@article{BlaserKruegerOhrnbergeretal.2010,
  author    = {Blaser, Lilian and Kr{\"u}ger, Frank and Ohrnberger, Matthias and Scherbaum, Frank},
  title     = {Scaling relations of earthquake source parameter estimates with special focus on subduction environment},
  issn      = {0037-1106},
  doi       = {10.1785/0120100111},
  year      = {2010},
  abstract  = {Earthquake rupture length and width estimates are in demand in many seismological applications. Earthquake magnitude estimates are often available, whereas the geometrical extensions of the rupture fault mostly are lacking. Therefore, scaling relations are needed to derive length and width from magnitude. Most frequently used are the relationships of Wells and Coppersmith (1994) derived on the basis of a large dataset including all slip types with the exception of thrust faulting events in subduction environments. However, there are many applications dealing with earthquakes in subduction zones because of their high seismic and tsunamigenic potential. There are no well-established scaling relations for moment magnitude and length/width for subduction events. Within this study, we compiled a large database of source parameter estimates of 283 earthquakes. All focal mechanisms are represented, but special focus is set on (large) subduction zone events, in particular. Scaling relations were fitted with linear least-square as well as orthogonal regression and analyzed regarding the difference between continental and subduction zone/oceanic relationships. Additionally, the effect of technical progress in earthquake parameter estimation on scaling relations was tested as well as the influence of different fault mechanisms. For a given moment magnitude we found shorter but wider rupture areas of thrust events compared to Wells and Coppersmith (1994). The thrust event relationships for pure continental and pure subduction zone rupture areas were found to be almost identical. The scaling relations differ significantly for slip types. The exclusion of events prior to 1964 when the worldwide standard seismic network was established resulted in a remarkable effect on strike-slip scaling relations: the data do not show any saturation of rupture width of strike- slip earthquakes. Generally, rupture area seems to scale with mean slip independent of magnitude. The aspect ratio L/W, however, depends on moment and differs for each slip type.},
  language  = {en}
}
@article{AlAtikAbrahamsonBommeretal.2010,
  author    = {Al Atik, Linda and Abrahamson, Norman A. and Bommer, Julian J. and Scherbaum, Frank and Cotton, Fabrice and Kuehn, Nicolas},
  title     = {The variability of ground-motion prediction models and its components},
  issn      = {0895-0695},
  doi       = {10.1785/gssrl.81.5.794},
  year      = {2010},
  language  = {en}
}
@article{ScherbaumDelavaudRiggelsen2009,
  author    = {Scherbaum, Frank and Delavaud, Elise and Riggelsen, Carsten},
  title     = {Model selection in seismic hazard analysis : an information-theoretic perspective},
  issn      = {0037-1106},
  doi       = {10.1785/0120080347},
  year      = {2009},
  abstract  = {Although the methodological framework of probabilistic seismic hazard analysis is well established, the selection of models to predict the ground motion at the sites of interest remains a major challenge. Information theory provides a powerful theoretical framework that can guide this selection process in a consistent way. From an information- theoretic perspective, the appropriateness of models can be expressed in terms of their relative information loss (Kullback-Leibler distance) and hence in physically meaningful units (bits). In contrast to hypothesis testing, information-theoretic model selection does not require ad hoc decisions regarding significance levels nor does it require the models to be mutually exclusive and collectively exhaustive. The key ingredient, the Kullback-Leibler distance, can be estimated from the statistical expectation of log-likelihoods of observations for the models under consideration. In the present study, data-driven ground-motion model selection based on Kullback-Leibler-distance differences is illustrated for a set of simulated observations of response spectra and macroseismic intensities. Information theory allows for a unified treatment of both quantities. The application of Kullback-Leibler-distance based model selection to real data using the model generating data set for the Abrahamson and Silva (1997) ground-motion model demonstrates the superior performance of the information-theoretic perspective in comparison to earlier attempts at data- driven model selection (e.g., Scherbaum et al., 2004).},
  language  = {en}
}
@article{KuehnScherbaumRiggelsen2009,
  author    = {K{\"u}hn, Nicolas M. and Scherbaum, Frank and Riggelsen, Carsten},
  title     = {Deriving empirical ground-motion models : balancing data constraints and physical assumptions to optimize prediction capability},
  issn      = {0037-1106},
  doi       = {10.1785/0120080136},
  year      = {2009},
  abstract  = {Empirical ground-motion models used in seismic hazard analysis are commonly derived by regression of observed ground motions against a chosen set of predictor variables. Commonly, the model building process is based on residual analysis and/or expert knowledge and/or opinion, while the quality of the model is assessed by the goodness-of-fit to the data. Such an approach, however, bears no immediate relation to the predictive power of the model and with increasing complexity of the models is increasingly susceptible to the danger of overfitting. Here, a different, primarily data-driven method for the development of ground-motion models is proposed that makes use of the notion of generalization error to counteract the problem of overfitting. Generalization error directly estimates the average prediction error on data not used for the model generation and, thus, is a good criterion to assess the predictive capabilities of a model. The approach taken here makes only few a priori assumptions. At first, peak ground acceleration and response spectrum values are modeled by flexible, nonphysical functions (polynomials) of the predictor variables. The inclusion of a particular predictor and the order of the polynomials are based on minimizing generalization error. The approach is illustrated for the next generation of ground-motion attenuation dataset. The resulting model is rather complex, comprising 48 parameters, but has considerably lower generalization error than functional forms commonly used in ground-motion models. The model parameters have no physical meaning, but a visual interpretation is possible and can reveal relevant characteristics of the data, for example, the Moho bounce in the distance scaling. In a second step, the regression model is approximated by an equivalent stochastic model, making it physically interpretable. The resulting resolvable stochastic model parameters are comparable to published models for western North America. In general, for large datasets generalization error minimization provides a viable method for the development of empirical ground-motion models.},
