439

Bulletin of the Seismological Society of America, Vol. 94, No. 2, pp. 439–452, April 2004

Changes in the Coda Decay Rate and Shear-Wave Splitting Parameters

Associated with Seismic Swarms at Mt. Vesuvius, Italy

by Edoardo Del Pezzo, Francesca Bianco, Simona Petrosino, and Gilberto Saccorotti

Abstract We study the time changes of (1) the b-value of the Gutenberg–Richterdistribution, (2) the inverse coda Q( ), and (3) the shear-wave splitting parameters�1QC

(i.e., the time delay Td between qS1 and qS2 phases and the polarization direction ofthe qS1 wave) for small-magnitude volcano-tectonic earthquakes of Mt. Vesuvius,Italy. We used for (1) the seismic catalog of Mt. Vesuvius seismicity starting fromJanuary 1994, for (2) a selected (on the basis of the best signal-to-noise ratio) set ofdata with hypocentral distances smaller than 4 km recorded at station BKE (analog-ical) with a 1-Hz vertical seismometer during the period from January 1994 until thepresent, and for (3) a set of data recorded at two digital, high dynamical range,portable short-period seismic stations. These stations (BKE and BKN) were in opera-tion in two periods, BKE (digital) from January 1999 to the middle of 2000 and BKNfrom January 1999 to the end of 1999; the hypocentral distances were not greaterthan 4 km. We found evidence of time changes of measured at high frequency�1QC

(6, 12, and 18 Hz). The changes seem to be correlated with the occurrence of twoswarms with largest magnitudes of 3.4 and 3.6, respectively in April 1996 and Oc-tober 1999. The earthquake with the largest magnitude in the second swarm appearsto be the largest event since the latest eruption in 1944. An increase in starts�1QC

after the occurrence of both swarms, reaching a maximum after more than 1 yr forthe first swarm and after 6 months for the second swarm. These two changes werenot accompained by any corresponding variation of the b-value, which shows analmost constant (inside the statistical uncertainty) pattern. The last swarm (M 3.6)was preceeded by an increase of Td at both stations, indicating a possible change ofthe stress state before the M 3.6 earthquake. The qS1 polarization direction also showsa variation in correspondence to the same earthquake, which was interpreted as gen-erated by an increase of the differential stress acting at a regional scale in the north–south direction shortly before the M 3.6 event. The strain change associated to thisearthquake was estimated to be of the order of 10�9 using data from the straingramrecorded at a Sacks–Evertson dilatometer located about 3 km from the epicenter.The given information allows us to estimate the sensitivity of the the measuredparameters to the strain change induced by the M 3.6 earthquake. The sensitivity isof the order of 1.4 � 109 ( /strain units) for and is of the order of 2 � 1010�1 �1Q QC C

(msec/strain units) for Td.

Introduction

The temporal changes in stress indicators are widelyrecognized as particularly useful to the problem of predictingvolcanic eruptions and major earthquakes; for this reason,their study is important in hazard analysis. In actual seis-mological practice, two observational parameters are oftenused to monitor these changes: the inverse of coda Q ( )�1QC

and the shear-wave splitting parameters. The first parameter( ) is often studied together with the time pattern of the�1QC

b-value of the Gutenberg–Richter relation.

The term “coda” indicates the part of a high-frequencyseismogram following the P and S waves. The S coda wavesof local earthquakes have attracted considerable attentionfrom both observational and theoretical seismologists sincethe pioneering works of Aki (1969) and Aki and Chouet(1975) and are almost universally interpreted as generatedby random scattering processes in the crust and lithosphere.A complete review of the seismic scattering processes, datahandling, and interpretation was reported in Sato and Fehler

440 E. Del Pezzo, F. Bianco, S. Petrosino, and G. Saccorotti

(1998). Coda waves can be used to measure the seismic at-tenuation in the lithosphere.

One of the most intriguing features of the coda wavesis that the coda envelope shows a stable and similar timedecay parameter for data from the same seismogenetic area;thus the coda decay parameter (or ) is often used to�1QC

parametrize the tectonic characteristics. For a given seis-mogenetic area, has been observed to change with time�1QC

before the occurrence of strong earthquakes and volcaniceruptions. This observation is intrinsically important, in thesense that can be considered a seismic precursor. How-�1QC

ever, this is controversial. The difficulty of accepting �1QC

changes as precursors of major earthquakes (in a homoge-neous seismogenetic area) is that there are a number of neg-ative observations. Antolik et al. (1996) used similar mi-croearthquakes recorded at a borehole station in Parkfield,California, to perform a differential analysis of . The�1QC

technique utilizes earthquake doublets that occurred at anidentical location but at different times, which allows theelimination of the errors due to different path and sourceeffects. In this way, Antolik et al. (1996) estimated DQ�1

(the variation of ) with a method more precise and stable�1QC

than the usual coda Q technique (Aki and Chouet, 1975).They observed no signs of sensitivity to the preparatory pro-cesses that are presumably occurring at Parkfield. Interest-ingly, Baish and Bokelmann (2001) used the same techniqueand found changes in the doublet coda similarity that grad-ually recover over a time interval of 5 yr after the LomaPrieta event. Apart from these two cases, there are a numberof studies that did not find changes in coda Q attenuationbut were able to give upper bounds (Hellweg et al., 1995;Aster et al., 1996). Other studies found variations beforelarge earthquakes (e.g., Wyss, 1985; Jin and Aki, 1986) orafter large earthquakes (Peng et al., 1987; Wang et al., 1989;Tselentis, 1997). A useful summary is reported in table 1 ofTselentis (1997).

How to relate the time change of to a physical�1QC

model is also matter of debate. Baish and Bokelmann (2001)suggested that the change is generated by a coseismic effectthat leads to crack opening either by local concentration ofshear stress or by an increase of pore fluid pressure. Thecracks act as additional scatterers, increasing the scatteringattenuation coefficient. The same interpretation was givenby Hiramatsu et al. (2000) for the 1995 Hyogo-ken Nanbuearthquake. In this case, the change in is accompanied�1QC

by a decrease in the b-value of the Gutenberg–Richter dis-tribution. They explained the decrease by the increase in thenumber of earthquakes with magnitude greater than 3. Asthe characteristic fault length for M 3 earthquakes is of thesame order of magnitude as the characteristic scale length ofheterogeneity, the observation was considered as explicablein terms of the same physical model.

