Initialised decadal forecast skill during the first years is usually associated with higher skill coming from the internally generated component. Its main natural modes of variability are high teleconnection areas affecting the regional climate over various areas in most sensitive parameters (as temperature, precipitation) mainly through circulation changes and physics-dynamics interaction. Winter storms resulting from intense extra-tropical cyclones particularly causing severe weather anomalies over North_America and Eurasia are shown to be related to AO phase that controls tropospheric blocking variability over the Pacific basin and the Atlantic/European sector.
A preliminary analysis of our modeling system ability in reproducing AO decadal variability in unforced and forced climate is ongoing using the ensemble of simulations produced.
We compute decadal model skills for AO index, BLI index (Blocking index) and 2m temperature (T2m) - against ERA data and model climatology (uninitialised hindcast -Ctrl). We compute AO index as the PC time series of the main loading mode of 1000hPa pressure anomalies over 50N-90N, 10 years round. The BLI uses Tibaldi and Molteni (1990) modified to account for model variability in defining the latitudinal belts; here only persistent blocks are considered.
The time correlation between model and ERA BLI decadal skill over 46 decades is significant at 0.95 level (r=0.31). Ctrl and ERA appear uncorrelated (Figure 1) that implies that ensemble initialization may supply skill for longer-period oscillation of decadal BLI (AO).
Moreover, the modelled AO index is positively (statistically significant) correlated with the observed AO index on decadal scale, in those cases when the AO phase is initially accurate, while worse correlations correspond to wrong phasing at initial time, as shown in Figure 2a. That indicates AO predictability in our system -or feature that should be improved at initial time to get a good decadal AO skill.
Then, besides known regional AO teleconnected-areas that would gain from that, Figure 2b. shows an interesting feature connecting AO prediction to global skill in 2m temperature: AO decadal skill is leading by 1 year the decadal skill of temperature at 2m (t2m) with a correlation coefficient of r=+0.507 over 36 decades (unlagged r=0.253). This might have been emphasised due to the use of a continuous forced chain for producing initial conditions - but indicates AO has a predictive potential driving global t2m decadal predictability.
Mitchell et al. (2012) The Influence of Stratospheric Vortex Displacements and Splits on Surface Climate. J. Climate, 2012
W. Hazeleger at al, 2013: “Multiyear climate predictions using two initialization strategies”,