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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 22, issue 2
Nonlin. Processes Geophys., 22, 157–166, 2015
https://doi.org/10.5194/npg-22-157-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Nonlin. Processes Geophys., 22, 157–166, 2015
https://doi.org/10.5194/npg-22-157-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 10 Mar 2015

Research article | 10 Mar 2015

Evaluation of empirical mode decomposition for quantifying multi-decadal variations and acceleration in sea level records

D. P. Chambers D. P. Chambers
  • College of Marine Science, University of South Florida, St. Petersburg, FL, USA

Abstract. The ability of empirical mode decomposition (EMD) to extract multi-decadal variability from sea level records is tested using three simulations: one based on a series of purely sinusoidal modes, one based on scaled climate indices of El Niño and the Pacific decadal oscillation (PDO), and the final one including a single month with an extreme sea level event. All simulations include random noise of similar variance to high-frequency variability in the San Francisco tide gauge record. The intrinsic mode functions (IMFs) computed using EMD were compared to the prescribed oscillations. In all cases, the longest-period modes are significantly distorted, with incorrect amplitudes and phases. This affects the estimated acceleration computed from the longest periodic IMF. In these simulations, the acceleration was underestimated in the case with purely sinusoidal modes, and overestimated by nearly 100% in the case with prescribed climate modes. Additionally, in all cases, extra low-frequency modes uncorrelated with the prescribed variability are found. These experiments suggest that using EMD to identify multi-decadal variability and accelerations in sea level records should be used with caution.

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The ability of empirical mode decomposition (EMD) to extract multi-decadal variability from sea level records is tested using three simulations, based on sinusoidal oscillations and climate indices. In all cases, the longest-period modes are significantly distorted, with incorrect amplitudes and phases. This affects the estimated acceleration computed from the longest periodic IMF. Additionally, in all cases, extra low-frequency modes uncorrelated with the prescribed variability are found.
The ability of empirical mode decomposition (EMD) to extract multi-decadal variability from sea...
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