43 citations as recorded by crossref.

1. A new bias-correction method for precipitation over complex terrain suitable for different climate states: a case study using WRF (version 3.8.1) P. Velasquez et al.
2. Learning to Correct Climate Projection Biases B. Pan et al.
3. Projected changes in rainfall amount and distribution in the Democratic Republic of Congo – Evidence from an ensemble of high-resolution climate simulations F. Bangelesa et al.
4. Soil moisture downscaling in the state of Oklahoma: Employing advanced machine learning S. Koujani et al.
5. Research on Meteorological Drought Risk Prediction in the Daqing River Basin Based on HADGEM3-RA M. Lv & Z. Wang
6. Correcting biases in tropical cyclone intensities in low-resolution datasets using dynamical systems metrics D. Faranda et al.
7. MIdASv0.2.1 – MultI-scale bias AdjuStment P. Berg et al.
8. The impact of using different probability representations in application of equidistant quantile matching for bias adjustment of daily precipitation over the Daqing River Basin, North China M. Lv et al.
9. Projected mean and extreme precipitation based on bias-corrected simulation outputs of CORDEX Southeast Asia S. Ngai et al.
10. Toward the reliable use of reanalysis data as a reference for bias correction in climate models: A multivariate perspective V. de Padua & K. Ahn
11. Uni- and multivariate bias adjustment methods in Nordic catchments: Complexity and performance in a changing climate F. Tootoonchi et al.
12. Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment) S. Marahatta et al.
13. Review of bias correction methods for climate model outputs in hydrology A. Menapace et al.
14. Assessing Extreme Precipitation in Northwest China’s Inland River Basin Under a Novel Low Radiative Forcing Scenario M. Yang et al.
15. Forecast and uncertainty analysis of extreme precipitation in China from ensemble of multiple climate models P. Deng & J. Zhu
16. Climate Change Projections of Extreme Temperatures for the Iberian Peninsula C. Viceto et al.
17. Improving marine sediment carbon stock estimates: the role of dry bulk density and predictor adjustments M. Chatting et al.
18. Extending Limited In Situ Mountain Weather Observations to the Baseline Climate: A True Verification Case Study M. Hofer & J. Horak
19. Predictability of water resources with global climate models. Case of Northern Tunisia M. Besbes & J. Chahed
20. Uni- and multivariate bias adjustment of climate model simulations in Nordic catchments: Effects on hydrological signatures relevant for water resources management in a changing climate F. Tootoonchi et al.
21. Projected precipitation changes over China for global warming levels at 1.5 °C and 2 °C in an ensemble of regional climate simulations: impact of bias correction methods L. Guo et al.
22. 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.
23. Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments A. Sharma et al.
24. Towards a More Robust Evaluation of Climate Model and Hydrological Impact Uncertainties E. Pastén-Zapata et al.
25. Multivariate stochastic bias corrections with optimal transport Y. Robin et al.
26. Sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study R. Bonnet et al.
27. Projection of future precipitation extremes across the Bangkok Metropolitan Region R. Cooper
28. 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.
29. Exploring the Effect of Occurrence-Bias-Adjustment Assumptions on Hydrological Impact Modeling J. Van de Velde et al.
30. Normalized coefficients of prediction accuracy for comparative forecast verification and modeling G. Müller-Plath & H. Lüdecke
31. Standard assessments of climate forecast skill can be misleading J. Risbey et al.
32. 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.
33. The effect of univariate bias adjustment on multivariate hazard estimates J. Zscheischler et al.
34. Bias correction of precipitation from convection-permitting models at the point scale: a case study in Switzerland T. Nguyen et al.
35. Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought H. Tabari et al.
36. 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.
37. Assessing internal changes in the future structure of dry–hot compound events: the case of the Pyrenees M. Lemus-Canovas & J. Lopez-Bustins
38. Impact of downscaled rainfall biases on projected runoff changes S. Charles et al.
39. Effects of univariate and multivariate bias correction on hydrological impact projections in alpine catchments J. Meyer et al.
40. Improved bioclimatic variables from regional climate models: a comparative analysis of three classic bias adjustment methods and a novel adjustment approach F. Bangelesa et al.
41. How does bias correction impact simulated drought characteristics by Regional Climate Models? P. Nguyen-Ngoc-Bich et al.
42. Statistical downscaling or bias adjustment? A case study involving implausible climate change projections of precipitation in Malawi R. Manzanas et al.
43. Assessment of plausible changes in Climatic Impact-Drivers relevant for the viticulture sector: A storyline approach with a climate service perspective J. Mindlin et al.