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Ž .Physics of the Earth and Planetary Interiors 108 1998 201–218

Lower mantle heterogeneity beneath Eurasia imaged byparametric migration of shear waves

Susan L. Bilek ), Thorne LayInstitute of Tectonics, UniÕersity of California, Santa Cruz, CA, USA

Received 3 November 1997; accepted 2 April 1998

Abstract

Lower mantle structure beneath central Eurasia is examined using a recently developed technique for migratingwparametric representations of shear waves from teleseismic events. The migration method of Lay and Young Lay, T.,

Young, C.J., 1996. Imaging scattering structures in the lower mantle by migration of long period shear waves. J. Geophys.xRes., 101: 20 023–20 040. assumes isotropic scattering from discrete heterogeneities to account for S wave coda arrivals,

and provides resolution at scale lengths of about 500 km. The migration is applied to 15 s period shear wave data from 21western Pacific earthquakes recorded in Europe and the Middle East that exhibit extra arrivals between S and ScS on the

wtransverse components. Migrations are performed using PREM as well as model SGLE Gaherty, J.B., Lay, T., 1992.Y xInvestigation of laterally heterogeneous shear velocity structure in D beneath Eurasia. J. Geophys. Res., 97: 417–435. ,

which has a discontinuity at 2605 km, 286 km above the core–mantle boundary. The migration images for the most coherentŽ .coda arrival Scd resemble those expected for a lower mantle discontinuity model and simulations are performed for models

with discontinuities at various depths. Quantitative correlation of the images for the data and synthetic migrations show theoptimal average depth of the discontinuity to be 2605 km. Migrations of subsets of the data suggest that the discontinuitydepth varies from 2605 km in the northern end of the study area to 2620 km in the southern end. An additional intermediate

Ž .arrival Scd2 is observed in a limited portion of the dataset, and migrations indicate this phase is generated by localizeddiscrete scatterers located at depths of 2750 to 2770 km under north–central Eurasia. These results are generally consistentwith previous forward modeling studies, but the migration approach allows lateral variations to be modeled moresystematically. The heterogeneous structure near the base of the mantle appears to be a manifestation of a complex boundarylayer. q 1998 Elsevier Science B.V. All rights reserved.

Keywords: Coda waves; Lower mantle; Shear waves; Discontinuity

) Corresponding author. Earth Sciences Department, Universityof California, Earth and Marine Sciences Building, Room A232,Santa Cruz, CA 95064, USA. Fax: q1 408 469 3074; e-mail:[email protected]

1. Introduction

The structure of the lower mantle has been char-acterized as very heterogeneous. Seismic tomogra-phy shows global patterns of large scale velocityheterogeneities, with lateral resolution of 2000–4000

Žkm e.g., Su et al., 1994; Li and Romanowicz, 1996;

0031-9201r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved.Ž .PII S0031-9201 98 00105-8

( )S.L. Bilek, T. LayrPhysics of the Earth and Planetary Interiors 108 1998 201–218202

.Masters et al., 1996 . The consistency between mid-mantle regions in two recent global tomographic

Žmodels Grand et al., 1997; van der Hilst et al.,.1997 indicates that the large scale heterogeneities

are gradually becoming well defined by arrival timetomography. There is less consistency between mod-els in the lowermost mantle, possibly due to strong

Ž .chemical and thermal effects Loper and Lay, 1995 .The main challenge in global arrival time tomogra-phy is obtaining large datasets with many crossingraypaths. In order to assess lateral heterogeneities atsmaller wavelength, tomographic models have beendeveloped for smaller regions such as beneath North

Žand South America and the adjacent oceans Grand,.1994 or the approximately 1008=1008 block en-

Žcompassing Southeast Asia and Australia Wyses-.sion et al., 1994 . Until more data become available,

the areas of the world where high resolution tomog-raphy is feasible will be limited.

Because arrival time tomography methods do notyet resolve small scale deep mantle heterogeneities,other techniques are being developed to accomplishthis goal. Most of these alternative techniques usedatasets which sample localized regions and exploita variety of phases found within the waveforms.Core reflected phases, phases diffracted by the core,and phases that enter the core have all been success-fully used to image lower mantle structure and the

Žcore–mantle boundary e.g., Vidale and Benz, 1992;Weber, 1993; Wysession et al., 1994; Garnero and

.Helmberger, 1993, 1996 . Analyses of 10–20 s pe-riod body waves augment the existing tomographicresults, providing higher resolution images of hetero-geneity with scale lengths between 500–2000 kmŽ .see Lay, 1995 for a review .