Shear-wave splitting is the elastic equivalent of the well-known phenomenon of optical birefringence. A shear wavepropagating through an anisotropic solid splits into two Swaves that travel with different velocities and with different

directions of polarization. The split S waves are named qS1

(the faster) and qS2 (the slower). In the upper crust, thisphenomenon has been interpreted to occur in zones of fluid-filled cracks, microcracks, or preferentially oriented porespaces. These observations have been generally explained interms of the extensive dilatancy anisotropy hypothesis(Crampin, 1987), where the physical explanation is that thestress tends to close the cracks that are normal and to openthe cracks that are oriented perpendicular to the minimumcompressive principal stress. Since the minimum stress isusually horizontal, shear waves traveling into this region areconsequently split into two components with different ve-locity, one polarized parallel and the other polarized normalto the direction of the minimum stress. The time delay be-tween these two components is generally proportional to thelength of the ray path through this anisotropic region. Re-cently, Zatsepin and Crampin (1997) modeled the evolutionof the anisotropic distribution of microcracks due to a dif-ferential stress, suggesting that the fluid migration alongpressure gradients between neighboring microcracks andpores is the driving mechanism leading to a nonlinear phe-nomenon called “anisotropic poroelasticity” (APE). In thisframework, both the time delay and the polarization of theqS1 wave are indirect indicators of the state of stress in theupper crust. Thus, time changes of the splitting parametersare possible indicators of stress changes and consequently aprecursor of an impending eruption or earthquake in the in-vestigated region. Interpreting changes in shear-wave split-ting, Crampin et al. (1999) successfully stress-forecast thetime and magnitude of an M 5 earthquake in southwest Ice-land. Changes in seismic anisotropy have been measuredafter the eruption of Mt. Ruapehu by Miller and Savage(2001); rapid variations of shear-wave splitting were ob-served after two moderate seismic events (M 4.2 and M 4.4)in southern California (Li et al., 1994), after an isolatedswarm of microearthquakes (maximum magnitude 3.6) insouthern China (Gao et al., 1998), before and after an M 4seismic event at Parkfield, California (Liu et al., 1997), andin an active experiment carried out in a borehole in south-eastern Germany after a fluid-induced swarm of microearth-quakes (Bokelmann and Harjes, 2000).

In the present work, we study the time pattern of ,�1QC

b-value, and shear-wave splitting parameters for Mt. Vesu-vius in southern Italy. The seismicity for this area is con-centrated in less than 8 km3, and the closest station is prac-tically above this volume at an average epicentral distanceof 3 km. Consequently, the data set is ideally suited to in-vestigate the possibility of near-source changes of elasticityand heterogeneity induced by the stress buildup and releasefor the major seismic events. The available data set includes(1) the complete catalog for the estimate of the b-value timepattern, (2) digitized data from an analogical station during8 yr for coda Q analysis, and (3) high dynamical range dig-ital data over 2 yr for splitting analysis. In the 8-yr time rangetwo major earthquakes (M 3.2 and M 3.6) occurred, whilein the 2-yr time range only the M 3.6 event was detected.

Changes in the Coda Decay Rate and Shear-Wave Splitting Parameters Associated with Seismic Swarms at Mt. Vesuvius, Italy 441

Figure 1. Shaded relief map of Mt. Vesuvius,southern Italy. White lines superimposed to the maprepresent the pattern of geological structures (faultsand cracks). Their direction histogram is plotted inthe inset. Coordinates are Universal Transverse Mer-cator (UTM). Shaded circles centered at stations BKEand BKN site represent the intersection of the base ofthe cone with vertex at the station, height equal to3 km (the average depth of the seismic events util-ized), and angle equal to the shear-wave window an-gle. Note that the pattern of crack inside each circleis roughly in agreement with the pattern of qS1 po-larization pattern reported in Figure 11.

The results show a change in the Td parameter before theM 3.6 event and a coseismic variation in the qS1 polarizationdirection parameter, a variation after the two major�1QC

events, and no variation of b-value. time change is con-�1QC

sequently interpreted as a coseismic effect, while the changein time delay of shear-wave splitting is interpreted as a pre-cursor-like effect. We explain the observation in terms ofstress buildup around the source volume, causing the shear-wave splitting phenomenon, and in terms of water volumechanges in the shallowest crust induced by the static strainchange after the major seismic events.

Mt. Vesuvius: An Introductory Geological andGeophysical Framework

Mt. Vesuvius is a stratovolcano located in the Campaniaplain (southern Italy) at the intersection of two main faultsystems oriented north-northwest–south-southeast and north-northeast–south-southwest (Fig. 1) (Hyppolite et al., 1994).It is formed by an ancient caldera (Mt. Somma) and by ayounger volcanic cone (Mt. Vesuvius). Volcanic activity isdated back to 300–500 ky (Santacroce, 1983) and charac-terized by both effusive and explosive regimes. Carta et al.(1981) distinguished three regimes of volcanic activity:large-scale explosive Plinian eruptions, intermediate sub-Plinian eruptions, and small-scale effusive eruptions. Thelast eruption, in March 1944, was effusive. It may havestarted a new obstructed conduit phase and hence a quiescentstage.

The velocity structure beneath Mt. Vesuvius has beendeduced by seismic tomography. Results obtained for depthsfrom surface down to a depth of 10 km below sea level(b.s.l.) (Zollo et al., 1996; Auger et al., 2001) suggest thepresence of a melting zone at a depth of about 8 km. Smalland shallow magma chambers, hypothesized by petrologicalconsiderations (Rosi et al., 1987), are undetected by anyseismic tomographic studies. One of the most recent studiesthat carried out simultaneous inversion of travel time andhypocentral parameters of the local earthquakes in the samearea (Scarpa et al., 2002) showed a high-resolution imageof the compressional wave velocities for the shallow edificeof Mt. Vesuvius. They showed a high P-wave velocity zone,with a rough cylindrical symmetry about the crater axis, ex-tending from the surface down to a depth of approximately2 km, where it encounters the carbonate basement (dashedline in east–west section of Fig. 2).

Information on the shallow structures comes also froma deep borehole drilled down to a depth of 2200 m b.s.l.(Principe et al., 1987) and from AGIP (Italian Petrol Com-pany) data recently reutilized to reconstruct the map of thecarbonate basement under the volcano (Bruno et al., 1998).Another interesting part is the presence of a large positivemagnetic anomaly, located below the central cone (Fedi etal., 1998), which is attributed to the presence of high mag-netic susceptivity of the volcanic rocks. An electrical andelectromagnetic survey carried out in the Mt. Somma–

Vesuvius area displayed (1) a migration of the volcanic ac-tivity along west–east–oriented fracture system, (2) a north–south–trending narrow fracture system cutting the lowestMt. Somma eastern slope, and (3) a large positive nucleusin the depth range 600–2200 m b.g.l. sensibly displaced to-ward the Tyrrhenian Sea. These features are interpreted asdue to an intensively altered and mineralized block of ce-mented volcanic breccia, with a strongly reduced porosity(Di Maio et al., 1998).

In the past 27 years, no notable variations of gravity orground deformation have been observed. The only actualexternal volcanic activity is a poorly energetic fumarolicfield, and the unique indicator of some active internal dy-namic is the seismic activity.

Seismic Network and Seismicity

A short-period seismic station (equipped with a 3DGeotech S-13 sensor) has been operating since 1972 in a 20-m-deep gallery close to the location of the historical buildingof Vesuvius Observatory (OVO) (Figs. 2 and 3). At present,the seismic monitoring system of Neapolitan volcanoes (Ve-suvius, Campi Flegrei, and Ischia Island) is made up by 23short-period stations telemetered to the acquisition center in

442 E. Del Pezzo, F. Bianco, S. Petrosino, and G. Saccorotti

Figure 2. Location of the earthquakes used in thepresent analysis. On the map the seismic stations usedfor Q coda and shear-wave splitting analysis are alsoreported. The dashed line drawn in the east–west sec-tion represents the limestone basement redrawn fromScarpa et al. (2002). The bottom panel shows the pat-tern of the hypocentral depth versus time. The con-tinuous line is the average. There are no significanttrends in the time pattern of hypocentral depth for theperiod analyzed in this article.

