Ocean impact on decadal Atlantic climate variability revealed by sea-level observations

Abstract

Decadal variability is a notable feature of the Atlantic Ocean and the climate of the regions it influences. Prominently, this is manifested in the Atlantic Multidecadal Oscillation (AMO) in sea surface temperatures. Positive (negative) phases of the AMO coincide with warmer (colder) North Atlantic sea surface temperatures. The AMO is linked with decadal climate fluctuations, such as Indian and Sahel rainfall1, European summer precipitation2, Atlantic hurricanes3 and variations in global temperatures4. It is widely believed that ocean circulation drives the phase changes of the AMO by controlling ocean heat content5. However, there are no direct observations of ocean circulation of sufficient length to support this, leading to questions about whether the AMO is controlled from another source6. Here we provide observational evidence of the widely hypothesized link between ocean circulation and the AMO. We take a new approach, using sea level along the east coast of the United States to estimate ocean circulation on decadal timescales. We show that ocean circulation responds to the first mode of Atlantic atmospheric forcing, the North Atlantic Oscillation, through circulation changes between the subtropical and subpolar gyres—the intergyre region7. These circulation changes affect the decadal evolution of North Atlantic heat content and, consequently, the phases of the AMO. The Atlantic overturning circulation is declining8 and the AMO is moving to a negative phase. This may offer a brief respite from the persistent rise of global temperatures4, but in the coupled system we describe, there are compensating effects. In this case, the negative AMO is associated with a continued acceleration of sea-level rise along the northeast coast of the United States9,10.

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Figure 1: Dynamic sea level and circulation along the western Atlantic seaboard.
Figure 2: Relating the sea-level circulation index to heat content changes.
Figure 3: Sea-level circulation index, the NAO and the AMO on multi-decadal timescales.

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Acknowledgements

G.D.M. and D.A.S. are supported by the UK Natural Environment Research Council (NERC) RAPID-WATCH programme. I.D.H. was partly supported by the UK NERC consortium project iGlass (NE/I009906/1). J.P.G. and J.J.-M.H. are supported by NERC National Capability funding.

Author information

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Authors

Contributions

G.D.M. originated and developed the concept. I.D.H. provided the tide gauge data analysis. J.P.G. and J.J.-M.H. provided the numerical model analysis. D.A.S. carried out the statistical analysis. All authors contributed to the shaping and production of the manuscript

Corresponding author

Correspondence to Gerard D. McCarthy.

Additional information

Comma-separated data used in the manuscript are available to download from http://bit.ly/1F7gtps.

Extended data figures and tables

Extended Data Figure 1 Tide gauges used in this study.

a, Locations and b, temporal coverage of the tide gauges used in this study.

Extended Data Figure 2 Dynamic sea-level anomalies from the 30 stations used in this study.

Linear trends were removed from each record. This removes the impact of glacial isostatic adjustment and other land subsidence effects, which have time periods of thousands of years and are known to affect tide gauges along this coastline. A seasonal cycle was removed using a 12-month boxcar filter. From 1920, there are multiple tide gauges both north and south of Cape Hatteras, so this is when we begin our study.

Extended Data Figure 3 Correlation of tide gauges along the US east coast relative to one another.

The dashed line indicates the location of Cape Hatteras. There is high correlation between tide gauges grouped north and south of Cape Hatteras.

Extended Data Figure 4 Surface velocity anomaly when the sea-level index is positive.

a, Magnitude (m s−1) and b, zonally integrated meridional velocity anomalies (103 m2 s−1) for the time period 1993 to 2011, corresponding to when (c) the sea-level index is positive. A positive sea-level index is associated with a more northerly circulation in the intergyre region and increased surface flow into the subpolar gyre. Velocities are geostrophic surface velocities derived from satellite altimetry.

Extended Data Figure 5 Model-derived surface velocity anomaly magnitude when the model-based sea-level index is positive.

Similar to observed velocities, positive indices are associated with more northerly circulation in the intergyre region. a, Surface velocity magnitude (m s−1) and b, percentage of meridional heat transport change (%) for the time period 1958 to 2001, corresponding to when (c) the model-derived sea-level index is positive. Similar to the satellite observations, a positive sea-level index is associated with a more northerly circulation in the intergyre region. Meridional heat transport change in both subtropical and subpolar gyres is positive when the sea-level index is positive.

Extended Data Figure 6 Model-derived sea-level index, heat transport and subpolar heat content.

The accumulated sea-level index (Acc. SL diff, blue, in mm months) leads the accumulated heat transport into the subpolar gyre across 40° N (Acc. HT40N, black, normalized units). The heat transport into the subpolar gyre dominates the top 500 m temperature anomaly (Subpolar HCA, green, °C) in the subpolar gyre.

Extended Data Figure 7 Relationship between sea-level index and the NAO.

a, 7-year sea-level difference (blue, cm) and 7-year NAO (green, normalized units). b, Lagged correlations between the two quantities. c, Scrambled correlation tests. The histogram indicates the typical correlations that would be expected from randomly generated timeseries with similar spectral properties to the original timeseries. The red line indicates the maximum correlation between the two timeseries.

Extended Data Figure 8 Relationship between sea-level index and the rate of change of the AMO.

a, 7-year sea-level difference (blue) and rate of change of the AMO (green). b, Lagged correlations between the two quantities. c, Scrambled correlation tests. The histogram indicates the typical correlations that would be expected from randomly generated timeseries with similar spectral properties to the original timeseries. The red line indicates the maximum correlation between the two timeseries.

Extended Data Table 1 Sea level, NAO and rates of change of the AMO statistics
Extended Data Table 2 Sub-sampled statistics

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McCarthy, G., Haigh, I., Hirschi, J. et al. Ocean impact on decadal Atlantic climate variability revealed by sea-level observations. Nature 521, 508–510 (2015). https://doi.org/10.1038/nature14491

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