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

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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.
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