Figure 3. Topography and the seismic subnet ofMt. Vesuvius. Triangles (black and white) representanalogical stations. Black stars indicate the positionof the temporary digital 3D stations. The crossed starindicates the dilatometer site. Coordinates are UTM.The X and Y axes are displayed at an interval of 1 km.The horizontal and vertical gray lines, crossing thevolcano crater, represent the intersection of the north–south and east–west section of Figure 2.

Naples and continuously sampled at 100 samples/sec. In ad-dition, five 3D stations (Lennartz PCM 5800) and seven 3Dstations (Lennartz MARS LITE) were set up in the area ofMt. Vesuvius from 1997 to the end of 2000 and from 9October 1999 to the present, respectively. Details of seismicnetwork configuration and of instruments are described inCastellano et al. (2002); the subnet of Mt. Vesuvius is de-picted in Figure 3.

The seismicity of Mt. Vesuvius has been described in anumber of papers (see Scarpa et al. [2002] and referencestherein). Here we briefly synthesize the main features of theearthquake space and time distribution, from the recent pa-pers by Scarpa et al. (2002) and Del Pezzo et al. (2003a,b).In the study of Scarpa et al. (2002), the relocated seismicityappears to extend down to 5 km below the central crater,with most of the energy (up to local magnitude 3.6) clusteredin a volume spanning 2 km in depth, positioned at the borderbetween the limestone basement and the volcanic edifice.

The hypocentral location for the data used in the presentarticle shows the same pattern of the overall seismicity (Fig.2). The dashed line reported in the east–west section of Fig-ure 2 represents the pattern of the limestone basement. Inthe bottom panel of the same figure, the time pattern of hy-pocentral depths is also reported. No volcanic tremor and/orLong Period (LP) events (following the classification ofChouet [1996]) have been ever recorded at Mt. Vesuvius bythe seismic network (Saccorotti et al., 2001). The earth-quakes are of volcano-tectonic type (VT) (Chouet, 1996),with fault-plane orientations showing a highly nonregularspatial pattern. The spectral content of the P- and S-wavetrains of the VT events is compatible with stress drops span-ning a range between 1 and 100 bars (100 bars for the largestmagnitude) and focal dimensions of the order of 100 m,apparently not scaling with seismic moment.

The time pattern of the cumulative seismic slip releasedfrom 1972 to the present (Fig. 4, redrawn from Del Pezzoet al., [2003a]) shows the occurrence of four major swarms,the last of which occurred in October 1999 with a largestmagnitude of 3.6. Interestingly, from the plot it can be seenthat the major change in cumulative slip occurs from 1989to 1991 and not at the time of occurrence of the largestearthquake (October 1999). This event appears to be thelargest since at least 1972 but possibly since the last eruptionoccurred in 1944. Overall, the seismicity of Mt. Vesuvius ischaracterized by a mean rate of 317 events per year.

Changes in the Coda Decay Rate and Shear-Wave Splitting Parameters Associated with Seismic Swarms at Mt. Vesuvius, Italy 443

Figure 4. Cumulative seismic slip releasecurve calculated for Mt. Vesuvius during theperiod from 1972 to 2002. The three curvesshow the pattern for three magnitude ranges.The vertical dashed line represents the time of9 October 1999 earthquake. The figure is re-drawn from Del Pezzo et al. (2003a), wheredetails of the calculation procedures are de-scribed.

Data, Methods, and Results

Data

The complete earthquake catalog of Mt. Vesuvius isused for the study of the time pattern of the Gutenberg–Richter b-value. The catalog is based on the analog recordsof station OVO (Fig. 3) and reported time of occurrence andduration magnitude. A discussion on the characteristics ofthis catalog was reported in Del Pezzo et al. (2003b), to-gether with a discussion on the method used for the estimateof the b-value.

Data of the vertical component from analog station BKE(Figs. 2 and 3) have been used for the analysis of the codaQ time pattern. For this station, digitized records (100 sam-ples/sec, with a dynamic range of 60 dB) are available sincethe beginning of 1994. BKE has been selected because it hasthe best signal-to-noise ratio among the stations of the Mt.Vesuvius network. Due to the low magnitude of the earth-quakes recorded, only a few traces are clipped immediatelyafter the S-wave arrival. Data consequently allow a denseand uniform sampling of the time interval around two majorbursts of seismicity that occurred at the end of April 1996and in October 1999.

Data from two Lennartz 5800 digital 3D stations (BKEand BKN, Fig. 3; 125 samples/sec with a dynamic range of120 dB) have been used for the analysis of the time delaysbetween qS1 and qS2 phases in the shear-wave splitting anal-ysis. Records from these stations are available from the be-ginning of 1999 until the end of 2000. Due to the high dy-namic range, the signals are not clipped in the S-wave timewindow, even for the largest magnitude event. Unfortu-nately, the stations were not continuously operating for theperiod including the seismicity burst of 1996, and the dataset suitable for a complete and uniform data sampling forshear-wave splitting analysis consists of a 2-yr intervalaround the seismic swarm of October 1999.

b-Value

Time changes in the b-value of the Gutenberg–Richterlaw (e.g., Udias, 1999) for a given area are claimed to be

indicators of changes in the elastic parameters of the rockmass. For volcanic areas, time changes in the b-value maybe considered as indicators of an impending change in vol-cano dynamics (Wyss et al. [1997] and references therein).

In the present article, we use the results already obtainedby Del Pezzo et al. (2003b) who, using both the weightedleast squares (WLS) method and the maximum likelihoodtechnique (ML), analyzed the seismic catalog of Mt. Vesu-vius using a 5-yr-long time window, sliding along the datawith increments of 1 yr. For each window position, theyestimated the b-value and corresponding errors through thecovariance matrix. The b-values thus obtained are then as-sociated to the time corresponding to the center of any win-dow. Results are reported in Figure 5. The temporal behaviorof the b-value shows an increasing trend starting at the endof 1980, reaching its maximum in 1982 and returning to theprevious values at the end of 1985. A small decrease can benoticed from 1996 to the present, but the range of variationsis smaller than the error bars. In the same figure, the corre-lation coefficient and the number of earthquakes with mag-nitude greater than 3 are also reported. Interestingly, thegreater changes in the b-value time pattern correspond to thegreater variations in Pearson’s correlation coefficient, whichincreases with b-inverse. Moreover, the time interval inwhich the b-value is largest (1980–1986) corresponds to aperiod with a lack of M �3 earthquakes. Moreover, the MLb-value pattern shows a decreasing time trend of the b-valuethat starts approximately in 1992 and is much more pro-nounced than that revealed by the WLS method, even thoughno time changes are shown by either method in the timeintervals in which shear-wave splitting analysis and coda Qanalysis were carried out.

