1. A dynamical/statistical approach to predict multidecadal AMOC variability and related North Atlantic SST anomalies
Mojib Latif
GEOMAR Helmholtz Centre for Ocean Research Kiel and University of Kiel
monthly AMO index
Thanks to M. Klöwer, H. Ding, R. Greatbatch, W. Park

2. SAT trend
There is a marked inter-hemispheric asymmetry in the warming during the last decades, especially in the Atlantic

3. New analysis of North Atlantic surface heat fluxes since 1880
suggests that the ocean drives SST at decadal time scales

4. Can we predict the AMO given the large model biases?
CMIP5 multi-model mean SST bias (39 models)
model bias may prevent us from exploiting the decadal full predictability potential

5. The null hypothesis for multi-decadal AMOC variability
NAO-related SAT pattern (°C), +1σ
The NAO affects Labrador Sea convection which in turn drives AMOC (Delworth and Greatbatch, 2000; Eden and Jung, 2001)

6. The NAO drives convection in the North Atlantic, which in turn drives the AMOC
Latif and Keenlyside 2011

7. Dynamical/statistical approach to predict North Atlantic SST
observed NA SST
force the Kiel Climate Model by NAO-related heat flux anomalies
use the KCM‘s AMOC as predictor to statistically predict observed North Atlantic SST

8. Hindcast of the AMOC 1900-2010 Kiel Climate Model forced by NAO-related heat flux anomalies
Klöwer et al. 2013

9. Link between the KCM‘s AMOC and observed North Atlantic SST
Klöwer et al. 2013

10. Statistical link between the model‘s AMOC and the observed NA SST
The Meridional Overturning Circulation (AMOC) and observed North Atlantic SST
AMOC lags SST by 10 years
AMOC leads SST by 21 years
Klöwer et al. 2013
Statistical link between the model‘s AMOC and the observed NA SST

11. Explained variances by the two CCA modes
Klöwer et al. 2013
AMOC lags SST by 10 years
AMOC leads SST by 21 years
suggests a rather high decadal predictability potential of North Atlantic SST

12. Forecast of North Atlantic SST until 2030
Klöwer et al. 2013
Dynamical/statistical prediction based on the North Atlantic Oscillation and the Kiel Climate Model’s AMOC

13. Take home message
Climate models are useful tools to study the dynamics and predictability of climate variability and change. However, they suffer from large biases. Model improvement is a key issue during the next years.
In the meantime, hybrid approaches may prove useful.

14. The research leading to these results has received funding from the European Union 7th Framework Programme (FP ), under grant agreement n NACLIM