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Ensemble empirical mode decomposition on storm surge separation from sea level data
Wu, L.; Kao, C.C.; Hsu, T.-W.; Jao, K.-C.; Wang, Y.-F. (2011). Ensemble empirical mode decomposition on storm surge separation from sea level data. Coast. Eng. J. 53(3): 223-243. http://dx.doi.org/10.1142/S0578563411002343
In: Coastal Engineering Journal. Japan Society of Civil Engineers, Committee on Coastal Engineering: Tokyo. ISSN 0578-5634; e-ISSN 1793-6292, more
Peer reviewed article  

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Keywords
    Analysis > Mathematical analysis > Numerical analysis > Functional analysis > Harmonic analysis
    Sea level data
    Surges > Surface water waves > Storm surges
    Marine/Coastal
Author keywords
    Ensemble empirical mode decomposition

Authors  Top 
  • Wu, L.
  • Kao, C.C.
  • Hsu, T.-W.
  • Jao, K.-C.
  • Wang, Y.-F.

Abstract
    This paper concerns the storm surge calculation based on the algorithm of ensemble empirical mode decomposition (EEMD). An accurate storm surge result is key information for coastal disaster warning and prevention. Separation of storm surge magnitude from sea level data has typically been done by specifying tidal input from main tidal harmonics. Obtaining accurate storm surge magnitude with harmonic analysis (HA) requires at least one month. This study discusses possible storm surge separation from short-term sea level time series using EEMD. The current work reveals that EEMD is predominant for short-term sea level data analysis shorter than thirty-five days. Due to different residues obtained from EEMD, this work proposes a method to determine most ideal residue for representing the storm surge.

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