100 citations as recorded by crossref.

1. Climate models underestimate the sensitivity of Arctic sea ice to carbon emissions F. Diebold & G. Rudebusch 10.1016/j.eneco.2023.107012
2. The distinct problems of physical inconsistency and of multivariate bias involved in the statistical adjustment of climate simulations M. Alavoine & P. Grenier 10.1002/joc.7878
3. Contrasting changes in hydrological processes of the Volta River basin under global warming M. Dembélé et al. 10.5194/hess-26-1481-2022
4. Fire weather index data under historical and shared socioeconomic pathway projections in the 6th phase of the Coupled Model Intercomparison Project from 1850 to 2100 Y. Quilcaille et al. 10.5194/essd-15-2153-2023
5. Future climate risk to UK agriculture from compound events F. Garry et al. 10.1016/j.crm.2021.100282
6. Assessing temperature and precipitation bias nonstationarity of CMIP6 global climate models over Iran N. Azad & A. Ahmadi 10.1007/s00704-024-05322-w
7. A Process-Conditioned and Spatially Consistent Method for Reducing Systematic Biases in Modeled Streamflow A. Bennett et al. 10.1175/JHM-D-21-0174.1
8. Regional sub-daily stochastic weather generator based on reanalyses for surface water stress estimation in central Tunisia N. Farhani et al. 10.1016/j.envsoft.2022.105448
9. Climate change impact on flood hazard over Italy M. García-Valdecasas Ojeda et al. 10.1016/j.jhydrol.2022.128628
10. MIdASv0.2.1 – MultI-scale bias AdjuStment P. Berg et al. 10.5194/gmd-15-6165-2022
11. Attributing the occurrence and intensity of extreme events with the flow analogue method R. Noyelle et al. 10.5194/wcd-6-817-2025
12. Global climate model bias correction using deep learning A. Pasula & D. Subramani 10.1088/3049-4753/ade9c3
13. Assessing the impact of artificial snowmaking on Dagu Glacier variation: a case study from a tourism glacier Y. Xie et al. 10.1038/s41598-025-89722-6
14. How does bias correction impact simulated drought characteristics by Regional Climate Models? P. Nguyen-Ngoc-Bich et al. 10.1007/s10584-025-03901-y
15. Present and future interannual variability in wildfire occurrence: a large ensemble application to the United States T. Keeping et al. 10.3389/ffgc.2025.1519836
16. Hotspot movement of compound events on the Europe continent S. Doshi et al. 10.1038/s41598-023-45067-6
17. Growth of spatial statistics for agriculture and environment: The example of BioSP at INRAE D. Allard 10.1016/j.spasta.2025.100938
18. ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1) F. Spuler et al. 10.5194/gmd-17-1249-2024
19. Bias-corrected high-resolution precipitation datasets assessment over a tropical mountainous region in Colombia: A case of study in Upper Cauca River Basin C. Romero-Hernández et al. 10.1016/j.jsames.2024.104898
20. Historical trends and future projections of annual rainfall from CMIP6 models in Ho Chi Minh City, Vietnam D. Phuong et al. 10.3354/cr01736
21. Compound droughts and hot extremes: Characteristics, drivers, changes, and impacts Z. Hao et al. 10.1016/j.earscirev.2022.104241
22. Multivariate Bias‐Correction of High‐Resolution Regional Climate Change Simulations for West Africa: Performance and Climate Change Implications D. Dieng et al. 10.1029/2021JD034836
23. Assessing the reliability of wind power operations under a changing climate with a non-Gaussian bias correction J. Zhang et al. 10.1214/21-AOAS1460
24. Learning to Correct Climate Projection Biases B. Pan et al. 10.1029/2021MS002509
25. A standardized index for assessing sub-monthly compound dry and hot conditions with application in China J. Li et al. 10.5194/hess-25-1587-2021
26. A non-stationary bias adjustment method for improving the inter-annual variability and persistence of projected precipitation M. Cantalejo et al. 10.1038/s41598-024-76848-2
27. Hydrological Modelling and Climate Adaptation under Changing Climate: A Review with a Focus in Sub-Saharan Africa V. Banda et al. 10.3390/w14244031
28. Towards an integrated system modeling of water scarcity with projected changes in climate and socioeconomic conditions S. Dehghani et al. 10.1016/j.spc.2022.07.023
29. Differentiated regional impacts of future meteorological changes and anthropogenic emission control on PM2.5 concentrations in China Y. Jiang et al. 10.1016/j.horiz.2025.100151
30. Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures X. Gao et al. 10.1007/s11356-021-16066-9
31. Projected increase in global compound agricultural drought and hot events under climate change W. Shi et al. 10.1016/j.gloplacha.2025.104962
32. High-resolution projections of outdoor thermal stress in the twenty-first century: a Tasmanian case study B. Weeding et al. 10.1007/s00484-024-02622-8
33. Is time a variable like the others in multivariate statistical downscaling and bias correction? Y. Robin & M. Vrac 10.5194/esd-12-1253-2021
