Abstract
Global Navigation Satellite System (GNSS) tomography has developed into an efficient tool for sensing the high spatiotemporal variability of atmospheric water vapor. The integration of GNSS top signals and side rays for tropospheric tomography systems using a novel height factor model (HFM) is proposed and discussed in this paper. Within the HFM, the sectional slant wet delay (SWD) of inside signals (the part of the side signal inside the tomography area), which is considered a key factor for modeling side rays, is separated into isotropic and anisotropic components. Correspondingly, two height factors are defined to calculate the isotropic and anisotropic part of tropospheric delays in the HFM. In addition, the dynamic tomography top boundary is first analyzed and determined based on 30-year radiosonde data to reasonably divide signals into top and side rays. Four special experimental schemes based on different tomography regions of Hong Kong are performed to assess the proposed HFM method, the results of which show increases of 33.42% in the mean utilization of rays, as well as decreases of 0.46 g/m3 in the average root mean square error (RMSE), compared to the traditional approach, revealing the improvement of tomography solutions when the side signals are included in the modeling. Furthermore, compared with the existing correction model for modeling side rays, the water vapor profiles retrieved from the proposed improved model are closer to the radiosonde data, which highlights the advantages of the proposed HFM for optimizing the GNSS tomography model.
Highlights
Global Navigation Satellite System (GNSS) technology has become an efficient atmospheric water vapor detection tool for studying rainstorm events and the El Niño-Southern Oscillation (ENSO) phenomenon [1,2,3,4]
Since voxels located on the side of the tomographic area do not travel by any ray, the water vapor density of these voxels can be estimated based on only constraint equations, which reduces the accuracy of the tomography solutions
Only GNSS observations went sent to the tomography system as input information for reconstructing the three-dimensional water vapor field, which shows that the proposed height factor model (HFM) does not interfere with the accuracy assessment of tomography results
Summary
Global Navigation Satellite System (GNSS) technology has become an efficient atmospheric water vapor detection tool for studying rainstorm events and the El Niño-Southern Oscillation (ENSO) phenomenon [1,2,3,4]. The tomography area was narrowed to ensure that side rays could pass from the side of the narrowing region, and the scale factor model was established by analyzing the proportional relationship between the part slant water vapor (part SWV) and height Both models fully utilized GNSS signals and improved the accuracy of tomographic results. To make full use of side observations and obtain the high-accuracy SWD of inside signals, we investigate the isotropic and anisotropic part of the GNSS SWD and propose the height factor model (HFM), where isotropic and anisotropic height factors are innovatively introduced The former, revealing the relationship between the height and the isotropic zenith wet delay (ZWD), is modeled by 30-year radiosonde data from different months. A further comparison of the proposed optimized model and the existing correction model is performed to illustrate the advantages of the proposed HFM in tomography modeling
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