東海 大学海洋研 究所報告書 第 35 号(2014) 43～ 52 頁
Bull Inst. Oceanic Res. & Develop. Tokai Univ. (2014), 43, 1-52

原著論文(Original Article)

Preliminary Analyses of Micro Pressure Data Associated with
Volcanic Eruption near Nishinoshima, Tsunami, and Storm at
Ogasawara, Japan
Fei Zhang 1), 2), 3), Maho Nakamura 1), Yuko Suzuki 1), Yoshiaki Orihara 1), 4),
Chiaki Tsurudome 1), Daiki Ikeda 1), Kosei Ohora 1), Jann-Yenq Liu 1), 2) ,3),
Masashi Kamogawa 1), *)Abstract
We report data quality of a micro barometer which observes atmospheric infrasonic waves at Ogasawara
islands, approximately 1000 kilometers south of Tokyo, Japan, showing the cases of three different natural
events including volcanic eruption, tsunami, strong wind and signals from one ordinary day. With considering
weather conditions, the wavelet spectrum analysis showed different features. The good quality of Ogasawara
data is verified, partly because microbarom caused by the nonlinear interaction of large-amplitude
storm-generated waves on the surface of the ocean has been clearly observed.

1. Introduction

wind and any event which lead to slow oscillations of
the air. Man-made sources are explosions, large

Inaudible infrasound propagates thousands ofkilometers through ducts formed in the troposphere,

combustion processes, slow speed fans and machinery,etc.

stratosphere, and lower thermosphere. While there are

Microbarometers, one of sensitive barometers,

several modes for propagation, dominant one ductsthat measure air pressure with high precision, have

between the earth's surface and a stratospheric region

been used

at a height of about 50 kilometers. There are many

Comprehensive Nuclear-Test-Ban Treaty by detecting

natural sources of infrasound such as meteors,the infrasound signature of a nuclear explosion (seevolcanic eruptions, ocean waves, avalanches, tsunamis,

Alcoverro et al., 2005; Alcoverro, 2008; Zumberge

to monitor compliance with

1) Department of Physics, Tokyo Gakugei University, 4-1-1 Nukuikitamachi, Koganeishi, Tokyo 184-8501, Japan.
2) Institute of Space Science, National Central University, No.300 Jhongda Road, Jhongli City,
Taoyuan County 32001, Taiwan.
3) College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology,
No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China.
4) Institute of Oceanic Research and Development, Tokai University, 3-20-1 Orido, Shimizu-ku, Shizuoka
424-8610, Japan.
*) Corresponding author(2014 年 2 月 17 日受付／ 2014 年 3 月 24 日受理)

the

44

Fei Zhang, Maho Nakamura, Yuko Suzuki, Yoshiaki Orihara, Chiaki Tsurudome, Daiki Ikeda,
Kosei Ohora, Jann-Yenq Liu, Masashi Kamogawa 1), *)et al., 2003; Catherine et al., 2013). Numerous

Off the Pacific Coast of Tohoku earthquake

volcanic eruptions and explosions have been

(Mw9.0) recorded by sensitive microbarographs.

detected by infrasound measurement during the last

They verified that the co-seismic atmospheric

decades (see, e.g., Goerke et al., 1965; Le Pichon etboundary waves were excited by the uplift andal., 2005; Liszka and Garcés, 2002). The dominant

subsidence of the ocean surface.

frequency and amplitude of infrasonic waves fromJapan has several arcs generating various

volcanic explosions depends on the size of thetectonic activities including volcanic eruptions andexplosion and the distance from the source. In

large earthquakes. In order to better understanda ddition,an dthese events, a microbarometer was installed bymeteorological sources like tornadoes, lightning andTokyo Gakugei University (TGU) in June, 2013 at

sprites also generate infrasound with frequencies

Ogasawara islands, 1000 kilometers south of Tokyo,

between 0.02 and 0.1 Hz. The source mechanism

Japan. Several interesting events have been recorded

for these waves is better understood now (Farges

by this micro barometer during last 6 months.

and Blanc, 2010; Liszka and Hobara, 2006; Assink

Taking into account meteorological conditions, fouret al., 2008). Arai et al. (2011) investigatedtypical events were analyzed with wavelet analysis

atmospheric pressure changes caused by the 2011

to evaluate the quality of data at Ogasawara.

severeco nve ctive

storms

2. Observation and Methodology

Quartz-pressure-transducer-type
microbarometer (Toho Mercantile, Co. Ltd.)
capableofrecordingtheabsolute

atmospheric pressure with a resolution of
0.001 hPa at 2 Hz sampling rate wasinstalled in Ogasawara, Japan as shown in
Fig. 1 and recorded pressure during last 6months. Fig. 2 shows an example of the timeseries of pressures recorded by ours (Tokyo
Gakugei