Coda Q�1 Analysis and Results

Spatial and temporal changes in the character of theseismic coda envelope are optimally achieved by the anal-ysis of identical signals (doublets), as demonstrated by Baishand Bokelmann (2001). In the case of Mt. Vesuvius, we havefound no multiplets sampling the source volume prior to or

444 E. Del Pezzo, F. Bianco, S. Petrosino, and G. Saccorotti

Figure 5. Time pattern of the b-value (bothWLS and ML methods) of the Gutenberg–Richter distribution, starting from 1972. The b-values are calculated for a time window of 5yr, and the first point on the plot correspondsto the middle of the first window. Pearson’scorrelation coefficient and the number of earth-quakes with MD �3 are also reported in thesame plot (redrawn from Del Pezzo et al.[2003b]).

after the occurrence of the major earthquake swarms. Mul-tiplets do exist among the VT earthquakes of Mt. Vesuvius,each multiplet spanning a time interval of few days, insuf-ficient to properly sample the major energy bursts. Thus thecoda Q analysis was performed using the ordinary methodby Aki and Chouet (1975).

We selected the BKE vertical station for two main rea-sons: the first is that it is the station with the highest signal-to-noise ratio (in the investigated area, the cultural noise ishigh due to the dense urbanization); the second is that itrecorded the largest number of shocks, being the nearest tothe epicentral area (close to the crater). A detailed study ofthe inverse coda Q at Mt. Vesuvius was made by Bianco etal. (1999a), who analyzed 250 seismic events recorded atdigital seismic stations of the Mt. Vesuvius network. Theyexperimentally demonstrated that the average inverse codaQ poorly changes with station position and lapse time (whichwas fixed at 8, 10, and 12 sec). In the same paper, it wasalso shown that the site effects are quite similar for seveninvestigated sites located on Mt. Vesuvius.

We assume, independent of any scattering model, thatthe envelope of the S coda, A(f , t) filtered at a given fre-quency band centered at a frequency f , is well approximatedby

�1 �1A( f, t) � Kt exp(�pftQ ( f )), (1)C

where K is the so-called source factor, is the coda decay�1QC

factor, and t is the time elapsed from the origin time (calledthe “lapse time”). Equation (1) corresponds to the 3D back-scattering model (Aki and Chouet, 1975) under the hypoth-esis that the coda is composed of S waves single-scatteredat uniformly distributed heterogeneities in a constant-velocityEarth medium. In a realistic Earth, these hypotheses can bedone only in a first rough approximation. There is debate onwhat really measures; the majority of the papers on this�1QC

argument (see, for a synthesis, Sato and Fehler [1998]) in-dicate that is close to the , the inverse quality�1 �1Q QC Intrinsic

factor that accounts for energy dissipation into heat.To estimate the time changes of , we follow the�1QC

procedure used by Bianco et al. (1999a). We bandpass filterthe trace into three frequency bands, centered at fc � 6, 12,and 18 Hz respectively with a bandwidth spanning fromfc/2 to 3fc/2. Then we estimate A(f , t) of equation (1) at fre-quency fc using the relationship

2 2A ( fc, t) � H(S) � S , (2)�obs

where S is the trace filtered at fc, H(S) is the Hilbert trans-form of the trace itself, and t starts from 2tS (where tS is theS-wave travel time) and ends at 12 sec from the origin time.Then we fit the envelope to equation (1) using a grid searchmethod for those values of and K that minimize the�1QC

misfit function

�1 2M(K, Q ) � |A ( fc, t) � A( f, t)| . (3)C � obst

The uncertainty associated with estimates of and K is�1QC

calculated in the following way. We plot MN(K, ), which�1QC

is defined as M(K, ) normalized (to the minimum value).�1QC

This is a random variable following the F distribution withN � 2 degrees of freedom (N is the number of data, corre-sponding to the points of the envelope). At 70% confidencelevel (1r), all the acceptable solutions are consequentlythose with MN(K, ) less than the value reported in the�1QC

F-test statistical table. We estimate rK and from the�1rQC

plot of the acceptable solutions (Fig. 6). On the basis ofvisual inspection of the misfit function, we eliminate all thesolutions showing multiple minima and/or a large trade-offbetween the estimates of and K.�1QC

Changes in the Coda Decay Rate and Shear-Wave Splitting Parameters Associated with Seismic Swarms at Mt. Vesuvius, Italy 445

Figure 6. An example of coda analysis showingthe coda envelope (upper panel) and the plot of misfitfunction (lower panel) used for the estimate of thestandard deviation of . The solid line represents�1QC

the envelope of the seismogram filtered at 12 Hz(shifted in Y for clarity of representation), the rectan-gle inset the portion of the envelope used for the anal-ysis. The gray scale represents the pattern of the nor-malized misfit function values exceeding the 1r levelof the F test. Diffuse light gray color is plotted whenthe misfit function values are outside the 1r level.

Figure 7. as a function of time starting from�1QC

September 1994. The black line is the ENF average;the red line is the ETF average. ETF is carried out ina 180-day window, sliding 180-day step. ENF is car-ried out over a window containing 18 events, slidingeach step by 9 events. The two vertical arrows markthe occurrence of the two major swarms in the studyperiod. Cumulative seismic energy and event numberare also plotted in the lower panel, together with thehistogram of their time distribution.

The time pattern of for the frequency bands cen-�1QC

tered at 6, 12, and 18 Hz is shown in the upper panel ofFigure 7. The timescale is in days from 5 September 1994.The plot shows the weighted averages (values weighted withtheir inverse variance) of the single estimates of in a�1QC

180-day time window (estimates for a fixed time interval[ETF]). In the same plot we also report the weighted averagescalculated for a time window of 18 events, sliding each stepof 6 events (estimates for a fixed number of events [ENF]).We assign to each average the center of the time intervalbetween the first and the last event in the moving window.To concisely describe the seismic energy release pattern, weplot in the lowermost panel of Figure 7 the cumulative seis-mic energy and the cumulative earthquake number, togetherwith the plot of the event number as a function of time forthe examined time interval. Variations of exceeding 1r�1QC

error bars are visible for the time interval successive to theoccurrence of the 9 October 1999 earthquake for 6-, 12-, and18-Hz frequency bands. The variation is less marked at 6Hz. Both ENFs and ETFs show an increase of after the�1QC

two main earthquake swarms. The increase successive to the1996 swarm appears approximately 400 days later, whereasthe one successive to the 1999 swarm appears less than 100days later. In addition, the ENFs evidence a marked variationaround 25 April 1996.

A t-test was carried out to exclude that the averages ofthe 1-yr values before and after the occurrence of the 9 Oc-tober earthquake are different only by chance. The test dem-onstrates that the averages are different for each frequencyband.

Shear Wave-Splitting Observation

The shear-wave splitting is characteristic of S wavespropagating through an anisotropic volume. We measuredthe shear-wave splitting parameters (the polarization direc-tion of the fast split shear waves and the time delay, Td,between the fast and the slow split shear waves) on a dataset that satisfies the following conditions: (1) incidence an-gles strictly inside the theoretical shear-wave window, thatis 35�, in order to avoid the contamination with S-to-P con-verted phase; (2) signal-to-noise ratio greater than 6; and(3) clear S onsets. We used the visual inspection technique,well described in Liu et al. (1997), to detect the S-wave

446 E. Del Pezzo, F. Bianco, S. Petrosino, and G. Saccorotti

Figure 8. An example of a shear-wave splittingmeasurement. (a) Three-component trace. The signalexamined is inside the dashed rectangle. (b) Particlemotion for the selected signal. (c) Zoomed portion ofthe examined signal. The two arrows indicate the ar-rival times of the two shear-wave phases. qS1 ismarked by the solid line and qS2 by the dashed line.

