Seismogeodesy for rapid earthquake and
tsunami characterization
Yehuda Bock
Scripps Orbit and Permanent Array Center
Scripps Institution of Oceanography
READI & NOAA-NASA Tsunami
Early Warning Projects
IN32A: Near Real-Time Data for Earth Science and
Space Weather Applications
2016 Fall AGU Meeting, San Francisco
December 14, 2016
Current tsunami warning systems based on seismic data may
significantly underestimate the magnitude of a tsunamigenic
earthquake in the critical first few minutes of an event leading
to inaccurate forecasts for those in the epicentral region
Local tsunami warning system
Global & Regional Continuous GNSS Stations
Cascadia Subduction
Zone – Mw 9.0
earthquake & tsunami
similar to 2011 Great
Japan Earthquake
Advantages of Seismogeodesy
• Provides very high-rate displacement
and velocity waveforms
• Provides broadband instrument that
does not clip even in the near field of the
largest earthquake
• Reduces effects of baseline offsets in
doubly-integrated accelerometer data
and preserves static offset
• Not affected by magnitude saturation for
earthquakes greater than ~M7.5
• Like seismic data, able to detect P-wave
arrivals, not possible with GNSS data
alone
• Very well suited for accurate
earthquake early warning for local
>Mw4-5 earthquakes, and rapid
magnitude and fault mechanism for
local tsunami warning
1-10 Hz100-200 Hz
Precise Point
Positioning
(PPP)
Doubly
Integrate
Accelerations
100-200 Hz
1-10 Hz
PPP-ARA/
Kalman
Filter
Seismic Geodetic Seismogeodetic
P-wave?
yes
P-wave?
no
less precise
P-wave?
yes
Seismogeodesy: Optimal Integration of GNSS and Seismic Data
Seismogeodetic waveforms for two earthquakes
Broadband seismometer with no
clipping in the near-source region of
any magnitude earthquake
Bock et al., BSSA, 2011
Melgar et al., GRL, 2013
2011 Mw9.0 Tohoku-oki, Japan
2010 Mw7.2 El Mayor-Cucapah, Mexico
Verified seismogeodetic method for
earthquakes in California, Japan, Nepal and
Chile
Real-Time GNSS
Stations
Real-Time
Seismogeodetic
Stations
Real-Time Seismogeodetic Station – Mt. Soledad, La Jolla
Antenna/Radome
Monument
SIO MEMS
Accelerometer
Radio Antennas
Solar Panel
MEMS Met Sensors
Equipment
Enclosures:
GNSS, Geodetic
Module,
Batteries, Radio
Photo Courtesy D. Glen Offield
Earthquake Simulation
Figure from
Diego Melgar
UC Berkeley
Tsunam
i Am
plitu
de (m
)
Tsunami Simulation
Slide and movie prepared by Jessie Saunders
Local tsunami early warning simulation for Cascadia Mw8.5
earthquake using current West Coast GNSS stations
Ve
rtica
l Defo
rma
tion
(m)
Seafloor Deformation
Elements of Seismogeodetic Early Warning
Elements of Local Tsunami Warnings
• Detection & Location
• Rapid magnitude estimation
• Rapid earthquake fault mechanism
• Issue warning
• Refinement
• Fault slip model
• Seafloor motion model
• Tsunami model
• Prediction of runup & inundation
• Issue refined warning
NOAA-NASA Tsunami Warning ProjectNOAA National & Pacific Tsunami Warning Centers, Central Wash. U., Jet
Propulsion Lab, Scripps Inst. Oceanography, UC Berkeley, Univ. Washington
GPS displacements in
geoJSON format merged from
three independent analysis
centers: CWU, JPL and SIO
with fail-over from each center
Seismogeodetic displacements
and velocities in tracebuf2
format from SIO
PPP-ARA (Geng et al.)
