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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 12, issue 6
Nonlin. Processes Geophys., 12, 965–977, 2005
https://doi.org/10.5194/npg-12-965-2005
© Author(s) 2005. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
Nonlin. Processes Geophys., 12, 965–977, 2005
https://doi.org/10.5194/npg-12-965-2005
© Author(s) 2005. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.

  09 Nov 2005

09 Nov 2005

Earthquake forecasting and its verification

J. R. Holliday1,2, K. Z. Nanjo2,3, K. F. Tiampo4, J. B. Rundle1,2, and D. L. Turcotte5 J. R. Holliday et al.
  • 1Department of Physics, University of California, Davis, USA
  • 2Computational Science and Engineering Center, University of California, Davis, USA
  • 3The Institute of Statistical Mathematics, Tokyo, Japan
  • 4Department of Earth Sciences, University of Western Ontario, Canada
  • 5Geology Department, University of California, Davis, USA

Abstract. No proven method is currently available for the reliable short time prediction of earthquakes (minutes to months). However, it is possible to make probabilistic hazard assessments for earthquake risk. In this paper we discuss a new approach to earthquake forecasting based on a pattern informatics (PI) method which quantifies temporal variations in seismicity. The output, which is based on an association of small earthquakes with future large earthquakes, is a map of areas in a seismogenic region ("hotspots'') where earthquakes are forecast to occur in a future 10-year time span. This approach has been successfully applied to California, to Japan, and on a worldwide basis. Because a sharp decision threshold is used, these forecasts are binary--an earthquake is forecast either to occur or to not occur. The standard approach to the evaluation of a binary forecast is the use of the relative (or receiver) operating characteristic (ROC) diagram, which is a more restrictive test and less subject to bias than maximum likelihood tests. To test our PI method, we made two types of retrospective forecasts for California. The first is the PI method and the second is a relative intensity (RI) forecast based on the hypothesis that future large earthquakes will occur where most smaller earthquakes have occurred in the recent past. While both retrospective forecasts are for the ten year period 1 January 2000 to 31 December 2009, we performed an interim analysis 5 years into the forecast. The PI method out performs the RI method under most circumstances.

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