Project Details
Projekt
Physics-based QPE using polarimetric radars and commercial microwave links
Subject Area
Atmospheric Science
Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
Term
since 2018
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 320397309
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.
DFG Programme
Research Units
Subproject of
FOR 2589:
Near-Realtime Quantitative Precipitation Estimation and Prediction (RealPEP)
Co-Investigator
Professor Dr. Harald Kunstmann
