The present-day seismicity variations in the Kuril-Kamchatka seismic zone

ISSN 07420463, Journal of Volcanology and Seismology, 2010, Vol. 4, No. 6, pp. 367377. Pleiades Publishing, Ltd., 2010.Original Russian Text G.A. Sobolev, 2010, published in Vulkanologiya i Seismologiya, 2010, No. 6, pp. 314.

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INTRODUCTION

In accordance with a longterm forecast [23], a largeearthquake is to be expected in Kamchatka in the nearfuture capable of causing shaking of intensity IX in thetown of PetropavlovskKamchatskii. Strengthening measures are being taken beforehand. More measures forreducing the impact of this impending earthquake requirea refined time of the occurrence of this event. One line ofresearch for solving this problem is to determine successive phases in the evolution of the future rupture zone.The phases of seismic quiescence and increased foreshock activity were identified in the source zones of several Kamchatka earthquakes [12, 13] using the RTLmethod [13]; this provided a real intermediateterm forecast of the magnitude 7.8 Kronotskii earthquake ofDecember 5, 1997, the largest for the last 30 years.Another independent forecast of this earthquake wasbased on an analysis of several seismological parametersand geodetic measurements [22].

It was found recently that the evolution of the seismicprocess prior to the Kronotskii earthquake and the magnitude 8.2 Simushir event of November 15, 2006 at theKurils followed the same pattern [17]. A few years beforean earthquake, a seismic quiescence was observed in anarea about 200 km across around the future epicenter. Anarea of subsequent activity about 100 km across enclosedthe future epicenter. The time interval between the earthquake and the subsequent quiescent and activity phaseswas longer than 1 year. A few days before the earthquakethe rate of seismic events was observed to increase nearthe epicenter; the magnitudes of some of these were inexcess of 5 and this process was accompanied by the

appearance of numerous clusters composed of eventswith magnitudes 45.

The methods in use for predicting the location, timeand size of a future earthquake can only be improvedupon if new knowledge is acquired on the physics of theseismic process. One promising line of research consistsin studying the variation of lowmagnitude seismicity,which is related to the stresses in a seismic region. Oneshould also take into account the effects of recent earthquakes in the region of study or in adjacent regions asthese effects are capable of either diminishing or increasing the time until the future large seismic event. Migrationand stress rearrangement came into focus when it wasfound that the Landers, US earthquake affected the seismicity of adjacent areas in California [26].

The present study is an attempt at assessing thechanges in the state of stress in Kamchatka that resultfrom the large earthquakes mentioned above, viz., theKronotskii and Simushir events. No methods for directmeasurement of stresses are available at present, whileindirect techniques for recording ground deformationcannot be applied to the seismic zone that is underwateroff the eastern coast of Kamchatka. It remains to assumethat the level of stresses is reflected in seismicity variations.

THE DATA

We studied seismicity variations in six areas along theeastern coast of Kamchatka extending at an angle of 38relative to the north (Fig. 1). The boundaries that separatethe areas are vertical to the ground surface; the boundariesthat are parallel to the Kamchatka coast dip landward at

The PresentDay Seismicity Variationsin the KurilKamchatka Seismic Zone

G. A. SobolevEnterprise of the Russian Academy of Sciences, Schmidt Institute of Physics of the Earth, Russian Academy of Sciences,

Moscow, 123995 Russiaemail: [email protected], [email protected]

Received January 18, 2010

AbstractThis study is concerned with seismicity variations in Kamchatka and the Kuril Islands for the period19622009; the effects of large earthquakes on the seismicity of adjacent areas are taken into account. The 1997Kronotskii earthquake was followed by seismicity decreases in most areas over Kamchatka, which is presumablyrelated to decreased tectonic stresses. After the 2007 Simushir earthquake synchronization and periodicities inseismicity were identified, indicating increased instabilities and the likelihood of a large event in Kamchatka inthe near future. The instability of seismic regions is discussed within the framework of the theory of nonequilibrium dynamical systems. We suggest successive phases in the occurrence of seismological precursors.

