Royal Netherlands Meteorological Institute; Ministery of Infrastructure and the Environment

Publications, presentations and other activities
Predicting multiyear north Atlantic ocean variability
2013
by W. Hazeleger (KNMI), B. Wouters (KNMI), G.J. van Oldenborgh (KNMI), S. Corti (ECMWF), T. Palmer (Univ. Oxford)D. Smith (UKMO)N. Dunstone (UKMO)J. Kroeger (MPI-M)H. Pohlmann (MPI-M)J.S. von Storch (MPI-M)
Abstract

We assess the skill of retrospective multi-year 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 multi-model 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. 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 multi-year 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 Atlantic meridional overturning circulation.

Observed (red curves) and ensemble mean predicted (magenta curves) AMO time series. Grey curves show the predictions from an AR1 model. Left panel 1 year lead time and yearly averaged anomalies, middle panel 2-5 years lead time and 2-5 year averaged anomalies and right panel 6-9 year lead time and 6-9 year averaged anomalies. Individual ensemble members are indicated by asterisks. Top left corner shows the root mean square error of the ensemble mean, the slope A between the ensemble mean and observed time series, and the anomaly correlations. The root mean square error has been computed after correcting for the biases in mean and amplitude (A). On the right hand side this is shown for the AR1 model.

Biblographic data
Hazeleger, W., B. Wouters, G.J. van Oldenborgh, S. Corti, T. Palmer, D. Smith, N. Dunstone, J. Kroeger, H. Pohlmann and J.S. von Storch, Predicting multiyear north Atlantic ocean variability
accepted, J. Geophys. Res., 2013.
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