application of detection probabilities in the idc global

1
Application of Detection Probabilities in the IDC Global Phase Association Process Tormod Kværna(1),Frode Ringdal(1) and Jeffrey Given(2) (1) NORSAR, Kjeller, Norway ([email protected]), (2) CTBTO Prep Com, International Data Centre, Vienna, Austria Abstract Examples of Application to SEL3 Event Lists Detection Capabilities The Global Association (GA) process at the IDC is an automated procedure that associ- ates detections by stations in the International Monitoring System (IMS) in order to form event hypotheses. These hypotheses will later be reviewed by analysts before the Reviewed Event Bulletin is issued. We have begun investigating ways to improve the GA process for seismic data, in particular by incorporating amplitude data and station detection probabilities in the automatic process. We build on a previous study which has provided regional detection capability estimates for individual primary and auxiliary IMS stations, and use these estimates to develop and test various consistency measures. The purpose of these measures is to provide a means to assess the validity of automati- cally defined seismic events and the consistency of individual phases associated with such events. By feeding the results of such assessments back to the GA procedure, we anticipate that the results of the global association can be iteratively improved. An important contribution to these assessments will be provided by incorporating the results of the continuous IDC Threshold Monitoring process. The initial results of this study are promising, and this paper will present some case studies illustrating our approach. We will illustrate the procedure by considering an example: We consider one sta- tion (ARCES) and a specific source area (1.5 degrees within 32N, 104E). Our pur- pose is to estimate the station detection threshold for events from this limited source area. From the REB, we obtain a large number of events, some detected by ARCES, some undetected (right figure above). We can the estimate the threshold directly by maximum likelihood (MLE), using the detection/nondetection infor- mation (Method 1). We would like to make use of the SNR information to obtain estimates when there are only few data. For each event detected by ARCES, we scale down the mb by its log(SNR), to arrive at an instantaneous 'noise magnitude'. We then add a signal-to- noise ratio of 3 (0.5 mb units) to obtain an instantaneous estimate of the ARCES detection threshold. This way we can obtain an average threshold based on the detected events. (See the figures to the right above). We denote this Method 2. Note that the undetected events will cause a bias in the application of Method 2. For this reason, we have developed Method 3, as indicated below. In Method 3, we compensate for the non-detections by applying maximum likelihood estimation to the scaled-down thresholds. This is is our preferred method and will be applied where possible (i.e. where information on non-detections is available). 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 0 100 200 300 Number of events Scaled Network mb1MLE - Detections - Non-detections Ndet : 722 Nnon : 697 MLEscale : 3.814 Std : 0.311 3 3.5 4 4.5 5 5.5 6 Network mb1MLE Signal-to-noise ratio 103 102 101 100 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 2.5 3 3.5 4 4.5 5 Network mb1MLE Scaled Network mb1 MLE MLEscale : 3.814 AVGscale : 3.690 0.21 1.07 4.40 10.86 ARCES P-beam, 2.5 - 4.5 Hz 10 15 20 0 5 SNR 10 15 20 0 5 Network mbmx 3.405 3.951 4.444 5.168 SNR4.92 Amp SNR21.37 SNR45.77 SNR131.34 mbmx - log10(SNRmax) 2.713 2.620 2.780 3.050 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 0 0.2 0.4 0.6 0.8 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 0 50 100 150 200 Magnitude ARCES Lat: 32 o N Lon: 104 o E Radius:1.5o Delta: 56.5 o Network mb1MLE Probability Number of events Network mb1MLE - Detections - Non-detections Ndet : 722 Nnon : 697 MLEdet : 3.745 Std : 0.271 20˚ 20˚ 40˚ 40˚ 60˚ 60˚ 80˚ 80˚ 100˚ 100˚ 120˚ 120˚ 20˚ 20˚ 30˚ 30˚ 40˚ 40˚ 50˚ 50˚ 60˚ 60˚ 70˚ 70˚ ARCES Map showing the estimated regional event detection thresholds for IMS primary station AKASG. For each of the 2x2 degree bins, a minimum of 5 events are required for calculation of the detection threshold. Distances of 20, 95 and 144 degrees from AKASG are illustrated by red dashed lines. 