With the widespread use of GNSS on civil aviation and UAV platforms, scenarios with large elevation differences are increasingly emerging, which puts higher demands on the accuracy of vertical corrections for tropospheric delays. As the most advanced ZTD model currently available, GPT3 has limitations in its vertical corrections for temperature and pressure, making it only suitable for near-surface applications. To address this issue, this paper proposes an improved method of GPT3 by integrating a global temperature lapse rate grid model and a multi-variable atmospheric pressure-altitude formula, constructing the IGPT3 model, and evaluating its adaptability. The results show that compared with UNB3 and GPT3, IGPT3 has improved accuracy by 25.0%, 18.2%, 16.1%, and 72.2%, 50.0%, 69.9% in predicting temperature lapse rate, temperature profile, and pressure profile, respectively. Moreover, the precision improvements in predicting ZHD and ZTD profiles using IGPT3 reached 29.3 mm and 29.0 mm, respectively. Furthermore, the precision of GNSS water vapor inversion at most IGS stations was improved with the use of IGPT3, with the maximum improvement reaching 3.07 mm.

tropospheric delay correction  /  temperature lapse rate  /  barometric height formula  /  GPT3 model