作者: Yuanjin Pan , Wen-Bin Shen , Hao Ding , Cheinway Hwang , Jin Li
DOI: 10.3390/S151026096
关键词: Identification (information) 、 Geology 、 Atmosphere 、 Meteorology 、 Series (mathematics) 、 Mode (statistics) 、 Nonlinear system 、 Global Positioning System 、 Hilbert–Huang transform 、 Assisted GPS
摘要: Modeling nonlinear vertical components of a GPS time series is critical to separating sources contributing mass displacements. Improved precision in positioning at stations for velocity fields key resolving the mechanism certain geophysical phenomena. In this paper, we use ensemble empirical mode decomposition (EEMD) analyze daily 89 continuous stations, spanning from 2002 2013. EEMD decomposes into different intrinsic functions (IMFs), which are used identify kinds signals and secular terms. Our study suggests that records contain not only well-known (such as semi-annual annual signals) but also seldom-noted quasi-biennial oscillations (QBS). The explained by modeled loadings atmosphere, non-tidal hydrology deform surface around stations. addition, derived GRACE gravity changes consistent with deformations observations. By removing components, weighted root-mean-square (WRMS) variation reduced 7.1% 42.3%, especially, after seasonal QBO signals, average improvement percentages 25.6% 7.5%, respectively, suggesting it significant consider QBS improve observed deformations.