Figure 9. (a) Time pattern of the total average nor-malized TD values (TN) for BKE. (b) Time pattern ofthe average normalized TD values (TN) for BKE inband 1. (c) Time pattern of the average normalizedTD values (TN) for BKE in band 2. (d) Time patternof the total average normalized TD values (TN) forBKN. (e) Time pattern of the average normalized TD

values (TN) for BKN in band 1. (f) Time pattern of theaverage normalized TD values (TN) for BKN in band2. Each point corresponds to the average of the datain sets of 18 consecutive normalized TN values, slid-ing each step of 9 events, assigning to each averagethe center of the time interval between the first andthe last event in the set. The vertical dashed line in-dicates the occurrence of the M 3.6 earthquake. Errorbars show the 1r interval.

splitting. Here we give only a concise sketch of this proce-dure. First, we obtain the polarization direction of the fast Swave on the horizontal polarization diagram; then we rotatethe horizontal seismograms into components that are paralleland perpendicular to the polarization direction of the fastsplit shear wave. Finally, we measure Td from the differencein arrival times of the two orthogonal shear-wave traces andnormalize for the hypocentral distance, obtaining

�1T � D T . (4)N d

We disregarded the measurement if the second arrival wasvisually unclear, since second split shear waves may be ob-scured by both signal-generated coda following the P wavesand/or background noise. Figure 8 shows an example of ap-plication. We then averaged the data in sets of 18 consecu-tive normalized TN, sliding each step of nine events, andassigned to each average the center of the time interval be-tween the first and the last event in the set. The error barscorrespond to the standard deviation evaluated in the follow-

ing way. We assume that the error associated to the estimateof Td, rTd, is of the order of three samples (0.02 sec) and theerror associated to the hypocentral distance, rD, of the orderof 0.2 km. Propagating the error into equation (4), it resultsthat

�2 2 �4 2 2r � D r � D T r . (5)�T Td d DN

Results are reported in Figure 9. The plot of TN versustime shows a marked peak at stations BKN and BKE somedays before the occurrence of the M 3.6 earthquake of 9October 1999. Interestingly, about 60 days after the event,station BKE shows a net decrease, with a trend asymptoti-cally tending toward an almost constant value. Since the APE

Changes in the Coda Decay Rate and Shear-Wave Splitting Parameters Associated with Seismic Swarms at Mt. Vesuvius, Italy 447

modeling (Crampin and Zatsepin, 1997) suggests that thetime delays change with the direction of propagation, wealso search for temporal variations of normalized time delaysin band 1 and band 2. Band 1 is the double-leafed solid angleof directions making angles 15�–35� to the plane of thecracks, and band 2 is the same for the directions within 15�(Crampin, 1999). The plot of TN versus, time in band 1, atboth stations, shows again a marked peak before the occur-rence of the M 3.6 event, as in the case without the separationin bands (Fig. 9). Also, the band 2 behavior (Fig. 9) showsan increase of TN before the 9 October 1999 earthquake, butit is less pronounced than the one in band 1.

Also for this observation, a t-test was carried out to ex-clude that the averages of the values before and after theapparent turning point at about 20 days before the occur-rence of the 9 October earthquake are different only bychance. We averaged the TN values in a time interval of 70days before and after the turning point for the total TN values,for the values in band 1, and for the ones in band 2. The testdemonstrates that the averages in all the cases are differentat a 0.01 confidence level.

The temporal pattern of the polarization directions forthe fast split shear wave is represented in the diagrams ofFigure 10. We calculated the mode of the distribution for 18consecutive values, sliding each step of 18 values. The timepattern at BKE (solid red line in Fig. 10) shows that the modeof the qS1 polarization direction varies between 70� and 110�in the days before the M 3.6 earthquake. After the M 3.6event, variation spans the interval between 100� and 140�.At BKN (black dashed line in Fig. 10), the pattern is ap-proximately constant (15�) with a peak (170�) in a time in-terval of about 40 days centered around the M 3.6 earth-quake. This peak is statistically meaningless, as it lies withinthe error bars of the adjacent values (15�). We plot in thesame figure the distribution of polarization direction (rosediagrams) of the values from which the mode was inferred.It is interesting to note that the distribution pattern shows avariation approximately 30 days before the M 3.6 earth-quake. The two rose diagrams calculated in this time intervalin fact show the presence of two equivalent peaks, the firstin the east–west direction, the second in the north–south di-rection. This pattern disappears after the occurrence of theM 3.6 earthquake, showing again the main east–west trendcharacterizing the overall seismicity at Mt. Vesuvius at sta-tion BKE. The rose diagrams for the complete set of data(Fig. 11, right) show that the qS1 polarization directionsstrike approximately toward the east–west direction at sta-tion BKE and toward the north–south at station BKN. Theobserved pattern of the normalized time delays versus sourcedepth confirms the presence of an anisotropic volume at Mt.Vesuvius already evidenced by Bianco et al. (1998, 1999b)using a different set of data. This anisotropic volume extendsfrom the surface to a depth of 1.5–2 km, since after this depthrange the pattern of TN as a function of depth becomes al-most constant (the two left-hand diagrams of Fig. 11).

Discussion

In synthesis, our observations described in the previoussections show the following:

1. The ETF changed after the occurrence of the largest�1QC

earthquakes of the two swarms occurred on 25 April 1996(M 3.4) and on 9 October 1999 (M 3.6). The ETF �1QC

increases, reaches a maximum 400 days after the swarmof April 1996, and then decreases until the occurrence ofthe M 3.6 earthquake. After this event the ETF in-�1QC

creases again, reaches a new maximum 100 days later,and then decreases again. This pattern is particularly evi-dent for the frequency bands centered at 6 and 12 Hz. At18 Hz the changes are within the range of the error bars.The ENF follows the same pattern, except around 25�1QC

April 1996, when, for the frequency band centered at 6Hz, one can observe a sharp increase soon after followedby a sudden decrease. This pulselike pattern (with anequivalent duration of about 100 days) is detected onlyby ENF averaging, due to the greater number of eventsoccurring during the swarm on 25 April 1996, which al-lows for averaging over 18 events in a short time window.This pulselike pattern is not present at the occurrence ofthe swarm of 9 October 1999. The variations are not�1QC

correlated with any time change in hypocentral location,as shown in the lower panel of Figure 2.

2. At both stations BKE and BKN the ENF average of TN

changed before the occurrence of the 9 October 1999earthquake, more clearly in band 1. An increase of TN isvisible 25 days before the occurrence of this shock; TN

begins to decrease 50 days later and reached at BKE analmost asymptotic value after 100 days.

3. No variation of the qS1 polarization direction of the fastsplit S wave was observed in spite of the occurrence ofthe major earthquake on 9 October 1999 at station BKN.The behavior at station BKE appears more complex,showing a variation associated with the major earth-quake.

