Regional and Far-Regional Earthquake Locations and Source Parameters Using Sparse Broadband Networks: A Test on the Ridgecrest Sequence

Transcription

1 Bulletin of the Seismological Society of America, Vol. 88, No. 6, pp , December 1998 Regional and Far-Regional Earthquake Locations and Source Parameters Using Sparse Broadband Networks: A Test on the Ridgecrest Sequence by Douglas Dreger, Robert Uhrhammer, Michael Pasyanos, Joseph Franck, and Barbara Romanowicz Abstract Events of the 1995 Ridgecrest, California, earthquake sequence were located and source parameters were estimated using data recorded by the broadband, high-dynamic-range instrumentation of the Berkeley Digital Seismic Network (BDSN). The purpose of this study is to investigate the capability of a sparse broadband network at monitoring a region located outside of the network, as will be the case in the monitoring of the Comprehensive Test Ban Treaty (CTBT) for lowmagnitude seismic events. In addition, we present a case study that is representative of the capabilities of other regional broadband networks. To assess the capability of a sparse network, we compared locations estimated from BDSN phase measurements to a "ground truth" catalog of high-quality earthquake locations derived from data recorded by the Southern California Seismic Network (SCSN). An adaptive grid search location program that utilizes the timing and azimuth of multiple-phase picks from one or more stations was used to determine the importance of the different types of data on absolute event locations. Sparse subnets of BDSN stations in the distance ranges from 25 to 5 km and 5 to 8 km were used. The results indicate that in the regional distance range, it is possible to obtain absolute event locations to within 18 km as is prescribed by the CTBT; however, in the far-regional distance range, the lower signal-to-noise levels precluded the location of the events to within the CTBT objective. Introduction Sparse broadband networks often offer the best opportunity to analyze seismic events, particularly in those cases in which the event of interest is located far outside the recording network. This will likely be the case in the monitoring of the Comprehensive Test Ban Treaty (CTBT) using the International Seismic Monitoring System (ISMS) for small-magnitude events and for studying earthquakes in the United States using the National Seismic Network (NSN). Sparse broadband networks have recently been deployed in northern and southern California (BDSN and TERRAscope, respectively), Mediterranean (MedNet), Japan (FREESIA), and the continental United States (USGS NSN), and on a global scale (IRIS GSN). Stations from some of these networks contribute to the International Seismic Monitoring System (ISMS). A key design consideration for the primary and auxiliary seismic networks of the ISMS was that these networks be capable of locating events M --> 4 with an uncertainty of less than 1 km 2, that is, within a circle of radius less than 18 kin. For low-yield explosions or evasively tested nuclear devices, the resulting small magnitudes will preclude the recording of signals from IMS stations at teleseismic distances and will necessarily focus the analysis effort at distances of a few hundred to perhaps 2 km, where lateral heterogeneity in Earth structure significantly complicates the problem. The purpose of this article is to report on our study that evaluated the effectiveness of a sparse broadband network at monitoring a region and to discuss the modifications to standard processing techniques, which can improve performance. Both location and moment tensor analyses are evaluated in the context of using the Berkeley Digital Seismic Network (BDSN) to monitor a region outside of the network coverage such as southern California. In particular, we focused our analysis on the recent Ridgecrest California sequence in southern California because the prolific aftershock sequence has both large events to provide calibration and small events to test location capability and threshold. BDSN stations are located at distances ranging from 25 to 8 kin from the Ridgecrest sequence, thereby providing a reasonable test of regional location capability (e.g., Fig. 1). 1353

