A radar-based quantitative precipitation estimation algorithm to overcome the impact of vertical gradients of warm-rain precipitation: the flood in western Germany on 14 July 2021

The importance of accurate and near real-time radar-based quantitative precipitation estimation (QPE) and derived nowcasting products, which are key to feed hydrological models and enable reliable flash flood predictions, was illustrated again by the disastrous flooding in West Germany after a long-lasting intense stratiform precipitation event on 14 July 2021. We applied three state-of-the-art rainfall algorithms to four operational polarimetric C-band radars of the German Meteorological Service (DWD, Deutscher Wetterdienst): one is based on radar reflectivities Z only, while two hybrid algorithms use specific differential phase K_DP in heavy rain combined with Z or specific attenuation A in light rain, respectively. Since large vertical variability of the precipitation flux was observed below the melting layer during the warm-rain process, all QPE products showed significant underestimation. To mitigate this impact on the accuracy of QPE, two approaches have been proposed in this work: i) the inclusion of a local X-band radar, JUXPOL, with lower-altitude observations, and ii) a vertical profile correction for Z and K_DP using so-called range-defined quasi-vertical profiles (RD-QVP) to quantify vertical changes of these variables. When evaluated with DWD rain gauge measurements, JUXPOL and vertical profile correction have considerably improved the accuracy of the rainfall estimates by reducing at least 8% and 30% of normalized mean bias, respectively. QPEs with vertical profile correction even beat DWD’s operational rainfall product, which is based on Z only but hourly adjusted to rain gauge measurements. This greatly increases the value of radar-based QPE algorithms for warm-rain events and potential flood alerts.