journal article·2019-04-06Open access

A New Method of GPS Water Vapor Tomography for Maximizing the Use of Signal Rays

Fei Yang, Jiming Guo, Junbo Shi, Yinzhi Zhao, Lv Zhou, Shengdeng Song

Applied Sciences· Volume 9· Issue 7

Abstract

The spatio-temporal distribution of atmospheric water vapor information can be obtained by global positioning system (GPS) water vapor tomography. GPS signal rays pass through the tomographic area from different boundaries because the scope of the research region (latitude, longitude, and altitude) is designated in the process of tomographic modeling, the influence of the geographic distribution of receivers, and the geometric location of satellite constellations. Traditionally, only signal rays penetrating the entire tomographic area are considered in the computation of water vapor information, whereas those passing through the sides are neglected. Therefore, the accuracy of the tomographic result, especially at the bottom of the area, does not reach its full potential. To solve this problem, this paper proposes a new method that simultaneously considers the discretized tomographic voxels and the troposphere outside the research area as unknown parameters. This method can effectively improve the utilization of existing GPS observations and increase the number of voxels crossed by satellite signals, especially by increasing the proportion of voxels penetrated. A tomographic experiment is implemented using GPS data from the Hong Kong Satellite Positioning Reference Station Network. Compared to the traditional method, the proposed method increases the number of voxels crossed by signal rays and the utilization of the observed data by 15.14% and 19.68% on average, respectively. Numerical results, including comparisons of slant water vapor (SWV), precipitable water vapor (PWV), and water vapor density profile, show that the proposed method is better than traditional methods. In comparison to the water vapor density profile, the root-mean-square error (RMS), mean absolute error (MAE), standard deviation (SD), and bias of the proposed method are 1.39, 1.07, 1.30, and −0.21 gm−3, respectively. For the SWV and PWV comparison, the RMS/MAE of the proposed method are 10.46/8.17 mm and 4.00/3.39 mm, respectively.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: GNSS positioning and interference · Geophysics and Gravity Measurements · Ionosphere and magnetosphere dynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China

Key laboratory of Precise Engineering and Industry Surveying of National Administration of Surveying, Mapping and Geoinformation, Wuhan University, Wuhan 430079, China

Research Center for High Accuracy Location Awareness, Wuhan University, Wuhan 430079, China

Guangxi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China

Sinohydro Engineering Bureau 4 Co., Ltd, Xining 810007, China

Funding

National Natural Science Foundation of China · Power Construction Corporation of China Project

References (31)

Show source-provided references
1. Sensing atmospheric water vapor with the global positioning system10.1029/93GL02935 ↗
2. Precipitable water vapor on the Tibetan Plateau estimated by GPS, water vapor radiometer, radiosonde, and numerical weather prediction analysis and its impact on the radiation budget10.1029/2004JD005715 ↗
3. Report of the first prospectus development team of the U.S. Weather Research Program to NOAA and the NSF
4. An overview of the international H2O project (IHOP_2002) and some preliminary highlights10.1175/BAMS-85-2-253 ↗
5. Operational assimilation of GPS slant path delay measurements into the MM5 4DVAR system10.1111/j.1600-0870.2010.00489.x ↗
6. The improvement and enlightenment of rainstorm waring modern in Japan
7. Storm-Scale Numerical Rainfall Prediction for Five Precipitating Events over France: On the Importance of the Initial Humidity Field10.1175/1520-0434(2002)017<1236:SSNRPF>2.0.CO;2 ↗
8. Anthropogenic greenhouse forcing and strong water vapor feedback increase temperature in Europe10.1029/2005GL023624 ↗
9. 4D GPS water vapor tomography: New parameterized approaches10.1007/s00190-011-0454-2 ↗
10. Water vapor tomography using GPS phase observations: Simulation results10.1109/TGRS.2006.877755 ↗
11. Local tomography troposphere model over mountains area10.1016/j.atmosres.2009.03.013 ↗
12. Limited constraint, robust Kalman filtering for GPS troposphere tomography10.5194/amt-7-1475-2014 ↗
13. An optimal weighting method of Global Positioning System (GPS) troposphere tomography10.1109/JSTARS.2016.2546316 ↗
14. Adaptive node parameterization for dynamic determination of boundaries and nodes of GNSS tomographic models10.1002/2017JD027748 ↗
15. Braun, J., Rocken, C., Meetrens, C., and Ware, R. (1999, January 22–26). Development of a Water Vapor Tomography System Using Low Cost L1 GPS Receivers. Proceedings of the 9th ARM Science Team Meeting, US Dep. of Energy, San Antonio, TX, USA.
16. 4D tropospheric tomography using GPS slant wet delays10.1007/s00585-000-0223-7 ↗
17. The verification of GPS troposphere tomography model in a mountainous area10.1016/j.asr.2010.04.017 ↗
18. Local GPS tropospheric tomography10.1186/BF03352308 ↗
19. Tomographic reconstruction of wet and total refractivity fields from GPS receiver networks10.1016/j.asr.2010.12.025 ↗
20. Assessing the performance of troposphere tomographic modeling using multi-source water vapor data during Hong Kong’s rainy season from May to October 2013
21. Experimental GPS tomography study in Lisbon (Portugal)10.5209/rev_FITE.2014.v26.46972 ↗
22. A method to improve the utilization of GPS observation for water vapor tomography10.5194/angeo-34-143-2016 ↗
23. An improved troposphere tomographic approach considering the signals coming from the side face of the tomographic area10.5194/angeo-35-87-2017 ↗
24. GPS water vapour tomography: Preliminary results from the ESCOMPTE field experiment10.1016/j.atmosres.2004.04.003 ↗
25. Voxel-optimized regional water vapor tomography and comparison with radiosonde and numerical weather model10.1007/s00190-014-0715-y ↗
26. Determination of weighted mean tropospheric temperature using ground meteorological measurement10.1007/BF02826630 ↗
27. Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length10.1029/RS020i006p01593 ↗
28. GPS meteorology: Mapping zenith wet delays onto precipitable water10.1175/1520-0450(1994)033<0379:GMMZWD>2.0.CO;2 ↗
29. Development of a GPS water vapour tomography system using algebraic reconstruction techniques10.1016/j.asr.2010.05.034 ↗
30. Improving the vertical resolution of ionospheric tomography with GPS occultations10.1029/97GL52283 ↗
31. Yang, F., Guo, J., Shi, J., Zhou, L., Xu, Y., and Chen, M. (2018). A method to improve the distribution of observations in GNSS water vapor tomography. Sensors, 8.10.3390/s18082526 ↗