Probabilistic seasonal prediction of the winter North Atlantic Oscillation and its impact on near surface temperature

Abstract

The North Atlantic Oscillation (NAO) is a major winter climate mode, describing one-third of the inter-annual variability of the upper-level flow in the Atlantic European mid-latitudes. It provides a statistically well-defined pattern to study the predictability of the European winter climate. In this paper, the predictability of the NAO and the associated surface temperature variations are considered using a dynamical prediction approach. Two state-of-the-art coupled atmosphere–ocean ensemble forecast systems are used, namely the seasonal forecast system 2 from the European Centre for Medium Range Weather Forecast (ECMWF) and the multi-model system developed within the joint European project DEMETER (Development of a European Multi-Model Ensemble Prediction System for Seasonal to Inter-annual Prediction). The predictability is defined in probabilistic space using the debiased ranked probability skill score with adapted discretization (RPSSD). The potential predictability of the NAO and its impact are also investigated in a perfect model approach, where each ensemble member is used once as “observation”. This approach assumes that the climate system is fully represented by the model physics.