In order to study the applicability of the elevation model with considering terrain fluctuation factor in the calculation of the atmospheric water vapor conversion coefficient, this article selects different elevation data for five years from Xinjiang region sounding stations, using elevation model and Emardson model without considering the terrain fluctuation to calculate water vapor conversion coefficient K, and analyzing the applicability of the elevation model in Xinjiang region where is a large area of terrain, then comparing the accuracy of the conversion coefficient between the same latitude and different elevations as well as between the same elevation and different latitudes by the elevation model, researching the influence on elevation model from station’s latitude and altitude. The research shows that: (1) Adding terrain fluctuation factor of elevation model and Emardson model without considering the effects of elevation will appear the phenomenon of increasing accuracy, and precision of elevation model is slightly better than that of Emardson model with station’s altitude increasing. (2) When latitude acts as influence factor, the lower latitude the measuring station is, the higher accuracy of the elevation model will be. When elevation acts as influence factor, the bigger elevation the measuring station is, the higher accuracy of the elevation model will be. (3) The applicability of elevation model is better in these regions which located in low latitude and high altitude.
Klobuchar model can reflect the spatial and temporal variations of ionospheric feature, but model fixed initial phase and night-time delay will introduce a large number of errors. Aiming at the shortcomings of the models, take least-squares surface fitting model as the background, using CORS network in Nanning region to measure the data correctly, the Klobuchar model's initial phase, amplitude, and night-time delay values are steadily corrected, so as to establish regional ionospheric model in Nanning, the results show that the accuracy of Klobuchar model is improved significantly.
Using the eleven Radiosonde Stations’ data in southwestern of China from 2010 to 2013 to calculate the conversion coefficient K which is a reference value of Precipitable Water Vapor (PWV). Then build the EMARDSON model and the EMARDSON K model which introduced with elevation parameter and altitude. And to analysis the accuracy of the two models in the southwest China by radiosonde data in 2014. The results show: 1) The K value calculated by EMARDSON model has good adaptability in southwest region. 2) The method of spatial interpolation prediction by choosing 7 Radiosonde Stations’ K value uniformity is more adaptable than using 11 Radiosonde Stations’ K value to build basic model in the case of predicting 11 Radiosonde Stations’ K value, and it has a certain accuracy when predicting by using spatial interpolation in some areas where lacking data. 3) The accuracy by using the A-EMARDSON model to predict K value was improved obviously. at the same time, when predicting K value by the method of spatial interpolation, both the precision of inner and the precision of outer are better than EMARDSON model. So it can be concluded that the altitude factor is an important factor to influence the K value prediction.
As the fact that most of the ground-based GPS lacks of the detection of the upper-air meteorological data, thus the application of ground-based GPS sensing of water vapor technology has been limited due to the inaccurately calculated weighted mean temperature. In that case, this paper has studied and analyzed the methods of obtaining weighted mean temperature by deriving the data from GGOS Atmosphere weighted mean temperature grid data in Xinjiang. By using the radiosonde data, this paper has evaluated the accuracy of the weighted mean temperature(GTm) derived from GGOS atmosphere weighted mean temperature grid data and considering the seasonal and geographic factors , we employed a correction model to fit the residuals of GTm. Results show that the GTm derived from mean value interpolation and corrected by correction model meet the requirements of ground-based GPS precision sensing of Water Vapor in Xinjiang ; The inner average precision RMSD is 2.33K , MAE is 1.80 K; The outer average precision RMSD is 2.36K , MAE is 1.85 K.