2010 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies

RAYLEIGH AND LOVE WAVE MAGNITUDES

Anastasia Stroujkova1, Jessie Bonner1, Robert Herrmann2, and Dale N. Anderson3

Weston Geophysical Corporation1, St. Louis University2, and Los Alamos National Laboratory3

Sponsored by the Air Force Research Laboratory

Award No. FA8718-09-C-0012 Proposal No. BAA09-75

ABSTRACT

We continue to study the Ms(VMAX) surface wave magnitude formula (Russell, 2006). During the past year, we have automated the method for both Rayleigh and Love waves, examined structural effects on the formula in the Middle East, applied the method to Italian earthquakes, and examined performance of the method at the United States Geological Survey National Earthquake Information Center (USGS NEIC). We are also in the process of incorporating a formal discriminant of Ms(VMAX):mb into the Event Classification Matrix (Anderson et al., 2007). We have applied the Ms (VMAX) analysis (Bonner et al., 2006) using both Love and Rayleigh waves to events in the Middle East, Italy, and the Yellow Sea/Korean Peninsula region.

The Middle East dataset consists of approximately 120 events with reported body wave magnitudes (mb) between 3.8 and 5.6. We found a significant surface wave magnitude bias between the stations situated to the northwest and northeast from the area of Middle East. We attribute this bias to the surface wave scattering by the Caspian and the Black Seas and the Great Caucasus Mountains.

As a part of this project we examined the validity of the Russell formula for Love waves using the Middle East dataset. We removed the attenuation correction term suggested by the Russell formula and examined the decrease in magnitude as a function of distance for both Rayleigh and Love waves. The attenuation coefficients calculated by fitting a linear regression to uncorrected Ms (VMAX) measurements are 0.0037 for the Rayleigh and 0.0042 for the Love waves. Application of the new corrections improves the residuals for the events used in the inversion; however it doesn’t improve the RMS residuals for the entire data set.

We studied the relationship between Love and Rayleigh-wave magnitudes for earthquakes occurring in Italy, with a primary focus on the L'Aquila earthquake (6 April 2009 Mw 6.1) and its aftershocks. We have estimated Ms(VMAX) for 125 Italian earthquakes with 2.8 < Mw < 6.1 at distances ranging from 50 to 414 km. The network- averaged magnitudes show that most of the events (80%) had a Love-wave Ms(VMAX) that was larger (by 0.2 m.u. on average) than the Rayleigh-wave estimate. In addition, we observe larger interstation standard deviation for the Love-wave magnitudes (0.2 m.u.) than for Rayleigh waves (0.17 m.u). Residual Ms(VMAX) estimates (e.g., station minus network average) show no significant distance dependence on the magnitudes; however, there is a clear azimuthal effect on the Rayleigh-wave station residuals.

Ms(VMAX) for Rayleigh waves is currently being tested in the automated USGS NEIC Hydra system. We will present results from the first four months of the test phase, showing comparisons of Ms(VMAX) with other surface wave magnitude formulas and to mb.

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OBJECTIVES

Russell (2006) developed a time-domain method for measuring surface waves with minimum digital processing using zero-phase Butterworth filters. We refer to this technique as Ms(VMAX) for Variable-period, MAXimum amplitude magnitude estimates. The technique was implemented in Matlab (program EVALSURF, Bonner et al., 2006) to estimate variable-period (8 < T < 40 sec) Rayleigh-wave magnitudes for comparison to the historical formulas of Marshall and Basham (1972) and Rezapour and Pearce (1998). The original version of the program requires considerable analyst involvement for the magnitude picking. We recently extended application of the Ms(VMAX) technique to Love waves in attempt to improve seismic event screening using the properties of Rayleigh and Love waves. We are accomplishing this through the development of a Love-wave magnitude formula that is complementary to the Russell (2006) formula for Rayleigh waves

