Articles | Volume 24, issue 6
https://doi.org/10.5194/hess-24-2963-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-2963-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jun 2020
Research article |
| 08 Jun 2020
| 08 Jun 2020
Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections
CSIRO Land and Water, Canberra ACT 2601, Australia
Francis H. S. Chiew
CSIRO Land and Water, Canberra ACT 2601, Australia
Stephen P. Charles
CSIRO Land and Water, Floreat WA 6148, Australia
Guobin Fu
CSIRO Land and Water, Floreat WA 6148, Australia
Hongxing Zheng
CSIRO Land and Water, Canberra ACT 2601, Australia
Lu Zhang
CSIRO Land and Water, Canberra ACT 2601, Australia
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Cited
23 citations as recorded by crossref.
- Introducing Narclim1.5: Evaluation and Projection of Climate Extremes for Southeast Australia F. Ji et al. 10.2139/ssrn.4174746
- Adapting Water Management to Climate Change in the Murray–Darling Basin, Australia I. Prosser et al. 10.3390/w13182504
- Effects of Climate Change on Hydrological Indicators of Subsurface Drainage for a Representative French Drainage Site A. Jeantet et al. 10.3389/fenvs.2022.899226
- Evaluating skills and issues of quantile-based bias adjustment for climate change scenarios F. Lehner et al. 10.5194/ascmo-9-29-2023
- Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling Y. Zheng et al. 10.1007/s00376-023-3118-2
- Managing impacts of extreme hydrological events on urban water services: the Australian experience J. Horne 10.1080/07900627.2020.1808447
- Introducing NARCliM1.5: Evaluation and projection of climate extremes for southeast Australia F. Ji et al. 10.1016/j.wace.2022.100526
- How May the Choice of Downscaling Techniques and Meteorological Reference Observations Affect Future Hydroclimate Projections? D. Rastogi et al. 10.1029/2022EF002734
- Hydrological Modelling and Climate Adaptation under Changing Climate: A Review with a Focus in Sub-Saharan Africa V. Banda et al. 10.3390/w14244031
- Review of bias correction methods for climate model outputs in hydrology A. Menapace et al. 10.1016/j.jhydrol.2025.133213
- Different Hydroclimate Modelling Approaches Can Lead to a Large Range of Streamflow Projections under Climate Change: Implications for Water Resources Management F. Chiew et al. 10.3390/w14172730
- Projections of future streamflow for Australia informed by CMIP6 and previous generations of global climate models H. Zheng et al. 10.1016/j.jhydrol.2024.131286
- Trends and variability of rainfall characteristics influencing annual streamflow: A case study of southeast Australia G. Fu et al. 10.1002/joc.7923
- Introducing NARCliM1.5: Evaluating the Performance of Regional Climate Projections for Southeast Australia for 1950–2100 N. Nishant et al. 10.1029/2020EF001833
- Continental-scale bias-corrected climate and hydrological projections for Australia J. Peter et al. 10.5194/gmd-17-2755-2024
- 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
- Impact of downscaled rainfall biases on projected runoff changes S. Charles et al. 10.5194/hess-24-2981-2020
- Uncertainty propagation in a modelling chain of climate change impact for a representative French drainage site A. Jeantet et al. 10.1080/02626667.2023.2203322
- Evaluating the uncertainty of climate model structure and bias correction on the hydrological impact of projected climate change in a Mediterranean catchment A. Senatore et al. 10.1016/j.ejrh.2022.101120
- A Climate-Mathematical Clustering of Rainfall Stations in the Río Bravo-San Juan Basin (Mexico) by Using the Higuchi Fractal Dimension and the Hurst Exponent F. Benavides-Bravo et al. 10.3390/math9212656
- Adapting rainfall bias-corrections to improve hydrological simulations generated from climate model forcings D. Robertson et al. 10.1016/j.jhydrol.2023.129322
- Significant contribution of bias correction methods to uncertainty in future runoff projections under CMIP6 climate change S. Chae & E. Chung 10.1016/j.ejrh.2024.101973
- Projection of rainfall variability in Egypt by regional climate model simulations T. Gado et al. 10.2166/wcc.2022.003
22 citations as recorded by crossref.
