analysis of short-period regional phase path effects associated...

Bulletin of the Seismological Society of America, Vol. 84, No. 1, pp. 119-132, February 1994

Analysis of Short-Period Regional Phase Path Effects

Associated with Topography in Eurasia

by Tianrun Zhang and Thorne Lay

Abstract Propagation of regional seismic phases is highly dependent on path effects, but we have a limited understanding of these effects and no general procedure for accounting for path variation influence on regional waveforms. Thus, there is strong regional variability in the effectiveness of regional wave discriminants used to identify small earthquakes and nuclear explosions. Moti- vated by many observations of correlation between surface geology and regional phase behavior, we empirically explore the relationship between short-period regional and upper mantle distance signal energy and statistics of topography along different travel paths using data for underground nuclear explosions at Semipalatinsk, Kazakhstan. We find strong linear correlations of the logarithmic rms amplitude ratio Sn/Lg (and to a lesser extent, P/Lg) with mean altitude, rms roughness, rms slope, and skewness of topography along the paths to receivers in Eurasia. This indicates that energy partitioning in the regional wave field is controlled by wave-guide structure and attenuation variations that are manifested in surface topography. This suggests that it is feasible in many cases to directly calibrate regional discriminants for path effects in terms of observable surface topography, as a surrogate for overall path properties. The relationships also help to understand the nature of regional phase propagation.

Introduction

Understanding short-period regional seismic wave propagation is of particular interest for nuclear explosion seismology, in which concerns have shifted to proliferation and very low threshold treaty monitoring. To achieve more accurate small explosion identification, it is necessary to monitor small events from close distances. Be- cause of this, monitoring methods based on regional phases have become of primary importance (e.g., Bland- ford, 1982; Bennett and Murphy, 1986; Taylor et al., 1989). The crust comprises a low-velocity strongly scattering layer that forms the primary wave guide in which regional seismic waves propagate. Pn and Sn propagate just below the Moho discontinuity in the mantle lid, and Pg and Lg propagate within the crust. The properties of the lid and wave guide vary along almost every path and have strong influence on the propagation of these regional phases (e.g., Kennett et al., 1990).

Many general observations of regional phase propagation efficiency associated with surface structure along the path have been documented since Press and Ewing (1952) reported the absence of Lg for paths that cross deep ocean basins. Examples include the absence of Lg for paths crossing the Tibetan plateau (Ruzaikin et al., 1977) and the strong Sn attenuation in the northernmost portion of the Iranian and Turkish plateaus and between

the Black and Caspian Seas (Kadinsky-Cade et al., 1981). Although some general rules for propagation efficiency have been deduced, no systematic correction procedure associated with surface tectonic structure has been developed. Spectral variations in Lg and Lg coda waves have been used to map crustal attenuation heterogeneity (e.g., Campillo, 1987; Campillo et al., 1993; Xie and Mitch- ell, 1990, 1991), and such models can be used to correct Lg amplitudes (e.g., Nuttli, 1986). However, blockage and signal conversion effects cannot be properly ac- counted for by such attenuation models, and only general associations of attenuation with surface structure have been derived.

Rather than qualitative characterizations of the "existence" or "non-existence" of one or more particular phases, studies of propagation characteristics along different paths by looking at the relative amplitudes of Sn and Lg (Gregersen, 1984; Kennett, 1985a, 1985b; Baum- gardt, 1990) or P and S (Molnar and Oliver, 1969) provide more quantitative measures of energy partitioning in the regional wave field. Using amplitude ratios min- imizes to a great extent the common effects for the phases being compared, especially the source effects. There- fore, the path effect can be partially isolated in an empirical fashion. In addition, some ratios, such as Pn/S,

119

120 T. Zhang and T. Lay

and Pn/Lg, have emerged as the principal discriminants for the identification of nuclear explosions at regional distances (e.g., Taylor et al., 1989). It is important to establish the path effects on these discriminants if they are to be applied in a proliferation context for which there will usually be no prior explosion experience by which to calibrate the discriminant.

From the observed path effects one can infer characteristics of the structure of the crust and upper mantle, e.g., inferring low Q in a given area to explain observed reduction or blockage of Lg (Singh and Herrmann, 1983; Campillo et al., 1993; Xie and Mitchell, 1990). How- ever, we may need a priori knowledge to correct for path effects in monitoring nuclear proliferation. For example, regional discriminants are known to be highly variable, and no universal behavior is observed (e.g., Lynnes and Baumstark, 1991; Baumgardt and Young, 1990). It is also difficult to correct discriminant ratios for crustal Q models given the complexity of the propagation paths. It would be very valuable to identify empirical relationships between discriminant behavior and observable (i.e., surface) path properties, if any such relationships exist. Because many previously observed propagation anom- alies for regional phases have an association with surface features, topography along the path may be linked to the propagation behavior. Topography represents the shape of the wave guide both at the surface and at depth (to the degree that the crust is isostatically compensated), which is expected to be an important factor for the propagation of guided waves. Topography may also reflect

thermal structure in the crust and upper mantle influ- encing attenuation heterogeneity.

In this study we explore the variability of regional phases for Eurasian nuclear explosions as a function of path properties manifested in topography. Our approach is empirical, given current limitations on our ability to realistically model regional phases, but the observations suggest that an empirical correction procedure may be viable to improve regional discriminant performance.