34. Towards more realistic climate model outputs: a multivariate bias correction based on zero-inflated vine copulas H. Funk et al. 10.1093/jrsssc/qlaf044
35. Bias adjustment to preserve changes in variability: the unbiased mapping of GCM changes C. Chadwick et al. 10.1080/02626667.2023.2201450
36. Projected changes of rain, sleet, and snowfall in Norway E. Kuya et al. 10.1080/00291951.2024.2360409
37. Compound Hydrometeorological Extremes: Drivers, Mechanisms and Methods W. Zhang et al. 10.3389/feart.2021.673495
38. Extreme gradient and boosting algorithm for improved bias-correction and downscaling of CMIP6 GCM data across indian river basin C. Thakur et al. 10.1016/j.ejrh.2025.102443
39. R2D2 v2.0: accounting for temporal dependences in multivariate bias correction via analogue rank resampling M. Vrac & S. Thao 10.5194/gmd-13-5367-2020
40. Multivariate bias correction of ERA5 climatic data for assessing climate-related road vulnerabilities in Nigeria A. Abdussalam et al. 10.1007/s44288-025-00151-4
41. Changes in temperature–precipitation correlations over Europe: are climate models reliable? M. Vrac et al. 10.1007/s00382-022-06436-5
42. Impact of diverse configuration in multivariate bias correction methods on large-scale hydrological modelling under climate change K. Ahn et al. 10.1016/j.jhydrol.2023.130406
43. Toward the reliable use of reanalysis data as a reference for bias correction in climate models: A multivariate perspective V. de Padua & K. Ahn 10.1016/j.jhydrol.2024.132102
44. Global evaluation of the “dry gets drier, and wet gets wetter” paradigm from a terrestrial water storage change perspective J. Xiong et al. 10.5194/hess-26-6457-2022
45. Evaluation of a Multivariate Statistical Downscaling Method over Canada's Largest Pacific Basin S. Sobie et al. 10.1080/07055900.2025.2478829
46. Multivariate bias corrections of CMIP6 model simulations of compound dry and hot events across China Y. Meng et al. 10.1088/1748-9326/ac8e86
47. A Stochastic Multisite Bias Correction Method for Hydro-Meteorological Impact Studies H. Liu et al. 10.3390/w17121807
48. Evaluating the dependence structure of compound precipitation and wind speed extremes J. Zscheischler et al. 10.5194/esd-12-1-2021
49. A temporal stochastic bias correction using a machine learning attention model O. Nivron et al. 10.1017/eds.2024.42
50. Stochastic downscaling of gridded precipitation to spatially coherent subgrid precipitation fields using a transformed Gaussian model M. Switanek et al. 10.1002/joc.7581
51. Future Projections of EURO‐CORDEX Raw and Bias‐Corrected Daily Maximum Wind Speeds Over Scandinavia C. Michel & A. Sorteberg 10.1029/2022JD037953
52. Cooperative adaptive management of the Nile River with climate and socio-economic uncertainties M. Basheer et al. 10.1038/s41558-022-01556-6
53. Improving biome and climate modelling for a set of past climate conditions: evaluating bias correction using the CDF-t approach A. Zapolska et al. 10.1088/2752-5295/accbe2
54. Multivariate bias correction and downscaling of climate models with trend-preserving deep learning F. Wang & D. Tian 10.1007/s00382-024-07406-9
55. Elevation dependency of snowfall changes under climate change over the Tibetan Plateau: Evidence from CMIP6 GCMs Y. Gao et al. 10.1016/j.atmosres.2024.107832
56. Evaluating Seasonal Forecast Models for Cambodia’s Northern Tonle Sap Basin L. Brigadier et al. 10.1007/s13143-025-00393-9
57. Adapting rainfall bias-corrections to improve hydrological simulations generated from climate model forcings D. Robertson et al. 10.1016/j.jhydrol.2023.129322
58. Observation-Based Simulations of Humidity and Temperature Using Quantile Regression A. Poppick & K. McKinnon 10.1175/JCLI-D-20-0403.1
59. Novel multivariate quantile mapping methods for ensemble post-processing of medium-range forecasts K. Whan et al. 10.1016/j.wace.2021.100310
60. Towards a compound-event-oriented climate model evaluation: a decomposition of the underlying biases in multivariate fire and heat stress hazards R. Villalobos-Herrera et al. 10.5194/nhess-21-1867-2021
61. Evaluation of bias correction methods for a multivariate drought index: case study of the Upper Jhelum Basin R. Ansari et al. 10.5194/gmd-16-2055-2023
62. Selection of climate simulations for climate change impact studies: case study of the Souss watershed, Morocco M. Meliho et al. 10.1007/s00704-025-05353-x
63. Downscaling and uncertainty analysis of future concurrent long-duration dry and hot events in China Y. Yang & J. Tang 10.1007/s10584-023-03481-9
64. Correction of ERA5 temperature and relative humidity biases by bivariate quantile mapping for contrail formation analysis K. Wolf et al. 10.5194/acp-25-157-2025
65. Climate data selection for multi-decadal wind power forecasts S. Morelli et al. 10.1088/1748-9326/adc01f
66. Assessing internal changes in the future structure of dry–hot compound events: the case of the Pyrenees M. Lemus-Canovas & J. Lopez-Bustins 10.5194/nhess-21-1721-2021
