16Global simulations with 1.45 km grid-spacing are presented that were per-17 formed with the Integrated Forecasting System (IFS) of the European Cen-18 tre for Medium-Range Weather Forecasts (ECMWF). Simulations are un-19 coupled (without ocean, sea-ice or wave model), using 62 or 137 vertical lev-20 els and the full complexity of weather forecast simulations including recent 21 date initial conditions, real-world topography, and state-of-the-art physical 22 parametrizations and diabatic forcing including shallow convection, turbu-23 lent diffusion, radiation and five categories for the water substance (vapour, 24 liquid, ice, rain, snow). Simulations are evaluated with regard to computa-25 tional efficiency and model fidelity. Scaling results are presented that were 26 performed on the fastest supercomputer in Europe -Piz Daint (Top 500, 27 Nov 2018). Important choices for the model configuration at this unprece-28 dented resolution for the IFS are discussed such as the use of hydrostatic 29 and non-hydrostatic equations or the time resolution of physical phenomena 30 which is defined by the length of the time step. 31 Our simulations indicate that the IFS model -based on spectral trans-32 forms with a semi-implicit, semi-Lagrangian time-stepping scheme in con-33 trast to more local discretisation techniques -can provide a meaningful 34 baseline reference for O(1) km global simulations.35 1

<p>Global simulations with 1.45 km grid-spacing are presented that were performed with the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Simulations are uncoupled (without ocean, sea-ice or wave model), using 62 or 137 vertical levels and the full complexity of weather forecast simulations including recent date initial conditions, real-world topography, and state-of-the-art physical parametrizations and diabatic forcing including shallow convection, turbulent diffusion, radiation and five categories for the water substance (vapour, liquid, ice, rain, snow). Simulations are evaluated with regard to computational efficiency and model fidelity. Scaling results are presented that were performed on the fastest supercomputer in Europe - Piz Daint (Top 500, Nov 2018). Important choices for the model configuration at this unprecedented resolution for the IFS are discussed such as the use of hydrostatic and non-hydrostatic equations or the time resolution of physical phenomena which is defined by the length of the time step. </p><p>Our simulations indicate that the IFS model — based on spectral transforms with a semi-implicit, semi-Lagrangian time-stepping scheme in contrast to more local discretization techniques — can provide a meaningful baseline reference for O(1) km global simulations.</p>

Abstract. The increase in computing power and recent model developments allow the use of global kilometer-scale weather and climate models for routine forecasts. At these scales, deep convective processes can be partially resolved explicitly by the model dynamics. Next to horizontal resolution, other aspects such as the applied numerical methods, the use of the hydrostatic approximation, and timestep size are factors that might influence a model's ability of resolving deep convective processes. In order to improve our understanding of the role of these factors, a model intercomparison between the nonhydrostatic COSMO model and the hydrostatic Integrated Forecast System (IFS) from ECMWF has been conducted. Both models have been run with different spatial and temporal resolutions in order to simulate two summer days over Europe with strong convection. The results are analyzed with focus on vertical wind speed and precipitation. Results show that even at around 3 km horizontal grid spacing the effect of the hydrostatic approximation seems to be negligible. However, timestep proves to be an important factor for deep convective processes, with a reduced timestep generally allowing for higher updraft velocities and thus more energy in vertical velocity spectra, in particular for smaller wavelengths. A shorter timestep is also causing an earlier onset and peak of the diurnal cycle. Furthermore, the amount of horizontal diffusion plays a crucial role for deep convection with more diffusion generally leading to larger convective cells and higher precipitation intensities. The study also shows that for both models the parameterization of deep convection leads to lower updraft and precipitation intensities and biases in the diurnal cycle with a precipitation peak which is too early.

Abstract. The increase in computing power and recent model developments allow for the use of global kilometer-scale weather and climate models for routine forecasts. At these scales, deep convective processes can be partially resolved explicitly by the model dynamics. Next to horizontal resolution, other aspects such as the applied numerical methods, the use of the hydrostatic approximation, and time step size are factors that might influence a model's ability to resolve deep convective processes. In order to improve our understanding of the role of these factors, a model intercomparison between the nonhydrostatic COSMO model and the hydrostatic Integrated Forecast System (IFS) from ECMWF has been conducted. Both models have been run with different spatial and temporal resolutions in order to simulate 2 summer days over Europe with strong convection. The results are analyzed with a focus on vertical wind speed and precipitation. Results show that even at around 3 km horizontal grid spacing the effect of the hydrostatic approximation seems to be negligible. However, time step proves to be an important factor for deep convective processes, with a reduced time step generally allowing for higher updraft velocities and thus more energy in vertical velocity spectra, in particular for shorter wavelengths. A shorter time step is also causing an earlier onset and peak of the diurnal cycle. Furthermore, the amount of horizontal diffusion plays a crucial role for deep convection with more diffusion generally leading to larger convective cells and higher precipitation intensities. The study also shows that for both models the parameterization of deep convection leads to lower updraft and precipitation intensities and biases in the diurnal cycle with a precipitation peak which is too early.