Contrasting spatial structures of Atlantic Multidecadal Oscillation between observations and slab ocean model simulations

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Abstract

The spatial structure of Atlantic multidecadal oscillation (AMO) is analyzed and compared between the observations and simulations from slab ocean models (SOMs) and fully coupled models. The observed sea surface temperature (SST) pattern of AMO is characterized by a basin-wide monopole structure, and there is a significantly high degree of spatial coherence of decadal SST variations across the entire North Atlantic basin. The observed SST anomalies share a common decadal-scale signal, corresponding to the basin-wide average (i. e., the AMO). In contrast, the simulated AMO in SOMs (AMOs) exhibits a tripole-like structure, with the mid-latitude North Atlantic SST showing an inverse relationship with other parts of the basin, and the SOMs fail to reproduce the observed strong spatial coherence of decadal SST variations associated with the AMO. The observed spatial coherence of AMO SST anomalies is identified as a key feature that can be used to distinguish the AMO mechanism. The tripole-like SST pattern of AMOs in SOMs can be largely explained by the atmosphere-forced thermodynamics mechanism due to the surface heat flux changes associated with the North Atlantic Oscillation (NAO). The thermodynamic forcing of AMOs by the NAO gives rise to a simultaneous inverse NAO–AMOs relationship at both interannual and decadal timescales and a seasonal phase locking of the AMOs variability to the cold season. However, the NAO-forced thermodynamics mechanism cannot explain the observed NAO–AMO relationship and the seasonal phase locking of observed AMO variability to the warm season. At decadal timescales, a strong lagged relationship between NAO and AMO is observed, with the NAO leading by up to two decades, while the simultaneous correlation of NAO with AMO is weak. This lagged relationship and the spatial coherence of AMO can be well understood from the view point of ocean dynamics. A time-integrated NAO index, which reflects the variations in Atlantic meridional overturning circulation (AMOC) and northward ocean heat transport caused by the accumulated effect of NAO forcing, reasonably well captures the observed multidecadal fluctuations in the AMO. Further analysis using the fully coupled model simulations provides direct modeling evidence that the observed spatial coherence of decadal SST variations across North Atlantic basin can be reproduced only by including the AMOC-related ocean dynamics, and the AMOC acts as a common forcing signal that results in a spatially coherent variation of North Atlantic SST.

Notes

Acknowledgements

The authors wish to thank the anonymous reviewers for their constructive comments that significantly improved the quality of this paper. This work was jointly supported by the National Science Foundation of China (41775038, 41790474), National Key Research and Development Plan (2016YFA0601801) and the National Programme on Global Change and Air–Sea Interaction (GASI-IPOVAI-06 and GASI-IPOVAI-03).

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Global Change and Earth System Science (GCESS)Beijing Normal UniversityBeijingChina
  2. 2.Laboratory for Regional Oceanography and Numerical ModelingQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  3. 3.The Abdus Salam International Centre for Theoretical PhysicsTriesteItaly
  4. 4.Department of Meteorology, Center of Excellence for Climate Change ResearchKing Abdulaziz UniversityJeddahSaudi Arabia
  5. 5.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid DynamicsInstitute of Atmospheric Physics, Chinese Academy of SciencesBeijingChina
  6. 6.Key Laboratory of Research on Marine Hazards ForecastingNational Marine Environmental Forecasting Center, State Oceanic AdministrationBeijingChina
  7. 7.College of Earth Science, University of Chinese Academy of SciencesBeijingChina

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