Contents

1 Introduction
2 Brief overview of seismic moment tensor
3 Automatic regional moment tensor inversion in the European-Mediterranean region
 3.1 Summary
 3.2 Introduction
 3.3 Data and method
  3.3.1 Data acquisition
  3.3.2 Algorithm
  3.3.3 Inversion
 3.4 Quality assessment of results
  3.4.1 True quality
  3.4.2 Automatic assigned quality
 3.5 Discussion
  3.5.1 Performance
  3.5.2 Frequency band and location
  3.5.3 Current improvements
 3.6 Conclusions and outlook
  Acknowledgments
4 Automatic moment tensor analysis of moderate earthquakes
 4.1 Summary
 4.2 Introduction
 4.3 Distance dependent short period cut-off
 4.4 Signal-to-noise ratio cut-off
 4.5 Application to MT data-set
 4.6 Discussion
 4.7 Conclusions and outlook
5 Seismic moment from regional surface wave amplitudes - applications to digital and analog seismograms
 5.1 Summary
 5.2 Introduction
 5.3 Procedure
 5.4 Recent earthquakes
  5.4.1 Data
  5.4.2 Reference period T
  5.4.3 Distance dependence
  5.4.4 Seismic moment
 5.5 Historical earthquakes
  5.5.1 Data
  5.5.2 Surface wave amplitude and seismic moment
  5.5.3 Seismic moment uncertainty
 5.6 Discussion and conclusions
  Acknowledgments
6 Conclusions and outlook
A Waveform fit examples
B MT from regional data
C Early instrumental seismograms
D Instrument characteristics of early instrumental seismographs

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Abstract

In this thesis, I present two methods to retrieve earthquake source parameters from regional surface wave data for moment magnitude M_w > 4.3 earthquakes. The first method involves fast and fully automatic moment tensor (MT) computation. Automatization includes near real-time earthquake alert screening, data collection from near-real time accessible broad-band stations at regional distances ( < 20^o), MT computation, solution quality assessment and dissemination. The routine is triggered by events with magnitude M > 4.7 in the European-Mediterranean region. MTs are computed using long period data with PREM synthetics. I tested various long period pass bands to evaluate the influence of location accuracy and of simple 1D synthetics on MT retrieval. The best fixed period band for the entire region is currently 50 - 100 s, because relatively few stations are near-real time accessible and often the quickly available locations are of low precision. To assess solution quality, the automatic results are compared with the independent, manually derived Swiss regional moment tensor catalog. Solutions are divided into three qualities. Near real-time application from April 2000 to April 2002 resulted in 38 quality A, with well resolved M_w, depth and focal mechanism, 21 B, with well resolved M_w and 28 unreliable quality C solutions. For M_w > 5.5 we consistently obtained A solutions. Between M_w = 4.5 - 5.5 we obtained quality A and B. In a second step, I significantly improved MT retrieval relative to the standard routine by selecting different period bands for each station and component. The band width depends on the epicentral distance and on the signal-to-noise ratio of each period within each seismogram component. For events in the eastern Mediterranean Sea and the near East, the shortest period used is 50 s. For events in Europe, the short period cut-off varies from 35 s for close stations to 50 s for distant stations. Only periods that exceed a signal-to-noise ratio R_m are actually used. The use of shorter periods and removal of noisy data leads to an improvement of solution quality for 4.3 < M_w < 4.7 earthquakes. For events between May 2002 and September 2003 the new routine provided 20% more quality A solutions than the standard routine. Successful analysis of more smaller earthquakes with the new routine suggests to lower the currently implemented trigger magnitude from M > 4.7 to about M > 4.3.

The second method retrieves seismic moment M_o directly from surface wave amplitudes recorded at regional distances. The amplitude-moment relation is derived from digital broad-band data of 18 earthquakes (3.9 < M_w < 5.1) in and near Switzerland with independent M_o values. The amplitudes were measured at empirically determined, distance varying, reference periods T. For amplitudes measured at T, the distance attenuation term of the surface wave magnitude relation S() = log(A/T)_max + 1.66log is independent of distance. M_o is then defined by logM_o = S() + 14.90 assuming 1:1 scaling of log M_o - M_S, which is true for M_S 7.2 in continental areas. Uncertainties of ±0.30 for the 14.90-constant correspond to a factor of 2M_o uncertainty, which was verified with independent data. This relation allows fast, direct M_o determination which can be applied to any earthquake. Re-calibration of the 14.90-constant, however, is probably required for other tectonic regions. I applied the amplitude-M_o relation to determine M_o of 25 stronger 20^th century events in Switzerland from analog data. The data recorded by early instrumental seismographs were collected from several European observatories. Amplitudes were measured from scans at large magnification and corrected for differences between T and the actual measurement period. The resulting magnitudes range from M_w = 4.6 to 5.8. The M_w = 5.8 1946 event in the Valais was the largest 20^th century earthquake. Magnitude uncertainties for the early-instrumental events are on the order of 0.4 units. The M_o estimates were then used for the up-date of the Earthquake Catalog of Switzerland to calibrate an intensity-M_o relationship for pre-instrumental data. Accurate intensity-M_o relations are fundamental for improved seismic hazard evaluations in regions characterized by moderate seismicity and by long recurrence times of larger events.