The method employed in this study images ;500km scale lateral variations in the lower mantle byusing a parametric migration of travel time andamplitude measurements of 10–20 s period shearwaves and their coda arrivals at distances of 708 to828. Several possibilities have been proposed for theorigin of the teleseismic S coda arrivals, such as SKSscattering, receiver reverberations, and source multi-pathing, but previous studies indicate that a lowermantle origin is a more likely explanation for the

Žsystematic arrivals observed between S and ScS Lay.and Young, 1986; Lay, 1986 . Long period SH

waves are used because they have simple waveforms

and the relatively low shear velocities in the lowermantle where their raypaths bottom separate arrivals

Ž .more than for P waves Young and Lay, 1987 . LayŽ .and Young 1996 developed the parametric migra-

tion technique to study the lower mantle shear veloc-ity structure beneath Alaska, but coda migrationtechniques have been used earlier in a variety of

Ž .areas e.g., Lynnes and Lay, 1989; Revenaugh, 1995 .Ž .Scherbaum et al. 1997 exploit back azimuth con-

straints on scattered secondary arrivals for P wavesto enhance lower mantle imaging, but this is onlyviable when array data are available. The most ambi-tious application of a complete diffraction tomogra-phy inversion for lower mantle structure was per-

Ž .formed by Ying and Nataf 1998 , who assumed aŽparticular scattering parameterization cylindrical

.plume structures . In general, we need methods thatcan image arbitrary scatterer geometries given thepossible complexity of lower mantle structure.

Ž .Fig. 1. Schematic drawing of the coda scattering concept. aRaypath for a direct S arrival and the scattering ellipsoid for anobserved coda arrival, Scd. The scattering surface is defined bythe differential time Scd–S and a reference background velocity

Ž .model. b Three source–receiver combinations and scatteringellipsoids for specific coda arrivals at each station. Intersections ofall three ellipsoids, denoted by stars, reveal possible locations ofcommon scatterers. Identifying kinematically viable scatteringlocations is the key concept for the parametric migration.

( )S.L. Bilek, T. LayrPhysics of the Earth and Planetary Interiors 108 1998 201–218 203

The parametric coda migration technique usedhere does not assume an a priori scatterer geometry,and a formal diffraction tomography method is notpursued. Instead, coda arrivals are attributed toisotropic scattering from deep velocity heterogeneity.The SH waveforms can generally be characterized asa sequence of discrete arrivals with measurable rela-tive arrival times and amplitudes. A spike-train pa-rameterization simplifies the signals and eliminatesinstrument and source complexity effects, while pre-serving the general characteristics of the main ar-rivals. For a large number of stations, time shifts aremeasured between the S coda arrivals and a refer-ence phase, either S or ScS. Assuming S to Sscattering, each differential time defines a scattering

Žellipsoid surrounding the direct S wave path Fig..1a . Multiple source–receiver combinations for sev-

eral events provide a large number of ellipsoidswhich intersect in areas where common scattering

Ž .can account for the coda arrivals Fig. 1b . A scatter-ing surface or reflector is indicated by a smooth,continuous surface of intersections, whereas a pointscatterer should yield a very small area with a large

Ž .number of intersections Lay and Young, 1996 .Because only one or two extra arrivals are typically

observed in the S coda, images with complex dis-crete scattering surfaces or convoluted structures areless probable, as every station should see multiplescattered arrivals in that case. This procedure isapplied to study deep mantle structure beneath Eura-sia.

2. Data

The data are transverse component waveformrecords from 21 magnitude 5.6–6.1 events in the

Ž .western Pacific between 1967 and 1984 Table 1 ,recorded by 45 long-period WWSSN stations in

Ž .Europe and the Middle East Fig. 2 . Fig. 3 showsrepresentative waveforms, and many additional data

Ž .are shown in Gaherty and Lay 1992 . Event depthsrange from 115 km to 566 km. All of the data haveclear S and ScS arrivals. Many observations between708 to 828 display an additional arrival, which iscommonly attributed to reflection from a discontinu-ity a few hundred kilometers above the core–mantle

Ž .boundary CMB . At wide angles of incidence, adiscontinuity produces a triplication, with two ar-rivals generated; Sbc, involving energy reflected from

Table 1Event information

Ž .Date Origin time, UT Latitude, deg Longitude, deg Depth km Region

7r4r74 2342:12.9 43.10 142.58 157 Sea of Okhotsk8r13r67 2006:52.3 35.43 135.49 367 Sea of Japan12r1r67 1357:03.4 49.45 154.40 144 Sea of Okhotsk2r28r68 1208:03.4 32.95 137.85 348 Izu-Bonin3r31r69 1925:27.0 38.49 134.52 397 Sea of Japan9r5r70 0752:27.2 52.28 151.49 560 Sea of Okhotsk1r29r71 2158:03.2 51.69 150.97 515 Sea of Okhotsk5r27r72 0406:49.6 54.97 156.33 397 Kamchatka1r31r73 2055:54.2 28.22 139.30 508 Izu-Bonin9r10r73 0743:32.2 42.48 131.05 552 Sea of Japan7r10r76 1137:14.0 47.31 145.75 402 Sea of Okhotsk12r12r7 0108:51.1 28.04 139.67 503 Izu-Bonin6r21r78 1110:38.7 48.27 148.66 380 Sea of Okhotsk9r2r78 0157:34.2 24.81 121.87 115 Taiwan8r16r79 2131:24.9 41.85 130.86 566 Sea of Japan3r31r80 0732:32.4 35.49 135.52 362 Sea of Japan11r27r8 1721:44.3 42.93 131.19 525 Sea of Japan7r3r83 0249:28.2 20.19 122.41 221 Philippine Tr.7r24r83 2307:31.8 53.91 158.36 190 Kamchatka10r8r83 0745:26.3 44.21 130.74 551 Sea of Japan4r23r84 2140:34.2 47.44 146.73 399 Sea of Okhotsk


