ϵO) = 8.80 ± 0.03, which is compatible with both granules and lanes within 1-σ. The spread of results is due to both systematic and random errors.
Key words: Sun: abundances / Sun: atmosphere / Sun: photosphere / methods: statistical
© ESO 2020
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