The thermal state of Volgo–Uralia from Bayesian inversion of surface heat flow and temperature [data set]

• Main Authors: Ognev, Igor, Ebbing, Jörg, Lösing, Mareen, Nurgaliev, Danis
• Format: Other/Unknown Material
• Language: English
• Published: Zenodo 2022
• Subjects: Heat flow; Heat generation and transport; Numerical modelling; Inverse theory; Statistical methods; Cratons; Radiogenic heat production; Bayesian inversion; Antarc*; Antarctica
• Online Access: https://doi.org/10.5281/zenodo.7009981

This collection contains the dataset and the code which were used to find the thermal parameters’ lateral variations of the Volgo–Uralian subcraton through the Bayesian Markov Chain Monte Carlo (MCMC) statistical approach. The code originally was given in the analogous study of Antarctica's geothermal structure by Lösing et al. (2020) and it can be found in https://github.com/MareenLoesing/GHF-Antarctica-Bayesian. The main changes to the code of Lösing et al. (2020) are listed in the section 2 of the readme file. For an official use of the Bayesian inversion code please also cite: Lösing, M., Ebbing, J. & Szwillus, W. (2020) Geothermal Heat Flux in Antarctica: Assessing Models and Observations by Bayesian Inversion. Front. Earth Sci., 8, 105. doi:10.3389/feart.2020.00105 The lateral variations of the thermal parameters for the single-layer and multi-layer crust are saved in “GHF_Volgo-Uralia_Single-layer.csv” and “GHF_Volgo-Uralia_Multi-layer.csv” respectively.