Fig. 2. Source–receiver geometry for this study shown in Mercator projection. Circles indicate the 21 western Pacific events and trianglesindicate the 45 long period WWSSN stations in Europe and the Middle East.

the discontinuity, and Scd, involving energy re-fracted from below the discontinuity. Separate Scdand Sbc arrivals are not distinguishable in our long-period data, and the extra arrival, which we call Scd,could be a single scattered phase rather than a com-posite of triplication arrivals. An intermittently ob-served additional arrival will be referred to as Scd2.Fig. 3 shows that the Scd and Scd2 arrivals appear tobe simple extra pulses in the waveforms, and we

Ž .treat them as such. Lay and Young 1996 discusspossible complexities if these arrivals are actuallytriplication phases, noting that minor bias in the finalinterpretations may be incurred, but these are intrin-sic given the resolution of the long-period data andare eliminated by the simulation approach used be-low. Because the Scd arrival is most stably observedin the 708–828 distance range, we only considersource–receiver combinations in this range.

Ž .Gaherty and Lay 1992 measured differentialtravel times between the direct S and ScS phases andthe intermediate Scd and Scd2 arrivals, as well as for

Žcorresponding surface reflected arrivals sS, sScS,.sScd , from the digitized WWSSN records. We use

these previously measured times directly, as Lay andŽ .Young 1996 found that more sophisticated methods

for measuring the differential travel times gave onlyminor changes for a comparable dataset beneathAlaska. We did return to the digitized records to

Ž . Ž .measure the relative amplitudes of the s S, s Scd,Ž . Ž .s Scd2 and s ScS phases for incorporation into theparametric migration. In total, 120 Scd, 25 sScd, 42Scd2 and 5 sScd2 arrivals were measured from theserecords. The measurements essentially characterizethe SH waveforms as spiketrains with three or fourarrivals with relative arrival times accurate to about"1 s and relative amplitudes accurate to 20%. Our


Fig. 3. Examples of transverse component data used in this study.Ž .Gaherty and Lay 1992 show many more waveforms. The S, ScS,

and coda arrivals, Scd and Scd2, are identified.

migration processing is not intended to detect thereadily observed arrivals but to explore the signifi-cance of amplitude and travel time fluctuations in thearrivals with respect to possible lower mantle struc-tures.

As the geometry of the dataset requires a lowermantle origin for the frequently observed Scd phase,a grid of possible scattering locations was definedwithin the lower mantle beneath Eurasia, extendingfrom 2200 km to the CMB, with 50–100 km depthspacing and about 18 horizontal spacing. The PREM

Ž1 s SH velocity model Dziewonski and Anderson,.1981 was initially used for migrations, but any

model can be considered, and we also use otherstructures. We do not make any a priori assumptionthat the intermediate arrivals are caused by disconti-nuities, but treat them as scattered phases. A scatter-ing ellipsoid intersection is recorded as a hit if the

Ž . Ž .measured and theoretical Scd 2 –S or ScS–Scd 2times for a particular grid location match within the"1 s tolerance level. Summing the ellipsoid inter-sections, or hits, at each grid point reveals areas with

large numbers of intersections or few intersections.Areas with many intersections indicate possible com-mon scatterers for many of the paths. Map projec-tions at each of the grid depths provide a visualrepresentation of the distribution of intersectionsthroughout the grid volume. The hits are typicallyweighed by the amplitude ratio of the scattered andreference phases to emphasize stronger arrivals. Theresulting migration images intrinsically contain arti-facts caused by incomplete raypath coverage, lack of

Ždestructive interference by noise as occurs in true.migration , and errors in the reference model. Simu-

lations allow us to account for the primary artifactscaused by geometry of the data distribution, and weadjust our reference model to match ScS–S times.