2 1354 D. Dreger, R. Uhrhammer, M. Pasyanos, J. Franck, and B. Romanowicz 42.5 BDSN Locations - No azimuth, No adjustments Table 1 SCSN Earthquake Catalog Locations Year.doy Origin Time Latitude (N) Long. (W) Depth (km) Magnitude ID Number ~D o A,o v4 Ridgecrest Sequence \~ PKD~ longitude Figure 1. Map showing the locations of BDSN station (triangles), northern California control events (hexagons) with mislocation vectors describing the relative locations when only P and S arrival-time information is used. The northern California control locations utilized phase picks from BDSN and the northern California Seismic Network (NCSN). Within BDSN, the location capability is very good, and outside the network mislocations become large. The Ridgecrest sequence in southern California is the focus of the present study. Methodology Event locations reported in the SCSN Earthquake Catalog distributed by the Southern California Earthquake Center (SCEC) are used as "ground truth." These locations are obtained from phase arrivals recorded by SCSN, which consists of more than 35 analog and digital instruments located throughout southern California. The Ridgecrest events used in this study (Table 1) are located to within a circle of radius 4 km and therefore will provide an excellent basis from which to test the capabilities of the BDSN network. All of the events in Table 1 are reported as quality A, which have sub-kilometer location errors both laterally and in depth (e.g., Given et al., 1987). Because the events are so closely located, they essentially have the same propagation path at regional and far-regional distances. Therefore, the effects of lateral heterogeneity on the waveforms for each event should be the same, and our analysis can focus on the effects of picking bias, methodology, and calibration. To examine the location capability of the sparse BDSN network, three analysts independently made P, S, and azimuth measurements and computed station adjustments. Each analyst was instructed to make consistent phase picks and to use the two largest events in the Ridgecrest sequence (Table 1) to derive average station adjustments for P, S, and azi :39: * :29: :54: :58: :37: :27: * :56: :46: :57: :11: :48: :15: :21: :47: :36: :1: :15: :45: :42: : :29: :32: :52: Origin time is UTC. Magnitudes are as reported by SCEC and may be either duration or M L. * denotes calibration events. muth. No instruction as to which regional phase to pick was given. One analyst chose to use the Sn arrival, and the other two used higher-frequency, later-arriving phases. All three picked the first-arriving Pn phase. Azimuth was estimated from either P~t or Love waves. The events were then located using combinations of different types of information to assess absolute location quality relative to the ground truth catalog. From our earlier work (Fig. 1; Dreger et ai., 1996), we knew that the linearized, iterative location algorithm we routinely employ (e.g., Canas et al., 1977) needed to be improved for sparse network configurations. In this work, we have used a newly developed location program that specializes in sparse network geometry and is discussed in the next section. The three analysts performed a number of event location simulations to test the importance of various types of observations, such as P and S arrival times, wave propagation azimuth, and network geometry on absolute location quality. Generally, the results of each of the analysts were very similar, and in the interest of brevity, we only present the results from analyst one. Analyst one used phase measurements from at most six stations, and for most events, four or fewer of the closest stations were used (e.g., CMB, MHC, PKD1, and SAO). In addition, only two stations (PKD1 and CMB) were used to measure azimuth. A gradient over a half-space approximation to the SoCal model of Dreger and Helmberger (1993) was used to compute P and S arrival times, where

3 Regional and Far-Regional Earthquake Locations and Source Parameters Using Sparse Broadband Networks 1355 or(z) = z; z < 35 km; ~ (~/( c~(z) = 7.8; z >35km, P = 1 = i=l - 2)(~r)2/nt + )],(A 6~)2/n~) n rm, fl(z) = z; fl(z) = 4.5; z >-- 35km, z < 35 km; where a, fl, and z are the P- and S-wave velocities (km/sec), and depth (km), respectively. The phase measurements were made on broadband (.1 to 1 Hz) displacement or velocity data, and azimuth measurements were performed on low-pass filtered (fourpole, zero-phase butterworth filter, with a corner of.1 Hz) displacement data. Determining the azimuth in this manner was relatively easy, and we estimated that our measurement resolution is on the order of _ 3. The measurement resolution is independent of the systematic adjustments that are needed due to the heterogeneity of the Earth's crust. Broadband Waveform Regional Earthquake Location Program (BW-RELP) To improve the sparse network locations, a new program, herein referred to as BW-RELP, was developed to make use of multiple-phase picks and azimuth