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An automatic tsunami warning system: TREMORS application in Europe
Phys. Chem. Earth, Vol. 21, No. 12, pp, 75--81, 1996 Copyright © 1997 Elsevier Science Ltd Printed in Great Britain. All fights reserved 0079-1946/96 $15,00 + 0.00
Pergamon
PII: S0079-1946(97)00013-X
An Automatic Tsunami Warning System: TREMORS Application in Europe D. Reymond, S. Robert, Y. Thomas and F. Schindel~ Laboratoire de G6ophysique, B.P. 640 Papeete Tahiti, French Polynesia
Received 4 July 1996: accepted 15 December 1996
Streikeisen STSI, STS2 etc .... The clock uses the worldspread GPS time which allows installation of TREMOR_System at any site.
Abstract. An integrated system named TREMORS (Tsunami Risk Evaluation through seismic Moment of a Real-time System) has been installed in EVORA station, in Portugal which has been affected by historical tsunamis. The system is based on a three component long period seismic station linked to a compatible IBM_PC with a specific software. The goals of this system are the followings: detect earthquake, locate them, compute their seismic moment, give a seismic warning. The warnings are based on the seismic moment estimation and all the processing are made automatically. The finality of this study is to check the quality of estimation of the main parameters of interest in a goal of tsunami warning: the location which depends of azimuth and distance, and at last the seismic moment, M~, which controls the earthquake size. The sine qua non condition for obtaining an automatic location is that the 3 main seismic phases P, S, R must be visible. This study gives satisfying results (automatic analysis): + 5° errors in azimuth and epicentral distance, and a standard deviation of less than a factor 2 for the seismic moment Mc~. © 1997 Elsevier Science Ltd. All rights reserved
1.2 Detection And Picking Algorithm System detectability is only a function of the magnitude and the seismic noise of the station. In appropriate sites, all earthquakes of magnitude greater than 4.8, within a distance of 2000 km from the station are detected (near field). Different software for detection are available based on amplitude, duration and variation of noise energy (Reymond et al., 1991) The most interesting feature of this system is the real time automatic method of identification of the type of seismic wave generated by the earthquake. P or S body waves, as well as Rayleigh or Love surface waves are recognized in function of the analysis of polarization parameters. The automatic phase picking is pertormed on the signal envelop (the filtered rectified signal). 3 kinds of envelops are computed in function of the frequency content of each wave (P, S and surface waves). Figure 2 shows an example of automatic phase picking for a near field event. Wave recognition is necessary to provide accurate location and moment estimation of the earthquake.
1 TREMORS: An Automatic Tsunami Warning System I. I Instrumentation And Hardware. The hardware consists of a single three component broad band (I to 300 s) seismic station with high dynamic feedback controlled sensors and an acquisition unit connected via digital radio link or leased line to an IBM compatible PC (figure 1). Six channels, 3 with high sensitivity and 3 others with a lower sensitivity, are recorded and digitized on double sensitivity by an Analogic-to-Digital converter (A/D, 20 bits, 120 dB); the sample fiequency is 4 Hz. The system is able to transmit alarm and warning by an INMARSAT-C transceiver. It is also adaptable to classical broad band sensors such as
1.3 Location The location of the epicenter using a single 3-component long period station is only based on two independent parameters which are azimuth and distance. The first one is computed from the polarization properties of the P wave; and the second one is calculated using the S-P time delay. The polarization is calculated on a small window in time centered on the first arrival of the P wave (Reymond et al.,
75
76
D. Reymond et al.
19931. The algorithm also provides an estimation of azimuth error which is a function of the polarization itself. As an example, tbr a perfectly polarized P wave with a polarization coefficient closed to 1, we can expect a 0.3 ° error; and in case of bad polarization (coefficient in the 0.6 range) the error would be [20-30 ° ] as shown on figure 3.1,1 fact the polarization quality strongly depends on the signal to noise ratio. Note that the estimation error only takes into account the uncertainties on the method itself, and not the errors due to propagation anomalies. Conceu'ning the distance estimation, when the automatic phase picking is correct, we can expect a + 3 ° error for far field events and + I ° in near field. The main cause of strong error in the epicentral distance evaluation is a mistake in the phase picking. The 3 main phases P, S and R a2-e absolutely needed to obtain a correct location. When the S phase is not round, the epicentral distance is calculated fi'om the R-P time delay. In case of very distant earthquakes (mo,e than I10 °) the epicentral distance can be obtained with [R-Pdiffl or [SS-PKP] waves difference time. The PKP waves are recognized from their small incidence angles (less than 13-15°). Another source of error is the case of deep quakes, for which the velocity m~xlel is not adapted (by default, the focus is fixed at 33 km depth). O,1 the other hand, the velocity model (P, S and R phases) tb," near field events can be locally defined at each seismic station.