3. Method validation

Prior to using this migration method on real data,we applied it to simulations with specified scatterersto test the resolution for our particular source–re-ceiver geometry. A synthetic dataset with the sameray coverage as the actual dataset was generated,with a single point scatterer located at 608N, 878E,and 2500 km depth. Isotropic scattering was as-

Ž ) .sumed, producing intermediate arrivals S in thesynthetic dataset. The result produced by migrationof the noise-free synthetic data is shown in Fig. 4.The largest symbol, representing 193 intersectionsŽ .the total number of source–receiver combinations ,is located at the true location because the velocitymodel used for the migration is correct. Placing thepoint scatterer at other grid locations produces simi-lar images with the point scatterer being accuratelyimaged in each case. This test indicates the type ofimage expected for a point scatterer, with somestreaking of the image caused by the particular ray-path geometry. This streaking is a function of boththe limited, nonisotropic ray coverage and the "1 stolerance assumed for the timing of the arrivals.

Ž .Similar results were found by Lay and Young 1996beneath Alaska, although there is better resolution inthe present case. Of course, if multiple arrivals arepresent, one can image multiple scatterers by consid-ering all coda arrivals at each station without need-ing to associate them a priori.


Fig. 4. Migration images produced for a simulation involving a single point scatterer. Circles indicate the number and location of ellipsoidŽ .intersections at points in the lower mantle grid. The largest symbol represents a hit count of 193 all possible source–receiver combinations

and the smallest represents a hit count of three. A point scatterer was inserted at 608N, 878E at a depth of 2500 km. This location is wellresolved but there is some smearing along the predominately east–west raypaths.

It is unlikely that most deep mantle scattering iscaused by isolated point scatterers. Another possibil-ity is that the extra arrivals are produced by localizedregions of strong velocity gradient, such as disconti-nuities, plumes, or slabs. As the core–mantle bound-ary is a spherical boundary with a strong velocitygradient, the ScS phase can be viewed as a scatteredarrival for the special case of a specular reflection, asthe smoothness of the boundary gives rise to onlyone arrival at each station rather than multiple ar-rivals from the finite surface. The ScS arrivals in thereal dataset were treated as scattered arrivals andtheir lag times measured with respect to the direct S

phase. These ScS–S differential times then definescattering ellipsoids, and a migration image isformed, with no amplitude weighing. As seen in Fig.5, the migration images for a phase reflected from aspherical boundary are quite different from those fora point scatterer. Instead of one grid point with alarge number of hits, the reflector is manifested in acoherent, or spatially concentrated, grouping of thelargest hit counts at the apex of the scattering ellip-soids, with many shallower artifacts. In this case, themost coherent scattering surface is near a depth of2850 km, shallower than the actual CMB depth of2891 km. This is because PREM overpredicts the


Fig. 5. Results of migration of ScS relative to S using the actual ScS–S differential times and PREM as the reference velocity model. In thiscase, we know that the correct interpretation is reflection from a surface, but there is a complex image formed throughout the volume. Themost coherent pattern is imaged at a depth of 2850 km rather than at the CMB depth of 2891 km. This is because PREM overpredicts theScS–S times on average in this region. The largest symbol represents 26 hit counts, with no amplitude weighing.

observed ScS–S differential times by about 1 s inthis region. Hence PREM is not a perfect referencemodel for migration. There are also blurring effectscaused by strong lateral variations in ScS–S anoma-

Ž .lies in these data Lay et al., 1997 . The artifacts atshallower depths can have large hit counts, but thespatial pattern is complex. Any complex distributionof scatterers should give rise to multiple coda ar-rivals at each station. A simple reflector gives rise toa single extra arrival in the data rather than multiplediscrete arrivals, so it is the uniformity of the imageat a particular depth that favors the interpretation ofthe simple coherent reflector, in this case represent-ing the CMB scatterer. The complex smearing of theimage can actually be used to an advantage as shown

below, as it results from the specific path samplingof the reflector.

This migration of the ScS data indicates thatPREM may bias the Scd migrations. A model whichmatches the ScS–S differential times more closelyshould be superior. Because we found that our initialmigrations indicated the existence of a lower mantlereflector, as previously proposed, we adopt a refer-ence discontinuity model that was specifically devel-

Ž .oped for this region. Gaherty and Lay 1992 derivedmodel SGLE as the best average model to explainthe differential time observations in this area. SGLEis identical to PREM at shallow depths, however,SGLE has a 2.75% shear velocity increase at a depth

Ž . Yof 2605 km Fig. 6 and has higher velocities in D


Fig. 6. Reference shear velocity models PREM and SGLE. Bothmodels are identical above a depth of 2300 km. SGLE has a2.75% shear wave velocity discontinuity at depth 2605 km.

than PREM. This predicts shorter ScS–S differentialtimes than PREM by about 1 s. We now considerresults for this reference model.