Data and Processing Methods

The seismic data we use are for 83 explosions distributed throughout the Semipalatinsk Test Site: 55 at Balapan, 22 at Degelen, and 6 in the Murzhik area. The events occurred from 1965 to 1988. Short-period regional (A < 15 °) and upper mantle distance (A = 15 to 30 ° ) recordings from Soviet-run stations were collected and digitized for these events as part of a data exchange associated with the Joint Verification Experiment. The stations providing sufficient numbers of recordings and instrument response information for our analysis are shown in Figure 1. Only vertical component data were available. Altogether 325 waveforms from the 83 explosions distributed over these 7 stations were used in the analysis. Lacking stations at close-in regional distances, we restrict our attention to stations at upper mantle distances for which the first arrival is a P wave diving into the mantle. Nontheless, the signals at these distances show

60"

Figure 1. Map showing the locations of the Semipalatinsk test site, marked with a triangle, and the seismological stations used, marked with circles, indicated by their codes. The lines between the triangle and the circles correspond to great circle paths. The topography is shown with contours, with intervals every 500 m from -1000 to 3000 m above sea level.

Analysis of Short-Period Regional Phase Path Effects Associated with Topography in Eurasia 121

clear regional phases such as high-frequency S. and Lg energy, most of which travels in the crust and mantle lid. This is a unique data set for Eurasian explosions. To equalize the instrument calibrations, we deconvolved the individual instrument responses from all of the waveforms, then convolved the ground motion with the response of the CKM-3 seismometer at station OBN for 1988. Sometimes portions of the records are missing, and we use only the phases that are reliably digitized. Many details about this data set and the signal quality are given by Israelsson (1992).

Regional phases are complex, and simple parametric measures are difficult to make in an objective fashion. Many studies have demonstrated the remarkable stability of gross averaging measures such as rms values for regional phases (e.g., Ringdal et al., 1992; Hansen et al., 1990; Gupta et al., 1992). We follow these studies in the use of rms measures for various portions of the short- period signal. The calculation of the rms values was based on traces filtered between 0.6 and 3.0 Hz. These frequency limits conform to bandpass filters used by Han-

9.0 7.0 GROUP VELOCITY (KM/SEC)

5.5 4.9 4.6 4.3 4.0 3.7 3.4 3 . ~

I I I I STIME SEE) L G

WLY Mb(ISC) 6.0 b a l S W / 1 9 8 3 2 7 9 D i s t a n c e ( k m ) 1746.3

9.0 7.0 GROUP VELOCITY (KM/SEC)

5.5 4.9 4.6 4.3 4.0 3.7 3.4 3.1

l•.dtil•k• . . . . . u , . . . . . . . *J mtia ,,

| I I [ I N

3;~0 460 4;~0 560 5~0 6~0 6;~0 760 7;~0 L S(~O 8~0 960 G g;~O TIME (SEC)

OBN Mb(ISC) 6.0 b a l S W / 1 9 8 3 2 7 9 D i s t a n c e ( k i n ) 2872.4

Figure 2. Representative seismograms for recordings on the Semipalatinsk-OBN path (lower part) and the Semipalatinsk-TLY path (upper part). The time scales are different so that the two signals from different distances can be put on the same group velocity scale (indicated at the top of each plot). The explosion occurred 6 October 1983 in southwest Balapan. The waveforms are the 0.6 to 3.0-Hz ban@ass-filtered traces. The vertical lines mark the windows used to calculate rms amplitudes. The S-N interval corresponds to the S, window of 4.8 to 4.3 km/sec, and L-G indicates the Lg window of 3.7 to 3.1 km/sec. The Sn coda window is between N and L. Notice the relatively weak P and S waves for the TLY recording.

sen et al. (1990) and are compatible with the limitations of our hand-digitized data. The rms amplitudes of each phase are calculated in corresponding group velocity windows. Lg is assigned the window 3.1 to 3.7 km/sec , following Israelsson (1992). The S, window is 4.3 to 4.8 km/sec , as described by Kennett (1989). We define another window between S, and Lg (3.7 to 4.3 km/sec) as the Sn coda, because this part of the record involves energy conversion between the crustal wave (Lg) and mantle wave (S,). All of these velocity windows are illus- trated in Figure 2. We use a time window instead of a velocity window for the P wave. Following Bennett et al. (1992), the rms of this phase is obtained from the time window extending 50 sec after the arrival time. This time window contains a complex set of components, in- cluding P triplications, P coda, P, , and Pg. Many characteristics of these P arrivals are discussed by Garnero et al. (1993). The later part of this window contains an increasing component that is multiply reflected within the crustal wave guide. We consider several P windows with different lengths to study the overall behavior. A noise correction was also applied to every measurement using the rms amplitude of the available recording prior to 5 sec preceding the manually picked P onset (usually 115 sec of data). Noise corrected rms values were calculated as

/lm~k ) 1~ rnlsij(k) = ~ j ( k ) m~l(k, xij(t)2 -- N ~1 xij(t)2'

Table 1 Summary of the Correlation Results of P/Lg with P

Amplitude taken from Four Different Time Windows

Correlation of P/Lg ratio with mean altitude

Window, sec 0 to 5 5 to 15 15 to 50 0 to 50

CC -0.80 -0.78 -0.86 -0.84 0.25 0.19 0.17 0.18

Slope, 1/km -0.76 -0.54 -0.66 -0.63

Correlation of P/Lg ratio with rms roughness

Window, see 0 to 5 5 to 15 15 to 50 0 to 50

CC -0.82 -0.81 -0.88 -0.86 cr 0.23 0.18 0.15 0.17 Slope, 1/kin -1.83 -1.31 -1.56 -1.50

