Geophysical Journal International

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1 Geophysical Journal International Geophys. J. Int. (2012) doi: /j X x Low-frequency and broad-band source models for the 2009 L Aquila, Italy, earthquake Natalia Poiata, 1 Kazuki Koketsu, 1 Alessandro Vuan 2 and Hiroe Miyake 1 1 Earthquake Research Institute, University of Tokyo, Yayoi, Bunkyo-ku, Tokyo , Japan. poiata@ipgp.fr 2 Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Borgo Grotta Gigante 42/c, 34010, Sgonico, Trieste, Italy Accepted 2012 July 1. Received 2012 May 23; in original form 2011 November 10 SUMMARY The 2009 L Aquila, Italy, earthquake (M w 6.3) produced an unprecedented number of seismological records for a normal faulting event, and hence represents an important case study of damaging moderate magnitude earthquakes occurring in densely inhabited areas. We have investigated the source process of the 2009 L Aquila earthquake in both the low- and broadband frequency ranges by analysing the teleseismic and strong motion data. A low-frequency (<0.5 Hz) source model has been determined by waveform inversion of teleseismic and nearfield strong motion data, yielding slip distributions with a major asperity located about 8 km southeast of the hypocentre. The broad-band ( Hz) source characteristics were estimated using the empirical Green s function method providing the strong motion generation area of about 42 km 2 located southeast of the hypocentre below the village of Onna. This coincides with the location of the asperity from the inversion analysis, indicating that the low-frequency and broad-band ground motions produced during the earthquake were generated at similar locations on the fault plane. The position of the strong motion generation area also correlates well with the distribution of observed macroseismic (MCS) intensities reported by INGV. The maximum macroseismic intensities of IX X were reported southeast of the epicentre, with an intensity of X measured in Onna. The source properties of the 2009 L Aquila mainshock reveal the estimated size of the strong motion generation area to be in agreement with predictions made using empirical source scaling relation for inland crustal earthquakes, implying a stress drop of approximately 10 MPa. This further indicates that the 2009 L Aquila earthquake involved a stress drop similar to that of previously recorded earthquakes in the Central and Southern Apennines. Key words: Time-series analysis; Earthquake ground motions; Earthquake source observations; Body waves. GJI Seismology 1 INTRODUCTION The L Aquila earthquake (Fig. 1a) struck the Abruzzo region of the Central Apennines, Italy, on 2009 April 6 at 01:32:40 UT. The Istituto Nazionale di Geofisica e Vulcanologia of Italy (INGV) reported that the earthquake was generated by normal faulting on a fault system running along the axis of the Apennine mountains and had a moment magnitude (M w ) of 6.3. The location of the hypocentre was later estimated to lie 2 km west of the city of L Aquila at N, E at a depth of 9.5 km (INGV 2009). This event caused extensive damage to the city of L Aquila and tens of villages in the Abruzzo region in the middle of the Aterno Valley. According to Now at: Seismology Laboratory, Institut de Physique du Globe de Paris (CNRS-UMR 7154 Paris Sorbonne Cité), 1 rue Jussieu, Paris Cedex 05, France. different sources (e.g. Italian Civil Protection Department; Akinci et al. 2010) most of the damage was concentrated within the city of L Aquila, located close to the hypocentre, and the villages of Castelnuovo, Onna and Paganica located further southeast. In spite of this earthquake not having been the largest known to have occurred in the Apennines, it was certainly the most disastrous event of the last century (Tertulliani et al. 2009). As of 2009 May, 305 people had lost their lives and over 1500 had been injured. This represents the highest death toll due to an earthquake in the European Union since the 1980 Irpinia event and was accompanied by the highest economic losses due to seismic activity since the 1999 Athens earthquake (Papanikolaou et al. 2009). The 2009 April 6 L Aquila mainshock was the strongest event in a seismic sequence that had started several months beforehand. Foreshock activity began in 2008 October and concluded with an event of magnitude M w 4.4 on 2009 March 30 (Chiarabba et al. 2009). Extensive aftershock activity that followed the mainshock C 2012 The Authors 1

2 2 N. Poiata et al. Figure 1. (a) Distribution of strong motion stations (triangles) of the RAN network that recorded the 2009 L Aquila mainshock. The red star marks the epicentre. The colours of the triangles (corresponding to the colour scale left of the map) indicate the PGA values in cm s 2 recorded at each location. (b) and (c) Three-component (EW, NS and UD) acceleration and velocity time series of the 2009 L Aquila earthquake, recorded at the AQU and AQV near-fault stations located on the hanging-wall side of the source fault. extended northwest southeast over more than 30 km (Fig. 2). The number of earthquakes recorded during the foreshock aftershock sequence exceeded ( Of these, the two largest aftershocks happened on 2009 April 7 (M w 5.6), and 2009 April 9 (M w 5.4), to the south and north, respectively, of the mainshock s epicentre (Chiarabba et al. 2009). Normal faulting focal mechanisms, consistent with the overall NW SE extensional regime of the Apennines, have been determined for the mainshock and the largest events (M w > 4.1) in the foreshock aftershock sequence (Pondrelli et al. 2010; Herrmann et al. 2011). The results of field observations of coseismic surface faulting conducted by several groups (Falcucci et al. 2009; Boncio et al. 2010; Emergeo Working Group 2010), analysis of the geodetic data (InSAR interferograms Atzori et al. 2009; and GPS displacements Anzidei et al. 2009), and the distribution of the relocated aftershocks (Chiarabba et al. 2009) reveal that the mainshock was produced by rupture of the Paganica fault, a northwest southeast-striking and southwest-dipping Quaternary normal fault located east of the city of L Aquila. This structure had been mapped in previous studies (e.g. Boncio et al. 2004; Foglio CARG 2009), but had not been documented as having produced the latest Pleistocene or Holocene seismic activity. However, a high seismic risk in the region of L Aquila had been appreciated prior to the 2009 April 6 event. The area was designated as seismic zone 2 by the Italian Civil Protection Department, corresponding to a medium level of seismic hazard (Protezione Civile Nazionale 2006). The 2009 L Aquila mainshock and its aftershocks were recorded by several local and regional seismic networks providing an unprecedented number of seismological records for a normal faulting event. Generally speaking, the normal faulting events are sparsely represented in the existing databases of the recorded ground motions. Most of the records from the damaging or significant crustal earthquakes (especially the ones occurred in the inhabited areas) are corresponding to the events with the predominant strike-slip or reverse faulting mechanisms (e.g. Anderson 2010). These makes the studies of the source process of the 2009 L Aquila earthquake important for understanding and quantifying the seismic hazard posed by future such normal faulting events. The high socio-economic impact of the 2009 April 6 L Aquila earthquake and the large number of high-quality observational data produced by this event, attracted wide attention from the geophysical community. One important observation came from a comparison of the observed macroseismic effects of this earthquake and those of historical events in the L Aquila region. Resemblances in the distribution of largest intensities have been pointed out (Rovida et al. 2009; Tertulliani et al. 2009), and it has been further suggested that similarities exist in the temporal patterns of the foreshock aftershock sequences for these earthquakes (Tertulliani et al. 2009). These findings underline the fact that the 2009 L Aquila earthquake provides essential data for understanding seismicity in the area and thus interpreting past earthquake activity. Moreover, the 2009 L Aquila earthquake offers an important case study of the effects of damaging moderate-magnitude earthquakes occurring in areas of high population density. An in-depth analysis of the earthquake source process is indispensible for better understand the factors controlling ground motions, macroseismic effects and the relation between the causative fault and foreshock aftershock activity. Several previous studies have produced source models for the 2009 L Aquila mainshock by inverting either geodetic data alone (Atzori et al. 2009; Walters et al. 2009) or by performing joint inversion of GPS and strong motion data (Cirella et al. 2009). In this study, however, we have attempted to determine the source process of the 2009 L Aquila earthquake in both the low- and broad-band frequency ranges by analysing teleseismic and strong motion seismological datasets only. The low-frequency (<0.5 Hz) source model has been determined via waveform inversion of the teleseismic records and near-field strong motion data. The broad-band ( Hz) source characteristics have then been determined using the empirical Green s function technique. Here, we present a comparison of the derived source characteristics and their correlation with the observed spatial distribution of macroseismic intensities.

