Articles | Volume 26, issue 19
https://doi.org/10.5194/hess-26-5069-2022
https://doi.org/10.5194/hess-26-5069-2022
Research article
 | 
11 Oct 2022
Research article |  | 11 Oct 2022

Enhancing the usability of weather radar data for the statistical analysis of extreme precipitation events

Andreas Hänsler and Markus Weiler

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Enhancing the usability of weather radar data for the statistical analysis of extreme precipitation events
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Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-366,https://doi.org/10.5194/hess-2021-366, 2021
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Subject: Engineering Hydrology | Techniques and Approaches: Mathematical applications
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Cited articles

Burn, D. H.: Evaluation of regional flood frequency analysis with a region of influence approach, Water Resour. Res., 26, 2257–2265, 1990. 
Cannon, A. J., Sobie, S. R., and Murdock, T. Q.: Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?, J. Climate, 28, 6938–6959, 2015. 
Charras-Garrido, M. and Lezaud, P.: Extreme value analysis: an introduction, Journal de la Société Française de Statistique, 154, 66–97, 2013. 
Cheng, L., AghaKouchak, A., Gilleland, E., and Katz, R. W.: Non-stationary extreme value analysis in a changing climate, Climatic Change, 127, 353–369, 2014. 
de Zea Bermudez, P. and Kotz, S.: Parameter estimation of the generalized Pareto distribution – Part I, J. Stat. Plan. Infer., 140, 1353–1373, 2010. 
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Spatially explicit quantification of design storms is essential for flood risk assessment and planning. However, available datasets are mainly based on spatially interpolated station-based design storms. Since the spatial interpolation of the data inherits a large potential for uncertainty, we develop an approach to be able to derive spatially explicit design storms on the basis of weather radar data. We find that our approach leads to an improved spatial representation of design storms.