RESEARCH ACCOMPLISHED

Love and Rayleigh Wave Ms(VMAX) in the Middle East

We computed Ms(VMAX) (Bonner et al., 2006) for over 120 seismic events located in the Middle East with reported body wave magnitudes (mb) between 3.8 and 5.6. The majority of the location and magnitude information (with a few exceptions) was obtained from the NEIC bulletin. The study area (Figure 1) is located in the zone of continental collision between Eurasian, African and Arabian plates. The complex tectonic setting of the region creates highly irregular velocity structure, with rapid changes between the areas with different crustal thicknesses and velocities. One of the world’s thickest sedimentary basins is located beneath the Caspian Sea. The South Caspian Basin and has a 15-25 km thick sedimentary layer overlying 10-15 km thick oceanic crust (Neprochnov 1968; Rezanov and Chamo, 1969). This basin forms a deep aseismic depression bounded to the south by the Alborz Mountains in Iran, to the east by the Turkmenistan lowlands and Kopet Dag Mountains of Iran, to the west by the Caucasus Mountains, and to the north by the Apsheron-Balkhan Sill (Priestley and Mangino, 1995).

Figure 1. Map of the seismic events (red circles) and stations (blue triangles) used for Ms (VMAX) study.

We have applied the Ms (VMAX) analysis to both Love and Rayleigh waves using the Russell (2006) formula:

8.1 1  T0   20  s aM b )log( += ( )()+∆ 0031.sinlog   fc −−−∆ log66.043.0)log(   (1) 2  T   T 

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The details of the processing used to estimate Ms(VMAX) are described in Bonner et al. (2006). Our initial hope is to be able to use the same formula for both surface wave types.

The Ms(VMAX) computed using Love waves is greater than the magnitude for Rayleigh waves for the majority of the events of larger magnitudes (above mb~4). For smaller events, however, we observe a large number of events with the Rayleigh Ms(VMAX) exceeding the Love Ms(VMAX). This peculiarity could be caused by either reduced SNR for smaller magnitude events, or by source radiation effects (e.g., due to normal fault mechanisms). In addition regional differences in the wave attenuation and/or anisotropy could cause changes in the amplitudes for the rays traveling in different directions. Since the station coverage is not homogeneous, these propagation effects could potentially result in biases in Ms(VMAX) estimate for smaller events with limited sampling.

Table 1. The average differences between Ms (VMAX) measured for each event at a single station and the mean value for all stations. These values represent biases in the magnitude measurements for individual stations.

Bias in M (VMAX) (in m.u.) Station s Rayleigh Love ANTO -0.04 0.13 BFO -0.16 -0.17 BRVK 0.13 0.07 GNI -0.05 0.03 KIEV -0.09 0.02 KIV -0.17 -0.14

Figure 2. Map of the mean residuals of the station Ms (VMAX) estimate as shown in Figure 2: a) Ms (VMAX) estimated using Rayleigh waves; b) Love waves.

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Figure 3. Ray trajectories from selected events to station GNI, showing the influence of the Caspian Sea on Love wave dispersion. The panels surrounding the map show multiple filter analysis results for the Rayleigh waves recorded at the station GNI.

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The average Ms (VMAX) residuals for each station are shown in Figure 2 with the red circles corresponding to the stations with positive bias, and the blue circles corresponding to the negative bias. Note that the sign of the bias is predominantly negative toward the northwest from the region of study and predominantly positive to the northeast. Negative bias is likely an indication of relatively higher attenuation in that direction. The numerical values of the bias for some of the stations of the region are shown in Table 1. Note that the values of the bias for some stations (e.g., KIV, BFO) are comparable to the Ms (VMAX) mean value of the interstation standard deviation computed for the entire dataset (0.2 m.u.). Therefore, determining surface wave magnitudes using different subsets of stations may lead to significant bias, especially for smaller events for which only a limited number of magnitude measurements are available.

