Skip to Main Content
Skip Nav Destination
GEOREF RECORD

A method of real-time tsunami detection using ensemble empirical mode decomposition

Yuchen Wang, Kenji Satake, Takuto Maeda, Masanao Shinohara and Shin'ichi Sakai
A method of real-time tsunami detection using ensemble empirical mode decomposition
Seismological Research Letters (July 2020) Pre-Issue Publication

Abstract

We propose a method of real-time tsunami detection using ensemble empirical mode decomposition (EEMD). EEMD decomposes the time series into a set of intrinsic mode functions adaptively. The tsunami signals of ocean-bottom pressure gauges (OBPGs) are automatically separated from the tidal signals, seismic signals, as well as background noise. Unlike the traditional tsunami detection methods, our algorithm does not need to make a prediction of tides. The application to the actual data of cabled OBPGs off the Tokohu coast shows that it successfully detects the tsunami from the 2016 Fukushima earthquake (M 7.4). The method was also applied to the extremely large tsunami from the 2011 Tohoku earthquake (M 9.0) and extremely small tsunami from the 1998 Sanriku earthquake (M 6.4). The algorithm detected the former huge tsunami that caused devastating damage, whereas it did not detect the latter microtsunami, which was not noticed on the coast. The algorithm was also tested for month-long OBPG data and caused no false alarm. Therefore, the algorithm is very useful for a tsunami early warning system, as it does not require any earthquake information to detect the tsunamis. It detects the tsunami with a short-time delay and characterizes the tsunami amplitudes accurately.


ISSN: 0895-0695
EISSN: 1938-2057
Serial Title: Seismological Research Letters
Serial Volume: Pre-Issue Publication
Title: A method of real-time tsunami detection using ensemble empirical mode decomposition
Affiliation: University of Tokyo, Earthquake Research Institute, Tokyo, Japan
Published: 20200722
Text Language: English
Publisher: Seismological Society of America, El Cerrito, CA, United States
References: 49
Accession Number: 2020-079369
Categories: Seismology
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. sketch map
N36°00'00" - N40°00'00", E140°00'00" - E144°00'00"
Secondary Affiliation: Hirosaki University, JPN, Japan
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2020, American Geosciences Institute. Abstract, Copyright, Seismological Society of America. Reference includes data from GeoScienceWorld, Alexandria, VA, United States
Update Code: 202022
Close Modal

or Create an Account

Close Modal
Close Modal