3 Source Models for the 2009 L Aquila Earthquake 3 Figure 2. Map showing the surface projection of the fault geometry for the 2009 L Aquila earthquake assumed in the inversion analysis (black rectangles). Blue triangles indicate the selected strong motion stations of the RAN network. The stations marked by grey rectangles were used for the empirical Green s function analysis (station AQK marked by the white triangle was used only in the EGF analysis). The focal mechanism of the mainshock determined in this study is illustrated together with the moment tensors of aftershocks used in the velocity structure modelling. The moment tensor of the empirical Green s function event is outlined in red. The red star indicates the epicentre of the mainshock, the black star outlined in red marks the epicentre of the empirical Green s function event, orange and blue stars correspond to the epicentres of significant foreshocks and aftershocks, respectively; orange and blue dots correspond to other foreshocks and aftershocks occurring in a 1 week period following the mainshock (from the INGV-CNT bulletin). The thick red line shows the location of observed coseismic surface ruptures modified after Boncio et al. (2010) and yellow squares mark the cities that suffered the largest damage. The schematic grouping of the strong motion stations on the basis of assumed velocity structure is indicated by the shading. The southern stations (violet) correspond to the CIA velocity model of Herrmann & Malagnini (2009), northern stations (grey) to the nncia velocity model of Herrmann & Malagnini (2009) and stations in Aterno Valley for which the velocity models were determined individually are marked by red. The rectangle marked by a dashed line corresponds to the extent of the near-source area presented in Figs 7(d), 9(d) and 13. Upper right inset: map of Italy with the L Aquila region marked by a black square. 2 LOW-FREQUENCY SOURCE PROCESS OF THE 2009 L AQUILA EARTHQUAKE It is possible to distinguish methods used to estimate the ground motions produced by an earthquake into three categories: theoretical, empirical and semi-empirical. All three are based on phenomena embodied in the representation theorem (Aki & Richards 1980). According to this theorem, the displacement generated by a shear dislocation on a fault can be described as a spatiotemporal convolution of slip on the fault, representing the source effect, with the partial derivatives of the Green s function, representing the earth response along the ray propagation path. In short, the representation theorem allows the displacements resulting from earthquake to be calculated everywhere if the slip on the fault is known. The estimation of an earthquake s source process by means of waveform inversion involves the calculation of realistic theoretical Green s functions. This significantly restricts the usable frequency