67. Direct and indirect application of univariate and multivariate bias corrections on heat-stress indices based on multiple regional-climate-model simulations L. Qiu et al. 10.5194/esd-14-507-2023
68. Assessing multivariate bias corrections of climate simulations on various impact models under climate change D. Allard et al. 10.5194/hess-29-4711-2025
69. Extending the global high-resolution downscaled projections dataset to include CMIP6 projections at increased resolution coherent with the ERA5-Land reanalysis T. Noël et al. 10.1016/j.dib.2022.108669
70. Should We Use Quantile-Mapping-Based Methods in a Climate Change Context? A “Perfect Model” Experiment M. Vrac et al. 10.3390/cli13070137
71. How the choice of model calibration procedure affects projections of lake surface water temperatures for future climatic conditions J. Napiorkowski et al. 10.1016/j.jhydrol.2025.133236
72. Deep Learning for Bias‐Correcting CMIP6‐Class Earth System Models P. Hess et al. 10.1029/2023EF004002
73. Distribution-based pooling for combination and multi-model bias correction of climate simulations M. Vrac et al. 10.5194/esd-15-735-2024
74. Advancing research on compound weather and climate events via large ensemble model simulations E. Bevacqua et al. 10.1038/s41467-023-37847-5
75. A Large Ensemble Global Dataset for Climate Impact Assessments X. Gao et al. 10.1038/s41597-023-02708-9
76. Revisiting the bias correction of climate models for impact studies T. Dinh & F. Aires 10.1007/s10584-023-03597-y
77. Comparison of bias correction methods in the arid region of Pakistan Z. Ali et al. 10.1088/1755-1315/1467/1/012026
78. Characterizing temperature and precipitation multi‐variate biases in 12 and 2.2 km UK Climate Projections F. Garry & D. Bernie 10.1002/joc.8006
79. Time of emergence of compound events: contribution of univariate and dependence properties B. François & M. Vrac 10.5194/nhess-23-21-2023
80. Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments A. Sharma et al. 10.2166/wcc.2023.230
81. Spatial, Temporal, and Multivariate Bias in Regional Climate Model Simulations Y. Kim et al. 10.1029/2020GL092058
82. Approximating the Internal Variability of Bias-Corrected Global Temperature Projections with Spatial Stochastic Generators W. Hu & S. Castruccio 10.1175/JCLI-D-21-0083.1
83. Quantile-based bias-correction of extreme rainfall: Pros & cons of popular methods for climate signal preservation R. Padulano et al. 10.1016/j.jhydrol.2025.132814
84. Ensemble bias correction of climate simulations: preserving internal variability P. Vaittinada Ayar et al. 10.1038/s41598-021-82715-1
85. Downscaling CORDEX Through Deep Learning to Daily 1 km Multivariate Ensemble in Complex Terrain D. Quesada‐Chacón et al. 10.1029/2023EF003531
86. Seasonal forecasts of the Saharan heat low characteristics: a multi-model assessment C. Ngoungue Langue et al. 10.5194/wcd-2-893-2021
87. Statistical reconstruction of European winter snowfall in reanalysis and climate models based on air temperature and total precipitation F. Pons & D. Faranda 10.5194/ascmo-8-155-2022
88. Combining global climate models using graph cuts S. Thao et al. 10.1007/s00382-022-06213-4
89. Time Variability Correction of CMIP6 Climate Change Projections Y. Shao et al. 10.1029/2023MS003640
90. Seasonal circulation regimes in the North Atlantic: Towards a new seasonality F. Breton et al. 10.1002/joc.7565
91. Future change in amplitude and timing of high-flow events in a Canadian subarctic watershed O. Champagne et al. 10.1016/j.coldregions.2023.103807
92. Performance of weather research forecasting model for seasonal prediction of precipitation over Indonesian maritime continent I. Sofiati et al. 10.1016/j.kjs.2024.100293
93. On deep learning-based bias correction and downscaling of multiple climate models simulations F. Wang & D. Tian 10.1007/s00382-022-06277-2
94. Impact of bias nonstationarity on the performance of uni- and multivariate bias-adjusting methods: a case study on data from Uccle, Belgium J. Van de Velde et al. 10.5194/hess-26-2319-2022
95. Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle L. Teckentrup et al. 10.5194/esd-14-549-2023
96. Climate change impacts on the Chiffa basin (northern Algeria) using bias-corrected RCM data A. Madani et al. 10.3389/frwa.2024.1507961
97. Multivariate bias correction of regional climate model boundary conditions Y. Kim et al. 10.1007/s00382-023-06718-6
98. Climate Projections for Precipitation and Temperature Indicators in the Douro Wine Region: The Importance of Bias Correction J. Martins et al. 10.3390/agronomy11050990
99. Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts D. Gergel et al. 10.5194/gmd-17-191-2024
100. Adjusting spatial dependence of climate model outputs with cycle-consistent adversarial networks B. François et al. 10.1007/s00382-021-05869-8