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Riassunto

In questo lavoro sono presentati due metodi, i quali, utilizzando onde di superficie, permettono di determinare i parametri della sorgente di terremoti regionali con magnitudine M_w > 4.3. Il primo calcola velocemente ed in maniera completamente automatica il tensore momento. Il processo di automatizzazione include l’analisi delle localizzazioni automatiche provenienti da diverse agenzie, la richiesta dei dati in tempo reale da stazioni a banda larga situate a distanza regionale ( < 20^o), il calcolo del tensore momento, la deteminazione dell’affidabilita della soluzione e la sua pubblicazione (sul web e via e-mail). La procedura analizza ogni evento dichiarato con magnitudine M > 4.7 e localizzato in Europea e nell’ area mediterranea. I tensori momento sono calcolati usando dati reali a lungo periodo e librerie di sismogrammi sintetici calcolati con modello PREM. Sono stati testati diversi intervalli di periodo, focalizzando l’analisi sulla stabilitá delle soluzioni in base alla precisione della localizzazione usata ed ai sismogrammi sintetici calcolati per un semplice modello 1D. La bassa affidabilità delle localizzazioni disponibili e l’ancora scarsa disponibilità di dati a banda larga in tempo reale evidenziano che l’intervallo compreso tra i 50 ed i 100 secondi risulta essere il più adatto per l’analisi dei terremoti nell’intera area europea e mediterranea. Il confronto dei risultati con un catalogo indipendent di soluzioni tensore momento ha permesso di stabilire le regole generali per determinare l’affidabilità delle soluzioni così ottenute. Quest’ultime sono state quindi divise in tre gruppi: soluzioni di ’tipo A’, con momento sismico M_o, profondità e meccanismo focale affidabili; soluzioni di ’tipo B’, con il solo valore di M_o affidabile ed infine, soluzioni di ’tipo C’, per cui nessuno dei tre parametri elencati può essere considerato affidabile. Durante il periodo compreso tra l’aprile 2000 e l’aprile 2002, la procedura ha ottenuto 28 soluzioni di tipo A, 21 di tipo B e 28 di tipo C. Per eventi con M_w > 5.5 generalmente si sono ottenute soluzioni di tipo A, mentre per eventi con M_w = 4.5 - 5.5 si sono ottenuti soluzioni di tipo A e B. In seguito la procedura è stata significativamente migliorata selezionando l’intervallo dei periodi in base alla distanza e al rapporto tra il segnale ed il rumore contenuto nei sismogrammi. Pertanto, eventi nel Mediterraneo orientale e nel vicino oriente sono stati analizzati con periodi compresi tra 50 e 100 secondi, mentre, quelli verificatisi in Europa, con il periodo più corto che varia tra i 35 s per le stazioni più vicine ed i 50 s per quelle più lontane. Inoltre sono stati utilizzati solo i periodi il cui segnale supera un determinato rapporto tra segnale e rumore, R_m. L’utilizzo di periodi più corti e la rimozione di sismogrammi contenenti rumore permettono un significativo miglioramento soprattutto per eventi con magnitudine 4.3 < M_w < 4.7. L’analisi di eventi occorsi tra il maggio 2002 ed il settembre 2003 con la nuova procedura ha prodotto 66 soluzioni con qualità A, migliorando del 20% le prestazioni rispetto alla prima procedura. L’efficacia della nuova procedura suggerisce di spostare la magnitudine di soglia da M > 4.7 verso M > 4.3.

Con il secondo metodo è possibile calcolare il momento sismico M_o direttamente dall’ampiezza delle onde di superficie. La relazione tra l’ampiezza ed il momento sismico è stata derivata utilizzando dati digitali di 18 terremoti (3.9 < M_w < 5.1) occorsi recentemente in Svizzera e nelle zone limitrofe, per i quali esistono stime indipendenti del momento sismico ottenute tramite inversione del tensore momento. L’ampiezza delle onde di superficie à stata misurata con periodi di riferimento T dipendenti dalla distanza e determinati empiricamente, cosicché il termine dell’attenuazione della magnitudine delle onde di superficie S() = log(A/T)_max + 1.66log non varia più rispetto alla distanza tra stazione ed evento. Assumendo un rapporto di 1:1 per l’espressione log M_o - M_S, considerata valida per terremoti continentali con magnitudine M_S 7.2, il momento sismico è di conseguenza definito dalla relazione logM_o = S() + 14.90. L’incertezza di ±0.30 della costante 14.90 porta ad un fattore di incertezza di 2M_o, verificato con dati indipendenti. Questa relazione permette di ottenere velocemente una stima di M_o per terremoti recenti ed è applicabile in ogni regione dopo aver ricalibrato la costante. L’applicazione a sismogrammi registrati su strumenti meccanici ed elettromeccanici, raccolti in vari osservatori europei ha permesso di determinare il momento sismico di 25 terremoti verificatisi in Svizzera e nelle zone limitrofe durante il 20^o secolo. Attraverso l’ingrandimento digitale delle immagini dei sismogrammi si è potuta effettuare una precisa lettura dell’ampiezza e del periodo. Questo è stato successivamente corretto rispetto il periodo di riferimento T. Le magnitudini M_w ottenute risultano comprese tra 4.6 e 5.8, quest’ultima per il più forte terremoto avvenuto in Svizzera (1946, Vallese). L’incertezza della magnitudine determinata con questi strumenti è di circa 0.4. I valori di M_o ottenuti hanno permesso la calibrazione tra l’intensità ed il momento sismico per gli eventi pre-strumentali, utile all’aggiornamento del catalogo dei terremoti in Svizzera (ECOS). Precise relazioni tra in momento sismico e l’intensità sono fondamentali per ottenere stime affidabili del l’azzardo sismico in regioni a sismicità moderata e con lunghi tempi di ricorrenza.

Chapter 1
Introduction

In this thesis I present two methods to retrieve earthquakes source parameters (seismic moment M_o, depth and focal mechanism) for moderate to strong earthquakes from regional surface waves. The first method, described in chapters 3 and 4, performs fully automatic and near-real time waveform inversion for the seismic moment tensor. The primary motivation is to provide rapid magnitude and depth estimates after strong and potentially damaging events to assist disaster relief agencies’ response efforts. The second method, described in chapter 5, retrieves M_o from surface wave amplitudes and can be applied to digital broad band seismograms or to early-instrumental analog seismograms. Here, this method is applied to derive M_o from 20^th century analog data, that are crucial for long term seismic hazard studies in areas characterized by low and moderate seismicity.

Fast intervention of disaster relief agencies needs accurate M_o and depth estimates within a short time after a potentially destructive event. In the European-Mediterranean area seismicity is mainly located in the eastern Mediterranean Sea (Figure 1.1), where several destructive earthquakes (e.g. the M_w = 7.6 August 17, 1999 Izmit event) occurred during the last years. In Europe and in the central and western Mediterranean Sea seismicity is lower, but strong destructive earthquakes are not rare (e.g. the M_w = 6.0 September 6, 2002 Molise, the M_w = 7.0 May 21, 2003 Northern Algeria and the M_w = 6.4 February 24, 2004 Morocco earthquakes). When such an earthquake occurs, tele-communications in and around the epicentral area are often interrupted. Magnitude and depth estimates, that are crucial for damage evaluation, can then be estimated only using far-field seismological data. Moment tensor (MT) analysis is particularly well suited because MT inversion prevents underestimation of the magnitude compared to the standard location techniques, since moment tensor derived seismic moment of large events does not saturate (Kanamori, 1977).

Fast size and depth estimates are also important after moderate events that do not cause serious damages, but are widely felt. Thanks to the world-wide-web, people search for information immediately after a felt earthquake. In Europe even after a moderate event, a large number of people want to be quickly informed about its magnitude and its consequences. For this reason the press, police and civil protection agencies need fast and precise information about location, size and depth of the earthquake. An example is the recent M_w = 4.5 February 23, 2004 Rigney eastern France event, that was felt over the western part of Switzerland. Within minutes the Swiss Seismological Service got swamped with calls from concerned people and press, and the web-server was heavily accessed.

