- © 2009 by the Seismological Society of America
In their paper Strasser et al. (2009) discussed some basics of regression analysis and the impact of different techniques on the residuals of empirical attenuation equations. They provided a completely incorrect representation of the methods developed by Klügel et al. (2006) aimed at combining tradional deterministic and neodeterministic methods with advanced probabilistic data models into a probabilistic scenario-based risk assessment methodology. This method removes many of the simplifications associated with the traditional probabilistic seismic hazard analysis (PSHA) methodology. The authors make the assertion (pages 44 to 45) that we reduce the aleatory variability of empirical ground-motion models based on engineering grounds, referring to the numerical example that accompanied the description of our methodology. According to the authors, “sigma” is a seismological characteristic and cannot be reduced on engineering grounds. They arrived at the conclusion: “Therefore, the results given in Klügel et al. (2006) showing a large impact on the estimated standard deviation due to measurement errors in magnitude are not credible.” Although the distorted representation of our work seems to be only a minor detail in this paper, it is worth discussing, because some fundamentals of mathematical uncertainty analysis and its application in engineering sciences are involved. The problem is that despite all allegations by Strasser et al. (2009), we did not reduce the aleatory variability in ground-motion models.
In my comment I will first shortly summarize the basic contents of our paper (Klügel et al. 2006) and explain what we have really done in our numerical example. Then I will explain the Ang-Tang uncertainty model and how it should be used according to the intention of the authors of this model (Ang 1970; Ang and Tang 1975, 1984, 2006). The Ang-Tang model is the basic uncertainty model used in traditional PSHA. Some proponents of the traditional …