Physics-based QPE using polarimetric radars and commercial microwave links

使用偏振雷达和商用微波链路的基于物理的 QPE

• 批准号: 404444033
• 负责人: Dr. Christian Chwala
• 金额: --
• 依托单位: Lehrstuhl für Regionales Klima und Hydrologie
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/404444033?language=en
• 关键词: Physics; based; QPE; using; polarimetric

The core objective of P1 is a most accurate and reliable near-real time quantitative precipitation estimation (QPE). The estimate will be primarily based on observations from a network of polarimetric radars and attenuation measurements of commercial microwave links (CMLs), which provide the backhaul of countrywide cell phone networks. We will improve, newly develop and evaluate novel, generally applicable methods and apply them to observations of the recently fully upgraded dual-polarization C-band radar network of the German national weather service (DWD) and of a CML subnet operated by Ericsson Germany. QPE for liquid precipitation will be based on specific attenuation R(A) following a method co-developed by the applicants and already successfully applied to S- and X-band radars. The method will be adapted, transferred to and optimized for DWDs radar network. For improving QPE for mixed-phase precipitation, we will exploit polarimetry for hydrometeor classification and develop new polarimetric methods for the quantification of snow fall intensity. To improve QPE at distances far away from the radars, we will develop the first polarimetric correction method for vertical reflectivity profiles, which will significantly improve QPE in regions with measurements only within and above the melting layer. Finally, we will further improve polarimetry-based QPE by a new synergistic approach pioneered by the proposers for exploiting a nationwide CML network to which we have real-time access. This approach will not only increase QPE quality in Germany, but also strengthen our processing tools for the derivation of rainfall information from CMLs alone, which is necessary when employing this emerging technique in the absence of weather radar information like in developing countries.

P1的核心目标是最准确和最可靠的近实时定量降水估计(QPE)。这一估计将主要基于对极化雷达网络的观察和商业微波链路(CML)的衰减测量，这些链路提供全国手机网络的回程。我们将改进、新开发和评估新的、普遍适用的方法，并将它们应用于最近完全升级的德国国家气象局(DWD)的双极化C波段雷达网和由爱立信德国公司运营的CML子网的观测。液体沉淀的QPE将以比衰减R(A)为基础，遵循申请人共同开发的方法，并已成功应用于S和X波段雷达。该方法将适用于DWDS雷达网，并对其进行优化。为了提高混合相降水的QPE，我们将利用旋光法对水流星进行分类，并开发新的旋光法来量化降雪强度。为了改善远离雷达的QPE，我们将开发第一个垂直反射率剖面的偏振校正方法，该方法将显著改善仅在熔融层及其以上测量的区域的QPE。最后，我们将通过一种新的协同方法来进一步改进基于旋光法的QPE，该方法由提出者开创，用于利用我们可以实时访问的全国CML网络。这种方法不仅将提高德国的QPE质量，还将加强我们仅从CMLS获得降雨信息的处理工具，这在发展中国家等缺乏天气雷达信息的情况下使用这一新兴技术是必要的。