The properties of European windstorms under present climate conditions are estimated on the basis of surface wind forecasts from the European Centre for Medium-Range Weather Forecast (ECMWF) Ensemble Prediction System (EPS). While the EPS is designed to provide forecast information of the range of possible weather developments starting from the observed state of weather, we use its archive in a climatological context. It provides a large number of modifications of observed storm events and includes storms that did not occur in reality. Thus it is possible to create a large sample of storm events, which entirely originate from a physically consistent model, whose ensemble spread represents feasible alternative storm realizations of the covered period. This paper shows that the huge amount of identifiable events in the EPS is applicable to reduce uncertainties in a wide range of fields of research focusing on winter storms. Windstorms are identified and tracked in this study over their lifetime using an algorithm based on the local exceedance of the 98th percentile of instantaneous 10 m wind speed, which is associated with a storm severity measure. After removing inhomogeneities in the data set arising from major modifications of the operational system, the distributions of storm severity, storm size, and storm duration are computed. The overall principal properties of the homogenized EPS storm data set are in good agreement with storms from the ERA-Interim data set, making it suitable for climatological investigations of these extreme events. A demonstrated benefit in the climatological context by the EPS is presented. It gives clear evidence of a linear increase of maximum storm intensity and wind field size with storm duration. This relation is not recognizable from a sparse ERA-Interim sample for long-lasting events, as the number of events in the reanalysis is not sufficient to represent these characteristics.

As part of a broader effort to develop next-generation models for numerical weather prediction and climate applications, a hydrostatic atmospheric dynamical core is developed as an intermediate step to evaluate a finite-difference discretization of the primitive equations on spherical icosahedral grids. Based on the need for mass-conserving discretizations for multi-resolution modelling as well as scalability and efficiency on massively parallel computing architectures, the dynamical core is built on triangular C-grids using relatively small discretization stencils. This paper presents the formulation and performance of the baseline version of the new dynamical core, focusing on properties of the numerical solutions in the setting of globally uniform resolution. Theoretical analysis reveals that the discrete divergence operator defined on a single triangular cell using the Gauss theorem is only first-order accurate, and introduces grid-scale noise to the discrete model. The noise can be suppressed by fourth-order hyper-diffusion of the horizontal wind field using a time-step and grid-size-dependent diffusion coefficient, at the expense of stronger damping than in the reference spectral model. A series of idealized tests of different complexity are performed. In the deterministic baroclinic wave test, solutions from the new dynamical core show the expected sensitivity to horizontal resolution, and converge to the reference solution at R2B6 (35 km grid spacing). In a dry climate test, the dynamical core correctly reproduces key features of the meridional heat and momentum transport by baroclinic eddies. In the aqua-planet simulations at 140 km resolution, the new model is able to reproduce the same equatorial wave propagation characteristics as in the reference spectral model, including the sensitivity of such characteristics to the meridional sea surface temperature profile. These results suggest that the triangular-C discretization provides a reasonable basis for further development. The main issues that need to be addressed are the grid-scale noise from the divergence operator which requires strong damping, and a phase error of the baroclinic wave at medium and low resolutions.

The Icosahedral Shallow Water Model (ICOSWM) has been a first step in the development of the ICON (acronym for ICOsahedral Nonhydrostatic) models. ICON is a joint project of the Max Planck Institute for Meteorology in Hamburg (MPI-M) and Deutscher Wetterdienst (DWD) for the development of new unified general circulation models for climate modeling and numerical weather forecasting on global or regional domains. A short description of ICOSWM is given. Standard test cases are used to test the performance of ICOSWM. The National Center for Atmospheric Research (NCAR) Spectral Transform Shallow Water Model (STSWM) has been used as reference for test cases without an analytical solution. The sensitivity of the model results to different model parameters is studied. The kinetic energy spectra are calculated and compared to the STSWM spectra. A comparison to the shallow water version of the current operational model GME at DWD is presented. The results presented in this paper use the ICOSWM version at the end of 2008 and are a benchmark for the new options implemented in the development of the ICON project.

The German Weather Service (Deutscher Wetterdienst) has recently developed a new operational global numerical weather prediction model, named GME, based on an almost uniform icosahedral‐hexagonal grid. The GME gridpoint approach avoids the disadvantages of spectral techniques as well as the pole problem in latitude‐ longitude grids and provides a data structure extremely well suited to high efficiency on distributed memory parallel computers. The formulation of the discrete operators for this grid is described and evaluations that demonstrate their second-order accuracy are provided. These operators are derived for local basis functions that are orthogonal and conform perfectly to the spherical surface. The local basis functions, unique for each grid point, are the latitude and longitude of a spherical coordinate system whose equator and zero meridian intersect at the grid point. The prognostic equations for horizontal velocities, temperature, and surface pressure are solved using a semi-implicit Eulerian approach and for two moisture fields using a semi-Lagrangian scheme to ensure monotonicity and positivity. In the vertical direction, finite differences are applied in a hybrid (sigma pressure) coordinate system to all prognostic variables. The semi-implicit treatment of gravity waves presented here leads to a 3D Helmholtz equation that is diagonalized into a set of 2D Helmholtz equations that are solved by successive relaxation. Most of the same physical parameterizations used in the authors’ previous operational regional model, named EM, are employed in GME. Some results from the verification process for GME are provided and GME performance statistics on a Cray T3E1200 as well as on the ECMWF Fujitsu VPP5000 systems are summarized. For the case of the severe Christmas 1999 storm over France and Germany the pronounced sensitivity of the model with respect to the initial state is discussed. Finally, a test case is shown where it is currently possible, though not yet operationally practical, to run GME at 15-km resolution on the VPP5000.