4 4 N. Poiata et al. range, and affects the resolution of the inversions. In general, source inversions accounting for broad-band ground motions over a wide range of epicentral distances are complicated by the need for accurate knowledge of wave propagation in geologically complex media. This represents substantial computational cost and requires detailed knowledge of the velocity structure in the area of interest. Consequently, earthquake source processes are typically studied in the low-frequency range (up to about 1 Hz) by inverting teleseismic and/or strong motion body waves, for which the necessary Green s functions can be calculated using simplified approximations of the velocity structure (e.g. Hartzell & Heaton 1983; Kikuchi & Kanamori 1991; Yoshida et al. 1996; Kikuchi et al. 2003). The use of seismological datasets recorded at different distances is expected to provide supplementary information on the rupture process, thereby yielding a more stable and detailed image of the source area, while the teleseismic and strong motion data carry complementary information on different period ranges of the source process. In this study, we have estimated a source model of the 2009 L Aquila earthquake by performing linear multiple-time-window waveform inversion of individual teleseismic and strong motion records in the low-frequency band (<0.5 Hz). In establishing the precise source model from the observed strong motion data, it is vital to employ appropriate Green s functions. The issue becomes of particular importance in the regions such as the Abruzzo which have undergone complex tectonic evolution (e.g. Bagh et al. 2007; Galli et al. 2010; Chiarabba et al. 2010) and which therefore constitute highly inhomogeneous geological settings. To address the complexity of the velocity structure of the region a set of calibrated 1-D Green s functions has been constructed for each of the strong motion stations by waveform modelling of the aftershock records. These Green s functions are then used for inversion of the strong motion data. 2.1 Methodology We first determined the focal mechanism of the 2009 L Aquila mainshock by applying the point source inversion method of Kikuchi & Kanamori (1991) to the teleseismic records discussed further in the data section below. Next, the spatiotemporal distribution of slip on the fault plane was estimated using the formulations of Kikuchi et al. (2003) for the teleseismic waveform inversion and Yoshida et al. (1996) for the strong motion waveform inversion. In both these formulations, moment release over the fault is discretized in space and time. The spatial discretization is performed by dividing the fault plane into M N rectangular subfaults of length x and width y. Each subfault is represented by a point source at its centre and Green s functions are estimated for each of these point sources and each observation point. The temporal moment release from each subfault is expressed as a summation of several non-overlapping ramp functions in the formulation of Yoshida et al. (1996) and as a series of overlapping triangular sliprate functions in that of Kikuchi et al. (2003). The mn th subfault is assumed to slip after a time interval corresponding to the arrival of the rupture front. Circular rupture propagation from the hypocentre at a constant velocity V r is assumed. The value of V r is determined in the inversion process by minimizing the residuals between the observed and synthetic seismograms. The source model used in both approaches allows for variations in the slip vectors by decomposing the slip vector on each subfault into a linear combination of two components, each differing from the original vector by ±45. As each method is based on the representation theorem relating the observed wavefield to the spatial and temporal evolution of slip over a fault (e.g. Aki & Richards 1980), the observational equations can be expressed in vector form as Am = d. (1) Here, A is a matrix containing the Green s function from every grid point on the fault plane to every station convolved with the basis source time function of each subfault, m is the solution vector of the slip values at each grid point, and d are the vectors containing the observed data. To stabilize the inverse problem represented by eq. (1), a smoothing constraint is introduced. Taking into consideration this constraint, eq. (1) can be rewritten as (AλS) T m = (d0) T, (2) where S is the smoothing matrix and λ is a hyperparameter controlling the degree of smoothing. The optimal value of λ in the formulation of Yoshida et al. (1996) is determined objectively using Akaike s Bayesian Information Criterion (ABIC; Akaike 1980). Another constraint used in the method is a positivity constraint confining the rake angles to ±45 from the original value. Eq. (2) is solved in a least-squares sense to determine the optimal hyperparameter. The optimal models are selected using an objective assessment of the fit between observed and synthetic waveforms for teleseismic waveform inversion using the method of Kikuchi et al. (2003), and the ABIC criteria for strong motion waveform inversion using the method of Yoshida et al. (1996). 2.2 Data In this analysis, we used broad-band teleseismic data from the IRIS-DMC and near-field strong motion recordings from the Italian Strong Motion Network (RAN), as well as the acceleration channels of station AQU in the MedNet (INGV) network. A more detailed description of each of the datasets is given below Teleseismic data The locations of the teleseismic stations providing data used in this study are displayed in Fig. 3. The data are digital records gathered by the Data Management Center of the Incorporated Research Institute for Seismology (IRIS-DMC). We retrieved broad-band seismograms from IRIS-DMC for stations at epicentral distances of 30 90, taking into consideration the quality of the records and the azimuthal coverage of the stations. The final dataset selected for the inversion consists of 34 vertical-component P-wave recordings. Due to the low signal-to-noise ratio, making it difficult to pick a precise arrival of the corresponding signal, we did not include the SH-wave part of teleseismic records in our inversion analysis. The record length for each original velocity waveform was set to 40 s, starting 5 s before the onset of the P wave; the time-series were bandpass filtered in the Hz frequency range and converted into ground displacements at a sampling rate of 0.5 s. We calculated Green s functions for the teleseismic P waves using the method of Kikuchi & Kanamori (1991). The assumed velocity structure around the source area is based on the results of receiver function analysis by Bianchi et al. (2010) and the structure near each of the stations is computed using the Jeffreys-Bullen model (Jeffreys & Bullen 1958): both velocity models are presented in Table 1. The attenuation factor for the P waves is incorporated by using the t attenuation operator with a value of 1 s. Accurate timing estimation (that is, the arrivals of the analysed phases) is an

5 Source Models for the 2009 L Aquila Earthquake 5 Figure 3. Global distribution of teleseismic broad-band stations (grey triangles) employed in the study. The red star represents the epicentre of the mainshock. The inner and outer circles represent epicentral distances of 30 and 100, respectively. The map is drawn using an azimuthal equidistant projection. Table 1. Velocity models used in the teleseismic waveform inversion analysis. V p (km s 1 ) V s (km s 1 ) Density (10 3 kg m 3 ) Thickness (km) Near-Station Crustal Structure Near-Source Crustal Structure important factor in the analysis of teleseismic records. To minimize the inaccuracy of calculations of expected traveltime arising from incomplete knowledge of the velocity structure, scalar time shifts were applied to the observed teleseismic waveforms to correct the timing of the inversion Strong motion data and velocity structure modelling The 2009 L Aquila mainshock was recorded by a large number of strong motion and broad-band instruments in both the near-field and regional distance ranges. Records from the Italian strong-motion network (RAN), operated by the Civil Protection Department, and MedNet station AQU have been integrated into the ITalian ACcelerometric Archive (ITACA) and made available via the internet. Fifty-eight strong motion stations within km of the mainshock epicentre (Fig. 1a) provided high-quality digital acceleration records of the mainshock. This dataset includes one of the largest peak ground accelerations (PGA 0.66 g) ever recorded in Italy, as well as the first strong motion record from station on the hanging wall of a normal faulting event in general. The near-fault stations (at epicentral distances of km) on the hanging wall side of the mainshock fault (R jb distance of 0 km) recorded the largest horizontal PGA values of g (Fig. 1a). The records from these stations are characterized by vertical PGAs as large as the horizontal ones (Fig. 1b). The largest PGA of 662 cm s 2 ( 0.66 g) was observed at station AQV (Fig. 1b) in the Aterno array. Stations located on the footwall recorded PGAs of less than 0.15 g. The velocity records of the near-fault stations (Fig. 1c) exhibit prominent short-duration pulses with PGVs exceeding 30 cm s 1 at all of these locations. The largest PGV value of 43.5 cm s 1 was recorded on the NS component of station AQV. A more detailed inspection of records from the near-fault hangingwall stations reveals that the Aterno array stations (e.g. AQV and AQG; Fig. 2) had

