approaches to array and network processing for … zalv asar yka cmar usrk txar akasg fines dbic...

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Approaches to Array and Network Processing for Enhanced Nuclear Explosion Monitoring Steven J. Gibbons, Johannes Schweitzer and Tormod Kværna NORSAR, P.O. Box 53, 2027 Norway [email protected], [email protected], [email protected] Site-specific ALERT warning system Array-Based Waveform Correlation Seismic Array Stations of the IMS Empirical Matched Field Processing Incoherent Array Processing Threshold Monitoring −180˚ −120˚ −60˚ 60˚ 60˚ 120˚ 120˚ 180˚ 180˚ −60˚ −30˚ 30˚ 30˚ 60˚ 60˚ SCHQ ULM MAW STKA NRIK KBZ KEST KMBO BOSA VNDA EKA KVAR MMAI KURK SPITS HFS BVAR PETK TORD GEYT NOA ESDC MJAR BRTR SONM MKAR ILAR ARCES NVAR KSRS GERES WRA PDAR ZALV ASAR YKA CMAR USRK TXAR AKASG FINES DBIC Primary Seismic Array Auxiliary Seismic Array Primary Seismic 3-C station ARCES (PS28) AKASG (PS45) ASAR (PS3) BRTR (PS43) BVAR (AS57) CMAR (PS41) EKA (AS104) ESDC (PS40) FINES (PS17) GERES (PS19) GEYT (PS44) HFS (AS101) ILAR (PS49) KSRS (PS31) KURK (AS58) KVAR (AS83) MJAR (PS22) MKAR (PS23) MMAI (AS49) NVAR (PS47) PDAR (PS48) PETK (PS36) SONM (PS25) SPITS (AS72) TORD (PS26) TXAR (PS46) WRA (PS2) YKA (PS9) USRK (PS37) ZALV (PS33) 40 km 20 km 10 km 10 km NOA - NC2 (PS27) NOA - NBO (PS27) NOA - NAO (PS27) NOA - NC6 (PS27) NOA - NB2 (PS27) NOA - NC4 (PS27) NOA - NC3 (PS27) 10 km The array stations of the IMS seismic network are the most powerful stations for the detection and classification of seismic signals. The time-delays between arrivals on the different sensors allows for beamforming for the optimized detection of signals from a given direction since noise from other directions is suppressed by the stacking operation. f-k analysis and related techniques can estimate the direction of arrival and assist in phase identification. We here examine the exploitation of seismic arrays for enhanced nuclear explosion monitoring. Azi: 302.0 o Vel: 10.59 km/s −0.4 −0.2 0.0 0.2 0.4 Sy −0.4 −0.2 0.0 0.2 0.4 Sx 2009-145:00.56.47 (May 25) 2006-282:01.37.34 (October 9) −0.4 −0.2 0.0 0.2 0.4 Sy −0.4 −0.2 0.0 0.2 0.4 Sx Azi: 311.2 o Vel: 9.41 km/s 306.5 o 306.5 o 5 km/s 10 km/s 5 km/s 10 km/s 2013-043:02.59.56 (Feb 12) −0.4 −0.2 0.0 0.2 0.4 Sy −0.4 −0.2 0.0 0.2 0.4 Sx Azi: 307.9 o Vel: 8.77 km/s 306.5 o 5 km/s 10 km/s 124˚ 124˚ 128˚ 128˚ 132˚ 132˚ 136˚ 136˚ 140˚ 140˚ 144˚ 144˚ 32˚ 32˚ 34˚ 34˚ 36˚ 36˚ 38˚ 38˚ 40˚ 40˚ 42˚ 42˚ 44˚ 44˚ 46˚ 46˚ USRK JKA MJAR JNU KSRS (402 km) (956 km) (439 km) (1152 km) (923 km) The array stations of the IMS seismic network are the most powerful stations for the detection and classification of seismic signals. The time-delays between arrivals on the different sensors allows for beamforming for the optimized detection of signals from a given direction since noise from other directions is suppressed by the stacking operation. f-k analysis and related techniques can estimate the direction of arrival and assist in phase identification. We here examine the exploitation of seismic arrays for enhanced nuclear explosion monitoring. The MJAR array in Japan is the only seismic array at a regional distance to have recorded all three DPRK nuclear tests as a certified primary IMS station. However, it failed to contribute to the automatic SEL3 bulletin for all 3 events - despite strong signals. 0.0 5.0 10.0 15.0 May 25, 2009, black. October 9, 2006, red. Waveforms filtered 2.0 - 8.0 Hz MJA0_HHZ MJB1_HHZ MJB2_HHZ MJB3_HHZ MJB8_HHZ Time (seconds) - absolute times not shown. The reason for the failure of classical array processing at MJAR for the Pn phase from the DPRK tests is that the waveforms are incoherent across the array for the frequency band with optimal signal-to-noise ratio (SNR) - see the 2006 and 2009 signals above. It can be demonstrated however that robust detections and parameter estimates can be obtained for all 3 arrivals (lowermost panel) by spectrogram beamforming and smoothing of the resulting slowness grids with the array