EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

The mean state and variability of the North Atlantic circulation: a perspective from ocean reanalyses

Laura Jackson1, Clotilde Dubois2,3, Gael Forget4, Keith Haines5, Matt Harrison6, Dorotea Iovino7, Armin Kohl8, Davi Mignac5, Ssimona Masina7, Drew Peterson1,9, Christopher Piecuch10, Chris Roberts11, Jon Robson12, Andrea Storto7,13, Takahiro Toyoda14, Maria Valdivieso5, Chris Wilson15, Yiguo Wang16, and Hao Zuo11
Laura Jackson et al.
  • 1Met Office, Exeter, UK
  • 2Mercator Ocean International, Ramonville-Saint-Agne, France
  • 3Météo France, Toulouse, France
  • 4Massachusetts Institute of Technology, Cambridge, MA, USA
  • 5University of Reading, Reading, UK
  • 6Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
  • 7Foundation Euro-Mediterranean Centre on Climate Change, Bologna, Italy
  • 8University of Hamburg, Hamburg, Germany
  • 9Environment and Climate Change Canada, Gatineau, Quebec, Canada
  • 10Woods Hole Oceanographic Institution, Woods Hole, MA, USA
  • 11European Centre for Medium-Range Weather Forecasts, Reading, UK
  • 12NCAS, Reading, UK
  • 13NATO STO Centre for Maritime Research and Experimentation, La Spezia, Italy
  • 14Japan Meteorological Agency, Tsukuba, Japan
  • 15National Oceanography Centre, Liverpool, UK
  • 16Nansen Environmental and Remote Sensing Centre/BjerknesCenter for Climate Research, Norway

The observational network around the North Atlantic has improved significantly over the last few decades with the advent of Argo and satellite observations, and the more recent efforts to monitor the Atlantic Meridional Overturning Circulation (AMOC) using arrays such as RAPID and OSNAP. These have shown decadal timescale changes across the North Atlantic including in heat content, heat transport and the circulation. 

However there are still significant gaps in the observational coverage, and significant uncertainties around some observational products. Ocean reanalyses integrate the observations with a dynamically consistent ocean model and are potentially tools that can be used to understand the observed changes. However the suitability of the reanalyses for the task must also be assessed.
We use an ensemble of global ocean reanalyses in comparison with observations in order to examine the mean state and interannual-decadal variability of the North Atlantic ocean since 1993. We assess how well the reanalyses are able to capture different processes and whether any understanding can be inferred. In particular we look at ocean heat content, transports, the AMOC and gyre strengths, water masses and convection. 


How to cite: Jackson, L., Dubois, C., Forget, G., Haines, K., Harrison, M., Iovino, D., Kohl, A., Mignac, D., Masina, S., Peterson, D., Piecuch, C., Roberts, C., Robson, J., Storto, A., Toyoda, T., Valdivieso, M., Wilson, C., Wang, Y., and Zuo, H.: The mean state and variability of the North Atlantic circulation: a perspective from ocean reanalyses, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5575,, 2020

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Display material version 1 – uploaded on 27 Apr 2020
  • CC1: Comment on EGU2020-5575, Eric Guilyardi, 08 May 2020

    Hi Laura, you write that the coherence in AMOC comes form the Ekman part. How different are the density driven contributions in the reanalysis ? Thanks for this very interesting work !

    • AC1: Reply to CC1, Laura Jackson, 08 May 2020

      Hi Eric,

      I meant that the interannual variability, which seems consistent across the ensemble, is coming from the Ekman contribution. The reanalyses do all show a weakening from 1995-2009 as well, which is probably density driven.

  • AC2: Qn and ans: Why is NorCPM different?, Laura Jackson, 08 May 2020

    NorCPM is a coupled reanalysis and also the only reanalysis with anomaly (rather than full field) assimilation. Hence the mean state is not constrained and it has a very strong AMOC.

  • AC4: Qn and ans: Should you use the MMM?, Laura Jackson, 08 May 2020

    Although it is better to use an ensemble, ideally you should identify which reanalyses are best able to represent the processes