SPP 2115: Polarimetric Radar Observations meet Atmospheric Modelling (PROM) - Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes

优先方案SPP2115“极化雷达观测满足大气建模(PROM)”是一项协调努力，旨在通过利用极化雷达观测的信息内容，挑战和改进大气模型中云和降水过程的表示。在PROM中，雷达偏振、大气建模和数据同化方面的专家共同努力，促进和加速观测和大气建模的融合。第一个供资阶段进行了一次尽可能全面的利用和了解全国极化雷达观测，并辅之以SuperSite提供的最先进的测量设备和技术。模型师第一次将与微物理相关的三维观测数据掌握在手中，以改进参数设置。此外，第一阶段开发了伴随着不确定性的新的微物理反演，并开始开发用于模式评估和雷达信息参数化的微物理反演。已开发的一些工具仍然需要改进，例如，雷达观测操作符需要一个与散布数据库的接口，该数据库具有更真实的冰雪颗粒表示。在第二阶段，将有更多的项目利用所开发的观测见解和工具，目的是改进参数和吸收偏振信息；因此，现在可以更积极地处理雷达偏振和大气模型的融合问题。

The priority programme SPP2115 „Polarimetric Radar Observations meet Atmospheric Modelling (PROM)“ is a coordinated effort to challenge and improve the representation of cloud and precipitation processes in atmospheric models by exploiting the information content of polarimetric radar observations. In PROM experts in radar polarimetry, atmospheric modelling, and data assimilation work together to facilitate and accelerate the fusion of observations and atmospheric modelling. The first funding phase engaged in an as complete as possible exploitation and understanding of nation-wide polarimetric radar observations complemented by state-of-the-art measurement devices and techniques available at supersites. For the first time, modellers hold three-dimensional microphysics-related observational data in their hands to improve parameterisations. In addition, Phase 1 developed new microphysical retrievals accompanied by uncertainties and started their exploitation for model evaluation and radar-informed parameterizations. Some tools developed still require refinements, e.g. the radar observation operator requires an interface to a scattering data base with more realistic representations of ice and snow particles. In Phase 2 more projects will exploit the observational insights and tools developed with the goal to improve parameterizations and assimilate polarimetric information; thus the fusion of radar polarimetry and atmospheric modelling can now be approached even more aggressively.