Preprints
https://doi.org/10.5194/hess-2021-640
https://doi.org/10.5194/hess-2021-640
 
27 Jan 2022
27 Jan 2022
Status: a revised version of this preprint was accepted for the journal HESS and is expected to appear here in due course.

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

Andreas Hänsler and Markus Weiler Andreas Hänsler and Markus Weiler
  • Chair of Hydrology, University of Freiburg, 79098 Freiburg, Germany

Abstract. Spatially explicit quantification on design storms are essential for flood risk assessment and planning. Since the limited temporal data availability from weather radar data, design storms are usually estimated on the basis of rainfall records of a few precipitation stations having a substantially long time coverage. To achieve a regional picture these station based estimates are spatially interpolated, incorporating a large source of uncertainty due to the typical low station density, in particular for short event durations.

In this study we present a method to estimate spatially explicit design storms with a return period of up to 100 years on the basis of statistically extended weather radar precipitation estimates based on the ideas of regional frequency analyses and subsequent bias correction. Associated uncertainties are quantified using an ensemble-sampling approach and event-based bootstrapping.

With the resulting dataset, we compile spatially explicit design storms for various return periods and event durations for the federal state of Baden Württemberg, Germany. We compare our findings with two reference datasets based on interpolated station estimates. We find that the transition in the spatial patterns of the design storms from a rather random short duration events, 15 minute) to a more structured, orographically influenced pattern (long duration events, 24 hours) seems to be much more realistic in the weather radar based product. However, the absolute magnitude of the design storms, although bias-corrected, is still generally lower in the weather radar product, which should be addressed in future studies in more detail.

Andreas Hänsler and Markus Weiler

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-640', Marc Schleiss, 24 Feb 2022
    • AC1: 'Reply on RC1', Andreas Hänsler, 24 Mar 2022
  • RC2: 'Comment on hess-2021-640', Anonymous Referee #2, 24 Feb 2022
    • AC2: 'Reply on RC2', Andreas Hänsler, 24 Mar 2022
  • RC3: 'Comment on hess-2021-640', Anonymous Referee #3, 25 Feb 2022
    • AC3: 'Reply on RC3', Andreas Hänsler, 24 Mar 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-640', Marc Schleiss, 24 Feb 2022
    • AC1: 'Reply on RC1', Andreas Hänsler, 24 Mar 2022
  • RC2: 'Comment on hess-2021-640', Anonymous Referee #2, 24 Feb 2022
    • AC2: 'Reply on RC2', Andreas Hänsler, 24 Mar 2022
  • RC3: 'Comment on hess-2021-640', Anonymous Referee #3, 25 Feb 2022
    • AC3: 'Reply on RC3', Andreas Hänsler, 24 Mar 2022

Andreas Hänsler and Markus Weiler

Andreas Hänsler and Markus Weiler

Viewed

Total article views: 669 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
528 118 23 669 8 8
  • HTML: 528
  • PDF: 118
  • XML: 23
  • Total: 669
  • BibTeX: 8
  • EndNote: 8
Views and downloads (calculated since 27 Jan 2022)
Cumulative views and downloads (calculated since 27 Jan 2022)

Viewed (geographical distribution)

Total article views: 581 (including HTML, PDF, and XML) Thereof 581 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 20 Sep 2022
Download
Short summary
Spatially explicit quantification on design storms are 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.