DOI: 10.1002/2017JD027748
Scopus记录号: 2-s2.0-85043368413
论文题名: Adaptive Node Parameterization for Dynamic Determination of Boundaries and Nodes of GNSS Tomographic Models
作者: Ding N. ; Zhang S.B. ; Wu S.Q. ; Wang X.M. ; Zhang K.F.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2018
卷: 123, 期: 4 起始页码: 1990
结束页码: 2003
语种: 英语
英文关键词: adaptive node parameterization
; GNSS tomography
; node parameterization
; tomographic region
; water vapor
Scopus关键词: algorithm
; atmospheric modeling
; detection method
; GNSS
; greenhouse gas
; model validation
; radiosonde
; satellite data
; spatiotemporal analysis
; three-dimensional modeling
; tomography
; water vapor
; China
; Hong Kong
英文摘要: Water vapor is one of the primary greenhouse gases and significantly impacts the atmosphere. Water vapor is the most active meteorological element and varies rapidly in both the spatial and temporal domains. As a promising means, Global Navigation Satellite Systems (GNSS) tomography has been used to construct the 3D distribution of water vapor in high resolutions. Currently, in the most commonly used node parameterization approaches, the region for the 3D modeling has a preset fixed regular shape for all tomographic epochs. As a result, too many unknown parameters need to be estimated and thus to degrade the performance of the tomographic solution. In this study, an innovative node parameterization approach using a combination of three meshing techniques to dynamically adjust both the boundary of the tomographic region and the position of nodes at each tomographic epoch is proposed. The three meshing techniques were boundary extraction, Delaunay triangulation, and force-displacement algorithm. The performance of the tomographic model resulting from the new approach was tested using one month GNSS data in May 2015 from the Hong Kong GNSS network and was compared against that of the conventional node parameterization approach. The reference for the validation of the accuracy of the test results were the radiosonde measurements from King's Park Meteorological Station (HKKP) in Hong Kong. Results showed that in terms of root-mean-square error the accuracy of the new approach significantly improved in comparison to the traditional approach. ©2018. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/114450
Appears in Collections: 气候减缓与适应
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作者单位: School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China; Satellite Positioning for Atmosphere, Climate and Environment Research Centre, the School of Science, Mathematical and Geospatial Sciences, RMIT University, Melbourne, VIC, Australia; Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China
Recommended Citation:
Ding N.,Zhang S.B.,Wu S.Q.,et al. Adaptive Node Parameterization for Dynamic Determination of Boundaries and Nodes of GNSS Tomographic Models[J]. Journal of Geophysical Research: Atmospheres,2018-01-01,123(4)