4. There is no variation of the Gutenberg–Richter b-value.

To explain the variations of with time, Jin and Aki�1QC

(1989) proposed a creep model. In this model the increasein is explained in terms of stress increase, which favors�1QC

the increase of crack density. The increased crack densityproduces more scattering, with the consequence of increas-ing . In reality, recent results seem to indicate that�1QC

is more sensitive to changes in intrinsic attenuation�1QC

rather than in total attenuation (intrinsic � scattering) (Satoand Fehler, 1998). At Mt. Vesuvius, making the assumptionthat is proportional to intrinsic attenuation, Bianco et�1QC

al. (1999a) estimated separately the average intrinsic andscattering attenuation, demonstrating that scattering attenu-ation dominates over intrinsic dissipation by a factor 2 at 18Hz and that most of the coda generation occurs near thesurface. Consequently, we would attribute the changes in

448 E. Del Pezzo, F. Bianco, S. Petrosino, and G. Saccorotti

Figure 10. Time pattern of the polarization angle for BKE and BKN. Each value isthe mode of the distribution inside a time window composed of 18 events and slidingat a step of 18 events. The error bar is the standard deviation of the mean. The verticalarrow indicates the occurrence of the M 3.6 earthquake. Rose diagrams show the dis-tribution of polarization directions of qS1 for each time window. Data are grouped into30� intervals for each rose diagram.

Figure 11. Normalized time delay versus hypo-central depth (left) and rose diagrams of the qS1 po-larization direction for stations BKE and BKN (right).

to significant changes in the inelastic properties of the�1QC

shallow geological structure of Mt. Vesuvius, which occurafter the major local earthquakes.

Changes of TN may be explained by the model of non-linear APE. The shear-wave splitting is produced by thealignment of the fluid-filled cracks due to the stress increasein the earthquake preparatory process (Zatsepin and Cram-pin, 1997).

Maximum average TN value changes at BKE are of theorder of 30 msec/km (Fig. 9). This value is much strongerthan the average TN observed at Parkfield by Liu et al. (1997)before and after an ML 4 earthquake observed at 15 km dis-tance from the source but is consistent with single obser-vations at closer distance (see figure 4a of Liu et al. [1997]).APE modeling (Crampin and Zatsepin, 1997) confirms thatthe increasing stress on a rockmass produces an increase in

Changes in the Coda Decay Rate and Shear-Wave Splitting Parameters Associated with Seismic Swarms at Mt. Vesuvius, Italy 449

Figure 12. (a) Rose diagram of the qS1 polariza-tion direction at station BKE for the seismicity re-corded in 1996; the gridded sector is the qS1 polari-zation direction for the March–May 1996 crisis only.(b) qS1 polarization direction at station BKE for theseismicity recorded between September 25 and Oc-tober 20.

the aspect ratios in vertical aligned microcracks; for the samemodel, variations of TN values in band 1 are controlled byvariations in aspect ratios for microcracks, while variationsof TN values in band 2 are controlled by variations in crackdensity of the crack distribution. According to our obser-vations of TN in both bands and for both stations, we suggestthat the crack aspect ratios increase until a level of fracturecriticality is reached and the ML 3.6 earthquake occurs. How-ever, a contribution of the variation in crack density cannotbe ruled out, but according to our measures this effect seemsto be a second-order effect. Interestingly, increases of TN

values in band 1 have been observed for an M 6 North PalmSprings earthquake (Peacock et al., 1988), for an M 4 earth-quake at Parkfield (Liu et al., 1997), for an M 3.8 earthquakein Enola, Arkansas (Booth et al., 1990), during an isolatedswarm on Hainan Island, China (Gao et al., 1998), and fora successfully stress-forecast earthquake in Iceland (Cram-pin et al., 1999).

Surprisingly, the pattern of the qS1 polarization direc-tion is more complicated than that expected by the APEmodel. The main qS1 polarization directions are not the samefor BKE and BKN, appearing almost orthogonal one to eachother (Fig. 11).

We can compare the results on polarization directionsobtained for the years 1999–2000 in the present article withthose for 1996, partly published by Bianco et al. (1999b).They showed that at BKE the qS1 polarization direction ispredominantly north–south oriented for the swarm that oc-curred during March–May 1996, as also shown in Figure12a. We also plot in the same rose diagram the polarizationdirection pattern calculated for the earthquakes that occurredduring the whole of 1996. Interestingly, the overall patternfor 1996, including the earthquakes belonging to the swarmof March–May, is comparable with the pattern for an intervalof 30 days centered at the occurrence of an M 3.6 event in1999 (Fig. 12b). This observation may indicate that at stationBKE the qS1 polarization direction pattern changed duringthe two main swarms of 1996 and 1999, showing an addi-tional north–south–oriented pattern, superimposed to thepre-existing east–west orientation. On the contrary, at BKNboth in 1996 and in 1999–2000, the qS1 polarization direc-tion remains always north–south oriented (see figure 8 ofBianco et al. [1999b] and our Fig. 11).

The framework of the APE model that accounts forchanges in the qS1 polarization direction when the system isoverpressurized indicates a possible explanation for the ob-servations carried out at BKE. We hypothesize that, in nor-mal conditions, cracks located around the BKN site arenorth–south oriented, whereas those located close to BKEare east–west oriented. This hypothesis is supported by thedistribution of cracks and faults reported in Figure 1. Thetwo shaded areas drawn in Figure 1 around BKE and BKN,representing the shear-wave window, show that the observeddirection of the geological structures around these stationsis approximately normal to each other. The differential stress

acting during the main seismic events is north–south ori-ented (Del Pezzo et al., 2003a). During the loading of thisstress, there is an additional crack opening around stationBKE in the north–south direction, which produces the ob-served distribution of qS1 polarization direction for BKE(Fig. 12a,b). At BKN the loading enhances the crack openingin the pre-existing north–south direction. The effect disap-pears after the occurrence of the major earthquakes and theconsequent stress readjustment.

This conceptual model and fluid migration dynamicswithin the shallow crust (Person and Baumgartner, 1995)accounts for time changes in both TN and observed at�1QC

Mt. Vesuvius. In this scheme pore pressure dilatation occursin rocks surrounding the fault zone prior to a major earth-quake, due to the increase in shear stress, frictional heating,and metamorphic fluid production. In this stage of the earth-quake preparatory process, fracture porosity normal to theleast principal stress is increased and is accompanied by in-jection of meteoric water into the rock pores, producing a

450 E. Del Pezzo, F. Bianco, S. Petrosino, and G. Saccorotti

water flow from the surface toward the focal zone. This ex-plains the observed change in shear-wave splitting parame-ters before the major earthquake of 9 October 1999. Thestress readjustment after the earthquake around the focalzone is accompanied by surface water flows (Muir-Wood,1994) and typically continues up to several years afterward,depending on the seismic event magnitude and/or strain re-lease. Further surface water flow after a seismic event is dueto the increased fracture permeability (Rojstaczer and Wolf,1992) and/or to the fault-valve mechanism (Sibson, 1994).The water volume increase after the major earthquakes inthe shallow rocks of Mt. Vesuvius is the cause of the in-creased level of intrinsic attenuation, which is monitored bythe change in . Interestingly, changes differently�1 �1Q QC C

after the occurrence of the two major earthquake swarms, ascan be observed in Figure 7; this difference may be due tothe different intensity of stress loading, greater in 1999 thanin 1996, producing a greater degree of porosity.

