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Climate Dynamics

, Volume 47, Issue 7–8, pp 2105–2119 | Cite as

Active AMOC–NAO coupling in the IPSL-CM5A-MR climate model

  • Na WenEmail author
  • Claude Frankignoul
  • Guillaume Gastineau
Article

Abstract

The atmospheric response to the AMOC variability is investigated in the IPSL-CM5A medium resolution climate model, using lagged maximum covariance analysis (MCA) of a control simulation. A robust atmospheric response is detected in winter, with a negative NAO-like response following by about 9-year an AMOC intensification in the North Atlantic, with a pattern broadly resembling the second mode of AMOC variability. The response is established through the SST footprint of the AMOC and the associated surface heat flux damping, with a dipole of SST anomalies made of cold SST in the Gulf Stream region and warm SST further northeast around the North Atlantic Current. The dipole SST anomaly pattern evolves synchronously with the AMOC changes at its dominant 20-year period, so that the lagged NAO-like response detected by MCA actually reflects the near-synchronous AMOC influence on the atmosphere, which is masked at short time lag by the stronger atmospheric forcing of the AMOC. The atmospheric response to an intensification of the AMOC is thus a positive NAO-like pattern, together with an anomalous low pressure over the Aleutians, opposite to that detected at 9-year lag by the MCA. Since the NAO also contributes to force the AMOC, there is a positive feedback between AMOC and NAO in the model, with the atmospheric feedback strength about 1/4 of that of the atmospheric forcing, which enhances the low frequency variability of AMOC. This is further confirmed by the lead-lag relation between the dominant mode of ocean and atmosphere, and by the robust 20-year period of the NAO.

Keywords

AMOC NAO Atlantic multi-decadal variability Air–sea interaction Climate models 

Notes

Acknowledgments

I’d like to thank Drs. Mignot J, Li ZX, Liu ZY and Otega P. for the helpful discussions. We thank the ciclad facility supported by CNRS, UPMC, Labex L-IPSL funded by the ANR (Grant #ANR-10-LABX-0018) and by the European FP7 IS-ENES2 project (Grant #312979). This work is supported by China Scholarship Council (CSC), the European Union 7th Framework Programme (FP7 2007-2013) under Grant Agreement Nos. 308299(NACLIM) and NSFC41475089.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Na Wen
    • 1
    • 2
    Email author
  • Claude Frankignoul
    • 2
  • Guillaume Gastineau
    • 2
  1. 1.Key Laboratory of Meteorological Disaster of Ministry of Education and College of Atmospheric SciencesNanjing University of Information Science and TechnologyNanjingChina
  2. 2.CNRS/IRD/MNHN, LOCEAN/IPSLSorbonne Universités (UPMC, Univ. Paris 06)ParisFrance

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