Are thermal effects responsible for micron-level motions recorded at deep- and shallow-braced monuments in a short-baseline network at Yucca Mountain, Nevada?

Emma Hill, Jim Davis, Pedro Elosegui, Brian Wernicke, Eric Malikowski, and Nathan Niemi

Station REPO

Introduction

Baseline lengths

SLI4-SLID (Slide Mtn): 0 mREPO-REP2: ~10 mREPO-REP3: ~100 mREPO-REP4: ~1000 m

(Similar instrumentation)

Blue dots = BARGEN sites

Southern Nevada

•Desert environment

•‘Low’ tectonic rates

Data Processing

Data processed using GAMIT:

•Fixed orbits (IGS final)

•No TZD estimation

•L1-only position estimates

•Only look at baselines

Site-specific effects:

•Phase errors

•Un-modeled physical motions

Photo by Beth Bartel

Time Series - EastShort baseline

Annual cycles:0.03-0.54 mm

RMS:0.06-0.20 mm

Time series have been offset for illustration

RMS calculated about model of seasonal cycle

Zero baseline (ZBL)

RMS:0.03 mm

Time Series - NorthShort baseline

Annual cycles:0.02-0.19 mm

RMS:0.06-0.23 mm

Zero baseline (ZBL)

RMS:0.03 mm

Time Series - RadialShort baseline

Annual cycles:0.10-0.40 mm

RMS:0.12-0.73 mm

Zero baseline (ZBL)

RMS:0.08 mm

Temperature Data

Temperature data was obtained from the Beatty weather station (~25 km NW of Yucca Mountain)

Longer-period Signals

“Longer-period” signals (quasi-periodic) = Gaussian-filtered time series

REP2-REPO (~10 m baseline)

For illustration, the north component time series has been reversed (i.e. figure shows REPO-REP2 for the north)

Longer-period Signals

REP2-REPOREP4-REPO

Cross-correlation between temperature and GPS time series

The GPS seasonal cycles might lag those of the temperature data, but it is hard to detect using this method.

Correlation coefficients:

East = 0.74-0.98North = 0.45-0.93Radial = 0.55-0.76

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Monte Carlo Analysis

1. Add noise to GPS and temperature time series

2. Gaussian filter to get long- and short-period signals

3. Cross-correlation as before

4. Record peak correlation and corresponding time step

5. Repeat 5000 times

Longer-period SignalsMonte Carlo analysis (cross-correlation between temperature and GPS)

Indicates a lag (15-30 days) for many baselines in the horizontal component…

EAST: Similar results for all other baselines to REP4 (no lag for shorter baselines).

NORTH: Similar results for all other baselines to REPO (no correlation for other baselines).

Longer-period Signals… but we do not see a lag for the radial component.

The temperature ‘lags’ the GPS by >50 days.

Although there is a correlation for the radial, it looks like we are comparing two periodic signals that do not appear to be related.

Shorter-period Signals

“Shorter-period” signals = residuals from Gaussian-filtered time series

REP2-REPO (~10 m baseline)

Shorter-period SignalsREP2-REPO (~10m)REP3-REPO (~90 m)

Both regular cross-correlation… … and Monte Carlo technique indicate no lag time for short-period signals

Highest correlation (0.67) for the east component and baselines to REP2 (shallow-braced monument)

Cor

rela

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coef

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Thermal Expansion

•Monument (shorter-period?) - Different leg lengths and orientation - REP2 different type of pipe

•Cliff / Bedrock (longer-period?) - Dong et al. [2002] estimate ~45 day lag - Differential effects from orientation of ridgeline?

•Upper ground layers (shorter-period?) - Deep versus shallow-braced monuments

Red = longest legGreen = shortest leg

Several processes occurring at different time-scales?

Steep cliffGradual slope

•Something else?

Baseline-dependent Noise

~0.2 mm/km

~0.3 mm/km

~0.8 mm/km

Orbits? ~0.002 mm over 1 km (assuming 5 cm accuracy of IGS final orbits)

Troposphere?

Ionosphere?

Multipath?

(and what is causing the seasonal cycles in the radial?)

Tropospheric DelayREP4-REPO

When TZD parameters are estimated:

•Time series for horizontal components are very similar.

•But seasonal cycles in the radial component are reduced by ~50% for the longer baselines.

No TZD estimationWith TZD estimation

A mean has been removed from both time series

Ionospheric DelayWhen LC is used:

•Time series are considerably noisier and have visible receiver change offsets.

•Seasonal signals remain.

REP4-REPO L1-onlyLC

A mean has been removed from both time series

Differences between L1- and L2-only(Receiver changes at REP4, Jan and Nov 2007 (NetRS to 4000 SSI to NetRS)

REP4-REPO

Elevation-Angle Dependence

•Multipath?

•Antenna differences?

Time series from results using different elevation cutoff angles are offset.

Largest effect in radial component.

REP3-REP2 (~10m)REP4-REP2 (~900 m)

Y-axes have different scales

Conclusions•The sites appear to be very stable (RMS 0.06-0.73 mm). However, the time series do show both seasonal (annual amplitude 0.03-0.54 mm) and shorter-period signals.

•We suspect the horizontal seasonal signals may be related to bedrock thermal expansion (they are correlated with temperature, but with a lag time of ~15-30 days), but this is not the case for the radial component (instead atmosphere/multipath?).

•Shorter-period signals are correlated with temperature, mainly for the east component and particularly for REP2 (the short-braced monument). We suspect this could be thermal expansion of the monument or upper ground layers (or both).

Thanks!

Rates

REP3-REP2 (~90 m) (north) -0.07 ± 0.01 mm/yr

REP3-REPO (~100 m) (east) 0.06 ± 0.01 mm/yr

REP4-REP3 (~1 km) (north) -0.24 ± 0.01 mm/yr

Elevation-Angle Dependence

Reduction in annual amplitude for the radial component with higher elevation angle cutoffs.

Mean annual amplitude