Quick moment tensor solutions are routinely provided by several groups at a global scale but only for large events (M_w > 5.5). These solutions are disseminated only after revision by a seismologist. Moment tensor solutions for moderate (M_w > 4.8) events in the European-Mediterranean region are now provided by the Swiss Seismological Service, the Italian INGV and the Spanish IGN. Such solutions are computed manually and only for the more relevant earthquakes the moment tensor is available within hours after event origin time, while other earthquakes are analyzed with a delay of weeks to months. The routine presented here computes fully automatic moment tensors from earthquake alert detection, to data collection, moment tensor inversion, solution assessment and finally solution dissemination (via e-mail and web). Computing fully automatic, near-real time moment tensors for a moderate event (4.5 < M_w < 5.0) requires near-real time access to dense networks of broadband and high dynamic range seismometer at regional distance ( < 20^o). Significant technological improvements and infrastructure investments during the last few years in the European-Mediterranean area allowed the development and implementation of the procedure described here.

The seismic moment tensor provides not only size and depth estimates to alert disaster relief agencies. Earthquake focal mechanisms, that can be obtained from the seismic moment tensor, provides indispensable information for seismotectonic studies, e.g. for stress field estimation in Switzerland (Kastrup et al., 2004). The strain rate tensor, that can be computed from the moment tensor, combined with GPS measurements and geological data can then be used to infer deformation fields of the crust, e.g. for deformation fields in the eastern Mediterranean See (Jenny et al., 2004). Seismic hazard studies then need accurate magnitude and depth estimates. The automatic routine presented here, will over time result in a complete moment tensor catalog that includes also moderate events, which are significant for regions of low and moderate seismicity.

The Swiss Seismological Service evaluates the seismic hazard in Switzerland. Accurate seismic hazard maps are indispensable for defining building codes in densely populated and industrialized regions or nuclear power plant construction requirements. An example is the Basel area, where strong destructive earthquakes have occurred in the past (e.g. the M_w = 6.9 1356 event, which is the largest event known in Europe north of the Alps) and where numerous chemical plants are operating. To evaluate seismic hazard for such areas with long term recurrent seismicity, requires a complete earthquake catalog covering long time periods.

The Swiss Seismological Service recently completed a comprehensive up-date of the earthquake catalog of Switzerland and surrounding regions (Fäh et al., 2003). The catalog expresses the size of all events using moment magnitude (M_w). The largest part of the catalog includes pre-instrumental events where only epicentral intensities are available. For these events, the epicentral intensities were linked to the seismic moment using a epicentral intensity - seismic moment relation that was inferred using earthquakes with both epicentral intensity and seismic moment available. To enlarge this data-set, also the major 20^th century events that occurred within or near Switzerland were used. Seismic moment determination of these events constitutes the second large part of this thesis.

For these events, I collected analog seismograms from various observatories in Europe that were recorded on mechanical and electromagnetic seismographs for which the instrument response is well known and the instrument calibrations were available. Figure 1.2 shows an example of a Wiechert seismograph and one of its recordings. Because of the low quality of such records, a reliable digitization was not possible for most of the collected data-set and, thus, the moment tensor inversion technique could not be applied to derive M_o estimates for most of the events investigated. Nevertheless, accurate readings of amplitude and periods were possible. I thus developed a method to evaluate seismic moment (M_o) directly from surface wave amplitude. The method, developed using broad-band digital seismograms of recent events, was then applied to the early-instrumental seismograms of the 20^th century major Swiss events.

Chapter 2
Brief overview of seismic moment tensor

(2.1)

,

(2.2)

(2.3)

(2.4)

A moment tensor can be decomposed into elementary tensors following two different approaches: a pure mathematical decomposition or a decomposition into source components with a physical meaning (e.g. double-couple, explosion, tension crack components, etc.). The decomposition into physical sources is not unique. The paper of Jost & Herrmann (1989) gives an excellent overview on the different decomposition methods that are generally applied in seismology. The MT decomposition performed in this thesis is described in the next paragraphs. Generally the MT can be decomposed uniquely into an isotropic and a deviatoric part. In order to derive a general formulation of the moment tensor decomposition, let m_i be the eigenvalues corresponding to the orthogonal eigenvector a_i = (a_ix,a_iy,a_iz)^T of M _pq. Using the orthogonality of the eigenvectors, we can write the principal axis transformation of M in reverse order as:

(2.5)

(2.6)

(2.7)

In this study the deviatoric part is decomposed into a double-couple component and a compensated linear vector dipole (CLVD) (Knopoff & Randall, 1970). Assuming |m₃^*|<|m ₂^*|<|m ₁^*| the deviatoric part can be rewritten as

(2.8)

(2.9)

(2.10)

The focal mechanism (strike, dip and slip) of the earthquake can be solved from the six elements of the seismic moment tensor:

(2.11)

The magnitude of an earthquake can be expressed in term of scalar seismic moment M_o that can be determined from the seismic moment tensor:

(2.12)

(2.13)

(2.14)

A more extensive and detailed description of the seismic moment tensor can be found in Jost & Herrmann (1989), Dahlen & Tromp (1998) and in Aki & Richards (2002). For details of the MT code see Giardini (1992).

Chapter 3
Automatic regional moment tensor inversion in the European-Mediterranean region

3.1 Summary

We produce fast and automatic moment tensor solutions for all moderate to strong earthquakes in the European-Mediterranean region. The procedure automatically screens near real-time earthquake alerts provided by a large number of agencies. Each event with magnitude M > 4.7 triggers an automatic request for near real-time data at several national and international data centers. Moment tensor inversion is performed using complete regional long period (50 - 100 s) waveforms. Initially the data are inverted for a fixed depth to remove traces with a low signal-to-noise ratio. The remaining data are then inverted for several trial depths to find the best-fit depth. Solutions are produced within 90 minutes after an earthquake. We analyze the results for the April 2000 to April 2002 period to evaluate the performance of the procedure. For quality assessment, we compared the results with the independent Swiss regional moment tensor catalog (SRMT) and divided the 87 moment tensor solutions into three groups: 38 quality A with well-resolved M_w, depth and focal mechanism; 21 quality B with well-resolved M_w; and 28 unreliable quality C solutions. The non-homogeneous station and event distribution, varying noise level, and inaccurate earthquake locations affected solution quality. For larger events (M_w > 5.5) we consistently obtained quality A solutions. Between M_w = 4.5 - 5.5 we obtained quality A and B solutions. Solutions that pass empirical rules mimicking the a posteriori quality for our data set are automatically disseminated.

3.2 Introduction

Quick and accurate source parameter determination (magnitude, depth and focal mechanism) provides important information for fast intervention in areas strongly damaged by large earthquakes. When compared to standard determination of earthquake location and magnitude, moment tensor inversion usually provides more accurate source parameters and particularly so for the size of large events, since their moment magnitudes M_w do not saturate (Kanamori, 1977). The recent increase in the number of near real-time accessible broadband stations in the European-Mediterranean region now allows automatic, near real-time moment tensor analysis monitoring strong events.