information. The details of this program will be discussed in a forthcoming article; however, it is useful to briefly describe its operation here. An adaptive grid search technique was used providing a level of flexibility that would be difficult to achieve with a standard inverse approach. For example, this code allows for path-dependent velocity models, station adjustments, and azimuth corrections. Flexible misfit norms can be used to analyze the effect that outlying observations have on a solution. An adaptive grid search scheme allows more control of the differential weighting of the various traveltime and azimuth data. The adaptive grid search is also more amenable to the incorporation of 3D velocity models because it is not necessary to compute complicated partial derivatives. BW-RELP searches over latitude, longitude, depth, and origin time. In our calculations, we fixed the depth at 8 km because the events are located far from the stations, and we did not pick depth phases to help constrain source depth. The value of 8 km was chosen because it is representative of an average source depth in California. The average hypocentral depth of the events in Table 1 is 5.5 km. The range of latitude and longitude was several degrees, each encompassing the Ridgecrest and surrounding region. For several events, a search area spanning the entire state of California and parts of Nevada and Arizona was tested, and the results from those experiments revealed that there was a single minimum centered in the Ridgecrest area. The misfit function that is used in BW-RELP is defined as where P is the misfit value and 2 is a parameter that provides relative weighting between travel time and azimuth residuals. The code utilizes only travel-time information if 2 = and only azimuth information if 2 = 1.6 r is the travel-time residual that is cast in terms of a distance metric (6 r = 6 t* metric) to provide a straightforward comparison to the arc length A6(. & is the azimuth residual and A is the distance to a station. The metric is set to an average seismic-wave velocity such as 6 km/sec, nt and n~o are the number of time picks and azimuth picks, respectively. The norm can range between and o~. Values of 1 and 2 correspond to the L 1 and L2 norms, respectively. In our calculations, we set norm to 1.25 following Kennett (1996). The summation is performed for n phase readings where the phase readings can be either P or S arrival times or wave azimuth. With the grid search algorithm, it is possible to map out the parameter space in order to analyze the resolution and uncertainty of a given calculation. For example, Figure 2a shows how the adaptive grid search procedure converges. The procedure is adaptive in the sense that if the best location lies near the edge of a grid, the grid will creep rather than contract. When the minimum is toward the center, the dimension of the grid shrinks and the sampling density increases, as shown in Figure 2a. Figures 2b to 2d show how the resulting parameter space changes with the addition of various types of waveform information. The calculation using only P arrival times is clearly poorly resolved. The addition of S-wave arrival times and Pnt azimuth determined from particle motions of the three-component broadband data serves to reduce the size of the minimum as well as provide a better location in the absolute sense. The addition of both travel-time and azimuth station adjustments are needed to focus the event onto the control location. The parameter space contains all of the information needed to estimate the precision of the solution. There is no direct mapping to standard error measures, and there is no guarantee that the parameter space will have an ellipsoidal shape. In fact, Figure 2 shows that it does not in some of the cases. Therefore, to provide an estimate of solution precision, travel-time and azimuth residuals are cast into a common distance metric that is then used to map the uncertainty surface around the global minimum. This is done by calculating the standard deviation of the travel-time residuals (o-) and then perturbing the origin time by either + cr for a normal measure of uncertainty and by +2~r'for a 95% confidence surface. P95 defines such a + 2cr precision surface in four-dimensional space around the global minimum. P95 is considered a better measure of the location precision because it accounts for the distortions from an idealized elliptical error surface. For example, as Figure 2 shows, the shape of the minimum is generally different from a simple ellipsoid that is due to the geometry of the observing network.

