Influences of crustal thickening in the Tibetan Plateau on loading modeling and inversion associated with water storage variation

Hansheng Wang, Longwei Xiang, Patrick Wu, Lulu Jia, Liming Jiang, Qiang Shen, Holger Steffen
2015 Geodesy and Geodynamics  
Average crustal structure a b s t r a c t We use the average crustal structure of the CRUST1.0 model for the Tibetan Plateau to establish a realistic earth model termed as TC1P, and data from the Global Land Data Assimilation System (GLDAS) hydrology model and Gravity Recovery and Climate Experiment (GRACE) data, to generate the hydrology signals assumed in this study. Modeling of surface radial displacements and gravity variation is performed using both TC1P and the global Preliminary
more » ... reliminary Reference Earth Model (PREM). Furthermore, inversions of the hydrology signals based on simulated Global Positioning System (GPS) and GRACE data are performed using PREM. Results show that crust in TC1P is harder and softer than that in PREM above and below a depth of 15 km, respectively, causing larger differences in the computed load Love numbers and loading Green's functions. When annual hydrology signals are assumed, the differences of the radial displacements are found to be as large as approximately 0.6 mm for the truncated degree of 180; while for hydrology-trend signals the differences are very small. When annual hydrology signals and the trends are assumed, the differences in the surface gravity variation are very small. It is considered that TC1P can be used to efficiently remove the hydrological effects on the monitoring of crustal movement. It was also found that when PREM is used inappropriately, the inversion of the hydrology signals from simulated annual GPS signals can only recover approximately 88.0% of the annual hydrology signals for the truncated degree of 180, and the inversion of hydrology signals from the simulated trend GPS signals can recover approximately 92.5% for the truncated degree of 90. However, when using the simulated GRACE data, it is possible to recover almost 100%. Therefore, in future, the TC1P model can be used in the inversions of
doi:10.1016/j.geog.2015.05.002 fatcat:lw4xybn6qbahtmzstfq34mzdpa