Influence of station density and multi-constellation GNSS observations on troposphere tomography
<p>Troposphere tomography, using multi-constellation observations from global navigation satellite systems (GNSSs), has become a novel approach for the three-dimensional (3-D) reconstruction of water vapour fields. An analysis of the integration of four GNSSs (BeiDou, GPS, GLONASS, and Galileo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-01-01
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| Series: | Annales Geophysicae |
| Online Access: | https://www.ann-geophys.net/37/15/2019/angeo-37-15-2019.pdf |
| _version_ | 1818130081232453632 |
|---|---|
| author | Q. Zhao K. Zhang K. Zhang W. Yao |
| author_facet | Q. Zhao K. Zhang K. Zhang W. Yao |
| author_sort | Q. Zhao |
| collection | DOAJ |
| description | <p>Troposphere tomography, using multi-constellation observations from global
navigation satellite systems (GNSSs), has
become a novel approach for the three-dimensional (3-D) reconstruction of
water vapour fields. An analysis of the integration of four GNSSs (BeiDou,
GPS, GLONASS, and Galileo) observations is presented to investigate the
impact of station density and single- and multi-constellation GNSS
observations on troposphere tomography. Additionally, the optimal horizontal
resolution of the research area is determined in Hong Kong considering both
the number of voxels divided, and the coverage rate of discretized voxels
penetrated by satellite signals. The results show that densification of the
GNSS network plays a more important role than using multi-constellation GNSS
observations in improving the retrieval of 3-D atmospheric water vapour
profiles. The root mean square of slant wet delay (SWD) residuals derived
from the single-GNSS observations decreased by 16 % when the data from
the other four stations are added. Furthermore, additional 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 and (2) the reconstructed
quality of 3-D atmospheric water vapour using multi-constellation GNSS data
can be improved by about 11 % when compared to the SWD estimated with
precise point positioning, but this was not as high as expected.</p> |
| first_indexed | 2024-12-11T07:59:22Z |
| format | Article |
| id | doaj.art-40f5907d081a485b971120c42ee09742 |
| institution | Directory Open Access Journal |
| issn | 0992-7689 1432-0576 |
| language | English |
| last_indexed | 2024-12-11T07:59:22Z |
| publishDate | 2019-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Annales Geophysicae |
| spelling | doaj.art-40f5907d081a485b971120c42ee097422022-12-22T01:15:10ZengCopernicus PublicationsAnnales Geophysicae0992-76891432-05762019-01-0137152410.5194/angeo-37-15-2019Influence of station density and multi-constellation GNSS observations on troposphere tomographyQ. Zhao0K. Zhang1K. Zhang2W. Yao3College of Geomatics, Xi'an University of Science and Technology, Xi'an, ChinaSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, ChinaSatellite Positioning for Atmosphere, Climate and Environment (SPACE) Research Centre, RMIT University, Melbourne, AustraliaCollege of Geomatics, Xi'an University of Science and Technology, Xi'an, China<p>Troposphere tomography, using multi-constellation observations from global navigation satellite systems (GNSSs), has become a novel approach for the three-dimensional (3-D) reconstruction of water vapour fields. An analysis of the integration of four GNSSs (BeiDou, GPS, GLONASS, and Galileo) observations is presented to investigate the impact of station density and single- and multi-constellation GNSS observations on troposphere tomography. Additionally, the optimal horizontal resolution of the research area is determined in Hong Kong considering both the number of voxels divided, and the coverage rate of discretized voxels penetrated by satellite signals. The results show that densification of the GNSS network plays a more important role than using multi-constellation GNSS observations in improving the retrieval of 3-D atmospheric water vapour profiles. The root mean square of slant wet delay (SWD) residuals derived from the single-GNSS observations decreased by 16 % when the data from the other four stations are added. Furthermore, additional 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 and (2) the reconstructed quality of 3-D atmospheric water vapour using multi-constellation GNSS data can be improved by about 11 % when compared to the SWD estimated with precise point positioning, but this was not as high as expected.</p>https://www.ann-geophys.net/37/15/2019/angeo-37-15-2019.pdf |
| spellingShingle | Q. Zhao K. Zhang K. Zhang W. Yao Influence of station density and multi-constellation GNSS observations on troposphere tomography Annales Geophysicae |
| title | Influence of station density and multi-constellation GNSS observations on troposphere tomography |
| title_full | Influence of station density and multi-constellation GNSS observations on troposphere tomography |
| title_fullStr | Influence of station density and multi-constellation GNSS observations on troposphere tomography |
| title_full_unstemmed | Influence of station density and multi-constellation GNSS observations on troposphere tomography |
| title_short | Influence of station density and multi-constellation GNSS observations on troposphere tomography |
| title_sort | influence of station density and multi constellation gnss observations on troposphere tomography |
| url | https://www.ann-geophys.net/37/15/2019/angeo-37-15-2019.pdf |
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