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The demand of accurate, near-real-time radar-based quantitative precipitation estimation (QPE), which is key to feed hydrological models and enable reliable flash flood predictions, was highlighted again by the disastrous floods following after an intense stratiform precipitation field passing western Germany on 14 July 2021. Three state-of-the-art rainfall algorithms based on reflectivity Z, specific differential phase KDP, and specific attenuation A were applied to observations of four polarimetric C-band radars operated by the German Meteorological Service [DWD (Deutscher Wetterdienst)]. Due to the large vertical gradients of precipitation below the melting layer suggesting warm-rain processes, all QPE products significantly underestimate surface precipitation. We propose two mitigation approaches: (i) vertical profile (VP) corrections for Z and KDP and (ii) gap filling using observations of a local X-band radar, JuXPol. We also derive rainfall retrievals from vertically pointing Micro Rain Radar (MRR) profiles, which indirectly take precipitation gradients in the lower few hundreds of meters into account. When evaluated with DWD rain gauge measurements, those retrievals result in pronounced improvements, especially for the A-based retrieval partly due to its lower sensitivity to the variability of raindrop size distributions. The VP correction further improves QPE by reducing the normalized root-mean-square error by 23% and the normalized mean bias by 20%. With the use of gap-filling JuXPol data, the A-based retrieval gives the lowest errors followed by the Z-based retrievals in combination with VP corrections. The presented algorithms demonstrate the increased value of radar-based QPE application for warm-rain events and related potential flash flooding warnings. [ABSTRACT FROM AUTHOR]

An important aspect of rainfall estimation is to accurately capture extreme events. Commercial microwave links (CMLs) can complement weather radar and rain gauge data by estimating path‐averaged rainfall intensities near ground. Our aim with this paper was to investigate attenuation induced complete loss of signal (blackout) in the CML data. This effect can occur during heavy rain events and leads to missing extreme values. We analyzed 3 years of attenuation data from 4,000 CMLs in Germany and compared it to a weather radar derived attenuation climatology covering 20 years. We observed that the average CML experiences 8.5 times more blackouts than we would have expected from the radar derived climatology. Blackouts did occur more often for longer CMLs (e.g., >10 km) despite their increased dynamic range. Therefore, both the hydrometeorological community and network providers can consider our analysis to develop mitigation measures. Plain Language Summary: Commercial microwave links (CMLs) are used to transmit information between towers of cellphone networks. If there is rainfall along the transmission path, the signal level is attenuated. By comparing the transmitted and received signal levels, the average rainfall intensity along the path can be estimated. If the attenuation is too strong, no signal is received, no information can be transmitted and no rainfall estimate is available. This is unfavorable both for network stability and rainfall estimation. In this study, we investigated the frequency of such blackouts in Germany. How many blackouts per year are observed in a 3 year CML data set covering around 4,000 link paths and how many are expected from 20 years of weather radar data? We observed that the average CML experiences 8.5 times more blackouts than we would have expected from the radar derived climatology. Blackouts did occur more often for long CMLs, which was an unexpected finding. While only one percent of the annual rainfall amount is missed during blackouts, the probability that a blackout occurs was very high for high rain rates. Both, the hydrometeorological community and network providers can consider our analysis to develop mitigation measures. Key Points: Complete loss of commercial microwave link (CML) signals during heavy rain leads to missing rainfall extremesMagnitude of observed blackouts exceeds climatologically expected valuesUnexpectedly, longer CMLs experience more blackouts [ABSTRACT FROM AUTHOR]