DOI: 10.1134/S0742046310060011

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an angle of 50. It is in this band that most earthquakes ofthe earthquakegenerating zone are concentrated. Eacharea is 100 km along the northeast direction and 100 kmacross it. We used the regional Kamchatka catalog for theperiod January 1, 1962 to July 30, 2009 as reported by theKamchatka Branch of the Seismological TechniqueTesting Team at the Geophysical Service of the Russian Academy of Sciences. The reporting is complete fromS.A. Fedotovs energy class Ks 8.5 (M > 2.6) upward [20].

The earthquakes to be examined are in the depth range20100 km. It was previously shown [13] that theseismicity variations at these depths reflect the precursory process of large earthquakes. The aftershocksof the s > 12 earthquakes were eliminated from the catalog using the program [10] in order to be able to analyzethe background seismicity. Earthquakes that are locatednortheast of area 6 are not included in the present analysis, because the seismicity distributions over depth and

over the landward dip are different for these events fromthose in the band of analysis. The final catalog thus prepared for analysis includes 10 876 seismic events.

THE METHODS AND THE RESULTS

Figure 2 shows the variation of earthquake rates forsuccessive 10day periods in each of the six areas. Thesedata have been smoothed by a Gaussian filter (1). If X(t) isan arbitrary bounded, integrable signal, then one can find

the mean ) at time t with scale parameter H > 0:

(1)

where () is an arbitrary bounded, symmetrical, integrable function, which is called the averaging kernel. If

X t H( )

X t H( ) X t H+( ) ( ) ( ) ,d

+

d

+

=

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Fig. 1. Earthquakes in six areas covering a band of the Kamchatka seismic zone.


THE PRESENTDAY SEISMICITY VARIATIONS 369

() = exp(2), then the quantity is a Gauss

ian trend with the averaging parameter (radius) H (6,27]. The thin lines show the results of smoothing by theGaussian filter with averaging radius H = 50 days, whichgives an effective suppression of highfrequency fluctuations with periods below 100 days (~0.3 years); thesolid lines are the results of smoothing with averagingradius H = 550 days to suppress periods below1100 days (~3 years). Arrows mark the occurrencetimes of the December 5, 1997 Kronotskii earthquake(M = 7.8) occurring in area 6 (Fig. 1) and of the Simushir,Kurils earthquake of November 15, 2006 (M = 8.2).

X t H( ) Calculations of the correlation for seismicity level thatwere carried out by trying all pairs of the six data serieswith an averaging radius of 50 days showed the following.Significant correlation coefficients were found betweenseries 5 and 6 (R = 0.3) and 3 and 4 (R = 0.24) at 95% significance level 0.16. The coefficients were observed toincrease with increasing averaging radius. For the averaging radius equal to 550 days we found a positive correlation between series 2 and 3 and a negative correlationbetween series 6 in the northeast and series 2, 3, 4. Fromthis analysis it follows that the seismicity variations at thecenter of the band of analysis in Kamchatka (areas 24)were different from those in the northeastern (areas 5 and

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Fig. 2. Variations in earthquake rate N in 10day intervals for six areas of Kamchatka (see Fig. 1). Arrows mark the occurrencetimes of the 1997 Kronotskii, Kamchatka and of the 2006 Simushir, Kuril Is. earthquakes.

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6) and the southwestern (area 1) margins. This probablystems from differences in geologic and tectonic structure.

Visual inspection of the plots in Fig. 2 reveals the following: (1) the seismicity increase in area 6 was observedafter a comparatively deep earthquake (August 17, 1983,55.64N, 161.53E, = 97 km, s = 15.4, M = 7.0),which occurred in the northwest of the area; (2) the seismicity level had been increasing in all areas except area 4until the mid1980s, when it began to decrease until 2007;(3) an appreciable drop in seismicity level took place afterthe Kronotskii earthquake in all areas except the southernmost ones; (4) areas 24 showed a gradual increase inseismicity level since 2007.

