TY  - JOUR
A1  - Blaser, Lilian
A1  - Ohrnberger, Matthias
A1  - Krüger, Frank
A1  - Scherbaum, Frank
T1  - Probabilistic tsunami threat assessment of 10 recent earthquakes offshore Sumatra
JF  - Geophysical journal international
N2  - 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.
KW  - Probabilistic forecasting
KW  - Tsunamis
KW  - Early warning
KW  - Indian Ocean
Y1  - 2012
U6  - https://doi.org/10.1111/j.1365-246X.2011.05324.x
SN  - 0956-540X
VL  - 188
IS  - 3
SP  - 1273
EP  - 1284
PB  - Wiley-Blackwell
CY  - Malden
ER  -