Seafloor geodetic observationsin the Japan Trench subduction zone
Ryota Hino
Graduate School of Science, TOHOKU UNIV.

2011 Tohoku-Oki Earthquake

Japan Metrological Agency

March 11, 2011, 14:46 M9.0
Strong ground shaking (intensity 7 in JMA scale),causing severe damage in broad area

Tall tsunami (over 30 m) causing devastating
damage along the coastal area2

Interplate earthquake in subduction zone
A subducting oceanic plate drags an overriding continental plate.
Shear stress builds up along the plate boundary until the stress level exceeds shear strength.
When the stress exceeds the strength, a sudden slip happens on the boundary to cause an earthquake
and a tsunami.

気象庁

Coseismic displacement by 2011 Tohoku-Oki Earthquake
GNSS MaxMax.
= 31 mMax.
= 5.3 mKido+ [2011]
Displacements on the seafloor by GNSS-A

GSJ
Displacements on land by GNSS

Observed coseismic displacements
ー uniformly eastward both in on- and offshore regions
ー increase monotonically toward the east
ー largest at the seafloor station closest to the Japan Trenchー decrease towards the north and south, in offshore region

Earthquake & Tsunami
Deformation of sea-surface
Propagation of tsunami

Deformation of seafloor
Propagation of shaking
Slip on a fault in the earth

by Dr. Sato at NIED

Vertical coseismic displacement by
Tohoku-Oki Earthquake
Observed coseismic displacements
ー large uplift near the trenchー small subsidence on the landward side of the offshore
as well as in all the onshore area

海溝寄り：
地震活動が低かった
たくさん動いた→ ずっと蓄えた歪を
東北沖地震で解消
宮城県沖：
普段から地震が多い
あまり動かなかった→ 普段の地震で少しずつ歪を解消→ それでも残った歪を
東北沖地震で解消
Hino [2013]

Slip distribution estimated by geodetic observations
w/o offshore data

Iinuma+ [2011]

With onshore data

Iinuma+ [2012]

Journal of Geophysical Research: Solid Earth

Principle of GNSS-A survey

Honsho et al.

10.1002/2017JB014733

POC Application to Travel-Tim

crustal movement. First, we explain an inversion method using the N

Waveformof
to determine
the position of individual PXPs for a particular campaig
signalthe method is extended to a multiple campaign analy
Acoustic
Second,(Matsumoto et al., 2008), where the array geometry and array displa
X-cor. mentsofbetween campaigns are determined simultaneously. We th
T/R waveforms
demonstrate the application of these methods to actual data obtainfrom the region off northeast Japan. We also discuss the validity aJournalof GeophysicalRes
meritsFIGURE
of 1theformulation
the (A)NTD.
| Reference
acoustic signal used for ourusing
GNSS-A observations.
Waveform of the beginning
5 ms of the entire, 25.4[2021]
ms-long signal. The carrie
Honsho+r (t )

frequency is 10 kHz. (B) Auto-correlation of the reference signal.

PS
Ks

i gn

al

Two-way time
2. Outline of GPS-Acoustic Observation and Analyses
T t = f p , r (t ), c ( z ) + d F (t )p1() ( i)0pi = pi0 +isd shownp
The GPS-acoustic observation system
schematically in Figure
T ( t ) = f (d p, r (t ),
c
(
z
)
+
d
F
(
t
)
)
0
10.1002/2017JB014733
Journal of Geophysical Research: Solid Earthp4

p2“Mirror” responsep3

Figure 1. Schematic illustration of the GPS-acoustic
observation
Honsho+[2017; system.
2019]

