98 citations as recorded by crossref.

1. Disaster risk assessment in villages near PT ANTAM UBPB West Kalimantan’s bauxite mining area A. Abdillah et al. https://doi.org/10.1088/1755-1315/1314/1/012022
2. Flood hazard assessment using design rainfall under climate change scenarios in the Kelantan River Basin, Malaysia T. Tam et al. https://doi.org/10.1108/IJDRBE-05-2022-0048
3. Erosion extremes under changing climate: Integrating extreme rainfall erosivity in a tropical mining landscape W. Kuntoro et al. https://doi.org/10.1016/j.envc.2026.101574
4. Investigation of climate change effects on Iraq dust activity using LSTM M. Hamidi & A. Roshani https://doi.org/10.1016/j.apr.2023.101874
5. Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6 D. Lafferty & R. Sriver https://doi.org/10.1038/s41612-023-00486-0
6. Downscaling of Precipitation for Climate Change Projections Using Multiple Machine Learning Techniques: Case Study of Shenzhen City, China J. Han et al. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001612
7. Future changes in mean and extreme precipitation over the Mediterranean and Sahara regions using bias‐corrected CMIP6 models H. Babaousmail et al. https://doi.org/10.1002/joc.7644
8. Enhancing Satellite Precipitation Product Accuracy for Hydrological and Environmental Analysis in Semi-Arid Urban Regions A. Heir et al. https://doi.org/10.3103/S106837392560014X
9. Estimations of potential evapotranspiration from CMIP6 multi-model ensemble over Africa I. Yahaya et al. https://doi.org/10.1016/j.atmosres.2024.107255
10. Evaluation of Rainfall Distribution Based on the Precipitation Concentration Index: A Case Study over the Selected Summer Rainfall Regions of South Africa C. Botai et al. https://doi.org/10.3390/hydrology12060136
11. Improving Daily CMIP6 Precipitation in Southern Africa Through Bias Correction— Part 2: Representation of Extreme Precipitation A. Addisuu et al. https://doi.org/10.3390/cli13050093
12. Downscaling sea surface height and currents in coastal regions using convolutional neural network B. Yuan et al. https://doi.org/10.1016/j.apor.2024.104153
13. Future changes of drought characteristics in Coupled Model Intercomparison Project phase 6 Shared Socioeconomic Pathway scenarios over Central Asia H. Guo et al. https://doi.org/10.1002/joc.7450
14. Projections of indices of daily temperature and precipitation based on bias-adjusted CORDEX-Africa regional climate model simulations A. Dosio et al. https://doi.org/10.1007/s10584-022-03307-0
15. Development of statistical downscaling methods for the assessment of rainfall characteristics under climate change scenarios T. Onarun et al. https://doi.org/10.2166/wcc.2023.490
16. Assessing the performance of blue-green solutions through a fine-scale water balance model for an urban area X. Wu et al. https://doi.org/10.1016/j.scitotenv.2024.174750
17. From past to future: Spatiotemporal insights into drought stress on Belgian pome fruit production for 1991–2090 B. Bamps et al. https://doi.org/10.1016/j.agwat.2026.110151
18. Evaluating the future of climate modeling: A critical review of CMIP6 applications and their role in climate risk and impact assessments R. Guria et al. https://doi.org/10.1016/j.pce.2026.104591
19. Spatiotemporal analysis of transition probabilities of wet and dry days under SSPs scenarios in the semi-arid Susurluk Basin, Türkiye M. Şan et al. https://doi.org/10.1016/j.scitotenv.2023.168641
20. Hydrological responses projection to the potential impact of climate change under CMIP6 models scenarios in Omo River Basin, Ethiopia T. Feyissa et al. https://doi.org/10.1016/j.rineng.2024.102708
21. Climate change impacts on hydrometeorological and river hydrological extremes in Quito, Ecuador S. Núñez Mejía et al. https://doi.org/10.1016/j.ejrh.2023.101522
22. Integrating multi-scale precipitation variability into ensemble modeling using maximum overlap discrete wavelet transform for improved drought projections under emission scenarios H. Abbas et al. https://doi.org/10.1007/s00704-026-06036-x
23. Total nitrogen and phosphorus loads in surface runoff from urban land use (city of Lublin) under climate change E. Szalińska et al. https://doi.org/10.1007/s11356-024-34365-9
24. Projections of precipitation change from CMIP6 based on a new downscaling method in the Poyang Lake basin, China N. Zhao et al. https://doi.org/10.1016/j.ejrh.2022.101138
