Integrating KONRAD3D-Sinfony Ensemble Information into the Nowcasting Guidance System NowCastMIX

Short-term warnings for severe thunderstorms are generated at the German Weather Service (DWD) through the NowCastMIX system, which provides automated warnings for the next 60 minutes. NowCastMIX processes meteorological fields from various sources, including NWP, radar, surface station reports, and lightning detections. Every five minutes, the system employs a hierarchy of fuzzy logic sets to calculate the potential for heavy rain, hail, and severe gusts based on the available data. Categorical thunderstorm warnings are then issued for detected cells, and regions requiring warnings are identified by condensing the information into clusters.
In previous work, the original KONRAD cell detection scheme within NowCastMIX was replaced by a newly developed and more sophisticated cell detection and tracking algorithm called KONRAD3D. This advancement enabled a more precise three-dimensional analysis of convective cells based on radar volume scans, leading to improved characterization of storm structures. Building on this foundation, the next step is to leverage the latest development: KONRAD3D-SINFONY. This extended version not only identifies convective cells but also generates ensemble-based information about future cell behavior.
Although NowCastMIX incorporates ensemble data from numerical weather prediction (NWP) models to characterize the near-storm environment, a limitation remains due to its primarily deterministic nature, which does not fully account for the inherent uncertainty in convective development. To address this, we investigate how the ensemble-based output of the newly developed KONRAD3D-SINFONY system can be utilized within the NowCastMIX framework. Our research focuses on methods to incorporate probabilistic cell detections into the existing warning system, enabling a more nuanced representation of forecast uncertainty.