Global Weighted Mean Temperature Model Considering Nonlinear Vertical Reduction

Weighted mean temperature (T_m) is a critical parameter in global navigation satellite system technology to retrieve precipitable water vapor. In this paper, the products from the European Center for Medium-Range Weather Forecasts (ECMWF) are used to analyze the distribution trait of T_m along the vertical direction, and to establish a new global T_m model. The ECMWF and radiosonde data are used to validate this newly built model, and an existing high-accuracy T_m model is employed for comparison. The results show that T_m has nonlinear variation trait along the vertical direction, and this trait is specifically apparent in the high-latitude regions, especially in the polar areas. When tested with the ECMWF and the radiosonde data, the root mean square (RMS) of the newly built model are 3.84 K and 4.36 K, respectively, achieving accuracy improvements of 27% and 20% compared to the existing model. The correction performance for T_m along the vertical direction is increased noticeably and the T_m profile calculated by the model proposed in this paper is much closer to the reference.