SDMBCv2 (v1.0): correcting systematic biases  in RCM inputs for future projection

Kim, Youngil; Evans, Jason P.

doi:10.5194/gmd-19-7457-2026

Articles | Volume 19, issue 15

https://doi.org/10.5194/gmd-19-7457-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-7457-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 15

Model description paper

|

13 Aug 2026

Model description paper |

| 13 Aug 2026

SDMBCv2 (v1.0): correcting systematic biases in RCM inputs for future projection

Youngil Kim and Jason P. Evans

Supplement

https://doi.org/10.5194/gmd-19-7457-2026-supplement

Data sets

SDMBC v2 – Input and Output Datasets (Version 1.0) Youngil Kim and Jason Evans https://doi.org/10.5281/zenodo.17577882

ERA5 hourly data on pressure levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.bd0915c6

CSIRO ACCESS-ESM1.5 model output prepared for CMIP6 CMIP historical Tilo Ziehn et al. https://doi.org/10.22033/ESGF/CMIP6.4272

Model code and software

young-ccrc/sdmbc_v2: SDMBC v2 – Version 1.0: Script Release for GMD Manuscript Submission Youngil Kim https://doi.org/10.5281/zenodo.17707370

Short summary

Climate models used to study future climate often contain systematic errors that affect high-resolution simulations. This study presents a new open-source tool that reduces these errors before regional climate simulations are run. By correcting multiple atmospheric variables together and at short time scales, the method improves realism and consistency in simulated climate patterns. This leads to more reliable regional projections, particularly for extreme weather events.