14 citations as recorded by crossref.

1. Comparison of Interpolation, Statistical, and Data-Driven Methods for Imputation of Missing Values in a Distributed Soil Moisture Dataset K. Kornelsen & P. Coulibaly https://doi.org/10.1061/(ASCE)HE.1943-5584.0000767
2. Potential for equation discovery with AI in the climate sciences C. Huntingford et al. https://doi.org/10.5194/esd-16-475-2025
3. Is time a variable like the others in multivariate statistical downscaling and bias correction? Y. Robin & M. Vrac https://doi.org/10.5194/esd-12-1253-2021
4. Harmonized evaluation of daily precipitation downscaled using SDSM and WRF+WRFDA models over the Iberian Peninsula S. González-Rojí et al. https://doi.org/10.1007/s00382-019-04673-9
5. Genetic Programming for the Downscaling of Extreme Rainfall Events on the East Coast of Peninsular Malaysia S. Pour et al. https://doi.org/10.3390/atmos5040914
6. Extrapolating the Fractal Characteristics of an Image Using Scale-Invariant Multiple-Point Statistics G. Mariethoz et al. https://doi.org/10.1007/s11004-011-9362-5
7. Dynamically vs. empirically downscaled medium-range precipitation forecasts G. Bürger https://doi.org/10.5194/hess-13-1649-2009
8. Intercomparison of statistical and dynamical downscaling models under the EURO- and MED-CORDEX initiative framework: present climate evaluations P. Vaittinada Ayar et al. https://doi.org/10.1007/s00382-015-2647-5
9. Hydrological responses to climate change in Mt. Elgon watersheds J. Musau et al. https://doi.org/10.1016/j.ejrh.2014.12.001
10. Early flood warnings from empirical (expanded) downscaling of the full ECMWF Ensemble Prediction System G. Bürger et al. https://doi.org/10.1029/2009WR007779
11. Quantile-Based Downscaling of Precipitation Using Genetic Programming: Application to IDF Curves in Saskatoon E. Hassanzadeh et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000854
12. The Statistical DownScaling Model: insights from one decade of application R. Wilby & C. Dawson https://doi.org/10.1002/joc.3544
13. Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling V. Sehgal et al. https://doi.org/10.1016/j.jhydrol.2016.10.048
14. An Artificial Intelligence-Driven Precipitation Downscaling Method Using Spatiotemporally Coupled Multi-Source Data C. Li et al. https://doi.org/10.3390/atmos16111226