Premium
Multi‐Timescale Analysis of Tidal Variability in the Indian Ocean Using Ensemble Empirical Mode Decomposition
Author(s) -
Devlin Adam T.,
Pan Jiayi,
Lin Hui
Publication year - 2020
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1029/2020jc016604
Subject(s) - tide gauge , ocean tide , anomaly (physics) , sea level , mode (computer interface) , climatology , environmental science , structural basin , tidal power , geology , oceanography , paleontology , ecology , physics , computer science , biology , condensed matter physics , operating system
Abstract Ocean tides have been observed to be changing worldwide for nonastronomical reasons, which can combine with rising mean sea level (MSL) to increase the long‐term impact to coastal regions. Tides can also exhibit variability at shorter timescales, which may be correlated with short‐term variability in MSL. This short‐term coupling may yield higher peak water levels and increased impacts of exceedance events that may be equally significant as long‐term sea level rise. Previous studies employed the tidal anomaly correlation (TAC) method to quantify the sensitivity of tides to MSL fluctuations at long‐period (>20 years) tide gauges in basin‐scale surveys of the Pacific and Atlantic Ocean, finding that TACs exist at most locations. The Indian Ocean also experiences significant sea level rise and tidal variability yet has been less studied due to a sparse network of tide gauges. However, since the beginning of the 21st century, more tide gauges have been established in a wider geographical range, bringing the possibility of better estimates of tidal and MSL variability. Here, we improve the TAC approach, using the ensemble empirical mode decomposition (EEMD) method to analyze tidal amplitudes and sea level at multiple frequency bands, allowing a more effective use of shorter record tide gauges and better understanding of multiple timescales of tidal variability. We apply this approach to 73 tide gauges in the Indian Ocean to better quantify tidal variability in these under‐studied regions, finding that the majority of locations exhibit significant correlations of tides and MSL.