Because electromagnetic waves propagate little in water, a ves
correction term
Motionof onarrayplacedthe sea surface serves as a relay element to communica
the acoustic signals from the seaﬂoor PXPs. In our system, three to
PXPs are settled on the seaﬂoor to form a square or triangle with a hizontal dimension comparable to the water depth. Onsite observatio
are carried out regularly a few times a year for each site. Duringobservation campaign, acoustic ranging is continued over a certain p( z)
iod ofc0time,and a relatively large number (several thousands) of trav
Figure 4. Illustration of ranging at time ti in a four‐precision acoustic transtimeSounddata
arecollected.
Thisponder
large
data
set isdesirable
inin orderto reduarray.
The example
indicates
the quantities
the observation
speed
profileFIGURE 2 | Examplesof actualcross-correlation between the reference and returned signals. (A) Part of ship tracks (small gray dots) of a campaign(14).
benchmark, which is settled on the seaﬂoor at ∼4.8 km
depth
and consists of four transponders (gray or orange circles) forming a ∼3.3 km square
the effectof random errors equation
inwaterthe
data and cancel out the effect of pcorrelations of the reference and returned signals from the eastern transponder (orange). The numbers in black bold indicate ship’s positions shown by crvert

Displacement time series
onshore GNSS vs offshore GNSS-A
Page 3 of 27

onshore station

her

rth
on
or1m
maons
hin
tato
NSS
0.5m
the
rea
ditaherTheaki
thefses
0.5m
ore,
5 yearsbyFig. 1 GNSS observation stations considered in this study. Fourthestations marked as red squares were used for predicting the time
kuseries. Fourstations markeddeformation
as blue squares areusing
used in Figs.
nd predicted
postseismic
the2,functional model. Deformation is presented for the four stations of a3, and 6, and the stations marked as black squares are the otherenai,
c Nadachi,
andin thisd Shizugawa(Fig. 1). land,
Theandthreecomponents of east–west (EW), north–south (NS), and up–down (UD) were
stations usedstudy. Gray area represents
a seafloor
bu;
topographic
map
is
depicted.
Gray
arrow
depictsthehorizontal
onthe day after the 2011 Tohoku-Oki earthquake to 2026.5. Black dots represent the daily observations. Dashed lines
of from
displacement rate observed at the sea bottom after the 2011
ter of predictedesvalues foreachfitting
periodcontours(2.0, 3.9,
5.8, and 8.9 years)
Tohoku-Oki earthquake(Honsho
et al.
2019). Isodepthoffor
the Pacific slab were estimated by Kita et al. (2010), Nakajima andGNS

offshore station

G01
1m

0.5m

Fujiwara+ [2022]

Tomita+ [2022]

Hasegawa (2006), and Nakajima et al. (2009)

5 years

Journal of Geophysical Research: Solid Earth

Causes of accuracy degradation in GNSS-A

10.1002/2017JB014733

T ( t )crustal= f (movement.
pi , r (t ), c0First,( z ) )we+ dexplain
F (t , anpi ,inversionr (t )) method using the N

PS
Ks

i gn

al

r (t )“Mirror” response
Honsho+ [2017]

Figure 1. Schematic illustration of the GPS-acoustic observation system.

to determine the position of individual PXPs for a particular campaig
Correction
term d Fisdepends
Second,the method
extendedalso
to ona multiple campaign analy
the positions
the shipandtransponders.
(Matsumoto
et al.,of
2008),
wherethethearraygeometry and array displa
ments between campaigns are determined simultaneously. We th
pi thesedemonstrate
the applicationto actual data obtain
The trade-off
between of
and dmethods
F is inevitablefromthe region
off northeastwith
Japan.
We alsothe validity ain GNSS-A
observations
limitedraydiscuss
coverage.
merits of the formulation using the NTD.

2. Outline of GPS-Acoustic Observation and Analyses

The GPS-acoustic observation system is shown schematically in Figure
Because electromagnetic waves propagate little in water, a ves
placed on the sea surface serves as a relay element to communica
the acoustic signals from the seaﬂoor PXPs. In our system, three to
PXPs are settled on the seaﬂoor to form a square or triangle with a hizontal dimension comparable to the water depth. Onsite observatio
are carried out regularly a few times a year for each site. During
acoustic
rangingcan
is continued
over a certain p
Inobservation
GNSS, 3-Dcampaign,atmosphericstructurebe estimatediod of time,and asatellite/observatory
relatively large numbernetworks.
(several thousands) of trav
owing
to densetime data are collected. This large data set is desirable in order to redu
the effect of random errors in the data and cancel out the effect of p