25. Trend analysis of historical and future precipitation projections over a diverse topographic region of Khyber Pakhtunkhwa using SDSM G. Rahman et al. https://doi.org/10.2166/wcc.2022.160
26. 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
27. Bias-corrected UKCP18 Convection-permitting model projections for England Q. Zha et al. https://doi.org/10.5194/hess-30-2395-2026
28. A stacked generalization-based multi-model ensemble framework for precipitation downscaling and drought characterization in a semi-arid region A. Mirdarsoltany et al. https://doi.org/10.1007/s11069-026-08147-0
29. Projection of Extreme Temperature Events over the Mediterranean and Sahara Using Bias-Corrected CMIP6 Models H. Babaousmail et al. https://doi.org/10.3390/atmos13050741
30. The skill of statistical downscaling in future climate with high-resolution climate models as pseudo-reality S. Mendoza Paz & P. Willems https://doi.org/10.1016/j.ejrh.2023.101477
31. Dam System and Reservoir Operational Safety: A Meta-Research A. Badr et al. https://doi.org/10.3390/w15193427
32. High-resolution snow water equivalent estimation: a data-driven method for localized downscaling of climate data F. Zakeri et al. https://doi.org/10.5194/hess-29-6935-2025
33. Evaluating changes in flood frequency due to climate change in the Western Cape, South Africa K. Pillay & M. Simatele https://doi.org/10.1007/s00477-024-02786-0
34. ECHIDNA: Extreme Climate Historical and Future Indices Data under Numerous Approaches across Major Chinese River Basins Based on CMIP6 Multi-Model Ensemble L. Xinlong et al. https://doi.org/10.1038/s41597-026-07510-x
35. Gazing into the flames: A guide to assessing the impacts of climate change on landscape fire H. Clarke et al. https://doi.org/10.1126/sciadv.adz2429
36. Measure-correlate-predict methods to improve the assessment of wind and wave energy availability at a semi-exposed coastal area G. Ayuso-Virgili et al. https://doi.org/10.1016/j.energy.2024.132904
37. Regional impacts of solar radiation modification on surface temperature and precipitation in Mainland Southeast Asia and the adjacent oceans P. Narenpitak et al. https://doi.org/10.1038/s41598-024-73149-6
38. Downscaling precipitation and temperature in the Andes: applied methods and performance—a systematic review protocol S. Núñez Mejía et al. https://doi.org/10.1186/s13750-023-00323-0
39. A multi-scenario ensemble approach incorporating stepwise cluster analysis to reduce uncertainty in large-scale watershed precipitation projections: a case study of Pearl River Basin, South China Z. Qi et al. https://doi.org/10.1007/s11356-024-35013-y
40. Uncertainties in water balance and low flow assessment along the network of navigable rivers and canals in Flanders L. Breugelmans & P. Willems https://doi.org/10.1016/j.ejrh.2026.103789
41. Projected changes in meteorological drought over East Africa inferred from bias-adjusted CMIP6 models B. Ayugi et al. https://doi.org/10.1007/s11069-022-05341-8
42. Machine learning-based spatial downscaling and bias-correction framework for high-resolution temperature forecasting X. Meng et al. https://doi.org/10.1007/s10489-024-05504-z
43. Comparison of precipitation projections of CMIP5 and CMIP6 global climate models over Yulin, China M. Shiru et al. https://doi.org/10.1007/s00704-021-03823-6
44. Assessing climate change impacts on flood risk in the Yeongsan River Basin, South Korea A. Ashu & J. Kang https://doi.org/10.1038/s41598-025-11921-y
45. Wet-environment Evapotranspiration and Precipitation Standardized Index (WEPSI) for drought assessment and monitoring A. Khoshnazar et al. https://doi.org/10.2166/nh.2022.062
46. Multi-Model Ensemble Enhances the Spatiotemporal Comprehensive Performance of Regional Climate in China Y. Wang et al. https://doi.org/10.3390/rs17040582
47. Assessment of climate change impacts on crop and irrigation water demand in the Awash River basin of Ethiopia using CMIP6 models E. Meskelu et al. https://doi.org/10.1007/s43832-025-00307-w
48. Evaluation and prediction of future droughts with multi-model ensembling of four models under CMIP6 scenarios over Iraq Y. Abduljaleel et al. https://doi.org/10.1007/s00704-023-04595-x
49. Catchment‐scale skill assessment of seasonal precipitation forecasts across South Korea Y. Lee et al. https://doi.org/10.1002/joc.8134
50. Comparative analysis of bias correction methods for projecting extreme precipitation and temeprature indices in Pakistan Z. Ali et al. https://doi.org/10.1016/j.atmosres.2025.107957
