144 citations as recorded by crossref.

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17. Assessment of the Impacts of Global Climate Change and Regional Water Projects on Streamflow Characteristics in the Geum River Basin in Korea S. Kim et al. https://doi.org/10.3390/w8030091
18. Comparison of Three Techniques to Adjust Daily Precipitation Biases from Regional Climate Models over Germany C. Ibebuchi et al. https://doi.org/10.3390/w14040600
19. Regression-based distribution mapping for bias correction of climate model outputs using linear quantile regression C. Passow & R. Donner https://doi.org/10.1007/s00477-019-01750-7
20. Bias Correction of Mixed Distributions of Temperature with Strong Diurnal Signal M. Haider et al. https://doi.org/10.1175/WAF-D-21-0108.1
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25. Quantifying the Impact of Future Climate Change on Runoff in the Amur River Basin Using a Distributed Hydrological Model and CMIP6 GCM Projections K. Wen et al. https://doi.org/10.3390/atmos12121560
26. Analysis of Precipitation Projections over the Climate Gradient of the Arkansas Red River Basin L. Qiao et al. https://doi.org/10.1175/JAMC-D-16-0201.1
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29. Bias correction of global and regional simulated daily precipitation and surface mean temperature over Southeast Asia using quantile mapping method S. Ngai et al. https://doi.org/10.1016/j.gloplacha.2016.12.009
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36. Effects of univariate and multivariate statistical downscaling methods on climatic and hydrologic indicators for Alberta, Canada H. Eum et al. https://doi.org/10.1016/j.jhydrol.2020.125065
37. Assessing the Effect of Bias Correction Methods on the Development of Intensity–Duration–Frequency Curves Based on Projections from the CORDEX Central America GCM-RCM Multimodel-Ensemble M. Mendez et al. https://doi.org/10.3390/w16233473
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39. SnowQM 1.0: a fast R package for bias-correcting spatial fields of snow water equivalent using quantile mapping A. Michel et al. https://doi.org/10.5194/gmd-17-8969-2024
40. Uncertainty assessment for climate change impact on intense precipitation: how many model runs do we need? P. Hosseinzadehtalaei et al. https://doi.org/10.1002/joc.5069
41. Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach F. Hanzer et al. https://doi.org/10.5194/hess-22-1593-2018
42. Bias nonstationarity of global climate model outputs: The role of internal climate variability and climate model sensitivity Y. Hui et al. https://doi.org/10.1002/joc.5950
43. Evaluating skills and issues of quantile-based bias adjustment for climate change scenarios F. Lehner et al. https://doi.org/10.5194/ascmo-9-29-2023
44. Nonparametric quantile mapping using the response surface method – bias correction of daily precipitation T. Bong et al. https://doi.org/10.2166/wcc.2017.127
45. When will meteorological droughts become the new normal climatic condition in Central-Southern Chile? F. González-Leiva et al. https://doi.org/10.1080/02626667.2026.2625979
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48. Designing ecological climate change impact assessments to reflect key climatic drivers H. Sofaer et al. https://doi.org/10.1111/gcb.13653
49. Evaluation of some distributional downscaling methods as applied to daily maximum temperature with emphasis on extremes J. Lanzante et al. https://doi.org/10.1002/joc.6288
50. Comparison of CMIP3 and CMIP5 projected hydrologic conditions over the Upper Colorado River Basin J. Ayers et al. https://doi.org/10.1002/joc.4594
51. Improved Bias Correction Techniques for Hydrological Simulations of Climate Change* D. Pierce et al. https://doi.org/10.1175/JHM-D-14-0236.1
52. Quantile-based bias-correction of extreme rainfall: Pros & cons of popular methods for climate signal preservation R. Padulano et al. https://doi.org/10.1016/j.jhydrol.2025.132814
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54. Statistical downscaling differences strongly alter projected climate damages S. Miller et al. https://doi.org/10.1038/s43247-025-02134-2
55. Impact of climate change on landslides frequency: the Esino river basin case study (Central Italy) L. Sangelantoni et al. https://doi.org/10.1007/s11069-018-3328-6
56. Intercomparison of projected changes in climate extremes for South Korea: application of trend preserving statistical downscaling methods to the CMIP5 ensemble H. Eum & A. Cannon https://doi.org/10.1002/joc.4924
57. Exacerbated fires in Mediterranean Europe due to anthropogenic warming projected with non-stationary climate-fire models M. Turco et al. https://doi.org/10.1038/s41467-018-06358-z
58. Responses of Unimpaired Flows, Storage, and Managed Flows to Scenarios of Climate Change in the San Francisco Bay‐Delta Watershed N. Knowles et al. https://doi.org/10.1029/2018WR022852
59. Case Study: Development of the CNN Model Considering Teleconnection for Spatial Downscaling of Precipitation in a Climate Change Scenario J. Kim et al. https://doi.org/10.3390/su14084719
60. The implications of bias correction methods and climate model ensembles on soil erosion projections under climate change J. Eekhout & J. de Vente https://doi.org/10.1002/esp.4563
61. The Impact of Future Climate Change and Human Activities on Hydro-climatological Drought, Analysis and Projections: Using CMIP5 Climate Model Simulations S. Javadinejad et al. https://doi.org/10.1007/s41101-019-00069-2
62. Evaluation and future projection of marine heatwaves in CMIP6 models in the Indian Ocean J. Sandaruwan et al. https://doi.org/10.1088/2515-7620/ae21a0
63. Trends in projections of standardized precipitation indices in a future climate in Poland M. Osuch et al. https://doi.org/10.5194/hess-20-1947-2016
64. Bayesian Bias Correction of Satellite Rainfall Estimates for Climate Studies M. Kimani et al. https://doi.org/10.3390/rs10071074
