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Annales Geophysicae An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/angeo-2018-106
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/angeo-2018-106
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Regular paper 02 Oct 2018

Regular paper | 02 Oct 2018

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Annales Geophysicae (ANGEO).

Influence of station density and multi-constellation GNSS observations on troposphere tomography

Qingzhi Zhao1, Kefei Zhang2,3, and Wanqiang Yao1 Qingzhi Zhao et al.
  • 1College of Geomatics, Xi'an University of Science and Technology, Xi'an, China
  • 2School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
  • 3Satellite Positioning for Atmosphere, Climate and Environment (SPACE) Research Centre, RMIT University, Melbourne, Australia

Abstract. Troposphere tomography, using multi-constellation GNSS observations, has become a novel approach for the three-dimensional (3-d) reconstruction of water vapour fields. An analysis of the integration of four Global Navigation Satellite Systems (BeiDou, GPS, GLONASS and Galileo) observations is presented to investigate the impact of station density and single/multi-constellation GNSS observations on troposphere tomography. Additionally, the optimal horizontal resolution of research area is determined in Hong Kong, which considers both the number of voxels divided, and the coverage rate of discretized voxels penetrated by satellite signals. Tomography experiment reveals that the influence of station density in a GNSS network is more significant than the multi-constellation GNSS observations on the reconstruction of 3-d atmospheric water vapour profiles. Compared to the tomographic result from the multi-constellation GNSS (BeiDou, GPS, GLONASS and Galileo) observations, the RMS of SWD residuals derived from the single-GNSS observations has been decreased by 16% when the data from the other four stations are added. Furthermore, more experiments have been carried out to analyse the contributions of different combined GNSS data to the reconstructed results, and the comparisons show some interesting results: (1) the number of iterations used in determining the weighting matrices of different equations in tomography modelling can be decreased when considering multi-constellation GNSS observations; (2) the tomographic result with multi-constellation GNSS data can improve the reconstructed quality of 3-d atmospheric water vapour by the largest RMS value of about 11% when compared to the PPP-estimated SWD, but this was not as high as was expected.

Qingzhi Zhao et al.
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Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Qingzhi Zhao et al.
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