Abstract
Reliable short-term tsunami forecast on the Kuril Islands when earthquakes occur in the Kuril-Kamchatka Trench is the most difficult. Forecasting by the traditional magnitude method often leads to false tsunami alarms. Based on the examples of the events of 2006, 2007 and 2020 on the Kuril Islands, as well as the event of 2018 in Alaska, it was shown that according to the data of the ocean level measuring stations closest to the tsunami source (tsunami travel time is 10–20 minutes) it is possible to adequately predict the tsunami near the coast. Calculations of tsunami waveforms near the coast from data containing seismic noise have shown that the resulting waveforms contain high-frequency oscillations. However, these fluctuations do not interfere with the assessment of the real waveform and the danger of the expected tsunami. In contrast to forecast methods based on the magnitude criterion, the applied method of short-term tsunami forecast makes it possible to calculate the waveform: the amplitudes of the first, maximum waves, their arrival time at a given point and the estimated duration of the tsunami. The proposed method can become a tool that will improve the quality of operational tsunami warning, significantly reducing the number of false tsunami alarms.
Highlights
Reliable short-term tsunami forecast on the Kuril Islands when earthquakes occur in the Kuril-Kamchatka Trench is the most difficult
Forecasting by the traditional magnitude method often leads to false tsunami alarms
Based on the examples of the events of 2006, 2007 and 2020 on the Kuril Islands, as well as the event of 2018 in Alaska, it was shown that according to the data of the ocean level measuring stations closest to the tsunami source it is possible to adequately predict the tsunami near the coast
Summary
Search Tsunami Events. URL: https://www.ngdc.noaa.gov/hazel/view/hazards/tsunami/event-search (accessed 6.11.2020) 2. National Data Buoy Center. URL: https://ndbc.noaa.gov/dart.shtml (accessed 6.11.2020) 3. NOAA Center for Tsunami Research: DART. URL: http://nctr.pmel.noaa.gov/Dart (accessed 6.11.2020)
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