4 1356 D. Dreger, R. Uhrhammer, M. Pasyanos, J. Franck, a~d B. Romanowicz Adapt~e Grid Search P picks only P, S, azimuth - no adjustments P, S, azimuth - with adjustments Figure 2. (a) Example of an adaptive grid search. The circles show the specific locations that were tested. The grid shifts and contracts as the method converges. (b) Plot showing ln(p) for the case in which only P arrival times are used. (c) ln(p) when P, S, and azimuth with no adjustments are used. (d) Same as (c) with travel-time and azimuth station adjustments applied. In all cases, the white circle shows the ground truth location. The full range of gray spans a range of 12.5 in P. Analysis of Event Locations The Ridgecrest events located using only BDSN phase picks and a linearized travel-time inverse procedure without adjustments were found to have large absolute mislocations, in some cases exceeding 1 kin. The direction of these mislocation errors can be either toward or away from the recording network, as shown in Figure 1. In the former case, the mislocation error is likely to be due to a bad phase pick at a station with considerable weight in the inversion and the nature of a locally linearized inverse procedure. In the latter case, it is a characteristic origin-time distance trade-off. Because the phase measurements used in Figure 1 were made over the course of 1 year, the consistency in the picks is not as good as they are in this article, where the measurements were made over several days. In Figure 3, we compare the absolute event locations obtained using BW-RELP with various combinations of phase and azimuth observations. Panel one compares the event locations that are obtained when only P phases are used. Generally, the events are distributed along a vector pointing away from the BDSN stations, which is characteristic of an origin time-distance trade-off. The inclusion of azimuth information, and static travel-time and azimuth station adjustments (panel two), improves the locations in terms of decreasing event cluster size and in terms of centering the events on the ground truth location. Panel three compares the absolute locations when both P- and S-phase readings are used, and panel four shows a blowup of the epicentral region. The large circle shows the 1-km 2 target region (18-kin radius). The inclusion of S phases greatly reduces the origin time-distance trade-off and focuses the events into a circular distribution rather than the linear trend characteristic of the P-wave-only calculations.

5 Regional and Far-Regional Earthquake Locations and Source Parameters Using Sparse Broadband Networks 1357 The event distribution shown in panels three and four are the result of careful, consistent phase picking, which was done sequentially over a period of several days. The phase picks in Figure 1 were made over the course of the year, as the events occurred. The inclusion of azimuth information (panel five) improves the clustering of the events and slightly reduces the absolute mislocation of the cluster. Although the dimension of the event distribution is greatly reduced, the absolute mislocation relative to ground truth can remain large. For example, the centroid of the distribution in panel five is 36.7 km from the centroid of the control catalog (center of the large circle). The dimension of the distribution is large, and a significant number of events lie more than 2 km from the distribution centroid. The average P95 errors in latitude and longitude are 19 kin. Thus, a number of events may have P95 errors that do not overlap the ground truth location. Recall that P95 is simply a surface, which describes the range of locations for which the calculated travel times fit the data to within 2a of the travel-time residuals. Of course, it is not necessary that P95 or conventional standard errors overlap with the absolute location because of unknown errors due to the 3D Earth being approximated by assumed 1D velocity models. As panel six shows, it is the incorporation of travel-time and azimuth station adjustments that focuses and tightens the event distributions onto the true location. It is remarkable that the locations, obtained using only a few stations with very limited aperture, are as good as shown in Figure 3. It is important to note, however, that if you examine the performance binned over magnitude, there are still mislocations exceeding the CTBT goal of absolute errors of less than 18 km (Fig. 4). Nevertheless, Figure 4 shows that it is possible to achieve absolute event location accuracy of better than 18 km to a low magnitude of 