Accurate and quick moment tensor inversion is routinely performed on a global scale by the Harvard Centroid-Moment Tensor (CMT) project (Dziewonski et al., 1981; Dziewonski & Woodhouse, 1983), the United States Geological Survey (Sipkin, 1982, 1986) and the Earthquake Research Institute (ERI), Japan (Kawakatsu, 1995). These approaches use teleseismic data, limiting analysis to stronger earthquakes (M_w > 5.5). Analysis of smaller earthquakes requires data recorded at regional distances, which is becoming possible with the growing number of broadband seismic networks. Several groups in the United States (Dreger & Helmberger, 1993; Ritsema & Lay, 1993; Romanowicz et al., 1993; Náblek & Xia, 1995; Braunmiller et al., 1995; Thio & Kanamori, 1995; Dreger et al., 1995; Pasyanos et al., 1996) and Japan (Kubo et al., 2002), routinely invert for the seismic moment tensor using seismic data recorded at near regional distances ( < 10^o).

In the European-Mediterranean region, event-station distances are generally larger ( > 10^o) than in the western United States. However, several studies (Arvidsson & Ekstrom, 1998; Braunmiller, 1998) showed that source parameters of moderate events can be determined routinely with long period regional data (T > 30 - 40s) for larger event-station distances. The Swiss Seismological Service (Braunmiller et al., 2000, 2002) and the Italian Istituto Nazionale di Geofisica e Vulcanologia (INGV) (Pondrelli et al., 2002) now routinely produce moment tensor solutions in the European-Mediterranean area for moderate to strong earthquakes (M_w > 4.5), and smaller earthquakes (M_w > 3.0) in the Alpine area (Braunmiller et al., 2000, 2002). Small to moderate earthquakes in the western Mediterranean region are regularly processed by the Spanish Instituto Andaluz de Geofísica (Stich et al., 2003).

Here we test whether the current near real-time data availability and location accuracy are sufficient for automatic regional moment tensor retrieval using intermediate to long period surface waves (50 - 100 s). Our goal is to develop a robust procedure that provides fully automatic, fast and reliable solutions for moderate to strong earthquakes in the European-Mediterranean region.

Our automatic procedure consists of two main parts: first, moment tensor inversion for a detected earthquake and second, automatic quality assessment of the solution. We first describe the method and show the reliability of the automatic solutions. Then we present empirical rules for automatic quality assessment. Finally, we discuss source parameters (focal mechanism, depth and M_w) and investigate factors that affect solution quality.

3.3 Data and method

Ultimately, we like to obtain a moment tensor within a few minutes after an event. This requires on-line data access to stations at close epicentral distances, currently unavailable for most of our study region. We anticipate that present waiting periods due to sparse networks and time delays for data acquisition will shorten considerably in the future.

3.3.1 Data acquisition

Automatic moment tensor inversion consists of several steps (Figure 3.1). A few minutes after an event, an automatic earthquake alert (location, magnitude) is generally available, provided by the Swiss Seismological Service (SED) and other agencies linked to our institute. Automatic information coming from many agencies may include false alarms, but guarantees that we miss no significant event. We screen incoming information and any event in the European-Mediterranean area (22^o < Lat < 68^o,-25^o < Long < 60^o) with magnitude M > 4.7, independent of magnitude type [M_L,m_b,M_S], starts the routine automatically.

We invert complete broadband waveforms recorded at regional epicentral distances ( < 20^o); therefore, our data window is 30 minutes long. We wait an additional 20 minutes to assure data availability (Figure 3.1) before sending data requests to the AutoDRM (Kradolfer, 1996) of several international (ORFEUS, USGS) and national data centers (in Austria, Czech Republic, Germany, Israel, Norway, Switzerland) that provide near real-time broadband seismograms. The data centers automatically process these requests and usually within 20 minutes all available seismograms are received at our server to be stored and prepared for inversion. 70 minutes after event origin time, data acquisition is considered complete and the inversion starts, resulting in an automatic moment tensor solution within 90 minutes after an earthquake.

Between April 2000 and April 2002 only stations in central and northern Europe, Israel, the Caucasus region and Russia provided near real-time data (black triangles in Figure 3.2). Data availability and the response time of data centers varied. To ensure that we received a sufficient number of seismograms, we chose a relatively long waiting period before requesting data and starting the inversion. Stations in the western and central Mediterranean Sea, Turkey and eastern Europe (white triangles in Figure 3.2), became available during mid-2002 and are only shown to illustrate the evolving and improving station coverage.

3.3.2 Algorithm

The algorithm uses intermediate to long period three-component regional data. The inversion code, described in Giardini (1992), has already been applied to many earthquakes (Giardini, 1992; Giardini et al., 1993a,b; Sicilia, 1999). Synthetic seismograms are generated by normal mode summation (Woodhouse, 1988) computed for the PREM-Earth model (Dziewonski & Anderson, 1981) at different source depths and stored in libraries for quick access. The moment tensor is constrained to be deviatoric. We do not invert for the source centroid but compute time corrections by re-aligning data and synthetics (Giardini, 1992). Depth is retrieved by minimizing the normalized variance (defined as ratio of variance over data vector norm) for different trial depths.

3.3.3 Inversion

The moment tensor inversion automatically starts 70 minutes after an event (Figure 3.1). The alert is the first available location, which is not necessarily the best epicenter estimate. 70 minutes after an event, several automatic and/or manual locations are usually available and we choose the a priori most accurate. We prefer a location from a network that surrounds the epicenter. When that is not available, we look for a manual location or one provided by an agency with a large aperture network.

The seismograms are bandpass filtered between 50 and 100 s period. A lowpass filter at 50 s applied to regional seismograms minimizes the effect of inaccurately known propagation paths and allows moment tensor retrieval of moderate sized earthquakes (M_w > 4.5) with a simple average 1D velocity model (Arvidsson & Ekstrom, 1998). We tested other filter parameters and report results in Section 3.5.2.

The automatic inversion consists of two main steps. First, the entire data set is inverted for a fixed depth (18 km) to remove traces with a low signal-to-noise ratio (high normalized variance > 0.8) and large re-alignment. From tests we found, that the choice of the fixed depth - 18 km or different depth - has little effect on the remaining data set and basically no effect on our results. The remaining traces are then inverted for several depths. The 50 - 100 s data have little depth resolution, because long period surface-wave excitation functions have little depth variation. Thus, we apply a limited number of depth-steps with increasing step width (10, 14, 18, 25, 31, 42, 55, 75, 100, 125, 150, 175 and 200 km) to find the best fitting depth. We use a minimum 10% variance increase to estimate depth uncertainty; our uncertainty range is simply defined by the trial depths that just exceed the 10% increase. We consider this uncertainty estimate conservative, since the waveform fit degrades visibly.

