Direct and indirect application of univariate  and multivariate bias corrections on heat-stress  indices based on multiple regional-climate-model simulations

Qiu, Liying; Im, Eun-Soon; Min, Seung-Ki; Kim, Yeon-Hee; Cha, Dong-Hyun; Shin, Seok-Woo; Ahn, Joong-Bae; Chang, Eun-Chul; Byun, Young-Hwa

doi:https://doi.org/10.5194/esd-14-507-2023

Articles | Volume 14, issue 2

https://doi.org/10.5194/esd-14-507-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esd-14-507-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 2

Research article

|

26 Apr 2023

Research article |

| 26 Apr 2023

Direct and indirect application of univariate and multivariate bias corrections on heat-stress indices based on multiple regional-climate-model simulations

Liying Qiu, Eun-Soon Im, Seung-Ki Min, Yeon-Hee Kim, Dong-Hyun Cha, Seok-Woo Shin, Joong-Bae Ahn, Eun-Chul Chang, and Young-Hwa Byun

Supplement

https://doi.org/10.5194/esd-14-507-2023-supplement

Data sets

Near-surface temperature and relative humidity data from the CORDEX-East domain downscaling product L. Qiu, E.-S. Im, S.-K. Min, Y.-H. Kim, D.-H. Cha, S.-W. Shin, J.-B. Ahn, E.-C. Chang, and Y.-H. Byun https://doi.org/10.14711/dataset/GTXJVQ

ERA5 hourly data on single levels from 1940 to present H. Hersbach, B. Bell, P. Berrisford, G. Biavati, A. Horányi, J. Muñoz Sabater, J. Nicolas, C. Peubey, R. Radu, I. Rozum, D. Schepers, A. Simmons, C. Soci, D. Dee, and J.-N. Thépaut https://doi.org/10.24381/cds.adbb2d47

Model code and software

R package "MBC": Multivariate Bias Correction of Climate Model Outputs A. J. Cannon https://CRAN.R-project.org/package=MBC

R package "qmap": Statistical Transformations for Post-Processing Climate Model Output L. Gudmundsson https://CRAN.R-project.org/package=qmap

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Short summary

This study evaluates four bias correction methods (three univariate and one multivariate) for correcting multivariate heat-stress indices. We show that the multivariate method can benefit the indirect correction that first adjusts individual components before index calculation, and its advantage is more evident for indices relying equally on multiple drivers. Meanwhile, the direct correction of heat-stress indices by the univariate quantile delta mapping approach also has comparable performance.