Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements
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 G...
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| Format: | Article |
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KeAi Communications Co., Ltd.
2025-01-01
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| Series: | Geodesy and Geodynamics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674984724000673 |
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| author | Liansheng Deng Yugang Xiao Qusen Chen Wei Peng Zhao Li Hua Chen Zhiwen Wu |
| author_facet | Liansheng Deng Yugang Xiao Qusen Chen Wei Peng Zhao Li Hua Chen Zhiwen Wu |
| author_sort | Liansheng Deng |
| collection | DOAJ |
| description | 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 time-varying seasonal signals. It could be applicable as an auxiliary tool in the improvement of non-linear variations investigations. |
| format | Article |
| id | doaj-art-8e42eb67bde247c7932f7949b25a441c |
| institution | Kabale University |
| issn | 1674-9847 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Geodesy and Geodynamics |
| spelling | doaj-art-8e42eb67bde247c7932f7949b25a441c2025-01-13T04:18:36ZengKeAi Communications Co., Ltd.Geodesy and Geodynamics1674-98472025-01-011614254Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurementsLiansheng Deng0Yugang Xiao1Qusen Chen2Wei Peng3Zhao Li4Hua Chen5Zhiwen Wu6School of Electrical and Electronic Information Engineering, Hubei Polytechnic University, Huangshi 435003, China; Hubei Luojia Laboratory, GNSS Research Center, Wuhan University, Wuhan 430079, ChinaChangjiang Spatial Information Technology Engineering Co., Ltd., Wuhan 430010, ChinaHubei Luojia Laboratory, GNSS Research Center, Wuhan University, Wuhan 430079, China; Corresponding author.Key Laboratory of Spatial Data Mining &Information Sharing of the Ministry of Education, Fuzhou University, Fuzhou 350108, ChinaHubei Luojia Laboratory, GNSS Research Center, Wuhan University, Wuhan 430079, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaThe First Surveying and Mapping Institute of Hunan Province, Changsha 410114, ChinaThe 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 time-varying seasonal signals. It could be applicable as an auxiliary tool in the improvement of non-linear variations investigations.http://www.sciencedirect.com/science/article/pii/S1674984724000673GNSS coordinate time seriesSingular spectrum analysisTime-varying seasonal signalsLoading effectsGRACE |
| spellingShingle | Liansheng Deng Yugang Xiao Qusen Chen Wei Peng Zhao Li Hua Chen Zhiwen Wu Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements Geodesy and Geodynamics GNSS coordinate time series Singular spectrum analysis Time-varying seasonal signals Loading effects GRACE |
| title | Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements |
| title_full | Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements |
| title_fullStr | Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements |
| title_full_unstemmed | Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements |
| title_short | Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements |
| title_sort | detection and interpretation of the time varying seasonal signals in china with multi geodetic measurements |
| topic | GNSS coordinate time series Singular spectrum analysis Time-varying seasonal signals Loading effects GRACE |
| url | http://www.sciencedirect.com/science/article/pii/S1674984724000673 |
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