GWORM system:
Data Entry
GWORM system:
Earthquake Detection &
Location
GWORM system:
Modeling
• STA/LTA algorithm to detect
P-waves from 100 Hz
accelerometer or
seismogeodetic velocity
data.
• Algorithm is implemented at
individual stations, thus
thresholds can be adjusted
to reflect noise
characteristics of the
station.
• Detections at each station
are corroborated by
additional stations. Once 4
stations indicate a detection,
the subsequent
seismogeodetic modules
are triggered.
Seismogeodetic Earthquake Picking
2016 Mw5.2 Borrego Springs Earthquake
Prepared by Dara Goldberg
Pick_sg
Earthquake Early Warning:
2016 Mw5.2 Borrego Springs Earthquake
Prepared by Dara Goldberg
Hypo_sg
Earthquake Magnitude Scaling Modules
These methods require accurate, high-rate displacement data, which are difficult to
obtain in the near-field in real time using traditional seismic instruments that suffer
from magnitude saturation
Figure from
Melgar et al. (2015)
PGD scaling, all components, GNSS only
P-wave displacement
amplitude (Pd)
Peak Ground
Displacement (PGD)
Figure from
Crowell et al. (2013)
Pd scaling
horizontal components,
seismogeodetic
Modified by
Jessie Saunders
GNSS only sensitivity ~ 15 mm
Seismogeodetic SIO GAP sensitivity ~ 8 mm
Mw_PGDMw_Pd
Line source rapid centroid moment tensor solution: fastCMT
Updated until shaking is complete and final coseismic offset is determined. fastCMT produces
accurate focal mechanisms within 2-3 minutes of earthquake onset. It provides information
about faulting mechanism, and is indicative of the likelihood that an event could be
tsunamigenic. Prepared by Dara Goldberg
2010 Mw 7.2 El Mayor-Cucapah
Lat = 32.39 Lon = -115.68 Depth = 4 km
Moment Tensor (Scale 1x10^19 Nm)
Mrr = -1.016 Mtt = -4.254 Mpp = 5.270
Mrt = 1.153 Mrp = -3.949 Mtp = -0.207
Best Double Couple
Plane Strike Dip Rake
NP1 228 52 0
NP2 318 90 217
2011 Mw 9.0 Tohoku-oki
Lat = 42.20 Lon =
144.00
Depth = 48
km
Moment Tensor (Scale 1x10^21 Nm)
Mrr = 1.001 Mtt = -0.463 Mpp = -0.539
Mrt = 1.353 Mrp = 1.871 Mtp = 0.518
Best Double Couple
Plane Strike Dip Rake
NP1 229 12 103
NP2 36 78 87
fastCMT_sg
Finite Fault Slip Model Modules
Total slip model for the
Mw9.0 Tohoku-oki
earthquake. Dashed lines
are depth contours of the
subducting slab in km.
(a) Model from land-based
seismogeodetic data only
(b) Estimate sea floor
deformation
(c) Model from
seismogeodetic and wave
gauge data (GNSS buoys
and ocean-bottom
pressure sensors) Static model
available within
about 3 minutes
Static model available
once wave gauge data
are ingested
FaultSlip_sg
Melgar and Bock, JGR, 2015
Seismogeodetic System: Land & Ocean
Earthquake models
Seafloor deformation
Tsunami propagation
Melgar & Bock, JGR, 2013,2015
100km
10km
Sendai
BayFukushima
Blue dots on shore denote tsunami inundation
measured by post-event land surveys showing
good agreement between the model and land
surveys (Melgar and Bock, JGR, 2015)
Tsunami Model for the 2011 Mw9.0 Tohoku-oki Earthquake
Sendai
Bay
Tsunami_sg
Accurate but time consuming. Simpler system
published by Melgar et al. in GRL – suitable for
real-time operations.
Seismogeodesy for rapid earthquake and
tsunami characterization
IN32A: Near Real-Time Data for Earth Science and
Space Weather Applications
2016 Fall AGU Meeting
December 14, 2016
Thank You!
Questions?