Abstract

Weighted mean temperature (Tm) is a crucial parameter for retrieving precipitable water vapor (PWV) in Global Navigation Satellite System (GNSS) meteorology. The difference between the height of the GNSS receiver and the height of the derived Tm may cause large uncertainty in the value of the retrieved PWV. In this study, we analyze the vertical variation of Tm on a global scale and build a new vertical correction model using the operational reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF). Another dataset from ECMWF and the radiosonde data derived from 678 globally distributed stations are used to independently validate the performance of the newly built model and demonstrate its superiority compared with the existing vertical correction method. The results show that the lapse rate of Tm has geographic and seasonal variations, and the Tm has large nonlinear variation along the vertical direction in the high-latitude regions, especially in the polar regions. A performance improvement of 15%–35% compared with the existing vertical correction method is achievable for the newly built model when tested with the ECMWF data, and the improvement is 10%–25% when tested with the radiosonde data.

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