waves at teleseismic distances (A > 10°), Mm can also be computed directly in the time domain (Okal, 1989). In practice, we need a few minutes (about 15) of surface waves to initiate the computation of the seismic moment. M,, is systematically calculated tbr each class of focal depth and printed by the compute,. The most plausible depth is decided under the responsibility of an operator (on call 24 hours a day). The automatic estimation of the focal depth is in study and will be further developed; from now, TREMOR_System just gives an indication on the probable class of depth of the detected event from spectral characteristics of surface waves (Reymond et al., 1993). The reliability of this indication is about 80% for f;lr field, but it does not work at all for near field. The expected accuracy of the seismic moment estimation is less than a 2 factor (standard deviation), that means 0.29 unit of magnitude.
1.5 Seismic Warning TREMOR_System can chronologically generate 3 types of warnings: • The first one is given from P wave amplitude level; this is essentially designed tot early warning in near field. The second one lies on the seismic moment computed on a growing window which can give reliable warnings, even tbr slow "tsunami earthquakes" (generating small P wave amplitude) with a minimized response time. In practice, the computation of the seismic moment is made each 50 seconds (thus on longer and longer time window, so taking into account longer and longer periods). M0 first grows quickly with the Rayleigh wave arrival and then reaches a stable value.
1.4 Seismic Moment And Mm Magnitude The seismic moment is estimated in real-time through the computation of the mantle magnitude M,,, which was designed by Okal and Talandier (1987) to obey the simple ,-elation: IogH) Mo = M,, + 13.0
with M0 in N.m
Note that the seismic moment is calculated under a magnitude concept which ignores the true focal mechanism. We ret~r to Okal and Talandier (1987; 1989; 1990), Okal (1990), and Talandier and Okal (1989; 1992) for the details of the computation of M.,, which is defined in the fi'equency domain as: M,,, = logic) X(co) + Co(co,A) + Cs(co) - 0.90, where X(co) is the spectral amplitude of ground motion in lum.s at the angular frequency co, Cs a source correction and CD a distance correction. This formalism can be applied both to Rayleigh and Love waves with obviously different expressions for the corrections. Notice that the source correction is in principle depth dependent; in practice, corrections are computed for 4 broad bins of hypocentral depths (Okal, 1990). In the case of Rayleigh
•
The last one is emitted on the final estimated seismic moment (after a complete analysis of the signal).
The threshold has to be defined in function of the goals in term of seismic risks; for example: a threshold of 5.0 10 '9 can be defined for tsunami warning in near field, but it obviously depends on local consideration and requirement. Concerning the delays of warning, the system is able to provide early warning in minutes after the earthquake (of course, they depend on epicentral distance); for a detail investigation of the delays, refer to Schindel6 et al. (in press).
An Automatic Tsunami Warning System
2 TREMORS Application In Europe 2.1 The Data The TREMORS station of EVORA was installed in 1994; this site is interesting because Portugal was concerned by historical destructive tsunamis. We have got 74 far field events from March 1994 to December 1995 with epicentral distance in the [21 °167.3 °] range (see figure 4 for the map Of epicenters). The references used for the locations are the Preliminary Determination of Epicenter (PDE). Only 2 near field quakes were recorded during this period: the event of Gibraltar May 26, 1994 (distance 4.4 ° ) and of Algeria 18 August 1994 (distance 7.0°). All the events detected were selected with the constraint that the 3 main seismic phases (P,S,R) must be visible (else the TREMORS location is not possible). Most of the events were analyzed automatically (only 5 manual analyses) with the same filtering (low pass filter fourth order at 10 s of cutting period) and processing. With regard to the seismic moment, Mo, the reference chosen is Harvard CMT solutions published also in the PDE. M~ varies in the [1017 - [021 N.m ] range. The smallest event detected (4.9 l0 ~7 N.m ) was the one of Algeria; the strongest recorded earthquake (3 1021 N.m) was the Kuril one (October 4, 1994), at 95 ° of epicentral distance.
