Seasonal multifactor modelling of weighted-mean temperature for ground-based GNSS Meteorology in Hunan, China

Li, L, Wu, S, Wang, X, Tian, Y, He, C and Zhang, K 2017, 'Seasonal multifactor modelling of weighted-mean temperature for ground-based GNSS Meteorology in Hunan, China', Advances in Meteorology, vol. 2017, pp. 1-13.


Document type: Journal Article
Collection: Journal Articles

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Title Seasonal multifactor modelling of weighted-mean temperature for ground-based GNSS Meteorology in Hunan, China
Author(s) Li, L
Wu, S
Wang, X
Tian, Y
He, C
Zhang, K
Year 2017
Journal name Advances in Meteorology
Volume number 2017
Start page 1
End page 13
Total pages 13
Publisher Hindawi
Abstract In this study, radiosonde observations during the period of 2012-2013 from three stations in the Hunan region, China, were used to establish regional Tm models (RTMs) that are a fitting function of multiple meteorological factors (Ts, Es, and Ps). One-factor, two-factor, and three-factor RTMs were assessed by comparing their Tm against the radiosonde-derived Tm (as the truth) during the period of 2013-2014. Statistical results showed that the bias and RMS of the one-factor RTM, in comparison to the BTM result, were reduced by 88% and 28%, respectively. The two-factor and three-factor RTMs showed similar accuracy and both outperformed the one-factor RTM, with an improvement of 7% in RMS. The bias and RMS of all the four seasonal two-factor RTMs were smaller than the yearly two-factor RTM, with the improvements of 3%, 10%, 2%, and 3% in RMS. The improvement of the conversion factors in mean bias and RMS resulting from the seasonal two-factor RTM is 92% and 31%. The bias and RMS of the PWV resulting from the seasonal two-factor RTM are improved by 37% and 12%, respectively. Therefore, the seasonal two-factor RTMs are recommended for the research and applications of GNSS meteorology in the Hunan region, China.
Subject Navigation and Position Fixing
Geodesy
DOI - identifier 10.1155/2017/3782687
Copyright notice Copyright © 2017 Li Li et al. This is an open access article distributed under the Creative Commons Attribution License
ISSN 1687-9309
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