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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]

This paper evaluates convective precipitation as simulated by the convection-permitting climate model (CPM) Consortium for Small-Scale Modeling in climate mode (COSMO-CLM) (with 2.8 km grid-spacing) over Germany in the period 2001–2015. Characteristics of simulated convective precipitation objects like lifetime, area, mean intensity, and total precipitation are compared to characteristics observed by weather radar. For this purpose, a tracking algorithm was applied to simulated and observed precipitation with 5-min temporal resolution. The total amount of convective precipitation is well simulated, with a small overestimation of 2%. However, the simulation underestimates convective activity, represented by the number of convective objects, by 33%. This underestimation is especially pronounced in the lowlands of Northern Germany, whereas the simulation matches observations well in the mountainous areas of Southern Germany. The underestimation of activity is compensated by an overestimation of the simulated lifetime of convective objects. The observed mean intensity, maximum intensity, and area of precipitation objects increase with their lifetime showing the spectrum of convective storms ranging from short-living single-cell storms to long-living organized convection like supercells or squall lines. The CPM is capable of reproducing the lifetime dependence of these characteristics but shows a weaker increase in mean intensity with lifetime resulting in an especially pronounced underestimation (up to 25%) of mean precipitation intensity of long-living, extreme events. This limitation of the CPM is not identifiable by classical evaluation techniques using rain gauges. The simulation can reproduce the general increase of the highest percentiles of cell area, total precipitation, and mean intensity with temperature but fails to reproduce the increase of lifetime. The scaling rates of mean intensity and total precipitation resemble observed rates only in parts of the temperature range. The results suggest that the evaluation of coarse-grained (e.g., hourly) precipitation fields is insufficient for revealing challenges in convection-permitting simulations. [ABSTRACT FROM AUTHOR]

This study presents δ26Mg values, Mg2+ concentrations, δ18O and δ2H values of monthly collected rain and snow samples between 2014 and 2017 from north‐west Germany. The δ26Mg values of snow are similar to those of rain. Unlike δ18O and δ2H, neither δ26Mgprecipitation values nor Mg2+ concentrations display a relationship with air temperature. In contrast, δ26Mgprecipitation values and Mg2+ concentrations are correlated with precipitation amount. As previously suggested by other studies but now based on a larger data set, it is proposed that the δ26Mg values and Mg2+ concentrations are affected by the mineralogical composition and amount of airborne dust. Consequently, a small number of random precipitation samples cannot represent the complex processes influencing the δ26Mgprecipitation values. δ26Mgprecipitation can be used to differentiate between seawater aerosols, carbonate and silicate dust. Silicate dust is typified by higher Mg concentrations and δ26Mg values compared to carbonate dust. Concerning carbonates, dolostone dust has higher Mg concentrations and δ26Mg values, while limestone dust is Mg‐lean with lower δ26Mg values. Dust of anthropogenic origin in the region can come from active limestone and dolostone quarries, surface mining of siliciclastics, and agriculture on silicate‐rich soils. Although dust of this mineralogy can also be of natural origin, most natural dust consists of airborne silicates transported by wind systems from the Sahara to Europe. Higher δ26Mgprecipitation values would indicate silicate or dolostone dust influx. Lower δ26Mgprecipitation values suggest lower dust concentrations and a predominantly calcitic dust mineralogy. It appears that δ26Mgprecipitation is most probably influenced by changes in weather conditions and natural and anthropogenic dust origin. This study implies that δ26Mgprecipitation is a potential proxy for dust mineralogy and fluxes. Nevertheless, further research should include the determination of atmospheric dust mineralogy and their fractions as well as air mass back trajectory analysis to identify the source(s) of dust. [ABSTRACT FROM AUTHOR]

Climate signal maps can be used to identify regions where robust climate changes can be derived from an ensemble of climate change simulations. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Climate signal maps do not show all information available from the model ensemble, but give a condensed view in order to be useful for non-climate scientists who have to assess climate change impact during the course of their work. Three different ensembles of regional climate projections have been analyzed regarding changes of seasonal mean and extreme precipitation (defined as the number of days exceeding the 95th percentile threshold of daily precipitation) for Germany, using climate signal maps. Although the models used and the scenario assumptions differ for the three ensembles (representative concentration pathway (RCP) 4.5 vs. RCP8.5 vs. A1B), some similarities in the projections of future seasonal and extreme precipitation can be seen. For the winter season, both mean and extreme precipitation are projected to increase. The strength, robustness and regional pattern of this increase, however, depends on the ensemble. For summer, a robust decrease of mean precipitation can be detected only for small regions in southwestern Germany and only from two of the three ensembles, whereas none of them projects a robust increase of summer extreme precipitation. [ABSTRACT FROM AUTHOR]

