Stochastic Parametrization and Model Uncertainty

Stochastic parametrization provides a methodology for representing model uncertainty in ensemble forecasts, and also has the capability of reducing systematic error through the concept of nonlinear noise-induced rectification. The stochastically perturbed parametrization tendencies scheme and the stochastic backscatter scheme are described and their impact on medium-range forecast skill is discussed. The impact of these schemes on ensemble data assimilation and in seasonal forecasting is also considered. In all cases, the results are positive. Validation of the form of these stochastic parametrizations can be found by coarse-grain budgets of high resolution (e.g. cloud-resolving) models; some results are shown. Stochastic parametrization has been pioneered at ECMWF over the last decade, and now most operational centres use stochastic parametrization in their operational ensemble prediction systems these are briefly discussed. The seamless prediction paradigm implies that serious consideration should now be given to the use of stochastic parametrization in next generation Earth System Models.