51. Accuracy Assessment of Atmospheric Large Eddy Simulations to Support Uncrewed Aircraft Systems Operations at GrandSKY, North Dakota C. Wooton et al. https://doi.org/10.3390/atmos17050468
52. Projection of precipitation extremes in China's mainland based on the statistical downscaled data from 27 GCMs in CMIP6 L. Wang et al. https://doi.org/10.1016/j.atmosres.2022.106462
53. A systematic review of climate downscaling and extremes in Coupled Model Intercomparison Project 6 (CMIP6) E. Devadarshini et al. https://doi.org/10.1016/j.envdev.2025.101280
54. Advances in Resilience Assessment and Adaptive Strategies for Watershed Non-Point Source Pollution Systems Under Climate Change B. Liu et al. https://doi.org/10.3390/su18136917
55. Risk assessment of agricultural green water security in Northeast China under climate change J. Sun et al. https://doi.org/10.1007/s11430-023-1278-2
56. Evaluation and comparison of the performances of the CMIP5 and CMIP6 models in reproducing extreme rainfall in the Upper Blue Nile basin of Ethiopia H. Belay et al. https://doi.org/10.1007/s00704-024-05187-z
57. Moving statistic method (MSM) for quantification of changes in precipitation intensity and dry periods caused by climate change and demonstration on major U.S. cities B. Barkdoll https://doi.org/10.1007/s40899-023-00880-9
58. Assessing blue-green infrastructures for urban flood and drought mitigation under changing climate scenarios X. Wu & P. Willems https://doi.org/10.1016/j.ejrh.2025.102798
59. Climate Change and Florida Groundwater Management—Actionable Data and Adaptations R. Maliva https://doi.org/10.3390/w17111572
60. Improving Daily CMIP6 Precipitation in Southern Africa Through Bias Correction—Part 1: Spatiotemporal Characteristics A. Addisuu et al. https://doi.org/10.3390/cli13050095
61. Observed and Future Precipitation and Evapotranspiration in Water Management Zones of Uganda: CMIP6 Projections C. Onyutha et al. https://doi.org/10.3390/atmos12070887
62. Changes in Precipitation Patterns in Poland Derived From Projected Downscaled Future Climate Data From CMIP5 and CMIP6 A. Rutkowska et al. https://doi.org/10.1002/joc.8822
63. Correcting dry/wet classification bias in precipitation downscaling via generative adversarial networks S. Singh et al. https://doi.org/10.1017/eds.2026.10039
64. CMIP6 multi-model projections and glacier-explicit hydrological modelling for seasonal runoff shifts in the Hunza River Basin H. Batool et al. https://doi.org/10.1007/s00703-026-01149-4
65. Lack of clear standards and usable comparisons of downscaled climate projections pose a roadblock for US climate discovery and adaptation S. Hartke et al. https://doi.org/10.1088/1748-9326/adc74e
66. Real-time integrated water availability – Salt intrusion modelling and management during droughts D. Bertels et al. https://doi.org/10.1016/j.jhydrol.2024.131894
67. Impact of climate change on blue and green water availability using bias corrected CMIP6 ensemble and SWAT models at Keleta catchment, Awash basin, Ethiopia E. Meskelu et al. https://doi.org/10.2166/wcc.2026.017
68. Using a two-step downscaling method to assess the impact of climate change on total nitrogen load in a small basin X. Li et al. https://doi.org/10.1016/j.jhydrol.2023.130510
69. Quantifying the impact of climate change and extreme heat on rice in the United States S. Li et al. https://doi.org/10.1016/j.agrformet.2024.110145
70. An assessment of the Statistical Bias Correction Techniques for CSIRO-Mk 3–6-0 model Rainfall and Temperature in Punjab, India A. Krishna et al. https://doi.org/10.1007/s00704-025-05613-w
71. Evaluating the enhanced benefits of multi-model ensemble mean from NEX-GDDP-CMIP6 versus native CMIP6 Models in accurately representing historical temperature patterns in South America H. Arregocés et al. https://doi.org/10.1016/j.envc.2025.101373
72. Methods for assessing climate uncertainty in energy system models — A systematic literature review L. Plaga & V. Bertsch https://doi.org/10.1016/j.apenergy.2022.120384
73. Future Drought Dynamics in Semi-Arid Central Türkiye Using CMIP6 Scenario-Based Simulations A. Çağlar et al. https://doi.org/10.1007/s41742-026-01208-z
74. Statistical downscaling of climate variables for local forecasts and applications to improve climate change prediction in upper Blue Nile Basin A. Bulti & G. Yutura https://doi.org/10.1016/j.pce.2025.103867
