scholarly journals Common Mode Component and Its Potential Effect on GPS-Inferred Three-Dimensional Crustal Deformations in the Eastern Tibetan Plateau

2019 ◽  
Vol 11 (17) ◽  
pp. 1975 ◽  
Author(s):  
Yuanjin Pan ◽  
Ruizhi Chen ◽  
Hao Ding ◽  
Xinyu Xu ◽  
Gang Zheng ◽  
...  
Keyword(s):  
Time Series ◽  
Tibetan Plateau ◽  
Crustal Deformation ◽  
Three Dimensional ◽  
Vertical Component ◽  
Eastern Tibetan Plateau ◽  
Frequency Spectra ◽  
Common Mode ◽  
Time Frequency ◽  
Gps Time Series

Surface and deep potential geophysical signals respond to the spatial redistribution of global mass variations, which may be monitored by geodetic observations. In this study, we analyze dense Global Positioning System (GPS) time series in the Eastern Tibetan Plateau using principal component analysis (PCA) and wavelet time-frequency spectra. The oscillations of interannual and residual signals are clearly identified in the common mode component (CMC) decomposed from the dense GPS time series from 2000 to 2018. The newly developed spherical harmonic coefficients of the Gravity Recovery and Climate Experiment Release-06 (GRACE RL06) are adopted to estimate the seasonal and interannual patterns in this region, revealing hydrologic and atmospheric/nontidal ocean loads. We stack the averaged elastic GRACE-derived loading displacements to identify the potential physical significance of the CMC in the GPS time series. Interannual nonlinear signals with a period of ~3 to ~4 years in the CMC (the scaled principal components from PC1 to PC3) are found to be predominantly related to hydrologic loading displacements, which respond to signals (El Niño/La Niña) of global climate change. We find an obvious signal with a period of ~6 yr on the vertical component that could be caused by mantle-inner core gravity coupling. Moreover, we evaluate the CMC’s effect on the GPS-derived velocities and confirm that removing the CMC can improve the recognition of nontectonic crustal deformation, especially on the vertical component. Furthermore, the effects of the CMC on the three-dimensional velocity and uncertainty are presented to reveal the significant crustal deformation and dynamic processes of the Eastern Tibetan Plateau.

scholarly journals Analysis of the Potential Contributors to Common Mode Error in Chuandian Region of China

2020 ◽  
Vol 12 (5) ◽  
pp. 751
Author(s):  
Weijie Tan ◽  
Junping Chen ◽  
Danan Dong ◽  
Weijing Qu ◽  
Xueqing Xu
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Principal Component ◽  
Mass Loading ◽  
Common Mode ◽  
Surface Mass ◽  
Common Mode Error ◽  
Comparison Results ◽  
Wide Range ◽  
Gps Time Series

Common mode error (CME) in Chuandian region of China is derived from 6-year continuous GPS time series and is identified by principal component analysis (PCA) method. It is revealed that the temporal behavior of the CME is not purely random, and contains unmodeled signals such as nonseasonal mass loadings. Its spatial distribution is quite uniform for all GPS sites in the region, and the first principal component, uniformly distributed in the region, has a spatial response of more than 70%. To further explore the potential contributors of CME, daily atmospheric mass loading and soil moisture mass loading effects are evaluated. Our results show that ~15% of CME can be explained by these daily surface mass loadings. The power spectral analysis is used to assess the CME. After removing atmospheric and soil moisture loadings from the CME, the power of the CME reduces in a wide range of frequencies. We also investigate the contribution of CME in GPS filtered residuals time series and it shows the Root Mean Squares (RMSs) of GPS time series are reduced by applying of the mass loading corrections in CME. These comparison results demonstrate that daily atmosphere pressure and the soil moisture mass loadings are a part of contributors to the CME in Chuandian region of China.

scholarly journals Uncertainty Assessments of Load Deformation from Different GPS Time Series Products, GRACE Estimates and Model Predictions: A Case Study over Europe

2021 ◽  
Vol 13 (14) ◽  
pp. 2765
Author(s):  
Song-Yun Wang ◽  
Jin Li ◽  
Jianli Chen ◽  
Xiao-Gong Hu
Keyword(s):  
Time Series ◽  
Noise Level ◽  
Climate Models ◽  
Linear Trend ◽  
Vertical Component ◽  
Deformation Analysis ◽  
Surface Displacements ◽  
Gravity Measurements ◽  
Gps Time Series ◽  
Gravity Recovery

A 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 ~ 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.

scholarly journals Three dimensional Lagrangian strain analysis using GPS time series without regularization (Case study: Washington)

2015 ◽  
Vol 3 (3) ◽  
pp. 39-52
Author(s):  
Yashar Tode Zaeem ◽  
Vahab Nafisi ◽  
Alireza Amiri Simkooii ◽  
◽  
◽  
...  
Keyword(s):  
Time Series ◽  
Three Dimensional ◽  
Strain Analysis ◽  
Lagrangian Strain ◽  
Gps Time Series

