References

  • Schwertfeger, Benjamin Thomas and Lohmann, Gerrit and Lipskoch, Henrik (2023) “Introduction of the BiasAdjustCXX command-line tool for the application of fast and efficient bias corrections in climatic research”, SoftwareX, Volume 22, 101379, ISSN 2352-7110, (https://doi.org/10.1016/j.softx.2023.101379)

  • Schwertfeger, Benjamin Thomas (2022) “The influence of bias corrections on variability, distribution, and correlation of temperatures in comparison to observed and modeled climate data in Europe” (https://epic.awi.de/id/eprint/56689/)

  • Delta Method based on: Beyer, R. and Krapp, M. and Manica, A. (2020) “An empirical evaluation of bias correction methods for palaeoclimate simulations” (https://doi.org/10.5194/cp-16-1493-2020)

  • Linear Scaling and Variance Scaling based on: Teutschbein, Claudia and Seibert, Jan (2012) “Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods” (https://doi.org/10.1016/j.jhydrol.2012.05.052)

  • Quantile Mapping based on: Alex J. Cannon and Stephen R. Sobie and Trevor Q. Murdock (2015) “Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?” (https://doi.org/10.1175/JCLI-D-14-00754.1)

  • Quantile Delta Mapping based on: Tong, Y., Gao, X., Han, Z. et al. “Bias correction of temperature and precipitation over China for RCM simulations using the QM and QDM methods”. Clim Dyn 57, 1425–1443 (2021). (https://doi.org/10.1007/s00382-020-05447-4)

  • Schulzweida, U.: “CDO User Guide”, (https://doi.org/10.5281/zenodo.7112925), 2022.

  • This project took advantage of netCDF software developed by UCAR/Unidata (http://doi.org/10.5065/D6H70CW6).