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@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}
}