3.4 Quality assessment of results

We started our procedure for automatic moment tensor inversion in April 2000. By April 2002, we obtained 87 moment tensor solutions (Figure 3.2, Table 3.1), mainly for events in the seismically active central-eastern Mediterranean region (Jackson & McKenzie, 1988).

We check the quality of the automatic moment tensors because solution accuracy depends on event location, location precision, station distribution and signal strength. First, we use an independent high-quality moment tensor catalog to quantify true quality. Second, to estimate solution quality automatically, we derive rules from solution parameters which reproduce overall true quality. These rules are applied automatically before disseminating solutions.

3.4.1 True quality

The Swiss automatic moment tensor (SAMT) catalog contains many moderate events not included in global catalogs, incomplete below M_w = 5.5 and with very few M_w < 5.0 events. Therefore, we compared our automatic solutions with those of the Swiss Seismological Service’s regional moment tensor (SRMT) catalog. The SRMT covers the European-Mediterranean area and is nearly complete down to m_b = 4.5 (Braunmiller et al., 2002). SRMT solutions are derived with a more complete data set available weeks to months after an event than the data set used for SAMT analysis. SRMT solution quality is high based on comparison with other independent source parameter estimates available for selected events (Braunmiller et al., 2002). For a few events east of SRMT coverage (> 55^oE), we compared our solutions with the Harvard catalog, or when not available, with magnitudes given by the USGS.

Figure 3.3: Sketch of true quality assignment. True quality of each automatic solution is based on mean principal axes’ orientation |Ax|, depth |z| and magnitude |Mw| differences relative to SRMT solutions (see text for details). Dark grey shaded area corresponds to true quality A, light grey to true quality B and white to true quality C.

The true quality of a SAMT solution is estimated by comparing its focal mechanism, depth and M_w relative to the SRMT solution. We distinguish three quality levels: A has well-resolved mechanisms, depths and M_w, B has only well-resolved M_w, and C is unreliable. Figure 3.3 provides a sketch  of the quality criteria described below.

The most stable focal mechanism parameters are the double couple part and the principal axes’ orientation. Moment tensor solutions for the same earthquake included in different catalogs may show differences in the non-double couple part (ratio of smallest to largest moment tensor eigenvalues following Dziewonski et al. (1981)). These differences are often introduced by an inaccurate source location (Zhang & Lay, 1990), differences in the station configuration (ílený & Vavryuk, 2002), inaccurate path-models (Henry et al., 2002; Fröhlich, 1994) and a poor resolution of M_r and M_r (Kuge & Lay, 1994). We therefore use mean axes’ difference |Ax|, defined as the average of the differences in principal axes’ orientation, to estimate the similarity between SAMT and SRMT focal mechanisms.

The mean difference |Ax| is zero for identical axes’ orientations. Interchanging two axes (for example changing a normal to a thrust or a left lateral to a right lateral mechanism) results in |Ax| = 60^o. We thus require A quality solutions to have |Ax|< 30^o; solutions with |Ax| > 30^o are either B or C quality, depending on the magnitude difference (Figure 3.3). Figure 3.4 (top) shows the distribution of |Ax|. For quality A solutions the mean value of |Ax| is 18.8^o ± 6.7^o. Two solutions with |Ax|< 30^o are not quality A, because one violates the depth (quality B) and one the magnitude criterion (quality C).

Figure 3.4: Top: Mean principal axes’ orientation difference |Ax| relative to SRMT for true quality A, B and C. Middle: Depth difference |z| relative to SRMT. Solutions are divided into two panels: left panel shows the number of quality A, B and C solutions where the SAMT depth uncertainty range includes the SRMT depth. Right panel shows |z| for SRMT depth estimates outside SAMT depth uncertainty range. Bottom: |Mw| relative to SRMT. Not all B and C solutions are shown in each panel. See text for details. Color scale as in Figure 3.2.

We also checked the focal parameter agreement between the SAMT and SRMT catalogs using the radiation pattern coefficient _P (Kuge & Kawakatsu, 1993), a parameter describing the radiation pattern similarity of two mechanisms. Our median _P = 0.85 for A quality solutions compares well with the median of _P = 0.88 found by Helffrich (1997) who compared ERI, Harvard and USGS catalogs for shallow earthquakes (most SAMTs are for shallow earthquakes).

Because of the low-depth resolution and the discrete set of trial depths, we require that the difference |z| between SAMT depth range (best-fit depth plus uncertainty) and SRMT depth is < 10 km for an A quality solution. A similar scheme was proposed by Kubo et al. (2002) when comparing the Japanese regional NIED catalog with the Harvard-CMT and the Japanese Meteorological Agency (JMA) focal mechanism catalog. Differences |z| > 10 km result in B or C solutions (Figure 3.3). Figure 3.4 (middle) shows |z| for the three quality groups.

The difference between SAMT and SRMT M_w estimates must be < 0.2 units for an A or B quality solution (M_w = - 10.73 following Kanamori (1977)). A required difference |M_w|< 0.2 is consistent with Pasyanos et al. (1996), who found that automatic and revised regional MT solutions in northern California have M_w estimates that usually differ by less than 0.2 units even when the focal mechanism and depth estimates differ strongly. M_w depends mainly on the signal amplitude and is therefore the parameter easiest to resolve. One goal for our automatic procedure is to provide robust M_w values so that disaster relief agencies may quickly estimate possible earthquake damages. Damages are governed by the rupture process and local site effects; our M_w can only help to estimate whether no, local or widespread damages are expected. Therefore we accept an M_w estimate as accurate even when the focal mechanism and/or the depth exceed their A-quality threshold: these are our quality B solutions. |M_w| > 0.2 are quality C, irrespective of focal mechanism and depth (Figure 3.3). The distribution of |M_w| is shown in Figure 3.4 (bottom).

For our data we observe that SAMTs with |Ax|< 30^o usually have |z|< 10 km and |M_w|< 0.2. Based on our rules, the 87 automatic moment tensors are divided into 38 quality A, 21 quality B and 28 quality C solutions.

3.4.2 Automatic assigned quality

The true quality can be verified only a posteriori. For automatic solution dissemination, we derive empirical rules, matching the a posteriori true qualities that can be implemented into the automatic procedure. The rules follow three principles: (1) applied to the whole data set, the rules should closely follow the true quality; (2) the rules should not overestimate quality: true quality B solutions should not be assigned A^a, and quality C should not be assigned A^a or B^a (we use the superscript ^a to denote assigned quality). We want to have high confidence that an automatic A^a solution is truly A; (3) the rules should be simple.

