Global sea level reconstruction for 1900–2015 reveals regional variability in ocean dynamics and an unprecedented long weakening in the Gulf Stream flow since the 1990s - Tal Ezer; Sönke Dangendorf (Ocean Science, 2020)
A new monthly global sea level reconstruction for 1900–2015 was analyzed and compared with various observations to examine regional variability and trends in the ocean dynamics of the western North Atlantic Ocean and the US East Coast. Proxies of the Gulf Stream (GS) strength in the Mid-Atlantic Bight (GS-MAB) and in the South Atlantic Bight (GS-SAB) were derived from sea level differences across the GS. While decadal oscillations dominate the 116-year record, the analysis showed an unprecedented long period of weakening in the GS flow since the late 1990s. The only other period of long weakening in the record was during the 1960s–1970s, and red noise experiments showed that is very unlikely that those just occurred by chance. Ensemble empirical mode decomposition (EEMD) was used to separate oscillations at different timescales, showing that the low-frequency variability of the GS is connected to the Atlantic Multi-decadal Oscillation (AMO) and the Atlantic Meridional Overturning Circulation (AMOC). The recent weakening of the reconstructed GS-MAB was mostly influenced by weakening of the upper mid-ocean transport component of AMOC as observed by the RAPID measurements for 2005–2015. Comparison between the reconstructed sea level near the coast and tide gauge data for 1927–2015 showed that the reconstruction underestimated observed coastal sea level variability for timescales less than ∼5 years, but lower-frequency variability of coastal sea level was captured very well in both amplitude and phase by the reconstruction. Comparison between the GS-SAB proxy and the observed Florida Current transport for 1982–2015 also showed significant correlations for oscillations with periods longer than ∼5 years. The study demonstrated that despite the coarse horizontal resolution of the global reconstruction (1∘ × 1∘), long-term variations in regional dynamics can be captured quite well, thus making the data useful for studies of long-term variability in other regions as well.