Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 30, issue 10
Articles | Volume 30, issue 10
https://doi.org/10.5194/hess-30-2953-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-2953-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 30, issue 10
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: 7,313 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
5,718 1,291 304 7,313 63 256 365
  • HTML: 5,718
  • PDF: 1,291
  • XML: 304
  • Total: 7,313
  • Supplement: 63
  • BibTeX: 256
  • EndNote: 365
Views and downloads (calculated since 10 Jun 2025)
Cumulative views and downloads (calculated since 10 Jun 2025)

Viewed (geographical distribution)

Total article views: 7,313 (including HTML, PDF, and XML) Thereof 7,265 with geography defined and 48 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Saved (final revised paper)

Latest update: 01 Nov 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.
Read more
Share
Altmetrics
Final-revised paper
Preprint