Recent advances demonstrate the benefits of radar-derived specific attenuation at horizontal polarization (AH) for quantitative precipitation estimation (QPE) at S and X band. To date the methodology has, however, not been adapted for the widespread European C-band radars such as those installed in the network of the German Meteorological Service (DWD, Deutscher Wetterdienst). Simulations based on a large dataset of drop size distributions (DSDs) measured over Germany are performed to investigate the DSD dependencies of the attenuation parameter αH for the AH estimates. The normalized raindrop concentration (Nw) and the change of differential reflectivity (ZDR) with reflectivity at horizontal polarization (ZH) are used to categorize radar observations into regimes for which scan-wise optimized αH values are derived. For heavier continental rain with ZH > 40 dBZ, the AH-based rainfall retrieval R(AH) is combined with a rainfall estimator using a substitute of specific differential phase ( K DP * ). We also assess the performance of retrievals based on specific attenuation at vertical polarization (AV). Finally, the regime-adapted hybrid QPE algorithms are applied to four convective cases and one stratiform case from 2017 to 2019, and compared to DWD's operational Radar-Online-Aneichung (RADOLAN) RW rainfall product, which is based on Zh only but adjusted to rain gauge measurements. For the convective cases, our hybrid retrievals outperform the traditional R(Zh) and pure R(AH/V) retrievals with fixed αH/V values when evaluated with gauge measurements and outperform RW when evaluated by disdrometer measurements. Potential improvements using ray-wise αH/V and segment-wise applications of the ZPHI method along the radials are discussed. [ABSTRACT FROM AUTHOR]

This work provides an analysis of the Weisseritz 2002 flood event in Eastern Germany, which was characterized by intense upslope storm movement and associated orographic enhancement of precipitation. Examination of the event is based on the availability of weather radar observations and post-event surveys to document the peak runoff rates. The analysis is based on the use of a set of statistics that clarify the dependence existing between spatial rainfall distribution, basin morphology, and runoff response. The statistics provide a description of overall spatial rainfall organization at the catchment scale in terms of concentration and dispersion statistics and storm motion, as a function of the flow distance coordinates, i.e., distance to the outlet measured along the flow path. The statistics are based on the observation that runoff routing through branched channel networks imposes an effective averaging of spatial rainfall at equal flow distance, despite the inherent spatial variability. A spatially distributed rainfall-runoff model is used to evaluate the effects of the rainfall spatial variability and storm velocity on flood modeling at various river sections. It is shown that storm velocity exhibits rather moderate values, despite the strong kinematic characteristics of individual storm elements. Consistently with this observation, hydrologic simulations show that orographically controlled rainfall spatial variability and storm motion have an almost negligible effect on flood response modeling. The drainage network structure filters out the effects of spatial rainfall variability for storm event hydrologic response, resulting in Weisseritz exhibiting striking uniformity of response to a storm with strongly varying precipitation. Overall, this shows the value of using the rainfall statistics introduced in this paper to isolate and describe the features of rainfall space-time variability that have significant impacts on runoff simulation. [ABSTRACT FROM AUTHOR]

Abstract: Pludix is an X-band disdrometer based on the Doppler effect, that provides rainfall intensity and drop size distribution output, and exhibits potential capabilities as a Present Weather Sensor (PWS). A Present Weather Sensor is an instrument capable of automatically detecting weather phenomena present at the time of observation. In order to verify the latter, two different methods have been developed to identify the precipitation types according to the WMO codes in its table 4680. With the first method (P-method), twelve precipitation codes are identified by analysing the characteristics of the Pludix power spectrum. With the second method (S-method), a statistical one based on a pattern recognition type algorithm, twenty-three precipitation codes are identified. With both methods main precipitation types are identified: drizzle, rain, snow, hail, ice crystals, mixed precipitation. Pludix is compared with the reference observations of a human observer during a campaign performed at the weather station of Wasserkuppe (central Germany, 950m a.s.l.). Two years of data are analysed (December 2000–January 2003); in this time interval there was a fair amount of both liquid and solid precipitation events, allowing us to evaluate the instrument capabilities. Pludix is also compared with the Vaisala FD12P PWS and with the optical disdrometer Parsivel which were tested in the same campaign. Since the S-method has only recently been developed and it is under investigation, the present analysis is mainly focusing on the P-method. The results show that Pludix performs quite well in distinguishing the precipitation type and it is generally in agreement with the human observations, especially for the rain case. Pludix also detects some situations (especially rain-showers with hail) that the human observer sometimes does not detect. The instrument is less sensitive to the slight precipitation, especially because it samples on a small measurement volume. We also test the performance of Pludix in measuring the rainfall-intensity, finding that it works better than the other instruments in the case of rain. [Copyright &y& Elsevier]