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Earthquake Early Warning Systems: Current Status and Perspectives

Chapter

Abstract

As increasing urbanization is taking place worldwide, earthquake hazards post strong threats to lives and properties for urban areas near major active faults on land or subduction zones offshore. Earthquake early warning systems can be a useful tool for reducing earthquake hazards, if cities are favorably located with respect to earthquake sources and their citizens are properly trained to response to earthquake warning messages. The physical basis for earthquake early warning systems is well understood, namely, destructive S- and surface waves travel at about half the speed of the P-waves, and seismic waves travel at much slower speed than signals transmitted by telephones or radios.

At least three countries have earthquake early warning systems in operation: (1) Japan, (2) Mexico, and (3) Taiwan. These systems can provide a few seconds to several tens of seconds of warning for large earthquakes. With recent emphasis on real-time seismology, operators of many regional and local seismic networks are now upgrading their systems to reduce the time for issuing an earthquake notice from several minutes to under a minute, thus potentially making earthquake early warning a technical possibility. More significantly, a properly upgraded seismic network can provide a shake map within minutes after a disastrous earthquake, so that loss estimation from an earthquake can be quickly assessed to aid disaster response and recovery.

At present, the Seismic Alert System (SAS) in Mexico City is the only system issuing earthquake warning directly to the public. As it is appropriated for the International IDNDR-Con-ference on Early Warning Systems for the Reduction of Natural Disasters (EWC’98), we will discuss the societal experience of this system during the past few years.

Keywords

Early Warning Mexico City Bull Seism Early Warning System Radio Receiver 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  1. 1.U.S. Geological SurveyMenlo ParkUSA
  2. 2.Centro de Instrumentacion y Registro SismicoMexico, D.F.Mexico

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