Articles | Volume 16, issue 12
https://doi.org/10.5194/nhess-16-2603-2016
https://doi.org/10.5194/nhess-16-2603-2016
Research article
 | 
09 Dec 2016
Research article |  | 09 Dec 2016

Tsunami arrival time detection system applicable to discontinuous time series data with outliers

Jun-Whan Lee, Sun-Cheon Park, Duk Kee Lee, and Jong Ho Lee

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Cited articles

Beltrami, G. M.: An ANN algorithm for automatic, real-time tsunami detection in deep-sea level measurements, Ocean Eng., 35, 572–587, 2008.
Beltrami, G. M.: Automatic, real-time detection and characterization of tsunamis in deep-sea level measurements, Ocean Eng., 38, 1677–1685, 2011.
Beltrami, G. M. and Risio, M. D.: Algorithms for automatic, real-time tsunami detection in wind–wave measurements Part I: Implementation strategies and basic tests, Coastal Eng., 58, 1062–1071, 2011.
Bressan, L. and Tinti, S.: Structure and performance of a real-time algorithm to detect tsunami or tsunami-like alert conditions based on sea-level records analysis, Nat. Hazards Earth Syst. Sci., 11, 1499–1521, https://doi.org/10.5194/nhess-11-1499-2011, 2011.
Bressan, L. and Tinti, S.: Detecting the 11 March 2011 Tohoku tsunami arrival on sea-level records in the Pacific Ocean: application and performance of the Tsunami Early Detection Algorithm (TEDA), Nat. Hazards Earth Syst. Sci., 12, 1583–1606, https://doi.org/10.5194/nhess-12-1583-2012, 2012.
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Short summary
Water level sensors often experience unexpected gaps and outliers that cause major difficulties in detecting tsunamis. Thus, we propose a tsunami arrival time detection system applicable to discontinuous time-series data with outliers. We want to stress that the efficiency and simplicity of the system enable its wide application in tsunami monitoring areas.
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