11 Dec 2012
Statistical bias correction of global climate projections – consequences for large scale modeling of flood flows
S. Eisner
University of Kassel, Center for Environmental Systems Research (CESR), Wilhelmshöher Allee 47, 34109 Kassel, Germany
F. Voss
University of Kassel, Center for Environmental Systems Research (CESR), Wilhelmshöher Allee 47, 34109 Kassel, Germany
E. Kynast
University of Kassel, Center for Environmental Systems Research (CESR), Wilhelmshöher Allee 47, 34109 Kassel, Germany
Viewed
Total article views: 5,755 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,594 | 2,925 | 236 | 5,755 | 300 | 335 |
- HTML: 2,594
- PDF: 2,925
- XML: 236
- Total: 5,755
- BibTeX: 300
- EndNote: 335
Cited
31 citations as recorded by crossref.
- Modeling the effects of climatic and land use changes on phytoplankton and water quality of the largest Turkish freshwater lake: Lake Beyşehir T. Bucak et al. https://doi.org/10.1016/j.scitotenv.2017.11.258
- Future Climate and Land Use Change Impacts on River Flows in the Tapajós Basin in the Brazilian Amazon F. Farinosi et al. https://doi.org/10.1029/2019EF001198
- Vulnerability of groundwater quantity for an arid coastal aquifer under the climate change and extensive exploitation K. Soliman & D. Amin https://doi.org/10.1007/s13201-025-02404-6
- Impact of climate change on the vulnerability of drinking water intakes in a northern region B. Leveque et al. https://doi.org/10.1016/j.scs.2020.102656
- Global Projections of Storm Surges Using High‐Resolution CMIP6 Climate Models S. Muis et al. https://doi.org/10.1029/2023EF003479
- On projected hydrological scenarios under the influence of bias-corrected climatic variables and LULC S. Sahoo et al. https://doi.org/10.1016/j.ecolind.2019.105440
- Fidelity of reanalysis datasets in floodplain mapping: Investigating performance at inundation level over large regions M. Mohanty & S. Simonovic https://doi.org/10.1016/j.jhydrol.2020.125757
- Future water availability in the largest freshwater Mediterranean lake is at great risk as evidenced from simulations with the SWAT model T. Bucak et al. https://doi.org/10.1016/j.scitotenv.2016.12.149
- 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
- Twenty-first century projections of extreme precipitations in the Plata Basin V. Barros et al. https://doi.org/10.1080/15715124.2013.819358
- Catchment response to climate change under CMIP6 scenarios: a case study of the Krishna River Basin S. Anil et al. https://doi.org/10.2166/wcc.2024.442
- Remaining error sources in bias-corrected climate model outputs J. Chen et al. https://doi.org/10.1007/s10584-020-02744-z
- Consortium of Management Practices in Long-Run Improves Soil Fertility and Carbon Sequestration in Drylands of Semi-Arid Tropics G. Chander et al. https://doi.org/10.1007/s42106-023-00249-0
- Analysis of hydrological extremes at different hydro-climatic regimes under present and future conditions I. Pechlivanidis et al. https://doi.org/10.1007/s10584-016-1723-0
- Evaluation of a New Statistical Method—TIN-Copula–for the Bias Correction of Climate Models’ Extreme Parameters G. Lazoglou et al. https://doi.org/10.3390/atmos11030243
- Simulation of future climate under changing temporal covariance structures W. Leeds et al. https://doi.org/10.5194/ascmo-1-1-2015
- Towards Reducing Climate Change Impact Assessment Process Uncertainty A. Gaur & S. Simonovic https://doi.org/10.1007/s40710-015-0070-x
- Review of bias correction methods for climate model outputs in hydrology A. Menapace et al. https://doi.org/10.1016/j.jhydrol.2025.133213
- Bias correction of surface air temperature and precipitation in CORDEX East Asia simulation: What should we do when applying bias correction? J. Chen et al. https://doi.org/10.1016/j.atmosres.2022.106439
- An exhaustive investigation of changes in projected extreme precipitation indices and streamflow using CMIP6 climate models: A case study S. Anil & P. Raj https://doi.org/10.1007/s12040-024-02267-6
- Climate change impact on river flow extremes in the Upper Blue Nile River basin H. Meresa & M. Gatachew https://doi.org/10.2166/wcc.2018.154
- Bias correction of CMIP6 GCMs for historical and future air temperatures across China S. Wei et al. https://doi.org/10.1016/j.atmosres.2025.108193
- Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6 V. Mishra et al. https://doi.org/10.1038/s41597-020-00681-1
- Impacts of Climate Change on the Precipitation and Streamflow Regimes in Equatorial Regions: Guayas River Basin M. Ilbay-Yupa et al. https://doi.org/10.3390/w13213138
- Global Climate Model Selection for Analysis of Uncertainty in Climate Change Impact Assessments of Hydro-Climatic Extremes P. Breach et al. https://doi.org/10.4236/ajcc.2016.54036
- TIN‐Copula bias‐correction method for model‐derived maximum temperature in the MENA region G. Lazoglou et al. https://doi.org/10.1002/joc.7364
- Projection of Future Extreme Precipitation and Flood Changes of the Jinsha River Basin in China Based on CMIP5 Climate Models Z. Yuan et al. https://doi.org/10.3390/ijerph15112491
- Modeling Hydrological and Environmental Consequences of Climate Change and Urbanization in the Boise River Watershed, Idaho J. Kim & J. Ryu https://doi.org/10.1111/1752-1688.12712
- Using Natural Variability as a Baseline to Evaluate the Performance of Bias Correction Methods in Hydrological Climate Change Impact Studies J. Chen et al. https://doi.org/10.1175/JHM-D-15-0099.1
- 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
- Hydrological reanalysis across the 20th century: A case study of the Amazon Basin S. Wongchuig et al. https://doi.org/10.1016/j.jhydrol.2019.01.025
Latest update: 29 Oct 2026
