Transcript Document 7405660

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
Blue dots = BARGEN sites
SLI4-SLID (Slide Mtn): 0 m
REPO-REP2: ~10 m
REPO-REP3: ~100 m
REPO-REP4: ~1000 m
(Similar instrumentation)
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 - East
Short baseline
Annual cycles:
0.03-0.54 mm
RMS:
0.06-0.20 mm
Zero baseline (ZBL)
RMS:
0.03 mm
Time series have been
offset for illustration
RMS calculated about
model of seasonal cycle
Time Series - North
Short baseline
Annual cycles:
0.02-0.19 mm
RMS:
0.06-0.23 mm
Zero baseline (ZBL)
RMS:
0.03 mm
Time Series - Radial
Short 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
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 (quasi-periodic) = Gaussian-filtered time series
Longer-period Signals
Cross-correlation
between
temperature and
GPS time series
Correlation coefficients:
East = 0.74-0.98
North = 0.45-0.93
Radial = 0.55-0.76
REP2-REPO
REP4-REPO
The GPS seasonal cycles might lag
those of the temperature data, but it is
hard to detect using this method.
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 Signals
Monte Carlo analysis (cross-correlation between temperature and GPS)
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).
Indicates a lag (15-30 days) for many baselines in
the horizontal component…
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
REP2-REPO
(~10 m
baseline)
“Shorter-period” signals = residuals from Gaussian-filtered time series
Shorter-period Signals
REP2-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)
Thermal Expansion
Several processes occurring at different time-scales?
•Cliff / Bedrock (longer-period?)
- Dong et al. [2002] estimate ~45 day lag
- Differential effects from orientation of ridgeline?
Steep cliff
Gradual
slope
•Upper ground layers (shorter-period?)
- Deep versus shallow-braced monuments
•Monument (shorter-period?)
- Different leg lengths and orientation
- REP2 different type of pipe
•Something else?
Red = longest leg
Green = shortest leg
Baseline-dependent Noise
(and what is causing the seasonal cycles in the radial?)
~0.2 mm/km
Orbits?
~0.002 mm over 1 km
(assuming 5 cm accuracy of
IGS final orbits)
~0.3 mm/km
~0.8 mm/km
Troposphere?
Ionosphere?
Multipath?
Tropospheric Delay
REP4-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 estimation
With TZD estimation
A mean has been removed
from both time series
Ionospheric Delay
REP4-REPO
When LC is used:
L1-only
LC
•Time series are
considerably noisier and
have visible receiver
change offsets.
•Seasonal signals remain.
Differences between L1- and L2-only
(Receiver changes at REP4, Jan and Nov
2007 (NetRS to 4000 SSI to NetRS)
A mean has been removed
from both time series
REP4-REPO
Elevation-Angle Dependence
Time series from
results using different
elevation cutoff angles
are offset.
Largest effect in radial
component.
•Multipath?
•Antenna differences?
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-REPO (~100 m) (east)
0.06 ± 0.01 mm/yr
REP3-REP2 (~90 m) (north)
-0.07 ± 0.01 mm/yr
REP4-REP3 (~1 km) (north)
-0.24 ± 0.01 mm/yr
Elevation-Angle Dependence
Mean annual amplitude
Reduction in
annual amplitude
for the radial
component with
higher elevation
angle cutoffs.