Doppler radars provide unique 3D information about precipitating clouds in high spatial and temporal resolutions. However, the observed quantities (reflectivity, Doppler velocity and polarization properties) are not directly comparable to the variables of numerical prediction models. In order to enable radar data assimilation, a comprehensive modular radar forward operator has been developed.

In this work, various simulation methods of the effective radar reflectivity factor and its attenuation by atmospheric particles from the variables of the COSMO model have been implemented within a so-called radar forward operator, and its output was compared to measurements from the German radar network. To perform a statistically reliable model verification, contoured frequency by altitude diagrams (CFADs) were used and refined.

This book presents the fundamentals of data assimilation and reviews the application of satellite remote sensing in hydrological data assimilation. Although hydrological models are valuable tools to monitor and understand global and regional water cycles, they are subject to various sources of errors. Satellite remote sensing data provides a great opportunity to improve the performance of models through data assimilation.

This work provides new insights into macro- and microphysical properties of Arctic mixed-phase clouds: first, by comparing semi-idealized large eddy simulations with observations; second, by dissecting the influences of different surface types and boundary layer structures on Arctic mixed- phase clouds; third, by elucidating the dissipation process; and finally by analyzing the main microphysical processes inside Arctic mixed-phase clouds.

The impact of land-surface properties like vegetation, soil type, soil moisture, and the orography on the atmosphere is manifold. These features determine the evolution of the atmospheric boundary layer, convective conditions, cloud evolution and precipitation. The impact of model grid spacing and land-surface resolution on convective precipitation over heterogeneous surfaces is investigated using ICOsahedral Nonhydrostatic (ICON) simulations within the framework of the HD(CP)2 project.

Coherent structures are patterns in the wind field of the atmospheric boundary layer. The deployment of two scanning Doppler lidars facilitates the measurement of the horizontal wind field, but the inherent averaging processes complicate an interpretation of the results. To assess the suitability of this technique for coherent structure detection large-eddy simulations are used as a basis for virtual measurements, and the effects of the lidar technique on the wind field structure are analyzed.

This study systematically investigates the representation of warm conveyor belts (WCBs) in large reforecast data sets of different numerical weather prediction models and evaluates the role of WCBs for the onset and life cycle of Atlantic-European weather regimes. The results emphasize the importance of accurate forecast of WCBs for sub-seasonal prediction on time scales beyond two weeks and tie the low forecast skill of blocked weather regimes over Europe to misrepresented WCBs.