6 6 N. Poiata et al. similar ground motion characteristics, while the ground motions at stations located within the city of L Aquila (AQK and AQU; Fig. 2) were significantly different. The difference is exemplified in terms of the polarity of the first arrivals, as well as the presence of pulses on the vertical components of the velocity traces from the city of L Aquila (see Fig. 1c for examples). This characteristic is likely to be demonstrative of the mainshock s source process complexity. A more detailed description of the strong-motion data recorded during the 2009 L Aquila mainshock aftershock sequence can be found in corresponding studies (e.g. Ameri et al. 2009; Akinci et al. 2010; Çelebiet al. 2010). For the strong motion inversion, we have selected 14 of these stations (13 RAN stations and MedNet station AQU) located within 55 km of the epicentre (Fig. 2). Two of the strong motion RAN stations in this original dataset located close to the source fault (GSG and AQK) were excluded from the analysis: no absolute timing information was available for station GSG, and pronounced site amplification at station AQK at a frequency of 0.6 Hz has been reported by several groups (e.g. De Luca et al. 2005; Ameri et al. 2009; Akinci et al. 2010). The availability of the three-component acceleration record from station AQU, which is located downtown in the city of L Aquila on a site with better soil conditions that at station AQK, enabled us to fill what would otherwise have been a gap in the azimuthal coverage. Moreover, this is particularly important because it provides records from within the heavily damaged city of L Aquila. The final set of 14 stations selected for the strong motion inversion provides satisfactory coverage of the near-fault area in terms of both distance and azimuth (Fig. 2). To prepare the raw three-component acceleration waveforms for inversion, the data were bandpass filtered in the frequency range of Hz with a zero-phase shift, second-order Butterworth filter, and then integrated to give ground velocities at a sampling rate of 0.2 s. The lower frequency limit used for the inversion is imposed by the signal-to-noise ratio, while the upper limit is governed by the bandwidth of the Green s functions derived from aftershock modelling. For each waveform, we inverted a segment of data spanning only the body wave (P and S) portion of the record. Consequently, the length of the inverted record varies between stations, starting 3 s before the onset of the P wave and ending before the arrival of surface waves. An important facet of our strong motion analysis is the construction of a set of well-calibrated Green s functions. As previously mentioned, the velocity structure in and around the source region of the 2009 L Aquila earthquake is complex, rendering the use of a single 1-D velocity model for calculating theoretical Green s functions inappropriate. The best way to include the realistic response of underground structure is to use a 3-D velocity model in the Green s function calculations. This information is unavailable for the area of interest, and developing an accurate 3-D model is a highly involved process. However, Graves & Wald (2001) demonstrated that slip distributions obtained using a set of calibrated 1-D Green s functions are comparable to those obtained with 3-D Green s functions. A number of previous analyses (e.g. Ichinose et al. 2003; Hikima & Koketsu 2005; Asano & Iwata 2009) have determined suitable 1-D layered models for each station based on waveform modelling of small events (e.g. aftershocks) and have successfully yielded detailed source rupture models. We follow that approach here. The 2009 L Aquila earthquake was followed by intense aftershock activity, and a number of records from these events have been made available through the ITACA database. This has enabled us to construct 1-D velocity models for each of the 14 strong motion stations by forward modelling of the aftershock records. Four aftershocks with moment magnitudes of M w located within the rupture area of the main event and recorded by most of the 14 stations have been used for this task. The exact number of events per station was restricted by the availability of records. The assumed locations of the aftershocks are those reported in the INGV- CNT bulletin, and the source parameters have been adopted after Herrmann et al. (2011) (see Table 2). The epicentres of the aftershocks and the corresponding focal mechanisms are illustrated in Fig. 2. The source process of each aftershock was approximated by a point source with a finite duration of the ramp function, and further tuned to fit the observed waveforms. With these assumptions, the Green s functions were then calculated theoretically by applying the extended reflectivity method of Kohketsu (1985), and the reference 1-D velocity structures were calibrated by trial and error to match the synthetic velocity records to the observations at frequencies of up to 0.5 Hz. The goodness of fit in terms of both the phase and amplitude was evaluated manually in each case by visual inspection. We have assumed a different reference velocity model for stations AQU, AQV and AQG in the Aterno Valley from that of the rest of the strong motion stations (Fig. 2). For these three sites, positioned on the hangingwall of the causative fault (R jb distance of 0 km), a 1-D velocity model resulting from the analysis of the receiver functions by Bianchi et al. (2010) was adopted as the reference model (Fig. 4a). This crustal model features a relatively high velocity at depths of 4 9 km and a wave velocity inversion below 9 km. The model was further adjusted by forward modelling the aforementioned aftershocks to develop station-specific calibrated 1-D velocity models accounting for the shallow low-velocity layers of the soft sediments from the Aterno Valley. For all other stations, the nncia and CIA velocity models (Figs 4b and c) obtained by Herrmann & Malagnini (2009) via surface wave dispersion analysis were evaluated as potential reference velocity structures. The nncia model exhibits a relatively high velocity upper layer, similar to that in the model of Bianchi et al. (2010): this layer is absent from the CIA model. Our analysis revealed that for all of these stations the nncia and CIA models both produce Table 2. Source parameters of the mainshock and the aftershocks used in the analyses. Hypocentre locations from the INGV-CNT Bulletin; Seismic moments and moment tensor solutions of the aftershocks from Herrmann et al. (2011); M w denotes the moment magnitude reported by INGV; # indicates the mainshock parameters estimated in this study. Aftershock # Date Time Latitude Longitude Depth M o M w Strike/Dip/Rake (UT) ( N) ( E) (km) (Nm) ( / / ) 1 6 April :37: /35/ April :47: /70/ 60 3/EGF event 7 April :34: /51/ April :14: /90/55 Mainshock 6 April :32: # # 6.3 # 140/46/ 96 #