4. SGLE migrations

Using SGLE as the reference velocity model forthe observed ScS–S differential time migration givesthe results in Fig. 7. Larger hits are recorded at 2891km, and the image at a depth of 2850 km is not as

Ž .coherent as in the migration using PREM Fig. 5 .Lateral variations appear to be responsible for thestill imperfect focusing of the image at 2891 km,with subregions suggesting shallower or deeper CMBdepths. Simulations with synthetic ScS–S times aresimilar to Fig. 7, but with greater coherence at 2891km. Since SGLE gives a better baseline for theScS–S times than PREM, we perform migrations ofScd using SGLE as the reference model. To assess

the effects of lateral variations in the S times, weconsider both Scd–S and ScS–Scd migrations.

Fig. 8 shows the migration of the Scd arrivalsrelative to the S phase. The hit counts are weighedby each ScdrS amplitude ratio. This scaling givesweight to more robust Scd arrivals and reduces theimportance of those Scd arrivals that were small orquestionable measurements. For each depth section,the circles indicate the amplitude weighed sum ofscattering ellipsoid intersections with the lower man-tle grid. The largest symbol results from 23 intersec-tions at a particular grid point, while the smallestsymbols involve three intersections. The most coher-ent scattering structure is located near 2600–2620km, where the maximum hit count is 17, with a verycoherent patch in northern Eurasia. Areas with highhit counts, but lower amplitudes are found beneathcentral Eurasia with the best coherence at 2620 km.The northernmost area coincides with the regionwhere clear evidence for both P and S wave disconti-

Žnuities has been previously presented e.g., Lay andHelmberger, 1983; Weber and Davis, 1990; Weber,

.1993 .Migration of the observed ScS–Scd differential

times is shown in Fig. 9, with the ScdrScS ampli-tude ratios being used as weights. As before, thecircles indicate location and number of amplitudeweighed hits, with the largest number of hits being26 and the smallest number being three. Similar tothe Scd–S case, the 2580–2620 km depth sectionsshows the most coherent overall structures. TheScS–Scd migrations are thought to be more stablebecause the turning depth of the ScS phase is at theCMB, closer to the depth at which Scd is generatedthan is the case for the S wave bottoming points. Theamplitude weighing again reduces the coherence andstrength of the southern section of the imaged reflec-

Ž .tor at this depth Fig. 10 , similar to the Scd–Smigrations, but the overall coherence near 2600 kmis better for the ScS–Scd case. This can be under-stood as the result of the larger Scd–S fluctuationsthan ScS–Scd fluctuations relative to model SGLE

Ž .in these data Lay et al., 1997 . The overall results ofthese migrations are in excellent agreement with

Ž .those of Gaherty and Lay 1992 , who determined adiscontinuity depth in this area at 2605 km.

Fig. 11 is a Mercator projection of the study areawith the grid point hit counts for the ScS–Scd


Fig. 7. Results of migration of ScS relative to S using the actual ScS–S differential times and SGLE as the reference velocity model. In thiscase, the most coherent surface appears to be deeper than in Fig. 5, although the image at the CMB is not perfectly imaged. The largestsymbol represents a hit count of 20, with no amplitude weighing.

migration at 2600 km depth. Also plotted are the ScSbottoming points for low amplitude and non-observa-tions of the Scd arrival as designated by Gaherty and

Ž .Lay 1992 . Diamonds indicate no Scd arrival ob-served for that particular station–event combination,while squares indicate a very weak or questionableScd arrival. All but one of the non-observationsoccur in areas where ray coverage is sparse and thereare few grid intersections of scattering ellipsoids.Most of the low amplitude Scd observations occur insimilar regions. Note that areas of sparse coveragewith low hit counts may actually have a strongreflector, and the migration image must be evaluatedby considering the hit counts as well as the ampli-tude weighed values. The somewhat weaker features

in the southern areas do correspond to low amplitudeScd arrivals with large hit counts. There are a fewlow amplitude observations and even one non-ob-servation located in the central area where the num-ber of grid intersections and relative amplitudes arehigh. This complexity may arise from interferenceeffects.

One further test of our method assesses whetherthe scattering images are a true product of coherenceof the data or merely a coincidence of the source–re-ceiver geometry. We use the observed differentialtimes but shuffle the latitude and longitude of thestations as well as the depths of the events. Twomigrations were performed for this test, one usingthe ScS–Scd times and the other using Scd–S times.


Fig. 8. Migration results for the observed Scd–S differential times, with ScdrS amplitude ratios used to weigh the data. Symbols indicatethe number of weighed hits at each grid point, with the largest hit count representing 23 ellipsoid intersections. The most coherent structureoccurs near depths of 2600–2620 km.

The results of these migrations reveal that while afew isolated grid points have moderate hit counts,the coherence of the scattering surface near 2600 kmdepth is much weaker when using the incorrectstation locations and event depths. Thus, we inferthat the data migrations do contain coherent struc-ture.