Correlation of P/Lg ratio with rms slope


C C - 0 . 7 7 - 0 . 7 3 - 0 . 8 2 - 0 . 7 9

tr 0 . 2 6 0 . 2 0 0 . 1 9 0 . 2 0

Slope -0.06 -0.04 -0.05 -0.05

Correlation of P/Lg ratio with skewness


C C 0 . 7 3 0 . 6 6 0 . 7 5 0 . 7 3

cr 0 . 2 8 0 . 2 2 0 . 2 2 0 . 2 2

S l o p e 0 . 3 4 0 . 2 3 0 . 2 8 0 . 2 7


where rmslj(k) defines the rms value of phase k at station j from explosion i, and xq(t) represents the associated filtered seismic record (normalized to the reference OBN instrument response) sampled at time t (sampling rate 20 samples/sec). The number of points in the time window of the noise sample is denoted N, with time limits nl and n~. The upper and lower time limits of the windows of the four phases at station j are denoted mjl(k) and mj~(k) respectively, with Mj(k) representing the number of points in the signal for each phase.

Characterization of Paths

Figure 1 shows the locations of the seismological stations and the Semipalatinsk test site along with the Eurasian topography. The topography contours were drawn according to digital elevation data supplied at 5' intervals from a world topography data base (ETOPO5 compiled by the National Geophysical Data Center, Boulder, Colorado). Higher resolution topographic data bases exist, but this resolution is adequate for our ex- ploratory study. Great-circle paths connect the test site

2

0

2

0

?, . . . . . . . . . . . . . . . . . : . . . . . . . . . . . . . . . ~ . . . . . . . . . . . . . . . . . . . . . . . . . . ~ . : : . . . . . . . . . .

0 500 ~ 1000

APA

. _ . . - . . °

500 Ic~ 1000

1500 2000 _ . . , . . . . . . . | . . . . . .

1500 2000 2500 3000

iOe N . . . . . . . . . . . . . . . . . . . . . . . . .

~o ~ ................................... ~ ............................................................... 0 500 ~ 1000 1500 20oo 2500

. . . . = . . . . , . . . . , . . . . = . . . . , . . . . , . . . . . , , , • =

0 . . . . . . . . . . . . . . . .

, - . , . . , . . . . , . . . . . . . . . .

0 500 k m 1000 1500 2000 2500 3000 3500 4000

' . . . . . • • , • ' . . . . . . . • , i • . . , ,

2 BOD f

0 500 Ion 1000 1500 2000

T U P . . . . . . . . . . .

0 500 km 1000 1500 2000 2500 . . . . . = . . . . . . . . , . .

0 500 km 1000 1500

Figure 3. Topography profiles along paths connecting the Semipalatinsk test site and seven stations. The mean altitude along each increases from top to bot- tom. The units of horizontal and vertical axes are both kilometers, but the vertical scale is exaggerated by a factor of 75. The dotted lines are sea levels.


and stations. Only a few of the paths cross predomi- nantly platform areas, whereas most of them traverse presumably more geologically complex structure (Zo- n e n s h a i n et al., 1990) .

Figure 3 shows topography profiles for each path ordered by mean altitude. The left end is the source region and the right end corresponds to the receiver. The profiles were drawn using mapping software GMT ( W e s - sel and Smith, 1991) with a sampling interval of 10 km. The path from Semipalatinsk to NRI is very low and fiat. Actually the first half of the path is in the Central Asian foldbelt and the second half is in the Siberian Platform. The path to APA consists of two parts of almost the same length: the first half within the western part of the Cen- tral Asian belt, the other half in the East European platform. The only noticeable feature is the Ural Mountains, which separate the platform and the foldbelt. This path

crosses the narrow neck of the White Sea, which may not affect the wave propagation very much, due to its shallow depth. The effect of underwater segments on the energy partitioning in regional phases is discussed in Zhang and Lay (1994). The path to OBN is similar to the APA path, consisting of two equal parts of East Eu- ropean plain and Central Asian foldbelt. This path is to the south of the APA path, so that it is close to the mountains to the south. The longest path is to UZH and lies to the south of the OBN path. Two thirds of its length is within the platform, one third in the foldbelt. The three highs along the profile are the Kazakhskiy undulating plain, the Urals and the Carpathians. We have three paths at eastem azimuths. In contrast to the low and gentle topography to the north and west, high mountains stand to the east of Semipalatinsk. Crustal seismic waves have to traverse three high mountains; Altai, West Sayan, and

0.6

0 .5

m

~" 0.4 r~

"r' O.a

0 0.~

m 0.1

(a)

~.5

2.0

1.5

r.D

1.0 Z

~O-~0-5

0.0

(o)

0.2 0 .4 0.6 0.8 1,0 1.2 1.4 , , i , i ' . ~ 18.0

, , / / / / ] 1 6 . 0 c c = 1.00 U I SIC= 0.01 ~" I 14.o SLO= 0.43 J"

, S ° 4oo /25

...,~ o 8,0 ,,/ ,~8.o / Q:~ 4.0

~// 2 .0

I I I I I l

% E A N m ~" ~ (b) ALTITUDE(KM)

0.2 0.4 0.6 0.8 1,0 1.2 1.4

\

~ , . " \ CC= - 0 . 9 6 2.o , , ' ~ " \ SIG= 0 . 2 5 "

" ~ \ .. S L 0 = - 1 . 9 5 1.5

i l.C

r~MO.~

O.C

I I I I I I \

MEAN ALTITUDE(KM)

0.2 0.4 0.6 0.8 1.0 1.2 1.4

/ / / /

CC= 0 .99 SIG= 0 .74 / / / SLO= 12.83 / / ~ / 5 / "