7 Source Models for the 2009 L Aquila Earthquake 7 Figure 4. (a) Velocity model (after Bianchi et al. 2010) used to represent near-source structure in the teleseismic waveform inversion and as the initial model in the velocity calibration for stations in the Aterno Valley. (b) The CIA velocity model of Herrmann & Malagnini (2009). (c) The nncia velocity model of Herrmann & Malagnini (2009). (d), (e) and (f) Results of the velocity structure calibration for stations AQU, AQV and AQG, respectively. satisfactory fits to the aftershock records at frequencies up to 0.5 Hz. However, stations located in the south were found to be fitted better by the CIA model and those in the north by the nncia model. Based on these results, we separated our stations into three groups (Fig. 2). The first group is composed of the six southern stations with a 1-D velocity structure approximated by the CIA model (Fig. 4b); the second contains five northern stations with the 1-D velocity structure approximated by the nncia model (Fig. 4c); and the third group contains the three Aterno Valley stations with station-specific calibrated 1-D velocity models (Figs 4d f). Figure presenting the comparisons of the observed and synthetic waveforms corresponding to the initial and final velocity models for some of the aftershocks and stations are presented in Fig. A1. The resulting 1-D velocity models were used to calculate Green s functions for the strong motion waveform inversion. 2.3 Fault plane settings A number of studies based on coseismic surface rupture observations (Falcucci et al. 2009; Boncio et al. 2010; EMERGEO Working Group 2010), geodetic data (e.g. Anzidei et al. 2009; Atzori et al. 2009) and the distribution of relocated aftershocks (Chiarabba et al. 2009) have confirmed that 2009 L Aquila earthquake was a result of a normal faulting along the northwest southeast oriented, southwest dipping Paganica fault. Taking into account those results, we assume that the rupture occurred on a single fault plane dipping southwestward and adopt a rupture initiation point of N, Eat a depth of 9.5 km, corresponding to the revised hypocentre obtained by INGV (2009). The assumed orientation of the fault plane strike/dip/rake = 147 /44 / 102 is based on the best-fit solution of the point source inversion analysis of teleseismic waveforms by Kikuchi & Kanamori (1991) referred to in the data section earlier (Fig. 3). This solution is in agreement with the results of the studies mentioned earlier as well as with the moment tensors reported by other agencies (e.g. INGV 2009, USGS 2009). We adopt fault plane dimensions of 24 km in length by 16 km in width based on the aftershock distribution documented by INGV. The fault is discretized into 6 4 subfaults, with an area of 4 4km each. Fig. 2 illustrates the model configuration in terms of the surface projection of the assumed fault plane. The temporal variation in the slip-rate function of each subfault for the two components of the rake ( 102 ± 45 ) is represented by a series of four overlapping triangle functions with a 1 s half-duration and 1 s lag offsets in the case of the teleseismic waveform inversions, and source time functions composed of a series of six ramp functions with a rise time τ = 0.8 s in the strong motion inversion case. These discretization schemes produce a total number of model parameters of = 192 and = 288 for the teleseismic and

8 8 N. Poiata et al. strong motion inversions, respectively. The rupture velocity V r was chosen in the inversion process to minimize the residuals between the observed and synthetic waveforms. The hypocentre (rupture starting point) was initially set to the same location as in the point source inversion (depth of 9.5 km). Next, a grid search for the best hypocentre depth was performed in the teleseismic and strong motion data inversion analyses. We also refined the fault orientation by fine-tuning the strike and dip angle values in the strong motion inversion analysis. The final source model and its comparison with the results of other studies are presented later. 2.4 Teleseismic inversion Figs 5 and 6 summarize the results of the teleseismic waveform inversion of P-wave displacements from the stations presented in Fig. 3. The comparison of the observed and synthetic waveforms corresponding to the best-fit teleseismic model is shown in Fig. 5. The synthetics are generally in satisfactory agreement with the observed records, accounting well for both the main pulse and the smaller disturbance preceding it at most of the stations. The spatial and temporal parameters describing the resulting model are presented in Fig. 6. The source time function (Fig. 6c) indicates that total seismic moment M 0 of Nm (M w 6.3) was released over a period of 10 s. The overall moment tensor solution for the model (Fig. 6d) agrees well with the results of the point source analysis and the pure normal faulting mechanism reported by other agencies (e.g. INGV 2009, USGS 2009). The slip distribution (Fig. 6a) corresponds to a single asperity model with a maximum slip of 0.56 m in the southeastern part of the fault. This correlates with the region of lower on-fault aftershock activity (Fig. 6d). The grid search analysis yielded a depth of 8 km for the rupture starting point, and the best-fit rupture velocity was estimated to be 2.2 km s 1. On the basis of this model, rupture extended both up-dip and southeastward from the epicentre, which is well illustrated by the slip distribution (Fig. 6a) and the moment-rate function distribution over the fault (Fig. 6b). The inferred source model indicates negligible variations in rake angle. The overall rake angle of 95 is in good agreement with the previously described mechanism (e.g. Cirella et al. 2009). It should be mentioned, however, that due to the relatively small size of the event (M w 6.3) the results of the teleseismic inversion should be interpreted in terms of general features only. While the data quality is relatively good (in the sense that most of the displacement records show low noise level prior to the P-wave s arrival; see Fig. 5) later complexities in the teleseismic waveforms remain unexplained for many of the stations (Fig. 5). We consider this to be due to the resolution limitation of teleseismic Figure 5. Comparison of the observed (black traces) and synthetic (red traces) teleseismic displacements for the teleseismic waveform inversion. The numbers above the station codes indicate the maximum observed amplitudes in µm and the numbers under the station codes are the azimuth from source to the stations.

9 Source Models for the 2009 L Aquila Earthquake 9 Figure 6. Results of the teleseismic waveform inversion. (a) Slip distribution plotted at contour intervals of 0.05 m. The red star indicates the hypocentre. The arrows denote the slip vectors. (b) Moment-rate functions for each subfault and the resultant rake angle. The red star indicates the hypocentre. (c) Total moment-rate function. (d) Surface projection of the slip distribution shown in (a): the contour interval is 0.05 m. The red star corresponds to the rupture initiation point of the 2009 L Aquila mainshock. The focal mechanism solution corresponding to the illustrated slip distribution is also shown. Other symbols are as described in Fig. 2. inversion analyses applied to relatively small events of the size of 2009 L Aquila earthquake (M w 6.3). Nevertheless, we were able to estimate the rupture velocity and hypocentre depth from the teleseismic analysis. The robust results can be further evaluated on the basis of the strong-motion analysis. 2.5 Strong motion inversion The next step in our analysis is strong motion waveform inversion using the velocity records from the 14 stations discussed previously and the Green s functions calculated using the estimated 1-D velocity models. For this step, we applied the same spatial discretization scheme as above, taking into account the fault orientation and hypocentre depth determined from the teleseismic waveform inversion. The best values of the hypocentre depth and the fault s strike and dip were then determined via a grid search procedure. Search ranges of , and for the strike, and dip angles, respectively, were selected to span the range of values obtained in other studies (e.g. Atzori et al. 2009; Cirella et al. 2009; Walters et al. 2009). The results of the strong motion inversion are summarized in Figs 7 and 8. Comparison of the observed and synthetic waveforms corresponding to the best-fit model shows good agreement (Fig. 7). The synthetics match the observed waveforms well at most of the stations. Discrepancies at some of the stations (e.g. AQU) are most likely the result of wave propagation not fully represented by the 1- D velocity structure approximation. The final slip distributions and other source parameters are presented in Fig. 8. The slip distribution (Fig. 8a) and the source time functions of the strong motion inversion (Fig. 8b) once again reveal a single main asperity undergoing maximum slip of 0.64 m and located about 8 km southeast of the hypocentre. The total seismic moment M 0 of about Nm was estimated to have been released over a 14 s period. As found with the teleseismic modelling, rupture appears to have propagated up-dip and southeastwards from the hypocentre, with the southeast

