Investigating mass loading contributes of annual GPS observations for the Eurasian plate. (November 2017)

• Record Type: Journal Article
• Authors: Li, Zhen; Yue, Jianping; Li, Wang; Lu, Dekai
• Is Part Of: Journal of geodynamics. Volume 111(2017)
• Page Start: 43
• Page End: 49
• Publication Date: 2017-11
• Subjects: GPS -- Singular spectrum analysis -- Cross wavelet transform -- Atmospheric -- Oceanic and hydrological loading -- Relative phasing; Geodynamics -- Periodicals; Earth movements -- Periodicals; Rock deformation -- Periodicals; Earth -- Internal structure -- Periodicals; 551.1
• DOI: 10.1016/j.jog.2017.07.001
• Languages: English
• ISSNs: 0264-3707

Abstract

Abstract: Singular spectrum analysis (SSA) is a non-parametric method, which outperforms least-squares fitting (LSF) in extracting amplitude and phase varying seasonal oscillations in GPS observations. Meanwhile, it is well known that the variations of regional mass loading (atmospheric, oceanic and hydrological loading (AOHL)), as potential contributors, are very important for understanding time-varying seasonal fluctuations in GPS station heights. We thus use SSA to extract the annual signals from the time series of GPS station heights and AOHL deformation, respectively. The result reveals whether AOHL is able to explain the annual fluctuations in GPS station heights depends on the relative phasing between the two time series. Therefore, the cross wavelet transform based (XWT-based) semblance analysis is adopted to investigate the phase relationship between GPS station heights and AOHL deformation. The result of the XWT-based semblance analysis indicates that the annual variations in the two time series are physically related for most sites; other geophysical effects, GPS systematic errors and AOHL modeling errors could result in the time-varying phasing asynchrony for some sites. The phasing asynchrony confirms that the annual oscillation in GPS station heights results from a combination of mass loading and systematic errors. Moreover, for the sites where the phase asynchrony is obvious, we propose to employ SSA to denoise GPS observations since SSA perform better than AOHL deformation in reducing the RMS of GPS observations.