Thu Apr 10, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Pan, Yuanjin, Shen, Wen-Bin, Ding, Hao, Hwang, Cheinway, Li, Jin, and Zhang, Tengxu, 2015. The Quasi-Biennial Vertical Oscillations at Global GPS Stations: Identification by Ensemble Empirical Mode Decomposition. Sensors, 15(10):26096–26114, doi:10.3390/s151026096.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2015Senso..1526096P,
author = {{Pan}, Yuanjin and {Shen}, Wen-Bin and {Ding}, Hao and {Hwang}, Cheinway and {Li}, Jin and {Zhang}, Tengxu},
title = "{The Quasi-Biennial Vertical Oscillations at Global GPS Stations: Identification by Ensemble Empirical Mode Decomposition}",
journal = {Sensors},
keywords = {GPS time series, ensemble empirical mode decomposition (EEMD), quasi-biennial vertical oscillations, loading effects},
year = 2015,
month = oct,
volume = {15},
number = {10},
pages = {26096-26114},
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.}",
doi = {10.3390/s151026096},
adsurl = {https://ui.adsabs.harvard.edu/abs/2015Senso..1526096P},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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Thu Apr 10, F. Flechtner