@article{BlaserOhrnbergerKruegeretal.2012, author = {Blaser, Lilian and Ohrnberger, Matthias and Kr{\"u}ger, Frank and Scherbaum, Frank}, title = {Probabilistic tsunami threat assessment of 10 recent earthquakes offshore Sumatra}, series = {Geophysical journal international}, volume = {188}, journal = {Geophysical journal international}, number = {3}, publisher = {Wiley-Blackwell}, address = {Malden}, issn = {0956-540X}, doi = {10.1111/j.1365-246X.2011.05324.x}, pages = {1273 -- 1284}, year = {2012}, abstract = {Tsunami early warning (TEW) is a challenging task as a decision has to be made within few minutes on the basis of incomplete and error-prone data. Deterministic warning systems have difficulties in integrating and quantifying the intrinsic uncertainties. In contrast, probabilistic approaches provide a framework that handles uncertainties in a natural way. Recently, we have proposed a method using Bayesian networks (BNs) that takes into account the uncertainties of seismic source parameter estimates in TEW. In this follow-up study, the method is applied to 10 recent large earthquakes offshore Sumatra and tested for its performance. We have evaluated both the general model performance given the best knowledge we have today about the source parameters of the 10 events and the corresponding response on seismic source information evaluated in real-time. We find that the resulting site-specific warning level probabilities represent well the available tsunami wave measurements and observations. Difficulties occur in the real-time tsunami assessment if the moment magnitude estimate is severely over- or underestimated. In general, the probabilistic analysis reveals a considerably large range of uncertainties in the near-field TEW. By quantifying the uncertainties the BN analysis provides important additional information to a decision maker in a warning centre to deal with the complexity in TEW and to reason under uncertainty.}, language = {en} } @article{HiemerRoesslerScherbaum2012, author = {Hiemer, Stefan and R{\"o}ßler, Dirk and Scherbaum, Frank}, title = {Monitoring the West Bohemian earthquake swarm in 2008/2009 by a temporary small-aperture seismic array}, series = {Journal of seismology}, volume = {16}, journal = {Journal of seismology}, number = {2}, publisher = {Springer}, address = {Dordrecht}, issn = {1383-4649}, doi = {10.1007/s10950-011-9256-5}, pages = {169 -- 182}, year = {2012}, abstract = {The most recent intense earthquake swarm in West Bohemia lasted from 6 October 2008 to January 2009. Starting 12 days after the onset, the University of Potsdam monitored the swarm by a temporary small-aperture seismic array at 10 km epicentral distance. The purpose of the installation was a complete monitoring of the swarm including micro-earthquakes (M (L) < 0). We identify earthquakes using a conventional short-term average/long-term average trigger combined with sliding-window frequency-wavenumber and polarisation analyses. The resulting earthquake catalogue consists of 14,530 earthquakes between 19 October 2008 and 18 March 2009 with magnitudes in the range of -aEuro parts per thousand 1.2 a parts per thousand currency signaEuro parts per thousand M (L) a parts per thousand currency signaEuro parts per thousand 2.7. The small-aperture seismic array substantially lowers the detection threshold to about M (c) = -aEuro parts per thousand 0.4, when compared to the regional networks operating in West Bohemia (M (c) > 0.0). In the course of this work, the main temporal features (frequency-magnitude distribution, propagation of back azimuth and horizontal slowness, occurrence rate of aftershock sequences and interevent-time distribution) of the recent 2008/2009 earthquake swarm are presented and discussed. Temporal changes of the coefficient of variation (based on interevent times) suggest that the swarm earthquake activity of the 2008/2009 swarm terminates by 12 January 2009. During the main phase in our studied swarm period after 19 October, the b value of the Gutenberg-Richter relation decreases from 1.2 to 0.8. This trend is also reflected in the power-law behavior of the seismic moment release. The corresponding total seismic moment release of 1.02x10(17) Nm is equivalent to M (L,max) = 5.4.