response function for a 4-5 second signal. References: Gibbons et al, Geophys. J. Int., 2008 http://dx.doi.org/10.1111/j.1365-246x.2007.03650.x Gibbons, Pure. appl. geophys., 2012, http://dx.doi.org/10.1007/s00024-012-0613-2 1 2 3 4 5 6 1 2 3 4 5 6 Detection Mag 1 2 3 4 5 6 1 2 3 4 5 6 Monitoring Mag 1:30 1:35 1:40 1:45 1:50 1:55 2:00 9 Oct 2006 Day 282 HH:MM (GMT) IMS Network + KSRS KSRS data The red “Detection” trace shows continuous estimates of the smallest seismic event that can be detected by 3 or more stations in the network (at the 90% confidence level). Only P-phases are considered. The blue “Monitoring” trace shows continuous estimates of the largest seismic event that could possibly have occurred (at the 90% confidence level). Both P- and S-phases are considered for stations at regional distances. In the context nuclear explosion monitoring it may be useful to obtain estimates of the largest events that might have occurred within a given location and time interval. Threshold monitor- ing is a method that applies the amplitude and travel-time pattern derived from previous events in the source region of interest to obtain continuous estimates of the largest events that could possibly have occurred (Monitoring), or the smallest seismic event that can be detected by e.g. 3 or more stations of the network (Detection). These estimates are based on the assumption that conventional methods like beamforming and band-pass filtering are used for data analysis. Reference: Kværna et al., Seismological Research Letters, 2007: http://dx.doi.org/10.1785/gssrl.78.5.487 Starting time 2011-296:15.00 (October 23) KKAR beam (2-4 Hz) AGRB_bz (2-4 Hz) Transformed empirical matched field statistic trace (KKAR) 15:00 15:10 15:20 15:30 15:40 15:50 CC trace (full array) with mainshock template (KKAR) CC trace (single channel KK01) with mainshock template 15:45 15:47 15:49 Zoom in In extensive aftershock sequences after very large earthquakes, corre- lation detectors using the mainshock signal as the template are usually very ineffective at detecting aftershocks (due to source location, spectral content of signals etc.). The narrowband EMFP method is effective at generating triggers. Here demonstrated for the October 23, 2011, Van earthquake, EMFP detects aftershock signals down to the noise level. 2 Hz 4 Hz 8 Hz Plane wave Real data (event 1) Real data (event 2) A waveform correlation detector compares the ups and downs of a template seismic signal with successive segments of incoming data and triggers a detection when a sufficiently close match is observed. A correlator is the optimal detector for two identical signals, but suffers when waveforms differ due to, for example, different source-time functions. Empirical Matched Field Processing (EMFP) is a narrowband technique which matches the phase and amplitude relations between the sensors of an array or network for a given incoming wavefront. The narrowband nature makes it far less sensitive to the source-time function and/or significant spectral differences between the master and detected signals. Reference: Harris and Kværna, Geophys. J. Int., 2010: http://dx.doi.org/10.1111/j.1365-246x.2010.04684.x A greatly enhanced detection capability results from the stacking of correlation coefficient traces across an array or network. False alarms - positive detections from noise or signals from sources unrelated to the master event - do occur. Two wavefronts approaching an array from the same direction will result in correlation coefficient traces which are well aligned at the time of a detection. If f-k analysis on the correlation coefficient traces does not result in an almost- zero slowness vector then the two wavefronts cannot come from the same direction and the detection has to be a false alarm. This allows us to run the detectors at aggressively lowthresholds with exceptionally low false alarm rates. The figures display the detection of the 2013 DPRK nuclear test on the NOA array using the 2009 test signal as a template (above) and the f-k verification that the wavefronts approached the array from the same direction (left). 