Tsunami Simulation Using Sources Inferred from Various Measurement Data: Implications for the Model Forecast

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• 作者：Edison Gica (1) (2)
  Vasily V. Titov (2)
  Christopher Moore (2)
  Yong Wei (1) (2)
  
  1. Joint Institute for the Study of Atmosphere and Ocean ; University of Washington ; Seattle ; WA ; 98105 ; USA
  2. NOAA Center for Tsunami Research ; Pacific Marine Environmental Laboratory ; Seattle ; WA ; 98115 ; USA
  
• 关键词：DART inversion ; Finite Fault Model ; GPS solution ; Tsunami forecast
• 刊名：Pure and Applied Geophysics
• 出版年：2015
• 出版时间：March 2015
• 年：2015
• 卷：172
• 期：3-4
• 页码：773-789
• 全文大小：6,299 KB
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  6. Hayes, G. (2011), Finite Fault Model: Updated Result of the Mar 11, 2011 Mw 9.0 Earthquake Offshore Honshu, Japan, http://earthquake.usgs.gov/earthquakes/eqinthenews/2011/usc0001xgp/finite_fault.php.
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• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Geophysics and Geodesy
  
• 出版者：Birkh盲user Basel
• ISSN：1420-9136

文摘

Model forecast applications use various models of tsunami sources inferred from different measurement data. Even the same type of observation data can produce substantially different tsunami source models during a real-time forecast when more data are obtained during the real-time analysis. Improved tsunami observations enable investigation of the influence of such model source variability on the final forecast using different source data sets of several events. The 2010 Maule, Chile and 2011 Tohoku, Japan tsunamis were two recent events that provide ample observations throughout the Pacific and were, thus, used here to study the sensitivity of different model inputs for forecasting. The sources for these events were derived using the following three different methods: (1) real time or post event inversion of tsunameter water level data; (2) prediction of sea floor deformations via analysis of seismic wave forms and application of a finite fault model; and (3) prediction of sea floor deformation using real-time GPS data. For the March 11, 2011 Tohoku tsunami, two examples of each method are used, while for the February 27, 2010 Maule event, only one tsunameter inversion and one finite fault model method were used due to a much more limited data set. Observed data from the Deep-ocean Assessment and Reporting for Tsunamis (DART) network, Japan GPS buoys, and select tide gauges across the Pacific were compared with forecasts to assess the sensitivity of these three methods using root-mean-square error analysis. We divided the analysis by the type of data and the distance from the source. This sensitivity analysis showed that increasing the resolution of a tsunami source model does not necessarily improve tsunami forecast quality, even in the near-field. Instead, the findings suggest that when forecasting coastal impact, defining the overall energy characteristic of a tsunami source may be more important than refining small source details. Source models based on direct tsunami observations are better at reproducing a tsunami signal: this finding is not very surprising but has implications for tsunami forecasting and warning operations.