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Sebastian Halsig
Type of contribution: oral

Augmenting the stochastic model in VLBI data analysis by correlations from atmospheric turbulence models

Sebastian Halsig, IGG, University of Bonn Thomas Artz, IGG, University of Bonn Andreas Iddink, IGG, University of Bonn Axel Nothnagel, IGG, University of Bonn

Dynamic processes in the neutral atmosphere contribute considerably to the VLBI error budget. In particular, micro-scale fluctuations in refractivity lead to elevation-dependent uncertainties and induce physical correlations between the observations. However, up to now such physical correlations are disregarded in the stochastic model of geodetic VLBI data analysis. In fact, in operational data analysis of the IVS only the uncertainties from the VLBI correlation process are used. Thus, the formal errors of e.g., station coordinates or Earth orientation parameters, are too optimistic. In this study, the standard stochastic model is augmented by correlations induced by atmospheric turbulence. Thus, dependencies of the observations in time and space are introduced. To model atmospheric turbulences, we follow the principles of the widely accepted Kolmogorov turbulence theory. For this purpose, several atmospheric turbulence models were adapted and modified for geodetic VLBI data analysis, which differ primarily in the parametrization and combination of spatial and temporal correlations as well as the parametrization of the wind direction and its magnitude. The different approaches are applied to the continuous VLBI campaign 2014 (CONT14) in order to validate the new stochastic model and to investigate the performance of the different approaches.