3.5. With further calibration and review of picks, it is likely that all of the events above magnitude 4. could be located to within 18 km of ground truth. Figure 5 details the improvements for two events of magnitude 4.2 (95-12) and 3.5 (95-131). The histogram shows that the addition of azimuth information greatly reduces the level of mislocation, especially when only P arrival time and azimuth are included. The best locations are obtained when azimuth and S-wave picks are used. To obtain locations within a radius of 18 km of ground truth, it is necessary to apply static travel-time and azimuth station adjustments. Note that even with the adjustments applied, it was not possible to locate the M 3.5 event (95-131) within a radius of 18 km of ground truth. The previous test is representative of the geometry presented to BDSN, TERRAscope, and the NSN for regional events; however, it is still a very favorable monitoring geometry in the context of the CTBT and ISMS. Another test that is more representative of future CTBT monitoring situations for small-magnitude events repeats the previous experiment using only stations CMB, MHC, and SAO, thereby reducing the aperture of the network to 3. The same station ~,,,.~anell " ~'.,~anel E ~ ~o ~ ~o m panel 5 Q o ~3~om o oo ~ o " * i panel 4 G C~OoO oo Oo o i i t o -117 panel 6 i i i i " -117 Figure 3. Event location maps for analyst 1 comparing the effects that the different combinations of phase, azimuth, and adjustment information have on absolute locations. The ground truth locations all plot within a square one-half the size shown. I I I I f I f I I I o 8 o ~ o o o~ :o "o o Analyst 1 Analyst Magnitude Figure 4. Mislocation relative to ground truth is plotted as a function of magnitude. Open circles show absolute mislocation obtained by two of the analysts. The average mislocation with 1 sigma error bat's is also shown (filled square). The horizontal line marks the 18-km level corresponding to a location accuracy of 1 knl 2. o

6 1358 D. Dreger, R. Uhrhammer, M. Pasyanos, J. Franck, and B. Romanowicz ~" 1 8 o 6.on IE 4 2 "~r~. 3km [] evt95-12 [] evt p P, az P, az, ad P,S P, S, az P, S, az, ad cedure that utilizes only direct arrival times cannot accurately determine source depth with such a sparse network. The moment tensor calculations in the following section demonstrate how source depth may be obtained from longperiod waveform data of a sparse network. It may be possible to constrain source depth if depth-sensitive phases such as pp, sp, and spmp can be identified in the data and adequate station adjustments could be determined. This is beyond the scope of this article, whose purpose is to demonstrate the level of performance that might be expected at regional and far-regional distances using standard event-location practice. Figure 5. Histogram showing the improvement in absolute mislocation for two events. The event information is listed in Table 1. The horizontal line defines the 18-km mislocafion level. Note that the absolute mislocation is generally greater for the smaller event, presumably due to reduced signal-to-noise quality. The addition of first azimuth measurements and then S picks and travel-time and azimuth adjustments systematically reduces the magnitude of the absolute mislocafion. adjustments were employed. In Figure 6, we compare the location maps obtained by analysts 1 and 2. The events are still well clustered; however, they are not as tightly grouped as in panel six on Figure 3. The mislocation versus magnitude plot (Fig. 6b) shows that many events lie below the 18- km CTBT objective; however, quite a few of the low-magnitude events have absolute mislocations greater than 18 km. Figure 7 shows the results using P, S, and azimuth picks that were obtained from only the far-regional stations, HOPS, CMB, WDC, and YBH. In this case, station adjustments were derived from event (Table 1). There is a marked improvement with the addition of the station adjustments; however, all of the events tested are located farther than 18 km from ground truth. The P95 surface intersects the ground truth location for only three of the six events tested. At these far-regional distances, it is difficult to consistently pick the first-arriving P wave, which is a low-amplitude Pn arrival. Although it was not examined further in this study, it may be possible to improve on the far-regional locations by picking later larger-amplitude arrivals and employing the appropriate static station adjustments. Furthermore, it is anticipated that an additional station between 5 and 8 km at a different