One of the main goals of the present study was toexamine the possible effects of large earthquakes on theseismicity in adjacent areas. If such an effect is detected,this may serve to indicate a change in the state of stress.We did a statistical analysis in which we took three samples of events, each of which lasted 2500 days, in each ofthe areas 1 through 6; these covered the following timeintervals: (I) 1984.2581991.066, (II) 1991.0671997.902, (III) 2000.0082006.816 The first two are inthe period before the Kronotskii earthquake, the thirdsamples cover the time interval between the Kronotskiiand the Simushir earthquakes. The starting point of samples III was shifted by 2 years after the Kronotskii earthquake in order to remove the effects due to the aftershocksof the latter event, which lasted 1.3 years, in accordancewith calculations following [7, 10]. Each sample included250 10day values of seismicity level. Testing the samplesfor randomness showed that the underlying distributions

were different from a normal distribution in half of thecases. Consequently, we used nonparametric tests [3].

The following results were obtained at significancelevels higher than 95%. In all six areas we found decreasedseismicity levels in samples III compared with II and Iusing the Wilcoxon and Van Der Warden tests (for differences between the medians), as well as by the Smirnov Dtest (integral differences) [3]. This indicates decreasedseismicity over all of Kamchatka (within the band of analysis) following the Kronotskii earthquake. In most of thecases, although the result was not as decisive, differenceswere found by the above tests between samples II and Icorresponding to a general lowering of seismicity levelafter the mid1980s. The plots in Fig. 3 help determinethe degree of this seismicity decrease. Open symbols arefor samples II (1991.0671997.902), the filled symbolsare for samples III (2000.0082006.816); the amplitudeshave been normalized relative to sample I (1984.2581991.066). The triangles show the means and the circlesthe medians. The differences along the horizontal axis arethose between the centers of areas 15 and the center ofarea 6, where the Kronotskii earthquake occurred. Allpoints in the plots are below 1, that is, a seismicitydecrease began in all these areas prior to the Kronotskiiearthquake (open symbols) and went faster after thatevent (filled symbols). The decreases were different in different areas. An especially large drop is recorded in area 2(the southern Avacha Bay).

A similar analysis was performed for variations inearthquake energy class. The resulting time series forareas 1 through 6 generally showed the same seismicityfeatures as those found in the series of earthquake rates.Nevertheless, the variance of variation amplitudes for theenergy class series was larger by a factor of a few times. Itwas concluded that the state of stress is best estimatedfrom earthquake rates rather than from earthquakeenergy, as the former method tends to reduce the nonstationarity of the seismicity that is due to the effects of largerearthquakes.

The next step was to test the hypothesis of seismicitychanges in Kamchatka following the Simushir earthquake at the Kuril island arc. The time interval thatremained until the end of the catalog (2006.8172009.551) was short, so it was possible to compare samples of 100 values only (1000 days). The various testsapplied to the data did not reveal significant differences, either before or after the Simushir earthquake.

However, several noteworthy effects were stilldetected. The Simushir earthquake produced synchronization between seismicity levels in Kamchatka. This phenomenon was investigated using the robust wavelet coherence measure between all six time series and between various choices of these series. The method was proposed byLyubushin [5] and was used earlier to estimate the correlation between microseisms recorded at different seismicstations [15]. A scaledependent measure of coherentbehavior was constructed in a moving time window of365 values (3650 days).

Am

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Fig. 3. Variations in the level of mathematical expectation(triangles) and medians (circles) before the Kronotskiiearthquake (open symbols) and after it (filled symbols) inareas as far as 500 km from the epicenter of that earthquake. For the other notation see main text.



Analysis is done for each position of the time window(when moved by one value to the right) independently ofthe analysis in the other windows. Prior to the waveletdecomposition of fragments of the time series under analysis in a given time window, we performed the followingoperations on each of these series: (i) the common lineartrend was eliminated within the current time window; (ii)a sampling estimate of the standard deviation was found,and each value was divided by the estimate; (iii) raw values were replaced in the analysis with differences betweenadjacent values of the time. The robust wavelet coherencemeasure is given by

(2)

where is the correlation coefficient between series kand the other series and and are the end time of thecurrent interval and the degree of detail between thewavelet coefficients (the Haar wavelets were used),respectively. The greater the degree of detail, thedeeper is the averaging over past time windows.

