are thermal effects responsible for micron-level motions recorded at deep- and shallow-braced...
DESCRIPTION
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 BartelTRANSCRIPT
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
Cor
rela
tion
coef
ficie
nt
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
tion
coef
ficie
nt
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