0 20 40 60 80 100 120 140 160 180 0 1 2 3 4 5 6 Distance (degrees) Detection Threshold (mb1) AKASG bin size 2.0 115°° 20°° 0°° The black dots show the estimated regional event detection thresholds for IMS primary station AKASG plotted versus epicentral distance. For each of the distance ranges 0-20 degrees, 20-90 degrees, and 115-180 degrees, the mb1 amplitude-distance curve is fitted to the data. The num- bers for each of the distance ranges, given in the lower right box, are: 1) the constant offset level of the mb1 amplitude-distance curve 2) the standard deviation, and 3) the number of bins. In general, the lower the constant offset level, the better is the overall station detection capability. Estimating detection thresholds The left figure above shows how to compensate for the average bias in the estimate by Method 2. We will need to use Method 2 for estimating the thresholds in those cases when non-detection information is not available. This means outside of the 20 -9 0 degrees distance range for primary stations and at all distance ranges for auxiliary stations The right hand figure above shows that Method 1 (MLEdet) and Method 3 (MLEscale) are consistent when there is sufficient data to obtain reliable estimates by both methods. The figure above illustrates, as an example, the number of IDC REB events with P-phases reported at IMS primary station AKASG. Only events with depth less than 50 km are considered. The upper map is a global projection where the colors correspond to the number of events in 2x2 degree bins. Distances of 20, 95 and 144 degrees from AKASG are illustrated by red dashed lines. The lower map is an azimuthal projection where the colors correspond to the number of events in 1x1 degree bins. The red dashed circle shows a distance of 20 degrees from AKASG. Ranking of primary stations (top) and auxiliary stations (bottom) in the distance range 20-90 degrees. We have developed a scheme to automatically process the individual candi- date events in either SEL1, SEL2 or SEL3. For each event a set of consis- tency measures is calculated, and some of them are shown in the examples. The consistency measures can be used individually or in combination. The most effective scheme is still to be developed. In the examples presented here, we have, in addition to calculating consis- tency measures based exclusively on SEL3 bulletin data, also correlated the candidate events with the events actually accepted in the REB (or LEB). This provides a possibility to evaluate the consistency measures against the decision of the analyst. In practical operation, it is intended to apply this processing scheme auto- matically, using the information from the SEL bulletins, the regionalized detection thresholds of the IMS stations, and the Threshold Monitoring results which are automatically computed at the IDC. Candidate events could be either accepted or rejected, or in some cases returned to the GA process for reanalysis, with one or more phases excluded from consider- ation. Besides producing improved SEL lists, this processing scheme could also be applied in an interactive mode to provide the analyst with an assessment of the quality of the candidate event with respect to the pattern of detections/non-detections in view of the individual station capabilities. First we show an example of one of many excellent automatic solutions in the SEL3. This is a candidate SEL3 event in the Afghanistan-Tajikistan border region, which has been accepted in the LEB and REB. It satisfies all our main indicators, and the REB location is only 16 km away from the automatic solution. This event would be acceptable for analyst review without any further processing. Non-detecting operational IMS primary stations Station Delta Event magnitude Detection threshold Sigma Detection probability TORD 9.70 3.5363 2.9086 0.3000 0.981800 MKAR 83.73 3.5363 3.7313 0.3300 0.277324 FINES 59.18 3.5363 3.8318 0.3370 0.190282 BRTR 48.14 3.5363 3.8190 0.3000 0.173042 AKASG 52.37 3.5363 3.8287 0.3000 0.164861 GERES 44.78 3.5363 