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

Related authors

ISARD (v1.0) : A Reproducible Geostatistical Framework for Daily Precipitation Ensemble in Mountainous Terrain
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
EGUsphere, https://doi.org/10.5194/egusphere-2025-5679,https://doi.org/10.5194/egusphere-2025-5679, 2025
Short summary
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024,https://doi.org/10.5194/hess-28-2579-2024, 2024
Short summary

Cited articles

Adhikary, S. K., Muttil, N., and Yilmaz, A. G.: Cokriging for enhanced spatial interpolation of rainfall in two Australian catchments, Hydrol. Process., 31, 2143–2161, https://doi.org/10.1002/hyp.11163, 2017. a
Alexandersson, H.: A homogeneity test applied to precipitation data, J. Climatol., 6, 661–675, 1986. a
Alpuim, T. and Barbosa, S.: The Kalman filter in the estimation of area precipitation, Environmetrics, 10, 377–394, https://doi.org/10.1002/(SICI)1099-095X(199907/08)10:4<377::AID-ENV363>3.0.CO;2-L, 1999. a
Ban, N., Caillaud, C., Coppola, E., Pichelli, E., Sobolowski, S., Adinolfi, M., Ahrens, B., Alias, A., Anders, I., Bastin, S., Belušić, D., Berthou, S., Brisson, E., Cardoso, R. M., Chan, S. C., Christensen, O. B., Fernández, J., Fita, L., Frisius, T., Gašparac, G., Giorgi, F., Goergen, K., Haugen, J. E., Hodnebrog, O., Kartsios, S., Katragkou, E., Kendon, E. J., Keuler, K., Lavin-Gullon, A., Lenderink, G., Leutwyler, D., Lorenz, T., Maraun, D., Mercogliano, P., Milovac, J., Panitz, H.-J., Raffa, M., Remedio, A. R., Schär, C., Soares, P. M. M., Srnec, L., Steensen, B. M., Stocchi, P., Tölle, M. H., Truhetz, H., Vergara-Temprado, J., de Vries, H., Warrach-Sagi, K., Wulfmeyer, V., and Zander, M. J.: The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation, Clim. Dynam., 57, 275–302, https://doi.org/10.1007/s00382-021-05708-w, 2021. a
Bárdossy, A. and Pegram, G.: Interpolation of precipitation under topographic influence at different time scales, Water Resour. Res., 49, 4545–4565, https://doi.org/10.1002/wrcr.20307, 2013. a
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