- Introducing Narclim1.5: Evaluation and Projection of Climate Extremes for Southeast Australia F. Ji et al. 10.2139/ssrn.4174746
- Adapting Water Management to Climate Change in the Murray–Darling Basin, Australia I. Prosser et al. 10.3390/w13182504
- Effects of Climate Change on Hydrological Indicators of Subsurface Drainage for a Representative French Drainage Site A. Jeantet et al. 10.3389/fenvs.2022.899226
- Evaluating skills and issues of quantile-based bias adjustment for climate change scenarios F. Lehner et al. 10.5194/ascmo-9-29-2023
- Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling Y. Zheng et al. 10.1007/s00376-023-3118-2
- Managing impacts of extreme hydrological events on urban water services: the Australian experience J. Horne 10.1080/07900627.2020.1808447
- Introducing NARCliM1.5: Evaluation and projection of climate extremes for southeast Australia F. Ji et al. 10.1016/j.wace.2022.100526
- How May the Choice of Downscaling Techniques and Meteorological Reference Observations Affect Future Hydroclimate Projections? D. Rastogi et al. 10.1029/2022EF002734
- Hydrological Modelling and Climate Adaptation under Changing Climate: A Review with a Focus in Sub-Saharan Africa V. Banda et al. 10.3390/w14244031
- Review of bias correction methods for climate model outputs in hydrology A. Menapace et al. 10.1016/j.jhydrol.2025.133213
- Different Hydroclimate Modelling Approaches Can Lead to a Large Range of Streamflow Projections under Climate Change: Implications for Water Resources Management F. Chiew et al. 10.3390/w14172730
- Projections of future streamflow for Australia informed by CMIP6 and previous generations of global climate models H. Zheng et al. 10.1016/j.jhydrol.2024.131286
- Trends and variability of rainfall characteristics influencing annual streamflow: A case study of southeast Australia G. Fu et al. 10.1002/joc.7923
- Introducing NARCliM1.5: Evaluating the Performance of Regional Climate Projections for Southeast Australia for 1950–2100 N. Nishant et al. 10.1029/2020EF001833
- Continental-scale bias-corrected climate and hydrological projections for Australia J. Peter et al. 10.5194/gmd-17-2755-2024
- 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
- Impact of downscaled rainfall biases on projected runoff changes S. Charles et al. 10.5194/hess-24-2981-2020
- Uncertainty propagation in a modelling chain of climate change impact for a representative French drainage site A. Jeantet et al. 10.1080/02626667.2023.2203322
- Evaluating the uncertainty of climate model structure and bias correction on the hydrological impact of projected climate change in a Mediterranean catchment A. Senatore et al. 10.1016/j.ejrh.2022.101120
- A Climate-Mathematical Clustering of Rainfall Stations in the Río Bravo-San Juan Basin (Mexico) by Using the Higuchi Fractal Dimension and the Hurst Exponent F. Benavides-Bravo et al. 10.3390/math9212656
- Adapting rainfall bias-corrections to improve hydrological simulations generated from climate model forcings D. Robertson et al. 10.1016/j.jhydrol.2023.129322
- Significant contribution of bias correction methods to uncertainty in future runoff projections under CMIP6 climate change S. Chae & E. Chung 10.1016/j.ejrh.2024.101973
1 citations as recorded by crossref.
Latest update: 30 May 2025
Short summary
There is a growing need for information about possible changes to water resource availability in the future due to climate change. Large-scale outputs from global climate models need to be translated to finer-resolution spatial scales before hydrological modelling. Biases in this downscaled data often need to be corrected. We show that usual bias correction methods can retain residual biases in multi-day occurrences of rainfall, which can result in biases in modelled runoff.
There is a growing need for information about possible changes to water resource availability in...