03:08:30 03:08:40 03:08:50 Starting time: 2013-043:03.08.30 Detection statistic stack (maximum 0.639) Detection statistic NC200_BHZ (maximum 0.746) Detection statistic NC602_BHZ (maximum 0.530) Detection statistic NAO01_BHZ (maximum 0.540) NC200_BHZ NC602_BHZ NAO01_BHZ max. amp. 838 max. amp. 578 max. amp. 865 max. amp. 495 max. amp. 1009 max. amp. 844 TEMPLATE TEMPLATE TEMPLATE 3 5 7 7 7 7 7 7 9 9 9 9 9 9 9 0.00 Slowness Sy (N-S) 0.00 0.25 -0.25 -0.25 0.25 Slowness Sx (E-W) NOA array: f-k analysis of single channel detection statistic traces Template time: 2009-145:01.05.30 Maximum of detection statistic: 2013-043:03.08.38.153 A matched filter or correlation detector is the most effective method for detecting a known signal in noisy data. Its applicability to verification seismology appears to be far broader than initial assumed due to the repeatability of signals generated by seismic events within close proximity of each other. If two events are co-located then the correspond- ing patterns in the waveforms from the two events are separated by the same time difference at all stations. This means that a zero delay stack- ing procedure can be applied across arrays and networks of, in principle, arbitrary size. The loss of coherence which precludes classical beam- forming over extended apertures no longer applies: the necessary conditions for waveform similarity are a proximity of the source locations and similarity of source mechanisms. Reference: Gibbons and Ringdal, Geophys. J. Int., 2006: http://dx.doi.org/10.1111/j.1365-246x.2006.02865.x! SPI ARC FIN HFS NOA EKA 03:07:00 03:08:00 03:09:00 03:10:00 Time (UTC) on 2013-043 (February 12) Triggering phase detection 1 3 3 5 5 7 7 9 9 9 -0.4 -0.2 0.0 0.2 0.4 Slowness Sy (N-S) -0.4 -0.2 0.0 0.2 0.4 Slowness Sx (E-W) FINES Isolines: dB below maximum 126˚ 126˚ 128˚ 128˚ 130˚ 130˚ 132˚ 132˚ 40˚ 40˚ 42˚ 42˚ 44˚ 44˚ Since a seismic array is able to provide an estimate of the direction from which a wavefront arrives, it is relatively simple to define criteria to decide if the arrival is a candidate for a phase generated by a seismic event at a site of special interest, such as a nuclear test site. In the case here, a detection with a high signal to noise ratio at the FINES array is found to be a P-phase from about 67 degrees azimuth, consistent with an arrival from the DPRK test site. If this is indeed an arrival from this site, then we know quite accurately the times at which P-phases from this hypothetical explosion would arrive at other seismic array stations (indicated by the blue boxes in the plot to the right). The blue boxes provide a kind of template for the site of interest. In each of the time-windows indicated by the boxes, detection lists are searched for phases which are consistent with an event at the target site. If there is evidence of characteristic phases in the time-windows defined by the template, the event hypothesis is strengthened and the associated phases are fed into an event location algorithm (using arrival times, backazimuth and slowness measurements). The figure to the left indicates the fully automatic ALERT location estimate (using the HYPOSAT program) for the event displayed above - the location is 12 km from the presumed location of the DPRK nuclear test site. The NORSAR Event Warning System (NEWS) provides automatic event alerts on http://www.norsardata.no/NDC/bulletins/alert/ Reference: Schweitzer, J., HYPOSAT – An Enhanced Routine to Locate Seismic Events, Pure appl. geophys., 2001: http://dx.doi.org/10.1007/pl00001160 The figure shows threshold monitoring results for a 30 minute time interval around the 2006 underground nuclear test in North Korea, using data from the operational IMS network. Notice that the array KSRS in South Korea was not certified at that time (and so not available to IDC operations) but that a 10 minute segment of KSRS data were subsequently added to illustrate the change in performance.