A combination of number of stations and components used (i.e., with good signal-to-noise ratio) provides a simple yet reasonably accurate measure to assess solution quality (Table 3.2). The empirical rules were defined based on the April 2000 to April 2002 data set and may be modified when, for example, station availability increases. Figure 3.5 shows that it is generally sufficient to use 2 or more components for each station to obtain quality A solutions even when only a few stations can be used. Using fewer stations and components results in lower quality solutions. Many solutions of earthquakes located in the larger Iran area result in quality B or C, because of the few stations available. For the southern Aegean Sea (34^o < Lat. < 38.5^o; 20^o < Long. < 30^o) we observe an interesting difference: we need more stations and components to obtain true quality A solutions (Figure 3.5). This exception is possibly due to large event-station distances (Figure 3.2).

3.5 Discussion

3.5.1 Performance

In this section we focus on the geographical event distribution and factors that cause low true quality solutions. We also compare our M_w, depths and focal mechanisms results with the SRMT, the Harvard (CMT) and INGV (MEDNET) moment tensor results to illustrate their high consistency.

Figure 3.6: Cumulative number of stations used to obtain all quality A (black) and B (grey) solutions versus distance from epicenter. Most BB stations are located in areas of lower seismicity (Figure 3.2) resulting in large event-station distances. Obtaining more high-quality solutions or successfully analyzing smaller events in the future critically hinges on improved availability of nearby ( < 7o) stations.

The distribution of the analyzed events (circles, Figure 3.2) reflects long-term seismicity (Jackson & McKenzie, 1988). The distribution of high quality solutions, however, is also affected by the station distribution (black triangles, Figure 3.2). Generally, analysis is hampered by long average event-station distances (Figure 3.6). Most data come from stations at distances > 7^o with a peak around = 14^o - 15^o caused by high seismicity in the Aegean Sea and high station density in central Europe. Most high quality solutions are produced for earthquakes in the central-eastern Mediterranean region, where data from stations in central Europe, Israel, the Caucasus region and Russia provide good azimuthal coverage. In the western Mediterranean region, seismicity is relatively low and the inadequate station distribution resulted in a quality B solution for the one event analyzed. Station coverage for events in the Caspian Sea and Zagros mountain regions is also low and few of the frequent events have well-recovered source parameters. In central and northern Europe we obtained few high quality automatic solutions. Although a large number of stations is available, there, the lowpass filter at 50 s precludes moment tensor retrieval for the typically smaller (M_w < 4.5) events of this region.

Not all events triggered by our automatic procedure resulted in a moment tensor. Triggered events result in no-solution when either (1) no data are available, (2) the automatic alert is a false alarm, (3) the epicenter is strongly mislocated, (4) the true magnitude is far lower than the alert magnitude or when any of these cases combine. Case (4) caused most no-solution events due to the low trigger-threshold set for analysis (M > 4.7), that assures the processing of all stronger events. We let the procedure decide whether a solution can be produced or not. For a few smaller events, few traces containing only long-period noise were inverted, resulting in quality C solutions.

Figure 3.7: Automatic Mw estimates relative to SRMT (top), CMT (middle) and MEDNET (bottom). Mean difference (), standard deviation (), slope and intercept of the linear regression (y = a + b . x, dashed line) are computed for qualities A and B combined. Solid line represents a one-to-one relation. Color scale as in Figure 3.2.

Earthquake size is the most stable source parameter and a few, good signal-to-noise seismograms generally constrain the seismic moment M_o. Figure 4.12 shows the high correlation of the automatic M_w estimates relative to SRMT, CMT and MEDNET M_w’s. Mean differences are very small, < 0.02 relative to SRMT and CMT, and lower than 0.1 unit relative to MEDNET, with standard deviations close to 0.1. The linear regressions (dashed lines in Figures 4.12) have slopes close to 1 and small intercepts, roughly consistent with a one-to-one relation between the magnitude estimates. We did not interpret small apparent differences because the data set is too small. Mean differences and regressions were determined for A and B quality solutions combined, because we did not see any significant systematic difference in the A and B quality M_w estimates (Figure 3.4 bottom).

Quality A solutions were obtained for earthquakes from M_w = 4.5 to M_w = 7.0. In general larger events (M_w > 5.5) result in quality A solutions (Figure 3.8), and earthquakes with M_w < 5.5 result in quality A or B. We obtained 3 quality B solutions for earthquakes with M_w > 5.5; in all cases the lower quality was caused by the inaccurate quick location used for the inversion. We repeated the inversion with the PDE-location. In two cases we obtained A quality solutions. One case stayed B quality, because of |Ax| = 31^o, just outside the A quality criterion (|Ax|< 30^o); the depth and magnitude differences both satisfied the A quality criteria. The number of MT solutions and the ratio of A/B solutions decrease for earthquakes with M_w < 5.0 due to lower signal strength and the large event-station distances (Figure 3.6).

Figure 3.9 illustrates the limitations of long-period (T > 50 s) analysis with respect to magnitude or signal strength. Variance increases with decreasing event size, effectively setting the lower limit for retrieving MT solutions to M_w 4.5. At such long periods signal strength at smaller magnitudes is just slightly above the noise level. We also observe that variance for quality B is higher than it is for A solutions.

Figure 3.10: SAMT depth estimate differences for true quality A solutions relative to SRMT (top), CMT (middle) and MEDNET (bottom). Differences are small: mean differences (long dashes) are < 4 km with standard deviations (short dashes) < 15 km.

Long period surface waves offer only limited depth resolution (Giardini, 1992). However, depth of quality A solutions agree very well with those in SRMT, CMT and MEDNET (Figure 3.10). The mean difference is always < 4 km with a standard deviation < 15 km. Our SAMT catalog contains only 3 deep earthquakes with quality A and we observe no significantly greater depth estimate differences for these events. Events with large depth difference (|z|> 20) are different events in each panel, reflecting the depth differences in the catalogs used for comparison. Note that quality A solutions for shallow and deep earthquakes are always correctly distinguished.

Figure 3.11 shows the focal mechanisms of the true quality A solutions together with the available SRMT, CMT and MEDNET solutions. Focal mechanisms show excellent agreement for all earthquakes: shallow, deep, weak and strong. Larger differences exist for only 3 CMT solutions (Nr. 20, 33, 36). These earthquakes are small (M_w = 5.0 - 5.1) for CMT analysis. Their CMTs have large non-double couple parts (0.316 < < 0.342) and large relative moment tensor uncertainties E (0.261 < E < 0.673) compared to the average values = 0.124 and E = 0.165 of all 19589 CMT solutions (1976 until November 2002). E is defined in Davis & Fröhlich (1995). Moment tensors with high and E have poorly constrained focal parameters (Fröhlich et al., 1997).

