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

Hänsler, Andreas; Weiler, Markus

doi:https://doi.org/10.5194/hess-26-5069-2022

Articles | Volume 26, issue 19

https://doi.org/10.5194/hess-26-5069-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-26-5069-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 19

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

Supplement

https://doi.org/10.5194/hess-26-5069-2022-supplement

Data sets

Index of /climate_environment/CDC/grids_germany/5_minutes/radolan/reproc/2017_002/bin/ DWD https://opendata.dwd.de/climate_environment/CDC/grids_germany/5_minutes/radolan/reproc/ 2017_002/bin/

Index of /climate_environment/CDC/grids_germany/return_periods/precipitation/KOSTRA/KOSTRA_DWD_2010R/ DWD https://opendata.dwd.de/climate_environment/CDC/grids_germany/return_periods/precipitation/ KOSTRA/KOSTRA_DWD_2010R/

Index of /climate_environment/CDC/grids_germany/daily/regnie/ DWD http://opendata.dwd.de/climate_environment/CDC/grids_germany/daily/regnie/

Short summary

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.