Multi-Timescale Analysis of Tidal Variability in the Indian Ocean Using Ensemble Empirical Mode Decomposition

Type Article
Date 2020-12
Language English
Author(s) Devlin Adam T.1, 2, 3, Pan JiayiORCID1, 2, 3, Lin Hui1, 2
Affiliation(s) 1 : 1Key Laboratory of Poyang Lake Wetland and Watershed Research of Ministry of Education, Nanchang, China,
2 : School of Geography and Environment, Jiangxi Normal University, Nanchang, China
3 : Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
Source Journal Of Geophysical Research-oceans (2169-9275) (Amer Geophysical Union), 2020-12 , Vol. 125 , N. 12 , P. e2020JC016604 (39p.)
DOI 10.1029/2020JC016604
WOS© Times Cited 6
Keyword(s) Tidal, variability, Sea level, variability, Ensemble Empirical Mode, Decomposition, Tidal evolution, Coastal risks, Indian Ocean
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.

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