2.2 Quality Of The Location Since the location is only a function of 2 independent parameters which are azimuth and epicentral distance, we have to check their respective estimation separately.
2.2. I Azimuth Estimation The azimuth estimation is based on the polarization properties of P wave which is in theory a progressive longitudinal plane wave; thus the projection of ground displacement in a given place into the horizontal plane would give a straight line defined by the intersection of the horizontal plane with the radial plane (the vertical plane containing the wave number vector I k I= 2x / ~, ). In practice, we can observe sometimes such a perfect polarization for strong far field events, but most of time, the polarization is perturbed by the seismic noise or, as a consequence of the propagation, by several waves arriving with slightly different azimuths, at very short time delays. The measure of polarization quality is made through the polarization coefficients Cp_H, Cp_Z (which are close to I tbr good polarization, and 0 for poor one, H means horizontal and Z vertical). The azimuth error represents the difference between observed azimuth and theoretical PCE 21:I/Z-F
77
azimuth (calculated from the published value of the epicenter) in function of the signal to noise ratio (S/N hereafter), which is the preponderant parameter. This ratio is computed on the 2 horizontal components by comparing the amplitude of the first arrival on a small time window (50 s), with the one of the noise extracted before the first arrival. These results are shown on figure 5; as expected, the error becomes larger and larger when signal S/N decreases, and can reach 70 ° and more. On the other hand for very large values of S/N, the error becomes very small (less than 3°). In practice and for giving a rough threshold, we can consider that the azimuthal error is less than 10° for S/N greater than 40. We have to mention also that all these values are obtained after a systematic correction of 7 ° due to a misorientation of the horizontal sensors, which is as we understand of crucial importance in the context of a single 3 components station.
2.2.2 Distance Estimation As we have seen before, the epicentral distance is calculated from the S-P time delay; P and S are automatically picked; so the error on distance will retlect the accuracy of the automatic phase picking, and on the other hand, the validity of the velocity model used by the software. Concerning the phase picker, its accuracy is also dependent on the signal to noise ratio as shown on figure 6: we clearly observe large errors on the distance (until 20 °) for small values of S/N; but for S/N ratio larger than 40, almost all the epicentral distances are estimated with an accuracy better than 3 ° . Two shallo,d events, with S/N ratio greater than 40, show an error of + 5 ° which is due to a mis-picked S phase; the manual phase picking helps to improve the epicentral distance estimation for those two events (triangles on figure 6). We also observe large errors (until 21 °) for 4 deep events with a S/N ratio bigger than 40; indeed, the velocity model used by the software is designed for superficial earthquakes and not for deep ones. As the tsunami warnings are only concerned with shallow earthquakes, we conclude that the accuracy on the epicentral distance calculation is efficient for S/N ratios greater than 40.
2.3 Seismic Moment Estimation As explained above, the seismic moment Mo is calculated at several periods between 50 and 300s. The retained value for each event is the greatest measure having a sufficient signal to noise ratio; the minimum value of S/N is 10, some weak events were rejected because they did not satisfy this criterion. Figure 7 shows the Ivlo calculated by TREMORS versus published value provided by Harvard which is our reference. All the locations were calculated
78
D. R e y m o n d
automatically. In the case of very deep earthquakes, the epicentral distance is always underestimated (as we have seen above, the default propagation time tables are designed tbr a 33 km focal depth). So the distance correction Co is underestimated and consequently, M0 is underevaluated in this case. Most of the events have their seismic moment correctly estimated (standard deviation is 0.30 which corresponds to a 2 factor in a linear scale between the published and the TREMORS estimated values of Mo. We may note that 2 events have not their Mo correctly estimated; this is due to their very bad location, with 15-20 ° error on the epicentral distance.