Contemporary uplift of the Kunlun Shan, Northern Tibetan Plateau

2020 ◽  
Author(s):  
Shaozhuo Liu ◽  
jean-Mathieu Nocquet ◽  
Yann Klinger ◽  
Xiwei Xu ◽  
Guihua Chen ◽  
...  
Keyword(s):  
Time Series ◽  
Tibetan Plateau ◽  
Mechanical Response ◽  
Qaidam Basin ◽  
Thrust Fault ◽  
Crustal Thickening ◽  
Mountain Range ◽  
Uplift Rate ◽  
Northern Tibetan Plateau ◽  
Gps Time Series

<p>GPS observations across active mountain ranges provide essential constraints on uplift rates, which sheds light on the underlying physical processes contributing to the development of topography. The Kunlun Shan (KLS) mountain range bounds the topographic high of the northern Tibetan Plateau. The elevation across the range sharply decreases from >4000 m in the interior of the plateau to ~2700 m in the Qaidam Basin. The mechanism responsible for its formation is debated with several models proposed on the basis of seismological and geological data. Here we consider data constraints from a cGPS profile that runs across the KLS and was installed in 2007. Our GPS time series reveal direct mechanical response to the crustal thickening across the KLS and therefore provide a promising dataset against which some geodynamical models can be tested.  Based on the GPS time series, we estimate rates of tectonic uplift and evaluate the impacts originating from reference frame drifts, common mode errors, some non-tectonic signals (e.g., hydrological loading), time-correlated noise, and postseismic transients of recent large earthquake. The GPS-derived uplift rate is ~1 mm/yr at the KLS. We find that ~2 mm/yr deep slip on a low- or intermediate-angle south-dipping thrust fault can explain the GPS-derived uplift rate. The possibility of a high-angle thrust fault, as has been proposed for the Longmen Shan (southeastern Tibetan Plateau), does not appear to be likely in the KLS case.</p>

scholarly journals Hydrologic Variations and Stochastic Modeling of Runoff in Zoige Wetland in the Eastern Tibetan Plateau

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Guanghua Qin ◽  
Hongxia Li ◽  
Zejiang Zhou ◽  
Kechao Song ◽  
Li Zhang
Keyword(s):  
Time Series ◽  
Tibetan Plateau ◽  
Nearest Neighbor ◽  
Time Series Data ◽  
Water Source ◽  
Annual Runoff ◽  
Series Data ◽  
Eastern Tibetan Plateau ◽  
Double Peaks ◽  
Zoige Wetland

Hydrological time series data (1988–2008) of the Hei River, the main water source to Zoige wetland in the Eastern Tibetan Plateau, were investigated. Results showed that the runoff distribution of Hei River varies with the relative change in amplitude (Cm=15.9) and the absolute change in amplitude (ΔQ=37.1 m3/s) during the year. There was a significant decreasing trend since 1988 with annual runoff of 20.0 m3/s (1988–1994), 19.0 m3/s (1995–2000), and 15.2 m3/s (2001–2008). There were double peaks in runoff during the water year: the highest peak in the period of 1988–2000 occurred in July while in the period of 2001–2008 it occurred in October. Shifting peak flow means less water quantity in wetland during growing season. Nearest neighbor bootstrapping regressive method was used to predict daily runoff of the Hei River. Model results show that it was fitted with 94.23% ofR2for daily time series, which can provide a basis for the development and utilization of regional water resources.

scholarly journals Impacts of Local Effects and Surface Loads on the Common Mode Error Filtering in Continuous GPS Measurements in the Northwest of Yunnan Province, China

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5408
Author(s):  
Keliang Zhang ◽  
Yuebing Wang ◽  
Weijun Gan ◽  
Shiming Liang
Keyword(s):  
Time Series ◽  
Yunnan Province ◽  
Vertical Component ◽  
Mass Loading ◽  
Gps Measurements ◽  
Local Effects ◽  
Common Mode ◽  
Common Mode Error ◽  
Grace Data ◽  
The Common

While seasonal hydrological mass loading, derived from Gravity Recovery and Climate Experiment (GRACE) measurements, shows coherent spatial patterns and is an important source for the common mode error (CME) in continuous global positioning system (cGPS) measurements in Yunnan, it is a challenge to quantify local effects and detailed changes in daily GPS measurements by using GRACE data due to its low time and spatial resolutions. In this study, we computed and compared two groups of CMEs for nine cGPS sites in the northwest Yunnan province; rCMEs were computed with the residual cGPS time series having high inter-station correlations, while oCMEs were computed with all the GPS time series. The rCMEs-filtered time series had smaller variances and larger root mean square (RMS) reductions than those that were oCMEs-filtered, and when the stations local effects were not removed, spurious transient-like signals occurred. Compared with hydrological mass loading (HYDL), its combination with non-tidal atmosphere pressure and ocean mass reached a better agreement with the CME in the vertical component, with the Nash–Sutcliffe efficiency (NSE) increasing from 0.28 to 0.55 and the RMS reduction increasing from 15.19% to 33.4%, respectively. Our results suggest that it is necessary to evaluate the inter-station correlation and remove the possible noisy stations before conducting CME filtering, and that one should carefully choose surface loading models to correct the raw cGPS time series if CME filtering is not conducted.

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