/ . - / / , /

/ / / /

/ / / / / / / ~.+" /

o ~ ~ MEAN ALTITUDE(KM)

0.1 0.2 0.3 0.4 0.5 0.6 z.5 ~ c~ ' ' ' ' '

\

\ CC= - 0 . 9 5 " SIG= 0 27 \ \

" " \ ~ \ _ _ ,, S L 0 = - 4 . 5 0

\ \ \ N \ \

\ \ \ \ \

\ \ \ \

\ \ \ \

RMS ROUGHNESS(KM)

Figure 4 . Correlation plots between the topography statistics on the seven paths studied. (a) and (b) show that the mean altitude has very close correlation with rms roughness and rms slope. (c) and (d) show moderate correlation of skewness with mean altitude and rms roughness. CC stands for correlation coefficient, SIG means the standard deviation, ~r, and SLO is the slope of the calculated correlation line. The dashed lines have shift o f +~r from the correlation line.


East Sayan, to reach station BOD. These mountains are much higher than those along the path to UZH. The path to TUP crosses all three mountains mentioned above at higher altitude as well as crossing the northern part of Lake Baikal. The last and roughest path is to TLY, which crosses the highest and steepest part of the Sayan Moun- tains. The rough topography is indicated by the sharp peaks on the profile.

In the OBN record (lower pan of Fig. 2), Lg is well developed, and there is substantial energy in the S, window. We do not see a clear triplicated S arrival and follow the common convention of describing the short-period arrivals in this window as Sn. Molnar and Oliver (1969) discuss the travel path of this phase and recognize that it is a complex sequence of lid arrivals and crustal reverberations. The amplitude of S, is about half that of L~. The signal to TLY (upper part of Fig. 2) travels along a relatively short path through a series of mountain ranges.

The topographic ruggedness appears to be associated with very weak energy of P and S waves but clear Lg. The signals at TUP are similar to those at TLY. These waveform patterns are rather persistent for a specific path for explosions detonated in different pans of the Semipa- latinsk test site with different magnitudes and burial depths. One reason for the consistency may be that the paths from Semipalatinsk to the seven stations are ex- tremely different, so that the path effect overwhelms any near-source effects.

Topography Statistics

To quantify the path properties, we calculate four statistical parameters for each path. They are mean altitude, root-mean-square roughness, root-mean-square slope, and skewness (Bennett and Mattsson, 1989). The

0.8

0.6

0.4

~ .~0 .2 '

Q

0.0

0 12-,

0

- 0 . 4 ,

- 0 . 6

0 . I 0,3 0 .5 0.7 0.9 I . i 1.3 i i i i i i

-" CC= -0.84

" 1 . . . " "~ . . -. S L O = - 0 . 6 3

}

-- Z ~ 117 I I n l I I

O ~ m E-, E-, ( a ) MEAN ALTITUDE(KM)

3.0 5.0 7.0 9.0 I I . 0 13.0 15.0 i ? . 0 0 .8 - i i i i i i i i

0.6 " " . . S I G = 0 . 2 0

0.4 J - ~ . . " ' ~ SLO= -0.05

0 0.0 "

0

" ~ - 0 . 2 . .

- 0 . 4

- 0 . 6

(e) ~ ~ ~ o ~ = ,~ ~ t--. (d) RMS SLOPE(M/KM)

0.8

0.6

0.4

0.2

0.0

- 0 . 2

- 0 . 4

-0 . f i

(b)

0.8

0.6

0.4

0.2

0.0

- 0 . 2

- 0 . 4

- 0 . 6

0, I 0.2 0.3 0 .4 0.5 0.6 ~ . i i i t i i

- T ~ .. ~ CC= - 0 . 6 6 ~ - , - ' . . $ sIG= o.17

sLo--

I - / I I I I m N o~ m ~ RMS ROUGHNESS(~)

0.0 0.5 1.0 1.5 2.0 2.5

i" /" /

I f I

SKEWNESS

Figure 5. The relationship of P/Lg with topography, rms P-wave amplitudes are taken from 0-to-50-sec window. The results using other P windows from 0-to- 5-, 5-to-15-, and 15-to-50-sec are listed in Table 1. Each circle indicates the average of all the P/Lg values obtained for a specific path. The error bar indicates the standard deviation. The logarithmic amplitude ratios are compared to (a) mean altitude, (b) rms roughness, (c) rms slope, and (d) skewness.

Analysis o f Short-Period Regional Phase Path Effects Associated with Topography in Eurasia 125

mean altitude is the arithmetic average of the altitude along the path. It generally reflects the thickness of the crustal wave guide. After subtracting the mean value from the elevation data, we can calculate the rms roughness. It is defined as the square root of the mean square value of the deviations from the mean elevation, zi, along the path

z,

Another parameter to describe the roughness is the rms slope. For the zero-mean elevation data, the rms slope can be defined as the square root of the mean of the squares of the slopes. Each slope mi is the difference between the heights of the adjacent points divided by the data sampling interval. The formula is

m = m 2

i = 1

where

Zi+ 1 - - Zi m i = - -

~o

and r 0 is the (constant) offset between data points. We multiply the slope values by 1000 to conveniently scale the dimensionless units to meters per kilometer.

The final topography parameter is skewness. If the surface is generally flat with only a few bumps on it, the mean surface level will be calculated to be slightly above the general surface. Points below the mean value will be more numerous than those with positive value. Therefore, the surface topography distribution would be distorted from Gaussian. Similarly, a surface containing

0 . 1 0 . 3 0 . 5 0 . 7 0 . 9 1 .1 1 . 3 i i i " i i i

CC= - 0 . 9 8 o.o ~ SIG= 0.05

.~-r]-,. SLO= -0.57

- 0 . 2 "" ~

"~o.~ " g ~ -.

