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The ability of empirical mode decomposition (EMD) toextract multi-decadal variability from sea level records is tested usingthree simulations: one based on a series of purely sinusoidal modes, onebased on scaled climate indices of El Niño and the Pacific decadaloscillation (PDO), and the final one including a single month with anextreme sea level event. All simulations include random noise of similarvariance to high-frequency variability in the San Francisco tide gaugerecord. The intrinsic mode functions (IMFs) computed using EMD were comparedto the prescribed oscillations. In all cases, the longest-period modes aresignificantly distorted, with incorrect amplitudes and phases. This affectsthe estimated acceleration computed from the longest periodic IMF. In thesesimulations, the acceleration was underestimated in the case with purelysinusoidal modes, and overestimated by nearly 100% in the case withprescribed climate modes. Additionally, in all cases, extra low-frequencymodes uncorrelated with the prescribed variability are found. Theseexperiments suggest that using EMD to identify multi-decadal variability andaccelerations in sea level records should be used with caution

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