Improving the weighted mean temperature model: A case study using nine year (2007–2015) radiosonde and COSMIC data in Hong Kong

Abstract

AbstractThe important role of a humidity conversion factor in mapping the zenith wet delay (ZWD) onto precipitable water vapour (PWV) makes it a vital parameter in Global Navigation Satellite System (GNSS) meteorology. The accuracy of the humidity conversion factor depends mainly on the quality of the atmospheric weighted mean temperature (Tm) calculation. Several effective models have been developed to calculate Tm with parameters such as the station's location, date of measurement and surface temperature. However, the drawbacks of these models, including low accuracy in some areas and complex model functions, cannot be ignored because they prevent further application in atmosphere analysis. Therefore, a new discrete integral formula for highly accurate calculation of Tm is proposed. Moreover, the linear relationships between time, surface temperature (Ts), height (H) and Tm are well studied based on radiosonde and Constellation Observation System for Meteorology Ionosphere and Climate (COSMIC) historical data (2007–2015). A new regional Tm model was investigated on the basis of parameters time, Ts and H in Hong Kong, China. The evaluation results indicate that the improvement of Tm derived from the new integral is > 4.6 K based on radiosonde data. In addition, the statistical results of Tm with different sampling based on radiosonde data and a COSMIC “wetPrf” profile show that the improvement of Tm derived from the new integral are > 2.10 and 2.75 K, respectively. Finally, wetPrf profiles collocated with Hong Kong and the 45,004 radiosonde station collected from January 1 to October 31, 2016, are used to evaluate the accuracy of the new Tm model. Compared with the Bevis model, the statistical results indicate that the Tm accuracy is improved by 34.75%. Therefore, the model for Ts and time is suggested to estimate the Tm in Hong Kong.