Characterization of site-specific GPS errors using a short-baseline network of braced monuments at Yucca Mountain
Full citation:
Hill, E. M., J. L. Davis, P. Elósegui, B. P. Wernicke, E. Malikowski, and N. A. Niemi (2009), Characterization of site-specific GPS errors using a short-baseline network of braced monuments at Yucca Mountain, southern Nevada, J. Geophys. Res., 114, B11402, doi:10.1029/2008JB006027.
Abstract
We use a short-baseline network of braced monuments to investigate site-specific GPS effects. The network has baseline lengths of 10, 100, and 1000 m. Baseline time series have root mean square (RMS) residuals, about a model for the seasonal cycle, of 0.05–0.24 mm for the horizontal components and 0.20Ð0.72 mm for the radial. Seasonal cycles occur, with amplitudes of 0.04–0.60 mm, even for the horizontal components and even for the shortest baselines. For many time series these lag seasonal cycles in local temperature measurements by 23Ð43 days. This could suggest that they are related to bedrock thermal expansion. Both shorter-period signals and seasonal cycles for shorter baselines to REP2, the one short-braced monument in our network, are correlated with temperature, with no lag time. Differences between REP2 and the other stations, which are deep-braced, should reflect processes occurring in the upper few meters of the ground. These correlations may be related to thermal expansion of these upper ground layers, and/or thermal expansion of the monuments themselves. Even over these short distances we see a systematic increase in RMS values with increasing baseline length. This, and the low RMS levels, suggests that site-specific effects are unlikely to be the limiting factor in the use of similar GPS sites for geophysical investigations.
Figures
High resolution images may be obtained by clicking the link above.
Figure 1.
Location of the GPS network at Yucca Mountain, southern Nevada. Black dots indicate BARGEN GPS stations. Contours on the detailed map represent height and are plotted with a 20 m interval.
Figure 2.
GPS time series for the east component of the baseline vector. For this, and all following time series plots, time series have been offset along the y axis by an arbitrary constant for clarity, error bars are based on 1-σ formal errors, and all baselines are oriented in a north to south direction. The time series labeled ZBL is, for comparison, a baseline time series for the zero-length baseline SLI4-SLID (see text). Temperature data from the Beatty weather station are also shown.
Figure 3.
Same as Figure 2 except for the north component.
Figure 4.
Same as Figure 2 except for the radial component. Note the change of scale along the y axis compared to Figures 2 and 3.
Figure 5.
RMS residuals (about a model of the seasonal cycle and linear term) for the GPS time series, as a function of baseline length. Note the change of scale, along the y axis, for the radial component.
Figure 6.
Shorter-period signals (residuals after removing a model for the seasonal cycle) for the temperature and REP2-REPO time series (the shortest, ˜10 m, baseline). For illustration purposes, the time series have been offset along the y axis.
Figure 7.
Example cross-correlation plots for residual temperature and GPS time series (after a model for the seasonal cycle has been removed). The plots show results for the shortest baselines, with REP2-REPO shown in black, REP3-REP2 shown in light gray and REP3-REPO in dark gray. The dotted line represents the 99% confidence level.