3 Conclusions In terms of tsunami warning, in case of near field events, rapid responses are of crucial importance for an evident reason of saving time. In this study only 2 near field events (at 4.4 ° in Gibraltar strait and 7.0 ° in Algeria) of moderate magnitudes were analyzed. Of course it is inconvenient to make statistics with 2 events, but another study (Schindel6 et al., 1996) has shown the efficiency of the system in near field, even in case of "tsunami earthquakes". This type of slow events represents a real and difficult problem for warning system based on classical magnitudes scales (recall the very small mb value of 5.3 and 5.5 for Nicaragua on September 1992 and Java on June 2 1994 respectively); but for a warning system having tbr basis the seismic moment estimation, the true earthquake size can be recognized. Concerning the far field case, the number of events was sufficient (about 65 quakes); their location and M0 estimations were correct when the signal to noise ratios were sufficient, especially for the location tbr which the contamination by the noise in the polarization analysis can be drastically important. We have to mention also that the location at very great epicentral distances (more than 110 °) is not so robust than at shorter ones but in this case, the tsunami risk is null for Portugal. Also for very deep earthquakes (more than 400 km depth) we need to impose the real location for improving the estimation of the seismic moment. As far as Portugal is not concerned by deep and very distant earthquakes, the former results show that automatic location and calculation of seismic moment can be estimated efficiently and rapidly by TREMOR_System within the framework of tsunami risk.
et al.
References Okal, E.A., A theoretical di~u~ion of time-domain Magnitudes: The Prague formula for M s and the mantle magnitude M m, J. Geophys. Res. 94, 4194-4204, 1989. Okal, E.A., M m : A Mantle wave magnitude for intermediate and deep earthquakes, Pure Applied Geophys., 134,333-354, 1990. Okal, E.A. and Talandier, J., M m : Theory of a variable-period mantle magnitude, Geophys. Res. Lefts.,14, 836-839, 1987. Okal, E.A. and Talandier, J., M m : A variable-periodmantle magnitude, J. Geophys. Res., 94, 4169-4193, 1989. Okal, E.A. and Talandier, J., M m : Extension to Love waves of the concept of a variable-periodmantle magnitude, Pure Applied Geophys. 134, 355384, 1990. Reymond, D., Hyvernand , O., and Talandier , J., Automatic detection, location and quantification of earthquakes: Application to Tsunami Warning, Pageoph, 135,361-382, 199 I. Reymond, D., Hyvernaud , O., and Talandier , J., The basis of tsunami warning: fast evaluation of location, focal depth and ~ismic source parameters, Proc. Tsunami Syrup. biter.Un. Geod. Geophys. Wakayama, 23-27 Ao~t 1093, 835-848, 1993. Schindel~, F., Reymond, D., Gaucher, E., and Okal, E.A., Analysis and automatic processing in near field of eight 1992-1994 tsunaroigenic earthquakes: improvements towards real-time tsunami warning, Pure Applied Geophys., 144, 381-408, 1996. Talandier, J. and Okal, E.A., An algorithm for automated tsunami warning in French Polynesia based on mantle magnitudes. BulL SeismoL Soc. Amer., 79, 1177-I 193, 1989. Talandier,J. and Okal, E.A., One stationestimatesof seismic moments from the mantle magnitude M m : The ca~ of the regional field( 1.5° < A < 15°), Pure Applied Geophys., 138, 43-60, 1992.
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An AutomaticTsunami WarningSystem
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Fig. 2. Example of automatic phase analysis : (quake of Gibraltar May 26 1994). The location is determined from both the parameters azimuth and epicentral distance. The main seismic phases (P, S, R, L) are picked on the envelops of vertical and transversal components (the 2 top frames). The gray curves correspond to the envelop used for the surface waves picking. Then the epicentral distance is calculated from the S-P, or R-P time. For distant earthquakes (D > 142°) the distance is obtained from SS-PKP time. The quality of the location depends on signal to noise ratio and polarization coefficients.
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Fig. 3. The azimuth is calculated from the polarization plane of the P wave computed on a small window (40 s length), after the automatic phase picking (given by the dot line). The bottom left frame represents the horizontal ground motion with its estimated azimuth (.solid line), and the middle bottom one corresponds to the motion in the incidence plane; both estimated eigendirection are calculated from the eigenvoctors of the covariance matrix. The identification of the phase at the trigger time is made from the polarization coefficients (Cp_H, Cp_Z) and from the incidence value.
