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《Chinese Journal of Geophysics》 2008-05
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Characteristics of daily position time series from the Hong Kong GPS fiducial network

YUAN Lin-Guo1,DING Xiao-Li1,CHEN Wu1,KWOK Simon2,CHAN Siu-Bun2,HUNG Pen-Shan3,CHAU Kam-Tim4 1 Department of Land Surveying and Geo-informatics,The Hong Kong Polytechnic University,Kowloon,Hong Kong2 Geodetic Survey Section,Lands Department,Hong Kong SAR,Hong Kong3 Department of Land Management,Feng-Chia University,Taichung,Taiwan4 Department of Civil and Structural Engineering,The Hong Kong Polytechnic University,Kowloon,Hong Kong  
Characteristics of daily position time series from January,2001 to August,2007 at 12 stations in the Hong Kong GPS fiducial network are investigated in this paper.A spatial filtering algorithm based on principal component analysis is employed to remove the common mode errors from the daily position time series.The noise characteristics of the filtered position time series are assessed by the method of maximum likelihood estimation.Contributions from atmospheric,nontidal oceanic,snow and soil moisture mass loading are evaluated.The results indicate that spatial filtering is an effective way to improve the precision of position time series and provide better resolution for detecting local deformation signals.The common mode errors have strong seasonal variation.The observed ~3 mm annual vertical variation of the common mode errors can be explained by the joint contribution of these seasonal surface mass redistributions.After removing these surface mass loading effects the residual common mode errors are highly related to the higher-order ionospheric effects.The noise in the filtered position time series can be described as a combination of variable white noise plus flicker noise.The velocity uncertainties are about 2~6 times larger if only variable white noise is assumed.The maximum relative horizontal velocity between the sites is 1.5 mm/yr,which indicates some local fault activities.In addition,there are obvious 1~2 mm local seasonal signals in the filtered position time series of some sites.The residual scatters of all filtered time series also show strong seasonal characteristics.
【Fund】: 香港特别行政区研究资助局项目(PolyU5157/05E;PolyU5161/06E);; 香港理工大学基金项目(GY-F81)资助
【CateGory Index】: P228.4
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