TY - JOUR A1 - Scherbaum, Frank A1 - Cotton, Fabrice A1 - Staedtke, Helmut T1 - The estimation of minimum-misfit stochastic models from empirical ground-motion prediction equations N2 - In areas of moderate to low seismic activity there is commonly a lack of recorded strong ground motion. As a consequence, the prediction of ground motion expected for hypothetical future earthquakes is often performed by employing empirical models from other regions. In this context, Campbell's hybrid empirical approach (Campbell, 2003, 2004) provides a methodological framework to adapt ground-motion prediction equations to arbitrary target regions by using response spectral host-to-target-region-conversion filters. For this purpose, the empirical ground-motion prediction equation has to be quantified in terms of a stochastic model. The problem we address here is how to do this in a systematic way and how to assess the corresponding uncertainties. For the determination of the model parameters we use a genetic algorithm search. The stochastic model spectra were calculated by using a speed-optimized version of SMSIM (Boore, 2000). For most of the empirical ground-motion models, we obtain sets of stochastic models that match the empirical models within the full magnitude and distance ranges of their generating data sets fairly well. The overall quality of fit and the resulting model parameter sets strongly depend on the particular choice of the distance metric used for the stochastic model. We suggest the use of the hypocentral distance metric for the stochastic Simulation of strong ground motion because it provides the lowest-misfit stochastic models for most empirical equations. This is in agreement with the results of two recent studies of hypocenter locations in finite-source models which indicate that hypocenters are often located close to regions of large slip (Mai et al., 2005; Manighetti et al., 2005). Because essentially all empirical ground-motion prediction equations contain data from different geographical regions, the model parameters corresponding to the lowest-misfit stochastic models cannot necessarily be expected to represent single, physically realizable host regions but to model the generating data sets in an average way. In addition, the differences between the lowest-misfit stochastic models and the empirical ground-motion prediction equation are strongly distance, magnitude, and frequency dependent, which, according to the laws of uncertainty propagation, will increase the variance of the corresponding hybrid empirical model predictions (Scherbaum et al., 2005). As a consequence, the selection of empirical ground-motion models for host-to-target-region conversions requires considerable judgment of the ground-motion analyst Y1 - 2006 U6 - https://doi.org/10.1785/0120050015 ER - TY - JOUR A1 - Scherbaum, Frank A1 - Cotton, Fabrice A1 - Smit, P. T1 - On the use of response spectral-reference data for the selection and ranking of ground-motion models for seismic-hazard analysis in regions of moderate seismicity : the case of rock motion N2 - The use of ground-motion-prediction equations to estimate ground shaking has become a very popular approach for seismic-hazard assessment, especially in the framework of a logic-tree approach. Owing to the large number of existing published ground-motion models, however, the selection and ranking of appropriate models for a particular target area often pose serious practical problems. Here we show how observed around-motion records can help to guide this process in a systematic and comprehensible way. A key element in this context is a new, likelihood based, goodness-of-fit measure that has the property not only to quantify the model fit but also to measure in some degree how well the underlying statistical model assumptions are met. By design, this measure naturally scales between 0 and 1, with a value of 0.5 for a situation in which the model perfectly matches the sample distribution both in terms of mean and standard deviation. We have used it in combination with other goodness-of-fit measures to derive a simple classification scheme to quantify how well a candidate ground-rnotion-prediction equation models a particular set of observed-response spectra. This scheme is demonstrated to perform well in recognizing a number of popular ground-motion models from their rock-site- recording, subsets. This indicates its potential for aiding the assignment of logic-tree weights in a consistent and reproducible way. We have applied our scheme to the border region of France, Germany, and Switzerland where the M-w 4.8 St. Die earthquake of 22 February 2003 in eastern France recently provided a small set of observed-response spectra. These records are best modeled by the ground-motion-prediction equation of Berge-Thierry et al. (2003), which is based on the analysis of predominantly European data. The fact that the Swiss model of Bay et al. (2003) is not able to model the observed records in an acceptable way may indicate general problems arising from the use of weak-motion data for strong-motion prediction Y1 - 2004 SN - 0037-1106 ER - TY - JOUR A1 - Scherbaum, Frank A1 - Bouin, M. P. T1 - FIR filter effects and nucleation phases Y1 - 1997 ER - TY - JOUR A1 - Scherbaum, Frank A1 - Bommer, Julian J. A1 - Bungum, Hilmar A1 - Cotton, Fabrice A1 - Abrahamson, Norman A. T1 - Composite ground-motion models and logic trees: Methodology, sensitivities, and uncertainties N2 - Logic trees have become a popular tool in seismic hazard studies. Commonly, the models corresponding to the end branches of the complete logic tree in a probabalistic seismic hazard analysis (PSHA) are treated separately until the final calculation of the set of hazard curves. This comes at the price that information regarding sensitivities and uncertainties in the ground-motion sections of the logic tree are only obtainable after disaggregation. Furthermore, from this end-branch model perspective even the designers of the logic tree cannot directly tell what ground-motion scenarios most likely would result from their logic trees for a given earthquake at a particular distance, nor how uncertain these scenarios might be or how they would be affected by the choices of the hazard analyst. On the other hand, all this information is already implicitly present in the logic tree. Therefore, with the ground-motion perspective that we propose in the present article, we treat the ground-motion sections of a complete logic tree for seismic hazard as a single composite model representing the complete state-of-knowledge-and-belief of a particular analyst on ground motion in a particular target region. We implement this view by resampling the