Abstract
Accurate three-dimensional (3D) atmospheric water vapor distribution, which plays a crucial role in understanding the meteorological phenomena and hazards, has been successfully retrieved using Global Navigation Satellite System (GNSS) tomography technique. Presently, the problem of the ill-posed tomography system, that results from poor GNSS acquisition geometry, remains a vital issue to be solved. In this paper, we develop a new hybrid observation GNSS tomography (HOGT) method, which constructs and introduces the virtual signals, inverted to the real rays, to address the acquisition geometry defect. Within the HOGT, the slant wet delay (SWD) of the virtual inverted signal (VIS) is estimated by means of the tropospheric parameters derived from the hourly ERA5 data using the ray-tracing algorithm. Two designed experiments, based on the dense and sparse GNSS networks (corresponding to Hong Kong and Xuzhou), respectively, are implemented to assess the performance of HOGT for the different networks. The results reveal that HOGT provides a more robust observation geometry and more accurate water vapor distribution than the traditional tomography model, with the mean number of the crossed voxels enhanced by 26.45% and 27.11% for the two networks, and the average root-mean-square error (RMSE) of the tomography solutions improved by 18.18% and 38.28% in the two areas, respectively. Furthermore, HOGT shows a significant improvement close to the Erath’s surface from 0 to 2 km, implying its superior capability to optimize the accuracy of tomography results. An additional experiment to investigate the performance of the proposed method under different time resolutions demonstrates that HOGT can be promised to retrieve more accurate water vapor distribution over short time intervals, especially for rainy days with an interval of 10 min or even shorter, which highlights the interest in tomography solutions for improving the understanding of severe weather.
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Data availability
GNSS data with the sampling rate of 30 s in Hong Kong used for this study can be accessed at: https://www.geodetic.gov.hk/sc/satref/satref.htm. The datasets in Xuzhou are not publicly available but are available from the corresponding author on reasonable request. Radiosonde data of station 45,004 and 58,027 can be accessed at: http://weather.uwyo.edu/upperair/sounding.html. The ERA5 reanalysis data with the horizontal resolution of 0.25° can be downloaded from the ECMWF public dataset at: https://cds.climate.copernicus.eu/cdsapp#!/home.
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Acknowledgements
The authors acknowledge the support of the Survey and Mapping Office (SMO) of Lands Department, Hong Kong, and the Department of Xuzhou Natural Resources and Planning, for providing the GNSS data. We also would like to appreciate University of Wyoming for the provision of the high-precision radiosonde data, and ECMWF for providing ERA5 products. The GAMIT/GLOBK software is provided by the Department of Earth Atmospheric and Planetary Sciences, MIT. The editor and reviewer team is also highly appreciated for their valuable comments, which makes great improvements in the quality of the paper. This research was supported by the Open Research Fund of Key Laboratory of Land Environment and Disaster Monitoring, Ministry of Natural Resources, China University of Mining and Technology (Grant number LEDM2021B13), by the National Natural Science Foundation of China (Grant numbers 41774026, 42074001, 41904013, and 41904033), by the Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) (Grant number XDA17010304), and by CAS Pioneer Hundred Talents Program.
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W. Z., S. Z., and N. D. designed the research; W. Z. and G. C. analyzed the data; W. Z., N. D. and X. W. performed the research; W. Z. and N. D. drafted the manuscript; S. Z, G. C., and X. W. reviewed and polished the paper. All authors read and approved the final manuscript.
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Zhang, W., Zhang, S., Chang, G. et al. A new hybrid observation GNSS tomography method combining the real and virtual inverted signals. J Geod 95, 128 (2021). https://doi.org/10.1007/s00190-021-01576-8
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DOI: https://doi.org/10.1007/s00190-021-01576-8