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https://doi.org/10.5194/nhess-2020-192
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-192
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  20 Jul 2020

20 Jul 2020

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This preprint is currently under review for the journal NHESS.

An analysis on temporal scaling behavior of extreme rainfall of Germany based on radar precipitation QPE data

Judith Marie Pöschmann1, Dongkyun Kim2, Rico Kronenberg1, and Christian Bernhofer1 Judith Marie Pöschmann et al.
  • 1Department of Hydrosciences, Institute of Hydrology and Meteorology, Technische Universität Dresden, 01069 Dresden, Germany
  • 2Department of Civil and Environmental Engineering, Hongik University, Wausanro 94, Mapo-gu, Seoul, 04066, Korea

Abstract. We investigate the depth–duration relationship of maximum rainfall over the whole of Germany based on 16 yrs of radar derived Quantitative Precipitation Estimates (namely, RADKLIM–YW, German Meteorological Service) with a space–time resolution of 1 km and 5 min. Contrary to the long–term historic records that identified a smooth power law scaling behavior between the maximum rainfall depth and duration, our analysis revealed three distinct scaling regimes of which boundaries are approximately 1.5 h and 1 d. Few extraordinary events dominate a wide range of durations and deviate to the usual power law. Furthermore, the shape of the depth–duration relationship varies with the sample size of randomly selected radar pixels. A smooth scaling behavior were identified when the sample size is 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 behavior, 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.

Judith Marie Pöschmann et al.

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Judith Marie Pöschmann et al.

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Latest update: 23 Oct 2020
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Short summary
We examined maximum rainfall values for different durations from 16 years of radar-based rainfall records for whole Germany. Unlike existing observations based on rain gauge data no clear linear relationship could be identified. However, by classifying all time series, we could identify three similar groups determined by the temporal structure of rainfall extremes observed in the study period. The study highlights the importance of using long data records and a dense measurement network.
We examined maximum rainfall values for different durations from 16 years of radar-based...
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