To show the effect of the structure variations on the surface wave dispersion, we plotted the results of the multiple filter analysis (MFA), which we used to verify the nature of the phases. Figures 3 show the application of the MFA analysis to the Love waves, in which the dispersion of the trace (illustrated by the colored contours) is compared to the dispersion predicted from the averaged dispersion curve explained earlier (white squares with uncertainty bars connected by the dashed white line). The white dots on each figure show the theoretical (averaged) Love wave group velocities with their error bars. Figures 3 shows rays going trough to Station GNI from different events located to the east from the station, where some of the ray paths cross the Caspian Sea, and others do not. Notice strong dispersion and high velocities for the short periods (less than 20 s) corresponding to the ray paths coming from south and central Iran. The surface waves from events separated by the Caspian Sea, however, are considerably degraded. Notice lowering of the group velocity for short periods (less than 20 s) caused by a thick layer of the sediments. In some cases the maximum of the group velocity becomes less than 2 km/s. The Rayleigh wave results are very similar. Since our processing window for group velocity estimation was between 2 km/s and 4 km/s, the magnitudes for these events could be underestimated. For some ray trajectories (e.g. event 2008.01.19) different periods apparently follow separate dispersion curves, which means that these paths go along the boundary between the different tectonic areas. Such complicated wavefield may lead to spurious errors in the magnitude estimation, because the scattered energy adds to the roughness of the spectra used to compute the magnitudes.

Developing Empirical Expressions for Rayleigh and Love Magnitudes

The Russell (2006) Ms formula has opened up new avenues of scientific research, such as the development of improved regional surface wave Q models (Stevens et al., 2006; Levshin et al., 2006; Cong and Mitchell, 2006) that may further reduce interstation variance of the magnitudes. The next step in our project is to either show the validity of Equation 1 for Love waves or to develop a new formula, which takes into account the excitation and attenuation of Love waves. For this task we needed in some instances to use the Russell formula without the attenuation and/or excitation corrections to evaluate the role of each one on Love wave magnitudes. Recalculating Ms(VMAX) without corrections is a time-consuming process, therefore we chose to simply subtract the correction values from already computed Ms(VMAX) values.

In order to find this correction we first need the values without the attenuation and the excitation corrections. 1 M VMAX a )log()( += f −−∆ 43.0)log())log(sin( (2) s b 2 c We then solve a system of equations: ,0 i i i s s aMM ∆−= j (3) i th th ,0 i where ∆ j is the distance between the i event and the j station and M s is the uncorrected magnitude values i obtained from (1) by subtracting the attenuation correction, to obtain the corrected magnitudes M s and the attenuation parameter a.

The solution of the inverse problem (3) yields the attenuation coefficient of 0.0037 for the Rayleigh and 0.0042 for the Love waves. We tried to incorporate the dependence on the period T into the inverse problem, but it didn’t improve the RMS residuals. The final formulas with the distance correction are: 1 M R* VMAX a )log()( += 0037.0))log(sin( f −−∆+∆ 43.0)log( (4) s b 2 c

533 2010 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies

1 M L* (VMAX a )log() += 0042.0))log(sin( f −−∆+∆ 43.0)log( (5) s b 2 c

The attenuation coefficients are very close to the value obtained by Russell (0.0031 in the original formula (Equation 1) vs. 0.0037 for the Rayleigh waves (Equation 4) and 0.0042 for the Love waves (Equation 5).

We compared the magnitude values Ms (VMAX) estimated with Russell formula and with Equations 4 and 5. The regression lines are given by the following equations: M R* VMAX = M RUS VMAX − 0424.0)(0085.1)( (6) ss s L* RUS M s VMAX = M s VMAX − 0817.0)(0201.1)( Application of the new corrections improves the residuals for the events used in the inversion; however it doesn’t improve the RMS residuals for the entire data set.

Automatic Detection of Rayleigh and Love Waves

To make automatic surface wave detection and association for the purposes of the magnitude estimate we modified EVALSURF program. In the original version the surface wave dispersion, SNR and the polarization direction for the Rayleigh waves are calculated, but only the degree of fitness of the dispersion curve is used for the decision making process (if the group velocities measured for less than 75% of the periods are outside one standard deviation the entire record is considered unacceptable). Other parameters are used by the analyst in order to visually determine the measurement quality. In the new version we first determine if the polarization of the surface wave is within 30 degrees from the great circle backazimuth. To determine polarization direction of Rayleigh waves we used the Chael (1997) technique based on the elliptical particle motion, while for the Love waves we used principal component analysis. If the record satisfies this condition we find the periods between 8 sec and 40 sec for which the following is satisfied:

1) The signal-to-noise ratio is greater than 3. This is an arbitrary number, which can be changed if we find more appropriate value. 2) The observed group velocity is within an acceptable error of the model-predicted dispersion curve.