Ocean bottom pressure (OBP) observations
Aoi et al. Earth, Planets and Space

Changes in sea-surface level(2020) 72:126

Page 3 of 31

Changes in seafloor levelrise
sea-surface
fall
Pressure increase (+DP)-D P

upliftPressure decrease (-DP)+DP

seafloor
subsidence

Fig. 1 MOWLAS station distribution for the three regions of the inset map. SM and PG indicate seismometers and pressure gauges, respectively

volcanoes, and the 15 of the 16 volcanoes excluding Ioto
are included in the 25 volcanoes selected by the Committee on Earthquake and Volcano, Subdivision on Geodesy
and Geophysics of the Council for Science and Technology of the Government of Japan for particularly extensive
observation.
Regarding earthquake and tsunami seafloor observations, while dense networks of earthquake observation

Aoi+ [2021]

in terms of lead time and precision for tsunami height
estimations, one of the most important lessons learned
from the 2011 Tohoku earthquake and tsunami is that
there was an insufficient number of offshore observation stations. At that time, cable-type seafloor observation systems for earthquakes and tsunamis had been
11
installed offshore by JMA, one off Tokai in 1979, one off
Boso Peninsula in 1985, and one off Tonankai in 2008.

Constituents of OBP recordspB (t ) = pB + DpB (t )DpB (t )mean~ 105 hPa

DpT (t )1 hPa 〜 1 cm H2O( µ depth of deployment)

DpB (t ) = DpC (t ) + DpO (t ) + DpI (t )DpO (t )geodetic
signal~ 1 hPa

non-tidal
fluctuation~ 10 hPa

instrumental
drift~ 10 hPa/year+DpT (t ) + Dp A (t )DpI (t )Dpc (t )atmospherictidal
fluctuation pressurepB ~ 10 ppm~ 100 hPa=0
(IB assumption)→ Required resolution < 1 ppm (~ 1 mm)
Hino+ [2014]12

Slow slip preceding 2011 Tohoku-Oki Earthquake

Ito+ [2012]

2012~2016

Horizontal motions after
2011 Tohoku-Oki Earthquake
Northern part (not ruptured by the 2011 mainshock)Slow deformation rate
Middle part (large coseismic slip during the 2011 MS)
Rapid landward motion
Southern part (not ruptured by the 2011 mainshock)Rapid oceanward motion
Onshore GNSS observations show
little spatial variations
Complex behavior in and aroundthe rupture area of Tohoku-Oki Eq.

Honsho+ [2019]

Horizontal motions after
2011 Tohoku-Oki Earthquake

2012~2016

Northern part (not ruptured by the 2011 mainshock)Slow deformation rate ? (balancing ① and ③)
Middle part (large coseismic slip during the 2011 MS)
Prevalence of VE-relaxation ②Southern part (not ruptured by the 2011 mainshock)Prevalence of slow slip (afterslip) ③
Onshore deformation:
combination of ② and ③

Honsho+ [2019]①②③

Locking between the plates
Viscoelastic relaxation
Slow slip on the plate boundary①②③
Elastic layer① Locking② relaxationw
Sl o

Mantle③sl i pslip③ Slow② relaxation
Visco-elastic mantle

Wang+ [2012]

SSE detected by GNSS-A observation in 2015
Journal of Geophysical Research: Solid Earth

10.1029/2018JB017135

Frequent SSEs have been pointed out by seismicity[Uchida+, 2016]
SSE-related seismicity change was observed in 2015.
GNSS-A displacement time series at several stations
seem to show “step” in 2015.
The steps were statistically significant.
The motions are consistent with the SSE fault model
derived from seismicity analysis.