-0.8 \ ~

~ ~ , ~, , ~,

L ) /dEAN ALTITUDE(K/I)

3.0 5.0 7 . 0 9 . 0 1 1 . 0 1 3 . 0 1 5 . 0 1 7 . 0 i i i i I i i i

CC= -0.97 o.o r ,~ SIG= 0.07

,...T- 0 . 4 \ \ \

"~ tuO. 6 \ \ 0 \ \

- 0 . 8 \ "-

RMS SLOPE(M/KM)

0 . 1 0 . 2 0 . 3 0 . 4 0 . 5 0 . 6 I i i i I I

CC= - 0 . 9 8 0.0 y~ SIC= 0.05

- 0 . 2

- 0 . 4

- 0 . 6

- 0 . 8

(b) ~ ~ o= m ~- ~- RMS ROUGHNESS(KM)

0 . 0 0 . 5 1 . 0 1 . 5 2 . 0 2 . 5

(d)

I i i i i /

CC= 0.96 0.o SIG= 0.07 ~ / ~

/ /

/ / / /

] / / 0 . 6

0 . 8

I I ~:11

SKEWNESS

Figure 6. The relationship of Sn/Lg with topography; the format is the same as in Figure 5. This figure shows strong correlation between S,/Lg ratios and statistics of topography.


localized troughs will have a mean surface level below the general surface level. The skewness is defined as

Skewness 83 N

where 8 is rms roughness. Skewness provides an indi- cation of how flat a profile is. Among all the paths analyzed, the flattest profile, to APA, has the highest skewness.

In the region of Eurasia analyzed, there are correlations among these topography statistics, as shown in Figure 4. The rms roughness and rms slope have high linear correlation with the mean altitude. This means that the higher the plateau, the more rugged its surface. Al- though the skewness is negatively correlated with the mean altitude or rms roughness, the correlations are weaker. These correlations make it difficult to distinguish the influence of mean altitude and rms roughness on the wave propagation. Given similar explosion data from flat but

high-altitude uplands, such as Africa or Iran, we may be able to make a distinction between their roles.

Results

We explore the behavior of relative amplitude ratios P/L~, S,/L~, S,, coda/L~, and P/S,, where each measure is the corresponding noise-corrected rms value. In Fig- ure 5 each circle indicates the logarithm of the average P/Lg for a path, using the rms values for the 0-to-50- sec P-wave window. P/Lg shows negative linear relationships with mean altitude, rms roughness, and rms slope. The positive correlation with skewness is as strong as with other parameters. The existence of these correlations is strongly dependent on the values at station TLY. The path of the first arrival of the P wave at these distances, >1500 kin, dives into the transition zone. The direct wave is not expected to be strongly influenced by the shape of the crustal wave guide. However, our window includes significant coda. The coda waves may have

0.1 0.3 0 .5 0.7 0.9 1.1 1.3 0.2 , i , , , ,

CC= -0 .95 SIG= 0.07

o.o SL0 = - 0.51

0

D~--0.4 ~'~. ~'~-

O ,..1

-0 .8

-0.8 ~ J l ~ ~

MEAN ALTITUDE(KM)

3.0 5.0 7.0 9.0 11.0 13.0 15.0 17.0 o.z[- . . . . . . . . - I

L cc=-0.94 / ~'..T SIG= 0.08 |

_, 0.0 ~,~ ~, SLO: -0.04 | pk~-"k. - . /

o " " x ~Wxx r..) ... ~ -.

~- -0 .4 " ' . ~ ' . .

, , , ,

(o) ~ = ~ RMS SLOPE(M/KM)

0 . 1 0 . 2 0 . 3 0 . 4 0 . 5 0 . 8 0 . 2 I - ' n , v ,

L CC= -0 .94 }" T SIG= 0.08

0"° ~t]~" ~ SLO= -1 .17

-0.4

.0., f (b] ~ ~ o~ • ~ " " RMS ROUGHNESS(KM)

0.0 0.5 1.0 1.5 2.0 2.5 0 . 2 1 i ; i i , ,

CC= 0.90 J / SIG= 0.I0 / / TI

°'° SL0= 0'24 ~ / / ~ /

-O.r, / / ¢ i

...f /i

• 0 . 4 / " / ¢ ¢

.I / j-'~

• O , e " ' . ~ z

/ /

(d) ~ ~ o ~ ~o SKEWNESS

Figure 7. The relationship of S,, coda/Lg with topography. The results are similar to those in Figure 6, but the correlations are a little weaker.


increasing crustal reverberations and conversions of S, ~ P, Lg ~ P and thus may exhibit some relationship with structure of the crustal wave guide. To assess this, we calculate rms amplitudes of the P wave using 0-to- 5-, 5-to-15-, 15-to-50- and 0-to-50-sec windows. The correlations are obtained in the same way as shown in Figure 5. The results are summarized in Table 1. Of the four cases, the P wave coda window 15-to-50-sec results in the highest correlation coefficients and the least standard deviations. This suggests that the sensitivity of the coda to the path structure increases with time, but much of the effect must involve Lg. There is no simple distance trend, so the apparent correlations are not simply a geometric spreading effect. For the 0-to-50-sec window the correlations are almost as strong as for the late coda, because the window includes a considerable portion of P -coda . It is not clear whether these trends will apply at close-in regional distances where there is less diving energy, but the behavior of the P - c o d a window suggests that correlations in P,/Lg may exist, if energy partitioning is caused by scattering on each path.