3.5.2 Frequency band and location

Our goal is to retrieve as many quality A solutions as possible, even for smaller earthquakes (4.5 < M_w < 5.0), while minimizing the number of quality C solutions. Solution quality depends on station distribution, location accuracy and the ability to correctly match phases in the seismograms. For the given station distribution (Figure 3.2), we performed two tests. First, we tried to find the optimum frequency band for analysis with the quickly available locations and data set used for near real-time processing. The frequency band needs to match phases - easy at longer periods - and contain good signal-to-noise seismograms - higher at shorter periods. We thus performed inversions for 5 selected period ranges (40 - 60, 45 - 80, 50 - 100, 60 - 125, and 70 - 140 s). In a second step, we repeated the same analysis with the more accurate PDE-locations to see whether location accuracy affects the choice of frequency band.

Figure 3.12: Performance of the automatic MT inversion routine for 5 different period ranges with quickly available (top) and PDE (bottom) locations. From left to right: (1) number of true quality A, B and C solutions. (2) median values of the radiation pattern correlation coefficients P (quality A), vertical dashed line is median P = 0.88 obtained by Helffrich (1997) comparing ERI, Harvard and USGS catalogs. (3) mean depth differences z with error (quality A) (4) mean Mw difference Mw with standard deviation (quality A and B combined). P , z and Mw are relative to SRMT. Focal mechanism, depth and Mw estimates are well-constrained for all period ranges, but performance changes: with quickly available locations, the best period range for our inversions is 50 - 100 s, with PDE-locations 45 - 80 s. Color scale as in Figure 3.2.

The number of quality A, B and C solutions changes strongly with different frequency bands (Figure 3.12, top left). The largest number of quality A solutions (and highest ratio of A/C solutions) is obtained with the 50 - 100 s band for the quickly available locations. Using the more accurate PDE-locations, the optimal period range shifts to lower periods of 45 - 80 s (Figure 3.12, bottom left). The reason for this shift is that mislocation introduces errors in the initial phase that are then mapped onto the moment tensor. The effect is smaller at longer periods (Patton & Aki, 1979) and the accuracy of the quick locations sets the optimum period range to 50 - 100 s. At longer periods (60 - 125, 70 - 140 s) the number of quality A and B solutions decreases for the quick and the PDE-locations because of weak signals for the smaller events. At these period ranges, only stronger earthquakes can be analyzed.

For shorter periods (40 - 60 s), the number of quality A solutions decreases strongly even for the PDE-locations. In most cases, quality A solutions at 45 - 80 s (or 50 - 100 s) become B at 40 - 60 s (Figure 3.12, bottom left). At periods below 50 s, surface waves become more sensitive to crustal thickness and average crustal velocity variations so that significant travel-time differences relative to PREM result (Larson & Ekström, 2001; Pasyanos et al., 2001). Unresolved near-source earth structure may also cause surface wave amplitude anomalies (van der Lee, 1998). Both phase and amplitude differences limit reliable moment tensor retrieval below 50 s period for our uneven station distribution and our average event-station distances of about 1500 km.

The frequency band chosen has little effect on the overall quality of the focal mechanism and depth estimates for quality A solutions. This also holds for the M_w estimates for A and B solutions measured relative to SRMT (Figure 3.12). The median values of the radiation pattern coefficient _P are generally high, close to the value found by Helffrich (1997), and decrease only slightly for shorter periods. There is no significant change for the mean depth difference; all means are < 3 km with standard deviations < 15 km. Magnitude M_w differences for quality A and B solutions are close to 0.0 unit with standard deviation < 0.1.

From our tests, we deduce that the 50 - 100 s period range is the best average range with the quickly available locations for the entire European-Mediterranean region. It allows routine MT analysis for earthquakes down to M_w 4.5.

3.5.3 Current improvements

Two factors limit automatic retrieval of well-resolved MT for M_w > 4.5 earthquakes: location accuracy (Figure 3.12), usually lower for smaller events (M_w < 5.0) and the limited, inhomogeneous distribution of near real-time accessible stations (Figure 3.2).

Location accuracy is more important for shorter period analysis. Accurate quick locations are starting to become routinely available from the European-Mediterranean Seismological Center (EMSC). The EMSC merges automatic arrival-time picks from several European institutions, and the virtual network’s improved station coverage and aperture is capable of accurate automatic locations (Bossu et al., 2002). The locations we have received since June 2002 are of good quality.

The geographical distribution of near real-time accessible broadband stations is limited and inhomogeneous (Figure 3.2). In the context of the European MEREDIAN project (van Eck et al., 2001), the ORFEUS data center now has near real-time access to an increased (and still growing) number of broadband stations. Their distribution (white triangles, Figure 3.2) partially fills gaps like the western and central Mediterranean Sea, Turkey and eastern Europe. Northern Africa, however, lacks sufficient broadband instruments. For events since mid-2002, these data are available to us. Preliminary scanning of the results shows that the smaller epicentral distances overall and improved azimuthal coverage already increased the number of quality A relative to quality B and C solutions.

Better quick locations and a denser network (and the resulting reduced epicentral distances) also may speed up analysis and lower magnitude thresholds in the future. For closer epicentral distances, 15-minute seismograms contain the entire surface wave train. Reducing the seismogram length by 50% and assuming faster data accessibility, automatic solutions could then be obtained within 45 - 60 min after an event. At closer epicentral distances, signal strength is larger and relatively less perturbed by crustal and upper mantle heterogeneities. Combined with analysis at shorter periods, we would expect more reliable source parameter estimates for smaller events than possible now.

Although improved EMSC locations and additional data from ORFEUS started becoming available in mid-2002, we did not include these more recent events here. We wanted to have constant conditions - location and data access - for the entire period covered in this paper and therefore did not mix the two intervals.

3.6 Conclusions and outlook

We presented a fast and fully automatic procedure for moment tensor retrieval of moderate to strong (M_w > 4.5) earthquakes in the European-Mediterranean region using long-period (50 - 100 s) regional ( < 20^o) seismograms. Automatic solutions are currently available within 90 minutes after an event. From April 2000 to April 2002, we obtained 87 moment tensor solutions that we grouped into three qualities based on main stress axes’ orientation, depth and M_w similarity with an independent, high quality moment tensor catalog. For 38 quality A solutions, magnitude, depth and focal mechanisms are well-resolved; 21 B solutions have well-resolved magnitude; 28 C solutions are not reliable. We derived simple empirical rules based on the number of stations and components used to predict the quality of a solution without a seismologist’s interference. Automatic quality A^a MTs are disseminated to EMSC (http://emsc-csem.org), quality A^a and B^a solutions are displayed on our web page (http://www.seismo.ethz.ch/mt), A^a and B^a solutions can be obtained via e-mail (contact first author for details).

In the near future, we foresee largely improved near real-time automatic waveform analysis capabilities and successful routine MT applications to smaller earthquakes (M_w 4.0) for most of the European-Mediterranean region. Many national networks are transitioning to BB stations with near real-time data transmission. Connecting these national data centers via internet will create a dense European-wide virtual network that could be used, for near real-time event detection, size determination and MT inversion in the European-Mediterranean region. We can realize this scenario by increasing both the number of BB stations, particularly where no or few stations currently exist, and near real-time open access to these data for the scientific community.

