Global Mean Sea Level Variation on Interannual–Decadal Timescales: Climatic Connections

The global mean sea level (GMSL) has been measured precisely by the space geodetic remote-sensing technique of radar altimetry since the 1990s. Aside from the well-studied seasonality and secular sea level rise, here we focus on GMSL variation on the interannual–decadal (ID) timescales (GMSL-ID) and...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: Ting-Juan Liao, Benjamin F. Chao
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2022
Subjects:
global mean sea level
interannual
decadal
correlation
climatic oscillations
Science
Q
Arctic
Antarctic
Pacific
Antarc*
Climate change
Online Access:https://doi.org/10.3390/rs14092159
https://doaj.org/article/35285d651a06478eabe49ba0541f0026
Description
Summary:The global mean sea level (GMSL) has been measured precisely by the space geodetic remote-sensing technique of radar altimetry since the 1990s. Aside from the well-studied seasonality and secular sea level rise, here we focus on GMSL variation on the interannual–decadal (ID) timescales (GMSL-ID) and investigate the influences of the climatic oscillations as physical causes. We conduct correlation analyses on the GMSL-ID time series with several climatic oscillations represented by their respective meteorological indices, including El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), Arctic Oscillation (AO), and Antarctic Oscillation (AAO). From the time-domain cross-correlation functions and the corresponding frequency-domain cross-coherence spectra, we find the following: (i) high correlation between GMSL-ID and ENSO, primarily befalling on the Central-Pacific (as opposed to the Eastern-Pacific) type of ENSO, on timescales longer than 1.5 years; (ii) moderate correlations of GMSL-ID with PDO on long-period timescales of over 4 years, and with AMO on a timescale of 2–10 years, with AMO leading in phase by 8 months; (iii) weak or practically no correlation of GMSL-ID with either AO or AAO, in the former case given the fact that our GMSL-ID data actually do not cover the Arctic sea. Finally, we least-squares fit the above five indices to GMSL-ID to assess the relative contribution of each oscillation in causing the observed GMSL-ID, for a better understanding of the GMSL under the influences of on-going climate change.

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