Glenn Shutts

TL;DR: In this paper, the failure to parametrize subgrid-scale orographic gravity wave drag may account for the westerly biases in the northern hemisphere wintertime flow of the Meteorological Office 15-layer operational model and 11-layer general circulation model.

TL;DR: In this paper, a spectral stochastic kinetic energy backscatter scheme is used to simulate upscale-propagating errors caused by unresolved subgrid-scale processes for numerical weather prediction models.

TL;DR: It is argued that multimodel and related ensemble are vastly superior to corresponding single-model ensembles, but do not provide a comprehensive representation of model uncertainty.

Abstract: 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.

TL;DR: In this paper, the authors describe a major upgrade to the global ensemble, which affected both the initial condition and model uncertainty perturbations applied in that ensemble, and show that the localization of the ETKF gives a distribution of the spread as a function of latitude that better matches the forecast error of the ensemble mean.