The behavior of S,/Lg with path topography shows similar patterns to those observed for P/L~, but the linear correlations are now very strong, with correlation coefficients close to one. The results are shown in Figure 6. These are the most valuable results of this study and clearly the trends are not produced by a single station. The slopes inferred from these correlations can be used to develop path corrections as discussed in Zhang and Lay (1994). Although Lg does vary on each path, it appears that increased sensitivity of the rms S, window to path properties causes the stronger correlations than for the P/Lg data. This may reflect the absence of strong triplication arrivals in the S, window, in contrast to the P window, as well as more pronounced energy partitioning between S, and L~.

Figure 7 shows the results for S, coda/L~ behavior with topography, which are very similar to the results of S,/Lg. It seems that S, coda has very similar path effects as S,, although the correlations with topography are a little weaker. The S, coda interval may contain Lg ~ S, energy scattered from some irregular part of the wave

0.1 0.3 0.5 0.7 0.9 1.1 1.3 1.4 , , , , , ,

CC= -0 .20 1.2 SIG= 0.17

SLO= -0.08

0.8

o' ~ 0.6

0.4 ~

0.2 ' , ~ ' ,

ALTITUDE(KM)

1.4

1.2 I

1,0

~ 0.8;

o, i ~ 0.8

0.4

3.0 5.0 7.0 9.0 11.0 13,0 15.0 17.0 I I I I I I I I

CO= -0.14 SIG= 0.17 SL0= 0.00

0.I 0.2 0.3 0.4 0.5 0.6 1.4 , , , , , ,

CC= -0.24 1.z SIG= 0.17

SLO= - 0 . 2 2

1.0

RMS ROUGHNESS(KM)

T 1 T

0.8

0.6

0.4

0.2

(b) I I

0.0 0.5 1.0 1.5 2.0 2.5

CC= 0.03 T r]

SIG= 0.17

SLO= 0.01

. . . . .

0.2 I I I I I I I I - - . I - - ~ L ~ T T ~

(°) RMs ST OPZ(M/KM) SZZ NESS

Figure 8. pattern.

The relationship of P/S, with topography. There is no significant


guide. The three ratios, P/tg, S./Lg, S. coda/Lg, have similar correlation patterns with path topography statistics. Because the S./Lg relationship is the strongest, we will concentrate on it in later discussion.

In contrast to the three aforementioned relationships, the P/S. ratio (Fig. 8) shows no significant relation with path properties. This ratio appears not to be affected by surface topography. To understand our observations, we must establish which phase is primarily responsible for the path effect on the S./Lg ratio, Lg or S.. If we assume the amplitudes of Lg are less sensitive to the path effect, then both S. and P vary with topography in similar ways but with slightly different extents as shown in Figures 5 and 6. Thus, their trends cancel out in the P/S. ratio and show no pattern with topography. If Lg is completely responsible for the S./Lg behavior, P and S. are then indifferent to the path, and so is their ratio. In that case, Lg station corrections or Q corrections can account for all of the behavior.

Several studies using the data set from Semipala- tinsk have concluded that r m s Lg amplitudes are very stable as long as station factors are allowed for (Hansen et al., 1990; Israelsson, 1992), but we must also consider the variation of each phase with distance. We display the mean amplitudes of P, S,, Sn coda, and Lg a s

functions of distance in Figure 9. All these amplitudes are first normalized to equivalent source strength with an Intemational Seismological Centre (ISC) mb = 5, then averaged for each path. If localized path effects associated with topography are strong, they will blur the smooth distance decay due to attenuation and geometric spreading; complexity due to upper mantle triplications may affect the P-wave signals as well. In Figure 9, Lg shows the most systematic relationship with distance, with the highest correlation coefficient and slope, although there is a great deal of scatter. The general trend is very similar to that found by Israelsson (1992). This suggests that any Lg topographic effect is superimposed on a

2.2

2.0

1.8

1 .6

1 . 4

1.2 Z 1.o

~ 0 . 8 0

0 . 6

0.4

(a) 0.2

2 0 0 0 2 5 0 0 3 0 0 0 3 5 0 0 4 0 0 0 1 .4 [ I I I [

CC= -0.15 ~_IG= 0.22 1.2

LO= -0.5E-04 -- -- . . . . -- -- ~ -- 1.0 ~ ~,o.I

z r ~ 0 . 6

g~ 0.4

2000 J 1,6

1.4

.ofl- m~l] °'8 t A-

o5I -,- i:f

(o)

0.2

DISTANC~,(KM) 2 5 0 0 3000 3 5 0 0 4000

(b)

I I i i

CC= -0.03 SIG= 0.19 SL0= -0.7E-05

"~ 1.0

~.~ 0.0

~ 0.6

I I 0.4

2 0 0 0 2 5 0 0 3 0 0 0 3 5 0 0 4 0 0 0 i i i J i

CC= -0.21 ~SlG= o.17

E-,O mSTANCE(KM)

2 0 0 0 2 5 0 0 3 0 0 0 3 5 0 0 4 0 0 0 i i i i i

CC= -0.64 1.5 [-T SIG= 0.14

~. SLO= -0.2E-03 1"4 ~i~ ~ ~

1.2 ~

DISTANCE(KM)

I I:~ I !~.*Z I I

(d) ~ ~ o == ~O ~ DISTANCE(KM)

Figure 9. Variation of the amplitudes of different phases with distance. The horizontal axis is distance with all the station names at the appropriate position. The vertical axis is the logarithm of rms amplitude for phases P, S,, S, coda, and Lg. All the events are.equalized to mb = 5.0. The conversion involves di- viding the logarithm of amplitude by the ISC magnitude, then multiplying by 5.


stronger distance trend. The variation of P and S, amplitudes with distance is not simple. A specific case involves the observations at TUP and OBN. The path to TUP is the second most rugged one (see Fig. 3) with a length of 2800 km. The path to OBN is relatively flat and spans 2877 km. Although the distances are similar, the mean elevation of the two paths are quite different. It appears that the rugged path makes the amplitudes of all four phases at TUP lower than those at OBN, perhaps due to high attenuation. However the Lg difference between TUP and OBN is the least among the phases.