The coherence measure can assume values between 0and 1. The greater the values of (, ), the stronger theoverall correlation is between the processes under analysis. Figure 4 shows plots of the coherence measure (, )for seismicity variations in all six areas of Kamchatka(top) and in areas 24. The coherence became greaterafter the Simushir earthquake (marked by the arrow). Theeffect is the most pronounced when all areas are compared, but is not as persistent as desired. For example,combined analysis of variations in three areas (24) gavespurious peaks that are difficult to relate either to previous or future large earthquakes. We note that synchronization of fluctuations is used as a criterion for increasedinstability in catastrophe theory [1].

We also did calculation to detect periodicities, if any,in earthquake occurrence for the regions here examined.A method for detecting hidden periodicities in a pointprocess was used. In our case we used the catalog with noaveraging over 10day windows in order to use the fullinformation contained in the data. The method was putforward in [4], and it helped reveal anomalies beforeKamchatka earthquakes [14]. We considered a modelof earthquake rate in current time t that was assumed toinvolve a harmonic component :

(3)

where the amplitude a, 0 a 1, the phase angle , [0, 2], and the factor 0 (which describes the Poisson part of the rate) are model parameters. The increment to the log likelihood of a point process involvinga harmonic component of a given frequency is

(4)

,( ) vk ,( ) ,k 1=

q

=

vk

t( ) 1 acos t +( )+( ),=

L a , ( )ln 1 a ti +( )cos+( )lnti

=

+ N T/ T a T +( )sin ( )sin( )+[ ]( ),ln

where ti is the sequence of times of detected local peaksin the signal within the window; N is the number ofthese peaks; and T the length of the time window.Maximum values of (4) show which values of the frequencies give the maximum gain in the increment oflog likelihood compared with a pure Poissonsequence, which indicates the presence of hiddenperiodicities in the seismicity under analysis.

Let be the time of the rightmost end of a moving timewindow with fixed length TW. The results were visualizedin the form of a frequencytime diagram with the arguments (, ); the window length was increased logarithmically in order to provide sufficient statistics for identification of low frequency components (Fig. 5). From thisfigure it follows that periodic oscillations at periods of1 year or less occurred in area 5 both before and after theKronotskii earthquake and after the Simushir event.

It was of interest to see whether these effects were feltin the area of the Kuril seismic zone. We used theregional catalog for the KurilSeaofOkhotsk regionthat was prepared by the Sakhalin Branch of the GS RASfor the same period of time as that for Kamchatka, viz.,January 1, 1962 through July 30, 2009. Our estimatesshowed that the catalog is complete for energy class (afterS.L. Solovev and O.N. Soloveva) 10 (M > 3.8) [18].Proceeding by analogy with Kamchatka, we examineearthquakes with depths of focus of 20100 km. Figure 6shows a band of earthquakes divided into four areas from

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Fig. 4. Wavelet coherence measure arising in a combinedanalysis of seismicity in six areas of Kamchatka (16) andthree areas (24) in central Kamchatka (see Fig. 1); thearrow marks the occurrence time of the 2006 Simushirearthquake.

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southwest to northeast. Since the data are less numerous(because of a higher magnitude of complete reporting),the sizes of the areas in the SWNE direction wereincreased compared with those in Kamchatka. We alsotook into account the positions of four M 8 earthquakes that occurred in the Kurils during the time periodof study: October 13, 1963, s = 17.2 (area 2); August 11,1969, Ks = 17.6 and October 4, 1994, Ks = 17.4 (area 1);and November 15, 2006, Ks = 17.0 (area 3). Their epicenters are marked by stars in Fig. 6. The dimensions ofareas 1, 2, 3, and 4 in the SWNE direction were 240,330, 260, and 300 km, respectively. The length in thetransverse direction was 100 km with the angle of dipequal to 50 for the plunging slab. The total number ofearthquakes for these four areas was 6471 events aftereliminating the aftershocks of Ks > 14 earthquakes.

Figure 7 presents the series of earthquake rates in successive 10day intervals for each of the four areas.Smoothing with a Gaussian filter (1) was carried out withthe same averaging radii as for Kamchatka; thin lines arefor H = 50 and the solid lines for H = 550. Arrows markthe times of occurrence for the large earthquakes listedabove. Visual inspection of the plots suggests the following: the 1969 and 1994 earthquakes occurred in area 1after an evident seismicity decrease; the Simushir earthquake of 2006 (area 3) occurred during a seismicity ratethat at least cannot be called high; no inference is possiblefor the 1963 event, as the sufficiently complete catalogdates from 1962 only.

