Forecast skill of the NAO in the subseasonal-to-seasonal prediction models

Abstract

The prediction skill of the North Atlantic Oscillation (NAO) in boreal winter is assessed in the operational models of the WCRP/WWRP Subseasonal-to-Seasonal (S2S) prediction project. Model performance in representing the contribution of different processes to the NAO forecast skill is evaluated. The S2S models with relatively higher stratospheric vertical resolutions (high-top models) are in general more skillful in predicting the NAO than those models with relatively lower stratospheric resolutions (low-top models). Comparison of skill is made between different groups of forecasts based on initial condition characteristics: phase and amplitude of theNAO, easterly andwesterly phases of the quasi-biennial oscillation (QBO), warm and cold phases of ENSO, and phase and amplitude of the Madden-Julian oscillation (MJO). The forecasts with a strong NAO in the initial condition are more skillful than with a weak NAO. Those with negative NAO tend to have more skillful predictions than positive NAO. Comparisons of NAO skill between forecasts during easterly and westerlyQBO and betweenwarmand coldENSOshow no consistent difference for the S2Smodels. Forecastswith strong initialMJO tend to bemore skillful in theNAOprediction thanweakMJO.Among the eight phases ofMJOin the initial condition, phases 3-4 and phase 7 have better NAO forecast skills compared with the other phases. The results of this study have implications for improving our understanding of sources of predictability of the NAO. The situation dependence of theNAOprediction skill is likely useful in identifying ''windows of opportunity'' for subseasonal to seasonal predictions.