Moo, Whoosh, Vroom, Beep, Twinkle: Identifying Non

Moo, Whoosh, Vroom, Beep, Twinkle: Identifying Non-Seismic Signals Recorded by
EarthScope’s USArray Transportable Array (TA) Stations
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Debi Kilb , Aaron A. Velasco and Kristine Pankow
1. Scripps Institution of Oceanography, UC San Diego, San Diego, CA, United States; 2. University of Texas at El Paso, El Paso, TX, United States; 3. University of Utah
Current Goal: Generate a detection catalog that will allow us to estimate a
background detection rate at each station. For each individual station also
identify times of significant rate changes, which could potentially be an
indication of remote triggering.
Station UPAO: Summer
Figure 2: Example of results from
our detection algorithm. Within
the 5Hz high pass filtered
seismogram (yellow) our
automatic detection algorithm
correctly identifies some
local/regional events (red-flag
markers).
Station UPAO: Winter
Station: UPAO: Stacked data from 37 mainschoks
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✓ Time of day histograms show most detections are in the daytime.
✓ Waveform data shows detections are likely not seismic.
✓ Do not select this station for use in our initial beta-testing (i.e., detections likely non-seimsic).
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Select this station for use in our initial beta-testing (i.e., detections likely seismic).
Airports
Small uncataloged local earthquakes
M7.3 El Salvador
Station R11A
Station: CIA: Stacked data from 37 mainschoks
Station: NEE2: Stacked data from 37 mainschoks
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✓ Time of day histograms show most detections are in the daytime.
✓ Waveform data shows detections are likely not seismic.
✓ Do not select this station for use in our initial beta-testing (i.e., detections likely non-seismic).
Love
Select this station for use in our initial beta-testing (i.e., detections likely seismic).
Farms (e.g., cows)
Rayleigh
Shuttle Launch
Station R11A
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Station: R11A: Stacked data from 37 mainschoks
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Figure 3: High pass filtered (top) seismograms for
USArray station R11A. Zoom of raw and filtered Chile
seismograms (bottom) that show local and regional
events at the time of the S-wave and Love-wave arrival
from the teleseismic event.
Time of day histograms show most detections are in the daytime.
Waveform data shows a detections are likely not seismic.
Do not select this station for use in our initial beta-testing (i.e., detections likely non-seismic).
✓ Select this station for use in our initial beta-testing (i.e., detections likely seismic).
Station: Z40A: Stacked data from 37 mainschoks
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Station Z40A
Station Z40A
✓ Time of day histograms show most detections are in the daytime.
✓ Waveform data shows detections are likely not seismic.
✓ Do not select this station for use in our initial beta-testing (i.e., detections likely non-seismic).
Select this station for use in our initial beta-testing (i.e., detections likely seismic).
Traffic
Summary
Our aim is to initially avoid using stations with obvious
non-seismic detections, opting instead to use only the cleanest
data (i.e., station R11A) to first test our algorithms. After testing
with the cleanest data we will subsequently move on and process
data that is more challenging to interpret.
Acknowledgements
Today’s Goal: Identify useful data
Funding for this work provided by NSF EAR-1053376 grant: Collaborative Research: Systematic Analysis
of Dynamic Earthquake Triggering Using the USArray Data. This work benefited from the REV
web-based seismogram viewing tool (http://rev.seis.sc.edu/index.html), which is an interactive data view
product funded by NSF, USC, and IRIS.
Station: SOL: Stacked data from 37 mainschoks
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Some data is not useful for our purposes because the small signals we
want to study are obscured. To identify non-optimal stations we create
time-of-day histograms of the detections for each station and also
examine the characteristics of a randomly selected suite of 24-hours of
waveform data.
Local/regional Events
Station CIA
Station NEE2
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We use the Antelope software’s short-term average (STA) to
long-term-average (LTA) ratio algorithm to create a catalog of “detections” at
each station as a function of time (HP at 5 Hz; STA = 8 s; LTA = 80 s; designed
for local events). We define a detection as simply a signal above the noise
level, which may, or may not, be an earthquake. We assume a strong change
in the rate of detections during, and/or following, the passage of surface
waves from a large teleseismic event could be indicative of remote
triggering.
Example: Chile M=8.8 2010
High Pass at 5 Hz, No Instrument Correction
Image from: http://anf.ucsd.edu/stations/deployment_history.php
What is a ‘detection’?
Troy Canyon (R11A)
Image from: http://anf.ucsd.edu/cacheimages/station_photos/R11A_top_pick_395111816.jpg
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Figure 1: Image of a USArray cumulative station deployment map. Stations are colorcoded according to their network provider (see
legend). On the first day of each month, maps
similar to this are automatically created based
on data acquired in the previous month. The
Transportable Array component of the
USArray/EarthScope project is a rolling array of
400 broadband stations deployed on a uniform 70-km grid.
Example of an Optimal Station
Air Circulation System
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Long Range Goal: Investigate if there exists a minimum dynamic stress
threshold (i.e., in amplitude, frequency or both) required to trigger remote
earthquakes using data collected by >400 stations in EarthScope’s USArray
Transportable Array (USArray TA) network (Figure 1), supplemented by data
from ~100 local seismic network stations when available.
Non-Optimal Stations
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Introduction
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Station SOL
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Station SOL
Good News: Our detection algorithm
correctly ignores signals caused by traffic as
evidenced by the minimal detections during the
daytime at station SOL.
Time of day histograms show most detections are in the daytime.
Waveform data shows detections are likely not seismic.
✓ Do not select this station for use in our initial beta-testing (i.e., detections likely non-seismic).
Select this station for use in our initial beta-testing (i.e., detections likely seismic).