We used the same method as in the case of Kamchatkato calculate the robust wavelet coherence measure betweenthe series (2) and the frequencytime diagrams fordetecting hidden periodicities for individual areas (4). Itfollows from Fig. 8 that the seismicity synchronizationfollowing the 1994 Shikotan earthquake (area 1) wasidentified both by a combined analysis of the time series

for all four areas and by examining areas 24 without theseismicity of area 1 taken into account. After the Simushirearthquake, evident synchronization was only detected bythe analysis of areas 24. This indicates that the presentidentification of the effect is unstable, possibly due to thefollowing reason. As mentioned above, the window ofanalysis according to (2) was 3650 days (~10 years);shorter windows provide insufficient data. This meansthat, when area 1 was included, the catalog may have beendistorted due to the elimination of the aftershocks of theOctober 4, 1994 Shikotan earthquake.

Figure 9 shows a frequencytime diagram based onthe time series of area 3. One clearly sees periodic effectsin the earthquake sequences before and after the Shikotanand Simushir earthquakes. The spectral peaks occupy awide range between a fraction of a year to 2 years (with asampling window of 5 years). Anomalous effects were alsonoted for the other areas, but the period bands are not aswell pronounced.

DISCUSSION OF RESULTS

Sobolev [17] found that the recent large earthquakesin the Russian Far East, the Kronotskii, Kamchatka eventof 1997 and the 2006 Simushir, Kuril Is., evolved according to a common scenario. The successive phases wereseismic quiescence, foreshock activity increase, a criticalacceleration of seismicity, and cluster generation. Thepresent study shows that these large earthquakes causedchanges in seismicity rates in adjacent areas as far as1000 km from the epicenters of these earthquakes; thisseems to have been related to changes in the level of tectonic stresses. As well, one notes an analogy between synchronization and periodicity of the seismic process beforeand after large earthquakes in areas of the same greatextent. This indicates a metastable state of crustal vol

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Fig. 5. Frequencytime diagram with indication of a periodicity of earthquake occurrence in area 5 of Kamchatka (dark bands)before the 1997 Kronotskii event and after the 2006 Simushir earthquake (the occurrence times are marked by arrows). On theright is the lnL scale.

Simushir event event



umes, which may be a precursor of a seismic catastrophe.

We will discuss one characteristic, viz., the reliabilityof detecting this effect before a specific earthquake. If theeffect appeared only once before an earthquake duringthe last segment of the time period of study, then we willconsider it to be reliable in a preliminary manner. Thedata available at present do not lend themselves to theconclusion that synchronization and periodicity in seismicity fluctuations are reliable precursors. It was foundthat periodicity and synchronization of seismic eventsand microseisms may appear and disappear several times,which also takes place after large teleseismic events orforeshocks [15, 32].

The effects investigated here belong to the class ofevents that is peculiar to the dynamics of nonequilibriumsystems [24, 28]. The causes of their appearance may bedue to external or internal factors relative to the solidEarth. The processes in the external shells of the Earth(the atmosphere and the ionosphere) involve both chaotic and quasiperiodic components. We shall assume thatat least some parts of a seismic zone are in a metastablestate during certain intervals of time and that the processes occurring there can be characterized by propertiesof deterministic chaos [8]. Suppose Eqs. (5) and (6)

describe timedependent variations in dynamic chaoticsystems in the external and internal shells of the Earth:

dx/dt = F(x) + K(x, y), (5)

dy/dt = G(y) + L(y, x). (6)

The variables x and y are vectors of the same or different dimensions and the functions and L characterizethe coupling between the parameters of the systems. Suppose 0 is the coefficient of coupling between air pressure and deformation in the seismic zone. Then dynamicchanges in the atmosphere will affect the seismicity. Chaotic systems of this type occur (5, 6), whose oscillationamplitudes vary chaotically over time from a minimum toa maximum while remaining finite; their attractors arerepresented by cyclic orbits [30]. Effects of phase synchronization manifest themselves in such systems. Synchronization of the dynamics of the systems may appear andthen be suspended, but again may be stable in certain timeintervals (a negative Lyapunoff exponent) [25]. LetEq. (7) describe a chaotic system under the action of periodic oscillations:

dx/dt = F(x) + KP(t). (7)

Suppose we have to deal with oscillations in the lithosphere, while the coefficient K indicates the degree ofinfluence on these oscillations on the part of an external

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Fig. 6. Earthquakes in four areas in the band of analysis, Kuril Is.

