Synergie eines effizienten polarimetrischen Radarvorwärtsoperators und eines hochentwickelten Klassifizierungsalgorithmus zur verbesserten Repräsentierung von Hydrometeoren im ICON-Modell (Operation Hydrometeors Part II)

高效的极化雷达前向算子和复杂的分类算法的协同作用，可改善 ICON 模型中水凝物的表示（水凝物操作第二部分）

• 批准号: 408027387
• 负责人: Dr. Ulrich Blahak
• 金额: --
• 依托单位: Abteilung FE1 für Meteorologische Analyse und Modellierung
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/408027387?language=en
• 关键词: Synergie; eines; effizienten; polarimetrischen; Radarvorw

In Phase 1 ‘Operation Hydrometeors’ provided an efficient polarimetric forward operator as a fundamental prerequisite to the Special Priority Programme required for the fusion of radar polarimetry and atmospheric modelling. The non-polarimetric Efficient Modular VOlume RADar OPerato (EMVORADO) has been extended to polarimetry assuming oblate spheroids at precipitation radar wavelengths in online implementations in the NWP-models COSMO and ICON and a stand-alone framework. We also developed a sophisticated and more robust hydrometeor classification (HMC) algorithm based on clustering with the additional capability to estimate hydrometeor partitioning ratios from both polarimetric radar observations and synthetic variables based on ICON simulations applying EMVORADO. With the tools developed, we evaluated polarimetric signatures and hydrometeors in stratiform rain employing a dual strategy, based on advanced radar-based hydrometeor typing and quantification and a direct comparison of multivariate observed and synthetic polarimetric signal distributions. Some improvements of the two-moment cloud microphysics parameterization in ICON resulted from this already.Phase 2 further refines the developed tools to broaden their applicability. We improve the melting scheme in EMVORADO, potentially also interface a scattering data base, and refine our new HMC to enable hydrometeor clusters to extend across the 0°C level. With these developments we evaluate and improve with our dual strategy the representation of three more key polarimetric signatures pointing to different model deficiencies: (1) Columns of enhanced differential reflectivity ZDR will guide improvements in the freezing process of raindrops, (2) ZDR near the surface is the key sign for a better parameterization of raindrop size distributions, and (3) polarimetric variables in the dendritic growth layer show pathways to improve and extend the representation of ice microphysical processes (e.g. secondary ice production) in ICON. Finally, we will exploit polarimetry-derived information for indirect data assimilation in ICON. Based on the developments of the project, we assimilate ZDR-column objects and/ or the partitioning ratios derived from our new HMC, most likely in the form of categorical ranking information.

在第一阶段，“水凝物行动”提供了一个有效的偏振测量前向操作员，作为雷达偏振测量和大气建模融合所需的特别优先方案的基本先决条件。非偏振有效的模块化体积雷达OPerato（EMVORADO）已扩展到偏振，假设扁球体在降水雷达波长在线实现的NWP模型COSMO和ICON和一个独立的框架。我们还开发了一个复杂的和更强大的水凝物分类（HMC）算法的基础上聚类与额外的能力，以估计水凝物分区比从偏振雷达观测和合成变量的基础上ICON模拟应用EMVORADO。与开发的工具，我们评估了偏振签名和水凝物在层状雨采用双重策略，先进的雷达为基础的水凝物分型和量化和直接比较的多元观测和合成的偏振信号分布。ICON的二阶矩云微物理参数化已经有了一些改进，第二阶段进一步完善了所开发的工具，以扩大其适用性。我们改进了EMVORADO中的熔化方案，还可能与散射数据库接口，并改进了我们新的HMC，使水凝物集群能够扩展到0°C水平。随着这些发展，我们评估并改进了我们的双重策略，三个更关键的极化签名的表示指向不同的模型缺陷：（1）增强的差反射率ZDR柱将指导雨滴冻结过程的改善，（2）近地面的ZDR是更好地参数化雨滴尺寸分布的关键标志，（3）枝晶生长层中的极化变量显示了改善和扩展ICON中冰微物理过程（例如二次制冰）的代表性的途径。最后，我们将利用偏振派生信息的间接资料同化在ICON。根据项目的发展，我们吸收ZDR柱对象和/或来自我们的新HMC的分区比，最有可能的形式分类排名信息。