Assimilating visible satellite reflectances in combination with radar data in a pre-operational convective-scale seamless prediction system

In the framework of the SINFONY project at Deutscher Wetterdienst (DWD) we have developed data assimilation of visible satellite reflectances of the SEVIRI instrument (MSG) and radar observations in a rapid update cycle (ICON-D2-KENDA-RUC) which will be running in a first 24/7-testsuite starting in spring of this year. Our major goal related to the assimilation of these new observation systems is to improve the positioning of cloud and precipitation systems and their intensities, needed for the seamless transition of radar nowcasting to numerical weather prediction (NWP) in our SINFONY system. We give an overview of the steps undertaken in the course of developing the data assimilation of visible satellite reflectances. This includes quality control, observation error modelling, data reduction and bias correction of the reflectances. Further development and enhancement of the forward operator MFASIS is still ongoing. A major step to allow for a successful assimilation has been the improvement of microphysical consistency between the NWP model and MFASIS both with 1-moment and 2-moment microphysics to reduce the bias of first-guess departures. To further enhance and stabilize the agreement of observations and model climatologies over the course of the year and different weather regimes, an innovative histogram-based bias correction has been developed. We show results of data assimilation experiments combining visible reflectances and radar data in the ICON-D2-KENDA-Rapid Update Cycle using 2-moment microphysics. Further, we discuss the improvement of forecast skill from both observing systems and the way they complement each other – putting special emphasis to the key variable of interest in the SINFONY system, namely radar reflectivity.