Impact of Stochastic Convection on the Ensemble Transform

Abstract The impact of stochastic convection on ensembles produced using the ensemble transform (ET) initial perturbation scheme is examined. This note compares the behavior of ensemble forecasts based only on initial ET perturbations with the behavior of ensemble forecasts based on the ET initial perturbations and forecasts that include stochastic convection. It is illustrated that despite the fact that stochastic convection occurs only after the forecast integrations have started, it induces changes in the initial perturbations as well. This is because the ET is a "cycling" scheme, in which previous short-term forecasts are used to produce the initial perturbations for the current forecast. The stochastic convection scheme induces rapid perturbation growth in regions where convection is active, primarily in the tropics. When combined with the ET scheme, this results in larger initial perturbation variance in the tropics, and, because of a global constraint on total initial perturbation variance, smaller initial perturbation variance in the extratropics. Thus, the inclusion of stochastic convection helps to mitigate a problem found in the practical implementation of the ET, namely, that of too little initial variance in the tropics and too much in the extratropics. Various skill scores show that stochastic convection improves ensemble performance in the tropics, with little impact to modest improvement in the extratropics. Experiments performed using the initial perturbations from the control ensemble run but forecast integrations using the stochastic convection scheme indicate that the improved performance of the stochastic convection ensemble at early forecast times is due to both "indirect" changes in the initial perturbations and "direct" changes in the forecast. At later forecast times, it appears that most of the improvement can be gained through stochastic convection alone