3.8528 0.3070 0.151312 YKA 92.09 3.5363 4.0508 0.4260 0.113574 ARCES 65.59 3.5363 4.0040 0.3740 0.105570 ZALV 84.80 3.5363 3.9853 0.3360 0.090752 LPAZ 65.64 3.5363 4.0100 0.3410 0.082410 ESDC 32.42 3.5363 3.9990 0.3120 0.069051 NOA 55.29 3.5363 4.0030 0.3000 0.059908 KBZ 56.13 3.5363 4.0293 0.3160 0.059384 WRA 139.62 3.5363 4.1460 0.3800 0.054315 ASAR 138.29 3.5363 4.1330 0.3620 0.049652 BOSA 46.69 3.5363 4.0929 0.3150 0.038626 GEYT 65.34 3.5363 4.0750 0.3000 0.036284 KEST 31.76 3.5363 4.2390 0.3460 0.021141 CPUP 59.80 3.5363 4.2120 0.3200 0.017361 BDFB 47.30 3.5363 4.1760 0.3000 0.016499 KMBO 44.03 3.5363 4.3623 0.3360 0.006981 SCHQ 67.56 3.5363 4.3396 0.3150 0.005388 MAW 88.74 3.5363 4.6437 0.3850 0.002011 ROSC 67.83 3.5363 4.5593 0.3340 0.001096 ILAR 102.56 3.5363 4.6168 0.3480 0.000952 KSRS 118.26 3.5363 4.8590 0.3970 0.000432 SONM 99.45 3.5363 4.6297 0.3160 0.000270 MJAR 125.17 3.5363 4.9410 0.3550 0.000038 CMAR 101.86 3.5363 4.9074 0.3420 0.000030 PETK 118.40 3.5363 5.0220 0.3650 0.000023 VNDA 109.40 3.5363 5.3630 0.4290 0.000010 NVAR 102.58 3.5363 4.9104 0.3000 0.000002 USRK 116.42 3.5363 5.1440 0.3370 0.000001 PPT 142.92 3.5363 5.5010 0.3000 0.000000 Number of primary non-detections: 34 Number of stations exceeding third detection probability 22 Number of stations exceeding lowest detection probability 22 Northwest Africa Event only in SEL3 Event id Year Mo Dy Hr Min Sec Lat Lon Depth REB Lat REB Lon REB-SEL3 loc. diff SEL3 mb New mbMLE 6828087 2010 11 10 03 24 24.400 7.17 -6.10 0.0f - - - 4.23 3.54 2) Detecting stations Station Phase Delta Event magnitude Detection threshold Sigma Detection probability Station magnitude DBIC Pg 1.33 3.5363 1.1059 0.4320 1.000000 - PLCA P 75.84 3.5363 4.3974 0.3000 0.002051 4.30 ULM P 84.40 3.5363 4.4208 0.3090 0.002102 4.50 TXAR P 93.08 3.5363 4.0911 0.3220 0.042467 3.90 Third highest detection probability 0.002102 Lowest detection probability 0.002051 This shows a candidate SEL3 event in Northwest Africa which has not been accepted in the REB. Three of the four detecting stations have a detection probability near zero. One non-detecting station (TORD) has a detection probability as high as 0.98. As many as 22 stations have better detection probability than the third best detecting stations. This event is clearly false. This shows a candidate SEL3 event in North Indian Ocean, which has been accepted in the REB, although with an epicentre moved by 586 km. We note that out of the three detecting stations, one (DBIC) has a detection probability as low as 0.000042. In this case, DBIC would be deleted from consideration, and the remaining detections would be returned to GA for reprocessing. North Indian Ocean Event in SEL, REB and LEB Event id Year Mo Dy Hr Min Sec Lat Lon Depth REB Lat REB Lon REB-SEL3 loc. diff SEL3 mb New mbMLE 6828625 2010 11 10 5 20 18.000 0.21 91.70 0.0f 3.87 95.52 586 km 5.10 3.49 3) Detecting stations Station Phase Delta Event magnitude Detection threshold Sigma Detection probability Station magnitude CMAR P 19.48 3.4880 3.6318 0.4020 0.360322 - ASAR P 47.34 3.4880 3.4294 0.3510 0.566320 - DBIC P 96.48 3.4880 4.7119 0.3110 0.000042 5.10 Third highest detection probability 0.000042 Lowest detection probability 0.000042 Non-detecting operational IMS primary stations Station Delta Event magnitude Detection threshold Sigma Detection probability WRA 46.31 3.4880 3.4691 0.3640 0.520715 MKAR 47.12 3.4880 3.4952 0.3300 0.491359 TXAR 147.16 3.4880 3.6420 0.3670 0.337386 SONM 49.12 3.4880 3.7132 0.3160 0.238007 ZALV 53.85 3.4880 3.7700 0.3360 0.200658 TORD 89.95 3.4880 3.8572 0.3390 0.138082 FINES 78.37 3.4880 3.9500 0.3370 0.085202 BRTR 65.77 3.4880 3.9190 0.3000 0.075408 AKASG 72.74 3.4880 3.9524 0.3000 0.060826 GEYT 48.62 3.4880 3.9750 0.3000 0.052261 ARCES 81.64 3.4880 4.1104 0.3740 0.048049 KSRS 49.86 3.4880 4.0816 0.3270 0.034737 KBZ 61.31 3.4880 4.0680 0.3160 0.033221 GERES 81.94 3.4880 4.0844 0.3070 0.026026 VNDA 85.97 3.4880 4.3682 0.3950 0.012930 USRK 56.55 3.4880 4.2385 0.3330 0.012105 YKA 114.39 3.4880 4.4480 0.4170 0.010663 BOSA 69.53 3.4880 4.2313 0.3150 0.009142 NOA 85.20 3.4880 4.2189 0.3000 0.007416 MAW 70.59 3.4880 4.4299 0.3850 0.007212 LPAZ 154.49 3.4880 4.4103 0.3680 0.006099 MJAR 56.21 