azimuth would greatly improve the results. In any case, the degradation of the locations due to decreased signal-to-noise levels indicates that arrays would be very useful for identifying both first arrivals in noisy far-regional data and for estimating the propagation azimuth at far-regional distances. In the foregoing, we have restrained the source depth of all events to 8 km. This was done because the closest station used in our analysis lies at a distance more than a factor of 3 to 5 of the average source depth of the sequence. The method used in this study as with any other location pro- Seismic Moment Tensors A time-domain inverse procedure (e.g., Dreger and Romanowicz, 1994; Pasyanos et al., 1996) was used to estimate the seismic moment tensor of events listed in Table 1. The three-component data were integrated to displacement and bandpass filtered between.2 and.5 Hz. In this passband, the average one-dimensional models that we employ perform quite well in the modeling of the data. For example, as Figure 8 shows, we are able to fit the data for the three events with greater than 8% variance reduction. Table 2 lists the moment tensor inversion results, and Figure 9 plots the moment tensor results in map view. Only three stations, namely, CMB, PKD1, and SAO, were used; however, for a number of events, one or more stations had to be removed due to poor signal-to-noise ratios. In these cases, the PAS and PFO TERRAscope stations were used to improve the station coverage, and in every case, the combined BDSN and TERRAscope solution compared very well with the BDSN only result. SOIl, in other cases, it was not possible to estimate the moment tensor using only the BDSN. The lower threshold appears to be in the M 3.8 to 3.9 range, and it depends on the background noise level of a given day and the distance to the stations used. Table 2 shows that the Ridgecrest sequence consists of quite diverse focal mechanisms, although the predominant mechanism is right-lateral slip on a northwest-trending plane. The seismicity located at the southwestern edge of the sequence appears to align with the northwest-trending nodal plane (Fig. 9). Other mechanisms appear to be associated with different clusters of seismicity. The agreement between data and synthetic is quite good in the.2- to.5-hz passband, and the variation in the resulting focal mechanisms is supported by significant differences in the low-frequency waveforms. In cases where independent estimates of the seismic moment tensor were available from either surface waves (Hong Kie Thio, written commun.) or broadband waveforms (Lupei Zhu, written commun.), the agreement is quite good with our sparse station results. Additionally, the first-motion results for the three largest events in 1995 as reported by Hauksson et al. (1995) are in good agreement with our moment tensor results. The first-motion data indicate that the mainshock

7 Regional and Far-Regional Earthquake Locations and Source Parameters Using Sparse Broadband Networks 1359 Analyst I Analyst 2 39" \ '. \, \ '. \, i. 37' :~ - A) \ B 33" %. -~2. ' -~o. ' -,h. ' -fie " -fi4. ' -m. ~'~u" -m. -~o. -lls' -116' -114' -112' II I 9 ~" so r- 7.9 ~ 6.~ 5 4 i I i i i I I I I o Analyst 1 Analyst ~. o o o 1 ~ i i i I i C) Magnitude O O i i ; ~ Figure 6. (a) Map showing analyst 1 event locations when only three stations are used. Triangles show the locations of the stations. P and S arrival times, azimuth, and station adjustments measured at CMB, MHC, and SAO were used. (b) Same as (a) for analyst 2. (c) The absolute mislocation relative to ground truth plotted against magnitude is compared for analysts 1 (open circles) and 2 (filled circles). The horizontal line marks the 18-km mislocation level. (event 95-78, Table 1) initiated as a normal event; however, the waveforms indicate that the earthquake evolved into strike-slip faulting (e.g., Hauksson et al., 1995; this study). As reported by Dreger and Helmberger (1993), the timedomain moment tensor method employed in this article is insensitive to lateral mislocation of the hypocenter. In Dreger and Helmberger (1993), it was reported that in the Press- Ewing (3 to 9) passband, lateral mislocations of 15 km could be tolerated. In the.2- to.5-hz passband used in this article, the magnitude of tolerable mislocation is substantially greater. For example, when event is inverted using the location in panel 5 of Figure 3 (a 35-kin mislocation to the SE), the following solution is obtained: strike = 339, dip = 88, rake = 173, depth = 8 km, and Mo = dyne-cm. This solution is within 1% of the