University)

and

Japan

Meteorological Agency (JMA) at Ogasawara
at the same period (From 1500 UT on 25
October, 2013 to 1500 UT on 26 October,2013) (http://www.jma.go.jp/jma/index.html).
Note that resolution and sampling rate of the
microbarometer installed by JMA are 0.3 hPa
and 0.002 Hz, respectively. Two time series
Fig. 1

Location of our micro barometer. Red stardenotes the epicenter of one M7.1 earthquakeat 1710 UT on 25 October, 2013; Red andpurple circles denote the new island and ourobservation point, respectively.

are shown so that a good correlation is foundas shown in Fig. 3. Almost all the points arelocated on the diagonal line. Statisticalanalysis demonstrated

that correlation

coefficients of 99% of the data are larger

Analysis of micro pressure datat.han 0.99

analyze the raw data of pressure. We also adopt

Compared with the common FFT method,
wavelet is more suitable for continuous and unstable

multiband narrow filter method to roughly observe thefrequency contents.

signals. In this paper, we use wavelet method toFig. 245

Infrasound signals from 1500 UT on 25 October, 2013 to 1500 UT on 26
October, 2013. A top and bottom panels are raw data of pressure recorded byours and JMA at Ogasawara, respectively.

Fig. 3

Correlation of micro pressure data recorded by ours
and JMA at Ogasawara.

46

Fei Zhang, Maho Nakamura, Yuko Suzuki, Yoshiaki Orihara, Chiaki Tsurudome, Daiki Ikeda,
Kosei Ohora, Jann-Yenq Liu, Masashi Kamogawa 1), *)Fig. 4

Infrasound signals possibly from a small volcanic event. The top panel is raw data
and the bottom panel is wavelet spectrum data.

3. Results

frequencies on 20, November.
In the lower panel of Fig. 4, continuous

3.1 Volcanic EruptionA

volcanic

eruptionvariations between 0.15 and 0.25 Hz were found.
nearThis is an intensive continuous infrasound waves

Nishinoshima Island, which locates 130 km west of

propagating over a large distance due to the

Chichi–jima in Ogasawara islands. Since there is nointeraction of ocean swell with the atmospherescientific observation around the new island, we

whichknew that the volcanic eruption was confirmed on

meteorological wind speed with the observed

20 November, 2013 by means of aerial survey.

pressure. Fig. 5(a) shows the mean and the

Figure 4 is expected to present volcanic events

maximum wind speed for a sampling of 10 minutes

recorded by our micro barometer located 120

drawn in red and blue lines, respectively. We foundkilometers away from the new island. A top panel

a small increase of wind speed and a broadof Fig. 4 shows the raw data of this event andspectrum of pressure shown in the lower panel offluctuations from 0100UT to 0700UT were found.

Fig. 4 from 0100UT to 0700UT. There are two

A next panel shows a spectrum by means ofpossibilities to explain the variations of pressure

wavelet method. This panel shows a broadband

from 0100UT to 0700UT. On one hand, the broad

infrasoundaccompanying

occurredhighistermedmicrobarom.

We

comparefrequency

spectrum may be caused by the sudden wind speed

component. Since similar cases, the eruption ofchange. On the other hand, this is caused by the

Tungurahua Volcano, Ecuador, in August 2006 (Feevolcanic eruption. Since we cannot make sure theet al., 2010) was recognized. We inferred that theaccurate volcanic eruption time, it is difficult for us

eruption begin gradually around 2200 UT on 19

to distinguish whether there are volcanic eruption

November and ended with evident shift to lower

signals inside if there is only one station.

Analysis of micro pressure data

Fig. 547

Wind speed for four cases:(a) Left and upper one: volcanic event on 20 November, 2013.
(b) Right and upper one: tsunami event on 25 October, 2013.
(c) Left and lower one: strong wind and rain event on 10 December, 2013.
(d) Right and lower one: ordinary signal event on 1 December, 2013.

3.2 Tsunamil) are shown in Fig. 7, following the calculation of

Tsunami is one of infrasound sources (LeHeki and Ping (2005). Estimated arrival time of

Pichon et al., 2005). An earthquake with ainfrasound at Ogasawara was 1748UT. Note that themagnitude of 7.1 struck off the coast of Fukushima

distance between source and our micro barometer is

at 1710 UT on 25 October, 2013 (Fig. 1). The

about 1142 km.

earthquake occurred 320 kilometers off the coast.

