Articles | Volume 23, issue 3
https://doi.org/10.5194/hess-23-1339-2019
© Author(s) 2019. 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-23-1339-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Effects of univariate and multivariate bias correction on hydrological impact projections in alpine catchments
Judith Meyer
Faculty of Environment and Natural Resources, University of Freiburg, 79098 Freiburg, Germany
now at: Catchment and Eco-Hydrology Research Group, Luxembourg Institute of Science and Technology, 4362 Esch-sur-Alzette, Luxembourg
Irene Kohn
CORRESPONDING AUTHOR
Faculty of Environment and Natural Resources, University of Freiburg, 79098 Freiburg, Germany
Kerstin Stahl
Faculty of Environment and Natural Resources, University of Freiburg, 79098 Freiburg, Germany
Kirsti Hakala
Department of Geography, University of Zurich, 8057 Zurich, Switzerland
Jan Seibert
Department of Geography, University of Zurich, 8057 Zurich, Switzerland
Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden
Alex J. Cannon
Climate Research Division, Environment and Climate Change Canada, BC V8W 2Y2, Victoria, Canada
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62 citations as recorded by crossref.
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- Impacts of Using State‐of‐the‐Art Multivariate Bias Correction Methods on Hydrological Modeling Over North America Q. Guo et al. 10.1029/2019WR026659
- Selection of representative near-future climate simulations by minimizing bias in average monthly temperature and precipitation V. Khokhlov et al. 10.1007/s00704-023-04792-8
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- Compound droughts and hot extremes: Characteristics, drivers, changes, and impacts Z. Hao et al. 10.1016/j.earscirev.2022.104241
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- Impact of correcting sub-daily climate model biases for hydrological studies M. Faghih et al. 10.5194/hess-26-1545-2022
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- Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble F. Willkofer et al. 10.5194/hess-28-2969-2024
- Predicting Hydrological Change in an Alpine Glacierized Basin and Its Sensitivity to Landscape Evolution and Meteorological Forcings C. Aubry‐Wake & J. Pomeroy 10.1029/2022WR033363
- Projected changes of rain, sleet, and snowfall in Norway E. Kuya et al. 10.1080/00291951.2024.2360409
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- Impact of Climate Change on the Hydrological Regime of the Yarkant River Basin, China: An Assessment Using Three SSP Scenarios of CMIP6 GCMs Y. Xiang et al. 10.3390/rs14010115
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- Impact of climate change on climate extreme indices in Kaduna River basin, Nigeria Z. Isa et al. 10.1007/s11356-023-27821-5
- Climatic Controls on Future Hydrologic Changes in a Subarctic River Basin in Canada R. Shrestha et al. 10.1175/JHM-D-18-0262.1
- Multivariate bias corrections of climate simulations: which benefits for which losses? B. François et al. 10.5194/esd-11-537-2020
- Assessing the influence of calibration methodology and model structure on glacio-hydrological simulations in the Cheakamus River Basin, British Columbia, Canada K. Tsuruta & M. Schnorbus 10.1016/j.hydroa.2022.100144
- Identifying major climate extreme indices driver of stream flow discharge variability using machine learning and SHaply Additive Explanation Z. Isa et al. 10.1007/s40899-023-00897-0
- Comparative assessment of dry- and humid-heat extremes in a warming climate: Frequency, intensity, and seasonal timing X. Fan et al. 10.1016/j.wace.2024.100698
- Multi-site bias correction of climate model outputs for hydro-meteorological impact studies: An application over a watershed in China T. Su et al. 10.1002/hyp.13750
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- Multi-decadal monsoon characteristics and glacier response in High Mountain Asia T. Shaw et al. 10.1088/1748-9326/ac9008
- Uni- and multivariate bias adjustment methods in Nordic catchments: Complexity and performance in a changing climate F. Tootoonchi et al. 10.1016/j.scitotenv.2022.158615
- Bias Correction for Climate Model Output (1) Method Characteristics and Classification S. WATANABE 10.3178/jjshwr.33.243
- Seamlessly combined historical and projected daily meteorological datasets for impact studies in Central Europe: The FORESEE v4.0 and the FORESEE-HUN v1.0 A. Kern et al. 10.1016/j.cliser.2023.100443
- A novel approach for bridging the gap between climate change scenarios and avalanche hazard indication mapping G. Ortner et al. 10.1016/j.coldregions.2024.104355
- The compensating effect of glaciers: Characterizing the relation between interannual streamflow variability and glacier cover M. van Tiel et al. 10.1002/hyp.13603
- Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies M. Tarek et al. 10.5194/hess-25-3331-2021
- 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
- Snow depth in high-resolution regional climate model simulations over southern Germany – suitable for extremes and impact-related research? B. Poschlod & A. Daloz 10.5194/tc-18-1959-2024
Discussed (final revised paper)
Latest update: 20 Nov 2024
Short summary
Several multivariate bias correction methods have been developed recently, but only a few studies have tested the effect of multivariate bias correction on hydrological impact projections. This study shows that incorporating or ignoring inter-variable relations between air temperature and precipitation can have a notable effect on the projected snowfall fraction. The effect translated to considerable consequences for the glacio-hydrological responses and streamflow components of the catchments.
Several multivariate bias correction methods have been developed recently, but only a few...