Fri Apr 10, F. Flechtner
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Pan, Yuanjin, Dong, Jie, He, Meilin, Yan, Qingyun, Wu, Qiwen, Chen, Tao, Jiao, Jiashuang, Lv, Yifei, and Zhou, Lv, 2026. 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. Geophysical Journal International, .
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026GeoJI.tmp...75P,
author = {{Pan}, Yuanjin and {Dong}, Jie and {He}, Meilin and {Yan}, Qingyun and {Wu}, Qiwen and {Chen}, Tao and {Jiao}, Jiashuang and {Lv}, Yifei and {Zhou}, Lv},
title = "{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}",
journal = {Geophysical Journal International},
year = 2026,
month = mar,
abstract = "{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.}",
doi = {10.1093/gji/ggag104},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026GeoJI.tmp...75P},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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