ground-motion models represented in the ground-motion sections of the logic tree by Monte Carlo simulation (separately for the median values and the sigma values) and then recombining the sets of simulated values in proportion to their logic-tree branch weights. The quantiles of this resampled composite model provide the hazard analyst and the decision maker with a simple, clear, and quantitative representation of the overall physical meaning of the ground-motion section of a logic tree and the accompanying epistemic uncertainty. Quantiles of the composite model also provide an easy way to analyze the sensitivities and uncertainties related to a given logic-tree model. We illustrate this for a composite ground- motion model for central Europe. Further potential fields of applications are seen wherever individual best estimates of ground motion have to be derived from a set of candidate models, for example, for hazard rnaps, sensitivity studies, or for modeling scenario earthquakes Y1 - 2005 SN - 0037-1106 ER - TY - JOUR A1 - Scherbaum, Frank T1 - Zero Phase FIR filters in digital seismic acquisition systems : blessing or curse Y1 - 1997 ER - TY - BOOK A1 - Scherbaum, Frank T1 - Of poles and zeros : fundamentals of digital seismology T3 - Modern approaches in geophysics Y1 - 2001 SN - 0-7923-6834-7 VL - 15 PB - Springer CY - Dordrecht ET - Rev. 2. ed., reprint with corr ER - TY - GEN A1 - Rößler, Dirk A1 - Hiemer, Stephan A1 - Bach, Christoph A1 - Delavaud, Elise A1 - Krüger, Frank A1 - Ohrnberger, Matthias A1 - Sauer, David A1 - Scherbaum, Frank A1 - Vollmer, Daniel T1 - Small-aperture seismic array monitors Vogtland earthquake swarm in 2008/09 N2 - The most recent intense earthquake swarm in the Vogtland lasted from 6 October 2008 until January 2009. Greatest magnitudes exceeded M3.5 several times in October making it the greatest swarm since 1985/86. In contrast to the swarms in 1985 and 2000, seismic moment release was concentrated near swarm onset. Focal area and temporal evolution are similar to the swarm in 2000. Work hypothysis: uprising upper-mantle fluids trigger swarm earthquakes at low stress level. To monitor the seismicity, the University of Potsdam operated a small aperture seismic array at 10 km epicentral distance between 18 October 2008 and 18 March 2009. Consisting of 12 seismic stations and 3 additional microphones, the array is capable of detecting earthquakes from larger to very low magnitudes (M<-1) as well as associated air waves. We use array techniques to determine properties of the incoming wavefield: noise, direct P and S waves, and converted phases. KW - Vogtland KW - Erdbebenschwarm 2008 KW - Arrayseismologie KW - Vogtland KW - West Bohemia KW - earthquake swarm KW - array seismology Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-29185 ER - TY - JOUR A1 - Runge, Antonia K. A1 - Scherbaum, Frank A1 - Curtis, Andrew A1 - Riggelsen, Carsten T1 - An interactive tool for the elicitation of subjective probabilities in probabilistic seismic-hazard analysis JF - Bulletin of the Seismological Society of America N2 - In probabilistic seismic-hazard analysis, epistemic uncertainties are commonly treated within a logic-tree framework in which the branch weights express the degree of belief of an expert in a set of models. For the calculation of the distribution of hazard curves, these branch weights represent subjective probabilities. A major challenge for experts is to provide logically consistent weight estimates (in the sense of Kolmogorovs axioms), to be aware of the multitude of heuristics, and to minimize the biases which affect human judgment under uncertainty. We introduce a platform-independent, interactive program enabling us to quantify, elicit, and transfer expert knowledge into a set of subjective probabilities by applying experimental design theory, following the approach of Curtis and Wood (2004). Instead of determining the set of probabilities for all models in a single step, the computer-driven elicitation process is performed as a sequence of evaluations of relative weights for small subsets of models. From these, the probabilities for the whole model set are determined as a solution of an optimization problem. The result of this process is a set of logically consistent probabilities together with a measure of confidence determined from the amount of conflicting information which is provided by the expert during the relative weighting process. We experiment with different scenarios simulating likely expert behaviors in the context of knowledge elicitation and show the impact this has on the results. The overall aim is to provide a smart elicitation technique, and our findings serve as a guide for practical applications. Y1 - 2013 U6 - https://doi.org/10.1785/0120130026 SN - 0037-1106 SN - 1943-3573 VL - 103 IS - 5 SP - 2862 EP - 2874 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Rodriguez-Marek, A. A1 - Rathje, E. M. A1 - Bommer, Julian J. A1 - Scherbaum, Frank A1 - Stafford, P. J. T1 - Application of single-station sigma and site-response characterization in a probabilistic Seismic-Hazard analysis for new uclear site JF - Bulletin of the Seismological Society of America N2 - Aleatory variability in ground-motion prediction, represented by the standard deviation (sigma) of a ground-motion prediction equation, exerts a very strong influence on the results of probabilistic seismic-hazard analysis (PSHA). This is especially so at the low annual exceedance frequencies considered for nuclear facilities; in these cases, even small reductions in sigma can have a marked effect on the hazard estimates. Proper separation and quantification of aleatory variability and epistemic uncertainty can lead to defensible reductions in sigma. One such approach is the single-station sigma concept, which removes that part of sigma corresponding to repeatable site-specific effects. However, the site-to-site component must then be constrained by site-specific measurements or else modeled as epistemic uncertainty and incorporated into the modeling of site effects. The practical application of the single-station sigma concept, including the characterization of the dynamic properties of the site and the incorporation of site-response effects into the hazard calculations, is illustrated for a PSHA conducted at a rock site under consideration for the potential construction of a nuclear power plant. Y1 - 2014 U6 - https://doi.org/10.1785/0120130196 SN - 0037-1106 SN - 1943-3573 VL - 104 IS - 4 SP - 1601 EP - 1619 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Rietbrock, Andreas A1 - Scherbaum, Frank T1 - Crustal scattering at the KTB from a combined microearthquake and receiver analysis Y1 - 1998 ER -