75. Deep-learning-based sub-seasonal precipitation and streamflow ensemble forecasting over the source region of the Yangtze River N. Dong et al. https://doi.org/10.5194/hess-29-2023-2025
76. Downscaling algorithms for CMIP6 GCM daily rainfall over India R. Raj et al. https://doi.org/10.1007/s12040-024-02323-1
77. Uncovering the strengths and weaknesses of an ensemble of quantile mapping methods for downscaling precipitation change in Southern Africa S. Mendoza Paz & P. Willems https://doi.org/10.1016/j.ejrh.2022.101104
78. Resilient agriculture: water management for climate change adaptation in Lower Saxony R. Cotera et al. https://doi.org/10.2166/wcc.2024.455
79. Projected climatic drought events in drought-prone cities: Insights from high-resolution downscaled CMIP6 data X. Li et al. https://doi.org/10.1016/j.cliser.2024.100488
80. A Comparison of the Statistical Downscaling and Long-Short-Term-Memory Artificial Neural Network Models for Long-Term Temperature and Precipitations Forecasting N. Fouotsa Manfouo et al. https://doi.org/10.3390/atmos14040708
81. Potential impact of precipitation temporal structure on meteorological drought and vegetation condition: A case study on Qinghai-Tibet Plateau H. Lu et al. https://doi.org/10.1016/j.ejrh.2024.102048
82. Statistical downscaling of precipitation using inclusive multiple modelling (IMM) at two levels S. Sadeghfam et al. https://doi.org/10.2166/wcc.2021.106
83. A hybrid machine learning-based past performance and envelope approach for rainfall projection in Sarawak, Malaysia Z. Sa'adi et al. https://doi.org/10.1016/j.uclim.2025.102442
84. A novel statistical downscaling approach for analyzing daily precipitation and extremes under the impact of climate change: Application to an arid region Q. Zhang et al. https://doi.org/10.1016/j.jhydrol.2022.128730
85. Understanding Future Climate in the Upper Awash Basin (UASB) with Selected Climate Model Outputs under CMIP6 Y. Balcha et al. https://doi.org/10.3390/cli10120185
86. Assessing downscaling techniques for frequency analysis, total precipitation and rainy day estimation in CMIP6 simulations over hydrological years D. Jimenez et al. https://doi.org/10.5194/hess-28-1981-2024
87. Once upon a future heatwave: A practical storyline chain from existing climate data to stakeholder engagement N. Carlier et al. https://doi.org/10.1016/j.cliser.2026.100681
88. Projections of precipitation extremes based on bias‐corrected Coupled Model Intercomparison Project phase 6 models ensemble over southern Africa K. Lim Kam Sian et al. https://doi.org/10.1002/joc.7707
89. Ecophysiological Response of Vitis vinifera L. in an Urban Agrosystem: Preliminary Assessment of Genetic Variability E. Brunori et al. https://doi.org/10.3390/plants11223026
90. Water resource vulnerabilities from climate-induced tipping point behaviour in runoff volumes and seasonality in the region of the ‘Karakoram Anomaly’: A snow-glacier melt perspective J. Ougahi & J. Rowan https://doi.org/10.1016/j.ejrh.2025.102386
91. Mitigating Flowering‐Stage Heat Stress for Sustainable Wheat Production: Climate Modelling and Advanced Crop Improvement Tools R. Sarwar et al. https://doi.org/10.1111/jac.70206
92. Unpacking dasymetric modelling to correct spatial bias in environmental model outputs M. Kallio et al. https://doi.org/10.1016/j.envsoft.2022.105511
93. A comprehensive review of recent progress on the drought-flood abrupt alternation G. Zhang et al. https://doi.org/10.1016/j.jhydrol.2025.133806
94. Enhancing ERA5 precipitation with improved predictor selection for regional climate change assessment M. Keskin et al. https://doi.org/10.1007/s11069-025-07664-8
95. Simulation of Extreme Flood Events Based on Precipitation Fusion: A Multi-Method Fusion Framework Combining RF and BMA L. Chao et al. https://doi.org/10.3390/rs18050715
96. A multi-catchment evaluation of hydrological model transferability and ensemble averaging under contrasting hydroclimatic conditions in Iran A. Jahanshahi & M. Booij https://doi.org/10.1016/j.jhydrol.2026.135878
97. Impact of climate change on rainfall erosivity in the Amazon and Cerrado biomes under CMIP6 scenarios L. de Mendonça et al. https://doi.org/10.1007/s43217-025-00237-6
98. Drought characteristics in the Middle East simulated by raw and bias-corrected CMIP6 models B. Ghazi et al. https://doi.org/10.1016/j.scitotenv.2025.180468