1School of Geodesy and Geomatics, Wuhan University, Wuhan, China
2Key Laboratory of Geospace Environment and Geodesy, Ministry of
Education, Wuhan University, Wuhan, China
3Collaborative Innovation Center for Geospatial Technology, Wuhan,
Received: 19 Oct 2016 – Revised: 08 Dec 2016 – Accepted: 08 Dec 2016 – Published: 11 Jan 2017
Abstract. The spatio-temporal distribution of atmospheric water vapour information plays a crucial role in the establishment of modern numerical weather forecast models and description of the different weather variations. A troposphere tomographic method has been proposed considering the signal rays penetrating from the side of the area of interest to solve the problem of the low utilisation rate of global navigation satellite system (GNSS) observations. Given the method above needs the establishment of a unit scale factor model using the radiosonde data at only one location in the research area, an improved approach is proposed by considering the reasonability of modelling data and the diversity of the modelling parameters for building a more accurate unit scale factor model. The new established model is established using grid point data derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) and evenly distributed in the tomographic area, which can enhance the number of calculated initial water vapour density values with high accuracy. We validated the improved method with respect to the previous methods, as well as the result from a radiosonde using data from 12 stations from the Hong Kong Satellite Positioning Reference Station Network. The obtained result shows that the number of initial values estimated by the new model is increased by 6.83 %, while the internal and external accuracies are 0.08 and 0.24 g m−3, respectively. Integrated water vapour (IWV) and water vapour density profile comparisons show that the improved method is superior to previous studies in terms of RMS, MAE, and bias, which suggests higher accuracy and reliability.
Zhao, Q. and Yao, Y.: An improved troposphere tomographic approach considering the signals coming from the side face of the tomographic area, Ann. Geophys., 35, 87-95, doi:10.5194/angeo-35-87-2017, 2017.