Acknowledgments

We thank Daniel Stich and an anonymous reviewer for their constructive comments. We thank Suzan van der Lee and Yuan Gao for providing modified moment tensor analysis codes. We appreciate discussions with Günter Bock about the topic, we will miss him. We thank Kathleen J. Jackson for enhancing the manuscript by correcting our grammar. Most figures were produced with GMT (Wessel & Smith, 1995). High quality near real-time broadband data were obtained from the following institutions and networks: GEOFON, Potsdam (Germany); Gräfenberg Seismological Observatory, Erlangen (Germany); Institute of Physics of the Earth, Masaryk University, Brno (Czech Republic); MEDNET, Istituto Nazionale di Geofisica e Vulcanologia, Roma (Italy); National Data Center, Soreq (Israel); Zentralanstalt für Meteorologie und Geodynamik, Wien (Austria); and the additional members of the MEREDIAN consortium and its lead agency ORFEUS, De Bilt (The Netherlands). Quick earthquake locations are send to us by EMSC (France); Geol. Survey B-W, Freiburg (Germany); GERESS array (Germany); GSR, Obninsk (Russia); IGN, Madrid (Spain); INGV, Rome (Italy); IPRG, Tel Aviv (Israel); LDG, Paris (France); NEIC (USGS); NIEP, Bucharest (Romania); SDAC, Hannover (Germany); (see http://www.seismo.ethz.ch/redpuma).

Chapter 4
Automatic moment tensor analysis of moderate earthquakes

4.1 Summary

I present an improved automatic Frequency Adaptive Regional Moment Tensor (FARMT) routine. FARMT computes moment tensors (MT) of events with magnitude down to M_w 4.3 in the European - Mediterranean area using complete surface wave seismograms recorded at regional distances ( < 20^o). Two features lead to significant improvements of FARMT compared to the original standard routine (SR) for 4.3 < M_w < 4.7 events. First, the short-period cut-off at each station depends on station-event distance. Second, FARMT performs a signal-to-noise analysis to remove noisy traces and period-bands that do not exceed a minimum signal-to-noise ratio R_m. Tests performed to asses the short period cut-off and R_m for automatic FARMT indicate that the short period cut-off for events in the eastern Mediterranean Sea and the near East is 50 s. Events in Europe can be analyzed with a distance-variable short period cut-off ranging from 35 s for the closest to 50 s for distant stations. Values of R_m = 1 - 5 lead to well resolved mechanisms and use more seismograms for inversion than the standard method. The automatic FARMT uses R_m = 2, since it assures usage of seismograms with weak, often nodal signal, and reduces the number of iterations by about 20% to reach the final MT. For the May 2002 to September 2003 data-set, the automatic FARMT resulted in 66 solutions with well determined MT, which is a 20% increase relative to SR.

4.2 Introduction

Since April 2000, the Swiss Seismological Service (SED) computes real-time and fully automatic moment tensor (MT) solutions for M_w > 4.5 earthquakes in the European-Mediterranean area (Bernardi et al., 2004). Moment tensors are computed using 50 - 100 s period surface waves recorded at regional distances ( < 20^o). For stronger events (M _w > 5.5) the complete moment tensor (seismic moment M_o, depth and focal mechanism) is generally well resolved. For 4.5 < M_w < 5.5 events, M_o is generally well resolved while depth and focal mechanism resolution decreases with decreasing event size. Goal of this work is to improve the results for 4.5 < M_w < 5.5 events and to extend automatic analysis to even smaller events.

Fast and reliable MT analysis for moderate events in densely populated areas like central Europe is becoming a necessity for the seismological community to provide rapid information to the public. An example is the recent M_w = 4.5 February 23, 2004 Rigney, eastern France, event, that was felt over the entire western part of Switzerland. Within minutes the press and a large number of concerned people called the SED or connected to the SED’s web-page looking for information about the event. In addition to rapid information, efficient automatic MT analysis for M_w >~126' 4.5 events will relatively quickly lead to a MT catalog, even in areas with low seismicity, like most of the European - Mediterranean region that is indispensable for seismic hazard and seismotectonic studies.

The current routine - called standard routine (SR) here - satisfactorily analyzes only few events with M_w 4.8, because analysis is performed at a fixed period band of 50 - 100 s. The 50 - 100 s interval is the best single period interval for automatic MT computation in European and Mediterranean region (Bernardi et al., 2004), considering the sparse set of near-real time accessible stations, the limited accuracy of quick locations, and the complicated tectonic setting.

However, since 2002 the number of near-real time data has significantly increased in the European - Mediterranean region. Many of these stations are part of the Virtual European Broadband Seismograph Network (van Eck et al., 2004) and data can be collected in near-real time from the ORFEUS data-center. Accuracy of quick automatic locations for M > 4.5 events has significantly increased in the European - Mediterranean region because more stations contribute data resulting in a relatively dense, large aperture European network. The quick, more accurate locations, provided by EMSC (Maset-Roux & Bossu, 2004) and by ORFEUS (van Eck et al., 2004), together with the VEBSN data are key factors for automatic MT analysis of moderate events.

In this chapter, I present a modified procedure, which significantly lowers the magnitude threshold for automatic MT analysis toward M_w 4.3. For such small events, signal energy above 50 s is generally weak and MT analysis requires inclusion of shorter periods. Although more near-real time broad-band stations exist, improving azimuthal coverage and lowering event-station distances, the distribution is still not homogeneous resulting in event data-sets that include near and far stations. Thus, I derived a distance dependent short period cut-off, which allows an optimal period band setting for MT inversion using near and far stations simultaneously (Section 4.3). An additional short and/or long period cut-off depending on the signal-to-noise ratio is applied to remove those periods without sufficient signal (Section 4.4). The notation from chapter 3 is kept, quality A solutions have well resolved M_o, depth and focal mechanism, quality B only well resolved M_o, and quality C is not reliable. Quality is assessed relative to SRMT (Braunmiller et al., 2002).

4.3 Distance dependent short period cut-off

The standard routine SR uses a short period cut-off at 50 s for all event-station distances, ensuring synthetics and observed seismograms are in phase even for large distances ( 20^o). At shorter distances, PREM synthetics can probably be used at shorter periods (Braunmiller et al., 2002). The test data-set consists of 20 events covering the entire European - Mediterranean region . The data-set includes crustal and intermediate deep events and covers the magnitude range 4.5 < M_w < 6.7. The automatic SR resulted in quality A solutions for each event, implying that a sufficient number of seismograms (from 39 to 115) could be used for inversion in the 50 - 100 s pass band. The automatic moment tensors were then revised using the PDE-location, to exclude low quality waveform fit because of inaccurate locations. These solutions are used as reference (Table 4.1 and Figure 4.1).