Offsets in Global Positioning System time series

Abstract

[1] Site velocities are a common product of continuous Global Positioning System (CGPS) networks. Estimation of site velocities from their time series can be biased if offsets are present. If left uncorrected, offsets can dominate velocity uncertainties. Artificial (nontectonic) discontinuities may arise from environmental and equipment changes or human intervention and error. Analysis of present GPS data sets reveals that on a component by component basis, one offset occurs every 9 years, although it could be as frequent as one offset every 2 years. The effect offset estimation has on rate uncertainty depends on the noise characteristics in the series. If the noise is white, then estimating a single offset in the center of the series doubles the uncertainty. If the noise is random walk, then neither the position nor the number of offsets in the time series seriously alters the rate uncertainty. Undetected offsets in the time series mimic random walk noise. If an offset detection algorithm is implemented, then there is threshold size below which the algorithm can select the wrong offset epoch. Offset position uncertainty increases as offset size decreases. However, small offset position uncertainties will still result in lower rate uncertainties with respect to undetected offsets. Despite the appeal of estimating offsets by detrending and averaging data either side of the discontinuity, such a strategy only serves to increase the rate and offset uncertainties. The best strategy is still to use the maximum likelihood estimator to simultaneously estimate the linear parameters and the noise components.

Improved Constraints on Models of Glacial Isostatic Adjustment: A Review of the Contribution of Ground-Based Geodetic Observations

“…These artificial offsets can be due to environmental, equipment malfunction, equipment change and even human error. The effect, whether the offset is known or unknown, is always to increase the uncertainty of the estimated velocity (Williams 2003). The switch from combining velocities to produce ITRF2000 to combining site time series to produce ITRF2005 (Altamimi et al 2007) resulted in a more reliable frame because of the ability to consistently treat linear site offsets.…”

The influence of seasonal signals on the estimation of the tectonic motion in short continuous GPS time-series

“…The reason why the noise properties vary over time is unknown and deserves further investigation. One possible explanation could be the existence of small offsets which have not been detected but are altering the noise properties (Williams, 2003a).…”

Noise characteristics in Zenith Total Delay from homogeneously reprocessed GPS time series

“…While the temporal consistency of the time series is addressed by keeping the bias models and processing methodology the same for the whole data period, the GPS position 5 time series are often subjected to discontinuities which are either due to real position changes or other factors that do not necessarily reflect real geophysical events. Such uncorrected discontinuities are known to adversely affect trend estimates of the concerned position time series (Williams et al, 2003a;Thomas et al, 2011;Griffiths and Ray, 2015) and introduce random-walk noise into the time series (Williams, 2003b;Santamaria-Gómez et al, 2011).…”

“…the need for 10 identifying and correcting discontinuities, is necessary (Vey et al, 2009;Gazeaux et al, 2011;Ostini, 2012). While automated change detection methods have also been dedicated to GPS time series (Williams et al, 2003a;Khodabandeh et al, 2011;Gazeaux et al, 2013), identifying all discontinuities still requires significant visual inspection and manual intervention. For ZTD time series the detection of all discontinuities is particularly crucial as in most cases the climate signal may be comparable in size to the magnitude of the amplitudes of the discontinuities.…”