3.4880 4.3241 0.3290 0.005522 PETK 75.63 3.4880 4.4923 0.3850 0.004546 NVAR 132.68 3.4880 4.4140 0.3370 0.003000 KMBO 54.46 3.4880 4.4266 0.3360 0.002608 KEST 83.66 3.4880 4.4626 0.3460 0.002426 ESDC 94.23 3.4880 4.4686 0.3120 0.000836 ILAR 102.71 3.4880 4.6138 0.3480 0.000608 PLCA 136.56 3.4880 4.9210 0.3980 0.000159 SCHQ 122.37 3.4880 4.9540 0.4000 0.000124 CPUP 140.45 3.4880 4.9090 0.3820 0.000100 ULM 129.31 3.4880 4.8710 0.3700 0.000093 BDFB 137.38 3.4880 5.0540 0.3730 0.000013 ROSC 165.16 3.4880 5.1427 0.3630 0.000003 PPT 117.36 3.4880 6.3010 0.3000 0.000000 Number of primary non-detections 35 Number of stations exceeding third detection probability 32 Number of stations exceeding lowest detection probability 32 Afghanistan-Tadjikistan border region Event in SEL, REB and LEB Event id Year Mo Dy Hr Min Sec Lat Lon Depth REB Lat REB Lon REB-SEL3 loc. diff SEL3 mb New mbMLE 6830385 2010 11 10 22 21 36.250 36.34 71.40 157.5 36.20 71.37 16 km 3.52 3.16 1) Detecting stations Station Phase Delta Event magnitude Detection threshold Sigma Detection probability Station magnitude AAK P 6.87 3.1557 2.7047 0.4260 0.855138 - GEYT P 10.73 3.1557 3.2519 0.4180 0.408932 - MKAR P 13.36 3.1557 2.6928 0.4470 0.849779 - KURK P 15.31 3.1557 2.8657 0.3910 0.770830 - BVAR P 16.84 3.1557 2.7482 0.3360 0.887391 - AKTO P 17.19 3.1557 2.8662 0.3030 0.830295 - ZALV P 20.07 3.1557 2.7491 0.3360 0.886870 3.40 BRTR P 29.81 3.1557 3.4075 0.3000 0.200592 3.20 FINES P 37.90 3.1557 3.2897 0.3370 0.345431 3.60 ARCES P 41.53 3.1557 3.4163 0.3740 0.242926 3.70 HFS P 43.48 3.1557 3.4440 0.4010 0.236025 3.60 TORD P 66.01 3.1557 3.1298 0.3390 0.530415 3.60 Third highest detection probability 0.855138 Lowest detection probability 0.200592 Non-detecting operational IMS primary stations Station Delta Event magnitude Detection threshold Sigma Detection probability ASAR 83.84 3.1557 3.2145 0.3510 0.433491 WRA 81.58 3.1557 3.2310 0.3640 0.418019 KBZ 23.00 3.1557 3.2372 0.3160 0.398225 ILAR 74.99 3.1557 3.2713 0.3480 0.369896 SONM 28.26 3.1557 3.2928 0.3160 0.332172 YKA 81.53 3.1557 3.3805 0.4260 0.298848 AKASG 33.36 3.1557 3.3591 0.3000 0.248844 CMAR 30.05 3.1557 3.4142 0.3420 0.224810 GERES 43.34 3.1557 3.3915 0.3070 0.221233 NOA 44.80 3.1557 3.4917 0.3000 0.131319 KSRS 44.67 3.1557 3.6005 0.3270 0.086881 ESDC 57.86 3.1557 3.6144 0.3120 0.070742 PLCA 150.00 3.1557 3.8126 0.3980 0.049416 USRK 46.06 3.1557 3.7229 0.3330 0.044235 KEST 49.41 3.1557 3.7904 0.3460 0.033292 PETK 59.98 3.1557 3.9567 0.3850 0.018741 DBIC 74.98 3.1557 3.8082 0.3110 0.017938 MJAR 52.82 3.1557 3.8620 0.3290 0.015901 BOSA 77.71 3.1557 3.8413 0.3150 0.014758 KMBO 48.85 3.1557 3.9416 0.3360 0.009665 TXAR 114.65 3.1557 4.0336 0.3670 0.008375 SCHQ 82.49 3.1557 3.9831 0.3150 0.004309 VNDA 125.13 3.1557 4.4546 0.4290 0.001232 LPAZ 138.99 3.1557 4.3666 0.3680 0.000500 CPUP 135.50 3.1557 4.5006 0.3820 0.000215 ULM 93.19 3.1557 4.3342 0.3090 0.000068 NVAR 105.20 3.1557 4.5056 0.3370 0.000031 BDFB 122.68 3.1557 4.6956 0.3730 0.000018 ROSC 128.05 3.1557 4.7096 0.3630 0.000009 MAW 103.69 3.1557 4.9377 0.3850 0.000002 PPT 139.41 3.1557 5.7926 0.3000 0.000000 Number of primary non/detections 31 Number of stations exceeding third detection probability 0 Number of stations exceeding lowest detection probability 9 3 3.5 4 4.5 5 −0.4 −0.2 0 0.2 0.4 Mean : 0.117 St.dev : 0.069 Nobs : 984 AVGscale mb1 MLEscale − AVGscale P1 = 0.103, P0 = −0.278 3 3.5 4 4.5 5 −0.4 −0.2 0 0.2 0.4 St.dev : 0.064 AVGscale mb1 MLEscale − AVGscale ARCES 3 3.5 4 4.5 5 3 3.5 4 4.5 5 MLEdet mb1 MLEscale mb1 ARCES Mean difference: 0.039 St. dev : 0.047 Nobs : 580 −1 −0.5 0 0.5 1 1.5 ASAR TORD WRA MKAR ILAR YKA TXAR BGCA SONM PDAR ZALV FINES AKASG BRTR CMAR NVAR GERES ARCES LPAZ NOA KBZ ESDC STKA KSRS DBIC VNDA BOSA CPUP BDFB ULM USRK SCHQ PLCA KEST THR MJAR MAW PETK KMBO ROSC PPT Station detection level (mb1 units) Primary stations Teleseismic distances (20 - 90 degrees) −1 −0.5 0 0.5 1 1.5 KURK BVAR QSPA SIV SNAA AKTO INK HFS MATP RES EKA AAK CFAA ELK LSZ FITZ MSKU SDV MLR ANMO APG LBTB TSUM MDT FRB SPITS DAVOX LVC NEW DLBC TKL YBH VRAC ASF IDI KDAK DAV MMAI PSI CTA ATAH Station detection level (mb1 units) Auxiliary stations Teleseismic distances (20 - 90 degrees) Database

