Articles | Volume 30, issue 10
https://doi.org/10.5194/hess-30-2953-2026
https://doi.org/10.5194/hess-30-2953-2026
Research article
 | 
18 May 2026
Research article |  | 18 May 2026

Improving precipitation interpolation using anisotropic variograms derived from convection-permitting regional climate model simulations

Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot

Viewed

Total article views: 6,320 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
5,093 1,021 206 6,320 169 269
  • HTML: 5,093
  • PDF: 1,021
  • XML: 206
  • Total: 6,320
  • BibTeX: 169
  • EndNote: 269
Views and downloads (calculated since 10 Jun 2025)
Cumulative views and downloads (calculated since 10 Jun 2025)

Viewed (geographical distribution)

Total article views: 6,320 (including HTML, PDF, and XML) Thereof 6,320 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 19 May 2026
Download
Short summary
Traditional precipitation analyses often misrepresent intense rainfall's spatial variability. This study evaluates different spatial covariances to capture this variability in a geostatistical framework. The best covariance includes anisotropy derived from daily climate model simulations, offering a reliable alternative to anisotropy estimation using rain gauges. These findings highlight the importance of including anisotropy when generating precipitation inputs for hydrological modeling.
Share