Deficient ocean–atmosphere feedbacks constrain seasonal NAO prediction

Abstract. As the North Atlantic Oscillation (NAO) accounts for a dominant share of wintertime weather variability across the North Atlantic, it is a coveted target for seasonal prediction. Yet dynamical forecast systems exhibit limited skill. Here I build on previous results linking November sea-surface temperature (SST) anomalies to the subsequent winter NAO via ocean–atmosphere feedback mechanisms involving baroclinicity and surface heat fluxes. I hypothesise that limited model skill is partly attributable to a deficient representation of these mechanisms. While remote influences such as tropical or stratospheric forcing can affect both SSTs and the NAO, thereby contributing to apparent but non-causal relationships, I find that the seasonal prediction system SEAS5's internal lagged SST–NAO relationship nonetheless correlates with its NAO forecast skill. Since this skill reflects the combined effects of all sources of predictability – including tropical and stratospheric forcing – this correlation is an important finding. Using mediation analysis to contrast the behaviour of SEAS5 with that of the ERA5 reanalysis, I find that SEAS5 produces weaker mediated effects via both fluxes and baroclinicity than those found in ERA5. Critically, the strength of these mediated effects in the model correlates with its NAO forecast skill. This suggests that models reproducing realistic mediation pathways for ocean–atmosphere interactions are likely to achieve higher NAO skill than models that do not.