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?