65. Quantifying future rainfall extremes in Türkiye: a CMIP6 ensemble approach with statistical downscaling T. Tugrul et al. https://doi.org/10.1007/s11600-025-01551-3
66. Global Bias-Corrected CORDEX Datasets at Half Degree Resolution F. Yakubu et al. https://doi.org/10.1038/s41597-025-06200-4
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68. Evaluation of Quantile Delta Mapping as a bias‐correction method in maximum rainfall dataset from downscaled models in São Paulo state (Brazil) A. Xavier et al. https://doi.org/10.1002/joc.7238
69. Bias adjustment and downscaling of snow cover fraction projections from regional climate models using remote sensing for the European Alps M. Matiu & F. Hanzer https://doi.org/10.5194/hess-26-3037-2022
70. Assessing the impact of bias correction approaches on climate extremes and the climate change signal H. Zhang et al. https://doi.org/10.1002/met.2204
71. The effect of empirical-statistical correction of intensity-dependent model errors on the temperature climate change signal A. Gobiet et al. https://doi.org/10.5194/hess-19-4055-2015
72. Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes A. Lutz et al. https://doi.org/10.1371/journal.pone.0165630
73. Extreme precipitation events under climate change in the Iberian Peninsula S. Cardoso Pereira et al. https://doi.org/10.1002/joc.6269
74. Piecewise‐quantile mapping improves bias correction of global climate model daily precipitation towards preserving quantiles and extremes Q. Zhang et al. https://doi.org/10.1002/joc.7687
75. Assessing future changes in hydroclimatic processes in the Metropolitan Region of Belo Horizonte, Brazil, with the expanded Bluecat framework L. Santos et al. https://doi.org/10.3389/frwa.2025.1541052
76. A Framework to Identify the Uncertainty and Credibility of GCMs for Projected Future Precipitation: A Case Study in the Yellow River Basin, China T. Guan et al. https://doi.org/10.3389/fenvs.2022.863575
77. Potential Changes in Runoff of California’s Major Water Supply Watersheds in the 21st Century M. He et al. https://doi.org/10.3390/w11081651
78. Impacts of drought, food security policy and climate change on performance of irrigation schemes in Sub-saharan Africa: The case of Sudan S. Ahmed https://doi.org/10.1016/j.agwat.2020.106064
79. Future Projections of Heat Mortality Risk for Major European Cities A. Karwat & C. Franzke https://doi.org/10.1175/WCAS-D-20-0142.1
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81. Climate Change-Driven Hydrological Shifts in the Kon-Ha Thanh River Basin C. Vu et al. https://doi.org/10.3390/w16233389
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84. Effects of Climate Change on Precipitation and the Maximum Daily Temperature (Tmax) at Two US Military Bases with Different Present-Day Climates J. Tadić & S. Biraud https://doi.org/10.3390/cli8020018
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116. Understanding Differences in California Climate Projections Produced by Dynamical and Statistical Downscaling D. Walton et al. https://doi.org/10.1029/2020JD032812
117. Climate Change Effects on Rainfall Intensity–Duration–Frequency (IDF) Curves for the Lake Erie Coast Using Various Climate Models S. Mainali & S. Sharma https://doi.org/10.3390/w15234063
118. Bias Correction for Climate Model Output (1) Method Characteristics and Classification S. WATANABE https://doi.org/10.3178/jjshwr.33.243
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120. Modeling crop yields amidst climate change in the Nile basin (2040–2079) S. Ahmed https://doi.org/10.1007/s40808-021-01199-0
121. Climate Model Biases and Modification of the Climate Change Signal by Intensity-Dependent Bias Correction M. Ivanov et al. https://doi.org/10.1175/JCLI-D-17-0765.1
122. Quantifying the Uncertainty Sources of Future Climate Projections and Narrowing Uncertainties With Bias Correction Techniques Y. Wu et al. https://doi.org/10.1029/2022EF002963
123. Impacts of business-as-usual management on ecosystem services in European mountain ranges under climate change H. Bugmann et al. https://doi.org/10.1007/s10113-016-1074-4
124. Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes M. Switanek et al. https://doi.org/10.5194/hess-21-2649-2017
125. The Effect of Climate Change on Forest Fire Danger and Severity in the Canadian Boreal Forests for the Period 1976–2100 Y. Wang https://doi.org/10.1029/2023JD039118
126. On the Use of Original and Bias-Corrected Climate Simulations in Regional-Scale Hydrological Scenarios in the Mediterranean Basin L. Sangelantoni et al. https://doi.org/10.3390/atmos10120799
127. Global Warming Impacts on Severe Drought Characteristics in Asia Monsoon Region J. Kim et al. https://doi.org/10.3390/w12051360
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131. Extreme Climate Event Changes in China in the 1.5 and 2 °C Warmer Climates: Results From Statistical and Dynamical Downscaling D. Li et al. https://doi.org/10.1029/2018JD028835
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136. Future Summer Marine Heatwaves in the Western South Atlantic N. Costa & R. Rodrigues https://doi.org/10.1029/2021GL094509
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140. Projections of suitable cultivation area for major fruit trees and climate‐type in South Korea under representative concentration pathway scenarios using the ensemble of high‐resolution regional climate models E. Kim et al. https://doi.org/10.1002/joc.8102
141. Managing uncertainty in flood protection planning with climate projections B. Dittes et al. https://doi.org/10.5194/hess-22-2511-2018
142. The method ADAMONT v1.0 for statistical adjustment of climate projections applicable to energy balance land surface models D. Verfaillie et al. https://doi.org/10.5194/gmd-10-4257-2017
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