Honsho+ [2019]
Figure 11. Slow slip event in early 2015 inferred from our GPS‐A observations. (a, upper map) Step motions that occurred at CE 2015.1, estimated from repeating
earthquake data (black arrows; Uchida et al., 2018) and the results of the present study (red arrows). Those from repeating earthquakes were calculated assuming a

of C2, we refer to this relationship as the diffusional earthquake
model. In this model, the stress drop Ds < mD/L is larger for an initialsmall event and decreases with increasing event size. The propagation
velocity L/T decreases proportionally to 1/L, as the stress concentration decreases. Equation (4) explains the rupture velocity of 0.1 m s21

19

Mw = 7
0.1

4

5

6

7

9
8

e

7

ETS

1 month

6
1 day

5

d

ke

4

Gap

3
a

2

VLF
1

s

b

ula
Reg

r

ake
hqu
t
r
a
e

LFE

Ide [2009]

−2
10

11

12

13

14
15
16
17
18
log[Seismic moment (N m)]

Mw = 280.001 0.01

0
−1

10

0.1
11
Possible
SSEs in northern Japan Trench
Mw = 1 ~ 10 days (based on tectonic tremor activity)
Duration:10
Frequency: ~ 5 events/year (basedonNtremor activity)
0.01 KWBH
2003/07/27 06:48
Estimated
size: ~ M6+ (based on scaling
relation)9
2004/12/28 14:49

ea

rth
qu
a

1 hour

c

14

12

s

c

OBP
U
Mw = 5SSEs previously
detected by seafloor TSAF
observations
2006/04/18
12:00
16
2006/04/18 12:33- SSE starting Feb., 2011 [Ito+,0.001
2014]
2006/04/18 20:37
2006/04/18 22:18- 15
AfterslipoftheM7
foreshockof
2011
Tohoku Eq. [Ohta+, 2012]
Mw = 40.01
0.1
1- Spontaneous SSE in Hikrangi, NZ [Wallace+,
Frequency2016](Hz)3
w =northern- 13
SSEMinJapan Trench [Honsho+, 2019](duration
was not constrained)
1

SSE

Sl
ow

log[Characteristic duration (s)]Silent EQ

1 year

0.01

19

20

|M0(f)|/M0

3

Mwlog[|M0(f) (N m)|]2

Mw = 6

17

Scaling of slow events
1

18|M0(f)|/M0

Possible size of SSEs in the Japan Trench

21

Figure 2 | Comparison between seismic moment and the characteristic
duration of various slow earthquakes in Table 1. LFE (red), VLF (orange),

0.1
1
10
Frequency (Hz)

100

0.001

2005/04/17 01:32
2005/04/19 06:50

1
10
Frequency (Hz)

Expected displacement

Figure 3 | Characteristics of moment rate spectrum of slow earthquakes.
< 10 cm(black
in horizontal
dashed lines)a, Scaling of moment rate spectrum of slow earthquakesb, An example
and regular earthquakes (grey lines) for different< magnitudes.
2 cm in verticalof displacement spectrum (moment rate spectrum) of a VLF event. Original(grey) and averaged (thick black) spectra are shown. The seismograms
represent the up–down (U) component at station TSAF for four VLFs that
occurred on 18 April 2006 at the times shown in Table S1 of ref. 3. The noise

GNSS-A

SSE detected by GNSS-A observation
Journal of Geophysical Research: Solid Earth

10.1029/2018JB017135

Horizontal displacements of ~10 cm are expected to
be detected by GNSS-A,
but are not convincing enough because
the sampling intervals are too coarse.
Systematic biases, if included, are difficult tobe identified from the coarsely sampled time series.

Challenges:
1) Increase time intervals of repeating surveys
2) Reduce the chances of systematic biases

Figure 11. Slow slip event in early 2015 inferred from our GPS‐A observations. (a, upper map) Step motions that occurred at CE 2015.1, estimated from repeating
earthquake data (black arrows; Uchida et al., 2018) and the results of the present study (red arrows). Those from repeating earthquakes were calculated assuming a

Improvement of detectability of SSEs by GNSS-A
Graphical Abstract

Simultaneous estimation of sound speed heterogeneity

Increase mobility by using unmanned vehicles
Wave glider

Iinuma et al.

