Revealing the structure of heavy precipitation events:  a spatio-temporal wavelet approach

Szemkus, Svenja; Buschow, Sebastian; Friederichs, Petra

doi:10.5194/nhess-26-3863-2026

Articles | Volume 26, issue 8

https://doi.org/10.5194/nhess-26-3863-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-26-3863-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 8

Research article

|

17 Aug 2026

Research article |

| 17 Aug 2026

Revealing the structure of heavy precipitation events: a spatio-temporal wavelet approach

Svenja Szemkus, Sebastian Buschow, and Petra Friederichs

Data sets

RADKLIM Version 2017.002: Reprocessed gauge-adjusted radar data, one-hour precipitation sums (RW) Tanja Winterrath et al. https://doi.org/10.5676/DWD/RADKLIM_RW_V2017.002

ERA5 hourly data on single levels from 1940 to present Hans Hersbach et al. https://doi.org/10.24381/cds.adbb2d47

Model code and software

dtcwt: a Python DualTree Complex Wavelet Transform Library (Version 0.12.0) Rich Wareham et al. https://doi.org/10.5281/zenodo.889246

Short summary

The impact of heavy rainfall is determined not only by the total amount of precipitation, but also by its spatial and temporal characteristics. We develop a statistical framework that extracts key event characteristics, including their time, length and speed from radar-based observations. The results reveal systematic patterns in heavy precipitation events and provide new insights for risk assessment and future climate studies.