The quasi-biennial vertical oscillations at global GPS stations: Identification by ensemble empirical mode decomposition

Yuanjin Pan, Wen Bin Shen*, Hao Ding, Chein-way Hwang, Jin Li, Tengxu Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Modeling nonlinear vertical components of a GPS time series is critical to separating sources contributing to mass displacements. Improved vertical precision in GPS positioning at stations for velocity fields is key to resolving the mechanism of certain geophysical phenomena. In this paper, we use ensemble empirical mode decomposition (EEMD) to analyze the daily GPS time series at 89 continuous GPS stations, spanning from 2002 to 2013. EEMD decomposes a GPS time series into different intrinsic mode functions (IMFs), which are used to identify different kinds of signals and secular terms. Our study suggests that the GPS records contain not only the well-known signals (such as semi-annual and annual signals) but also the seldom-noted quasi-biennial oscillations (QBS). The quasi-biennial signals are explained by modeled loadings of atmosphere, non-tidal and hydrology that deform the surface around the GPS stations. In addition, the loadings derived from GRACE gravity changes are also consistent with the quasi-biennial deformations derived from the GPS observations. By removing the modeled components, the weighted root-mean-square (WRMS) variation of the GPS time series is reduced by 7.1% to 42.3%, and especially, after removing the seasonal and QBO signals, the average improvement percentages for seasonal and QBO signals are 25.6% and 7.5%, respectively, suggesting that it is significant to consider the QBS signals in the GPS records to improve the observed vertical deformations.

Original languageEnglish
Pages (from-to)26096-26114
Number of pages19
JournalSensors (Switzerland)
Volume15
Issue number10
DOIs
StatePublished - 14 Oct 2015

Keywords

  • Ensemble empirical mode decomposition (EEMD)
  • GPS time series
  • Loading effects
  • Quasi-biennial vertical oscillations

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