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Uncertainty Assessments of Load Deformation from Different GPS Time Series Products, GRACE Estimates and Model Predictions: A Case Study over Europe
Wang, Song-Yun1,2; Li, Jin1,3; Chen, Jianli4; Hu, Xiao-Gong1,2
2021-07-01
Source PublicationREMOTE SENSING
Volume13Issue:14Pages:16
AbstractA good understanding of the accuracy of the Global Positioning System (GPS) surface displacements provided by different processing centers plays an important role in load deformation analysis. We estimate the noise level in both vertical and horizontal directions for four representative GPS time series products, and compare GPS results with load deformation derived from the Gravity Recovery and Climate Experiment (GRACE) gravity measurements and climate models in Europe. For the extracted linear trend signals, the differences among different GPS series are small in all the three (east, north, and up) directions, while for the annual signals the differences are large. The mean standard deviations of annual amplitudes retrieved from the four GPS series are 3.54 mm in the vertical component (69% of the signal itself) and similar to 0.3 mm in the horizontal component (30% of the signal itself). The Scripps Orbit and Permanent Array Center (SOPAC) and MEaSUREs series have the lowest noise level in vertical and horizontal directions, respectively. Through consistency/discrepancy analysis among GPS, GRACE, and model vertical series, we find that the Jet Propulsion Laboratory (JPL) and Nevada Geodetic Laboratory (NGL) series show good consistency, the SOPAC series show good agreements in annual signal with the GRACE and model, and the MEaSUREs series show substantially large annual amplitude. We discuss the possible reasons for the notable differences among GPS time series products.
KeywordGPS load deformation noise GRACE model
Funding OrganizationNatural Science Foundation of Shanghai ; Natural Science Foundation of Shanghai ; Natural Science Foundation of China ; Natural Science Foundation of China ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Natural Science Foundation of Shanghai ; Natural Science Foundation of Shanghai ; Natural Science Foundation of China ; Natural Science Foundation of China ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Natural Science Foundation of Shanghai ; Natural Science Foundation of Shanghai ; Natural Science Foundation of China ; Natural Science Foundation of China ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Natural Science Foundation of Shanghai ; Natural Science Foundation of Shanghai ; Natural Science Foundation of China ; Natural Science Foundation of China ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques
DOI10.3390/rs13142765
WOS KeywordWATER STORAGE ; VARIABILITY ; CALIFORNIA ; MOTION ; EARTH
Language英语
Funding ProjectNatural Science Foundation of Shanghai[19ZR1466900] ; Natural Science Foundation of Shanghai[20ZR1467400] ; Natural Science Foundation of China[12003057] ; Natural Science Foundation of China[11873075] ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques
Funding OrganizationNatural Science Foundation of Shanghai ; Natural Science Foundation of Shanghai ; Natural Science Foundation of China ; Natural Science Foundation of China ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Natural Science Foundation of Shanghai ; Natural Science Foundation of Shanghai ; Natural Science Foundation of China ; Natural Science Foundation of China ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Natural Science Foundation of Shanghai ; Natural Science Foundation of Shanghai ; Natural Science Foundation of China ; Natural Science Foundation of China ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Natural Science Foundation of Shanghai ; Natural Science Foundation of Shanghai ; Natural Science Foundation of China ; Natural Science Foundation of China ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques ; Shanghai Key Laboratory of Space Navigation and Positioning Techniques
WOS Research AreaEnvironmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000677136900001
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/76254
Collection中国科学院国家天文台
Corresponding AuthorWang, Song-Yun
Affiliation1.Chinese Acad Sci, Shanghai Astron Observ, Shanghai 200030, Peoples R China
2.Chinese Acad Sci, Shanghai Astron Observ, Shanghai Key Lab Space Nav & Positioning Tech, Shanghai 200030, Peoples R China
3.Univ Chinese Acad Sci, Sch Astron & Space Sci, Beijing 100049, Peoples R China
4.Univ Texas Austin, Ctr Space Res, Austin, TX 78759 USA
Recommended Citation
GB/T 7714
Wang, Song-Yun,Li, Jin,Chen, Jianli,et al. Uncertainty Assessments of Load Deformation from Different GPS Time Series Products, GRACE Estimates and Model Predictions: A Case Study over Europe[J]. REMOTE SENSING,2021,13(14):16.
APA Wang, Song-Yun,Li, Jin,Chen, Jianli,&Hu, Xiao-Gong.(2021).Uncertainty Assessments of Load Deformation from Different GPS Time Series Products, GRACE Estimates and Model Predictions: A Case Study over Europe.REMOTE SENSING,13(14),16.
MLA Wang, Song-Yun,et al."Uncertainty Assessments of Load Deformation from Different GPS Time Series Products, GRACE Estimates and Model Predictions: A Case Study over Europe".REMOTE SENSING 13.14(2021):16.
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