80
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S I G N A L / N O I S E (energy) Fig. 5. Errors on azimuth• The quality of azimuth estimated by TREMORS is tested by comparison with the locations published by USGS, This figure shows clearly that the polarization quality of P waves is strongly dependent on the Signal to Noise ratio. It seems that below a threshold of 40, the precision of the results becomes worse. Above this threshold, we can expect a +/- 10° precision in the azimuth estimation. Obviously, the sensors orientation is of crucial importance; and we had to apply a systematic correction of-7 degrees to every measure of azimuth, in the case of EVORA station• As expected, we notice that focal depth does not affect the azimuth estimation•
81
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Mo HARVARD (N,m) Fig. 7. Reliability of the automatic Mo computation. The Mo performed by TREMORS are compared to the published Harvard values (our reference). Because of inappropriate distance estimation, the seismic moments of deep events can be wrong. By fixing locations for deep events to the true ones, we observe an improvement of Mo. In the other cases, that means for shallow earthquakes, seismic moments are correctly estimated, in particular for the strongest events (M. > 1.102" N.m) for which tsunami generation is concerned. The reliability of tsunami warning lies on M. evaluation; but the system can not predict the tsunami amplitude in a given place (strongly dependent of the bathymetry).
Pergamon
PII: S0079-1946(97)00013-X
An Automatic Tsunami Warning System: TREMORS Application in Europe D. Reymond, S. Robert, Y. Thomas and F. Schindel~ Laboratoire de G6ophysique, B.P. 640 Papeete Tahiti, French Polynesia
Received 4 July 1996: accepted 15 December 1996
Streikeisen STSI, STS2 etc .... The clock uses the worldspread GPS time which allows installation of TREMOR_System at any site.
Abstract. An integrated system named TREMORS (Tsunami Risk Evaluation through seismic Moment of a Real-time System) has been installed in EVORA station, in Portugal which has been affected by historical tsunamis. The system is based on a three component long period seismic station linked to a compatible IBM_PC with a specific software. The goals of this system are the followings: detect earthquake, locate them, compute their seismic moment, give a seismic warning. The warnings are based on the seismic moment estimation and all the processing are made automatically. The finality of this study is to check the quality of estimation of the main parameters of interest in a goal of tsunami warning: the location which depends of azimuth and distance, and at last the seismic moment, M~, which controls the earthquake size. The sine qua non condition for obtaining an automatic location is that the 3 main seismic phases P, S, R must be visible. This study gives satisfying results (automatic analysis): + 5° errors in azimuth and epicentral distance, and a standard deviation of less than a factor 2 for the seismic moment Mc~. © 1997 Elsevier Science Ltd. All rights reserved
1.2 Detection And Picking Algorithm System detectability is only a function of the magnitude and the seismic noise of the station. In appropriate sites, all earthquakes of magnitude greater than 4.8, within a distance of 2000 km from the station are detected (near field). Different software for detection are available based on amplitude, duration and variation of noise energy (Reymond et al., 1991) The most interesting feature of this system is the real time automatic method of identification of the type of seismic wave generated by the earthquake. P or S body waves, as well as Rayleigh or Love surface waves are recognized in function of the analysis of polarization parameters. The automatic phase picking is pertormed on the signal envelop (the filtered rectified signal). 3 kinds of envelops are computed in function of the frequency content of each wave (P, S and surface waves). Figure 2 shows an example of automatic phase picking for a near field event. Wave recognition is necessary to provide accurate location and moment estimation of the earthquake.
1 TREMORS: An Automatic Tsunami Warning System I. I Instrumentation And Hardware. The hardware consists of a single three component broad band (I to 300 s) seismic station with high dynamic feedback controlled sensors and an acquisition unit connected via digital radio link or leased line to an IBM compatible PC (figure 1). Six channels, 3 with high sensitivity and 3 others with a lower sensitivity, are recorded and digitized on double sensitivity by an Analogic-to-Digital converter (A/D, 20 bits, 120 dB); the sample fiequency is 4 Hz. The system is able to transmit alarm and warning by an INMARSAT-C transceiver. It is also adaptable to classical broad band sensors such as
1.3 Location The location of the epicenter using a single 3-component long period station is only based on two independent parameters which are azimuth and distance. The first one is computed from the polarization properties of the P wave; and the second one is calculated using the S-P time delay. The polarization is calculated on a small window in time centered on the first arrival of the P wave (Reymond et al.,
