Stochastic atmospheric perturbations in the EC-Earth3 global coupled model: impact of SPPT on seasonal forecast quality

Atmospheric model uncertainties at a seasonal time scale can be addressed by introducing stochastic perturbations in the model formulation. In this paper the stochastically perturbed parameterization tendencies (SPPT) technique is activated in the atmospheric component of the EC-Earth global coupled model and the impact on seasonal forecast quality is assessed, both at a global scale and focusing on the Tropical Pacific region. Re-forecasts for winter and summer seasons using two different settings for the perturbation patterns are evaluated and compared to a reference experiment without stochastic perturbations. We find that SPPT tends to increase the systematic error of the model sea-surface temperature over most regions of the globe, whereas the impact on precipitation and sea-level pressure is less clear. In terms of ensemble spread, larger-scale perturbation patterns lead to a greater increase in spread and in the model spread-skill ratio in a system that is overconfident. Over the Tropical Pacific, improvements in the representation of key processes associated with ENSO are highlighted. The evaluation of probabilistic re-forecasts shows that SPPT improves their reliability. Finally, we discuss the limitations to this study and future prospects with EC-Earth.