In southern Tibet, ongoing vertical and horizontal motions due to the collision between India and Eurasia are monitored by large numbers of global positioning system (GPS) continuous and campaign sites installed in the past decade. Displacements measured by GPS usually include tectonic deformation as well as non-tectonic, time-dependent signals. To estimate the regional long-term tectonic deformation using GPS more precisely, seasonal elastic deformation signals associated with surface loading must be removed from the observations. In this study, we focus on seasonal variation in vertical and horizontal motions of southern Tibet by performing a joint analysis of GRACE (Gravity Recovery and Climate Experiment) and GPS data, not only using continuous sites but also GPS campaign-mode sites. We found that the GPS-observed and GRACE-modeled seasonal oscillations are in good agreements, and a seasonal displacement model demonstrates that the main reason for seasonal variations in southern Tibet is from the summer monsoon and its precipitation. The biggest loading appears from July to August in the summer season. Vertical deformations observed by GPS and modeled by GRACE are two to three times larger than horizontal oscillations, and the north components demonstrate larger amplitudes than the east components. We corrected the GPS position time series using the GRACE-modeled seasonal variations, which gives significant reductions in the misfit and weighted root-mean-squares (WRMS). Misfit ( χ 2 divided by degree of freedom) reductions for campaign sites range between 20% and 56% for the vertical component, and are much smaller for the horizontal components. Moreover, time series of continuous GPS (cGPS) sites near the 2015 Nepal earthquakes must be corrected using appropriate models of seasonal loading for analyzing postseismic deformation to avoid biasing estimates of the postseismic relaxation.

In addition to studies of sea level change and mantle rheology, reliable Glacial Isostatic Adjustment (GIA) models are necessary as a background model to correct the widely used Gravity Recovery and Climate Experiment (GRACE) monthly gravity solutions to determine subsecular, nonviscous variations. Based on spherical harmonic analyses, we developed a method using degree-dependent weighting to assimilate the Global Positioning System (GPS) derived crustal uplift rates into GIA model predictions, in which the good global pattern of GIA model predictions and better local resolution of GPS solutions are both retained. Some systematic errors in global GPS uplift rates were also corrected during the spherical harmonic analyses. Further, we used the refined GIA uplift rates to infer the GIA-induced rates of Stokes coefficients (complete to degree/order 120) relying on the accurate relationship between GIA vertical surface deformation and gravitational potential changes. The results show notable improvements relative to GIA model outputs, and may serve as a GIA-correction model for GRACE time-variable gravity data.