Preprints
https://doi.org/10.5194/hess-2018-184
https://doi.org/10.5194/hess-2018-184

  02 May 2018

02 May 2018

Review status: this preprint was under review for the journal HESS but the revision was not accepted.

Explorative Analysis of Long Time Series of Very High Resolution Spatial Rainfall

Emma Dybro Thomassen1, Hjalte Jomo Danielsen Sørup1, Marc Scheibel2, Thomas Einfalt3, and Karsten Arnbjerg-Nielsen1 Emma Dybro Thomassen et al.
  • 1Department of Environmental Engineering, Technical University of Denmark, Lyngby, 2800, Denmark
  • 2Wupperverband, Wuppertal, 42289, Germany
  • 3hydro & meteo GmbH&Co.KG, Lübeck, 23552, Germany

Abstract. Rainfall is often represented by a design storm with uniform intensity in urban hydrological models even though rainfall is a highly dynamic process across very small temporal and spatial scales. This study examines characteristics of high-resolution radar data (5-minute temporal resolution, 1x1 km spatial resolution) over an area of 1824 km2 covering the catchment of the river Wupper, North Rhine-Westphalia, Germany. Extreme events were sampled by a Peak Over Threshold method using several sampling strategies, all based on selecting an average of three events per year. A simple identification- and tracking algorithm for rain cells based on intensity threshold and fitting of ellipsoids, is developed for the study. Both hourly and daily extremes were analysed with respect to a set of 16 descriptive variables. The spatio-temporal properties of the extreme events are explored by means of principal component analysis, cluster analysis, and linear models for these 16 variables. The PCA indicated between 5 and 9 dimensions in the extreme event characteristic data. The cluster analyses identified four rainfall types: extreme convective, convective, convective events in front systems and front system events. The stepwise regression for each variable identified independent variables that correspond well with the correlation structure identified in the clusters. This indicates that the correlation structure may prove useful in setting up a weather generator.

Emma Dybro Thomassen et al.

 
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Emma Dybro Thomassen et al.

Emma Dybro Thomassen et al.

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Short summary
This article takes the first steps in describing rainfall with spatio-temporal variations. A detailed description of rainfall will provide an improved planning tool for protecting cities against pluvial flooding. The article uses high resolution radar data from the catchment of the river Wupper, North Rhine-Westphalia, Germany. The spatio-temporal properties of extreme rain events was described with 16 variables. Three statistical methods were applied and four rainfall types were identified.