The correlations between rms amplitudes and rms roughness give some additional information. In Figure 10, P, S,, and S, coda phases decrease with increasing roughness, although only slightly, and there is much scatter. Lg shows a positive correlation with roughness, but this correlation is just caused by the shortest path to TLY. Because the different phases have different geo- metrical spreading and attenuation factors, and we do

not know them accurately, we did not remove the distance influence in Figure 10. The strong trends of Sn/L 8 in Figure 6 appear even more surprising, given the complex behavior in Figures 9 and 10.

From the comparison of the above two figures, we cannot attribute all of the S,/Lg ratio sensitivity to either S, or Lg separately. We do have independent knowledge from the studies of Israelsson (1992). The Lg path terms he calculated also have strong negative linear relationship with distance, largely explainable by geometric spreading and attenuation. The scatter around the distance trend does not have any correlation with topographic measurement. He inferred that the rms amplitudes of Lg waves appear to be fairly stable for a variety of propagation paths across large parts of Eurasia. This suggests that L 8 is not completely controlled by roughness, and thus S, must have sensitivity to roughness brought out in the S,/Lg ratio. One interpretation is that the distance effect dominates or trades off with any path

;~.2.

2.0

1.8

1.6

1.4

~-" 1.8

Lo

0.8 0

0,6

0. I 0.2 0,3 0.4 0.5 0.6 1.4 0.1 0.2 0.3 0.4 0.5 0.6 i i i i p i i i i J i i'-"

CC= - 0 . 3 0 CC= - 0 . 3 8 T SIG= 0.21 1.2 SIG= 0.16

T SLO= ~ 0 ~ 3 5

a.o "

~ 0 . 6

~ 0 . 4

0 .4- 0 . 2

0 . 2

(a ) ~ ~ z ~ ' ~ ' ~,' ' ' .4 z m ' U ' '~' ' '

RMS ROUCHNESS(KM) RMS ROUGHNESS(KM) 0. i 0.2 0.3 0 . 4 0.5 0.6 0.1 0.2 0.3 0.4 0.5 0.8

I I I I r I l I w I I I f

1.s CC= - 0 . 2 9 t CC= 0 .63 SIG= 0 . 1 8 1.6~- SIG= 0.15 T

1.4 SL0=-0 .29 [" SL0= 0.6~I~(~ ~ , , - - , 1 . 4 / ~

"~0 1 . 0 CD

0 0 8 ...........

0 . 4 0 . 6

0 . 2 ~ z a : l ' ~ ' m I ' I 0.4 I I I ,

o= = , - ( d ) =" = o~ ~ (c) RMS ROUGHNESS(KM) RMS ROUGHNESS(KM)

Figure 10. Variation of the amplitudes of different phases with rms roughness. The horizontal axis is rms roughness with all the station names at the appropriate position. The vertical axis is the logarithm of rms amplitude for phases P, S,, S, coda, and Lg. All the events are equalized to mb = 5.0.


roughness effect for Lg propagation, whereas the roughness effect is stronger than the distance effect for Sn phase. S, proves to have greater variability than Lg for data from other Soviet test sites (Zhang and Lay, 1994). However, the simplest way to interpret these strong correlations is that partitioning of energy throughout the wave field is controlled by path effects that, for these paths, are manifested in surface variations.

The sample interval of our topography profile is 10 kin, i.e., the wavelength of the roughness we can study is no shorter than 20 kin. To determine which scale of surface roughness is the most influential for regional wave propagation, we calculated the power spectra of the roughness along each profile, as shown in Figure 11. These points are smoothed power spectra, obtained by averaging over a bin centered at the wavenumber of each point and ranging between the left and right adjacent points. The shapes of these spectra for all profiles are similar, especially at longer wavelengths. This provides a basis for

using simple statistics to quantify the path structure. If a path crosses a sea or consists of a combination of low plains and very high mountains, it may not be suitable for the statistical description used in this study.

We use these spectra to correlate with the observed S,/Lg ratios. The relationships are similar to those for the statistical parameters (Fig. 6). However, the correlation strengthens as the wavelength decreases. The shortest wavelengths of 26.7 and 22.9 km give the highest correlation coefficients and slopes and the smallest standard deviations. We infer that short wavelength roughness has more effect on the S,/Lg propagation. To determine the propagation influence of roughness for wavelengths <20 km is beyond the resolution of our preliminary topography data set. The correlations of P/L~ with topography spectra are similar to those of S,/Lg but less strong. Figure 12 summarizes the correlation results of both sets of ratios. The general trends for the two ratios are very close.

(.D

U}

o 0

(D

500 ;~00

I i i0 ~ _

10 ° _

~ff~ _

I 0 ,000 0 .005

1{~ 80 WAVELENGTH(KM)

I I I I I

o APA i ",. + BOD

'\ "~, • NI~

' ". o OBN

,, e.,, × TLY ,,% '~

• . "x.. ",, • TUP

"~',~'.""\.,.. .... "':"~IL,..~:~....~" • UZH

",'¢,,, "--.. "~'~'-:z'--,. "~'¢,~, " ' - I . "- .~<_'.,=.,.<... . . . . . . . ~ . . . . . . . . . . . . . X \~\ ~'.. -.... ",:,~,, "-.. ~ .....

