69 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. Adapting rainfall bias-corrections to improve hydrological simulations generated from climate model forcings D. Robertson et al. 10.1016/j.jhydrol.2023.129322
5. Observation-Based Simulations of Humidity and Temperature Using Quantile Regression A. Poppick & K. McKinnon 10.1175/JCLI-D-20-0403.1
6. 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
7. Future climate risk to UK agriculture from compound events F. Garry et al. 10.1016/j.crm.2021.100282
8. 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
9. 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
10. Novel multivariate quantile mapping methods for ensemble post-processing of medium-range forecasts K. Whan et al. 10.1016/j.wace.2021.100310
11. 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
12. 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
13. Climate change impact on flood hazard over Italy M. García-Valdecasas Ojeda et al. 10.1016/j.jhydrol.2022.128628
14. 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
15. MIdASv0.2.1 – MultI-scale bias AdjuStment P. Berg et al. 10.5194/gmd-15-6165-2022
16. 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
17. 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
18. 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
19. Deep Learning for Bias‐Correcting CMIP6‐Class Earth System Models P. Hess et al. 10.1029/2023EF004002
20. Hotspot movement of compound events on the Europe continent S. Doshi et al. 10.1038/s41598-023-45067-6
21. Exploring the Effect of Occurrence-Bias-Adjustment Assumptions on Hydrological Impact Modeling J. Van de Velde et al. 10.3390/w13111573
22. 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
23. Historical trends and future projections of annual rainfall from CMIP6 models in Ho Chi Minh City, Vietnam D. Phuong et al. 10.3354/cr01736
24. Compound droughts and hot extremes: Characteristics, drivers, changes, and impacts Z. Hao et al. 10.1016/j.earscirev.2022.104241
25. Advancing research on compound weather and climate events via large ensemble model simulations E. Bevacqua et al. 10.1038/s41467-023-37847-5
26. A Large Ensemble Global Dataset for Climate Impact Assessments X. Gao et al. 10.1038/s41597-023-02708-9
27. 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
28. 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
29. Revisiting the bias correction of climate models for impact studies T. Dinh & F. Aires 10.1007/s10584-023-03597-y
30. Learning to Correct Climate Projection Biases B. Pan et al. 10.1029/2021MS002509
31. Characterizing temperature and precipitation multi‐variate biases in 12 and 2.2 km UK Climate Projections F. Garry & D. Bernie 10.1002/joc.8006
32. Time of emergence of compound events: contribution of univariate and dependence properties B. François & M. Vrac 10.5194/nhess-23-21-2023
33. Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments A. Sharma et al. 10.2166/wcc.2023.230
34. Spatial, Temporal, and Multivariate Bias in Regional Climate Model Simulations Y. Kim et al. 10.1029/2020GL092058
35. 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
36. 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
37. Hydrological Modelling and Climate Adaptation under Changing Climate: A Review with a Focus in Sub-Saharan Africa V. Banda et al. 10.3390/w14244031
38. 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
39. The Importance of Weather and Climate to Energy Systems: A Workshop on Next Generation Challenges in Energy–Climate Modeling H. Bloomfield et al. 10.1175/BAMS-D-20-0256.1
40. Ensemble bias correction of climate simulations: preserving internal variability P. Vaittinada Ayar et al. 10.1038/s41598-021-82715-1
41. Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures X. Gao et al. 10.1007/s11356-021-16066-9
42. Downscaling CORDEX Through Deep Learning to Daily 1 km Multivariate Ensemble in Complex Terrain D. Quesada‐Chacón et al. 10.1029/2023EF003531
43. Seasonal forecasts of the Saharan heat low characteristics: a multi-model assessment C. Ngoungue Langue et al. 10.5194/wcd-2-893-2021
44. 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
45. 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
46. Combining global climate models using graph cuts S. Thao et al. 10.1007/s00382-022-06213-4
47. Is time a variable like the others in multivariate statistical downscaling and bias correction? Y. Robin & M. Vrac 10.5194/esd-12-1253-2021
48. Time Variability Correction of CMIP6 Climate Change Projections Y. Shao et al. 10.1029/2023MS003640
49. Seasonal circulation regimes in the North Atlantic: Towards a new seasonality F. Breton et al. 10.1002/joc.7565
50. 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
51. Bias adjustment to preserve changes in variability: the unbiased mapping of GCM changes C. Chadwick et al. 10.1080/02626667.2023.2201450
52. Compound Hydrometeorological Extremes: Drivers, Mechanisms and Methods W. Zhang et al. 10.3389/feart.2021.673495
53. R<sup>2</sup>D<sup>2</sup> v2.0: accounting for temporal dependences in multivariate bias correction via analogue rank resampling M. Vrac & S. Thao 10.5194/gmd-13-5367-2020
54. Changes in temperature–precipitation correlations over Europe: are climate models reliable? M. Vrac et al. 10.1007/s00382-022-06436-5
55. On deep learning-based bias correction and downscaling of multiple climate models simulations F. Wang & D. Tian 10.1007/s00382-022-06277-2
56. 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
57. 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
58. 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
59. 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
60. Multivariate bias correction of regional climate model boundary conditions Y. Kim et al. 10.1007/s00382-023-06718-6
61. Multivariate bias corrections of CMIP6 model simulations of compound dry and hot events across China Y. Meng et al. 10.1088/1748-9326/ac8e86
62. Evaluating the dependence structure of compound precipitation and wind speed extremes J. Zscheischler et al. 10.5194/esd-12-1-2021
63. Climate Projections for Precipitation and Temperature Indicators in the Douro Wine Region: The Importance of Bias Correction J. Martins et al. 10.3390/agronomy11050990
64. Stochastic downscaling of gridded precipitation to spatially coherent subgrid precipitation fields using a transformed Gaussian model M. Switanek et al. 10.1002/joc.7581
65. Future Projections of EURO‐CORDEX Raw and Bias‐Corrected Daily Maximum Wind Speeds Over Scandinavia C. Michel & A. Sorteberg 10.1029/2022JD037953
66. Cooperative adaptive management of the Nile River with climate and socio-economic uncertainties M. Basheer et al. 10.1038/s41558-022-01556-6
67. 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
68. 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
69. Adjusting spatial dependence of climate model outputs with cycle-consistent adversarial networks B. François et al. 10.1007/s00382-021-05869-8