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Approaches to Array and Network Processing for Enhanced Nuclear Explosion Monitoring

Steven J. Gibbons, Johannes Schweitzer and Tormod KværnaNORSAR, P.O. Box 53, 2027 Norway

[email protected], [email protected], [email protected]

Site-specific ALERT warning system

Array-Based Waveform Correlation

Seismic Array Stations of the IMS

Empirical Matched Field Processing

Incoherent Array Processing

Threshold Monitoring

−180˚

−180˚

−120˚

−120˚

−60˚

−60˚

60˚

60˚

120˚

120˚

180˚

180˚

−60˚ −60˚

−30˚ −30˚

0˚ 0˚

30˚ 30˚

60˚ 60˚

SCHQULM

PPT

ROSC

LPAZ BDFB

CPUP

PLCA

MAW

STKA

NRIK

KBZ

KEST

KMBO

BOSA

VNDA

EKA

KVAR

MMAI

KURK

SPITS

HFS BVAR PETK

TORD

GEYT

NOA

ESDCMJARBRTR

SONM

MKAR

ILAR ARCES

NVARKSRS

GERES

WRA

PDAR

ZALV

ASAR

YKA

CMAR

USRK

TXAR

AKASG

FINES

DBIC

Primary Seismic Array

Auxiliary Seismic Array

Primary Seismic 3-C station

ARCES (PS28)

AKASG(PS45)

ASAR(PS3)

BRTR(PS43)

BVAR(AS57)

CMAR(PS41)

EKA(AS104)

ESDC(PS40)

FINES(PS17)

GERES(PS19)

GEYT(PS44)

HFS(AS101)

ILAR(PS49)

KSRS(PS31)

KURK(AS58)

KVAR(AS83)

MJAR(PS22)

MKAR(PS23)

MMAI(AS49)

NVAR(PS47)

PDAR(PS48)

PETK(PS36)

SONM(PS25)

SPITS(AS72)

TORD(PS26)

TXAR(PS46)

WRA(PS2)

YKA(PS9)

USRK(PS37)

ZALV(PS33)

40 km

20 km

10 km

10 kmNOA - NC2(PS27)

NOA - NBO(PS27)

NOA - NAO(PS27)

NOA - NC6(PS27)

NOA - NB2(PS27)

NOA - NC4(PS27)

NOA - NC3(PS27)

10 km

The array stations of the IMS seismic network are the most powerful stations for the detection and classification of seismicsignals. The time-delays between arrivals on the different sensorsallows for beamforming for the optimized detection of signalsfrom a given direction since noise from other directions is suppressed by the stacking operation. f-k analysis and relatedtechniques can estimate the direction of arrival and assist in phaseidentification. We here examine the exploitation of seismic arraysfor enhanced nuclear explosion monitoring.

Azi: 302.0o Vel: 10.59 km/s

−0.4

−0.2

0.0

0.2

0.4

Sy

−0.4 −0.2 0.0 0.2 0.4Sx

2009-145:00.56.47 (May 25) 2006-282:01.37.34 (October 9)

−0.4

−0.2

0.0

0.2

0.4

Sy

−0.4 −0.2 0.0 0.2 0.4Sx

Azi: 311.2o Vel: 9.41 km/s

306.5 o306.5 o

5 km/s

10 km/s

5 km/s

10 km/s

2013-043:02.59.56 (Feb 12)

−0.4

−0.2

0.0

0.2

0.4

Sy

−0.4 −0.2 0.0 0.2 0.4Sx

Azi: 307.9o Vel: 8.77 km/s

306.5 o

5 km/s

10 km/s

124˚

124˚

128˚

128˚

132˚

132˚

136˚

136˚

140˚

140˚

144˚

144˚

32˚ 32˚

34˚ 34˚

36˚ 36˚

38˚ 38˚

40˚ 40˚

42˚ 42˚

44˚ 44˚

46˚ 46˚

USRKJKA

MJAR

JNU

KSRS

(402 km)

(956 km)(439 km)

(1152 km)

(923 km)

The array stations of the IMS seismic network are the most powerful stations for the detection and classification of seismicsignals. The time-delays between arrivals on the different sensorsallows for beamforming for the optimized detection of signalsfrom a given direction since noise from other directions is suppressed by the stacking operation. f-k analysis and relatedtechniques can estimate the direction of arrival and assist in phaseidentification. We here examine the exploitation of seismic arraysfor enhanced nuclear explosion monitoring.

The MJAR array in Japan is the only seismic array ata regional distance to have recorded all three DPRKnuclear tests as a certified primary IMS station. However, it failed to contribute to the automaticSEL3 bulletin for all 3 events - despite strong signals.