5. Synthetic migrations

The migrations of the Scd phase are clearly morecompatible with a scattering surface than with apoint scatter or small number of point scatterers. Wediscuss above how a scattering surface will produceextensive streaking artifacts in the images which are

results of the geometry. While we can qualitativelyinterpret the existence of a reflector within the depthrange 2580 km to 2620 km, a more quantitativemethod of choosing the optimal depth is desired. Inorder to determine this depth in a more systematicfashion, we perform simulations for modified ver-sions of the SGLE discontinuity model, allowing usto account for predictable streaking effects. Thesemodels, shown in Fig. 12, are identical to SGLE atshallow depths, but vary in both the depth and sizeof velocity increase in the depth range of 2400–2680km. Seven models were created; the shallow discon-tinuity models have 100 km increments in reflectordepth, as the migration images do not support thelikelihood of a simple reflector between depths 2400km–2580 km. Velocity discontinuities with depth


Fig. 9. Migration results for the observed ScS–Scd differential times, with ScdrScS amplitude ratios used to weigh each datum. Symbolsindicate the number of weighed hits at each grid point, with the largest hit count representing 26 ellipsoid intersections. The images at 2600km and 2620 km depths are the most coherent, but the results for depth 2600 km have higher hit counts.

Fig. 10. Migration results for observed ScS–Scd differential times at 2600 km depth showing hit counts on the left and amplitude weighedŽ .ScdrScS hit counts on the right.

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Fig. 11. Mercator projection of the study area showing hit counts from the unweighed ScS–Scd migration at depth 2600 km. Also plotted are the ScS turning points of rays thatŽ . Ž . Ž .have weak Scd arrivals squares and no Scd observations diamonds , as determined by Gaherty and Lay 1992 . Three regions of dense ray sampling are defined as well.


Fig. 12. Discontinuity models used for the synthetic data migra-tions. The models mimic SGLE except for size and depth of theshear wave velocity discontinuity. The numbers for each modelindicate the depth of the discontinuity.

increments of 20 km from 2580 km to 2680 wereconstructed to fine tune the reflector model.

Travel times were calculated for each of thesemodels, using the actual source–receiver combina-tions of the data and assuming that the Scd phase isthe forward triplication branch involving energyturning just below the discontinuity. While the re-

Ž .flected branch Sbc could be used to more preciselyimage the boundary, it is likely that actual observa-

Ž .tions ScS–Scd and Scd–S differential times in-volve a combination of Scd and Sbc arrivals. Syn-thetic migrations were performed for each modelusing the same procedure as in the data migrations.Synthetic amplitudes were not calculated and norelative amplitude weighing was made, thus the syn-thetic migration results are compared to unweighedhit counts for the actual data.

The images for simulations with different discon-tinuity depths vary at every point in the grid volume.Correlation coefficients are calculated between thedata and synthetic migration results for each trialreflector depth. For each model, the individual grid

depths were 2200 km to 2500 km in 100 km incre-ments and 2580 km to 2700 km in 20 km incre-ments. Correlations for each grid depth were com-puted and averaged to find an overall value for eachmodel. To avoid bias toward the deeper models withfiner depth increments in the grid we averaged onlythe correlations for grid layers down to the actualreflector depth. For example, to calculate the averagecorrelation coefficient for the model with a disconti-nuity at 2640 km, the individual coefficients of the2200–2500 km, 2600 km and 2640 km grid depthswere summed and averaged.

Fig. 13 shows the correlation coefficients as afunction of model discontinuity depth for both theScS–Scd and Scd–S cases. In both cases, modelSGLE, with the velocity discontinuity at 2605 kmdepth, has the highest average correlation coeffi-cients. The ScS–Scd case has a correlation of 0.79,and the Scd–S case has a correlation coefficient of0.67 for model SGLE. This indicates that the com-plex images are actually well accounted for by asimple discontinuity model. The Scd–S case doesnot have a sharp peak like the ScS–Scd case; insteadit has a broader peak of high correlation for modelswith discontinuity depths of 2580–2605. As notedabove, this may reflect the large lateral variations indirect S times.

In order to explore small scale lateral variations inthe depth of the discontinuity, the lower mantle gridwas dissected into three discrete areas defined by the

Ž .most coherent patches with high hit counts Fig. 11 .The source–receiver geometries were then examinedand only those that had a portion of their raypathtraveling within the latitude and longitude bound-aries of the respective areas were chosen for migra-tion.

Migrations were performed for the three differentpatches separately, using the real data as well as thesynthetic datasets generated for the previous migra-tions. The results of the migrations were as expected;the high hit count areas were reduced from the fullmigration and generally confined to the area aroundthe assigned box. Since both data and synthetic caseswere considered, correlations were calculated forthese results. Fig. 13 shows the average correlationcoefficients as a function of discontinuity depth foreach area for both the ScS–Scd and Scd–S measure-ments.


Fig. 13. Correlation coefficients between the data and synthetic migrations. Average correlation coefficients as a function of modeldiscontinuity depth for both the ScS–Scd and Scd–S migrations averaged over the entire lower mantle grid.

