Predicting multiyear North Atlantic Ocean variability

W. Hazeleger, B. Wouters, G.J. van Oldenborgh, S. Corti, T. Palmer, D. Lloyd Smith, N. Dunstone, J. Kroger, H. Pohlmann, J.S. von Storch

Research output: Contribution to journalArticleAcademicpeer-review

34 Citations (Scopus)


We assess the skill of retrospective multiyear forecasts of North Atlantic ocean characteristics obtained with ocean-atmosphere-sea ice models that are initialized with estimates from the observed ocean state. We show that these multimodel forecasts can skilfully predict surface and subsurface ocean variability with lead times of 2 to 9 years. We focus on assessment of forecasts of major well-observed oceanic phenomena that are thought to be related to the Atlantic meridional overturning circulation (AMOC). Variability in the North Atlantic subpolar gyre, in particular that associated with the Atlantic Multidecadal Oscillation, is skilfully predicted 2-9 years ahead. The fresh water content and heat content in major convection areas such as the Labrador Sea are predictable as well, although individual events are not captured. The skill of these predictions is higher than that of uninitialized coupled model simulations and damped persistence. However, except for heat content in the subpolar gyre, differences between damped persistence and the initialized predictions are not significant. Since atmospheric variability is not predictable on multiyear time scales, initialization of the ocean and oceanic processes likely provide skill. Assessment of relationships of patterns of variability and ocean heat content and fresh water content shows differences among models indicating that model improvement can lead to further improvements of the predictions. The results imply there is scope for skilful predictions of the AMOC.
Original languageEnglish
Pages (from-to)1087-1098
JournalJournal of Geophysical Research: Oceans
Issue number3
Publication statusPublished - 2013


  • meridional overturning circulation
  • coupled climate models
  • surface-temperature
  • physical parametrizations
  • multidecadal variability
  • decadal variability
  • data assimilation
  • labrador sea
  • ecmwf model
  • ec-earth

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