Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China

Peng, Yingguo; Li, Zhao; Jiang, Weiping; Ma, Yi; Chen, Wu; Sneeuw, Nico

doi:10.3390/rs10060958

Cited by 23 publications

(13 citation statements)

References 57 publications

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“…Moreover, unmodeled nonstationary signals will also have an effect on velocities and their uncertainties [35,52]. Filtering unmodeled CMCs will not only improve the precision of the velocity due to the interannual elastic loading correction, but also improve the signal-to-noise ratio of the velocity [16,53]. Therefore, the CMCs in GPS time series should be considered when estimating the ground velocity using regionally dense GPS sites.…”

Section: Velocities and Uncertainties Of The Etpmentioning

confidence: 99%

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

et al. 2019

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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.

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Section: Velocities and Uncertainties Of The Etpmentioning

confidence: 99%

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

et al. 2019

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“…The nonlinear variations of GPS coordinate time series contain a variety of geophysical signals. Current research focuses are on the displacements of GPS stations under the impact of surface environmental loadings such as atmospheric pressure, oceanic tide and hydrology [19,39]. The displacements caused by environmental loadings in vertical component (Up) are much bigger than that in horizontal components (North and East).…”

Section: Relevant Geophysical Signalsmentioning

confidence: 99%

“…Effective extraction of CMC is quite beneficial in improving the accuracy of coordinate time series, quantifying the station displacement caused by geophysical signals and accurately describing the features of regional earth surface deformation. As a result, recent years have seen CMC become a heated research topic [9][10][11][12][13][14][15][16][17][18][19]. Jiang et al [20] analyzed 29 stations in the Chinese CORS network and extracted the CMC series by using a PCA method.…”

Section: Introductionmentioning

confidence: 99%

A Sub-Regional Extraction Method of Common Mode Components from IGS and CMONOC Stations in China

Nie

Liu

et al. 2019

Remote Sensing

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There is always a need to extract more accurate regional common mode component (CMC) series from coordinate time series of Global Positioning System (GPS) stations, which would be of great benefit to describe the deformation features of the Earth’s surface with more reliability. For this purpose, this paper combines all 11 International Global Navigation Satellite System (GNSS) Service (IGS) stations in China with over 70 stations selected from the Crustal Movement Observation Network of China (CMONOC) to compute CMC series of IGS stations by using a principal component analysis (PCA) method under cases of one whole region and eight sub-regions. The comparison results show that the percentage of first-order principal component (PC1) in North, East and Up components increase by 10.8%, 16.1% and 25.1%, respectively, after dividing the whole China region into eight sub-regions. Meanwhile, Root Mean Square (RMS) reduction rates of residual series that have removed CMC also improve obviously after partitioning. In addition, we compute displacements of these IGS stations caused by environmental loadings (including atmospheric pressure loading, non-tidal oceanic loading and hydrological loading) to analyze their contributions to the non-linear variation in GPS coordinate time series. The comparison result shows that the method we raise, PCA filtering in sub-regions, performs better than the environmental loading corrections (ELCs) in improving the signal-to-noise ratio (SNR) of GPS coordinate time series. This paper raises new criteria for selecting appropriate CMONOC stations around IGS stations when computing sub-regional CMC, involving three criteria of interstation distance, geology and self-condition of stations themselves. According to experiments, these criteria are implemental and effective in selecting suitable stations, by which to extract sub-regional CMC with higher accuracy.

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“…In recent two decades, many researchers have undertaken various topics on earth science by means of Global Positioning System (GPS) time series obtained from continuous GPS (CGPS) stations, including analysis of periodic signals [1][2][3][4][5], detection of stochastic models [6][7][8][9], spatial filtering methods [10][11][12][13][14], and surface loading models (SLMs) [15][16][17][18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

“…In the last two years, the effect of ELCs is still a heated topic. Yuan et al [22] analyzed 235 Crustal Movement Observation Network of China (CMONOC) stations for the nonlinear motion at GPS stations. They calculated the displacement series caused by environmental loadings (including atmospheric loading, nontidal oceanic loading and hydrological loading) and found that after ELCs, the average root mean square (RMS) of GPS height time series could be reduced by~20%.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of the Effect of the Loading Series from GFZ and EOST on Long-Term GPS Height Time Series

Nie

Meng

et al. 2020

Remote Sensing

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In order to investigate the effect of different loading models on the nonlinear variations in Global Positioning System (GPS) height time series, the characteristics of annual signals (amplitude and phase) of GPS time series, loading series from Deutsche GeoForschungsZentrum, Germany (GFZ) and School and Observatory of Earth Sciences, France (EOST) at 633 global GPS stations are processed and analyzed. The change characteristics of the root mean square (RMS) reduction rate, annual amplitude and phase of GPS time series after environmental loading corrections (ELCs) are then detected. Results show that ELCs have a positive effect on the reduction in the nonlinear deformation contained in most GPS stations around the world. RMS reduction rates are positive at 82.6% stations after GFZ correction and 87.4% after EOST correction, and the average reduction rates of all stations are 10.6% and 15.4%, respectively. As for the environmental loading series from GFZ and EOST, their average annual amplitudes are 2.7 and 3.1 mm, which explains ~40% annual amplitude of GPS height time series (7.2 mm). Further analysis of some specific stations indicates that the annual phase difference between GPS height time series and the environmental loading series is an important reason that affects the reduction rates of the RMS and annual amplitude. The linear relationship between the annual phase difference and the annual amplitude reduction rate is significant. The linear fitting results show that when there is no annual phase difference between GPS and loading series, the reduction rates of the RMS and annual amplitude will increase to the maximum of 15.6% and 41.6% for GFZ, and 22.0% and 46.6% for EOST.

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Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China

Cited by 23 publications

References 57 publications

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

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

A Sub-Regional Extraction Method of Common Mode Components from IGS and CMONOC Stations in China

Comparative Analysis of the Effect of the Loading Series from GFZ and EOST on Long-Term GPS Height Time Series

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