This study investigates the direct influence of urban areas on storm events (heavy rainfall above 17 mm/hr). An 11‐year climatology of summertime precipitation was performed to capture and describe storm events for Berlin, Germany. An hourly radar composite product from the German Weather Service with a 1‐km grid resolution was used for the analysis. Berlin was chosen due to the relatively modest influences of topography and distinct urban‐rural landscape heterogeneity potentially affecting storms. The analysis identified 96 storm events for the period from 2006 to 2016. Individual storm characteristics were evaluated before the city (upwind), over the city, and behind the city (downwind). Both visual and statistical estimations quantified storm modifications caused by the urban area. Around 60% of the events showed typical patterns of storm alteration by the city. In conformance to earlier studies, we found evidence of urban rainfall intensification about 20 to 50 km downwind of the urban center. Most storms were suppressed, deflected, or split by the city, whereas intensification over the city typically occurred at night or when storms formed over the city. In the present study, results indicate an urban influence on storms in and around Berlin. But, unlike other studies, downwind intensification of storm rainfall was not a typical feature. This study on urban rainfall modification marks one of the first observations‐based climatological assessments for the European region.
We investigated the depth–duration relationship of maximum rainfall over all of Germany based on 16 years of radar-derived quantitative precipitation estimates (namely, RADKLIM-YW, German Meteorological Service) with a space–time resolution of 1 km2 and 5 min. Contrary to the long-term historic records that identified a smooth power law scaling behaviour between the maximum rainfall depth and duration, our analysis revealed three distinct scaling regimes of which boundaries are approximately 1 h and 1 d. A few extraordinary events dominated a wide range of durations and deviate to the usual power law. Furthermore, the shape of the depth–duration relationship varied with the sample size of randomly selected radar pixels. A smooth scaling behaviour was identified when the sample size was small (e.g. 10 to 100), but the original three distinct scaling regimes became more apparent as the sample size increases (e.g. 1000 to 10 000). Lastly, a pixel-wise classification of the depth–duration relationship of the maximum rainfall at all individual pixels in Germany revealed three distinguishable types of scaling behaviour, clearly determined by the temporal structure of the extreme rainfall events at a pixel. Thus, the relationship might change with longer time series and can be improved once available.
Convective rainfall can cause dangerous flash floods within less than six hours. Thus, simple approaches are required for issuing quick warnings. The flash flood guidance (FFG) approach pre-calculates rainfall levels (thresholds) potentially causing critical water levels for a specific catchment. Afterwards, only rainfall and soil moisture information are required to issue warnings. This study applied the principle of FFG to the Wernersbach Catchment (Germany) with excellent data coverage using the BROOK90 water budget model. The rainfall thresholds were determined for durations of 1 to 24 h, by running BROOK90 in “inverse” mode, identifying rainfall values for each duration that led to exceedance of critical discharge (fixed value). After calibrating the model based on its runoff, we ran it in hourly mode with four precipitation types and various levels of initial soil moisture for the period 1996–2010. The rainfall threshold curves showed a very high probability of detection (POD) of 91% for the 40 extracted flash flood events in the study period, however, the false alarm rate (FAR) of 56% and the critical success index (CSI) of 42% should be improved in further studies. The proposed adjusted FFG approach has the potential to provide reliable support in flash flood forecasting.
8 March 2019 in Asia-Pacific Journal of Atmospheric Sciences
Evaporation plays an important role in the water balance on a different spatial scale. However, its direct and indirect measurements are globally scarce and accurate estimations are a challenging task. Thus the correct process approximation in modelling of the terrestrial evaporation plays a crucial part. A physically based 1D lumped soil–plant–atmosphere model (BROOK90) is applied to study the role of parameter selection and meteorological input for modelled evaporation on the point scale. Then, with the integration of the model into global, regional and local frameworks, we made cross-combinations out of their parameterization and forcing schemes to show and analyse their roles in the estimations of the evaporation. Five sites with different land uses (grassland, cropland, deciduous broadleaf forest, two evergreen needleleaf forests) located in Saxony, Germany, were selected for the study. All tested combinations showed a good agreement with FLUXNET measurements (Kling–Gupta efficiency, KGE, values 0.35–0.80 for a daily scale). For most of the sites, the best results were found for the calibrated model with in situ meteorological input data, while the worst was observed for the global setup. The setups' performance in the vegetation period was much higher than for the winter period. Among the tested setups, the model parameterization showed higher spread in performance than meteorological forcings for fields and evergreen forests sites, while the opposite was noticed in deciduous forests. Analysis of the of evaporation components revealed that transpiration dominates (up to 65 %–75 %) in the vegetation period, while interception (in forests) and soil/snow evaporation (in fields) prevail in the winter months. Finally, it was found that different parameter sets impact model performance and redistribution of evaporation components throughout the whole year, while the influence of meteorological forcing was evident only in summer months.