The present results allow us to quantitatively estimatethe sensitivity of coda Q and Td to the strain changes asso-ciated to the two major seismic events that occurred at Mt.Vesuvius. The signal wavelength at which estimates of

are carried out is in the range 80–250 m, that is, the�1QC

same order of magnitude of the fault dimension inferred byspectral analysis of waveforms (Del Pezzo et al., 2003a).The strain change due to the earthquake on 9 October 1999was measured by a Sacks-Everston borehole (250-m depth)dilatometer, located at about 4 km from the source (seeFig. 3), and is of the order of 10�9. Defining the sensitivityof as�1QC

�1DQ�1s � ,QC De

where DQ�1 is the observed change in and De is the�1QC

strain change measured by the dilatometer, we find fora value of 1.4 � 109 [strain unit]�1. The same consid-�1sQC

eration can be used to find the order of magnitude of the Td

sensitivity to the strain variation:

DTds � ,Td De

which is equal to 2 � 1010 [msec/strain unit]. Unfortunatelythere is a lack of this kind of measurement in other volcanicareas, so we cannot make any comparison. However, �1sQC

and may be useful in monitoring Mt. Vesuvius for futuresTd

estimates of strain variations.

Conclusions

The framework of APE modeling is used to explain thetemporal change of the Td pattern observed at Mt. Vesuviusabout 20 days before an M 3.6 earthquake, at a distance of

less than 4 km from the receiver. We hypothesize that astress field with the maximum north–south–oriented hori-zontal component increases the crack aspect ratio for thecracks aligned with the maximum stress orientation. Thiscauses an increase in the pore fluid flow toward the zone ofcrack opening, which is detected by the rising of the ob-served Td before the major earthquake. After this earthquake,the increased fracture permeability in the shallow rocks fa-vors the fluid flow toward the surface, increasing the valueof intrinsic attenuation. This change is detected by the co-seismic increase of the coda Q inverse.

This observation confirms the importance of continuousmonitoring of the shear-wave splitting together with coda Qinverse parameters at Mt. Vesuvius. The seismicity is con-centrated in a rock volume not larger than 2–3 km3, and thestations closest to the source are at a distance not greaterthan 3–4 km. This allows us to detect significant changes insplitting parameters and accompanied by earthquakes�1QC

with magnitudes as low as 3.6. As the occurrence of majorearthquakes can be concurrent to an eruptive preparatoryprocess, this monitoring has further importance in the high-risk area of Mt. Vesuvius. This area is highly populated, andfor this reason the sensors of the seismic network are set upin sites with high cultural noise. Major precision and an in-creased sensitivity of the method should be achieved con-sequently with the use of borehole sensors, which shoulddrastically reduce the signal-to-noise ratio, allowing betterquality signals.

Acknowledgments

Stuart Crampin is gratefully acknowledged for useful discussions, en-couragement, suggestions, and a revision of the manuscript. PierdomenicoRomano and Carlo Barone performed part of the data pre-analysis for theirdegree theses in physics. Data have been furnished by the Seismic Lab ofVesuvius Observatory. Two anonymous reviewers greatly improved thequality of the text.

References

Aki, K. (1969). Analisys of seismic coda of local earthquakes as scatteredwaves, J. Geophys. Res. 72, 1217–1231.

Aki, K., and B. Chouet (1975). Origin of coda waves: source, attenuation,and scattering effects, J. Geophys. Res. 80, 3322–3342.

Antolik, M., R. M. Nadeau, R. C. Aster, and T. V. McEvilly (1996). Dif-ferential analysis of coda Q using similar microearthquakes in seismicgaps, part II: Application to seismograms recorded by the Parkfieldhigh resolution seismic network, Bull. Seism. Soc. Am. 86, 890–910.

Aster, R. C., G. Slad, J. Henton, and M. Antolik (1996). Differential anal-ysis of coda Q using similar microearthquakes in seismic gaps, partI: Techniques and application to seismograms recorded in the Anzaseismic gap, Bull. Seism. Soc. Am. 86, 868–889.

Auger, E., P. Gasparini, J. Virieux, and A. Zollo (2001). Seismic evidenceof an extended magmatic sill under Mt. Vesuvius, Science 294, 1510–1512.

Baisch, S., and G. H. Bokelmann (2001). Seismic waveform attributes be-fore and after the Loma Prieta earthquake; scattering change near theearthquake and temporal recovery, J. Geophys. Res. 106, 16,323–16,337.

Changes in the Coda Decay Rate and Shear-Wave Splitting Parameters Associated with Seismic Swarms at Mt. Vesuvius, Italy 451

Bianco, F., M. Castellano, G. Milano, G. Ventura, and G. Vilardo (1998).The Somma–Vesuvius stress-field induced by regional tectonics: ev-idences from seismological and mesostructural data, J. Volcanol.Geothern. Res. 82, 199–218.

Bianco, F., M. Castellano, E. Del Pezzo, and J. Ibanez (1999a). Attenuationof the short period seismic waves at Mt. Vesuvius, Italy, Geophys. J.Int. 138, 67–76.

Bianco, F., M. Castellano, G. Milano, G. Vilardo, F. Ferrucci, and S. Gresta(1999b). The seismic crisis at Mt. Vesuvius during 1995 and 1996,Phys. Chem. Earth 24, 977–983.

Bokelmann, G. H., and H. P. Harjes (2000). Evidence for temporal variationof seismic velocity within the upper continental crust, J. Geophys.Res. 105, 23,879–23,894.

Booth, D. C., J. H. Lovell, and J. M. Chiu (1990). Temporal changes inshear wave splitting during an earthquake swarm in Arkansas, J. Geo-phys. Res. 95, 11,151–11,164.

Bruno, P., G. Cippitelli, and A. Rapolla (1998). Seismic study of the Me-sozoic carbonate basement around Mt. Somma–Vesuvius, Italy, J.Volcanol. Geotherm. Res. 84, 311–322.

Carta, S., R. Figari, G. Sartoris, E. Sassi, and R. Scandone (1981). A sta-tistical model of Vesuvius and its volcanological implication, Bull.Volcanol. 44, no. 2, 129–151.

Castellano, M., C. Buonocunto, M. Capello, and M. La Rocca (2002). Seis-mic surveillance of active volcanoes: the Osservatorio VesuvianoSeismic Network (OVSN–southern Italy), Seim. Res. Lett. 73, 168–175.

Chouet, B. (1996). New methods and future trends in seismological volcanomonitoring, in Monitoring and Mitigation of Volcano Hazards, R.Scarpa and R. I. Tilling (Editors), Springer, New York, 23–97.

Crampin, S. (1987). Geological and industrial implications of extensivedilatancy anisotropy, Nature 328, 491–496.

Crampin, S. (1999). Calculable fluid–rock interactions, J. Geol. Soc. Lon-don 156, 501–514.

Crampin, S., and S. V. Zatsepin (1997). Modelling the compliance ofcrustal rock, II. Response to temporal changes before earthquakes,Geophys. J. Int. 129, 495–506.

Crampin, S., T. Volti, and R. Stefansson (1999). A successfully stress-forecast earthquake, Geophys. J. Int. 138, F1–F5.

