Adaptive Node Parameterization for Dynamic Determination of Boundaries and Nodes of GNSS Tomographic Models. Issue 4 (18th February 2018)

• Record Type: Journal Article
• Authors: Ding, N.; Zhang, S. B.; Wu, S. Q.; Wang, X. M.; Zhang, K. F.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 4(2018)
• Page Start: 1990
• Page End: 2003
• Publication Date: 2018-02-18
• Subjects: GNSS tomography -- water vapor -- node parameterization -- adaptive node parameterization -- tomographic region; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1002/2017JD027748
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: 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. Key Points: A new approach for dynamic determination of tomographic boundary at each tomographic epoch is proposed Meshing techniques are used to adjust tomographic nodes—the position of unknown parameters—to equidistance according to a topology The new approach outperforms conventional node parameterization approaches