10 10 N. Poiata et al. Figure 7. Comparison of the observed (black traces) and synthetic (red traces) ground velocities for the strong motion inversion. The numbers above the station codes indicate the maximum amplitudes in cm s 1. direction predominating. The rupture velocity that provides the best fit between observed and synthetic waveforms for the source models is 2.0 km s 1 and the optimal depth of the hypocentre is 8.2 km. The purely normal faulting mechanism of the strong motion model (Fig. 8d) and the revised strike and dip estimates of 140 and 46, respectively, are in close agreement with the teleseismic results. Comparison of the slip distributions from the teleseismic and strong motion inversions also reveals good agreement in the estimated locations of the maximum slip areas and the total seismic moments. In both cases (Figs 6a and 8a), maximum slip is located about 8 km southeast of the rupture starting point and extends beneath the heavily damaged city of Onna (Figs 6d and 8d). The slip distributions correlate well with the lower on-fault aftershock activity (Figs 6d and 8d). One discrepancy between the two results, however, is that the teleseismic model indicates a significant amount of slip occurring up-dip of the hypocentre. This feature is almost totally absent from the strong motion inversion slip distribution. The optimum value of the dip obtained with the strong-motion analysis (46 ) is in good agreement with the estimation provided by the detailed analysis of the relocated aftershocks of Chiaraluce et al. (2011). However, it differs somewhat from the values of obtained via geodetic inversion (Anzidei et al. 2009; Atzori et al. 2009; Walters et al. 2009). We have investigated the influence of different dip angles on the strong motion inversion results and confirmed that larger values of dip provide systematically worse fits, at some stations in particular. We consider that the difference in dip angles determined from analysis of the seismological and geodetic datasets is likely to be caused by the fault s complex geometry at depth (bending of the fault) that cannot be accounted for in the geodetic analysis due to the limited depth resolution. 3 BROAD-BAND SOURCE MODELLING OF THE 2009 L AQUILA EARTHQUAKE One of the main objectives of source process estimation is to provide source models capable of reproducing broad-band ground motions the near-field region with sufficient accuracy for engineering purposes. The frequency range of interest for most of the earthquake engineering studies is Hz. Waveform inversions have generally proven successful in a low-frequency range of up to 1Hzfor near-source ground motions (e.g. Hartzell & Heaton 1983). At frequencies higher than 1 Hz, deterministic simulations of ground motions are limited by a lack of precise information about the velocity structure as well as the complexity of the source description. A useful approach to overcoming these difficulties is to estimate ground motions of an earthquake using records of nearby smaller events, treated as empirical Green s functions (Hartzell 1978; Irikura 1986; Irikura & Kamae 1994). The main idea of the empirical Green s function method is that records of the smaller events incorporate the properties of the propagation path and local site effects. Source modelling using this method has been applied successfully to

11 Source Models for the 2009 L Aquila Earthquake 11 Figure 8. Results of the strong motion waveform inversion. (a) Slip distribution plotted at contour intervals of 0.05 m. The red star indicates the hypocentre. The arrows denote the slip vectors. (b) Moment-rate functions for each subfault and the resultant rake angle. The red star indicates the hypocentre. (c) Total moment-rate function. (d) Surface projection of the slip distribution shown in (a): the contour interval is 0.05 m. The red star corresponds to the hypocentre of the 2009 L Aquila mainshock. The focal mechanism solution corresponding to the illustrated slip distribution is also shown. The white rectangle indicates the position assumed initially for the strong motion generation area (corresponding to the location of the asperity) in the empirical Green s function analysis. Other symbols are as described in Fig. 2. explain broadband near-source strong ground motions by a number of researchers (e.g. Miyake et al. 2003). We have applied the empirical Green s function method formulated by Irikura (1986) and Irikura & Kamae (1994) to the 2009 L Aquila earthquake to determine the strong motion generation area that best reproduces near-fault records in the Hz frequency band. According to Miyake et al. (2003), the strong motion generation area can be identified as the portion of the total rupture area that is characterized by high slip velocity and reproduces near-source ground motions at frequencies of up to 10 Hz. The initial position of the strong motion generation area in our case is assumed based on the location of the asperity (large-slip region) determined using low-frequency inversion analysis presented earlier. We estimated a number of parameters describing the strong motion generation area to wit, the number and size of subfaults, the rupture velocity, the rise time of source time function, and the stress drop using the spectral fitting procedure (Miyake et al. 1999) and forward modelling of observed broad-band ground motions applied to a corresponding mainshock aftershock pair. Source modelling using the empirical Green s function technique requires records from appropriate small events as Green s functions. In view of the large number of aftershocks produced by the 2009 L Aquila earthquake, we were able to select suitable events that had been recorded by a number of stations providing satisfactory azimuthal coverage and that best approximated the focal mechanism and location of the mainshock. 3.1 Methodology Formulation of the empirical Green s function method The empirical Green s function method of Irikura (1986) and Irikura & Kamae (1994) takes into consideration two similarity relations

