Comparison of wind profiles in the operational ICON-D2 analysis with Doppler wind lidar observations in complex topography from the Swabian MOSES 2023 campaign

High-impact convective events are a common weather phenomenon around the world and can pose significant threats to people and property. However, our understanding of the governing processes of these events still remains incomplete, in particular their initiation and spatio-temporal evolution in regions with complex topography. Systematic validation of the quality of analysis and forecast data over complex terrain is often limited by poor availability of detailed observations. Together, these issues constitute a challenge for understanding and predicting convective events.

We aim at contributing to improved forecast quality and process understanding of convective summer-time conditions by leveraging extensive field campaign observations from the KITcube, the mobile atmospheric measurement platform of IMKTRO at KIT. To achieve this, we focus on the 'Swabian MOSES campaign' which took place in the Black Forest region, Germany, during the summer 2023 and provides, among others, observations from a large network of 12 Doppler wind lidars. From each Doppler wind lidar, we retrieve vertical profiles of the wind speed and direction. These observations of the dynamic structure of the lower troposphere are used to characterize the mesoscale (pre-)convective environment and are compared to the operational high-resolution analysis data of the German Weather Service. The three months of observations provide a comprehensive independent data set for the validation of the analysis data across the Black Forest. We present initial results from the field campaign, emphasizing convective conditions, and illustrate the comparison between high-resolution analysis and campaign observations for vertical profiles of wind speed and direction. First results show that the analysis bias differs between different sites, and at different altitudes, with a larger bias in the lowest 2 km. The comparison further reveals that the zonal component of the wind more strongly contributes to the bias. The campaign observations facilitate a better understanding of the complex interactions between the terrain and the overlying atmospheric processes as well as the evaluation of the performance and limitations of a convective-scale numerical weather prediction system.