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Page 1: Application of Detection Probabilities in the IDC Global

Application of Detection Probabilities in the IDC Global Phase Association ProcessTormod Kværna(1),Frode Ringdal(1) and Jeffrey Given(2)

(1) NORSAR, Kjeller, Norway ([email protected]), (2) CTBTO Prep Com, International Data Centre, Vienna, Austria

Abstract Examples of Application to SEL3 Event ListsDetection CapabilitiesThe Global Association (GA) process at the IDC is an automated procedure that associ-ates detections by stations in the International Monitoring System (IMS) in order to formevent hypotheses. These hypotheses will later be reviewed by analysts before theReviewed Event Bulletin is issued. We have begun investigating ways to improve theGA process for seismic data, in particular by incorporating amplitude data and stationdetection probabilities in the automatic process. We build on a previous study which hasprovided regional detection capability estimates for individual primary and auxiliaryIMS stations, and use these estimates to develop and test various consistency measures.The purpose of these measures is to provide a means to assess the validity of automati-cally defined seismic events and the consistency of individual phases associated withsuch events. By feeding the results of such assessments back to the GA procedure, weanticipate that the results of the global association can be iteratively improved. Animportant contribution to these assessments will be provided by incorporating the resultsof the continuous IDC Threshold Monitoring process. The initial results of this study arepromising, and this paper will present some case studies illustrating our approach.

We will illustrate the procedure by considering an example: We consider one sta-tion (ARCES) and a specific source area (1.5 degrees within 32N, 104E). Our pur-pose is to estimate the station detection threshold for events from this limitedsource area. From the REB, we obtain a large number of events, some detected byARCES, some undetected (right figure above). We can the estimate the thresholddirectly by maximum likelihood (MLE), using the detection/nondetection infor-mation (Method 1).

We would like to make use of the SNR information to obtain estimates when thereare only few data. For each event detected by ARCES, we scale down the mb by itslog(SNR), to arrive at an instantaneous 'noise magnitude'. We then add a signal-to-noise ratio of 3 (0.5 mb units) to obtain an instantaneous estimate of the ARCESdetection threshold. This way we can obtain an average threshold based on thedetected events. (See the figures to the right above). We denote this Method 2.

Note that the undetected events will cause a bias in the application of Method 2. Forthis reason, we have developed Method 3, as indicated below.

In Method 3, we compensate for the non-detections by applying maximum likelihoodestimation to the scaled-down thresholds. This is is our preferred method and will beapplied where possible (i.e. where information on non-detections is available).

1.5 2 2.5 3 3.5 4 4.5 5 5.5 60

100

200

300

Num

ber o

f eve

nts

Scaled Network mb1MLE

- Detections- Non-detections

Ndet : 722Nnon : 697MLEscale : 3.814Std : 0.311

3 3.5 4 4.5 5 5.5 6

Network mb1MLE

Sign

al-t

o-no

ise

ratio

103

102

101

100

1.5 2 2.5 3 3.5 4 4.5 5 5.5 62.5

3

3.5

4

4.5

5

Network mb1MLE

Scal

ed N

etw

ork

mb1

MLE

MLEscale : 3.814AVGscale : 3.690

0.21

1.07

4.40

10.86

ARCES P-beam, 2.5 - 4.5 Hz

10 15 200 5

SNR

10 15 200 5

Networkmbmx

3.405

3.951

4.444

5.168

SNRmax 4.92

Amp

SNRmax 21.37

SNRmax 45.77

SNRmax 131.34

mbmx - log10(SNRmax)

2.713

2.620

2.780

3.050

1.5 2 2.5 3 3.5 4 4.5 5 5.5 60

0.2

0.4

0.6

0.8

1

1.5 2 2.5 3 3.5 4 4.5 5 5.5 60

50

100

150

200

Magnitude

ARCES Lat: 32oN Lon: 104oE Radius:1.5o Delta: 56.5o

Network mb1MLE

Prob

abili

tyN

umbe

r of e

vent

s

Network mb1MLE

- Detections- Non-detections

Ndet : 722Nnon : 697MLEdet : 3.745Std : 0.271

20˚

20˚

40˚

40˚

60˚

60˚

80˚

80˚

100˚

100˚

120˚

120˚

20˚ 20˚

30˚ 30˚

40˚ 40˚

50˚ 50˚

60˚ 60˚

70˚ 70˚ARCES

Map showing the estimated regional event detection thresholds for IMS primarystation AKASG. For each of the 2x2 degree bins, a minimum of 5 events arerequired for calculation of the detection threshold. Distances of 20, 95 and 144degrees from AKASG are illustrated by red dashed lines.

0 20 40 60 80 100 120 140 160 1800

1

2

3

4

5

6

Distance (degrees)

Det

ectio

n Th

resh

old

(mb1

)

AKASG bin size 2.0

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The black dots show the estimatedregional event detection thresholdsfor IMS primary station AKASGplotted versus epicentral distance.For each of the distance ranges 0-20degrees, 20-90 degrees, and 115-180degrees, the mb1 amplitude-distancecurve is fitted to the data. The num-bers for each of the distance ranges,given in the lower right box, are:1) the constant offset level of the mb1 amplitude-distance curve2) the standard deviation, and3) the number of bins.In general, the lower the constantoffset level, the better is the overallstation detection capability.

