Effects of univariate and multivariate bias correction on  hydrological impact projections in alpine catchments

Meyer, Judith; Kohn, Irene; Stahl, Kerstin; Hakala, Kirsti; Seibert, Jan; Cannon, Alex J.

doi:https://doi.org/10.5194/hess-23-1339-2019

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.

https://doi.org/10.5194/hess-23-1339-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 3

Research article

| Highlight paper

|

11 Mar 2019

Research article | Highlight paper |

| 11 Mar 2019

Effects of univariate and multivariate bias correction on hydrological impact projections in alpine catchments

Judith Meyer, Irene Kohn, Kerstin Stahl, Kirsti Hakala, Jan Seibert, and Alex J. Cannon

Supplement

https://doi.org/10.5194/hess-23-1339-2019-supplement

Data sets

Multivariate Bias Correction of Climate Model Outputs, R package 'MBC' version 0.10-4 A. J. Cannon https://CRAN.R-project.org/package=MBC

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.