According to Fig. 7, the propagation path from the

About 40 minutes later, tsunami measuring up to

Tsunami source area to the observation point also

0.4 meters hit the coasts of Fukushima, Miyagi andexists in the ionosphere. In order to verify that the

Iwate,

sufficient intensity of tsunami-origin acoustic wave

accordingto

JMA(http://www.jma.go.jp/en/tsunami/focus_03_2013102

was not excited, the measurement of Global

6025051.html). A top panel of Fig. 6 presents raw

Positioning System total electron content

data from 0000UT of 25 October to 1400UT of 27

TEC) (see Kakinami et al., 2012) is used. From

October, 2013. A huge pressure decreased by 21.51

GPS TEC measurement, the ionospheric disturbancehPa from standard atmospheric pressure. However,generated by the tsunami-origin acoustic waves isfrom the lower multiband filter panels, any usefulconfirmed. In this analysis, the F region is assumed

information was not obtained. Ray tracing curves

to be a thin-layer located at 300 km altitude. The

based

Model

point of intersection between the ionospheric thin(http://omniweb.gsfc.nasa.gov/vitmo/msis_vitmo.htm

layer and the propagation path between the GPSon

MSIS-E-90

Atmosphere

(GPS

48

Fei Zhang, Maho Nakamura, Yuko Suzuki, Yoshiaki Orihara, Chiaki Tsurudome, Daiki Ikeda,
Kosei Ohora, Jann-Yenq Liu, Masashi Kamogawa 1), *)Fig. 6

A period of infrasound signals associated with a small tsunami on 25 October, 2013.
Data are filtered between 0.01 and 0.4 Hz.

Fig. 7

Ray tracing curves on 25 October, 2013 based on MSIS-E-90 Atmosphere Model

49

Analysis of micro pressure data

satellites

and

their

receivers

istermedionospheric point and its foot print on the
ground surface is termed sub-ionospheric point(SIP). A sampling period of GEONET data is
30 seconds. In order to extract the TEC
variation with a few minutes, we calculated thedifference between the slant TEC and the least
mean square estimation for 40 minutes before
and 20 minutes after the mainshock andconvert these difference into the vertical TEC(∆vTEC) from the zenith angle of the GPS
satellite direction. In Fig. 8, the time-series of∆vTEC are drawn as the distance between theepicenter and the sub-ionospheric point. In thisanalysis, we have no signature of seismogenic
ionosphericdisturbance,

as

well

as

seismogenic infrasound from our pressure data.
In Fig. 9, wavelet method was used toreanalysis the period from 1600 UT of 25
October 2013 to 1400 UT of 25 October 2013.
The major frequency of infrasound originatingfrom tsunami ranges from 0.5 to 2 Hz (LeFig. 8 Time series of TEC variation before andafter tsunami on 25 October, 2013

Pichon et al., 2005). from tsunami ranges from
0.5 to 2 Hz

(Le Pichon et al., 2005). Fig. 9shows large intensity from 0 to 0.3 Hz. Wind

Fig. 9Infrasound signals from a tsunami event caused by one earthquake.
The top panel is raw data and the bottom panel is wavelet spectrum data.

50

speed

Fei Zhang, Maho Nakamura, Yuko Suzuki, Yoshiaki Orihara, Chiaki Tsurudome, Daiki Ikeda,
Kosei Ohora, Jann-Yenq Liu, Masashi Kamogawa 1), *)is larger

than

other

day

duringourinfrasonic waves caused by a lightning discharge

observation period as shown in Fig. 5(b). In

during the storm also generate a clear sudden

general, wind-generated noise is the most major

increase observed from three different frequency

source of infrasonic background. In other words,

bands (Farges and Blanc, 2010). We found thestrong wind hides weak signals. Therefore, even if

lightning activities from 0300UT to 0500UT fromwe have an array observation of infrasoundour measurement of atmospheric electric field nearincluding more than three instruments and intensive

the infrasound observation. Therefore, the signature

signals generated by tsunami was emitted, it isshown in Fig. 11 is caused by lightning-relateddifficult to discriminate the signals from the current

storm.

observed data.
3.4 Ordinary Infrasound Signals
3.3 Strong Wind and Rain
One of infrasound sources with frequencies

Micro barometer records many backgroundnoises at most time. The primary sources ofbetween 0.02 and 0.1 Hz is generated by severe

background noise areconvective storms. Other meteorological sources ofWind-generated

infrasound such as microbursts, tornadoes, lightningassociated with turbulent eddies in the atmosphericand sprites have been also reported. Micro pressure

boundary layer, of which intensity enhances in all

variations associated with a thunderstorm is shown infrequencies. (2) Microbarom infrasonic waves in theFig. 10. According to the meteorological conditions

0.12–0.35 Hz passbands. The microbarom is almost

provided by JMA, strong wind due to severe storm

always present at any point on the surface of theoccurred on 10 December, 2013 as shown in Fig. 5

provided by JMA, strong wind due to severe storm(c). The dominant frequency is about 0.1 Hz whenoccurred on 10 December, 2013 as shown in Fig. 5

the pressure reaches the lowest. Furthermore,(c). The dominant frequency is about 0.1 Hz when

Fig. 10

given as follows:

micropressure

Infrasound signals from a strong wind and rain event.
The top panel is raw data and the bottom panel is wavelet spectrum data.

