An algorithm for global troposphere delay determination by the combination of GPT/UNB3m and classic models

Determination of troposphere delay has always been a challenging issue in Global Navigation Satellite System (GNSS) applications, such as high precision GNSS positioning and atmospheric delay parameter estimation. In this study, an improved algorithm, named SEU, is proposed, using a modified classic model to calculate the zenith tropospheric delay. The temperature and barometric pressure in the algorithm are derived from the Global Pressure and Temperature (GPT) model, while the water vapour pressure parameters are obtained by applying the relative humidity calculation in the UNB3m model, instead of the conventional method of using standard meteorological parameters. For verification, datasets for the whole year of 2011 from 242 globally distributed stations were calculated. Annual mean error, standard deviation and RMS of the difference between the results from this algorithm and Centre for Orbit Determination in Eucrope (CODE) are about 0.67 cm, 4.11 cm and 5.2 cm. Distinctively, the proposed algorithm is better than the classic models, such as Hopfield and compared with UNB3m, the advantages of SEU are regional and seasonal. In regional analysis, SEU algorithm performs better than UNB3m model in the southern hemisphere especially Antarctica, and the accuracy of the proposed algorithm is nearly uniform in the global scope while the accuracy of UNB3m shows decreasing trend from north to south in general; while in seasonal analysis, the precision of SEU algorithm is superior to that of UNB3m model in the southern hemisphere, except in June and July. From November to next April i.e. during winter SEU algorithm is better than UNB3m during the period in the northern hemisphere. Therefore the proposed algorithm still being an empirical model with simple operation, just the location and the time required, an accurate priori tropospheric delay value with real-time practicability and worldwide availability could be achieved for GNSS positioning and other space research.