  language  = {en}
}
@article{KoehlerOhrnbergerScherbaum2009,
  author    = {Koehler, Andreas and Ohrnberger, Matthias and Scherbaum, Frank},
  title     = {Unsupervised feature selection and general pattern discovery using Self-Organizing Maps for gaining insights into the nature of seismic wavefields},
  issn      = {0098-3004},
  doi       = {10.1016/j.cageo.2009.02.004},
  year      = {2009},
  abstract  = {This study presents an unsupervised feature selection and learning approach for the discovery and intuitive imaging of significant temporal patterns in seismic single-station or network recordings. For this purpose, the data are parametrized by real-valued feature vectors for short time windows using standard analysis tools for seismic data, such as frequency-wavenumber, polarization, and spectral analysis. We use Self-Organizing Maps (SOMs) for a data-driven feature selection, visualization and clustering procedure, which is in particular suitable for high-dimensional data sets. Our feature selection method is based on significance testing using the Wald-Wolfowitz runs test for-individual features and on correlation hunting with SOMs in feature subsets. Using synthetics composed of Rayleigh and Love waves and real-world data, we show the robustness and the improved discriminative power of that approach compared to feature subsets manually selected from individual wavefield parametrization methods. Furthermore, the capability of the clustering and visualization techniques to investigate the discrimination of wave phases is shown by means of synthetic waveforms and regional earthquake recordings.},
  language  = {en}
}
@article{FaenzaHainzlScherbaum2009,
  author    = {Faenza, Licia and Hainzl, Sebastian and Scherbaum, Frank},
  title     = {Statistical analysis of the Central-Europe seismicity},
  issn      = {0040-1951},
  doi       = {10.1016/j.tecto.2008.04.030},
  year      = {2009},
  abstract  = {The aim of this paper is to characterize the spatio-temporal distribution of Central-Europe seismicity. Specifically, by using a non-parametric statistical approach, the proportional hazard model, leading to an empirical estimation of the hazard function, we provide some constrains on the time behavior of earthquake generation mechanisms. The results indicate that the most conspicuous characteristics of M-w 4.0+ earthquakes is a temporal clustering lasting a couple of years. This suggests that the probability of occurrence increases immediately after a previous event. After a few years, the process becomes almost time independent. Furthermore, we investigate the cluster properties of the seismicity of Central-Europe, by comparing the obtained result with the one of synthetic catalogs generated by the epidemic type aftershock sequences (ETAS) model, which previously have been successfully applied for short term clustering. Our results indicate that the ETAS is not well suited to describe the seismicity as a whole, while it is able to capture the features of the short- term behaviour. Remarkably, similar results have been previously found for Italy using a higher magnitude threshold.},
  language  = {en}
}
@article{DelavaudScherbaumKuehnetal.2009,
  author    = {Delavaud, Elise and Scherbaum, Frank and Kuehn, Nicolas and Riggelsen, Carsten},
  title     = {Information-theoretic selection of ground-motion prediction equations for seismic hazard analysis : an applicability study using Californian data},
  issn      = {0037-1106},
  doi       = {10.1785/0120090055},
  year      = {2009},
  abstract  = {Considering the increasing number and complexity of ground-motion prediction equations available for seismic hazard assessment, there is a definite need for an efficient, quantitative, and robust method to select and rank these models for a particular region of interest. In a recent article, Scherbaum et al. (2009) have suggested an information- theoretic approach for this purpose that overcomes several shortcomings of earlier attempts at using data-driven ground- motion prediction equation selection procedures. The results of their theoretical study provides evidence that in addition to observed response spectra, macroseismic intensity data might be useful for model selection and ranking. We present here an applicability study for this approach using response spectra and macroseismic intensities from eight Californian earthquakes. A total of 17 ground-motion prediction equations, from different regions, for response spectra, combined with the equation of Atkinson and Kaka (2007) for macroseismic intensities are tested for their relative performance. The resulting data-driven rankings show that the models that best estimate ground motion in California are, as one would expect, Californian and western U. S. models, while some European models also perform fairly well. Moreover, the model performance appears to be strongly dependent on both distance and frequency. The relative information of intensity versus response spectral data is also explored. The strong correlation we obtain between intensity-based rankings and spectral-based ones demonstrates the great potential of macroseismic intensities data for model selection in the context of seismic hazard assessment.},
  language  = {en}
}
@article{Scherbaum1997,
  author    = {Scherbaum, Frank},
  title     = {Zero Phase FIR filters in digital seismic acquisition systems : blessing or curse},
  year      = {1997},
  language  = {en}
}
@article{ScherbaumBouin1997,
  author    = {Scherbaum, Frank and Bouin, M. P.},
  title     = {FIR filter effects and nucleation phases},
  year      = {1997},
  language  = {en}
}
@article{ScherbaumKruegerWeber1997,
  author    = {Scherbaum, Frank and Kr{\"u}ger, Frank and Weber, Michael H.},
  title     = {Double beam imaging : mapping lower mantle heterogeneities using combinations of source and receiver arrays},
  year      = {1997},
  language  = {en}
}