26 citations as recorded by crossref.

1. Differential Impacts of 1.5 and 2 °C Warming on Extreme Events Over China Using Statistically Downscaled and Bias-Corrected CESM Low-Warming Experiment Y. Yang et al. 10.1029/2018GL079272
2. Subseasonal hydrometeorological ensemble predictions in small- and medium-sized mountainous catchments: benefits of the NWP approach S. Monhart et al. 10.5194/hess-23-493-2019
3. Exploration of Daily Rainfall Intensity Change in South Korea 1900–2010 Using Bias-Corrected ERA-20C D. Kim et al. 10.1061/(ASCE)HE.1943-5584.0001928
4. Comparison of statistical downscaling methods with respect to extreme events over Europe: Validation results from the perfect predictor experiment of the COST Action VALUE E. Hertig et al. 10.1002/joc.5469
5. Copula-based downscaling of daily precipitation fields M. Lorenz et al. 10.1002/hyp.13271
6. The Value of Subseasonal Hydrometeorological Forecasts to Hydropower Operations: How Much Does Preprocessing Matter? D. Anghileri et al. 10.1029/2019WR025280
7. Bias correction of daily precipitation over South Korea from the long-term reanalysis using a composite Gamma-Pareto distribution approach D. Kim et al. 10.2166/nh.2019.127
8. The VALUE perfect predictor experiment: Evaluation of temporal variability D. Maraun et al. 10.1002/joc.5222
9. Performance Evaluation of Bias Correction Methods for Climate Change Monthly Precipitation Projections over Costa Rica M. Mendez et al. 10.3390/w12020482
10. Classificação Climática de Thornthwaite para o Brasil com Base em Cenários de Mudanças Climáticas do IPCC-AR5 A. Marcos Junior et al. 10.1590/0102-7786334007
11. Projections of climate change in streamflow and affluent natural energy in the Brazilian hydroelectric sector of CORDEX models M. Silva et al. 10.1590/2318-0331.252020200020
12. Remaining error sources in bias-corrected climate model outputs J. Chen et al. 10.1007/s10584-020-02744-z
13. An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment J. Gutiérrez et al. 10.1002/joc.5462
14. Impact of bias correction and downscaling through quantile mapping on simulated climate change signal: a case study over Central Italy L. Sangelantoni et al. 10.1007/s00704-018-2406-8
15. Impact of Reference Dataset Selection on RCM Evaluation, Bias Correction, and Resulting Climate Change Signals of Precipitation D. Gampe et al. 10.1175/JHM-D-18-0108.1
16. Impacts of Using State‐of‐the‐Art Multivariate Bias Correction Methods on Hydrological Modeling Over North America Q. Guo et al. 10.1029/2019WR026659
17. Towards process-informed bias correction of climate change simulations D. Maraun et al. 10.1038/nclimate3418
18. Changes in Future Synoptic Circulation Patterns: Consequences for Extreme Event Attribution D. Faranda et al. 10.1029/2020GL088002
19. Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R<sup>2</sup>D<sup>2</sup>) bias correction M. Vrac 10.5194/hess-22-3175-2018
20. New Approach for Bias Correction and Stochastic Downscaling of Future Projections for Daily Mean Temperatures to a High-Resolution Grid Q. Yuan et al. 10.1175/JAMC-D-19-0086.1
21. On the Joint Calibration of Multivariate Seasonal Climate Forecasts from GCMs A. Schepen et al. 10.1175/MWR-D-19-0046.1
22. Time Scale Decomposition of Climate and Correction of Variability Using Synthetic Samples of Stable Distributions M. Gomez‐Garcia et al. 10.1029/2018WR023053
23. Regional modeling of daily precipitation fields across the Great Lakes region (Canada) using the CFSR reanalysis D. Khedhaouiria et al. 10.1007/s00477-019-01722-x
24. Nonstationary stochastic rain type generation: accounting for climate drivers L. Benoit et al. 10.5194/hess-24-2841-2020
25. A Censored Shifted Mixture Distribution Mapping Method to Correct the Bias of Daily IMERG Satellite Precipitation Estimates Q. Ma et al. 10.3390/rs11111345
26. The stationarity of two statistical downscaling methods for precipitation under different choices of cross-validation periods Y. Wang et al. 10.1002/joc.5375