Szabolcs Rózsa

Modelling Tropospheric Zenith Delays Using Regression Models Based on Surface Meteorology Data

The tropospheric zenith delay (ZTD) of GPS observations is closely related to the integrated water vapour (IWV) content of the atmosphere. The scale factor between the IWV and the ZWD is a function of the mean temperature of the water vapour, which can be computed by a linear regression equation based on the surface temperature. A similar linear regression can be used to compute the IWV from surface water vapour density. In this paper we show a formula derived from more than 10,000 radiosonde observations in Hungary. Using this relation, it is possible to estimate the IWV content of the atmosphere, which could be scaled down to tropospheric zenith wet delay. Two time intervals are used for the validation of the results. The first one was a stormy summer period, while the other was a dry winter period. The results show that this approach provides slightly better coordinate RMS than the Niell or the Hopfield model. Moreover the coordinate solutions are relatively stable during the summer period as well, when a heavy storm caused unstable weather conditions. Studying the performance of the local regression model, the Hopfield and the Niell (Saastamoinen+Niell mapping function) model it could be seen that the local regression model gave the best a priori tropospheric delays for the processing.