seismic moment of the solution in Table 2. The maximum deviation is 13 in rake and 6 km in depth. In another case, event had a 54-km absolute mislocation from ground truth when station adjustments were not employed. This mislocation translates to a maximum of 24-km error in source-station distance to CMB and a 9 error in azimuth to the PKD1 station. Nevertheless, a solution of strike = 358, dip = 25, rake = 128, depth = 5 km, and M = 7.1 X 121 dyne-cm was obtained. This represents a 38 change in the rake angle; however, the predominantly normal nature of this event is preserved. Velocity models need to be relatively well calibrated to essentially explain the average P- and S-wave velocities and crustal thickness. If the model is not calibrated, unreliable results may be obtained from a sparse network. In California, only two velocity models are

8 _ 136 D. Dreger, R. Uhrhammer, M. Pasyanos, J. Franck, and B. Romanowicz 42" Tangential Radial Vertical 4" 38" 36" \ " P K D ~ M a x ~ V R = ~ 3. see Strike=334 ; 66 Rake =161 ; 7 Dip =84 ; 71 Mo =1.13c+24 Mw Percent DC=51 Percent CLVD=49 Var. Red=8.22e+1 RES/Pde.=I.97e-9 84" r 32" -128" 42" 4" -126" -124" -122" -t2" -I18" -i16" -114" -i12" \ C M ~ M a x ~ V R = ~ S A ~ M a x Amp=3.74e-'~ cm VR=86.6 P Max Amp=5.13e-4 cm VR= see Strik~18 ; 18 Rake =-155 ;-1 Dip =89 ; 65 Mo =9.13e+22 Mw Percent DC=93 Percent CLVD=7 Var. Red=8.75e+1 RES/Pdc.=9.7e-12 38" g6" 34" r 32" C M ~ M a x Amp=1.86e-4 cm VR=87.3 P.., Max =. - VR= see Stfike=189 ; 1 Rake =-91 ; -89 Dip =54 ; 36 Mo =9.64c+22 Mw =4.6 Percent DC=93 Percent CLVD=7 Variance=6.62c- 1 Vat. Rcd=8.33e+1 RES/Pde.=7.1 le " -126" -124" -122" -12" -i18" -116" -i14" -I12" Figure 7. (a) Map showing the locations (circles) obtained using P, S, and azimuth picks from stations HOPS, CMB, WDC, and YBH. The small square shows the aftershock area from the SCEC control catflog. (b) Same as (a) with travel-time and azimuth station adjustments applied. The filled circle shows the 1-krn 2 area surrounding the Ridgecrest source region. needed: one for the region west of the coast ranges thrust and the other for the Sierra Nevada and southern California (e.g., Pasyanos et al., 1996). Conclusion and Discussion The results of our analysis of the Ridgecrest sequence reveal that it is possible to obtain event locations with better than 18-kin accuracy using a sparse network of regional distance broadband, three-component stations to magnitudes as low as 3.5. However, as Figure 4 shows, substantial mislocations result for some events with magnitude less than 4.1. The consistency of the phase picks achieved by analyzing Figure 8. Compares the level of fit between lowfrequency data (solid) and synthetic (dashed) for three representative events of the Ridgecrest sequence. Note that the locations of both SH and P-SV nodes differ for the three events and that the differences in the focal mechanisms are strongly supported by the wave forms. all of the waveforms at one time leads to better relative event locations, and the calibration of travel-time and azimuth adjustments leads to low absolute mislocation. The lower threshold of course depends upon the ambient background noise level, and other regions of interest may have higher or lower thresholds. Large absolute mislocations were obtained in the very sparse network experiment (Fig. 7), indicating that better calibration and phase picks would be needed to obtain the desired accuracy level, although another station in the far-regional distance range but at a different azimuth would be expected to improve the results. Generally, the addition of azimuth information from a few stations greatly

9 Regional and Far-Regional Earthquake Locations and Source Parameters Using Sparse Broadband Networks 1361 Table 2 Moment Tensor Solutions Magnitude Origin Time Seismic ID Year.doy (UTC) SCEC Mw M o (124) Strike Dip Rake Depth Number :39: :29: :54: * :58: * :37: :27: :56: too noisy :46: * :57: * :11: too noisy :48: * :15: too noisy :21: too noisy :47: :36: too noisy :1: * :15: too noisy :45: too noisy :42: too noisy :49: too noisy :29: :32: :52: *PKD too noisy. Stations CMB, SAO, PAS, and PFO were used. The solutions compare well with that obtained using only CMB and SAO. tpkd too noisy. Stations CMB and SAO were used. The TERRAscope stations PAS and PFO were too noisy to include in the inversion. *PKD and SAO too noisy. CMB, PAS, and PFO were used. The solution compares very well with what is obtained when only CMB is used. Units are dyne cm. 36* 35 48' ' i t -118 ' -117"48' ' ' ' -117 ' Figure 9. Map showing the locations