Development and Assessment of Improved Global Pressure and Temperature Series Models

Global pressure and temperature (GPT) series models can provide the underlying meteorological parameters for tropospheric corrections without any other meteorological observations, which allows them to be widely used for a series of geodetic as well as meteorological and climatological purposes. Due to the height difference between the empirical model height and user location, a vertical correction of meteorological parameters is inevitable, particularly for airborne users. Unfortunately, the GPT series models have limitations on the vertical correction. We explored the temperature lapse rate for the vertical adjustment using 10 years of reanalysis data provided by the National Centers for Environmental Prediction (NCEP), and extended the GPT models to improved global pressure and temperature (IGPT) series models by introducing a new temperature lapse rate model and a new formulation of pressure reduction. An evaluation of the IGPT models expression determines that the IGPT models have better accuracy than the GPT models, particularly under large height differences, which is attributed to their ability to consider the real behavior of temperature in the atmosphere and adiabatic effects on air pressure. The performance of the IGPT models in zenith tropospheric delay (ZTD) estimations was also evaluated by comparison with the fifth-generation European Centers for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA5) data and International GNSS Service (IGS) data. The results confirm that our new models can effectively improve the accuracy of ZTDs, particularly at larger altitude differences between the target height and the corresponding four grid points of the model, not only enhancing the performance of the model in complex terrain but also extending the feasibility of the IGPT models from the Earth’s surface to higher altitudes.