12 12 N. Poiata et al. between large and small earthquakes: the first is the scaling of source parameters (Kanamori & Anderson 1975) and the second is the ω 2 spectral source model (Aki 1967; Brune 1970; Brune 1971). The waveform of the large event U(t) is represented in terms of the waveform of the small event u(t) in the following way U(t) = C where N i=1 t ij = r ij r 0 β N j=1 1 F(t) = δ(t) + n ( ) 1 1 e r r ij F ( t t ij ) u(t), (3) + ξ ij V R (4) (N 1)n k=1 { 1 δ e (k 1) (N 1)n [ t t ij ] } (k 1)T (N 1)n and the components r, r ij and r 0 represent the distances from the site to the hypocentre of the small event, from the site to the (i, j) subfault, and from the site to the rupture starting point of the large event, respectively. The term ξ ij corresponds to the distance between the rupture starting point and the subfault (i, j); β is the S-wave velocity; V r is the velocity of rupture propagation; T represents the rise time of the large event; n is an integer introduced to eliminate artificial periodicity (Irikura 1983); represents the convolution operation; F(t) is a modified filtering function (Irikura et al. 1997) accounting for the difference in the slip time functions of the large and the small events; and N and C, respectively, are the ratios of the fault dimensions and stress drops between the large and small events. To simulate strong ground motions of the large event using the record of a small event as the Green s function, we must first determine the scaling parameters C and N. These parameters can be derived from the constant levels of the displacement and acceleration amplitude spectra of the two events U 0 /u 0 = M 0 /m 0 = CN 3, A 0 /a 0 = CN, (6) where U 0, u 0 are the flat levels of the displacement spectra of large and small events, respectively, and A 0 and a 0 are the corresponding flat levels of the acceleration spectra; and M 0 /m 0 corresponds to the ratio of seismic moments for the large and small events at the lowest frequencies. The fault plane of the target event is then divided into N N subfaults of sizes equivalent to the rupture area of the small event. The waveforms for the large event can then be calculated as superposition of the recordings of the small event, considering the difference in slip functions of the large and small events according to the scaling laws mentioned previously Spectral analysis and scaling factor determination To obtain objective estimates of parameters N and C, wehave used the source-spectral fitting method proposed by Miyake et al. (1999). The method enables the parameters to be derived by fitting the observed source spectral ratio between the large and small events to that of a theoretical source that obeys the omega-squared model of Brune (1970, 1971). In the frequency domain, the observed spectrum can be represented as a product of terms describing the source S(f ), the path P(f ), and site amplification effects G(f ). The source amplitude spectral ratio of the large and small events at one station can thus be expressed as a spectral ratio of the observed waveforms corrected (5) for the propagation path effect produced by geometrical spreading of the body waves and the frequency-dependent attenuation factor Q S (f ) for the S waves (eq. 7) / 1 S( f ) O( f ) s( f ) = / o( f ) e π fr Q S ( f )V S R. (7) 1 e π fr Q S ( f )V S r Here the upper- and lowercase letters indicate parameters pertaining to the large and small events, respectively. Based on the omega-squared source model of Brune (1970, 1971), the source spectral ratio function can be expressed as R( f ) = M ( f/f ca) 2 (8) m ( f/f cm ) 2 In this equation, f cm and f ca are the corner frequencies of the large and small events. We have applied the weighted least-squares method of Miyake et al. (1999, 2003) to fit the theoretical source spectral ratio function R(f ) (eq. 8) and the observed source amplitude spectral ratio (eq. 7) and thus estimate M 0 /m 0, f cm and f ca.the values of N and C are then found based on the high- (f ) and low-frequency (f 0) limits of eq. (8) subject to eq. (6). The observed source amplitude spectral ratios have been determined for each of the stations using the large and small events amplitude spectra, calculated from vector summation of the threecomponent amplitude spectra. The mean observed source amplitude spectral ratio has then been calculated and used in deriving the C and N parameters. The frequency-dependent attenuation factor of S waves Q S (f) in the target area of central Italy was adopted after Bindi et al. (2009). 3.2 Data The intense aftershock activity that followed the 2009 L Aquila earthquake (M w 6.3) was recorded by a number of stations in the RAN and INGV networks (station AQU). As with the mainshock, the strong motion records from some of the aftershocks (generally those of M w > 4.2) have been made available through the ITACA database. In our analysis, we have used a M w 4.6 aftershock that occurred on 2009 April 7 (21:34:29 UT) as the empirical Green s function event. The source parameters of both the large and the small events are listed in Table 2, and the relative locations and the distribution of the stations that recorded both events are shown in Fig. 2. Selection of the small event was made based on the hypocentral location, the similarity of its focal mechanism to that of the mainshock, and the azimuthal coverage of the recording stations. The latter factor is necessary to account for the eventual directivity effects that may distort the spectral shapes at low frequencies (Miyake et al. 2001). A homogeneous azimuthal distribution of stations cancels out the effects of directivity on the average amplitude spectral ratio and permits reliable estimation of the source parameters. In general, all of the strong motion stations selected for analysis are located within 30 km of the epicentre (Fig. 2), and provide satisfactory coverage of the near source area. 3.3 Broad-band source model of the 2009 L Aquila earthquake We have used data from nine stations located within 30 km from the target epicentre to estimate the parameters N and C (Fig. 2). These and other estimated parameters are presented in Fig. 10.

13 Source Models for the 2009 L Aquila Earthquake 13 Figure 9. Mean observed source spectral ratios of the mainshock to the empirical Green s function event (black line) at the stations used in the broadband source modelling. The red curve corresponds to a ω 2 source spectral model fit to the observed data. The values of the parameters determined from the spectral fitting are listed. The lower frequency limit imposed by the signal-to-noise characteristics of the small event is 0.2 Hz and we have fixed the upper limit of the frequency range used to 10 Hz. We further estimated the parameters of the strong motion generation area by forward modelling of two-component (EW and NS) horizontal acceleration, velocity and displacement waveform traces (S-wave portion) at four near-fault stations (Fig. 2) on the hanging wall side of the mainshock fault. These stations are used for this purpose because of their proximity to the source area, the impulsive character of the velocity and displacement traces, and their locations within the area of largest observed macroseismic effects (namely the city of L Aquila, and the villages of Paganica, Onna, and Castelnuovo; Fig. 2). Assessment of the final model was based on waveform fitting at these hangingwall stations and other stations located at greater distances discussed earlier. We identify the strong motion generation area that best accounts for particular characteristics of the records from the hangingwall stations while providing satisfactory fits at the rest of the stations. The initial position of the strong motion generation area is assumed based on the asperity determined from the strong motion inversion analysis (Fig. 8d). Based on the spectral estimation of N ( 3.4; Fig. 9) we have experimented with integer values of both N = 3andN = 4 in the source simulations. This reveals that N = 4 provides generally better fitting of the observed records, and in particular the velocity pulses at the near-fault hangingwall stations. On this basis, we fixed the value of N to be equal to 4, and divide the strong motion generation area into 4 4 subfaults. The value of C determined from the spectral fitting is 3.5 (Fig. 9). The size and precise location of the strong motion generation area for the target event could then be determined via forward modelling by minimizing the residuals between the displacements and the envelopes of the acceleration waveforms (Miyake et al. 1999). The final parameters of the broad-band source model are summarized in the Table 3. Comparisons of the observed and synthetic waveforms for the four near-fault stations are shown in Fig. 10. It is evident that the estimated strong motion generation area accounts well for the velocity and displacement pulses recorded at the four near-fault stations. The noticeable overestimation of the acceleration components is most probably due to the difference in the attenuation characteristics of the soft sediments from the Aterno Valley (e.g. non-linear amplification) for the target and empirical Green s function events. Validation of the broad-band source model for the 2009 L Aquila mainshock using the strong ground motion records of the five stations located at greater distances from the epicentre is presented in Fig. 11 as comparisons of the synthetic and observed waveforms. The figure illustrates that the estimated strong motion generation area reproduces satisfactorily the observed ground motions at some of the stations (e.g. MTR). However, significant discrepancies exists elsewhere (e.g. AVZ), which we take to be indicative of differences in the source characteristics and/or attenuation along the propagation path for the small and large events that are not taken into account in our analysis. Fig. 12(a) illustrates the relative locations of the strong motion generation area and the slip distribution determined from lowfrequency waveform inversion. It can be seen that the two largely coincide, with the strong motion generation area having a slightly larger along-strike dimension. This indicates that the low-frequency and broad-band ground motions produced by the 2009 L Aquila mainshock were generated at similar locations on the fault plane. The result is important for understanding and predicting the spatial distribution of strong ground motions, as well as explaining the observed macroseismic effects. 3.4 Source scaling Based on the results of the broad-band modelling, we have performed a study of source scaling properties of the 2009 L Aquila (M w 6.3) earthquake by comparing the estimated source parameters (Table 3) with the empirical source scaling relationship for inland crustal earthquakes proposed by Somerville et al. (1999) and Miyake et al. (2003). The scaling relationship of Somerville et al. (1999) was derived using the results of waveform inversions at frequencies less than 1 Hz, and that of Miyake et al. (2003) using empirical Green s function simulations in the Hz frequency band. The comparison is made in terms of the size of the strong motion generation area versus moment magnitude, and the rise time for the strong motion generation area versus moment magnitude. The strong motion generation area size and the rise time value Table 3. Parameters of the strong motion generation area for the 2009 L Aquila mainshock estimated using the empirical Green s function method. C N Element event Target event 1(km) w (km) τ (s) L (km) W (km) S (km 2 ) T (s) V r (km s 1 ) V s (km s 1 )

