中文版 | English
Title

Potential Contributors to CME and Optimal Noise Model Analysis in the Chinese Region Based on Different HYDL Models

Author
Corresponding AuthorChen, Kejie
Publication Years
2023-02
DOI
Source Title
EISSN
2072-4292
Volume15
Abstract
Optimizing the noise model for global navigation satellite system (GNSS) vertical time series is vital to obtain reliable uplift (or subsidence) deformation velocity fields and assess the associated uncertainties. In this study, by thoroughly considering the effects of hydrological loading (HYDL) that dominates the seasonal fluctuations and common mode error (CME), we analyzed the optimal noise characteristics of GNSS vertical time series at 39 stations spanning from January 2011 to August 2019 in the Chuandian region, southeast of the Qinghai–Tibet Plateau. Our results showed that the optimal noise models without HYDL correction were white noise plus flicker noise (WN + FN), white noise plus power law noise (WN + PL), and white noise plus Gauss–Markov noise (WN + GGM), which accounted for 87%, 10%, and 3% of GNSS stations, respectively. By contrast, the optimal noise models at all stations were WN + FN and WN + PL after correction by different HYDLs. The correlation between CME and HYDL provided by the School and Observatory of Earth Sciences (EOST), namely EOST_HYDL, was 0.63~0.8 and the value of RMS reduction was 18.9~40.3% after removing EOST_HYDL time series from the CME, with a mean value of 31.8%, there is a good correlation and consistency between CME and EOST_HYDL. The absolute value of vertical velocity and its uncertainty with and without EOST_HYDL correction varied from 0.11 to 0.55 mm/a and 0 to 0.23 mm/a, respectively, implying that the effect of HYDL should not be neglected when performing optimal noise model analysis for GNSS vertical time series in the Chuandian region.
© 2023 by the authors.
Indexed By
EI ; SCI
Language
English
SUSTech Authorship
First ; Corresponding
Funding Project
This research was financially supported by the Open Foundation of the United Laboratory of Numerical Earthquake Forecasting (Grant No. 2021LNEF01), Natural Science Foundation of Guangdong Province (Grant No. 2023A1515011062), and the National Natural Science Foundation of China (Grant No. 42074024 and 41672192).
WOS Accession No
WOS:000942272000001
Publisher
EI Accession Number
20231013672602
EI Keywords
Global positioning system ; Time series analysis ; Uncertainty analysis ; White noise
ESI Classification Code
Probability Theory:922.1 ; Mathematical Statistics:922.2
Data Source
EV Compendex
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/519665
DepartmentDepartment of Earth and Space Sciences
Affiliation
1.Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen; 518055, China
2.China Earthquake Networks Center, Beijing; 100045, China
3.Institute of Earthquake Science, China Earthquake Administration, Beijing; 100036, China
4.College of Resource Environment and Tourism, Capital Normal University, Beijing; 100048, China
First Author AffilicationDepartment of Earth and Space Sciences
Corresponding Author AffilicationDepartment of Earth and Space Sciences
First Author's First AffilicationDepartment of Earth and Space Sciences
Recommended Citation
GB/T 7714
Hu, Shunqiang,Chen, Kejie,Zhu, Hai,et al. Potential Contributors to CME and Optimal Noise Model Analysis in the Chinese Region Based on Different HYDL Models[J]. Remote Sensing,2023,15.
APA
Hu, Shunqiang,Chen, Kejie,Zhu, Hai,Wang, Tan,Zhao, Qian,&Yang, Zhenyu.(2023).Potential Contributors to CME and Optimal Noise Model Analysis in the Chinese Region Based on Different HYDL Models.Remote Sensing,15.
MLA
Hu, Shunqiang,et al."Potential Contributors to CME and Optimal Noise Model Analysis in the Chinese Region Based on Different HYDL Models".Remote Sensing 15(2023).
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