Evaluation of Virtual Reference Station Constraints for GNSS Tropospheric Tomography in Austria Region

Abstract

One of the most promising methods of GNSS meteorology is GNSS Tomography. This method can be used for the determination of water vapor distribution, which contributes to the reliability of weather forecasting and early warning of severe weather. Therefore, GNSS Tomography is a valuable source of information for meteorological and weather forecast. The system of equations of this problem is mixed-determined because propagated signals do not pass through some of the model elements within the area of interest. Consequently, the normal matrix is close to singular without any unique solution. To avoid singularity and achieve a unique solution, additional sources or horizontal and/or vertical constraints are usually applied. Here, three schemes have been considered for remedying the rank deficiency of the problem. In the first scheme, minimum horizontal and vertical constraints were imposed on the system of observation equations. Then, we have defined three schemes to evaluate the impact of Virtual Reference Stations (VRS) in comparison to horizontal and vertical constraints in the sparse GNSS network. Within a network of Austrian GNSS reference stations these schemes have been analyzed and validated with available radiosonde profiles for the period DoY 245–256 in 2017. According to our results, the consistency of the estimated refractivity field with radiosonde profiles in the dense GNSS network was generally better (RMSE 2.80 ppm) than for the two other schemes in the period of interest. Moreover, in the sparse GNSS network, the average of RMSE for schemes with VRS stations and constraints equation was about 3.02 and 3.27 ppm, respectively. Hence, the obtained results illustrate that applying VRS stations in the sparse GNSS network can lead to a better solution in comparison to applying horizontal and vertical constraints.