25 citations as recorded by crossref.

1. Statistical Postprocessing of High-Resolution Regional Climate Model Output P. Mendoza et al. 10.1175/MWR-D-14-00159.1
2. Towards Reducing Climate Change Impact Assessment Process Uncertainty A. Gaur & S. Simonovic 10.1007/s40710-015-0070-x
3. Bias correction of global and regional simulated daily precipitation and surface mean temperature over Southeast Asia using quantile mapping method S. Ngai et al. 10.1016/j.gloplacha.2016.12.009
4. Assessment of an analogue downscaling method for modelling climate change impacts on runoff J. Teng et al. 10.1016/j.jhydrol.2012.09.024
5. Constraining Climate Model Projections of Regional Precipitation Change B. Zhang & B. Soden 10.1029/2019GL083926
6. Correcting for model changes in statistical postprocessing – an approach based on response theory J. Demaeyer & S. Vannitsem 10.5194/npg-27-307-2020
7. Evaluating the Time-Invariance Hypothesis of Climate Model Bias Correction: Implications for Hydrological Impact Studies J. Velázquez et al. 10.1175/JHM-D-14-0159.1
8. Improving the Reliability and Added Value of Dynamical Downscaling via Correction of Large‐Scale Errors: A Norwegian Perspective M. Pontoppidan et al. 10.1029/2018JD028372
9. Assessment of calibration assumptions under strong climate changes B. Van Schaeybroeck & S. Vannitsem 10.1002/2016GL067721
10. Projected Changes to Extreme Runoff and Precipitation Events From a Downscaled Simulation Over the Western United States M. Wrzesien & T. Pavelsky 10.3389/feart.2019.00355
11. Downscaling fire weather extremes from historical and projected climate models P. Jain et al. 10.1007/s10584-020-02865-5
12. HESS Opinions "Should we apply bias correction to global and regional climate model data?" U. Ehret et al. 10.5194/hess-16-3391-2012
13. Climate Change in the Mediterranean Basin (Part II): A Review of Challenges and Uncertainties in Climate Change Modeling and Impact Analyses L. Noto et al. 10.1007/s11269-023-03444-w
14. Multivariate bias corrections of mechanistic water quality model predictions D. Libera & A. Sankarasubramanian 10.1016/j.jhydrol.2018.07.043
15. A multi-perspective approach for selecting CMIP6 scenarios to project climate change impacts on glacio-hydrology with a case study in Upper Indus river basin M. Shafeeque & Y. Luo 10.1016/j.jhydrol.2021.126466
16. Towards process-informed bias correction of climate change simulations D. Maraun et al. 10.1038/nclimate3418
17. Bias Correcting Climate Change Simulations - a Critical Review D. Maraun 10.1007/s40641-016-0050-x
18. Hydrological impacts of climate change on small ungauged catchments – results from a global climate model–regional climate model–hydrologic model chain A. Tsegaw et al. 10.5194/nhess-20-2133-2020
19. What is the importance of climate model bias when projecting the impacts of climate change on land surface processes? M. Liu et al. 10.5194/bg-11-2601-2014
20. How to assess climate change impact models: uncertainty analysis of streamflow statistics via approximate Bayesian computation (ABC) J. Romero-Cuellar & F. Francés 10.1080/02626667.2023.2231437
21. Evolution of urban heat wave intensity for the Brussels Capital Region in the ARPEGE-Climat A1B scenario R. Hamdi et al. 10.1016/j.uclim.2016.08.001
22. The Upper Tail of Precipitation in Convection‐Permitting Regional Climate Models and Their Utility in Nonstationary Rainfall and Flood Frequency Analysis G. Yu et al. 10.1029/2020EF001613
23. Low-frequency variability and heat transport in a low-order nonlinear coupled ocean–atmosphere model S. Vannitsem et al. 10.1016/j.physd.2015.07.006
24. Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB) A. Khan & M. Koch 10.3390/cli6040089
25. Comparative analysis of bias correction techniques for future climate assessment using CMIP6 hydrological variables for the Indian subcontinent M. Shah et al. 10.1007/s11600-024-01378-4