0.0 5.0 10.0 15.0

May 25, 2009, black.October 9, 2006, red.

Waveforms filtered 2.0 - 8.0 Hz

MJA0_HHZ

MJB1_HHZ

MJB2_HHZ

MJB3_HHZ

MJB8_HHZ

Time (seconds) - absolute times not shown.

The reason for the failure of classical array processing at MJAR for thePn phase from the DPRK tests is that the waveforms are incoherentacross the array for the frequency band with optimal signal-to-noiseratio (SNR) - see the 2006 and 2009 signals above.It can be demonstrated however that robust detections and parameterestimates can be obtained for all 3 arrivals (lowermost panel) by spectrogram beamforming and smoothing of the resulting slownessgrids with the array response function for a 4-5 second signal.

References:Gibbons et al, Geophys. J. Int., 2008 http://dx.doi.org/10.1111/j.1365-246x.2007.03650.xGibbons, Pure. appl. geophys., 2012, http://dx.doi.org/10.1007/s00024-012-0613-2

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ectio

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Mon

itorin

g

Mag

1:30 1:35 1:40 1:45 1:50 1:55 2:00

9 Oct 2006 Day 282HH:MM (GMT)

IMS Network + KSRS

KSRS data

The red “Detection” trace shows continuous estimates of the smallest seismic event that can be detected by 3 or more stations in the network (at the 90% confidence level). Only P-phases are considered.The blue “Monitoring” trace shows continuous estimates of the largest seismic event that could possibly have occurred (at the 90% confidence level). Both P- and S-phases are considered for stations at regional distances.

In the context nuclear explosion monitoring it may be useful toobtain estimates of the largest events that might have occurredwithin a given location and time interval. Threshold monitor-ing is a method that applies the amplitude and travel-time pattern derived from previous events in the source region ofinterest to obtain continuous estimates of the largest events thatcould possibly have occurred (Monitoring), or the smallestseismic event that can be detected by e.g. 3 or more stations ofthe network (Detection). These estimates are based on theassumption that conventional methods like beamforming and band-pass filtering are used for data analysis.

Reference:Kværna et al., Seismological Research Letters, 2007: http://dx.doi.org/10.1785/gssrl.78.5.487

Starting time 2011-296:15.00 (October 23)

KKAR beam (2-4 Hz)

AGRB_bz (2-4 Hz)

Transformed empirical matched field statistic trace (KKAR)

15:00 15:10 15:20 15:30 15:40 15:50

CC trace (full array) with mainshock template (KKAR)

CC trace (single channel KK01) with mainshock template

15:45 15:47 15:49

Zoom in

In extensive aftershocksequences after verylarge earthquakes, corre-lation detectors using themainshock signal as thetemplate are usually veryineffective at detectingaftershocks (due tosource location, spectralcontent of signals etc.).The narrowband EMFPmethod is effective atgenerating triggers. Heredemonstrated for theOctober 23, 2011, Vanearthquake, EMFPdetects aftershock signalsdown to the noise level.

2 Hz

4 Hz

8 Hz

Plane wave Real data (event 1) Real data (event 2)A waveform correlation detector compares the ups anddowns of a template seismic signal with successive segmentsof incoming data and triggers a detection when a sufficientlyclose match is observed.A correlator is the optimal detector for two identical signals,but suffers when waveforms differ due to, for example, different source-time functions. Empirical Matched FieldProcessing (EMFP) is a narrowband technique whichmatches the phase and amplitude relations between the sensors of an array or network for a given incoming wavefront. The narrowband nature makes it far less sensitiveto the source-time function and/or significant spectral differences between the master and detected signals.

Reference:Harris and Kværna, Geophys. J. Int., 2010: http://dx.doi.org/10.1111/j.1365-246x.2010.04684.x

A greatly enhanced detection capability results from the stacking of correlationcoefficient traces across an array or network. False alarms - positive detectionsfrom noise or signals from sources unrelated to the master event - do occur.Two wavefronts approaching an array from the same direction will result incorrelation coefficient traces which are well aligned at the time of a detection.If f-k analysis on the correlation coefficient traces does not result in an almost-zero slowness vector then the two wavefronts cannot come from the samedirection and the detection has to be a false alarm. This allows us to run thedetectors at aggressively lowthresholds with exceptionally low false alarmrates.The figures display the detection of the 2013 DPRK nuclear test on the NOAarray using the 2009 test signal as a template (above) and the f-k verificationthat the wavefronts approached the array from the same direction (left).