14 14 N. Poiata et al. Figure 10. Comparison of the observed (black lines) and synthetic (red lines) waveforms for the four near-fault stations used in the estimation of the strong motion generation area parameters. determined from the empirical Green s function method modelling of the 2009 L Aquila event are S = 41.6 km 2 and T = 0.8 s, respectively. The results of the source scaling characteristic analysis are presented in Fig. 13: these show that the 2009 L Aquila earthquake exhibited similar scaling properties to inland crustal earthquakes and imply a stress drop of about 10 MPa for this event. This value of the stress drop is in good agreement with the results of Bindi et al. (2009) who examined the corner frequencies of source spectra. According to their estimates, the stress drop of the mainshock was 9.2 MPa, while the values for the aftershocks vary within the range of 2.4 to 16.8 MPa. These estimates are consistent with the stress drop variability observed in the Central and Southern Apennines as a whole (Bindi et al. 2009). 4 DISCUSSION The large number of strong motion records available for the 2009 L Aquila mainshock and its aftershocks provide a rare opportunity for detailed analysis of this moderate-magnitude normal faulting event. In this study, we have developed source models of the L Aquila earthquake using waveform inversions of teleseismic and strong motion data in the Hz frequency band, and empirical Green s function modelling in the Hz band. The low-frequency slip distributions obtained via teleseismic and strong motion waveform inversions have consistent features: in particular, both results reveal a single major asperity located about 8 km southeast of the hypocentre (Figs 6d and 8d) beneath the city of Onna. The rupture is estimated to have propagated up-dip and southeastwards from the hypocentre, with the southeast direction predominating in the strong motion source model. A comparison of the source time functions (Figs 6c and 8c) emphasizes that the maximum moment release occurred away from the hypocentre approximately 7 s (teleseismic model) or 8 s (strong motion model) after rupture initiated. The overall rupture duration in the case of the strong motion inversions is estimated to be 14 s. This value is larger than the teleseismic estimate of 10 s, but the corresponding total seismic moments, which are equal to the area beneath the source time function, are similar for the two models. Given this, the variation of the rupture duration may be related simply to the different rupture velocities of 2.0 km s 1 and 2.2 km s 1 determined from the strong motion and teleseismic analyses, respectively. Teleseismic data made available by IRIS-DMC are probably the first information obtainable in the immediate aftermath of a major earthquake. These facilitate the rapid estimation of source parameters, which are important for the post-earthquake response. Based on the results of this study, however, we believe that for events of relatively small size (such as the 2009 L Aquila earthquake) the source models obtainable from teleseismic inversions should be treated as indicative of general features only, due to the limited resolution attainable with teleseismic data. Consequently, in view of the large number of high-quality strong ground motion records for both the mainshock and many aftershocks of the 2009 L Aquila earthquake, we suggest that the results of strong motion inversion be regarded as the authoritative low-frequency source model for this event. The source model found here, characterized by a single main asperity southeast from the hypocentre, is a robust representation of the low-frequency source process of the 2009 L Aquila earthquake, as confirmed by other studies (Atzori et al. 2009; Cirella et al. 2009) and lower on-fault aftershock activity. The empirical Green s function method utilized in this study to determine a broadband ( Hz) source model for the 2009 L Aquila mainshock yielded a strong motion generation area of 41.6 km 2, with a rise time of 0.8 s. From this analysis, the rupture was estimated to have propagated predominantly towards the southeast

15 Source Models for the 2009 L Aquila Earthquake 15 Figure 11. Comparison of the observed and synthetic waveforms used for the source model validation by the empirical Green s function method. Figure 12. (a) Map view of the near-source region of the 2009 L Aquila earthquake showing the relative locations of the surface projection of the strong motion generation area determined by empirical Green s function analysis (black rectangles) and the slip distribution determined from the strong motion inversion. The red star marks the epicentre of the mainshock, the black star outlined in red represents the epicentre of the empirical Green s function event, and the black star outlined in white marks the rupture initiation point of the strong motion generation area. The focal mechanisms and seismic moments determined by INGV are also shown. Other symbols are as described in Fig. 2. (b) Distribution of the observed macroseismic (MCS) intensity in the nearsource area of the 2009 L Aquila event. The data were collected during a field survey conducted by INGV (from INGV-Database Macrosismico Italiano, The red star marks the epicentre of the mainshock. The location of the cities of L Aquila, Paganica, Onna and Castelnuovo are marked for reference. C 2012 The Authors, GJI C 2012 RAS Geophysical Journal International