Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements  

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作  者:Liansheng Deng Yugang Xiao Qusen Chen Wei Peng Zhao Li Hua Chen Zhiwen Wu 

机构地区:[1]School of Electrical and Electronic Information Engineering,Hubei Polytechnic University,Huangshi 435003,China [2]Hubei Luojia Laboratory,GNSS Research Center,Wuhan University,Wuhan 430079,China [3]Changjiang Spatial Information Technology Engineering Co.,Ltd.,Wuhan 430010,China [4]Key Laboratory of Spatial Data Mining&Information Sharing of the Ministry of Education,Fuzhou University,Fuzhou 350108,China [5]School of Geodesy and Geomatics,Wuhan University,Wuhan 430079,China [6]The First Surveying and Mapping Institute of Hunan Province,Changsha 410114,China

出  处:《Geodesy and Geodynamics》2025年第1期42-54,共13页大地测量与地球动力学(英文版)

基  金:supported by the National Natural Science Foundation of China(NO.42104028,42174030 and 42004017);the Open Fund of Hubei Luojia Laboratory(No.220100048 and 230100021);the Scientific Research Project of Hubei Provincial Department of Education,and Research Foundation of the Department of Natural Resources of Hunan Province(No.20230104CH)。

摘  要:The time-varying periodic variations in Global Navigation Satellite System(GNSS)stations affect the reliable time series analysis and appropriate geophysical interpretation.In this study,we apply the singular spectrum analysis(SSA)method to characterize and interpret the periodic patterns of GNSS deformations in China using multiple geodetic datasets.These include 23-year observations from the Crustal Movement Observation Network of China(CMONOC),displacements inferred from the Gravity Recovery and Climate Experiment(GRACE),and loadings derived from Geophysical models(GM).The results reveal that all CMONOC time series exhibit seasonal signals characterized by amplitude and phase modulations,and the SSA method outperforms the traditional least squares fitting(LSF)method in extracting and interpreting the time-varying seasonal signals from the original time series.The decrease in the root mean square(RMS)correlates well with the annual cycle variance estimated by the SSA method,and the average reduction in noise amplitudes is nearly twice as much for SSA filtered results compared with those from the LSF method.With SSA analysis,the time-varying seasonal signals for all the selected stations can be identified in the reconstructed components corresponding to the first ten eigenvalues.Moreover,both RMS reduction and correlation analysis imply the advantages of GRACE solutions in explaining the GNSS periodic variations,and the geophysical effects can account for 71%of the GNSS annual amplitudes,and the average RMS reduction is 15%.The SSA method has proved to be useful for investigating the GNSS timevarying seasonal signals.It could be applicable as an auxiliary tool in the improvement of nonlinear variations investigations.

关 键 词:GNSS coordinate time series Singularspectrumanalysis Time-varying seasonal signals Loading effects GRACE 

分 类 号:P228.4[天文地球—大地测量学与测量工程]

 

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