We examined 3 years of measured daily values of all major water budget components (precipitation P, potential evapotranspiration PET, actual evapotranspiration ET, and runoff R) and volumetric soil water content θ of a small, forested catchment located in the west of Germany. The spatial distribution of θ was determined from a wireless sensor network of 109 points with 3 measurement depths each; ET was calculated from eddy-covariance tower measurements. The water budget was dominantly energy limited, with ET amounting to approximately 90% of PET, and a runoff ratio R/P of 56%. P, ET, and R closed the long-term water budget with a residual of 2% of precipitation. On the daily time scale, the residual of the water budget was larger than on the annual time scale, and explained to a moderate extent by θ ( R2 = 0.40). Wavelet analysis revealed subweekly time scales, presumably dominated by unaccounted fast-turnover storage terms such as interception, as a major source of uncertainty in water balance closure. At weekly resolution, soil water content explained more than half ( R2 = 0.62) of the residual. By means of combined empirical orthogonal function and cluster analysis, two slightly different spatial patterns of θ could be identified that were associated with mean θ values below and above 0.35 cm3/cm3, respectively. The timing of these patterns as well as the varying coherence between PET, ET, and soil water content responded to changes in water availability, including a moderate response to the European drought in spring 2011. [ABSTRACT FROM AUTHOR]

Simulations of orographic precipitation over the low mountain ranges of southwestern Germany and eastern France with two different physics-based linear precipitation models are presented. Both models are based on 3D airflow dynamics from linear theory and consider advection of condensed water and leeside drying. Sensitivity studies for idealized conditions and a real case study show that the amount and spatial distribution of orographic precipitation is strongly controlled by characteristic time scales for cloud and hydrometeor advection and background precipitation due to large-scale lifting. These parameters are estimated by adjusting the model results on a 2.5-km grid to observed precipitation patterns for a sample of 40 representative orography-dominated stratiform events (24 h) during a calibration period (1971--80). In general, the best results in terms of lowest rmse and bias are obtained for characteristic time scales of 1600 s and background precipitation of 0.4 mm h−−1. Model simulations of a sample of 84 events during an application period (1981--2000) with fixed parameters demonstrate that both models are able to reproduce quantitatively precipitation patterns obtained from observations and reanalyses from a numerical model [[Consortium for Small-scale Modeling (COSMO)]]. Combining model results with observation data shows that heavy precipitations over mountains are restricted to situations with strong atmospheric forcings in terms of synoptic-scale lifting, horizontal wind speed, and moisture content. [ABSTRACT FROM AUTHOR]

To determine return values at various return periods for extreme daily precipitation events over complex orography, an appropriate threshold value and distribution function are required. The return values are calculated using the peak-over-threshold approach in which only a reduced sample of precipitation events exceeding a predefined threshold is analyzed. To fit the distribution function to the sample, the L-moment method is used. It is found that the deviation between the fitted return values and the plotting positions of the ranked precipitation events is smaller for the kappa distribution than for the generalized Pareto distribution. As a second focus, the ability of regional climate models to realistically simulate extreme daily precipitation events is assessed. For this purpose the return values are derived using precipitation events exceeding the 90th percentile of the precipitation time series and a fit of a kappa distribution. The results of climate simulations with two different regional climate models are analyzed for the 30-yr period 1971–2000: the so-called consortium runs performed with the climate version of the Lokal Modell (referred to as the CLM-CR) at 18-km resolution and the Regional Model (REMO)–Umweltbundesamt (UBA) simulations at 10-km resolution. It was found that generally the return values are overestimated by both models. Averaged across the region the overestimation is higher for REMO–UBA compared to CLM-CR. [ABSTRACT FROM AUTHOR]

The precipitation diurnal cycle (PDC) varies with the season and location. Its link to large-scale weather circulations has been studied in different regions. However, comparable information is lacking for Central Europe. Two decades of hourly precipitation data were combined with records of objective weather patterns over Germany, focusing on the general atmospheric wind directions (WD). The PDC is characterized by the frequency and the average amount of hourly precipitation. The precipitation frequency generally has two peaks: one in the morning and the other in the afternoon. The morning peak of the precipitation amount is small compared to that of the afternoon peak. Remarkably, WD has a prominent influence on the PDC. Days with southwesterly WD have a high afternoon peak and a lower morning peak, while days with northwesterly WD have a high morning peak and a lower afternoon peak. Furthermore, the seasonal variations of PDC are dominated by the seasonal frequency of WD classes. This study presents a general overview of the PDC in Germany with regard to its variation with seasonality, geographical location, elevation, and WD. [ABSTRACT FROM AUTHOR]