Teleconnection-based evaluation of seasonal forecast quality

Abstract

In response to the high demand for more skillful climate forecasts at the seasonal timescale, innovative climate prediction systems are developed with improved physics and increased spatial resolution. Alongside the model development process, seasonal predictions need to be evaluated on past years to provide robust information on the forecast performance. This work presents the quality assessment of the Meteo-France coupled climate prediction system, taking advantage of an experiment performed with 90 ensemble members over a 37-year re-forecast period from 1979 to 2015. We focus on the boreal winter season initialised in November. Beyond typical skill measures we evaluate the model capability in reproducing ENSO and NAO teleconnections on precipitation and near surface temperature respectively. Such an assessment is carried out first through a composite analysis, and shows that the model succeeds in reproducing the main patterns for near surface temperature and precipitation. A covariance method leads to consistent results. Finally we find that the teleconnection representation of the model is not affected by shortening the verification period and reducing the ensemble size and therefore can be used to evaluate operational seasonal forecast systems.