Preprints
https://doi.org/10.5194/hess-2023-288
https://doi.org/10.5194/hess-2023-288
16 Jan 2024
 | 16 Jan 2024
Status: a revised version of this preprint was accepted for the journal HESS.

Probabilistic downscaling of EURO-CORDEX precipitation data for the assessment of future areal precipitation extremes of different durations

Abbas El Hachem, Jochen Seidel, and András Bárdossy

Abstract. This work presents a methodology to inspect the changing statistical properties of precipitation extremes with climate change. Data from regional climate models for the European continent (EURO-CORDEX 11) were used. The use of climate model data requires first an inspection of the data and a correction of the biases of the meteorological model. Both the correction of biases of the point precipitation and those of the spatial structure were performed. For this purpose, a quantile-quantile transformation of the point precipitation and a spatial recorrelation method were used. Once bias-corrected, the data from the regional climate model were downscaled to a finer spatial scale using a stochastic method with equally probable outcomes. This enables the assessment of the corresponding uncertainties. The downscaled fields were used to derive area-depth-duration-frequency (ADDF) curves, and area-reduction-factors (ARF) for selected regions in Germany. The estimated curves were compared to those derived from a reference weather radar data set. While the corrected and downscaled data show good agreement with the observed reference data over all temporal and spatial scales, the future climate simulations indicate an increase in the estimated areal rainfall depth for future periods. Moreover, the future ARFs for short durations and large spatial scales increase compared to the reference value, while for longer durations the difference is smaller.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Abbas El Hachem, Jochen Seidel, and András Bárdossy

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2023-288', Anonymous Referee #1, 24 Jun 2024
    • AC1: 'Reply on RC1', Abbas El Hachem, 15 Jul 2024
  • RC2: 'Comment on hess-2023-288', Anonymous Referee #2, 25 Jun 2024
    • AC2: 'Reply on RC2', Abbas El Hachem, 15 Jul 2024
Abbas El Hachem, Jochen Seidel, and András Bárdossy
Abbas El Hachem, Jochen Seidel, and András Bárdossy

Viewed

Total article views: 883 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
680 168 35 883 31 32
  • HTML: 680
  • PDF: 168
  • XML: 35
  • Total: 883
  • BibTeX: 31
  • EndNote: 32
Views and downloads (calculated since 16 Jan 2024)
Cumulative views and downloads (calculated since 16 Jan 2024)

Viewed (geographical distribution)

Total article views: 889 (including HTML, PDF, and XML) Thereof 889 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 Dec 2024
Download
Short summary
The influence of climate change on areal precipitation extremes is examined. After an upscaling of reference observations, the climate model data are corrected and a downscaling to a finer spatial scale is done. For different temporal durations and spatial scales, areal precipitation extremes are derived. The final result indicates an increase in the expected rainfall depth compared to reference values. However, the increase varied with the duration and area size.