The maximum amplitude is then computed only for the periods satisfying these conditions. To further enhance the surface wave detection and association, we are working on a surface wave “quality” measure, similar to the ones proposed by Levshin et al. (1992). We use the wave polarization and the number of periods fitting the dispersion curve to develop a preliminary scale for determining “quality” of the surface wave and the magnitude evaluation. Figure 4 shows an example of the automated magnitude picking for a large event (2006.06.03, mb=5.4) using three different stations. For this event the SNR is acceptable for most stations and periods. The largest Rayleigh wave amplitude recorded by station KIV, however, fails the dispersion test; therefore a different magnitude value is picked. Notice that there is a significant difference between the magnitudes estimated at GNI and KIV, even though these stations are separated by approximately 500 km.

Love and Rayleigh Wave Ms(VMAX) in Italy

We applied the Ms(VMAX) measurement technique (Equation 1) to 125 earthquakes in Italy. Many of these events were aftershocks of the damaging L'Aquila mainshock that occurred on 6 April 2009 (Mw=6.1) in central Italy. The analysis resulted in 1449 and 1142 magnitude estimates for Rayleigh and Love waves, respectively, with over 90% of the estimates at source-station of less than 200 km. The dominant period of the measurements was ~8 seconds for Rayleigh waves and between 8 and 12 seconds for the Love waves. The interstation standard deviation for the Rayleigh waves averaged 0.17 m.u., which was slightly lower than for the Love waves (~0.20 m.u.). Comparison of the magnitude residuals with azimuth show the increased variance for the Love waves was due to more complicated radiation patterns. Figure 5a shows the results of the Italian earthquake analysis. The network-averaged magnitudes show that most of the events (80%) had a Love-wave Ms that was larger (average 0.2 m.u.) than the Rayleigh-wave estimate. Relationships between moment magnitude (Mw) and Ms(VMAX) for both Rayleigh and Love waves were estimated using orthogonal regression and include:

534 2010 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies

R R M w = M s VMAX + 78.1)(68.0 (7) L L M w = M s VMAX + 64.1)(69.0

Figure 4. Example of Ms(VMAX) estimate using the new version of the program with automatic picking for event 2006.06.03 (mb=5.4): a) Station ANTO, b) Station GNI, and c) Station KIV. The blue lines show the results for Rayleigh waves, the green lines are Love waves.

Love and Rayleigh Wave Ms(VMAX) in the Yellow Sea/Korean Peninsula Region

The last dataset that we used to study the Ms(VMAX) measurement technique originated from the in the Yellow Sea/Korean Peninsula region (YSKP). We found Ms(VMAX) for 31 earthquakes and 2 announced nuclear explosions. The analysis resulted in 266 and 298 magnitude estimates for Rayleigh and Love waves, respectively, with over 90% of the estimates at source-station of less than 700 km. The dominant periods of the measurements for Rayleigh waves less than 13 seconds; however, the Love wave magnitudes equally sampled periods between 8 and 20 seconds. The interstation magnitude standard deviation for the Rayleigh and Love waves averaged 0.11 and 0.22 m.u., respectively. Figure 5b shows the results of the YSKP magnitude analysis. The network-averaged magnitudes show that most of the events (81%) had a Love-wave Ms that was larger than the Rayleigh-wave estimate. For comparison, the Ms(VMAX) was 3.6 and 3.1 for Rayleigh and Love waves, respectively, recorded from the 25 May 2009 announced nuclear explosion. Relationships between moment magnitude (Mw) and Ms(VMAX) were estimated using orthogonal regression and include:

R R M w = M s VMAX + 18.2)(60.0 (8) L L M w = M s VMAX + 83.1)(65.0

535 2010 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies

Figure 5. Ms(VMAX) Love versus Ms (VMAX) Rayleigh for 125 events in Italy (left) and 32 events in the YSKP (right).

CONCLUSIONS AND RECOMMENDATIONS

During the past year, we continued studying the application of the Ms(VMAX) magnitude measuring technique (Russell, 2006) to both Rayleigh and Love waves. We have automated the method, examined structural effects on the formula in the Middle East, applied the method to earthquakes in Italy, Korea and Yellow Sea regions, and examined performance of the method at the United States Geological Survey National Earthquake Information Center (USGS NEIC).

