Infrastructure project: Multi-Sensor Compositing for Hydrometeor Classification, High-Impact Weather, Nowcasting and Data Assimilation

• Applicant: Privatdozentin Silke Trömel, Ph.D.
• Subject Area: Atmospheric Science ; Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
• Term: since 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 320397309

RealPEP follows the hypothesis, that Quantitative Precipitation Estimation (QPE), Quantitative Precipitation Nowcasting (QPN) and Quantitative Precipitation Forecasting (QPF) by Numerical Weather Prediction (NWP) can be significantly improved by exploiting the full observational state evolution information of the precipitation-generating atmosphere, which will be provided by this central service project. C1 will build and maintain a data collection and exploitation platform, which combines all cloud and precipitation-related observations in a 3D composite with at least 1 km x 1 km horizontal, 500 m vertical, and 5 minute temporal resolution covering Germany. This gridded observation-based state evolution constitutes the prime data base for projects P1 (QPE), P2 (QPN), and P3 (QPF), which in turn all provide the central input to P4 (Flood Prediction) in the form of observed, nowcasted, and predicted surface rainfall intensity and type. In addition to the composite, C1 will provide processed single-sensor data in their innate coordinate systems for the development of highest-quality attenuation-based precipitation retrievals in P1 and for data assimilation experiments in the Ensemble Kalman Filter approach in P3.Besides polarimetric radar observations of the DWD network and NWP analyses and predictions C1 will integrate satellite-based near- and thermal infrared observations, GNSS-derived total column water vapor fields and lightning data. In cooperation with P2, advection and convergence of total water vapor fields will enrich observation-based nowcasting with indications of convection initiation and intensifying precipitation.The data collection and exploitation platform will employ the DWD C++ processing platform POLARA, which includes already several standard radar processing and analysis tools suitable for creating initial data for P1 to P4, and which will be expanded during the course of RealPEP. C1 will initiate and guide the updating of POLARA with developments by RealPEP and from other sources, and its integration into the RealPEP process chain from QPE to flood prediction.

• DFG Programme: Research Units
• Subproject of: FOR 2589: Near-Realtime Quantitative Precipitation Estimation and Prediction (RealPEP)
• Co-Investigator: Professor Dr. Clemens Simmer