Del Pezzo, E., F. Bianco, and G. Saccorotti (2003a). Seismic source dy-namics at Vesuvius volcano, Italy, J. Volcanol. Geotherm. Res. 3017,1–18.

Del Pezzo, E., F. Bianco, and G. Saccorotti (2003b). Duration magnitudeuncertainty due to seismic noise: inferences on the temporal patternof Gutenberg–Richter b-value at Mt. Vesuvius, Italy, Bull. Seism. Soc.Am. 93, 1847–1853.

Di Maio, R., P. Mauriello, D. Patella, Z. Petrillo, S. Piscitelli, and A. Sin-iscalchi (1998). Electric and electromagnetic outline of the MountSomma–Vesuvius structural setting, J. Volcanol. Geotherm. Res. 82,219–238.

Fedi, M., G. Florio, and A. Rapolla (1998). 2.5D modelling of Somma–Vesuvius structure by aeromagnetic data, J. Volcanol. Geotherm. Res.82, 239–247.

Gao, Y., P. Wang, S. Zheng, M. Wang, Y. Chen, and H. Zhou (1998).Temporal changes in shear-wave splitting at an isolated swarm ofsmall earthquakes in 1992 near Dongfang, Hainan Island, southernChina, Geophys. J. Int. 135, 102–112.

Hellweg, M. P., P. Spudich, J. B. Fletcher, and L. M. Baker (1995). Stabilityof coda Q in the region of Parkfield, California: the view from theUSGS Parkfield dense seismograph array, J. Geophys. Res. 100,2089–2102.

Hiramatsu, Y., N. Hayashi, and M. Furumoto (2000). Temporal changes incoda Q�1 and b value due to the static stress change associated withthe 1995 Hyogo-ken Nambu earthquake, J. Geophys. Res. 105, 6141–6151.

Hyppolite, J., J. Angelier, and F. Roure (1994). A major change revealed

by Quaternary stress patterns in the southern Apennines, Tectono-physics 230, 199–210.

Jin, A., and K. Aki (1986). Temporal changes in coda Q before the Tang-shan earthquake of 1976 and the Haicheng earthquake of 1975,J. Geophys. Res. 91, 665–673.

Jin, A., and K. Aki (1989). Spatial and temporal correlation between codaQ�1 and seismicity and its physical mechanism, J. Geophys. Res. 94,14,041–14,059.

Li, Y. G., T. L. Teng, and T. L. Henyey (1994). Shear-wave splitting ob-servations in the northern Los Angeles Basin, southern California,Bull. Seism. Soc. Am. 84, no. 2, 307–323.

Liu, Y., S. Crampin, and I. Main (1997). Shear-wave anisotropy: spatialand temporal variations in time delays at Parkfield, central California,Geophys. J. Int. 130, 771–785.

Miller, V., and M. Savage (2001). Changes in seismic anisotropy aftervolcanic eruptions: evidence from Mt. Ruapehu, Science 293, 2231–2233.

Muir-Wood, R. (1994). Earthquakes, strain-cycling, and the mobilizationof fluids, in Geofluids: Origin, Migration, and Evolution of Fluids inSedimentary Basins, J. Parnell (Editor), Geological Society SpecialPublication 78, 85–98.

Peacock, S., S. Crampin, D. C. Booth, and J. B. Fletcher (1988). Shearwave splitting in the Anza seismic gap, southern California: temporalvariations as possible precursors, J. Geophys. Res. 93, 3339–3356.

Peng, J. Y., K. Aki, B. Chouet, P. Johnson, W. H. K. Lee, S. Marks, J. T.Newberry, A. S. Ryall, S. W. Stewart, and D. M. Tottingham (1987).Temporal change in coda Q associated with the Round Valley, Cali-fornia, earthquake of November 23, 1984, J. Geophys. Res. 92, 3507–3526.

Person, M., and L. Baumgartner (1995). New evidence for long-distancefluid migration within the Earth’s crust, Rev. Geophys. 33 (Suppl.)6152–6174.

Principe, C., M. Rosi, R. Santacroce, and A. Sbrana (1987). Explanatorynotes to the geological map, in Somma-Vesuvius, R. Santacroce (Ed-itor), Quad. Ric. Sci. 114, 11–51.

Rojstaczer, S., and S. Wolf (1992). Permeability changes associated withlarge earthquakes: an example from Loma Prieta, California, Geology20, 211–214.

Rosi, M., R. Santacroce, and M. F. Sheridan (1987). Volcanic hazard, inSomma-Vesuvius, R. Santacroce (Editor), Quad. Ric. Sci., 1141, 197–234.

Saccorotti, G., R. Maresca, and E. Del Pezzo (2001). Array analyses ofseismic noise at Mt. Vesuvius Volcano, Italy, J. Volanol. Geotherm.Res. 110, 79–100.

Santacroce, R. (1983). A general model for the behavior of the Somma–Vesuvius volcanic complex, J. Volcanol. Geotherm. Res. 17, 237–248.

Sato, H., and M. C. Fehler (1998). Seismic Wave Propagation and Scat-tering in the Heterogeneous Earth, Springer, New York.

Scarpa, R., F. Tronca, F. Bianco, and E. Del Pezzo (2002). High resolutionvelocity structure beneath Mount Vesuvius from seismic array data,Geophys. Res. Lett. 29, no. 21, 2040, doi 10029/2002GL015576.

Sibson, R. H. (1994). Crustal stress, faulting, and fluid flow, in Geofluids:Origin, Migration, and Evolution of Fluids in Sedimentary Basins,Parnell (Editor), Geological Society Special Publication 78, 69–84.

Tselentis, G. A. (1997). Evidence for stability in coda Q associated withthe Egion (central Greece) earthquake of 15 June 1995, Bull. Seism.Soc. Am. 87, 1679–1684.

Udias, A. (1999). Principles of Seismology, Cambridge U Press, New York.Wang, J. H., T. L. Teng, and K. F. Ma (1989). Temporal variation of coda

Q during Hualien earthquake of 1986 in eastern Taiwan, Pageoph130, 617–634.

Wyss, M. (1985). Precursors to large earthquakes, Earthquake Pred. Res.3, 519–543.

Wyss, M., K. Shimazaki, and S. Wiemer (1997). Mapping active magma

452 E. Del Pezzo, F. Bianco, S. Petrosino, and G. Saccorotti

chambers by b-values beneath the off-Ito volcano, Japan, J. Geophys.Res. 102, 20,413–20,422.

Zatsepin, S. V., and S. Crampin (1997). Modelling the compliance ofcrustal rock, I. Response of shear wave splitting to differential stress,Geophys. J. Int. 129, 477–494.

Zollo, A., P. Gasparini, J. Virieux, H. Le Meur, G. De Natale, G. Biella,E. Boschi, P. Capuano, R. De Franco, P. Dell’ Aversana, R. De Mat-teis, I. Guerra, G. Iannaccone, L. Mirabile, and G. Vilardo (1996).

Seismic evidence for a low-velocity zone in the upper crust beneathMt. Vesuvius, Science 274, 592–594.

INGV—Osservatorio VesuvianoVia Diocleziano 32880124 Napoli, Italy

Manuscript received 15 July 2003.