"., "~..".. ....... "o

.., -.'-~.~. "-.... '\, ~I~ _'-'.~_...._~. ~- "~'~I- .....

0 - - ~ , . . . . . . . . . , e . - - ~ , ~ . . . . . 0

I I I I i I I I 0 .010 0 .015 0 ,020 0 .025 0 .030 0 .035 0 .040 0 .045

WAVENUMBER( 1/KM)

Figu re 11. The Fourier spectrum of roughness for each path. The mean altitude has been subtracted before Fourier transforming. The points are obtained from averaging over the bin centered at each point, ranging from the left to right adjacent points.

20

0.0511


Discussion and Conclusions

Regional phases are sensitive to source characteristics but are also strongly influenced by path effects. We have found that rms amplitude ratios at upper mantle distance have surprisingly strong correlations with topography statistics along the corresponding paths. Because P,,/Ls and P,,/S. ratios are used as regional discriminants, the relationships reported in this study provide a basis for path correction procedures that may reduce scatter in measurements used for discrimination. Although the present data set only includes explosion signals, all discriminants suffer when scatter is large, so procedures analogous to ours may be useful in improving the performance of earthquake and explosion discriminants.

The most interesting result of this study is the strong correlation between various measures of the path topography and the logarithmic S./L~ rms amplitude ratio. This observation relates inefficient S,, propagation to strong roughness or high altitude of the path. Because S. waves

0.28

0.24

0.20

0.16

0.12

0.08

0.04

Slo =_

20 30 40 50 60 70 80 90 100 110 120 130 140 t50 160

1.0

~ ~J g

Standard Deviation

20 30 40 50 60 70 80 90 100 110 120 130 140 150 160

0.9

0.8

0.7

0,6

0,5-

0.4

0.6-

0.5-

0.4.

0 .3 ,

02 .

0.1.

0.0

~ ~ . ~ ~ Correlation Coefficient

30 40 50 60 70 80 90 100 110 120 130 140 150

Wavelength (km)

Figure 12. Summary of the correlation results of P/Lg and S,/Lg with topography spectra. The horizontal coordinates are wavelengths of topography spectra. Circles, P/Lg; diamonds, S,/Lg. Short wavelengths correspond to better correlation, i.e., higher correlation coefficient, lower standard deviation, and greater slope. Two groups of curves have similar variation trends.

160

primarily travel through the upper mantle and Lg waves are confined in the crustal wave guide, variable L~ Q and S, Q may affect their propagation. There have been several studies of laterally varying Q values using L~ and coda waves in the study area (e.g., Nuttli, 1986; Xie and Mitchell, 1991; Jih, 1992). Kadinsky-Cade et al. (1981) infer that a zone(s) of high attenuation (possibly partially molten) exists in the upper mantle beneath regions of inefficient S,, propagation. The upper mantle under the mountainous areas (Sayan and Altai mountains) may have low intrinsic Q values, because of tectonic activity that has created the topography. However, we have seen that the strongest trends are for the S,,/Lg ratios, not just the S,, phases.

The reduction of S. and relative stability of Lg in topographically rough regions may be connected to another phenomenon. L~ modes involve a wide range of incidence angles greater than the critical angle. When reflected from a rough surface, part of the energy may leak out of the wave guide if the angle becomes smaller than the critical angle, but most of the modes will just convert among themselves. This process is mode coupling. Because the heterogeneity is almost random, the distribution of the modes tend to concentrate around a central mode. This behavior decreases the dispersion among the modes, making the guided wave train nar- rower (Snyder and Love, 1983). Mode coupling can have the effect of shortening the primary L 8 wave train and reducing the amplitude of later S,, (Clouser and Langs- ton, 1993). However, scattering and wave conversions can broaden overall Lg and S,, waveforms (Kennett, 1989), so the effects on S,/Lg ratios are not easily predicted.

To deepen our understanding of these empirical observations, we plan further studies of both theoretical and empirical aspects. This preliminary work has used data from explosions only, and for discriminant purposes, it is clearly necessary to also consider earthquake signals. Our paths are also particularly simple, and for paths with oceanic legs or on continental margins, other measures of surface properties will be needed (Zhang and Lay, 1994). In addition, quantitative modeling is warranted for attaining a complete understanding of how surface topography reflects wave-guide characteristics affecting regional phases. Finally, the generality of our results needs to be explored, for there are clearly well-studied paths that would deviate from the behavior of this dataset. Nonetheless, the potential for developing useful path corrections based on path surface properties for a large number of cases appears high.

Acknowledgments

The waveform data set used here was made available by Dr. Alan Ryall and Dr. Susan Schwartz. We thank Dr. Hans Israelsson for


extensive information about the instrument responses. We thank Dr. Xiaobi Xie for suggestions on graphics and comments on the manuscript. The anonymous reviewer provided helpful comments and a thorough review. This research was supported by the W.M. Keck Foundation and the Defense Advanced Research Projects Agency and was monitored by the Phillips Laboratory under Contract F29601-91- K-DB21. This is contribution number 195 of the Institute of Tectonics and the C.F. Richter Seismological Laboratory.

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Institute of Tectonics University of California Santa Cruz, California 95064

Manuscript received 18 May 1993.

analysis of short-period regional phase path effects associated...

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