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source. The time series of oscillation amplitude that areexhibited by some parameters of systems (5, 6, 7) thatcontain chaotic and periodic components are presentedschematically by curves 1 and 2 in Fig. 10. The regionof their synchronization in the frequency band (diagram 3 in Fig. 10) is characterized by the following properties [28]: the region is not seen for couplingcoefficients 0 below a certain threshold and itexpands as K increases.

We can suppose that, as a macroinstability (earthquake) is approached, the metastable region in the lithosphere (the value of K) becomes more sensitive to theaction of an external source, while the synchronization ofseismicity fluctuations in areas as far away from oneanother as some thousands of kilometers indicates a common source. It should be noted that Saltykov et al. [9] and

Sobolev and Lyubushin [32] described appearing and disappearing phase synchronization of high frequency seismic noise and microseisms. The occurrence of rhythms isalso a phenomenon that frequently occurs in the evolution of nonequilibrium systems [8, 29]. In this connectionit is not ruled out that the source of the periodic oscillations that are seen in Figs. 5 and 9 is inside the metastableregions of the lithosphere.

It follows from Figs. 4, 5, 8, and 9 that synchronizationand periodic fluctuations do not invariably terminate in alarge earthquake (catastrophe). These effects may beviewed as signs of instabilities in the seismic zone of study,but not as reliable precursors of a future seismic event.One has to look for other predictive features as well.

Turning to a practical evaluation of the current seismic situation in Kamchatka and bearing in mind the high

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Fig. 7. Variations in seismicity rate N in 10day intervals for four areas of the Kuril island arc (see Fig. 6). Solid arrows mark theoccurrence times of M 8.0 earthquakes.



likelihood that a damaging earthquake will occur near thetown of PetropavlovskKamchatskii [23], we show a diagram of successive seismological precursors (Fig. 11).Phases IV cover almost the entire interval of seismicityincrease before a large earthquake; Fedotov [19] calledthis the third phase of a seismic cycle with typical durationT 15 years before M > 7.7 earthquakes.

Phase I involves a gradual increase in seismicity rateand occupies about 2/3T. The results of studies using theRTL prediction method suggest a quiescence phase IIand foreshock activity increase III. These phases were

clearly seen before four M > 7 earthquakes in Kamchatka[13], as well as before the Kobe, Japan M > 7 event [31],the Neftegorsk and Uglegorsk M 7 earthquakes inSakhalin [16], and before the Simushir, Kuril Is., M > 8.2event [17]. At the times of passage from phase II to phaseIII, successful intermediateterm forecasts were developed for the December 5, 1997 Kronotskii, Kamchatkaand the November 11, 2006 Simushir, Kuril Is. earthquake. Phase II lasted ~23 years before M 7 earthquakes, the duration of phase II was ~1 year. However,these estimates are based on sparse data (eight events). Inall the cases listed above, the large earthquake did notoccur at once after the termination of phase III. Forexample, for the two largest earthquakes of those investigated, the M 7.8 Kronotskii and the M 8.2 Simushirevents, the delays (phase IV) were 0.9 and 2.7 years. PhaseIV frequently showed anomalous effects of synchronization and periodicity of seismic oscillations in some areasof the seismic zone. The former are marked by trianglesand the latter by sinusoidal segments in Fig. 11.

The terminal phase V involves multiple clusters ofseismic events (filled ellipses) and a critical acceleration ofseismicity rate around the future hypocenter. The duration of that phase before the Kronotskii and Simushirearthquakes was less than 1 month.

