Remote infrasound in SE-Asia: A case study of the 2014 Kelud eruption
and minimum detection threshold through space and time
Presented by B. Taisne1,2, C. Caudron1, M. Garces3, A. Le Pichon3,, P. Mialle3
Earth Observatory of Singapore 2 Asian School of the Environment 3 Infrasound Laboratory, Hawaii,USA
4
CEA/DAM/DIF, Arpajon, France 5 CTBTO, Vienna, Austria
1
Volcanic Ash and Air Traffic
Review on the detection capability of two remote sensing techniques: Satellite and Infrasound.
We focus our analysis on South East Asia where climatic conditions are challenging both techniques.
120° E
10°
Cloud cover fraction
Satellite
0°
Infrasound
Zone IV (Sumatra)
9 years time serie for zone IV
400
1
Acoustic Pressure
100° E
When are we blind when are we deaf ?
0.8
0.6
0.4
2005
2006
2007
2008
2009
2010
2011
2012
2013
Good visibility
Bad visibility
2014
300
200
100
0
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Zone XIV (Sulawesi)
Zone IV (Sumatra)
Flight line
Potential ash producing
volcano
Ash cloud (1979-2010)
Ash-airplane encounter
-10°
Ash cloud image after A. Tupper, Australia Bureau of Meteorology [2002]
VEI 4
VEI 3
VEI 2
8 days average cloud cover over South East Asia in June 2014
(ranging between 0 (no clouds) and 1 (fully covered)).
Black dots are different volcanic zones.
Source: http://neo.sci.gsfc.nasa.gov/ (Modis product)
Simulations of the minimum pressure detectable by one array of the IMS infrasound network
complemented or not by Singapore Network. Maps are calculated for the same day
with/without Singapore station for zone 4 (above) and 14 (below)
9 years time serie for zone XIV
1
0.8
0.6
0.4
0.2
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
150
100
50
2005
2006
2007
2008
2009
Detection tresholds at 0.4 Hz.
for a Signal to Noise Ratio of 4.5
0.1
4
Factor of improvement
3.5
achieved by adding Singapore to IMS for zone IV (blue)
3
and zone XIV (black)
Polar plot highlighting azimuth and distance of each
volcanic zones with respect to Singapore.
Most frequent situation
Source:
http://neo.sci.gsfc.nasa.gov/
2010
2011
2012
2013
2014
Zone IV
2.5
20 % of the time, improvement
2
treshold of:
- 3.5 in zone IV
1.5
- 1.25 in zone XIV
l
km n
00 i
10 0 m
km in
~5
00 m
20 0
0
km in
~1
0
0
m
30 50
m
~1 00 k min
40 00
~2
Quiet Volcanic zone
Zone XIV
1
Active Volcanic zone
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
D
ist
a
tim nce
e t an
o ds
Si ou
ng n
ap d t
or ra
e ve
200
5
‘Ideal’ situation
Source:
http://neo.sci.gsfc.nasa.gov/
The proposed study will allow an automated detection of strong volcanic activity, and trigger a set of ash
dispersal simulations that will be refined as information is collected.
Acoustic Pressure
Detections (circles) and non-detections (crosses) of volcanic infrasound from 110 eruptions occurring at
39 globally distributed volcanoes. The most distant detection is highlighted by filled black circles. The
dashed lines represent the linear best-fit line to the maximum detected distances only. From Dabrowa et
al. [2012], EPSL. Horizontal lines represents the plume elevation for VEI 2, 3 and 4.
Cloud cover fraction
Zone XIV (Sulawesi)
Infrasound array in Singapore
Infrasound Array (5 sensors)
Infrasound network (Bukit Timah)
On the use of remote infrasound and seismic stations to detect volcanic eruptions
Case study: 2014 Kelud eruption
Signal recorded at GE-UGM (Yogyakarta, Central Java,
Indonesia, 198 km from Kelud volcano). (a) Spectrogram of signals having a high Signal to Noise Ratio
(SNR, in dB, where the noise is considered as the
energy averaged over the record at each frequency
band) (b) raw spectrogram (c) corresponding seismogram. (a) and (b) are computed using 6th octave
bands and 1/f window scaling with a 75% overlap (dB
re 1 micron/s). A tectonic earthquake (EQ) is indicated
on the plot (b).
(a)
3
Longitude
2
1
STA1
Network resolution
Azimuth error
Latitude
S_LL
I_1
SP_1
SP_2 Seismic
No seismic detection
I_LL Infrasound
No infrasound detection
The different arrivals altogether as a function of the
distance with respect to Kelud volcano.
(b)
Longitude
~0.3 km/s
~3 km/s
Attenuation [dB]
Latitude
Kelud volcano (Central Java, Indonesia, cyan triangle on (a)
and (b)). (a) Seismic detections: the pies are divided in three
and correspond to the broadband sensors detections (IRIS
and GEOFON networks) used in this study. Infrasound detections: the half pies are the infrasound stations (IMS network).
White colors correspond to a non detection, green to the detection of S_P1, blue of S_LL, red of S_P2, magenta of I_1 and
yellow of I_LL. (a) zoom on the region of interest (b) global detections.
Installation
Singapore: Redvox array
10 days of PSDs recorded at STA1 between
1-10 August 2015 (green curves: noise models /
red curve: median of the 1-hr curves displayed
in black)
Results of preliminary PMCC analysis for the Thai
bolide recorded in Singapore on 7 September
2015 (time is in UTC and origin time ~01:45 UTC)
Marapi (Sumatra, Indonesia):
3 different technologies
experiment:
Redvox (ISLA, Hawai’i)
Unifi (Firenze University)
Infra BSU (Boise University)
Gede (Java, Indonesia):
5 sensors array
−35
o
20 N
−40
o
10 N
−45
o
0
−50
o
10 S
−55
o
20 S
−60
o
30 S
o
40 S0o E
8
Predicted attenuation map of the acoustic signal
(central frequency of 0.06 Hz and using European
Centre for Medium-Range Weather Forecasts
(ECMWF) wind conditions) using parabolic equation
numericalmodelling [Le Pichon et al., 2012)
−65
o
100 E
120oE
140oE
−70
160 oE
Caudron, C., Taisne, B., Garcés, M., Le Pichon, A., & Mialle, P. (2015). On the
use of remote infrasound and seismic stations to constrain the eruptive
sequence and intensity for the 2014 Kelud eruption. Geophysical Research
Letters, 42(16), 6614-6621.
Future perspectives for next year
Redvox Inc: A project from M.A. Garces, ISLA
Redvox system
UNIFI + Redvox
Indonesia
Infra BSU
Korea
Marapi volcano
Sumatra (Indonesia)
Japan
REDVOX
INFRASOUND
UNIFI sensors
Gede volcano
Java (Indonesia)
RECORDER
Kilauea, Hawaii
In App
Store
Singapore
Old Faithful, Yellowstone
http://www.redvoxsound.com/
www.earthobservatory.sg