The Super Ground Motion Visualization (SGMV) depicts seismic waves rolling across the contiguous United States and Alaska after an earthquake. This time-space visualization of ground motion is created from a group of regular Ground Motion Visualizations (GMVs) for earthquakes in the Gulf of California. Time of these earthquakes coincide with the USArray Transportable Array (TA) stations deployment in the contiguous United States and Alaska (2004-2019).
The Transportable Array (TA) component of the USArray, a rolling array of about 400 broadband stations with station spacing of ~70km (~85km in Alaska), was deployed in the contiguous United States and Alaska. The array established its first footprint in the western United States in 2007 and rolled eastward and then moved to Alaska as the stations from the western edge of the array were removed and redeployed. Each station location was occupied for at least 18 months (Figure 1, click image to play an animation of TA deployment).
The ground motion data recorded by this very large aperture array, along with some other stations, are used to create Ground Motion Visualization (GMV) animations. GMV is a video-based IRIS Data Services (DS) data product that illustrates how seismic waves travel away from an earthquake location. In these animations, the normalized recorded wave amplitudes at each seismometer location is depicted using colored circles to represent seismic wave amplitudes, e.g., GMV for the 2013-10-19 M6.4 Gulf of California earthquake.
To visualize ground motion in an area larger than the TA footprint at the time of an earthquake, one must combine GMVs from multiple “similar” earthquakes. These earthquakes must have occurred during TA deployment and be about 1 to 1.5 years apart to capture ground motion at “all” TA station sites. Such a combined GMVs is dubbed a Super GMV (SGMV) and simulates a GMV as if all the station locations were occupied.
Super GMV—Gulf of California, 2007-2019
The 10 highlighted Gulf of California earthquakes in Figure 2 that occurred between September 1, 2007 and January 31, 2019, have similar focal mechanisms and qualify for production of SGMV (Figure 3). The steps to create an SGMV from these events are:
- Compute relative P-arrival time shift between events using P travel times for the US network station NEW (Newport, WA).
- For each station request 30 minutes of (BHZ or LHZ) data starting about 20 seconds before the event time (in case of multiple events for a single station, request data for the most recent event).
- Deconvolve responses (output as displacement), remove trend and filter traces between 500 and 50 seconds.
- Individually normalize traces to their maximum amplitude. Update time of each trace to be the offset time (in seconds) from event’s origin time.
- Shift traces based on the previously computed P-travel time differences (synchronize traces).
- Use the synchronized traces to produce the Super GMV (Figure 3, click image to play the Super GMV).
NOTE: In this SGMV (Figure 3), a group of stations that are located along the event’s nodal plane continue to show activity after the main seismic phases have passed through (on Figure 4 these stations are marked by a gray oval). This is an animation artifact caused by normalization of traces (step 4 above). In this SGMV, the affected stations are situated along the event’s nodal plane and as a result contain weaker primary seismic arrivals. For these stations, trace amplitude normalization in step 4 above would amplify noise and the stations would appear as active dots on the GMV/SGMV, even after the main seismic waves have passed through.
A 3-component super GMV (Figure 4) is also produced that plots vector field (quiver) with the direction and length of the tails representing direction and amplitude of the normalized horizontal ground motion at the corresponding location.
Citations and DOIs
- Trabant, C., A. R. Hutko, M. Bahavar, R. Karstens, T. Ahern and R. Aster (2012), Data products at the IRIS DMC: stepping-stones for research and other application, Seismological Research Letters, 83(6), 846:854. “doi: https://doi.org/10.1785/0220120032":http://srl.geoscienceworld.org/content/83/5/846
- Manochehr Bahavar, IRIS DMC
- 2007-2013 online
- extended to 2019
- added the 3-C visualization