GNSS-A Using a Wave Glider

Iinuma+ [2021]
Tomita+ [2022]

FIGURE 1 | (A) Block diagram of the GNSS-A data acquisition system. Items within a rounded rectangle with dashed line are installed inside a water-proof

Introduction
Over the last 10 years, seafloor geodetic observational techniques, particularly the GNSS-acoustic(GNSS-A) technique, have provided important geophysical results and have been technically improved.

positioning method
and it has shown ge
related to fault slips
plate coupling) in subd
Fujita et al. 2006; Kide by aseismic slip increased in 2005,
hquake. This could be an example ofdeformation events with a long leaddata, Hirose (2011) found no shortrmation rate preceding the Tohokuoncluded that no short-term preslip
curred on the deeper extension of the

Mar Geophys Res

141˚

142˚

143˚

144˚

40

20

P08
GJT3

an T

ren
c

h

P09

38˚

Jap

ch
ren
nT
pa

9.0

TJT1

seafloor level [cm]

40

P02

P07

GJT3
TJT1
P08 P07
P03
P02

20

P06

NE Japanoriginal traces

30

39˚

P03

M6.6 M9.0
M7.3
P09

50

50 km

Ja

e
hat
est
ock.
to the
val).
with
the
2012),
withhee[0.3 mgest
12)

Improvement of detectability of SSEs by OBP

60

entralu-Oki
ate thee,esent
ck, theshock, an Mw 7.3 event, occurred about 20 km northeastof the mainshock hypocenter. This was followed by anumber of smaller interplate earthquakes, including thesecond-largest foreshock (Mw 6.6) 18 h later. Coseismic
and postseismic deformation from the largest foreshocks
were clearly observed by cGPS and OBPRs (Ohta et al.
2012). Ito et al. (2013) analyzed OBPR data and reported

10
0
−10

1st PC−20−30

remove 1st PC

−40
−50

TJT1
10

20

Hino+ [2014]

DpB (t ) = DpC (t ) + DpO (t ) + DpI (t )oceanographic fluctuation

P06

remove steps

30

40

50

60

70

days from Jan. 1, 2011
Fig. 3 Time series of SFL variation derived from ocean bottompressure records from 1 January 2011 to the origin time of the
Tohoku-Oki earthquake mainshock on 11 March. The top group of
traces is SFLs after removing ocean tides and nontidal fluctuation

predicted by the global ocean model. The second group is SFL traces
after removing coseismic steps. The trace in the third row is the firstprincipal component (1st PC). The bottom group is SFL traces after
subtracting the 1st PC

Table 2 Noise level and cross-correlation coefficient of SFL records

factor. In this study, we adopted a value of s of 0.2 days
20 Figaccording to the estimation by Ohta et al. (2012).
ure 4b shows the SFL after removing the postseismic

Challenges:
3) Reduce noise components included in OBP records

StationWithout CMNR

With CMNRaaImprovement of detectability of SSEs by OBP

Ohta+ [2019]

DpB (t ) = DpC (t ) + DpO (t ) + DpI (t )instrumental drift

Challenges:
3) Reduce noise components included in OBP records

Self-calibrating system for drift correction

http://www.aob.gp.tohoku.ac.jp

A-0-A 適用後時系列
A: Seafloorpressure(after tide removal)
水圧計時系列(潮汐フィルタ適用済)
B: Internal pressure
ゼロ点(ガラス球内)時系列

C: Internal pressure by precise
barometer
ガラス球内気圧計時系列( D:0.3hPa)

A-0-A適用後 水圧計時系列
Drift-correctedseafloor pressure = A- (B-C)

Ohta+ [2021]9

Summary• The importance and effectiveness of seafloor geodetic observations
were proven by capturing various important aspects of the 2011
Tohoku-oki earthquake.
• Seismic slip monotonically increased towards the trench• SSE preceded the main shock• Postseismic deformation shows significant regional variations• Efforts are underway to improve observation techniques to detect
smaller SSEs
• GNSS-A observation using unmanned vehicles• New methods to reduce the noises due to oceanographic fluctuations• Developing self-calibration pressure recorders