}, language = {en} } @article{DelavaudScherbaumKuehnetal.2012, author = {Delavaud, Elise and Scherbaum, Frank and K{\"u}hn, Nicolas and Allen, Trevor}, title = {Testing the global applicability of ground-motion prediction equations for active shallow crustal regions}, series = {Bulletin of the Seismological Society of America}, volume = {102}, journal = {Bulletin of the Seismological Society of America}, number = {2}, publisher = {Seismological Society of America}, address = {El Cerrito}, issn = {0037-1106}, doi = {10.1785/0120110113}, pages = {707 -- 721}, year = {2012}, abstract = {Large research initiatives such as the Global Earthquake Model (GEM) or the Seismic HAzard haRmonization in Europe (SHARE) projects concentrate a great collaborative effort on defining a global standard for seismic hazard estimations. In this context, there is an increasing need for identifying ground-motion prediction equations (GMPEs) that can be applied at both global and regional scale. With increasing amounts of strong-motion records that are now available worldwide, observational data can provide a valuable resource to tackle this question. Using the global dataset of Allen and Wald (2009), we evaluate the ability of 11 GMPEs to predict ground-motion in different active shallow crustal regions worldwide. Adopting the approach of Scherbaum et al. (2009), we rank these GMPEs according to their likelihood of having generated the data. In particular, we estimate how strongly data support or reject the models with respect to the state of noninformativeness defined by a uniform weighting. Such rankings derived from this particular global dataset enable us to explore the potential of GMPEs to predict ground motions in their host region and also in other regions depending on the magnitude and distance considered. In the ranking process, we particularly focus on the influence of the distribution of the testing dataset compared with the GMPE's native dataset. One of the results of this study is that some nonindigenous models present a high degree of consistency with the data from a target region. Two models in particular demonstrated a strong power of geographically wide applicability in different geographic regions with respect to the testing dataset: the models of Akkar and Bommer (2010) and Chiou et al. (2010).}, language = {en} } @article{DelavaudCottonAkkaretal.2012, author = {Delavaud, Elise and Cotton, Fabrice and Akkar, Sinan and Scherbaum, Frank and Danciu, Laurentiu and Beauval, Celine and Drouet, Stephane and Douglas, John and Basili, Roberto and Sandikkaya, M. Abdullah and Segou, Margaret and Faccioli, Ezio and Theodoulidis, Nikos}, title = {Toward a ground-motion logic tree for probabilistic seismic hazard assessment in Europe}, series = {Journal of seismology}, volume = {16}, journal = {Journal of seismology}, number = {3}, publisher = {Springer}, address = {Dordrecht}, issn = {1383-4649}, doi = {10.1007/s10950-012-9281-z}, pages = {451 -- 473}, year = {2012}, abstract = {The Seismic Hazard Harmonization in Europe (SHARE) project, which began in June 2009, aims at establishing new standards for probabilistic seismic hazard assessment in the Euro-Mediterranean region. In this context, a logic tree for ground-motion prediction in Europe has been constructed. Ground-motion prediction equations (GMPEs) and weights have been determined so that the logic tree captures epistemic uncertainty in ground-motion prediction for six different tectonic regimes in Europe. Here we present the strategy that we adopted to build such a logic tree. This strategy has the particularity of combining two complementary and independent approaches: expert judgment and data testing. A set of six experts was asked to weight pre-selected GMPEs while the ability of these GMPEs to predict available data was evaluated with the method of Scherbaum et al. (Bull Seismol Soc Am 99:3234-3247, 2009). Results of both approaches were taken into account to commonly select the smallest set of GMPEs to capture the uncertainty in ground-motion prediction in Europe. For stable continental regions, two models, both from eastern North America, have been selected for shields, and three GMPEs from active shallow crustal regions have been added for continental crust. For subduction zones, four models, all non-European, have been chosen. Finally, for active shallow crustal regions, we selected four models, each of them from a different host region but only two of them were kept for long periods. In most cases, a common agreement has been also reached for the weights. In case of divergence, a sensitivity analysis of the weights on the seismic hazard has been conducted, showing that once the GMPEs have been selected, the associated set of weights has a smaller influence on the hazard.}, language = {en} }