Modelling tropospheric delays using the global surface meteorological parameter model GPT2

Abstract

In case of autonomous positioning the tropospheric delays are taken into consideration by ‘blind’ models. These models do not require any observed meteorological input parameters. Currently the Radio Transmission Commission for Aeronautics defines the Minimum Operational Performance Standards of GNSS, which includes a state-of-the-art blind tropospheric model, too. Recently a new surface meteorological parameter model, the GPT2 has been released. Our study investigates the performance of this new model in the estimation of tropospheric delays using a global radiosonde data set for the period of 2010-2013. Our results showed that GPT2 helped to remove more than 90% of the bias in tropospheric delay estimates found in the RTCA model. Moreover the uncertainties of the estimates are decreased by approximately 10%. The validation showed that the performance of the tropospheric modelling using GPT2 is more stable geographically compared to the performance of the RTCA model.