75
76
D. Reymond et al.
19931. The algorithm also provides an estimation of azimuth error which is a function of the polarization itself. As an example, tbr a perfectly polarized P wave with a polarization coefficient closed to 1, we can expect a 0.3 ° error; and in case of bad polarization (coefficient in the 0.6 range) the error would be [20-30 ° ] as shown on figure 3.1,1 fact the polarization quality strongly depends on the signal to noise ratio. Note that the estimation error only takes into account the uncertainties on the method itself, and not the errors due to propagation anomalies. Conceu'ning the distance estimation, when the automatic phase picking is correct, we can expect a + 3 ° error for far field events and + I ° in near field. The main cause of strong error in the epicentral distance evaluation is a mistake in the phase picking. The 3 main phases P, S and R a2-e absolutely needed to obtain a correct location. When the S phase is not round, the epicentral distance is calculated fi'om the R-P time delay. In case of very distant earthquakes (mo,e than I10 °) the epicentral distance can be obtained with [R-Pdiffl or [SS-PKP] waves difference time. The PKP waves are recognized from their small incidence angles (less than 13-15°). Another source of error is the case of deep quakes, for which the velocity m~xlel is not adapted (by default, the focus is fixed at 33 km depth). O,1 the other hand, the velocity model (P, S and R phases) tb," near field events can be locally defined at each seismic station.
waves at teleseismic distances (A > 10°), Mm can also be computed directly in the time domain (Okal, 1989). In practice, we need a few minutes (about 15) of surface waves to initiate the computation of the seismic moment. M,, is systematically calculated tbr each class of focal depth and printed by the compute,. The most plausible depth is decided under the responsibility of an operator (on call 24 hours a day). The automatic estimation of the focal depth is in study and will be further developed; from now, TREMOR_System just gives an indication on the probable class of depth of the detected event from spectral characteristics of surface waves (Reymond et al., 1993). The reliability of this indication is about 80% for f;lr field, but it does not work at all for near field. The expected accuracy of the seismic moment estimation is less than a 2 factor (standard deviation), that means 0.29 unit of magnitude.
1.5 Seismic Warning TREMOR_System can chronologically generate 3 types of warnings: • The first one is given from P wave amplitude level; this is essentially designed tot early warning in near field. The second one lies on the seismic moment computed on a growing window which can give reliable warnings, even tbr slow "tsunami earthquakes" (generating small P wave amplitude) with a minimized response time. In practice, the computation of the seismic moment is made each 50 seconds (thus on longer and longer time window, so taking into account longer and longer periods). M0 first grows quickly with the Rayleigh wave arrival and then reaches a stable value.
1.4 Seismic Moment And Mm Magnitude The seismic moment is estimated in real-time through the computation of the mantle magnitude M,,, which was designed by Okal and Talandier (1987) to obey the simple ,-elation: IogH) Mo = M,, + 13.0
with M0 in N.m
Note that the seismic moment is calculated under a magnitude concept which ignores the true focal mechanism. We ret~r to Okal and Talandier (1987; 1989; 1990), Okal (1990), and Talandier and Okal (1989; 1992) for the details of the computation of M.,, which is defined in the fi'equency domain as: M,,, = logic) X(co) + Co(co,A) + Cs(co) - 0.90, where X(co) is the spectral amplitude of ground motion in lum.s at the angular frequency co, Cs a source correction and CD a distance correction. This formalism can be applied both to Rayleigh and Love waves with obviously different expressions for the corrections. Notice that the source correction is in principle depth dependent; in practice, corrections are computed for 4 broad bins of hypocentral depths (Okal, 1990). In the case of Rayleigh
•
The last one is emitted on the final estimated seismic moment (after a complete analysis of the signal).
The threshold has to be defined in function of the goals in term of seismic risks; for example: a threshold of 5.0 10 '9 can be defined for tsunami warning in near field, but it obviously depends on local consideration and requirement. Concerning the delays of warning, the system is able to provide early warning in minutes after the earthquake (of course, they depend on epicentral distance); for a detail investigation of the delays, refer to Schindel6 et al. (in press).
