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A major issue in convective‐scale ensemble prediction systems (EPSs) is the specification of effective initial condition perturbations (ICPs). The present work considers the suitability of downscaled ICPs from a multi‐model global EPS for short‐range regional ensemble forecasts of convective precipitation at convection‐permitting resolution. Previous studies indicated the importance of convective‐scale initial condition uncertainties, with the most pronounced impact in weather conditions characterised by weak versus strong synoptic‐scale forcing of convection. However, the downscaled ICPs do not explicitly represent small‐scale uncertainty, which questions their effectiveness in convective‐scale EPSs. To investigate the issue, the high‐resolution ensemble system of the Deutscher Wetterdienst, COSMO‐DE‐EPS, which includes physics perturbations and lateral boundary condition perturbations in addition to ICPs, is employed. Forecasts are compared with a second EPS, identical but without ICPs, for a period of 3.5 months in the central European warm season. Weakly forced conditions are considered separately from strongly forced conditions, using an objective classification based on the area‐averaged convective adjustment time‐scale. Generally for all EPSs, forecast quality measures show a distinct behaviour in strong versus weak forcing conditions. However, the impact of the ICPs is found to be similar in the two regimes. The impact of the ICPs is clearly largest and positive (consistently in terms of ensemble variance and probabilistic forecast quality, but negative for the equitable threat score) in the first six forecast hours when the ICPs dominate the physics perturbations and lateral boundary condition perturbations. The ICPs then decay relatively quickly with lead time as the physics perturbations and lateral boundary condition perturbations start to become important and later dominant. Probabilistic precipitation forecasts by the EPSs outperform the deterministic COSMO‐DE at the same convection‐permitting resolution, and this more strongly in the first nine forecast hours with the EPS applying the ICPs.

Abstract. Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the NavierStokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each system.

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