While studying the variability of Ms (VMAX) measurements in the Middle East, we found a significant magnitude bias between the stations situated to the northwest and northeast from the area of Middle East. We attribute this bias to the surface wave scattering by the Caspian and the Black Seas and the Great Caucasus Mountains.

We studied the suitability of the Russell formula for Love waves. We computed the attenuation correction by fitting a linear regression to uncorrected Ms (VMAX) measurements for both Rayleigh and Love waves. The attenuation coefficients calculated as a result are 0.0037 for the Rayleigh and 0.0042 for the Love waves (compared to 0.0031 in the original formula). Application of the new corrections improves the residuals for the events used in the inversion; however it doesn’t improve the RMS residuals for the entire data set.

For the past 50 years, comparing Ms:mb has been a workhorse in the teleseismic discrimination of earthquakes and explosions. Figure 6 shows the comparison of Ms(VMAX):mb for the Weston Geophysical Corp. database. We note that the Murphy et al. (1997) screening line, which was developed exclusive of this dataset, does an excellent job of separating the earthquake and explosion populations, with the exception of the announced North Korean nuclear explosions. The two North Korean explosions plot either on or slightly above the descision line; however, when the error of the screening line is considered, the North Korean events would not have been screened as earthquakes. Selby and Bowers (2009) have suggested that a new screening line would ensure that no explosions are screened as earthquakes. Our approach is to consider additional properties of surface waves in the screening process before the Murphy et al. (1997) screening line is abandoned. Our results to date show there is potential event screening information in comparing Rayleigh- and Love-wave magnitudes for earthquakes and explosions. In the final year of this project, we will incorporate a formal discriminant of Ms(VMAX):mb into the Event Classification Matrix (Anderson et al., 2007) and seek methods of combining those results with new techniques for Ms(Love): Ms(Rayleigh) screening (Figure 6).

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Figure 6. (Left). Traditional Ms(VMAX):mb discrimination of earthquakes and explosions using the Murphy et al. (1997) screening line. (Right). New techniques that compare Ms(Love) versus Ms(Rayleigh). Of 292 earthquakes, only 58 (20%) have Rayleigh-wave magnitudes larger than the Love wave magnitudes. To date, all of the explosions we have analyzed have exhibited larger Rayleigh-wave magnitudes than Love waves.

REFERENCES

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Murphy, J. R., B. W. Barker, and M. E. Marshall (1997). Event screening at the IDC using the Ms/mb discriminant. Maxwell Technologies Final Report. 23 p. Neprochnov, Y. P. (1968). Structure of the earth’s crust in epi-continental seas: Caspian, Black, and Mediterranean, Can. J. Earth. Sci. 5: 1037–1043. Priestley, K. and S. Mangino (1995). Seismic studies of the Caspian Basin and surrounding regions. Final Report. PL-TR-95-2154. 73 p. Rezanov, I. A. and S. S. Chamo, (1969). Reasons for absence of a granitic layer in the basins of the South Caspian and Black Sea type. Can. J. Earth Sci. 6: 671–678.

Rezapour, M., and R. G. Pearce (1998). Bias in surface-wave magnitude Ms due to inadequate distance correction. Bull. Seism. Soc. Am. 88: 43–61. Russell, D. R. (2006). Development of a time-domain, variable-period surface wave magnitude measurement procedure for application at regional and teleseismic distances. Part I—Theory. Bull. Seism. Soc. Am. 96: 665–677. Selby, N. D. and D. Bowers (2009). UK National Data Centre analysis of the 2006 and 2009 DPRK nuclear tests, and implications for event screening in the context of the CTBT. AGU Abstracts for the Fall 2009 Meeting, Abstract # SW31C-1735. Stevens, J., J. Given, G. Baker, and H. Xu (2006). Development of surface wave dispersion and attenuation maps and improved methods for measuring surface waves, in Proceedings of the 28th Seismic Research Review: Ground-Based Nuclear Explosion Monitoring Technologies, LA-UR-06-5471, Vol. 1, pp. 273–281.

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