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

Abstract. The impact of a heavy precipitation event is determined not only by the total amount of precipitation, but also by its spatial and temporal distribution. This study introduces a framework to quantify key spatiotemporal properties of precipitation events – namely their characteristic time, length and speed – based on radar observations. The method employs a wavelet-based spectral filtering approach to isolate precipitation signals at distinct temporal and spatial scales. Focusing on Germany, we analyse 100 heavy precipitation events from the high-resolution RadKlim dataset. We assess the physical consistency of the derived characteristics and examine their links to large-scale atmospheric dynamics. Our results reveal systematic patterns in the spatiotemporal structure of heavy precipitation events. The proposed framework provides a robust basis for process-oriented analysis and offers potential for improved risk assessment and climate studies.

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Publication Details

Journal
Natural hazards and earth system sciences
Published
2026-08-17
DOI
https://doi.org/10.5194/nhess-26-3863-2026
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Svenja Szemkus, Petra Friederichs, Sebastian Buschow
Natural hazards and earth system sciences
Precipitation Measurement and Analysis
article

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

Svenja Szemkus, Petra Friederichs, Sebastian Buschow
article en

Abstract

Abstract. The impact of a heavy precipitation event is determined not only by the total amount of precipitation, but also by its spatial and temporal distribution. This study introduces a framework to quantify key spatiotemporal properties of precipitation events – namely their characteristic time, length and speed – based on radar observations. The method employs a wavelet-based spectral filtering approach to isolate precipitation signals at distinct temporal and spatial scales. Focusing on Germany, we analyse 100 heavy precipitation events from the high-resolution RadKlim dataset. We assess the physical consistency of the derived characteristics and examine their links to large-scale atmospheric dynamics. Our results reveal systematic patterns in the spatiotemporal structure of heavy precipitation events. The proposed framework provides a robust basis for process-oriented analysis and offers potential for improved risk assessment and climate studies.

Natural hazards and earth system sciencesVol. 26(8)
University of Bonn (DE)
Deutsches Klimarechenzentrum, Bundesministerium für Bildung und Forschung, Universität Stuttgart
Climate action
Openalex Percentile: Top 13%
Precipitation Measurement and Analysis
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