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Seamless Combination of Convective Cells from Nowcasting and NWP with KONRAD3D-SINFONY – Part 2: Verification and Visualization

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KONRAD3D-SINFONY aims to improve the prediction of convective thunderstorms by integrating object-based nowcasting with ensemble forecasts from the high-resolution ICON-RUC model. This contribution focuses on the verification of KONRAD3D-SINFONY, beginning with a detailed evaluation of how accurately the ICON-RUC model reproduces the position, geometry, intensity, and temporal evolution of observed convective cells. In the subsequent analysis, we quantify the extent to which incorporating nowcasting data enhances these characteristics across a range of forecast lead times.Building on the ensemble of both corrected and model-derived cells, we investigate various methods to calculate probabilistic watch regions, which mark the areas where thunderstorms are most likely to occur. In addition, we aim to visualize the most relevant cell characteristics — including intensity, size, and associated weather hazards — in a format that is both clear and easily interpretable by forecasters. The quality of this condensed forecast visualization is assessed by comparing our predictions to both detected convective cells and the operational thunderstorm warnings issued by the German Weather Service (DWD).KONRAD3D-SINFONY is still under active development at DWD, and several physical effects and sources of information are not yet fully utilized within the current system. We highlight how incorporating these additional components could further optimize the cell combination process and improve the overall forecast quality. We conclude by outlining our plans for ongoing refinements and future development, with the goal of combining the results from nowcasting and numerical weather prediction in an optimal way and clearly presenting the most relevant information to users.
Title: Seamless Combination of Convective Cells from Nowcasting and NWP with KONRAD3D-SINFONY – Part 2: Verification and Visualization
Description:
KONRAD3D-SINFONY aims to improve the prediction of convective thunderstorms by integrating object-based nowcasting with ensemble forecasts from the high-resolution ICON-RUC model.
This contribution focuses on the verification of KONRAD3D-SINFONY, beginning with a detailed evaluation of how accurately the ICON-RUC model reproduces the position, geometry, intensity, and temporal evolution of observed convective cells.
In the subsequent analysis, we quantify the extent to which incorporating nowcasting data enhances these characteristics across a range of forecast lead times.
Building on the ensemble of both corrected and model-derived cells, we investigate various methods to calculate probabilistic watch regions, which mark the areas where thunderstorms are most likely to occur.
In addition, we aim to visualize the most relevant cell characteristics — including intensity, size, and associated weather hazards — in a format that is both clear and easily interpretable by forecasters.
The quality of this condensed forecast visualization is assessed by comparing our predictions to both detected convective cells and the operational thunderstorm warnings issued by the German Weather Service (DWD).
KONRAD3D-SINFONY is still under active development at DWD, and several physical effects and sources of information are not yet fully utilized within the current system.
We highlight how incorporating these additional components could further optimize the cell combination process and improve the overall forecast quality.
We conclude by outlining our plans for ongoing refinements and future development, with the goal of combining the results from nowcasting and numerical weather prediction in an optimal way and clearly presenting the most relevant information to users.

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