For the ScS–Scd cases, the northern and centralareas show peaks at 2605 km, although in the centralpatch, it is a broad peak extending to 2620 km. Thesouthern area indicates a sharp peak at 2620 km. TheScd–S cases are similar, with the northern areahaving a sharp peak at 2605 km, a broad peakaround 2620 km in the central area, and a sharperpeak at 2620 km in the south. These results indicateminor topography on the boundary, but, of course,lateral variations in velocity structure could accountfor the apparent topography.

6. Scd2 arrival

We now consider the second intermediate arrival,Scd2, which appears more intermittently than Scd.This phase is observed after the Scd arrival andbefore the ScS arrival for events located in the Japan

Ž .and Kurile arcs. Gaherty and Lay 1992 modifiedmodel SGLE to incorporate two 2.3% velocity dis-continuities, placed at depths of 2591 km and 2731km in order to fit the second intermediate arrivalobserved in the data. This model can match thewaveform features, but does not address the spatialextent of the structure. We use the parametric migra-tion method to explore the spatial extent and depthof the structure causing the additional arrival.

For this set of migrations, we use SGLE as thereference velocity model, as there is always an Scdarrival when Scd2 is observed. There is nothinginherent in SGLE that would produce a second inter-mediate arrival. We treat the Scd2 arrival as a scat-tered arrival and determine the grid intersections ofthe ellipsoids with a lag time that matches the Scd2arrival times.

Similar to the other data migrations, we use boththe ScS–Scd2 and Scd2–S differential times in sepa-rate migrations. Fig. 14 shows the migration resultsfor ScS–Scd2, with the circles again representing theamplitude ratio weighed number of ellipsoid inter-sections at each grid point. These images are similarto unweighed hit count images. The ScS–Scd2 im-age is more coherent and stronger than the Scd2–S

Ž .image not shown , again the expected result giventhe proximity of the CMB to the scatterer image andthe known lateral fluctuation of the S times. Thus weplace greater weight on the results shown in Fig. 14,particularly the coherent localized feature near 2750km. While the higher amplitude observations of Scd2appear to be very localized, there are relativelywidespread observations of the corresponding ar-rival. A second patch, slightly to the south of themain feature, has peak coherency at 2770 km.

The relatively small size of the most coherentScS–Scd2 patch in Fig. 14 is significant. This fea-


Fig. 14. Migration results using ScS as a reference phase for the Scd2 arrival. Scd2 amplitudes are weighed by ScS amplitudes. Symbolsrepresent weighed hit counts at lower mantle grid points, with the largest indicating 12 intersections. This migration results in a strong yetlocalized scatterer at a depth of 2750 km.

ture is much smaller than the reflector surface im-Ž .aged in the Scd migrations Fig. 9 , indicating that

the deeper scatterer is spatially concentrated. A fewscenarios could account for such a scatterer. WeberŽ .1993 suggests that strong lateral gradients in asingle discontinuity depth can give rise to doublearrivals at some stations. It is possible that this areais a depression of the velocity discontinuity bound-ary that is imaged elsewhere at 2605 km. In thiscase, the second arrival could be energy reflectedfrom the sides or bottom of this valley. This isdifficult to reconcile with the relatively strong imageformed for the Scd arrival in the same area in Fig. 9.A more likely possibility for the origin of this arrivalgiven the migration features is a localized scattererbeneath the 2605 km discontinuity, perhaps similarto the discrete heterogeneities proposed by Hadden

Ž .and Buchbinder 1987 . The small size of the scatter-ing image resembles the single scatterer in Fig. 4,although spread over a larger region. These resultsare consistent with the findings of Gaherty and LayŽ .1992 , who felt the heterogeneity must be limitedspatially in order to produce the intermittent natureof the Scd2 arrival, but they did not locate it. Thesecondary Scd2 scatterer near 2770 km appears tohave similar dimensions, but a weaker scatteringcoefficient.

7. Discussion

A large number of studies indicate that the lower-most mantle is quite complex globally and not char-acterized by any single class of velocity structure


ŽLay and Helmberger, 1983; Weber and Kornig,¨1992; Garnero et al., 1993; Nataf and Houard, 1993;Vidale and Benz, 1992, 1993; Kendall and Shearer,1994; Kruger et al., 1995; Kendall and Nangini,¨

.1996; Revenaugh and Jordan, 1991 . Several studieshave concentrated on structure beneath Eurasia, find-

Žing evidence for a deep mantle discontinuity Layand Helmberger, 1983; Weber and Davis, 1990;Houard and Nataf, 1992, 1993; Weber, 1993; Thomas

.and Weber, 1997; Scherbaum et al., 1997 . Themigration results here support the previous work andsuggest that the lower mantle complexity takes theform of mildly varying depth of the shear velocitydiscontinuity throughout the area as well as thepresence of small discrete scatterers within the DY

layer.Array based methods that measure slownesses and

azimuths provide alternate tools for high resolutionexamination of the lower mantle. A number of stud-ies have demonstrated the benefits of using arrays inmany different areas of the world, such as detectingsignals not observed with conventional networksŽ .Kohler et al., 1997 and developing new lower

