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

RealPEP基于数值天气预报（NWP）的定量降水估计（QPE）、定量降水临近预报（QPN）和定量降水预报（QPF）的假设，利用该中心服务项目提供的降水生成大气的全观测状态演变信息，可以显著提高数值天气预报（NWP）的定量降水估计（QPE）、定量降水临近预报（QPN）和定量降水预报（QPF）。C1将建立和维护一个数据收集和开发平台，该平台将所有云和降水相关的观测数据结合在一个三维复合材料中，水平至少1公里x 1公里，垂直至少500米，时间分辨率为5分钟，覆盖德国。这种基于观测的网格状态演变构成了项目P1 （QPE）、P2 （QPN）和P3 （QPF）的主要数据基础，这些项目反过来又以观测、现播和预测地面降雨强度和类型的形式为P4（洪水预测）提供中心输入。除了复合材料，C1将在其固有坐标系中提供处理过的单传感器数据，用于P1中基于衰减的最高质量降水检索的开发，以及P3中集成卡尔曼滤波方法的数据同化实验。除了DWD网络的极化雷达观测和NWP分析和预测外，C1将整合基于卫星的近红外和热红外观测、gnss衍生的总柱水汽场和闪电数据。总水汽场的平流和辐合将与P2合作，丰富基于观测的近预报，显示对流的启动和降水的增强。数据收集和开发平台将采用DWD c++处理平台POLARA，该平台已经包含了几种标准的雷达处理和分析工具，适用于创建P1到P4的初始数据，并将在RealPEP过程中进行扩展。C1将通过RealPEP和其他来源的开发启动和指导POLARA的更新，并将其整合到从QPE到洪水预测的RealPEP流程链中。

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.