(1)

fluctuations

51

Analysis of micro pressure data

the pressure reaches the lowest. Furthermore,

3.4 Ordinary Infrasound Signals

infrasonic waves caused by a lightning discharge

Micro barometer records many background

during the storm also generate a clear suddennoises at most time. The primary sources ofincrease observed from three different frequency

background noise are

bands (Farges and Blanc, 2010). We found theWind-generated

lightning activities from 0300UT to 0500UT fromassociated with turbulent eddies in the atmospheric

our measurement of atmospheric electric field nearboundary layer, of which intensity enhances in all

the infrasound observation. Therefore, the signature

frequencies. (2) Microbarom infrasonic waves in theshown in Fig. 11 is caused by lightning-related

0.12–0.35 Hz passbands. The microbarom is almost

given as follows:

micropressurestorm.

Fig. 11A period of infrasound signals associated with a strong wind and rainon 10 December, 2013. Data are filtered between 0.012 and 0.3 Hz.

Fig. 12 Infrasound signals from ordinary event. The top panel is raw data
and the bottom panel is wavelet spectrum data.

(1)

fluctuations

52

Fei Zhang, Maho Nakamura, Yuko Suzuki, Yoshiaki Orihara, Chiaki Tsurudome, Daiki Ikeda,
Kosei Ohora, Jann-Yenq Liu, Masashi Kamogawa 1), *)always present at any point on the surface of the
globe at any time. We show the typical signals

Inframatics, 9, 1–10.
Alcoverro, B. (2008): The design and performancerecorded under the circumstance without strongof

infrasoundnoise-reducing

wind and rain,i. e. fair weather, as shown in Fig. 5

Handbook of signal processing in acoustics,(d) on 1 December, 2013 in Fig. 12. Clear

chap. 80, Springer, New York, 1473–1486.

microbarom during the whole period was observed.

Arai, N., Iwakuni, M., Watada, S., Imanishi, Y.,
T.,

and

Nogami,pipe

M.

arrays.

How to reduce these micrcobarom is an important

Murayama,(2011):

issue for infrasound research.

Atmospheric boundary waves excited by thetsunami generation related to the 2011 great
Tohoku ‐ Oki earthquake. Geophys. Res. Lett.,

4. Conclusions

38, L00G18, doi:10.1029/2011GL049146.
Assink, J. D., Evers, L. G., Holleman, I., andWe

reportthepreliminary

resultsofPaulssen,H.

(2008):

Characterizationofinfrasound recorded at Ogasawara islands, showing

infrasound from lightning. Geophys Res Lett.,four typical cases to verify the data quality.

35, L15802.

Although significant events as volcano, tsunami,Catherine, D. G. H, Michael, A. H. H., Kristoffer T.

and storm could cause significant change, we partly

W. (2013): Detection of gravity waves across theshow the signals related to them. In addition, we

US Array: A case study. Earth and Planetaryconfirm the existence of microbarom in our

Scienceobservation points, so that we verify the sensitivityof our micro barometer.

Letters,

http://dx.doi.org/10.1016/j.epsl.2013.06.042.
Farges, T., and Blanc, E., (2010): Characteristics ofinfrasound from lightning and sprites near
thunderstorm areas. J. Geophys. Res., 115,

Acknowledgements

A00E31, doi:10.1029/2009JA014700.
Fee, D., Garces, M., and Steffke, A. (2010):

We also thank S. Saito, S. Togo, Y. Suto,

Infrasoundfro mTung urahua

VolcanoT. Shoji and R. Tanaka (Tokyo Gakugei University)

2006–2008: Strombolian to Plinian eruptive

for their supports for this analysis and T. Ohi (Tohoactivity. Journal of Volcanology and Geothermal

Mercantile Co., Ltd.) for system installation. GPS

Research, 193 (1–2), 67–81.

and meteorological data in this study were provided

Goerke, V. H., Young, J. M., and Cook, R. K.

by the Geographical Survey Institute of Japan and(1965): Infrasonic observations of the 1963

Japan Meteorological Agency. This research was

volcanic explosion on the island of Bali. J

supported by the Ministry of Education, Science,

Geophys Res., 70, 6017–6022.

Sports and Culture, Scientific Research (B), No.
24310129, 2012 (M. K.).

Heki, K. and Ping, J. S. (2005): Directivity andapparent velocity of the coseismic ionosphericdisturbances observed with a dense GPS array.
Earth Planet. Sci. Lett., 236, 845-855.

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