Estimating detection thresholds

The left figure above shows how to compensate for the average bias in theestimate by Method 2. We will need to use Method 2 for estimating thethresholds in those cases when non-detection information is not available.This means outside of the 20 -9 0 degrees distance range for primary stations and at all distance ranges for auxiliary stations

The right hand figure above shows that Method 1 (MLEdet) and Method 3(MLEscale) are consistent when there is sufficient data to obtain reliableestimates by both methods.

The figure above illustrates, as an example, the number of IDC REB events with P-phases reported at IMS primary station AKASG. Only events with depth less than 50 km are considered. The upper map is a global projection where the colors correspond to the number of events in 2x2 degree bins. Distances of 20, 95 and 144 degrees from AKASG are illustrated by red dashed lines. The lower map is an azimuthal projection where the colors correspond to the number of events in 1x1 degree bins. The red dashed circle shows a distance of 20 degrees from AKASG. Ranking of primary stations (top) and auxiliary stations (bottom) in the

distance range 20-90 degrees.

We have developed a scheme to automatically process the individual candi-date events in either SEL1, SEL2 or SEL3. For each event a set of consis-tency measures is calculated, and some of them are shown in the examples.The consistency measures can be used individually or in combination. Themost effective scheme is still to be developed.

In the examples presented here, we have, in addition to calculating consis-tency measures based exclusively on SEL3 bulletin data, also correlated thecandidate events with the events actually accepted in the REB (or LEB).This provides a possibility to evaluate the consistency measures against thedecision of the analyst.

In practical operation, it is intended to apply this processing scheme auto-matically, using the information from the SEL bulletins, the regionalizeddetection thresholds of the IMS stations, and the Threshold Monitoringresults which are automatically computed at the IDC. Candidate eventscould be either accepted or rejected, or in some cases returned to the GAprocess for reanalysis, with one or more phases excluded from consider-ation.

Besides producing improved SEL lists, this processing scheme could also beapplied in an interactive mode to provide the analyst with an assessment ofthe quality of the candidate event with respect to the pattern of detections/non-detections in view of the individual station capabilities.

First we show an example of one of manyexcellent automatic solutions in the SEL3.This is a candidate SEL3 event in theAfghanistan-Tajikistan border region,which has been accepted in the LEB andREB. It satisfies all our main indicators,and the REB location is only 16 km awayfrom the automatic solution. This eventwould be acceptable for analyst reviewwithout any further processing.

Non-detecting operational IMS primary stations

Station DeltaEvent

magnitudeDetectionthreshold

SigmaDetectionprobability

TORD 9.70 3.5363 2.9086 0.3000 0.981800

MKAR 83.73 3.5363 3.7313 0.3300 0.277324

FINES 59.18 3.5363 3.8318 0.3370 0.190282

BRTR 48.14 3.5363 3.8190 0.3000 0.173042

AKASG 52.37 3.5363 3.8287 0.3000 0.164861

GERES 44.78 3.5363 3.8528 0.3070 0.151312

YKA 92.09 3.5363 4.0508 0.4260 0.113574

ARCES 65.59 3.5363 4.0040 0.3740 0.105570

ZALV 84.80 3.5363 3.9853 0.3360 0.090752

LPAZ 65.64 3.5363 4.0100 0.3410 0.082410

ESDC 32.42 3.5363 3.9990 0.3120 0.069051

NOA 55.29 3.5363 4.0030 0.3000 0.059908

KBZ 56.13 3.5363 4.0293 0.3160 0.059384

WRA 139.62 3.5363 4.1460 0.3800 0.054315

ASAR 138.29 3.5363 4.1330 0.3620 0.049652

BOSA 46.69 3.5363 4.0929 0.3150 0.038626

GEYT 65.34 3.5363 4.0750 0.3000 0.036284

KEST 31.76 3.5363 4.2390 0.3460 0.021141

CPUP 59.80 3.5363 4.2120 0.3200 0.017361

BDFB 47.30 3.5363 4.1760 0.3000 0.016499

KMBO 44.03 3.5363 4.3623 0.3360 0.006981

SCHQ 67.56 3.5363 4.3396 0.3150 0.005388

MAW 88.74 3.5363 4.6437 0.3850 0.002011

ROSC 67.83 3.5363 4.5593 0.3340 0.001096

ILAR 102.56 3.5363 4.6168 0.3480 0.000952

KSRS 118.26 3.5363 4.8590 0.3970 0.000432

SONM 99.45 3.5363 4.6297 0.3160 0.000270

MJAR 125.17 3.5363 4.9410 0.3550 0.000038

CMAR 101.86 3.5363 4.9074 0.3420 0.000030

PETK 118.40 3.5363 5.0220 0.3650 0.000023

VNDA 109.40 3.5363 5.3630 0.4290 0.000010

NVAR 102.58 3.5363 4.9104 0.3000 0.000002

USRK 116.42 3.5363 5.1440 0.3370 0.000001

PPT 142.92 3.5363 5.5010 0.3000 0.000000

Number of primary non-detections: 34

Number of stations exceeding third detection probability 22

Number of stations exceeding lowest detection probability 22

Northwest Africa Event only in SEL3

Event id Year Mo Dy Hr Min Sec Lat Lon DepthREBLat

REBLon

REB-SEL3loc. diff

SEL3mb

NewmbMLE

6828087 2010 11 10 03 24 24.400 7.17 -6.10 0.0f - - - 4.23 3.54

2)