03:08:30 03:08:40 03:08:50

Starting time: 2013-043:03.08.30

Detection statistic stack (maximum 0.639)

Detection statistic NC200_BHZ (maximum 0.746)

Detection statistic NC602_BHZ (maximum 0.530)

Detection statistic NAO01_BHZ (maximum 0.540)

NC200_BHZ

NC602_BHZ

NAO01_BHZ max. amp. 838

max. amp. 578

max. amp. 865

max. amp. 495

max. amp. 1009

max. amp. 844

TEMPLATE

TEMPLATE

TEMPLATETEMPLATE

TEMPLATE

TEMPLATE

35

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7

7 7

7

7

9

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9

9

9

0.00

Slow

ness

Sy

(N-S

)

0.00 0.25-0.25

-0.25

0.25

Slowness Sx (E-W)

NOA array:f-k analysis of single channel detection statistic tracesTemplate time: 2009-145:01.05.30Maximum of detection statistic: 2013-043:03.08.38.153

A matched filter or correlation detector is themost effective method for detecting a known signal in noisy data. Its applicability to verification seismology appears to be far broaderthan initial assumed due to the repeatability ofsignals generated by seismic events within closeproximity of each other.

If two events are co-located then the correspond-ing patterns in the waveforms from the twoevents are separated by the same time differenceat all stations. This means that a zero delay stack-ing procedure can be applied across arrays andnetworks of, in principle, arbitrary size. The lossof coherence which precludes classical beam-forming over extended apertures no longerapplies: the necessary conditions for waveformsimilarity are a proximity of the source locationsand similarity of source mechanisms.

Reference:Gibbons and Ringdal, Geophys. J. Int., 2006: http://dx.doi.org/10.1111/j.1365-246x.2006.02865.x!

SPI

ARC

FIN

HFS

NOA

EKA

03:07:00 03:08:00 03:09:00 03:10:00

Time (UTC) on 2013-043 (February 12)

Triggering phase detection

1

3

3

5

5

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9

9

-0.4

-0.2

0.0

0.2

0.4

Slow

ness

Sy

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)

-0.4 -0.2 0.0 0.2 0.4

Slowness Sx (E-W)

FINESIsolines: dB below maximum

126˚

126˚

128˚

128˚

130˚

130˚

132˚

132˚

40˚ 40˚

42˚ 42˚

44˚ 44˚

Since a seismic array is able to provide anestimate of the direction from which awavefront arrives, it is relatively simple todefine criteria to decide if the arrival is acandidate for a phase generated by a seismic event at a site of special interest,such as a nuclear test site.

In the case here, a detection with a highsignal to noise ratio at the FINES array isfound to be a P-phase from about 67degrees azimuth, consistent with an arrivalfrom the DPRK test site. If this is indeedan arrival from this site, then we knowquite accurately the times at which P-phases from this hypothetical explosionwould arrive at other seismic array stations(indicated by the blue boxes in the plot tothe right).

The blue boxes provide a kind of template for the site of interest. In each of the time-windows indicated by the boxes, detection lists are searched for phases whichare consistent with an event at the target site. If there is evidence of characteristicphases in the time-windows defined by the template, the event hypothesis is strengthened and the associated phases are fed into an event location algorithm (usingarrival times, backazimuth and slowness measurements). The figure to the left indicates the fully automatic ALERT location estimate (using the HYPOSAT program) for the event displayed above - the location is 12 km from the presumedlocation of the DPRK nuclear test site.The NORSAR Event Warning System (NEWS) provides automatic event alerts onhttp://www.norsardata.no/NDC/bulletins/alert/

Reference:Schweitzer, J., HYPOSAT – An Enhanced Routine to Locate Seismic Events,Pure appl. geophys., 2001: http://dx.doi.org/10.1007/pl00001160

The figure shows threshold monitoring results for a 30 minutetime interval around the 2006 underground nuclear test inNorth Korea, using data from the operational IMS network.Notice that the array KSRS in South Korea was not certified atthat time (and so not available to IDC operations) but that a 10minute segment of KSRS data were subsequently added toillustrate the change in performance.