JDR Vol.9 No.3 pp. 339-357
doi: 10.20965/jdr.2014.p0339


Review on Near-Field Tsunami Forecasting from Offshore Tsunami Data and Onshore GNSS Data for Tsunami Early Warning

Hiroaki Tsushima* and Yusaku Ohta**

*Meteorological Research Institute, Japan Meteorological Agency, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan

**Research Center for Prediction of Earthquakes and Volcanic Eruptions, Graduate School of Science, Tohoku University, 6-6 Aoba Aramaki-Aza, Aoba-ku, Sendai 980-8578, Japan

February 3, 2014
April 10, 2014
June 1, 2014
offshore tsunami observation, real-time GNSS (GPS), near-field tsunamis, tsunami early warning system, combination use

This paper reviews recent studies on methods of realtime forecasting for near-field tsunamis that use either offshore tsunami data or onshore global navigation satellite system (GNSS) data. Tsunami early warning systems for near-field coastal communities are vital because evacuation time before tsunami arrival is usually very short. We focus on forecasting between the occurrence of a tsunamigenic earthquake and the arrival of the first tsunami at a near-field coast – typically a few tens of minutes or less after the earthquake. Offshore tsunami measurement that provides coastal communities with direct information on impending tsunamis is very effective in providing reliable tsunami predictions. Crustal deformation due to coseismic slips at an earthquake fault detected by real-time GNSS analysis is quite useful in estimating fault expansion and the amount of slip, which in turn contributes to timely tsunami warnings, e.g., within 10 minutes, even for huge interplate earthquakes. Our review encompasses methods on the leading edge of research and those already in the process of being applied practically. We also discuss an effective combination of methods developed for mitigating tsunami disasters.

Cite this article as:
H. Tsushima and Y. Ohta, “Review on Near-Field Tsunami Forecasting from Offshore Tsunami Data and Onshore GNSS Data for Tsunami Early Warning,” J. Disaster Res., Vol.9, No.3, pp. 339-357, 2014.
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