KONRAD3D-SINFONY (K3DS) aims to provide the most accurate prediction of convective events by combining cells detected in radar observations with predictions from the ICON Rapid Update Cycle (ICON-RUC) model. To achieve this, we move model cells spatially and temporally and modify them to match observed cells better and we add nowcasting cells to the ensemble. For increasing lead times, the impact of observation and nowcasting diminishes and after about two hours the prediction becomes purely model based.K3DS depends on many underlying systems such as the radar data, the cell detection algorithm, nowcasting, the model, and simulated radar sweeps. To improve K3DS systematically, we set up a framework to recalculate and evaluate days with strong convection in summer 2024. This allows us to measure the performance of K3DS and test which modifications yield more realistic predictions. Our tests can, hence, reveal disprepancies between predicted and observed convective cells and can provide hints how these underlying systems can be improved.A current focus of our work is the visualization and interpretation of the K3DS results. As part of this effort, we transform the K3DS cell ensemble into a probabilistic forecast, which we aim to optimize. In the future, this probabilistic prediction can serve as the basis for issuing automated thunderstorm potential warnings with lead times of up to six hours. The automation of these warnings is currently under development within the framework of the DWD RainBoW project.
Strotjohann et al. (Fri,) studied this question.