Abstract
<p><span>The study of radar data assimilation (reflectivity, radial wind and cell object) in NWP models and its effect particularly on short-term forecast has been intensified recently at DWD. In particular, the seamless Integrated ForecastiNg sYstem (SINFONY) project, which develops a short-term forecasting system with a focus on convective events from minutes up to 12 hours ahead, shows clearly the benefit of radar data assimilation in improving the short-term forecast. This system integrates Nowcasting techniques for radar data with numerical weather prediction (NWP based on the new ICON-model) in a seamless way with initial focus on severe summertime convective events and associated hazards such as heavy precipitation, hail and wind gusts. </span></p><p><span>Besides, radar data assimilation is being operationally used in the short-range ensemble numerical weather prediction (SRNWP) system (ICON-D2-KENDA LETKF system) at DWD since 2020 (radial wind starting in March 2020 and reflectivity starting in June 2020). This is in addition to the traditional Latent Heat Nudging (LHN) of 2D radar-derived precipitation rates. For both systems, SRNWP and SINFONY, the usage of 3D radar data is not only advantageous but crucial to improve the forecast skills related to convection and precipitation.</span></p><p><span>We will present the latest results of our research in radar assimilation at DWD including the application of radar data assimilation together with a more sophisticated cloud microphysiscs parameterization (a 2-moment bulk scheme) and in combination with the LHN in the SINFONY forecasting system. We also study to assimilate radar information in the alternative form of convective cell objects. Of particular interest are for example the specification of the radar observation error, but also other topics related to the improvement of short-term forecasts.</span></p>
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