ENSO components of the Atlantic multidecadal oscillation and their relation to North Atlantic interannual coastal sea level anomalies

• Published in: Ocean Science
• Main Authors: J. Park, G. Dusek
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2013
• Subjects: Geography. Anthropology. Recreation; G; Environmental sciences; GE1-350; North Atlantic
• Online Access: https://doi.org/10.5194/os-9-535-2013; https://doaj.org/article/b905d674d5184ff799cb77b745b49832

The El Niño Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO) are known to influence coastal water levels along the East Coast of the United States. By identifying empirical orthogonal functions (EOFs), which coherently contribute from the Multivariate ENSO Index (MEI) to the AMO index (AMOI), we characterize both the expression of ENSO in the unsmoothed AMOI, and coherent relationships between these indices and interannual sea level anomalies at six stations in the Gulf of Mexico and western North Atlantic. Within the ENSO band (2–7 yr periods) the total contribution of MEI to unsmoothed AMOI variability is 79%. Cross correlation suggests that the MEI leads expression of the ENSO signature in the AMOI by six months, consistent with the mechanism of an atmospheric bridge. Within the ENSO band, essentially all of the coupling between the unsmoothed AMOI and sea level anomalies is the result of ENSO expression in the AMOI. At longer periods we find decadal components of sea level anomalies linked to the AMOI at three southern stations (Key West, Pensacola, Charleston), but not at the northern stations (Baltimore, Boston, Portland), with values of coherence ranging from 20 to 50%. The coherence of MEI to coastal sea level anomalies has a different structure and is generally weaker than that of the ENSO expressed AMOI influence, suggesting distinct physical mechanisms are influencing sea level anomalies due to a direct ENSO teleconnection when compared to teleconnections based on ENSO expression in the AMOI. It is expected that applying this analysis to extremes of sea level anomalies will reveal additional influences.