Quantifying the influence of (multi-) decadal sea-level oscillations on rates of mean sea-level change using empirical mode decomposition

Abstract

Coastal communities face heightened exposure to extreme sea-level (ESL) events, amplified by rising sea levels. While most mean sea-level research has concentrated on the long-term linear trend, studies have found the frequency of these extreme events is amplified by shorter-term variability. To quantify this variability, this study applies empirical mode decomposition to a global mean sea-level (GMSL) reconstruction (1900-2018) and a global set of 96 tide-gauge records (spanning 1845-2025); expanding the number, spatial coverage, and temporal window of tide gauges used in such analyses. A set of dominant periodicities was identified from each dataset, with the tide gauges divided by ocean basin. These quasi-periodic oscillations cover sub- (6.7 ± 2.7 year), to multi- (87.2 ± 11.2 year) decadal timescales. Their contributions to 30-year rates (from 1845-2025) of coastal sea-level change were quantified, and the results illustrate that such oscillations both amplify and dampen mean sea-level rates by between -54916% and 30529%, relative to the observed trends. Correlation coefficients between these modes of variability at each tide gauge and major climate indices, along with an investigation of possible physical drivers, imply that (sub-) decadal variability is related to the El Niño Southern Oscillation and the North Atlantic Oscillation (NAO), as well as sterodynamic changes typical of boundary current regions. Bi-decadal variability appears to be associated with the 18.61-year lunar nodal cycle and affected by both the NAO and the Pacific Decadal Oscillation (PDO). Multi-decadal GSML variability aligns with changes in terrestrial water storage, and coefficients suggest that the NAO, the PDO, and the Atlantic Multi-decadal Oscillation influence sea levels in the North Atlantic and Pacific basins. These results provide statistical evidence that (multi-) decadal oscillations modulate longer-term rates of mean sea-level change and highlight the importance of incorporating these oscillations into future sea-level projections. By accounting for this variability, estimates of ESL event probabilities may be improved, ultimately supporting the development of more effective and sustainable adaptation strategies.