scholarly journals The Relation between the North Atlantic Oscillation and SSTs in the North Atlantic Basin

2004 ◽  
Vol 17 (24) ◽  
pp. 4752-4759 ◽  
Author(s):  
Weile Wang ◽  
Bruce T. Anderson ◽  
Robert K. Kaufmann ◽  
Ranga B. Myneni

Abstract The authors use the notion of Granger causality to investigate the relationship between the North Atlantic Oscillation (NAO) index and the sea surface temperatures (SSTs) over the Northern Hemisphere. The Granger causality analysis ensures that any apparent oceanic influence upon the atmosphere (as measured by the NAO) is provided by the ocean and is not related to preexisting conditions within the NAO itself (and vice versa when looking at the atmospheric influence upon the ocean). Although this statistical technique does not imply physical forcing of one field on the other, it is generally more reliable compared to the simple lead/lagged correlation. Using this technique, the authors find that on seasonal time scales, the preceding NAO anomalies' influence on the wintertime SST field is rather restricted. Conversely, preceding SST anomalies have a statistically significant causal effect on the wintertime NAO. However, the causal relation between preceding SSTs and the wintertime NAO is limited to the Gulf Stream extension; in contrast to the canonical tripole SST pattern typically associated with the NAO, the authors do not find that SST anomalies in either the Greenland or subtropical regions have a significant causal effect on the NAO. These results suggest that the Gulf Stream SSTs have an important influence in initiating disturbances of the atmospheric circulation over the wintertime North Atlantic.

2019 ◽  
Vol 32 (22) ◽  
pp. 7697-7712 ◽  
Author(s):  
Yu Nie ◽  
Hong-Li Ren ◽  
Yang Zhang

Abstract Considerable progress has been made in understanding the internal eddy–mean flow feedback in the subseasonal variability of the North Atlantic Oscillation (NAO) during winter. Using daily atmospheric and oceanic reanalysis data, this study highlights the role of extratropical air–sea interaction in the NAO variability during autumn when the daily sea surface temperature (SST) variability is more active and eddy–mean flow interactions are still relevant. Our analysis shows that a horseshoe-like SST tripolar pattern in the North Atlantic Ocean, marked by a cold anomaly in the Gulf Stream and two warm anomalies to the south of the Gulf Stream and off the western coast of northern Europe, can induce a quasi-barotropic NAO-like atmospheric response through eddy-mediated processes. An initial southwest–northeast tripolar geopotential anomaly in the North Atlantic forces this horseshoe-like SST anomaly tripole. Then the SST anomalies, through surface heat flux exchange, alter the spatial patterns of the lower-tropospheric temperature and thus baroclinicity anomalies, which are manifested as the midlatitude baroclinicity shifted poleward and reduced baroclinicity poleward of 70°N. In response to such changes of the lower-level baroclinicity, anomalous synoptic eddy generation, eddy kinetic energy, and eddy momentum forcing in the midlatitudes all shift poleward. Meanwhile, the 10–30-day low-frequency anticyclonic wave activities in the high latitudes decrease significantly. We illustrate that both the latitudinal displacement of midlatitude synoptic eddy activities and intensity variation of high-latitude low-frequency wave activities contribute to inducing the NAO-like anomalies.


2017 ◽  
Vol 47 (11) ◽  
pp. 2741-2754 ◽  
Author(s):  
Sylvain Watelet ◽  
Jean-Marie Beckers ◽  
Alexander Barth

AbstractIn this study, the Gulf Stream (GS)’s response to the North Atlantic Oscillation (NAO) is investigated by generating an observation-based reconstruction of the GS path between 70° and 50°W since 1940. Using in situ data from the World Ocean Database (WOD), SeaDataNet, International Council for the Exploration of the Sea (ICES), Hydrobase3, and Argo floats, a harmonized database of more than 40 million entries is created. A variational inverse method implemented in the software Data Interpolating Variational Analysis (DIVA) allows the production of time series of monthly analyses of temperature and salinity over the North Atlantic (NA). These time series are used to derive two GS indices: the GS north wall (GSNW) index for position and the GS delta (GSD) index as a proxy of its transport. This study finds a significant correlation (0.37) between the GSNW and the NAO at a lag of 1 year (NAO preceding GS) since 1940 and significant correlations (0.50 and 0.43) between the GSD and the NAO at lags of 0 and 2 years between 1960 and 2014. The authors suggest this 2-yr lag is due to Rossby waves, generated by NAO variability, that propagate westward from the center of the NA. This is the first reconstruction of GS indices over a 75-yr period based on an objective method using the largest in situ dataset so far.


2006 ◽  
Vol 19 (7) ◽  
pp. 1182-1194 ◽  
Author(s):  
Timothy J. Mosedale ◽  
David B. Stephenson ◽  
Matthew Collins ◽  
Terence C. Mills

Abstract This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs on the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO—the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%–30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.


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