Detecting stations

Station Phase DeltaEvent

magnitudeDetectionthreshold

SigmaDetectionprobability

Stationmagnitude

DBIC Pg 1.33 3.5363 1.1059 0.4320 1.000000 -

PLCA P 75.84 3.5363 4.3974 0.3000 0.002051 4.30

ULM P 84.40 3.5363 4.4208 0.3090 0.002102 4.50

TXAR P 93.08 3.5363 4.0911 0.3220 0.042467 3.90

Third highest detection probability 0.002102

Lowest detection probability 0.002051

This shows a candidate SEL3 event in Northwest Africa which has not been accepted in the REB. Three of the four detecting stations have a detection probability near zero. One non-detecting station (TORD) has a detection probability as high as 0.98. As many as 22 stations have better detection probability than the third best detecting stations. This event is clearly false.

This shows a candidate SEL3 event in North Indian Ocean, which has been accepted in the REB, although with an epicentre moved by 586 km. We note that out of the three detecting stations, one (DBIC) has a detection probability as low as 0.000042. In this case, DBIC would be deleted from consideration, and the remaining detections would be returned to GA for reprocessing.

North Indian Ocean Event in SEL, REB and LEB

Event id Year Mo Dy Hr Min Sec Lat Lon DepthREBLat

REBLon

REB-SEL3loc. diff

SEL3mb

NewmbMLE

6828625 2010 11 10 5 20 18.000 0.21 91.70 0.0f 3.87 95.52 586 km 5.10 3.49

3)

Detecting stations

Station Phase DeltaEvent

magnitudeDetectionthreshold

SigmaDetection

probabilityStation

magnitude

CMAR P 19.48 3.4880 3.6318 0.4020 0.360322 -

ASAR P 47.34 3.4880 3.4294 0.3510 0.566320 -

DBIC P 96.48 3.4880 4.7119 0.3110 0.000042 5.10

Third highest detection probability 0.000042

Lowest detection probability 0.000042

Non-detecting operational IMS primary stations

Station DeltaEvent

magnitudeDetectionthreshold

SigmaDetectionprobability

WRA 46.31 3.4880 3.4691 0.3640 0.520715

MKAR 47.12 3.4880 3.4952 0.3300 0.491359

TXAR 147.16 3.4880 3.6420 0.3670 0.337386

SONM 49.12 3.4880 3.7132 0.3160 0.238007

ZALV 53.85 3.4880 3.7700 0.3360 0.200658

TORD 89.95 3.4880 3.8572 0.3390 0.138082

FINES 78.37 3.4880 3.9500 0.3370 0.085202

BRTR 65.77 3.4880 3.9190 0.3000 0.075408

AKASG 72.74 3.4880 3.9524 0.3000 0.060826

GEYT 48.62 3.4880 3.9750 0.3000 0.052261

ARCES 81.64 3.4880 4.1104 0.3740 0.048049

KSRS 49.86 3.4880 4.0816 0.3270 0.034737

KBZ 61.31 3.4880 4.0680 0.3160 0.033221

GERES 81.94 3.4880 4.0844 0.3070 0.026026

VNDA 85.97 3.4880 4.3682 0.3950 0.012930

USRK 56.55 3.4880 4.2385 0.3330 0.012105

YKA 114.39 3.4880 4.4480 0.4170 0.010663

BOSA 69.53 3.4880 4.2313 0.3150 0.009142

NOA 85.20 3.4880 4.2189 0.3000 0.007416

MAW 70.59 3.4880 4.4299 0.3850 0.007212

LPAZ 154.49 3.4880 4.4103 0.3680 0.006099

MJAR 56.21 3.4880 4.3241 0.3290 0.005522

PETK 75.63 3.4880 4.4923 0.3850 0.004546

NVAR 132.68 3.4880 4.4140 0.3370 0.003000

KMBO 54.46 3.4880 4.4266 0.3360 0.002608

KEST 83.66 3.4880 4.4626 0.3460 0.002426

ESDC 94.23 3.4880 4.4686 0.3120 0.000836

ILAR 102.71 3.4880 4.6138 0.3480 0.000608

PLCA 136.56 3.4880 4.9210 0.3980 0.000159

SCHQ 122.37 3.4880 4.9540 0.4000 0.000124

CPUP 140.45 3.4880 4.9090 0.3820 0.000100

ULM 129.31 3.4880 4.8710 0.3700 0.000093

BDFB 137.38 3.4880 5.0540 0.3730 0.000013

ROSC 165.16 3.4880 5.1427 0.3630 0.000003

PPT 117.36 3.4880 6.3010 0.3000 0.000000

Number of primary non-detections 35

Number of stations exceeding third detection probability 32

Number of stations exceeding lowest detection probability 32

Afghanistan-Tadjikistan border region Event in SEL, REB and LEB

Event id Year Mo Dy Hr Min Sec Lat Lon DepthREBLat

REBLon

REB-SEL3loc. diff

SEL3mb

NewmbMLE

6830385 2010 11 10 22 21 36.250 36.34 71.40 157.5 36.20 71.37 16 km 3.52 3.16

1)

