Mass redistribution within the Earth system deforms the surface elastically. Loading theory allows us to predict loading induced displacement anywhere on the Earth’s surface using environmental loading models, e.g., Global Land Data Assimilation System. In addition, different publicly available loading products are available. However, there are differences among those products and the differences among the combinations of loading models cannot be ignored when precisions of better than 1 cm are required. Many scholars have applied these loading corrections to Global Navigation Satellite System (GNSS) time series from mainland China without considering or discussing the differences between the available models. Evaluating the effects of different loading products over this region is of paramount importance for accurately removing the loading signal. In this study, we investigate the performance of these different publicly available loading products on the scatter of GNSS time series from the Crustal Movement Observation Network of China. We concentrate on five different continental water storage loading models, six different non-tidal atmospheric loading models, and five different non-tidal oceanic loading models. We also investigate all the different combinations of loading products. The results show that the difference in RMS reduction can reach 20% in the vertical component depending on the loading correction applied. We then discuss the performance of different loading combinations and their effects on the noise characteristics of GNSS height time series and horizontal velocities. The results show that the loading products from NASA may be the best choice for corrections in mainland China. This conclusion could serve as an important reference for loading products users in this region.

Complex tectonic and non-tectonic movements exist in the Tianshan area. However, we have not acquired good knowledge of such movements yet. In this study, we combine Global Positioning System (GPS), the Gravity Recovery and Climate Experiment (GRACE) and Surface Loading Models (SLMs) data to study the seasonal vertical crustal displacements in the Tianshan area. The results show that all three datasets exhibit significant annual variations at all 26 local GPS stations. Correlation coefficients higher than 0.8 between the GRACE and GPS data were observed at 85% of the stations, and it became 92% when comparing GPS and SLMs. The Weighted Root Mean Squares (WRMS) reductions were 41% and 47% after removing the annual displacements of GRACE and SLMs from the GPS time series, respectively. The consistency between the GPS and SLMs data was higher than that between the GPS and GRACE data, which is mainly due to the dominant position of atmospheric loading in the study area. For the abnormal station XJYN (43°N, 81°E), the GPS time series showed an abnormal uplift from early 2013 to early 2015, but this not shown in the GRACE and SLMs results. We attribute this discrepancy to groundwater variations, which are not resolvable by GRACE and SLMs for small-scale regions.

The importance of studying the sea-level change (SLC) in Hong Kong (HK) is emphasized by factors related to high population density, intensive urban, and industrial development, particularly along the coast that involves a considerable landreclamation. To address this issue, we investigate the spatiotemporal characteristics of SLC in the HK territories by analyzing tide-gauge (TG) records collected from 1954 to 2019 and satellite-altimetry (SA) data from 1993 to 2019. The application of the ocean-tide and inverted barometer corrections to TG data substantially decreased uncertaintie by achieving a submillimeter accuracy. The SLC rates detected at six TG stations vary significantly even within this relatively small coastline. According to our estimates, the annual rates vary between 0.32 ± 0.51 and 4.19 ± 0.46 mm/yr from 1997 to 2019. These large differences are related to different patterns of ocean currents and the freshwater discharge in the Pearl River Estuary. The empirical orthogonal function analysis confirms the expected increasing rising in SLC with two anomalous periods during 2002-2003 and 2015-2016 that are likely attributed to the El Niño-Southern Oscillation (ENSO). SLCs are positively correlated with the ENSO index and ENSO precedes several months (normally 5 months) the interannual SLC. The analysis of the GPS trends reveals a prevailing subsidence in the HK territories, which aggravates the relative SLC estimates. Between 1997 and 2019, the absolute sea level raised at the annual rate of 3.17 ± 1.56 mm/yr (when using the GPS+TG) and 2.88 ± 0.59 mm/yr (when using SA observations).

We re-estimated the seismic moment of the 2011 M_w 9.0 Tohoku earthquake by using far-field coseismic displacements from 41 continuous GPS stations in Northeast Asia. In support of nearly 100 GPS campaign stations, we interpolate precise interseismic velocities at continuous GPS stations which are lacked of pre-seismic observations by using the Gaussian distance-based interpolation method, aiming to pursuiting more accurate post-seismic displacements. Then, we invert for the mantle viscosity and effective lithosphere thickness in the study area by employing nonlinear least squares fitting of the high signal-to-noise horizontal post-seismic displacements from 2.5 to 4.5 yr after the earthquake at 9 GPS stations distributed perpendicular to the fault plane of the earthquake, and the viscoelastic spherical Earth dislocation theory with modified fault slip model. The optimum solution of the inversion realizes the viscosity being 1.0× 10¹⁹ Pa s and the lithospheric thickness being 30 km. We find that the far-field post-seismic displacements caused by afterslip and mantle viscoelastic relaxation are approximately equal within 2.5 yr, and after 4.5 yr the cumulative effects of the latter component dominate the total far-field post-displacements. The result indicated that we cannot ignore the effects of mantle viscoelastic relaxation in the far field, even immediately after this earthquake. In addition, in the study of the far-field post-seismic displacements, we should take the signal-to-noise ratio of the GPS data into account with adequate observations to ensure the accuracy of the inversion.

Seasonal variations in the vertical Global Positioning System (GPS) time series are mainly caused by environmental loading, e.g., hydrological loading (HYDL), atmospheric loading (ATML), and nontidal oceanic loading (NTOL), which can be synthesized based on models developed by various institutions. A comprehensive comparison among these models is essential to extract reliable vertical deformation data, especially on a regional scale. In this study, we selected 4 HYDL, 5 ATML, 2 NTOL, and their 40 combined products to investigate their effects on seasonal variations in vertical GPS time series at 27 GPS stations in Yunnan, southwest China. These products were provided by the German Research Center for Geosciences (GFZ), School and Observatory of Earth Sciences (EOST), and International Mass Loading Service (IMLS). Furthermore, we used the Cross Wavelet Transform (XWT) method to analyze the relative phase relationship between the GPS and the environmental loading time series. Our result showed that the largest average Root-Mean-Square (RMS) reduction value was 1.32 mm after removing the deformation associated with 4 HYDL from the vertical GPS time series, whereas the RMS reductions after 5 ATML and 2 NTOL model corrections were negative at most stations in Yunnan. The average RMS reduction value of the optimal combination of environmental loading products was 1.24 mm, which was worse than the HYDL (IMLS_GEOSFPIT)-only correction, indicating that HYDL was the main factor responding for seasonal variations at most stations in Yunnan. The XWT result showed that HYDL also explained the annual variations reasonably. Our finding implies that HYDL (IMLS_GEOSFPIT) contributes the most to the environmental loading in Yunnan, and that the ATML and NTOL models used in this paper cannot be effective to correct seasonal variations.