Clusters were identified following a simple, but sufficiently effective rule. It was assumed that a cluster is theoccurrence of two or more earthquakes if their hypocenters and the differences in time of occurrence and theenergy satisfy the following requirements. The distancebetween the hypocenters should be below the criticalvalue given by

Rcr = 3L + C. (8)

Here, L is the rupture length found from the energyclass of the earthquake. The factor 3 is in agreement withthe concentration criterion of fracture when applied to

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YearFig. 8. Wavelet coherence measure arising from a combined analysis of seismicity for four (14) and three (24)areas along the Kuril Is.; arrows mark the occurrence timesof the 1994 Shikotan and 2006 Simushir earthquakes.

Fig. 9. Frequencytime diagram with indication of a periodicity in earthquake occurrence in area 3 (Kuril Is., dark bands) beforethe 1994 Shikotan earthquake and after the 2006 Simushir earthquake (marked by arrows). On the right is the LnL scale.

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seismology [11, 2]. The term C allows for hypocenterlocation uncertainty. The time between two events shouldbe below the critical value given by

(9)

where = 0.5, = 0.065; Ki is the energy class of current events, and K0 = 8.

The interval of critical seismicity acceleration wasfound from the deviation of the rate of seismic strain

Tcr 10 Ki K0( )

=

buildup from a linear trend in an area of interest as givenby [33, 24]

Q(t) = A B(tf ti)m, (10)

where Q(t) ~ E1/2 is the Benioff strain; E is the energyof current seismic events; tf is the time of a large earthquake; ti is the current time; and A, B, and m are freeparameters.

Following Fig. 11, one can infer that the seismic situation in Kamchatka is characterized by the following features. A seismic quiescence (phase II) was identified forthe year 2002 in southern Kamchatka after the Kronotskiiearthquake using the RTL method. The quiescence wascentered at 51.5N, 158.5E. It has decreased andincreased in magnitude several times since that time.Phase IV began in 2007, after the Simushir, Kuril Is.earthquake. There were the effects described above, viz.,synchronization and periodicities in seismicity fluctuations. However, an increased number of clusters and thecritical acceleration of the seismicity rate (see (10)) havenot yet been detected (the transition to phase V).

CONCLUSIONS

The seismicity rate decreased in most areas of Kamchatka following the 1997 Kronotskii earthquake, presumably because of decreased tectonic stresses.

Synchronization and periodicities in seismicity rateappeared after the 2006 Simushir earthquake, indicatingincreasing instability and a high likelihood of a largeearthquake in Kamchatka in the near future.

Nevertheless, no reliable shortterm precursors (withadvance times below 1 month) have yet (November 2009)been detected for an M ~8 earthquake in Kamchatka.

Near realtime monitoring of the seismic situation isrequired in order to have a chance to provide advancedetection of the effects that are peculiar to the terminalphase V in the evolution of a future rupture zone.

ACKNOWLEDGEMENTS

The author is grateful to A.A. Lyubushin, who kindlylent me a program for calculating several parameters, andto K.N. Akatova for technical aid. This work was supported by the RAS Presidium Program no. 16.

REFERENCES

1. Gilmore, R., Catastrophe Theory for Scientists andEngi1.Gilmore, R., Catastrophe Theory for Scientists and Engineers, New York: Wiley, 1981.

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3. Kulaichev, A.P., Metody i sredstva analiza dannykh vsrede Windows. Stadia 6.0 (Methods and Tools for DataAnalysis in the Windows Environment: Stadia 6.0),Moscow: NPO Informatika i Kompyutery, 1996.

Time

K

KOs

Synchronization

1

2

3

Fig. 10. Synchronization and periodicities in seismicityrate for various Kamchatka areas: (1, 2) time series thatcontain chaotic and periodic components, (3) synchronization diagram.

Longte

rm seism

icity

increase

Quiescence

For

esho

ck a

ctiv

ity

incr

ease

Delay

Cri

tica

lac

cele

rati

on

I II III IV V

Fig. 11. Successive seismological precursors: synchronization effects are shown by triangles, periodic fluctuations bysinusoidal segments, and clusters of seismic events by filledellipses. The arrow marks the occurrence time of a largeearthquake.



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The present-day seismicity variations in the Kuril-Kamchatka seismic zone