of events from the SCSN Earthquake Catalog and seismic moment tensors obtained by inverting low-frequency waveforms recorded at BDSN stations CMB, PKD1, and SAO. improved the clustering of the event locations. Finally, our best locations were obtained using station adjustments ob- tained from two large calibration events. Without such ad- justments, the best that we did is shown in panel 5 of Figure 3. While many of the events in this case are located fairly well in terms of the small size of the P95 error, the cluster centroid is 36.7 km from ground truth, and there are many individual events that fall outside of the 18-kin accuracy level. For the far-regional cases, all of the events fell outside the desired accuracy goal. Thus, in regions with few calibration events, large absolute mislocation errors may be expected, although a more uniform azimuthal coverage than used in this study would be expected to improve uncalibrated results. This remains true even when standard errors of locations are small because of systematic errors due to the assumed velocity model. As we have demonstrated, however, it is possible to bootstrap from large mainshocks that are well located from regional (or global) networks in order to calibrate paths and locate smaller events. The addition of S waves factored considerably in the improvements of the locations we obtained. In the case of nuclear explosions, this may pose a problem; however, it should be possible to use other regional phases such as Rayleigh waves given proper calibration. It was possible to estimate the seismic moment tensor of events to a low magnitude of M w 3.7. We used three stations in the moment tensor analysis. The closest station PKD1 was located at a distance 25 km and was also the noisiest of the three stations. For the low-magnitude events, PKD1 was typically removed, and only CMB or SAO (both at a distance of 35 km) were used except where noted on Table 2. The moment tensor solutions presented in this ar-

10 1362 D. Dreger, R. Uhrhammer, M. Pasyanos, J. Franck, and B. Romanowicz ticle compare well with the results of other groups who used surface waves and broadband waveforms recorded by the TERRAscope network. Absolute errors in source-station distance of 35 km and azimuth of 9 were found to not significantly degrade the moment tensor results. Acknowledgments We wish to thank two anonymous reviewers for their constructive comments that improved the clarity of this article. We also wish to thank Alan Ryall of LLNL for helpful discussions. This work is Contribution Number 98-6 of the Berkeley Seismological Laboratory and was partially supported by the Lawrence Livermore National Laboratory through the Department of Energy's Comprehensive Test Ban Treaty Research and Development (CTBT R&D) Program, under the Inter-University (IUT) Agreement No. B References Canas, J., R. D. Miller, and R. A. Uhrhammer (1977). Bulletin of the Seismographic Stations, Berkeley Seismology Laboratory, Vol. 47, no. 1, 55 pp. Dreger, D. S. and D. V. Helmberger (1993). Determination of source parameters at regional distances with single station or sparse network data, J. Geophys. Res. 98, Dreger, D. and B. Romanowicz (1994). Source characteristics of events in the San Francisco Bay region, U.S. GeoL Surv. Open-File Rept , Dreger, D., M. Pasyanos, R. Uhrhammer, B. Romanowicz, and A. Ryall (1996). Evaluation of the performance of broadband networks and short-period arrays in global monitoring, Proc. of the 18th Annual Seismic Research Symposium on Monitoring a CTBT, PL-TR , Dreger, D., M. Pasyanos, R. Uhrhammer, J. Franck, and B. Romanowicz (1997). Evaluation of the Performance of Broadband Stations and Regional Arrays in Global Monitoring--Phase II Final Report, submitted July 1997, 1 pp. Given, D., K. Hutton, and L. Jones (1987). The southern California network bulletin: July-December, 1986, U.S. GeoL Surv. Open-File Rept , 43 pp. Hauksson, E., K. Hutton, H. Kanamori, L. Jones, J. Moil, S. Hough, and G. Roquemore (1995). Preliminary report on the 1995 Ridgecrest earthquake sequence in eastern California, Seism. Res. Lett. 66, Kennett, B. L. N. (1996). Event location and source characterization, in Monitoring a Comprehensive Test Ban Treaty, E. S. Husebye and A. M. Dainty (Editors), Kluwer Academic Publishers, Hingham, MA, Pasyanos, M. E., D. S. Dreger, and B. Romanowicz (1996). Toward realtime estimation of regional moment tensors, Bull. Seism. Soc. Am. 86~ Department of Geology and Geophysics 31 McCone Hall University of California Berkeley, California 9472 Manuscript received 31 July 1997.