An Automatic Tsunami Warning System
2 TREMORS Application In Europe 2.1 The Data The TREMORS station of EVORA was installed in 1994; this site is interesting because Portugal was concerned by historical destructive tsunamis. We have got 74 far field events from March 1994 to December 1995 with epicentral distance in the [21 °167.3 °] range (see figure 4 for the map Of epicenters). The references used for the locations are the Preliminary Determination of Epicenter (PDE). Only 2 near field quakes were recorded during this period: the event of Gibraltar May 26, 1994 (distance 4.4 ° ) and of Algeria 18 August 1994 (distance 7.0°). All the events detected were selected with the constraint that the 3 main seismic phases (P,S,R) must be visible (else the TREMORS location is not possible). Most of the events were analyzed automatically (only 5 manual analyses) with the same filtering (low pass filter fourth order at 10 s of cutting period) and processing. With regard to the seismic moment, Mo, the reference chosen is Harvard CMT solutions published also in the PDE. M~ varies in the [1017 - [021 N.m ] range. The smallest event detected (4.9 l0 ~7 N.m ) was the one of Algeria; the strongest recorded earthquake (3 1021 N.m) was the Kuril one (October 4, 1994), at 95 ° of epicentral distance.
2.2 Quality Of The Location Since the location is only a function of 2 independent parameters which are azimuth and epicentral distance, we have to check their respective estimation separately.
2.2. I Azimuth Estimation The azimuth estimation is based on the polarization properties of P wave which is in theory a progressive longitudinal plane wave; thus the projection of ground displacement in a given place into the horizontal plane would give a straight line defined by the intersection of the horizontal plane with the radial plane (the vertical plane containing the wave number vector I k I= 2x / ~, ). In practice, we can observe sometimes such a perfect polarization for strong far field events, but most of time, the polarization is perturbed by the seismic noise or, as a consequence of the propagation, by several waves arriving with slightly different azimuths, at very short time delays. The measure of polarization quality is made through the polarization coefficients Cp_H, Cp_Z (which are close to I tbr good polarization, and 0 for poor one, H means horizontal and Z vertical). The azimuth error represents the difference between observed azimuth and theoretical PCE 21:I/Z-F
77
azimuth (calculated from the published value of the epicenter) in function of the signal to noise ratio (S/N hereafter), which is the preponderant parameter. This ratio is computed on the 2 horizontal components by comparing the amplitude of the first arrival on a small time window (50 s), with the one of the noise extracted before the first arrival. These results are shown on figure 5; as expected, the error becomes larger and larger when signal S/N decreases, and can reach 70 ° and more. On the other hand for very large values of S/N, the error becomes very small (less than 3°). In practice and for giving a rough threshold, we can consider that the azimuthal error is less than 10° for S/N greater than 40. We have to mention also that all these values are obtained after a systematic correction of 7 ° due to a misorientation of the horizontal sensors, which is as we understand of crucial importance in the context of a single 3 components station.
2.2.2 Distance Estimation As we have seen before, the epicentral distance is calculated from the S-P time delay; P and S are automatically picked; so the error on distance will retlect the accuracy of the automatic phase picking, and on the other hand, the validity of the velocity model used by the software. Concerning the phase picker, its accuracy is also dependent on the signal to noise ratio as shown on figure 6: we clearly observe large errors on the distance (until 20 °) for small values of S/N; but for S/N ratio larger than 40, almost all the epicentral distances are estimated with an accuracy better than 3 ° . Two shallo,d events, with S/N ratio greater than 40, show an error of + 5 ° which is due to a mis-picked S phase; the manual phase picking helps to improve the epicentral distance estimation for those two events (triangles on figure 6). We also observe large errors (until 21 °) for 4 deep events with a S/N ratio bigger than 40; indeed, the velocity model used by the software is designed for superficial earthquakes and not for deep ones. As the tsunami warnings are only concerned with shallow earthquakes, we conclude that the accuracy on the epicentral distance calculation is efficient for S/N ratios greater than 40.
2.3 Seismic Moment Estimation As explained above, the seismic moment Mo is calculated at several periods between 50 and 300s. The retained value for each event is the greatest measure having a sufficient signal to noise ratio; the minimum value of S/N is 10, some weak events were rejected because they did not satisfy this criterion. Figure 7 shows the Ivlo calculated by TREMORS versus published value provided by Harvard which is our reference. All the locations were calculated
78
D. R e y m o n d
automatically. In the case of very deep earthquakes, the epicentral distance is always underestimated (as we have seen above, the default propagation time tables are designed tbr a 33 km focal depth). So the distance correction Co is underestimated and consequently, M0 is underevaluated in this case. Most of the events have their seismic moment correctly estimated (standard deviation is 0.30 which corresponds to a 2 factor in a linear scale between the published and the TREMORS estimated values of Mo. We may note that 2 events have not their Mo correctly estimated; this is due to their very bad location, with 15-20 ° error on the epicentral distance.
