Spatial heterogeneity of nonlinear signals, background noise and vertical velocities in GNSS vertical time series across the Tibetan Plateau: A systematic analysis of multi-source loading corrections

Summary This study quantifies the spatial heterogeneity of nonlinear signals, background noise, and vertical velocities in GNSS vertical time series across the Tibetan Plateau (TP), using multi-source loading corrections to isolate tectonic deformation. We analyzed 20 years of GNSS data (2002–2021) from CMONOC and NGL networks, processed via GipsyX and referenced to ITRF2014. Non-tidal atmospheric (NTAL), oceanic (NTOL), and hydrological (HYDL) loading effects were applied utilizing operational models from GFZ and GRACE mascon data (CSR/JPL/GSFC), followed by common mode error (CME) filtering. The findings highlight significant spatial heterogeneity: Monsoon-dominated southern TP exhibits 10–20 per cent RMS reduction after non-tidal atmospheric-oceanic (AO) loading corrections, while northern TP shows minimal improvement (<10 per cent), highlighting non-atmospheric noise dominance. Integration of AO and GRACE-modeled hydrological (AOG) loading corrections outperform soil moisture-based models (AOH), achieving 25–35 per cent RMS reduction in glacier-covered Himalayas by resolving cryospheric mass loss. Spectral and principal component analysis (PCA) analyses confirm AOG’s superiority in suppressing interannual signals (PC1 variance: 62.7 per cent vs. AOH’s 60.3 per cent), particularly in monsoon-ENSO-affected regions. Noise modeling demonstrates high spatiotemporal correlations (63.1 per cent WN + FN in raw data), with flicker noise (FN > 5.2 mm) linked to seismic activity in southeastern TP and power-law noise (PL > 3.5 mm) to permafrost dynamics in the north. Post-AOG_CME processing simplifies noise structures (WN + GGM dominance: 32.9 per cent), reducing velocity uncertainties by 26.9 per cent and revealing a residual + 1.2 mm/yr uplift in the southern inner TP, indicative of mid-crustal flow. Persistent uncertainties (>0.55 mm/yr) along the Himalayan thrust front correlate with deep lithospheric boundaries. Our findings demonstrate the necessity of integrating GRACE-derived corrections with CME filtering to accurately delineate tectonic signals within the intricate suture zones of the TP, offering crucial insights into plateau-wide geodynamic processes.

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Publication Details

Journal
Geophysical Journal International
Published
2026-03-13
DOI
https://doi.org/10.1093/gji/ggag104
Primary Topic
GNSS positioning and interference
Type
article
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article

Spatial heterogeneity of nonlinear signals, background noise and vertical velocities in GNSS vertical time series across the Tibetan Plateau: A systematic analysis of multi-source loading corrections

Yuanjin Pan, Jiashuang Jiao, Meilin He, Qiwen Wu et al.
Geophysical Journal International
GNSS positioning and interference
article

Spatial heterogeneity of nonlinear signals, background noise and vertical velocities in GNSS vertical time series across the Tibetan Plateau: A systematic analysis of multi-source loading corrections

Yuanjin Pan, Jiashuang Jiao, Meilin He, Qiwen Wu, Jie Dong, Xiang Zhou, Yifei Lv, Tao Chen, Qingyun Yan
article en

Abstract

Summary This study quantifies the spatial heterogeneity of nonlinear signals, background noise, and vertical velocities in GNSS vertical time series across the Tibetan Plateau (TP), using multi-source loading corrections to isolate tectonic deformation. We analyzed 20 years of GNSS data (2002–2021) from CMONOC and NGL networks, processed via GipsyX and referenced to ITRF2014. Non-tidal atmospheric (NTAL), oceanic (NTOL), and hydrological (HYDL) loading effects were applied utilizing operational models from GFZ and GRACE mascon data (CSR/JPL/GSFC), followed by common mode error (CME) filtering. The findings highlight significant spatial heterogeneity: Monsoon-dominated southern TP exhibits 10–20 per cent RMS reduction after non-tidal atmospheric-oceanic (AO) loading corrections, while northern TP shows minimal improvement (<10 per cent), highlighting non-atmospheric noise dominance. Integration of AO and GRACE-modeled hydrological (AOG) loading corrections outperform soil moisture-based models (AOH), achieving 25–35 per cent RMS reduction in glacier-covered Himalayas by resolving cryospheric mass loss. Spectral and principal component analysis (PCA) analyses confirm AOG’s superiority in suppressing interannual signals (PC1 variance: 62.7 per cent vs. AOH’s 60.3 per cent), particularly in monsoon-ENSO-affected regions. Noise modeling demonstrates high spatiotemporal correlations (63.1 per cent WN + FN in raw data), with flicker noise (FN > 5.2 mm) linked to seismic activity in southeastern TP and power-law noise (PL > 3.5 mm) to permafrost dynamics in the north. Post-AOG_CME processing simplifies noise structures (WN + GGM dominance: 32.9 per cent), reducing velocity uncertainties by 26.9 per cent and revealing a residual + 1.2 mm/yr uplift in the southern inner TP, indicative of mid-crustal flow. Persistent uncertainties (>0.55 mm/yr) along the Himalayan thrust front correlate with deep lithospheric boundaries. Our findings demonstrate the necessity of integrating GRACE-derived corrections with CME filtering to accurately delineate tectonic signals within the intricate suture zones of the TP, offering crucial insights into plateau-wide geodynamic processes.

Geophysical Journal International
Nanjing University of Information Science and Technology (CN), Wuhan University (CN), Guilin University of Technology (CN), Institute of Geodesy and Geophysics (CN), Chinese Academy of Surveying and Mapping (CN), Center For Remote Sensing (United States) (US), State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN), Institute of Navigation (US)
Life below water
Openalex Percentile: Top 22%
GNSS positioning and interference
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