Ž .mantle imaging methods Kruger et al., 1993, 1995 .¨Ž .Weber and Davis 1990 use array data to find

evidence for a reflector located 290 km above theCMB beneath Eurasia with velocity increases of 3%for P waves and 2% for S waves, while WeberŽ .1993 locates a P wave reflector at 2612 km under

Ž .the Nansen basin and 2605 "10–20 km beneathnorthern Siberia with similar velocity increases as

Ž .Weber and Davis 1990 . While our dataset providesonly sparse coverage in the Nansen basin area, thecompatibility between our results and the previouswork in the Kara Sea and northern Siberia is encour-aging, with the discontinuity depth found using arraydata agreeing with ours to within the error estimates.The possibility of topography on the reflector is

Ž .examined by Thomas and Weber 1997 , who com-pare PdP observations and non–observations withsynthetics for 2-D models to suggest a DY disconti-nuity beneath northern Siberia 400–1200 km in lat-eral extent with 10–100 km of topography. In thisregion, we do not observe significant topographychanges of this magnitude, but the large Fresnelzones of our data could conceivably average over

Ž .rough topography. Scherbaum et al. 1997 apply thedouble beam stacking method to source and receiver

arrays to examine the lower mantle beneath theArctic and northern Siberia, finding a P wave discon-tinuity 293 km above the CMB in northern Siberia.

Most array studies use P wave data as, unfortu-nately, array data for S waves are quite limited. The

Žparametric migration technique Lay and Young,.1996 was developed to use sparse shear wave

datasets to examine lower mantle structure. Thistechnique avoids the restrictive constraints neededfor full inversions, such as assumption of the scat-

Ž .terer geometry as used in Ying and Nataf, 1998 ,and simplifies the three dimensional imaging. Astomography and waveform modeling studies betterconstrain deep mantle structure, it may become pos-sible to formulate useful diffraction tomography forlowermost mantle structure.

It is still unclear what causes the velocity discon-tinuity and how DY relates to dynamics of the lower

Ž .mantle region Lay, 1995; Wysession et al., 1998 .Possibilities for the origin of the discontinuity in-clude a decrease in temperatures caused by sub-ducted slabs ponding at the base of the mantle,mineralogical phase changes at the high CMB P–Tconditions, perovskite reacting with the liquid iron of

Žthe outer core to generate reaction products Knittle.and Jeanloz, 1989, 1991 , or residual material from

core formation. Most likely, it is a combination offactors in the boundary layer above the core thatcreates the velocity heterogeneity. The results of thiscontribute to the evidence for both large and smallscale heterogeneities in the boundary layer, possiblyof thermal or chemical origin. However, resolvingthe precise nature of these structures is a majorchallenge intimately linked to issues such as mantleplume formation, the fate of subducting slabs, andlower mantle mineralogy and thermo-chemical pro-cesses.

8. Conclusions

The migration method used here provides a sys-tematic approach to mapping lateral variations in the

Ž .lower mantle. Lay and Young 1996 first used thetechnique to examine heterogeneities beneath Alaska,favoring a lower mantle reflector. Similar conclu-sions are drawn here regarding a lower mantle dis-continuity beneath Eurasia. This study further sug-


gests the presence of internal structure in the DY

layer below the main shear velocity discontinuity.This study advanced the methodology in Lay and

Ž .Young 1996 by incorporating correlation with sim-ulations to account for smearing artifacts in theimages produced by non-uniform ray coverage, whichenhances the resolution for reflectors with mild depthundulations.

The optimal correlations found are with simula-tions for models with discontinuities at depths near2600"20 km. Separating the well sampled regionsof the lower mantle into three distinct groups sug-gests mild variations in the depth of the discontinu-ity, from 2605 km in the northern and central areas,deepening to 2620 km in the south. The observationof a second intermediate arrival located between theScd and ScS phases in 25% of the data indicates thepresence of small, localized scatterers at depths of2750 and 2770 km beneath Central Eurasia. Whileneither the main discontinuity nor the localized scat-terers within DY are yet understood in terms ofprecise boundary layer processes, continued effortsto resolve the strength and scale lengths of DY struc-tures are paramount to making progress in quantify-ing dynamics in DY.

Acknowledgements

This research was supported by NSF Grant EAR-9418643. Contribution No. 342 of the Institute ofTectonics. We made extensive use of the GMT

Ž .software provided by Wessel and Smith 1991 . Wewish to thank S. Schwartz, R. Hartog, M. Hagerty,and S. Russell for helpful comments on themanuscript, as well as H.-C. Nataf and an anony-mous reviewer for careful reviews.

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