3 Conclusions In terms of tsunami warning, in case of near field events, rapid responses are of crucial importance for an evident reason of saving time. In this study only 2 near field events (at 4.4 ° in Gibraltar strait and 7.0 ° in Algeria) of moderate magnitudes were analyzed. Of course it is inconvenient to make statistics with 2 events, but another study (Schindel6 et al., 1996) has shown the efficiency of the system in near field, even in case of "tsunami earthquakes". This type of slow events represents a real and difficult problem for warning system based on classical magnitudes scales (recall the very small mb value of 5.3 and 5.5 for Nicaragua on September 1992 and Java on June 2 1994 respectively); but for a warning system having tbr basis the seismic moment estimation, the true earthquake size can be recognized. Concerning the far field case, the number of events was sufficient (about 65 quakes); their location and M0 estimations were correct when the signal to noise ratios were sufficient, especially for the location tbr which the contamination by the noise in the polarization analysis can be drastically important. We have to mention also that the location at very great epicentral distances (more than 110 °) is not so robust than at shorter ones but in this case, the tsunami risk is null for Portugal. Also for very deep earthquakes (more than 400 km depth) we need to impose the real location for improving the estimation of the seismic moment. As far as Portugal is not concerned by deep and very distant earthquakes, the former results show that automatic location and calculation of seismic moment can be estimated efficiently and rapidly by TREMOR_System within the framework of tsunami risk.
et al.
References Okal, E.A., A theoretical di~u~ion of time-domain Magnitudes: The Prague formula for M s and the mantle magnitude M m, J. Geophys. Res. 94, 4194-4204, 1989. Okal, E.A., M m : A Mantle wave magnitude for intermediate and deep earthquakes, Pure Applied Geophys., 134,333-354, 1990. Okal, E.A. and Talandier, J., M m : Theory of a variable-period mantle magnitude, Geophys. Res. Lefts.,14, 836-839, 1987. Okal, E.A. and Talandier, J., M m : A variable-periodmantle magnitude, J. Geophys. Res., 94, 4169-4193, 1989. Okal, E.A. and Talandier, J., M m : Extension to Love waves of the concept of a variable-periodmantle magnitude, Pure Applied Geophys. 134, 355384, 1990. Reymond, D., Hyvernand , O., and Talandier , J., Automatic detection, location and quantification of earthquakes: Application to Tsunami Warning, Pageoph, 135,361-382, 199 I. Reymond, D., Hyvernaud , O., and Talandier , J., The basis of tsunami warning: fast evaluation of location, focal depth and ~ismic source parameters, Proc. Tsunami Syrup. biter.Un. Geod. Geophys. Wakayama, 23-27 Ao~t 1093, 835-848, 1993. Schindel~, F., Reymond, D., Gaucher, E., and Okal, E.A., Analysis and automatic processing in near field of eight 1992-1994 tsunaroigenic earthquakes: improvements towards real-time tsunami warning, Pure Applied Geophys., 144, 381-408, 1996. Talandier, J. and Okal, E.A., An algorithm for automated tsunami warning in French Polynesia based on mantle magnitudes. BulL SeismoL Soc. Amer., 79, 1177-I 193, 1989. Talandier,J. and Okal, E.A., One stationestimatesof seismic moments from the mantle magnitude M m : The ca~ of the regional field( 1.5° < A < 15°), Pure Applied Geophys., 138, 43-60, 1992.
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An AutomaticTsunami WarningSystem
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Fig. 2. Example of automatic phase analysis : (quake of Gibraltar May 26 1994). The location is determined from both the parameters azimuth and epicentral distance. The main seismic phases (P, S, R, L) are picked on the envelops of vertical and transversal components (the 2 top frames). The gray curves correspond to the envelop used for the surface waves picking. Then the epicentral distance is calculated from the S-P, or R-P time. For distant earthquakes (D > 142°) the distance is obtained from SS-PKP time. The quality of the location depends on signal to noise ratio and polarization coefficients.
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80
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81
A n Automatic T s u n a m i W a r n i n g System
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