Detecting stations

Station Phase DeltaEvent

magnitudeDetectionthreshold

SigmaDetectionprobability

Stationmagnitude

AAK P 6.87 3.1557 2.7047 0.4260 0.855138 -

GEYT P 10.73 3.1557 3.2519 0.4180 0.408932 -

MKAR P 13.36 3.1557 2.6928 0.4470 0.849779 -

KURK P 15.31 3.1557 2.8657 0.3910 0.770830 -

BVAR P 16.84 3.1557 2.7482 0.3360 0.887391 -

AKTO P 17.19 3.1557 2.8662 0.3030 0.830295 -

ZALV P 20.07 3.1557 2.7491 0.3360 0.886870 3.40

BRTR P 29.81 3.1557 3.4075 0.3000 0.200592 3.20

FINES P 37.90 3.1557 3.2897 0.3370 0.345431 3.60

ARCES P 41.53 3.1557 3.4163 0.3740 0.242926 3.70

HFS P 43.48 3.1557 3.4440 0.4010 0.236025 3.60

TORD P 66.01 3.1557 3.1298 0.3390 0.530415 3.60

Third highest detection probability 0.855138

Lowest detection probability 0.200592

Non-detecting operational IMS primary stations

Station DeltaEvent

magnitudeDetectionthreshold

SigmaDetectionprobability

ASAR 83.84 3.1557 3.2145 0.3510 0.433491

WRA 81.58 3.1557 3.2310 0.3640 0.418019

KBZ 23.00 3.1557 3.2372 0.3160 0.398225

ILAR 74.99 3.1557 3.2713 0.3480 0.369896

SONM 28.26 3.1557 3.2928 0.3160 0.332172

YKA 81.53 3.1557 3.3805 0.4260 0.298848

AKASG 33.36 3.1557 3.3591 0.3000 0.248844

CMAR 30.05 3.1557 3.4142 0.3420 0.224810

GERES 43.34 3.1557 3.3915 0.3070 0.221233

NOA 44.80 3.1557 3.4917 0.3000 0.131319

KSRS 44.67 3.1557 3.6005 0.3270 0.086881

ESDC 57.86 3.1557 3.6144 0.3120 0.070742

PLCA 150.00 3.1557 3.8126 0.3980 0.049416

USRK 46.06 3.1557 3.7229 0.3330 0.044235

KEST 49.41 3.1557 3.7904 0.3460 0.033292

PETK 59.98 3.1557 3.9567 0.3850 0.018741

DBIC 74.98 3.1557 3.8082 0.3110 0.017938

MJAR 52.82 3.1557 3.8620 0.3290 0.015901

BOSA 77.71 3.1557 3.8413 0.3150 0.014758

KMBO 48.85 3.1557 3.9416 0.3360 0.009665

TXAR 114.65 3.1557 4.0336 0.3670 0.008375

SCHQ 82.49 3.1557 3.9831 0.3150 0.004309

VNDA 125.13 3.1557 4.4546 0.4290 0.001232

LPAZ 138.99 3.1557 4.3666 0.3680 0.000500

CPUP 135.50 3.1557 4.5006 0.3820 0.000215

ULM 93.19 3.1557 4.3342 0.3090 0.000068

NVAR 105.20 3.1557 4.5056 0.3370 0.000031

BDFB 122.68 3.1557 4.6956 0.3730 0.000018

ROSC 128.05 3.1557 4.7096 0.3630 0.000009

MAW 103.69 3.1557 4.9377 0.3850 0.000002

PPT 139.41 3.1557 5.7926 0.3000 0.000000

Number of primary non/detections 31

Number of stations exceeding third detection probability 0

Number of stations exceeding lowest detection probability 9

3 3.5 4 4.5 5−0.4

−0.2

0

0.2

0.4

Mean : 0.117St.dev : 0.069Nobs : 984

AVGscale mb1

MLE

scal

e −

AVG

scal

e

P1 = 0.103, P0 = −0.278

3 3.5 4 4.5 5−0.4

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St.dev : 0.064

AVGscale mb1

MLE

scal

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AVG

scal

e

ARCES

3 3.5 4 4.5 53

3.5

4

4.5

5

MLEdet mb1

MLE

scal

e m

b1

ARCES

Mean difference: 0.039St. dev : 0.047Nobs : 580

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−0.5

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RTO

RDWRA

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RILAR YKA TXAR

BGCA

SONM

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FINES

AKA

SGBR

TRCM

AR

NVA

RGER

ESARC

ESLP

AZ

NOA

KBZ

ESDC

STKA

KSRS

DBIC

VNDA

BOSA

CPUP

BDFB

ULM USR

KSC

HQ

PLCA

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MJAR

MAW

PETK KM

BORO

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Primary stations Teleseismic distances (20 - 90 degrees)

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KURK BV

AR

QSP

ASIV SN

AA

AKT

OINK HFS MATP

RES EKA

AAK

CFAA

ELK

LSZ

FITZ MSK

USD

VMLR

ANMO

APG LBTB

TSUM

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Auxiliary stations Teleseismic distances (20 - 90 degrees)

Database